Application of Latent Class Analysis to Identify Behavioral Patterns of Response to Behavioral Lifestyle Interventions in Overweight and Obese Adults.

PubMed

Fitzpatrick, Stephanie L; Coughlin, Janelle W; Appel, Lawrence J; Tyson, Crystal; Stevens, Victor J; Jerome, Gerald J; Dalcin, Arlene; Brantley, Phillip J; Hill-Briggs, Felicia

2015-08-01

Examining responders and non-responders to behavioral lifestyle interventions among overweight/obese adults with additional comorbidities may aid in refining and tailoring obesity treatment. The purpose of this study is to demonstrate the use of latent class analysis to identify patterns of response to behavioral lifestyle interventions based on adherence to diet and exercise recommendations. Repeated measures latent class analysis was applied to two clinical trial datasets, combination of two active interventions in the PREMIER Trial (n = 501) and phase 1 of the Weight Loss Maintenance Trial (WLM; n = 1685), to identify patterns of response to behavioral lifestyle interventions. Treatment response was based on adherence to daily recommendations for fruit/vegetable, fat, saturated fat, sodium, and exercise at baseline and 6 months. In PREMIER, three distinct latent classes emerged: responders (45.9%), non-responders (23.6%), and early adherers (30.5%). Responders and Early Adherers had greater weight loss at 6 and 18 months and were more likely to meet behavioral recommendations at 18 months than Non-responders. For WLM, there were four latent classes: partial responders (16%), non-responders (40%), early adherers (2%), and fruit/veggie only responders (41%). Non-responders in WLM had significantly less weight loss at 6 months compared to that of the other three latent classes. Latent class analysis is a useful method to apply to clinical trial data to identify distinct patterns of response to behavioral interventions. Overweight/ obese participants who respond to behavioral lifestyle treatment (i.e., meet behavioral recommendations) have significantly greater weight loss than that of participants who do not make behavioral changes.

Using latent class analysis to identify academic and behavioral risk status in elementary students.

PubMed

King, Kathleen R; Lembke, Erica S; Reinke, Wendy M

2016-03-01

Identifying classes of children on the basis of academic and behavior risk may have important implications for the allocation of intervention resources within Response to Intervention (RTI) and Multi-Tiered System of Support (MTSS) models. Latent class analysis (LCA) was conducted with a sample of 517 third grade students. Fall screening scores in the areas of reading, mathematics, and behavior were used as indicators of success on an end of year statewide achievement test. Results identified 3 subclasses of children, including a class with minimal academic and behavioral concerns (Tier 1; 32% of the sample), a class at-risk for academic problems and somewhat at-risk for behavior problems (Tier 2; 37% of the sample), and a class with significant academic and behavior problems (Tier 3; 31%). Each class was predictive of end of year performance on the statewide achievement test, with the Tier 1 class performing significantly higher on the test than the Tier 2 class, which in turn scored significantly higher than the Tier 3 class. The results of this study indicated that distinct classes of children can be determined through brief screening measures and are predictive of later academic success. Further implications are discussed for prevention and intervention for students at risk for academic failure and behavior problems. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

Identifying classes of persons with mild intellectual disability or borderline intellectual functioning: a latent class analysis.

PubMed

Nouwens, Peter J G; Lucas, Rosanne; Smulders, Nienke B M; Embregts, Petri J C M; van Nieuwenhuizen, Chijs

2017-07-17

Persons with mild intellectual disability or borderline intellectual functioning are often studied as a single group with similar characteristics. However, there are indications that differences exist within this population. Therefore, the aim of this study was to identify classes of persons with mild intellectual disability or borderline intellectual functioning and to examine whether these classes are related to individual and/or environmental characteristics. Latent class analysis was performed using file data of 250 eligible participants with a mean age of 26.1 (SD 13.8, range 3-70) years. Five distinct classes of persons with mild intellectual disability or borderline intellectual functioning were found. These classes significantly differed in individual and environmental characteristics. For example, persons with a mild intellectual disability experienced fewer problems than those with borderline intellectual disability. The identification of five classes implies that a differentiated approach is required towards persons with mild intellectual disability or borderline intellectual functioning.

A Finite Element Analysis of a Class of Problems in Elasto-Plasticity with Hidden Variables.

DTIC Science & Technology

1985-09-01

RD-R761 642 A FINITE ELEMENT ANALYSIS OF A CLASS OF PROBLEMS IN 1/2 ELASTO-PLASTICITY MIlT (U) TEXAS INST FOR COMPUTATIONAL MECHANICS AUSTIN J T ODEN...end Subtitle) S. TYPE OF REPORT & PERIOD COVERED A FINITE ELEMENT ANALYSIS OF A CLASS OF PROBLEMS Final Report IN ELASTO-PLASTICITY WITH HIDDEN...aieeoc ede It neceeeary nd Identify by block number) ;"Elastoplasticity, finite deformations; non-convex analysis ; finite element methods, metal forming

Do recognizable lifetime eating disorder phenotypes naturally occur in a culturally asian population? A combined latent profile and taxometric approach.

PubMed

Thomas, Jennifer J; Eddy, Kamryn T; Ruscio, John; Ng, King Lam; Casale, Kristen E; Becker, Anne E; Lee, Sing

2015-05-01

We examined whether empirically derived eating disorder (ED) categories in Hong Kong Chinese patients (N = 454) would be consistent with recognizable lifetime ED phenotypes derived from latent structure models of European and American samples. We performed latent profile analysis (LPA) using indicator variables from data collected during routine assessment, and then applied taxometric analysis to determine whether latent classes were qualitatively versus quantitatively distinct. Latent profile analysis identified four classes: (i) binge/purge (47%); (ii) non-fat-phobic low-weight (34%); (iii) fat-phobic low-weight (12%); and (iv) overweight disordered eating (6%). Taxometric analysis identified qualitative (categorical) distinctions between the binge/purge and non-fat-phobic low-weight classes, and also between the fat-phobic and non-fat-phobic low-weight classes. Distinctions between the fat-phobic low-weight and binge/purge classes were indeterminate. Empirically derived categories in Hong Kong showed recognizable correspondence with recognizable lifetime ED phenotypes. Although taxometric findings support two distinct classes of low weight EDs, LPA findings also support heterogeneity among non-fat-phobic individuals. Copyright © 2015 John Wiley & Sons, Ltd and Eating Disorders Association.

Patterns of HIV Risks and Related Factors among People Who Inject Drugs in Kermanshah, Iran: A Latent Class Analysis.

PubMed

Sharifi, Hamid; Mirzazadeh, Ali; Noroozi, Alireza; Marshall, Brandon D L; Farhoudian, Ali; Higgs, Peter; Vameghi, Meroe; Mohhamadi Shahboulaghi, Farahnaz; Qorbani, Mostafa; Massah, Omid; Armoon, Bahram; Noroozi, Mehdi

2017-01-01

The objective of this study was to explore patterns of drug use and sexual risk behaviors among people who inject drugs (PWID) in Iran. We surveyed 500 PWID in Kermanshah concerning demographic characteristics, sexual risk behaviors, and drug-related risk behaviors in the month prior to study. We used latent class analysis (LCA) to establish a baseline model of risk profiles and to identify the optimal number of latent classes, and we used ordinal regression to identify factors associated with class membership. Three classes of multiple HIV risk were identified. The probability of membership in the high-risk class was 0.33, compared to 0.26 and 0.40 for the low- and moderate-risk classes, respectively. Compared to members in the lowest-risk class (reference group), the highest-risk class members had higher odds of being homeless (OR = 4.5, CI: 1.44-8.22; p = 0.001) in the past 12 months. Members of the high-risk class had lower odds of regularly visiting a needle and syringe exchange program as compared to the lowest-risk class members (AOR = 0.42, CI: 0.2-0.81; p = 0.01). Findings show the sexual and drug-related HIV risk clusters among PWID in Iran, and emphasize the importance of developing targeted prevention and harm reduction programs for all domains of risk behaviors, both sexual and drug use related.

Severity of mental illness as a result of multiple childhood adversities: US National Epidemiologic Survey.

PubMed

Curran, Emma; Adamson, Gary; Stringer, Maurice; Rosato, Michael; Leavey, Gerard

2016-05-01

To examine patterns of childhood adversity, their long-term consequences and the combined effect of different childhood adversity patterns as predictors of subsequent psychopathology. Secondary analysis of data from the US National Epidemiologic Survey on alcohol and related conditions. Using latent class analysis to identify childhood adversity profiles; and using multinomial logistic regression to validate and further explore these profiles with a range of associated demographic and household characteristics. Finally, confirmatory factor analysis substantiated initial latent class analysis findings by investigating a range of mental health diagnoses. Latent class analysis generated a three-class model of childhood adversity in which 60 % of participants were allocated to a low adversity class; 14 % to a global adversities class (reporting exposures for all the derived latent classes); and 26 % to a domestic emotional and physical abuse class (exposed to a range of childhood adversities). Confirmatory Factor analysis defined an internalising-externalising spectrum to represent lifetime reporting patterns of mental health disorders. Using logistic regression, both adversity groups showed specific gender and race/ethnicity differences, related family discord and increased psychopathology. We identified underlying patterns in the exposure to childhood adversity and associated mental health. These findings are informative in their description of the configuration of adversities, rather than focusing solely on the cumulative aspect of experience. Amelioration of longer-term negative consequences requires early identification of psychopathology risk factors that can inform protective and preventive interventions. This study highlights the utility of screening for childhood adversities when individuals present with symptoms of psychiatric disorders.

Profiles of Community Violence Exposure Among African American Youth: An Examination of Desensitization to Violence Using Latent Class Analysis.

PubMed

Gaylord-Harden, Noni K; Dickson, Daniel; Pierre, Cynthia

2016-07-01

The current study employed latent class analysis (LCA) to identify distinct profiles of community violence exposure and their associations to desensitization outcomes in 241 African American early adolescents (M age = 12.86, SD = 1.28) in the sixth through eighth grade from under-resourced urban communities. Participants self-reported on their exposure to community violence, as well as on depressive and anxiety symptoms. The LCA revealed three distinct classes: a class exposed to low levels of violence (low exposure class), a class exposed to moderately high levels of victimization (victimization class), and a class exposed to high levels of all types of violence (high exposure class). Consistent with predictions, the high exposure class showed the lowest levels of depressive symptoms, suggesting a desensitization outcome. Gender and age were also examined in relation to the classes, and age was significantly associated with an increased risk of being a member of the high exposure class relative to the low exposure class. Using person-based analyses to examine desensitization outcomes provides useful information for prevention and intervention efforts, as it helps to identify a specific subgroup of youth that may be more likely to show desensitization outcomes in the context of community violence. © The Author(s) 2015.

Bayesian Analysis of Hmi Images and Comparison to Tsi Variations and MWO Image Observables

NASA Astrophysics Data System (ADS)

Parker, D. G.; Ulrich, R. K.; Beck, J.; Tran, T. V.

2015-12-01

We have previously applied the Bayesian automatic classification system AutoClass to solar magnetogram and intensity images from the 150 Foot Solar Tower at Mount Wilson to identify classes of solar surface features associated with variations in total solar irradiance (TSI) and, using those identifications, modeled TSI time series with improved accuracy (r > 0.96). (Ulrich, et al, 2010) AutoClass identifies classes by a two-step process in which it: (1) finds, without human supervision, a set of class definitions based on specified attributes of a sample of the image data pixels, such as magnetic field and intensity in the case of MWO images, and (2) applies the class definitions thus found to new data sets to identify automatically in them the classes found in the sample set. HMI high resolution images capture four observables-magnetic field, continuum intensity, line depth and line width-in contrast to MWO's two observables-magnetic field and intensity. In this study, we apply AutoClass to the HMI observables for images from June, 2010 to December, 2014 to identify solar surface feature classes. We use contemporaneous TSI measurements to determine whether and how variations in the HMI classes are related to TSI variations and compare the characteristic statistics of the HMI classes to those found from MWO images. We also attempt to derive scale factors between the HMI and MWO magnetic and intensity observables.The ability to categorize automatically surface features in the HMI images holds out the promise of consistent, relatively quick and manageable analysis of the large quantity of data available in these images. Given that the classes found in MWO images using AutoClass have been found to improve modeling of TSI, application of AutoClass to the more complex HMI images should enhance understanding of the physical processes at work in solar surface features and their implications for the solar-terrestrial environment.Ulrich, R.K., Parker, D, Bertello, L. and Boyden, J. 2010, Solar Phys. , 261 , 11.

Investigating Subtypes of Child Development: A Comparison of Cluster Analysis and Latent Class Cluster Analysis in Typology Creation

ERIC Educational Resources Information Center

DiStefano, Christine; Kamphaus, R. W.

2006-01-01

Two classification methods, latent class cluster analysis and cluster analysis, are used to identify groups of child behavioral adjustment underlying a sample of elementary school children aged 6 to 11 years. Behavioral rating information across 14 subscales was obtained from classroom teachers and used as input for analyses. Both the procedures…

Psychological Distress among Victimized Women on Probation and Parole: A Latent Class Analysis

PubMed Central

Golder, Seana; Engstrom, Malitta; Hall, Martin T.; Higgins, George; Logan, TK

2015-01-01

Latent class analysis was used to identify subgroups of victimized women (N=406) on probation and parole differentiated by levels of general psychological distress. The nine primary symptom dimensions from the Brief Symptom Inventory (BSI) were used individually as latent class indicators (Derogatis, 1993). Results identified three classes of women characterized by increasing levels of psychological distress; classes were further differentiated by posttraumatic stress disorder symptoms, cumulative victimization, substance use and other domains of psychosocial functioning (i.e., sociodemographic characteristics; informal social support and formal service utilization; perceived life stress; and resource loss). The present research was effective in uncovering important heterogeneity in psychological distress using a highly reliable and easily accessible measure of general psychological distress. Differentiating levels of psychological distress and associated patterns of psychosocial risk can be used to develop intervention strategies targeting the needs of different subgroups of women. Implications for treatment and future research are presented. PMID:25915692

SU-F-T-247: Collision Risks in a Modern Radiation Oncology Department: An Efficient Approach to Failure Modes and Effects Analysis

DOE Office of Scientific and Technical Information (OSTI.GOV)

Schubert, L; Westerly, D; Vinogradskiy, Y

Purpose: Collisions between treatment equipment and patients are potentially catastrophic. Modern technology now commonly involves automated remote motion during imaging and treatment, yet a systematic assessment to identify and mitigate collision risks has yet to be performed. Failure modes and effects analysis (FMEA) is a method of risk assessment that has been increasingly used in healthcare, yet can be resource intensive. This work presents an efficient approach to FMEA to identify collision risks and implement practical interventions within a modern radiation therapy department. Methods: Potential collisions (e.g. failure modes) were assessed for all treatment and simulation rooms by teams consistingmore » of physicists, therapists, and radiation oncologists. Failure modes were grouped into classes according to similar characteristics. A single group meeting was held to identify implementable interventions for the highest priority classes of failure modes. Results: A total of 60 unique failure modes were identified by 6 different teams of physicists, therapists, and radiation oncologists. Failure modes were grouped into four main classes: specific patient setups, automated equipment motion, manual equipment motion, and actions in QA or service mode. Two of these classes, unusual patient setups and automated machine motion, were identified as being high priority in terms severity of consequence and addressability by interventions. The two highest risk classes consisted of 33 failure modes (55% of the total). In a single one hour group meeting, 6 interventions were identified. Those interventions addressed 100% of the high risk classes of failure modes (55% of all failure modes identified). Conclusion: A class-based approach to FMEA was developed to efficiently identify collision risks and implement interventions in a modern radiation oncology department. Failure modes and interventions will be listed, and a comparison of this approach against traditional FMEA methods will be presented.« less

Tailoring community-based wellness initiatives with latent class analysis--Massachusetts Community Transformation Grant projects.

PubMed

Arcaya, Mariana; Reardon, Timothy; Vogel, Joshua; Andrews, Bonnie K; Li, Wenjun; Land, Thomas

2014-02-13

Community-based approaches to preventing chronic diseases are attractive because of their broad reach and low costs, and as such, are integral components of health care reform efforts. Implementing community-based initiatives across Massachusetts' municipalities presents both programmatic and evaluation challenges. For effective delivery and evaluation of the interventions, establishing a community typology that groups similar municipalities provides a balanced and cost-effective approach. Through a series of key informant interviews and exploratory data analysis, we identified 55 municipal-level indicators of 6 domains for the typology analysis. The domains were health behaviors and health outcomes, housing and land use, transportation, retail environment, socioeconomics, and demographic composition. A latent class analysis was used to identify 10 groups of municipalities based on similar patterns of municipal-level indicators across the domains. Our model with 10 latent classes yielded excellent classification certainty (relative entropy = .995, minimum class probability for any class = .871), and differentiated distinct groups of municipalities based on health-relevant needs and resources. The classes differentiated healthy and racially and ethnically diverse urban areas from cities with similar population densities and diversity but worse health outcomes, affluent communities from lower-income rural communities, and mature suburban areas from rapidly suburbanizing communities with different healthy-living challenges. Latent class analysis is a tool that may aid in the planning, communication, and evaluation of community-based wellness initiatives such as Community Transformation Grants projects administrated by the Centers for Disease Control and Prevention.

Determination of Pain Phenotypes in Knee Osteoarthritis: A Latent Class Analysis using Data from the Osteoarthritis Initiative Study

PubMed Central

Kittelson, Andrew J.; Stevens-Lapsley, Jennifer E.; Schmiege, Sarah J.

2017-01-01

Objective Knee osteoarthritis (OA) is a broadly applied diagnosis that may encompass multiple subtypes of pain. The purpose of this study was to identify phenotypes of knee OA, using measures from the following pain-related domains: 1) knee OA pathology, 2) psychological distress, and 3) altered pain neurophysiology. Methods Data were selected from a total of 3494 participants at Visit #6 of the Osteoarthritis Initiative (OAI) study. Latent Class Analysis was applied to the following variables: radiographic OA severity, quadriceps strength, Body Mass Index (BMI), Charlson Comorbidity Index (CCI), Center for Epidemiologic Studies Depression subscale (CES-D), Coping Strategies Questionnaire-Catastrophizing subscale (CSQ-Cat), number of bodily pain sites, and knee joint tenderness at 4 sites. Resulting classes were compared on the following demographic and clinical factors: age, sex, pain severity, disability, walking speed, and use of arthritis-related healthcare. Results A four-class model was identified. Class 1 (4% of the study population) had higher CCI scores. Class 2 (24%) had higher knee joint sensitivity. Class 3 (10%) had greater psychological distress. Class 4 (62%) had lesser radiographic OA, little psychological involvement, greater strength, and less pain sensitivity. Additionally, Class 1 was the oldest, on average. Class 4 was the youngest, had the lowest disability, and least pain. Class 3 had the worst disability and most pain. Conclusions Four distinct pain phenotypes of knee OA were identified. Psychological factors, comorbidity status, and joint sensitivity appear to be important in defining phenotypes of knee OA-related pain. PMID:26414884

Determination of Pain Phenotypes in Knee Osteoarthritis: A Latent Class Analysis Using Data From the Osteoarthritis Initiative.

PubMed

Kittelson, Andrew J; Stevens-Lapsley, Jennifer E; Schmiege, Sarah J

2016-05-01

Knee osteoarthritis (OA) is a broadly applied diagnosis that may describe multiple subtypes of pain. The purpose of this study was to identify phenotypes of knee OA, using measures from the following pain-related domains: 1) knee OA pathology, 2) psychological distress, and 3) altered pain neurophysiology. Data were selected from a total of 3,494 participants at visit 6 of the Osteoarthritis Initiative study. Latent class analysis was applied to the following variables: radiographic OA severity, quadriceps strength, body mass index, the Charlson Comorbidity Index (CCI), the Center for Epidemiologic Studies Depression Scale, the Coping Strategies Questionnaire-Catastrophizing subscale, number of bodily pain sites, and knee joint tenderness at 4 sites. The resulting classes were compared on the following demographic and clinical factors: age, sex, pain severity, disability, walking speed, and use of arthritis-related health care. A 4-class model was identified. Class 1 (4% of the study population) had higher CCI scores. Class 2 (24%) had higher knee joint sensitivity. Class 3 (10%) had greater psychological distress. Class 4 (62%) had lesser radiographic OA, little psychological involvement, greater strength, and less pain sensitivity. Additionally, class 1 was the oldest, on average. Class 4 was the youngest, had the lowest disability, and least pain. Class 3 had the worst disability and most pain. Four distinct pain phenotypes of knee OA were identified. Psychological factors, comorbidity status, and joint sensitivity appear to be important in defining phenotypes of knee OA-related pain. © 2016, American College of Rheumatology.

Patterns and predictors of posttraumatic stress disorder in refugees: A latent class analysis.

PubMed

Minihan, Savannah; Liddell, Belinda J; Byrow, Yulisha; Bryant, Richard A; Nickerson, Angela

2018-05-01

Although elevated rates of posttraumatic stress disorder (PTSD) have been well-documented in refugees, no study has investigated the heterogeneity of DSM-5 PTSD symptomatology in such populations. This study aimed to determine whether there are unique patterns of DSM-5 defined PTSD symptomatology in refugees, and investigate whether factors characteristic of the refugee experience, including trauma exposure and post-migration stress, predict symptom profiles. Participants were 246 refugees and asylum-seekers from an Arabic-, English-, Farsi-, or Tamil-speaking background who had been resettled in Australia. Participants completed measures of post-migration living difficulties, trauma exposure, PTSD symptoms and functional disability. Latent class analysis was used to identify PTSD symptom profiles, and predictors of class membership were elucidated via multinomial logistic regression. Four classes were identified: a high-PTSD class (21.3%), a high-re-experiencing/avoidance class (15.3%), a moderate-PTSD class (23%), and a no PTSD class (40.3%). Trauma exposure and post-migration stress significantly predicted class membership and classes differed in degree of functional disability. The current study employed a cross-sectional design, which precluded inferences regarding the stability of classes of PTSD symptomatology. This study provides evidence for distinct patterns of PTSD symptomatology in refugees. We identified a novel class, characterized by high-re-experiencing and avoidance symptoms, as well as classes characterized by pervasive, moderate, and no symptomatology. Trauma exposure and post-migration stress differentially contributed to the emergence of these profiles. Individuals with high and moderate probability of PTSD symptoms evidenced substantial disability. These results support conceptualizations of PTSD as a heterogeneous construct, and highlight the importance of considering sub-clinical symptom presentations, as well as the post-migration environment, in clinical contexts. Copyright © 2018. Published by Elsevier B.V.

Patterns of perceived barriers to medical care in older adults: a latent class analysis.

PubMed

Thorpe, Joshua M; Thorpe, Carolyn T; Kennelty, Korey A; Pandhi, Nancy

2011-08-03

This study examined multiple dimensions of healthcare access in order to develop a typology of perceived barriers to healthcare access in community-dwelling elderly. Secondary aims were to define distinct classes of older adults with similar perceived healthcare access barriers and to examine predictors of class membership to identify risk factors for poor healthcare access. A sample of 5,465 community-dwelling elderly was drawn from the 2004 wave of the Wisconsin Longitudinal Study. Perceived barriers to healthcare access were measured using items from the Group Health Association of America Consumer Satisfaction Survey. We used latent class analysis to assess the constellation of items measuring perceived barriers in access and multinomial logistic regression to estimate how risk factors affected the probability of membership in the latent barrier classes. Latent class analysis identified four classes of older adults. Class 1 (75% of sample) consisted of individuals with an overall low level of risk for perceived access problems (No Barriers). Class 2 (5%) perceived problems with the availability/accessibility of healthcare providers such as specialists or mental health providers (Availability/Accessibility Barriers). Class 3 (18%) perceived problems with how well their providers' operations arise organized to accommodate their needs and preferences (Accommodation Barriers). Class 4 (2%) perceived problems with all dimension of access (Severe Barriers). Results also revealed that healthcare affordability is a problem shared by members of all three barrier groups, suggesting that older adults with perceived barriers tend to face multiple, co-occurring problems. Compared to those classified into the No Barriers group, those in the Severe Barrier class were more likely to live in a rural county, have no health insurance, have depressive symptomatology, and speech limitations. Those classified into the Availability/Accessibility Barriers group were more likely to live in rural and micropolitan counties, have depressive symptomatology, more chronic conditions, and hearing limitations. Those in the Accommodation group were more likely to have depressive symptomatology and cognitive limitations. The current study identified a typology of perceived barriers in healthcare access in older adults. The identified risk factors for membership in perceived barrier classes could potentially assist healthcare organizations and providers with targeting polices and interventions designed to improve access in their most vulnerable older adult populations, particularly those in rural areas, with functional disabilities, or in poor mental health.

The Overlap of Youth Violence Among Aggressive Adolescents with Past-Year Alcohol Use—A Latent Class Analysis: Aggression and Victimization in Peer and Dating Violence in an Inner City Emergency Department Sample

PubMed Central

Whiteside, Lauren K.; Ranney, Megan L.; Chermack, Stephen T.; Zimmerman, Marc A.; Cunningham, Rebecca M.; Walton, Maureen A.

2013-01-01

Objective: The purpose of this study was to identify overlap and violence types between peer and dating aggression and victimization using latent class analysis (LCA) among a sample of aggressive adolescents with a history of alcohol use and to identify risk and protective factors associated with each violence class. Method: From September 2006 to September 2009, a systematic sample of patients (14–18 years old) seeking care in an urban emergency department were approached. Adolescents reporting any past-year alcohol use and aggression completed a survey using validated measures including types of violence (severe and moderate aggression, severe and moderate victimization with both peers and dating partners). Using LCA, violence classes were identified; correlates of membership in each LCA class were determined. Results: Among this sample (n = 694), LCA identified three classes described as (a) peer aggression (PA) (52.2%), (b) peer aggression + peer victimization (PAPV) (18.6%), and (c) multiple domains of violence (MDV) (29.3%). Compared with those in the PA class, those in the PAPV class were more likely to be male, report injury in a fight, and have delinquent peers. Compared with the PA class, those in the MDV class were more likely to be female, African American, report injury in a fight, carry a weapon, experience negative consequences from alcohol use, and have delinquent peers and more family conflict. Compared with the PAPV class, those in the MDV class were likely to be female, African American, receive public assistance, carry a weapon, experience negative consequences from alcohol use, and use marijuana. Conclusions: There is extensive overlap of victimization and aggression in both peer and dating relationships. Also, those with high rates of violence across relationships have increased alcohol misuse and marijuana use. Thus, violence-prevention efforts should consider addressing concomitant substance use. PMID:23200158

Static analysis of class invariants in Java programs

NASA Astrophysics Data System (ADS)

Bonilla-Quintero, Lidia Dionisia

2011-12-01

This paper presents a technique for the automatic inference of class invariants from Java bytecode. Class invariants are very important for both compiler optimization and as an aid to programmers in their efforts to reduce the number of software defects. We present the original DC-invariant analysis from Adam Webber, talk about its shortcomings and suggest several different ways to improve it. To apply the DC-invariant analysis to identify DC-invariant assertions, all that one needs is a monotonic method analysis function and a suitable assertion domain. The DC-invariant algorithm is very general; however, the method analysis can be highly tuned to the problem in hand. For example, one could choose shape analysis as the method analysis function and use the DC-invariant analysis to simply extend it to an analysis that would yield class-wide invariants describing the shapes of linked data structures. We have a prototype implementation: a system we refer to as "the analyzer" that infers DC-invariant unary and binary relations and provides them to the user in a human readable format. The analyzer uses those relations to identify unnecessary array bounds checks in Java programs and perform null-reference analysis. It uses Adam Webber's relational constraint technique for the class-invariant binary relations. Early results with the analyzer were very imprecise in the presence of "dirty-called" methods. A dirty-called method is one that is called, either directly or transitively, from any constructor of the class, or from any method of the class at a point at which a disciplined field has been altered. This result was unexpected and forced an extensive search for improved techniques. An important contribution of this paper is the suggestion of several ways to improve the results by changing the way dirty-called methods are handled. The new techniques expand the set of class invariants that can be inferred over Webber's original results. The technique that produces better results uses in-line analysis. Final results are promising: we can infer sound class invariants for full-scale, not just toy applications.

A Simple Test of Class-Level Genetic Association Can Reveal Novel Cardiometabolic Trait Loci.

PubMed

Qian, Jing; Nunez, Sara; Reed, Eric; Reilly, Muredach P; Foulkes, Andrea S

2016-01-01

Characterizing the genetic determinants of complex diseases can be further augmented by incorporating knowledge of underlying structure or classifications of the genome, such as newly developed mappings of protein-coding genes, epigenetic marks, enhancer elements and non-coding RNAs. We apply a simple class-level testing framework, termed Genetic Class Association Testing (GenCAT), to identify protein-coding gene association with 14 cardiometabolic (CMD) related traits across 6 publicly available genome wide association (GWA) meta-analysis data resources. GenCAT uses SNP-level meta-analysis test statistics across all SNPs within a class of elements, as well as the size of the class and its unique correlation structure, to determine if the class is statistically meaningful. The novelty of findings is evaluated through investigation of regional signals. A subset of findings are validated using recently updated, larger meta-analysis resources. A simulation study is presented to characterize overall performance with respect to power, control of family-wise error and computational efficiency. All analysis is performed using the GenCAT package, R version 3.2.1. We demonstrate that class-level testing complements the common first stage minP approach that involves individual SNP-level testing followed by post-hoc ascribing of statistically significant SNPs to genes and loci. GenCAT suggests 54 protein-coding genes at 41 distinct loci for the 13 CMD traits investigated in the discovery analysis, that are beyond the discoveries of minP alone. An additional application to biological pathways demonstrates flexibility in defining genetic classes. We conclude that it would be prudent to include class-level testing as standard practice in GWA analysis. GenCAT, for example, can be used as a simple, complementary and efficient strategy for class-level testing that leverages existing data resources, requires only summary level data in the form of test statistics, and adds significant value with respect to its potential for identifying multiple novel and clinically relevant trait associations.

A Latent Class Analysis of Maternal Responsiveness and Autonomy-Granting in Early Adolescence: Prediction to Later Adolescent Sexual Risk-Taking

PubMed Central

Lanza, H. Isabella; Huang, David Y. C.; Murphy, Debra A.; Hser, Yih-Ing

2013-01-01

The present study sought to extend empirical inquiry related to the role of parenting on adolescent sexual risk-taking by using latent class analysis (LCA) to identify patterns of adolescent-reported mother responsiveness and autonomy-granting in early adolescence and examine associations with sexual risk-taking in mid- and late-adolescence. Utilizing a sample of 12- to 14-year-old adolescents (N = 4,743) from the 1997 National Longitudinal Survey of Youth (NLSY97), results identified a four-class model of maternal responsiveness and autonomy-granting: low responsiveness/high autonomy-granting, moderate responsiveness/moderate autonomy-granting, high responsiveness/low autonomy-granting, high responsiveness/moderate autonomy-granting. Membership in the low responsiveness/high autonomy-granting class predicted greater sexual risk-taking in mid- and late-adolescence compared to all other classes, and membership in the high responsiveness/ moderate autonomy-granting class predicted lower sexual risk-taking. Gender and ethnic differences in responsiveness and autonomy-granting class membership were also found, potentially informing gender and ethnic disparities of adolescent sexual risk-taking. PMID:23828712

Cognitive competence of graduates, oriented to work in the knowledge management system in the state corporation “Rosatom”

NASA Astrophysics Data System (ADS)

Kireev, V.; Silenko, A.; Guseva, A.

2017-01-01

This article describes an approach to the determination of the level of formation of competences of university graduates, oriented to work in the state corporation “Rosatom” in a knowledge management system. With the use of cluster analysis graduate classes were identified, focused on knowledge transfer, analysis and the search for new knowledge, creative transformation of knowledge. In addition, the class innovators were identified, which were fully formed the necessary cognitive competences.

Medical Complexity among Children with Special Health Care Needs: A Two-Dimensional View.

PubMed

Coller, Ryan J; Lerner, Carlos F; Eickhoff, Jens C; Klitzner, Thomas S; Sklansky, Daniel J; Ehlenbach, Mary; Chung, Paul J

2016-08-01

To identify subgroups of U.S. children with special health care needs (CSHCN) and characterize key outcomes. Secondary analysis of 2009-2010 National Survey of CSHCN. Latent class analysis grouped individuals into substantively meaningful classes empirically derived from measures of pediatric medical complexity. Outcomes were compared among latent classes with weighted logistic or negative binomial regression. LCA identified four unique CSHCN subgroups: broad functional impairment (physical, cognitive, and mental health) with extensive health care (Class 1), broad functional impairment alone (Class 2), predominant physical impairment requiring family-delivered care (Class 3), and physical impairment alone (Class 4). CSHCN from Class 1 had the highest ED visit rates (IRR 3.3, p < .001) and hospitalization odds (AOR: 12.0, p < .001) and lowest odds of a medical home (AOR: 0.17, p < .001). CSHCN in Class 3, despite experiencing more shared decision making and medical home attributes, had more ED visits and missed school than CSHCN in Class 2 (p < .001); the latter, however, experienced more cost-related difficulties, care delays, and parents having to stop work (p < .001). Recognizing distinct impacts of cognitive and mental health impairments and health care delivery needs on CSHCN outcomes may better direct future intervention efforts. © Health Research and Educational Trust.

Novel Computational Protocols for Functionally Classifying and Characterising Serine Beta-Lactamases

PubMed Central

Das, Sayoni; Dawson, Natalie L.; Dobrijevic, Dragana; Orengo, Christine

2016-01-01

Beta-lactamases represent the main bacterial mechanism of resistance to beta-lactam antibiotics and are a significant challenge to modern medicine. We have developed an automated classification and analysis protocol that exploits structure- and sequence-based approaches and which allows us to propose a grouping of serine beta-lactamases that more consistently captures and rationalizes the existing three classification schemes: Classes, (A, C and D, which vary in their implementation of the mechanism of action); Types (that largely reflect evolutionary distance measured by sequence similarity); and Variant groups (which largely correspond with the Bush-Jacoby clinical groups). Our analysis platform exploits a suite of in-house and public tools to identify Functional Determinants (FDs), i.e. residue sites, responsible for conferring different phenotypes between different classes, different types and different variants. We focused on Class A beta-lactamases, the most highly populated and clinically relevant class, to identify FDs implicated in the distinct phenotypes associated with different Class A Types and Variants. We show that our FunFHMMer method can separate the known beta-lactamase classes and identify those positions likely to be responsible for the different implementations of the mechanism of action in these enzymes. Two novel algorithms, ASSP and SSPA, allow detection of FD sites likely to contribute to the broadening of the substrate profiles. Using our approaches, we recognise 151 Class A types in UniProt. Finally, we used our beta-lactamase FunFams and ASSP profiles to detect 4 novel Class A types in microbiome samples. Our platforms have been validated by literature studies, in silico analysis and some targeted experimental verification. Although developed for the serine beta-lactamases they could be used to classify and analyse any diverse protein superfamily where sub-families have diverged over both long and short evolutionary timescales. PMID:27332861

Colorectal Cancer Screening: Preferences, Past Behavior, and Future Intentions.

PubMed

Mansfield, Carol; Ekwueme, Donatus U; Tangka, Florence K L; Brown, Derek S; Smith, Judith Lee; Guy, Gery P; Li, Chunyu; Hauber, Brett

2018-05-09

Screening rates for colorectal cancer are below the Healthy People 2020 goal. There are several colorectal cancer screening tests that differ in terms of accuracy, recommended frequency, and administration. In this article, we compare how a set of personal characteristics correlates with preferences for colorectal cancer screening test attributes, past colorectal cancer screening behavior, and future colorectal cancer screening intentions. We conducted a discrete-choice experiment survey to assess relative preferences for attributes of colorectal cancer screening tests among adults aged 50-75 years in USA. We used a latent class logit model to identify classes of preferences and calculated willingness to pay for changes in test attributes. A set of personal characteristics were included in the latent class analysis and analyses of self-reported past screening behavior and self-assessed likelihood of future colorectal cancer screening. Latent class analysis identified three types of respondents. Class 1 valued test accuracy, class 2 valued removing polyps and avoiding discomfort, and class 3 valued cost. Having had a prior colonoscopy and a higher income were predictors of the likelihood of future screening and membership in classes 1 and 2. Health insurance and a self-reported higher risk of developing colorectal cancer were associated with prior screening and higher future screening intentions, but not class membership. We identified distinct classes of preferences focusing on different test features and personal characteristics associated with reported behavior and intentions. Healthcare providers should engage in a careful assessment of patient preferences when recommending colorectal cancer test options to encourage colorectal cancer screening uptake.

Exploring heterogeneity in clinical trials with latent class analysis

PubMed Central

Abarda, Abdallah; Contractor, Ateka A.; Wang, Juan; Dayton, C. Mitchell

2018-01-01

Case-mix is common in clinical trials and treatment effect can vary across different subgroups. Conventionally, a subgroup analysis is performed by dividing the overall study population by one or two grouping variables. It is usually impossible to explore complex high-order intersections among confounding variables. Latent class analysis (LCA) provides a framework to identify latent classes by observed manifest variables. Distal clinical outcomes and treatment effect can be different across these classes. This paper provides a step-by-step tutorial on how to perform LCA with R. A simulated dataset is generated to illustrate the process. In the example, the classify-analyze approach is employed to explore the differential treatment effects on distal outcomes across latent classes. PMID:29955579

Clustering of adversity in young adults on disability pension due to mental disorders: a latent class analysis.

PubMed

Joensuu, Matti; Mattila-Holappa, Pauliina; Ahola, Kirsi; Ervasti, Jenni; Kivimäki, Mika; Kivekäs, Teija; Koskinen, Aki; Vahtera, Jussi; Virtanen, Marianna

2016-02-01

Mental disorders are the leading cause of work disability among young adults. This study examined whether distinct classes could be identified among young adults on the basis of medical history before receiving a disability pension due to a mental disorder. Medical history was obtained from pension applications and attached medical certificates for 1163 individuals aged 18-34 years who, in 2008, received a disability pension due to a mental disorder. Using latent class analysis, 10 clinical and individual adversities and their associations with sex, age and diagnostic category were examined. Three classes were identified: childhood adversity (prevalence, 33%), comorbidity (23%), and undefined (44%). The childhood adversity class was characterized by adverse events and symptoms reported during childhood and it associated with depressive disorders. The comorbidity class was characterized by comorbid mental disorders, suicide attempts and substance abuse and associated with younger age and bipolar disorder. The undefined class formed no distinct profile; individuals in this class had the lowest number of adversities and it associated with psychotic disorders. The identification of subgroups characterized by childhood circumstances and comorbidity may help planning of prevention and support practices for young adults with mental disorders and risk of work disability.

A latent transition analysis of bullying and victimization in Chinese primary school students

PubMed Central

Lau, Puiyi; Luo, Fang

2017-01-01

Bullying is a social phenomenon that impacts a large number of children and young people, worldwide. This study aimed to longitudinally examine the development of bullying and victimization in Chinese students in grades 4, 5, and 6. We used latent class analysis to empirically identify groups of youth with different bullying and victimization patterns, and then used latent transition analysis to explore the movement of children between these latent classes over time. Results showed that: (1) across the three time points, students could be classified into four classes: bullies, victims, bully-victims, and non-involved children; and (2) students in the non-involved class tended to remain in that class when moving to higher grades, students in the bully and victims classes tended to transition to the non-involved class, while students in the bully-victims class tended to transition to the bullies class. Thus, future intervention should be implemented to prevent bully-victims from bullying behaviors. PMID:28837571

Parent–Child Relationships in Stepfather Families and Adolescent Adjustment: A Latent Class Analysis

PubMed Central

Amato, Paul R.; King, Valarie; Thorsen, Maggie L.

2015-01-01

In the current study the authors drew on Waves I and III from Add Health to examine the closeness of parent–adolescent relationships in married mother–stepfather families (N = 1,934). They used latent class analysis to identify family constellations defined by adolescents’ relationships with all of their parents: mothers, stepfathers, and biological nonresident fathers. In particular, the authors (a) identified the most common underlying patterns of adolescent–parent relationships in stepfamilies; (b) determined the background characteristics that predict membership in these groups; and (c) examined how adolescents in these groups fare with respect to depressive symptoms, delinquency, and substance use. The results indicate that adolescents’ relationships can be represented with 4 latent classes. Adolescents in these classes differ on measures of adjustment, and many of these differences persist into the early adult years. PMID:27022199

Bayesian Analysis Of HMI Solar Image Observables And Comparison To TSI Variations And MWO Image Observables

NASA Astrophysics Data System (ADS)

Parker, D. G.; Ulrich, R. K.; Beck, J.

2014-12-01

We have previously applied the Bayesian automatic classification system AutoClass to solar magnetogram and intensity images from the 150 Foot Solar Tower at Mount Wilson to identify classes of solar surface features associated with variations in total solar irradiance (TSI) and, using those identifications, modeled TSI time series with improved accuracy (r > 0.96). (Ulrich, et al, 2010) AutoClass identifies classes by a two-step process in which it: (1) finds, without human supervision, a set of class definitions based on specified attributes of a sample of the image data pixels, such as magnetic field and intensity in the case of MWO images, and (2) applies the class definitions thus found to new data sets to identify automatically in them the classes found in the sample set. HMI high resolution images capture four observables-magnetic field, continuum intensity, line depth and line width-in contrast to MWO's two observables-magnetic field and intensity. In this study, we apply AutoClass to the HMI observables for images from May, 2010 to June, 2014 to identify solar surface feature classes. We use contemporaneous TSI measurements to determine whether and how variations in the HMI classes are related to TSI variations and compare the characteristic statistics of the HMI classes to those found from MWO images. We also attempt to derive scale factors between the HMI and MWO magnetic and intensity observables. The ability to categorize automatically surface features in the HMI images holds out the promise of consistent, relatively quick and manageable analysis of the large quantity of data available in these images. Given that the classes found in MWO images using AutoClass have been found to improve modeling of TSI, application of AutoClass to the more complex HMI images should enhance understanding of the physical processes at work in solar surface features and their implications for the solar-terrestrial environment. Ulrich, R.K., Parker, D, Bertello, L. and Boyden, J. 2010, Solar Phys. , 261 , 11.

Longitudinal burnout-collaboration patterns in Japanese medical care workers at special needs schools: a latent class growth analysis

PubMed Central

Kanayama, Mieko; Suzuki, Machiko; Yuma, Yoshikazu

2016-01-01

The present study aimed to identify and characterize potential burnout types and the relationship between burnout and collaboration over time. Latent class growth analysis and the growth mixture model were used to identify and characterize heterogeneous patterns of longitudinal stability and change in burnout, and the relationship between burnout and collaboration. We collected longitudinal data at three time points based on Japanese academic terms. The 396 study participants included academic teachers, yogo teachers, and registered nurses in Japanese special needs schools. The best model included four types of both burnout and collaboration in latent class growth analysis with intercept, slope, and quadratic terms. The four types of burnout were as follows: low stable, moderate unstable, high unstable, and high decreasing. They were identified as involving inverse collaboration function. The results indicated that there could be dynamic burnout types, namely moderate unstable, high unstable, and high decreasing, when focusing on growth trajectories in latent class analyses. The finding that collaboration was dynamic for dynamic burnout types and stable for stable burnout types is of great interest. This was probably related to the inverse relationship between the two constructs. PMID:27366107

Social space, social class and Bourdieu: health inequalities in British Columbia, Canada.

PubMed

Veenstra, Gerry

2007-03-01

This article adopts Pierre Bourdieu's cultural-structuralist approach to conceptualizing and identifying social classes in social space and seeks to identify health effects of class in one Canadian province. Utilizing data from an original questionnaire survey of randomly selected adults from 25 communities in British Columbia, social (class) groupings defined by cultural tastes and dispositions, lifestyle practices, social background, educational capital, economic capital, social capital and occupational categories are presented in visual mappings of social space constructed by use of exploratory multiple correspondence analysis techniques. Indicators of physical and mental health are then situated within this social space, enabling speculations pertaining to health effects of social class in British Columbia.

Clinical classes of injured workers with chronic low back pain: a latent class analysis with relationship to working status.

PubMed

Carlesso, Lisa C; Raja Rampersaud, Y; Davis, Aileen M

2018-01-01

To determine (a) clinical classes of injured workers with chronic low back pain (CLBP), (b) predictors of class membership and (c) associations of classes with baseline work status. Patients with CLBP from a tertiary care outpatient clinic in Toronto, Canada were sampled. Latent class analysis was applied to determine class structure using physical, psychological and coping indicators. Classes were interpreted by class-specific means and analyzed for predictors of membership. Lastly, association of the classes with being off work was modeled. A 3-class model was chosen based on fit criteria, theoretical and clinical knowledge of this population. The resultant 3 classes represented low, moderate and high levels of clinical severity. Predictors of being in the high severity group compared to the low severity group were < high school education [odds ratio (OR) 3.06, 95% CI (1.47, 6.37)] and comorbidity total [OR 1.28, 95% CI (1.03, 1.59)]. High severity class membership was associated with four times increased risk of being off work at baseline compared to those in the low severity group [OR 3.98, 95% CI (1.61, 6.34)]. In a cohort of injured workers with CLBP, 3 clinical classes were identified with distinct psychological and physical profiles. These profiles are useful in aiding clinicians to identify patients of high clinical severity who may be potentially at risk for problematic return to work.

Multilevel Latent Class Analysis: Parametric and Nonparametric Models

ERIC Educational Resources Information Center

Finch, W. Holmes; French, Brian F.

2014-01-01

Latent class analysis is an analytic technique often used in educational and psychological research to identify meaningful groups of individuals within a larger heterogeneous population based on a set of variables. This technique is flexible, encompassing not only a static set of variables but also longitudinal data in the form of growth mixture…

Arabidopsis Class I and Class II TCP Transcription Factors Regulate Jasmonic Acid Metabolism and Leaf Development Antagonistically1[C][W

PubMed Central

Danisman, Selahattin; van der Wal, Froukje; Dhondt, Stijn; Waites, Richard; de Folter, Stefan; Bimbo, Andrea; van Dijk, Aalt DJ; Muino, Jose M.; Cutri, Lucas; Dornelas, Marcelo C.; Angenent, Gerco C.; Immink, Richard G.H.

2012-01-01

TEOSINTE BRANCHED1/CYCLOIDEA/PROLIFERATING CELL FACTOR1 (TCP) transcription factors control developmental processes in plants. The 24 TCP transcription factors encoded in the Arabidopsis (Arabidopsis thaliana) genome are divided into two classes, class I and class II TCPs, which are proposed to act antagonistically. We performed a detailed phenotypic analysis of the class I tcp20 mutant, showing an increase in leaf pavement cell sizes in 10-d-old seedlings. Subsequently, a glucocorticoid receptor induction assay was performed, aiming to identify potential target genes of the TCP20 protein during leaf development. The LIPOXYGENASE2 (LOX2) and class I TCP9 genes were identified as TCP20 targets, and binding of TCP20 to their regulatory sequences could be confirmed by chromatin immunoprecipitation analyses. LOX2 encodes for a jasmonate biosynthesis gene, which is also targeted by class II TCP proteins that are under the control of the microRNA JAGGED AND WAVY (JAW), although in an antagonistic manner. Mutation of TCP9, the second identified TCP20 target, resulted in increased pavement cell sizes during early leaf developmental stages. Analysis of senescence in the single tcp9 and tcp20 mutants and the tcp9tcp20 double mutants showed an earlier onset of this process in comparison with wild-type control plants in the double mutant only. Both the cell size and senescence phenotypes are opposite to the known class II TCP mutant phenotype in JAW plants. Altogether, these results point to an antagonistic function of class I and class II TCP proteins in the control of leaf development via the jasmonate signaling pathway. PMID:22718775

Characterizing Longitudinal Patterns of Physical Activity in Mid-Adulthood Using Latent Class Analysis: Results From a Prospective Cohort Study

PubMed Central

Silverwood, Richard J.; Nitsch, Dorothea; Pierce, Mary; Kuh, Diana; Mishra, Gita D.

2011-01-01

The authors aimed to describe how longitudinal patterns of physical activity during mid-adulthood (ages 31–53 years) can be characterized using latent class analysis in a population-based birth cohort study, the Medical Research Council’s 1946 National Survey of Health and Development. Three different types of physical activity—walking, cycling, and leisure-time physical activity—were analyzed separately using self-reported data collected from questionnaires between 1977 and 1999; 3,847 study members were included in the analysis for one or more types of activity. Patterns of activity differed by sex, so stratified analyses were conducted. Two walking latent classes were identified representing low (52.8% of males in the cohort, 33.5% of females) and high (47.2%, 66.5%) levels of activity. Similar low (91.4%, 82.1%) and high (8.6%, 17.9%) classes were found for cycling, while 3 classes were identified for leisure-time physical activity: “low activity” (46.2%, 48.2%), “sports and leisure activity” (31.0%, 35.3%), and “gardening and do-it-yourself activities” (22.8%, 16.5%). The classes were reasonably or very well separated, with the exception of walking in females. Latent class analysis was found to be a useful tool for characterizing longitudinal patterns of physical activity, even when the measurement instrument differs slightly across ages, which added value in comparison with observed activity at a single age. PMID:22074812

Patterns of Alcohol Policy Enforcement Activities among Local Law Enforcement Agencies: A Latent Class Analysis

PubMed Central

Erickson, Darin J.; Rutledge, Patricia C.; Lenk, Kathleen M.; Nelson, Toben F.; Jones-Webb, Rhonda; Toomey, Traci L.

2015-01-01

Aims We assessed levels and patterns of alcohol policy enforcement activities among U.S. local law enforcement agencies. Design/Setting/Participants We conducted a cross-sectional survey of a representative sample of 1,631 local law enforcement agencies across the 50 states. Measures/Methods We assessed 29 alcohol policy enforcement activities within each of five enforcement domains—underage alcohol possession/consumption, underage alcohol provision, underage alcohol sales, impaired driving, and overservice of alcohol—and conducted a series of latent class analyses to identify unique classes or patterns of enforcement activity for each domain. Findings We identified three to four unique enforcement activity classes for each of the enforcement domains. In four of the domains, we identified a Uniformly Low class (i.e., little or no enforcement) and a Uniformly High enforcement activity class (i.e., relatively high levels of enforcement), with one or two middle classes where some but not all activities were conducted. The underage provision domain had a Uniformly Low class but not a Uniformly High class. The Uniformly Low class was the most prevalent class in three domains: underage provision (58%), underage sales (61%), and overservice (79%). In contrast, less than a quarter of agencies were in Uniformly High classes. Conclusions We identified qualitatively distinct patterns of enforcement activity, with a large proportion of agencies in classes characterized by little or no enforcement and fewer agencies in high enforcement classes. An important next step is to determine if these patterns are associated with rates of alcohol use and alcohol-related injury and mortality. PMID:26877822

Questions of Degree? Middle-Class Rejection of Higher Education and Intra-Class Differences in Educational Decision-Making

ERIC Educational Resources Information Center

Morrison, Andrew

2011-01-01

This article is an analysis of middle-class rejection of higher education. The author uses accounts of the educational decision-making of three female students, all identified to be from broadly middle-class backgrounds, from within full-time vocational further education in the United Kingdom, as a means to consider two issues. First, the author…

Latent profile analysis of sixth graders based on teacher ratings: Association with school dropout.

PubMed

Orpinas, Pamela; Raczynski, Katherine; Peters, Jaclyn Wetherington; Colman, Laura; Bandalos, Deborah

2015-12-01

The goal of this study was to identify meaningful groups of sixth graders with common characteristics based on teacher ratings of assets and maladaptive behaviors, describe dropout rates for each group, and examine the validity of these groups using students' self-reports. The sample consisted of racially diverse students (n = 675) attending sixth grade in public schools in Northeast Georgia. The majority of the sample was randomly selected; a smaller group was identified by teachers as high risk for aggression. Based on teacher ratings of externalizing behaviors, internalizing problems, academic skills, leadership, and social assets, latent profile analysis yielded 7 classes that can be displayed along a continuum: Well-Adapted, Average, Average-Social Skills Deficit, Internalizing, Externalizing, Disruptive Behavior with School Problems, and Severe Problems. Dropout rate was lowest for the Well-adapted class (4%) and highest for the Severe Problems class (58%). However, students in the Average-Social Skills Deficit class did not follow the continuum, with a large proportion of students who abandoned high school (29%). The proportion of students identified by teachers as high in aggression consistently increased across the continuum from none in the Well-Adapted class to 84% in the Severe Problems class. Students' self-reports were generally consistent with the latent profile classes. Students in the Well-Adapted class reported low aggression, drug use, and delinquency, and high life satisfaction; self-reports went in the opposite direction for the Disruptive Behaviors with School Problems class. Results highlight the importance of early interventions to improve academic performance, reduce externalizing behaviors, and enhance social assets. (c) 2015 APA, all rights reserved).

Studying Psychosocial Barriers to Drug Treatment Among Chinese Methamphetamine Users Using A 3-Step Latent Class Analysis.

PubMed

Wang, Jichuan; Kelly, Brian C; Liu, Tieqiao; Hao, Wei

2016-03-01

Given the growth in methamphetamine use in China during the 21st century, we assessed perceived psychosocial barriers to drug treatment among this population. Using a sample of 303 methamphetamine users recruited via Respondent Driven Sampling, we use Latent Class Analysis (LCA) to identify possible distinct latent groups among Chinese methamphetamine users on the basis of their perceptions of psychosocial barriers to drug treatment. After covariates were included to predict latent class membership, the 3-step modeling approach was applied. Our findings indicate that the Chinese methamphetamine using population was heterogeneous on perceptions of drug treatment barriers; four distinct latent classes (subpopulations) were identified--Unsupported Deniers, Deniers, Privacy Anxious, and Low Barriers--and individual characteristics shaped the probability of class membership. Efforts to link Chinese methamphetamine users to treatment may require a multi-faceted approach that attends to differing perceptions about impediments to drug treatment. Copyright © 2015. Published by Elsevier Inc.

Examining Variation in Adolescent Bystanders' Responses to Bullying

ERIC Educational Resources Information Center

Waasdorp, Tracy Evian; Bradshaw, Catherine P.

2018-01-01

Latent class analysis was used to examine whether patterns of bystander responses varied as a function of both student- and school-level characteristics. Data from 18,863 high school students from 58 schools who "ever witnessed bullying" were used to identify five latent classes of bystander behavior. Three of the classes identified…

Analysis of Frequency of Tests and Varying Feedback Delays in College Mathematics Achievement

ERIC Educational Resources Information Center

Townsend, Neal R.; Wheatley, Grayson H.

1975-01-01

Sixteen beginning analytic geometry and calculus classes (442 students) followed eight testing regimes for one academic quarter. Three aptitude subgroups were identified in each class. Classes to which daily quizzes were given achieved significantly higher on a specially constructed test than those which had only a single midterm examination.…

Characterisation of a type 1 Avian Paramyxovirus belonging to a divergent group.

PubMed

Briand, François-Xavier; Massin, Pascale; Jestin, Véronique

2014-01-10

Newcastle disease, induced by a type 1 Avian Paramyxovirus (APMV-1), is one of the most serious poultry diseases. APMV-1 are divided into two classes based on genetic analysis: class II strains have been recovered from wild or domestic birds and include virulent and avirulent isolates whereas class I strains have been mainly isolated from wild birds and are avirulent. Within class I, a new proposed genotype has recently been reported. The only full genome strain of this group is presently characterised from the point of view of codon usage with reference to class I and class II specificities. Class-specific residues were identified on HN and F proteins that are the two major proteins involved in cell attachment and pathogenicity. Comparison of protein patterns and codon usage for this newly identified APMV-1 strain indicates it is similar to class I viruses but contains a few characteristics close to the viruses of class II. Transmission of viruses from this recently identified divergent group from wild birds to domestic birds could have a major impact on the domestic poultry industry. Copyright © 2013 Elsevier B.V. All rights reserved.

The job content questionnaire in various occupational contexts: applying a latent class model

PubMed Central

Santos, Kionna Oliveira Bernardes; de Araújo, Tânia Maria; Karasek, Robert

2017-01-01

Objective To evaluate Job Content Questionnaire(JCQ) performance using the latent class model. Methods We analysed cross-sectional studies conducted in Brazil and examined three occupational categories: petroleum industry workers (n=489), teachers (n=4392) and primary healthcare workers (3078)and 1552 urban workers from a representative sample of the city of Feira de Santana in Bahia, Brazil. An appropriate number of latent classes was extracted and described each occupational category using latent class analysis, a multivariate method that evaluates constructs and takes into account the latent characteristics underlying the structure of measurement scales. The conditional probabilities of workers belonging to each class were then analysed graphically. Results Initially, the latent class analysis extracted four classes corresponding to the four job types (active, passive, low strain and high strain) proposed by the Job-Strain model (JSM) and operationalised by the JCQ. However, after taking into consideration the adequacy criteria to evaluate the number of extracted classes, three classes (active, low strain and high strain) were extracted from the studies of urban workers and teachers and four classes (active, passive, low strain and high strain) from the study of primary healthcare and petroleum industry workers. Conclusion The four job types proposed by the JSM were identified among primary healthcare and petroleum industry workers—groups with relatively high levels of skill discretion and decision authority. Three job types were identified for teachers and urban workers; however, passive job situations were not found within these groups. The latent class analysis enabled us to describe the conditional standard responses of the job types proposed by the model, particularly in relation to active jobs and high and low strain situations. PMID:28515185

Multilevel Latent Class Analysis: An Application of Adolescent Smoking Typologies with Individual and Contextual Predictors

ERIC Educational Resources Information Center

Henry, Kimberly L.; Muthen, Bengt

2010-01-01

Latent class analysis (LCA) is a statistical method used to identify subtypes of related cases using a set of categorical or continuous observed variables. Traditional LCA assumes that observations are independent. However, multilevel data structures are common in social and behavioral research and alternative strategies are needed. In this…

Exploring the Relationship between Autism Spectrum Disorder and Epilepsy Using Latent Class Cluster Analysis

ERIC Educational Resources Information Center

Cuccaro, Michael L.; Tuchman, Roberto F.; Hamilton, Kara L.; Wright, Harry H.; Abramson, Ruth K.; Haines, Jonathan L.; Gilbert, John R.; Pericak-Vance, Margaret

2012-01-01

Epilepsy co-occurs frequently in autism spectrum disorders (ASD). Understanding this co-occurrence requires a better understanding of the ASD-epilepsy phenotype (or phenotypes). To address this, we conducted latent class cluster analysis (LCCA) on an ASD dataset (N = 577) which included 64 individuals with epilepsy. We identified a 5-cluster…

Applying Latent Class Analysis to Risk Stratification for Perioperative Mortality in Patients Undergoing Intraabdominal General Surgery.

PubMed

Kim, Minjae; Wall, Melanie M; Li, Guohua

2016-07-01

Perioperative risk stratification is often performed using individual risk factors without consideration of the syndemic of these risk factors. We used latent class analysis (LCA) to identify the classes of comorbidities and risk factors associated with perioperative mortality in patients presenting for intraabdominal general surgery. The 2005 to 2010 American College of Surgeons National Surgical Quality Improvement Program was used to obtain a cohort of patients undergoing intraabdominal general surgery. Risk factors and comorbidities were entered into LCA models to identify the latent classes, and individuals were assigned to a class based on the highest posterior probability of class membership. Relative risk regression was used to determine the associations between the latent classes and 30-day mortality, with adjustments for procedure. A 9-class model was fit using LCA on 466,177 observations. After combining classes with similar adjusted mortality risks, 5 risk classes were obtained. Compared with the class with average mortality risk (class 4), the risk ratios (95% confidence interval) ranged from 0.020 (0.014-0.027) in the lowest risk class (class 1) to 6.75 (6.46-7.02) in the highest risk class. After adjusting for procedure and ASA physical status, the latent classes remained significantly associated with 30-day mortality. The addition of the risk class variable to a model containing ASA physical status and surgical procedure demonstrated a significant increase in the area under the receiver operator characteristic curve (0.892 vs 0.915; P < 0.0001). Latent classes of risk factors and comorbidities in patients undergoing intraabdominal surgery are predictive of 30-day mortality independent of the ASA physical status and improve risk prediction with the ASA physical status.

The association between school exclusion, delinquency and subtypes of cyber- and F2F-victimizations: identifying and predicting risk profiles and subtypes using latent class analysis.

PubMed

Barboza, Gia Elise

2015-01-01

This purpose of this paper is to identify risk profiles of youth who are victimized by on- and offline harassment and to explore the consequences of victimization on school outcomes. Latent class analysis is used to explore the overlap and co-occurrence of different clusters of victims and to examine the relationship between class membership and school exclusion and delinquency. Participants were a random sample of youth between the ages of 12 and 18 selected for inclusion to participate in the 2011 National Crime Victimization Survey: School Supplement. The latent class analysis resulted in four categories of victims: approximately 3.1% of students were highly victimized by both bullying and cyberbullying behaviors; 11.6% of youth were classified as being victims of relational bullying, verbal bullying and cyberbullying; a third class of students were victims of relational bullying, verbal bullying and physical bullying but were not cyberbullied (8%); the fourth and final class, characteristic of the majority of students (77.3%), was comprised of non-victims. The inclusion of covariates to the latent class model indicated that gender, grade and race were significant predictors of at least one of the four victim classes. School delinquency measures were included as distal outcomes to test for both overall and pairwise associations between classes. With one exception, the results were indicative of a significant relationship between school delinquency and the victim subtypes. Implications for these findings are discussed. Copyright © 2014 Elsevier Ltd. All rights reserved.

Latent Cognitive Phenotypes in De Novo Parkinson's Disease: A Person-Centered Approach.

PubMed

LaBelle, Denise R; Walsh, Ryan R; Banks, Sarah J

2017-08-01

Cognitive impairment is an important aspect of Parkinson's disease (PD), but there is considerable heterogeneity in its presentation. This investigation aims to identify and characterize latent cognitive phenotypes in early PD. Latent class analysis, a data-driven, person-centered, cluster analysis was performed on cognitive data from the Parkinson's Progressive Markers Initiative baseline visit. This analytic method facilitates identification of naturally occurring endophenotypes. Resulting classes were compared across biomarker, symptom, and demographic data. Six cognitive phenotypes were identified. Three demonstrated consistent performance across indicators, representing poor ("Weak-Overall"), average ("Typical-Overall"), and strong ("Strong-Overall") cognition. The remaining classes demonstrated unique patterns of cognition, characterized by "Strong-Memory," "Weak-Visuospatial," and "Amnestic" profiles. The Amnestic class evidenced greater tremor severity and anosmia, but was unassociated with biomarkers linked with Alzheimer's disease. The Weak-Overall class was older and reported more non-motor features associated with cognitive decline, including anxiety, depression, autonomic dysfunction, anosmia, and REM sleep behaviors. The Strong-Overall class was younger, more female, and reported less dysautonomia and anosmia. Classes were unrelated to disease duration, functional independence, or available biomarkers. Latent cognitive phenotypes with focal patterns of impairment were observed in recently diagnosed individuals with PD. Cognitive profiles were found to be independent of traditional biomarkers and motoric indices of disease progression. Only globally impaired class was associated with previously reported indicators of cognitive decline, suggesting this group may drive the effects reported in studies using variable-based analysis. Longitudinal and neuroanatomical characterization of classes will yield further insight into the evolution of cognitive change in the disease. (JINS, 2017, 23, 551-563).

Do Plants Contain G Protein-Coupled Receptors?1[C][W][OPEN

PubMed Central

Taddese, Bruck; Upton, Graham J.G.; Bailey, Gregory R.; Jordan, Siân R.D.; Abdulla, Nuradin Y.; Reeves, Philip J.; Reynolds, Christopher A.

2014-01-01

Whether G protein-coupled receptors (GPCRs) exist in plants is a fundamental biological question. Interest in deorphanizing new GPCRs arises because of their importance in signaling. Within plants, this is controversial, as genome analysis has identified 56 putative GPCRs, including G protein-coupled receptor1 (GCR1), which is reportedly a remote homolog to class A, B, and E GPCRs. Of these, GCR2 is not a GPCR; more recently, it has been proposed that none are, not even GCR1. We have addressed this disparity between genome analysis and biological evidence through a structural bioinformatics study, involving fold recognition methods, from which only GCR1 emerges as a strong candidate. To further probe GCR1, we have developed a novel helix-alignment method, which has been benchmarked against the class A-class B-class F GPCR alignments. In addition, we have presented a mutually consistent set of alignments of GCR1 homologs to class A, class B, and class F GPCRs and shown that GCR1 is closer to class A and/or class B GPCRs than class A, class B, or class F GPCRs are to each other. To further probe GCR1, we have aligned transmembrane helix 3 of GCR1 to each of the six GPCR classes. Variability comparisons provide additional evidence that GCR1 homologs have the GPCR fold. From the alignments and a GCR1 comparative model, we have identified motifs that are common to GCR1, class A, B, and E GPCRs. We discuss the possibilities that emerge from this controversial evidence that GCR1 has a GPCR fold. PMID:24246381

Flipped Class - Making that One Hour Effective in a Resource Constrained Setting.

PubMed

Zafar, Afsheen

2016-09-01

Flipped-class teaching has a great potential to replace traditional lectures in medical education. This study was designed to explore attitude of undergraduate medical students from Pakistan towards flipped-class. Five flipped classes were conducted in third year MBBS by a single teacher for a class of 100 students. Quantitative data was collected through a survey questionnaire to assess students' response to the new method. Afocused group discussion was then conducted with students who disliked the method and preferred traditional lectures. Asequential mixed methods approach was used for analysis. Seventy-one students participated in the survey, 84.5% students liked this method of teaching. Students identified fruitful interaction, better retention, better conceptualisation, prior knowledge, active learning, individual student attention, and application of knowledge as strengths of the class. Noise, limited time, lack of self-confidence, and presence of uninterested students were identified as problems for engaging in the class.

Dynamic transcriptomic analysis in hircine longissimus dorsi muscle from fetal to neonatal development stages.

PubMed

Zhan, Siyuan; Zhao, Wei; Song, Tianzeng; Dong, Yao; Guo, Jiazhong; Cao, Jiaxue; Zhong, Tao; Wang, Linjie; Li, Li; Zhang, Hongping

2018-01-01

Muscle growth and development from fetal to neonatal stages consist of a series of delicately regulated and orchestrated changes in expression of genes. In this study, we performed whole transcriptome profiling based on RNA-Seq of caprine longissimus dorsi muscle tissue obtained from prenatal stages (days 45, 60, and 105 of gestation) and neonatal stage (the 3-day-old newborn) to identify genes that are differentially expressed and investigate their temporal expression profiles. A total of 3276 differentially expressed genes (DEGs) were identified (Q value < 0.01). Time-series expression profile clustering analysis indicated that DEGs were significantly clustered into eight clusters which can be divided into two classes (Q value < 0.05), class I profiles with downregulated patterns and class II profiles with upregulated patterns. Based on cluster analysis, GO enrichment analysis found that 75, 25, and 8 terms to be significantly enriched in biological process (BP), cellular component (CC), and molecular function (MF) categories in class I profiles, while 35, 21, and 8 terms to be significantly enriched in BP, CC, and MF in class II profiles. KEGG pathway analysis revealed that DEGs from class I profiles were significantly enriched in 22 pathways and the most enriched pathway was Rap1 signaling pathway. DEGs from class II profiles were significantly enriched in 17 pathways and the mainly enriched pathway was AMPK signaling pathway. Finally, six selected DEGs from our sequencing results were confirmed by qPCR. Our study provides a comprehensive understanding of the molecular mechanisms during goat skeletal muscle development from fetal to neonatal stages and valuable information for future studies of muscle development in goats.

Combined Patterns of Risk for Problem and Obesogenic Behaviors in Adolescents: A Latent Class Analysis Approach

ERIC Educational Resources Information Center

Fleary, Sasha A.

2017-01-01

Background: Several studies have used latent class analyses to explore obesogenic behaviors and substance use in adolescents independently. We explored a variety of health risks jointly to identify distinct patterns of risk behaviors among adolescents. Methods: Latent class models were estimated using Youth Risk Behavior Surveillance System…

Variations in Care Quality Outcomes of Dying People: Latent Class Analysis of an Adult National Register Population.

PubMed

Öhlén, Joakim; Russell, Lara; Håkanson, Cecilia; Alvariza, Anette; Fürst, Carl Johan; Årestedt, Kristofer; Sawatzky, Richard

2017-01-01

Symptom relief is a key goal of palliative care. There is a need to consider complexities in symptom relief patterns for groups of people to understand and evaluate symptom relief as an indicator of quality of care at end of life. The aims of this study were to distinguish classes of patients who have different symptom relief patterns during the last week of life and to identify predictors of these classes in an adult register population. In a cross-sectional retrospective design, data were used from 87,026 decedents with expected deaths registered in the Swedish Register of Palliative Care in 2011 and 2012. Study variables were structured into patient characteristics, and processes and outcomes of quality of care. A latent class analysis was used to identify symptom relief patterns. Multivariate multinomial regression analyses were used to identify predictors of class membership. Five latent classes were generated: "relieved pain," "relieved pain and rattles," "relieved pain and anxiety," "partly relieved shortness of breath, rattles and anxiety," and "partly relieved pain, anxiety and confusion." Important predictors of class membership were age, sex, cause of death, and having someone present at death, individual prescriptions as needed (PRN) and expert consultations. Interindividual variability and complexity in symptom relief patterns may inform quality of care and its evaluation for dying people across care settings. Copyright © 2016 American Academy of Hospice and Palliative Medicine. Published by Elsevier Inc. All rights reserved.

Friendship networks of inner-city adults: a latent class analysis and multi-level regression of supporter types and the association of supporter latent class membership with supporter and recipient drug use.

PubMed

Bohnert, Amy S B; German, Danielle; Knowlton, Amy R; Latkin, Carl A

2010-03-01

Social support is a multi-dimensional construct that is important to drug use cessation. The present study identified types of supportive friends among the social network members in a community-based sample and examined the relationship of supporter-type classes with supporter, recipient, and supporter-recipient relationship characteristics. We hypothesized that the most supportive network members and their support recipients would be less likely to be current heroin/cocaine users. Participants (n=1453) were recruited from low-income neighborhoods with a high prevalence of drug use. Participants identified their friends via a network inventory, and all nominated friends were included in a latent class analysis and grouped based on their probability of providing seven types of support. These latent classes were included as the dependent variable in a multi-level regression of supporter drug use, recipient drug use, and other characteristics. The best-fitting latent class model identified five support patterns: friends who provided Little/No Support, Low/Moderate Support, High Support, Socialization Support, and Financial Support. In bivariate models, friends in the High, Low/Moderate, and Financial Support were less likely to use heroin or cocaine and had less conflict with and were more trusted by the support recipient than friends in the Low/No Support class. Individuals with supporters in those same support classes compared to the Low/No Support class were less likely to use heroin or cocaine, or to be homeless or female. Multivariable models suggested similar trends. Those with current heroin/cocaine use were less likely to provide or receive comprehensive support from friends. Published by Elsevier Ireland Ltd.

Identifying a combined construct of grief and explosive anger as a response to injustice amongst survivors of mass conflict: A latent class analysis of data from Timor-Leste.

PubMed

Rees, Susan J; Tay, Alvin Kuowei; Savio, Elisa; Maria Da Costa, Zelia; Silove, Derrick

2017-01-01

Previous studies have identified high rates of explosive anger amongst post-conflict populations including Timor-Leste. We sought to test whether explosive anger was integrally associated with symptoms of grief amongst the Timorese, a society that has experienced extensive conflict-related losses. In 2010 and 2011 we recruited adults (n = 2964), 18-years and older, living in an urban and a rural village in Timor-Leste. We applied latent class analysis to identify subpopulations based on symptoms of explosive anger and grief. The best fitting model comprised three classes: grief (24%), grief-anger (25%), and a low symptom group (51%). There were more women and urban dwellers in the grief and grief-anger classes compared to the reference class. Persons in the grief and grief-anger classes experienced higher rates of witnessing murder and atrocities and traumatic losses, ongoing poverty, and preoccupations with injustice for the two historical periods of conflict (the Indonesian occupation and the later internal conflict). Compared to the reference class, only the grief-anger class reported greater exposure to extreme deprivations during the conflict, ongoing family conflict, and preoccupations with injustice for contemporary times; and compared to the grief class, greater exposure to traumatic losses, poverty, family conflict and preoccupations with injustice for both the internal conflict and contemporary times. A substantial number of adults in this post-conflict country experienced a combined constellation of grief and explosive anger associated with extensive traumatic losses, deprivations, and preoccupations with injustice. Importantly, grief-anger may be linked to family conflict in this post-conflict environment.

Identifying a combined construct of grief and explosive anger as a response to injustice amongst survivors of mass conflict: A latent class analysis of data from Timor-Leste

PubMed Central

Rees, Susan J.; Tay, Alvin Kuowei; Savio, Elisa; Maria Da Costa, Zelia; Silove, Derrick

2017-01-01

Previous studies have identified high rates of explosive anger amongst post-conflict populations including Timor-Leste. We sought to test whether explosive anger was integrally associated with symptoms of grief amongst the Timorese, a society that has experienced extensive conflict-related losses. In 2010 and 2011 we recruited adults (n = 2964), 18-years and older, living in an urban and a rural village in Timor-Leste. We applied latent class analysis to identify subpopulations based on symptoms of explosive anger and grief. The best fitting model comprised three classes: grief (24%), grief-anger (25%), and a low symptom group (51%). There were more women and urban dwellers in the grief and grief-anger classes compared to the reference class. Persons in the grief and grief-anger classes experienced higher rates of witnessing murder and atrocities and traumatic losses, ongoing poverty, and preoccupations with injustice for the two historical periods of conflict (the Indonesian occupation and the later internal conflict). Compared to the reference class, only the grief-anger class reported greater exposure to extreme deprivations during the conflict, ongoing family conflict, and preoccupations with injustice for contemporary times; and compared to the grief class, greater exposure to traumatic losses, poverty, family conflict and preoccupations with injustice for both the internal conflict and contemporary times. A substantial number of adults in this post-conflict country experienced a combined constellation of grief and explosive anger associated with extensive traumatic losses, deprivations, and preoccupations with injustice. Importantly, grief-anger may be linked to family conflict in this post-conflict environment. PMID:28430793

Developmental Typologies of Identity Formation and Adjustment in Female Emerging Adults: A Latent Class Growth Analysis Approach

ERIC Educational Resources Information Center

Luyckx, Koen; Schwartz, Seth J.; Goossens, Luc; Soenens, Bart; Beyers, Wim

2008-01-01

The developmental interplay between identity and adjustment was examined in a seven-wave longitudinal study of 428 European female college students (M[subscript age] = 18.8 years) over a period of 3 years, with semi-annual measurement waves each year. Latent Class Growth Analysis (LCGA) was used to identify developmental typologies of both…

Discontinuous Patterns of Cigarette Smoking From Ages 18 to 50 in the United States: A Repeated-Measures Latent Class Analysis.

PubMed

Terry-McElrath, Yvonne M; O'Malley, Patrick M; Johnston, Lloyd D

2017-12-13

Effective cigarette smoking prevention and intervention programming is enhanced by accurate understanding of developmental smoking pathways across the life span. This study investigated within-person patterns of cigarette smoking from ages 18 to 50 among a US national sample of high school graduates, focusing on identifying ages of particular importance for smoking involvement change. Using data from approximately 15,000 individuals participating in the longitudinal Monitoring the Future study, trichotomous measures of past 30-day smoking obtained at 11 time points were modeled using repeated-measures latent class analyses. Sex differences in latent class structure and membership were examined. Twelve latent classes were identified: three characterized by consistent smoking patterns across age (no smoking; smoking < pack per day; smoking pack + per day); three showing uptake to a higher category of smoking across age; four reflecting successful quit behavior by age 50; and two defined by discontinuous shifts between smoking categories. The same latent class structure was found for both males and females, but membership probabilities differed between sexes. Although evidence of increases or decreases in smoking behavior was observed at virtually all ages through 35, 21/22 and 29/30 appeared to be particularly key for smoking category change within class. This examination of latent classes of cigarette smoking among a national US longitudinal sample of high school graduates from ages 18 to 50 identified unique patterns and critical ages of susceptibility to change in smoking category within class. Such information may be of particular use in developing effective smoking prevention and intervention programming. This study examined cigarette smoking among a national longitudinal US sample of high school graduates from ages 18 to 50 and identified distinct latent classes characterized by patterns of movement between no cigarette use, light-to-moderate smoking, and the conventional definition of heavy smoking at 11 time points via repeated-measures latent class analysis. Membership probabilities for each smoking class were estimated, and critical ages of susceptibility to change in smoking behaviors were identified. © The Author 2017. Published by Oxford University Press on behalf of the Society for Research on Nicotine and Tobacco. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Is scaffold hopping a reliable indicator for the ability of computational methods to identify structurally diverse active compounds?

NASA Astrophysics Data System (ADS)

Dimova, Dilyana; Bajorath, Jürgen

2017-07-01

Computational scaffold hopping aims to identify core structure replacements in active compounds. To evaluate scaffold hopping potential from a principal point of view, regardless of the computational methods that are applied, a global analysis of conventional scaffolds in analog series from compound activity classes was carried out. The majority of analog series was found to contain multiple scaffolds, thus enabling the detection of intra-series scaffold hops among closely related compounds. More than 1000 activity classes were found to contain increasing proportions of multi-scaffold analog series. Thus, using such activity classes for scaffold hopping analysis is likely to overestimate the scaffold hopping (core structure replacement) potential of computational methods, due to an abundance of artificial scaffold hops that are possible within analog series.

Patient factors and quality of life outcomes differ among four subgroups of oncology patients based on symptom occurrence.

PubMed

Astrup, Guro Lindviksmoen; Hofsø, Kristin; Bjordal, Kristin; Guren, Marianne Grønlie; Vistad, Ingvild; Cooper, Bruce; Miaskowski, Christine; Rustøen, Tone

2017-03-01

Reviews of the literature on symptoms in oncology patients undergoing curative treatment, as well as patients receiving palliative care, suggest that they experience multiple, co-occurring symptoms and side effects. The purposes of this study were to determine if subgroups of oncology patients could be identified based on symptom occurrence rates and if these subgroups differed on a number of demographic and clinical characteristics, as well as on quality of life (QoL) outcomes. Latent class analysis (LCA) was used to identify subgroups (i.e. latent classes) of patients with distinct symptom experiences based on the occurrence rates for the 13 most common symptoms from the Memorial Symptom Assessment Scale. In total, 534 patients with breast, head and neck, colorectal, or ovarian cancer participated. Four latent classes of patients were identified based on probability of symptom occurrence: all low class [i.e. low probability for all symptoms (n = 152)], all high class (n = 149), high psychological class (n = 121), and low psychological class (n = 112). Patients in the all high class were significantly younger compared with patients in the all low class. Furthermore, compared to the other three classes, patients in the all high class had lower functional status and higher comorbidity scores, and reported poorer QoL scores. Patients in the high and low psychological classes had a moderate probability of reporting physical symptoms. Patients in the low psychological class reported a higher number of symptoms, a lower functional status, and poorer physical and total QoL scores. Distinct subgroups of oncology patients can be identified based on symptom occurrence rates. Patient characteristics that are associated with these subgroups can be used to identify patients who are at greater risk for multiple co-occurring symptoms and diminished QoL, so that these patients can be offered appropriate symptom management interventions.

Attachment in psychosis: A latent profile analysis of attachment styles and association with symptoms in a large psychosis cohort.

PubMed

Bucci, Sandra; Emsley, Richard; Berry, Katherine

2017-01-01

Attachment has been identified as one of various possible mechanisms involved in understanding models of psychosis, but measures that reliably and validly assess attachment styles in psychosis are limited. The aim of this study was to identify attachment patterns in psychosis and examine demographic and clinical correlates across attachment groups. Latent profile analysis on attachment data from 588 participants who met criteria for non-affective psychosis was used to classify people into attachment classes. Four latent classes of attachment were identified: secure, insecure-anxious, insecure-avoidant and disorganised. Secure attachment was the most common attachment style, suggesting that a significant number of clients with psychosis are inherently resilient. Disorganised attachment was associated with a higher proportion of sexual and physical abuse and more severe positive symptoms compared to other attachment classes. This is not only the largest study to examine attachment styles, their demographic and clinical profile, and the clinical profile of disorganised attachment more specifically, in psychosis, but also the first study to use a validated self-report measure of attachment in psychosis to identify four classes of attachment style. Findings advance developmental models of attachment and psychosis; participants with disorganised attachment report more frequent trauma history and more severe psychotic symptoms. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Multiple Chronic Conditions and Hospitalizations Among Recipients of Long-Term Services and Supports

PubMed Central

Van Cleave, Janet H.; Egleston, Brian L.; Abbott, Katherine M.; Hirschman, Karen B.; Rao, Aditi; Naylor, Mary D.

2016-01-01

Background Among older adults receiving long term-services and supports (LTSS), debilitating hospitalizations is a pervasive clinical and research problem. Multiple chronic conditions (MCC) are prevalent in LTSS recipients. However, the combination of MCC and diseases associated with hospitalizations of LTSS recipients is unclear. Objective The purpose of this analysis was to determine the association between classes of MCC in newly enrolled LTSS recipients and the number of hospitalizations over a one-year period following enrollment. Methods This report is based on secondary analysis of extant data from a longitudinal cohort study of 470 new recipients of LTSS, ages 60 years and older, receiving services in assisted living facilities, nursing homes, or through home- and community-based services. Using baseline chronic conditions reported in medical records, latent class analysis (LCA) was used to identify classes of MCC and posterior probabilities of membership in each class. Poisson regressions were used to estimate the relative ratio between posterior probabilities of class membership and number of hospitalizations during the 3 month period prior to the start of LTSS (baseline) and then every three months forward through 12 months. Results Three latent MCC-based classes named Cardiopulmonary, Cerebrovascular/Paralysis, and All Other Conditions were identified. The Cardiopulmonary class was associated with elevated numbers of hospitalization compared to the All Other Conditions class (relative ratio [RR] = 1.88, 95% CI [1.33, 2.65], p < .001). Conclusion Older LTSS recipients with a combination of MCCs that includes cardiopulmonary conditions have increased risk for hospitalization. PMID:27801713

Likelihood analysis of spatial capture-recapture models for stratified or class structured populations

USGS Publications Warehouse

Royle, J. Andrew; Sutherland, Christopher S.; Fuller, Angela K.; Sun, Catherine C.

2015-01-01

We develop a likelihood analysis framework for fitting spatial capture-recapture (SCR) models to data collected on class structured or stratified populations. Our interest is motivated by the necessity of accommodating the problem of missing observations of individual class membership. This is particularly problematic in SCR data arising from DNA analysis of scat, hair or other material, which frequently yields individual identity but fails to identify the sex. Moreover, this can represent a large fraction of the data and, given the typically small sample sizes of many capture-recapture studies based on DNA information, utilization of the data with missing sex information is necessary. We develop the class structured likelihood for the case of missing covariate values, and then we address the scaling of the likelihood so that models with and without class structured parameters can be formally compared regardless of missing values. We apply our class structured model to black bear data collected in New York in which sex could be determined for only 62 of 169 uniquely identified individuals. The models containing sex-specificity of both the intercept of the SCR encounter probability model and the distance coefficient, and including a behavioral response are strongly favored by log-likelihood. Estimated population sex ratio is strongly influenced by sex structure in model parameters illustrating the importance of rigorous modeling of sex differences in capture-recapture models.

Psychometric properties and a latent class analysis of the 12-item World Health Organization Disability Assessment Schedule 2.0 (WHODAS 2.0) in a pooled dataset of community samples.

PubMed

MacLeod, Melissa A; Tremblay, Paul F; Graham, Kathryn; Bernards, Sharon; Rehm, Jürgen; Wells, Samantha

2016-12-01

The 12-item World Health Organization Disability Assessment Schedule 2.0 (WHODAS 2.0) is a brief measurement tool used cross-culturally to capture the multi-dimensional nature of disablement through six domains, including: understanding and interacting with the world; moving and getting around; self-care; getting on with people; life activities; and participation in society. Previous psychometric research supports that the WHODAS 2.0 functions as a general factor of disablement. In a pooled dataset from community samples of adults (N = 447) we used confirmatory factor analysis to confirm a one-factor structure. Latent class analysis was used to identify subgroups of individuals based on their patterns of responses. We identified four distinct classes, or patterns of disablement: (1) pervasive disability; (2) physical disability; (3) emotional, cognitive, or interpersonal disability; (4) no/low disability. Convergent validity of the latent class subgroups was found with respect to socio-demographic characteristics, number of days affected by disabilities, stress, mental health, and substance use. These classes offer a simple and meaningful way to classify people with disabilities based on the 12-item WHODAS 2.0. Focusing on individuals with a high probability of being in the first three classes may help guide interventions. Copyright © 2016 John Wiley & Sons, Ltd.

Substance Use, Violence, and Antiretroviral Adherence: A Latent Class Analysis of Women Living with HIV in Canada.

PubMed

Carter, Allison; Roth, Eric Abella; Ding, Erin; Milloy, M-J; Kestler, Mary; Jabbari, Shahab; Webster, Kath; de Pokomandy, Alexandra; Loutfy, Mona; Kaida, Angela

2018-03-01

We used latent class analysis to identify substance use patterns for 1363 women living with HIV in Canada and assessed associations with socio-economic marginalization, violence, and sub-optimal adherence to combination antiretroviral therapy (cART). A six-class model was identified consisting of: abstainers (26.3%), Tobacco Users (8.81%), Alcohol Users (31.9%), 'Socially Acceptable' Poly-substance Users (13.9%), Illicit Poly-substance Users (9.81%) and Illicit Poly-substance Users of All Types (9.27%). Multinomial logistic regression showed that women experiencing recent violence had significantly higher odds of membership in all substance use latent classes, relative to Abstainers, while those reporting sub-optimal cART adherence had higher odds of being members of the poly-substance use classes only. Factors significantly associated with Illicit Poly-substance Users of All Types were sexual minority status, lower income, and lower resiliency. Findings underline a need for increased social and structural supports for women who use substances to support them in leading safe and healthy lives with HIV.

Prolonged grief and post-traumatic growth after loss: Latent class analysis.

PubMed

Zhou, Ningning; Yu, Wei; Tang, Suqin; Wang, Jianping; Killikelly, Clare

2018-06-06

Bereavement may trigger different psychological outcomes, such as prolonged grief disorder or post-traumatic growth. The relationship between these two outcomes and potential precipitators remain unknown. The current study aimed to identify classes of Chinese bereaved individuals based on prolonged grief symptoms and post-traumatic growth and to examine predictors for these classes. We used data from 273 Chinese individuals who lost a relative due to disease (92.3%), accident (4.4%) and other reasons (1.8%). Latent class analysis revealed three classes: a resilient class, a growth class, and a combined grief/growth class. A higher level of functional impairment was found for the combined grief/growth class than for the other two classes. Membership in the combined grief/growth class was significantly predicted by the younger age of the deceased and the death of a parent, child or spouse. Subjective closeness with the deceased and gender were marginally significant predictors. When the four variables were included in the multinomial regression analysis, death of a parent, child or spouse significantly predicted the membership to the combined grief/growth class. These findings provide valuable information for the development of tailored interventions that may build on the bereaved individuals' personal strengths. Copyright © 2018. Published by Elsevier B.V.

Do Specific Transitional Patterns of Antisocial Behavior during Adolescence Increase Risk for Problems in Young Adulthood?

PubMed Central

Cook, Emily C.; Pflieger, Jacqueline C.; Connell, Arin M.; Connell, Christian M.

2014-01-01

Latent transition analysis was used to identify patterns and trajectories of antisocial behavior (ASB) and their association with young adult outcomes in a nationally representative sample of adolescents (N = 5,422; 53.9% female). Participants were on average 13.96 years of age (SD= 1.06) at wave 1 of the study. Latent class analysis identified four classes of ASB including a non-ASB class, an aggressive class, a petty theft class, and a serious ASB class. In general, youth who were classified as serious stable ASB were the most at risk for problematic functioning in young adulthood. Youth who escalated to more serious patterns of ASB or reduced involvement also were at greater risk of negative outcomes in young adulthood compared to stable non-ASB youth, although they generally fared better than youth involved in stable patterns of more serious ASB. Gender differences indicated that involvement in ASB was a greater risk factor for alcohol use among boys and a greater risk factor for depression among girls in young adulthood. Results are discussed in terms of the predictive validity of classes of ASB to functioning in young adulthood and the implications of this research for prevention efforts. PMID:24893667

Schizophrenia with prominent catatonic features ('catatonic schizophrenia') III. Latent class analysis of the catatonic syndrome.

PubMed

Ungvari, Gabor S; Goggins, William; Leung, Siu-Kau; Lee, Edwin; Gerevich, Jozsef

2009-02-01

No reports have yet been published on catatonia using latent class analysis (LCA). This study applied LCA to a large, diagnostically homogenous sample of patients with chronic schizophrenia who also presented with catatonic symptoms. A random sample of 225 Chinese inpatients with DSM-IV schizophrenia was selected from the long-stay wards of a psychiatric hospital. Their psychopathology, extrapyramidal motor status and level of functioning were evaluated with standardized rating scales. Catatonia was rated using a modified version of the Bush-Francis Catatonia Rating Scale. LCA was then applied to the 178 patients who presented with at least one catatonic sign. In LCA a four-class solution was found to fit best the statistical model. Classes 1, 2, 3 and 4 constituted 18%, 39.4%, 20.1% and 22.5% of the whole catatonic sample, respectively. Class 1 included patients with symptoms of 'automatic' phenomena (automatic obedience, Mitgehen, waxy flexibility). Class 2 comprised patients with 'repetitive/echo' phenomena (perseveration, stereotypy, verbigeration, mannerisms and grimacing). Class 3 contained patients with symptoms of 'withdrawal' (immobility, mutism, posturing, staring and withdrawal). Class 4 consisted of 'agitated/resistive' patients, who displayed symptoms of excitement, impulsivity, negativism and combativeness. The symptom composition of these 4 classes was nearly identical with that of the four factors identified by factor analysis in the same cohort of subjects in an earlier study. In multivariate regression analysis, the 'withdrawn' class was associated with higher scores on the Scale of Assessment of Negative Symptoms and lower and higher scores for negative and positive items respectively on the Nurses' Observation Scale for Inpatient Evaluation's (NOSIE). The 'automatic' class was associated with lower values on the Simpson-Angus Extrapyramidal Side Effects Scale, and the 'repetitive/echo' class with higher scores on the NOSIE positive items. These results provide preliminary support for the notion that chronic schizophrenia patients with catatonic features can be classified into 4 distinct syndromal groups on the basis of their motor symptoms. Identifying distinct catatonic syndromes would help to find their biological substrates and to develop specific therapeutic measures.

Developmental trajectories of paediatric headache - sex-specific analyses and predictors.

PubMed

Isensee, Corinna; Fernandez Castelao, Carolin; Kröner-Herwig, Birgit

2016-01-01

Headache is the most common pain disorder in children and adolescents and is associated with diverse dysfunctions and psychological symptoms. Several studies evidenced sex-specific differences in headache frequency. Until now no study exists that examined sex-specific patterns of change in paediatric headache across time and included pain-related somatic and (socio-)psychological predictors. Latent Class Growth Analysis (LCGA) was used in order to identify different trajectory classes of headache across four annual time points in a population-based sample (n = 3 227; mean age 11.34 years; 51.2 % girls). In multinomial logistic regression analyses the influence of several predictors on the class membership was examined. For girls, a four-class model was identified as the best fitting model. While the majority of girls reported no (30.5 %) or moderate headache frequencies (32.5 %) across time, one class with a high level of headache days (20.8 %) and a class with an increasing headache frequency across time (16.2 %) were identified. For boys a two class model with a 'no headache class' (48.6 %) and 'moderate headache class' (51.4 %) showed the best model fit. Regarding logistic regression analyses, migraine and parental headache proved to be stable predictors across sexes. Depression/anxiety was a significant predictor for all pain classes in girls. Life events, dysfunctional stress coping and school burden were also able to differentiate at least between some classes in both sexes. The identified trajectories reflect sex-specific differences in paediatric headache, as seen in the number and type of classes extracted. The documented risk factors can deliver ideas for preventive actions and considerations for treatment programmes.

Stress, Mental Health, and Substance Abuse Problems in a Sample of Diversion Program Youths: An Exploratory Latent Class Analysis

ERIC Educational Resources Information Center

Dembo, Richard; Briones, Rhissa; Gulledge, Laura; Karas, Lora; Winters, Ken C.; Belenko, Steven; Greenbaum, Paul E.

2012-01-01

Reflective of interest in mental health and substance abuse issues among youths involved with the justice system, we performed a latent class analysis on baseline information collected on 100 youths involved in two diversion programs. Results identified two groups of youths: Group 1: a majority of the youths, who had high levels of delinquency,…

A Latent Class Growth Analysis of School Bullying and Its Social Context: The Self-Determination Theory Perspective

ERIC Educational Resources Information Center

Lam, Shui-fong; Law, Wilbert; Chan, Chi-Keung; Wong, Bernard P. H.; Zhang, Xiao

2015-01-01

The contribution of social context to school bullying was examined from the self-determination theory perspective in this longitudinal study of 536 adolescents from 3 secondary schools in Hong Kong. Latent class growth analysis of the student-reported data at 5 time points from grade 7 to grade 9 identified 4 groups of students: bullies (9.8%),…

A personality-based latent class typology of outpatients with major depressive disorder: association with symptomatology, prescription pattern and social function.

PubMed

Hori, Hiroaki; Teraishi, Toshiya; Nagashima, Anna; Koga, Norie; Ota, Miho; Hattori, Kotaro; Kim, Yoshiharu; Higuchi, Teruhiko; Kunugi, Hiroshi

2017-08-01

While major depressive disorder (MDD) is considered to be a heterogeneous disorder, the nature of the heterogeneity remains unclear. Studies have attempted to classify patients with MDD using latent variable techniques, yet the empirical approaches to symptom-based subtyping of MDD have not provided conclusive evidence. Here we aimed to identify homogeneous classes of MDD based on personality traits, using a latent profile analysis. We studied 238 outpatients with DSM-IV MDD recruited from our specialized depression outpatient clinic and assessed their dimensional personality traits with the Temperament and Character Inventory. Latent profile analysis was conducted with 7 dimensions of the Temperament and Character Inventory as indicators. Relationships of the identified classes with symptomatology, prescription pattern, and social function were then examined. The latent profile analysis indicated that a 3-class solution best fit the data. Of the sample, 46.2% was classified into a "neurotic" group characterized by high harm avoidance and low self-directedness; 30.3% into an "adaptive" group characterized by high self-directedness and cooperativeness; and 23.5% into a "socially-detached" group characterized by low reward dependence and cooperativeness and high self-transcendence. The 2 maladaptive groups, namely neurotic and socially-detached groups, demonstrated unique patterns of symptom expression, different classes of psychotropic medication use, and lower social functioning. Generalizability of the findings was limited since our patients were recruited from the specialized depression outpatient clinic. Our personality-based latent profile analysis identified clinically meaningful 3 MDD groups that were markedly different in their personality profiles associated with distinct symptomatology and functioning. Copyright © 2017 Elsevier B.V. All rights reserved.

Content Themes of Alcohol Advertising in U.S. Television-Latent Class Analysis.

PubMed

Morgenstern, Matthis; Schoeppe, Franziska; Campbell, Julie; Braam, Marloes W G; Stoolmiller, Michael; Sargent, James D

2015-09-01

There is little alcohol research that reports on the thematic contents of contemporary alcohol advertisements in U.S. television. Studies of alcohol ads from 2 decades ago did not identify "Partying" as a social theme. Aim of this study was to describe and classify alcohol advertisements aired in national television in terms of contents, airing times, and channel placements and to identify different marketing strategies of alcohol brands. Content analysis of all ads from the top 20 U.S. beer and spirit brands aired between July 2009 and June 2011. These were 581 unique alcohol ads accounting for 272,828 (78%) national television airings. Ads were coded according to predefined definitions of 13 content areas. A latent class analysis (LCA) was conducted to define content cluster themes and determine alcoholic brands that were more likely to exploit these themes. About half of the advertisements (46%) were aired between 3 am and 8 pm, and the majority were placed either in Entertainment (40%) and Sports (38%) channels. Beer ads comprised 64% of the sample, with significant variation in airing times and channels between types of products and brands. LCA revealed 5 content classes that exploited the "Partying," "Quality," "Sports," "Manly," and "Relax" themes. The partying class, indicative of ad messages surrounding partying, love, and sex, was the dominant theme comprising 42% of all advertisements. Ads for alcopops, flavored spirits, and liqueur were more likely to belong to the party class, but there were also some beer brands (Corona, Heineken) where more than 67% of ads exploited this theme. This is the first analysis to identify a partying theme to contemporary alcohol advertising. Future analyses can now determine whether exposure to that or other themes predicts alcohol misuse among youth audiences. Copyright © 2015 by the Research Society on Alcoholism.

Profiling Physical Activity, Diet, Screen and Sleep Habits in Portuguese Children

PubMed Central

Pereira, Sara; Katzmarzyk, Peter T.; Gomes, Thayse Natacha; Borges, Alessandra; Santos, Daniel; Souza, Michele; dos Santos, Fernanda K.; Chaves, Raquel N.; Champagne, Catherine M.; Barreira, Tiago V.; Maia, José A.R.

2015-01-01

Obesity in children is partly due to unhealthy lifestyle behaviours, e.g., sedentary activity and poor dietary choices. This trend has been seen globally. To determine the extent of these behaviours in a Portuguese population of children, 686 children 9.5 to 10.5 years of age were studied. Our aims were to: (1) describe profiles of children’s lifestyle behaviours; (2) identify behaviour pattern classes; and (3) estimate combined effects of individual/socio-demographic characteristics in predicting class membership. Physical activity and sleep time were estimated by 24-h accelerometry. Nutritional habits, screen time and socio-demographics were obtained. Latent Class Analysis was used to determine unhealthy lifestyle behaviours. Logistic regression analysis predicted class membership. About 78% of children had three or more unhealthy lifestyle behaviours, while 0.2% presented no risk. Two classes were identified: Class 1-Sedentary, poorer diet quality; and Class 2-Insufficiently active, better diet quality, 35% and 65% of the population, respectively. More mature children (Odds Ratio (OR) = 6.75; 95%CI = 4.74–10.41), and boys (OR = 3.06; 95% CI = 1.98–4.72) were more likely to be overweight/obese. However, those belonging to Class 2 were less likely to be overweight/obese (OR = 0.60; 95% CI = 0.43–0.84). Maternal education level and household income did not significantly predict weight status (p ≥ 0.05). PMID:26043034

Redo surgery risk in patients with cardiac prosthetic valve dysfunction

PubMed Central

Maciejewski, Marek; Piestrzeniewicz, Katarzyna; Bielecka-Dąbrowa, Agata; Piechowiak, Monika; Jaszewski, Ryszard

2011-01-01

Introduction The aim of the study was to analyse the risk factors of early and late mortality in patients undergoing the first reoperation for prosthetic valve dysfunction. Material and methods A retrospective observational study was performed in 194 consecutive patients (M = 75, F = 119; mean age 53.2 ±11 years) with a mechanical prosthetic valve (n = 103 cases; 53%) or bioprosthesis (91; 47%). Univariate and multivariate Cox statistical analysis was performed to determine risk factors of early and late mortality. Results The overall early mortality was 18.6%: 31.4% in patients with symptoms of NYHA functional class III-IV and 3.4% in pts in NYHA class I-II. Multivariate analysis identified symptoms of NYHA class III-IV and endocarditis as independent predictors of early mortality. The overall late mortality (> 30 days) was 8.2% (0.62% year/patient). Multivariate analysis identified age at the time of reoperation as a strong independent predictor of late mortality. Conclusions Reoperation in patients with prosthetic valves, performed urgently, especially in patients with symptoms of NYHA class III-IV or in the case of endocarditis, bears a high mortality rate. Risk of planned reoperation, mostly in patients with symptoms of NYHA class I-II, does not differ from the risk of the first operation. PMID:22291767

Depression and Alcohol Use in a National Sample of Hispanic Adolescents.

PubMed

Merianos, Ashley L; Swoboda, Christopher M; Oluwoye, Oladunni A; Gilreath, Tamika D; Unger, Jennifer B

2018-04-16

Underage alcohol use and depression remain public health concerns for Hispanic adolescents nationwide. The study purpose was to identify the profiles of depression among Hispanic adolescents who reported experiencing depressive symptoms in their lifetime and classify them into groups based on their symptoms. Based on classifications, we examined the relationship between past year alcohol use and severity of depressive symptoms while controlling for sex and age. A secondary analysis of the 2013 NSDUH was conducted among Hispanic adolescents from 12 to 17 years of age (n = 585) who reported experiencing depressive symptoms. Latent class analysis was used to identify latent classes of depressive symptoms among Hispanic adolescents. A zero-inflated negative-binomial regression model was used to examine the relationship between alcohol use and depressive symptoms. "High depressive" and "moderate depressive" classes were formed. The items that highly differentiated among the groups were felt worthless nearly every day, others noticed they were restless or lethargic, and had changes in appetite or weight. There was a significant difference (p = 0.03) between the classes based on alcohol use; those in the moderate depressive class were 1.71 times more likely to be identified as not reporting past alcohol use. Results indicated the high depressive class was estimated to have 1.62 more days of past year alcohol use than those in the moderate depressive class for adolescents who used alcohol (p < 0.001). Conclusions/Importance: Study findings can be used to address these significant public health issues impacting Hispanic adolescents. Recommendations are included.

Latent Classes of PTSD Symptoms in Vietnam Veterans

ERIC Educational Resources Information Center

Steenkamp, Maria M.; Nickerson, Angela; Maguen, Shira; Dickstein, Benjamin D.; Nash, William P.; Litz, Brett T.

2012-01-01

The authors examined heterogeneity in posttraumatic stress disorder (PTSD) symptom presentation among veterans (n = 335) participating in the clinical interview subsample of the National Vietnam Veterans Readjustment Study. Latent class analysis was used to identify clinically homogeneous subgroups of Vietnam War combat veterans. Consistent with…

Discrete subgroups of adolescents diagnosed with borderline personality disorder: a latent class analysis of personality features.

PubMed

Ramos, Vera; Canta, Guilherme; de Castro, Filipa; Leal, Isabel

2014-08-01

Research suggests that borderline personality disorder (BPD) can be diagnosed in adolescents and is marked by considerable heterogeneity. This study aimed to identify personality features characterizing adolescents with BPD and possible meaningful patterns of heterogeneity that could lead to personality subgroups. The authors analyzed data on 60 adolescents, ages 15 to 18 years, who met DSM criteria for a BPD diagnosis. The authors used latent class analysis (LCA) to identify subgroups based on the personality pattern scales from the Millon Adolescent Clinical Inventory (MACI). LCA indicated that the best-fitting solution was a two-class model, identifying two discrete subgroups of BPD adolescents that were described as internalizing and externalizing. The subgroups were then compared on clinical and sociodemographic variables, measures of personality dimensions, DSM BPD criteria, and perception of attachment styles. Adolescents with a BPD diagnosis constitute a heterogeneous group and vary meaningfully on personality features that can have clinical implications for treatment.

Textual Analysis of General Surgery Residency Personal Statements: Topics and Gender Differences.

PubMed

Ostapenko, Laura; Schonhardt-Bailey, Cheryl; Sublette, Jessica Walling; Smink, Douglas S; Osman, Nora Y

Applicants to US general surgery residency training programs submit standardized applications. Applicants use the personal statement to express their individual rationale for a career in surgery. Our research explores common topics and gender differences within the personal statements of general surgery applicants. We analyzed the electronic residency application service personal statements of 578 applicants (containing 3,82,405 words) from Liaison Committee on Medical Education-accredited medical schools to a single ACGME-accredited general surgery program using an automated textual analysis program to identify common topics and gender differences. Using a recursive algorithm, the program identified common words and clusters, grouping them into topic classes, which are internally validated. We identified and labeled 8 statistically significant topic classes through independent review: "my story," "the art of surgery," "clinical vignettes," "why I love surgery," "residency program characteristics," "working as a team," "academics and research," and "global health and policy." Although some classes were common to all applications, we also identified gender-specific differences. Notably, women were significantly more likely than men to be represented within the class of "working as a team." (p < 0.01) Furthermore, men were significantly more likely than women to be represented within the class of "clinical vignettes" (p < 0.01). Applying textual analysis to a national cohort, we identified common narrative topics in the personal statements of aspiring general surgeons, noting differences between the statements of men and women. Women were more likely to discuss surgery as a team endeavor while men were more likely to focus on the details of their surgical experiences. Our work mirrors what has been found in social psychology research on gender-based differences in how men and women communicate their career goals and aspirations in other competitive professional situations. Copyright © 2017 Association of Program Directors in Surgery. Published by Elsevier Inc. All rights reserved.

USE OF BIOASSAY-DIRECTED CHEMICAL ANALYSIS FOR IDENTIFYING MUTAGENIC COMPOUNDS IN URBAN AIR AND COMBUSTION EMISSIONS

EPA Science Inventory

Bioassay-directed chemical analysis fractionation has been used for 30 years to identify mutagenic classes of compounds in complex mixtures. Most studies have used the Salmonella (Ames) mutagenicity assay, and we have recently applied this methodology to two standard reference sa...

A social network-informed latent class analysis of patterns of substance use, sexual behavior, and mental health: Social Network Study III, Winnipeg, Manitoba, Canada.

PubMed

Hopfer, Suellen; Tan, Xianming; Wylie, John L

2014-05-01

We assessed whether a meaningful set of latent risk profiles could be identified in an inner-city population through individual and network characteristics of substance use, sexual behaviors, and mental health status. Data came from 600 participants in Social Network Study III, conducted in 2009 in Winnipeg, Manitoba, Canada. We used latent class analysis (LCA) to identify risk profiles and, with covariates, to identify predictors of class. A 4-class model of risk profiles fit the data best: (1) solitary users reported polydrug use at the individual level, but low probabilities of substance use or concurrent sexual partners with network members; (2) social-all-substance users reported polydrug use at the individual and network levels; (3) social-noninjection drug users reported less likelihood of injection drug and solvent use; (4) low-risk users reported low probabilities across substances. Unstable housing, preadolescent substance use, age, and hepatitis C status predicted risk profiles. Incorporation of social network variables into LCA can distinguish important subgroups with varying patterns of risk behaviors that can lead to sexually transmitted and bloodborne infections.

Trajectories of functional limitation in early rheumatoid arthritis and their association with mortality.

PubMed

Norton, Sam; Sacker, Amanda; Dixey, Josh; Done, John; Williams, Peter; Young, Adam

2013-11-01

This study aimed to identify subgroups with distinct trajectories of functional (HAQ) progression over 10 years following diagnosis of RA and identify baseline characteristics associated with the trajectories and their prognostic value for mortality. Between 1986 and 1998, 1460 patients with RA symptoms <2 years and prior to disease-modifying treatment (DMARDs) were recruited to an inception cohort (Early RA Study). Standard clinical, functional and laboratory assessments were performed at presentation and annually. Deaths were tracked by the National Health Service Central Register. Growth mixture modelling was used to identify distinct trajectories of HAQ score progression and survival analysis employed to compare all-cause mortality across the trajectory classes. Four HAQ score progression classes were identified: moderate increasing (46%), low stable (6%), moderate stable (28%) and high stable (20%). Only the moderate-increasing class exhibited an accelerated decline in function over normal ageing. Compared with the moderate-increasing class, individuals with high-stable HAQ scores were more likely to be female, have more severe disease and other coexistent conditions. Low-stable class patients were more likely to be male and report less pain. The high-stable class had increased risk of mortality compared with the moderate-increasing class after adjusting for potential confounding factors, whereas low-stable and moderate-stable classes were at reduced mortality risk. The effect of RA on function is set within the first few years and is affected by comorbidity. Identifying distinct groups of patients may help to target those at greater risk of poor functional outcome and mortality.

Organizational Supports for Research Evidence Use in State Public Health Agencies: A Latent Class Analysis.

PubMed

Hu, Hengrui; Allen, Peg; Yan, Yan; Reis, Rodrigo S; Jacob, Rebekah R; Brownson, Ross C

2018-05-30

Use of research evidence in public health decision making can be affected by organizational supports. Study objectives are to identify patterns of organizational supports and explore associations with research evidence use for job tasks among public health practitioners. In this longitudinal study, we used latent class analysis to identify organizational support patterns, followed by mixed logistic regression analysis to quantify associations with research evidence use. The setting included 12 state public health department chronic disease prevention units and their external partnering organizations involved in chronic disease prevention. Chronic disease prevention staff from 12 US state public health departments and partnering organizations completed self-report surveys at 2 time points, in 2014 and 2016 (N = 872). Latent class analysis was employed to identify subgroups of survey participants with distinct patterns of perceived organizational supports. Two classify-analyze approaches (maximum probability assignment and multiple pseudo-class draws) were used in 2017 to investigate the association between latent class membership and research evidence use. The optimal model identified 4 latent classes, labeled as "unsupportive workplace," "low agency leadership support," "high agency leadership support," and "supportive workplace." With maximum probability assignment, participants in "high agency leadership support" (odds ratio = 2.08; 95% CI, 1.35-3.23) and "supportive workplace" (odds ratio = 1.74; 95% CI, 1.10-2.74) were more likely to use research evidence in job tasks than "unsupportive workplace." The multiple pseudo-class draws produced comparable results with odds ratio = 2.09 (95% CI, 1.31-3.30) for "high agency leadership support" and odds ratio = 1.74 (95% CI, 1.07-2.82) for "supportive workplace." Findings suggest that leadership support may be a crucial element of organizational supports to encourage research evidence use. Organizational supports such as supervisory expectations, access to evidence, and participatory decision-making may need leadership support as well to improve research evidence use in public health job tasks.This is an open-access article distributed under the terms of the Creative Commons Attribution-Non Commercial-No Derivatives License 4.0 (CCBY-NC-ND), where it is permissible to download and share the work provided it is properly cited. The work cannot be changed in any way or used commercially without permission from the journal.

A Latent Class Analysis of Pathological-Gambling Criteria Among High School Students: Associations With Gambling, Risk and Health/Functioning Characteristics

PubMed Central

Kong, Grace; Tsai, Jack; Krishnan-Sarin, Suchitra; Cavallo, Dana A.; Hoff, Rani A.; Steinberg, Marvin A.; Rugle, Loreen; Potenza, Marc N.

2015-01-01

Objectives To identify subtypes of adolescent gamblers based on the 10 Diagnostic and Statistical Manual of Mental Disorders, fourth edition criteria for pathological gambling and the 9 Diagnostic and Statistical Manual of Mental Disorders, fifth edition criteria for gambling disorder and to examine associations between identified subtypes with gambling, other risk behaviors, and health/functioning characteristics. Methods Using cross-sectional survey data from 10 high schools in Connecticut (N = 3901), we conducted latent class analysis to classify adolescents who reported past-year gambling into gambling groups on the basis of items from the Massachusetts Gambling Screen. Adolescents also completed questions assessing demographic information, substance use (cigarette, marijuana, alcohol, and other drugs), gambling behaviors (relating to gambling formats, locations, motivations, and urges), and health/functioning characteristics (eg, extracurricular activities, mood, aggression, and body mass index). Results The optimal solution consisted of 4 classes that we termed low-risk gambling (86.4%), at-risk chasing gambling (7.6%), at-risk negative consequences gambling (3.7%), and problem gambling (PrG) (2.3%). At-risk and PrG classes were associated with greater negative functioning and more gambling behaviors. Different patterns of associations between at-risk and PrG classes were also identified. Conclusions Adolescent gambling classifies into 4 classes, which are differentially associated with demographic, gambling patterns, risk behaviors, and health/functioning characteristics. Early identification and interventions for adolescent gamblers should be sensitive to the heterogeneity of gambling subtypes. PMID:25275877

Characterizing Health Disparities in the Age of Autism Diagnosis in a Study of 8-Year-Old Children

ERIC Educational Resources Information Center

Parikh, Chandni; Kurzius-Spencer, Margaret; Mastergeorge, Ann M.; Pettygrove, Sydney

2018-01-01

The diagnosis of autism spectrum disorder (ASD) is often delayed from the time of noted concerns to the actual diagnosis. The current study used child- and family-level factors to identify homogeneous classes in a surveillance-based sample (n = 2303) of 8-year-old children with ASD. Using latent class analysis, a 5-class model emerged and the…

In silico genome-wide identification and characterization of the glutathione S-transferase gene family in Vigna radiata.

PubMed

Vaish, Swati; Awasthi, Praveen; Tiwari, Siddharth; Tiwari, Shailesh Kumar; Gupta, Divya; Basantani, Mahesh Kumar

2018-05-01

Plant glutathione S-transferases (GSTs) are integral to normal plant metabolism and biotic and abiotic stress tolerance. The GST gene family has been characterized in diverse plant species using molecular biology and bioinformatics approaches. In the current study, in silico analysis identified 44 GSTs in Vigna radiata. Of the total 44 GSTs identified, chromosomal locations of 31 GSTs were confirmed. The pI value of GST proteins ranged from 5.10 to 9.40. The predicted molecular weights ranged from 13.12 to 50 kDa. Subcellular localization analysis revealed that all GSTs were predominantly localized in the cytoplasm. The active site amino acids were confirmed to be serine in tau, phi, theta, zeta, and TCHQD; cysteine in lambda, DHAR, and omega; and tyrosine in EF1G. The gene architecture conformed to the two-exon/one-intron and three-exon/two-intron organization in the case of tau and phi classes, respectively. MEME analysis identified 10 significantly conserved motifs with the width of 8-50 amino acids. The motifs identified were either specific to a specific GST class or were shared by multiple GST classes. The results of the current study will be of potential importance in the characterization of the GST gene family in V. radiata, an economically important leguminous crop.

The job content questionnaire in various occupational contexts: applying a latent class model.

PubMed

Santos, Kionna Oliveira Bernardes; Araújo, Tânia Maria de; Carvalho, Fernando Martins; Karasek, Robert

2017-05-17

To evaluate Job Content Questionnaire(JCQ) performance using the latent class model. We analysed cross-sectional studies conducted in Brazil and examined three occupational categories: petroleum industry workers (n=489), teachers (n=4392) and primary healthcare workers (3078)and 1552 urban workers from a representative sample of the city of Feira de Santana in Bahia, Brazil. An appropriate number of latent classes was extracted and described each occupational category using latent class analysis, a multivariate method that evaluates constructs and takes into accountthe latent characteristics underlying the structure of measurement scales. The conditional probabilities of workers belonging to each class were then analysed graphically. Initially, the latent class analysis extracted four classes corresponding to the four job types (active, passive, low strain and high strain) proposed by the Job-Strain model (JSM) and operationalised by the JCQ. However, after taking into consideration the adequacy criteria to evaluate the number of extracted classes, three classes (active, low strain and high strain) were extracted from the studies of urban workers and teachers and four classes (active, passive, low strain and high strain) from the study of primary healthcare and petroleum industry workers. The four job types proposed by the JSM were identified among primary healthcare and petroleum industry workers-groups with relatively high levels of skill discretion and decision authority. Three job types were identified for teachers and urban workers; however, passive job situations were not found within these groups. The latent class analysis enabled us to describe the conditional standard responses of the job types proposed by the model, particularly in relation to active jobs and high and low strain situations. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2017. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

Classes of Physical Activity and Sedentary Behavior in 5th Grade Children

PubMed Central

Dowda, Marsha; Dishman, Rod K; Pate, Russell R.

2016-01-01

Objectives To identify classes of physical activity (PA) and sedentary behaviors (SB) in 5th grade children, associated factors, and trajectories of change into 7th grade. Methods This study included n=495 children (221 boys, 274 girls) who participated in the Transitions and Activity Changes in Kids (TRACK) Study. PA was assessed objectively and via self-report. Children, parents, and school administrators completed surveys to assess related factors. Latent class analysis, growth modeling, and adjusted multinomial logistic regression procedures were used to classify children based on self-reported PA and SB and examine associated factors. Results Three classes of behavior were identified: Class 1: Low PA/Low SB, Class 2: Moderate PA/High SB, and Class 3: High PA/High SB (boys) or Class 3: High PA (girls). Class 3 children had higher levels of self-efficacy (boys), and enjoyment, parental support, and physical activity equipment at home (girls). Class 2 boys and Class 3 girls did not experience decline in PA (accelerometer) over time. Conclusions Self-efficacy (boys) and home environment (girls) may play a role in shaping patterns of PA in children. Findings may help to inform future interventions to encourage children to meet national PA guidelines. PMID:27103414

Ontology-based literature mining and class effect analysis of adverse drug reactions associated with neuropathy-inducing drugs.

PubMed

Hur, Junguk; Özgür, Arzucan; He, Yongqun

2018-06-07

Adverse drug reactions (ADRs), also called as drug adverse events (AEs), are reported in the FDA drug labels; however, it is a big challenge to properly retrieve and analyze the ADRs and their potential relationships from textual data. Previously, we identified and ontologically modeled over 240 drugs that can induce peripheral neuropathy through mining public drug-related databases and drug labels. However, the ADR mechanisms of these drugs are still unclear. In this study, we aimed to develop an ontology-based literature mining system to identify ADRs from drug labels and to elucidate potential mechanisms of the neuropathy-inducing drugs (NIDs). We developed and applied an ontology-based SciMiner literature mining strategy to mine ADRs from the drug labels provided in the Text Analysis Conference (TAC) 2017, which included drug labels for 53 neuropathy-inducing drugs (NIDs). We identified an average of 243 ADRs per NID and constructed an ADR-ADR network, which consists of 29 ADR nodes and 149 edges, including only those ADR-ADR pairs found in at least 50% of NIDs. Comparison to the ADR-ADR network of non-NIDs revealed that the ADRs such as pruritus, pyrexia, thrombocytopenia, nervousness, asthenia, acute lymphocytic leukaemia were highly enriched in the NID network. Our ChEBI-based ontology analysis identified three benzimidazole NIDs (i.e., lansoprazole, omeprazole, and pantoprazole), which were associated with 43 ADRs. Based on ontology-based drug class effect definition, the benzimidazole drug group has a drug class effect on all of these 43 ADRs. Many of these 43 ADRs also exist in the enriched NID ADR network. Our Ontology of Adverse Events (OAE) classification further found that these 43 benzimidazole-related ADRs were distributed in many systems, primarily in behavioral and neurological, digestive, skin, and immune systems. Our study demonstrates that ontology-based literature mining and network analysis can efficiently identify and study specific group of drugs and their associated ADRs. Furthermore, our analysis of drug class effects identified 3 benzimidazole drugs sharing 43 ADRs, leading to new hypothesis generation and possible mechanism understanding of drug-induced peripheral neuropathy.

The character strengths of class clowns.

PubMed

Ruch, Willibald; Platt, Tracey; Hofmann, Jennifer

2014-01-01

Class clowns traditionally were studied as a type concept and identified via sociometric procedures. In the present study a variable-centered approach was favored and class clown behaviors were studied in the context of character strengths, orientations to happiness and satisfaction with life. A sample of 672 Swiss children and adolescents filled in an 18 item self-report instrument depicting class clown behaviors. A hierarchical model of class clown behaviors was developed distinguishing a general factor and the four positively correlated dimensions of "identified as a class clown," "comic talent," "disruptive rule-breaker," and "subversive joker." Analysis of the general factor showed that class clowns were primarily male, and tended to be seen as class clowns by the teacher. Analyses of the 24 character strengths of the VIA-Youth (Park and Peterson, 2006) showed that class clowns were high in humor and leadership, and low in strengths like prudence, self-regulation, modesty, honesty, fairness, perseverance, and love of learning. An inspection of signature strengths revealed that 75% of class clowns had humor as a signature strength. Furthermore, class clown behaviors were generally shown by students indulging in a life of pleasure, but low life of engagement. The four dimensions yielded different character strengths profiles. While all dimensions of class clowns behaviors were low in temperance strengths, the factors "identified as the class clown" and "comic talent" were correlated with leadership strengths and the two negative factors ("disruptive rule-breaker," "subversive joker") were low in other directed strengths. The disruptive rule breaking class clown was additionally low in intellectual strengths. While humor predicted life satisfaction, class clowning tended to go along with diminished satisfaction with life. It is concluded that different types of class clowns need to be kept apart and need different attention by teachers.

Separating "Rotators" from "Nonrotators" in the Mental Rotations Test: A Multigroup Latent Class Analysis

ERIC Educational Resources Information Center

Geiser, Christian; Lehmann, Wolfgang; Eid, Michael

2006-01-01

Items of mental rotation tests can not only be solved by mental rotation but also by other solution strategies. A multigroup latent class analysis of 24 items of the Mental Rotations Test (MRT) was conducted in a sample of 1,695 German pupils and students to find out how many solution strategies can be identified for the items of this test. The…

[BIOINFORMATIC SEARCH AND PHYLOGENETIC ANALYSIS OF THE CELLULOSE SYNTHASE GENES OF FLAX (LINUM USITATISSIMUM)].

PubMed

Pydiura, N A; Bayer, G Ya; Galinousky, D V; Yemets, A I; Pirko, Ya V; Podvitski, T A; Anisimova, N V; Khotyleva, L V; Kilchevsky, A V; Blume, Ya B

2015-01-01

A bioinformatic search of sequences encoding cellulose synthase genes in the flax genome, and their comparison to dicots orthologs was carried out. The analysis revealed 32 cellulose synthase gene candidates, 16 of which are highly likely to encode cellulose synthases, and the remaining 16--cellulose synthase-like proteins (Csl). Phylogenetic analysis of gene products of cellulose synthase genes allowed distinguishing 6 groups of cellulose synthase genes of different classes: CesA1/10, CesA3, CesA4, CesA5/6/2/9, CesA7 and CesA8. Paralogous sequences within classes CesA1/10 and CesA5/6/2/9 which are associated with the primary cell wall formation are characterized by a greater similarity within these classes than orthologous sequences. Whereas the genes controlling the biosynthesis of secondary cell wall cellulose form distinct clades: CesA4, CesA7, and CesA8. The analysis of 16 identified flax cellulose synthase gene candidates shows the presence of at least 12 different cellulose synthase gene variants in flax genome which are represented in all six clades of cellulose synthase genes. Thus, at this point genes of all ten known cellulose synthase classes are identify in flax genome, but their correct classification requires additional research.

Why Does Rebalancing Class-Unbalanced Data Improve AUC for Linear Discriminant Analysis?

PubMed

Xue, Jing-Hao; Hall, Peter

2015-05-01

Many established classifiers fail to identify the minority class when it is much smaller than the majority class. To tackle this problem, researchers often first rebalance the class sizes in the training dataset, through oversampling the minority class or undersampling the majority class, and then use the rebalanced data to train the classifiers. This leads to interesting empirical patterns. In particular, using the rebalanced training data can often improve the area under the receiver operating characteristic curve (AUC) for the original, unbalanced test data. The AUC is a widely-used quantitative measure of classification performance, but the property that it increases with rebalancing has, as yet, no theoretical explanation. In this note, using Gaussian-based linear discriminant analysis (LDA) as the classifier, we demonstrate that, at least for LDA, there is an intrinsic, positive relationship between the rebalancing of class sizes and the improvement of AUC. We show that the largest improvement of AUC is achieved, asymptotically, when the two classes are fully rebalanced to be of equal sizes.

Predicting the decision to pursue mediation in civil disputes: a hierarchical classes analysis.

PubMed

Reich, Warren A; Kressel, Kenneth; Scanlon, Kathleen M; Weiner, Gary A

2007-11-01

Clients (N = 185) involved in civil court cases completed the CPR Institute's Mediation Screen, which is designed to assist in making a decision about pursuing mediation. The authors modeled data using hierarchical classes analysis (HICLAS), a clustering algorithm that places clients into 1 set of classes and CPRMS items into another set of classes. HICLAS then links the sets of classes so that any class of clients can be identified in terms of the classes of items they endorsed. HICLAS-derived item classes reflected 2 underlying themes: (a) suitability of the dispute for a problem-solving process and (b) potential benefits of mediation. All clients who perceived that mediation would be beneficial also believed that the context of their conflict was favorable to mediation; however, not all clients who saw a favorable context believed they would benefit from mediation. The majority of clients who agreed to pursue mediation endorsed items reflecting both contextual suitability and perceived benefits of mediation.

A Three-Step Latent Class Analysis to Identify How Different Patterns of Teen Dating Violence and Psychosocial Factors Influence Mental Health.

PubMed

Choi, Hye Jeong; Weston, Rebecca; Temple, Jeff R

2017-04-01

Although multiple forms (i.e., physical, threatening, psychological, sexual, and relational abuse) and patterns (i.e., perpetration and victimization) of violence can co-occur, most existing research examines these experiences individually. Thus, the purpose of this study is to investigate: (1) homogenous subgroups based on victimization and perpetration of multiple forms of teen dating violence; (2) predictors of membership in these subgroups; and (3) mental health consequences associated with membership in each subgroup. Nine hundred eighteen adolescents in the 9 th or 10 th grade at seven public high schools in Texas participated in the survey (56 % female, White: 30 %, Hispanic: 32 %, African American: 29 %, others: 9 %). A three-step latent class analysis was employed. Five latent teen dating violence classes were identified: (1) nonviolence; (2) emotional/verbal abuse; (3) forced sexual contact; (4) psychological + physical violence; and (5) psychological abuse. Females, African Americans, and youth who had higher acceptance of couple violence scores and whose parents had less education were more likely to members of dating violence classes compared with the nonviolence class. Adolescents who experienced multiple types of dating violence reported greater mental health concerns. Prevention programs may benefit by identifying the homogenous subgroups of teen dating violence and targeting adolescent teen dating violence accordingly.

Four Distinct Subgroups of Self-Injurious Behavior among Chinese Adolescents: Findings from a Latent Class Analysis

PubMed Central

Xin, Xiuhong; Ming, Qingsen; Zhang, Jibiao; Wang, Yuping; Liu, Mingli; Yao, Shuqiao

2016-01-01

Self-injurious behavior (SIB) among adolescents is an important public health issue worldwide. It is still uncertain whether homogeneous subgroups of SIB can be identified and whether constellations of SIBs can co-occur due to the high heterogeneity of these behaviors. In this study, a cross-sectional study was conducted on a large school-based sample and latent class analysis was performed (n = 10,069, mean age = 15 years) to identify SIB classes based on 11 indicators falling under direct SIB (DSIB), indirect SIB (ISIB), and suicide attempts (SAs). Social and psychological characteristics of each subgroup were examined after controlling for age and gender. Results showed that a four-class model best fit the data and each class had a distinct pattern of co-occurrence of SIBs and external measures. Class 4 (the baseline/normative group, 65.3%) had a low probability of SIB. Class 3 (severe SIB group, 3.9%) had a high probability of SIB and the poorest social and psychological status. Class 1 (DSIB+SA group, 14.2%) had similar scores for external variables compared to class 3, and included a majority of girls [odds ratio (OR) = 1.94]. Class 2 (ISIB group, 16.6%) displayed moderate endorsement of ISIB items, and had a majority of boys and older adolescents (OR = 1.51). These findings suggest that SIB is a heterogeneous entity, but it may be best explained by four homogenous subgroups that display quantitative and qualitative differences. Findings in this study will improve our understanding on SIB and may facilitate the prevention and treatment of SIB. PMID:27392132

Polydrug Use and HIV Risk Among People Who Inject Heroin in Tijuana, Mexico: A Latent Class Analysis.

PubMed

Meacham, Meredith C; Rudolph, Abby E; Strathdee, Steffanie A; Rusch, Melanie L; Brouwer, Kimberly C; Patterson, Thomas L; Vera, Alicia; Rangel, Gudelia; Roesch, Scott C

2015-01-01

Although most people who inject drugs (PWID) in Tijuana, Mexico, primarily inject heroin, injection and non-injection use of methamphetamine and cocaine is common. We examined patterns of polydrug use among heroin injectors to inform prevention and treatment of drug use and its health and social consequences. Participants were PWID residing in Tijuana, aged ≥18 years who reported heroin injection in the past six months and were recruited through respondent-driven sampling (n = 1,025). Latent class analysis was conducted to assign individuals to classes on a probabilistic basis, using four indicators of past six-month polydrug and polyroute use: cocaine injecting, cocaine smoking or snorting, methamphetamine injecting, and methamphetamine smoking or snorting. Latent class membership was regressed onto covariates in a multinomial logistic regression. Latent class analyses testing 1, 2, 3, and 4 classes were fit, with the 3-class solution fitting best. Class 1 was defined by predominantly heroin use (50.2%, n = 515); class 2 by methamphetamine and heroin use (43.7%, n = 448), and class 3 by methamphetamine, cocaine, and heroin use (6.0%, n = 62). Bivariate and multivariate analyses indicated a group of methamphetamine and cocaine users that exhibited higher-risk sexual practices and lower heroin injecting frequency, and a group of methamphetamine users who were younger and more likely to be female. Discrete subtypes of heroin PWID were identified based on methamphetamine and cocaine use patterns. These findings have identified subtypes of heroin injectors who require more tailored interventions to reduce the health and social harms of injecting drug use.

Polydrug use and HIV risk among people who inject heroin in Tijuana, Mexico: A Latent class analysis

PubMed Central

Meacham, M.C.; Rudolph, A.E.; Strathdee, S.A.; Rusch, M.L.; Brouwer, K.C.; Patterson, T.L.; Vera, A.; Rangel, G.; Roesch, S.C.

2016-01-01

Background Although most people who inject drugs (PWID) in Tijuana, Mexico, primarily inject heroin, injection and non-injection use of methamphetamine and cocaine is common. We examined patterns of polydrug use among heroin injectors to inform prevention and treatment of drug use and its health and social consequences. Methods Participants were PWID residing in Tijuana aged ≥ 18 years who reported heroin injection in the past 6 months and were recruited through respondent driven sampling (n=1025). Latent class analysis was conducted to assign individuals to classes on a probabilistic basis, using four indicators of past 6 month polydrug and polyroute use: cocaine injecting, cocaine smoking or snorting, methamphetamine injecting, methamphetamine smoking or snorting. Latent class membership was regressed onto covariates in a multinomial logistic regression. Results Latent class analyses testing 1, 2, 3, and 4 classes were fit, with the 3-class solution fitting best. Class 1 was defined by predominantly heroin use (50.2%, n=515); class 2 by methamphetamine and heroin use (43.7%, n=448), and class 3 by methamphetamine, cocaine, and heroin use (6.0%, n=62). Bivariate and multivariate analyses indicated a group of methamphetamine and cocaine users that exhibited higher risk sexual practices and lower heroin injecting frequency, and a group of methamphetamine users who were younger and more likely to be female. Conclusions Discrete subtypes of heroin PWID were identified based on methamphetamine and cocaine use patterns. These findings have identified subtypes of heroin injectors who require more tailored interventions to reduce the health and social harms of injecting drug use. PMID:26444185

Newly Identified Gait Patterns in Patients With Multiple Sclerosis May Be Related to Push-off Quality.

PubMed

Kempen, Jiska C E; Doorenbosch, Caroline A M; Knol, Dirk L; de Groot, Vincent; Beckerman, Heleen

2016-11-01

Limited walking ability is an important problem for patients with multiple sclerosis. A better understanding of how gait impairments lead to limited walking ability may help to develop more targeted interventions. Although gait classifications are available in cerebral palsy and stroke, relevant knowledge in MS is scarce. The aims of this study were: (1) to identify distinctive gait patterns in patients with MS based on a combined evaluation of kinematics, gait features, and muscle activity during walking and (2) to determine the clinical relevance of these gait patterns. This was a cross-sectional study of 81 patients with MS of mild-to-moderate severity (Expanded Disability Status Scale [EDSS] median score=3.0, range=1.0-7.0) and an age range of 28 to 69 years. The patients participated in 2-dimensional video gait analysis, with concurrent measurement of surface electromyography and ground reaction forces. A score chart of 73 gait items was used to rate each gait analysis. A single rater performed the scoring. Latent class analysis was used to identify gait classes. Analysis of the 73 gait variables revealed that 9 variables could distinguish 3 clinically meaningful gait classes. The 9 variables were: (1) heel-rise in terminal stance, (2) push-off, (3) clearance in initial swing, (4) plantar-flexion position in mid-swing, (5) pelvic rotation, (6) arm-trunk movement, (7) activity of the gastrocnemius muscle in pre-swing, (8) M-wave, and (9) propulsive force. The EDSS score and gait speed worsened in ascending classes. Most participants had mild-to-moderate limitations in walking ability based on their EDSS scores, and the number of walkers who were severely limited was small. Based on a small set of 9 variables measured with 2-dimensional clinical gait analysis, patients with MS could be divided into 3 different gait classes. The gait variables are suggestive of insufficient ankle push-off. © 2016 American Physical Therapy Association.

Social class and body weight among Chinese urban adults: the role of the middle classes in the nutrition transition.

PubMed

Bonnefond, Céline; Clément, Matthieu

2014-07-01

While a plethoric empirical literature addresses the relationship between socio-economic status and body weight, little is known about the influence of social class on nutritional outcomes, particularly in developing countries. The purpose of this article is to contribute to the analysis of the social determinants of adult body weight in urban China by taking into account the influence of social class. More specifically, we propose to analyse the position of the Chinese urban middle class in terms of being overweight or obese. The empirical investigations conducted as part of this research are based on a sample of 1320 households and 2841 adults from the China Health and Nutrition Survey for 2009. For the first step, we combine an economic approach and a sociological approach to identify social classes at household level. First, households with an annual per capita income between 10,000 Yuan and the 95th income percentile are considered as members of the middle class. Second, we strengthen the characterization of the middle class using information on education and employment. By applying clustering methods, we identify four groups: the elderly and inactive middle class, the old middle class, the lower middle class and the new middle class. For the second step, we implement an econometric analysis to assess the influence of social class on adult body mass index and on the probability of being overweight or obese. We use multinomial treatment regressions to deal with the endogeneity of the social class variable. Our results show that among the four subgroups of the urban middle class, the new middle class is the only one to be relatively well-protected against obesity. We suggest that this group plays a special role in adopting healthier food consumption habits and seems to be at a more advanced stage of the nutrition transition. Copyright © 2014 Elsevier Ltd. All rights reserved.

Entry, Descent and Landing Systems Analysis: Exploration Class Simulation Overview and Results

NASA Technical Reports Server (NTRS)

DwyerCianciolo, Alicia M.; Davis, Jody L.; Shidner, Jeremy D.; Powell, Richard W.

2010-01-01

NASA senior management commissioned the Entry, Descent and Landing Systems Analysis (EDL-SA) Study in 2008 to identify and roadmap the Entry, Descent and Landing (EDL) technology investments that the agency needed to make in order to successfully land large payloads at Mars for both robotic and exploration or human-scale missions. The year one exploration class mission activity considered technologies capable of delivering a 40-mt payload. This paper provides an overview of the exploration class mission study, including technologies considered, models developed and initial simulation results from the EDL-SA year one effort.

Students' Perceptions of Study Modes

ERIC Educational Resources Information Center

Hagel, Pauline; Shaw, Robin N.

2006-01-01

This paper reports on a survey of how Australian undergraduate students perceive the benefits of broad study modes: face-to-face classes, web-based study, and print-based study. Two benefit types were identified through factor analysis: engagement and functionality. Respondents rated face-to-face classes highest on engagement and print-based study…

Teacher Deployment of "Oh" in Known-Answer Question Sequences

ERIC Educational Resources Information Center

Hosoda, Yuri

2016-01-01

This conversation analytic study describes some specific interactional contexts in which native English-speaking teachers produce "oh" in known-answer question sequences in English language classes. The data for this study come from 10 video-recorded Japanese primary school English language class sessions. The analysis identified three…

Job Satisfaction among Health-Care Staff in Township Health Centers in Rural China: Results from a Latent Class Analysis

PubMed Central

Wang, Haipeng; Tang, Chengxiang; Zhao, Shichao; Meng, Qingyue; Liu, Xiaoyun

2017-01-01

Background: The lower job satisfaction of health-care staff will lead to more brain drain, worse work performance, and poorer health-care outcomes. The aim of this study was to identify patterns of job satisfaction among health-care staff in rural China, and to investigate the association between the latent clusters and health-care staff’s personal and professional features; Methods: We selected 12 items of five-point Likert scale questions to measure job satisfaction. A latent-class analysis was performed to identify subgroups based on the items of job satisfaction; Results: Four latent classes of job satisfaction were identified: 8.9% had high job satisfaction, belonging to “satisfied class”; 38.2% had low job satisfaction, named as “unsatisfied class”; 30.5% were categorized into “unsatisfied class with the exception of interpersonal relationships”; 22.4% were identified as “pseudo-satisfied class”, only satisfied with management-oriented items. Low job satisfaction was associated with specialty, training opportunity, and income inequality. Conclusions: The minority of health-care staff belong to the “satisfied class”. Three among four subgroups are not satisfied with income, benefit, training, and career development. Targeting policy interventions should be implemented to improve the items of job satisfaction based on the patterns and health-care staff’s features. PMID:28937609

Characterizing the successful student in general chemistry and physical science classes in terms of Jung's personality types as identified by the Myers-Briggs Type Indicator

NASA Astrophysics Data System (ADS)

Riley, Wayne David

1998-11-01

A student's success in a science class can depend upon previous experiences, motivation, and the level of interest in the subject. Since psychological type is intrinsic to a person's whole being, it can be influential upon the student's motivation and interests. Thus, a study of student psychological types versus the level of success in a class, as measured by a percentage, has potential to uncover certain personality characteristics which may be helpful to or which may hinder a student's learning environment. This study was initiated, using the Myers-Briggs Type Indicator, to evaluate any correlation between a student's personality type and his/her performance in a science class. A total of 1041 students from three classes: Chemistry 121/122, Chemistry 112, Physical Science 100, volunteered for the study. An analysis of variance (ANOVA) was used to determine the levels of significance among sixteen personality types' averages. The results reveal that for the Chemistry 1121/122 course, the average score of the INTJ personality type was 5.1 to 12.6 points higher than every other personality type. The ANOVA identifies 3 personality types with averages significantly below the INTJ at the p < 0.05 significance level. The ANOVA analysis for the Chemistry 112 course identified significances between student scores at p = 0.08. The significance level for the differences among scores for the Physical Science 100 course was determined at a level of p = 0.02. Significance levels for p < 0.05 and <0.01 were identified between several groups in this course. The data suggest, that although personality type may not predict a particular student's success in a science class, students with certain personality traits may be favored in a chemistry class due the structure of the instruction and the presentation of the subject matter.

Who Should Be Targeted for the Prevention of Birth Defects? A Latent Class Analysis Based on a Large, Population-Based, Cross-Sectional Study in Shaanxi Province, Western China.

PubMed

Zhu, Zhonghai; Cheng, Yue; Yang, Wenfang; Li, Danyang; Yang, Xue; Liu, Danli; Zhang, Min; Yan, Hong; Zeng, Lingxia

2016-01-01

The wide range and complex combinations of factors that cause birth defects impede the development of primary prevention strategies targeted at high-risk subpopulations. Latent class analysis (LCA) was conducted to identify mutually exclusive profiles of factors associated with birth defects among women between 15 and 49 years of age using data from a large, population-based, cross-sectional study conducted in Shaanxi Province, western China, between August and October, 2013. The odds ratios (ORs) and 95% confidence intervals (CIs) of associated factors and the latent profiles of indicators of birth defects and congenital heart defects were computed using a logistic regression model. Five discrete subpopulations of participants were identified as follows: No folic acid supplementation in the periconceptional period (reference class, 21.37%); low maternal education level + unhealthy lifestyle (class 2, 39.75%); low maternal education level + unhealthy lifestyle + disease (class 3, 23.71%); unhealthy maternal lifestyle + advanced age (class 4, 4.71%); and multi-risk factor exposure (class 5, 10.45%). Compared with the reference subgroup, the other subgroups consistently had a significantly increased risk of birth defects (ORs and 95% CIs: class 2, 1.75 and 1.21-2.54; class 3, 3.13 and 2.17-4.52; class 4, 5.02 and 3.20-7.88; and class 5, 12.25 and 8.61-17.42, respectively). For congenital heart defects, the ORs and 95% CIs were all higher, and the magnitude of OR differences ranged from 1.59 to 16.15. A comprehensive intervention strategy targeting maternal exposure to multiple risk factors is expected to show the strongest results in preventing birth defects.

A latent profile analysis of intimate partner victimization and aggression and examination of between-class differences in psychopathology symptoms and risky behaviors

PubMed Central

Weiss, Nicole H.; Dixon-Gordon, Katherine L.; Peasant, Courtney; Jaquier, Véronique; Johnson, Clinesha; Sullivan, Tami P.

2016-01-01

Objective Intimate partner violence (IPV) is associated with heightened psychopathology symptoms and risky behaviors. However, extant investigations are limited by their focus on IPV victimization, despite evidence to suggest that victimization and aggression frequently co-occur. Further, research on these correlates often has not accounted for the heterogeneity of women who experience victimization. Method The present study utilized latent profile analysis to identify patterns of physical, psychological, and sexual victimization and aggression in a convenience sample of 212 community women experiencing victimization (M age=36.63, 70.8% African American), as well as examined differences in psychopathology symptoms (i.e., posttraumatic stress symptoms and depressive symptoms) and risky behaviors (i.e., drug problems, alcohol problems, deliberate self-harm, HIV-risk behaviors) across these classes. Results Four classes of women differentiated by severities of victimization and aggression were identified. Greater psychopathology symptoms were found among classes defined by greater victimization and aggression, regardless of IPV type. Risky behaviors were more prevalent among classes defined by greater sexual victimization and aggression in particular. Conclusions Findings highlight the importance of developing interventions that target the particular needs of subgroups of women who experience victimization. PMID:27736140

Are poker players all the same? Latent class analysis.

PubMed

Dufour, Magali; Brunelle, Natacha; Roy, Élise

2015-06-01

Poker is the gambling game that is currently gaining the most in popularity. However, there is little information on poker players' characteristics and risk factors. Furthermore, the first studies described poker players, often recruited in universities, as an homogeneous group who played in only one of the modes (land based or on the Internet). This study aims to identify, through latent class analyses, poker player subgroups. A convenience sample of 258 adult poker players was recruited across Quebec during special events or through advertising in various media. Participants filled out a series of questionnaires (Canadian Problem Gambling Index, Beck Depression, Beck Anxiety, erroneous belief and alcohol/drug consumption). The latent class analysis suggests that there are three classes of poker players. Class I (recreational poker players) includes those who have the lowest probability of engaging intensively in different game modes. Participants in class II (Internet poker players) all play poker on the Internet. This class includes the highest proportion of players who consider themselves experts or professionals. They make a living in part or in whole from poker. Class III (multiform players) includes participants with the broadest variety of poker patterns. This group is complex: these players are positioned halfway between professional and recreational players. Results indicate that poker players are not an homogeneous group identified simply on the basis of the form of poker played. The specific characteristics associated with each subgroup points to vulnerabilities that could potentially be targeted for preventive interventions.

Latent profile analysis of teacher perceptions of parent contact and comfort.

PubMed

Stormont, Melissa; Herman, Keith C; Reinke, Wendy M; David, Kimberly B; Goel, Nidhi

2013-09-01

The purpose of the study was to explore patterns of parent involvement as perceived by teachers and identify correlates of these patterns. Parent involvement indicators and correlates were selected from a review of existing research. Participants included 34 teachers and 577 children in kindergarten through third grade. The vast majority of the sample was African American (78%), followed by Caucasian (19%) and other ethnic backgrounds (2%). Two subscales from the Parent Involvement-Teacher scale, contact and comfort, were entered as indicators in a latent profile analysis to determine the number and types of parent involvement classes. Contact included the frequency of interactions between parents and teachers; comfort included the quality of their relationship with the parent and how well their goals were aligned. Subsequent latent class regressions were conducted to identify student, school, and family characteristics associated with class membership. Three classes provided the optimal solution. This included two classes of parents with low contact with teachers but different comfort levels; one with low contact and low comfort (11%), and one with low contact but high comfort (71%). The remaining class, representing 18% of parents, was rated high on both contact and comfort. Low income status, family problems, and social, emotional, academic, and self-regulation problems distinguished the low comfort class from the other two classes. It is imperative to help teachers feel more comfortable working with families who may be experiencing substantial stressors and who also have children who need support across school and home settings.

Nottingham Prognostic Index Plus (NPI+): a modern clinical decision making tool in breast cancer.

PubMed

Rakha, E A; Soria, D; Green, A R; Lemetre, C; Powe, D G; Nolan, C C; Garibaldi, J M; Ball, G; Ellis, I O

2014-04-02

Current management of breast cancer (BC) relies on risk stratification based on well-defined clinicopathologic factors. Global gene expression profiling studies have demonstrated that BC comprises distinct molecular classes with clinical relevance. In this study, we hypothesised that molecular features of BC are a key driver of tumour behaviour and when coupled with a novel and bespoke application of established clinicopathologic prognostic variables can predict both clinical outcome and relevant therapeutic options more accurately than existing methods. In the current study, a comprehensive panel of biomarkers with relevance to BC was applied to a large and well-characterised series of BC, using immunohistochemistry and different multivariate clustering techniques, to identify the key molecular classes. Subsequently, each class was further stratified using a set of well-defined prognostic clinicopathologic variables. These variables were combined in formulae to prognostically stratify different molecular classes, collectively known as the Nottingham Prognostic Index Plus (NPI+). The NPI+ was then used to predict outcome in the different molecular classes. Seven core molecular classes were identified using a selective panel of 10 biomarkers. Incorporation of clinicopathologic variables in a second-stage analysis resulted in identification of distinct prognostic groups within each molecular class (NPI+). Outcome analysis showed that using the bespoke NPI formulae for each biological BC class provides improved patient outcome stratification superior to the traditional NPI. This study provides proof-of-principle evidence for the use of NPI+ in supporting improved individualised clinical decision making.

A hybrid method for prediction and repositioning of drug Anatomical Therapeutic Chemical classes.

PubMed

Chen, Lei; Lu, Jing; Zhang, Ning; Huang, Tao; Cai, Yu-Dong

2014-04-01

In the Anatomical Therapeutic Chemical (ATC) classification system, therapeutic drugs are divided into 14 main classes according to the organ or system on which they act and their chemical, pharmacological and therapeutic properties. This system, recommended by the World Health Organization (WHO), provides a global standard for classifying medical substances and serves as a tool for international drug utilization research to improve quality of drug use. In view of this, it is necessary to develop effective computational prediction methods to identify the ATC-class of a given drug, which thereby could facilitate further analysis of this system. In this study, we initiated an attempt to develop a prediction method and to gain insights from it by utilizing ontology information of drug compounds. Since only about one-fourth of drugs in the ATC classification system have ontology information, a hybrid prediction method combining the ontology information, chemical interaction information and chemical structure information of drug compounds was proposed for the prediction of drug ATC-classes. As a result, by using the Jackknife test, the 1st prediction accuracies for identifying the 14 main ATC-classes in the training dataset, the internal validation dataset and the external validation dataset were 75.90%, 75.70% and 66.36%, respectively. Analysis of some samples with false-positive predictions in the internal and external validation datasets indicated that some of them may even have a relationship with the false-positive predicted ATC-class, suggesting novel uses of these drugs. It was conceivable that the proposed method could be used as an efficient tool to identify ATC-classes of novel drugs or to discover novel uses of known drugs.

The heterogeneous health latent classes of elderly people and their socio-demographic characteristics in Taiwan.

PubMed

Liu, Li-Fan; Tian, Wei-Hua; Yao, Hui-Ping

2014-01-01

The health care needs of elderly people were influenced by their heterogeneity. This study aimed to identify the health latent classes of elderly people by using latent class analysis to deal with heterogeneity and examine their socio-demographic characteristics. Data came from the 2005 National Health Interview Survey (NHIS) in Taiwan. In total, 2449 elderly individuals with available health indicators were examined in latent class analysis (LCA), and 2217 elderly community-dwellings with complete socio-demographic data were analyzed by multinomial logistic regression. Four health latent classes were identified which included 1066 (43.5%) people in the High Comorbidity (HC), 152 (6.2%) in the Functional Impairment (FI), 252 (10.3%) in the Frail (FR), and 979 (40.0%) in the Relatively Healthy (RH) group. Multinomial logistic regressions revealed socio-demographic characteristics among health classes. The variables associated with an increased likelihood of being in the FR group were age, female, and living with families. They were also correlated to ethnicity and educations. Apart from age and gender, the Functional Impairment group was less likely to be ethnicity of Hakka, more likely to live with others than were the RH group. The HC group tended to be younger, with higher educations, and more likely to live in urban area than the Functional Impairment group. The correlations between health classes and socio-demographic factors were discussed. The health status of elderly people includes a variety of health indicators. A person-centered approach is critical to identify the health heterogeneity of elderly people and manage their care needs by targeting differential aging. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

Patterns of Drug Use and Serum Sodium Concentrations in Older Hospitalized Patients: A Latent Class Analysis Approach.

PubMed

Woodman, Richard J; Wood, Karen M; Kunnel, Aline; Dedigama, Maneesha; Pegoli, Matthew A; Soiza, Roy L; Mangoni, Arduino A

2016-12-01

Several drugs may lower serum sodium concentrations (NaC) in older patients. However, distinguishing their individual effects is particularly difficult in this population because of the high prevalence of polypharmacy and disease states that are per se associated with hyponatremia. Our objective was to identify specific patterns of medication use in older hospitalized patients and determine whether these patterns were associated with serum NaC. We collected clinical and demographic data, pre-admission drugs, Drug Burden Index (DBI) score, and average NaC during hospitalization in a consecutive series of older medical patients (n = 101, mean ± standard deviation [SD] age 87 ± 6 years). We used latent class analysis (LCA) to identify specific patterns of drug use and multivariate regression to determine the associations between 14 separate drug classes, identified patterns of drug use, and NaC. LCA revealed three patterns: lower overall drug use (class 1), anticoagulant use and higher drug use (class 2), and antiplatelet use (class 3). Mean (±SD) DBI score in each class was 2.7 ± 1.3, 3.3 ± 1.6, and 2.4 ± 1.5, respectively (p = 0.04). Mean (± SD) NaC in classes 1, 2, and 3 were 140.6 ± 6.8, 138.7 ± 5.3, and 136.5 ± 4.7 mmol/l, respectively (p = 0.006). After adjustment for age, sex, Charlson Comorbidity Index score, estimated glomerular filtration rate (eGFR), DBI score, and digoxin use, mean NaC in class 2 and class 3 was significantly lower than in class 1 (-3.9 mmol/l; 95% confidence interval [CI] -7.1 to -0.8, p = 0.01 and -5.2 mmol/l; 95% CI -7.9 to -2.5, p < 0.001, respectively). Mean serum NaC was not significantly associated with any of the 14 individually assessed drug classes. In addition to latent class, increasing age and higher eGFR were also independently associated with lower serum NaC (p = 0.002 and p = 0.03, respectively). LCA enabled us to identify patterns of drug use associated with lower serum NaC in older inpatients. Our results suggest that older patients using antiplatelets or anticoagulants are especially at risk of lower serum NaC.

Symptoms of prolonged grief and posttraumatic stress following loss: A latent class analysis.

PubMed

Maccallum, Fiona; Bryant, Richard A

2018-04-01

Individuals vary in how they respond to bereavement. Those who experience poor bereavement outcomes often report symptoms from more than one diagnostic category. This study sought to identify groups of individuals who share similar patterns of prolonged grief disorder and posttraumatic stress disorder symptoms to determine whether these profiles are differentially related to negative appraisals thought to contribute to prolonged grief disorder and posttraumatic stress disorder symptomatology. Participants were 185 bereaved adults. Latent class analysis was used to identify subgroups of individuals who showed similar patterns of co-occurrence of prolonged grief disorder and posttraumatic stress disorder symptoms. Multinomial regression was used to examine the extent to which appraisal domains and sociodemographic and loss factors predicted class membership. Latent class analysis revealed three classes of participants: a low symptom group, a high prolonged grief disorder symptom group, and a high prolonged grief disorder and posttraumatic stress disorder symptom group. Membership of the prolonged grief disorder group and prolonged grief disorder and posttraumatic stress disorder group was predicted by higher mean negative self-related appraisals. Demographic and loss-related factors did not predict group membership. These findings have implications for understanding co-occurrence of prolonged grief disorder and posttraumatic stress disorder symptoms following bereavement. Findings are consistent with theoretical models highlighting the importance of negative self-related beliefs in prolonged grief disorder.

An examination of generalized anxiety disorder and dysthymic disorder by latent class analysis.

PubMed

Rhebergen, D; van der Steenstraten, I M; Sunderland, M; de Graaf, R; Ten Have, M; Lamers, F; Penninx, B W J H; Andrews, G

2014-06-01

The nosological status of generalized anxiety disorder (GAD) versus dysthymic disorder (DD) has been questioned. The aim of this study was to examine qualitative differences within (co-morbid) GAD and DD symptomatology. Latent class analysis was applied to anxious and depressive symptomatology of respondents from three population-based studies (2007 Australian National Survey of Mental Health and Wellbeing; National Comorbidity Survey Replication; and Netherlands Mental Health Survey and Incidence Study-2; together known as the Triple study) and respondents from a multi-site naturalistic cohort [Netherlands Study of Depression and Anxiety (NESDA)]. Sociodemographics and clinical characteristics of each class were examined. A three-class (Triple study) and two-class (NESDA) model best fitted the data, reflecting mainly different levels of severity of symptoms. In the Triple study, no division into a predominantly GAD or DD co-morbidity subtype emerged. Likewise, in spite of the presence of pure GAD and DD cases in the NESDA sample, latent class analysis did not identify specific anxiety or depressive profiles in the NESDA study. Next, sociodemographics and clinical characteristics of each class were examined. Classes only differed in levels of severity. The absence of qualitative differences in anxious or depressive symptomatology in empirically derived classes questions the differentiation between GAD and DD.

Molecular Characterization, Gene Evolution, and Expression Analysis of the Fructose-1, 6-bisphosphate Aldolase (FBA) Gene Family in Wheat (Triticum aestivum L.)

PubMed Central

Lv, Geng-Yin; Guo, Xiao-Guang; Xie, Li-Ping; Xie, Chang-Gen; Zhang, Xiao-Hong; Yang, Yuan; Xiao, Lei; Tang, Yu-Ying; Pan, Xing-Lai; Guo, Ai-Guang; Xu, Hong

2017-01-01

Fructose-1, 6-bisphosphate aldolase (FBA) is a key plant enzyme that is involved in glycolysis, gluconeogenesis, and the Calvin cycle. It plays significant roles in biotic and abiotic stress responses, as well as in regulating growth and development processes. In the present paper, 21 genes encoding TaFBA isoenzymes were identified, characterized, and categorized into three groups: class I chloroplast/plastid FBA (CpFBA), class I cytosol FBA (cFBA), and class II chloroplast/plastid FBA. By using a prediction online database and genomic PCR analysis of Chinese Spring nulli-tetrasomic lines, we have confirmed the chromosomal location of these genes in 12 chromosomes of four homologous groups. Sequence and genomic structure analysis revealed the high identity of the allelic TaFBA genes and the origin of different TaFBA genes. Numerous putative environment stimulus-responsive cis-elements have been identified in 1,500-bp regions of TaFBA gene promoters, of which the most abundant are the light-regulated elements (LREs). Phylogenetic reconstruction using the deduced protein sequence of 245 FBA genes indicated an independent evolutionary pathway for the class I and class II groups. Although, earlier studies have indicated that class II FBA only occurs in prokaryote and fungi, our results have demonstrated that a few class II CpFBAs exist in wheat and other closely related species. Class I TaFBA was predicted to be tetramers and class II to be dimers. Gene expression analysis based on microarray and transcriptome databases suggested the distinct role of TaFBAs in different tissues and developmental stages. The TaFBA 4–9 genes were highly expressed in leaves and might play important roles in wheat development. The differential expression patterns of the TaFBA genes in light/dark and a few abiotic stress conditions were also analyzed. The results suggested that LRE cis-elements of TaFBA gene promoters were not directly related to light responses. Most TaFBA genes had higher expression levels in the roots than in the shoots when under various stresses. Class I cytosol TaFBA genes, particularly TaFBA10/12/18 and TaFBA13/16, and three class II TaFBA genes are involved in responses to various abiotic stresses. Class I CpFBA genes in wheat are apparently sensitive to different stress conditions. PMID:28659962

Professional service use for a serious personal problem: Comparing older African Americans, Black Caribbeans, and non-Hispanic Whites using the National Survey of American Life

PubMed Central

Woodward, Amanda Toler; Chatters, Linda M.; Taylor, Harry Owen; Taylor, Robert Joseph

2014-01-01

Objectives Examines combinations of professionals visited for a serious personal problem. Methods The sample includes those aged 55 and older (n=862) from the National Survey of American Life (NSAL). Latent class analysis was used to identify groups of respondents based on types of professionals visited. Multinomial logistic regression was used to identify factors associated with group membership. Results Classes included health provider plus clergy, physician plus mental health provider, and limited provider use. Whites were more likely than African Americans to fall into the health provider plus clergy and physician plus mental health provider classes. Those with physical and emotional problems were more likely to be in the health provider plus clergy and physician plus mental health provider classes, respectively. Discussion Most respondents were in the limited provider use class suggesting that for many of problems, minimal professional help is utilized. Physicians and clergy were important across all three classes. PMID:25552527

Latent classes of emotional and behavioural problems in epidemiological and referred samples and their relations to DSM-IV diagnoses.

PubMed

Bianchi, Valentina; Brambilla, Paolo; Garzitto, Marco; Colombo, Paola; Fornasari, Livia; Bellina, Monica; Bonivento, Carolina; Tesei, Alessandra; Piccin, Sara; Conte, Stefania; Perna, Giampaolo; Frigerio, Alessandra; Castiglioni, Isabella; Fabbro, Franco; Molteni, Massimo; Nobile, Maria

2017-05-01

Researchers' interest have recently moved toward the identification of recurrent psychopathological profiles characterized by concurrent elevations on different behavioural and emotional traits. This new strategy turned to be useful in terms of diagnosis and outcome prediction. We used a person-centred statistical approach to examine whether different groups could be identified in a referred sample and in a general-population sample of children and adolescents, and we investigated their relation to DSM-IV diagnoses. A latent class analysis (LCA) was performed on the Child Behaviour Checklist (CBCL) syndrome scales of the referred sample (N = 1225), of the general-population sample (N = 3418), and of the total sample. Models estimating 1-class through 5-class solutions were compared and agreement in the classification of subjects was evaluated. Chi square analyses, a logistic regression, and a multinomial logistic regression analysis were used to investigate the relations between classes and diagnoses. In the two samples and in the total sample, the best-fitting models were 4-class solutions. The identified classes were Internalizing Problems (15.68%), Severe Dysregulated (7.82%), Attention/Hyperactivity (10.19%), and Low Problems (66.32%). Subsequent analyses indicated a significant relationship between diagnoses and classes as well as a main association between the severe dysregulated class and comorbidity. Our data suggested the presence of four different psychopathological profiles related to different outcomes in terms of psychopathological diagnoses. In particular, our results underline the presence of a profile characterized by severe emotional and behavioural dysregulation that is mostly associated with the presence of multiple diagnosis.

Latent Profile Analysis of Schizotypy and Paranormal Belief: Associations with Probabilistic Reasoning Performance

PubMed Central

Denovan, Andrew; Dagnall, Neil; Drinkwater, Kenneth; Parker, Andrew

2018-01-01

This study assessed the extent to which within-individual variation in schizotypy and paranormal belief influenced performance on probabilistic reasoning tasks. A convenience sample of 725 non-clinical adults completed measures assessing schizotypy (Oxford-Liverpool Inventory of Feelings and Experiences; O-Life brief), belief in the paranormal (Revised Paranormal Belief Scale; RPBS) and probabilistic reasoning (perception of randomness, conjunction fallacy, paranormal perception of randomness, and paranormal conjunction fallacy). Latent profile analysis (LPA) identified four distinct groups: class 1, low schizotypy and low paranormal belief (43.9% of sample); class 2, moderate schizotypy and moderate paranormal belief (18.2%); class 3, moderate schizotypy (high cognitive disorganization) and low paranormal belief (29%); and class 4, moderate schizotypy and high paranormal belief (8.9%). Identification of homogeneous classes provided a nuanced understanding of the relative contribution of schizotypy and paranormal belief to differences in probabilistic reasoning performance. Multivariate analysis of covariance revealed that groups with lower levels of paranormal belief (classes 1 and 3) performed significantly better on perception of randomness, but not conjunction problems. Schizotypy had only a negligible effect on performance. Further analysis indicated that framing perception of randomness and conjunction problems in a paranormal context facilitated performance for all groups but class 4. PMID:29434562

Latent Profile Analysis of Schizotypy and Paranormal Belief: Associations with Probabilistic Reasoning Performance.

PubMed

Denovan, Andrew; Dagnall, Neil; Drinkwater, Kenneth; Parker, Andrew

2018-01-01

This study assessed the extent to which within-individual variation in schizotypy and paranormal belief influenced performance on probabilistic reasoning tasks. A convenience sample of 725 non-clinical adults completed measures assessing schizotypy (Oxford-Liverpool Inventory of Feelings and Experiences; O-Life brief), belief in the paranormal (Revised Paranormal Belief Scale; RPBS) and probabilistic reasoning (perception of randomness, conjunction fallacy, paranormal perception of randomness, and paranormal conjunction fallacy). Latent profile analysis (LPA) identified four distinct groups: class 1, low schizotypy and low paranormal belief (43.9% of sample); class 2, moderate schizotypy and moderate paranormal belief (18.2%); class 3, moderate schizotypy (high cognitive disorganization) and low paranormal belief (29%); and class 4, moderate schizotypy and high paranormal belief (8.9%). Identification of homogeneous classes provided a nuanced understanding of the relative contribution of schizotypy and paranormal belief to differences in probabilistic reasoning performance. Multivariate analysis of covariance revealed that groups with lower levels of paranormal belief (classes 1 and 3) performed significantly better on perception of randomness, but not conjunction problems. Schizotypy had only a negligible effect on performance. Further analysis indicated that framing perception of randomness and conjunction problems in a paranormal context facilitated performance for all groups but class 4.

Relationships among Behavioral Profiles, Reading Performance, and Disability Labels: A Latent Class Analysis of Students in the ED, LD, and OHI Special Education Categories

ERIC Educational Resources Information Center

Weingarten, Zachary

2018-01-01

The aim of this study was to explore the variation in student behavior across the ED, LD, and OHI disability categories and to examine demographic, behavioral, and academic factors that may place students at risk for negative outcomes. This study used teachers' rating of students' in-class behavior to identify latent classes of students in the ED,…

Identifying Patterns of Situational Antecedents to Heavy Drinking among College Students

PubMed Central

Lau-Barraco, Cathy; Linden-Carmichael, Ashley N.; Braitman, Abby L.; Stamates, Amy L.

2016-01-01

Background Emerging adults have the highest prevalence of heavy drinking as compared to all other age groups. Given the negative consequences associated with such drinking, additional research efforts focused on at-risk consumption are warranted. The current study sought to identify patterns of situational antecedents to drinking and to examine their associations with drinking motivations, alcohol involvement, and mental health functioning in a sample of heavy drinking college students. Method Participants were 549 (65.8% women) college student drinkers. Results Latent profile analysis identified three classes based on likelihood of heavy drinking across eight situational precipitants. The “High Situational Endorsement” group reported the greatest likelihood of heavy drinking in most situations assessed. This class experienced the greatest level of alcohol-related harms as compared to the “Low Situational Endorsement” and “Moderate Situational Endorsement” groups. The Low Situational Endorsement class was characterized by the lowest likelihood of heavy drinking across all situational antecedents and they experienced the fewest alcohol-related harms, relative to the other classes. Class membership was related to drinking motivations with the “High Situational Endorsement” class endorsing the highest coping- and conformity-motivated drinking. The “High Situational Endorsement” class also reported experiencing more mental health symptoms than other groups. Conclusions The current study contributed to the larger drinking literature by identifying profiles that may signify a particularly risky drinking style. Findings may help guide intervention work with college heavy drinkers. PMID:28163666

Features and Natural Classes in ASL Handshapes

ERIC Educational Resources Information Center

Whitworth, Cecily

2011-01-01

This article argues for the necessity of phonetic analysis in signed language linguistics and presents a case study of one analytical system being used in a preliminary attempt to identify natural classes and investigate variation in ASL handshapes. Robbin Battison (1978) first described what is now a widely accepted list of basic handshapes,…

The Latent Classes of Subclinical ADHD Symptoms: Convergences of Multiple Informant Reports

ERIC Educational Resources Information Center

Kobor, Andrea; Takacs, Adam; Urban, Robert; Csepe, Valeria

2012-01-01

The purpose of the present study was to conduct latent class analysis on the Hyperactivity scale of the Strengths and Difficulties Questionnaire in order to identify distinct subgroups of subclinical ADHD in a multi-informant framework. We hypothesized a similar structure between teachers and parents, and differences in symptom severity across…

A Comparison of Classification Approaches for Cyberbullying and Traditional Bullying Using Data from Six European Countries

ERIC Educational Resources Information Center

Schultze-Krumbholz, Anja; Göbel, Kristin; Scheithauer, Herbert; Brighi, Antonella; Guarini, Annalisa; Tsorbatzoudis, Haralambos; Barkoukis, Vassilis; Pyzalski, Jacek; Plichta, Piotr; Del Rey, Rosario; Casas, José A.; Thompson, Fran; Smith, Peter K.

2015-01-01

In recently published studies on cyberbullying, students are frequently categorized into distinct (cyber)bully and (cyber)victim clusters based on theoretical assumptions and arbitrary cut-off scores adapted from traditional bullying research. The present study identified involvement classes empirically using latent class analysis (LCA), to…

Latent profile analysis and principal axis factoring of the DSM-5 dissociative subtype.

PubMed

Frewen, Paul A; Brown, Matthew F D; Steuwe, Carolin; Lanius, Ruth A

2015-01-01

A dissociative subtype has been recognized based on the presence of experiences of depersonalization and derealization in relation to DSM-IV posttraumatic stress disorder (PTSD). However, the dissociative subtype has not been assessed in a community sample in relation to the revised DSM-5 PTSD criteria. Moreover, the 20-item PTSD Checklist for DSM-5 (PCL-5) currently does not assess depersonalization and derealization. We therefore evaluated two items for assessing depersonalization and derealization in 557 participants recruited online who endorsed PTSD symptoms of at least moderate severity on the PCL-5. A five-class solution identified two PTSD classes who endorsed dissociative experiences associated with either 1) severe or 2) moderate PTSD symptom severity (D-PTSD classes). Those in the severe dissociative class were particularly likely to endorse histories of childhood physical and sexual abuse. A principal axis factor analysis of the symptom list identified six latent variables: 1) Reexperiencing, 2) Emotional Numbing/Anhedonia, 3) Dissociation, 4) Negative Alterations in Cognition & Mood, 5) Avoidance, and 6) Hyperarousal. The present results further support the presence of a dissociative subtype within the DSM-5 criteria for PTSD.

When addiction symptoms and life problems diverge: a latent class analysis of problematic gaming in a representative multinational sample of European adolescents.

PubMed

Colder Carras, Michelle; Kardefelt-Winther, Daniel

2018-04-01

The proposed diagnosis of Internet gaming disorder (IGD) in DSM-5 has been criticized for "borrowing" criteria related to substance addiction, as this might result in misclassifying highly involved gamers as having a disorder. In this paper, we took a person-centered statistical approach to group adolescent gamers by levels of addiction-related symptoms and gaming-related problems, compared these groups to traditional scale scores for IGD, and checked how groups were related to psychosocial well-being using a preregistered analysis plan. We performed latent class analysis and regression with items from IGD and psychosocial well-being scales in a representative sample of 7865 adolescent European gamers. Symptoms and problems matched in only two groups: an IGD class (2.2%) having a high level of symptoms and problems and a Normative class (63.5%) having low levels of symptoms and problems. We also identified two classes comprising 30.9% of our sample that would be misclassified based on their report of gaming-related problems: an Engaged class (7.3%) that seemed to correspond to the engaged gamers described in previous literature, and a Concerned class (23.6%) reporting few symptoms but moderate to high levels of problems. Our findings suggest that a reformulation of IGD is needed. Treating Engaged gamers as having IGD when their poor well-being might not be gaming related may delay appropriate treatment, while Concerned gamers may need help to reduce gaming but would not be identified as such. Additional work to describe the phenomenology of these two groups would help refine diagnosis, prevention and treatment for IGD.

SU-F-T-312: Identifying Distinct Radiation Therapy Plan Classes Through Multi-Dimensional Analysis of Plan Complexity Metrics

DOE Office of Scientific and Technical Information (OSTI.GOV)

Desai, V; Labby, Z; Culberson, W

Purpose: To determine whether body site-specific treatment plans form unique “plan class” clusters in a multi-dimensional analysis of plan complexity metrics such that a single beam quality correction determined for a representative plan could be universally applied within the “plan class”, thereby increasing the dosimetric accuracy of a detector’s response within a subset of similarly modulated nonstandard deliveries. Methods: We collected 95 clinical volumetric modulated arc therapy (VMAT) plans from four body sites (brain, lung, prostate, and spine). The lung data was further subdivided into SBRT and non-SBRT data for a total of five plan classes. For each control pointmore » in each plan, a variety of aperture-based complexity metrics were calculated and stored as unique characteristics of each patient plan. A multiple comparison of means analysis was performed such that every plan class was compared to every other plan class for every complexity metric in order to determine which groups could be considered different from one another. Statistical significance was assessed after correcting for multiple hypothesis testing. Results: Six out of a possible 10 pairwise plan class comparisons were uniquely distinguished based on at least nine out of 14 of the proposed metrics (Brain/Lung, Brain/SBRT lung, Lung/Prostate, Lung/SBRT Lung, Lung/Spine, Prostate/SBRT Lung). Eight out of 14 of the complexity metrics could distinguish at least six out of the possible 10 pairwise plan class comparisons. Conclusion: Aperture-based complexity metrics could prove to be useful tools to quantitatively describe a distinct class of treatment plans. Certain plan-averaged complexity metrics could be considered unique characteristics of a particular plan. A new approach to generating plan-class specific reference (pcsr) fields could be established through a targeted preservation of select complexity metrics or a clustering algorithm that identifies plans exhibiting similar modulation characteristics. Measurements and simulations will better elucidate potential plan-class specific dosimetry correction factors.« less

Race Differences in Patterns of Risky Behavior and Associated Risk Factors in Adolescence.

PubMed

Childs, Kristina K; Ray, James V

2017-05-01

Using data from the National Longitudinal Study of Adolescent Health (Add Health), this study expands on previous research by (a) examining differences across race in patterns or "subgroups" of adolescents based on nine self-reported behaviors (e.g., delinquency, substance use, risky sexual practices) and (b) comparing the risk factors (e.g., peer association, parenting, neighborhood cohesion), both within and across the race-specific subgroups, related to membership into the identified latent classes. The data used in this study include respondents aged 13 to 17 who participated in Waves 1 and 2 of the Add Health in-home interview. Latent class analysis (LCA) identified key differences in the number and characteristics of the latent classes across the racial subgroups. In addition, both similarities and differences in the risk factors for membership into the latent classes were identified across and within the race-specific subgroups. Implications for understanding risky behavior in adolescence, as well as directions for future research, are discussed.

Wildlife management by habitat units: A preliminary plan of action

NASA Technical Reports Server (NTRS)

Frentress, C. D.; Frye, R. G.

1975-01-01

Procedures for yielding vegetation type maps were developed using LANDSAT data and a computer assisted classification analysis (LARSYS) to assist in managing populations of wildlife species by defined area units. Ground cover in Travis County, Texas was classified on two occasions using a modified version of the unsupervised approach to classification. The first classification produced a total of 17 classes. Examination revealed that further grouping was justified. A second analysis produced 10 classes which were displayed on printouts which were later color-coded. The final classification was 82 percent accurate. While the classification map appeared to satisfactorily depict the existing vegetation, two classes were determined to contain significant error. The major sources of error could have been eliminated by stratifying cluster sites more closely among previously mapped soil associations that are identified with particular plant associations and by precisely defining class nomenclature using established criteria early in the analysis.

Everyday Discrimination and Mood and Substance Use Disorders: A Latent Profile Analysis with African Americans and Caribbean Blacks

PubMed Central

Clark, Trenette T.; Salas-Wright, Christopher P.; Vaughn, Michael G.; Whitfield, Keith E.

2016-01-01

Perceived discrimination is a major source of health-related stress. The purpose of this study was to model the heterogeneity of everyday-discrimination experiences among African American and Caribbean Blacks and to identify differences in the prevalence of mood and substance use outcomes, including generalized anxiety disorder, major depressive disorder, alcohol-use disorder, and illicit drug-use disorder among the identified subgroups. The study uses data from the National Survey of American Life obtained from a sample of African American and Caribbean Black respondents (N = 4,462) between 18 and 65 years. We used latent profile analysis and multinomial regression analyses to identify and validate latent subgroups and test hypotheses, yielding 4 classes of perceived everyday discrimination: Low Discrimination, Disrespect and Condescension, General Discrimination, and Chronic Discrimination. Findings show significant differences exist between the Low Discrimination and General Discrimination classes for major depressive disorder, alcohol-use disorder, and illicit drug-use disorder. Moreover, we find significant differences exist between the Low Discrimination and Chronic Discrimination classes for the four disorders examined. Compared with the Chronic Discrimination class, members of the other classes were significantly less likely to meet criteria for generalized anxiety disorder, major depressive disorder, alcohol-use disorder, and illicit drug-use disorder. Findings suggest elevated levels of discrimination increase risk for mood and substance-use disorders. Importantly, results suggest the prevalence of mood and substance-use disorders is a function of the type and frequency of discrimination that individuals experience. PMID:25254321

Predominant typologies of psychopathology in the United States: a latent class analysis.

PubMed

El-Gabalawy, Renée; Tsai, Jack; Harpaz-Rotem, Ilan; Hoff, Rani; Sareen, Jitender; Pietrzak, Robert H

2013-11-01

Latent class analysis (LCA) offers a parsimonious way of classifying common typologies of psychiatric comorbidity. We used LCA to identify the nature and correlates of predominant typologies of Axis I and II disorders in a large and comprehensive population-based sample of U.S. adults. We analyzed data from Wave 2 of the National Epidemiologic Survey on Alcohol and Related Conditions (2004-2005; n = 34,653), a population-based sample of U.S. adults. We derived latent classes based on all assessed Axis I and II disorders and examined the relationship between the identified Axis I classes and lifetime psychiatric disorders and suicide attempts, and physical and mental health-related quality of life. A four-class solution was optimal in characterizing predominant typologies of both Axis I and II disorders. For Axis I disorders, these included low psychopathology (n = 28,935, 84.0%), internalizing (n = 3693, 9.9%), externalizing (n = 1426, 4.5%), and high psychopathology (n = 599, 1.6%) classes. For Axis II disorders, these included no/low personality disorders (n = 31,265, 90.9%), obsessive/paranoid (n = 1635, 4.6%), borderline/dysregulated (n = 1319, 3.4%), and highly comorbid (n = 434, 1.1%) classes. Compared to the low psychopathology class, all other Axis I classes had significantly increased odds of mental disorders, elevated Axis II classes, suicide attempts and poorer quality of life, with the high psychopathology class having the overall highest rates of these correlates, with the exception of substance use disorders. Compared to the low psychopathology class, the internalizing and externalizing classes had increased rates of mood and anxiety disorders, and substance use disorders, respectively. Axis I and II psychopathology among U.S. adults may be best represented by four predominant typologies. Characterizing co-occurring patterns of psychopathology using person-based typologies represents a higher-order classification system that may be useful in clinical and research settings. Published by Elsevier Ltd.

Use of Latent Class Analysis to define groups based on validity, cognition, and emotional functioning.

PubMed

Morin, Ruth T; Axelrod, Bradley N

Latent Class Analysis (LCA) was used to classify a heterogeneous sample of neuropsychology data. In particular, we used measures of performance validity, symptom validity, cognition, and emotional functioning to assess and describe latent groups of functioning in these areas. A data-set of 680 neuropsychological evaluation protocols was analyzed using a LCA. Data were collected from evaluations performed for clinical purposes at an urban medical center. A four-class model emerged as the best fitting model of latent classes. The resulting classes were distinct based on measures of performance validity and symptom validity. Class A performed poorly on both performance and symptom validity measures. Class B had intact performance validity and heightened symptom reporting. The remaining two Classes performed adequately on both performance and symptom validity measures, differing only in cognitive and emotional functioning. In general, performance invalidity was associated with worse cognitive performance, while symptom invalidity was associated with elevated emotional distress. LCA appears useful in identifying groups within a heterogeneous sample with distinct performance patterns. Further, the orthogonal nature of performance and symptom validities is supported.

Latent Classes of Adolescent Sexual and Romantic Relationship Experiences: Implications for Adult Sexual Health and Relationship Outcomes

PubMed Central

Vasilenko, Sara A.; Kugler, Kari C.; Lanza, Stephanie T.

2015-01-01

Adolescents’ sexual and romantic relationship experiences are multidimensional, but often studied as single constructs. Thus, it is not clear how different patterns of sexual and relationship experience may interact to differentially predict later outcomes. In this study we used latent class analysis to model patterns (latent classes) of adolescent sexual and romantic experiences, and then examined how these classes are associated with young adult sexual health and relationship outcomes in data from the National Longitudinal Study of Adolescent to Adult Health. We identified six adolescent relationship classes: No Relationship (33%), Waiting (22%), Intimate (38%), Private (3%), Low Involvement (3%), and Physical (2%). Adolescents in the Waiting and Intimate classes were more likely to have married by young adulthood than those in other classes, and those in the Physical class had a greater number of sexual partners and higher rates of STIs. Some gender differences were found; for example, women in the Low-involvement and Physical classes in adolescence had average or high odds of marriage, whereas men in these classes had relatively low odds of marriage. Our findings identify more and less normative patterns of romantic and sexual experiences in late adolescence, and elucidate associations between adolescent experiences and adult outcomes. PMID:26445133

Discordant inflammation and pain in early and established rheumatoid arthritis: Latent Class Analysis of Early Rheumatoid Arthritis Network and British Society for Rheumatology Biologics Register data.

PubMed

McWilliams, Daniel F; Ferguson, Eamonn; Young, Adam; Kiely, Patrick D W; Walsh, David A

2016-12-13

Rheumatoid arthritis (RA) disease activity is often measured using the 28-joint Disease Activity Score (DAS28). We aimed to identify and independently verify subgroups of people with RA that may be discordant with respect to self-reported and objective disease state, with potentially different clinical needs. Data were derived from three cohorts: (1) the Early Rheumatoid Arthritis Network (ERAN) and the British Society for Rheumatology Biologics Register (BSRBR), (2) those commencing tumour necrosis factor (TNF)-α inhibitors and (3) those using non-biologic drugs. In latent class analysis, we used variables related to pain, central pain mechanisms or inflammation (pain, vitality, mental health, erythrocyte sedimentation rate, swollen joint count, tender joint count, visual analogue scale of general health). Clinically relevant outcomes were examined. Five, four and four latent classes were found in the ERAN, BSRBR TNF inhibitor and non-biologic cohorts, respectively. The proportions of people assigned with >80% probability into latent classes were 76%, 58% and 72% in the ERAN, TNF inhibitor and non-biologic cohorts, respectively. The latent classes displayed either concordance between measures indicative of mild, moderate or severe disease activity; discordantly worse patient-reported measures despite less markedly elevated inflammation; or discordantly less severe patient-reported measures despite elevated inflammation. Latent classes with discordantly worse patient-reported measures represented 12%, 40% and 21% of the ERAN, TNF inhibitor and non-biologic cohorts, respectively; contained more females; and showed worse function. In those latent classes with worse scores at baseline, DAS28 and function improved over 1 year (p < 0.001 for all comparisons), and scores differed less at follow-up than at baseline. Discordant latent classes can be identified in people with RA, and these findings are robust across three cohorts with varying disease duration and activity. These findings could be used to identify a sizeable subgroup of people with RA who might gain added benefit from pain management strategies.

Content Themes of Alcohol Advertising in US Television — Latent Class Analysis

PubMed Central

Morgenstern, Matthis; Schoeppe, Franziska; Campbell, Julie; Braam, Marloes W.G.; Stoolmiller, Michael; Sargent, James D.

2015-01-01

Background There is little alcohol research that reports on the thematic contents of contemporary alcohol advertisements in US television. Studies of alcohol ads from two decades ago did not identify “partying” as a social theme. Aim of the present study was to describe and classify alcohol advertisements aired in national television in terms of contents, airing times, and channel placements and to identify different marketing strategies of alcohol brands. Methods Content analysis of all ads from the top 20 US beer and spirit brands aired between July 2009 and June 2011. These were 581 unique alcohol ads accounting for 272,828 (78%) national television airings. Ads were coded according to predefined definitions of 13 content areas. A latent class analysis (LCA) was conducted to define content cluster themes and determine alcoholic brands that were more likely to exploit these themes. Results About half of the advertisements (46%) were aired between 3am and 8pm, and the majority were placed either in Entertainment (40%) and Sports (38%) channels. Beer ads comprised 64% of the sample, with significant variation in airing times and channels between types of products and brands. LCA revealed five content classes that exploited the “Partying”, “Quality”, “Sports”, “Manly”, and “Relax” themes. The partying class, indicative of ad messages surrounding partying, love and sex, was the dominant theme, comprising 42% of all advertisements. Ads for alcopops, flavored spirits, and liqueur were more likely to belong to the party class, but there were also some beer brands (Corona, Heineken) where more than 67% of ads exploited this theme. Conclusions This is the first analysis to identify a partying theme to contemporary alcohol advertising. Future analyses can now determine whether exposure to that or other themes predicts alcohol misuse among youth audiences. PMID:26207317

Analysis of MHC class I genes across horse MHC haplotypes

PubMed Central

Tallmadge, Rebecca L.; Campbell, Julie A.; Miller, Donald C.; Antczak, Douglas F.

2010-01-01

The genomic sequences of 15 horse Major Histocompatibility Complex (MHC) class I genes and a collection of MHC class I homozygous horses of five different haplotypes were used to investigate the genomic structure and polymorphism of the equine MHC. A combination of conserved and locus-specific primers was used to amplify horse MHC class I genes with classical and non-classical characteristics. Multiple clones from each haplotype identified three to five classical sequences per homozygous animal, and two to three non-classical sequences. Phylogenetic analysis was applied to these sequences and groups were identified which appear to be allelic series, but some sequences were left ungrouped. Sequences determined from MHC class I heterozygous horses and previously described MHC class I sequences were then added, representing a total of ten horse MHC haplotypes. These results were consistent with those obtained from the MHC homozygous horses alone, and 30 classical sequences were assigned to four previously confirmed loci and three new provisional loci. The non-classical genes had few alleles and the classical genes had higher levels of allelic polymorphism. Alleles for two classical loci with the expected pattern of polymorphism were found in the majority of haplotypes tested, but alleles at two other commonly detected loci had more variation outside of the hypervariable region than within. Our data indicate that the equine Major Histocompatibility Complex is characterized by variation in the complement of class I genes expressed in different haplotypes in addition to the expected allelic polymorphism within loci. PMID:20099063

The character strengths of class clowns

PubMed Central

Ruch, Willibald; Platt, Tracey; Hofmann, Jennifer

2014-01-01

Class clowns traditionally were studied as a type concept and identified via sociometric procedures. In the present study a variable-centered approach was favored and class clown behaviors were studied in the context of character strengths, orientations to happiness and satisfaction with life. A sample of 672 Swiss children and adolescents filled in an 18 item self-report instrument depicting class clown behaviors. A hierarchical model of class clown behaviors was developed distinguishing a general factor and the four positively correlated dimensions of “identified as a class clown,” “comic talent,” “disruptive rule-breaker,” and “subversive joker.” Analysis of the general factor showed that class clowns were primarily male, and tended to be seen as class clowns by the teacher. Analyses of the 24 character strengths of the VIA-Youth (Park and Peterson, 2006) showed that class clowns were high in humor and leadership, and low in strengths like prudence, self-regulation, modesty, honesty, fairness, perseverance, and love of learning. An inspection of signature strengths revealed that 75% of class clowns had humor as a signature strength. Furthermore, class clown behaviors were generally shown by students indulging in a life of pleasure, but low life of engagement. The four dimensions yielded different character strengths profiles. While all dimensions of class clowns behaviors were low in temperance strengths, the factors “identified as the class clown” and “comic talent” were correlated with leadership strengths and the two negative factors (“disruptive rule-breaker,” “subversive joker”) were low in other directed strengths. The disruptive rule breaking class clown was additionally low in intellectual strengths. While humor predicted life satisfaction, class clowning tended to go along with diminished satisfaction with life. It is concluded that different types of class clowns need to be kept apart and need different attention by teachers. PMID:25324796

Differences in Weight-Related Behavioral Profiles by Sexual Orientation Among College Men: A Latent Class Analysis

PubMed Central

VanKim, Nicole A.; Erickson, Darin J.; Eisenberg, Marla E.; Lust, Katherine; Rosser, B. R. Simon; Laska, Melissa N.

2015-01-01

Purpose To identify and describe homogenous classes of male college students based on their weight-related behaviors (e.g., eating habits, physical activity, and unhealthy weight control) and to examine differences by sexual orientation. Design Study design was a cross-sectional sample of 2- and 4-year college students. Setting Study setting was forty-six 2- and 4-year colleges in Minnesota. Subjects Study subjects comprised 10,406 college males. Measures Measures were five categories of sexual orientation derived from self-reported sexual identity and behavior (heterosexual, discordant heterosexual [identifies as heterosexual and engages in same-sex sexual behavior], gay, bisexual, and unsure) and nine weight-related behaviors (including measures for eating habits, physical activity, and unhealthy weight control). Analysis Latent class models were fit for each of the five sexual orientation groups, using the nine weight-related behaviors. Results Overall, four classes were identified: “healthier eating habits” (prevalence range, 39.4%–77.3%), “moderate eating habits” (12.0%–30.2%), “unhealthy weight control” (2.6%–30.4%), and “healthier eating habits, more physically active” (35.8%). Heterosexual males exhibited all four patterns, gay and unsure males exhibited four patterns that included variations on the overall classes identified, discordant heterosexual males exhibited two patterns (“healthier eating habits” and “unhealthy weight control”), and bisexual males exhibited three patterns (“healthier eating habits,” “moderate eating habits,” and “unhealthy weight control”). Conclusion Findings highlight the need for multibehavioral interventions for discordant heterosexual, gay, bisexual, and unsure college males, particularly around encouraging physical activity and reducing unhealthy weight control behaviors. PMID:26305726

Sexual Behavior Latent Classes Among Men Who Have Sex With Men: Associations With Sexually Transmitted Infections.

PubMed

Rice, Cara E; Norris Turner, Abigail; Lanza, Stephanie T

2017-01-01

Men who have sex with men (MSM) are at disproportionate risk of acquisition of sexually transmitted infections (STIs). We used latent class analysis (LCA) to examine patterns of sexual behavior among MSM and how those patterns are related to STIs. We examined patterns of sexual behavior using behavioral and clinical data from a cross-sectional study of 235 MSM who presented to an urban sexual health clinic for STI testing. Analyzed data were collected using a combination of interviewer- and self-administered surveys and electronic health records. We used LCA to identify underlying subgroups of men based on their sexual behavior, described the demographics of the latent classes, and examined the association between the latent classes and STI status. We identified three latent classes of sexual behavior: Unprotected Anal Intercourse (UAI) Only (67%), Partner Seekers (14%), and Multiple Behaviors (19%). Men in the Multiple Behaviors class had a 67% probability of being STI positive, followed by men in the UAI Only class (27%) and men in the Partner Seekers class (22%). Examining the intersection of a variety of sexual practices indicates particular subgroups of MSM have the highest probability of being STI positive.

AVO Analysis of a Shallow Gas Accumulation in the Marmara Sea

NASA Astrophysics Data System (ADS)

Er, M.; Dondurur, D.; Çifçi, G.

2012-04-01

In recent years, Amplitude versus Offset-AVO analysis is widely used in determination and classification of gas anomalies from wide-offset seismic data. Bright spots which are among the significant factors in determining the hydrocarbon accumulations, can also be determined sucessfully using AVO analysis. A bright spot anomaly were identified on the multi-channel seismic data collected by R/V K. Piri Reis research vessel in the Marmara Sea in 2008. On prestack seismic data, the associated AVO anomalies are clearly identified on the supergathers. Near- and far-offset stack sections are plotted to show the amplitudes changes at different offsets and the bright amplitudes were observed on the far-offset stack. AVO analysis was applied to the observed bright spot anomaly following the standart data processing steps. The analysis includes the preparation of Intercept, Gradient and Fluid Factor sections of AVO attribues. Top and base boundaries of gas bearing sediment were shown by intercept - gradient crossplot method. 1D modelling was also performed to show AVO classes and models were compared with the analysis results. It is interpreted that the bright spot anomaly arises from a shallow gas accumulation. In addition, the gas saturation from P-wave velocity was also estimated by the analysis. AVO analysis indicated Class 3 and Class 4 AVO anomalies observed on the bright spot anomaly.

A Latent Class Analysis of Early Adolescent Peer and Dating Violence: Associations With Symptoms of Depression and Anxiety.

PubMed

Garthe, Rachel C; Sullivan, Terri N; Behrhorst, Kathryn L

2018-02-01

Violence within peer and dating contexts is prevalent among early adolescents. Youth may be victims and/or aggressors and be involved in violence across multiple contexts, resulting in negative outcomes. This study identified patterns of perpetration and victimization for peer and dating violence, using a latent class analysis (LCA), and examined how different patterns of engaging in or experiencing violence among early adolescents were associated with symptoms of depression and anxiety. Participants included a sample of 508 racially and ethnically diverse youth (51% male) who had dated in the past 3 months. Youth were in the seventh grade within 37 schools and were primarily from economically disadvantaged communities across four sites in the United States. LCA identified three classes: (a) a low involvement in violence class, (b) a peer aggression and peer victimization class, and (c) a peer and dating violence class. Youth involved with multiple forms of violence displayed significantly higher levels of depressive and anxious symptoms than those with low involvement in violence. Study findings revealed the importance of understanding how peer and dating violence co-occur, and how different patterns of aggression and victimization were related to internalizing symptoms. Prevention efforts should address the intersection of victimization and perpetration in peer and dating contexts in potentially reducing internalizing symptoms among early adolescents.

Identification of Heterogeneous Cognitive Subgroups in Community-Dwelling Older Adults: A Latent Class Analysis of the Einstein Aging Study.

PubMed

Zammit, Andrea R; Hall, Charles B; Lipton, Richard B; Katz, Mindy J; Muniz-Terrera, Graciela

2018-05-01

The aim of this study was to identify natural subgroups of older adults based on cognitive performance, and to establish each subgroup's characteristics based on demographic factors, physical function, psychosocial well-being, and comorbidity. We applied latent class (LC) modeling to identify subgroups in baseline assessments of 1345 Einstein Aging Study (EAS) participants free of dementia. The EAS is a community-dwelling cohort study of 70+ year-old adults living in the Bronx, NY. We used 10 neurocognitive tests and 3 covariates (age, sex, education) to identify latent subgroups. We used goodness-of-fit statistics to identify the optimal class solution and assess model adequacy. We also validated our model using two-fold split-half cross-validation. The sample had a mean age of 78.0 (SD=5.4) and a mean of 13.6 years of education (SD=3.5). A 9-class solution based on cognitive performance at baseline was the best-fitting model. We characterized the 9 identified classes as (i) disadvantaged, (ii) poor language, (iii) poor episodic memory and fluency, (iv) poor processing speed and executive function, (v) low average, (vi) high average, (vii) average, (viii) poor executive and poor working memory, (ix) elite. The cross validation indicated stable class assignment with the exception of the average and high average classes. LC modeling in a community sample of older adults revealed 9 cognitive subgroups. Assignment of subgroups was reliable and associated with external validators. Future work will test the predictive validity of these groups for outcomes such as Alzheimer's disease, vascular dementia and death, as well as markers of biological pathways that contribute to cognitive decline. (JINS, 2018, 24, 511-523).

Comparative phylogenomic analysis provides insights into TCP gene functions in Sorghum

PubMed Central

Francis, Aleena; Dhaka, Namrata; Bakshi, Mohit; Jung, Ki-Hong; Sharma, Manoj K.; Sharma, Rita

2016-01-01

Sorghum is a highly efficient C4 crop with potential to mitigate challenges associated with food, feed and fuel. TCP proteins are of particular interest for crop improvement programs due to their well-demonstrated roles in crop domestication and shaping plant architecture thereby, affecting agronomic traits. We identified 20 TCP genes from Sorghum. Except SbTCP8, all are either intronless or contain introns in the untranslated regions. Comparative phylogenetic analysis of Arabidopsis, rice, Brachypodium and Sorghum TCP proteins revealed two distinct classes categorized into ten sub-clades. Sub-clade F is dicot-specific, whereas A2, G1 and I1 groups only contained genes from grasses. Sub-clade B was missing in Sorghum, whereas group A1 was missing in rice indicating species-specific divergence of TCP proteins. TCP proteins of Sorghum are enriched in disorder promoting residues with class I containing higher percent disorder than class II proteins. Seven pairs of paralogous TCP genes were identified from Sorghum, five of which seem to predate Rice-Sorghum divergence. All of them have diverged in their expression. Based on the expression and orthology analysis, five Sorghum genes have been shortlisted for further investigation for their roles in regulating plant morphology. Whereas, three genes have been identified as candidates for engineering abiotic stress tolerance. PMID:27917941

Comparative phylogenomic analysis provides insights into TCP gene functions in Sorghum.

PubMed

Francis, Aleena; Dhaka, Namrata; Bakshi, Mohit; Jung, Ki-Hong; Sharma, Manoj K; Sharma, Rita

2016-12-05

Sorghum is a highly efficient C4 crop with potential to mitigate challenges associated with food, feed and fuel. TCP proteins are of particular interest for crop improvement programs due to their well-demonstrated roles in crop domestication and shaping plant architecture thereby, affecting agronomic traits. We identified 20 TCP genes from Sorghum. Except SbTCP8, all are either intronless or contain introns in the untranslated regions. Comparative phylogenetic analysis of Arabidopsis, rice, Brachypodium and Sorghum TCP proteins revealed two distinct classes categorized into ten sub-clades. Sub-clade F is dicot-specific, whereas A2, G1 and I1 groups only contained genes from grasses. Sub-clade B was missing in Sorghum, whereas group A1 was missing in rice indicating species-specific divergence of TCP proteins. TCP proteins of Sorghum are enriched in disorder promoting residues with class I containing higher percent disorder than class II proteins. Seven pairs of paralogous TCP genes were identified from Sorghum, five of which seem to predate Rice-Sorghum divergence. All of them have diverged in their expression. Based on the expression and orthology analysis, five Sorghum genes have been shortlisted for further investigation for their roles in regulating plant morphology. Whereas, three genes have been identified as candidates for engineering abiotic stress tolerance.

Latino cigarette smoking patterns by gender in a US national sample

PubMed Central

Kristman-Valente, Allison; Flaherty, Brian P.

2015-01-01

Background Latino smokers are a rising public health concern who experience elevated tobacco related health disparities. Purpose Additional information on Latino smoking is needed to inform screening and treatment. Analysis Latent class analysis using smoking frequency, cigarette preferences, onset, smoking duration, cigarettes per day and minutes to first cigarette were used to create multivariate latent smoking profiles for Latino men and women. Results Final models found seven classes for Latinas and nine classes for Latinos. Despite a common finding in the literature that Latino smokers are more likely to be low-risk, intermittent smokers, the majority of classes, for both males and females, described patterns of high-risk, daily smoking. Gender variations in smoking classes were noted. Conclusions Several markers of smoking risk were identified among both male and female Latino smokers including long durations of smoking, daily smoking and preference for specialty cigarettes, all factors associated with long-term health consequences. PMID:26304857

Principal component analysis and analysis of variance on the effects of Entellan New on the Raman spectra of fibers.

PubMed

Yu, Marcia M L; Sandercock, P Mark L

2012-01-01

During the forensic examination of textile fibers, fibers are usually mounted on glass slides for visual inspection and identification under the microscope. One method that has the capability to accurately identify single textile fibers without subsequent demounting is Raman microspectroscopy. The effect of the mountant Entellan New on the Raman spectra of fibers was investigated to determine if it is suitable for fiber analysis. Raman spectra of synthetic fibers mounted in three different ways were collected and subjected to multivariate analysis. Principal component analysis score plots revealed that while spectra from different fiber classes formed distinct groups, fibers of the same class formed a single group regardless of the mounting method. The spectra of bare fibers and those mounted in Entellan New were found to be statistically indistinguishable by analysis of variance calculations. These results demonstrate that fibers mounted in Entellan New may be identified directly by Raman microspectroscopy without further sample preparation. © 2011 American Academy of Forensic Sciences.

Maltreatment and Mental Health Outcomes among Ultra-Poor Children in Burkina Faso: A Latent Class Analysis

PubMed Central

Ismayilova, Leyla; Gaveras, Eleni; Blum, Austin; Tô-Camier, Alexice; Nanema, Rachel

2016-01-01

Objectives Research about the mental health of children in Francophone West Africa is scarce. This paper examines the relationships between adverse childhood experiences, including exposure to violence and exploitation, and mental health outcomes among children living in ultra-poverty in rural Burkina Faso. Methods This paper utilizes baseline data collected from 360 children ages 10–15 and 360 of their mothers recruited from twelve impoverished villages in the Nord Region of Burkina, located near the Sahel Desert and affected by extreme food insecurity. We used a Latent Class Analysis to identify underlying patterns of maltreatment. Further, the relationships between latent classes and mental health outcomes were tested using mixed effected regression models adjusted for clustering within villages. Results About 15% of the children in the study scored above the clinical cut-off for depression, 17.8% for posttraumatic stress disorder (PTSD), and 6.4% for low self-esteem. The study identified five distinct sub-groups (or classes) of children based on their exposure to adverse childhood experiences. Children with the highest exposure to violence at home, at work and in the community (Abused and Exploited class) and children not attending school and working for other households, often away from their families (External Laborer class), demonstrated highest symptoms of depression and trauma. Despite living in adverse conditions and working to assist families, the study also identified a class of children who were not exposed to any violence at home or at work (Healthy and Non-abused class). Children in this class demonstrated significantly higher self-esteem (b = 0.92, SE = 0.45, p<0.05) and lower symptoms of trauma (b = -3.90, SE = 1.52, p<0.05). Conclusions This study offers insight into the psychological well-being of children in the context of ultra-poverty in Burkina Faso and associated context-specific adverse childhood experiences. Identifying specific sub-groups of children with increased exposure to life stressors has implications for program developers. Study findings indicate a further need to explore the mental health consequences of traumatic experiences within the context of ultra-poverty and to develop integrated economic and psychosocial interventions that prevent or mitigate childhood adversities linked with the family-level poverty and violence in the family. PMID:27764155

Maltreatment and Mental Health Outcomes among Ultra-Poor Children in Burkina Faso: A Latent Class Analysis.

PubMed

Ismayilova, Leyla; Gaveras, Eleni; Blum, Austin; Tô-Camier, Alexice; Nanema, Rachel

2016-01-01

Research about the mental health of children in Francophone West Africa is scarce. This paper examines the relationships between adverse childhood experiences, including exposure to violence and exploitation, and mental health outcomes among children living in ultra-poverty in rural Burkina Faso. This paper utilizes baseline data collected from 360 children ages 10-15 and 360 of their mothers recruited from twelve impoverished villages in the Nord Region of Burkina, located near the Sahel Desert and affected by extreme food insecurity. We used a Latent Class Analysis to identify underlying patterns of maltreatment. Further, the relationships between latent classes and mental health outcomes were tested using mixed effected regression models adjusted for clustering within villages. About 15% of the children in the study scored above the clinical cut-off for depression, 17.8% for posttraumatic stress disorder (PTSD), and 6.4% for low self-esteem. The study identified five distinct sub-groups (or classes) of children based on their exposure to adverse childhood experiences. Children with the highest exposure to violence at home, at work and in the community (Abused and Exploited class) and children not attending school and working for other households, often away from their families (External Laborer class), demonstrated highest symptoms of depression and trauma. Despite living in adverse conditions and working to assist families, the study also identified a class of children who were not exposed to any violence at home or at work (Healthy and Non-abused class). Children in this class demonstrated significantly higher self-esteem (b = 0.92, SE = 0.45, p<0.05) and lower symptoms of trauma (b = -3.90, SE = 1.52, p<0.05). This study offers insight into the psychological well-being of children in the context of ultra-poverty in Burkina Faso and associated context-specific adverse childhood experiences. Identifying specific sub-groups of children with increased exposure to life stressors has implications for program developers. Study findings indicate a further need to explore the mental health consequences of traumatic experiences within the context of ultra-poverty and to develop integrated economic and psychosocial interventions that prevent or mitigate childhood adversities linked with the family-level poverty and violence in the family.

Towards an Analysis of Review Article in Applied Linguistics: Its Classes, Purposes and Characteristics

ERIC Educational Resources Information Center

Azar, Ali Sorayyaei; Hashim, Azirah

2014-01-01

The classes, purposes and characteristics associated with the review article in the field of applied linguistics were analyzed. The data were collected from a randomly selected corpus of thirty two review articles from a discipline-related key journal in applied linguistics. The findings revealed that different sub-genres can be identified within…

The Relationship of Academic Self-Efficacy to Class Participation and Exam Performance

ERIC Educational Resources Information Center

Galyon, Charles E.; Blondin, Carolyn A.; Yaw, Jared S.; Nalls, Meagan L.; Williams, Robert L.

2012-01-01

This study examined the relationship of academic self-efficacy to engagement in class discussion and performance on major course exams among students (N = 165) in an undergraduate human development course. Cluster analysis was used to identify three levels of academic self-efficacy: high (n = 34), medium (n = 91), and low (n = 40). Results…

College Algebra Students' Attitudes toward Mathematics in Their Careers

ERIC Educational Resources Information Center

Champion, Joe; Parker, Frieda; Mendoza-Spencer, Bernadette; Wheeler, Ann

2011-01-01

The purpose of this study was to identify the degree to which college algebra students' value mathematical skills in their prospective careers. A survey was administered to N = 144 students in 6 college algebra classes at a mid-sized doctoral granting university. Students in half the classes completed a data analysis project, and half of the…

The Structure of Student Satisfaction with College Services: A Latent Class Model

ERIC Educational Resources Information Center

Adwere-Boamah, Joseph

2011-01-01

Latent Class Analysis (LCA) was used to identify distinct groups of Community college students based on their self-ratings of satisfaction with student service programs. The programs were counseling, financial aid, health center, student programs and student government. The best fitting model to describe the data was a two Discrete-Factor model…

Comparative structural modeling of six old yellow enzymes (OYEs) from the necrotrophic fungus Ascochyta rabiei: insight into novel OYE classes with differences in cofactor binding, organization of active site residues and stereopreferences.

PubMed

Nizam, Shadab; Gazara, Rajesh Kumar; Verma, Sandhya; Singh, Kunal; Verma, Praveen Kumar

2014-01-01

Old Yellow Enzyme (OYE1) was the first flavin-dependent enzyme identified and characterized in detail by the entire range of physical techniques. Irrespective of this scrutiny, true physiological role of the enzyme remains a mystery. In a recent study, we systematically identified OYE proteins from various fungi and classified them into three classes viz. Class I, II and III. However, there is no information about the structural organization of Class III OYEs, eukaryotic Class II OYEs and Class I OYEs of filamentous fungi. Ascochyta rabiei, a filamentous phytopathogen which causes Ascochyta blight (AB) in chickpea possesses six OYEs (ArOYE1-6) belonging to the three OYE classes. Here we carried out comparative homology modeling of six ArOYEs representing all the three classes to get an in depth idea of structural and functional aspects of fungal OYEs. The predicted 3D structures of A. rabiei OYEs were refined and evaluated using various validation tools for their structural integrity. Analysis of FMN binding environment of Class III OYE revealed novel residues involved in interaction. The ligand para-hydroxybenzaldehyde (PHB) was docked into the active site of the enzymes and interacting residues were analyzed. We observed a unique active site organization of Class III OYE in comparison to Class I and II OYEs. Subsequently, analysis of stereopreference through structural features of ArOYEs was carried out, suggesting differences in R/S selectivity of these proteins. Therefore, our comparative modeling study provides insights into the FMN binding, active site organization and stereopreference of different classes of ArOYEs and indicates towards functional differences of these enzymes. This study provides the basis for future investigations towards the biochemical and functional characterization of these enigmatic enzymes.

Attachment typologies and posttraumatic stress disorder (PTSD), depression and anxiety: a latent profile analysis approach

PubMed Central

Armour, Cherie; Elklit, Ask; Shevlin, Mark

2011-01-01

Background Bartholomew (1990) proposed a four category adult attachment model based on Bowlby's (1973) proposal that attachment is underpinned by an individual's view of the self and others. Previous cluster analytic techniques have identified four and two attachment styles based on the Revised Adult Attachment Scale (RAAS). In addition, attachment styles have been proposed to meditate the association between stressful life events and subsequent psychiatric status. Objective The current study aimed to empirically test the attachment typology proposed by Collins and Read (1990). Specifically, LPA was used to determine if the proposed four styles can be derived from scores on the dimensions of closeness/dependency and anxiety. In addition, we aimed to test if the resultant attachment styles predicted the severity of psychopathology in response to a whiplash trauma. Method A large sample of Danish trauma victims (N=1577) participated. A Latent Profile Analysis was conducted, using Mplus 5.1, on scores from the RAAS scale to ascertain if there were underlying homogeneous attachment classes/subgroups. Class membership was used in a series of one-way ANOVA tests to determine if classes were significantly different in terms of mean scores on measures of psychopathology. Results The three class solution was considered optimal. Class one was termed Fearful (18.6%), Class two Preoccupied (34.5%), and Class three Secure (46.9%). The secure class evidenced significantly lower mean scores on PTSD, depression, and anxiety measures compared to other classes, whereas the fearful class evidenced significantly higher mean scores compared to other classes. Conclusions The results demonstrated evidence of three discrete classes of attachment styles, which were labelled secure, preoccupied, and fearful. This is in contrast to previous cluster analytic techniques which have identified four and two attachment styles based on the RAAS.In addition, Securely attached individuals display lower levels of psychopathology post whiplash trauma. PMID:22893805

A latent class analysis of substance use and culture among gay, bisexual and other men who have sex with men.

PubMed

Card, Kiffer G; Armstrong, Heather L; Carter, Allison; Cui, Zishan; Wang, Lu; Zhu, Julia; Lachowsky, Nathan J; Moore, David M; Hogg, Robert S; Roth, Eric A

2018-03-28

Assessments of gay and bisexual men's substance use often obscures salient sociocultural and identity-related experiences related to how they use drugs. Latent class analysis was used to examine how patterns of substance use represent the social, economic and identity-related experiences of this population. Participants were sexually active gay and bisexual men (including other men who have sex with men), aged ≥ 16 years, living in Metro Vancouver (n = 774). LCA indicators included all substances used in the past six months self-reported by more than 30 men. Model selection was made with consideration to model parsimony, interpretability and optimisation of statistical criteria. Multinomial regression identified factors associated with class membership. A six-class solution was identified representing: 'assorted drug use' (4.5%); 'club drug use' (9.5%); 'street drug use' (12.1%); 'sex drug use' (11.4%); 'conventional drug use' (i.e. tobacco, alcohol, marijuana; 25.9%); and 'limited drug use' (36.7%). Factors associated with class membership included age, sexual orientation, annual income, occupation, income from drug sales, housing stability, group sex event participation, gay bars/clubs attendance, sensation seeking and escape motivation. These results highlight the need for programmes and policies that seek to lessen social disparities and account for social distinctions among this population.

Detection of 224 candidate structured RNAs by comparative analysis of specific subsets of intergenic regions

PubMed Central

Lünse, Christina E.; Corbino, Keith A.; Ames, Tyler D.; Nelson, James W.; Roth, Adam; Perkins, Kevin R.; Sherlock, Madeline E.

2017-01-01

Abstract The discovery of structured non-coding RNAs (ncRNAs) in bacteria can reveal new facets of biology and biochemistry. Comparative genomics analyses executed by powerful computer algorithms have successfully been used to uncover many novel bacterial ncRNA classes in recent years. However, this general search strategy favors the discovery of more common ncRNA classes, whereas progressively rarer classes are correspondingly more difficult to identify. In the current study, we confront this problem by devising several methods to select subsets of intergenic regions that can concentrate these rare RNA classes, thereby increasing the probability that comparative sequence analysis approaches will reveal their existence. By implementing these methods, we discovered 224 novel ncRNA classes, which include ROOL RNA, an RNA class averaging 581 nt and present in multiple phyla, several highly conserved and widespread ncRNA classes with properties that suggest sophisticated biochemical functions and a multitude of putative cis-regulatory RNA classes involved in a variety of biological processes. We expect that further research on these newly found RNA classes will reveal additional aspects of novel biology, and allow for greater insights into the biochemistry performed by ncRNAs. PMID:28977401

A latent class regression analysis of men's conformity to masculine norms and psychological distress.

PubMed

Wong, Y Joel; Owen, Jesse; Shea, Munyi

2012-01-01

How are specific dimensions of masculinity related to psychological distress in specific groups of men? To address this question, the authors used latent class regression to assess the optimal number of latent classes that explained differential relationships between conformity to masculine norms and psychological distress in a racially diverse sample of 223 men. The authors identified a 2-class solution. Both latent classes demonstrated very different associations between conformity to masculine norms and psychological distress. In Class 1 (labeled risk avoiders; n = 133), conformity to the masculine norm of risk-taking was negatively related to psychological distress. In Class 2 (labeled detached risk-takers; n = 90), conformity to the masculine norms of playboy, self-reliance, and risk-taking was positively related to psychological distress, whereas conformity to the masculine norm of violence was negatively related to psychological distress. A post hoc analysis revealed that younger men and Asian American men (compared with Latino and White American men) had significantly greater odds of being in Class 2 versus Class 1. The implications of these findings for future research and clinical practice are examined. (c) 2012 APA, all rights reserved.

Latent Class Analysis of HIV Risk Behaviors Among Russian Women at Risk for Alcohol-Exposed Pregnancies.

PubMed

Bohora, Som; Chaffin, Mark; Shaboltas, Alla; Bonner, Barbara; Isurina, Galina; Batluk, Julia; Bard, David; Tsvetkova, Larissa; Skitnevskaya, Larissa; Volkova, Elena; Balachova, Tatiana

2017-11-01

The number of HIV cases attributed to heterosexual contact and the proportion of women among HIV positive individuals has increased worldwide. Russia is a country with the highest rates of newly diagnosed HIV infections in the region, and the infection spreads beyond traditional risk groups. While young women are affected disproportionately, knowledge of HIV risk behaviors in women in the general population remains limited. The objectives of this study were to identify patterns of behaviors that place women of childbearing age at high risk for HIV transmission and determine whether socio-demographic characteristics and alcohol use are predictive of the risk pattern. A total of 708 non-pregnant women, aged between 18 and 44 years, who were at risk for an alcohol-exposed pregnancy were enrolled in two regions in Russia. Participants completed a structured interview focused on HIV risk behaviors, including risky sexual behavior and alcohol and drug use. Latent class analysis was utilized to examine associations between HIV risk and other demographic and alcohol use characteristics and to identify patterns of risk among women. Three classes were identified. 34.93% of participants were at high risk, combining their risk behaviors, e.g., having multiple sexual partners, with high partner's risk associated with partner's drug use (class I). Despite reporting self-perceived risk for HIV/STI, this class of participants was unlikely to utilize adequate protection (i.e., condom use). The second high risk class included 13.19% of participants who combined their risky sexual behaviors, i.e., multiple sexual partners and having STDs, with partner's risk that included partner's imprisonment and partner's sex with other women (class II). Participants in this class were likely to utilize protection/condoms. Finally, 51.88% of participants were at lower risk, which was associated primarily with their partners' risk, and these participants utilized protection (class III). The odds of being in class I compared with class III were 3.3 (95% CI [1.06, 10.38]) times higher for those women who had Alcohol Use Disorders Identification Test scores ≥ 8 than those who had lower scores, and were 3.9 (95% CI [1.69, 8.97]) times higher for those who used alcohol before sex than those who did not. In addition, women who drank more days per week were 1.36 times more likely to be in class II than in class III. The study informs prevention by identifying specific population groups and targets for interventions. Alcohol use is a significant predictor and an overarching factor of HIV risk in women. Since at-risk drinking is common among young Russian women, alcohol risk reduction should be an essential component of HIV prevention efforts.

Subgroups of Chemotherapy Patients With Distinct Morning and Evening Fatigue Trajectories

PubMed Central

Kober, Kord M.; Cooper, Bruce A.; Paul, Steven M.; Dunn, Laura B.; Levine, Jon D.; Wright, Fay; Hammer, Marilyn J.; Mastick, Judy; Venook, Alan; Aouizerat, Bradley E.; Miaskowski, Christine

2017-01-01

Purpose Purposes of this study were to: identify subgroups of patients with distinct trajectories for morning and evening fatigue; evaluate for differences in demographic and clinical characteristics among these subgroups; and compare and contrast the predictors of subgroup membership for morning and evening fatigue. Methods Outpatients with breast, gastrointestinal, gynecological, or lung cancer (n=582) completed questionnaires a total of six times over two cycles of CTX. Morning and evening fatigue severity were evaluated using the Lee Fatigue Scale. Latent profile analysis (LPA) was used to identify distinct subgroups. Results Three latent classes were identified for morning fatigue (i.e., Low (31.8%), High (51.4%), and Very High (16.8%)) and for evening evening fatigue (i.e., Moderate (20.0%), High (21.8%), and Very High (58.2%)). Most of the disease and treatment characteristics did not distinguish among the morning and evening fatigue classes. Compared to the Low class, patients in the High and Very High morning fatigue class were younger, had a lower functional status and higher level of comorbidity. Compared to the Moderate class, patients in the Very High evening fatigue class were younger, more likely to be female, had child care responsibilities, had a lower functional status, and a higher level of comorbidity. Conclusion LPA allows for the identification of risk factors for more severe fatigue. Since an overlap was not observed across the morning and evening fatigue classes and unique predictors for morning and evening fatigue were identified, these findings suggest that morning and evening fatigue may have distinct underlying mechanisms. PMID:26361758

Chronic Disease Risk Typologies among Young Adults in Community College.

PubMed

Jeffries, Jayne K; Lytle, Leslie; Sotres-Alvarez, Daniela; Golden, Shelley; Aiello, Allison E; Linnan, Laura

2018-03-01

To address chronic disease risk holistically from a behavioral perspective, insights are needed to refine understanding of the covariance of key health behaviors. This study aims to identify distinct typologies of young adults based on 4 modifiable risk factors of chronic disease using a latent class analysis approach, and to describe patterns of class membership based on demographic characteristics, living arrangements, and weight. Overall, 441 young adults aged 18-35 attending community colleges in the Minnesota Twin Cities area completed a baseline questionnaire for the Choosing Healthy Options in College Environments and Settings study, a RCT. Behavioral items were used to create indicators for latent classes, and individuals were classified using maximum-probability assignment. Three latent classes were identified: 'active, binge-drinkers with a healthy dietary intake' (13.1%); 'non-active, moderate-smokers and non-drinkers with poor dietary intake' (38.2%); 'moderately active, non-smokers and non-drinkers with moderately healthy dietary intake' (48.7%). Classes exhibited unique demographic and weight-related profiles. This study may contribute to the literature on health behaviors among young adults and provides evidence that there are weight and age differences among subgroups. Understanding how behaviors cluster is important for identifying groups for targeted interventions in community colleges.

Identifying Gender-Specific Developmental Trajectories of Nonviolent and Violent Delinquency from Adolescence to Young Adulthood

PubMed Central

Zheng, Yao; Cleveland, H. Harrington

2013-01-01

Most research examining gender differences in developmental trajectories of antisocial behavior does not consider subtypes of antisocial behavior and is difficult to generalize due to small nonrepresentative samples. The current study investigated gender difference in developmental trajectories from adolescence to young adulthood while addressing those limitations. Analyses were limited to respondents ages 15 and 16 in wave 1 (16–17 in wave 2, and 21–22 in wave 3) of the National Longitudinal Study of Adolescent Health (n = 6244, 49.5% males). Self-report nonviolent and violent delinquencies were simultaneously entered into latent class analysis. Four latent classes were identified: low, desister, decliner, and chronic (male-only). In addition to finding a male-specific chronic class, gender differences included differences in levels of nonviolent and violent delinquency between synonymous classes of males and females, and differences in prevalence of classes across genders. Neighborhood disadvantage and family support predicted trajectories. PMID:23375843

Identify the ability to purchase a house in the five major cities of Java for the Indonesian middle class using correspondence analysis

NASA Astrophysics Data System (ADS)

Ginanjar, Irlandia; Indratno, Sapto W.

2015-12-01

Ministry of Housing Republic of Indonesia explained that the Constitution mandates that every citizen has the right to reside. Jakarta, Surabaya, Bandung, Semarang, and Yogyakarta are five of Java's major cities with high population and investment opportunities, so the housing needs in that five cities is very high. Market sentiment analysis recorded the average of property purchasing power for Indonesian society around Rp 250 million, which the author assumes that the highest price for Indonesian middle class. Based on the fact, does the Indonesian middle class have the ability to purchase a house in the five major cities of Java? What facilities do they get? Both questions can be answered using the results of correspondence analysis.

Patterns of physical activity, sedentary behavior, and diet in U.S. adolescents.

PubMed

Iannotti, Ronald J; Wang, Jing

2013-08-01

To identify patterns in adolescents' obesogenic behaviors and their relations to physical and psychological health. A nationally representative sample of 9,174 U.S. adolescents ages 11 to 16 years was surveyed on physical activity (PA), screen-based sedentary behavior (SB), frequency of consumption of healthy and unhealthy food items, weight status, weight control behavior, depression, physical symptoms, body dissatisfaction, overall health, and life satisfaction. Latent class analysis was used to identify patterns of PA, SB, and diet. A model with three latent classes best fit the data: Class 1 with high PA and high fruit and vegetable intake and low SB and intake of sweets, soft drinks, chips, and fries; Class 2 with high SB and high intake of sweets, soft drinks, chips, and fries; and Class 3 with low PA, low fruit and vegetable intake, and low intake of sweets, chips, and fries. Membership in the three classes was related to age, gender, race/ethnicity, and socioeconomic status. In addition, members of Class 1 (26.5%) were more likely to be of normal weight status and to fare well on most of the other health indices; of Class 2 (26.4%) were less likely to be trying to lose weight but scored poorly on the mental health indices; and of Class 3 (47.2%) were less likely to be underweight and reported greater body dissatisfaction. Three prevalent patterns of adolescent obesogenic behaviors were identified and these patterns related to weight status, depression, and other indicators of physical and psychological health. Published by Elsevier Inc.

Behavioral and mental health risk factor profiles among diverse primary care patients.

PubMed

Glenn, Beth A; Crespi, Catherine M; Rodriguez, Hector P; Nonzee, Narissa J; Phillips, Siobhan M; Sheinfeld Gorin, Sherri N; Johnson, Sallie Beth; Fernandez, Maria E; Estabrooks, Paul; Kessler, Rodger; Roby, Dylan H; Heurtin-Roberts, Suzanne; Rohweder, Catherine L; Ory, Marcia G; Krist, Alex H

2018-06-01

Behavioral and mental health risk factors are prevalent among primary care patients and contribute substantially to premature morbidity and mortality and increased health care utilization and costs. Although prior studies have found most adults screen positive for multiple risk factors, limited research has attempted to identify factors that most commonly co-occur, which may guide future interventions. The purpose of this study was to identify subgroups of primary care patients with co-occurring risk factors and to examine sociodemographic characteristics associated with these subgroups. We assessed 12 behavioral health risk factors in a sample of adults (n=1628) receiving care from nine primary care practices across six U.S. states in 2013. Using latent class analysis, we identified four distinct patient subgroups: a 'Mental Health Risk' class (prevalence=14%; low physical activity, high stress, depressive symptoms, anxiety, and sleepiness), a 'Substance Use Risk' class (29%; highest tobacco, drug, alcohol use), a 'Dietary Risk' class (29%; high BMI, poor diet), and a 'Lower Risk' class (27%). Compared to the Lower Risk class, patients in the Mental Health Risk class were younger and less likely to be Latino/Hispanic, married, college educated, or employed. Patients in the Substance Use class tended to be younger, male, African American, unmarried, and less educated. African Americans were over 7 times more likely to be in the Dietary Risk versus Lower Risk class (OR 7.7, 95% CI 4.0-14.8). Given the heavy burden of behavioral health issues in primary care, efficiently addressing co-occurring risk factors in this setting is critical. Copyright © 2018 Elsevier Inc. All rights reserved.

Diversity and evolution of class 2 CRISPR–Cas systems

PubMed Central

Shmakov, Sergey; Smargon, Aaron; Scott, David; Cox, David; Pyzocha, Neena; Yan, Winston; Abudayyeh, Omar O.; Gootenberg, Jonathan S.; Makarova, Kira S.; Wolf, Yuri I.; Severinov, Konstantin; Zhang, Feng; Koonin, Eugene V.

2018-01-01

Class 2 CRISPR–Cas systems are characterized by effector modules that consist of a single multidomain protein, such as Cas9 or Cpf1. We designed a computational pipeline for the discovery of novel class 2 variants and used it to identify six new CRISPR–Cas subtypes. The diverse properties of these new systems provide potential for the development of versatile tools for genome editing and regulation. In this Analysis article, we present a comprehensive census of class 2 types and class 2 subtypes in complete and draft bacterial and archaeal genomes, outline evolutionary scenarios for the independent origin of different class 2 CRISPR–Cas systems from mobile genetic elements, and propose an amended classification and nomenclature of CRISPR–Cas. PMID:28111461

Organized Sport Trajectories from Childhood to Adolescence and Health Associations.

PubMed

Howie, Erin K; McVeigh, Joanne A; Smith, Anne J; Straker, Leon M

2016-07-01

The purpose of this study was to identify unique organized sport trajectories from early childhood to late adolescence in an Australian pregnancy cohort, the Raine Study. Participation in organized sport was assessed at ages 5, 8, 10, 14, and 17 yr. Physical activity, body composition, and self-rated physical and mental health were assessed at the age of 20 yr. Latent class analysis was used to identify patterns of sport participation. To assess the internal validity of the trajectory classes, differences in health characteristics between trajectories were analyzed using generalized linear models. For girls, three trajectory classes were identified: consistent sport participators (47.5%), sport dropouts (34.3%), and sport nonparticipators (18.1%). For boys, three trajectory classes were identified: consistent sport participators (55.2%), sport dropouts (36.9%), and sport joiners (8.1%). For girls, there were overall differences across trajectory classes in lean body mass (P = 0.003), lean mass index (P = 0.06), and physical health (P = 0.004). For boys, there were differences across classes in physical activity (P = 0.018), percent body fat (P = 0.002), lean body mass (P < 0.001), lean mass index (P < 0.001), physical health (P = 0.06), and depression scores (P = 0.27). This study identified unique, sex-specific trajectories of organized sport participation. The differences in health outcomes between trajectory classes, such as participants with consistent sport participation having more preferable health outcomes at the age of 20 yr, support the internal validity of the trajectories. Strategies are needed to identify and encourage those in the dropout trajectory to maintain their participation and those in the nonparticipator or joiner trajectories to join sport earlier. Specifically, interventions to encourage early sport participation in girls and help nonparticipating boys to join sport during adolescence may help more children receive the benefits of sport participation.

Gender Differences in Patterns of Substance Use and Delinquency: A Latent Transition Analysis

PubMed Central

Bright, Charlotte Lyn; Sacco, Paul; Kolivoski, Karen M.; Stapleton, Laura M.; Jun, Hyun-Jin; Morris-Compton, Darnell

2017-01-01

This study explores gender-specific patterns and transitions of adolescent substance use and delinquency in a sample of youths at ages 12, 15, and 18 (N = 803). Latent transition analysis identified “Primary Delinquent,” “Delinquency and Substance Use,” and “Low Risk” classes. Females were less likely to be in the “Primary Delinquent” class at age 12 than males. From 15 to 18, females were approximately equally likely to transition from “Primary Delinquent” to both other classes, whereas males were more likely to transition from “Primary Delinquent” to “Delinquency and Substance Use.” These gender differences in behavior can inform services. PMID:28603406

Evaluating the reforested area for the municipality of Buri by automatic analysis of LANDSAT imagery. [Sao Paulo, Brazil

NASA Technical Reports Server (NTRS)

Dejesusparada, N. (Principal Investigator); Lee, D. C. L.; Filho, R. H.; Shimabukuro, Y. E.

1979-01-01

The author has identified the following significant results. The class of reforestation (Pinus, Eucalyptus, Araucaria) was defined using iterative image analysis (1-100) and LANDSAT MSS data. Estimates of class area by 1-100 were compared with data supplied by the forestry institute in Sao Paulo. LANDSAT channels 4 and 5 served to differentiate the Pinus, Eucalyptus, and Araucaria from the other trees. Channels 6 and 7 gave best results for differentiating between the classes. A good representative spectral response was obtained for Auraucaria on these two channels. The small relative differences obtained were +4.24% for Araucaria, -7.51% for Pinus, and -32.07% for Eucalyptus.

Using the Mixed Rasch Model to analyze data from the beliefs and attitudes about memory survey.

PubMed

Smith, Everett V; Ying, Yuping; Brown, Scott W

2012-01-01

In this study, we used the Mixed Rasch Model (MRM) to analyze data from the Beliefs and Attitudes About Memory Survey (BAMS; Brown, Garry, Silver, and Loftus, 1997). We used the original 5-point BAMS data to investigate the functioning of the "Neutral" category via threshold analysis under a 2-class MRM solution. The "Neutral" category was identified as not eliciting the model expected responses and observations in the "Neutral" category were subsequently treated as missing data. For the BAMS data without the "Neutral" category, exploratory MRM analyses specifying up to 5 latent classes were conducted to evaluate data-model fit using the consistent Akaike information criterion (CAIC). For each of three BAMS subscales, a two latent class solution was identified as fitting the mixed Rasch rating scale model the best. Results regarding threshold analysis, person parameters, and item fit based on the final models are presented and discussed as well as the implications of this study.

Meta-Analysis at Middle Age: A Personal History

ERIC Educational Resources Information Center

Glass, Gene V.

2015-01-01

The 40-year history of meta-analysis is traced from the vantage point of one of its originators. Research syntheses leading to the first examples of meta-analysis are identified. Early meta-analyses of the literature on psychotherapy outcomes and school class size are recounted. The influence on the development of meta-analysis of several…

Analysis of substrate specificity of human DHHC protein acyltransferases using a yeast expression system

PubMed Central

Ohno, Yusuke; Kashio, Atsushi; Ogata, Ren; Ishitomi, Akihiro; Yamazaki, Yuki; Kihara, Akio

2012-01-01

Palmitoylation plays important roles in the regulation of protein localization, stability, and activity. The protein acyltransferases (PATs) have a common DHHC Cys-rich domain. Twenty-three DHHC proteins have been identified in humans. However, it is unclear whether all of these DHHC proteins function as PATs. In addition, their substrate specificities remain largely unknown. Here we develop a useful method to examine substrate specificities of PATs using a yeast expression system with six distinct model substrates. We identify 17 human DHHC proteins as PATs. Moreover, we classify 11 human and 5 yeast DHHC proteins into three classes (I, II, and III), based on the cellular localization of their respective substrates (class I, soluble proteins; class II, integral membrane proteins; class III, lipidated proteins). Our results may provide an important clue for understanding the function of individual DHHC proteins. PMID:23034182

Combinational pixel-by-pixel and object-level classifying, segmenting, and agglomerating in performing quantitative image analysis that distinguishes between healthy non-cancerous and cancerous cell nuclei and delineates nuclear, cytoplasm, and stromal material objects from stained biological tissue materials

DOEpatents

Boucheron, Laura E

2013-07-16

Quantitative object and spatial arrangement-level analysis of tissue are detailed using expert (pathologist) input to guide the classification process. A two-step method is disclosed for imaging tissue, by classifying one or more biological materials, e.g. nuclei, cytoplasm, and stroma, in the tissue into one or more identified classes on a pixel-by-pixel basis, and segmenting the identified classes to agglomerate one or more sets of identified pixels into segmented regions. Typically, the one or more biological materials comprises nuclear material, cytoplasm material, and stromal material. The method further allows a user to markup the image subsequent to the classification to re-classify said materials. The markup is performed via a graphic user interface to edit designated regions in the image.

Latent class analysis of accident risks in usage-based insurance: Evidence from Beijing.

PubMed

Jin, Wen; Deng, Yinglu; Jiang, Hai; Xie, Qianyan; Shen, Wei; Han, Weijian

2018-06-01

Car insurance is quickly becoming a big data industry, with usage-based insurance (UBI) poised to potentially change the business of insurance. Telematics data, which are transmitted from wireless devices in car, are widely used in UBI to obtain individual-level travel and driving characteristics. While most existing studies have introduced telematics data into car insurance pricing, the telematics-related characteristics are directly obtained from the raw data. In this study, we propose to quantify drivers' familiarity with their driving routes and develop models to quantify drivers' accident risks using the telematics data. In addition, we build a latent class model to study the heterogeneity in travel and driving styles based on the telematics data, which has not been investigated in literature. Our main results include: (1) the improvement to the model fit is statistically significant by adding telematics-related characteristics; (2) drivers' familiarity with their driving trips is critical to identify high risk drivers, and the relationship between drivers' familiarity and accident risks is non-linear; (3) the drivers can be classified into two classes, where the first class is the low risk class with 0.54% of its drivers reporting accidents, and the second class is the high risk class with 20.66% of its drivers reporting accidents; and (4) for the low risk class, drivers with high probability of reporting accidents can be identified by travel-behavior-related characteristics, while for the high risk class, they can be identified by driving-behavior-related characteristics. The driver's familiarity will affect the probability of reporting accidents for both classes. Copyright © 2018 Elsevier Ltd. All rights reserved.

Everyday discrimination and mood and substance use disorders: a latent profile analysis with African Americans and Caribbean Blacks.

PubMed

Clark, Trenette T; Salas-Wright, Christopher P; Vaughn, Michael G; Whitfield, Keith E

2015-01-01

Perceived discrimination is a major source of health-related stress. The purpose of this study was to model the heterogeneity of everyday-discrimination experiences among African American and Caribbean Blacks and to identify differences in the prevalence of mood and substance use outcomes, including generalized anxiety disorder, major depressive disorder, alcohol-use disorder, and illicit drug-use disorder among the identified subgroups. The study uses data from the National Survey of American Life obtained from a sample of African American and Caribbean Black respondents (N=4,462) between 18 and 65 years. We used latent profile analysis and multinomial regression analyses to identify and validate latent subgroups and test hypotheses, yielding 4 classes of perceived everyday discrimination: Low Discrimination, Disrespect and Condescension, General Discrimination, and Chronic Discrimination. Findings show significant differences exist between the Low Discrimination and General Discrimination classes for major depressive disorder, alcohol-use disorder, and illicit drug-use disorder. Moreover, we find significant differences exist between the Low Discrimination and Chronic Discrimination classes for the four disorders examined. Compared with the Chronic Discrimination class, members of the other classes were significantly less likely to meet criteria for generalized anxiety disorder, major depressive disorder, alcohol-use disorder, and illicit drug-use disorder. Findings suggest elevated levels of discrimination increase risk for mood and substance-use disorders. Importantly, results suggest the prevalence of mood and substance-use disorders is a function of the type and frequency of discrimination that individuals experience. Copyright © 2014 Elsevier Ltd. All rights reserved.

Familial psychosocial risk classes and preschooler body mass index: The moderating effect of caregiver feeding style.

PubMed

Horodynski, Mildred A; Brophy-Herb, Holly E; Martoccio, Tiffany L; Contreras, Dawn; Peterson, Karen; Shattuck, Mackenzie; Senehi, Neda; Favreau, Zachary; Miller, Alison L; Sturza, Julie; Kaciroti, Niko; Lumeng, Julie C

2018-04-01

Early child weight gain predicts adolescent and adult obesity, underscoring the need to determine early risk factors affecting weight status and how risk factors might be mitigated. Socioeconomic status, food insecurity, caregiver depressive symptomology, single parenthood, and dysfunctional parenting each have been linked to early childhood weight status. However, the associations between these risk factors and children's weight status may be moderated by caregiver feeding styles (CFS). Examining modifiable factors buffering risk could provide key information to guide early obesity intervention efforts. This analysis used baseline data from the Growing Healthy project that recruited caregivers/child dyads (N = 626) from Michigan Head Start programs. Caregivers were primarily non-Hispanic white (62%) and African American (30%). After using latent class analysis to identify classes of familial psychosocial risk, CFS was tested as a moderator of the association between familial psychosocial risk class and child body mass index (BMI) z-score. Latent class analysis identified three familial psychosocial risk classes: (1) poor, food insecure and depressed families; (2) poor, single parent families; and (3) low risk families. Interactive effects for uninvolved feeding styles and risk group indicated that children in poor, food insecure, and depressed families had higher BMI z-scores compared to children in the low risk group. Authoritative feeding styles in low risk and poor, food insecure, and depressed families showed lower child BMI z-scores relative to poor, single parent families with authoritative feeding styles. Uninvolved feeding styles intensified the risk and an authoritative feeding style muted the risk conferred by living in a poor, food-insecure, and depressed family. Interventions that promote responsive feeding practices could help decrease the associations of familial psychosocial risks with early child weight outcomes. Copyright © 2017 Elsevier Ltd. All rights reserved.

Anxiety, depression, and the suicidal spectrum: a latent class analysis of overlapping and distinctive features.

PubMed

Podlogar, Matthew C; Rogers, Megan L; Stanley, Ian H; Hom, Melanie A; Chiurliza, Bruno; Joiner, Thomas E

2017-03-20

Anxiety and depression diagnoses are associated with suicidal thoughts and behaviours. However, a categorical understanding of these associations limits insight into identifying dimensional mechanisms of suicide risk. This study investigated anxious and depressive features through a lens of suicide risk, independent of diagnosis. Latent class analysis of 97 depression, anxiety, and suicidality-related items among 616 psychiatric outpatients indicated a 3-class solution, specifically: (1) a higher suicide-risk class uniquely differentiated from both other classes by high reported levels of depression and anxious arousal; (2) a lower suicide-risk class that reported levels of anxiety sensitivity and generalised worry comparable to Class 1, but lower levels of depression and anxious arousal; and (3) a low to non-suicidal class that reported relatively low levels across all depression and anxiety measures. Discriminants of the higher suicide-risk class included borderline personality disorder; report of worthlessness, crying, and sadness; higher levels of anxious arousal and negative affect; and lower levels of positive affect. Depression and anxiety diagnoses were not discriminant between higher and lower suicide risk classes. This transdiagnostic and dimensional approach to understanding the suicidal spectrum contrasts with treating it as a depressive symptom, and illustrates the advantages of a tripartite model for conceptualising suicide risk.

Vip3C, a Novel Class of Vegetative Insecticidal Proteins from Bacillus thuringiensis

PubMed Central

Palma, Leopoldo; Hernández-Rodríguez, Carmen Sara; Maeztu, Mireya; Hernández-Martínez, Patricia; Ruiz de Escudero, Iñigo; Escriche, Baltasar; Muñoz, Delia; Van Rie, Jeroen; Ferré, Juan

2012-01-01

Three vip3 genes were identified in two Bacillus thuringiensis Spanish collections. Sequence analysis revealed a novel Vip3 protein class (Vip3C). Preliminary bioassays of larvae from 10 different lepidopteran species indicated that Vip3Ca3 caused more than 70% mortality in four species after 10 days at 4 μg/cm2. PMID:22865065

Assessing Child Rearing Style in Ecological Settings: Its Relation to Culture, Social Class, Early Age Intervention and Scholastic Achievement.

ERIC Educational Resources Information Center

Portes, Pedro R.; And Others

Fifty-four middle and lower class, black and white adolescents were observed interacting with their mothers during a discussion of seven child rearing problems. Maternal references to a range of disciplinary measures were identified, analyzed, and related to the subjects' scholastic performances. A factor analysis of process measures confirmed…

Longitudinal Physical Activity Patterns Among Older Adults: A Latent Transition Analysis.

PubMed

Mooney, Stephen J; Joshi, Spruha; Cerdá, Magdalena; Kennedy, Gary J; Beard, John R; Rundle, Andrew G

2018-05-14

Most epidemiologic studies of physical activity measure either total energy expenditure or engagement in a single activity type, such as walking. These approaches may gloss over important nuances in activity patterns. We performed a latent transition analysis to identify patterns of activity types as well as neighborhood and individual determinants of changes in those activity patterns over two years in a cohort of 2,023 older adult residents of New York City, NY, surveyed between 2011 and 2013. We identified seven latent classes: 1) Mostly Inactive, 2) Walking, 3) Exercise, 4) Household Activities and Walking, 5) Household Activities and Exercise, 6) Gardening and Household Activities, and 7) Gardening, Household Activities, and Exercise. The majority of subjects retained the same activity patterns between waves (54% unchanged between waves 1 and 2, 66% unchanged between waves 2 and 3).Most latent class transitions were between classes distinguished only by one form of activity, and only neighborhood unemployment was consistently associated with changing between activity latent classes. Future latent transition analyses of physical activity would benefit from larger cohorts and longer follow-up periods to assess predictors of and long-term impacts of changes in activity patterns.

[Latent Class Analysis of Gambling Activities among Korean Adolescents].

PubMed

Kang, Kyonghwa; Kim, Hyeongsu; Park, Ae Ran; Kim, Hee Young; Lee, Kunsei

2018-04-01

The aim of this study is to identify the types of gambling among adolescents and provide basic prevention information regarding adolescents' gambling problems. Secondary data from representative national survey on 2015 Youth Gambling Problems of Korea Center on Gambling Problems were used. Using latent class analysis (LCA), 13 gambling types such as offline and online games of 14,011 adolescents were classified, and gambling experiences and characteristics were analyzed. The subgroups of adolescent gambling were identified as four latent classes: a rare group (84.5% of the sample), a risk group (1.0%), an offline group (11.9%), and an expanded group (2.6%). The types and characteristics of gambling among the latent classes differed. In the risk group, adolescents participated in online illegal sports betting and internet casino, and gambling time, gambling expenses, and the number of gambling types were higher than other groups. Gambling frequently occur among adolescent, and the subtypes of gambling did not reveal homogeneous characteristics. In order to prevent adolescent gambling problems, it is a necessary to develop tailored prevention intervention in the nursing field, which is appropriate to the characteristics of adolescent gambling group and can help with early identification. © 2018 Korean Society of Nursing Science.

Retail Tobacco Exposure: Using Geographic Analysis to Identify Areas With Excessively High Retail Density

PubMed Central

2014-01-01

Introduction: There is great disparity in tobacco outlet density (TOD), with density highest in low-income areas and areas with greater proportions of minority residents, and this disparity may affect cancer incidence. We sought to better understand the nature of this disparity by assessing how these socio-demographic factors relate to TOD at the national level. Methods: Using mixture regression analysis and all of the nearly 65,000 census tracts in the contiguous United States, we aimed to determine the number of latent disparity classes by modeling the relations of proportions of Blacks, Hispanics, and families living in poverty with TOD, controlling for urban/rural status. Results: We identified six disparity classes. There was considerable heterogeneity in relation to TOD for Hispanics in rural settings. For Blacks, there was no relation to TOD in an urban moderate disparity class, and for rural census tracts, the relation was highest in a moderate disparity class. Conclusions: We demonstrated the utility of classifying census tracts on heterogeneity of tobacco risk exposure. This approach provides a better understanding of the complexity of socio-demographic influences of tobacco retailing and creates opportunities for policy makers to more efficiently target areas in greatest need. PMID:23999651

Retail tobacco exposure: using geographic analysis to identify areas with excessively high retail density.

PubMed

Rodriguez, Daniel; Carlos, Heather A; Adachi-Mejia, Anna M; Berke, Ethan M; Sargent, James

2014-02-01

There is great disparity in tobacco outlet density (TOD), with density highest in low-income areas and areas with greater proportions of minority residents, and this disparity may affect cancer incidence. We sought to better understand the nature of this disparity by assessing how these socio-demographic factors relate to TOD at the national level. Using mixture regression analysis and all of the nearly 65,000 census tracts in the contiguous United States, we aimed to determine the number of latent disparity classes by modeling the relations of proportions of Blacks, Hispanics, and families living in poverty with TOD, controlling for urban/rural status. We identified six disparity classes. There was considerable heterogeneity in relation to TOD for Hispanics in rural settings. For Blacks, there was no relation to TOD in an urban moderate disparity class, and for rural census tracts, the relation was highest in a moderate disparity class. We demonstrated the utility of classifying census tracts on heterogeneity of tobacco risk exposure. This approach provides a better understanding of the complexity of socio-demographic influences of tobacco retailing and creates opportunities for policy makers to more efficiently target areas in greatest need.

Latent profile analysis and principal axis factoring of the DSM-5 dissociative subtype

PubMed Central

Frewen, Paul A.; Brown, Matthew F. D.; Steuwe, Carolin; Lanius, Ruth A.

2015-01-01

Objective A dissociative subtype has been recognized based on the presence of experiences of depersonalization and derealization in relation to DSM-IV posttraumatic stress disorder (PTSD). However, the dissociative subtype has not been assessed in a community sample in relation to the revised DSM-5 PTSD criteria. Moreover, the 20-item PTSD Checklist for DSM-5 (PCL-5) currently does not assess depersonalization and derealization. Method We therefore evaluated two items for assessing depersonalization and derealization in 557 participants recruited online who endorsed PTSD symptoms of at least moderate severity on the PCL-5. Results A five-class solution identified two PTSD classes who endorsed dissociative experiences associated with either 1) severe or 2) moderate PTSD symptom severity (D-PTSD classes). Those in the severe dissociative class were particularly likely to endorse histories of childhood physical and sexual abuse. A principal axis factor analysis of the symptom list identified six latent variables: 1) Reexperiencing, 2) Emotional Numbing/Anhedonia, 3) Dissociation, 4) Negative Alterations in Cognition & Mood, 5) Avoidance, and 6) Hyperarousal. Conclusions The present results further support the presence of a dissociative subtype within the DSM-5 criteria for PTSD. PMID:25854673

Spectral Variability among Rocks in Visible and Near Infrared Multispectral Pancam Data Collected at Gusev Crater: Examinations using Spectral Mixture Analysis and Related Techniques

NASA Technical Reports Server (NTRS)

Farrand, W. H.; Bell, J. F., III; Johnson, J. R.; Squyres, S. W.; Soderblom, J.; Ming, D. W.

2006-01-01

Visible and Near Infrared (VNIR) multispectral observations of rocks made by the Mars Exploration Rover Spirit s Panoramic camera (Pancam) have been analysed using a spectral mixture analysis (SMA) methodology. Scenes have been examined from the Gusev crater plains into the Columbia Hills. Most scenes on the plains and in the Columbia Hills could be modeled as three endmember mixtures of a bright material, rock, and shade. Scenes of rocks disturbed by the rover s Rock Abrasion Tool (RAT) required additional endmembers. In the Columbia Hills there were a number of scenes in which additional rock endmembers were required. The SMA methodology identified relatively dust-free areas on undisturbed rock surfaces, as well as spectrally unique areas on RAT abraded rocks. Spectral parameters from these areas were examined and six spectral classes were identified. These classes are named after a type rock or area and are: Adirondack, Lower West Spur, Clovis, Wishstone, Peace, and Watchtower. These classes are discriminable based, primarily, on near-infrared (NIR) spectral parameters. Clovis and Watchtower class rocks appear more oxidized than Wishstone class rocks and Adirondack basalts based on their having higher 535 nm band depths. Comparison of the spectral parameters of these Gusev crater rocks to parameters of glass-dominated basaltic tuffs indicates correspondence between measurements of Clovis and Watchtower classes, but divergence for the Wishstone class rocks which appear to have a higher fraction of crystalline ferrous iron bearing phases. Despite a high sulfur content, the rock Peace has NIR properties resembling plains basalts.

Is there Complex Trauma Experience typology for Australian's experiencing extreme social disadvantage and low housing stability?

PubMed

Keane, Carol A; Magee, Christopher A; Kelly, Peter J

2016-11-01

Traumatic childhood experiences predict many adverse outcomes in adulthood including Complex-PTSD. Understanding complex trauma within socially disadvantaged populations has important implications for policy development and intervention implementation. This paper examined the nature of complex trauma experienced by disadvantaged individuals using a latent class analysis (LCA) approach. Data were collected through the large-scale Journeys Home Study (N=1682), utilising a representative sample of individuals experiencing low housing stability. Data on adverse childhood experiences, adulthood interpersonal trauma and relevant covariates were collected through interviews at baseline (Wave 1). Latent class analysis (LCA) was conducted to identify distinct classes of childhood trauma history, which included physical assault, neglect, and sexual abuse. Multinomial logistic regression investigated childhood relevant factors associated with class membership such as biological relationship of primary carer at age 14 years and number of times in foster care. Of the total sample (N=1682), 99% reported traumatic adverse childhood experiences. The most common included witnessing of violence, threat/experience of physical abuse, and sexual assault. LCA identified six distinct childhood trauma history classes including high violence and multiple traumas. Significant covariate differences between classes included: gender, biological relationship of primary carer at age 14 years, and time in foster care. Identification of six distinct childhood trauma history profiles suggests there might be unique treatment implications for individuals living in extreme social disadvantage. Further research is required to examine the relationship between these classes of experience, consequent impact on adulthood engagement, and future transitions though homelessness. Copyright © 2016 Elsevier Ltd. All rights reserved.

Identification by random forest method of HLA class I amino acid substitutions associated with lower survival at day 100 in unrelated donor hematopoietic cell transplantation.

PubMed

Marino, S R; Lin, S; Maiers, M; Haagenson, M; Spellman, S; Klein, J P; Binkowski, T A; Lee, S J; van Besien, K

2012-02-01

The identification of important amino acid substitutions associated with low survival in hematopoietic cell transplantation (HCT) is hampered by the large number of observed substitutions compared with the small number of patients available for analysis. Random forest analysis is designed to address these limitations. We studied 2107 HCT recipients with good or intermediate risk hematological malignancies to identify HLA class I amino acid substitutions associated with reduced survival at day 100 post transplant. Random forest analysis and traditional univariate and multivariate analyses were used. Random forest analysis identified amino acid substitutions in 33 positions that were associated with reduced 100 day survival, including HLA-A 9, 43, 62, 63, 76, 77, 95, 97, 114, 116, 152, 156, 166 and 167; HLA-B 97, 109, 116 and 156; and HLA-C 6, 9, 11, 14, 21, 66, 77, 80, 95, 97, 99, 116, 156, 163 and 173. In all 13 had been previously reported by other investigators using classical biostatistical approaches. Using the same data set, traditional multivariate logistic regression identified only five amino acid substitutions associated with lower day 100 survival. Random forest analysis is a novel statistical methodology for analysis of HLA mismatching and outcome studies, capable of identifying important amino acid substitutions missed by other methods.

Latent Class Symptom Profiles of Selective Mutism: Identification and Linkage to Temperamental and Social Constructs.

PubMed

Diliberto, Rachele; Kearney, Christopher A

2017-11-21

Selective mutism (SM) is a stable, debilitating psychiatric disorder in which a child fails to speak in most public situations. Considerable debate exists as to the typology of this population, with empirically-based studies pointing to possible dimensions of anxiety, oppositionality, and communication problems, among other aspects. Little work has juxtaposed identified symptom profiles with key temperamental and social constructs often implicated in SM. The present study examined a large, diverse, non-clinical, international sample of children aged 6-10 years with SM to empirically identify symptom profiles and to link these profiles to key aspects of temperament (i.e., emotionality, shyness, sociability, activity) and social functioning (i.e., social problems, social competence). Exploratory and confirmatory factor analysis revealed anxiety/distress, oppositionality, and inattention domains. In addition, latent class analysis revealed nuanced profiles labeled as (1) moderately anxious, oppositional, and inattentive, (2) highly anxious, and moderately oppositional and inattentive, and (3) mildly to moderately anxious, and mildly oppositional and inattentive. Class 2 was the most impaired group and was associated with greater emotionality, shyness, and social problems. Class 3 was the least impaired group and was associated with better sociability and social competence and activity. Class 1 was largely between the other classes, demonstrating less shyness and social problems than Class 2. The results help confirm previous findings of anxiety and oppositional profiles among children with SM but that nuanced classes may indicate subtle variations in impairment. The results have implications not only for subtyping this population but also for refining assessment and case conceptualization strategies and pursuing personalized and perhaps less lengthy treatment.

Taxonomy of Caribbean Tourism Alcohol Venues: Implications for HIV Transmission*

PubMed Central

GUILAMO-RAMOS, Vincent; JACCARD, James; MCCARTHY, Katharine; QUIÑONES, Zahira; LUSHIN, Viktor; SKINNER-DAY, Molly; PADILLA, Mark; MEISTERLIN, Leah

2013-01-01

Background Tourism areas represent ecologies of heightened HIV vulnerability characterized by a disproportionate concentration of alcohol venues. Limited research has explored how alcohol venues facilitate HIV transmission. Methods We spatially mapped locations of alcohol venues in a Dominican tourism town and conducted a venue-based survey of key informants (n=135) focused on three facets of alcohol venues: structural features, type of patrons, and HIV risk behaviors. Using latent class analysis, we identified evidence-based typologies of alcohol venues for each of the three facets. Focused contrasts identified the co-occurrence of classes of structural features, classes of types of patrons, and classes of HIV risk behavior, thus elaborating the nature of high risk venues. Results We identified three categories of venue structural features, three for venue patrons, and five for HIV risk behaviors. Analysis revealed that alcohol venues with the greatest structural risks (e.g., sex work on site with lack of HIV prevention services) were most likely frequented by the venue patron category characterized by high population-mixing between locals and foreign tourists, who were in turn most likely to engage in the riskiest behaviors. Conclusion Our results highlight the stratification of venue patrons into groups who engage in behaviors of varying risk in structural settings that vary in risk. The convergence of high-risk patron groups in alcohol venues with the greatest structural risk suggests these locations have potential for HIV transmission. Policymakers and prevention scientists can use these methods and data to target HIV prevention resources to identified priority areas. PMID:23478154

Taxonomy of Caribbean tourism alcohol venues: implications for HIV transmission.

PubMed

Guilamo-Ramos, Vincent; Jaccard, James; McCarthy, Katharine; Quiñones, Zahira; Lushin, Viktor; Skinner-Day, Molly; Padilla, Mark; Meisterlin, Leah

2013-09-01

Tourism areas represent ecologies of heightened HIV vulnerability characterized by a disproportionate concentration of alcohol venues. Limited research has explored how alcohol venues facilitate HIV transmission. We spatially mapped locations of alcohol venues in a Dominican tourism town and conducted a venue-based survey of key informants (n=135) focused on three facets of alcohol venues: structural features, type of patrons, and HIV risk behaviors. Using latent class analysis, we identified evidence-based typologies of alcohol venues for each of the three facets. Focused contrasts identified the co-occurrence of classes of structural features, classes of types of patrons, and classes of HIV risk behavior, thus elaborating the nature of high risk venues. We identified three categories of venue structural features, three for venue patrons, and five for HIV risk behaviors. Analysis revealed that alcohol venues with the greatest structural risks (e.g. sex work on-site with lack of HIV prevention services) were most likely frequented by the venue patron category characterized by high population-mixing between locals and foreign tourists, who were in turn most likely to engage in the riskiest behaviors. Our results highlight the stratification of venue patrons into groups who engage in behaviors of varying risk in structural settings that vary in risk. The convergence of high-risk patron groups in alcohol venues with the greatest structural risk suggests these locations have potential for HIV transmission. Policymakers and prevention scientists can use these methods and data to target HIV prevention resources to identified priority areas. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

Filtering Essays by Means of a Software Tool: Identifying Poor Essays

ERIC Educational Resources Information Center

Seifried, Eva; Lenhard, Wolfgang; Spinath, Birgit

2017-01-01

Writing essays and receiving feedback can be useful for fostering students' learning and motivation. When faced with large class sizes, it is desirable to identify students who might particularly benefit from feedback. In this article, we tested the potential of Latent Semantic Analysis (LSA) for identifying poor essays. A total of 14 teaching…

Genome-wide identification and expression analysis of the ClTCP transcription factors in Citrullus lanatus.

PubMed

Shi, Pibiao; Guy, Kateta Malangisha; Wu, Weifang; Fang, Bingsheng; Yang, Jinghua; Zhang, Mingfang; Hu, Zhongyuan

2016-04-12

The plant-specific TCP transcription factor family, which is involved in the regulation of cell growth and proliferation, performs diverse functions in multiple aspects of plant growth and development. However, no comprehensive analysis of the TCP family in watermelon (Citrullus lanatus) has been undertaken previously. A total of 27 watermelon TCP encoding genes distributed on nine chromosomes were identified. Phylogenetic analysis clustered the genes into 11 distinct subgroups. Furthermore, phylogenetic and structural analyses distinguished two homology classes within the ClTCP family, designated Class I and Class II. The Class II genes were differentiated into two subclasses, the CIN subclass and the CYC/TB1 subclass. The expression patterns of all members were determined by semi-quantitative PCR. The functions of two ClTCP genes, ClTCP14a and ClTCP15, in regulating plant height were confirmed by ectopic expression in Arabidopsis wild-type and ortholog mutants. This study represents the first genome-wide analysis of the watermelon TCP gene family, which provides valuable information for understanding the classification and functions of the TCP genes in watermelon.

Prevention of school bullying: the important role of autonomy-supportive teaching and internalization of pro-social values.

PubMed

Roth, Guy; Kanat-Maymon, Yaniv; Bibi, Uri

2011-12-01

This study examined students' perceptions of autonomy-supportive teaching (AST) and its relations to internalization of pro-social values and bullying in class. We hypothesized that: (1) teachers' AST, which involves provision of rationale and taking the student's perspective, would relate positively to students' identified internalization of considerateness towards classmates, and would relate negatively to external regulation (considerateness to obtain rewards or avoid punishments); (2) students' identified regulation would relate negatively to self-reported bullying in class, whereas external regulation would relate positively to bullying; and (3) the relation between teachers' AST and student bullying would be mediated by students' identification with the value of considerateness towards others. The sample consisted of 725 junior high school students (50% females) in Grades 7 and 8 from 27 classes in four schools serving students from lower-middle to middle-class socioeconomic backgrounds.   The participants completed questionnaires assessing the variables of interest. Correlational analysis supported the hypotheses. Moreover, mediational analyses using hierarchical linear modelling (HLM) demonstrated that identified regulation mediates the negative relation between AST and self-reported bullying in class. The mediational hypothesis was supported at the between-class level and at the within-class level.   The findings suggest that school policy aimed at bullying reduction should go beyond external control that involves external rewards and sanctions and should help teachers acquire autonomy-supportive practices focusing on students' meaningful internalization. ©2010 The British Psychological Society.

Time-Series Analysis: Assessing the Effects of Multiple Educational Interventions in a Small-Enrollment Course

NASA Astrophysics Data System (ADS)

Warren, Aaron R.

2009-11-01

Time-series designs are an alternative to pretest-posttest methods that are able to identify and measure the impacts of multiple educational interventions, even for small student populations. Here, we use an instrument employing standard multiple-choice conceptual questions to collect data from students at regular intervals. The questions are modified by asking students to distribute 100 Confidence Points among the options in order to indicate the perceived likelihood of each answer option being the correct one. Tracking the class-averaged ratings for each option produces a set of time-series. ARIMA (autoregressive integrated moving average) analysis is then used to test for, and measure, changes in each series. In particular, it is possible to discern which educational interventions produce significant changes in class performance. Cluster analysis can also identify groups of students whose ratings evolve in similar ways. A brief overview of our methods and an example are presented.

Outcomes Associated with Adolescent Marijuana and Alcohol Use Among Urban Young Adults: A Prospective Study

PubMed Central

Green, Kerry M.; Musci, Rashelle J.; Johnson, Renee M.; Matson, Pamela A.; Reboussin, Beth A.; Ialongo, Nicholas S.

2015-01-01

Objective This study identifies and compares outcomes in young adulthood associated with longitudinal patterns of alcohol and marijuana use during adolescence among urban youth. Method Data come from a cohort of 678 urban, predominantly Black children followed from ages 6–25 (1993–2012). Analyses are based on the 608 children who participated over time (53.6% male). Longitudinal patterning of alcohol and marijuana use were based on annual frequency reports from grades 8–12 and estimated through latent profile analysis. Results We identified four classes of alcohol and marijuana use including Non-Use (47%), Moderate Alcohol Use (28%), Moderate Alcohol/Increasing Marijuana Use (12%) and High Dual Use (13%). A marijuana only class was not identified. Analyses show negative outcomes in adulthood associated with all three adolescent substance use classes. Compared to the non-use class, all use classes had statistically significantly higher rates of substance dependence. Those in the ‘High Dual Use’ class had the lowest rate of high school graduation. Comparing classes with similar alcohol but different marijuana patterns, the ‘Moderate Alcohol/Increasing Marijuana Use’ class had a statistically significant increased risk of having a criminal justice record and developing substance use dependence in adulthood. Conclusion Among urban youth, heterogeneous patterns of alcohol and marijuana use across adolescence are evident, and these patterns are associated with distinct outcomes in adulthood. These findings suggest a need for targeted education and intervention efforts to address the needs of youth using both marijuana and alcohol, as well as the importance of universal early preventive intervention efforts. PMID:26517712

Maternal eating disorder and infant diet. A latent class analysis based on the Norwegian Mother and Child Cohort Study (MoBa).

PubMed

Torgersen, Leila; Ystrom, Eivind; Siega-Riz, Anna Maria; Berg, Cecilie Knoph; Zerwas, Stephanie C; Reichborn-Kjennerud, Ted; Bulik, Cynthia M

2015-01-01

Knowledge of infant diet and feeding practices among children of mothers with eating disorders is essential to promote healthy eating in these children. This study compared the dietary patterns of 6-month-old children of mothers with anorexia nervosa, bulimia nervosa, binge eating disorder, and eating disorder not otherwise specified-purging subtype, to the diet of children of mothers with no eating disorders (reference group). The study was based on 53,879 mothers in the Norwegian Mother and Child Cohort Study (MoBa). Latent class analysis (LCA) was used to identify discrete latent classes of infant diet based on the mothers' responses to questions about 16 food items. LCA identified five classes, characterized by primarily homemade vegetarian food (4% of infants), homemade traditional food (8%), commercial cereals (35%), commercial jarred baby food (39%), and a mix of all food groups (11%). The association between latent dietary classes and maternal eating disorders were estimated by multinomial logistic regression. Infants of mothers with bulimia nervosa had a lower probability of being in the homemade traditional food class compared to the commercial jarred baby food class, than the referent (O.R. 0.59; 95% CI 0.36-0.99). Infants of mothers with binge eating disorder had a lower probability of being in the homemade vegetarian class compared to the commercial jarred baby food class (O.R. 0.77; 95% CI 0.60-0.99), but only before adjusting for relevant confounders. Anorexia nervosa and eating disorder not otherwise specified-purging subtype were not statistically significantly associated with any of the dietary classes. These results suggest that maternal eating disorders may to some extent influence the child's diet at 6 months; however, the extent to which these differences influence child health and development remains an area for further inquiry. Copyright © 2014 Elsevier Ltd. All rights reserved.

Community analysis of pigment patterns from 37 microalgae strains reveals new carotenoids and porphyrins characteristic of distinct strains and taxonomic groups

PubMed Central

Bérard, Jean-Baptiste; Kaas, Raymond; Pasquet, Virginie; Picot, Laurent; Cadoret, Jean-Paul

2017-01-01

Phytoplankton, with an estimated 30 000 to 1 000 000 species clustered in 12 phyla, presents a high taxonomic and ecophysiological diversity, reflected by the complex distribution of pigments among the different algal classes. High performance liquid chromatography is the gold standard method for qualitative and quantitative analysis of phytoplankton pigments in seawater and culture samples, but only a few pigments can be used as robust chemotaxonomic markers. A major challenge is thus to identify new ones, characteristic of a strain, species, class or taxon that cannot be currently identified on the basis of its pigment signature. Using an optimized extraction process coupled to a HPLC de-replication strategy, we examined the pigment composition of 37 microalgae strains, representative of the broad taxonomic diversity of marine and freshwater species (excluding cyanobacteria). For each species, the major pigments already described were unambiguously identified. We also observed the presence of several minor unidentified pigments in each chromatogram. The global analysis of pigment compositions revealed a total of 124 pigments, including 98 pigments or derivatives unidentified using the standards. Absorption spectra indicated that 35 corresponded to chlorophyll/porphyrin derivatives, 57 to carotenoids and six to derivatives having both spectral signatures. Sixty-one of these unidentified or new carotenoids and porphyrin derivatives were characteristic of particular strains or species, indicating their possible use as highly specific chemotaxonomic markers capable of identifying one strain out of the 37 selected. We developed a graphical analysis using Gephi software to give a clear representation of pigment communities among the various phytoplankton strains, and to reveal strain-characteristic and shared pigments. This made it possible to reconstruct the taxonomic evolution of microalgae classes, on the basis of the conservation, loss, and/or appearance of pigments. PMID:28231253

Localisation of deformations of the midfacial complex in subjects with class III malocclusions employing thin-plate spline analysis

PubMed Central

SINGH, G. D.; McNAMARA JR, J. A.; LOZANOFF, S.

1997-01-01

This study determines deformations of the midface that contribute to a class III appearance, employing thin-plate spline analysis. A total of 135 lateral cephalographs of prepubertal children of European-American descent with either class III malocclusions or a class I molar occlusion were compared. The cephalographs were traced and checked, and 7 homologous landmarks of the midface were identified and digitised. The data sets were scaled to an equivalent size and subjected to Procrustes analysis. These statistical tests indicated significant differences (P<0.05) between the averaged class I and class III morphologies. Thin-plate spline analysis indicated that both affine and nonaffine transformations contribute towards the total spline for the averaged midfacial configuration. For nonaffine transformations, partial warp 3 had the highest magnitude, indicating the large scale deformations of the midfacial configuration. These deformations affected the palatal landmarks, and were associated with compression of the midfacial complex in the anteroposterior plane predominantly. Partial warp 4 produced some vertical compression of the posterior aspect of the midfacial complex whereas partial warps 1 and 2 indicated localised shape changes of the maxillary alveolus region. Large spatial-scale deformations therefore affect the midfacial complex in an anteroposterior axis, in combination with vertical compression and localised distortions. These deformations may represent a developmental diminution of the palatal complex anteroposteriorly that, allied with vertical shortening of midfacial height posteriorly, results in class III malocclusions with a retrusive midfacial profile. PMID:9449078

Localisation of deformations of the midfacial complex in subjects with class III malocclusions employing thin-plate spline analysis.

PubMed

Singh, G D; McNamara, J A; Lozanoff, S

1997-11-01

This study determines deformations of the midface that contribute to a class III appearance, employing thinplate spline analysis. A total of 135 lateral cephalographs of prepubertal children of European-American descent with either class III malocclusions or a class I molar occlusion were compared. The cephalographs were traced and checked, and 7 homologous landmarks of the midface were identified and digitised. The data sets were scaled to an equivalent size and subjected to Procrustes analysis. These statistical tests indicated significant differences (P < 0.05) between the averaged class I and class III morphologies. Thinplate spline analysis indicated that both affine and nonaffine transformations contribute towards the total spline for the averaged midfacial configuration. For nonaffine transformations, partial warp 3 had the highest magnitude, indicating the large scale deformations of the midfacial configuration. These deformations affected the palatal landmarks, and were associated with compression of the midfacial complex in the anteroposterior plane predominantly. Partial warp 4 produced some vertical compression of the posterior aspect of the midfacial complex whereas partial warps 1 and 2 indicated localised shape changes of the maxillary alveolus region. large spatial-scale deformations therefore affect the midfacial complex in an anteroposterior axis, in combination with vertical compression and localised distortions. These deformations may represent a developmental diminution of the palatal complex anteroposteriorly that, allied with vertical shortening of midfacial height posteriorly, results in class III malocclusions with a retrusive midfacial profile.

Symptom Trajectories in Children Receiving Treatment for Leukemia: A Latent Class Growth Analysis With Multitrajectory Modeling.

PubMed

Hockenberry, Marilyn J; Hooke, Mary C; Rodgers, Cheryl; Taylor, Olga; Koerner, Kari M; Mitby, Pauline; Moore, Ida; Scheurer, Michael E; Pan, Wei

2017-07-01

Cancer treatment symptoms play a major role in determining the health of children with cancer. Symptom toxicity often results in complications, treatment delays, and therapy dose reductions that can compromise leukemia therapy and jeopardize chances for long-term survival. Critical to understanding symptom experiences during treatment is the need for exploration of "why" inter-individual symptom differences occur; this will determine who may be most susceptible to treatment toxicities. This study examined specific symptom trajectories during the first 18 months of childhood leukemia treatment. Symptom measures included fatigue, sleep disturbances, pain, nausea, and depression. Symptom trajectories of 236 children with leukemia three to 18 years old were explored prospectively over four periods: initiation of post-induction therapy, four and eight post-induction therapy, and the last time point was at the beginning of maintenance/continuation therapy. Latent class growth analysis was used to classify patients into distinctive groups with similar symptom trajectories based on patients' response patterns on the symptom measures over time. Three latent classes of symptom trajectories were identified and classified into mild, moderate, and severe symptom trajectories. The only demographic characteristic with a significant relationship to membership in the latent class symptom trajectories was race/ethnicity. All other demographic characteristics including leukemia risk levels showed no significant relationships. This study is unique in that groups of patients with similar symptoms were identified rather than groups of symptoms. Further research using latent class growth analysis is needed. Copyright © 2017 American Academy of Hospice and Palliative Medicine. Published by Elsevier Inc. All rights reserved.

COVD-QOL questionnaire: An adaptation for school vision screening using Rasch analysis

PubMed Central

Abu Bakar, Nurul Farhana; Ai Hong, Chen; Pik Pin, Goh

2012-01-01

Purpose To adapt the College of Optometrist in Vision Development (COVD-QOL) questionnaire as a vision screening tool for primary school children. Methods An interview session was conducted with children, teachers or guardians regarding visual symptoms of 88 children (45 from special education classes and 43 from mainstream classes) in government primary schools. Data was assessed for response categories, fit items (infit/outfit: 0.6–1.4) and separation reliability (item/person: 0.80). The COVD-QOL questionnaire results were compared with vision assessment in identifying three categories of vision disorders: reduce visual acuity, accommodative response anomaly and convergence insufficiency. Analysis on the screening performance using the simplified version of the questionnaire was evaluated based on receiver-operating characteristic analysis for detection of any type of target conditions for both types of classes. Predictive validity analysis was used a Spearman rank correlation (>0.3). Results Two of the response categories were underutilized and therefore collapsed to the adjacent category and items were reduced to 14. Item separation reliability for the simplified version of the questionnaire was acceptable (0.86) but the person separation reliability was inadequate for special education classes (0.79) similar to mainstream classes (0.78). The discriminant cut-off score of 9 (mainstream classes) and 3 (special education classes) from the 14 items provided sensitivity and specificity of (65% and 54%) and (78% and 80%) with Spearman rank correlation of 0.16 and 0.40 respectively. Conclusion The simplified version of COVD-QOL questionnaire (14-items) performs adequately among children in special education classes suggesting its suitability as a vision screening tool.

Thin-plate spline analysis of the cranial base in subjects with Class III malocclusion.

PubMed

Singh, G D; McNamara, J A; Lozanoff, S

1997-08-01

The role of the cranial base in the emergence of Class III malocclusion is not fully understood. This study determines deformations that contribute to a Class III cranial base morphology, employing thin-plate spline analysis on lateral cephalographs. A total of 73 children of European-American descent aged between 5 and 11 years of age with Class III malocclusion were compared with an equivalent group of subjects with a normal, untreated, Class I molar occlusion. The cephalographs were traced, checked and subdivided into seven age- and sex-matched groups. Thirteen points on the cranial base were identified and digitized. The datasets were scaled to an equivalent size, and statistical analysis indicated significant differences between average Class I and Class III cranial base morphologies for each group. Thin-plate spline analysis indicated that both affine (uniform) and non-affine transformations contribute toward the total spline for each average cranial base morphology at each age group analysed. For non-affine transformations, Partial warps 10, 8 and 7 had high magnitudes, indicating large-scale deformations affecting Bolton point, basion, pterygo-maxillare, Ricketts' point and articulare. In contrast, high eigenvalues associated with Partial warps 1-3, indicating localized shape changes, were found at tuberculum sellae, sella, and the frontonasomaxillary suture. It is concluded that large spatial-scale deformations affect the occipital complex of the cranial base and sphenoidal region, in combination with localized distortions at the frontonasal suture. These deformations may contribute to reduced orthocephalization or deficient flattening of the cranial base antero-posteriorly that, in turn, leads to the formation of a Class III malocclusion.

Acculturative heterogeneity among Asian/Pacific Islanders in the United States: Associations with DSM mental and substance use disorders.

PubMed

Salas-Wright, Christopher P; Lee, Sharon; Vaughn, Michael G; Jang, Yuri; Sanglang, Cindy C

2015-07-01

Extant studies on the links between acculturation and mental and substance use disorders among Asian/Pacific Islanders have been based on the assumption that acculturation is a homogeneous construct. However, emerging evidence suggests that the various components of acculturation do not manifest independently, but rather cluster in ways that reflect distinct profiles. We employ data on Asian/Pacific Islanders from the National Epidemiologic Survey on Alcohol and Related Conditions (n = 968). Latent profile analysis is used to identify acculturation subgroups on the basis of indicator variables related to cultural identification, language ability and preference, and social engagement. Subsequently, the distribution of outcome variables in the domains of DSM disorders (lifetime history of clinical, personality, and substance use disorders) is examined across latent subgroups. We identified a 5-class solution: Class 1: Separated (12.91%), Class 2: Partial Bilingual/Bicultural (30.06%), Class 3: English Dominant/Asian Oriented (12.29%), Class 4: Full Bilingual/Bicultural (19.42%) and Class 5: Assimilated (25.31%). The highest rates of clinical disorders were observed among members of the 2 classes characterized by a strong preference for the use of the English language (Classes 3 and 5). The highest prevalence of nicotine (12%) and illicit drug use (15%) disorders was observed among members of the Assimilated class. Consistent with prior research, findings suggest that risk of morbidity is greater among more acculturated individuals; however, findings also suggest that an important level of nuance can be observed with respect to acculturative subtypes identified on the basis of cultural identification, language ability and preference, and social engagement. (c) 2015 APA, all rights reserved).

Acculturative Heterogeneity among Asian/Pacific Islanders in the United States: Associations with DSM Mental and Substance Use Disorders

PubMed Central

Salas-Wright, Christopher P.; Lee, Sharon; Vaughn, Michael G.; Jang, Yuri; Sanglang, Cindy C.

2014-01-01

Extant studies on the links between acculturation and mental and substance use disorders among Asian/Pacific Islanders have been based on the assumption that acculturation is a homogeneous construct. However, emerging evidence suggests that the various components of acculturation do not manifest independently, but rather cluster in ways that reflect distinct profiles. We employ data on Asian/Pacific Islanders from the National Epidemiologic Survey on Alcohol and Related Conditions (n = 968). Latent profile analysis is used to identify acculturation subgroups on the basis of indicator variables related to cultural identification, language ability and preference, and social engagement. Subsequently, the distribution of outcome variables in the domains of DSM disorders (lifetime history of clinical, personality, and substance use disorders) is examined across latent subgroups. We identified a five class solution: Class 1: “Separated” (12.91%), Class 2: “Partial Bilingual/Bicultural” (30.06%), Class 3: “English Dominant/Asian Oriented” (12.29%), Class 4:”Full Bilingual/Bicultural” (19.42%) and Class 5: “Assimilated” (25.31%). The highest rates of clinical disorders were observed among members of the two classes characterized by a strong preference for the use of the English language (Classes 3 and 5). The highest prevalence of nicotine (12%) and illicit drug use (15%) disorders was observed among members of the “Assimilated” class. Consistent with prior research, findings suggest that risk of morbidity is greater among more acculturated individuals; however, findings also suggest that an important level of nuance can be observed with respect to acculturative subtypes identified on the basis of cultural identification, language ability and preference, and social engagement. PMID:26167805

Higher derivative field theories: degeneracy conditions and classes

NASA Astrophysics Data System (ADS)

Crisostomi, Marco; Klein, Remko; Roest, Diederik

2017-06-01

We provide a full analysis of ghost free higher derivative field theories with coupled degrees of freedom. Assuming the absence of gauge symmetries, we derive the degeneracy conditions in order to evade the Ostrogradsky ghosts, and analyze which (non)trivial classes of solutions this allows for. It is shown explicitly how Lorentz invariance avoids the propagation of "half" degrees of freedom. Moreover, for a large class of theories, we construct the field redefinitions and/or (extended) contact transformations that put the theory in a manifestly first order form. Finally, we identify which class of theories cannot be brought to first order form by such transformations.

Parental attitudes towards measles vaccination in the canton of Aargau, Switzerland: a latent class analysis.

PubMed

Weiss, Carine; Schröpfer, Daniel; Merten, Sonja

2016-08-11

Despite the successes of routine national childhood vaccination programmes, measles remains a public health concern. The purpose of this paper is to investigate how patterns of parental attitudes are linked to the decision-making process for or against MMR vaccination. This exploratory study was designed to identify distinct patterns of attitudes towards or against measles vaccination through Latent Class Analysis (LCA) in a sub-sample of mothers living in the canton of Aargau in Switzerland. Parents of young children below 36 months of age were randomly selected through parents' counsellors' registries. Among other questions, respondents were asked to state their agreement in response to 14 belief statements regarding measles vaccination on a 5-point Likert scale. To identify groups of parents showing distinct patterns of attitudes and beliefs regarding measles vaccination, we used Latent Class Analysis (LCA). The LCA showed three classes of parents with different attitudes and believes towards measles vaccination: The biggest group (class 1) are those having positive attitudes towards immunisation, followed by the second biggest group (class 2) which is characterised by having fearful attitudes and by showing uncertainty about immunisation. The third group (class 3) shows distinct patterns of critical attitudes against immunisation. Within this group over 90 % agree or totally agree that immunisation is an artificial intrusion into the natural immune system and therefore want to vaccinate their children only if necessary. We find that parents in the Canton Aargau who hesitate to vaccinate their children against measles, mumps and rubella show distinct opinions and attitudes. Health professionals should be aware of these perceptions to tailor their messages accordingly and positively influence these parents to vaccinate their children. Special attention needs to be given to those parents who are planning to vaccinate their children but are not following the national guidelines.

Duration of the peak of adolescent growth spurt in class i and ii malocclusion subjects using a cervical vertebrae maturation analysis.

PubMed

Salazar-Lazo, Rodrigo; Arriola-Guillén, Luis E; Flores-Mir, Carlos

2014-01-01

The aim of the present work was to determine the duration of the adolescent peak growth spurt using cervical vertebral maturation analysis in class I and II malocclusion subjects. The study was conducted on a sample which consisted of 154 lateral cephalograms of children and adolescents aged 9-15 years (84 females and 70 males). The evaluation of skeletal maturation stage was performed using a visual morphological analysis of CS3 and CS4 cervical vertebrae. The sagittal skeletal relation was evaluated according to Steiner analysis. Descriptive statistics were used to summarize chronological age in each malocclusion group and for each CS3 and CS4 skeletal maturation stage. Due to a lack of normal distribution, comparisons of CS3 and CS4 age intervals on class I and II subjects were compared using the Mann-Whitney U test for independent samples. The results show that the mean duration of the adolescent peak growth spurt was 10 months between CS3 and CS4 stages in class I malocclusion subjects, whereas in class II malocclusion patients the duration was 6 months. This difference of 4 months was statistically significant (p<0.001). Finally, a clinically significant difference of 4 months in the duration of the adolescent peak growth spurt for class I and II malocclusion subjects was identified.

Skeletal effects in Angle Class II/1 patients treated with the functional regulator type II : Cephalometric and tensor analysis.

PubMed

Schulz, Simone; Koos, Bernd; Duske, Kathrin; Stahl, Franka

2016-11-01

The purpose of this work was to employ both cephalometric and tensor analysis in characterizing the skeletal changes experienced by patients with Angle Class II/1 malocclusion during functional orthodontic treatment with the functional regulator type II. A total of 23 patients with Class II/1 malocclusion based on lateral cephalograms obtained before and after treatment with the functional regulator type II were analyzed. Another 23 patients with Angle Class II/1 malocclusion who had not undergone treatment were included as controls. Our cephalometric data attest to significant therapeutic effects of the functional regulator type II on the skeletal mandibular system, including significant advancement of the mandible, increases in effective mandibular length with enhancement of the chin profile, and reduction of growth-related bite deepening. No treatment-related effects were observed at the cranial-base and midface levels. In addition, tensor analysis revealed significant stimulation of mandibular growth in sagittal directions, without indications of growth effects on the maxilla. Its growth-pattern findings differed from those of cephalometric analysis by indicating that the appliance did promote horizontal development, which supports the functional orthodontic treatment effect in Angle Class II/1 cases. Tensor analysis yielded additional insights into sagittal and vertical growth changes not identifiable by strictly cephalometric means. The functional regulator type II was an effective treatment modality for Angle Class II/1 malocclusion and influenced the skeletal development of these patients in favorable ways.

Microaggressions, Discrimination, and Phenotype among African Americans: A Latent Class Analysis of the Impact of Skin Tone and BMI.

PubMed

Keith, Verna M; Nguyen, Ann W; Taylor, Robert Joseph; Mouzon, Dawne M; Chatters, Linda M

2017-05-01

Data from the 2001-2003National Survey of American Life are used to investigate the effects of phenotype on everyday experiences with discrimination among African Americans (N=3343). Latent class analysis is used to identify four classes of discriminatory treatment: 1) low levels of discrimination, 2) disrespect and condescension, 3) character-based discrimination, and 4) high levels of discrimination. We then employ latent class multinomial logistic regression to evaluate the association between skin tone and body weight and these four classes of discrimination. Designating the low level discrimination class as the reference group, findings revealed that respondents with darker skin were more likely to be classified into the disrespect/condescension and the high level microaggression types. BMI was unrelated to the discrimination type, although there was a significant interaction effect between gender and BMI. BMI was strongly and positively associated with membership in the disrespect and condescension type among men but not among women. These findings indicate that skin tone and body weight are two phenotypic characteristics that influence the type and frequency of discrimination experienced by African Americans.

Probing photoelectron multiple interferences via Fourier spectroscopy in energetic photoionization of Xe@C60

NASA Astrophysics Data System (ADS)

Potter, Andrea; McCune, Matthew A.; de, Ruma; Madjet, Mohamed E.; Chakraborty, Himadri S.

2010-09-01

Considering the photoionization of the Xe@C60 endohedral compound, we study in detail the ionization cross sections of various levels of the system at energies higher than the plasmon resonance region. Five classes of single-electron levels are identified depending on their spectral character. Each class engenders distinct oscillations in the cross section, emerging from the interference between active ionization modes specific to that class. Analysis of the cross sections based on their Fourier transforms unravels oscillation frequencies that carry unique fingerprints of the emitting level.

Lipidomic analysis of biological samples: Comparison of liquid chromatography, supercritical fluid chromatography and direct infusion mass spectrometry methods.

PubMed

Lísa, Miroslav; Cífková, Eva; Khalikova, Maria; Ovčačíková, Magdaléna; Holčapek, Michal

2017-11-24

Lipidomic analysis of biological samples in a clinical research represents challenging task for analytical methods given by the large number of samples and their extreme complexity. In this work, we compare direct infusion (DI) and chromatography - mass spectrometry (MS) lipidomic approaches represented by three analytical methods in terms of comprehensiveness, sample throughput, and validation results for the lipidomic analysis of biological samples represented by tumor tissue, surrounding normal tissue, plasma, and erythrocytes of kidney cancer patients. Methods are compared in one laboratory using the identical analytical protocol to ensure comparable conditions. Ultrahigh-performance liquid chromatography/MS (UHPLC/MS) method in hydrophilic interaction liquid chromatography mode and DI-MS method are used for this comparison as the most widely used methods for the lipidomic analysis together with ultrahigh-performance supercritical fluid chromatography/MS (UHPSFC/MS) method showing promising results in metabolomics analyses. The nontargeted analysis of pooled samples is performed using all tested methods and 610 lipid species within 23 lipid classes are identified. DI method provides the most comprehensive results due to identification of some polar lipid classes, which are not identified by UHPLC and UHPSFC methods. On the other hand, UHPSFC method provides an excellent sensitivity for less polar lipid classes and the highest sample throughput within 10min method time. The sample consumption of DI method is 125 times higher than for other methods, while only 40μL of organic solvent is used for one sample analysis compared to 3.5mL and 4.9mL in case of UHPLC and UHPSFC methods, respectively. Methods are validated for the quantitative lipidomic analysis of plasma samples with one internal standard for each lipid class. Results show applicability of all tested methods for the lipidomic analysis of biological samples depending on the analysis requirements. Copyright © 2017 Elsevier B.V. All rights reserved.

Using Latent Class Analysis to Model Temperament Types.

PubMed

Loken, Eric

2004-10-01

Mixture models are appropriate for data that arise from a set of qualitatively different subpopulations. In this study, latent class analysis was applied to observational data from a laboratory assessment of infant temperament at four months of age. The EM algorithm was used to fit the models, and the Bayesian method of posterior predictive checks was used for model selection. Results show at least three types of infant temperament, with patterns consistent with those identified by previous researchers who classified the infants using a theoretically based system. Multiple imputation of group memberships is proposed as an alternative to assigning subjects to the latent class with maximum posterior probability in order to reflect variance due to uncertainty in the parameter estimation. Latent class membership at four months of age predicted longitudinal outcomes at four years of age. The example illustrates issues relevant to all mixture models, including estimation, multi-modality, model selection, and comparisons based on the latent group indicators.

[Poverty profile regarding households participating in a food assistance program].

PubMed

Álvarez-Uribe, Martha C; Aguirre-Acevedo, Daniel C

2012-06-01

This study was aimed at establishing subgroups having specific socioeconomic characteristics by using latent class analysis as a method for segmenting target population members of the MANA-ICBF supplementary food program in the Antioquia department of Colombia and determine their differences regarding poverty and health conditions in efficiently addressing pertinent resources, programs and policies. The target population consisted of 200,000 children and their households involved in the MANA food assistance program; a representative sample by region was used. Latent class analysis was used, as were the expectation-maximization and Newton Raphson algorithms for identifying the appropriate number of classes. The final model classified the households into four clusters or classes, differing according to well-defined socio-demographic conditions affecting children's health. Some homes had a greater depth of poverty, therefore lowering the families' quality of life and affecting the health of the children in this age group.

Three subgroups of pain profiles identified in 227 women with arthritis: a latent class analysis.

PubMed

de Luca, Katie; Parkinson, Lynne; Downie, Aron; Blyth, Fiona; Byles, Julie

2017-03-01

The objectives were to identify subgroups of women with arthritis based upon the multi-dimensional nature of their pain experience and to compare health and socio-demographic variables between subgroups. A latent class analysis of 227 women with self-reported arthritis was used to identify clusters of women based upon the sensory, affective, and cognitive dimensions of the pain experience. Multivariate multinomial logistic regression analysis was used to determine the relationship between cluster membership and health and sociodemographic characteristics. A three-class cluster model was most parsimonious. 39.5 % of women had a unidimensional pain profile; 38.6 % of women had moderate multidimensional pain profile that included additional pain symptomatology such as sensory qualities and pain catastrophizing; and 21.9 % of women had severe multidimensional pain profile that included prominent pain symptomatology such as sensory and affective qualities of pain, pain catastrophizing, and neuropathic pain. Women with severe multidimensional pain profile have a 30.5 % higher risk of poorer quality of life and a 7.3 % higher risk of suffering depression, and women with moderate multidimensional pain profile have a 6.4 % higher risk of poorer quality of life when compared to women with unidimensional pain. This study identified three distinct subgroups of pain profiles in older women with arthritis. Women had very different experiences of pain, and cluster membership impacted significantly on health-related quality of life. These preliminary findings provide a stronger understanding of profiles of pain and may contribute to the development of tailored treatment options in arthritis.

Spline analysis of the mandible in human subjects with class III malocclusion.

PubMed

Singh, G D; McNamara, J A; Lozanoff, S

1997-05-01

This study determines deformations that contribute to a Class III mandibular morphology, employing thin-plate spline (TPS) analysis. A total of 133 lateral cephalographs of prepubertal children of European-American descent with either a Class I molar occlusion or a Class III malocclusion were compared. The cephalographs were traced and checked, and eight homologous landmarks on the mandible were identified and digitized. The datasets were scaled to an equivalent size and subjected to statistical analyses. These tests indicated significant differences between average Class I and Class III mandibular morphologies. When the sample was subdivided into seven age and sex-matched groups statistical differences were maintained for each group. TPS analysis indicated that both affine (uniform) and non-affine transformations contribute towards the total spline, and towards the average mandibular morphology at each age group. For non-affine transformations, partial warp 5 had the highest magnitude, indicating large-scale deformations of the mandibular configuration between articulare and pogonion. In contrast, partial warp 1 indicated localized shape changes in the mandibular symphyseal region. It is concluded that large spatial-scale deformations affect the body of the mandible, in combination with localized distortions further anteriorly. These deformations may represent a developmental elongation of the mandibular corpus antero-posteriorly that, allied with symphyseal changes, leads to the appearance of a Class III prognathic mandibular profile.

Common Mental Disorders among Occupational Groups: Contributions of the Latent Class Model

PubMed Central

Martins Carvalho, Fernando; de Araújo, Tânia Maria

2016-01-01

Background. The Self-Reporting Questionnaire (SRQ-20) is widely used for evaluating common mental disorders. However, few studies have evaluated the SRQ-20 measurements performance in occupational groups. This study aimed to describe manifestation patterns of common mental disorders symptoms among workers populations, by using latent class analysis. Methods. Data derived from 9,959 Brazilian workers, obtained from four cross-sectional studies that used similar methodology, among groups of informal workers, teachers, healthcare workers, and urban workers. Common mental disorders were measured by using SRQ-20. Latent class analysis was performed on each database separately. Results. Three classes of symptoms were confirmed in the occupational categories investigated. In all studies, class I met better criteria for suspicion of common mental disorders. Class II discriminated workers with intermediate probability of answers to the items belonging to anxiety, sadness, and energy decrease that configure common mental disorders. Class III was composed of subgroups of workers with low probability to respond positively to questions for screening common mental disorders. Conclusions. Three patterns of symptoms of common mental disorders were identified in the occupational groups investigated, ranging from distinctive features to low probabilities of occurrence. The SRQ-20 measurements showed stability in capturing nonpsychotic symptoms. PMID:27630999

Patterns of Gambling Activities and Gambling Problems Among Italian High School Students: Results from a Latent Class Analysis.

PubMed

De Luigi, Nicola; Gibertoni, Dino; Randon, Emanuela; Scorcu, Antonello E

2018-06-01

This study aims to provide an estimate of the prevalence of gambling among Italian adolescents and a description of their patterns of gambling activities (PGAs) using a latent class analysis on 13 different types of games. A nationwide sample of 10,959 Italian high school students was recruited in 2013. We assessed problem gambling using the South Oaks Gambling Screen: Revisited for Adolescent (SOGS-RA) scale. Approximately half (50.6%) of students reported gambling at least once in the previous year; 5.0% of them were problem gamblers and 9.1% were at-risk gamblers according to their SOGS-RA scores. Eight PGAs were identified, among which heavy players (1.7% of students) could be classified as problem gamblers and broad skill players (2.0%) and lotteries & sports players (2.4%) as "at-risk" players. These high-risk classes were consistently associated with risky behaviours in terms of substance use, school performance, money spent on gambling and family environment; the other five classes identified low-risk players associated with safe behaviours. To the best of our knowledge, this is the first study to identify PGAs among Italian adolescents. Problem gamblers are not a homogeneous group in terms of patterns of gambling activities and are associated with different risk factors, among which environmental factors, such as parents' gambling attitude and behaviour, deserve special attention. The acknowledgment of such patterns and risk factors could be useful in developing sensible public policies addressing prevention strategies and regulatory instruments.

Depression symptoms are persistent in Type 2 diabetes: risk factors and outcomes of 5-year depression trajectories using latent class growth analysis.

PubMed

Whitworth, S R; Bruce, D G; Starkstein, S E; Davis, W A; Davis, T M E; Skinner, T C; Bucks, R S

2017-08-01

To describe the long-term trajectories of depression symptom severity in people with Type 2 diabetes, and to identify predictors and associates of these trajectories. A community-dwelling cohort of 1201 individuals with Type 2 diabetes from the Fremantle Diabetes Study Phase II was followed for 5 years. The nine-item version of the Patient Health Questionnaire was administered annually to assess depression symptoms, and biomedical and psychosocial measures were assessed at baseline and biennially. Latent class growth analysis was used to identify classes of depression severity trajectories and associated outcomes, and logistic regression models were used to determine predictors of class membership. Three trajectories of depression symptoms were identified: continuously low depression symptoms (85.2%); gradually worsening symptoms that then began to improve (persistent depression - low-start; 7.3%); and gradually improving symptoms which later worsened (persistent depression - high-start; 7.5%). Younger age, being a woman, and a lifetime history of major depressive disorder, were associated with greater risk of persistent depression symptoms. Persistent depression was associated with consistently higher BMI over time, but not with changes in HbA 1c or self-monitoring of blood glucose. A subset of individuals with Type 2 diabetes is at risk of depression symptoms that remain elevated over time. Younger, overweight individuals with a history of depression may benefit from early and intensive depression management and ongoing follow-up as part of routine Type 2 diabetes care. © 2017 Diabetes UK.

The Variety of Ecstasy/MDMA Users: Results from the National Epidemiologic Survey on Alcohol and Related Conditions

PubMed Central

Wu, Li-Tzy; Parrott, Andy C.; Ringwalt, Christopher L.; Yang, Chongming; Blazer, Dan G.

2011-01-01

This study investigates the potential heterogeneity of ecstasy or MDMA (3,4-methylenedioxy-N-methylamphetamine) users. Data came from the 2001–2002 National Epidemiologic Survey on Alcohol and Related Conditions (NESARC). Latent class analysis (LCA) and multinomial logistic regression procedures were used to identify subtypes of ecstasy users. Approximately 1.6% (n=562) of adult participants (N=43,093) reported lifetime ecstasy use. LCA identified three subtypes of ecstasy users. Class 1 exhibited pervasive use of most drug classes (ecstasy–polydrug users, 37%). Class 2 reported a high rate of use of marijuana and cocaine and a moderate use of amphetamines (ecstasy–marijuana–stimulant users, 29%). Class 3 was characterized by a high rate of use of marijuana and a low use of primarily prescription-type drugs (ecstasy– marijuana users, 34%). Subtypes were distinguished by family income, history of substance abuse treatment, and familial substance abuse. Class 1 exhibited the highest prevalence of disorders related to the use of marijuana (77%), tobacco (66%), amphetamines (36%), opioids (35%), sedatives (31%), and tranquilizers (30%). The recent resurgence in ecstasy use among adults underscores the need to monitor trends in its use. PMID:19874166

Voluntary climate change mitigation actions of young adults: a classification of mitigators through latent class analysis.

PubMed

Korkala, Essi A E; Hugg, Timo T; Jaakkola, Jouni J K

2014-01-01

Encouraging individuals to take action is important for the overall success of climate change mitigation. Campaigns promoting climate change mitigation could address particular groups of the population on the basis of what kind of mitigation actions the group is already taking. To increase the knowledge of such groups performing similar mitigation actions we conducted a population-based cross-sectional study in Finland. The study population comprised 1623 young adults who returned a self-administered questionnaire (response rate 64%). Our aims were to identify groups of people engaged in similar climate change mitigation actions and to study the gender differences in the grouping. We also determined if socio-demographic characteristics can predict group membership. We performed latent class analysis using 14 mitigation actions as manifest variables. Three classes were identified among men: the Inactive (26%), the Semi-active (63%) and the Active (11%) and two classes among women: the Semi-active (72%) and the Active (28%). The Active among both genders were likely to have mitigated climate change through several actions, such as recycling, using environmentally friendly products, preferring public transport, and conserving energy. The Semi-Active had most probably recycled and preferred public transport because of climate change. The Inactive, a class identified among men only, had very probably done nothing to mitigate climate change. Among males, being single or divorced predicted little involvement in climate change mitigation. Among females, those without tertiary degree and those with annual income €≥16801 were less involved in climate change mitigation. Our results illustrate to what extent young adults are engaged in climate change mitigation, which factors predict little involvement in mitigation and give insight to which segments of the public could be the audiences of targeted mitigation campaigns.

Voluntary Climate Change Mitigation Actions of Young Adults: A Classification of Mitigators through Latent Class Analysis

PubMed Central

Korkala, Essi A. E.; Hugg, Timo T.; Jaakkola, Jouni J. K.

2014-01-01

Encouraging individuals to take action is important for the overall success of climate change mitigation. Campaigns promoting climate change mitigation could address particular groups of the population on the basis of what kind of mitigation actions the group is already taking. To increase the knowledge of such groups performing similar mitigation actions we conducted a population-based cross-sectional study in Finland. The study population comprised 1623 young adults who returned a self-administered questionnaire (response rate 64%). Our aims were to identify groups of people engaged in similar climate change mitigation actions and to study the gender differences in the grouping. We also determined if socio-demographic characteristics can predict group membership. We performed latent class analysis using 14 mitigation actions as manifest variables. Three classes were identified among men: the Inactive (26%), the Semi-active (63%) and the Active (11%) and two classes among women: the Semi-active (72%) and the Active (28%). The Active among both genders were likely to have mitigated climate change through several actions, such as recycling, using environmentally friendly products, preferring public transport, and conserving energy. The Semi-Active had most probably recycled and preferred public transport because of climate change. The Inactive, a class identified among men only, had very probably done nothing to mitigate climate change. Among males, being single or divorced predicted little involvement in climate change mitigation. Among females, those without tertiary degree and those with annual income €≥16801 were less involved in climate change mitigation. Our results illustrate to what extent young adults are engaged in climate change mitigation, which factors predict little involvement in mitigation and give insight to which segments of the public could be the audiences of targeted mitigation campaigns. PMID:25054549

Emotional climate of a pre-service science teacher education class in Bhutan

NASA Astrophysics Data System (ADS)

Rinchen, Sonam; Ritchie, Stephen M.; Bellocchi, Alberto

2016-09-01

This study explored pre-service secondary science teachers' perceptions of classroom emotional climate in the context of the Bhutanese macro-social policy of Gross National Happiness. Drawing upon sociological perspectives of human emotions and using Interaction Ritual Theory this study investigated how pre-service science teachers may be supported in their professional development. It was a multi-method study involving video and audio recordings of teaching episodes supported by interviews and the researcher's diary. Students also registered their perceptions of the emotional climate of their classroom at 3-minute intervals using audience response technology. In this way, emotional events were identified for video analysis. The findings of this study highlighted that the activities pre-service teachers engaged in matter to them. Positive emotional climate was identified in activities involving students' presentations using video clips and models, coteaching, and interactive whole class discussions. Decreases in emotional climate were identified during formal lectures and when unprepared presenters led presentations. Emotions such as frustration and disappointment characterized classes with negative emotional climate. The enabling conditions to sustain a positive emotional climate are identified. Implications for sustaining macro-social policy about Gross National Happiness are considered in light of the climate that develops in science teacher education classes.

A latent class approach to understanding patterns of peer victimization in four low-resource settings.

PubMed

Nguyen, Amanda J; Bradshaw, Catherine; Townsend, Lisa; Gross, Alden L; Bass, Judith

2016-08-17

Peer victimization is a common form of aggression among school-aged youth, but research is sparse regarding victimization dynamics in low- and middle-income countries (LMIC). Person-centered approaches have demonstrated utility in understanding patterns of victimization in the USA. We aimed to empirically identify classes of youth with unique victimization patterns in four LMIC settings using latent class analysis (LCA). We used data on past-year exposure to nine forms of victimization reported by 3536 youth (aged 15 years) from the Young Lives (YL) study in Ethiopia, India (Andhra Pradesh and Telangana states), Peru, and Vietnam. Sex and rural/urban context were examined as predictors of class membership. LCA supported a 2-class model in Peru, a 3-class model in Ethiopia and Vietnam, and a 4-class model in India. Classes were predominantly ordered by severity, suggesting that youth who experienced one form of victimization were likely to experience other forms as well. In India, two unordered classes were also observed, characterized by direct and indirect victimization. Boys were more likely than girls to be in the highly victimized (HV) class in Ethiopia and India. Urban contexts, compared with rural, conferred higher risk of victimization in Ethiopia and Peru, and lower risk in India and Vietnam. The identified patterns of multiple forms of victimization highlight a limitation of common researcher-driven classifications and suggest avenues for future person-centered research to improve intervention development in LMIC settings.

Obesity and Cigarette Smoking: Extending the Link to E-cigarette/Vaping Use.

PubMed

Lanza, H Isabella; Pittman, Patricia; Batshoun, Jennifer

2017-05-01

In recent years, electronic tobacco (e-cigarette/vaping) use among young adults has grown exponentially. Given past research linking obesity and cigarette smoking, assessing whether this relationship extends to electronic tobacco use is warranted. The current study examined weight status as a correlate of substance use patterns reflecting electronic tobacco use. Survey data were collected from a convenience sample of 452 (59% female) undergraduates attending a large, public university during the 2015-2016 academic year. Latent class analysis (LCA) was conducted to identify substance use classes and examine weight status as a covariate of class membership. LCA analyses identified 4 classes: High Substance Use (19%), Risky Alcohol Use (14%), Cigarette/Electronic Tobacco Use (17%), and Low Substance Use (50%). Both obesity status and greater deviation from one's group body mass index (BMI) norm were associated with a higher likelihood of belonging to the Cigarette/Electronic Tobacco Use class. Findings suggest that electronic tobacco use may fit well into previously established relationships between higher weight status and tobacco use. Future research should examine the longitudinal processes and pathways underlying the relationship between weight status and electronic tobacco use.

Patterns of co-occurring addictions, posttraumatic stress disorder, and major depressive disorder in detoxification treatment seekers: Implications for improving detoxification treatment outcomes.

PubMed

Anderson, RaeAnn E; Hruska, Bryce; Boros, Alec P; Richardson, Christopher J; Delahanty, Douglas L

2018-03-01

Poly-substance use and psychiatric comorbidity are common among individuals receiving substance detoxification services. Posttraumatic stress disorder (PTSD) and major depressive disorder (MDD) are the most common co-occurring psychiatric disorders with substance use disorder (SUD). Current treatment favors a one-size-fits-all approach to treating addiction focusing on one substance or one comorbidity. Research examining patterns of substance use and comorbidities can inform efforts to effectively identify and differentially treat individuals with co-occurring conditions. Using latent class analysis, the current study identified four patterns of PTSD, MDD, and substance use among 375 addiction treatment seekers receiving medically supervised detoxification. The four identified classes were: 1) a PTSD-MDD-Poly SUD class characterized by PTSD and MDD occurring in the context of opioid, cannabis, and tobacco use disorders; 2) an MDD-Poly SUD class characterized by MDD and alcohol, opioid, tobacco, and cannabis use disorders; 3) an alcohol-tobacco class characterized by alcohol and tobacco use disorders; and 4) an opioid-tobacco use disorder class characterized by opioid and tobacco use disorders. The observed classes differed on gender and clinical characteristics including addiction severity, trauma history, and PTSD/MDD symptom severity. The observed classes likely require differing treatment approaches. For example, people in the PTSD-MDD-Poly SUD class would likely benefit from treatment approaches targeting anxiety sensitivity and distress tolerance, while the opioid-tobacco class would benefit from treatments that incorporate motivational interviewing. Appropriate matching of treatment to class could optimize treatment outcomes for polysubstance and comorbid psychiatric treatment seekers. These findings also underscore the importance of well-developed referral networks to optimize outpatient psychotherapy for detoxification treatment-seekers to enhance long-term recovery, particularly those that include transdiagnostic treatment components. Copyright © 2017. Published by Elsevier Inc.

Spectral variability among rocks in visible and near-infrared mustispectral Pancam data collected at Gusev crater: Examinations using spectral mixture analysis and related techniques

USGS Publications Warehouse

Farrand, W. H.; Bell, J.F.; Johnson, J. R.; Squyres, S. W.; Soderblom, J.; Ming, D. W.

2006-01-01

Visible and near-infrared (VNIR) multispectral observations of rocks made by the Mars Exploration Rover Spirit's Panoramic camera (Pancam) have been analyzed using a spectral mixture analysis (SMA) methodology. Scenes have been examined from the Gusev crater plains into the Columbia Hills. Most scenes on the plains and in the Columbia Hills could be modeled as three end-member mixtures of a bright material, rock, and shade. Scenes of rocks disturbed by the rover's Rock Abrasion Tool (RAT) required additional end-members. In the Columbia Hills, there were a number of scenes in which additional rock end-members were required. The SMA methodology identified relatively dust-free areas on undisturbed rock surfaces as well as spectrally unique areas on RAT abraded rocks. Spectral parameters from these areas were examined, and six spectral classes were identified. These classes are named after a type rock or area and are Adirondack, Lower West Spur, Clovis, Wishstone, Peace, and Watchtower. These classes are discriminable based, primarily, on near-infrared (NIR) spectral parameters. Clovis and Watchtower class rocks appear more oxidized than Wishstone class rocks and Adirondack basalts based on their having higher 535 nm band depths. Comparison of the spectral parameters of these Gusev crater rocks to parameters of glass-dominated basaltic tuffs indicates correspondence between measurements of Clovis and Watchtower classes but divergence for the Wishstone class rocks, which appear to have a higher fraction of crystalline ferrous iron-bearing phases. Despite a high sulfur content, the rock Peace has NIR properties resembling plains basalts. Copyright 2006 by the American Geophysical Union.

Patterns of Drug Use, Risky Behavior, and Health Status Among Persons Who Inject Drugs Living in San Diego, California: A Latent Class Analysis

PubMed Central

Roth, Alexis M.; Armenta, Richard A.; Wagner, Karla D.; Roesch, Scott C.; Bluthenthal, Ricky N.; Cuevas-Mota, Jazmine; Garfein, Richard S.

2015-01-01

Background Among persons who inject drugs (PWID), polydrug use (the practice of mixing multiple drugs/alcohol sequentially or simultaneously) increases risk for HIV transmission and unintentional overdose deaths. Research has shown local drug markets influence drug use practices. However, little is known about the impact of drug mixing in markets dominated by black tar heroin and methamphetamine, such as the western United States. Methods Data were collected through an ongoing longitudinal study examining drug use, risk behavior, and health status among PWID. Latent class analysis (LCA) was used to identify patterns of substance use (heroin, methamphetamine, prescription drugs, alcohol, and marijuana) via multiple administration routes (injecting, smoking, and swallowing). Logistic regression was used to identify behaviors and health indicators associated with drug use class. Results The sample included 511 mostly white (51.5%) males (73.8%), with mean age of 43.5 years. Two distinct classes of drug users predominated: methamphetamine by multiple routes (51%) and heroin by injection (49%). In multivariable logistic regression, class membership was associated with age, race, and housing status. PWID who were HIV-seropositive and reported prior sexually transmitted infections had increased odds of belonging to the methamphetamine class. Those who were HCV positive and reported previous opioid overdose had an increased odds of being in the primarily heroin injection class (all P-values < .05). Conclusion Risk behaviors and health outcomes differed between PWID who primarily inject heroin vs. those who use methamphetamine. The findings suggest that in a region where PWID mainly use black tar heroin or methamphetamine, interventions tailored to sub-populations of PWID could improve effectiveness. PMID:25313832

An approach to understanding sleep and depressed mood in adolescents: person-centred sleep classification.

PubMed

Shochat, Tamar; Barker, David H; Sharkey, Katherine M; Van Reen, Eliza; Roane, Brandy M; Carskadon, Mary A

2017-12-01

Depressive mood in youth has been associated with distinct sleep dimensions, such as timing, duration and quality. To identify discrete sleep phenotypes, we applied person-centred analysis (latent class mixture models) based on self-reported sleep patterns and quality, and examined associations between phenotypes and mood in high-school seniors. Students (n = 1451; mean age = 18.4 ± 0.3 years; 648 M) completed a survey near the end of high-school. Indicators used for classification included school night bed- and rise-times, differences between non-school night and school night bed- and rise-times, sleep-onset latency, number of awakenings, naps, and sleep quality and disturbance. Mood was measured using the total score on the Center for Epidemiologic Studies-Depression Scale. One-way anova tested differences between phenotype for mood. Fit indexes were split between 3-, 4- and 5-phenotype solutions. For all solutions, between phenotype differences were shown for all indicators: bedtime showed the largest difference; thus, classes were labelled from earliest to latest bedtime as 'A' (n = 751), 'B' (n = 428) and 'C' (n = 272) in the 3-class solution. Class B showed the lowest sleep disturbances and remained stable, whereas classes C and A each split in the 4- and 5-class solutions, respectively. Associations with mood were consistent, albeit small, with class B showing the lowest scores. Person-centred analysis identified sleep phenotypes that differed in mood, such that those with the fewest depressive symptoms had moderate sleep timing, shorter sleep-onset latencies and fewer arousals. Sleep characteristics in these groups may add to our understanding of how sleep and depressed mood associate in teens. © 2017 European Sleep Research Society.

Delirium superimposed on dementia: defining disease states and course from longitudinal measurements of a multivariate index using latent class analysis and hidden Markov chains.

PubMed

Ciampi, Antonio; Dyachenko, Alina; Cole, Martin; McCusker, Jane

2011-12-01

The study of mental disorders in the elderly presents substantial challenges due to population heterogeneity, coexistence of different mental disorders, and diagnostic uncertainty. While reliable tools have been developed to collect relevant data, new approaches to study design and analysis are needed. We focus on a new analytic approach. Our framework is based on latent class analysis and hidden Markov chains. From repeated measurements of a multivariate disease index, we extract the notion of underlying state of a patient at a time point. The course of the disorder is then a sequence of transitions among states. States and transitions are not observable; however, the probability of being in a state at a time point, and the transition probabilities from one state to another over time can be estimated. Data from 444 patients with and without diagnosis of delirium and dementia were available from a previous study. The Delirium Index was measured at diagnosis, and at 2 and 6 months from diagnosis. Four latent classes were identified: fairly healthy, moderately ill, clearly sick, and very sick. Dementia and delirium could not be separated on the basis of these data alone. Indeed, as the probability of delirium increased, so did the probability of decline of mental functions. Eight most probable courses were identified, including good and poor stable courses, and courses exhibiting various patterns of improvement. Latent class analysis and hidden Markov chains offer a promising tool for studying mental disorders in the elderly. Its use may show its full potential as new data become available.

Functional Analyses and Treatment of Precursor Behavior

ERIC Educational Resources Information Center

Najdowski, Adel C.; Wallace, Michele D.; Ellsworth, Carrie L.; MacAleese, Alicia N.; Cleveland, Jackie

2008-01-01

Functional analysis has been demonstrated to be an effective method to identify environmental variables that maintain problem behavior. However, there are cases when conducting functional analyses of severe problem behavior may be contraindicated. The current study applied functional analysis procedures to a class of behavior that preceded severe…

Characterisation of major histocompatibility complex class I transcripts in an Australian dragon lizard.

PubMed

Hacking, Jessica; Bertozzi, Terry; Moussalli, Adnan; Bradford, Tessa; Gardner, Michael

2018-07-01

Characterisation of squamate major histocompatibility complex (MHC) genes has lagged behind other taxonomic groups. MHC genes encode cell-surface glycoproteins that present self- and pathogen-derived peptides to T cells and play a critical role in pathogen recognition. Here we characterise MHC class I transcripts for an agamid lizard (Ctenophorus decresii) and investigate the evolution of MHC class I in Iguanian lizards. An iterative assembly strategy was used to identify six full-length C. decresii MHC class I transcripts, which were validated as likely to encode classical class I MHC molecules. Evidence for exon shuffling recombination was uncovered for C. decresii transcripts and Bayesian phylogenetic analysis of Iguanian MHC class I sequences revealed a pattern expected under a birth-and-death mode of evolution. This work provides a stepping stone towards further research on the agamid MHC class I region. Copyright © 2018 Elsevier Ltd. All rights reserved.

A Spatial Approach to Identify Slum Areas in East Wara Sub-Districts, South Sulawesi

NASA Astrophysics Data System (ADS)

Anurogo, W.; Lubis, M. Z.; Pamungkas, D. S.; Hartono; Ibrahim, F. M.

2017-12-01

Spatial approach is one of the main approaches of geography, its analysis emphasizes the existence of space that serves to accommodate human activities. The dynamic development of the city area brings many impacts to the urban community’s own life patterns. The development of the city center which is the center of economic activity becomes the attraction for the community that can bring influence to the high flow of labor both from within the city itself and from outside the city area, thus causing the high flow of urbanization. Urbanization has caused an explosion in urban population and one implication is the occurrence of labor-clumping in major cities in Indonesia. Another impact of the high urbanization flow of cities is the problem of urban settlements. The more populations that come in the city, the worse the quality of the existing settlements in the city if not managed properly. This study aims to determine the location of slum areas in East Wara Sub-Districts using remote sensing technology tools and Geographic Information System (GIS). Parameters used to identify slum areas partially extracted using remote sensing data and for parameters that cannot be extracted using remote sensing data, information obtained from field surveys with information retrieval based on reference data. Analysis results for slum settlements taken from the parameters indicate that the East Wara Sub-District has the largest slum areas located in Pontap village. The village of Pontap has two classes of slums that are very shabby and slums. Slum classes are also in Surutangga Village. The result of the analysis shows that the slum settlement area has 46,324 Ha, which is only located in Pontap Village, whereas for the slum class are found in some villages of Pontap and Surutangga Urban Village, there are 37.797 Ha area. The class of slum settlement areas has the largest proportion of the area among other classes in East Wara Subdistrict. The class of slum settlement areas has an area of 74,481 Ha. This class is located in Kelurahan Salekoe and Kelurahan Benteng. The less grungy and quite shabby class is the rest which each has an area of 29,144 Ha and 18,228 Ha. There is quite a slum class in Kelurahan Ponjale and Less Slum Class Available in Malatunrung Urban Village.

Acculturation and Self-Rated Mental Health Among Latino and Asian Immigrants in the United States: A Latent Class Analysis.

PubMed

Bulut, Elif; Gayman, Matthew D

2016-08-01

This study assesses variations in acculturation experiences by identifying distinct acculturation classes, and investigates the role of these acculturation classes for self-rated mental health among Latino and Asian immigrants in the United States. Using 2002-2003 the National Latino and Asian American Study, Latent Class Analysis is used to capture variations in immigrant classes (recent arrivals, separated, bicultural and assimilated), and OLS regressions are used to assess the link between acculturation classes and self-rated mental health. For both Latinos and Asians, bicultural immigrants reported the best mental health, and separated immigrants and recent arrivals reported the worst mental health. The findings also reveal group differences in acculturation classes, whereby Latino immigrants were more likely to be in the separated class and recent arrivals class relative to Asian immigrants. While there was not a significant group difference in self-rated mental health at the bivariate level, controlling for acculturation classes revealed that Latinos report better self-rated mental health than Asians. Thus, Latino immigrants would actually have better self-rated mental health than their Asian counterparts if they were not more likely to be represented in less acculturated classes (separated class and recent arrivals) and/or as likely to be in the bicultural class as their Asian counterparts. Together the findings underscore the nuanced and complex nature of the acculturation process, highlighting the importance of race differences in this process, and demonstrate the role of acculturation classes for immigrant group differences in self-rated mental health.

Identification of broadly reactive epitopes targeting major glycoproteins of Herpes simplex virus (HSV) 1 and 2 - An immunoinformatics analysis.

PubMed

Chauhan, Varun; Goyal, Kapil; Singh, Mini P

2018-07-01

Infections due to both HSV-1 and HSV-2 constitute an enormous health burden worldwide. Development of vaccine against herpes infections is a WHO supported public health priority. The viral glycoproteins have always been the major hotspots for vaccine designing. The present study was aimed to identify the conserved T and B cell epitopes in the major glycoproteins of both HSV-1 and HSV-2 via rigorous computational approaches. Identification of promiscuous T cell epitopes is of utmost importance in vaccine designing as such epitopes are capable of binding to several allelic forms of HLA and could generate effective immune response in the host. The criteria designed for identification of T and B cell epitopes was that it should be conserved in both HSV-1 and 2, promiscuous, have high affinity towards HLA alleles, should be located on the surface of glycoproteins and not be present in the glycosylation sites. This study led to the identification of 17 HLA Class II and 26 HLA Class I T cell epitopes, 9 linear and some conformational B cell epitopes. The identified T cell epitopes were further subjected to molecular docking analysis to analyze their binding patterns. Altogether we have identified 4 most promising regions in glycoproteins (2-gB, 1-gD, 1-gH) of HSV-1 and 2 which are promiscuous to HLA Class II alleles and have overlapping HLA Class I and B cell epitopes, which could be very useful in generating both arms of immune response in the host i.e. adaptive as well as humoral immunity. Further the authors propose the cross-validation of the identified epitopes in experimental settings for confirming their immunogenicity to support the present findings. Copyright © 2018 Elsevier B.V. All rights reserved.

Who Is at Risk for Diagnostic Discrepancies? Comparison of Pre- and Postmortal Diagnoses in 1800 Patients of 3 Medical Decades in East and West Berlin

PubMed Central

Wittschieber, Daniel; Klauschen, Frederick; Kimmritz, Anna-Christin; von Winterfeld, Moritz; Kamphues, Carsten; Scholman, Hans-Joachim; Erbersdobler, Andreas; Pfeiffer, Heidi; Denkert, Carsten; Dietel, Manfred; Weichert, Wilko

2012-01-01

Background Autopsy rates in Western countries consistently decline to an average of <5%, although clinical autopsies represent a reasonable tool for quality control in hospitals, medically and economically. Comparing pre- and postmortal diagnoses, diagnostic discrepancies as uncovered by clinical autopsies supply crucial information on how to improve clinical treatment. The study aimed at analyzing current diagnostic discrepancy rates, investigating their influencing factors and identifying risk profiles of patients that could be affected by a diagnostic discrepancy. Methods and Findings Of all adult autopsy cases of the Charité Institute of Pathology from the years 1988, 1993, 1998, 2003 and 2008, the pre- and postmortal diagnoses and all demographic data were analyzed retrospectively. Based on power analysis, 1,800 cases were randomly selected to perform discrepancy classification (class I-VI) according to modified Goldman criteria. The rate of discrepancies in major diagnoses (class I) was 10.7% (95% CI: 7.7%–14.7%) in 2008 representing a reduction by 15.1%. Subgroup analysis revealed several influencing factors to significantly correlate with the discrepancy rate. Cardiovascular diseases had the highest frequency among class-I-discrepancies. Comparing the 1988-data of East- and West-Berlin, no significant differences were found in diagnostic discrepancies despite an autopsy rate differing by nearly 50%. A risk profile analysis visualized by intuitive heatmaps revealed a significantly high discrepancy rate in patients treated in low or intermediate care units at community hospitals. In this collective, patients with genitourinary/renal or infectious diseases were at particularly high risk. Conclusions This is the current largest and most comprehensive study on diagnostic discrepancies worldwide. Our well-powered analysis revealed a significant rate of class-I-discrepancies indicating that autopsies are still of value. The identified risk profiles may aid both pathologists and clinicians to identify patients at increased risk for a discrepant diagnosis and possibly suboptimal treatment intra vitam. PMID:22629399

Developmental Trajectories of Irritability and Bidirectional Associations With Maternal Depression

PubMed Central

Wiggins, Jillian Lee; Mitchell, Colter; Stringaris, Argyris; Leibenluft, Ellen

2014-01-01

Objective Irritability is a dimensional trait in typical development and a common presenting symptom in many psychiatric disorders, including depression. However, little is known about the developmental trajectory of irritability or how child irritability interacts with maternal depression. The present study (1) identifies classes of irritability trajectories from toddlerhood to middle childhood; (2) characterizes maternal depression and other family, social environment, and child variables within each irritability trajectory class; and (3) as a more exploratory analysis, examines bidirectional associations between maternal depression and child irritability. Method 4,898 families from the Fragile Families and Child Wellbeing Study reported on irritability symptoms at ages 3, 5, and 9, assessed with items from the Child Behavior Checklist. Parental major depressive episode was assessed using the Composite International Diagnostic Interview – Short Form at child ages 1, 3, 5, 9. Results A latent class growth analysis identified five irritability classes: low decreasing; moderate decreasing; high steady; initially very high, then decreasing; and high increasing. Children with more severe irritability trajectories are more likely to have mothers with recurrent depression, and, with the exception of the most severe (high increasing irritability) class, were more likely to have mothers who were exposed to violence. Moreover, paternal depression and alcohol use, as well as maternal drug and alcohol use, were also risk factors for membership in the more severe irritability classes. A latent auto-regressive cross-lag model showed that child irritability at ages 3 and 5 is associated with increased mother depression at 5 and 9, respectively. Conversely, mother depression at child ages 1 and 3 is associated with increased child irritability at 3 and 5. Conclusion Irritability development across toddlerhood and middle childhood has five main trajectory types, which differ on maternal depression recurrence and exposure to violence. Maternal depression and child irritability influence each other bidirectionally, particularly early in development. Understanding irritability development and its bidirectional relationship with maternal depression and association with violence exposure may help identify intervention targets. PMID:25440309

Developmental trajectories of irritability and bidirectional associations with maternal depression.

PubMed

Wiggins, Jillian Lee; Mitchell, Colter; Stringaris, Argyris; Leibenluft, Ellen

2014-11-01

Irritability is a dimensional trait in typical development and a common presenting symptom in many psychiatric disorders, including depression. However, little is known about the developmental trajectory of irritability or how child irritability interacts with maternal depression. The present study identifies classes of irritability trajectories from toddlerhood to middle childhood; characterizes maternal depression and other family, social environment, and child variables within each irritability trajectory class; and, as a more exploratory analysis, examines bidirectional associations between maternal depression and child irritability. A total of 4,898 families from the Fragile Families and Child Wellbeing Study reported on irritability symptoms at ages 3, 5, and 9 years, assessed with items from the Child Behavior Checklist. Parental major depressive episode was assessed using the Composite International Diagnostic Interview-Short Form at child ages 1, 3, 5, and 9 years. A latent class growth analysis identified 5 irritability classes: low decreasing; moderate decreasing; high steady; initially very high, then decreasing; and high increasing. Children with more severe irritability trajectories are more likely to have mothers with recurrent depression, and, with the exception of the most severe (high increasing irritability) class, were more likely to have mothers who were exposed to violence. Moreover, paternal depression and alcohol abuse, as well as maternal drug and alcohol abuse, were also risk factors for membership in the more severe irritability classes. A latent auto-regressive cross-lag model showed that child irritability at ages 3 and 5 years is associated with increased mother depression at ages 5 and 9, respectively. Conversely, mother depression at child ages 1 and 3 years is associated with increased child irritability at 3 and 5. Irritability development across toddlerhood and middle childhood has 5 main trajectory types, which differ on maternal depression recurrence and exposure to violence. Maternal depression and child irritability influence each other bidirectionally, particularly early in development. Understanding irritability development and its bidirectional relationship with maternal depression and association with violence exposure may help identify intervention targets. Published by Elsevier Inc.

Constructing Social Networks From Secondary Storage With Bulk Analysis Tools

DTIC Science & Technology

2016-06-01

that classic measures of centrality are effective for identifying important nodes and close associates, and that further study of modularity classes...which ground truth was determined by interviews with the owners, and which can be used for future study in this area. Two objectives motivated this thesis...tifying important nodes and close associates, and that further study of modularity classes may be a promising method of partitioning complex components

On the origins of naming and other symbolic behavior

PubMed Central

Horne, Pauline J.; Lowe, C. Fergus

1996-01-01

We identify naming as the basic unit of verbal behavior, describe the conditions under which it is learned, and outline its crucial role in the development of stimulus classes and, hence, of symbolic behavior. Drawing upon B. F. Skinner's functional analysis and the theoretical work of G. H. Mead and L. S. Vygotsky, we chart how a child, through learning listener behavior and then echoic responding, learns bidirectional relations between classes of objects or events and his or her own speaker-listener behavior, thus acquiring naming—a higher order behavioral relation. Once established, the bidirectionality incorporated in naming extends across behavior classes such as those identified by Skinner as the mand, tact, and intraverbal so that each becomes a variant of the name relation. We indicate how our account informs the specification of rule-governed behavior and provides the basis for an experimental analysis of symbolic behavior. Furthermore, because naming is both evoked by, and itself evokes, classes of events it brings about new or emergent behavior such as that reported in studies of stimulus equivalence. This account is supported by data from a wide range of match-to-sample studies that also provide evidence that stimulus equivalence in humans is not a unitary phenomenon but the outcome of a number of different types of naming behavior. PMID:16812780

A Bioinformatic Strategy for the Detection, Classification and Analysis of Bacterial Autotransporters

PubMed Central

Celik, Nermin; Webb, Chaille T.; Leyton, Denisse L.; Holt, Kathryn E.; Heinz, Eva; Gorrell, Rebecca; Kwok, Terry; Naderer, Thomas; Strugnell, Richard A.; Speed, Terence P.; Teasdale, Rohan D.; Likić, Vladimir A.; Lithgow, Trevor

2012-01-01

Autotransporters are secreted proteins that are assembled into the outer membrane of bacterial cells. The passenger domains of autotransporters are crucial for bacterial pathogenesis, with some remaining attached to the bacterial surface while others are released by proteolysis. An enigma remains as to whether autotransporters should be considered a class of secretion system, or simply a class of substrate with peculiar requirements for their secretion. We sought to establish a sensitive search protocol that could identify and characterize diverse autotransporters from bacterial genome sequence data. The new sequence analysis pipeline identified more than 1500 autotransporter sequences from diverse bacteria, including numerous species of Chlamydiales and Fusobacteria as well as all classes of Proteobacteria. Interrogation of the proteins revealed that there are numerous classes of passenger domains beyond the known proteases, adhesins and esterases. In addition the barrel-domain-a characteristic feature of autotransporters-was found to be composed from seven conserved sequence segments that can be arranged in multiple ways in the tertiary structure of the assembled autotransporter. One of these conserved motifs overlays the targeting information required for autotransporters to reach the outer membrane. Another conserved and diagnostic motif maps to the linker region between the passenger domain and barrel-domain, indicating it as an important feature in the assembly of autotransporters. PMID:22905239

Integrated Safety Assessment of 2′-O-Methoxyethyl Chimeric Antisense Oligonucleotides in NonHuman Primates and Healthy Human Volunteers

PubMed Central

Crooke, Stanley T; Baker, Brenda F; Kwoh, T Jesse; Cheng, Wei; Schulz, Dan J; Xia, Shuting; Salgado, Nelson; Bui, Huynh-Hoa; Hart, Christopher E; Burel, Sebastien A; Younis, Husam S; Geary, Richard S; Henry, Scott P; Bhanot, Sanjay

2016-01-01

The common chemical and biological properties of antisense oligonucleotides provide the opportunity to identify and characterize chemical class effects across species. The chemical class that has proven to be the most versatile and best characterized is the 2′-O-methoxyethyl chimeric antisense oligonucleotides. In this report we present an integrated safety assessment of data obtained from controlled dose-ranging studies in nonhuman primates (macaques) and healthy human volunteers for 12 unique 2′-O-methoxyethyl chimeric antisense oligonucleotides. Safety was assessed by the incidence of safety signals in standardized laboratory tests for kidney and liver function, hematology, and complement activation; as well as by the mean test results as a function of dose level over time. At high doses a number of toxicities were observed in nonhuman primates. However, no class safety effects were identified in healthy human volunteers from this integrated data analysis. Effects on complement in nonhuman primates were not observed in humans. Nonhuman primates predicted safe doses in humans, but over predicted risk of complement activation and effects on platelets. Although limited to a single chemical class, comparisons from this analysis are considered valid and accurate based on the carefully controlled setting for the specified study populations and within the total exposures studied. PMID:27357629

Classifying Married Adults Diagnosed with Alpha-1 Antitrypsin Deficiency Based on Spousal Communication Patterns Using Latent Class Analysis: Insights for Intervention

PubMed Central

Smith, Rachel A.; Wienke, Sara E.; Baker, Michelle K.

2013-01-01

Married adults are increasingly exposed to test results that indicate an increased genetic risk for adult-onset conditions. For example, a SERPINA1 mutation, associated with alpha-1 antitrypsin deficiency (AATD), predisposes affected individuals to diseases such as chronic obstructive pulmonary disease (COPD) and cancer, which are often detected in adulthood. Married adults are likely to discuss genetic test results with their spouses, and interpersonal research suggests that spouses’ communication patterns differ. Latent class analysis was used to identify subgroups of spousal communication patterns about AATD results from a sample of married adults in the Alpha-1 Research Registry (N = 130). A five-class model was identified, and the subgroups were consistent with existing spousal-communication typologies. This study also showed that genetic beliefs (e.g., genetic stigma), emotions, and experiences (e.g., insurance difficulties) covaried with membership in particular subgroups. Understanding these differences can serve as the foundation for the creation of effective, targeted communications interventions to address the specific needs and conversational patterns of different kinds of couples. PMID:24177906

Factors associated with patterns of mobile technology use among persons who inject drugs.

PubMed

Collins, Kelly M; Armenta, Richard F; Cuevas-Mota, Jazmine; Liu, Lin; Strathdee, Steffanie A; Garfein, Richard S

2016-01-01

New and innovative methods of delivering interventions are needed to further reduce risky behaviors and increase overall health among persons who inject drugs (PWID). Mobile health (mHealth) interventions have potential for reaching PWID; however, little is known about mobile technology use (MTU) in this population. In this study, the authors identify patterns of MTU and identified factors associated with MTU among a cohort of PWID. Data were collected through a longitudinal cohort study examining drug use, risk behaviors, and health status among PWID in San Diego, California. Latent class analysis (LCA) was used to define patterns of MTU (i.e., making voice calls, text messaging, and mobile Internet access). Multinomial logistic regression was then used to identify demographic characteristics, risk behaviors, and health indicators associated with mobile technology use class. In LCA, a 4-class solution fit the data best. Class 1 was defined by low MTU (22%, n = 100); class 2, by PWID who accessed the Internet using a mobile device but did not use voice or text messaging (20%, n = 95); class 3, by primarily voice, text, and connected Internet use (17%, n = 91); and class 4, by high MTU (41%, n = 175). Compared with low MTU, high MTU class members were more likely to be younger, have higher socioeconomic status, sell drugs, and inject methamphetamine daily. The majority of PWID in San Diego use mobile technology for voice, text, and/or Internet access, indicating that rapid uptake of mHealth interventions may be possible in this population. However, low ownership and use of mobile technology among older and/or homeless individuals will need to be considered when implementing mHealth interventions among PWID.

Integrating end-to-end threads of control into object-oriented analysis and design

NASA Technical Reports Server (NTRS)

Mccandlish, Janet E.; Macdonald, James R.; Graves, Sara J.

1993-01-01

Current object-oriented analysis and design methodologies fall short in their use of mechanisms for identifying threads of control for the system being developed. The scenarios which typically describe a system are more global than looking at the individual objects and representing their behavior. Unlike conventional methodologies that use data flow and process-dependency diagrams, object-oriented methodologies do not provide a model for representing these global threads end-to-end. Tracing through threads of control is key to ensuring that a system is complete and timing constraints are addressed. The existence of multiple threads of control in a system necessitates a partitioning of the system into processes. This paper describes the application and representation of end-to-end threads of control to the object-oriented analysis and design process using object-oriented constructs. The issue of representation is viewed as a grouping problem, that is, how to group classes/objects at a higher level of abstraction so that the system may be viewed as a whole with both classes/objects and their associated dynamic behavior. Existing object-oriented development methodology techniques are extended by adding design-level constructs termed logical composite classes and process composite classes. Logical composite classes are design-level classes which group classes/objects both logically and by thread of control information. Process composite classes further refine the logical composite class groupings by using process partitioning criteria to produce optimum concurrent execution results. The goal of these design-level constructs is to ultimately provide the basis for a mechanism that can support the creation of process composite classes in an automated way. Using an automated mechanism makes it easier to partition a system into concurrently executing elements that can be run in parallel on multiple processors.

Stability of ARDS subphenotypes over time in two randomised controlled trials.

PubMed

Delucchi, Kevin; Famous, Katie R; Ware, Lorraine B; Parsons, Polly E; Thompson, B Taylor; Calfee, Carolyn S

2018-05-01

Two distinct acute respiratory distress syndrome (ARDS) subphenotypes have been identified using data obtained at time of enrolment in clinical trials; it remains unknown if these subphenotypes are durable over time. To determine the stability of ARDS subphenotypes over time. Secondary analysis of data from two randomised controlled trials in ARDS, the ARMA trial of lung protective ventilation (n=473; patients randomised to low tidal volumes only) and the ALVEOLI trial of low versus high positive end-expiratory pressure (n=549). Latent class analysis (LCA) and latent transition analysis (LTA) were applied to data from day 0 and day 3, independent of clinical outcomes. In ALVEOLI, LCA indicated strong evidence of two ARDS latent classes at days 0 and 3; in ARMA, evidence of two classes was stronger at day 0 than at day 3. The clinical and biological features of these two classes were similar to those in our prior work and were largely stable over time, though class 2 demonstrated evidence of progressive organ failures by day 3, compared with class 1. In both LCA and LTA models, the majority of patients (>94%) stayed in the same class from day 0 to day 3. Clinical outcomes were statistically significantly worse in class 2 than class 1 and were more strongly associated with day 3 class assignment. ARDS subphenotypes are largely stable over the first 3 days of enrolment in two ARDS Network trials, suggesting that subphenotype identification may be feasible in the context of clinical trials. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2018. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

The effects of rurality on substance use disorder diagnosis: A multiple-groups latent class analysis.

PubMed

Brooks, Billy; McBee, Matthew; Pack, Robert; Alamian, Arsham

2017-05-01

Rates of accidental overdose mortality from substance use disorder (SUD) have risen dramatically in the United States since 1990. Between 1999 and 2004 alone rates increased 62% nationwide, with rural overdose mortality increasing at a rate 3 times that seen in urban populations. Cultural differences between rural and urban populations (e.g., educational attainment, unemployment rates, social characteristics, etc.) affect the nature of SUD, leading to disparate risk of overdose across these communities. Multiple-groups latent class analysis with covariates was applied to data from the 2011 and 2012 National Survey on Drug Use and Health (n=12.140) to examine potential differences in latent classifications of SUD between rural and urban adult (aged 18years and older) populations. Nine drug categories were used to identify latent classes of SUD defined by probability of diagnosis within these categories. Once the class structures were established for rural and urban samples, posterior membership probabilities were entered into a multinomial regression analysis of socio-demographic predictors' association with the likelihood of SUD latent class membership. Latent class structures differed across the sub-groups, with the rural sample fitting a 3-class structure (Bootstrap Likelihood Ratio Test P value=0.03) and the urban fitting a 6-class model (Bootstrap Likelihood Ratio Test P value<0.0001). Overall the rural class structure exhibited less diversity in class structure and lower prevalence of SUD in multiple drug categories (e.g. cocaine, hallucinogens, and stimulants). This result supports the hypothesis that different underlying elements exist in the two populations that affect SUD patterns, and thus can inform the development of surveillance instruments, clinical services, and prevention programming tailored to specific communities. Copyright © 2017 Elsevier Ltd. All rights reserved.

Laban Movement Analysis Approach to Classical Ballet Pedagogy

ERIC Educational Resources Information Center

Whittier, Cadence

2006-01-01

As a Certified Laban Movement Analyst and a classically trained ballet dancer, I consistently weave the Laban Movement Analysis/Bartenieff Fundamentals (LMA/BF) theories and philosophies into the ballet class. This integration assists in: (1) Identifying the qualitative movement elements both in the art of ballet and in the students' dancing…

Sequence, distribution and chromosomal context of class I and class II pilin genes of Neisseria meningitidis identified in whole genome sequences

PubMed Central

2014-01-01

Background Neisseria meningitidis expresses type four pili (Tfp) which are important for colonisation and virulence. Tfp have been considered as one of the most variable structures on the bacterial surface due to high frequency gene conversion, resulting in amino acid sequence variation of the major pilin subunit (PilE). Meningococci express either a class I or a class II pilE gene and recent work has indicated that class II pilins do not undergo antigenic variation, as class II pilE genes encode conserved pilin subunits. The purpose of this work was to use whole genome sequences to further investigate the frequency and variability of the class II pilE genes in meningococcal isolate collections. Results We analysed over 600 publically available whole genome sequences of N. meningitidis isolates to determine the sequence and genomic organization of pilE. We confirmed that meningococcal strains belonging to a limited number of clonal complexes (ccs, namely cc1, cc5, cc8, cc11 and cc174) harbour a class II pilE gene which is conserved in terms of sequence and chromosomal context. We also identified pilS cassettes in all isolates with class II pilE, however, our analysis indicates that these do not serve as donor sequences for pilE/pilS recombination. Furthermore, our work reveals that the class II pilE locus lacks the DNA sequence motifs that enable (G4) or enhance (Sma/Cla repeat) pilin antigenic variation. Finally, through analysis of pilin genes in commensal Neisseria species we found that meningococcal class II pilE genes are closely related to pilE from Neisseria lactamica and Neisseria polysaccharea, suggesting horizontal transfer among these species. Conclusions Class II pilins can be defined by their amino acid sequence and genomic context and are present in meningococcal isolates which have persisted and spread globally. The absence of G4 and Sma/Cla sequences adjacent to the class II pilE genes is consistent with the lack of pilin subunit variation in these isolates, although horizontal transfer may generate class II pilin diversity. This study supports the suggestion that high frequency antigenic variation of pilin is not universal in pathogenic Neisseria. PMID:24690385

How do older adult drivers self-regulate? Characteristics of self-regulation classes defined by latent class analysis.

PubMed

Bergen, Gwen; West, Bethany A; Luo, Feijun; Bird, Donna C; Freund, Katherine; Fortinsky, Richard H; Staplin, Loren

2017-06-01

Motor-vehicle crashes were the second leading cause of injury death for adults aged 65-84years in 2014. Some older drivers choose to self-regulate their driving to maintain mobility while reducing driving risk, yet the process remains poorly understood. Data from 729 older adults (aged ≥60years) who joined an older adult ride service program between April 1, 2010 and November 8, 2013 were analyzed to define and describe classes of driving self-regulation. Latent class analysis was employed to characterize older adult driving self-regulation classes using driving frequency and avoidance of seven driving situations. Logistic regression was used to explore associations between characteristics affecting mobility and self-regulation class. Three classes were identified (low, medium, and high self-regulation). High self-regulating participants reported the highest proportion of always avoiding seven risky driving situations and the lowest driving frequency followed by medium and low self-regulators. Those who were female, aged 80years or older, visually impaired, assistive device users, and those with special health needs were more likely to be high self-regulating compared with low self-regulating. Avoidance of certain driving situations and weekly driving frequency are valid indicators for describing driving self-regulation classes in older adults. Understanding the unique characteristics and mobility limitations of each class can guide optimal transportation strategies for older adults. Published by Elsevier Ltd.

An Airline-Based Multilevel Analysis of Airfare Elasticity for Passenger Demand

NASA Technical Reports Server (NTRS)

Castelli, Lorenzo; Ukovich, Walter; Pesenti, Raffaele

2003-01-01

Price elasticity of passenger demand for a specific airline is estimated. The main drivers affecting passenger demand for air transportation are identified. First, an Ordinary Least Squares regression analysis is performed. Then, a multilevel analysis-based methodology to investigate the pattern of variation of price elasticity of demand among the various routes of the airline under study is proposed. The experienced daily passenger demands on each fare-class are grouped for each considered route. 9 routes were studied for the months of February and May in years from 1999 to 2002, and two fare-classes were defined (business and economy). The analysis has revealed that the airfare elasticity of passenger demand significantly varies among the different routes of the airline.

ADVERSE CHILDHOOD EXPERIENCES AMONG YOUTH AGING OUT OF FOSTER CARE: A LATENT CLASS ANALYSIS

PubMed Central

Rebbe, Rebecca; Nurius, Paula S.; Ahrens, Kym R.; Courtney, Mark E.

2017-01-01

Research has demonstrated that youth who age out, or emancipate, from foster care face deleterious outcomes across a variety of domains in early adulthood. This article builds on this knowledge base by investigating the role of adverse childhood experience accumulation and composition on these outcomes. A latent class analysis was performed to identify three subgroups: Complex Adversity, Environmental Adversity, and Lower Adversity. Differences are found amongst the classes in terms of young adult outcomes in terms of socio-economic outcomes, psychosocial problems, and criminal behaviors. The results indicate that not only does the accumulation of adversity matter, but so does the composition of the adversity. These results have implications for policymakers, the numerous service providers and systems that interact with foster youth, and for future research. PMID:28458409

Substance Use Patterns Among Adolescents in Europe: A Latent Class Analysis.

PubMed

Göbel, Kristin; Scheithauer, Herbert; Bräker, Astrid-Britta; Jonkman, Harrie; Soellner, Renate

2016-07-28

Several researchers have investigated substance use patterns using a latent class analysis; however, hardly no studies exist on substance use patterns across countries. Adolescent substance use patterns, demographic factors, and international differences in the prevalence of substance use patterns were explored. Data from 25 European countries were used to identify patterns of adolescent (12-16 years, 50.6% female) substance use (N = 33,566). Latent class analysis revealed four substance use classes: nonusers (68%), low-alcohol users (recent use of beer, wine, and alcopops; 16.1%), alcohol users (recent use of alcohol and lifetime use of marijuana; 11.2%), and polysubstance users (recent use of alcohol, marijuana, and other illicit drugs; 4.7%). Results support a general pattern of adolescent substance use across all countries; however, the prevalence rates of use patterns vary for each country. The present research provides insight into substance use patterns across Europe by using a large international adolescent sample, multidimensional indicators and a variety of substances. Substance use patterns are helpful when targeting policy and prevention strategies.

Changes in Classes of Injury-Related Risks and Consequences of Risk-Level Drinking: a Latent Transition Analysis.

PubMed

Cochran, Gerald; Field, Craig; Caetano, Raul

2015-07-01

Risk-level drinking, drinking and driving, and alcohol-related violence are risk factors that result in injuries. The current study sought to identify which subgroups of patients experience the most behavioral change following a brief intervention. A secondary analysis of data from a brief alcohol intervention study was conducted. The sample (N = 664) includes at-risk drinkers who experienced an injury and were admitted for care to a Level 1 trauma center. Injury-related items from the Short Inventory of Problems+6 were used to perform a latent transition analysis to describe class transitions participants experienced following discharge. Four classes emerged for the year before and after the current injury. Most individuals transitioned from higher-risk classes into those with lower risk. Some participants maintained risky profiles, and others increased risks and consequences. Drinking and driving remained a persistent problem among the study participants. Although a large portion of intervention recipients improved risks and consequences of alcohol use following discharge, more intensive intervention services may be needed for a subset of patients who showed little or no improvement.

A person-centered approach to individualizing a school-based universal preventive intervention.

PubMed

Caldwell, Linda L; Bradley, Stephanie; Coffman, Donna

2009-01-01

This manuscript focuses on how individualized components may be embedded within a universal preventive intervention (TimeWise: Taking Charge of Leisure Time) to make program delivery more effective. Leisure related variables (motivation, boredom/interest and peer and parental influence) were used to suggest ways to individualize the program. Latent Class Analysis was used to develop individualized risk and strength profiles of adolescents (N = 617). Comparisons were made between a treatment and control group. Four classes were identified: undifferentiated high, intrinsic motivation, extrinsic motivation/amotivation, undifferentiated low. These classes were related to substance use. Membership in the intrinsic class was associated with intervention group while the extrinsic class was related to the control group. Results were useful in suggesting ways to tailor a universal prevention program.

Prevalence and characteristics of addictive behaviors in a community sample: A latent class analysis.

PubMed

Deleuze, Jory; Rochat, Lucien; Romo, Lucia; Van der Linden, Martial; Achab, Sophia; Thorens, Gabriel; Khazaal, Yasser; Zullino, Daniele; Maurage, Pierre; Rothen, Stéphane; Billieux, Joël

2015-06-01

While addictions to substances such as alcohol, tobacco, and other drugs have been extensively investigated, interest has been growing in potential non-substance-related addictive behaviors (e.g., excessive gambling, buying or playing video games). In the current study, we sought to determine the prevalence and characteristics of a wide range of addictive behaviors in a general population sample and to identify reliable subgroups of individuals displaying addictive behaviors. Seven hundred seventy participants completed an online survey. The survey screened for the presence and characteristics of the main recognized substance and behavioral addictions (alcohol, tobacco, cannabis, other drugs, gambling, compulsive shopping, intensive exercise, Internet and mobile phone overuse, intensive work involvement, and overeating) in a three-month period. Key aspects of addiction were measured for each reported behavior, including negative outcomes, emotional triggers (positive and negative emotional contexts), search for stimulation or pleasure, loss of control, and cognitive salience. Latent class analysis allowed us to identify three theoretically and clinically relevant subgroups of individuals. The first class groups problematic users, i.e., addiction-prone individuals. The second class groups at-risk users who frequently engage in potentially addictive behaviors to regulate emotional states (especially overinvolvement in common behaviors such as eating, working, or buying). The third class groups individuals who are not prone to addictive behaviors. The existence of different groups in the population sheds new light on the distinction between problematic and non-problematic addiction-like behaviors.

Accuracy assessment/validation methodology and results of 2010–11 land-cover/land-use data for Pools 13, 26, La Grange, and Open River South, Upper Mississippi River System

USGS Publications Warehouse

Jakusz, J.W.; Dieck, J.J.; Langrehr, H.A.; Ruhser, J.J.; Lubinski, S.J.

2016-01-11

Similar to an AA, validation involves generating random points based on the total area for each map class. However, instead of collecting field data, two or three individuals not involved with the photo-interpretative mapping separately review each of the points onscreen and record a best-fit vegetation type(s) for each site. Once the individual analyses are complete, results are joined together and a comparative analysis is performed. The objective of this initial analysis is to identify areas where the validation results were in agreement (matches) and areas where validation results were in disagreement (mismatches). The two or three individuals then perform an analysis, looking at each mismatched site, and agree upon a final validation class. (If two vegetation types at a specific site appear to be equally prevalent, the validation team is permitted to assign the site two best-fit vegetation types.) Following the validation team’s comparative analysis of vegetation assignments, the data are entered into a database and compared to the mappers’ vegetation assignments. Agreements and disagreements between the map and validation classes are identified, and a contingency table is produced. This document presents the AA processes/results for Pools 13 and La Grange, as well as the validation process/results for Pools 13 and 26 and Open River South.

Associations Between Latent Classes of Interpersonal Polyvictimization and Polyperpetration and Sexual Risk Behaviors Among Young Pregnant Couples: A Dyadic Analysis.

PubMed

Willie, Tiara; Kershaw, Trace S

2018-05-24

Interpersonal violence victimization and perpetration have been associated with sexual risk behaviors among adolescents and young adults, but research is lacking on: (1) how patterns of interpersonal polyvictimization and polyperpetration are associated with sexual risk among young pregnant couples, and (2) how individual and partner experiences of violence differentially impact sexual risk. The current analyses used baseline data from a longitudinal study that followed 296 pregnant young couples from pregnancy to 12 months postpartum. Couples were recruited at obstetrics and gynecology clinics, and an ultrasound clinic in the U.S. Latent class analysis identified subgroups based on polyvictimization and polyperpetration. Using the Actor-Partner Interdependence Model, path analyses assessed actor-partner effects of class membership on sexual risk. Three latent classes were used for women: Class 1: Polyvictim-Polyperpetrator; Class 2: Nonvictim-Nonperpetrator; and Class 3: Community and Prior IPV Victim. Four latent classes were used for men: Class 1: Community and Prior IPV Victim; Class 2: Polyvictim-Nonpartner Perpetrator; Class 3: Prior IPV and Peer Victim; and Class 4: Nonvictim-Nonperpetrator. Path analyses revealed that females in Class 2 and their male partners had higher condom use than females in Class 3. Males in Class 2 had more sexual partners than males in Class 1. Among nonmonogamous couples, males in Class 2 were less likely to be involved with a female partner reporting unprotected sex than males in Class 1. Among nonmonogamous couples, females in Class 2 had more acts of unprotected sex than females in Class 1. Males in Class 4 were less likely to have concurrent sexual partners compared to males in Class 1. Risk reduction interventions should address both victimization and perpetration. Additional research is needed to understand how mechanisms driving differential sexual risk by patterns of interpersonal polyvictimization and polyperpetration.

Evaluation of objective structured clinical examination for advanced orthodontic education 12 years after introduction.

PubMed

Fields, Henry W; Kim, Do-Gyoon; Jeon, Minjeong; Firestone, Allen R; Sun, Zongyang; Shanker, Shiva; Mercado, Ana M; Deguchi, Toru; Vig, Katherine W L

2017-05-01

Advanced education programs in orthodontics must ensure student competency in clinical skills. An objective structure clinical examination has been used in 1 program for over a decade. The results were analyzed cross-sectionally and longitudinally to provide insights regarding the achievement of competency, student growth, question difficulty, question discrimination, and question predictive ability. In this study, we analyzed 218 (82 first-year, 68 second-year, and 68 third-year classes) scores of each station from 85 orthodontic students. The grades originated from 13 stations and were collected anonymously for 12 consecutive years during the first 2 decades of the 2000s. The stations tested knowledge and skills regarding dental relationships, analyzing a cephalometric tracing, performing a diagnostic skill, identifying cephalometric points, bracket placement, placing first-order and second-order bends, forming a loop, placing accentuated third-order bends, identifying problems and planning mixed dentition treatment, identifying problems and planning adolescent dentition treatment, identifying problems and planning nongrowing skeletal treatment, superimposing cephalometric tracings, and interpreting cephalometric superimpositions. Results were evaluated using multivariate analysis of variance, chi-square tests, and latent growth analysis. The multivariate analysis of variance showed that all stations except 3 (analyzing a cephalometric tracing, forming a loop, and identifying cephalometric points) had significantly lower mean scores for the first-year student class than the second- and third-year classes (P <0.028); scores between the second- and third-year student classes were not significantly different (P >0.108). The chi-square analysis of the distribution of the number of noncompetent item responses decreased from the first to the second years (P <0.0003), from the second to the third years (P <0.0042), and from the first to the third years (P <0.00003). The latent growth analysis showed a wide range of difficulty and discrimination between questions. It also showed continuous growth for some areas and the ability of 6 questions to predict competency at greater than the 80% level. Objective structure clinical examinations can provide a method of evaluating student performance and curriculum impact over time, but cross-sectional and longitudinal analyses of the results may not be complementary. Significant learning appears to occur during all years of a 3-year program. Valuable questions were both easy and difficult, discriminating and not discriminating, and came from all domains: diagnostic, technical, and evaluation/synthesis. Copyright © 2017 American Association of Orthodontists. Published by Elsevier Inc. All rights reserved.

Modeling Optimal Cutoffs for the Brazilian Household Food Insecurity Measurement Scale in a Nationwide Representative Sample.

PubMed

Interlenghi, Gabriela S; Reichenheim, Michael E; Segall-Corrêa, Ana M; Pérez-Escamilla, Rafael; Moraes, Claudia L; Salles-Costa, Rosana

2017-07-01

Background: This is the second part of a model-based approach to examine the suitability of the current cutoffs applied to the raw score of the Brazilian Household Food Insecurity Measurement Scale [Escala Brasileira de Insegurança Alimentar (EBIA)]. The approach allows identification of homogeneous groups who correspond to severity levels of food insecurity (FI) and, by extension, discriminant cutoffs able to accurately distinguish these groups. Objective: This study aims to examine whether the model-based approach for identifying optimal cutoffs first implemented in a local sample is replicated in a countrywide representative sample. Methods: Data were derived from the Brazilian National Household Sample Survey of 2013 ( n = 116,543 households). Latent class factor analysis (LCFA) models from 2 to 5 classes were applied to the scale's items to identify the number of underlying FI latent classes. Next, identification of optimal cutoffs on the overall raw score was ascertained from these identified classes. Analyses were conducted in the aggregate data and by macroregions. Finally, model-based classifications (latent classes and groupings identified thereafter) were contrasted to the traditionally used classification. Results: LCFA identified 4 homogeneous groups with a very high degree of class separation (entropy = 0.934-0.975). The following cutoffs were identified in the aggregate data: between 1 and 2 (1/2), 5 and 6 (5/6), and 10 and 11 (10/11) in households with children and/or adolescents <18 y of age (score range: 0-14), and 1/2, between 4 and 5 (4/5), and between 6 and 7 (6/7) in adult-only households (range: 0-8). With minor variations, the same cutoffs were also identified in the macroregions. Although our findings confirm, in general, the classification currently used, the limit of 1/2 (compared with 0/1) for separating the milder from the baseline category emerged consistently in all analyses. Conclusions: Nationwide findings corroborate previous local evidence that households with an overall score of 1 are more akin to those scoring negative on all items. These results may contribute to guide experts' and policymakers' decisions on the most appropriate EBIA cutoffs. © 2017 American Society for Nutrition.

Excavating the surface-associated and secretory proteome of Mycobacterium leprae for identifying vaccines and diagnostic markers relevant immunodominant epitopes.

PubMed

Rana, Aarti; Thakur, Shweta; Bhardwaj, Nupur; Kumar, Devender; Akhter, Yusuf

2016-12-01

For centuries, Mycobacterium leprae, etiological agent of leprosy, has been afflicting mankind regardless of extensive use of live-attenuated vaccines and antibiotics. Surface-associated and secretory proteins (SASPs) are attractive targets against bacteria. We have integrated biological knowledge with computational approaches and present a proteome-wide identification of SASPs. We also performed computational assignment of immunodominant epitopes as coordinates of prospective antigenic candidates in most important class of SASPs, the outer membrane proteins (OMPs). Exploiting the known protein sequence and structural characteristics shared by the SASPs from bacteria, 17 lipoproteins, 11 secretory and 19 novel OMPs (including 4 essential proteins) were identified in M. leprae As OMPs represent the most exposed antigens on the cell surface, their immunoinformatics analysis showed that the identified 19 OMPs harbor T-cell MHC class I epitopes and class II epitopes against HLA-DR alleles (54), while 15 OMPs present potential T-cell class II epitopes against HLA-DQ alleles (6) and 7 OMPs possess T-cell class II epitopes against HLA-DP alleles (5) of humans. Additionally, 11 M. leprae OMPs were found to have B-cell epitopes and these may be considered as prime candidates for the development of new immunotherapeutics against M. leprae. © FEMS 2016. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Authenticity assessment of banknotes using portable near infrared spectrometer and chemometrics.

PubMed

da Silva Oliveira, Vanessa; Honorato, Ricardo Saldanha; Honorato, Fernanda Araújo; Pereira, Claudete Fernandes

2018-05-01

Spectra recorded using a portable near infrared (NIR) spectrometer, Soft Independent Modeling of Class Analogy (SIMCA) and Linear Discriminant Analysis (LDA) associated to Successive Projections Algorithm (SPA) models were applied to identify counterfeit and authentic Brazilian Real (R$20, R$50 and R$100) banknotes, enabling a simple field analysis. NIR spectra (950-1650nm) were recorded from seven different areas of the banknotes (two with fluorescent ink, one over watermark, three with intaglio printing process and one over the serial numbers with typography printing). SIMCA and SPA-LDA models were built using 1st derivative preprocessed spectral data from one of the intaglio areas. For the SIMCA models, all authentic (300) banknotes were correctly classified and the counterfeits (227) were not classified. For the two classes SPA-LDA models (authentic and counterfeit currencies), all the test samples were correctly classified into their respective class. The number of selected variables by SPA varied from two to nineteen for R$20, R$50 and R$100 currencies. These results show that the use of the portable near-infrared with SIMCA or SPA-LDA models can be a completely effective, fast, and non-destructive way to identify authenticity of banknotes as well as permitting field analysis. Copyright © 2018 Elsevier B.V. All rights reserved.

Latent Classes of Symptoms related to Clinically Depressed Mood in Adolescents.

PubMed

Blom, Eva Henje; Forsman, Mats; Yang, Tony T; Serlachius, Eva; Larsson, Jan-Olov

2014-01-01

The diagnosis of major depressive disorder (MDD), according to the Diagnostic and Statistical Manual of Mental Disorders , is based only on adult symptomatology of depression and not adapted for age and gender. This may contribute to the low diagnostic specificity and validity of adolescent MDD. In this study, we investigated whether latent classes based on symptoms associated with depressed mood could be identified in a sample of adolescents seeking psychiatric care, regardless of traditionally defined diagnostic categories. Self-reports of the Strengths and Difficulties Questionnaire and the Development and Well-Being Assessment were collected consecutively from all new patients between the ages of 13 and 17 years at two psychiatric outpatient clinics in Stockholm, Sweden. Those who reported depressed mood at intake yielded a sample of 21 boys and 156 girls. Latent class analyses were performed for all screening items and for the depression-specific items of the Development and Well-Being Assessment. The symptoms that were reported in association with depressed mood differentiated the adolescents into two classes. One class had moderate emotional severity scores on the Strengths and Difficulties Questionnaire and mainly symptoms that were congruent with the Diagnostic and Statistical Manual of Mental Disorders criteria for MDD. The other class had higher emotional severity scores and similar symptoms to those reported in the first class. However, in addition, this group demonstrated more diverse symptomatology, including vegetative symptoms, suicidal ideation, anxiety, conduct problems, body dysmorphic symptoms, and deliberate vomiting. The classes predicted functional impairment in that the members of the second class showed more functional impairment. The relatively small sample size limited the generalizability of the results of this study, and the amount of items included in the analysis was restricted by the rules of latent class analysis. No conclusions about gender differences between the classes could be could be drawn as a result of the low number of boys included in the study. Two distinct classes were identified among adolescents with depressed mood. The class with highest emotional symptom severity score and the most functional impairment had a more diverse symptomatology that included symptoms that were not congruent with the traditional diagnostic criteria of MDD. However, this additional symptomatology is clinically important to consider. As a result, the clinical usefulness of the Diagnostic and Statistical Manual of Mental Disorders during the diagnostic process of adolescent depression is questioned.

Association between physical activity, participation in Physical Education classes, and social isolation in adolescents.

PubMed

Santos, Simone José dos; Hardman, Carla Menêses; Barros, Simone Storino Honda; Santos da Franca, Carolina; Santos, Carolina da F B F; Barros, Mauro Virgilio Gomes de

2015-01-01

To analyze the association between physical activity, participation in Physical Education classes, and indicators of social isolation among adolescents. This was an epidemiological study based on secondary analysis of data from a representative sample of students (14-19 years) from public high schools (n=4,207). Data were collected through the questionnaire Global School-based Student Health Survey. The independent variables were the level of physical activity and enrollment in Physical Education classes, while the dependent variables were two indicators of social isolation (feeling of loneliness and having few friends). Descriptive and inferential procedures were used in the statistical analysis. Most of the adolescents were classified as insufficiently active (65.1%) and reported not attending Physical Education classes (64.9%). Approximately two in each ten participants reported feeling of loneliness (15.8%) and, in addition, about one in each five adolescents reported have only one friend (19.5%). In the bivariate analysis, a significantly lower proportion of individuals reporting social isolation was observed among adolescents who referred higher enrollment in Physical Education classes. After adjustment for confounding variables, binary logistic regression showed that attending Physical Education classes was identified as a protective factor in relation to the indicator of social isolation 'having few friends,' but only for girls. It was concluded that participation in Physical Education classes is associated with reduced social isolation among female adolescents. Copyright © 2015 Sociedade Brasileira de Pediatria. Published by Elsevier Editora Ltda. All rights reserved.

An Assessment of Worldview-2 Imagery for the Classification Of a Mixed Deciduous Forest

NASA Astrophysics Data System (ADS)

Carter, Nahid

Remote sensing provides a variety of methods for classifying forest communities and can be a valuable tool for the impact assessment of invasive species. The emerald ash borer (Agrilus planipennis) infestation of ash trees (Fraxinus) in the United States has resulted in the mortality of large stands of ash throughout the Northeast. This study assessed the suitability of multi-temporal Worldview-2 multispectral satellite imagery for classifying a mixed deciduous forest in Upstate New York. Training sites were collected using a Global Positioning System (GPS) receiver, with each training site consisting of a single tree of a corresponding class. Six classes were collected; Ash, Maple, Oak, Beech, Evergreen, and Other. Three different classifications were investigated on four data sets. A six class classification (6C), a two class classification consisting of ash and all other classes combined (2C), and a merging of the ash and maple classes for a five class classification (5C). The four data sets included Worldview-2 multispectral data collection from June 2010 (J-WV2) and September 2010 (S-WV2), a layer stacked data set using J-WV2 and S-WV2 (LS-WV2), and a reduced data set (RD-WV2). RD-WV2 was created using a statistical analysis of the processed and unprocessed imagery. Statistical analysis was used to reduce the dimensionality of the data and identify key bands to create a fourth data set (RD-WV2). Overall accuracy varied considerably depending upon the classification type, but results indicated that ash was confused with maple in a majority of the classifications. Ash was most accurately identified using the 2C classification and RD-WV2 data set (81.48%). A combination of the ash and maple classes yielded an accuracy of 89.41%. Future work should focus on separating the ash and maple classifiers by using data sources such as hyperspectral imagery, LiDAR, or extensive forest surveys.

What a Difference a Day Makes: Differences in Initial Abstinence Response During a Smoking Cessation Attempt

PubMed Central

Piper, Megan E.; Vasilenko, Sara A.; Cook, Jessica W.; Lanza, Stephanie T.

2016-01-01

Aims To 1) identify distinct classes of smokers based on quit day withdrawal symptoms and 2) explore the relations between withdrawal classes and demographics, tobacco dependence, treatment, and smoking outcomes. Design Secondary data analysis of participants (N=1504) in a randomized double-blind placebo-controlled multi-site smoking cessation trial who provided ecological momentary assessments of withdrawal symptoms on their quit day. Participants received smoking cessation counseling and were randomized to receive placebo or one of five active pharmacotherapies. Setting Research offices in Madison and Milwaukee, Wisconsin, USA. Participants Adult smokers (N=1236; 58% female, 86% white), recruited from the community via advertisements, who abstained on their quit day. Measurements Demographics and tobacco dependence were assessed at baseline and participants carried palmtop computers to record withdrawal symptoms (craving, negative affect, difficulty concentrating, hunger, and anhedonia) on their quit day. Point-prevalence abstinence and latency to relapse were assessed at Weeks 8 and 26. Findings Latent class analysis identified four withdrawal classes (AIC=70.09): Moderate Withdrawal (64% of sample), High Craving-Anhedonia (8% of sample), Affective Withdrawal (13% of sample) and Hunger (15% of sample). The High Craving-Anhedonia class reported significantly higher dependence (p<0.01), were less likely to have received combination nicotine replacement, reported lower Week 8 abstinence rates, and relapsed sooner than those in the Moderate Withdrawal class (p<0.05). The Affective Withdrawal class reported higher levels of baseline negative affect and lifetime psychopathology (p<0.05) and relapsed more quickly than the Moderate Withdrawal class (p<0.01). Conclusions While the majority of smokers report typical levels of withdrawal symptoms on their quit day, more than one-third report extreme craving or extreme negative affective or extreme hunger responses to initial abstinence. These distinct quit-day withdrawal symptom patterns are related to baseline characteristics, treatment, and cessation success. PMID:27633341

Evaluation of SLAR and thematic mapper MSS data for forest cover mapping using computer-aided analysis techniques

NASA Technical Reports Server (NTRS)

Hoffer, R. M. (Principal Investigator); Knowlton, D. J.; Dean, M. E.

1981-01-01

Supervised and cluster block training statistics were used to analyze the thematic mapper simulation MSS data (both 1979 and 1980 data sets). Cover information classes identified on SAR imagery include: hardwood, pine, mixed pine hardwood, clearcut, pasture, crops, emergent crops, bare soil, urban, and water. Preliminary analysis of the HH and HV polarized SAR data indicate a high variance associated with each information class except for water and bare soil. The large variance for most spectral classes suggests that while the means might be statistically separable, an overlap may exist between the classes which could introduce a significant classification error. The quantitative values of many cover types are much larger on the HV polarization than on the HH, thereby indicating the relative nature of the digitized data values. The mean values of the spectral classes in the areas with larger look angles are greater than the means of the same cover type in other areas having steeper look angles. Difficulty in accurately overlaying the dual polarization of the SAR data was resolved.

Prognostic factors affecting survival after whole brain radiotherapy in patients with brain metastasized lung cancer.

PubMed

Tsakonas, Georgios; Hellman, Fatou; Gubanski, Michael; Friesland, Signe; Tendler, Salomon; Lewensohn, Rolf; Ekman, Simon; de Petris, Luigi

2018-02-01

Whole-brain radiotherapy (WBRT) has been the standard of care for multiple NSCLC brain metastases but due to its toxicity and lack of survival benefit, its use in the palliative setting is being questioned. This was a single institution cohort study including brain metastasized lung cancer patients who received WBRT at Karolinska University Hospital. Information about Recursive Partitioning Analysis (RPA) and Graded Prognostic Assessment (GPA) scores, demographics, histopathological results and received oncological therapy were collected. Predictors of overall survival (OS) from the time of received WBRT were identified by Cox regression analyses. OS between GPA and RPA classes were compared by pairwise log rank test. A subgroup OS analysis was performed stratified by RPA class. The cohort consisted of 280 patients. RPA 1 and 2 classes had better OS compared to class 3, patients with GPA <1.5 points had better OS compared to GPA≥ 1.5 points and age >70 years was associated with worse OS (p< .0001 for all comparisons). In RPA class 2 subgroup analysis GPA ≥1.5 points, age ≤70 years and CNS surgery before salvage WBRT were independent positive prognostic factors. RPA class 3 patients should not receive WBRT, whereas RPA class 1 patients should receive WBRT if clinically indicated. RPA class 2 patients with age ≤70 years and GPA ≥1.5 points should be treated as RPA 1. WBRT should be omitted in RPA 2 patients with age >70. In RPA 2 patients with age ≤70 years and GPA <1.5 points WBRT could be a reasonable option.

Sampling and Analysis of Emerging Pollutants

EPA Science Inventory

Historically, environmental monitoring programs have focused on organic chemicals which are known to resist degradation, bioaccumulate in the fatty tissues of organisms and have a known adverse toxicological effect. The Stockholm Convention identified several classes of chemical...

Comprehensive analysis of MHC class I genes from the U-, S-, and Z-lineages in Atlantic salmon.

PubMed

Lukacs, Morten F; Harstad, Håvard; Bakke, Hege G; Beetz-Sargent, Marianne; McKinnel, Linda; Lubieniecki, Krzysztof P; Koop, Ben F; Grimholt, Unni

2010-03-05

We have previously sequenced more than 500 kb of the duplicated MHC class I regions in Atlantic salmon. In the IA region we identified the loci for the MHC class I gene Sasa-UBA in addition to a soluble MHC class I molecule, Sasa-ULA. A pseudolocus for Sasa-UCA was identified in the nonclassical IB region. Both regions contained genes for antigen presentation, as wells as orthologues to other genes residing in the human MHC region. The genomic localisation of two MHC class I lineages (Z and S) has been resolved. 7 BACs were sequenced using a combination of standard Sanger and 454 sequencing. The new sequence data extended the IA region with 150 kb identifying the location of one Z-lineage locus, ZAA. The IB region was extended with 350 kb including three new Z-lineage loci, ZBA, ZCA and ZDA in addition to a UGA locus. An allelic version of the IB region contained a functional UDA locus in addition to the UCA pseudolocus. Additionally a BAC harbouring two MHC class I genes (UHA) was placed on linkage group 14, while a BAC containing the S-lineage locus SAA (previously known as UAA) was placed on LG10. Gene expression studies showed limited expression range for all class I genes with exception of UBA being dominantly expressed in gut, spleen and gills, and ZAA with high expression in blood. Here we describe the genomic organization of MHC class I loci from the U-, Z-, and S-lineages in Atlantic salmon. Nine of the described class I genes are located in the extension of the duplicated IA and IB regions, while three class I genes are found on two separate linkage groups. The gene organization of the two regions indicates that the IB region is evolving at a different pace than the IA region. Expression profiling, polymorphic content, peptide binding properties and phylogenetic relationship show that Atlantic salmon has only one MHC class Ia gene (UBA), in addition to a multitude of nonclassical MHC class I genes from the U-, S- and Z-lineages.

Psychological features of North Korean female refugees on the MMPI-2: latent profile analysis.

PubMed

Kim, Seong-Hyeon; Kim, Hee Kyung; Lee, Narae

2013-12-01

This study examined the heterogeneity in the Minnesota Multiphasic Personality Inventory-2nd Edition (MMPI-2; Butcher, Dahlstrom, Graham, Tellegen, & Kaemmer, 1989) profiles of North Korean female refugee population (N = 2,163) using latent profile analysis (LPA). The North Korean female refugee sample arrived at Hanawon, South Korea's resettlement center for North Korean refugees in 2008 and 2009 and took the MMPI-2 as part of an initial psychological screen. The analysis, which included the T scores of the 6 validity scales and the 10 standard clinical scales, identified 4 classes with distinctive psychological features: Class 1 (nonclinical), Class 2 (demoralized), Class 3 (somatized), and Class 4 (detached). The 4 covariates entered into the model (age, education, affiliation with a religion, and the number of forced repatriations) impacted the likelihood of belonging to certain classes. As hypothesized, older age, fewer years of education, and more incidents of forced repatriation predicted higher proneness to psychopathology. However, contrary to our expectation, having a religious faith did not emerge as a salient protective factor. The current LPA results revealed distinct heterogeneous subgroups that previous research on the MMPI and MMPI-2 profiles of refugee populations overlooked with the assumption of a homogeneous sample. Clinical implications for the treatment of North Korean female refugees and the limitations of the study are discussed. (c) 2013 APA, all rights reserved.

Patterns of Adolescent Sexual Behavior Predicting Young Adult Sexually Transmitted Infections: A Latent Class Analysis Approach

PubMed Central

Vasilenko, Sara A.; Kugler, Kari C.; Butera, Nicole M.; Lanza, Stephanie T.

2014-01-01

Adolescent sexual behavior is multidimensional, yet most studies of the topic use variable-oriented methods that reduce behaviors to a single dimension. In this study, we used a person-oriented approach to model adolescent sexual behavior comprehensively, using data from the National Longitudinal Study of Adolescent Health. We identified five latent classes of adolescent sexual behavior: Abstinent (39%), Oral Sex (10%), Low-Risk (25%), Multi-Partner Normative (12%), and Multi-Partner Early (13%). Membership in riskier classes of sexual behavior was predicted by substance use and depressive symptoms. Class membership was also associated with young adult STI outcomes although these associations differed by gender. Male adolescents' STI rates increased with membership in classes with more risky behaviors whereas females' rates were consistent among all sexually active classes. These findings demonstrate the advantages of examining adolescent sexuality in a way that emphasizes its complexity. PMID:24449152

Patterns of adolescent sexual behavior predicting young adult sexually transmitted infections: a latent class analysis approach.

PubMed

Vasilenko, Sara A; Kugler, Kari C; Butera, Nicole M; Lanza, Stephanie T

2015-04-01

Adolescent sexual behavior is multidimensional, yet most studies of the topic use variable-oriented methods that reduce behaviors to a single dimension. In this study, we used a person-oriented approach to model adolescent sexual behavior comprehensively, using data from the National Longitudinal Study of Adolescent Health. We identified five latent classes of adolescent sexual behavior: Abstinent (39%), Oral Sex (10%), Low-Risk (25%), Multi-Partner Normative (12%), and Multi-Partner Early (13%). Membership in riskier classes of sexual behavior was predicted by substance use and depressive symptoms. Class membership was also associated with young adult STI outcomes although these associations differed by gender. Male adolescents' STI rates increased with membership in classes with more risky behaviors whereas females' rates were consistent among all sexually active classes. These findings demonstrate the advantages of examining adolescent sexuality in a way that emphasizes its complexity.

Characterization of Lipooligosaccharide-Biosynthetic Loci of Campylobacter jejuni Reveals New Lipooligosaccharide Classes: Evidence of Mosaic Organizations▿ †

PubMed Central

Parker, Craig T.; Gilbert, Michel; Yuki, Nobuhiro; Endtz, Hubert P.; Mandrell, Robert E.

2008-01-01

The lipooligosaccharide (LOS) biosynthesis region is one of the more variable genomic regions between strains of Campylobacter jejuni. Indeed, eight classes of LOS biosynthesis loci have been established previously based on gene content and organization. In this study, we characterize additional classes of LOS biosynthesis loci and analyze various mechanisms that result in changes to LOS structures. To gain further insights into the genomic diversity of C. jejuni LOS biosynthesis region, we sequenced the LOS biosynthesis loci of 15 strains that possessed gene content that was distinct from the eight classes. This analysis identified 11 new classes of LOS loci that exhibited examples of deletions and insertions of genes and cassettes of genes found in other LOS classes or capsular biosynthesis loci leading to mosaic LOS loci. The sequence analysis also revealed both missense mutations leading to “allelic” glycosyltransferases and phase-variable and non-phase-variable gene inactivation by the deletion or insertion of bases. Specifically, we demonstrated that gene inactivation is an important mechanism for altering the LOS structures of strains possessing the same class of LOS biosynthesis locus. Together, these observations suggest that LOS biosynthesis region is a hotspot for genetic exchange and variability, often leading to changes in the LOS produced. PMID:18556784

The Severe 5%: A Latent Class Analysis of the Externalizing Behavior Spectrum in the United States

PubMed Central

Vaughn, Michael G.; DeLisi, Matt; Gunterbh, Tracy; Fu, Qiang; Beaver, Kevin M.; Perron, Brian E.; Howard, Matthew O.

2012-01-01

Objective Criminological research consistently demonstrates that approximately 5% of study populations are comprised of pathological offenders who account for a preponderance of antisocial behavior and violent crime. Unfortunately, there have been no nationally representative epidemiological studies characterizing the severe 5% group. Materials and Methods Data from the 2001–2002 National Epidemiologic Survey on Alcohol and Related Conditions (NESARC), a nationally representative sample of 43,093 non-institutionalized U.S. residents aged 18 years and older were analyzed using latent class analysis to assess sociodemographic, psychiatric, and behavioral characteristics. Results Four-classes of respondents were identified vis-à-vis lifetime externalizing behaviors. A normative class (66.1% of respondents) demonstrated little involvement in antisocial conduct. A low substance use/high antisocial behavior class (20.7% of respondents) and high substance use/moderate antisocial behavior (8.0% of respondents) class evinced diverse externalizing and psychiatric symptoms. Finally, a severe class (5.3% of respondents) was characterized by pathological involvement in more varied and intensive forms of antisocial and externalizing behaviors and extensive psychiatric disturbance. Conclusions The current study is the first nationally representative epidemiological study of criminal careers/externalizing behavior spectrum in the United States and validates the existence of the 5% pathological group demonstrated by prior research. PMID:22942480

Maternal eating disorder and infant diet. A latent class analysis based on the Norwegian Mother and Child Cohort Study (MoBa)

PubMed Central

Torgersen, Leila; Ystrom, Eivind; Siega-Riz, Anna Maria; Berg, Cecilie Knoph; Zerwas, Stephanie; Reichborn-Kjennerud, Ted; Bulik, Cynthia M.

2015-01-01

Knowledge of infant diet and feeding practices among children of mothers with eating disorders is essential to promote healthy eating in these children. This study compared the dietary patterns of 6-month-old children of mothers with anorexia nervosa, bulimia nervosa, binge eating disorder, and eating disorder not otherwise specified - purging subtype, to the diet of children of mothers with no eating disorders. The study was based on 53,879 mothers in the Norwegian Mother and Child Cohort Study (MoBa). Latent class analysis (LCA) was used to identify discrete latent classes of infant diet based on the mothers’ responses to questions about 16 food items. LCA identified five classes, characterized by primarily homemade vegetarian food (4% of the infants in the sample), homemade traditional food (8%), commercial infant cereals (35%), commercial jarred baby food (39%), and a mix of all food groups (11%). We then estimated the association between the different latent dietary classes and maternal eating disorders using a multinomial logistic regression model. Infants of mothers with bulimia nervosa had a lower probability of being in the homemade traditional food class compared to the commercial jarred baby food class, than the referent without an eating disorder (O.R. 0.59; 95% CI 0.36–0.99). Infants of mothers with binge eating disorder had a lower probability of being in the homemade vegetarian class compared to the commercial jarred baby food class, than the referent (O.R. 0.77; 95% CI 0.60–0.99), but only before controlling for relevant confounders. Anorexia nervosa and eating disorder not otherwise specified-purging subtype were not statistically significant associated with any of the dietary classes. These results suggest that in the general population, maternal eating disorders may to some extent influence the child’s diet as early as 6 months after birth; however, the extent to which these differences influence child health and development remain an area for further inquiry. PMID:25453594

Latent classes of childhood poly-victimization and associations with suicidal behavior among adult trauma victims: Moderating role of anger.

PubMed

Charak, Ruby; Byllesby, Brianna M; Roley, Michelle E; Claycomb, Meredith A; Durham, Tory A; Ross, Jana; Armour, Cherie; Elhai, Jon D

2016-12-01

The aims of the present study were first to identify discrete patterns of childhood victimization experiences including crime, child maltreatment, peer/sibling victimization, sexual violence, and witnessing violence among adult trauma victims using latent class analysis; second, to examine the association between class-membership and suicidal behavior, and third to investigate the differential role of dispositional anger on the association between class-membership and suicidal behavior. We hypothesized that those classes with accumulating exposure to different types of childhood victimization (e.g., poly-victimization) would endorse higher suicidal behavior, than the other less severe classes, and those in the most severe class with higher anger trait would have stronger association with suicidal behavior. Respondents were 346 adults (N=346; M age =35.0years; 55.9% female) who had experienced a lifetime traumatic event. Sixty four percent had experienced poly-victimization (four or more victimization experiences) and 38.8% met the cut-off score for suicidal behavior. Three distinct classes emerged namely, the Least victimization (Class 1), the Predominantly crime and sibling/peer victimization (Class 2), and the Poly-victimization (Class 3) classes. Regression analysis controlling for age and gender indicated that only the main effect of anger was significantly associated with suicidal behavior. The interaction term suggested that those in the Poly-victimization class were higher on suicidal behavior as a result of a stronger association between anger and suicidal behavior in contrast to the association found in Class 2. Clinical implications of findings entail imparting anger management skills to facilitate wellbeing among adult with childhood poly-victimization experiences. Copyright © 2016 Elsevier Ltd. All rights reserved.

Matching biomedical ontologies based on formal concept analysis.

PubMed

Zhao, Mengyi; Zhang, Songmao; Li, Weizhuo; Chen, Guowei

2018-03-19

The goal of ontology matching is to identify correspondences between entities from different yet overlapping ontologies so as to facilitate semantic integration, reuse and interoperability. As a well developed mathematical model for analyzing individuals and structuring concepts, Formal Concept Analysis (FCA) has been applied to ontology matching (OM) tasks since the beginning of OM research, whereas ontological knowledge exploited in FCA-based methods is limited. This motivates the study in this paper, i.e., to empower FCA with as much as ontological knowledge as possible for identifying mappings across ontologies. We propose a method based on Formal Concept Analysis to identify and validate mappings across ontologies, including one-to-one mappings, complex mappings and correspondences between object properties. Our method, called FCA-Map, incrementally generates a total of five types of formal contexts and extracts mappings from the lattices derived. First, the token-based formal context describes how class names, labels and synonyms share lexical tokens, leading to lexical mappings (anchors) across ontologies. Second, the relation-based formal context describes how classes are in taxonomic, partonomic and disjoint relationships with the anchors, leading to positive and negative structural evidence for validating the lexical matching. Third, the positive relation-based context can be used to discover structural mappings. Afterwards, the property-based formal context describes how object properties are used in axioms to connect anchor classes across ontologies, leading to property mappings. Last, the restriction-based formal context describes co-occurrence of classes across ontologies in anonymous ancestors of anchors, from which extended structural mappings and complex mappings can be identified. Evaluation on the Anatomy, the Large Biomedical Ontologies, and the Disease and Phenotype track of the 2016 Ontology Alignment Evaluation Initiative campaign demonstrates the effectiveness of FCA-Map and its competitiveness with the top-ranked systems. FCA-Map can achieve a better balance between precision and recall for large-scale domain ontologies through constructing multiple FCA structures, whereas it performs unsatisfactorily for smaller-sized ontologies with less lexical and semantic expressions. Compared with other FCA-based OM systems, the study in this paper is more comprehensive as an attempt to push the envelope of the Formal Concept Analysis formalism in ontology matching tasks. Five types of formal contexts are constructed incrementally, and their derived concept lattices are used to cluster the commonalities among classes at lexical and structural level, respectively. Experiments on large, real-world domain ontologies show promising results and reveal the power of FCA.

Identifying Mechanisms of Teaching Practices: A Study in Swedish Comprehensive Schooling

ERIC Educational Resources Information Center

Reichenberg, Olof

2018-01-01

The aim of this article is to identify the mechanisms behind the occurrence of teaching practices of seatwork and recitation across lessons. The study is based on an analysis of 74 video recorded lessons from 4 school classes in Swedish comprehensive schools during 2013. Firstly, the results suggest that teaching practices such as seatwork…

HLA-typing analysis following allogeneic bone grafting for sinus lifting.

PubMed

Piaia, Marcelo; Bub, Carolina Bonet; Succi, Guilherme de Menezes; Torres, Margareth; Costa, Thiago Henrique; Pinheiro, Fabricio Costa; Napimoga, Marcelo Henrique

2017-03-01

According to the Brazilian Association of Organ Transplants, in 2015, 19,408 bone transplants were performed in Brazil, over 90% by Dental Surgeons. The surgical technique itself has a respectable number of reports regarding its clinical efficacy, as measured by long-term survival of dental implants in grafted areas. Uncertainty remains, however, as to whether fresh frozen grafts from human bone donors remain immunologically innocuous in the body of the host. Six male with no previous medical history of note, including systemic diseases, surgery or blood transfusion were selected. These patients underwent reconstructive procedures (sinus lifting) using fresh frozen human bone from a tissue bank. All patients had venous blood samples collected prior to surgery and 6 months after the procedure. Anti-HLA analysis for the detection of HLA (human leukocyte antigen) antibodies was performed using methods such as the LABScreen PRA Class I and Class II, LABScreen Single Antigen Class I and Class II, Luminex Platform. Reactive individuals to the screening tests (LABScreen PRA) were further investigated to determine the specificity of the antibodies detected (LABScreen Single Antigen) with a cutoff value of median fluorescence intensity ≥500. As a result, it was observed that two patients (33%) were positive in screening tests, one presenting with anti-HLA Class I and II sensitization and the other with anti-HLA class II. The specificity analysis showed that the patients sensitized to HLA class II presented 4 specificities, 3 of which immunologically relevant. In the second individual, 23 specificities were identified, 6 of which immunologically important for HLA class I and 4 specificities for HLA class II, 3 of these were immunologically important. All specificities detected had average fluorescence. These findings are suggestive that sinus-lifting procedures with allogeneic bone can induce immunological sensitization.

Personality and trajectories of posttraumatic psychopathology: A latent change modelling approach.

PubMed

Fletcher, Susan; O'Donnell, Meaghan; Forbes, David

2016-08-01

Survivors of traumatic events may develop a range of psychopathology, across the internalizing and externalizing dimensions of disorder and associated personality traits. However, research into personality-based internalizing and externalizing trauma responses has been limited to cross-sectional investigations of PTSD comorbidity. Personality typologies may present an opportunity to identify and selectively intervene with survivors at risk of posttraumatic disorder. Therefore this study examined whether personality prospectively influences the trajectory of disorder in a broader trauma-exposed sample. During hospitalization for a physical injury, 323 Australian adults completed the Multidimensional Personality Questionnaire-Brief Form and Structured Clinical Interview for DSM-IV, with the latter readministered 3 and 12 months later. Latent profile analysis conducted on baseline personality scores identified subgroups of participants, while latent change modelling examined differences in disorder trajectories. Three classes (internalizing, externalizing, and normal personality) were identified. The internalizing class showed a high risk of developing all disorders. Unexpectedly, however, the normal personality class was not always at lowest risk of disorder. Rather, the externalizing class, while more likely than the normal personality class to develop substance use disorders, were less likely to develop PTSD and depression. Results suggest that personality is an important mechanism in influencing the development and form of psychopathology after trauma, with internalizing and externalizing subtypes identifiable in the early aftermath of injury. These findings suggest that early intervention using a personality-based transdiagnostic approach may be an effective method of predicting and ultimately preventing much of the burden of posttraumatic disorder. Copyright © 2016 Elsevier Ltd. All rights reserved.

Differences in Weight-Related Behavioral Profiles by Sexual Orientation Among College Men: A Latent Class Analysis.

PubMed

VanKim, Nicole A; Erickson, Darin J; Eisenberg, Marla E; Lust, Katherine; Rosser, B R Simon; Laska, Melissa N

2016-11-01

To identify and describe homogenous classes of male college students based on their weight-related behaviors (e.g., eating habits, physical activity, and unhealthy weight control) and to examine differences by sexual orientation. Study design was a cross-sectional sample of 2- and 4-year college students. Study setting was forty-six 2- and 4-year colleges in Minnesota. Study subjects comprised 10,406 college males. Measures were five categories of sexual orientation derived from self-reported sexual identity and behavior (heterosexual, discordant heterosexual [identifies as heterosexual and engages in same-sex sexual behavior], gay, bisexual, and unsure) and nine weight-related behaviors (including measures for eating habits, physical activity, and unhealthy weight control). Latent class models were fit for each of the five sexual orientation groups, using the nine weight-related behaviors. Overall, four classes were identified: "healthier eating habits" (prevalence range, 39.4%-77.3%), "moderate eating habits" (12.0%-30.2%), "unhealthy weight control" (2.6%-30.4%), and "healthier eating habits, more physically active" (35.8%). Heterosexual males exhibited all four patterns, gay and unsure males exhibited four patterns that included variations on the overall classes identified, discordant heterosexual males exhibited two patterns ("healthier eating habits" and "unhealthy weight control"), and bisexual males exhibited three patterns ("healthier eating habits," "moderate eating habits," and "unhealthy weight control"). Findings highlight the need for multibehavioral interventions for discordant heterosexual, gay, bisexual, and unsure college males, particularly around encouraging physical activity and reducing unhealthy weight control behaviors. © 2016 by American Journal of Health Promotion, Inc.

Space: The Final Frontier in the Learning of Science?

ERIC Educational Resources Information Center

Milne, Catherine

2014-01-01

In "Space", relations, and the learning of science", Wolff-Michael Roth and Pei-Ling Hsu use ethnomethodology to explore high school interns learning shopwork and shoptalk in a research lab that is located in a world class facility for water quality analysis. Using interaction analysis they identify how spaces, like a research…

An Analysis of Culturalism in Latino Mental Health: Folk Medicine as a Case in Point.

ERIC Educational Resources Information Center

De La Cancela, Victor; Martinez, Iris Zavala

1983-01-01

Identifies limitations of culturalist perspective often advocated by Latino mental health workers outlines folk healing practices they favor. Notes that culturalist perspective suffers from ahistorical/asocial/static conceptualization, and lacks analysis of class/sex/structural dimensions of so-called cultural expressions. Calls for recognition of…

A Cognitive Task Analysis for Dental Hygiene.

ERIC Educational Resources Information Center

Cameron, Cheryl A.; Beemsterboer, Phyllis L.; Johnson, Lynn A.; Mislevy, Robert J.; Steinberg, Linda S.; Breyer, F. Jay

2000-01-01

As part of the development of a scoring algorithm for a simulation-based dental hygiene initial licensure examination, this effort conducted a task analysis of the dental hygiene domain. Broad classes of behaviors that distinguish along the dental hygiene expert-novice continuum were identified and applied to the design of nine paper-based cases…

Perceived Treatment Needs Among Women With Co-occurring Substance Use Disorders and PTSD.

PubMed

Resko, Stella M; Brown, Suzanne; Mendoza, Natasha S; Crosby, Shantel; González-Prendes, Antonio

2016-01-01

Perception of need is a key factor that influences decisions to seek help and complete treatment for substance use and mental health problems. In the current study, we examine patterns of perceived treatment needs among women with co-occurring substance use disorders and posttraumatic stress disorder (PTSD) and explore how these patterns are associated with demographics, psychosocial variables, and treatment-related factors. Secondary data analysis of the Women and Trauma Study from the National Institute on Drug Abuse's Clinical Trial Network was conducted. The sample included 353 women with co-occurring substance use disorders and PTSD (full or subthreshold) receiving outpatient substance abuse treatment. Latent class analysis was used to examine patterns of perceived treatment need and multinomial logistic regression was used to identify characteristics associated with these patterns. The sample included women between the ages of 18 and 65 (mean = 39.2, SD = 9.3) and was 46% White, 34% African American, and 21% other races/ethnicities. A three-class model representing unique perceptions of treatment needs demonstrated the best fit (Bayesian information criterion = 2101.43; entropy = 0.76; average posterior probabilities ≤ 0.82). Class one reported elevated needs in multiple areas (38%), class two reported low needs (23%), and class three reported substance use and psychological needs (40%). Living with a substance abuser, depression symptoms, recent substance use, and treatment coercion were significantly associated with membership in class 2 (OR = .28, .84, .22, and 2.32, respectively). Other race, being married, depression symptoms, recent substance use, and criminal justice involvement were associated with membership in class 3 (OR = 2.32, 2.32, .94, .42, and 1.69, respectively). Number of treatment sessions attended was not significantly associated with class membership. Results provide insight into how women with co-occurring PTSD and substance use disorders view their treatment needs. While some women reported high levels of self-identified need in other areas (e.g., physical health, employment/financial support, and family or social relationships), others did not identify as having any problems (including substance use or psychological problems). Level of severity and temporal aspects of problems may be significant factors that influence women's perceived need for treatment. This clinical trial is registered at www.clinicaltrials.gov as trial #NCT00078156.

Obesity and Cigarette Smoking: Extending the Link to E cigarette/Vaping Use

PubMed Central

Lanza, H. Isabella; Pittman, Patricia; Batshoun, Jennifer

2017-01-01

Objectives In recent years, electronic tobacco (e-cigarette/vaping) use among young adults has grown exponentially. Given past research linking obesity and cigarette smoking, assessing whether this relationship extends to electronic tobacco use is warranted. The current study examined weight status as a correlate of substance use patterns reflecting electronic tobacco use. Methods Survey data were collected from a convenience sample of 452 (59% female) undergraduates attending a large, public university during the 2015–2016 academic year. Latent class analysis (LCA) was conducted to identify substance use classes and examine weight status as a covariate of class membership. Results LCA analyses identified 4 classes: High Substance Use (19%), Risky Alcohol Use (14%), Cigarette/Electronic Tobacco Use (17%), and Low Substance Use (50%). Both obesity status and greater deviation from one’s group body mass index (BMI) norm were associated with a higher likelihood of belonging to the Cigarette/Electronic Tobacco Use class. Conclusions Findings suggest that electronic tobacco use may fit well into previously established relationships between higher weight status and tobacco use. Future research should examine the longitudinal processes and pathways underlying the relationship between weight status and electronic tobacco use. PMID:28376978

Perceived risk associated with ecstasy use: a latent class analysis approach

PubMed Central

Martins, SS; Carlson, RG; Alexandre, PK; Falck, RS

2011-01-01

This study aims to define categories of perceived health problems among ecstasy users based on observed clustering of their perceptions of ecstasy-related health problems. Data from a community sample of ecstasy users (n=402) aged 18 to 30, in Ohio, was used in this study. Data was analyzed via Latent Class Analysis (LCA) and Regression. This study identified five different subgroups of ecstasy users based on their perceptions of health problems they associated with their ecstasy use. Almost one third of the sample (28.9%) belonged to a class with “low level of perceived problems” (Class 4). About one fourth (25.6%) of the sample (Class 2), had high probabilities of “perceiving problems on sexual-related items”, but generally low or moderate probabilities of perceiving problems in other areas. Roughly one-fifth of the sample (21.1%, Class 1) had moderate probabilities of perceiving ecstasy health-related problems in all areas. A small proportion of respondents (11.9%, Class 5) had high probabilities of reporting “perceived memory and cognitive problems, and of perceiving “ecstasy related-problems in all areas” (12.4%, Class 3). A large proportion of ecstasy users perceive either low or moderate risk associated with their ecstasy use. It is important to further investigate whether lower levels of risk perception are associated with persistence of ecstasy use. PMID:21296504

Classes and continua of hippocampal CA1 inhibitory neurons revealed by single-cell transcriptomics.

PubMed

Harris, Kenneth D; Hochgerner, Hannah; Skene, Nathan G; Magno, Lorenza; Katona, Linda; Bengtsson Gonzales, Carolina; Somogyi, Peter; Kessaris, Nicoletta; Linnarsson, Sten; Hjerling-Leffler, Jens

2018-06-18

Understanding any brain circuit will require a categorization of its constituent neurons. In hippocampal area CA1, at least 23 classes of GABAergic neuron have been proposed to date. However, this list may be incomplete; additionally, it is unclear whether discrete classes are sufficient to describe the diversity of cortical inhibitory neurons or whether continuous modes of variability are also required. We studied the transcriptomes of 3,663 CA1 inhibitory cells, revealing 10 major GABAergic groups that divided into 49 fine-scale clusters. All previously described and several novel cell classes were identified, with three previously described classes unexpectedly found to be identical. A division into discrete classes, however, was not sufficient to describe the diversity of these cells, as continuous variation also occurred between and within classes. Latent factor analysis revealed that a single continuous variable could predict the expression levels of several genes, which correlated similarly with it across multiple cell types. Analysis of the genes correlating with this variable suggested it reflects a range from metabolically highly active faster-spiking cells that proximally target pyramidal cells to slower-spiking cells targeting distal dendrites or interneurons. These results elucidate the complexity of inhibitory neurons in one of the simplest cortical structures and show that characterizing these cells requires continuous modes of variation as well as discrete cell classes.

Nonsuicidal Self-Injury and Suicidal Behavior: A Latent Class Analysis among Young Adults

PubMed Central

Hamza, Chloe A.; Willoughby, Teena

2013-01-01

Although there is a general consensus among researchers that engagement in nonsuicidal self-injury (NSSI) is associated with increased risk for suicidal behavior, little attention has been given to whether suicidal risk varies among individuals engaging in NSSI. To identify individuals with a history of NSSI who are most at risk for suicidal behavior, we examined individual variability in both NSSI and suicidal behavior among a sample of young adults with a history of NSSI (N = 439, Mage = 19.1). Participants completed self-report measures assessing NSSI, suicidal behavior, and psychosocial adjustment (e.g., depressive symptoms, daily hassles). We conducted a latent class analysis using several characteristics of NSSI and suicidal behaviors as class indicators. Three subgroups of individuals were identified: 1) an infrequent NSSI/not high risk for suicidal behavior group, 2) a frequent NSSI/not high risk for suicidal behavior group, and 3) a frequent NSSI/high risk for suicidal behavior group. Follow-up analyses indicated that individuals in the ‘frequent NSSI/high risk for suicidal behavior’ group met the clinical-cut off score for high suicidal risk and reported significantly greater levels of suicidal ideation, attempts, and risk for future suicidal behavior as compared to the other two classes. Thus, this study is the first to identity variability in suicidal risk among individuals engaging in frequent and multiple methods of NSSI. Class 3 was also differentiated by higher levels of psychosocial impairment relative to the other two classes, as well as a comparison group of non-injuring young adults. Results underscore the importance of assessing individual differences in NSSI characteristics, as well as psychosocial impairment, when assessing risk for suicidal behavior. PMID:23544113

Differentiation of functional constipation and constipation predominant irritable bowel syndrome based on Rome III criteria: a population-based study.

PubMed

Koloski, N A; Jones, M; Young, M; Talley, N J

2015-05-01

While the Rome III classification recognises functional constipation (FC) and constipation predominant IBS (IBS-C) as distinct disorders, recent evidence has suggested that these disorders are difficult to separate in clinical practice. To identify whether clinical and lifestyle factors differentiate Rome III-defined IBS-C from FC based on gastrointestinal symptoms and lifestyle characteristics. 3260 people randomly selected from the Australian population returned a postal survey. FC and IBS-C were defined according to Rome III. The first model used logistic regression to differentiate IBS-C from FC based on lifestyle, quality-of-life and psychological characteristics. The second approach was data-driven employing latent class analysis (LCA) to identify naturally occurring clusters in the data considering all symptoms involved in the Rome III criteria for IBS-C and FC. We found n = 206 (6.5%; 95% CI 5.7-7.4%) people met strict Rome III FC whereas n = 109 (3.5%; 95% CI 2.8-4.1%) met strict Rome III IBS-C. The case-control approach indicated that FC patients reported an older age at onset of constipation, were less likely to exercise, had higher mental QoL and less health care seeking than IBS-C. LCA yielded one latent class that was predominantly (75%) FC, while the other class was approximately half IBS-C and half FC. The FC-dominated latent class had clearly lower levels of symptoms used to classify IBS (pain-related symptoms) and was more likely to be male (P = 0.046) but was otherwise similar in distribution of lifestyle factors to the mixed class. The latent class analysis approach suggests a differentiation based more on symptom severity rather than the Rome III view. © 2015 John Wiley & Sons Ltd.

HIV-related sexual risk behavior among African American adolescent girls.

PubMed

Danielson, Carla Kmett; Walsh, Kate; McCauley, Jenna; Ruggiero, Kenneth J; Brown, Jennifer L; Sales, Jessica M; Rose, Eve; Wingood, Gina M; Diclemente, Ralph J

2014-05-01

Latent class analysis (LCA) is a useful statistical tool that can be used to enhance understanding of how various patterns of combined sexual behavior risk factors may confer differential levels of HIV infection risk and to identify subtypes among African American adolescent girls. Data for this analysis is derived from baseline assessments completed prior to randomization in an HIV prevention trial. Participants were African American girls (n=701) aged 14-20 years presenting to sexual health clinics. Girls completed an audio computer-assisted self-interview, which assessed a range of variables regarding sexual history and current and past sexual behavior. Two latent classes were identified with the probability statistics for the two groups in this model being 0.89 and 0.88, respectively. In the final multivariate model, class 1 (the "higher risk" group; n=331) was distinguished by a higher likelihood of >5 lifetime sexual partners, having sex while high on alcohol/drugs, less frequent condom use, and history of sexually transmitted diseases (STDs), when compared with class 2 (the "lower risk" group; n=370). The derived model correctly classified 85.3% of participants into the two groups and accounted for 71% of the variance in the latent HIV-related sexual behavior risk variable. The higher risk class also had worse scores on all hypothesized correlates (e.g., self-esteem, history of sexual assault or physical abuse) relative to the lower risk class. Sexual health clinics represent a unique point of access for HIV-related sexual risk behavior intervention delivery by capitalizing on contact with adolescent girls when they present for services. Four empirically supported risk factors differentiated higher versus lower HIV risk. Replication of these findings is warranted and may offer an empirical basis for parsimonious screening recommendations for girls presenting for sexual healthcare services.

Application of PCA and SIMCA statistical analysis of FT-IR spectra for the classification and identification of different slag types with environmental origin.

PubMed

Stumpe, B; Engel, T; Steinweg, B; Marschner, B

2012-04-03

In the past, different slag materials were often used for landscaping and construction purposes or simply dumped. Nowadays German environmental laws strictly control the use of slags, but there is still a remaining part of 35% which is uncontrolled dumped in landfills. Since some slags have high heavy metal contents and different slag types have typical chemical and physical properties that will influence the risk potential and other characteristics of the deposits, an identification of the slag types is needed. We developed a FT-IR-based statistical method to identify different slags classes. Slags samples were collected at different sites throughout various cities within the industrial Ruhr area. Then, spectra of 35 samples from four different slags classes, ladle furnace (LF), blast furnace (BF), oxygen furnace steel (OF), and zinc furnace slags (ZF), were determined in the mid-infrared region (4000-400 cm(-1)). The spectra data sets were subject to statistical classification methods for the separation of separate spectral data of different slag classes. Principal component analysis (PCA) models for each slag class were developed and further used for soft independent modeling of class analogy (SIMCA). Precise classification of slag samples into four different slag classes were achieved using two different SIMCA models stepwise. At first, SIMCA 1 was used for classification of ZF as well as OF slags over the total spectral range. If no correct classification was found, then the spectrum was analyzed with SIMCA 2 at reduced wavenumbers for the classification of LF as well as BF spectra. As a result, we provide a time- and cost-efficient method based on FT-IR spectroscopy for processing and identifying large numbers of environmental slag samples.

Identifying desertification risk areas using fuzzy membership and geospatial technique - A case study, Kota District, Rajasthan

NASA Astrophysics Data System (ADS)

Dasgupta, Arunima; Sastry, K. L. N.; Dhinwa, P. S.; Rathore, V. S.; Nathawat, M. S.

2013-08-01

Desertification risk assessment is important in order to take proper measures for its prevention. Present research intends to identify the areas under risk of desertification along with their severity in terms of degradation in natural parameters. An integrated model with fuzzy membership analysis, fuzzy rule-based inference system and geospatial techniques was adopted, including five specific natural parameters namely slope, soil pH, soil depth, soil texture and NDVI. Individual parameters were classified according to their deviation from mean. Membership of each individual values to be in a certain class was derived using the normal probability density function of that class. Thus if a single class of a single parameter is with mean μ and standard deviation σ, the values falling beyond μ + 2 σ and μ - 2 σ are not representing that class, but a transitional zone between two subsequent classes. These are the most important areas in terms of degradation, as they have the lowest probability to be in a certain class, hence highest probability to be extended or narrowed down in next or previous class respectively. Eventually, these are the values which can be easily altered, under extrogenic influences, hence are identified as risk areas. The overall desertification risk is derived by incorporating the different risk severity of each parameter using fuzzy rule-based interference system in GIS environment. Multicriteria based geo-statistics are applied to locate the areas under different severity of desertification risk. The study revealed that in Kota, various anthropogenic pressures are accelerating land deterioration, coupled with natural erosive forces. Four major sources of desertification in Kota are, namely Gully and Ravine erosion, inappropriate mining practices, growing urbanization and random deforestation.

Can the dissociative PTSD subtype be identified across two distinct trauma samples meeting caseness for PTSD?

PubMed

Hansen, Maj; Műllerová, Jana; Elklit, Ask; Armour, Cherie

2016-08-01

For over a century, the occurrence of dissociative symptoms in connection to traumatic exposure has been acknowledged in the scientific literature. Recently, the importance of dissociation has also been recognized in the long-term traumatic response within the DSM-5 nomenclature. Several studies have confirmed the existence of the dissociative posttraumatic stress disorder (PTSD) subtype. However, there is a lack of studies investigating latent profiles of PTSD solely in victims with PTSD. This study investigates the possible presence of PTSD subtypes using latent class analysis (LCA) across two distinct trauma samples meeting caseness for DSM-5 PTSD based on self-reports (N = 787). Moreover, we assessed if a number of risk factors resulted in an increased probability of membership in a dissociative compared with a non-dissociative PTSD class. The results of LCA revealed a two-class solution with two highly symptomatic classes: a dissociative class and a non-dissociative class across both samples. Increased emotion-focused coping increased the probability of individuals being grouped into the dissociative class across both samples. Social support reduced the probability of individuals being grouped into the dissociative class but only in the victims of motor vehicle accidents (MVAs) suffering from whiplash. The results are discussed in light of their clinical implications and suggest that the dissociative subtype can be identified in victims of incest and victims of MVA suffering from whiplash meeting caseness for DSM-5 PTSD.

LC-ESI-MS/MS identification of polar lipids of two thermophilic Anoxybacillus bacteria containing a unique lipid pattern.

PubMed

Rezanka, Tomáš; Kambourova, Margarita; Derekova, Anna; Kolouchová, Irena; Sigler, Karel

2012-07-01

Phospholipids and glycolipids from two recently described species belonging to the thermophilic genus Anoxybacillus were analyzed by liquid chromatography-electrospray tandem mass spectrometry (LC/ESI-MS/MS). Analysis of total lipids from the facultatively anaerobic A. bogrovensis on a HILIC (Hydrophilic Interaction LIquid Chromatography) column succeeded in separating diacyl- and plasmalogen phospholipids. The LC/ESI-MS/MS analysis of the strict aerobe A. rupiensis revealed the presence of different unique polar lipids, predominantly alanyl-, lysyl-, and glucosyl-phosphatidylglycerols and cardiolipins. Each of the classes of polar lipids was then analyzed by means of the ESI-MS/MS and more than 140 molecular species of six lipid classes from A. bogrovensis and nearly 200 molecular species of nine classes of polar lipids from A. rupiensis were identified. Five classes of unidentified polar lipids were detected in both strains. Plasmalogens were thus determined for the first time in a facultatively anaerobic bacterium, i.e. A. bogrovensis.

Fuel spill identification using solid-phase extraction and solid-phase microextraction. 1. Aviation turbine fuels.

PubMed

Lavine, B K; Brzozowski, D M; Ritter, J; Moores, A J; Mayfield, H T

2001-12-01

The water-soluble fraction of aviation jet fuels is examined using solid-phase extraction and solid-phase microextraction. Gas chromatographic profiles of solid-phase extracts and solid-phase microextracts of the water-soluble fraction of kerosene- and nonkerosene-based jet fuels reveal that each jet fuel possesses a unique profile. Pattern recognition analysis reveals fingerprint patterns within the data characteristic of fuel type. By using a novel genetic algorithm (GA) that emulates human pattern recognition through machine learning, it is possible to identify features characteristic of the chromatographic profile of each fuel class. The pattern recognition GA identifies a set of features that optimize the separation of the fuel classes in a plot of the two largest principal components of the data. Because principal components maximize variance, the bulk of the information encoded by the selected features is primarily about the differences between the fuel classes.

Predictors of Patterns of Alcohol-Related Blackouts Over Time in Youth From the Collaborative Study of the Genetics of Alcoholism: The Roles of Genetics and Cannabis

PubMed Central

Schuckit, Marc A.; Smith, Tom L.; Shafir, Alexandra; Clausen, Peyton; Danko, George; Gonçalves, Priscila Dib; Anthenelli, Robert M.; Chan, Grace; Kuperman, Samuel; Hesselbrock, Michie; Hesselbrock, Victor; Kramer, John; Bucholz, Kathleen K.

2017-01-01

Objective: Alcohol-related blackouts (ARBs) are anterograde amnesias related to heavy alcohol intake seen in about 50% of drinkers. Although a major determinant of ARBs relates to blood alcohol concentrations, additional contributions come from genetic vulnerabilities and possible impacts of cannabis use disorders (CUDs). We evaluated relationships of genetics and cannabis use to latent class trajectories of ARBs in 829 subjects from the Collaborative Study of the Genetics of Alcoholism (COGA). Method: The number of ARBs experienced every 2 years from subjects with average ages of 18 to 25 were entered into a latent class growth analysis in Mplus, and resulting class membership was evaluated in light of baseline characteristics, including CUDs. Correlations of number of ARBs across assessments were also compared for sibling pairs versus unrelated subjects. Results: Latent class growth analysis identified ARB-based Classes 1 (consistent low = 42.5%), 2 (moderate low = 28.3%), 3 (moderate high = 22.9%), and 4 (consistent high = 6.3%). A multinomial logistic regression analysis within latent class growth analysis revealed that baseline CUDs related most closely to Classes 3 and 4. The number of ARBs across time correlated .23 for sibling pairs and -.10 for unrelated subjects. Conclusions: Baseline CUDs related to the most severe latent ARB course over time, even when considered along with other trajectory predictors, including baseline alcohol use disorders and maximum number of drinks. Data indicated significant roles for genetic factors for alcohol use disorder patterns over time. Future research is needed to improve understanding of how cannabis adds to the ARB risk and to find genes that contribute to risks for ARBs among drinkers. PMID:27936363

Evaluation of LANDSAT-2 (ERTS) images applied to geologic structures and mineral resources of South America. [Salar de Coposa, Chile and Salar of Uyuni, Bolivia

NASA Technical Reports Server (NTRS)

Carter, W. D. (Principal Investigator); Kowalik, W. S.

1976-01-01

The author has identified the following significant results. The Salar of Coposa is located in northern Chile along the frontier with Bolivia. The surface was divided into six general classes of materials. Analysis of LANDSAT image 1243-14001 by use of interactive multispectral computer (Image 100) enabled accurate repetition of these general classes based on reflectance. The Salar of Uyuni is the largest of the South American evaporite deposits. Using image 1243-13595, and parallel piped computer classification of reflectance units, the Salar was divided into nine classes ranging from deep to shallow water, water over salt, salt saturated with water, and several classes of dry salt.

Latent class profile of psychiatric symptoms and treatment utilization in a sample of patients with co-occurring disorders.

PubMed

Villalobos-Gallegos, Luis; Marín-Navarrete, Rodrigo; Roncero, Calos; González-Cantú, Hugo

2017-01-01

To identify symptom-based subgroups within a sample of patients with co-occurring disorders (CODs) and to analyze intersubgroup differences in mental health services utilization. Two hundred and fifteen patients with COD from an addiction clinic completed the Symptom Checklist 90-Revised. Subgroups were determined using latent class profile analysis. Services utilization data were collected from electronic records during a 3-year span. The five-class model obtained the best fit (Bayesian information criteria [BIC] = 3,546.95; adjusted BIC = 3,363.14; bootstrapped likelihood ratio test p < 0.0001). Differences between classes were quantitative, and groups were labeled according to severity: mild (26%), mild-moderate (28.8%), moderate (18.6%), moderate-severe (17.2%), and severe (9.3%). A significant time by class interaction was obtained (chi-square [χ2[15

Gene expression pattern recognition algorithm inferences to classify samples exposed to chemical agents

NASA Astrophysics Data System (ADS)

Bushel, Pierre R.; Bennett, Lee; Hamadeh, Hisham; Green, James; Ableson, Alan; Misener, Steve; Paules, Richard; Afshari, Cynthia

2002-06-01

We present an analysis of pattern recognition procedures used to predict the classes of samples exposed to pharmacologic agents by comparing gene expression patterns from samples treated with two classes of compounds. Rat liver mRNA samples following exposure for 24 hours with phenobarbital or peroxisome proliferators were analyzed using a 1700 rat cDNA microarray platform. Sets of genes that were consistently differentially expressed in the rat liver samples following treatment were stored in the MicroArray Project System (MAPS) database. MAPS identified 238 genes in common that possessed a low probability (P < 0.01) of being randomly detected as differentially expressed at the 95% confidence level. Hierarchical cluster analysis on the 238 genes clustered specific gene expression profiles that separated samples based on exposure to a particular class of compound.

McIntosh active-region class similarities and suggestions for mergers

NASA Technical Reports Server (NTRS)

Bornmann, P. L.; Kalmbach, D.; Kulhanek, D.

1994-01-01

McIntosh active-region classifications reported during a five-year period were examined to determine similarities among the classes. Two methods were used extensively to determine these similarities. The number of transitions among classes were used to determine the most frequent transitions out of each class, and the alternative classes reported for the same region by different sites were used to establish which classes were neighboring classes. These transition frequencies and neighboring classes were used to identify classes that could be eliminated or merged with other classes. Class similarities were used to investigate the relative importance of several pairs of decisions that occur within a single McIntosh parameter. In particular, the redundancy of parameters in some classes was examined, and the class similarities were used to identify which of these parameters could be eliminated. Infrequently reported classes were also considered, and suggestions for mergers were made when similarities between classes could be identified.

Alcohol marketing in televised English professional football: a frequency analysis.

PubMed

Graham, Andrew; Adams, Jean

2014-01-01

The aim of the study was to explore the frequency of alcohol marketing (both formal commercials and otherwise) in televised top-class English professional football matches. A purposive sample of six broadcasts (total = 1101 min) of televised top-class English club football matches were identified and recorded in full. A customized coding framework was used to identify and categorize all verbal and visual alcohol references in non-commercial broadcasting. The number and the duration of all formal alcohol commercials were also noted. A mean of 111 visual references and 2 verbal references to alcohol per hour of broadcast were identified. Nearly all visual references were to beer products and were primarily simple logos or branding. The majority of verbal alcohol references were related to title-sponsorship of competitions. A total of 17 formal alcohol commercials were identified, accounting for <1% of total broadcast time. Visual alcohol references in televised top-class English football matches are common with an average of nearly two per minute. Verbal references are rare and formal alcohol commercials account for <1% of broadcast time. Restriction of all alcohol sports sponsorship, as seen for tobacco, may be justified.

Librarian instruction-delivery modality preferences for professional continuing education

PubMed Central

Lynn, Valerie A.; Bose, Arpita; Boehmer, Susan J.

2010-01-01

Objectives: Attending professional continuing education (CE) is an important component of librarianship. This research study identified librarians' preferences in delivery modalities of instruction for professional CE. The study also identified influential factors associated with attending CE classes. Methods: Five instruction-delivery modalities and six influential factors were identified for inclusion in an online survey. The survey completed by members of the American Library Association (ALA), Special Libraries Association (SLA), and Medical Library Association (MLA) provided the data for analysis of librarian preferences and influential factors. Results: The majority of respondents were MLA members, followed by ALA and SLA members. Librarians from all three library associations preferred the face-to-face instructional modality. The most influential factor associated with the decision to attend a professional CE class was cost. Conclusions: All five instruction-delivery modalities present useful structures for imparting professional CE. As librarians' experience with different modalities increases and as technology improves, preferences in instruction delivery may shift. But at present, face-to-face remains the most preferred modality. Based on the results of this study, cost was the most influential factor associated with attending a CE class. This may change as additional influential factors are identified and analyzed in future studies. PMID:20098656

Librarian instruction-delivery modality preferences for professional continuing education.

PubMed

Lynn, Valerie A; Bose, Arpita; Boehmer, Susan J

2010-01-01

Attending professional continuing education (CE) is an important component of librarianship. This research study identified librarians' preferences in delivery modalities of instruction for professional CE. The study also identified influential factors associated with attending CE classes. Five instruction-delivery modalities and six influential factors were identified for inclusion in an online survey. The survey completed by members of the American Library Association (ALA), Special Libraries Association (SLA), and Medical Library Association (MLA) provided the data for analysis of librarian preferences and influential factors. The majority of respondents were MLA members, followed by ALA and SLA members. Librarians from all three library associations preferred the face-to-face instructional modality. The most influential factor associated with the decision to attend a professional CE class was cost. All five instruction-delivery modalities present useful structures for imparting professional CE. As librarians' experience with different modalities increases and as technology improves, preferences in instruction delivery may shift. But at present, face-to-face remains the most preferred modality. Based on the results of this study, cost was the most influential factor associated with attending a CE class. This may change as additional influential factors are identified and analyzed in future studies.

Childhood adversity profiles and adult psychopathology in a representative Northern Ireland study.

PubMed

McLafferty, Margaret; Armour, Cherie; McKenna, Aine; O'Neill, Siobhan; Murphy, Sam; Bunting, Brendan

2015-10-01

Childhood adversities are key aetiological factors in the onset and persistence of psychopathology. The aims of this study were to identify childhood adversity profiles, and investigate the relationship between the adversity classes and psychopathology in Northern Ireland. The study utilized data from the Northern Ireland Study of Health and Stress, an epidemiological survey (N=1986), which used the CIDI to examine mental health disorders and associated risk factors. Latent Class Analysis revealed 3 distinct typologies; a low risk class (n=1709; 86%), a poly-adversity class (n=122; 6.1%), and an economic adversity class (n=155; 7.8%). Logistic Regression models revealed that individuals in the economic adversity class had a heightened risk of anxiety and substance disorders, with individuals in the poly-adversity class more likely to have a range of mental health problems and suicidality. The findings indicate the importance of considering the impact of co-occurring childhood adversities when planning treatment, prevention, and intervention programmes. Copyright © 2015 Elsevier Ltd. All rights reserved.

Older Adults' Uptake and Adherence to Exercise Classes: Instructors' Perspectives.

PubMed

Hawley-Hague, Helen; Horne, Maria; Skelton, Dawn A; Todd, Chris

2016-01-01

Exercise classes provide a range of benefits for older adults, but adherence levels are poor. We know little of instructors' experiences of delivering exercise classes to older adults. Semistructured interviews, informed by the Theory of Planned Behavior (TPB), were conducted with instructors (n = 19) delivering multicomponent exercise classes to establish their perspectives on older adults' uptake and adherence to exercise classes. Analysis revealed 'barriers' to uptake related to identity, choice/control, cost, and venue, and 'solutions' included providing choice/control, relating exercise to identity, a personal touch, and social support. Barriers to adherence included unrealistic expectations and social influences, and solutions identified were encouraging commitment, creating social cohesion, and an emphasis on achieving outcomes. Older adults' attitudes were an underlying theme, which related to all barriers and solutions. The instructor plays an important, but not isolated, role in older adults' uptake and adherence to classes. Instructors' perspectives help us to further understand how we can design successful exercise classes.

Use of LANDSAT imagery for wildlife habitat mapping in northeast and east central Alaska

NASA Technical Reports Server (NTRS)

Lent, P. C. (Principal Investigator)

1975-01-01

The author has identified the following significant results. Two scenes were analyzed by applying an iterative cluster analysis to a 2% random data sample and then using the resulting clusters as a training set basis for maximum likelihood classification. Twenty-six and twenty-seven categorical classes, respectively resulted from this process. The majority of classes in each case were quite specific vegetation types; each of these types has specific value as moose habitat.

A Typology of Substance Use Among Pregnant Teens in the United States.

PubMed

Salas-Wright, Christopher P; Vaughn, Michael G; Ugalde, Jenny

2016-03-01

Previous research suggests that, in general, youth who become pregnant during their teenage years tend to report elevated levels of substance use prior to conception and substantial reductions in use during pregnancy. While such studies provide insight into aggregate patterns of adolescent substance use in relation to pregnancy, they may have the unintended effect of masking the behavioral heterogeneity of pregnant teens. The present study employs data from a large, population-based study of adolescents in the United States. We employ latent class analysis to identify subgroups of pregnant adolescents (ages 12-17; n = 810) on the basis of variables measuring the past 12-month and past 30-day use of an extensive array of substances. Results revealed a four class solution. Classes were identified as Class 1: Abstainers (n = 344, 42.47 %), Class 2: Drinkers (n = 303, 37.41 %), Class 3: Alcohol and Cannabis Users (n = 77, 9.51 %), and Class 4: Polydrug Users (n = 86, 10.62 %). The Abstainers class had the highest proportion of Hispanic youth (34.3 %) as well as the highest proportion of youth residing in households earning less than $20,000 per year (44.2 %). The Polydrug Users class had the highest proportion of youth who were in late adolescence (75.58 %), non-Hispanic white (54.65 %), high-income (13.95 %), and in their first trimester of pregnancy (58.33 %). Findings point to an important degree of heterogeneity among pregnant teens and may have implications for the development of interventions designed for youth exhibiting disconcerting patterns of substance use prior to pregnancy.

Exposure to Different Types of Violence and Subsequent Sexual Risk Behavior among Female STD Clinic Patients: A Latent Class Analysis

PubMed Central

Walsh, Jennifer L.; Senn, Theresa E.; Carey, Michael P.

2013-01-01

Objective Diverse forms of violence, including childhood maltreatment (CM), intimate partner violence (IPV), and exposure to community violence (ECV), have been linked separately with sexual risk behaviors. However, few studies have explored multiple experiences of violence simultaneously in relation to sexual risk-taking, especially in women who are most vulnerable to violent experiences. Methods Participants were 481 women (66% African American, Mage = 27 years) attending a publicly-funded STD clinic who reported on their past and current experiences with violence and their current sexual risk behavior. We identified patterns of experience with violence using latent class analysis (LCA) and investigated which combinations of experiences were associated with the riskiest sexual outcomes. Results Four classes of women with different experiences of violence were identified: Low Violence (39%), Predominantly ECV (20%), Predominantly CM (23%), and Multiply Victimized (18%). Women in the Multiply Victimized and Predominantly ECV classes reported the highest levels of sexual risk behavior, including more lifetime sexual partners and a greater likelihood of receiving STD treatment and using substances before sex. Conclusions Women with different patterns of violent experiences differed in their sexual risk behavior. Interventions to reduce sexual risk should address violence against women, focusing on experiences with multiple types of violence and experiences specifically with ECV. Additional research is needed to determine the best ways to address violence in sexual risk reduction interventions. PMID:23626921

Potential vorticity regimes over East Asia during winter

NASA Astrophysics Data System (ADS)

Huang, Wenyu; Chen, Ruyan; Wang, Bin; Wright, Jonathon S.; Yang, Zifan; Ma, Wenqian

2017-02-01

Nine potential vorticity (PV) regimes over East Asia are identified by applying a Self-Organizing Map and Hierarchical Ascendant Classification regime analysis to the daily PV reanalysis fields on the 300 K isentropic surface for December-March 1948-2014. According to the surface temperature anomalies over East Asia, these nine regimes are further classified into three classes, i.e., cold class (three regimes), warm class (four regimes), and neutral class (two regimes). The PV-based East Asian winter monsoon index (EAWMI) is used to study the relationship between PV distributions and the temperature anomalies. The magnitude of cold (warm) anomalies over the land areas of East Asia increases (decreases) quasi-linearly with the EAWMI. Regression analysis reveals that cold temperature anomalies preferentially occur when the EAWMI exceeds a threshold at ˜0.2 PVU (where 1 PVU ≡ 10-6 m2 K kg-1 s-1). PV inversion uncovers the mechanisms behind the relationships between the PV regimes and surface temperature anomalies and reveals that cold (warm) PV regimes are associated with significant warming (cooling) in the upper troposphere and lower stratosphere. On average, cold regimes have longer durations than warm regimes. Interclass transition probabilities are much higher for paths from warm/neutral regimes to cold regimes than for paths from cold regimes to warm/neutral regimes. Besides, intraclass transitions are rare within the warm or neutral regimes. The PV regime analysis provides insight into the causes of severe cold spells over East Asia, with blocking circulation patterns identified as the primary factor in initiating and maintaining these cold spells.

Exploring the relationship between entheseal changes and physical activity: a multivariate study.

PubMed

Milella, Marco; Cardoso, Francisca Alves; Assis, Sandra; Lopreno, Geneviève Perréard; Speith, Nivien

2015-02-01

Analyses of entheseal changes (EC) in identified skeletal samples employ a common research strategy based on the comparison between occupations grouped on the basis of shared biomechanical and/or social characteristics. Results from this approach are often ambiguous, with some studies that point to differences in EC between occupational samples and others failing to provide evidence of behavioral effects on EC. Here we investigate patterns of EC among documented occupations by means of a multivariate analysis of robusticity scores in nine postcranial entheses from a large (N = 372) contemporary skeletal sample including specimens from one Italian and two Portuguese identified collections. Data on entheseal robusticity, analyzed by pooled sides as well by separated sides and levels of asymmetry, are converted in binary scores and then analyzed through nonlinear principal component analysis and hierarchical cluster analysis. Results of these analyses are then used for the classification of occupations. Differences between occupational classes are tested by MANOVA and pairwise Hotelling's test. Results evidence three classes which separate occupations related to farming, physically demanding but generalized occupation, and physically undemanding occupations, with the more consistent differences between the first and the last classes. Our results are consistent with differences in biomechanical behavior between the occupations included in each class, and point to the physical and social specificity of farming activities. On the other hand, our study exemplifies the usefulness of alternative analytical protocols for the investigation of EC, and the value of research designs devoid of a priori assumptions for the test of biocultural hypotheses. Copyright © 2014 Wiley Periodicals, Inc.

Identifying risk factors associated with acquiring measles in an outbreak among age-appropriately vaccinated school children: a cohort analysis.

PubMed

O'Connor, Bernadette; Doyle, Sarah

2018-04-10

A measles outbreak occurred in age-appropriately vaccinated children in a school in a town in the South East of Ireland in September-November 2013. The purpose of this study was to investigate the risk factors associated with catching measles during the outbreak. Ninety-five children (4-5 years) in three classes, in the first year of primary school, were included in the study. Immunisation records on the South East Child Health Information System for first Measles Mumps and Rubella (MMR) vaccine for the 95 children were reviewed. Data collected included age at MMR, date of administration of MMR, MMR brand and batch number, and the General Practice at which MMR was administered. The risk factors analysed included age at vaccination, time of vaccination, class and the GP practice where MMR was administered. Statistical analysis was performed using Epi info 7 and SPSS v24. Thirteen children in the cohort developed measles during the outbreak. All children in the cohort were age-appropriately vaccinated, with one dose of MMR vaccine. Analysis demonstrated statistically significant differences in the relative risk of developing measles according to the class a child was in, and the General Practice at which they were vaccinated. The reason for intense measles activity in one class was not established. Although a concurrent investigation into cold chain and vaccine stock management did not identify a cause for the high relative risk of measles in children vaccinated, recommendations were made for improving cold chain and vaccine stock management in General Practices.

Overeating phenotypes in overweight and obese children.

PubMed

Boutelle, Kerri N; Peterson, Carol B; Crosby, Ross D; Rydell, Sarah A; Zucker, Nancy; Harnack, Lisa

2014-05-01

The purpose of this study was to identify overeating phenotypes and their correlates in overweight and obese children. One hundred and seventeen treatment-seeking overweight and obese 8-12year-old children and their parents completed the study. Children completed an eating in the absence of hunger (EAH) paradigm, the Eating Disorder Examination interview, and measurements of height and weight. Parents and children completed questionnaires that evaluated satiety responsiveness, food responsiveness, negative affect eating, external eating and eating in the absence of hunger. Latent profile analysis was used to identify heterogeneity in overeating phenotypes in the child participants. Latent classes were then compared on measures of demographics, obesity status and nutritional intake. Three latent classes of overweight and obese children were identified: High Satiety Responsive, High Food Responsive, and Moderate Satiety and Food Responsive. Results indicated that the High Food Responsive group had higher BMI and BMI-Z scores compared to the High Satiety Responsive group. No differences were found among classes in demographics or nutritional intake. This study identified three overeating phenotypes, supporting the heterogeneity of eating patterns associated with overweight and obesity in treatment-seeking children. These finding suggest that these phenotypes can potentially be used to identify high risk groups, inform prevention and intervention targets, and develop specific treatments for these behavioral phenotypes. Copyright © 2014. Published by Elsevier Ltd.

Latent classes of polydrug and polyroute use and associations with human immunodeficiency virus risk behaviours and overdose among people who inject drugs in Tijuana, Baja California, Mexico.

PubMed

Meacham, Meredith C; Roesch, Scott C; Strathdee, Steffanie A; Lindsay, Suzanne; Gonzalez-Zuniga, Patricia; Gaines, Tommi L

2018-01-01

Patterns of polydrug use among people who inject drugs (PWID) may be differentially associated with overdose and unique human immunodeficiency virus (HIV) risk factors. Subgroups of PWID in Tijuana, Mexico, were identified based on substances used, route of administration, frequency of use and co-injection indicators. Participants were PWID residing in Tijuana age ≥18 years sampled from 2011 to 2012 who reported injecting an illicit substance in the past month (n = 735). Latent class analysis identified discrete classes of polydrug use characterised by 11 indicators of past 6 months substance use. Multinomial logistic regression examined class membership association with HIV risk behaviours, overdose and other covariates using an automated three-step procedure in mplus to account for classification error. Participants were classified into five subgroups. Two polydrug and polyroute classes were defined by use of multiple substances through several routes of administration and were primarily distinguished from each other by cocaine use (class 1: 5%) or no cocaine use (class 2: 29%). The other classes consisted primarily of injectors: cocaine, methamphetamine and heroin injection (class 3: 4%); methamphetamine and heroin injection (class 4: 10%); and heroin injection (class 5: 52%). Compared with the heroin-only injection class, memberships in the two polydrug and polyroute use classes were independently associated with both HIV injection and sexual risk behaviours. Substance use patterns among PWID in Tijuana are highly heterogeneous, and polydrug and polyroute users are a high-risk subgroup who may require more tailored prevention and treatment interventions. [Meacham MC, Roesch SC, Strathdee SA, Lindsay S, Gonzalez-Zuniga P, Gaines TL. Latent classes of polydrug and polyroute use and associations with human immunodeficiency virus risk behaviours and overdose among people who inject drugs in Tijuana, Baja California, Mexico. Drug Alcohol Rev 2018;37:128-136]. © 2017 Australasian Professional Society on Alcohol and other Drugs.

Distinct Evening Fatigue Profiles in Oncology Outpatients Receiving Chemotherapy

PubMed Central

Wright, Fay; Cooper, Bruce A.; Conley, Yvette P.; Hammer, Marilyn J.; Chen, Lee-May; Paul, Steven M.; Levine, Jon D.; Miaskowski, Christine; Kober, Kord M.

2018-01-01

Background Fatigue is the most common and debilitating symptom experienced by oncology patients during chemotherapy (CTX). Fatigue severity demonstrates a large amount of inter-individual and diurnal variability. Purpose Study purposes were to evaluate for subgroups of patients with distinct evening fatigue profiles and evaluate how these subgroups differed on demographic, clinical, and symptom characteristics. Methods Outpatients with breast, gastrointestinal, gynecological, or lung cancer (n=1332) completed questionnaires six times over two cycles of CTX. Lee Fatigue Scale (LFS) evaluated evening fatigue severity. Latent profile analysis was used to identify distinct evening fatigue profiles. Results Four distinct evening fatigue classes (i.e., Low (14.0%), Moderate (17.2%), High (36.0%), Very High (32.8%)) were identified. Compared to the Low class, patients in the Very High evening fatigue class were: younger, female, had childcare responsibilities, had more years of education, had a lower functional status, had a higher comorbidity burden, and were diagnosed with breast cancer. Patients in the Very High class reported higher levels of depressive symptoms, sleep disturbance, and evening fatigue at enrollment. Conclusions Findings provide new insights into modifiable risk factors for higher levels of evening fatigue. Clinicians can use this information to identify higher risk patients and plan appropriate interventions. PMID:29725554

Caregiver profiles in dementia related to quality of life, depression and perseverance time in the European Actifcare study: the importance of social health.

PubMed

Janssen, Eveline P C J; de Vugt, Marjolein; Köhler, Sebastian; Wolfs, Claire; Kerpershoek, Liselot; Handels, Ron L H; Orrell, Martin; Woods, Bob; Jelley, Hannah; Stephan, Astrid; Bieber, Anja; Meyer, Gabriele; Engedal, Knut; Selbaek, Geir; Wimo, Anders; Irving, Kate; Hopper, Louise; Gonçalves-Pereira, Manuel; Portolani, Elisa; Zanetti, Orazio; Verhey, Frans R

2017-01-01

To identify caregiver profiles of persons with mild to moderate dementia and to investigate differences between identified caregiver profiles, using baseline data of the international prospective cohort study Actifcare. A latent class analysis was used to discover different caregiver profiles based on disease related characteristics of 453 persons with dementia and their 453 informal caregivers. These profiles were compared with regard to quality of life (CarerQoL score), depressive symptoms (HADS-D score) and perseverance time. A 5-class model was identified, with the best Bayesian Information Criterion value, significant likelihood ratio test (p < 0.001), high entropy score (0.88) and substantive interpretability. The classes could be differentiated on two axes: (i) caregivers' age, relationship with persons with dementia, severity of dementia, and (ii) tendency towards stress and difficulty adapting to stress. Classes showed significant differences with all dependent variables, and were labelled 'older low strain', 'older intermediate strain', 'older high strain', 'younger low strain' and 'younger high strain'. Differences exist between types of caregivers that explain variability in quality of life, depressive symptoms and perseverance time. Our findings may give direction for tailored interventions for caregivers of persons with dementia, which may improve social health and reduce health care costs.

General practitioners' knowledge and concern about electromagnetic fields.

PubMed

Berg-Beckhoff, Gabriele; Breckenkamp, Jürgen; Larsen, Pia Veldt; Kowall, Bernd

2014-12-01

Our aim is to explore general practitioners' (GPs') knowledge about EMF, and to assess whether different knowledge structures are related to the GPs' concern about EMF. Random samples were drawn from lists of GPs in Germany in 2008. Knowledge about EMF was assessed by seven items. A latent class analysis was conducted to identify latent structures in GPs' knowledge. Further, the GPs' concern about EMF health risk was measured using a score comprising six items. The association between GPs' concern about EMF and their knowledge was analysed using multiple linear regression. In total 435 (response rate 23.3%) GPs participated in the study. Four groups were identified by the latent class analysis: 43.1% of the GPs gave mainly correct answers; 23.7% of the GPs answered low frequency EMF questions correctly; 19.2% answered only the questions relating EMF with health risks, and 14.0% answered mostly "don't know". There was no association between GPs' latent knowledge classes or between the number of correct answers given by the GPs and their EMF concern, whereas the number of incorrect answers was associated with EMF concern. Greater EMF concern in subjects with more incorrect answers suggests paying particular attention to misconceptions regarding EMF in risk communication.

Linear or linearizable first-order delay ordinary differential equations and their Lie point symmetries

NASA Astrophysics Data System (ADS)

Dorodnitsyn, Vladimir A.; Kozlov, Roman; Meleshko, Sergey V.; Winternitz, Pavel

2018-05-01

A recent article was devoted to an analysis of the symmetry properties of a class of first-order delay ordinary differential systems (DODSs). Here we concentrate on linear DODSs, which have infinite-dimensional Lie point symmetry groups due to the linear superposition principle. Their symmetry algebra always contains a two-dimensional subalgebra realized by linearly connected vector fields. We identify all classes of linear first-order DODSs that have additional symmetries, not due to linearity alone, and we present representatives of each class. These additional symmetries are then used to construct exact analytical particular solutions using symmetry reduction.

Comparing humans and deep learning performance for grading AMD: A study in using universal deep features and transfer learning for automated AMD analysis.

PubMed

Burlina, Philippe; Pacheco, Katia D; Joshi, Neil; Freund, David E; Bressler, Neil M

2017-03-01

When left untreated, age-related macular degeneration (AMD) is the leading cause of vision loss in people over fifty in the US. Currently it is estimated that about eight million US individuals have the intermediate stage of AMD that is often asymptomatic with regard to visual deficit. These individuals are at high risk for progressing to the advanced stage where the often treatable choroidal neovascular form of AMD can occur. Careful monitoring to detect the onset and prompt treatment of the neovascular form as well as dietary supplementation can reduce the risk of vision loss from AMD, therefore, preferred practice patterns recommend identifying individuals with the intermediate stage in a timely manner. Past automated retinal image analysis (ARIA) methods applied on fundus imagery have relied on engineered and hand-designed visual features. We instead detail the novel application of a machine learning approach using deep learning for the problem of ARIA and AMD analysis. We use transfer learning and universal features derived from deep convolutional neural networks (DCNN). We address clinically relevant 4-class, 3-class, and 2-class AMD severity classification problems. Using 5664 color fundus images from the NIH AREDS dataset and DCNN universal features, we obtain values for accuracy for the (4-, 3-, 2-) class classification problem of (79.4%, 81.5%, 93.4%) for machine vs. (75.8%, 85.0%, 95.2%) for physician grading. This study demonstrates the efficacy of machine grading based on deep universal features/transfer learning when applied to ARIA and is a promising step in providing a pre-screener to identify individuals with intermediate AMD and also as a tool that can facilitate identifying such individuals for clinical studies aimed at developing improved therapies. It also demonstrates comparable performance between computer and physician grading. Copyright © 2017 Elsevier Ltd. All rights reserved.

Heterogeneity in the pharmacodynamics of two long-acting methylphenidate formulations for children with attention deficit/hyperactivity disorder. A growth mixture modelling analysis.

PubMed

Sonuga-Barke, Edmund J S; Van Lier, Pol; Swanson, James M; Coghill, David; Wigal, Sharon; Vandenberghe, Mieke; Hatch, Simon

2008-06-01

To use growth mixture modelling (GMM) to identify subgroups of children with attention deficit hyperactive disorder (ADHD) who have different pharmacodynamic profiles in response to extended release methylphenidate as assessed in a laboratory classroom setting. GMM analysis was performed on data from the COMACS study (Comparison of Methylphenidates in the Analog Classroom Setting): a large (n = 184) placebo-controlled cross-over study comparing three treatment conditions in the Laboratory School Protocol (with a 1.5-h cycle of attention and deportment assessments). Two orally administered, once-daily methylphenidate (MPH) bioequivalent formulations [Metadate CD/Equasym XL (MCD-EQXL) and Concerta XL (CON)] were compared with placebo (PLA). Three classes of children with distinct severity profiles in the PLA condition were identified. For both MCD-EQXL and CON, the more severe their PLA symptoms the better, the children's response. However, the formulations produced different growth curves by class, with CON having essentially a flat profile for all three classes (i.e. no effect of PLA severity) and MCD-EQXL showing a marked decline in symptoms immediately post-dosing in the two most severe classes compared with the least severe. Comparison of daily doses matched for immediate-release (IR) components accounted for this difference. The results suggest considerable heterogeneity in the pharmacodynamics of MPH response by children with ADHD. When treatment response for near-equal, bioequivalent daily doses the two formulations was compared, marked differences were seen for children in the most severe classes with a strong curvilinear trajectory for MCD-EQXL related to the greater IR component.

Gradient of association between parenting styles and patterns of drug use in adolescence: A latent class analysis.

PubMed

Valente, Juliana Y; Cogo-Moreira, Hugo; Sanchez, Zila M

2017-11-01

To identify different patterns of drug use in adolescence and determine if these are associated with parenting styles and other sociodemographic factors. A latent class analysis was conducted using baseline data collected in a sample (n=6381) from a randomized controlled trial conducted to evaluate the effectiveness of the #Tamojunto drug-use prevention program, carried out with 7th- and 8th-grade public school students in six Brazilian cities. Three latent classes were identified among the students: 1) abstainers/low users (81.54%), 2) alcohol users/binge drinkers (16.65%), and 3) polydrug users (1.80%). A gradient of inverse association was found between parenting styles (authoritative, authoritarian, and indulgent, with the neglectful style as a reference point) and the classes "alcohol users/binge drinkers" (aOR=0.36, 95%CI=0.27-0.47; aOR=0.56, 95%CI=0.43-0.72; and aOR=0.64, 95%CI=0.51-0.80, respectively) and "polydrug users" (aOR=0.09, 95%CI=0.03-0.24; aOR=0.23, 95%CI=0.11-0.52; and aOR=0.24, 95%CI=0.08-0.74, respectively). Associations were also revealed between the latent classes and the adolescent's age and socioeconomic status. The results suggest that activities to develop parenting skills should be included in school programs aimed at the prevention of drug use among adolescents in order to reduce neglectful practices and thereby possibly reduce drug use among the children. Copyright © 2017. Published by Elsevier B.V.

Dyadic Taxonomy of Delinquent Youth: Exploring Risks and Outcomes Associated With Maternal-Youth Reporting Discrepancies of Delinquent Behavior

ERIC Educational Resources Information Center

Reid, Joan A.; Sullivan, Christopher J.

2016-01-01

Using latent class analysis (LCA), this study identified a dyadic taxonomy of delinquent youth categorized by varying types of maternal-youth reporting discrepancies (i.e., youth < maternal, youth > maternal) within a sample of 764 14-year-old high-risk youth. Four distinctive subgroups of youth were identified, two of which reported more…

Grades and Graduation: A Longitudinal Risk Perspective to Identify Student Dropouts

ERIC Educational Resources Information Center

Bowers, Alex J.

2010-01-01

Studies of student risk of school dropout have shown that present predictors of at-risk status do not accurately identify a large percentage of students who eventually drop out. Through the analysis of the entire Grade 1-12 longitudinal cohort-based grading histories of the class of 2006 for two school districts in the United States, the author…

The Association of Latino Children's Kindergarten School Readiness Profiles with Grade 2-5 Literacy Achievement Trajectories

ERIC Educational Resources Information Center

Quirk, Matthew; Grimm, Ryan; Furlong, Michael J.; Nylund-Gibson, Karen; Swami, Sruthi

2016-01-01

This study utilized latent class analysis (LCA) to identify 5 discernible profiles of Latino children's (N = 1,253) social-emotional, physical, and cognitive school readiness at the time of kindergarten entry. In addition, a growth mixture modeling (GMM) approach was used to identify 3 unique literacy achievement trajectories, across Grades 2-5,…

Alexithymia and psychosocial problems among Italian preadolescents. A latent class analysis approach.

PubMed

Mannarini, Stefania; Balottin, Laura; Toldo, Irene; Gatta, Michela

2016-10-01

The study, conducted on Italian preadolscents aged 11 to 13 belonging to the general population, aims to investigate the relationship between the emotional functioning, namely, alexithymia, and the risk of developing behavioral and emotional problems measured using the Strength and Difficulty Questionnaire. The latent class analysis approach allowed to identify two latent variables, accounting for the internalizing (emotional symptoms and difficulties in emotional awareness) and for the externalizing problems (conduct problems and hyperactivity, problematic relationships with peers, poor prosocial behaviors and externally oriented thinking). The two latent variables featured two latent classes: the difficulty in dealing with problems and the strength to face problems that was representative of most of the healthy participants with specific gender differences. Along with the analysis of psychopathological behaviors, the study of resilience and strengths can prove to be a key step in order to develop valuable preventive approaches to tackle psychiatric disorders. © 2016 Scandinavian Psychological Associations and John Wiley & Sons Ltd.

Exploratory Mediation Analysis via Regularization

PubMed Central

Serang, Sarfaraz; Jacobucci, Ross; Brimhall, Kim C.; Grimm, Kevin J.

2017-01-01

Exploratory mediation analysis refers to a class of methods used to identify a set of potential mediators of a process of interest. Despite its exploratory nature, conventional approaches are rooted in confirmatory traditions, and as such have limitations in exploratory contexts. We propose a two-stage approach called exploratory mediation analysis via regularization (XMed) to better address these concerns. We demonstrate that this approach is able to correctly identify mediators more often than conventional approaches and that its estimates are unbiased. Finally, this approach is illustrated through an empirical example examining the relationship between college acceptance and enrollment. PMID:29225454

The effectiveness and cost-effectiveness of diversion and aftercare programmes for offenders using class A drugs: a systematic review and economic evaluation.

PubMed

Hayhurst, Karen P; Leitner, Maria; Davies, Linda; Flentje, Rachel; Millar, Tim; Jones, Andrew; King, Carlene; Donmall, Michael; Farrell, Michael; Fazel, Seena; Harris, Rochelle; Hickman, Matthew; Lennox, Charlotte; Mayet, Soraya; Senior, Jane; Shaw, Jennifer

2015-01-01

The societal costs of problematic class A drug use in England and Wales exceed £15B; drug-related crime accounts for almost 90% of costs. Diversion plus treatment and/or aftercare programmes may reduce drug-related crime and costs. To assess the effectiveness and cost-effectiveness of diversion and aftercare for class A drug-using offenders, compared with no diversion. Adult class A drug-using offenders diverted to treatment or an aftercare programme for their drug use. Programmes to identify and divert problematic drug users to treatment (voluntary, court mandated or monitored services) at any point within the criminal justice system (CJS). Aftercare follows diversion and treatment, excluding care following prison or non-diversionary drug treatment. Thirty-three electronic databases and government online resources were searched for studies published between January 1985 and January 2012, including MEDLINE, PsycINFO and ISI Web of Science. Bibliographies of identified studies were screened. The UK Drug Data Warehouse, the UK Drug Treatment Outcomes Research Study and published statistics and reports provided data for the economic evaluation. Included studies evaluated diversion in adult class A drug-using offenders, in contact with the CJS. The main outcomes were drug use and offending behaviour, and these were pooled using meta-analysis. The economic review included full economic evaluations for adult opiate and/or crack, or powder, cocaine users. An economic decision analytic model, estimated incremental costs per unit of outcome gained by diversion and aftercare, over a 12-month time horizon. The perspectives included the CJS, NHS, social care providers and offenders. Probabilistic sensitivity analysis and one-way sensitivity analysis explored variance in parameter estimates, longer time horizons and structural uncertainty. Sixteen studies met the effectiveness review inclusion criteria, characterised by poor methodological quality, with modest sample sizes, high attrition rates, retrospective data collection, limited follow-up, no random allocation and publication bias. Most study samples comprised US methamphetamine users. Limited meta-analysis was possible, indicating a potential small impact of diversion interventions on reducing drug use [odds ratio (OR) 1.68, 95% confidence interval (CI) 1.12 to 2.53 for reduced primary drug use, and OR 2.60, 95% CI 1.70 to 3.98 for reduced use of other drugs]. The cost-effectiveness review did not identify any relevant studies. The economic evaluation indicated high uncertainty because of variance in data estimates and limitations in the model design. The primary analysis was unclear whether or not diversion was cost-effective. The sensitivity analyses indicated some scenarios where diversion may be cost-effective. Nearly all participants (99.6%) in the effectiveness review were American (Californian) methamphetamine users, limiting transfer of conclusions to the UK. Data and methodological limitations mean it is unclear whether or not diversion is effective or cost-effective. High-quality evidence for the effectiveness and cost-effectiveness of diversion schemes is sparse and does not relate to the UK. Importantly this research identified a range of methodological limitations in existing evidence. These highlight the need for research to conceptualise, define and develop models of diversion programmes and identify a core outcome set. A programme of feasibility, pilot and definitive trials, combined with process evaluation and qualitative research is recommended to assess the effectiveness and cost-effectiveness of diversionary interventions in class A drug-using offenders. The National Institute for Health Research Health Technology Assessment programme.

Prevalence of and Factors Associated With Minimal Hepatic Encephalopathy in Patients With Cirrhosis of Liver.

PubMed

Bale, Abhijith; Pai, C Ganesh; Shetty, Shiran; Balaraju, Girisha; Shetty, Anurag

2018-06-01

Minimal hepatic encephalopathy (MHE), though highly prevalent, is a frequently underdiagnosed complication of cirrhosis of the liver. Because lack of time is reported as the major reason for non-testing, identifying patients at high risk of MHE would help in targeting them for screening. We aimed to determine the factors associated with MHE to help identify patient subgroups with a higher risk of MHE for targeted screening. Patients with cirrhosis of liver presenting between April 2015 and November 2016 were included. Those with a Psychometric Hepatic Encephalopathy Score (PHES) of ≤-5 points on psychometric testing were diagnosed to have MHE. Various demographic, clinical and laboratory parameters were included in a univariate and later multiple logistic regression models. Of the 180 (male = 166, 92.2%) patients included 94 (52.2%) had MHE. Though serum albumin, serum total bilirubin, serum aspartate aminotransferase, international normalized ration, Child-Turcotte-Pugh and Model-For-End-Stage-Liver-Disease scores were significant on univariate analysis, only CTP score was found to be significantly associated with MHE ( P  = 0.002) on multivariate analysis. A higher CTP class was associated with a higher risk of the presence of MHE. The Odds ratio for having MHE was higher with CTP classes of B ( P  ≤ 0.001) and C ( P  ≤ 0.001) compared to class A. MHE is a common complication in patients with cirrhosis of liver and higher CTP scores independently predict the presence of MHE. Patients with CTP class B and C have a higher risk of suffering from MHE than CTP class A. Screening of patients in CTP class B and C is likely to increase the MHE detection rates while saving time, although select CTP class A patients may also need screening in view of public safety or poor quality of life.

Intimate partner violence against low-income women in Mexico City and associations with work-related disruptions: a latent class analysis using cross-sectional data.

PubMed

Gupta, Jhumka; Willie, Tiara C; Harris, Courtney; Campos, Paola Abril; Falb, Kathryn L; Garcia Moreno, Claudia; Diaz Olavarrieta, Claudia; Okechukwu, Cassandra A

2018-03-07

Disrupting women's employment is a strategy that abusive partners could use to prevent women from maintaining economic independence and stability. Yet, few studies have investigated disruptions in employment among victims of intimate partner violence (IPV) in low-income and middle-income countries. Moreover, even fewer have sought to identify which female victims of IPV are most vulnerable to such disruptions. Using baseline data from 947 women in Mexico City enrolled in a randomised controlled trial, multilevel latent class analysis (LCA) was used to classify women based on their reported IPV experiences. Furthermore, multilevel logistic regression analyses were performed on a subsample of women reporting current work (n=572) to investigate associations between LCA membership and IPV-related employment disruptions. Overall, 40.6% of women who were working at the time of the survey reported some form of work-related disruption due to IPV. LCA identified four distinct classes of IPV experiences: Low Physical and Sexual Violence (39.1%); High Sexual and Low Physical Violence class (9.6%); High Physical and Low Sexual Violence and Injuries (36.5%); High Physical and Sexual Violence and Injuries (14.8%). Compared with women in the Low Physical and Sexual Violence class, women in the High Physical and Sexual Violence and Injuries class and women in the High Physical and Low Sexual Violence and Injuries class were at greater risk of work disruption (adjusted relative risk (ARR) 2.44, 95% CI 1.80 to 3.29; ARR 2.05, 95% CI 1.56 to 2.70, respectively). No other statistically significant associations emerged. IPV, and specific patterns of IPV experiences, must be considered both in work settings and, more broadly, by economic development programmes. NCT01661504. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2018. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

Social Anxiety Disorder and Social Skills: A Critical Review of the Literature

ERIC Educational Resources Information Center

Angelico, Antonio Paulo; Crippa, Jose Alexandre S.; Loureiro, Sonia Regina

2013-01-01

The objective of this article is to present a critical analysis of the research outlines used in empirical studies published between the years 2000 and March of 2007 about social anxiety disorder and its associations with social skills. Seventeen papers were identified and grouped into two classes for analysis, namely: Characterization of Social…

Lipoprotein lipase S447X variant associated with VLDL, LDL and HDL diameter clustering in the MetS

USDA-ARS?s Scientific Manuscript database

Previous analysis clustered 1,238 individuals from the general population Genetics of Lipid Lowering Drugs Network (GOLDN) study by the size of their fasting very low-density, low-density and high-density lipoproteins (VLDL, LDL, HDL) using latent class analysis. From two of the eight identified gro...

Application of Data Envelopment Analysis on the Indicators Contributing to Learning and Teaching Performance

ERIC Educational Resources Information Center

Montoneri, Bernard; Lin, Tyrone T.; Lee, Chia-Chi; Huang, Shio-Ling

2012-01-01

This paper applies data envelopment analysis (DEA) to explore the quantitative relative efficiency of 18 classes of freshmen students studying a course of English conversation in a university of Taiwan from the academic year 2004-2006. A diagram of teaching performance improvement mechanism is designed to identify key performance indicators for…

Use of LANDSAT imagery for wildlife habitat mapping in northeast and eastcentral Alaska

NASA Technical Reports Server (NTRS)

Lent, P. C. (Principal Investigator)

1976-01-01

The author has identified the following significant results. There is strong indication that spatially rare feature classes may be missed in clustering classifications based on 2% random sampling. Therefore, it seems advisable to augment random sampling for cluster analysis with directed sampling of any spatially rare features which are relevant to the analysis.

Population heterogeneity in the salience of multiple risk factors for adolescent delinquency.

PubMed

Lanza, Stephanie T; Cooper, Brittany R; Bray, Bethany C

2014-03-01

To present mixture regression analysis as an alternative to more standard regression analysis for predicting adolescent delinquency. We demonstrate how mixture regression analysis allows for the identification of population subgroups defined by the salience of multiple risk factors. We identified population subgroups (i.e., latent classes) of individuals based on their coefficients in a regression model predicting adolescent delinquency from eight previously established risk indices drawn from the community, school, family, peer, and individual levels. The study included N = 37,763 10th-grade adolescents who participated in the Communities That Care Youth Survey. Standard, zero-inflated, and mixture Poisson and negative binomial regression models were considered. Standard and mixture negative binomial regression models were selected as optimal. The five-class regression model was interpreted based on the class-specific regression coefficients, indicating that risk factors had varying salience across classes of adolescents. Standard regression showed that all risk factors were significantly associated with delinquency. Mixture regression provided more nuanced information, suggesting a unique set of risk factors that were salient for different subgroups of adolescents. Implications for the design of subgroup-specific interventions are discussed. Copyright © 2014 Society for Adolescent Health and Medicine. Published by Elsevier Inc. All rights reserved.

Mapping coastal vegetation, land use and environmental impact from ERTS-1. [Delaware coastal zone

NASA Technical Reports Server (NTRS)

Klemas, V. (Principal Investigator)

1973-01-01

The author has identified the following significant results. Digital analysis of ERTS-1 imagery was used in an attempt to map and inventory the significant ecological communities of Delaware's coastal zone. Eight vegetation and land use discrimination classes were selected: (1) Phragmites communis (giant reed grass); (2) Spartina alterniflora (salt marsh cord grass); (3) Spartina patens (salt marsh hay); (4) shallow water and exposed mud; (5) deep water (greater than 2 m); (6) forest; (7) agriculture; and (8) exposed sand and concrete. Canonical analysis showed the following classification accuracies: Spartina alterniflora, exposed sand, concrete, and forested land - 94% to 100%; shallow water - mud and deep water - 88% and 93% respectively; Phragmites communis 83%; Spartina patens - 52%. Classification accuracy for agriculture was very poor (51%). Limitations of time and available class-memory space resulted in limiting the analysis of agriculture to very gross identification of a class which actually consists of many varied signature classes. Abundant ground truth was available in the form of vegetation maps compiled from color and color infrared photographs. It is believed that with further refinement of training set selection, sufficiently accurate results can be obtained for all categories.

Coupling GIS and multivariate approaches to reference site selection for wadeable stream monitoring.

PubMed

Collier, Kevin J; Haigh, Andy; Kelly, Johlene

2007-04-01

Geographic Information System (GIS) was used to identify potential reference sites for wadeable stream monitoring, and multivariate analyses were applied to test whether invertebrate communities reflected a priori spatial and stream type classifications. We identified potential reference sites in segments with unmodified vegetation cover adjacent to the stream and in >85% of the upstream catchment. We then used various landcover, amenity and environmental impact databases to eliminate sites that had potential anthropogenic influences upstream and that fell into a range of access classes. Each site identified by this process was coded by four dominant stream classes and seven zones, and 119 candidate sites were randomly selected for follow-up assessment. This process yielded 16 sites conforming to reference site criteria using a conditional-probabilistic design, and these were augmented by an additional 14 existing or special interest reference sites. Non-metric multidimensional scaling (NMS) analysis of percent abundance invertebrate data indicated significant differences in community composition among some of the zones and stream classes identified a priori providing qualified support for this framework in reference site selection. NMS analysis of a range standardised condition and diversity metrics derived from the invertebrate data indicated a core set of 26 closely related sites, and four outliers that were considered atypical of reference site conditions and subsequently dropped from the network. Use of GIS linked to stream typology, available spatial databases and aerial photography greatly enhanced the objectivity and efficiency of reference site selection. The multi-metric ordination approach reduced variability among stream types and bias associated with non-random site selection, and provided an effective way to identify representative reference sites.

Detecting trace pesticides in real time using single particle aerosol mass spectrometry.

PubMed

Barker, Zachary; Venkatchalam, Veena; Martin, Audrey N; Farquar, George R; Frank, Matthias

2010-02-28

Pesticides are toxic substances and may cause unintentional harm if improperly used. The ubiquitous nature of pesticides, with frequent use in agriculture and the household, and the potential for harm that pesticides pose to non-target organisms such as wildlife, humans, and pets, demonstrate the need for rapid and effective detection and identification of these compounds. In this study, single particle aerosol mass spectrometry (SPAMS) was used to rapidly detect compounds from four classes of pesticides commonly used in agricultural and household applications. These include permethrin (pyrethroid class), malathion and dichlorvos (organophosphate class), imidacloprid (chloronicotinyl class), and carbaryl (carbamate class). Analytical standards of each compound were diluted and aerosolized using a nebulizer to create particles for analysis in the SPAMS instrument. The resultant dual-polarity time-of-flight mass spectra were then analyzed to identify the characteristic peaks of the compound in each sample. In addition, samples of commercial products containing pesticides, a commercial insecticide spray, containing permethrin, and a canine flea collar, containing carbaryl, were analyzed in their original form using SPAMS without any significant sample preparation. The characteristic mass spectral peaks of the active pesticides in these samples were identified using the mass spectra obtained earlier from the pesticide analytical standards. By successfully identifying pesticides in analytical standards and in commercial products, it is demonstrated herein that the SPAMS system may be capable of pesticide detection in numerous environmental and agricultural situations. Copyright 2010 Elsevier B.V. All rights reserved.

The three latent classes of adolescent delinquency and the risk factors for membership in each class.

PubMed

Hasking, Penelope Anne; Scheier, Lawrence M; Abdallah, Arbi Ben

2011-01-01

This study used latent class analysis to examine subpopulation membership based on self-reports of delinquent behaviors obtained from Australian youth. Three discrete identifiable classes were derived based on 51 indicators of physical violence, property damage, minor infractions, drug use, and social delinquency. One class of youth engaged in primarily rule breaking and norm violations including underage alcohol use, typical of this age period. A second class was more actively delinquent emphasizing drug use, trespassing, and various forms of disobedience. A third class of highly delinquent youth differed from their counterparts by endorsing drug use, thievery that involved stealing money, goods, and cars, property damage, gambling, precocious sexual experiences, involvement with pornographic materials, and fighting. Multinomial logistic regression predicting class membership indicated highly delinquent youth were more likely to be older males, use venting coping strategies, and be fun or novelty seeking compared with rule breakers. Findings are discussed in terms of refining current taxonomic arguments regarding the structure of delinquency and implications for prevention of early-stage antisocial behavior. © 2010 Wiley-Liss, Inc.

Reasons for Vaping Among U.S. 12th Graders.

PubMed

Evans-Polce, Rebecca J; Patrick, Megan E; Lanza, Stephanie T; Miech, Richard A; O'Malley, Patrick M; Johnston, Lloyd D

2018-04-01

Vaping has recently increased in popularity among adolescents. Little is known about heterogeneity of vapers, particularly in terms of why they vape. Identifying major subgroups of adolescent vapers by reasons for vaping is important to understand adolescent vaping behavior and to identify those most at risk for other substance use. Monitoring Future data from 2015 and 2016 were used in a latent class analysis to identify subgroups of 12th graders based on their endorsement of 10 potential reasons for vaping. Multinomial regression with a latent class outcome was used to predict class membership. Three distinct classes of vapers were identified: adolescents who were (1) Vaping to Experiment (29.4%), (2) Vaping to Replace Cigarettes (7.3%), and (3) Vaping for Taste + Entertainment (63.4%). Vaping only flavors was associated with lower odds of membership and cigarette use was associated with higher odds of membership in the Vaping to Replace Cigarettes subgroup, and marijuana was associated with lower odds of membership in the Vaping to Experiment subgroup, compared with the Vaping for Taste + Entertainment subgroup. This study identified multiple subgroups of vapers based on reasons for vaping. Whereas a small subgroup vaped for reasons related to cigarette use, most adolescent vapers reported vaping for reasons unrelated to cigarette use. There were considerable differences in primary reasons for vaping and risk for traditional cigarette and other substance use, suggesting different intervention strategies may be needed for different subgroups of vapers. Copyright © 2017 The Society for Adolescent Health and Medicine. Published by Elsevier Inc. All rights reserved.

Long-Term Exposure to Ozone and Life Expectancy in the United States, 2002 to 2008

PubMed Central

Li, Chaoyang; Balluz, Lina S.; Vaidyanathan, Ambarish; Wen, Xiao-Jun; Hao, Yongping; Qualters, Judith R.

2016-01-01

Abstract Long-term exposure to ground-level ozone is associated with increased risk of morbidity and mortality. The association remains uncertain between long-term exposure to ozone and life expectancy. We assessed the associations between seasonal mean daily 8-hour maximum (8-hr max) ozone concentrations measured during the ozone monitoring seasons and life expectancy at birth in 3109 counties of the conterminous U.S. during 2002 to 2008. We used latent class growth analysis to identify latent classes of counties that had distinct mean levels and rates of change in ozone concentrations over the 7-year period and used linear regression analysis to determine differences in life expectancy by ozone levels. We identified 3 classes of counties with distinct seasonal mean daily 8-hr max ozone concentrations and rates of change. When compared with the counties with the lowest ozone concentrations, the counties with the highest ozone concentrations had 1.7- and 1.4-year lower mean life expectancy in males and females (both P < 0.0001), respectively. The associations remained statistically significant after controlling for potential confounding effects of seasonal mean PM2.5 concentrations and other selected environmental, demographic, socio-economic, and health-related factors (both P < 0.0001). A 5 ppb higher ozone concentration was associated with 0.25 year lower life expectancy in males (95% CI: −0.30 to −0.19) and 0.21 year in females (95% CI: −0.25 to −0.17). We identified 3 classes of counties with distinct mean levels and rates of change in ozone concentrations. Our findings suggest that long-term exposure to a higher ozone concentration may be associated with a lower life expectancy. PMID:26886595

Risk-taking behaviors and subgrouping of suicide in Iran: A latent class analysis of national registries data.

PubMed

Hajebi, Ahmad; Abbasi-Ghahramanloo, Abbas; Hashemian, Seyed Sepehr; Khatibi, Seyed Reza; Ghasemzade, Masomeh; Khodadost, Mahmoud

2017-09-01

Suicide is one the most important public health problem which is rapidly growing concerns. The aim of this study was to subgroup suicide using LCA method. This cross-sectional study was conducted in Iran based on 66990 records registered in Ministry of Health in 2014. A case report questionnaire in the form of software was used for case registries. Latent class analysis was used to achieve the research objectives. Four latent classes were identified; (a) Non-lethal attempters without a history of psychiatric disorders, (b) Non-lethal attempters with a history of psychiatric disorders, (c) Lethal attempters without a history of psychiatric disorders, (d) Lethal attempters with a history of psychiatric disorders. The probability of completed/an achieved suicide is high in lethal attempter classes. Being male increases the risk of inclusion in lethal attempters' classes (OR = 4.93). Also, being single (OR = 1.16), having an age lower than 25 years (OR = 1.14) and being a rural citizen (OR = 2.36) associate with lethal attempters classes. The males tend to use more violent methods and have more completed suicide. Majority of the individuals are non-lethal attempters who need to be addressed by implementing preventive interventions and mental support provision. Copyright © 2017. Published by Elsevier B.V.

On Identifying Clusters Within the C-type Asteroids of the Sloan Digital Sky Survey

NASA Astrophysics Data System (ADS)

Poole, Renae; Ziffer, J.; Harvell, T.

2012-10-01

We applied AutoClass, a data mining technique based upon Bayesian Classification, to C-group asteroid colors in the Sloan Digital Sky Survey (SDSS). Previous taxonomic studies relied mostly on Principal Component Analysis (PCA) to differentiate asteroids within the C-group (e.g. B, G, F, Ch, Cg and Cb). AutoClass's advantage is that it calculates the most probable classification for us, removing the human factor from this part of the analysis. In our results, AutoClass divided the C-groups into two large classes and six smaller classes. The two large classes (n=4974 and 2033, respectively) display distinct regions with some overlap in color-vs-color plots. Each cluster's average spectrum is compared to 'typical' spectra of the C-group subtypes as defined by Tholen (1989) and each cluster's members are evaluated for consistency with previous taxonomies. Of the 117 asteroids classified as B-type in previous taxonomies, only 12 were found with SDSS colors that matched our criteria of having less than 0.1 magnitude error in u and 0.05 magnitude error in g, r, i, and z colors. Although this is a relatively small group, 11 of the 12 B-types were placed by AutoClass in the same cluster. By determining the C-group sub-classifications in the large SDSS database, this research furthers our understanding of the stratigraphy and composition of the main-belt.

A Latent Class Analysis of Maternal Depressive Symptoms over 12 Years and Offspring Adjustment in Adolescence

PubMed Central

Campbell, Susan B.; Morgan-Lopez, Antonio A.; Cox, Martha J.; McLoyd, Vonnie C.

2009-01-01

We used data from the NICHD Study of Early Child Care and Youth Development and latent class analysis to model patterns of maternal depressive symptoms from infant age 1 month to the transition to adolescence (age 12), and then examined adolescent adjustment at age 15 as a function of the course and severity of maternal symptoms. We identified five latent classes of symptoms in these 1357 women while also taking into account sociodemographic measures: never depressed; stable subclinical; early-decreasing; moderately elevated; chronic. Women with few symptoms were more likely to be married, better educated, and in better physical health than women with more elevated symptoms. Family size and whether the pregnancy was planned also differentiated among classes. At age 15, adolescents whose mothers were in the chronic, elevated, and stable subclinical latent classes reported more internalizing and externalizing problems and acknowledged engaging in more risky behavior than did children of never-depressed mothers. Latent class differences in self-reported loneliness and dysphoria were also found. Finally, several significant interactions between sex and latent class suggested that girls whose mothers reported elevated symptoms of depression over time experienced more internalizing distress and dysphoric mood relative to their male counterparts. Discussion focuses on adolescent adjustment, especially among offspring whose mothers report stable symptoms of depression across their childhoods. PMID:19685946

The Interactomic Analysis Reveals Pathogenic Protein Networks in Phomopsis longicolla Underlying Seed Decay of Soybean.

PubMed

Li, Shuxian; Musungu, Bryan; Lightfoot, David; Ji, Pingsheng

2018-01-01

Phomopsis longicolla T. W. Hobbs (syn. Diaporthe longicolla ) is the primary cause of Phomopsis seed decay (PSD) in soybean, Glycine max (L.) Merrill. This disease results in poor seed quality and is one of the most economically important seed diseases in soybean. The objectives of this study were to infer protein-protein interactions (PPI) and to identify conserved global networks and pathogenicity subnetworks in P. longicolla including orthologous pathways for cell signaling and pathogenesis. The interlog method used in the study identified 215,255 unique PPIs among 3,868 proteins. There were 1,414 pathogenicity related genes in P. longicolla identified using the pathogen host interaction (PHI) database. Additionally, 149 plant cell wall degrading enzymes (PCWDE) were detected. The network captured five different classes of carbohydrate degrading enzymes, including the auxiliary activities, carbohydrate esterases, glycoside hydrolases, glycosyl transferases, and carbohydrate binding molecules. From the PPI analysis, novel interacting partners were determined for each of the PCWDE classes. The most predominant class of PCWDE was a group of 60 glycoside hydrolases proteins. The glycoside hydrolase subnetwork was found to be interacting with 1,442 proteins within the network and was among the largest clusters. The orthologous proteins FUS3, HOG, CYP1, SGE1, and the g5566t.1 gene identified in this study could play an important role in pathogenicity. Therefore, the P. longicolla protein interactome (PiPhom) generated in this study can lead to a better understanding of PPIs in soybean pathogens. Furthermore, the PPI may aid in targeting of genes and proteins for further studies of the pathogenicity mechanisms.

The Interactomic Analysis Reveals Pathogenic Protein Networks in Phomopsis longicolla Underlying Seed Decay of Soybean

PubMed Central

Li, Shuxian; Musungu, Bryan; Lightfoot, David; Ji, Pingsheng

2018-01-01

Phomopsis longicolla T. W. Hobbs (syn. Diaporthe longicolla) is the primary cause of Phomopsis seed decay (PSD) in soybean, Glycine max (L.) Merrill. This disease results in poor seed quality and is one of the most economically important seed diseases in soybean. The objectives of this study were to infer protein–protein interactions (PPI) and to identify conserved global networks and pathogenicity subnetworks in P. longicolla including orthologous pathways for cell signaling and pathogenesis. The interlog method used in the study identified 215,255 unique PPIs among 3,868 proteins. There were 1,414 pathogenicity related genes in P. longicolla identified using the pathogen host interaction (PHI) database. Additionally, 149 plant cell wall degrading enzymes (PCWDE) were detected. The network captured five different classes of carbohydrate degrading enzymes, including the auxiliary activities, carbohydrate esterases, glycoside hydrolases, glycosyl transferases, and carbohydrate binding molecules. From the PPI analysis, novel interacting partners were determined for each of the PCWDE classes. The most predominant class of PCWDE was a group of 60 glycoside hydrolases proteins. The glycoside hydrolase subnetwork was found to be interacting with 1,442 proteins within the network and was among the largest clusters. The orthologous proteins FUS3, HOG, CYP1, SGE1, and the g5566t.1 gene identified in this study could play an important role in pathogenicity. Therefore, the P. longicolla protein interactome (PiPhom) generated in this study can lead to a better understanding of PPIs in soybean pathogens. Furthermore, the PPI may aid in targeting of genes and proteins for further studies of the pathogenicity mechanisms. PMID:29666630

Ca-asp bound X-ray structure and inhibition of Bacillus anthracis dihydroorotase (DHOase).

PubMed

Rice, Amy J; Lei, Hao; Santarsiero, Bernard D; Lee, Hyun; Johnson, Michael E

2016-10-01

Dihydroorotase (DHOase) is the third enzyme in the de novo pyrimidine synthesis pathway and is responsible for the reversible cyclization of carbamyl-aspartate (Ca-asp) to dihydroorotate (DHO). DHOase is further divided into two classes based on several structural characteristics, one of which is the length of the flexible catalytic loop that interacts with the substrate, Ca-asp, regulating the enzyme activity. Here, we present the crystal structure of Class I Bacillus anthracis DHOase with Ca-asp in the active site, which shows the peptide backbone of glycine in the shorter loop forming the necessary hydrogen bonds with the substrate, in place of the two threonines found in Class II DHOases. Despite the differences in the catalytic loop, the structure confirms that the key interactions between the substrate and active site residues are similar between Class I and Class II DHOase enzymes, which we further validated by mutagenesis studies. B. anthracis DHOase is also a potential antibacterial drug target. In order to identify prospective inhibitors, we performed high-throughput screening against several libraries using a colorimetric enzymatic assay and an orthogonal fluorescence thermal binding assay. Surface plasmon resonance was used for determining binding affinity (KD) and competition analysis with Ca-asp. Our results highlight that the primary difference between Class I and Class II DHOase is the catalytic loop. We also identify several compounds that can potentially be further optimized as potential B. anthracis inhibitors. Copyright © 2016 Elsevier Ltd. All rights reserved.

Adolescent stalking and risk of violence✩

PubMed Central

Smith-Darden, Joanne P.; Reidy, Dennis E.; Kernsmith, Poco D.

2018-01-01

Stalking perpetration and the associated risk for violence among adolescents has generally been neglected. In the present study, 1236 youth completed surveys assessing empirically established stalking indicators, threats and aggression toward stalking victims, dating violence, and violent delinquency. Latent Profile Analysis identified 3 latent classes of boys: non-perpetrators (NP), hyper-intimate pursuit (HIP), and comprehensive stalking perpetrators (CSP) and, and 2 classes for girls: NP and HIP. Boys in the CSP class were the most violent youth on nearly all indices with boys in the HIP class demonstrating an intermediate level of violence compared to NP boys. Girls in the HIP class were more violent than NP girls on all indices. These findings suggest stalking in adolescence merits attention by violence prevention experts. In particular, juvenile stalking may signify youth at risk for multiple forms of violence perpetrated against multiple types of victims, not just the object of their infatuation. PMID:27641644

A Latent Class Analysis of Family Characteristics Linked to Youth Offending Outcomes.

PubMed

Chng, Grace S; Chu, Chi Meng; Zeng, Gerald; Li, Dongdong; Ting, Ming Hwa

2016-11-01

There were two aims to this study: firstly, to identify family subtypes of Singaporean youth offenders based on eight family variables. Secondly, the associations of these family subtypes with youth offending outcomes were tested. With a sample of 3,744 youth, a latent class analysis was first conducted based on eight family variables. Multivariate analyses and a Cox regression were subsequently performed to analyze the associations of the family classes with age at first arrest, age at first charge, and recidivism. A three-class solution was found to have the best fit to the data: (1) intact functioning families had little family risk; (2) families with criminality had higher probabilities of family criminality, of drug/alcohol abuse, and of being nonintact; and (3) poorly managed families received the poorest parenting and were more likely to be nonintact. Youth offenders from the latter two classes were arrested and charged at younger ages. Additionally, they reoffended at a quicker rate. Family backgrounds matter for youth offending outcomes. Interventions have to be multifaceted and targeted at the family in order to mitigate the risk of young offenders from developing into pathological adult criminals.

Patterns of client behavior with their most recent male escort: an application of latent class analysis.

PubMed

Grov, Christian; Starks, Tyrel J; Wolff, Margaret; Smith, Michael D; Koken, Juline A; Parsons, Jeffrey T

2015-05-01

Research examining interactions between male escorts and clients has relied heavily on data from escorts, men working on the street, and behavioral data aggregated over time. In the current study, 495 clients of male escorts answered questions about sexual behavior with their last hire. Latent class analysis identified four client sets based on these variables. The largest (n = 200, 40.4 %, labeled Typical Escort Encounter) included men endorsing behavior prior research found typical of paid encounters (e.g., oral sex and kissing). The second largest class (n = 157, 31.7 %, Typical Escort Encounter + Erotic Touching) included men reporting similar behaviors, but with greater variety along a spectrum of touching (e.g., mutual masturbation and body worship). Those classed BD/SM and Kink (n = 76, 15.4 %) reported activity along the kink spectrum (BD/SM and role play). Finally, men classed Erotic Massage Encounters (n = 58, 11.7 %) primarily engaged in erotic touch. Clients reporting condomless anal sex were in the minority (12.2 % overall). Escorts who engage in anal sex with clients might be appropriate to train in HIV prevention and other harm reduction practices-adopting the perspective of "sex workers as sex educators."

A Latent Class Analysis of Family Characteristics Linked to Youth Offending Outcomes

PubMed Central

Chu, Chi Meng; Zeng, Gerald; Li, Dongdong; Ting, Ming Hwa

2016-01-01

Objectives: There were two aims to this study: firstly, to identify family subtypes of Singaporean youth offenders based on eight family variables. Secondly, the associations of these family subtypes with youth offending outcomes were tested. Methods: With a sample of 3,744 youth, a latent class analysis was first conducted based on eight family variables. Multivariate analyses and a Cox regression were subsequently performed to analyze the associations of the family classes with age at first arrest, age at first charge, and recidivism. Results: A three-class solution was found to have the best fit to the data: (1) intact functioning families had little family risk; (2) families with criminality had higher probabilities of family criminality, of drug/alcohol abuse, and of being nonintact; and (3) poorly managed families received the poorest parenting and were more likely to be nonintact. Youth offenders from the latter two classes were arrested and charged at younger ages. Additionally, they reoffended at a quicker rate. Conclusions: Family backgrounds matter for youth offending outcomes. Interventions have to be multifaceted and targeted at the family in order to mitigate the risk of young offenders from developing into pathological adult criminals. PMID:28736458

Caffeinated Alcohol Consumption Profiles and Associations with Use Severity and Outcome Expectancies

PubMed Central

Lau-Barraco, Cathy; Milletich, Robert J.; Linden, Ashley N.

2014-01-01

Growing evidence suggests that the consumption of caffeinated alcoholic beverages (CAB) may be riskier than alcohol alone. Efforts to identify patterns of CAB use and the correlates of such drinking patterns could further our conceptualization of and intervention for this health issue. Consequently, the current study aimed to (1) identify distinct classes of CAB users, (2) examine differences between classes on measures of alcohol and caffeine problems, and (3) compare distinct classes of CAB users on caffeine and alcohol outcome expectancies. Participants were 583 (31% men) undergraduate students from a psychology research pool. Latent profile analysis models were derived using four indicators: CAB use quantity, CAB use frequency, alcohol use quantity, and alcohol use frequency. Finding revealed four classes of drinkers: High Alcohol/High CAB (6.00%), High Alcohol/Moderate CAB (5.15%), High Alcohol/Low CAB (22.99%), and Low Alcohol/Low CAB (65.87%). The Low Alcohol/Low CAB class reported the lowest relative levels of caffeine dependence symptoms, caffeine withdrawal, alcohol use problems, and heavy episodic drinking frequency. Further, results indicated differential expectancy endorsement based on use profiles. CAB users in the High Alcohol/Low CAB class endorsed more positive alcohol expectancies than the Low Alcohol/Low CAB group. Those in the High Alcohol/High CAB class endorsed stronger withdrawal symptoms caffeine expectancies than all other classes. Inclusion of substance-specific expectancies into larger theoretical frameworks in future work of CAB use may be beneficial. Findings may inform intervention efforts for those at greatest risk related to CAB consumption. PMID:24210683

Profiles of youth in therapeutic group care: Associations with involuntary psychiatric examinations and readmissions.

PubMed

Yampolskaya, Svetlana; Mowery, Debra

2017-01-01

The study aims were to identify distinct subgroups among youth placed in therapeutic group care (TGC) and to examine the effect of specific constellations of risk factors on readmission to residential mental health care and involuntary psychiatric examination among youth in TGC. Several administrative databases were merged to examine outcomes for youth placed in TGC during fiscal year FY04-05 through FY07-08 (N = 1,009). Latent class analysis (LCA) was conducted. Two classes were identified: youth with multiple needs (Class 1) and lower risk youth (Class 2). Class 1 represented 45% of youth in TGC. Compared with Class 2, these youth had a greater probability of having physical health problems, parents with substance abuse problems, and more extensive histories of maltreatment. Compared with Class 2, youth with multiple needs were almost twice more likely to exhibit self-injurious behavior leading to involuntary mental health examinations, but they were less likely to be readmitted to a residential mental health care of higher level of restrictiveness, such as state inpatient psychiatric programs (SIPPs). Youth placed in Florida TGC represent a heterogeneous population and services tailored to these youth's needs are important. Youth with multiple risk factors would benefit from interventions that would address multiple areas of risk. Lower risk youth (Class 2) would benefit from interventions that would focus on promoting mental health, especially among those who have experienced threatened harm, and providing services and supports necessary for stabilizing these youth in the community. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

Social networks and their influence on drinking behaviors: differences related to cognitive impairment in clients receiving alcoholism treatment.

PubMed

Buckman, Jennifer F; Bates, Marsha E; Cisler, Ron A

2007-09-01

Mechanisms of behavioral change that support positive addiction treatment outcomes in individuals with co-occurring alcohol-use disorders and cognitive impairment remain largely unknown. This article combines person- and variable-centered approaches to examine the interrelated influence of cognitive impairment and social support on stability of and changes in drinking behaviors of Project MATCH (Matching Alcoholism Treatments to Client Heterogeneity) outpatients and aftercare clients (N = 1,726) during the first year after their entry into treatment. Latent class analysis identified homogeneous groups of clients based on the nature and extent of social support for abstinence or drinking at treatment entry. Cognitive impairment and drinking outcomes were compared across latent classes, and the interaction between impairment and social support on drinking outcomes was examined using mixture probit regression. Three independent social support classes (frequent positive, limited positive, and negative) were identified. In the outpatient sample, the frequent positive support class had greater cognitive impairment at treatment entry versus other classes, and extent of impairment significantly predicted improved drinking outcomes in this class. In the aftercare sample, the frequent positive and negative support classes had heightened impairment, yet cognitive impairment significantly predicted relatively poorer drinking outcomes in the negative support class only. Cognitive impairment may increase the influence of the social network on the drinking outcomes of persons receiving treatment for alcohol-use disorders, but more research is needed to understand client characteristics that determine whether this influence is more likely to be manifest as increased salience of helping agents or of hindering agents in the social network.

Caffeinated alcohol consumption profiles and associations with use severity and outcome expectancies.

PubMed

Lau-Barraco, Cathy; Milletich, Robert J; Linden, Ashley N

2014-01-01

Growing evidence suggests that the consumption of caffeinated alcoholic beverages (CAB) may be riskier than alcohol alone. Efforts to identify patterns of CAB use and the correlates of such drinking patterns could further our conceptualization of and intervention for this health issue. Consequently, the current study aimed to (1) identify distinct classes of CAB users, (2) examine differences between classes on measures of alcohol and caffeine problems, and (3) compare distinct classes of CAB users on caffeine and alcohol outcome expectancies. Participants were 583 (31% men) undergraduate students from a psychology research pool. Latent profile analysis models were derived using four indicators: CAB use quantity, CAB use frequency, alcohol use quantity, and alcohol use frequency. Finding revealed four classes of drinkers: High Alcohol/High CAB (6.00%), High Alcohol/Moderate CAB (5.15%), High Alcohol/Low CAB (22.99%), and Low Alcohol/Low CAB (65.87%). The Low Alcohol/Low CAB class reported the lowest relative levels of caffeine dependence symptoms, caffeine withdrawal, alcohol use problems, and heavy episodic drinking frequency. Further, results indicated differential expectancy endorsement based on use profiles. CAB users in the High Alcohol/Low CAB class endorsed more positive alcohol expectancies than the Low Alcohol/Low CAB group. Those in the High Alcohol/High CAB class endorsed stronger withdrawal symptom caffeine expectancies than all other classes. Inclusion of substance-specific expectancies into larger theoretical frameworks in future work of CAB use may be beneficial. Findings may inform intervention efforts for those at greatest risk related to CAB consumption. © 2013.

Patterns of Physical Activity Among Older Adults in New York City

PubMed Central

Mooney, Stephen J.; Joshi, Spruha; Cerdá, Magdalena; Quinn, James W.; Beard, John R.; Kennedy, Gary J.; Benjamin, Ebele O.; Ompad, Danielle C.; Rundle, Andrew G.

2015-01-01

Introduction Little research to date has explored typologies of physical activity among older adults. An understanding of physical activity patterns may help to both determine the health benefits of different types of activity and target interventions to increase activity levels in older adults. This analysis, conducted in 2014, used a latent class analysis approach to characterize patterns of physical activity in a cohort of older adults. Methods A total of 3,497 men and women aged 65–75 years living in New York City completed the Physical Activity Scale for the Elderly (PASE) in 2011. PASE scale items were used to classify subjects into latent classes. Multinomial regression was then used to relate individual and neighborhood characteristics to class membership. Results Five latent classes were identified: “least active,” “walkers,” “domestic/gardening,” “athletic,” and “domestic/gardening athletic.” Individual-level predictors, including more education, higher income, and better self-reported health, were associated with membership in the more-active classes, particularly the athletic classes. Residential characteristics, including living in single-family housing and living in the lower-density boroughs of New York City, were predictive of membership in one of the domestic/gardening classes. Class membership was associated with BMI even after controlling for total PASE score. Conclusions This study suggests that individual and neighborhood characteristics are associated with distinct physical activity patterns in a group of older urban adults. These patterns are associated with body habitus independent of overall activity. PMID:26091927

Media experiences and associations with mental health among the bereaved of the MH17-disaster: A latent profile analysis.

PubMed

van der Velden, Peter G; van der Meulen, Erik; Lenferink, Lonneke I M; Yzermans, Joris C

2018-06-01

Research has shown that the amount of media exposure is associated with post-event mental health problems. Whether bereaved individuals have negative experiences with media reports and whether they are associated with post-event mental health is unclear. This study evaluated these experiences and associations following the MH17-disaster. How media reports were experienced (nine topics, modified MAS), depression symptoms (QIDS-SR), functional problems (WSAS) and event-related coping-self-efficacy (CSE) were assessed about one year post-disaster (May-August 2015) among Dutch bereaved (N = 152). A substantial minority reported negative experiences such as reports made me angry (30%) and made me sad (48%). Latent profile analysis with symptoms, problems and coping self-efficacy as indicators, identified four classes of post-disaster mental health: a Well-functioning (class 1) , 35.1%; a Mild-problems (class 2) , 30.4%; a Sub-clinical (class 3) , 27.0%; and a Clinical (class 4) , 7.4%. Differences in symptoms, problems and coping self-efficacy levels between classes were large according to Cohen's ds. Multivariate logistic regression (MLR) showed that the Clinical (class 4) compared to the Well-functioning (class 1) , more often that felt that reports strongly "embarrassed me," "made me feel sad," "filled me with fear" and "served as a magnifying glass." Future research should assess opportunities and effects of limiting media consumption. © 2018 Tilburg University. Scandinavian Journal of Psychology published by Scandinavian Psychological Associations and John Wiley & Sons Ltd.

Evaluation of reforested areas using LANDSAT imagery

NASA Technical Reports Server (NTRS)

Dejesusparada, N. (Principal Investigator); Filho, P. H.; Shimabukuro, Y. E.

1978-01-01

The author has identified the following significant results. Visual and automatic interpretation of LANDSAT imagery was used to classify the general Pinus and Eucalyptus according to their age and species. A methodology was derived, based on training areas, to define the legend and spectral characteristics of the analyzed classes. Imager analysis of the training areas show that Pinus taeda is separable from the other Pinus species based on JM distance measurement. No difference of JM measurements was observed among Eucalyptus species. Two classes of Eucalyptus were separated according to their ages: those under and those over two years of age. Channel 6 and 7 were suitable for the discrimination of the reforested classes. Channel 5 was efficient to separated reforested areas from nonforested targets in the region. The automatic analysis shows the highest classification precision was obtained for Eucalyptus over two years of age (95.12 percent).

Latent classes of resilience and psychological response among only-child loss parents in China.

PubMed

Wang, An-Ni; Zhang, Wen; Zhang, Jing-Ping; Huang, Fei-Fei; Ye, Man; Yao, Shu-Yu; Luo, Yuan-Hui; Li, Zhi-Hua; Zhang, Jie; Su, Pan

2017-10-01

Only-child loss parents in China recently gained extensive attention as a newly defined social group. Resilience could be a probable solution out of the psychological dilemma. Using a sample of 185 only-child loss people, this study employed latent class analysis (a) to explore whether different classes of resilience could be identified, (b) to determine socio-demographic characteristics of each class, and (c) to compare the depression and the subjective well-being of each class. The results supported a three-class solution, defined as 'high tenacity-strength but moderate optimism class', 'moderate resilience but low self-efficacy class' and 'low tenacity but moderate adaption-dependence class'. Parents with low income and medical insurance of low reimbursement type and without endowment insurance occupied more proportions in the latter two classes. The latter two classes also had a significant higher depression scores and lower subjective well-being scores than high tenacity-strength but moderate optimism class. Future work should care those socio-economically vulnerable bereaved parents, and an elastic economic assistance policy was needed. To develop targeted resilience interventions, the emphasis of high tenacity-strength but moderate optimism class should be the optimism. Moderate resilience but low self-efficacy class should be self-efficacy, and low tenacity but moderate adaption-dependence class should be tenacity. Copyright © 2016 John Wiley & Sons, Ltd.

Longitudinal analysis of latent classes of psychopathology and patterns of class migration in survivors of severe injury.

PubMed

Forbes, David; Nickerson, Angela; Alkemade, Nathan; Bryant, Richard A; Creamer, Mark; Silove, Derrick; McFarlane, Alexander C; Van Hooff, Miranda; Fletcher, Susan L; O'Donnell, Meaghan

2015-09-01

Little research to date has explored the typologies of psychopathology following trauma, beyond development of particular diagnoses such as posttraumatic stress disorder (PTSD). The objective of this study was to determine the longitudinal patterns of these typologies, especially the movement of persons across clusters of psychopathology. In this 6-year longitudinal study, 1,167 hospitalized severe injury patients who were recruited between April 2004-February 2006 were analyzed, with repeated measures at baseline, 3 months, 12 months, and 72 months after injury. All patients met the DSM-IV criterion A1 for PTSD. Structured clinical interviews were used to assess psychiatric disorders at each follow-up point. Latent class analysis and latent transition analysis were applied to assess clusters of individuals determined by psychopathology. The Mini International Neuropsychiatric Interview (MINI) and Clinician-Administered PTSD Scale (CAPS) were employed to complete diagnoses. Four latent classes were identified at each time point: (1) Alcohol/Depression class (3 months, 2.1%; 12 months, 1.3%; and 72 months, 1.1%), (2) Alcohol class (3 months, 3.3%; 12 months, 3.7%; and 72 months, 5.4%), (3) PTSD/Depression class (3 months, 10.3%; 12 months, 11.5%; and 72 months, 6.4%), and (4) No Disorder class (3 months, 84.2%; 12 months, 83.5%; and 72 months, 87.1%). Latent transition analyses conducted across the 2 transition points (12 months and 72 months) found consistently high levels of stability in the No Disorder class (90.9%, 93.0%, respectively) but lower and reducing levels of consistency in the PTSD/Depression class (81.3%, 46.6%), the Alcohol/Depression class (59.7%, 21.5%), and the Alcohol class (61.0%, 36.5%), demonstrating high levels of between-class migration. Despite the array of psychiatric disorders that may develop following severe injury, a 4-class model best described the data with excellent classification certainty. The high levels of migration across classes indicate a complex pattern of psychopathology expression over time. The findings have considerable implications for tailoring multifocused interventions to class type, as well as flexible stepped care models, and for the potential development and delivery of transdiagnostic interventions targeting underlying mechanisms. © Copyright 2015 Physicians Postgraduate Press, Inc.

Novel molecular subtypes of serous and endometrioid ovarian cancer linked to clinical outcome.

PubMed

Tothill, Richard W; Tinker, Anna V; George, Joshy; Brown, Robert; Fox, Stephen B; Lade, Stephen; Johnson, Daryl S; Trivett, Melanie K; Etemadmoghadam, Dariush; Locandro, Bianca; Traficante, Nadia; Fereday, Sian; Hung, Jillian A; Chiew, Yoke-Eng; Haviv, Izhak; Gertig, Dorota; DeFazio, Anna; Bowtell, David D L

2008-08-15

The study aim to identify novel molecular subtypes of ovarian cancer by gene expression profiling with linkage to clinical and pathologic features. Microarray gene expression profiling was done on 285 serous and endometrioid tumors of the ovary, peritoneum, and fallopian tube. K-means clustering was applied to identify robust molecular subtypes. Statistical analysis identified differentially expressed genes, pathways, and gene ontologies. Laser capture microdissection, pathology review, and immunohistochemistry validated the array-based findings. Patient survival within k-means groups was evaluated using Cox proportional hazards models. Class prediction validated k-means groups in an independent dataset. A semisupervised survival analysis of the array data was used to compare against unsupervised clustering results. Optimal clustering of array data identified six molecular subtypes. Two subtypes represented predominantly serous low malignant potential and low-grade endometrioid subtypes, respectively. The remaining four subtypes represented higher grade and advanced stage cancers of serous and endometrioid morphology. A novel subtype of high-grade serous cancers reflected a mesenchymal cell type, characterized by overexpression of N-cadherin and P-cadherin and low expression of differentiation markers, including CA125 and MUC1. A poor prognosis subtype was defined by a reactive stroma gene expression signature, correlating with extensive desmoplasia in such samples. A similar poor prognosis signature could be found using a semisupervised analysis. Each subtype displayed distinct levels and patterns of immune cell infiltration. Class prediction identified similar subtypes in an independent ovarian dataset with similar prognostic trends. Gene expression profiling identified molecular subtypes of ovarian cancer of biological and clinical importance.

An assessment of the cultivated cropland class of NLCD 2006 using a multi-source and multi-criteria approach

USGS Publications Warehouse

Danielson, Patrick; Yang, Limin; Jin, Suming; Homer, Collin G.; Napton, Darrell

2016-01-01

We developed a method that analyzes the quality of the cultivated cropland class mapped in the USA National Land Cover Database (NLCD) 2006. The method integrates multiple geospatial datasets and a Multi Index Integrated Change Analysis (MIICA) change detection method that captures spectral changes to identify the spatial distribution and magnitude of potential commission and omission errors for the cultivated cropland class in NLCD 2006. The majority of the commission and omission errors in NLCD 2006 are in areas where cultivated cropland is not the most dominant land cover type. The errors are primarily attributed to the less accurate training dataset derived from the National Agricultural Statistics Service Cropland Data Layer dataset. In contrast, error rates are low in areas where cultivated cropland is the dominant land cover. Agreement between model-identified commission errors and independently interpreted reference data was high (79%). Agreement was low (40%) for omission error comparison. The majority of the commission errors in the NLCD 2006 cultivated crops were confused with low-intensity developed classes, while the majority of omission errors were from herbaceous and shrub classes. Some errors were caused by inaccurate land cover change from misclassification in NLCD 2001 and the subsequent land cover post-classification process.

The perception of the relationship between environment and health according to data from Italian Behavioural Risk Factor Surveillance System (PASSI).

PubMed

Sampaolo, Letizia; Tommaso, Giulia; Gherardi, Bianca; Carrozzi, Giuliano; Freni Sterrantino, Anna; Ottone, Marta; Goldoni, Carlo Alberto; Bertozzi, Nicoletta; Scaringi, Meri; Bolognesi, Lara; Masocco, Maria; Salmaso, Stefania; Lauriola, Paolo

2017-01-01

"OBJECTIVES: to identify groups of people in relation to the perception of environmental risk and to assess the main characteristics using data collected in the environmental module of the surveillance network Italian Behavioral Risk Factor Surveillance System (PASSI). perceptive profiles were identified using a latent class analysis; later they were included as outcome in multinomial logistic regression models to assess the association between environmental risk perception and demographic, health, socio-economic and behavioural variables. the latent class analysis allowed to split the sample in "worried", "indifferent", and "positive" people. The multinomial logistic regression model showed that the "worried" profile typically includes people of Italian nationality, living in highly urbanized areas, with a high level of education, and with economic difficulties; they pay special attention to their own health and fitness, but they have a negative perception of their own psychophysical state. the application of advanced statistical analysis enable to appraise PASSI data in order to characterize the perception of environmental risk, making the planning of interventions related to risk communication possible. ".

Maltreatment histories of foster youth exiting out-of-home care through emancipation: a latent class analysis.

PubMed

Havlicek, Judy

2014-01-01

Little is known about maltreatment among foster youth transitioning to adulthood. Multiple entries into out-of-home care and unsuccessful attempts at reunification may nevertheless reflect extended exposure to chronic maltreatment and multiple types of victimization. This study used administrative data from the Illinois Department of Children and Family Services to identify all unduplicated allegations of maltreatment in a cohort of 801 foster youth transitioning to adulthood in the state of Illinois. A latent variable modeling approach generated profiles of maltreatment based on substantiated and unsubstantiated reports of maltreatment taken from state administrative data. Four indicators of maltreatment were included in the latent class analysis: multiple types of maltreatment, predominant type of maltreatment, chronicity, and number of different perpetrators. The analysis identified four subpopulations of foster youth in relation to maltreatment. Study findings highlight the heterogeneity of maltreatment in the lives of foster youth transitioning to adulthood and draw attention to a need to raise awareness among service providers to screen for chronic maltreatment and multiple types of victimization. © The Author(s) 2014.

Transcriptome-wide analysis of WRKY transcription factors in wheat and their leaf rust responsive expression profiling.

PubMed

Satapathy, Lopamudra; Singh, Dharmendra; Ranjan, Prashant; Kumar, Dhananjay; Kumar, Manish; Prabhu, Kumble Vinod; Mukhopadhyay, Kunal

2014-12-01

WRKY, a plant-specific transcription factor family, has important roles in pathogen defense, abiotic cues and phytohormone signaling, yet little is known about their roles and molecular mechanism of function in response to rust diseases in wheat. We identified 100 TaWRKY sequences using wheat Expressed Sequence Tag database of which 22 WRKY sequences were novel. Identified proteins were characterized based on their zinc finger motifs and phylogenetic analysis clustered them into six clades consisting of class IIc and class III WRKY proteins. Functional annotation revealed major functions in metabolic and cellular processes in control plants; whereas response to stimuli, signaling and defense in pathogen inoculated plants, their major molecular function being binding to DNA. Tag-based expression analysis of the identified genes revealed differential expression between mock and Puccinia triticina inoculated wheat near isogenic lines. Gene expression was also performed with six rust-related microarray experiments at Gene Expression Omnibus database. TaWRKY10, 15, 17 and 56 were common in both tag-based and microarray-based differential expression analysis and could be representing rust specific WRKY genes. The obtained results will bestow insight into the functional characterization of WRKY transcription factors responsive to leaf rust pathogenesis that can be used as candidate genes in molecular breeding programs to improve biotic stress tolerance in wheat.

Patterns of Chronic Conditions and Their Associations With Behaviors and Quality of Life, 2010

PubMed Central

Mitchell, Sandra A.; Thompson, William W.; Zack, Matthew M.; Reeve, Bryce B.; Cella, David; Smith, Ashley Wilder

2015-01-01

Introduction Co-occurring chronic health conditions elevate the risk of poor health outcomes such as death and disability, are associated with poor quality of life, and magnify the complexities of self-management, care coordination, and treatment planning. This study assessed patterns of both singular and multiple chronic conditions, behavioral risk factors, and quality of life in a population-based sample. Methods In a national survey, adults (n = 4,184) answered questions about the presence of 27 chronic conditions. We used latent class analysis to identify patterns of chronic conditions and to explore associations of latent class membership with sociodemographic characteristics, behavioral risk factors, and health. Results Latent class analyses indicated 4 morbidity profiles: a healthy class (class 1), a class with predominantly physical health conditions (class 2), a class with predominantly mental health conditions (class 3), and a class with both physical and mental health conditions (class 4). Class 4 respondents reported significantly worse physical health and well-being and more days of activity limitation than those in the other latent classes. Class 4 respondents were also more likely to be obese and sedentary, and those with predominantly mental health conditions were most likely to be current smokers. Conclusions Subgroups with distinct patterns of chronic conditions can provide direction for screening and surveillance, guideline development, and the delivery of complex care services. PMID:26679491

The Education of Migrant Children in Michigan: A Policy Analysis Report. JSRI Occasional Paper No. 72. Latino Studies Series.

ERIC Educational Resources Information Center

Tatto, Maria Teresa; Lundstrom-Ndibongo, Virginia; Newman, Brenda E.; Nogle, Sally E.; Sarroub, Loukia K.; Weiler, James M.

A Michigan State University policy analysis class explored migrant education in Michigan through literature reviews and interviews with policymakers, teachers, and migrant children and their families. They identified four areas that need attention. First, people who understand the learning needs of migrant students should be recruited as teachers.…

Genome-Wide Identification, Characterization and Expression Analysis of the Chalcone Synthase Family in Maize

PubMed Central

Han, Yahui; Ding, Ting; Su, Bo; Jiang, Haiyang

2016-01-01

Members of the chalcone synthase (CHS) family participate in the synthesis of a series of secondary metabolites in plants, fungi and bacteria. The metabolites play important roles in protecting land plants against various environmental stresses during the evolutionary process. Our research was conducted on comprehensive investigation of CHS genes in maize (Zea mays L.), including their phylogenetic relationships, gene structures, chromosomal locations and expression analysis. Fourteen CHS genes (ZmCHS01–14) were identified in the genome of maize, representing one of the largest numbers of CHS family members identified in one organism to date. The gene family was classified into four major classes (classes I–IV) based on their phylogenetic relationships. Most of them contained two exons and one intron. The 14 genes were unevenly located on six chromosomes. Two segmental duplication events were identified, which might contribute to the expansion of the maize CHS gene family to some extent. In addition, quantitative real-time PCR and microarray data analyses suggested that ZmCHS genes exhibited various expression patterns, indicating functional diversification of the ZmCHS genes. Our results will contribute to future studies of the complexity of the CHS gene family in maize and provide valuable information for the systematic analysis of the functions of the CHS gene family. PMID:26828478

Information analysis of a spatial database for ecological land classification

NASA Technical Reports Server (NTRS)

Davis, Frank W.; Dozier, Jeff

1990-01-01

An ecological land classification was developed for a complex region in southern California using geographic information system techniques of map overlay and contingency table analysis. Land classes were identified by mutual information analysis of vegetation pattern in relation to other mapped environmental variables. The analysis was weakened by map errors, especially errors in the digital elevation data. Nevertheless, the resulting land classification was ecologically reasonable and performed well when tested with higher quality data from the region.

The gate studies: Assessing the potential of future small general aviation turbine engines

NASA Technical Reports Server (NTRS)

Strack, W. C.

1979-01-01

Four studies were completed that explore the opportunities for future General Aviation turbine engines (GATE) in the 150-1000 SHP class. These studies forecasted the potential impact of advanced technology turbine engines in the post-1988 market, identified important aircraft and missions, desirable engine sizes, engine performance, and cost goals. Parametric evaluations of various engine cycles, configurations, design features, and advanced technology elements defined baseline conceptual engines for each of the important missions identified by the market analysis. Both fixed-wing and helicopter aircraft, and turboshaft, turboprop, and turbofan engines were considered. Sizable performance gains (e.g., 20% SFC decrease), and large engine cost reductions of sufficient magnitude to challenge the reciprocating engine in the 300-500 SHP class were predicted.

Classification and analysis of the Rudaki's Area

NASA Astrophysics Data System (ADS)

Zambon, F.; De sanctis, M.; Capaccioni, F.; Filacchione, G.; Carli, C.; Ammannito, E.; Frigeri, A.

2011-12-01

During the first two MESSENGER flybys the Mercury Dual Imaging System (MDIS) has mapped 90% of the Mercury's surface. An effective way to study the different terrain on planetary surfaces is to apply classification methods. These are based on clustering algorithms and they can be divided in two categories: unsupervised and supervised. The unsupervised classifiers do not require the analyst feedback and the algorithm automatically organizes pixels values into classes. In the supervised method, instead, the analyst must choose the "training area" that define the pixels value of a given class. We applied an unsupervised classifier, ISODATA, to the WAC filter images of the Rudaki's area where several kind of terrain have been identified showing differences in albedo, topography and crater density. ISODATA classifier divides this region in four classes: 1) shadow regions, 2) rough regions, 3) smooth plane, 4) highest reflectance area. ISODATA can not distinguish the high albedo regions from highly reflective illuminated edge of the craters, however the algorithm identify four classes that can be considered different units mainly on the basis of their reflectances at the various wavelengths. Is not possible, instead, to extrapolate compositional information because of the absence of clear spectral features. An additional analysis was made using ISODATA to choose the "training area" for further supervised classifications. These approach would allow, for example, to separate more accurately the edge of the craters from the high reflectance areas and the low reflectance regions from the shadow areas.

Exploring emotional climate in preservice science teacher education

NASA Astrophysics Data System (ADS)

Bellocchi, Alberto; Ritchie, Stephen M.; Tobin, Kenneth; Sandhu, Maryam; Sandhu, Satwant

2013-09-01

Classroom emotional climates (ECs) are interrelated with students' engagement with university courses. Despite growing interest in emotions and EC research, little is known about the ways in which social interactions and different subject matter mediate ECs in preservice science teacher education classes. In this study we investigated the EC and associated classroom interactions in a preservice science teacher education class. We were interested in the ways in which salient classroom interactions were related to the EC during lessons centered on debates about science-based issues (e.g., nuclear energy alternatives). Participants used audience response technology to indicate their perceptions of the EC. Analysis of conversation for salient video clips and analysis of non-verbal conduct (acoustic parameters, body movements, and facial expressions) supplemented EC data. One key contribution that this study makes to preservice science teacher education is to identify the micro-processes of successful and unsuccessful class interactions that were associated with positive and neutral EC. The structure of these interactions can inform the practice of other science educators who wish to produce positive ECs in their classes. The study also extends and explicates the construct of intensity of EC.

Supervised Detection of Anomalous Light Curves in Massive Astronomical Catalogs

NASA Astrophysics Data System (ADS)

Nun, Isadora; Pichara, Karim; Protopapas, Pavlos; Kim, Dae-Won

2014-09-01

The development of synoptic sky surveys has led to a massive amount of data for which resources needed for analysis are beyond human capabilities. In order to process this information and to extract all possible knowledge, machine learning techniques become necessary. Here we present a new methodology to automatically discover unknown variable objects in large astronomical catalogs. With the aim of taking full advantage of all information we have about known objects, our method is based on a supervised algorithm. In particular, we train a random forest classifier using known variability classes of objects and obtain votes for each of the objects in the training set. We then model this voting distribution with a Bayesian network and obtain the joint voting distribution among the training objects. Consequently, an unknown object is considered as an outlier insofar it has a low joint probability. By leaving out one of the classes on the training set, we perform a validity test and show that when the random forest classifier attempts to classify unknown light curves (the class left out), it votes with an unusual distribution among the classes. This rare voting is detected by the Bayesian network and expressed as a low joint probability. Our method is suitable for exploring massive data sets given that the training process is performed offline. We tested our algorithm on 20 million light curves from the MACHO catalog and generated a list of anomalous candidates. After analysis, we divided the candidates into two main classes of outliers: artifacts and intrinsic outliers. Artifacts were principally due to air mass variation, seasonal variation, bad calibration, or instrumental errors and were consequently removed from our outlier list and added to the training set. After retraining, we selected about 4000 objects, which we passed to a post-analysis stage by performing a cross-match with all publicly available catalogs. Within these candidates we identified certain known but rare objects such as eclipsing Cepheids, blue variables, cataclysmic variables, and X-ray sources. For some outliers there was no additional information. Among them we identified three unknown variability types and a few individual outliers that will be followed up in order to perform a deeper analysis.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Nun, Isadora; Pichara, Karim; Protopapas, Pavlos

The development of synoptic sky surveys has led to a massive amount of data for which resources needed for analysis are beyond human capabilities. In order to process this information and to extract all possible knowledge, machine learning techniques become necessary. Here we present a new methodology to automatically discover unknown variable objects in large astronomical catalogs. With the aim of taking full advantage of all information we have about known objects, our method is based on a supervised algorithm. In particular, we train a random forest classifier using known variability classes of objects and obtain votes for each ofmore » the objects in the training set. We then model this voting distribution with a Bayesian network and obtain the joint voting distribution among the training objects. Consequently, an unknown object is considered as an outlier insofar it has a low joint probability. By leaving out one of the classes on the training set, we perform a validity test and show that when the random forest classifier attempts to classify unknown light curves (the class left out), it votes with an unusual distribution among the classes. This rare voting is detected by the Bayesian network and expressed as a low joint probability. Our method is suitable for exploring massive data sets given that the training process is performed offline. We tested our algorithm on 20 million light curves from the MACHO catalog and generated a list of anomalous candidates. After analysis, we divided the candidates into two main classes of outliers: artifacts and intrinsic outliers. Artifacts were principally due to air mass variation, seasonal variation, bad calibration, or instrumental errors and were consequently removed from our outlier list and added to the training set. After retraining, we selected about 4000 objects, which we passed to a post-analysis stage by performing a cross-match with all publicly available catalogs. Within these candidates we identified certain known but rare objects such as eclipsing Cepheids, blue variables, cataclysmic variables, and X-ray sources. For some outliers there was no additional information. Among them we identified three unknown variability types and a few individual outliers that will be followed up in order to perform a deeper analysis.« less

Fingerprinting of HLA class I genes for improved selection of unrelated bone marrow donors.

PubMed

Martinelli, G; Farabegoli, P; Buzzi, M; Panzica, G; Zaccaria, A; Bandini, G; Calori, E; Testoni, N; Rosti, G; Conte, R; Remiddi, C; Salvucci, M; De Vivo, A; Tura, S

1996-02-01

The degree of matching of HLA genes between the selected donor and recipient is an important aspect of the selection of unrelated donors for allogeneic bone marrow transplantation (UBMT). The most sensitive methods currently used are serological typing of HLA class I genes, mixed lymphocyte culture (MLC), IEF and molecular genotyping of HLA class II genes by direct sequencing of PCR products. Serological typing of class I antigenes (A, B and C) fails to detect minor differences demonstrated by direct sequencing of DNA polymorphic regions. Molecular genotyping of HLA class I genes by DNA analysis is costly and work-intensive. To improve compatibility between donor and recipient, we have set up a new rapid and non-radioisotopic application of the 'fingerprinting PCR' technique for the analysis of the polymorphic second exon of the HLA class I A, B and C genes. This technique is based on the formation of specific patterns (PCR fingerprints) of homoduplexes and heteroduplexes between heterologous amplified DNA sequences. After an electrophoretic run on non-denaturing polyacrylamide gel, different HLA class I types give allele-specific banding patterns. HLA class I matching is performed, after the gel has been soaked in ethidium bromide or silver-stained, by visual comparison of patients' fingerprints with those of donors. Identity can be confirmed by mixing donor and recipient DNAs in an amplification cross-match. To assess the technique, 10 normal samples, 22 related allogeneic bone marrow transplanted pairs and 10 unrelated HLA-A and HLA-B serologically matched patient-donor pairs were analysed for HLA class I polymorphic regions. In all the related pairs and in 1/10 unrelated pairs, matched donor-recipient patterns were identified. This new application of PCR fingerprinting may confirm the HLA class I serological selection of unrelated marrow donors.

A bioinformatic analysis of ribonucleotide reductase genes in phage genomes and metagenomes

PubMed Central

2013-01-01

Background Ribonucleotide reductase (RNR), the enzyme responsible for the formation of deoxyribonucleotides from ribonucleotides, is found in all domains of life and many viral genomes. RNRs are also amongst the most abundant genes identified in environmental metagenomes. This study focused on understanding the distribution, diversity, and evolution of RNRs in phages (viruses that infect bacteria). Hidden Markov Model profiles were used to analyze the proteins encoded by 685 completely sequenced double-stranded DNA phages and 22 environmental viral metagenomes to identify RNR homologs in cultured phages and uncultured viral communities, respectively. Results RNRs were identified in 128 phage genomes, nearly tripling the number of phages known to encode RNRs. Class I RNR was the most common RNR class observed in phages (70%), followed by class II (29%) and class III (28%). Twenty-eight percent of the phages contained genes belonging to multiple RNR classes. RNR class distribution varied according to phage type, isolation environment, and the host’s ability to utilize oxygen. The majority of the phages containing RNRs are Myoviridae (65%), followed by Siphoviridae (30%) and Podoviridae (3%). The phylogeny and genomic organization of phage and host RNRs reveal several distinct evolutionary scenarios involving horizontal gene transfer, co-evolution, and differential selection pressure. Several putative split RNR genes interrupted by self-splicing introns or inteins were identified, providing further evidence for the role of frequent genetic exchange. Finally, viral metagenomic data indicate that RNRs are prevalent and highly dynamic in uncultured viral communities, necessitating future research to determine the environmental conditions under which RNRs provide a selective advantage. Conclusions This comprehensive study describes the distribution, diversity, and evolution of RNRs in phage genomes and environmental viral metagenomes. The distinct distributions of specific RNR classes amongst phages, combined with the various evolutionary scenarios predicted from RNR phylogenies suggest multiple inheritance sources and different selective forces for RNRs in phages. This study significantly improves our understanding of phage RNRs, providing insight into the diversity and evolution of this important auxiliary metabolic gene as well as the evolution of phages in response to their bacterial hosts and environments. PMID:23391036

Predictors of Latent Trajectory Classes of Dating Violence Victimization

PubMed Central

Brooks-Russell, Ashley; Foshee, Vangie; Ennett, Susan

2014-01-01

This study identified classes of developmental trajectories of physical dating violence victimization from grades 8 to 12 and examined theoretically-based risk factors that distinguished among trajectory classes. Data were from a multi-wave longitudinal study spanning 8th through 12th grade (n = 2,566; 51.9% female). Growth mixture models were used to identify trajectory classes of physical dating violence victimization separately for girls and boys. Logistic and multinomial logistic regressions were used to identify situational and target vulnerability factors associated with the trajectory classes. For girls, three trajectory classes were identified: a low/non-involved class; a moderate class where victimization increased slightly until the 10th grade and then decreased through the 12th grade; and a high class where victimization started at a higher level in the 8th grade, increased substantially until the 10th grade, and then decreased until the 12th grade. For males, two classes were identified: a low/non-involved class, and a victimized class where victimization increased slightly until the 9th grade, decreased until the 11th grade, and then increased again through the 12th grade. In bivariate analyses, almost all of the situational and target vulnerability risk factors distinguished the victimization classes from the non-involved classes. However, when all risk factors and control variables were in the model, alcohol use (a situational vulnerability) was the only factor that distinguished membership in the moderate trajectory class from the non-involved class for girls; anxiety and being victimized by peers (target vulnerability factors) were the factors that distinguished the high from the non-involved classes for the girls; and victimization by peers was the only factor distinguishing the victimized from the non-involved class for boys. These findings contribute to our understanding of the heterogeneity in physical dating violence victimization during adolescence and the malleable risk factors associated with each trajectory class for boys and girls. PMID:23212350

Novel approach to characterising individuals with low back-related leg pain: cluster identification with latent class analysis and 12-month follow-up.

PubMed

Stynes, Siobhán; Konstantinou, Kika; Ogollah, Reuben; Hay, Elaine M; Dunn, Kate M

2018-04-01

Traditionally, low back-related leg pain (LBLP) is diagnosed clinically as referred leg pain or sciatica (nerve root involvement). However, within the spectrum of LBLP, we hypothesised that there may be other unrecognised patient subgroups. This study aimed to identify clusters of patients with LBLP using latent class analysis and describe their clinical course. The study population was 609 LBLP primary care consulters. Variables from clinical assessment were included in the latent class analysis. Characteristics of the statistically identified clusters were compared, and their clinical course over 1 year was described. A 5 cluster solution was optimal. Cluster 1 (n = 104) had mild leg pain severity and was considered to represent a referred leg pain group with no clinical signs, suggesting nerve root involvement (sciatica). Cluster 2 (n = 122), cluster 3 (n = 188), and cluster 4 (n = 69) had mild, moderate, and severe pain and disability, respectively, and response to clinical assessment items suggested categories of mild, moderate, and severe sciatica. Cluster 5 (n = 126) had high pain and disability, longer pain duration, and more comorbidities and was difficult to map to a clinical diagnosis. Most improvement for pain and disability was seen in the first 4 months for all clusters. At 12 months, the proportion of patients reporting recovery ranged from 27% for cluster 5 to 45% for cluster 2 (mild sciatica). This is the first study that empirically shows the variability in profile and clinical course of patients with LBLP including sciatica. More homogenous groups were identified, which could be considered in future clinical and research settings.

A meta-analysis synthesizing the effects of pesticides on swim speed and activity of aquatic vertebrates.

PubMed

Shuman-Goodier, Molly E; Propper, Catherine R

2016-09-15

Pesticide contaminants are ubiquitous in aquatic environments and pose a threat to biodiversity. Pesticides also have diverse mechanisms of action that make it difficult to identify impacts on exposed wildlife. Behavioral measures represent an important link between physiological and ecological processes, and are often used to generalize sub-lethal effects of pesticide exposure. In order to bridge the toxicological and behavioral literature, and identify chemical classes that denote the largest threat, we conducted a meta-analysis summarizing the effects of pesticides on swim speed and activity of aquatic vertebrates. We found that exposure to environmentally relevant concentrations of pesticides reduced the swim speed of exposed amphibians and fish by 35%, and reduced overall activity by 72%. There were also differences in the magnitude of this effect across chemical classes, which likely reflect underlying physiological processes. Pyrethroids, carbamates, and organophosphates all produced a large decrease in swim speed, where as phosphonoglycines and triazines showed no overall effect. Pyrethroids, carbamates, organophosphates, organochlorines, and organotins also produced a large decrease in activity, while phosphonoglycines had no overall effect, and triazines had the opposite effect of increasing activity. Our results indicate that even sub-lethal concentrations of pesticides have a strong effect on critical behaviors of aquatic vertebrates, which can affect fitness and alter species interactions. We expect our synthesis can be used to identify chemical classes producing the largest sub-lethal effects for further research and management. Copyright © 2016 Elsevier B.V. All rights reserved.

Robust Classification of Small-Molecule Mechanism of Action Using a Minimalist High-Content Microscopy Screen and Multidimensional Phenotypic Trajectory Analysis

PubMed Central

Twarog, Nathaniel R.; Low, Jonathan A.; Currier, Duane G.; Miller, Greg; Chen, Taosheng; Shelat, Anang A.

2016-01-01

Phenotypic screening through high-content automated microscopy is a powerful tool for evaluating the mechanism of action of candidate therapeutics. Despite more than a decade of development, however, high content assays have yielded mixed results, identifying robust phenotypes in only a small subset of compound classes. This has led to a combinatorial explosion of assay techniques, analyzing cellular phenotypes across dozens of assays with hundreds of measurements. Here, using a minimalist three-stain assay and only 23 basic cellular measurements, we developed an analytical approach that leverages informative dimensions extracted by linear discriminant analysis to evaluate similarity between the phenotypic trajectories of different compounds in response to a range of doses. This method enabled us to visualize biologically-interpretable phenotypic tracks populated by compounds of similar mechanism of action, cluster compounds according to phenotypic similarity, and classify novel compounds by comparing them to phenotypically active exemplars. Hierarchical clustering applied to 154 compounds from over a dozen different mechanistic classes demonstrated tight agreement with published compound mechanism classification. Using 11 phenotypically active mechanism classes, classification was performed on all 154 compounds: 78% were correctly identified as belonging to one of the 11 exemplar classes or to a different unspecified class, with accuracy increasing to 89% when less phenotypically active compounds were excluded. Importantly, several apparent clustering and classification failures, including rigosertib and 5-fluoro-2’-deoxycytidine, instead revealed more complex mechanisms or off-target effects verified by more recent publications. These results show that a simple, easily replicated, minimalist high-content assay can reveal subtle variations in the cellular phenotype induced by compounds and can correctly predict mechanism of action, as long as the appropriate analytical tools are used. PMID:26886014

Robust Classification of Small-Molecule Mechanism of Action Using a Minimalist High-Content Microscopy Screen and Multidimensional Phenotypic Trajectory Analysis.

PubMed

Twarog, Nathaniel R; Low, Jonathan A; Currier, Duane G; Miller, Greg; Chen, Taosheng; Shelat, Anang A

2016-01-01

Phenotypic screening through high-content automated microscopy is a powerful tool for evaluating the mechanism of action of candidate therapeutics. Despite more than a decade of development, however, high content assays have yielded mixed results, identifying robust phenotypes in only a small subset of compound classes. This has led to a combinatorial explosion of assay techniques, analyzing cellular phenotypes across dozens of assays with hundreds of measurements. Here, using a minimalist three-stain assay and only 23 basic cellular measurements, we developed an analytical approach that leverages informative dimensions extracted by linear discriminant analysis to evaluate similarity between the phenotypic trajectories of different compounds in response to a range of doses. This method enabled us to visualize biologically-interpretable phenotypic tracks populated by compounds of similar mechanism of action, cluster compounds according to phenotypic similarity, and classify novel compounds by comparing them to phenotypically active exemplars. Hierarchical clustering applied to 154 compounds from over a dozen different mechanistic classes demonstrated tight agreement with published compound mechanism classification. Using 11 phenotypically active mechanism classes, classification was performed on all 154 compounds: 78% were correctly identified as belonging to one of the 11 exemplar classes or to a different unspecified class, with accuracy increasing to 89% when less phenotypically active compounds were excluded. Importantly, several apparent clustering and classification failures, including rigosertib and 5-fluoro-2'-deoxycytidine, instead revealed more complex mechanisms or off-target effects verified by more recent publications. These results show that a simple, easily replicated, minimalist high-content assay can reveal subtle variations in the cellular phenotype induced by compounds and can correctly predict mechanism of action, as long as the appropriate analytical tools are used.

Patterns of productive activity engagement among older adults in urban China.

PubMed

Liu, Huiying; Lou, Wei Qun

2016-12-01

This study aims to identify patterns of productive activity engagement among older adults in urban China. Once patterns are identified, we further explore how a set of individual characteristics is associated with these patterns. Using data from the 2011 baseline survey of the China Health and Retirement Longitudinal Study (CHARLS), we performed a latent class analysis (LCA) on a national representative sample of adults aged 60 years and over ( N  = 3019). A specified range of productive activity indicators that fit the context of urban China was used for performing LCA (including working, grandchildren's care, parental care, spousal care, informal helping, and formal volunteering). A multinomial logistic regression was used to assess whether individual characteristics are associated with the identified patterns. The results indicated that a four-class model fit the data well, with the interpretable set of classes: spouse carer (51.2 %), working grandparents (21.7 %), multifaceted contributor (16.6 %), and light-engaged volunteer (10.5 %). Age, gender, education, number of children, proximity with the nearest child, household composition and functional status contributed to differentiating these classes. This study captured the reality of productive engagement among older adults by drawing attention to how multiple productive activities intersect in later-life stages. Our findings have implications for policy-makers, health care practitioners, and community advocates to develop programs that facilitate this aging population in assuming meaningful productive activities.

Class III obesity is a risk factor for the development of acute-on-chronic liver failure in patients with decompensated cirrhosis.

PubMed

Sundaram, Vinay; Jalan, Rajiv; Ahn, Joseph C; Charlton, Michael R; Goldberg, David S; Karvellas, Constantine J; Noureddin, Mazen; Wong, Robert J

2018-04-28

Acute-on-chronic liver failure (ACLF) is a syndrome of systemic inflammation and organ failures. Obesity, also characterized by chronic inflammation, is a risk factor among patients with cirrhosis for decompensation, infection, and mortality. Our aim was to test the hypothesis that obesity predisposes patients with decompensated cirrhosis to the development of ACLF. We examined the United Network for Organ Sharing (UNOS) database, from 2005-2016, characterizing patients at wait-listing as non-obese (body mass index [BMI] <30), obese class I-II (BMI 30-39.9) and obese class III (BMI ≥40). ACLF was determined based on the CANONIC study definition. We used Cox proportional hazards regression to assess the association between obesity and ACLF development at liver transplantation (LT). We confirmed our findings using the Nationwide Inpatient Sample (NIS), years 2009-2013, using validated diagnostic coding algorithms to identify obesity, hepatic decompensation and ACLF. Logistic regression evaluated the association between obesity and ACLF occurrence. Among 387,884 patient records with decompensated cirrhosis, 116,704 (30.1%) were identified as having ACLF in both databases. Multivariable modeling from the UNOS database revealed class III obesity to be an independent risk factor for ACLF at LT (hazard ratio 1.24; 95% CI 1.09-1.41; p <0.001). This finding was confirmed using the NIS (odds ratio 1.30; 95% CI 1.25-1.35; p <0.001). Regarding specific organ failures, analysis of both registries demonstrated patients with class I-II and class III obesity had a greater prevalence of renal failure. Class III obesity is a newly identified risk factor for ACLF development in patients with decompensated cirrhosis. Obese patients have a particularly high prevalence of renal failure as a component of ACLF. These findings have important implications regarding stratifying risk and preventing the occurrence of ACLF. In this study, we identify that among patients with decompensated cirrhosis, class III obesity (severe/morbid obesity) is a modifiable risk factor for the development of acute-on-chronic liver failure (ACLF). We further demonstrate that regarding the specific organ failures associated with ACLF, renal failure is significantly more prevalent in obese patients, particularly those with class III obesity. These findings underscore the importance of weight management in cirrhosis, to reduce the risk of ACLF. Patients with class III obesity should be monitored closely for the development of renal failure. Copyright © 2018 European Association for the Study of the Liver. Published by Elsevier B.V. All rights reserved.

Ontogenetic dietary shifts and bioaccumulation of diphenhydramine in Mugil cephalus from an urban estuary.

PubMed

Haddad, Samuel P; Du, Bowen; Scott, W Casan; Saari, Gavin N; Breed, Christopher; Kelly, Martin; Broach, Linda; Chambliss, C Kevin; Brooks, Bryan W

2017-06-01

Though bioaccumulation of pharmaceuticals has received attention in inland waters, studies of pharmaceutical bioaccumulation in estuarine and marine systems are limited. Further, an understanding of pharmaceutical bioaccumulation across size classes of organisms displaying ontogenetic feeding shifts is lacking. We selected the striped mullet, Mugil cephalus, a euryhaline and eurythermal species that experiences dietary shifts with age, to identify whether a model base, diphenhydramine, accumulated in a tidally influenced urban bayou. We further determined whether diphenhydramine accumulation differed among size classes of striped mullet over a two year study period. Stable isotope analysis identified that ontogenetic feeding shifts of M. cephalus occurred from juveniles to adults. However, bioaccumulation of diphenhydramine did not significantly increase across age classes of M. cephalus but corresponded to surface water levels of the pharmaceutical, which suggests inhalational uptake to diphenhydramine was more important for bioaccumulation than dietary exposure in this urban estuary. Copyright © 2017 Elsevier Ltd. All rights reserved.

Classification of multiple sclerosis patients by latent class analysis of magnetic resonance imaging characteristics.

PubMed

Zwemmer, J N P; Berkhof, J; Castelijns, J A; Barkhof, F; Polman, C H; Uitdehaag, B M J

2006-10-01

Disease heterogeneity is a major issue in multiple sclerosis (MS). Classification of MS patients is usually based on clinical characteristics. More recently, a pathological classification has been presented. While clinical subtypes differ by magnetic resonance imaging (MRI) signature on a group level, a classification of individual MS patients based purely on MRI characteristics has not been presented so far. To investigate whether a restricted classification of MS patients can be made based on a combination of quantitative and qualitative MRI characteristics and to test whether the resulting subgroups are associated with clinical and laboratory characteristics. MRI examinations of the brain and spinal cord of 50 patients were scored for 21 quantitative and qualitative characteristics. Using latent class analysis, subgroups were identified, for whom disease characteristics and laboratory measures were compared. Latent class analysis revealed two subgroups that mainly differed in the extent of lesion confluency and MRI correlates of neuronal loss in the brain. Demographics and disease characteristics were comparable except for cognitive deficits. No correlations with laboratory measures were found. Latent class analysis offers a feasible approach for classifying subgroups of MS patients based on the presence of MRI characteristics. The reproducibility, longitudinal evolution and further clinical or prognostic relevance of the observed classification will have to be explored in a larger and independent sample of patients.

Assessment of Learning Gains Associated with Independent Exam Analysis in Introductory Biology

PubMed Central

William, Adrienne E.; Aguilar-Roca, Nancy M.; Tsai, Michelle; Wong, Matthew; Beaupré, Marin Moravec; O’Dowd, Diane K.

2011-01-01

This study evaluates the impact of an independent postmidterm question analysis exercise on the ability of students to answer subsequent exam questions on the same topics. It was conducted in three sections (∼400 students/section) of introductory biology. Graded midterms were returned electronically, and each student was assigned a subset of questions answered incorrectly by more than 40% of the class to analyze as homework. The majority of questions were at Bloom's application/analysis level; this exercise therefore emphasized learning at these higher levels of cognition. Students in each section answered final exam questions matched by topic to all homework questions, providing a within-class control group for each question. The percentage of students who correctly answered the matched final exam question was significantly higher (p < 0.05) in the Topic Analysis versus Control Analysis group for seven of 19 questions. We identified two factors that influenced activity effectiveness: 1) similarity in topic emphasis of the midterm–final exam question pair and 2) quality of the completed analysis homework. Our data suggest that this easy-to-implement exercise will be useful in large-enrollment classes to help students develop self-regulated learning skills. Additional strategies to help introductory students gain a broader understanding of topic areas are discussed. PMID:22135369

Assessment of learning gains associated with independent exam analysis in introductory biology.

PubMed

Williams, Adrienne E; William, Adrienne E; Aguilar-Roca, Nancy M; Tsai, Michelle; Wong, Matthew; Beaupré, Marin Moravec; O'Dowd, Diane K

2011-01-01

This study evaluates the impact of an independent postmidterm question analysis exercise on the ability of students to answer subsequent exam questions on the same topics. It was conducted in three sections (∼400 students/section) of introductory biology. Graded midterms were returned electronically, and each student was assigned a subset of questions answered incorrectly by more than 40% of the class to analyze as homework. The majority of questions were at Bloom's application/analysis level; this exercise therefore emphasized learning at these higher levels of cognition. Students in each section answered final exam questions matched by topic to all homework questions, providing a within-class control group for each question. The percentage of students who correctly answered the matched final exam question was significantly higher (p < 0.05) in the Topic Analysis versus Control Analysis group for seven of 19 questions. We identified two factors that influenced activity effectiveness: 1) similarity in topic emphasis of the midterm-final exam question pair and 2) quality of the completed analysis homework. Our data suggest that this easy-to-implement exercise will be useful in large-enrollment classes to help students develop self-regulated learning skills. Additional strategies to help introductory students gain a broader understanding of topic areas are discussed.

The Viral Transcription Group Determines the HLA Class I Cellular Immune Response Against Human Respiratory Syncytial Virus*

PubMed Central

Johnstone, Carolina; Lorente, Elena; Barriga, Alejandro; Barnea, Eilon; Infantes, Susana; Lemonnier, François A.; David, Chella S.; Admon, Arie; López, Daniel

2015-01-01

The cytotoxic T-lymphocyte-mediated killing of virus-infected cells requires previous recognition of short viral antigenic peptides bound to human leukocyte antigen class I molecules that are exposed on the surface of infected cells. The cytotoxic T-lymphocyte response is critical for the clearance of human respiratory syncytial virus infection. In this study, naturally processed viral human leukocyte antigen class I ligands were identified with mass spectrometry analysis of complex human leukocyte antigen-bound peptide pools isolated from large amounts of human respiratory syncytial virus-infected cells. Acute antiviral T-cell response characterization showed that viral transcription determines both the immunoprevalence and immunodominance of the human leukocyte antigen class I response to human respiratory syncytial virus. These findings have clear implications for antiviral vaccine design. PMID:25635267

Identifying clinical net benefit of psychotropic medication use with latent variable techniques: Evidence from Systematic Treatment Enhancement Program for Bipolar Disorder (STEP-BD).

PubMed

Bareis, Natalie; Lu, Juan; Kirkwood, Cynthia K; Kornstein, Susan G; Wu, Elwin; Mezuk, Briana

2018-05-29

Poor medication adherence is common among individuals with Bipolar Disorder (BD). Understanding the sources of heterogeneity in clinical net benefit (CNB) and how it is related to psychotropic medications can provide new insight into ways to improve adherence. Data come from the baseline assessments of the Systematic Treatment Enhancement Program for Bipolar Disorder (STEP-BD). Latent class analysis identified groups of CNB, and validity of this construct was assessed using the SF-36. Adherence was defined as taking 75% or more of medications as prescribed. Associations between CNB and adherence were tested using multiple logistic regression adjusting for sociodemographic characteristics. Five classes of CNB were identified: High (24%), Moderately high (12%), Moderate (26%), Moderately low (27%) and Low (12%). Adherence to psychotropic medications did not differ across classes (71% to 75%, χ 2   = 3.43, p = 0.488). Medication regimens differed by class: 57% of the High CNB were taking ≤2 medications, whereas 49% of the Low CNB were taking ≥4. CNB classes had good concordance with the SF-36. Missing data limited measures used to define CNB. Participants' perceptions of their illness and treatment were not assessed. This novel operationalization of CNB has construct validity as indicated by the SF-36. Although CNB and polypharmacy regimens are heterogeneous in this sample, adherence is similar across CNB. Studying adherent individuals, despite suboptimal CNB, may provide novel insights into aspects influencing adherence. Copyright © 2018 Elsevier B.V. All rights reserved.

Using Networks To Understand Medical Data: The Case of Class III Malocclusions

PubMed Central

Scala, Antonio; Auconi, Pietro; Scazzocchio, Marco; Caldarelli, Guido; McNamara, James A.; Franchi, Lorenzo

2012-01-01

A system of elements that interact or regulate each other can be represented by a mathematical object called a network. While network analysis has been successfully applied to high-throughput biological systems, less has been done regarding their application in more applied fields of medicine; here we show an application based on standard medical diagnostic data. We apply network analysis to Class III malocclusion, one of the most difficult to understand and treat orofacial anomaly. We hypothesize that different interactions of the skeletal components can contribute to pathological disequilibrium; in order to test this hypothesis, we apply network analysis to 532 Class III young female patients. The topology of the Class III malocclusion obtained by network analysis shows a strong co-occurrence of abnormal skeletal features. The pattern of these occurrences influences the vertical and horizontal balance of disharmony in skeletal form and position. Patients with more unbalanced orthodontic phenotypes show preponderance of the pathological skeletal nodes and minor relevance of adaptive dentoalveolar equilibrating nodes. Furthermore, by applying Power Graphs analysis we identify some functional modules among orthodontic nodes. These modules correspond to groups of tightly inter-related features and presumably constitute the key regulators of plasticity and the sites of unbalance of the growing dentofacial Class III system. The data of the present study show that, in their most basic abstraction level, the orofacial characteristics can be represented as graphs using nodes to represent orthodontic characteristics, and edges to represent their various types of interactions. The applications of this mathematical model could improve the interpretation of the quantitative, patient-specific information, and help to better targeting therapy. Last but not least, the methodology we have applied in analyzing orthodontic features can be applied easily to other fields of the medical science. PMID:23028552

Analysis of human serum lipoprotein lipid composition using MALDI-TOF mass spectrometry.

PubMed

Hidaka, Hiroya; Hanyu, Noboru; Sugano, Mitsutoshi; Kawasaki, Kenji; Yamauchi, Kazuyoshi; Katsuyama, Tsutomu

2007-01-01

This study used matrix-assisted laser desorption and ionization time-of-flight mass spectrometry (MALDI-TOF MS) to identify all lipid classes in human serum lipoproteins. After the major lipoproteins classes were isolated from serum by ultracentrifugation, the lipids were extracted and mixed with 2,5-dihydroxybenzoic acid (2,5-DHB) dissolved in Folch's solution (chloroform/methanol 2:1, v/v). MALDI-TOF MS analysis of the samples identified phospholipids (PLs), lysophospholipids (lysoPLs), sphingolipids (SLs), triglycerides (TGs), cholesteryl esters (CEs), and free cholesterol; it also showed the characteristics of individual fatty acid chains in serum lipids. MALDI-TOF MS allowed analysis of strongly hydrophobic and non-polar molecules such as CEs and TGs as well as hydrophilic molecules such as phospholipids. Direct analysis of fatty acids was not possible. The concentrations of lipids were not consistent with the ion peak intensities, since the extent of polarity affected the ionization characteristics of the molecules. However, lipid molecules with similar molecular structures but various fatty acid chains, such as phosphatidylcholine (PCs), were analyzed quantitatively by MALDI-TOF MS. Quantitative measurement of cholesterol was possible with the use of an internal standard. This study shows that MALDI-TOF MS can be used for direct investigation and quantitative analysis of the phospholipid composition of serum lipoproteins.

On-site phytoremediation applicability assessment in Alur Ilmu, Universiti Kebangsaan Malaysia based on spatial and pollution removal analyses.

PubMed

Mahmud, Mohd Hafiyyan; Lee, Khai Ern; Goh, Thian Lai

2017-10-01

The present paper aims to assess the phytoremediation performance based on pollution removal efficiency of the highly polluted region of Alur Ilmu urban river for its applicability of on-site treatment. Thirteen stations along Alur Ilmu were selected to produce thematic maps through spatial distribution analysis based on six water quality parameters of Malaysia's Water Quality Index (WQI) for dry and raining seasons. The maps generated were used to identify the highly polluted region for phytoremediation applicability assessment. Four free-floating plants were tested in treating water samples from the highly polluted region under three different conditions, namely controlled, aerated and normal treatments. The selected free-floating plants were water hyacinth (Eichhornia crassipes), water lettuce (Pistia stratiotes), rose water lettuce (Pistia sp.) and pennywort (Centella asiatica). The results showed that Alur Ilmu was more polluted during dry season compared to raining season based on the water quality analysis. During dry season, four parameters were marked as polluted along Alur Ilmu, namely dissolve oxygen (DO), 4.72 mg/L (class III); ammoniacal nitrogen (NH 3 -N), 0.85 mg/L (class IV); total suspended solid (TSS), 402 mg/L (class V) and biological oxygen demand (BOD), 3.89 mg/L (class III), whereas, two parameters were classed as polluted during raining season, namely total suspended solid (TSS), 571 mg/L (class V) and biological oxygen demand (BOD), 4.01 mg/L (class III). The thematic maps generated from spatial distribution analysis using Kriging gridding method showed that the highly polluted region was recorded at station AL 5. Hence, water samples were taken from this station for pollution removal analysis. All the free-floating plants were able to reduce TSS and COD in less than 14 days. However, water hyacinth showed the least detrimental effect from the phytoremediation process compared to other free-floating plants, thus made it a suitable free-floating plants to be used for on-site treatment.

Job satisfaction among Australian doctors: the use of latent class analysis.

PubMed

Joyce, Catherine; Wang, Wei Chun

2015-10-01

To identify patterns of job satisfaction among Australian doctors using latent class analysis, and to determine the relationships of these patterns to personal and professional characteristics so as to improve satisfaction and minimize medical wastage. MABEL (Medicine in Australia: Balancing Employment and Life) data in 2011 were used. The study collected information on 5764 doctors about their job satisfaction, demographic characteristics, their health, country of medical training, opportunities for professional development and social interaction, taking time off work, views of patients' expectations, unpredictable working hours, hours worked per week, preference to reduce hours and intention to leave the medical workforce. Four latent classes of job satisfaction were identified: 5.8% had high job satisfaction; 19.4% had low satisfaction with working hours; 16.1% had high satisfaction with working hours but felt undervalued; and 6.5% had low job satisfaction. Low job satisfaction was associated with reporting poor health, having trained outside Australia, having poor opportunities for professional development and working longer hours. Low satisfaction was associated with a preference to reduce work hours and an intention to leave the medical workforce. To improve job satisfaction and minimize medical wastage, policies need to address needs of overseas trained doctors, provide continuing professional development and provide good health care for doctors. © The Author(s) 2015.

Strain-based HLA association analysis identified HLA-DRB1*09:01 associated with modern strain tuberculosis.

PubMed

Toyo-Oka, L; Mahasirimongkol, S; Yanai, H; Mushiroda, T; Wattanapokayakit, S; Wichukchinda, N; Yamada, N; Smittipat, N; Juthayothin, T; Palittapongarnpim, P; Nedsuwan, S; Kantipong, P; Takahashi, A; Kubo, M; Sawanpanyalert, P; Tokunaga, K

2017-09-01

Tuberculosis (TB) occurs as a result of complex interactions between the host immune system and pathogen virulence factors. Human leukocyte antigen (HLA) class II molecules play an important role in the host immune system. However, no study has assessed the association between HLA class II genes and susceptibility to TB caused by specific strains. This study investigated the possible association of HLA class II genes with TB caused by modern and ancient Mycobacterium tuberculosis (MTB). The study included 682 patients with TB and 836 control subjects who were typed for HLA-DRB1 and HLA-DQB1 alleles. MTB strains were classified using a large sequence polymorphism typing method. Association analysis was performed using common HLA alleles and haplotypes in different MTB strains. HLA association analysis of patients infected with modern MTB strains showed significant association for HLA-DRB1*09:01 (odds ratio [OR] = 1.82; P-value = 9.88 × 10 -4 ) and HLA-DQB1*03:03 alleles (OR = 1.76; P-value = 1.31 × 10 -3 ) with susceptibility to TB. Haplotype analysis confirmed that these alleles were in strong linkage disequilibrium and did not exert an interactive effect. Thus, the results of this study showed an association between HLA class II genes and susceptibility to TB caused by modern MTB strains, suggesting the importance of strain-specific analysis to determine susceptibility genes associated with TB. © 2017 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Binary Logistic Regression Analysis in Assessment and Identifying Factors That Influence Students' Academic Achievement: The Case of College of Natural and Computational Science, Wolaita Sodo University, Ethiopia

ERIC Educational Resources Information Center

Zewude, Bereket Tessema; Ashine, Kidus Meskele

2016-01-01

An attempt has been made to assess and identify the major variables that influence student academic achievement at college of natural and computational science of Wolaita Sodo University in Ethiopia. Study time, peer influence, securing first choice of department, arranging study time outside class, amount of money received from family, good life…

Patterns and predictors of violence against children in Uganda: a latent class analysis

PubMed Central

Clarke, Kelly; Patalay, Praveetha; Allen, Elizabeth; Knight, Louise; Naker, Dipak; Devries, Karen

2016-01-01

Objective To explore patterns of physical, emotional and sexual violence against Ugandan children. Design Latent class and multinomial logistic regression analysis of cross-sectional data. Setting Luwero District, Uganda. Participants In all, 3706 primary 5, 6 and 7 students attending 42 primary schools. Main outcome and measure To measure violence, we used the International Society for the Prevention of Child Abuse and Neglect Child Abuse Screening Tool—Child Institutional. We used the Strengths and Difficulties Questionnaire to assess mental health and administered reading, spelling and maths tests. Results We identified three violence classes. Class 1 (N=696 18.8%) was characterised by emotional and physical violence by parents and relatives, and sexual and emotional abuse by boyfriends, girlfriends and unrelated adults outside school. Class 2 (N=975 26.3%) was characterised by physical, emotional and sexual violence by peers (male and female students). Children in Classes 1 and 2 also had a high probability of exposure to emotional and physical violence by school staff. Class 3 (N=2035 54.9%) was characterised by physical violence by school staff and a lower probability of all other forms of violence compared to Classes 1 and 2. Children in Classes 1 and 2 were more likely to have worked for money (Class 1 Relative Risk Ratio 1.97, 95% CI 1.54 to 2.51; Class 2 1.55, 1.29 to 1.86), been absent from school in the previous week (Class 1 1.31, 1.02 to 1.67; Class 2 1.34, 1.10 to 1.63) and to have more mental health difficulties (Class 1 1.09, 1.07 to 1.11; Class 2 1.11, 1.09 to 1.13) compared to children in Class 3. Female sex (3.44, 2.48 to 4.78) and number of children sharing a sleeping area predicted being in Class 1. Conclusions Childhood violence in Uganda forms distinct patterns, clustered by perpetrator and setting. Research is needed to understand experiences of victimised children, and to develop mental health interventions for those with severe violence exposures. Trial registration number NCT01678846; Results. PMID:27221125

Prototype Development of a Tradespace Analysis Tool for Spaceflight Medical Resources.

PubMed

Antonsen, Erik L; Mulcahy, Robert A; Rubin, David; Blue, Rebecca S; Canga, Michael A; Shah, Ronak

2018-02-01

The provision of medical care in exploration-class spaceflight is limited by mass, volume, and power constraints, as well as limitations of available skillsets of crewmembers. A quantitative means of exploring the risks and benefits of inclusion or exclusion of onboard medical capabilities may help to inform the development of an appropriate medical system. A pilot project was designed to demonstrate the utility of an early tradespace analysis tool for identifying high-priority resources geared toward properly equipping an exploration mission medical system. Physician subject matter experts identified resources, tools, and skillsets required, as well as associated criticality scores of the same, to meet terrestrial, U.S.-specific ideal medical solutions for conditions concerning for exploration-class spaceflight. A database of diagnostic and treatment actions and resources was created based on this input and weighed against the probabilities of mission-specific medical events to help identify common and critical elements needed in a future exploration medical capability. Analysis of repository data demonstrates the utility of a quantitative method of comparing various medical resources and skillsets for future missions. Directed database queries can provide detailed comparative estimates concerning likelihood of resource utilization within a given mission and the weighted utility of tangible and intangible resources. This prototype tool demonstrates one quantitative approach to the complex needs and limitations of an exploration medical system. While this early version identified areas for refinement in future version development, more robust analysis tools may help to inform the development of a comprehensive medical system for future exploration missions.Antonsen EL, Mulcahy RA, Rubin D, Blue RS, Canga MA, Shah R. Prototype development of a tradespace analysis tool for spaceflight medical resources. Aerosp Med Hum Perform. 2018; 89(2):108-114.

The association between mood state and chronobiological characteristics in bipolar I disorder: a naturalistic, variable cluster analysis-based study.

PubMed

Gonzalez, Robert; Suppes, Trisha; Zeitzer, Jamie; McClung, Colleen; Tamminga, Carol; Tohen, Mauricio; Forero, Angelica; Dwivedi, Alok; Alvarado, Andres

2018-02-19

Multiple types of chronobiological disturbances have been reported in bipolar disorder, including characteristics associated with general activity levels, sleep, and rhythmicity. Previous studies have focused on examining the individual relationships between affective state and chronobiological characteristics. The aim of this study was to conduct a variable cluster analysis in order to ascertain how mood states are associated with chronobiological traits in bipolar I disorder (BDI). We hypothesized that manic symptomatology would be associated with disturbances of rhythm. Variable cluster analysis identified five chronobiological clusters in 105 BDI subjects. Cluster 1, comprising subjective sleep quality was associated with both mania and depression. Cluster 2, which comprised variables describing the degree of rhythmicity, was associated with mania. Significant associations between mood state and cluster analysis-identified chronobiological variables were noted. Disturbances of mood were associated with subjectively assessed sleep disturbances as opposed to objectively determined, actigraphy-based sleep variables. No associations with general activity variables were noted. Relationships between gender and medication classes in use and cluster analysis-identified chronobiological characteristics were noted. Exploratory analyses noted that medication class had a larger impact on these relationships than the number of psychiatric medications in use. In a BDI sample, variable cluster analysis was able to group related chronobiological variables. The results support our primary hypothesis that mood state, particularly mania, is associated with chronobiological disturbances. Further research is required in order to define these relationships and to determine the directionality of the associations between mood state and chronobiological characteristics.

Prognostic Validation of SKY92 and Its Combination With ISS in an Independent Cohort of Patients With Multiple Myeloma.

PubMed

van Beers, Erik H; van Vliet, Martin H; Kuiper, Rowan; de Best, Leonie; Anderson, Kenneth C; Chari, Ajai; Jagannath, Sundar; Jakubowiak, Andrzej; Kumar, Shaji K; Levy, Joan B; Auclair, Daniel; Lonial, Sagar; Reece, Donna; Richardson, Paul; Siegel, David S; Stewart, A Keith; Trudel, Suzanne; Vij, Ravi; Zimmerman, Todd M; Fonseca, Rafael

2017-09-01

High risk and low risk multiple myeloma patients follow a very different clinical course as reflected in their PFS and OS. To be clinically useful, methodologies used to identify high and low risk disease must be validated in representative independent clinical data and available so that patients can be managed appropriately. A recent analysis has indicated that SKY92 combined with the International Staging System (ISS) identifies patients with different risk disease with high sensitivity. Here we computed the performance of eight gene expression based classifiers SKY92, UAMS70, UAMS80, IFM15, Proliferation Index, Centrosome Index, Cancer Testis Antigen and HM19 as well as the combination of SKY92/ISS in an independent cohort of 91 newly diagnosed MM patients. The classifiers identified between 9%-21% of patients as high risk, with hazard ratios (HRs) between 1.9 and 8.2. Among the eight signatures, SKY92 identified the largest proportion of patients (21%) also with the highest HR (8.2). Our analysis also validated the combination SKY92/ISS for identification of three classes; low risk (42%), intermediate risk (37%) and high risk (21%). Between low risk and high risk classes the HR is >10. Copyright © 2017 Elsevier Inc. All rights reserved.

Analysis of phenolic compounds in different parts of pomegranate (Punica granatum) fruit by HPLC-PDA-ESI/MS and evaluation of their antioxidant activity: application to different Italian varieties.

PubMed

Russo, Marina; Fanali, Chiara; Tripodo, Giusy; Dugo, Paola; Muleo, Rosario; Dugo, Laura; De Gara, Laura; Mondello, Luigi

2018-06-01

The analysis of pomegranate phenolic compounds belonging to different classes in different fruit parts was performed by high-performance liquid chromatography coupled with photodiode array and mass spectrometry detection. Two different separation methods were optimized for the analysis of anthocyanins and hydrolyzable tannins along with phenolic acids and flavonoids. Two C 18 columns, core-shell and fully porous particle stationary phases, were used. The parameters for separation of phenolic compounds were optimized considering chromatographic resolution and analysis time. Thirty-five phenolic compounds were found, and 28 of them were tentatively identified as belonging to four different phenolic compound classes; namely, anthocyanins, phenolic acids, hydrolyzable tannins, and flavonoids. Quantitative analysis was performed with a mixture of nine phenolic compounds belonging to phenolic compound classes representative of pomegranate. The method was then fully validated in terms of retention time precision, expressed as the relative standard deviation, limit of detection, limit of quantification, and linearity range. Phenolic compounds were analyzed directly in pomegranate juice, and after solvent extraction with a mixture of water and methanol with a small percentage of acid in peel and pulp samples. The accuracy of the extraction method was also assessed, and satisfactory values were obtained. Finally, the method was used to study identified analytes in pomegranate juice, peel, and pulp of six different Italian varieties and one international variety. Differences in phenolic compound profiles among the different pomegranate parts were observed. Pomegranate peel samples showed a high concentration of phenolic compounds, ellagitannins being the most abundant ones, with respect to pulp and juice samples for each variety. With the same samples, total phenols and antioxidant activity were evaluated through colorimetric assays, and the results were correlated among them.

Behavioral and Mental Health Correlates of Youth Stalking Victimization: A Latent Class Approach.

PubMed

Reidy, Dennis E; Smith-Darden, Joanne P; Kernsmith, Poco D

2016-12-01

Although recognized as a public health problem, little attention has been paid to the problem of stalking among youth. Latent profile analysis was used to identify latent groups of adolescent stalking victims and their behavioral and mental health correlates. A cross-sectional sample of 1,236 youths were randomly selected from 13 schools stratified by community risk level (i.e., low, moderate, and high risk) and gender. Students completed surveys assessing behavioral indicators of stalking victimization, as well as substance use, sexual behavior, dating violence, and psychiatric symptoms. Data were collected in 2013 and data analyses were performed in 2015. Analysis indicated the presence of a non-victim class, a minimal exposure class, and a victim class for boys and girls alike. Approximately 14% of girls and 13% of boys were in the stalking victim class. Adolescents in the victim class reported more symptoms of post-traumatic stress, mood disorder, and hopelessness, as well as more instances of alcohol use, binge drinking, and physical dating violence victimization. Girls in the victim class also reported engaging in sexting behaviors and oral sex with significantly more partners than their non-victim peers. These findings provide valuable knowledge of the prevalence and pertinent health correlates of stalking victimization in adolescence. The data suggest a substantial proportion of adolescents are victims of stalking and are likewise at risk for a number of deleterious health outcomes. As such, this population merits further attention by prevention researchers and practitioners. Published by Elsevier Inc.

Preferences for Early Intervention Mental Health Services: A Discrete-Choice Conjoint Experiment.

PubMed

Becker, Mackenzie P E; Christensen, Bruce K; Cunningham, Charles E; Furimsky, Ivana; Rimas, Heather; Wilson, Fiona; Jeffs, Lisa; Bieling, Peter J; Madsen, Victoria; Chen, Yvonne Y S; Mielko, Stephanie; Zipursky, Robert B

2016-02-01

Early intervention services (EISs) for mental illness may improve outcomes, although treatment engagement is often a problem. Incorporating patients' preferences in the design of interventions improves engagement. A discrete-choice conjoint experiment was conducted in Canada to identify EIS attributes that encourage treatment initiation. Sixteen four-level attributes were formalized into a conjoint survey, completed by patients, family members, and mental health professionals (N=562). Participants were asked which EIS option people with mental illness would contact. Latent-class analysis identified respondent classes characterized by shared preferences. Randomized first-choice simulations predicted which hypothetical options, based on attributes, would result in maximum utilization. Participants in the conventional-service class (N=241, 43%) predicted that individuals would contact traditional services (for example, hospital location and staffed by psychologists or psychiatrists). Membership was associated with being a patient or family member and being male. Participants in the convenient-service class (N=321, 57%) predicted that people would contact services promoting easy access (for example, self-referral and access from home). Membership was associated with being a professional. Both classes predicted that people would contact services that included short wait times, direct contact with professionals, patient autonomy, and psychological treatment information. The convenient-service class predicted that people would use an e-health model, whereas the conventional-service class predicted that people would use a primary care or clinic-hospital model. Provision of a range of services may maximize EIS use. Professionals may be more apt to adopt EISs in line with their beliefs regarding patient preferences. Considering several perspectives is important for service design.

Empirical redefinition of comprehensive health and well-being in the older adults of the United States.

PubMed

McClintock, Martha K; Dale, William; Laumann, Edward O; Waite, Linda

2016-05-31

The World Health Organization (WHO) defines health as a "state of complete physical, mental and social well-being and not merely the absence of disease or infirmity." Despite general acceptance of this comprehensive definition, there has been little rigorous scientific attempt to use it to measure and assess population health. Instead, the dominant model of health is a disease-centered Medical Model (MM), which actively ignores many relevant domains. In contrast to the MM, we approach this issue through a Comprehensive Model (CM) of health consistent with the WHO definition, giving statistically equal consideration to multiple health domains, including medical, physical, psychological, functional, and sensory measures. We apply a data-driven latent class analysis (LCA) to model 54 specific health variables from the National Social Life, Health, and Aging Project (NSHAP), a nationally representative sample of US community-dwelling older adults. We first apply the LCA to the MM, identifying five health classes differentiated primarily by having diabetes and hypertension. The CM identifies a broader range of six health classes, including two "emergent" classes completely obscured by the MM. We find that specific medical diagnoses (cancer and hypertension) and health behaviors (smoking) are far less important than mental health (loneliness), sensory function (hearing), mobility, and bone fractures in defining vulnerable health classes. Although the MM places two-thirds of the US population into "robust health" classes, the CM reveals that one-half belong to less healthy classes, independently associated with higher mortality. This reconceptualization has important implications for medical care delivery, preventive health practices, and resource allocation.

Better Glycemic Control Is Associated With Maintenance of Lower-Extremity Function Over Time in Mexican American and European American Older Adults With Diabetes

PubMed Central

Wang, Chen-Pin; Hazuda, Helen P.

2011-01-01

OBJECTIVE Diabetes is a major cause of functional decline among older adults, but the role of glycemic control remains unclear. This article assesses whether better glycemic control is associated with better maintenance of lower-extremity function over time in older adults with diabetes. RESEARCH DESIGN AND METHODS Participants (n = 119) in the San Antonio Longitudinal Study of Aging, ages 71–85, who met American Diabetes Association diabetes criteria were followed over a 36-month period. Seven measures of A1C (HbA1c) were obtained at 6-month intervals; three measures of lower-extremity function were obtained at 18-month intervals using the Short Physical Performance Battery (SPPB). A two-step analytic approach was used, first, to identify distinct glycemic control classes using latent growth mixture modeling and, second, to examine trajectories of lower-extremity function based on these classes using path analysis. RESULTS Two glycemic control classes were identified: a poorer control class with higher means (all >7%) and higher within-subject variability in HbA1c and a better control class with lower means (all <7%) and lower within-subject variability. The short-term and long-term maintenance of lower-extremity function, assessed by the association between the first and second SPPB measures and the first and third SPPB measures, were both greater in the better control class than in the poorer control class. CONCLUSIONS Among older adults with diabetes, better glycemic control may improve both short-term and long-term maintenance of lower-extremity function. PMID:21216857

Better glycemic control is associated with maintenance of lower-extremity function over time in Mexican American and European American older adults with diabetes.

PubMed

Wang, Chen-Pin; Hazuda, Helen P

2011-02-01

Diabetes is a major cause of functional decline among older adults, but the role of glycemic control remains unclear. This article assesses whether better glycemic control is associated with better maintenance of lower-extremity function over time in older adults with diabetes. Participants (n = 119) in the San Antonio Longitudinal Study of Aging, ages 71-85, who met American Diabetes Association diabetes criteria were followed over a 36-month period. Seven measures of A1C (HbA(1c)) were obtained at 6-month intervals; three measures of lower-extremity function were obtained at 18-month intervals using the Short Physical Performance Battery (SPPB). A two-step analytic approach was used, first, to identify distinct glycemic control classes using latent growth mixture modeling and, second, to examine trajectories of lower-extremity function based on these classes using path analysis. Two glycemic control classes were identified: a poorer control class with higher means (all >7%) and higher within-subject variability in HbA(1c) and a better control class with lower means (all <7%) and lower within-subject variability. The short-term and long-term maintenance of lower-extremity function, assessed by the association between the first and second SPPB measures and the first and third SPPB measures, were both greater in the better control class than in the poorer control class. Among older adults with diabetes, better glycemic control may improve both short-term and long-term maintenance of lower-extremity function.

Personality modulates the efficacy of treatment in patients with major depressive disorder.

PubMed

Wardenaar, Klaas J; Conradi, Henk Jan; Bos, Elisabeth H; de Jonge, Peter

2014-09-01

Effects of depression treatment are obscured by heterogeneity among patients. Personality types could be one source of heterogeneity that explains variability in treatment response. Clinically meaningful variations in personality patterns could be captured with data-driven subgroups. The aim of this study was to identify such personality types and to explore their predictive value for treatment efficacy. Participants (N = 146) in the current exploratory study came from a randomized controlled trial in primary care depressed patients, conducted between January 1998 and June 2003, comparing different treatments. All participants were diagnosed with a major depressive disorder (MDD) according to the DSM-IV. Primary (care as usual [CAU] or CAU plus a psychoeducational prevention program [PEP]) and specialized (CAU + PEP + psychiatric consultation or cognitive-behavioral therapy) treatment were compared. Personality was assessed with the Neuroticism-Extraversion-Openness Five-Factor Inventory (NEO-FFI). Personality classes were identified with latent profile analysis (LPA). During 1 year, weekly depression ratings were obtained by trimonthly assessment with the Composite International Diagnostic Interview. Mixed models were used to analyze the effects of personality on treatment efficacy. A 2-class LPA solution fit best to the NEO-FFI data: Class 1 (vulnerable, n = 94) was characterized by high neuroticism, low extraversion, and low conscientiousness, and Class 2 (resilient, n = 52) by medium neuroticism and extraversion and higher agreeableness and conscientiousness. Recovery was quicker in the resilient class (class × time: P < .001). Importantly, specialized treatment had added value only in the vulnerable class, in which it was associated with quicker recovery than primary treatment (class × time × treatment: P < .001). Personality profile may predict whether specialized clinical efforts have added value, showing potential implications for planning of treatments. © Copyright 2014 Physicians Postgraduate Press, Inc.

What Doesn't Work for Whom? Exploring Heterogeneity in Responsiveness to the Family Check-Up in Early Childhood Using a Mixture Model Approach.

PubMed

Pelham, William E; Dishion, Thomas J; Tein, Jenn-Yun; Shaw, Daniel S; Wilson, Melvin N

2017-11-01

This study applied latent class analysis to a family-centered prevention trial in early childhood to identify subgroups of families with differential responsiveness to the Family Check-Up (FCU) intervention. The sample included 731 families with 2-year-olds randomized to the FCU or control condition and followed through age 5 with yearly follow-up assessments. A two-step mixture model was used to examine whether specific constellations of family characteristics at age 2 (baseline) were related to intervention response across ages 3, 4, and 5. The first step empirically identified latent classes of families based on several family risk and adjustment variables selected on the basis of previous research. The second step modeled the effect of the FCU on longitudinal change in children's problem behavior in each of the empirically derived latent classes. Results suggested a five-class solution, where a significant intervention effect of moderate to large size was observed in one of the five classes-the class characterized by child neglect, legal problems, and parental mental health issues. Pairwise comparisons revealed that the intervention effect was significantly greater in this class of families than in two other classes that were generally less at risk for the development of child disruptive behavior problems, albeit still low-income. Thus, findings suggest that (a) the FCU is most successful in reducing child problem behavior in more highly distressed, low-income families, and (b) the FCU may have little impact for relatively low-risk, low-income families. Future directions include the development of a brief screening process that can triage low-income families into groups that should be targeted for intervention, redirected to other services, monitored prospectively, or left alone.

Prediction of incidence and stability of alcohol use disorders by latent internalizing psychopathology risk profiles in adolescence and young adulthood.

PubMed

Behrendt, Silke; Bühringer, Gerhard; Höfler, Michael; Lieb, Roselind; Beesdo-Baum, Katja

2017-10-01

Comorbid internalizing mental disorders in alcohol use disorders (AUD) can be understood as putative independent risk factors for AUD or as expressions of underlying shared psychopathology vulnerabilities. However, it remains unclear whether: 1) specific latent internalizing psychopathology risk-profiles predict AUD-incidence and 2) specific latent internalizing comorbidity-profiles in AUD predict AUD-stability. To investigate baseline latent internalizing psychopathology risk profiles as predictors of subsequent AUD-incidence and -stability in adolescents and young adults. Data from the prospective-longitudinal EDSP study (baseline age 14-24 years) were used. The study-design included up to three follow-up assessments in up to ten years. DSM-IV mental disorders were assessed with the DIA-X/M-CIDI. To investigate risk-profiles and their associations with AUD-outcomes, latent class analysis with auxiliary outcome variables was applied. AUD-incidence: a 4-class model (N=1683) was identified (classes: normative-male [45.9%], normative-female [44.2%], internalizing [5.3%], nicotine dependence [4.5%]). Compared to the normative-female class, all other classes were associated with a higher risk of subsequent incident alcohol dependence (p<0.05). AUD-stability: a 3-class model (N=1940) was identified with only one class (11.6%) with high probabilities for baseline AUD. This class was further characterized by elevated substance use disorder (SUD) probabilities and predicted any subsequent AUD (OR 8.5, 95% CI 5.4-13.3). An internalizing vulnerability may constitute a pathway to AUD incidence in adolescence and young adulthood. In contrast, no indication for a role of internalizing comorbidity profiles in AUD-stability was found, which may indicate a limited importance of such profiles - in contrast to SUD-related profiles - in AUD stability. Copyright © 2017 Elsevier B.V. All rights reserved.

Length and sequence heterogeneity in 5S rDNA of Populus deltoides.

PubMed

Negi, Madan S; Rajagopal, Jyothi; Chauhan, Neeti; Cronn, Richard; Lakshmikumaran, Malathi

2002-12-01

The 5S rRNA genes and their associated non-transcribed spacer (NTS) regions are present as repeat units arranged in tandem arrays in plant genomes. Length heterogeneity in 5S rDNA repeats was previously identified in Populus deltoides and was also observed in the present study. Primers were designed to amplify the 5S rDNA NTS variants from the P. deltoides genome. The PCR-amplified products from the two accessions of P. deltoides (G3 and G48) suggested the presence of length heterogeneity of 5S rDNA units within and among accessions, and the size of the spacers ranged from 385 to 434 bp. Sequence analysis of the non-transcribed spacer (NTS) revealed two distinct classes of 5S rDNA within both accessions: class 1, which contained GAA trinucleotide microsatellite repeats, and class 2, which lacked the repeats. The class 1 spacer shows length variation owing to the microsatellite, with two clones exhibiting 10 GAA repeat units and one clone exhibiting 16 such repeat units. However, distance analysis shows that class 1 spacer sequences are highly similar inter se, yielding nucleotide diversity (pi) estimates that are less than 0.15% of those obtained for class 2 spacers (pi = 0.0183 vs. 0.1433, respectively). The presence of microsatellite in the NTS region leading to variation in spacer length is reported and discussed for the first time in P. deltoides.

The long noncoding RNA landscape of neuroendocrine prostate cancer and its clinical implications.

PubMed

Ramnarine, Varune Rohan; Alshalalfa, Mohammed; Mo, Fan; Nabavi, Noushin; Erho, Nicholas; Takhar, Mandeep; Shukin, Robert; Brahmbhatt, Sonal; Gawronski, Alexander; Kobelev, Maxim; Nouri, Mannan; Lin, Dong; Tsai, Harrison; Lotan, Tamara L; Karnes, R Jefferey; Rubin, Mark A; Zoubeidi, Amina; Gleave, Martin E; Sahinalp, Cenk; Wyatt, Alexander W; Volik, Stanislav V; Beltran, Himisha; Davicioni, Elai; Wang, Yuzhuo; Collins, Colin C

2018-05-10

Treatment induced neuroendocrine prostate cancer (tNEPC) is an aggressive variant of late-stage metastatic castrate resistant (mCRPC) prostate cancer that commonly arises through neuroendocrine transdifferentiation (NEtD). Treatment options are limited, ineffective, and for most patients, results in death in less than a year. We previously developed a first-in-field patient-derived xenograft (PDX) model of NEtD. Longitudinal deep transcriptome profiling of this model enabled monitoring of dynamic transcriptional changes during NEtD and in the context of androgen deprivation. Long non-coding RNA (lncRNA) are implicated in cancer where they can control gene regulation. Until now the expression of lncRNAs during NEtD and their clinical associations were unexplored. We implemented a next-generation sequence analysis pipeline that can detect transcripts at low expression levels and built a genome-wide catalogue (n = 37,749) of lncRNAs. We applied this pipeline to 927 clinical samples and our high fidelity NEtD model LTL331 and identified 821 lncRNAs in NEPC. Among these are 122 lncRNAs that robustly distinguish NEPC from prostate adenocarcinoma (AD) patient tumours. The highest expressed lncRNAs within this signature are H19, LINC00617, and SSTR5-AS1. Another 742 are associated with the NEtD process and fall into four distinct patterns of expression (NEtD lncRNA Class I, II, III, and IV) in our PDX model and clinical samples. Each class has significant (z-scores>2) and unique enrichment for transcription factor binding site (TFBS) motifs in their sequences. Enriched TFBS include (1) TP53 and BRN1 in Class I, (2) ELF5, SPIC, and HOXD1 in Class II, (3) SPDEF in Class III, (4) HSF1 and FOXA1 in Class IV, and (5) TWIST1 when merging Class III with IV. Common TFBS in all NEtD lncRNA were also identified and include, E2F, REST, PAX5, PAX9, and STAF. Interrogation of the top deregulated candidates (n = 100) in radical prostatectomy adenocarcinoma samples with long-term follow-up (median 18 years) revealed significant clinicopathological associations. Specifically, we identified 25 that are associated with rapid metastasis following androgen deprivation therapy (ADT). Two of these lncRNAs (SSTR5-AS1 and LINC00514) stratified patients undergoing ADT based on patient outcome. To date, a comprehensive characterization of the dynamic landscape of lncRNAs during the NEtD process has not been performed. A temporal analysis of the PDX-based NEtD model has for the first time provided this dynamic landscape. TFBS analysis identified NEPC-related TF motifs present within the NEtD lncRNA sequences, suggesting functional roles for these lncRNAs in NEPC pathogenesis. Furthermore, select NEtD lncRNAs appear to be associated with metastasis and patients receiving ADT. Treatment-related metastasis is a clinical consequence of NEPC tumours. Top candidate lncRNAs FENDRR, H19, LINC00514, LINC00617, and SSTR5-AS1 identified in this study are implicated in the development of NEPC. We present here for the first time a genome-wide catalogue of NEtD lncRNAs that characterize the transdifferentiation process and a robust NEPC lncRNA patient expression signature. To accomplish this, we carried out the largest integrative study that applied a PDX NEtD model to clinical samples. These NEtD and NEPC lncRNAs are strong candidates for clinical biomarkers and therapeutic targets and warrant further investigation.

Personality and changes in comorbidity patterns among anxiety and depressive disorders.

PubMed

Spinhoven, Philip; de Rooij, Mark; Heiser, Willem; Smit, Jan H; Penninx, Brenda W J H

2012-11-01

This prospective study examined the prognostic value of the Big Five personality model for changes in comorbidity patterns of emotional disorders both from a person- and trait-centered perspective. Moreover, it is investigated whether the predictive effect of personality can be attributed to symptom severity at baseline. We followed a cohort of 2566 persons (18-65 years) recruited in primary and specialized mental health care during two years. Personality dimensions at baseline were assessed with the NEO-FFI. The Diagnostic and Statistical Manual of Mental Disorders (4th ed.)-based diagnostic interviews with the CIDI allowed assessment of changes in comorbidity patterns of anxiety and depressive disorders over two years. Data were analyzed with latent class analysis (LCA) and latent transition analysis (LTA). LCA identified a four-class latent comorbidity class solution (Few Disorders, Fear Disorders, Distress Disorders, and Comorbid Fear and Distress Disorders) and a five-class latent personality class solution (High Resilients, Medium Resilients, Low Overcontrollers, Medium Overcontrollers, and High Overcontrollers). LTA showed that the likelihood of remaining in the same latent class was larger than that of transitioning to a less severe comorbidity class. Also, after correcting for symptom severity, medium and high Overcontrollers as well as participants with lower levels of conscientiousness were less likely to transition to a less severe comorbidity class. In particular, the individual trait of conscientiousness may be less dependent on current levels of anxiety and depressive symptoms and be a key pathoplastic or even predisposing variable in anxiety and depression and needs more theoretical and empirical study. (PsycINFO Database Record (c) 2012 APA, all rights reserved).

Panic disorder and its subtypes: a comprehensive analysis of panic symptom heterogeneity using epidemiological and treatment seeking samples

PubMed Central

Roberson-Nay, R.; Kendler, K. S.

2014-01-01

Background Panic disorder (PD) is a heterogeneous syndrome that can present with a variety of symptom profiles that potentially reflect distinct etiologic pathways. The present study represents the most comprehensive examination of phenotypic variance in PD with and without agoraphobia for the purpose of identifying clinically relevant and etiologically meaningful subtypes. Method Latent class (LC) and factor mixture analysis were used to examine panic symptom data ascertained from three national epidemiologic surveys [Epidemiological Catchment Area (ECA), National Comorbidity Study (NCS), National Epidemiologic Survey on Alcohol and Related Conditions (NESARC), Wave 1], a twin study [Virginia Adult Twin Study of Psychiatric and Substance Use Disorders (VATSPSUD)] and a clinical trial (Cross-National Collaborative Panic Study [CNCPS]). Results Factor mixture models (versus LC) generally provided better fit to panic symptom data and suggested two panic classes for the ECA, VATSPSUD and CNCPS, with one class typified by prominent respiratory symptoms. The NCS yielded two classes, but suggested both qualitative and quantitative differences. The more contemporary NESARC sample supported a two and three class model, with the three class model suggesting two variants of respiratory panic. The NESARC’s three class model continued to provide the best fit when the model was restricted to a more severe form of PD/panic disorder with agoraphobia. Conclusions Results from epidemiologic and clinical samples suggest two panic subtypes, with one subtype characterized by a respiratory component and a second class typified by general somatic symptoms. Results are discussed in light of their relevance to the etiopathogenesis of PD. PMID:21557895

Development of two socioeconomic indices for Saudi Arabia.

PubMed

AlOmar, Reem S; Parslow, Roger C; Law, Graham R

2018-06-26

Health and socioeconomic status (SES) are linked in studies worldwide. Measures of SES exist for many countries, however not for Saudi Arabia (SA). We describe two indices of area-based SES for SA. Routine census data has been used to construct two indices of SES at the geographically-delimited administrative region of Governorates in SA (n = 118). The data used included indicators of educational status, employment status, car and material ownership. A continuous measure of SES was constructed using exploratory factor analysis (EFA) and a categorical measure of SES using latent class analysis (LCA). Both indices were mapped by Governorates. The EFA identified three factors: The first explained 51.58% of the common variance within the interrelated factors, the second 15.14%, and the third 14.26%. These proportions were used in the formulation of the standard index. The scores were fixed to range from 100 for the affluent Governorate and 0 for the deprived. The LCA found a 4 class model as the best model fit. Class 1 was termed "affluent" and included 11.01% of Governorates, class 2 "upper middle class" (44.91%), class 3 "lower middle class" (33.05%) and class 4 "deprived" (11.01%). The populated urbanised Governorates were found to be the most affluent whereas the smaller rural Governorates were the most deprived. This is the first description of measures of SES in SA at a geographical level. Two measures have been successfully constructed and mapped. The maps show similar patterns suggesting validity. Both indices support the common perception of SES in SA.

Association Studies and Legume Synteny Reveal Haplotypes Determining Seed Size in Vigna unguiculata.

PubMed

Lucas, Mitchell R; Huynh, Bao-Lam; da Silva Vinholes, Patricia; Cisse, Ndiaga; Drabo, Issa; Ehlers, Jeffrey D; Roberts, Philip A; Close, Timothy J

2013-01-01

Highly specific seed market classes for cowpea and other grain legumes exist because grain is most commonly cooked and consumed whole. Size, shape, color, and texture are critical features of these market classes and breeders target development of cultivars for market acceptance. Resistance to biotic and abiotic stresses that are absent from elite breeding material are often introgressed through crosses to landraces or wild relatives. When crosses are made between parents with different grain quality characteristics, recovery of progeny with acceptable or enhanced grain quality is problematic. Thus genetic markers for grain quality traits can help in pyramiding genes needed for specific market classes. Allelic variation dictating the inheritance of seed size can be tagged and used to assist the selection of large seeded lines. In this work we applied 1,536-plex SNP genotyping and knowledge of legume synteny to characterize regions of the cowpea genome associated with seed size. These marker-trait associations will enable breeders to use marker-based selection approaches to increase the frequency of progeny with large seed. For 804 individuals derived from eight bi-parental populations, QTL analysis was used to identify markers linked to 10 trait determinants. In addition, the population structure of 171 samples from the USDA core collection was identified and incorporated into a genome-wide association study which supported more than half of the trait-associated regions important in the bi-parental populations. Seven of the total 10 QTLs were supported based on synteny to seed size associated regions identified in the related legume soybean. In addition to delivering markers linked to major trait determinants in the context of modern breeding, we provide an analysis of the diversity of the USDA core collection of cowpea to identify genepools, migrants, admixture, and duplicates.

Damage modeling and statistical analysis of optics damage performance in MJ-class laser systems.

PubMed

Liao, Zhi M; Raymond, B; Gaylord, J; Fallejo, R; Bude, J; Wegner, P

2014-11-17

Modeling the lifetime of a fused silica optic is described for a multiple beam, MJ-class laser system. This entails combining optic processing data along with laser shot data to account for complete history of optic processing and shot exposure. Integrating with online inspection data allows for the construction of a performance metric to describe how an optic performs with respect to the model. This methodology helps to validate the damage model as well as allows strategic planning and identifying potential hidden parameters that are affecting the optic's performance.

Patterns of adverse childhood experiences and substance use among young adults: A latent class analysis.

PubMed

Shin, Sunny H; McDonald, Shelby Elaine; Conley, David

2018-03-01

Adverse childhood experiences (ACEs) have been strongly linked with subsequent substance use. The aim of this study was to investigate how different patterns of ACEs influence substance use in young adulthood. Using a community sample of young individuals (N=336; ages 18-25), we performed latent class analyses (LCA) to identify homogenous groups of young people with similar patterns of ACEs. Exposure to ACEs incorporates 13 childhood adversities including childhood maltreatment, household dysfunction, and community violence. Multiple linear and logistic regression models were used in an effort to examine the associations between ACEs classes and four young adult outcomes such as alcohol-related problems, current tobacco use, drug dependence symptoms, and psychological distress. LCA identified four heterogeneous classes of young people distinguished by different patterns of ACEs exposure: Low ACEs (56%), Household Dysfunction/Community Violence (14%), Emotional ACEs (14%), and High/Multiple ACEs (16%). Multiple regression analyses found that compared to those in the Low ACEs class, young adults in the High/Multiple ACEs class reported more alcohol-related problems, current tobacco use, and psychological symptoms, controlling for sociodemographic characteristics and common risk factors for substance use such as peer substance use. Our findings confirm that for many young people, ACEs occur as multiple rather than single experiences. The results of this research suggest that exposure to poly-victimization during childhood is particularly related to substance use during young adulthood. Copyright © 2017 Elsevier Ltd. All rights reserved.

Errors Analysis of Solving Linear Inequalities among the Preparatory Year Students at King Saud University

ERIC Educational Resources Information Center

El-khateeb, Mahmoud M. A.

2016-01-01

The purpose of this study aims to investigate the errors classes occurred by the Preparatory year students at King Saud University, through analysis student responses to the items of the study test, and to identify the varieties of the common errors and ratios of common errors that occurred in solving inequalities. In the collection of the data,…

Department-Generated Microcomputer Software.

ERIC Educational Resources Information Center

Mantei, Erwin J.

1986-01-01

Explains how self-produced software can be used to perform rapid number analysis or number-crunching duties in geology classes. Reviews programs in mineralogy and petrology and identifies areas in geology where computers can be used effectively. Discusses the advantages and benefits of integrating department-generated software into a geology…

Searching for chemical classes among metal-poor stars using medium-resolution spectroscopy

NASA Astrophysics Data System (ADS)

Cruz, Monique A.; Cogo-Moreira, Hugo; Rossi, Silvia

2018-04-01

Astronomy is in the era of large spectroscopy surveys, with the spectra of hundreds of thousands of stars in the Galaxy being collected. Although most of these surveys have low or medium resolution, which makes precise abundance measurements not possible, there is still important information to be extracted from the available data. Our aim is to identify chemically distinct classes among metal-poor stars, observed by the Sloan Digital Sky Survey, using line indices. The present work focused on carbon-enhanced metal-poor (CEMP) stars and their subclasses. We applied the latent profile analysis technique to line indices for carbon, barium, iron and europium, in order to separate the sample into classes with similar chemical signatures. This technique provides not only the number of possible groups but also the probability of each object to belong to each class. The method was able to distinguish at least two classes among the observed sample, with one of them being probable CEMP stars enriched in s-process elements. However, it was not able to separate CEMP-no stars from the rest of the sample. Latent profile analysis is a powerful model-based tool to be used in the identification of patterns in astrophysics. Our tests show the potential of the technique for the attainment of additional chemical information from `poor' data.

Child abuse and neglect profiles and their psychosocial consequences in a large sample of incarcerated males.

PubMed

Debowska, Agata; Boduszek, Daniel

2017-03-01

Research examining child abuse and neglect (CAN) profiles among adult offender populations is lacking. Therefore, the primary aim of the present study was to address this limitation by using latent class analysis (LCA) to identify meaningful classes of individuals who have experienced physical abuse, emotional abuse, sexual abuse, as well as neglect. Another aim was to estimate the association between CAN class membership and external criteria (psychopathy factors, self-esteem, attitudes towards male sexual violence in dating relationships, child sexual abuse myth acceptance, violent offending, and age). Data were collected among a large systematically selected sample of adult male inmates (N=1261). Based on LCA, three unique classes of CAN were distinguished, including a 'low abuse' group (43.4% of the sample), a 'high physical and emotional abuse' group (51.3%), and a 'poly-victimized' group (5.3%). The analysis revealed that the CAN classes were differentially associated with affective responsiveness, cognitive responsiveness, personal self-esteem, prison self-esteem, attitudes towards male sexual violence in dating relationships, and violent offending. Findings highlight the unique nature of CAN constellations among criminal justice involved participants. The significance of the present results is discussed in relation to past and future research. Potential contributions to treatment strategies are also presented. Copyright © 2016 Elsevier Ltd. All rights reserved.

Heterogeneity of postpartum depression: a latent class analysis

PubMed Central

2016-01-01

Summary Background Maternal depression in the postpartum period confers substantial morbidity and mortality, but the definition of postpartum depression remains controversial. We investigated the heterogeneity of symptoms with the aim of identifying clinical subtypes of postpartum depression. Methods Data were aggregated from the international perinatal psychiatry consortium Postpartum Depression: Action Towards Causes and Treatment, which represents 19 institutions in seven countries. 17 912 unique subject records with phenotypic data were submitted. We applied latent class analyses in a two-tiered approach to assess the validity of empirically defined subtypes of postpartum depression. Tier one assessed heterogeneity in women with complete data on the Edinburgh postnatal depression scale (EPDS) and tier two in those with postpartum depression case status. Findings 6556 individuals were assessed in tier one and 4245 in tier two. A final model with three latent classes was optimum for both tiers. The most striking characteristics associated with postpartum depression were severity, timing of onset, comorbid anxiety, and suicidal ideation. Women in class 1 had the least severe symptoms (mean EPDS score 10·5), followed by those in class 2 (mean EPDS score 14·8) and those in class 3 (mean EPDS score 20·1). The most severe symptoms of postpartum depression were significantly associated with poor mood (mean EPDS score 20·1), increased anxiety, onset of symptoms during pregnancy, obstetric complications, and suicidal ideation. In class 2, most women (62%) reported symptom onset within 4 weeks postpartum and had more pregnancy complications than in other two classes (69% vs 67% in class 1 and 29% in class 3). Interpretation PPD seems to have several distinct phenotypes. Further assessment of PPD heterogeneity to identify more precise phenotypes will be important for future biological and genetic investigations. Funding Sources of funding are listed at the end of the article. PMID:26359613

The Role of HLA Class I Gene Variation in Autoimmune Diabetes

PubMed Central

Sia, Charles; Weinem, Michael

2005-01-01

The use of DNA-based genetic typing has enabled the identification of type 1 diabetes mellitus (T1DM) susceptible and protective major histocompatibility complex (MHC) class II alleles and haplotypes. The application of this approach has also progressed to locate MHC class I alleles that contribute to the clinicopathology of T1DM. Recent studies have shown a widespread involvement of genes from the MHC class I gene region in the clinicopathology of T1DM. These genes are shown to be involved in contributing to progression from the preclinical stage of the disease, which is characterized by the occurrence of islet-specific antibodies, to clinical disease and also to the occurrence of autoimmunity. They can either contribute directly to disease development or indirectly in concert with other susceptible MHC class II alleles or haplotypes via linkage disequilibrium. Class I alleles may also be negatively associated with T1DM. These findings are useful for the development of future strategies in designing tolerogenic approaches for the prevention or even reversal of T1DM. In this article, the latest evidence for the different kinds of participation of HLA class I genes in the etiology of T1DM is reviewed. A meta-analysis which included existing association studies was also carried out in order to re-assess the relevance of class I genes in diabetes development. The analysis of an enlarged heterogeneous sample confirmed the involvement of previously detected serotypes in the etiology of T1DM, such as A24, B8 and B18, and revealed hitherto unknown associations with B60 and B62. The analysis points out that much of the conflicting results of previous association studies originate from inadequate sample sizes and accentuate the value of future investigations of larger samples for identifying linkage in multigenic diseases. PMID:17491685

A latent class analysis of social activities and health among community-dwelling older adults in Korea.

PubMed

Park, Mi Jin; Park, Nan Sook; Chiriboga, David A

2018-05-01

This study presents an empirical typology of social activity and its association with the depressive symptoms and self-rated health of community-dwelling older adults (n = 464) in South Korea. Latent class analysis (LCA) was used to classify the types of social activities. Data analyses were conducted using Mplus 7.2 program for LCA and SPSS 22.0 for multiple regression analyses. LCA identified people who fell into one of the four activity groups: Diverse, Community Center/Disengaged, Religion Plus, and Friendship/Leisure. Membership in these four groups predicted differences in depressive symptoms and self-rated health. Results indicate that typologies of social activity could enhance practitioners' understanding of activity patterns and their associations with health and well-being.

Programming Probabilistic Structural Analysis for Parallel Processing Computer

NASA Technical Reports Server (NTRS)

Sues, Robert H.; Chen, Heh-Chyun; Twisdale, Lawrence A.; Chamis, Christos C.; Murthy, Pappu L. N.

1991-01-01

The ultimate goal of this research program is to make Probabilistic Structural Analysis (PSA) computationally efficient and hence practical for the design environment by achieving large scale parallelism. The paper identifies the multiple levels of parallelism in PSA, identifies methodologies for exploiting this parallelism, describes the development of a parallel stochastic finite element code, and presents results of two example applications. It is demonstrated that speeds within five percent of those theoretically possible can be achieved. A special-purpose numerical technique, the stochastic preconditioned conjugate gradient method, is also presented and demonstrated to be extremely efficient for certain classes of PSA problems.

Child Conduct Problems across Home and School Contexts: A Person-Centered Approach

PubMed Central

Sulik, Michael J.; Blair, Clancy; Greenberg, Mark

2018-01-01

To examine patterns of conduct problems across the home and school context, we used latent class analysis to analyze primary caregivers' and teachers' ratings on the conduct problems subscale of the Strengths and Difficulties Questionnaire (R. Goodman, 1997) in the Family Life Project (N = 1,292), a prospective study of child development in rural and small town contexts. We found a similar four-class solution at five and seven years of age. In decreasing prevalence, the following classes were identified: (1) low symptoms reported by both informants (low cross-context); (2) high parent-reported symptoms, low teacher-reported symptoms (home context); (3) low parent-reported symptoms, moderate teacher-reported symptoms (school context); and (4) high symptoms reported by both informants (high cross-context). Classes exhibited stability from age five to age seven: children were more likely to remain in the same class than to transition to a different class, and longitudinal stability was especially high for children in the low cross-context class at age 5. A number of child and family characteristics measured in early childhood (executive function, verbal ability, poverty-related risk, sensitive parenting, and parental depressive symptoms) were associated with class membership at age five and age seven, but were generally not associated with longitudinal transitions between classes. PMID:29720784

Adolescent stalking and risk of violence.

PubMed

Smith-Darden, Joanne P; Reidy, Dennis E; Kernsmith, Poco D

2016-10-01

Stalking perpetration and the associated risk for violence among adolescents has generally been neglected. In the present study, 1236 youth completed surveys assessing empirically established stalking indicators, threats and aggression toward stalking victims, dating violence, and violent delinquency. Latent Profile Analysis identified 3 latent classes of boys: non-perpetrators (NP), hyper-intimate pursuit (HIP), and comprehensive stalking perpetrators (CSP) and, and 2 classes for girls: NP and HIP. Boys in the CSP class were the most violent youth on nearly all indices with boys in the HIP class demonstrating an intermediate level of violence compared to NP boys. Girls in the HIP class were more violent than NP girls on all indices. These findings suggest stalking in adolescence merits attention by violence prevention experts. In particular, juvenile stalking may signify youth at risk for multiple forms of violence perpetrated against multiple types of victims, not just the object of their infatuation. Copyright © 2016 The Foundation for Professionals in Services for Adolescents. Published by Elsevier Ltd. All rights reserved.

Analysis of A Drug Target-based Classification System using Molecular Descriptors.

PubMed

Lu, Jing; Zhang, Pin; Bi, Yi; Luo, Xiaomin

2016-01-01

Drug-target interaction is an important topic in drug discovery and drug repositioning. KEGG database offers a drug annotation and classification using a target-based classification system. In this study, we gave an investigation on five target-based classes: (I) G protein-coupled receptors; (II) Nuclear receptors; (III) Ion channels; (IV) Enzymes; (V) Pathogens, using molecular descriptors to represent each drug compound. Two popular feature selection methods, maximum relevance minimum redundancy and incremental feature selection, were adopted to extract the important descriptors. Meanwhile, an optimal prediction model based on nearest neighbor algorithm was constructed, which got the best result in identifying drug target-based classes. Finally, some key descriptors were discussed to uncover their important roles in the identification of drug-target classes.

Mars Exploration Rovers Entry, Descent, and Landing Trajectory Analysis

NASA Technical Reports Server (NTRS)

Desai, Prasun N.; Knocke, Philip C.

2007-01-01

In this study we present a novel method of land surface classification using surface-reflected GPS signals in combination with digital imagery. Two GPS-derived classification features are merged with visible image data to create terrain-moisture (TM) classes, defined here as visibly identifiable terrain or landcover classes containing a surface/soil moisture component. As compared to using surface imagery alone, classification accuracy is significantly improved for a number of visible classes when adding the GPS-based signal features. Since the strength of the reflected GPS signal is proportional to the amount of moisture in the surface, use of these GPS features provides information about the surface that is not obtainable using visible wavelengths alone. Application areas include hydrology, precision agriculture, and wetlands mapping.

INSIGHT responsive parenting intervention is associated with healthier patterns of dietary exposures in infants.

PubMed

Hohman, Emily E; Paul, Ian M; Birch, Leann L; Savage, Jennifer S

2017-01-01

To determine whether a responsive parenting (RP) intervention affects infant dietary patterns. Primiparous mother-newborn dyads (n = 291) were randomized to the Intervention Nurses Start Infants Growing on Healthy Trajectories (INSIGHT) RP intervention or control. Curricula were delivered at nurse home visits at ages 3, 16, 28, and 40 weeks. RP group feeding guidance advised responsive feeding, delayed introduction of solids, repeated exposure to novel foods, and age-appropriate portion sizes. Latent class analysis identified patterns of dietary exposure at 9 months. Class membership at 9 months was used to predict BMI percentile at 2 years. Five dietary patterns were identified: "Breastfed, Fruits and Vegetables," "Breastfed, Low Variety," "Formula, Fruits and Vegetables," "Formula, Low Variety," and "Formula, High Energy Density." Over 60% of infants had patterns low in fruits and vegetables or high in energy-dense foods. RP group infants were less likely than control to be in the "Formula, Low Variety" class (OR = 0.40, 95% CI 0.23-0.71) or "Formula, High Energy Density" class (OR = 0.28, 95% CI 0.12-0.61) relative to the "Formula, Fruits and Vegetables" class. Dietary pattern at 9 months was significantly associated with BMI percentile at 2 years. While a majority of infants consumed diets low in fruits and vegetables, the INSIGHT RP intervention was associated with healthier dietary patterns. © 2016 The Obesity Society.

Interactions between lower urinary tract symptoms and cardiovascular risk factors determine distinct patterns of erectile dysfunction: a latent class analysis.

PubMed

Barbosa, João A B A; Muracca, Eduardo; Nakano, Élcio; Assalin, Adriana R; Cordeiro, Paulo; Paranhos, Mario; Cury, José; Srougi, Miguel; Antunes, Alberto A

2013-12-01

An epidemiological association between lower urinary tract symptoms and erectile dysfunction is well established. However, interactions among multiple risk factors and the role of each in pathological mechanisms are not fully elucidated We enrolled 898 men undergoing prostate cancer screening for evaluation with the International Prostate Symptom Score (I-PSS) and simplified International Index of Erectile Function-5 (IIEF-5) questionnaires. Age, race, hypertension, diabetes, dyslipidemia, metabolic syndrome, cardiovascular disease, serum hormones and anthropometric parameters were also evaluated. Risk factors for erectile dysfunction were identified by logistic regression. The 333 men with at least mild to moderate erectile dysfunction (IIEF 16 or less) were included in a latent class model to identify relationships across erectile dysfunction risk factors. Age, hypertension, diabetes, lower urinary tract symptoms and cardiovascular event were independent predictors of erectile dysfunction (p<0.05). We identified 3 latent classes of patients with erectile dysfunction (R2 entropy=0.82). Latent class 1 had younger men at low cardiovascular risk and a moderate/high prevalence of lower urinary tract symptoms. Latent class 2 had the oldest patients at moderate cardiovascular risk with an increased prevalence of lower urinary tract symptoms. Latent class 3 had men of intermediate age with the highest prevalence of cardiovascular risk factors and lower urinary tract symptoms. Erectile dysfunction severity and lower urinary tract symptoms increased from latent class 1 to 3. Risk factor interactions determined different severities of lower urinary tract symptoms and erectile dysfunction. The effect of lower urinary tract symptoms and cardiovascular risk outweighed that of age. While in the youngest patients lower urinary tract symptoms acted as a single risk factor for erectile dysfunction, the contribution of vascular disease resulted in significantly more severe dysfunction. Applying a risk factor interaction model to prospective trials could reveal distinct classes of drug responses and help define optimal treatment strategies for specific groups. Copyright © 2013 American Urological Association Education and Research, Inc. Published by Elsevier Inc. All rights reserved.

External Validation of the European Hernia Society Classification for Postoperative Complications after Incisional Hernia Repair: A Cohort Study of 2,191 Patients.

PubMed

Kroese, Leonard F; Kleinrensink, Gert-Jan; Lange, Johan F; Gillion, Jean-Francois

2018-03-01

Incisional hernia is a frequent complication after midline laparotomy. Surgical hernia repair is associated with complications, but no clear predictive risk factors have been identified. The European Hernia Society (EHS) classification offers a structured framework to describe hernias and to analyze postoperative complications. Because of its structured nature, it might prove to be useful for preoperative patient or treatment classification. The objective of this study was to investigate the EHS classification as a predictor for postoperative complications after incisional hernia surgery. An analysis was performed using a registry-based, large-scale, prospective cohort study, including all patients undergoing incisional hernia surgery between September 1, 2011 and February 29, 2016. Univariate analyses and multivariable logistic regression analysis were performed to identify risk factors for postoperative complications. A total of 2,191 patients were included, of whom 323 (15%) had 1 or more complications. Factors associated with complications in univariate analyses (p < 0.20) and clinically relevant factors were included in the multivariable analysis. In the multivariable analysis, EHS width class, incarceration, open surgery, duration of surgery, Altemeier wound class, and therapeutic antibiotic treatment were independent risk factors for postoperative complications. Third recurrence and emergency surgery were associated with fewer complications. Incisional hernia repair is associated with a 15% complication rate. The EHS width classification is associated with postoperative complications. To identify patients at risk for complications, the EHS classification is useful. Copyright © 2017. Published by Elsevier Inc.

Classes of conduct disorder symptoms and their life course correlates in a US national sample.

PubMed

Breslau, J; Saito, N; Tancredi, D J; Nock, M; Gilman, S E

2012-05-01

Population data on conduct disorder (CD) symptoms can help determine whether hypothesized subtypes of CD are sufficiently disparate in their familial, psychiatric and life course correlates to distinguish separate diagnostic entities. Latent class analysis (LCA) of CD symptoms occurring before age 15 was conducted in a national sample of adults aged 18-44 years from the National Epidemiological Study of Alcohol and Related Conditions. Associations of latent class membership with parental behavior problems, onset of psychiatric disorders and anti-social behaviors after age 15, adolescent life events (e.g. high school drop-out), and past-year life events (e.g. divorce/separation, bankruptcy) were estimated. LCA identified a no-CD class with low prevalence of all symptoms, three intermediate classes - deceit/theft, rule violations, aggression - and a severe class. The prevalence of CD, according to DSM-IV criteria, was 0% in the no-CD class, between 13.33% and 33.69% in the intermediate classes and 62.20% in the severe class. Latent class membership is associated with all the familial, psychiatric and life course outcomes examined. Among the intermediate classes, risk for subsequent mood/anxiety disorders and anti-social behavior was higher in the deceit/theft and aggressive classes than in the rule violations class. However, risk for adolescent life events is highest in the rule violations class. CD symptoms tend to occur in a partially ordered set of classes in the general population. Prognostically meaningful distinctions can be drawn between classes, but only at low levels of symptoms.

The viral transcription group determines the HLA class I cellular immune response against human respiratory syncytial virus.

PubMed

Johnstone, Carolina; Lorente, Elena; Barriga, Alejandro; Barnea, Eilon; Infantes, Susana; Lemonnier, François A; David, Chella S; Admon, Arie; López, Daniel

2015-04-01

The cytotoxic T-lymphocyte-mediated killing of virus-infected cells requires previous recognition of short viral antigenic peptides bound to human leukocyte antigen class I molecules that are exposed on the surface of infected cells. The cytotoxic T-lymphocyte response is critical for the clearance of human respiratory syncytial virus infection. In this study, naturally processed viral human leukocyte antigen class I ligands were identified with mass spectrometry analysis of complex human leukocyte antigen-bound peptide pools isolated from large amounts of human respiratory syncytial virus-infected cells. Acute antiviral T-cell response characterization showed that viral transcription determines both the immunoprevalence and immunodominance of the human leukocyte antigen class I response to human respiratory syncytial virus. These findings have clear implications for antiviral vaccine design. © 2015 by The American Society for Biochemistry and Molecular Biology, Inc.

Understanding fall meaning and context in marketing balance classes to older adults.

PubMed

Clark, Lauren; Thoreson, Sallie; Goss, Cynthia W; Zimmer, Lorena Marquez; Marosits, Mark; DiGuiseppi, Carolyn

2013-02-01

This study explored older, community-dwelling adults' attitudes and values about proposed church-delivered balance classes for fall prevention. Community observation, group interviews with stakeholders, key informant interviews, and focus groups with church members ≥ 60 years of age were analyzed in two ways: first for inductive themes expressing community sentiment about fall prevention for older adults, then for content useful in creating locally tailored social marketing messages. Four themes expressed perceptions of fall-prevention programming: de-emphasizing fall risk and emphasizing strength and independence, moving older adults out of their "comfort zones" to join classes, identifying relationships to support fall-prevention activities, and considering gender-based differences in approaches to fall prevention. A content analysis of the same dataset yielded information about preferred places in the community, promotion through churches, a tolerable price, and the balance class product itself. The qualitative results will inform the social marketing program to increase intervention delivery success.

An empirical analysis of ontology reuse in BioPortal.

PubMed

Ochs, Christopher; Perl, Yehoshua; Geller, James; Arabandi, Sivaram; Tudorache, Tania; Musen, Mark A

2017-07-01

Biomedical ontologies often reuse content (i.e., classes and properties) from other ontologies. Content reuse enables a consistent representation of a domain and reusing content can save an ontology author significant time and effort. Prior studies have investigated the existence of reused terms among the ontologies in the NCBO BioPortal, but as of yet there has not been a study investigating how the ontologies in BioPortal utilize reused content in the modeling of their own content. In this study we investigate how 355 ontologies hosted in the NCBO BioPortal reuse content from other ontologies for the purposes of creating new ontology content. We identified 197 ontologies that reuse content. Among these ontologies, 108 utilize reused classes in the modeling of their own classes and 116 utilize reused properties in class restrictions. Current utilization of reuse and quality issues related to reuse are discussed. Copyright © 2017 Elsevier Inc. All rights reserved.

Statistical analysis and definition of blockages-prediction formulae for the wastewater network of Oslo by evolutionary computing.

PubMed

Ugarelli, Rita; Kristensen, Stig Morten; Røstum, Jon; Saegrov, Sveinung; Di Federico, Vittorio

2009-01-01

Oslo Vann og Avløpsetaten (Oslo VAV)-the water/wastewater utility in the Norwegian capital city of Oslo-is assessing future strategies for selection of most reliable materials for wastewater networks, taking into account not only material technical performance but also material performance, regarding operational condition of the system.The research project undertaken by SINTEF Group, the largest research organisation in Scandinavia, NTNU (Norges Teknisk-Naturvitenskapelige Universitet) and Oslo VAV adopts several approaches to understand reasons for failures that may impact flow capacity, by analysing historical data for blockages in Oslo.The aim of the study was to understand whether there is a relationship between the performance of the pipeline and a number of specific attributes such as age, material, diameter, to name a few. This paper presents the characteristics of the data set available and discusses the results obtained by performing two different approaches: a traditional statistical analysis by segregating the pipes into classes, each of which with the same explanatory variables, and a Evolutionary Polynomial Regression model (EPR), developed by Technical University of Bari and University of Exeter, to identify possible influence of pipe's attributes on the total amount of predicted blockages in a period of time.Starting from a detailed analysis of the available data for the blockage events, the most important variables are identified and a classification scheme is adopted.From the statistical analysis, it can be stated that age, size and function do seem to have a marked influence on the proneness of a pipeline to blockages, but, for the reduced sample available, it is difficult to say which variable it is more influencing. If we look at total number of blockages the oldest class seems to be the most prone to blockages, but looking at blockage rates (number of blockages per km per year), then it is the youngest class showing the highest blockage rate. EPR allowed identifying the relation between attitude to block and pipe's attributes in order to understand what affects the possibility to have a blockage in the pipe. EPR provides formulae to compute the accumulated number of blockages for a pipe class at the end of a given period of time. Those formulae do not represent simply regression models but highlight those variables which affect the physical phenomenon in question.

Content analysis to detect high stress in oral interviews and text documents

NASA Technical Reports Server (NTRS)

Thirumalainambi, Rajkumar (Inventor); Jorgensen, Charles C. (Inventor)

2012-01-01

A system of interrogation to estimate whether a subject of interrogation is likely experiencing high stress, emotional volatility and/or internal conflict in the subject's responses to an interviewer's questions. The system applies one or more of four procedures, a first statistical analysis, a second statistical analysis, a third analysis and a heat map analysis, to identify one or more documents containing the subject's responses for which further examination is recommended. Words in the documents are characterized in terms of dimensions representing different classes of emotions and states of mind, in which the subject's responses that manifest high stress, emotional volatility and/or internal conflict are identified. A heat map visually displays the dimensions manifested by the subject's responses in different colors, textures, geometric shapes or other visually distinguishable indicia.

Individual and Class Norms Differentially Predict Proactive and Reactive Aggression: A Functional Analysis

ERIC Educational Resources Information Center

Frey, Karin S.; Higheagle Strong, Zoe; Onyewuenyi, Adaurennaya C.

2017-01-01

Theory and research using a social-information processing framework indicate that reward-focused (proactive) aggression has different social consequences than defense-focused (reactive) aggression. Students use norms that identify expected and socially approved behaviors as guides to their own actions. Differences in social-cognitive processing…

Analysis of a MULE-cyanide hydratase gene fusion in Verticillium dahliae

USDA-ARS?s Scientific Manuscript database

The genome of the phytopathogenic fungus Verticillium dahliae encodes numerous Class II “cut-and-paste” transposable elements, including those of a small group of MULE transposons. We have previously identified a fusion event between a MULE transposon sequence and sequence encoding a cyanide hydrata...

Open Classes to Local Communities: A Reflection Analysis of a School Environmental Project

ERIC Educational Resources Information Center

Kalathaki, Maria

2017-01-01

School projects of environmental education promote discovery learning, through teamwork, by involving local communities, scientists, organizations, authorities, and bodies and are carried out largely online in virtual environments. This research aimed to identify and highlight those characteristics of local communities that can be exploited by…

Characterizing High School Chemistry Teachers' Use of Assessment Data via Latent Class Analysis

ERIC Educational Resources Information Center

Harshman, Jordan; Yezierski, Ellen

2016-01-01

In this study, which builds on a previous qualitative study and literature review, high school chemistry teachers' characteristics regarding the design of chemistry formative assessments and interpretation of results for instructional improvement are identified. The Adaptive Chemistry Assessment Survey for Teachers (ACAST) was designed to elicit…

Contributions to Variations in Academic Trajectories amongst Recent Immigrant Youth

ERIC Educational Resources Information Center

Suarez-Orozco, Carola; Bang, Hee Jin; Onaga, Marie

2010-01-01

Immigration presents both challenges and opportunities that affect students' academic achievement. Over the course of five years, varying academic trajectories were identified for recent immigrant students from Central America, China, the Dominican Republic, Haiti, and Mexico. Latent class growth curve analysis revealed that although some students…

Identifying Transfer Student Subgroups by Academic and Social Adjustment: A Latent Class Analysis

ERIC Educational Resources Information Center

Fematt, Veronica Lavenant

2017-01-01

Community college transfer students often experience "transfer shock" at receiving four-year institutions, which includes a variety of academic, social, and institutional challenges associated with the first-year transfer experience. Research has demonstrated that first-year program interventions can facilitate the transition of…

Youth with Psychopathy Features Are Not a Discrete Class: A Taxometric Analysis

ERIC Educational Resources Information Center

Murrie, Daniel C.; Marcus, David K.; Douglas, Kevin S.; Lee, Zina; Salekin, Randall T.; Vincent, Gina

2007-01-01

Background: Recently, researchers have sought to measure psychopathy-like features among youth in hopes of identifying children who may be progressing toward a particularly destructive form of adult pathology. However, it remains unclear whether psychopathy-like personality features among youth are best conceptualized as dimensional (distributed…

Classifying Korean Adolescents' Career Preparedness

ERIC Educational Resources Information Center

Lee, In Heok; Rojewski, Jay W.; Hill, Roger B.

2013-01-01

Latent class analysis was used to examine the career preparation of 5,227 11th-grade Korean adolescents taken from the Korean Education Longitudinal Study of 2005 (KELS:2005). Three career preparedness groups were identified, to reflecting Skorikov's ("J Vocat Behav" 70:8-24, 2007) conceptualization of career preparedness: prepared,…

Immigrant Success Stories in ESL Textbooks

ERIC Educational Resources Information Center

Gulliver, Trevor

2010-01-01

Immigrant success stories found in English as a second language (ESL) textbooks used in government-funded language instruction in Canada imagine Canada as a redeemer of immigrant newcomers. Through a critical discourse analysis of ESL textbooks used in Language Instruction for Newcomers to Canada classes in Ontario, I identify two primary…

A USER'S GUIDE TO ALDEHYDE ANALYSIS USING PFBHA DERIVATIZATION AND GC/ECD DETECTION: AVOIDING THE PITFALLS

EPA Science Inventory

Aldehydes are of interest because they have been identified as by-products of drinking water disinfection, particularly ozonation. In order to monitor treatment practices, assess exposure to consumers, and control health risks that might be associated with this class of by-produ...

Enhanced Lipidome Coverage in Shotgun Analyses by using Gas-Phase Fractionation

NASA Astrophysics Data System (ADS)

Nazari, Milad; Muddiman, David C.

2016-11-01

A high resolving power shotgun lipidomics strategy using gas-phase fractionation and data-dependent acquisition (DDA) was applied toward comprehensive characterization of lipids in a hen ovarian tissue in an untargeted fashion. Using this approach, a total of 822 unique lipids across a diverse range of lipid categories and classes were identified based on their MS/MS fragmentation patterns. Classes of glycerophospholipids and glycerolipids, such as glycerophosphocholines (PC), glycerophosphoethanolamines (PE), and triglycerides (TG), are often the most abundant peaks observed in shotgun lipidomics analyses. These ions suppress the signal from low abundance ions and hinder the chances of characterizing low abundant lipids when DDA is used. These issues were circumvented by utilizing gas-phase fractionation, where DDA was performed on narrow m/z ranges instead of a broad m/z range. Employing gas-phase fractionation resulted in an increase in sensitivity by more than an order of magnitude in both positive- and negative-ion modes. Furthermore, the enhanced sensitivity increased the number of lipids identified by a factor of ≈4, and facilitated identification of low abundant lipids from classes such as cardiolipins that are often difficult to observe in untargeted shotgun analyses and require sample-specific preparation steps prior to analysis. This method serves as a resource for comprehensive profiling of lipids from many different categories and classes in an untargeted manner, as well as for targeted and quantitative analyses of individual lipids. Furthermore, this comprehensive analysis of the lipidome can serve as a species- and tissue-specific database for confident identification of other MS-based datasets, such as mass spectrometry imaging.

Detecting Unknown Artificial Urban Surface Materials Based on Spectral Dissimilarity Analysis.

PubMed

Jilge, Marianne; Heiden, Uta; Habermeyer, Martin; Mende, André; Juergens, Carsten

2017-08-08

High resolution imaging spectroscopy data have been recognised as a valuable data resource for augmenting detailed material inventories that serve as input for various urban applications. Image-specific urban spectral libraries are successfully used in urban imaging spectroscopy studies. However, the regional- and sensor-specific transferability of such libraries is limited due to the wide range of different surface materials. With the developed methodology, incomplete urban spectral libraries can be utilised by assuming that unknown surface material spectra are dissimilar to the known spectra in a basic spectral library (BSL). The similarity measure SID-SCA (Spectral Information Divergence-Spectral Correlation Angle) is applied to detect image-specific unknown urban surfaces while avoiding spectral mixtures. These detected unknown materials are categorised into distinct and identifiable material classes based on their spectral and spatial metrics. Experimental results demonstrate a successful redetection of material classes that had been previously erased in order to simulate an incomplete BSL. Additionally, completely new materials e.g., solar panels were identified in the data. It is further shown that the level of incompleteness of the BSL and the defined dissimilarity threshold are decisive for the detection of unknown material classes and the degree of spectral intra-class variability. A detailed accuracy assessment of the pre-classification results, aiming to separate natural and artificial materials, demonstrates spectral confusions between spectrally similar materials utilizing SID-SCA. However, most spectral confusions occur between natural or artificial materials which are not affecting the overall aim. The dissimilarity analysis overcomes the limitations of working with incomplete urban spectral libraries and enables the generation of image-specific training databases.

Detecting Unknown Artificial Urban Surface Materials Based on Spectral Dissimilarity Analysis

PubMed Central

Jilge, Marianne; Heiden, Uta; Habermeyer, Martin; Mende, André; Juergens, Carsten

2017-01-01

High resolution imaging spectroscopy data have been recognised as a valuable data resource for augmenting detailed material inventories that serve as input for various urban applications. Image-specific urban spectral libraries are successfully used in urban imaging spectroscopy studies. However, the regional- and sensor-specific transferability of such libraries is limited due to the wide range of different surface materials. With the developed methodology, incomplete urban spectral libraries can be utilised by assuming that unknown surface material spectra are dissimilar to the known spectra in a basic spectral library (BSL). The similarity measure SID-SCA (Spectral Information Divergence-Spectral Correlation Angle) is applied to detect image-specific unknown urban surfaces while avoiding spectral mixtures. These detected unknown materials are categorised into distinct and identifiable material classes based on their spectral and spatial metrics. Experimental results demonstrate a successful redetection of material classes that had been previously erased in order to simulate an incomplete BSL. Additionally, completely new materials e.g., solar panels were identified in the data. It is further shown that the level of incompleteness of the BSL and the defined dissimilarity threshold are decisive for the detection of unknown material classes and the degree of spectral intra-class variability. A detailed accuracy assessment of the pre-classification results, aiming to separate natural and artificial materials, demonstrates spectral confusions between spectrally similar materials utilizing SID-SCA. However, most spectral confusions occur between natural or artificial materials which are not affecting the overall aim. The dissimilarity analysis overcomes the limitations of working with incomplete urban spectral libraries and enables the generation of image-specific training databases. PMID:28786947

Analysis of rice purchase decision on rice consumer in Bandung city

NASA Astrophysics Data System (ADS)

Kusno, K.; Imannurdin, A.; Syamsiyah, N.; Djuwendah, E.

2018-03-01

This study was conducted at three kinds of purchase location which were traditional market, rice kiosk, and supermarket in Bandung City, with survey data of 108 respondents which were selected by systematic random sampling. The aim of this study is to (1) identify consumer characteristics, (2) identify which atribute is considered by consumer in buying rice, and (3) analyze the relationship between purchase decision and income class. Data were analyzed by descriptive analysis and Chi Square test. The results showed most consumers in the traditional market were middle-educated and lower middle-income, at the rice kiosk, the consumer were generally middle-educated and middle-income, and in the supermarkets, the majority were high-educated and upper middle-income consumers. “Kepulenan” be the first priority of most consumers, but for the lower-middle class, the main priority was price. Thus, in case of scarcity and rice price increase, the government should immediately arrange market operations which targeting to lower-middle class consumers. There was a significant relationship between (1) the quality of rice consumed, (2) the frequency of rice purchase per month, and (3) attitudes toward rice price increase; each with the income class. Although the price of rice increase, consumers of middle and upper-middle were remain loyal to the quality of rice they consumed. This indicates rice market in Bandung city is an ideal market for premium rice so that traders and producers are expected to maintain the quality of rice, such as keep using superior seeds and applying good cultivation based on Good Agricultural Practice (GAP) rules.

Learning from examples - Generation and evaluation of decision trees for software resource analysis

NASA Technical Reports Server (NTRS)

Selby, Richard W.; Porter, Adam A.

1988-01-01

A general solution method for the automatic generation of decision (or classification) trees is investigated. The approach is to provide insights through in-depth empirical characterization and evaluation of decision trees for software resource data analysis. The trees identify classes of objects (software modules) that had high development effort. Sixteen software systems ranging from 3,000 to 112,000 source lines were selected for analysis from a NASA production environment. The collection and analysis of 74 attributes (or metrics), for over 4,700 objects, captured information about the development effort, faults, changes, design style, and implementation style. A total of 9,600 decision trees were automatically generated and evaluated. The trees correctly identified 79.3 percent of the software modules that had high development effort or faults, and the trees generated from the best parameter combinations correctly identified 88.4 percent of the modules on the average.

A new class of anthocyanin-procyanidin condensation products detected in red wine by electrospray ionization multi-stage mass spectrometry analysis.

PubMed

Sun, Baoshan; Fernandes, Tiago A; Spranger, M Isabel

2010-02-01

In our previous work, we have identified, in a model wine solution containing malvidin 3-glucoside, epicatechin and acetaldehyde, a new condensation product--hydroxylethyl-malvidin-3-glucoside-ethyl-epicatechin. The objective of this work was to verify the presence of such new condensation products in red wine. For this purpose, red wine was fractionated into various fractions by column chromatography on LiChroprep RP 18 and on Toyopearl 40 (F). The phenolic composition of each fraction was verified by HPLC-DAD and direct-infusion ESI-MS(n) analysis. In addition to the well-known anthocyanins and their acetyl and coumaroyl derivatives, and several direct and indirect anthocyanin-(epi)catechin condensation products, a new class of pigmented products, namely hydroxyethyl-anthocyanin-ethyl-flavanol compounds, have been detected in red wine. The new class of pigmented products would be expected to be the major pigments responsible for the color of aged red wine. Copyright 2010 John Wiley & Sons, Ltd.

Determinants of Patient Satisfaction Two Year after Spinal Deformity Surgery: A Latent Class Analysis.

PubMed

Yang, Jingyan; Lafage, Virginie; Lafage, Renaud; Smith, Justin; Klineberg, Eric O; Shaffrey, Christopher I; Mundis, Gregory; Hostin, Richard; Burton, Douglas; Ames, Christopher P; Bess, Shay; Kim, Han Jo; Schwab, Frank

2018-06-21

Retrospective review of prospective multicenter database. To investigate the determinants of patient satisfaction with respect to changes in functional limitations two-year after spinal deformity surgery. For operatively treated adult spine deformity (ASD), patient satisfaction has become an important component of evaluating quality of care. 430 operative ASD patients with two-year follow-up were analyzed. Patient satisfaction was assessed using the Scoliosis Research Society 22-item (SRS-22r). Latent class analysis (LCA) was performed to assign individuals to classes based on the changes in pre- and 2-year post-operative functions, assessed using the Oswestry Disability Index (ODI). An ordered logistic regression was conducted to assess the association of class membership and satisfaction. LCA identified 4 classes. The worsened-condition class (WC: 1.4%) consisted of patients who were likely to experience worsened function, particularly in lifting and pain intensity. The remained-same class (RS: 13.0%) included patients who remained the same, as the majority reported approximately no change in walking, standing and sitting. The mild-improved class (Mild-I: 40.2%) included patients with mildly enhanced conditions, specifically, in standing, social life and employment. The most-improved class (Most-I: 45.3%) included patients with great improvement after surgery mainly in standing, followed by social life and employment. The odds of being satisfied were significantly increased by 3.91-(p < 0.001) and 16.99-fold (p < 0.001), comparing patients in Mild-I and Most-I to the RS/WC class, respectively, after controlling for confounders. Improvement in standing, social life and employment are the most important determinants of patient satisfaction post-surgery. Reduced pain intensity and enhanced walking ability also help to elevate patient satisfaction. However, lifting, personal care, sitting, sleeping and travelling may be of less importance. Examining the heterogeneity of patient-reported outcome in ASD patients allows the identification of classes with different patient characteristics and satisfaction, and thus, help to guide tailored provision of care. 4.

Screening for oral potentially malignant disorders among areca (betel) nut chewers in Guam and Saipan.

PubMed

Paulino, Yvette C; Hurwitz, Eric L; Warnakulasuriya, Saman; Gatewood, Robert R; Pierson, Kenneth D; Tenorio, Lynnette F; Novotny, Rachel; Palafox, Neal A; Wilkens, Lynne R; Badowski, Grazyna

2014-12-11

The Mariana Islands, including Guam and Saipan, are home to many ethnic subpopulations of Micronesia. Oral cancer incidence rates vary among subpopulations, and areca (betel) nut chewing, a habit with carcinogenic risks, is common. Our objectives were to conduct a screening program to detect oral potentially malignant disorders (OPMD) in betel nut chewers, measure their betel nut chewing practices, and assess the prevalence of the oral human papillomavirus (HPV) infection in a subset of betel nut chewers in these islands. A cross-section of 300 betel nut chewers ≥18 years old [in Guam (n = 137) and in Saipan (n = 163)] were recruited between January 2011-June 2012. We collected demographic, socioeconomic, and oral behavioural characteristics. Latent class analysis was used to identify chewing patterns from selected chewing behaviours. Following calibration of OPMD against an expert, a registered oral hygienist conducted oral examinations by house to house visits and referred positive cases to the study dentist for a second oral examination. Buccal smears were collected from a subset (n = 123) for HPV testing. Two classes of betel nut chewers were identified on 7 betel nut behaviours, smoking, and alcohol use; a key difference between the two Classes was the addition of ingredients to the betel quid among those in Class 2. When compared on other characteristics, Class 1 chewers were older, had been chewing for more years, and chewed fewer nuts per day although chewing episodes lasted longer than Class 2 chewers. More Class 1 chewers visited the dentist regularly than Class 2 chewers. Of the 300 participants, 46 (15.3%; 3.8% for Class 1 and 19.4% for Class 2) had OPMD and one (0.3%) was confirmed to have squamous cell carcinoma. The prevalence of oral HPV was 5.7% (7/123), although none were high-risk types. We found two patterns of betel nut chewing behaviour; Class 2 had a higher frequency of OPMD. Additional epidemiologic research is needed to examine the relationship between pattern of chewing behaviours and oral cancer incidence. Based on risk stratification, oral screening in Guam and Saipan can be targeted to Class 2 chewers.

Proteomic analysis of secreted protein induced by a component of prey in pitcher fluid of the carnivorous plant Nepenthes alata.

PubMed

Hatano, Naoya; Hamada, Tatsuro

2012-08-03

The Nepenthes species are carnivorous plants that have evolved a specialized leaf organ, the 'pitcher', to attract, capture, and digest insects. The digested insects provide nutrients for growth, allowing these plants to grow even in poor soil. Several proteins have been identified in the pitcher fluid, including aspartic proteases (nepenthesin I and II) and pathogenesis-related (PR) proteins (β-1,3-glucanase, class IV chitinase, and thaumatin-like protein). In this study, we collected and concentrated pitcher fluid to identify minor proteins. In addition, we tried to identify the protein secreted in response to trapping the insect. To make a similar situation in which the insect falls into the pitcher, chitin which was a major component of the insect exoskeleton was added to the fluid in the pitcher. Three PR proteins, class III peroxidase (Prx), β-1,3-glucanase, and class III chitinase, were newly identified. Prx was induced after the addition of chitin to the pitcher fluid. Proteins in the pitcher fluid of the carnivorous plant Nepenthes alata probably have two roles in nutrient supply: digestion of prey and the antibacterial effect. These results suggest that the system for digesting prey has evolved from the defense system against pathogens in the carnivorous plant Nepenthes. Copyright © 2012 Elsevier B.V. All rights reserved.

Diuresis and reduced urinary osmolality in rats produced by small-molecule UT-A-selective urea transport inhibitors.

PubMed

Esteva-Font, Cristina; Cil, Onur; Phuan, Puay-Wah; Su, Tao; Lee, Sujin; Anderson, Marc O; Verkman, A S

2014-09-01

Urea transport (UT) proteins of the UT-A class are expressed in epithelial cells in kidney tubules, where they are required for the formation of a concentrated urine by countercurrent multiplication. Here, using a recently developed high-throughput assay to identify UT-A inhibitors, a screen of 50,000 synthetic small molecules identified UT-A inhibitors of aryl-thiazole, γ-sultambenzosulfonamide, aminocarbonitrile butene, and 4-isoxazolamide chemical classes. Structure-activity analysis identified compounds that inhibited UT-A selectively by a noncompetitive mechanism with IC50 down to ∼1 μM. Molecular modeling identified putative inhibitor binding sites on rat UT-A. To test compound efficacy in rats, formulations and administration procedures were established to give therapeutic inhibitor concentrations in blood and urine. We found that intravenous administration of an indole thiazole or a γ-sultambenzosulfonamide at 20 mg/kg increased urine output by 3-5-fold and reduced urine osmolality by ∼2-fold compared to vehicle control rats, even under conditions of maximum antidiuresis produced by 1-deamino-8-D-arginine vasopressin (DDAVP). The diuresis was reversible and showed urea > salt excretion. The results provide proof of concept for the diuretic action of UT-A-selective inhibitors. UT-A inhibitors are first in their class salt-sparing diuretics with potential clinical indications in volume-overload edemas and high-vasopressin-associated hyponatremias. © FASEB.

Regression mixture models: Does modeling the covariance between independent variables and latent classes improve the results?

PubMed Central

Lamont, Andrea E.; Vermunt, Jeroen K.; Van Horn, M. Lee

2016-01-01

Regression mixture models are increasingly used as an exploratory approach to identify heterogeneity in the effects of a predictor on an outcome. In this simulation study, we test the effects of violating an implicit assumption often made in these models – i.e., independent variables in the model are not directly related to latent classes. Results indicated that the major risk of failing to model the relationship between predictor and latent class was an increase in the probability of selecting additional latent classes and biased class proportions. Additionally, this study tests whether regression mixture models can detect a piecewise relationship between a predictor and outcome. Results suggest that these models are able to detect piecewise relations, but only when the relationship between the latent class and the predictor is included in model estimation. We illustrate the implications of making this assumption through a re-analysis of applied data examining heterogeneity in the effects of family resources on academic achievement. We compare previous results (which assumed no relation between independent variables and latent class) to the model where this assumption is lifted. Implications and analytic suggestions for conducting regression mixture based on these findings are noted. PMID:26881956

LMFBR system-wide transient analysis: the state of the art and US validation needs

DOE Office of Scientific and Technical Information (OSTI.GOV)

Khatib-Rahbar, M.; Guppy, J.G.; Cerbone, R.J.

1982-01-01

This paper summarizes the computational capabilities in the area of liquid metal fast breeder reactor (LMFBR) system-wide transient analysis in the United States, identifies various numerical and physical approximations, the degree of empiricism, range of applicability, model verification and experimental needs for a wide class of protected transients, in particular, natural circulation shutdown heat removal for both loop- and pool-type plants.

A Comparative Study of High School Advanced Placement and Dual Enrollment Programs Using a Mixed Methods Analysis

ERIC Educational Resources Information Center

Haley, Katrina A.

2013-01-01

This study provides an in-depth analysis of whether students who take dual enrollment and/or AP classes have higher ACT test scores compared to a group of their peers that did not take dual enrollment or AP courses. The study also identified the demographic characteristics (ethnicity, gender, and socio-economic status) of students with a 3.0 or…

Arcjet thruster research and technology

NASA Technical Reports Server (NTRS)

Makel, Darby B.; Cann, Gordon L.

1988-01-01

The design, analysis, and performance testing of an advanced lower power arcjet is described. A high impedance, vortex stabilized 1-kw class arcjet has been studied. A baseline research thruster has been built and endurance and performance tested. This advanced arcjet has demonstrated long lifetime characteristics, but lower than expected performance. Analysis of the specific design has identified modifications which should improve performance and maintain the long life time shown by the arcjet.

Mining pathway associations for disease-related pathway activity analysis based on gene expression and methylation data.

PubMed

Lee, Hyeonjeong; Shin, Miyoung

2017-01-01

The problem of discovering genetic markers as disease signatures is of great significance for the successful diagnosis, treatment, and prognosis of complex diseases. Even if many earlier studies worked on identifying disease markers from a variety of biological resources, they mostly focused on the markers of genes or gene-sets (i.e., pathways). However, these markers may not be enough to explain biological interactions between genetic variables that are related to diseases. Thus, in this study, our aim is to investigate distinctive associations among active pathways (i.e., pathway-sets) shown each in case and control samples which can be observed from gene expression and/or methylation data. The pathway-sets are obtained by identifying a set of associated pathways that are often active together over a significant number of class samples. For this purpose, gene expression or methylation profiles are first analyzed to identify significant (active) pathways via gene-set enrichment analysis. Then, regarding these active pathways, an association rule mining approach is applied to examine interesting pathway-sets in each class of samples (case or control). By doing so, the sets of associated pathways often working together in activity profiles are finally chosen as our distinctive signature of each class. The identified pathway-sets are aggregated into a pathway activity network (PAN), which facilitates the visualization of differential pathway associations between case and control samples. From our experiments with two publicly available datasets, we could find interesting PAN structures as the distinctive signatures of breast cancer and uterine leiomyoma cancer, respectively. Our pathway-set markers were shown to be superior or very comparable to other genetic markers (such as genes or gene-sets) in disease classification. Furthermore, the PAN structure, which can be constructed from the identified markers of pathway-sets, could provide deeper insights into distinctive associations between pathway activities in case and control samples.

Assessing the longitudinal stability of latent classes of substance use among gay, bisexual, and other men who have sex with men.

PubMed

Card, Kiffer G; Armstrong, Heather L; Carter, Allison; Cui, Zishan; Wang, Lu; Zhu, Julia; Lachowsky, Nathan J; Moore, David M; Hogg, Robert S; Roth, Eric A

2018-05-22

Association between substance use and HIV-risk among gay and bisexual men (GBM) is well documented. However, their substance use patterns are diverse, and it is unknown whether self-reported use patterns are stable over time. Sexually-active GBM, aged >16 years, were recruited in Metro Vancouver using respondent-driven sampling and followed across 5 study visits at six-month intervals (n = 449). To identify distinct patterns of substance use and their longitudinal stability, Latent Transition Analysis (LTA) was conducted for drugs reported by at least 30 participants. Intraclass correlation coefficients (ICC) quantified the stability of class assignments. Six classes characterizing 'limited drug use' (i.e., low use of all drugs, except alcohol), 'conventional drug use' (i.e., use of alcohol, marijuana, and tobacco), 'club drug use' (i.e., use of alcohol, cocaine, and psychedelics), 'sex drug use' (i.e., use of alcohol, crystal meth, GHB, poppers, and erectile dysfunction drugs), 'street drug use' (i.e., use of alcohol and street opioids) and 'assorted drug use' (i.e., use of most drugs) were identified. Across five visits (2.5 years), 26.3% (n = 118/449) of GBM transitioned between classes. The prevalence of limited use trended upwards (Baseline:24.5%, Visit 5:28.3%, p < 0.0001) and assorted use trended downwards (13.4%-9.6%, p = 0.001). All classes had strong longitudinal stability (ICC > 0.97). The stability of latent substance use patterns highlight the utility of these measures in identifying patterns of substance use among people who use drugs - potentially allowing for better assessment of these groups and interventions related to their health. Copyright © 2018 Elsevier B.V. All rights reserved.

Identifying subgroups of patients using latent class analysis: should we use a single-stage or a two-stage approach? A methodological study using a cohort of patients with low back pain.

PubMed

Nielsen, Anne Molgaard; Kent, Peter; Hestbaek, Lise; Vach, Werner; Kongsted, Alice

2017-02-01

Heterogeneity in patients with low back pain (LBP) is well recognised and different approaches to subgrouping have been proposed. Latent Class Analysis (LCA) is a statistical technique that is increasingly being used to identify subgroups based on patient characteristics. However, as LBP is a complex multi-domain condition, the optimal approach when using LCA is unknown. Therefore, this paper describes the exploration of two approaches to LCA that may help improve the identification of clinically relevant and interpretable LBP subgroups. From 928 LBP patients consulting a chiropractor, baseline data were used as input to the statistical subgrouping. In a single-stage LCA, all variables were modelled simultaneously to identify patient subgroups. In a two-stage LCA, we used the latent class membership from our previously published LCA within each of six domains of health (activity, contextual factors, pain, participation, physical impairment and psychology) (first stage) as the variables entered into the second stage of the two-stage LCA to identify patient subgroups. The description of the results of the single-stage and two-stage LCA was based on a combination of statistical performance measures, qualitative evaluation of clinical interpretability (face validity) and a subgroup membership comparison. For the single-stage LCA, a model solution with seven patient subgroups was preferred, and for the two-stage LCA, a nine patient subgroup model. Both approaches identified similar, but not identical, patient subgroups characterised by (i) mild intermittent LBP, (ii) recent severe LBP and activity limitations, (iii) very recent severe LBP with both activity and participation limitations, (iv) work-related LBP, (v) LBP and several negative consequences and (vi) LBP with nerve root involvement. Both approaches identified clinically interpretable patient subgroups. The potential importance of these subgroups needs to be investigated by exploring whether they can be identified in other cohorts and by examining their possible association with patient outcomes. This may inform the selection of a preferred LCA approach.

No Evidence of a Common DNA Variant Profile Specific to World Class Endurance Athletes

PubMed Central

Wolfarth, Bernd; Wang, Guan; Sarzynski, Mark A.; Alexeev, Dmitry G.; Ahmetov, Ildus I.; Boulay, Marcel R.; Cieszczyk, Pawel; Eynon, Nir; Filipenko, Maxim L.; Garton, Fleur C.; Generozov, Edward V.; Govorun, Vadim M.; Houweling, Peter J.; Kawahara, Takashi; Kostryukova, Elena S.; Kulemin, Nickolay A.; Larin, Andrey K.; Maciejewska-Karłowska, Agnieszka; Miyachi, Motohiko; Muniesa, Carlos A.; Murakami, Haruka; Ospanova, Elena A.; Padmanabhan, Sandosh; Pavlenko, Alexander V.; Pyankova, Olga N.; Santiago, Catalina; Sawczuk, Marek; Scott, Robert A.; Uyba, Vladimir V.; Yvert, Thomas; Perusse, Louis; Ghosh, Sujoy; Rauramaa, Rainer; North, Kathryn N.; Lucia, Alejandro; Pitsiladis, Yannis; Bouchard, Claude

2016-01-01

There are strong genetic components to cardiorespiratory fitness and its response to exercise training. It would be useful to understand the differences in the genomic profile of highly trained endurance athletes of world class caliber and sedentary controls. An international consortium (GAMES) was established in order to compare elite endurance athletes and ethnicity-matched controls in a case-control study design. Genome-wide association studies were undertaken on two cohorts of elite endurance athletes and controls (GENATHLETE and Japanese endurance runners), from which a panel of 45 promising markers was identified. These markers were tested for replication in seven additional cohorts of endurance athletes and controls: from Australia, Ethiopia, Japan, Kenya, Poland, Russia and Spain. The study is based on a total of 1520 endurance athletes (835 who took part in endurance events in World Championships and/or Olympic Games) and 2760 controls. We hypothesized that world-class athletes are likely to be characterized by an even higher concentration of endurance performance alleles and we performed separate analyses on this subsample. The meta-analysis of all available studies revealed one statistically significant marker (rs558129 at GALNTL6 locus, p = 0.0002), even after correcting for multiple testing. As shown by the low heterogeneity index (I2 = 0), all eight cohorts showed the same direction of association with rs558129, even though p-values varied across the individual studies. In summary, this study did not identify a panel of genomic variants common to these elite endurance athlete groups. Since GAMES was underpowered to identify alleles with small effect sizes, some of the suggestive leads identified should be explored in expanded comparisons of world-class endurance athletes and sedentary controls and in tightly controlled exercise training studies. Such studies have the potential to illuminate the biology not only of world class endurance performance but also of compromised cardiac functions and cardiometabolic diseases. PMID:26824906

No Evidence of a Common DNA Variant Profile Specific to World Class Endurance Athletes.

PubMed

Rankinen, Tuomo; Fuku, Noriyuki; Wolfarth, Bernd; Wang, Guan; Sarzynski, Mark A; Alexeev, Dmitry G; Ahmetov, Ildus I; Boulay, Marcel R; Cieszczyk, Pawel; Eynon, Nir; Filipenko, Maxim L; Garton, Fleur C; Generozov, Edward V; Govorun, Vadim M; Houweling, Peter J; Kawahara, Takashi; Kostryukova, Elena S; Kulemin, Nickolay A; Larin, Andrey K; Maciejewska-Karłowska, Agnieszka; Miyachi, Motohiko; Muniesa, Carlos A; Murakami, Haruka; Ospanova, Elena A; Padmanabhan, Sandosh; Pavlenko, Alexander V; Pyankova, Olga N; Santiago, Catalina; Sawczuk, Marek; Scott, Robert A; Uyba, Vladimir V; Yvert, Thomas; Perusse, Louis; Ghosh, Sujoy; Rauramaa, Rainer; North, Kathryn N; Lucia, Alejandro; Pitsiladis, Yannis; Bouchard, Claude

2016-01-01

There are strong genetic components to cardiorespiratory fitness and its response to exercise training. It would be useful to understand the differences in the genomic profile of highly trained endurance athletes of world class caliber and sedentary controls. An international consortium (GAMES) was established in order to compare elite endurance athletes and ethnicity-matched controls in a case-control study design. Genome-wide association studies were undertaken on two cohorts of elite endurance athletes and controls (GENATHLETE and Japanese endurance runners), from which a panel of 45 promising markers was identified. These markers were tested for replication in seven additional cohorts of endurance athletes and controls: from Australia, Ethiopia, Japan, Kenya, Poland, Russia and Spain. The study is based on a total of 1520 endurance athletes (835 who took part in endurance events in World Championships and/or Olympic Games) and 2760 controls. We hypothesized that world-class athletes are likely to be characterized by an even higher concentration of endurance performance alleles and we performed separate analyses on this subsample. The meta-analysis of all available studies revealed one statistically significant marker (rs558129 at GALNTL6 locus, p = 0.0002), even after correcting for multiple testing. As shown by the low heterogeneity index (I2 = 0), all eight cohorts showed the same direction of association with rs558129, even though p-values varied across the individual studies. In summary, this study did not identify a panel of genomic variants common to these elite endurance athlete groups. Since GAMES was underpowered to identify alleles with small effect sizes, some of the suggestive leads identified should be explored in expanded comparisons of world-class endurance athletes and sedentary controls and in tightly controlled exercise training studies. Such studies have the potential to illuminate the biology not only of world class endurance performance but also of compromised cardiac functions and cardiometabolic diseases.

Efficacy of Enhanced External Counterpulsation in Patients With Chronic Refractory Angina on Canadian Cardiovascular Society (CCS) Angina Class: An Updated Meta-Analysis.

PubMed

Zhang, Chunmei; Liu, Xiangjuan; Wang, Xiaomeng; Wang, Qi; Zhang, Yun; Ge, Zhiming

2015-11-01

A growing number of patients with chronic artery disease suffer from angina, despite the optimal medical management (ie, β-blockers, calcium channel blockers, and long-acting nitrates) and revascularization. Currently, enhanced external counterpulsation (EECP) therapy has been verified as a noninvasive, safe therapy for refractory angina. The study was designed to evaluate the efficacy of EECP in patients with chronic refractory angina according to Canadian Cardiovascular Society (CCS) angina class.We identified systematic literature through MEDLINE, EMBASE, the Cochrane Clinical Trials Register Database, and the ClinicalTrials. gov Website from 1990 to 2015. Studies were considered eligible if they were prospective and reported data on CCS class before and after EECP treatment. Meta-analysis was performed to assess the efficacy of EECP therapy by at least 1 CCS angina class improvement, and proportion along with the 95% confidence interval (CI) was calculated. Statistical heterogeneity was calculated by I statistic and the Q statistic. Sensitivity analysis was addressed to test the influence of trials on the overall pooled results. Subgroup analysis was applied to explore potential reasons for heterogeneity.Eighteen studies were enrolled in our meta-analysis. Pooled analysis showed 85% of patients underwent EECP had a reduction by at least one CCS class (95%CI 0.81-0.88, I = 58.5%, P < 0.001). The proportion of patients enrolled at primarily different studies with chronic heart failure (CHF) improved by at least 1 CCS class was about 84% after EECP (95%CI 0.81-0.88, I = 32.7%, P = 0.1668). After 3 large studies were excluded, the pooled proportion was 82% (95%CI 0.79-0.86, I = 18%, P = 0.2528). Funnel plot indicated that some asymmetry while the Begg and Egger bias statistic showed no publication bias (P = 0.1495 and 0.2859, respectively).Our study confirmed that EECP provided an effective treatment for patients who were unresponsive to medical management and/or invasive therapy. However, the long-term benefits of EECP therapy needed further studies to evaluate in the management of chronic refractory angina.

Latent class models for joint analysis of disease prevalence and high-dimensional semicontinuous biomarker data.

PubMed

Zhang, Bo; Chen, Zhen; Albert, Paul S

2012-01-01

High-dimensional biomarker data are often collected in epidemiological studies when assessing the association between biomarkers and human disease is of interest. We develop a latent class modeling approach for joint analysis of high-dimensional semicontinuous biomarker data and a binary disease outcome. To model the relationship between complex biomarker expression patterns and disease risk, we use latent risk classes to link the 2 modeling components. We characterize complex biomarker-specific differences through biomarker-specific random effects, so that different biomarkers can have different baseline (low-risk) values as well as different between-class differences. The proposed approach also accommodates data features that are common in environmental toxicology and other biomarker exposure data, including a large number of biomarkers, numerous zero values, and complex mean-variance relationship in the biomarkers levels. A Monte Carlo EM (MCEM) algorithm is proposed for parameter estimation. Both the MCEM algorithm and model selection procedures are shown to work well in simulations and applications. In applying the proposed approach to an epidemiological study that examined the relationship between environmental polychlorinated biphenyl (PCB) exposure and the risk of endometriosis, we identified a highly significant overall effect of PCB concentrations on the risk of endometriosis.

A Latent Class Analysis of Gambling Activity Patterns in a Canadian University Sample of Emerging Adults: Socio-demographic, Motivational, and Mental Health Correlates.

PubMed

Sanscartier, Matthew D; Edgerton, Jason D; Roberts, Lance W

2017-12-02

This analysis of gambling habits of Canadian university students (ages 18-25) dovetails two recent developments in the field of gambling studies. First, the popularity of latent class analysis to identify heterogeneous classes of gambling patterns in different populations; second, the validation of the Gambling Motives Questionnaire (with financial motives) among university students-specifically to understand both how and why emerging adults gamble. Our results support a four-class model of gambling activity patterns, consisting of female-preponderant casual and chance-based gambling groups, and male-preponderant skill-based and extensive gambling groups. Each class shows a specific combination of motives, underscoring the necessity for nuanced responses to problem gambling among emerging adults. More specifically, gambling for the skill-based group appears primarily to be a source of thrill and a way to cope; for the chance-based group, gambling appears but one symptom of a set of wider issues involving depression, anxiety, substance use, and low self-esteem; while extensive gamblers seem to seek excitement, sociality, and coping, in that order. Only the chance-based group was significantly more likely than casual gamblers to be motivated by financial reasons. Situating our analysis in the literature, we suggest that interventions for the predominantly male subtypes should address gambling directly (e.g. re-focusing excitement seeking into other activities, instilling more productive coping mechanisms) while interventions for predominantly female subtypes should address low self-esteem in conjunction with depression, substance abuse, and problematic levels of gambling. We conclude future research should focus on links between self-esteem, depression, substance abuse, and financial motives for gambling among female emerging adults.

Clustering of modifiable biobehavioral risk factors for chronic disease in US adults: a latent class analysis.

PubMed

Leventhal, Adam M; Huh, Jimi; Dunton, Genevieve F

2014-11-01

Examining the co-occurrence patterns of modifiable biobehavioral risk factors for deadly chronic diseases (e.g. cancer, cardiovascular disease, diabetes) can elucidate the etiology of risk factors and guide disease-prevention programming. The aims of this study were to (1) identify latent classes based on the clustering of five key biobehavioral risk factors among US adults who reported at least one risk factor and (2) explore the demographic correlates of the identified latent classes. Participants were respondents of the National Epidemiologic Survey of Alcohol and Related Conditions (2004-2005) with at least one of the following disease risk factors in the past year (N = 22,789), which were also the latent class indicators: (1) alcohol abuse/dependence, (2) drug abuse/dependence, (3) nicotine dependence, (4) obesity, and (5) physical inactivity. Housing sample units were selected to match the US National Census in location and demographic characteristics, with young adults oversampled. Participants were administered surveys by trained interviewers. Five latent classes were yielded: 'obese, active non-substance abusers' (23%); 'nicotine-dependent, active, and non-obese' (19%); 'active, non-obese alcohol abusers' (6%); 'inactive, non-substance abusers' (50%); and 'active, polysubstance abusers' (3.7%). Four classes were characterized by a 100% likelihood of having one risk factor coupled with a low or moderate likelihood of having the other four risk factors. The five classes exhibited unique demographic profiles. Risk factors may cluster together in a non-monotonic fashion, with the majority of the at-risk population of US adults expected to have a high likelihood of endorsing only one of these five risk factors. © Royal Society for Public Health 2013.

An unsupervised hierarchical dynamic self-organizing approach to cancer class discovery and marker gene identification in microarray data.

PubMed

Hsu, Arthur L; Tang, Sen-Lin; Halgamuge, Saman K

2003-11-01

Current Self-Organizing Maps (SOMs) approaches to gene expression pattern clustering require the user to predefine the number of clusters likely to be expected. Hierarchical clustering methods used in this area do not provide unique partitioning of data. We describe an unsupervised dynamic hierarchical self-organizing approach, which suggests an appropriate number of clusters, to perform class discovery and marker gene identification in microarray data. In the process of class discovery, the proposed algorithm identifies corresponding sets of predictor genes that best distinguish one class from other classes. The approach integrates merits of hierarchical clustering with robustness against noise known from self-organizing approaches. The proposed algorithm applied to DNA microarray data sets of two types of cancers has demonstrated its ability to produce the most suitable number of clusters. Further, the corresponding marker genes identified through the unsupervised algorithm also have a strong biological relationship to the specific cancer class. The algorithm tested on leukemia microarray data, which contains three leukemia types, was able to determine three major and one minor cluster. Prediction models built for the four clusters indicate that the prediction strength for the smaller cluster is generally low, therefore labelled as uncertain cluster. Further analysis shows that the uncertain cluster can be subdivided further, and the subdivisions are related to two of the original clusters. Another test performed using colon cancer microarray data has automatically derived two clusters, which is consistent with the number of classes in data (cancerous and normal). JAVA software of dynamic SOM tree algorithm is available upon request for academic use. A comparison of rectangular and hexagonal topologies for GSOM is available from http://www.mame.mu.oz.au/mechatronics/journalinfo/Hsu2003supp.pdf

Latent class analysis of lifestyle characteristics and health risk behaviors among college youth.

PubMed

Laska, Melissa Nelson; Pasch, Keryn E; Lust, Katherine; Story, Mary; Ehlinger, Ed

2009-12-01

Few studies have examined the context of a wide range of risk behaviors among emerging adults (ages 18-25 years), approximately half of whom in the USA enroll in post-secondary educational institutions. The objective of this research was to examine behavioral patterning in weight behaviors (diet and physical activity), substance use, sexual behavior, stress, and sleep among undergraduate students. Health survey data were collected among undergraduates attending a large, public US university (n = 2,026). Latent class analysis was used to identify homogeneous, mutually exclusive "classes" (patterns) of ten leading risk behaviors. Resulting classes differed for males and females. Female classes were defined as: (1) poor lifestyle (diet, physical activity, sleep), yet low-risk behaviors (e.g., smoking, binge drinking, sexual risk, drunk driving; 40.0% of females), (2) high risk (high substance use, intoxicated sex, drunk driving, poor diet, inadequate sleep) (24.3%), (3) moderate lifestyle, few risk behaviors (20.4%), (4) "health conscious" (favorable diet/physical activity with some unhealthy weight control; 15.4%). Male classes were: (1) poor lifestyle, low risk (with notably high stress, insufficient sleep, 9.2% of males), (2) high risk (33.6% of males, similar to class 2 in females), (3) moderate lifestyle, low risk (51.0%), and (4) "classic jocks" (high physical activity, binge drinking, 6.2%). To our knowledge, this is among the first research to examine complex lifestyle patterning among college youth, particularly with emphasis on the role of weight-related behaviors. These findings have important implications for targeting much needed health promotion strategies among emerging adults and college youth.

Suicidality and profiles of childhood adversities, conflict related trauma and psychopathology in the Northern Ireland population.

PubMed

McLafferty, Margaret; Armour, Cherie; O'Neill, Siobhan; Murphy, Sam; Ferry, Finola; Bunting, Brendan

2016-08-01

Over 30 years of conflict in Northern Ireland (NI) has impacted on the population's mental health. However, childhood adversities may add to the psychological impact of conflict. The aims of the study were to assess co-occurrence across childhood adversities, conflict related traumas, and psychological health, then explore demographic variations between identified classes, and examine the impact of class membership on suicidal ideation and behaviour. Data was obtained from the Northern Ireland Study of Health and Stress, a representative epidemiological study which used the CIDI to assess psychopathology and related risk factors in the NI population (N=4340, part 2 n=1986; response rate 64%). Latent Class Analysis uncovered 4 discrete profiles; a conflict class (n=191; 9.6%), a multi-risk class endorsing elevated levels of childhood adversities, conflict related traumas and psychopathology (n=85; 4.3%), a psychopathology class (n=290; 14.6%), and a low risk class (n=1420; 71.5%). Multinomial logistic regression analysis revealed that individuals who grew up during the worst years of the Troubles were more likely to have experienced multiple traumas and psychopathology. Individuals in the multi-risk class were more than fifteen times more likely to endorse suicidal ideation and behaviour. The main limitations are that the study may not be fully representative of the NI population due to the exclusion criteria applied and also the possible misclassification of conflict related events. The findings indicate that treatment providers should be cognisant that those with wide ranging adversity profiles are those also likely to be reporting psychological distress and suicidality. Copyright © 2016 Elsevier B.V. All rights reserved.

Statistically Derived Subtypes and Associations with Cerebrospinal Fluid and Genetic Biomarkers in Mild Cognitive Impairment: A Latent Profile Analysis.

PubMed

Eppig, Joel S; Edmonds, Emily C; Campbell, Laura; Sanderson-Cimino, Mark; Delano-Wood, Lisa; Bondi, Mark W

2017-08-01

Research demonstrates heterogeneous neuropsychological profiles among individuals with mild cognitive impairment (MCI). However, few studies have included visuoconstructional ability or used latent mixture modeling to statistically identify MCI subtypes. Therefore, we examined whether unique neuropsychological MCI profiles could be ascertained using latent profile analysis (LPA), and subsequently investigated cerebrospinal fluid (CSF) biomarkers, genotype, and longitudinal clinical outcomes between the empirically derived classes. A total of 806 participants diagnosed by means of the Alzheimer's Disease Neuroimaging Initiative (ADNI) MCI criteria received a comprehensive neuropsychological battery assessing visuoconstructional ability, language, attention/executive function, and episodic memory. Test scores were adjusted for demographic characteristics using standardized regression coefficients based on "robust" normal control performance (n=260). Calculated Z-scores were subsequently used in the LPA, and CSF-derived biomarkers, genotype, and longitudinal clinical outcome were evaluated between the LPA-derived MCI classes. Statistical fit indices suggested a 3-class model was the optimal LPA solution. The three-class LPA consisted of a mixed impairment MCI class (n=106), an amnestic MCI class (n=455), and an LPA-derived normal class (n=245). Additionally, the amnestic and mixed classes were more likely to be apolipoprotein e4+ and have worse Alzheimer's disease CSF biomarkers than LPA-derived normal subjects. Our study supports significant heterogeneity in MCI neuropsychological profiles using LPA and extends prior work (Edmonds et al., 2015) by demonstrating a lower rate of progression in the approximately one-third of ADNI MCI individuals who may represent "false-positive" diagnoses. Our results underscore the importance of using sensitive, actuarial methods for diagnosing MCI, as current diagnostic methods may be over-inclusive. (JINS, 2017, 23, 564-576).

Behavioral and Mental Health Correlates of Youth Stalking Victimization

PubMed Central

Reidy, Dennis E.; Smith-Darden, Joanne P.; Kernsmith, Poco D.

2018-01-01

Introduction Although recognized as a public health problem, little attention has been paid to the problem of stalking among youth. Latent profile analysis was used to identify latent groups of adolescent stalking victims and their behavioral and mental health correlates. Methods A cross-sectional sample of 1,236 youths were randomly selected from 13 schools stratified by community risk level (i.e., low, moderate, and high risk) and gender. Students completed surveys assessing behavioral indicators of stalking victimization, as well as substance use, sexual behavior, dating violence, and psychiatric symptoms. Data were collected in 2013 and data analyses were performed in 2015. Results Analysis indicated the presence of a non-victim class, a minimal exposure class, and a victim class for boys and girls alike. Approximately 14% of girls and 13% of boys were in the stalking victim class. Adolescents in the victim class reported more symptoms of post-traumatic stress, mood disorder, and hopelessness, as well as more instances of alcohol use, binge drinking, and physical dating violence victimization. Girls in the victim class also reported engaging in sexting behaviors and oral sex with significantly more partners than their non-victim peers. Conclusions These findings provide valuable knowledge of the prevalence and pertinent health correlates of stalking victimization in adolescence. The data suggest a substantial proportion of adolescents are victims of stalking and are likewise at risk for a number of deleterious health outcomes. As such, this population merits further attention by prevention researchers and practitioners. PMID:27743623

Identifying "social smoking" U.S. young adults using an empirically-driven approach.

PubMed

Villanti, Andrea C; Johnson, Amanda L; Rath, Jessica M; Williams, Valerie; Vallone, Donna M; Abrams, David B; Hedeker, Donald; Mermelstein, Robin J

2017-07-01

The phenomenon of "social smoking" emerged in the past decade as an important area of research, largely due to its high prevalence in young adults. The purpose of this study was to identify classes of young adult ever smokers based on measures of social and contextual influences on tobacco use. Latent class models were developed using social smoking measures, and not the frequency or quantity of tobacco use. Data come from a national sample of young adult ever smokers aged 18-24 (Truth Initiative Young Adult Cohort Study, N=1564). The optimal models identified three latent classes: Class 1 - nonsmokers (52%); Class 2 - social smokers (18%); and Class 3 - smokers (30%). Nearly 60% of the "social smoker" class self-identified as a social smoker, 30% as an ex-smoker/tried smoking, and 12% as a non-smoker. The "social smoker" class was most likely to report using tobacco mainly or only with others. Past 30-day cigarette use was highest in the "smoker" class. Hookah use was highest in the "social smoker" class. Other tobacco and e-cigarette use was similar in the "social smoker" and "smoker" classes. Past 30-day tobacco and e-cigarette use was present for all products in the "non-smoker" class. Young adult social smokers emerge empirically as a sizable, distinct class from other smokers, even without accounting for tobacco use frequency or intensity. The prevalence of hookah use in "social smokers" indicates a group for which the social aspect of tobacco use could drive experimentation and progression to regular use. Copyright © 2017 Elsevier Ltd. All rights reserved.

Variations in adolescents' motivational characteristics across gender and physical activity patterns: A latent class analysis approach.

PubMed

Lawler, Margaret; Heary, Caroline; Nixon, Elizabeth

2017-08-17

Neglecting to take account of the underlying context or type of physical activity (PA) that underpins overall involvement has resulted in a limited understanding of adolescents' PA participation. The purpose of the present research was to identify male and female adolescents' leisure time PA patterns and examine whether psychological processes derived from self-determination theory differ as a function of the pattern of PA undertaken. Nine hundred ninety-five students (61.2% females, 38.8% males; M age = 13.72 years, SD = 1.25) from eight secondary schools in Dublin, Ireland completed a physical activity recall 7 day diary and measures of intrinsic motivation, competence, relatedness, autonomy and autonomy support. Based on the diary five binary indicators of physical activity were derived reflecting recommended levels of MVPA on a minimum of 3 days, at least three sessions of non-organized physical activity (e.g. jog), team sport, individual sport, and organized non-sport physical activity (e.g. dance). Latent class analysis was used to identify subgroups of adolescents that engaged in similar patterns of physical activity. Profiles of physical activity participation were subsequently compared on motivational characteristics using Kruskal-Wallis tests. Latent class analysis revealed six distinct classes for girls (Organized Run/Swim & Dance/Gym; Organized Dance; Leisure Active Team Sport; Active Individual Sport; Walk/Run/Outdoor games; Non-Participation) and five for boys (Leisure Active Gym; Leisure Active Individual Sport; Active Team Sport; Active Mixed Type; Non-Participation). Significant differences were found between the classes. Girls characterized by participation in team or individual sport, and boys represented by team sport participation demonstrated significantly higher self-determined motivational characteristics relative to other profiles of physical activity. This research offers a nuanced insight into the underlying type of activities that constitute overall patterns of PA among adolescent boys and girls and further reveals that psychological processes vary dependent on the profile of physical activity undertaken. The findings may be useful for informing interventions aimed at promoting physical activity among young people.

Sexual Health and Positive Subjective Well-Being in Partnered Older Men and Women

PubMed Central

Vanhoutte, Bram; Nazroo, James; Pendleton, Neil

2016-01-01

Objectives: We examine the associations between different patterns of sexual behavior and function and three indicators of subjective well-being (SWB) covering eudemonic, evaluative, and affective well-being in a representative sample of partnered older people. Method: Using data from a Sexual Relationships and Activities Questionnaire (SRA-Q) in Wave 6 of the English Longitudinal Study of Ageing, latent class analysis identified groups characterized by distinctive patterns of sexual behavior and function and then examined their link to SWB. Eudemonic SWB was measured using a revised 15-item version of the CASP-19, evaluative SWB using the Satisfaction With Life Scale, and affective SWB using the 8-item version of the Centre for Epidemiologic Studies-Depression scale. Results: Sexual behavior and function was best described by six classes among men and five classes among women. These ranged from high sexual desire, frequent partnered sexual activities, and few sexual problems (Class 1) to low sexual desire, infrequent/no sexual activity, and problems with sexual function (Class 5[women]/6[men]). Men and women who reported either infrequent/no sexual activity, or were sexually active but reported sexual problems, generally had lower SWB than those individuals identified in Class 1. Poorer SWB in men was more strongly associated with sexual function difficulties, whereas in women desire and frequency of partnered activities appeared more important in relation to SWB. Discussion: Within the context of a partnered relationship continuing sexual desire, activity and functioning are associated with higher SWB, with distinctive patterns for women and men. PMID:26993519

Should I Stay or Should I Go Now? Or Should I Wait and See? Influences on Wildfire Evacuation Decisions.

PubMed

McCaffrey, Sarah; Wilson, Robyn; Konar, Avishek

2017-11-23

As climate change has contributed to longer fire seasons and populations living in fire-prone ecosystems increase, wildfires have begun to affect a growing number of people. As a result, interest in understanding the wildfire evacuation decision process has increased. Of particular interest is understanding why some people leave early, some choose to stay and defend their homes, and others wait to assess conditions before making a final decision. Individuals who tend to wait and see are of particular concern given the dangers of late evacuation. To understand what factors might influence different decisions, we surveyed homeowners in three areas in the United States that recently experienced a wildfire. The Protective Action Decision Model was used to identify a suite of factors previously identified as potentially relevant to evacuation decisions. Our results indicate that different beliefs about the efficacy of a particular response or action (evacuating or staying to defend), differences in risk attitudes, and emphasis on different cues to act (e.g., official warnings, environmental cues) are key factors underlying different responses. Further, latent class analysis indicates there are two general classes of individuals: those inclined to evacuate and those inclined to stay, and that a substantial portion of each class falls into the wait and see category. © 2017 Society for Risk Analysis.

Identification of a Transcriptionally Forward α Gene and Two υ Genes within the Pigeon (Columba livia) IgH Gene Locus.

PubMed

Huang, Tian; Wang, Xifeng; Si, Run; Chi, Hao; Han, Binyue; Han, Haitang; Cao, Gengsheng; Zhao, Yaofeng

2018-06-01

Compared with mammals, the bird Ig genetic system relies on gene conversion to create an Ab repertoire, with inversion of the IgA-encoding gene and very few cases of Ig subclass diversification. Although gene conversion has been studied intensively, class-switch recombination, a mechanism by which the IgH C region is exchanged, has rarely been investigated in birds. In this study, based on the published genome of pigeon ( Columba livia ) and high-throughput transcriptome sequencing of immune-related tissues, we identified a transcriptionally forward α gene and found that the pigeon IgH gene locus is arranged as μ-α-υ1-υ2. In this article, we show that both DNA deletion and inversion may result from IgA and IgY class switching, and similar junction patterns were observed for both types of class-switch recombination. We also identified two subclasses of υ genes in pigeon, which share low sequence identity. Phylogenetic analysis suggests that divergence of the two pigeon υ genes occurred during the early stage of bird evolution. The data obtained in this study provide new insight into class-switch recombination and Ig gene evolution in birds. Copyright © 2018 by The American Association of Immunologists, Inc.