Testing for Two-Way Interactions in the Multigroup Common Factor Model

ERIC Educational Resources Information Center

van Smeden, Maarten; Hessen, David J.

2013-01-01

In this article, a 2-way multigroup common factor model (MG-CFM) is presented. The MG-CFM can be used to estimate interaction effects between 2 grouping variables on 1 or more hypothesized latent variables. For testing the significance of such interactions, a likelihood ratio test is presented. In a simulation study, the robustness of the…

Genetic and environmental structure of DSM-IV criteria for Antisocial Personality Disorder: a twin study

PubMed Central

Rosenström, Tom; Ystrom, Eivind; Torvik, Fartein Ask; Czajkowski, Nikolai Olavi; Gillespie, Nathan A.; Aggen, Steven H.; Krueger, Robert F.; Kendler, Kenneth S; Reichborn-Kjennerud, Ted

2017-01-01

Results from previous studies on DSM-IV and DSM-5 Antisocial Personality Disorder (ASPD) have suggested that the construct is etiologically multidimensional. To our knowledge, however, the structure of genetic and environmental influences in ASPD has not been examined using an appropriate range of biometric models and diagnostic interviews. The 7 ASPD criteria (section A) were assessed in a population-based sample of 2794 Norwegian twins by a structured interview for DSM-IV personality disorders. Exploratory analyses were conducted at the phenotypic level. Multivariate biometric models, including both independent and common pathways, were compared. A single phenotypic factor was found, and the best-fitting biometric model was a single-factor common pathway model, with common-factor heritability of 51% (95% CI = 40–67%). In other words, both genetic and environmental correlations between the ASPD criteria could be accounted for by a single common latent variable. The findings support the validity of ASPD as a unidimensional diagnostic construct. PMID:28108863

Genetic and Environmental Structure of DSM-IV Criteria for Antisocial Personality Disorder: A Twin Study.

PubMed

Rosenström, Tom; Ystrom, Eivind; Torvik, Fartein Ask; Czajkowski, Nikolai Olavi; Gillespie, Nathan A; Aggen, Steven H; Krueger, Robert F; Kendler, Kenneth S; Reichborn-Kjennerud, Ted

2017-05-01

Results from previous studies on DSM-IV and DSM-5 Antisocial Personality Disorder (ASPD) have suggested that the construct is etiologically multidimensional. To our knowledge, however, the structure of genetic and environmental influences in ASPD has not been examined using an appropriate range of biometric models and diagnostic interviews. The 7 ASPD criteria (section A) were assessed in a population-based sample of 2794 Norwegian twins by a structured interview for DSM-IV personality disorders. Exploratory analyses were conducted at the phenotypic level. Multivariate biometric models, including both independent and common pathways, were compared. A single phenotypic factor was found, and the best-fitting biometric model was a single-factor common pathway model, with common-factor heritability of 51% (95% CI 40-67%). In other words, both genetic and environmental correlations between the ASPD criteria could be accounted for by a single common latent variable. The findings support the validity of ASPD as a unidimensional diagnostic construct.

Contextual effects and cancer outcomes in the United States: a systematic review of characteristics in multilevel analyses.

PubMed

Zahnd, Whitney E; McLafferty, Sara L

2017-11-01

There is increasing call for the utilization of multilevel modeling to explore the relationship between place-based contextual effects and cancer outcomes in the United States. To gain a better understanding of how contextual factors are being considered, we performed a systematic review. We reviewed studies published between January 1, 2002 and December 31, 2016 and assessed the following attributes: (1) contextual considerations such as geographic scale and contextual factors used; (2) methods used to quantify contextual factors; and (3) cancer type and outcomes. We searched PubMed, Scopus, and Web of Science and initially identified 1060 studies. One hundred twenty-two studies remained after exclusions. Most studies utilized a two-level structure; census tracts were the most commonly used geographic scale. Socioeconomic factors, health care access, racial/ethnic factors, and rural-urban status were the most common contextual factors addressed in multilevel models. Breast and colorectal cancers were the most common cancer types, and screening and staging were the most common outcomes assessed in these studies. Opportunities for future research include deriving contextual factors using more rigorous approaches, considering cross-classified structures and cross-level interactions, and using multilevel modeling to explore understudied cancers and outcomes. Copyright © 2017 Elsevier Inc. All rights reserved.

The Relationship between Clients' Conformity to Masculine Norms and Their Perceptions of Helpful Therapist Actions

ERIC Educational Resources Information Center

Owen, Jesse; Wong, Y. Joel; Rodolfa, Emil

2010-01-01

T. J. G. Tracey et al.'s (2003) common factors model derived from therapists and psychotherapy researchers has provided a parsimonious structure to inform research and practice. Accordingly, the current authors used the 14 common factor categories identified in Tracey et al.'s model as a guide to code clients' perceptions of helpful therapist…

Measuring self-rated productivity: factor structure and variance component analysis of the Health and Work Questionnaire.

PubMed

von Thiele Schwarz, Ulrica; Sjöberg, Anders; Hasson, Henna; Tafvelin, Susanne

2014-12-01

To test the factor structure and variance components of the productivity subscales of the Health and Work Questionnaire (HWQ). A total of 272 individuals from one company answered the HWQ scale, including three dimensions (efficiency, quality, and quantity) that the respondent rated from three perspectives: their own, their supervisor's, and their coworkers'. A confirmatory factor analysis was performed, and common and unique variance components evaluated. A common factor explained 81% of the variance (reliability 0.95). All dimensions and rater perspectives contributed with unique variance. The final model provided a perfect fit to the data. Efficiency, quality, and quantity and three rater perspectives are valid parts of the self-rated productivity measurement model, but with a large common factor. Thus, the HWQ can be analyzed either as one factor or by extracting the unique variance for each subdimension.

The Houdini Transformation: True, but Illusory.

PubMed

Bentler, Peter M; Molenaar, Peter C M

2012-01-01

Molenaar (2003, 2011) showed that a common factor model could be transformed into an equivalent model without factors, involving only observed variables and residual errors. He called this invertible transformation the Houdini transformation. His derivation involved concepts from time series and state space theory. This paper verifies the Houdini transformation on a general latent variable model using algebraic methods. The results show that the Houdini transformation is illusory, in the sense that the Houdini transformed model remains a latent variable model. Contrary to common knowledge, a model that is a path model with only observed variables and residual errors may, in fact, be a latent variable model.

The Houdini Transformation: True, but Illusory

PubMed Central

Bentler, Peter M.; Molenaar, Peter C. M.

2012-01-01

Molenaar (2003, 2011) showed that a common factor model could be transformed into an equivalent model without factors, involving only observed variables and residual errors. He called this invertible transformation the Houdini transformation. His derivation involved concepts from time series and state space theory. This paper verifies the Houdini transformation on a general latent variable model using algebraic methods. The results show that the Houdini transformation is illusory, in the sense that the Houdini transformed model remains a latent variable model. Contrary to common knowledge, a model that is a path model with only observed variables and residual errors may, in fact, be a latent variable model. PMID:23180888

A Common Factors Approach to Supporting University Students Experiencing Psychological Distress

ERIC Educational Resources Information Center

Surette, Tanya E.; Shier, Micheal L.

2017-01-01

This study empirically assessed the applicability of the common factors model to students accessing university-based counseling (n = 102). Participants rated symptoms of depression, anxiety, and somatization at intake and discharge. Therapists kept detailed session notes on client factors and therapy process variables. Data were analyzed utilizing…

A Two-Factor Model Better Explains Heterogeneity in Negative Symptoms: Evidence from the Positive and Negative Syndrome Scale.

PubMed

Jang, Seon-Kyeong; Choi, Hye-Im; Park, Soohyun; Jaekal, Eunju; Lee, Ga-Young; Cho, Young Il; Choi, Kee-Hong

2016-01-01

Acknowledging separable factors underlying negative symptoms may lead to better understanding and treatment of negative symptoms in individuals with schizophrenia. The current study aimed to test whether the negative symptoms factor (NSF) of the Positive and Negative Syndrome Scale (PANSS) would be better represented by expressive and experiential deficit factors, rather than by a single factor model, using confirmatory factor analysis (CFA). Two hundred and twenty individuals with schizophrenia spectrum disorders completed the PANSS; subsamples additionally completed the Brief Negative Symptom Scale (BNSS) and the Motivation and Pleasure Scale-Self-Report (MAP-SR). CFA results indicated that the two-factor model fit the data better than the one-factor model; however, latent variables were closely correlated. The two-factor model's fit was significantly improved by accounting for correlated residuals between N2 (emotional withdrawal) and N6 (lack of spontaneity and flow of conversation), and between N4 (passive social withdrawal) and G16 (active social avoidance), possibly reflecting common method variance. The two NSF factors exhibited differential patterns of correlation with subdomains of the BNSS and MAP-SR. These results suggest that the PANSS NSF would be better represented by a two-factor model than by a single-factor one, and support the two-factor model's adequate criterion-related validity. Common method variance among several items may be a potential source of measurement error under a two-factor model of the PANSS NSF.

On Studying Common Factor Dominance and Approximate Unidimensionality in Multicomponent Measuring Instruments with Discrete Items

ERIC Educational Resources Information Center

Raykov, Tenko; Marcoulides, George A.

2018-01-01

This article outlines a procedure for examining the degree to which a common factor may be dominating additional factors in a multicomponent measuring instrument consisting of binary items. The procedure rests on an application of the latent variable modeling methodology and accounts for the discrete nature of the manifest indicators. The method…

A New Look at Genetic and Environmental Architecture on Lipids Using Non-Normal Structural Equation Modeling in Male Twins: The NHLBI Twin Study.

PubMed

Wu, Sheng-Hui; Ozaki, Koken; Reed, Terry; Krasnow, Ruth E; Dai, Jun

2017-07-01

This study examined genetic and environmental influences on the lipid concentrations of 1028 male twins using the novel univariate non-normal structural equation modeling (nnSEM) ADCE and ACE models. In the best fitting nnSEM ADCE model that was also better than the nnSEM ACE model, additive genetic factors (A) explained 4%, dominant genetic factors (D) explained 17%, and common (C) and unique (E) environmental factors explained 47% and 33% of the total variance of high-density lipoprotein cholesterol (HDL-C). The percentage of variation explained for other lipids was 0% (A), 30% (D), 34% (C) and 37% (E) for low-density lipoprotein cholesterol (LDL-C); 30, 0, 31 and 39% for total cholesterol; and 0, 31, 12 and 57% for triglycerides. It was concluded that additive and dominant genetic factors simultaneously affected HDL-C concentrations but not other lipids. Common and unique environmental factors influenced concentrations of all lipids.

Bayes Factor Covariance Testing in Item Response Models.

PubMed

Fox, Jean-Paul; Mulder, Joris; Sinharay, Sandip

2017-12-01

Two marginal one-parameter item response theory models are introduced, by integrating out the latent variable or random item parameter. It is shown that both marginal response models are multivariate (probit) models with a compound symmetry covariance structure. Several common hypotheses concerning the underlying covariance structure are evaluated using (fractional) Bayes factor tests. The support for a unidimensional factor (i.e., assumption of local independence) and differential item functioning are evaluated by testing the covariance components. The posterior distribution of common covariance components is obtained in closed form by transforming latent responses with an orthogonal (Helmert) matrix. This posterior distribution is defined as a shifted-inverse-gamma, thereby introducing a default prior and a balanced prior distribution. Based on that, an MCMC algorithm is described to estimate all model parameters and to compute (fractional) Bayes factor tests. Simulation studies are used to show that the (fractional) Bayes factor tests have good properties for testing the underlying covariance structure of binary response data. The method is illustrated with two real data studies.

Relating Factor Models for Longitudinal Data to Quasi-Simplex and NARMA Models

ERIC Educational Resources Information Center

Rovine, Michael J.; Molenaar, Peter C. M.

2005-01-01

In this article we show the one-factor model can be rewritten as a quasi-simplex model. Using this result along with addition theorems from time series analysis, we describe a common general model, the nonstationary autoregressive moving average (NARMA) model, that includes as a special case, any latent variable model with continuous indicators…

Old and New Ideas for Data Screening and Assumption Testing for Exploratory and Confirmatory Factor Analysis

PubMed Central

Flora, David B.; LaBrish, Cathy; Chalmers, R. Philip

2011-01-01

We provide a basic review of the data screening and assumption testing issues relevant to exploratory and confirmatory factor analysis along with practical advice for conducting analyses that are sensitive to these concerns. Historically, factor analysis was developed for explaining the relationships among many continuous test scores, which led to the expression of the common factor model as a multivariate linear regression model with observed, continuous variables serving as dependent variables, and unobserved factors as the independent, explanatory variables. Thus, we begin our paper with a review of the assumptions for the common factor model and data screening issues as they pertain to the factor analysis of continuous observed variables. In particular, we describe how principles from regression diagnostics also apply to factor analysis. Next, because modern applications of factor analysis frequently involve the analysis of the individual items from a single test or questionnaire, an important focus of this paper is the factor analysis of items. Although the traditional linear factor model is well-suited to the analysis of continuously distributed variables, commonly used item types, including Likert-type items, almost always produce dichotomous or ordered categorical variables. We describe how relationships among such items are often not well described by product-moment correlations, which has clear ramifications for the traditional linear factor analysis. An alternative, non-linear factor analysis using polychoric correlations has become more readily available to applied researchers and thus more popular. Consequently, we also review the assumptions and data-screening issues involved in this method. Throughout the paper, we demonstrate these procedures using an historic data set of nine cognitive ability variables. PMID:22403561

Language-Independent and Language-Specific Aspects of Early Literacy: An Evaluation of the Common Underlying Proficiency Model.

PubMed

Goodrich, J Marc; Lonigan, Christopher J

2017-08-01

According to the common underlying proficiency model (Cummins, 1981), as children acquire academic knowledge and skills in their first language, they also acquire language-independent information about those skills that can be applied when learning a second language. The purpose of this study was to evaluate the relevance of the common underlying proficiency model for the early literacy skills of Spanish-speaking language-minority children using confirmatory factor analysis. Eight hundred fifty-eight Spanish-speaking language-minority preschoolers (mean age = 60.83 months, 50.2% female) participated in this study. Results indicated that bifactor models that consisted of language-independent as well as language-specific early literacy factors provided the best fits to the data for children's phonological awareness and print knowledge skills. Correlated factors models that only included skills specific to Spanish and English provided the best fits to the data for children's oral language skills. Children's language-independent early literacy skills were significantly related across constructs and to language-specific aspects of early literacy. Language-specific aspects of early literacy skills were significantly related within but not across languages. These findings suggest that language-minority preschoolers have a common underlying proficiency for code-related skills but not language-related skills that may allow them to transfer knowledge across languages.

Structure of the Wechsler Intelligence Scale for Children - Fourth Edition in a Group of Children with ADHD.

PubMed

Gomez, Rapson; Vance, Alasdair; Watson, Shaun D

2016-01-01

This study used confirmatory factor analysis to examine the factor structure for the 10 core WISC-IV subtests in a group of children (N = 812) with ADHD. The study examined oblique four- and five-factor models, higher order models with one general secondary factor and four and five primary factors, and a bifactor model with a general factor and four specific factors. The findings supported all models tested, with the bifactor model being the optimum model. For this model, only the general factor had high explained common variance and omega hierarchical value, and it predicted reading and arithmetic abilities. The findings favor the use of the FSIQ scores of the WISC-IV, but not the subscale index scores.

Considering Horn's Parallel Analysis from a Random Matrix Theory Point of View.

PubMed

Saccenti, Edoardo; Timmerman, Marieke E

2017-03-01

Horn's parallel analysis is a widely used method for assessing the number of principal components and common factors. We discuss the theoretical foundations of parallel analysis for principal components based on a covariance matrix by making use of arguments from random matrix theory. In particular, we show that (i) for the first component, parallel analysis is an inferential method equivalent to the Tracy-Widom test, (ii) its use to test high-order eigenvalues is equivalent to the use of the joint distribution of the eigenvalues, and thus should be discouraged, and (iii) a formal test for higher-order components can be obtained based on a Tracy-Widom approximation. We illustrate the performance of the two testing procedures using simulated data generated under both a principal component model and a common factors model. For the principal component model, the Tracy-Widom test performs consistently in all conditions, while parallel analysis shows unpredictable behavior for higher-order components. For the common factor model, including major and minor factors, both procedures are heuristic approaches, with variable performance. We conclude that the Tracy-Widom procedure is preferred over parallel analysis for statistically testing the number of principal components based on a covariance matrix.

Depression and Anxiety Symptoms in Mothers of Newborns Hospitalized on the Neonatal Intensive Care Unit

PubMed Central

Segre, Lisa S.; McCabe, Jennifer E.; Chuffo-Siewert, Rebecca; O’Hara, Michael W.

2014-01-01

Background Mothers of infants hospitalized in the neonatal intensive care unit (NICU) are at risk for clinically significant levels of depression and anxiety symptoms; however, the maternal/infant characteristics that predict risk have been difficult to determine. Previous studies have conceptualized depression and anxiety symptoms separately, ignoring their comorbidity. Moreover, risk factors for these symptoms have not been assessed together in one study sample. Objectives The primary aim of this study was to determine whether a diagnostic classification approach or a common-factor model better explained the pattern of symptoms reported by NICU mothers, including depression, generalized anxiety, panic, and trauma. A secondary aim was to assess risk factors of aversive emotional states in NICU mothers based on the supported conceptual model. Method In this cross-sectional study, a nonprobability convenience sample of 200 NICU mothers completed questionnaires assessing maternal demographic and infant health characteristics, as well as maternal depression and anxiety symptoms. Structural equation modeling was used to test a diagnostic classification model, and a common-factor model of aversive emotional states and the risk factors of aversive emotional states in mothers in the NICU. Results Maximum likelihood estimates indicated that examining symptoms of depression and anxiety disorders as separate diagnostic classifications did not fit the data well, whereas examining the common factor of negative emotionality rendered an adequate fit to the data, and identified a history of depression, infant illness, and infant prematurity as significant risk factors. Discussion This study supports a multidimensional view of depression, and should guide both clinical practice and future research with NICU mothers. PMID:25171558

Bayesian inference for psychology, part IV: parameter estimation and Bayes factors.

PubMed

Rouder, Jeffrey N; Haaf, Julia M; Vandekerckhove, Joachim

2018-02-01

In the psychological literature, there are two seemingly different approaches to inference: that from estimation of posterior intervals and that from Bayes factors. We provide an overview of each method and show that a salient difference is the choice of models. The two approaches as commonly practiced can be unified with a certain model specification, now popular in the statistics literature, called spike-and-slab priors. A spike-and-slab prior is a mixture of a null model, the spike, with an effect model, the slab. The estimate of the effect size here is a function of the Bayes factor, showing that estimation and model comparison can be unified. The salient difference is that common Bayes factor approaches provide for privileged consideration of theoretically useful parameter values, such as the value corresponding to the null hypothesis, while estimation approaches do not. Both approaches, either privileging the null or not, are useful depending on the goals of the analyst.

The Relationship Between the Genetic and Environmental Influences on Common Externalizing Psychopathology and Mental Wellbeing

PubMed Central

Kendler, Kenneth S.; Myers, John M.; Keyes, Corey L. M.

2012-01-01

To determine the relationship between the genetic and environmental risk factors for externalizing psychopathology and mental wellbeing, we examined detailed measures of emotional, social and psychological wellbeing, and a history of alcohol-related problems and smoking behavior in the last year in 1,386 individual twins from same-sex pairs from the MIDUS national US sample assessed in 1995. Cholesky decomposition analyses were performed with the Mx program. The best fit model contained one highly heritable common externalizing psychopathology factor for both substance use/abuse measures, and one strongly heritable common factor for the three wellbeing measures. Genetic and environmental risk factors for externalizing psychopathology were both negatively associated with levels of mental wellbeing and accounted for, respectively, 7% and 21% of its genetic and environmental influences. Adding internalizing psychopathology assessed in the last year to the model, genetic risk factors unique for externalizing psychopathology were now positively related to levels of mental wellbeing, although accounting for only 5% of the genetic variance. Environmental risk factors unique to externalizing psychopathology continued to be negatively associated with mental wellbeing, accounting for 26% of the environmental variance. When both internalizing psychopathology and externalizing psychopathology are associated with mental wellbeing, the strongest risk factors for low mental wellbeing are genetic factors that impact on both internalizing psychopathology and externalizing psychopathology, and environmental factors unique to externalizing psychopathology. In this model, genetic risk factors for externalizing psychopathology predict, albeit weakly, higher levels of mental wellbeing. PMID:22506307

Temperament factors and dimensional, latent bifactor models of child psychopathology: Transdiagnostic and specific associations in two youth samples.

PubMed

Hankin, Benjamin L; Davis, Elysia Poggi; Snyder, Hannah; Young, Jami F; Glynn, Laura M; Sandman, Curt A

2017-06-01

Common emotional and behavioral symptoms co-occur and are associated with core temperament factors. This study investigated links between temperament and dimensional, latent psychopathology factors, including a general common psychopathology factor (p factor) and specific latent internalizing and externalizing liabilities, as captured by a bifactor model, in two independent samples of youth. Specifically, we tested the hypothesis that temperament factors of negative affectivity (NA), positive affectivity (PA), and effortful control (EC) could serve as both transdiagnostic and specific risks in relation to recent bifactor models of child psychopathology. Sample 1 included 571 youth (average age 13.6, SD =2.37, range 9.3-17.5) with both youth and parent report. Sample 2 included 554 preadolescent children (average age 7.7, SD =1.35, range =5-11 years) with parent report. Structural equation modeling showed that the latent bifactor models fit in both samples. Replicated in both samples, the p factor was associated with lower EC and higher NA (transdiagnostic risks). Several specific risks replicated in both samples after controlling for co-occurring symptoms via the p factor: internalizing was associated with higher NA and lower PA, lower EC related to externalizing problems. Copyright © 2017 Elsevier Ireland Ltd. All rights reserved.

Bayes factors based on robust TDT-type tests for family trio design.

PubMed

Yuan, Min; Pan, Xiaoqing; Yang, Yaning

2015-06-01

Adaptive transmission disequilibrium test (aTDT) and MAX3 test are two robust-efficient association tests for case-parent family trio data. Both tests incorporate information of common genetic models including recessive, additive and dominant models and are efficient in power and robust to genetic model specifications. The aTDT uses information of departure from Hardy-Weinberg disequilibrium to identify the potential genetic model underlying the data and then applies the corresponding TDT-type test, and the MAX3 test is defined as the maximum of the absolute value of three TDT-type tests under the three common genetic models. In this article, we propose three robust Bayes procedures, the aTDT based Bayes factor, MAX3 based Bayes factor and Bayes model averaging (BMA), for association analysis with case-parent trio design. The asymptotic distributions of aTDT under the null and alternative hypothesis are derived in order to calculate its Bayes factor. Extensive simulations show that the Bayes factors and the p-values of the corresponding tests are generally consistent and these Bayes factors are robust to genetic model specifications, especially so when the priors on the genetic models are equal. When equal priors are used for the underlying genetic models, the Bayes factor method based on aTDT is more powerful than those based on MAX3 and Bayes model averaging. When the prior placed a small (large) probability on the true model, the Bayes factor based on aTDT (BMA) is more powerful. Analysis of a simulation data about RA from GAW15 is presented to illustrate applications of the proposed methods.

The Common Factors Model: Implications for Transtheoretical Clinical Social Work Practice

ERIC Educational Resources Information Center

Cameron, Mark; Keenan, Elizabeth King

2010-01-01

Direct practice social workers today are challenged to address the requirements of the complex array of professional, organizational, institutional, and regulatory demands placed on them in the broader socioeconomic context of fewer resources and diminished public support for social welfare services in the United States. The common factors model…

Unidimensional and Multidimensional Models for Item Response Theory.

ERIC Educational Resources Information Center

McDonald, Roderick P.

This paper provides an up-to-date review of the relationship between item response theory (IRT) and (nonlinear) common factor theory and draws out of this relationship some implications for current and future research in IRT. Nonlinear common factor analysis yields a natural embodiment of the weak principle of local independence in appropriate…

Item Parameter Estimation for the MIRT Model: Bias and Precision of Confirmatory Factor Analysis-Based Models

ERIC Educational Resources Information Center

Finch, Holmes

2010-01-01

The accuracy of item parameter estimates in the multidimensional item response theory (MIRT) model context is one that has not been researched in great detail. This study examines the ability of two confirmatory factor analysis models specifically for dichotomous data to properly estimate item parameters using common formulae for converting factor…

Separating Common from Unique Variance Within Emotional Distress: An Examination of Reliability and Relations to Worry.

PubMed

Marshall, Andrew J; Evanovich, Emma K; David, Sarah Jo; Mumma, Gregory H

2018-01-17

High comorbidity rates among emotional disorders have led researchers to examine transdiagnostic factors that may contribute to shared psychopathology. Bifactor models provide a unique method for examining transdiagnostic variables by modelling the common and unique factors within measures. Previous findings suggest that the bifactor model of the Depression Anxiety and Stress Scale (DASS) may provide a method for examining transdiagnostic factors within emotional disorders. This study aimed to replicate the bifactor model of the DASS, a multidimensional measure of psychological distress, within a US adult sample and provide initial estimates of the reliability of the general and domain-specific factors. Furthermore, this study hypothesized that Worry, a theorized transdiagnostic variable, would show stronger relations to general emotional distress than domain-specific subscales. Confirmatory factor analysis was used to evaluate the bifactor model structure of the DASS in 456 US adult participants (279 females and 177 males, mean age 35.9 years) recruited online. The DASS bifactor model fitted well (CFI = 0.98; RMSEA = 0.05). The General Emotional Distress factor accounted for most of the reliable variance in item scores. Domain-specific subscales accounted for modest portions of reliable variance in items after accounting for the general scale. Finally, structural equation modelling indicated that Worry was strongly predicted by the General Emotional Distress factor. The DASS bifactor model is generalizable to a US community sample and General Emotional Distress, but not domain-specific factors, strongly predict the transdiagnostic variable Worry.

Enforced Sparse Non-Negative Matrix Factorization

DTIC Science & Technology

2016-01-23

documents to find interesting pieces of information. With limited resources, analysts often employ automated text - mining tools that highlight common...represented as an undirected bipartite graph. It has become a common method for generating topic models of text data because it is known to produce good results...model and the convergence rate of the underlying algorithm. I. Introduction A common analyst challenge is searching through large quantities of text

A psychological model of mental disorder.

PubMed

Kinderman, Peter

2005-01-01

A coherent conceptualization of the role of psychological factors is of great importance in understanding mental disorder. Academic articles and professional reports alluding to psychological models of the etiology of mental disorder are becoming increasingly common, and there is evidence of a marked policy shift toward the provision of psychological therapies and interventions. This article discusses the relationship between biological, social, and psychological factors in the causation and treatment of mental disorder. It argues that simple biological reductionism is not scientifically justified, and also that the specific role of psychological processes within the biopsychosocial model requires further elaboration. The biopsychosocial model is usually interpreted as implying that biological, psychological, and social factors are co-equal partners in the etiology of mental disorder. The psychological model of mental disorder presented here suggests that disruption or dysfunction in psychological processes is a final common pathway in the development of mental disorder. These processes include, but are not limited to, cognitive processes. The model proposes that biological and social factors, together with a person's individual experiences, lead to mental disorder through their conjoint effects on those psychological processes. Implications for research, interventions, and policy are discussed.

The cross-national structure of mental disorders: results from the World Mental Health Surveys.

PubMed

de Jonge, Peter; Wardenaar, Klaas J; Lim, Carmen C W; Aguilar-Gaxiola, Sergio; Alonso, Jordi; Andrade, Laura Helena; Bunting, Brendan; Chatterji, Somnath; Ciutan, Marius; Gureje, Oye; Karam, Elie G; Lee, Sing; Medina-Mora, Maria Elena; Moskalewicz, Jacek; Navarro-Mateu, Fernando; Pennell, Beth-Ellen; Piazza, Marina; Posada-Villa, José; Torres, Yolanda; Kessler, Ronald C; Scott, Kate

2017-12-19

The patterns of comorbidity among mental disorders have led researchers to model the underlying structure of psychopathology. While studies have suggested a structure including internalizing and externalizing disorders, less is known with regard to the cross-national stability of this model. Moreover, little data are available on the placement of eating disorders, bipolar disorder and psychotic experiences (PEs) in this structure. We evaluated the structure of mental disorders with data from the World Health Organization Composite International Diagnostic Interview, including 15 lifetime mental disorders and six PEs. Respondents (n = 5478-15 499) were included from 10 high-, middle- and lower middle-income countries across the world aged 18 years or older. Confirmatory factor analyses (CFAs) were used to evaluate and compare the fit of different factor structures to the lifetime disorder data. Measurement invariance was evaluated with multigroup CFA (MG-CFA). A second-order model with internalizing and externalizing factors and fear and distress subfactors best described the structure of common mental disorders. MG-CFA showed that this model was stable across countries. Of the uncommon disorders, bipolar disorder and eating disorder were best grouped with the internalizing factor, and PEs with a separate factor. These results indicate that cross-national patterns of lifetime common mental-disorder comorbidity can be explained with a second-order underlying structure that is stable across countries and can be extended to also cover less common mental disorders.

"A psychometric investigation of gender differences and common processes across borderline and antisocial personality disorders": Correction to Chun et al. (2017).

PubMed

2017-07-01

Reports an error in "A psychometric investigation of gender differences and common processes across borderline and antisocial personality disorders" by Seokjoon Chun, Alexa Harris, Margely Carrion, Elizabeth Rojas, Stephen Stark, Carl Lejuez, William V. Lechner and Marina A. Bornovalova ( Journal of Abnormal Psychology , 2017[Jan], Vol 126[1], 76-88). In the article, there were two errors in the article's supplemental material. The supplemental material stated, "In each case, if the relaxed model fit significantly better than the baseline model (i.e., Δ X ²> 3.84, Δ df =2), then the item under investigation was flagged as noninvariant; otherwise the item was marked as invariant." The value for Δ X ² should have been 5.99. The supplemental material also stated, "If there was no decrement in fit as a function of constraining a given item, the item in question was flagged as noninvariant." It should have stated that these items were flagged as invariant. The online version of this article has been corrected. (The following abstract of the original article appeared in record 2016-53090-001.) The comorbidity between borderline personality disorder (BPD) and antisocial personality disorder (ASPD) is well-established, and the 2 disorders share many similarities. However, there are also differences across disorders: most notably, BPD is diagnosed more frequently in women and ASPD in men. We investigated if (a) comorbidity between BPD and ASPD is attributable to 2 discrete disorders or the expression of common underlying processes, and (b) if the model of comorbidity is true across sex. Using a clinical sample of 1,400 drug users in residential substance abuse treatment, we tested 3 competing models to explore whether the comorbidity of ASPD and BPD should be represented by a single common factor, 2 correlated factors, or a bifactor structure involving a general and disorder-specific factors. Next, we tested whether our resulting model was meaningful by examining its relationship with criterion variables previously reported to be associated with BPD and ASPD. The bifactor model provided the best fit and was invariant across sex. Overall, the general factor of the bifactor model significantly accounted for a large percentage of the variance in criterion variables, whereas the BPD and AAB specific factors added little to the models. The association of the general and specific factor with all criterion variables was equal for men and women. Our results suggest common underlying vulnerability accounts for both the comorbidity between BPD and AAB (across sex), and this common vulnerability drives the association with other psychopathology and maladaptive behavior. This in turn has implications for diagnostic classification systems and treatment. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

Genetic and environmental influences on dimensional representations of DSM-IV cluster C personality disorders: a population-based multivariate twin study.

PubMed

Reichborn-Kjennerud, Ted; Czajkowski, Nikolai; Neale, Michael C; Ørstavik, Ragnhild E; Torgersen, Svenn; Tambs, Kristian; Røysamb, Espen; Harris, Jennifer R; Kendler, Kenneth S

2007-05-01

The DSM-IV cluster C Axis II disorders include avoidant (AVPD), dependent (DEPD) and obsessive-compulsive (OCPD) personality disorders. We aimed to estimate the genetic and environmental influences on dimensional representations of these disorders and examine the validity of the cluster C construct by determining to what extent common familial factors influence the individual PDs. PDs were assessed using the Structured Interview for DSM-IV Personality (SIDP-IV) in a sample of 1386 young adult twin pairs from the Norwegian Institute of Public Health Twin Panel (NIPHTP). A single-factor independent pathway multivariate model was applied to the number of endorsed criteria for the three cluster C disorders, using the statistical modeling program Mx. The best-fitting model included genetic and unique environmental factors only, and equated parameters for males and females. Heritability ranged from 27% to 35%. The proportion of genetic variance explained by a common factor was 83, 48 and 15% respectively for AVPD, DEPD and OCPD. Common genetic and environmental factors accounted for 54% and 64% respectively of the variance in AVPD and DEPD but only 11% of the variance in OCPD. Cluster C PDs are moderately heritable. No evidence was found for shared environmental or sex effects. Common genetic and individual environmental factors account for a substantial proportion of the variance in AVPD and DEPD. However, OCPD appears to be largely etiologically distinct from the other two PDs. The results do not support the validity of the DSM-IV cluster C construct in its present form.

Competence across Europe: Highest Common Factor or Lowest Common Denominator?

ERIC Educational Resources Information Center

Winterton, Jonathan

2009-01-01

Purpose: The purpose of this article is to explore diversity in competence models across Europe and consider the extent to which there is sufficient common ground for a common European approach to underpin the European Qualifications Framework. Design/methodology/approach: The paper uses a literature review and interviews with policy makers.…

Do executive functions explain the covariance between internalizing and externalizing behaviors?

PubMed

Hatoum, Alexander S; Rhee, Soo Hyun; Corley, Robin P; Hewitt, John K; Friedman, Naomi P

2017-11-16

This study examined whether executive functions (EFs) might be common features of internalizing and externalizing behavior problems across development. We examined relations between three EF latent variables (a common EF factor and factors specific to updating working memory and shifting sets), constructed from nine laboratory tasks administered at age 17, to latent growth intercept (capturing stability) and slope (capturing change) factors of teacher- and parent-reported internalizing and externalizing behaviors in 885 individual twins aged 7 to 16 years. We then estimated the proportion of intercept-intercept and slope-slope correlations predicted by EF as well as the association between EFs and a common psychopathology factor (P factor) estimated from all 9 years of internalizing and externalizing measures. Common EF was negatively associated with the intercepts of teacher-rated internalizing and externalizing behavior in males, and explained 32% of their covariance; in the P factor model, common EF was associated with the P factor in males. Shifting-specific was positively associated with the externalizing slope across sex. EFs did not explain covariation between parent-rated behaviors. These results suggest that EFs are associated with stable problem behavior variation, explain small proportions of covariance, and are a risk factor that that may depend on gender.

Orthogonal higher order structure and confirmatory factor analysis of the French Wechsler Adult Intelligence Scale (WAIS-III).

PubMed

Golay, Philippe; Lecerf, Thierry

2011-03-01

According to the most widely accepted Cattell-Horn-Carroll (CHC) model of intelligence measurement, each subtest score of the Wechsler Intelligence Scale for Adults (3rd ed.; WAIS-III) should reflect both 1st- and 2nd-order factors (i.e., 4 or 5 broad abilities and 1 general factor). To disentangle the contribution of each factor, we applied a Schmid-Leiman orthogonalization transformation (SLT) to the standardization data published in the French technical manual for the WAIS-III. Results showed that the general factor accounted for 63% of the common variance and that the specific contributions of the 1st-order factors were weak (4.7%-15.9%). We also addressed this issue by using confirmatory factor analysis. Results indicated that the bifactor model (with 1st-order group and general factors) better fit the data than did the traditional higher order structure. Models based on the CHC framework were also tested. Results indicated that a higher order CHC model showed a better fit than did the classical 4-factor model; however, the WAIS bifactor structure was the most adequate. We recommend that users do not discount the Full Scale IQ when interpreting the index scores of the WAIS-III because the general factor accounts for the bulk of the common variance in the French WAIS-III. The 4 index scores cannot be considered to reflect only broad ability because they include a strong contribution of the general factor.

Mind the Gap: Why Do People Act Environmentally and What Are the Barriers to Pro-Environmental Behavior?

ERIC Educational Resources Information Center

Kollmuss, Anja; Agyeman, Julian

2002-01-01

Describes a few of the most influential and commonly used analytical frameworks including early U.S. linear progression models; altruism, empathy, and prosocial behavior models; and sociological models. Analyzes factors that have been found to have some influence, positive or negative, on pro-environmental behavior such as demographic factors,…

Shared additive genetic influences on DSM-IV criteria for alcohol dependence in subjects of European ancestry.

PubMed

Palmer, Rohan H C; McGeary, John E; Heath, Andrew C; Keller, Matthew C; Brick, Leslie A; Knopik, Valerie S

2015-12-01

Genetic studies of alcohol dependence (AD) have identified several candidate loci and genes, but most observed effects are small and difficult to reproduce. A plausible explanation for inconsistent findings may be a violation of the assumption that genetic factors contributing to each of the seven DSM-IV criteria point to a single underlying dimension of risk. Given that recent twin studies suggest that the genetic architecture of AD is complex and probably involves multiple discrete genetic factors, the current study employed common single nucleotide polymorphisms in two multivariate genetic models to examine the assumption that the genetic risk underlying DSM-IV AD is unitary. AD symptoms and genome-wide single nucleotide polymorphism (SNP) data from 2596 individuals of European descent from the Study of Addiction: Genetics and Environment were analyzed using genomic-relatedness-matrix restricted maximum likelihood. DSM-IV AD symptom covariance was described using two multivariate genetic factor models. Common SNPs explained 30% (standard error=0.136, P=0.012) of the variance in AD diagnosis. Additive genetic effects varied across AD symptoms. The common pathway model approach suggested that symptoms could be described by a single latent variable that had a SNP heritability of 31% (0.130, P=0.008). Similarly, the exploratory genetic factor model approach suggested that the genetic variance/covariance across symptoms could be represented by a single genetic factor that accounted for at least 60% of the genetic variance in any one symptom. Additive genetic effects on DSM-IV alcohol dependence criteria overlap. The assumption of common genetic effects across alcohol dependence symptoms appears to be a valid assumption. © 2015 Society for the Study of Addiction.

Exploring the possibility of a common structural model measuring associations between safety climate factors and safety behaviour in health care and the petroleum sectors.

PubMed

Olsen, Espen

2010-09-01

The aim of the present study was to explore the possibility of identifying general safety climate concepts in health care and petroleum sectors, as well as develop and test the possibility of a common cross-industrial structural model. Self-completion questionnaire surveys were administered in two organisations and sectors: (1) a large regional hospital in Norway that offers a wide range of hospital services, and (2) a large petroleum company that produces oil and gas worldwide. In total, 1919 and 1806 questionnaires were returned from the hospital and petroleum organisation, with response rates of 55 percent and 52 percent, respectively. Using a split sample procedure principal factor analysis and confirmatory factor analysis revealed six identical cross-industrial measurement concepts in independent samples-five measures of safety climate and one of safety behaviour. The factors' psychometric properties were explored with satisfactory internal consistency and concept validity. Thus, a common cross-industrial structural model was developed and tested using structural equation modelling (SEM). SEM revealed that a cross-industrial structural model could be identified among health care workers and offshore workers in the North Sea. The most significant contributing variables in the model testing stemmed from organisational management support for safety and supervisor/manager expectations and actions promoting safety. These variables indirectly enhanced safety behaviour (stop working in dangerous situations) through transitions and teamwork across units, and teamwork within units as well as learning, feedback, and improvement. Two new safety climate instruments were validated as part of the study: (1) Short Safety Climate Survey (SSCS) and (2) Hospital Survey on Patient Safety Culture-short (HSOPSC-short). Based on development of measurements and structural model assessment, this study supports the possibility of a common safety climate structural model across health care and the offshore petroleum industry. 2010 Elsevier Ltd. All rights reserved.

The Houdini Transformation: True, but Illusory

ERIC Educational Resources Information Center

Bentler, Peter M.; Molenaar, Peter C. M.

2012-01-01

Molenaar (2003, 2011) showed that a common factor model could be transformed into an equivalent model without factors, involving only observed variables and residual errors. He called this invertible transformation the Houdini transformation. His derivation involved concepts from time series and state space theory. This article verifies the…

Defining the genetic connection linking amyotrophic lateral sclerosis (ALS) with frontotemporal dementia (FTD).

PubMed

Lattante, Serena; Ciura, Sorana; Rouleau, Guy A; Kabashi, Edor

2015-05-01

Several genetic causes have been recently described for neurological diseases, increasing our knowledge of the common pathological mechanisms involved in these disorders. Mutation analysis has shown common causative factors for two major neurodegenerative disorders, ALS and FTD. Shared pathological and genetic markers as well as common neurological signs between these diseases have given rise to the notion of an ALS/FTD spectrum. This overlap among genetic factors causing ALS/FTD and the coincidence of mutated alleles (including causative, risk and modifier variants) have given rise to the notion of an oligogenic model of disease. In this review we summarize major advances in the elucidation of novel genetic factors in these diseases which have led to a better understanding of the common pathogenic factors leading to neurodegeneration. Copyright © 2015 Elsevier Ltd. All rights reserved.

Bayes factors and multimodel inference

USGS Publications Warehouse

Link, W.A.; Barker, R.J.; Thomson, David L.; Cooch, Evan G.; Conroy, Michael J.

2009-01-01

Multimodel inference has two main themes: model selection, and model averaging. Model averaging is a means of making inference conditional on a model set, rather than on a selected model, allowing formal recognition of the uncertainty associated with model choice. The Bayesian paradigm provides a natural framework for model averaging, and provides a context for evaluation of the commonly used AIC weights. We review Bayesian multimodel inference, noting the importance of Bayes factors. Noting the sensitivity of Bayes factors to the choice of priors on parameters, we define and propose nonpreferential priors as offering a reasonable standard for objective multimodel inference.

Development of a prediction model for crash occurrence by analyzing traffic crash and citation data : final report.

DOT National Transportation Integrated Search

2017-04-30

It is commonly acknowledged that factors such as human factors, vehicle characteristics, road design and environmental factors highly contribute to the occurrence of traffic crashes (WHO, 2004). Since human factors usually have the most significant i...

Structure and Etiology of Co-Occurring Internalizing and Externalizing Disorders in Adolescents

ERIC Educational Resources Information Center

Cosgrove, Victoria E.; Rhee, Soo H.; Gelhorn, Heather L.; Boeldt, Debra; Corley, Robin C.; Ehringer, Marissa A.; Young, Susan E.; Hewitt, John K.

2011-01-01

Several studies suggest that a two-factor model positing internalizing and externalizing factors explains the interrelationships among psychiatric disorders. However, it is unclear whether the covariation between internalizing and externalizing disorders is due to common genetic or environmental influences. We examined whether a model positing two…

Critical Factors in Data Governance for Learning Analytics

ERIC Educational Resources Information Center

Elouazizi, Noureddine

2014-01-01

This paper identifies some of the main challenges of data governance modelling in the context of learning analytics for higher education institutions, and discusses the critical factors for designing data governance models for learning analytics. It identifies three fundamental common challenges that cut across any learning analytics data…

State-Space Modeling of Dynamic Psychological Processes via the Kalman Smoother Algorithm: Rationale, Finite Sample Properties, and Applications

ERIC Educational Resources Information Center

Song, Hairong; Ferrer, Emilio

2009-01-01

This article presents a state-space modeling (SSM) technique for fitting process factor analysis models directly to raw data. The Kalman smoother via the expectation-maximization algorithm to obtain maximum likelihood parameter estimates is used. To examine the finite sample properties of the estimates in SSM when common factors are involved, a…

Testing Structural Models of DSM-IV Symptoms of Common Forms of Child and Adolescent Psychopathology

ERIC Educational Resources Information Center

Lahey, Benjamin B.; Rathouz, Paul J.; Van Hulle, Carol; Urbano, Richard C.; Krueger, Robert F.; Applegate, Brooks; Garriock, Holly A.; Chapman, Derek A.; Waldman, Irwin D.

2008-01-01

Confirmatory factor analyses were conducted of "Diagnostic and Statistical Manual of Mental Disorders", Fourth Edition (DSM-IV) symptoms of common mental disorders derived from structured interviews of a representative sample of 4,049 twin children and adolescents and their adult caretakers. A dimensional model based on the assignment of symptoms…

Final Technical Report: Advanced Measurement and Analysis of PV Derate Factors.

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

King, Bruce Hardison; Burton, Patrick D.; Hansen, Clifford

2015-12-01

The Advanced Measurement and Analysis of PV Derate Factors project focuses on improving the accuracy and reducing the uncertainty of PV performance model predictions by addressing a common element of all PV performance models referred to as “derates”. Widespread use of “rules of thumb”, combined with significant uncertainty regarding appropriate values for these factors contribute to uncertainty in projected energy production.

Transdiagnostic Factors and Mediation of the Relationship Between Perceived Racial Discrimination and Mental Disorders.

PubMed

Rodriguez-Seijas, Craig; Stohl, Malki; Hasin, Deborah S; Eaton, Nicholas R

2015-07-01

Multivariable comorbidity research indicates that many common mental disorders are manifestations of 2 latent transdiagnostic factors, internalizing and externalizing. Environmental stressors are known to increase the risk for experiencing particular mental disorders, but their relationships with transdiagnostic disorder constructs are unknown. The present study investigated one such stressor, perceived racial discrimination, which is robustly associated with a variety of mental disorders. To examine the direct and indirect associations between perceived racial discrimination and common forms of psychopathology. Quantitative analysis of 12 common diagnoses that were previously assessed in a nationally representative sample (N = 5191) of African American and Afro-Caribbean adults in the United States, taken from the National Survey of American Life, and used to test the possibility that transdiagnostic factors mediate the effects of discrimination on disorders. The data were obtained from February 2001 to March 2003. Latent variable measurement models, including factor analysis, and indirect effect models were used in the study. Mental health diagnoses from reliable and valid structured interviews and perceived race-based discrimination. While perceived discrimination was positively associated with all examined forms of psychopathology and substance use disorders, latent variable indirect effects modeling revealed that almost all of these associations were significantly mediated by the transdiagnostic factors. For social anxiety disorder and attention-deficit/hyperactivity disorder, complete mediation was found. The pathways linking perceived discrimination to psychiatric disorders were not direct but indirect (via transdiagnostic factors). Therefore, perceived discrimination may be associated with risk for myriad psychiatric disorders due to its association with transdiagnostic factors.

Quantum Common Causes and Quantum Causal Models

NASA Astrophysics Data System (ADS)

Allen, John-Mark A.; Barrett, Jonathan; Horsman, Dominic C.; Lee, Ciarán M.; Spekkens, Robert W.

2017-07-01

Reichenbach's principle asserts that if two observed variables are found to be correlated, then there should be a causal explanation of these correlations. Furthermore, if the explanation is in terms of a common cause, then the conditional probability distribution over the variables given the complete common cause should factorize. The principle is generalized by the formalism of causal models, in which the causal relationships among variables constrain the form of their joint probability distribution. In the quantum case, however, the observed correlations in Bell experiments cannot be explained in the manner Reichenbach's principle would seem to demand. Motivated by this, we introduce a quantum counterpart to the principle. We demonstrate that under the assumption that quantum dynamics is fundamentally unitary, if a quantum channel with input A and outputs B and C is compatible with A being a complete common cause of B and C , then it must factorize in a particular way. Finally, we show how to generalize our quantum version of Reichenbach's principle to a formalism for quantum causal models and provide examples of how the formalism works.

Prediction of breast cancer risk by genetic risk factors, overall and by hormone receptor status.

PubMed

Hüsing, Anika; Canzian, Federico; Beckmann, Lars; Garcia-Closas, Montserrat; Diver, W Ryan; Thun, Michael J; Berg, Christine D; Hoover, Robert N; Ziegler, Regina G; Figueroa, Jonine D; Isaacs, Claudine; Olsen, Anja; Viallon, Vivian; Boeing, Heiner; Masala, Giovanna; Trichopoulos, Dimitrios; Peeters, Petra H M; Lund, Eiliv; Ardanaz, Eva; Khaw, Kay-Tee; Lenner, Per; Kolonel, Laurence N; Stram, Daniel O; Le Marchand, Loïc; McCarty, Catherine A; Buring, Julie E; Lee, I-Min; Zhang, Shumin; Lindström, Sara; Hankinson, Susan E; Riboli, Elio; Hunter, David J; Henderson, Brian E; Chanock, Stephen J; Haiman, Christopher A; Kraft, Peter; Kaaks, Rudolf

2012-09-01

There is increasing interest in adding common genetic variants identified through genome wide association studies (GWAS) to breast cancer risk prediction models. First results from such models showed modest benefits in terms of risk discrimination. Heterogeneity of breast cancer as defined by hormone-receptor status has not been considered in this context. In this study we investigated the predictive capacity of 32 GWAS-detected common variants for breast cancer risk, alone and in combination with classical risk factors, and for tumours with different hormone receptor status. Within the Breast and Prostate Cancer Cohort Consortium, we analysed 6009 invasive breast cancer cases and 7827 matched controls of European ancestry, with data on classical breast cancer risk factors and 32 common gene variants identified through GWAS. Discriminatory ability with respect to breast cancer of specific hormone receptor-status was assessed with the age adjusted and cohort-adjusted concordance statistic (AUROC(a)). Absolute risk scores were calculated with external reference data. Integrated discrimination improvement was used to measure improvements in risk prediction. We found a small but steady increase in discriminatory ability with increasing numbers of genetic variants included in the model (difference in AUROC(a) going from 2.7% to 4%). Discriminatory ability for all models varied strongly by hormone receptor status. Adding information on common polymorphisms provides small but statistically significant improvements in the quality of breast cancer risk prediction models. We consistently observed better performance for receptor-positive cases, but the gain in discriminatory quality is not sufficient for clinical application.

Multi-domain models of risk factors for depression and anxiety symptoms in preschoolers: evidence for common and specific factors.

PubMed

Hopkins, Joyce; Lavigne, John V; Gouze, Karen R; LeBailly, Susan A; Bryant, Fred B

2013-07-01

Relatively few studies have examined multiple pathways by which risk factors from different domains are related to symptoms of anxiety and depression in young children; even fewer have assessed risks for these symptoms specifically, rather than for internalizing symptoms in general. We examined a theoretically- and empirically-based model of variables associated with these symptom types in a diverse community sample of 796 4-year-olds (391 boys, 405 girls) that included factors from the following domains: contextual (SES, stress and family conflict); parent characteristics (parental depression); parenting (support/engagement, hostility and scaffolding); and child characteristics including negative affect (NA) effortful control (EC) sensory regulation (SR), inhibitory control (IC) and attachment. We also compared the models to determine which variables contribute to a common correlates of symptoms of anxiety or depression, and which correlates differentiate between those symptom types. In the best-fitting model for these symptom types (a) SES, stress and conflict had indirect effects on both symptom types via long-chain paths; (b) caregiver depression had direct effects and indirect ones (mediated through parenting and child effortful control) on both symptom types; (c) parenting had direct and indirect effects (via temperament and SR); and temperament had direct effects on both symptom types. These data provide evidence of common risk factors, as well as indicate some specific pathways/mediators for the different symptom types. EC was related to anxiety, but not depression symptoms, suggesting that strategies to improve child EC may be particularly effective for treatment of anxiety symptoms in young children.

Towards a General Model of Temporal Discounting

ERIC Educational Resources Information Center

van den Bos, Wouter; McClure, Samuel M.

2013-01-01

Psychological models of temporal discounting have now successfully displaced classical economic theory due to the simple fact that many common behavior patterns, such as impulsivity, were unexplainable with classic models. However, the now dominant hyperbolic model of discounting is itself becoming increasingly strained. Numerous factors have…

The big five personality traits: psychological entities or statistical constructs?

PubMed

Franić, Sanja; Borsboom, Denny; Dolan, Conor V; Boomsma, Dorret I

2014-11-01

The present study employed multivariate genetic item-level analyses to examine the ontology and the genetic and environmental etiology of the Big Five personality dimensions, as measured by the NEO Five Factor Inventory (NEO-FFI) [Costa and McCrae, Revised NEO personality inventory (NEO PI-R) and NEO five-factor inventory (NEO-FFI) professional manual, 1992; Hoekstra et al., NEO personality questionnaires NEO-PI-R, NEO-FFI: manual, 1996]. Common and independent pathway model comparison was used to test whether the five personality dimensions fully mediate the genetic and environmental effects on the items, as would be expected under the realist interpretation of the Big Five. In addition, the dimensionalities of the latent genetic and environmental structures were examined. Item scores of a population-based sample of 7,900 adult twins (including 2,805 complete twin pairs; 1,528 MZ and 1,277 DZ) on the Dutch version of the NEO-FFI were analyzed. Although both the genetic and the environmental covariance components display a 5-factor structure, applications of common and independent pathway modeling showed that they do not comply with the collinearity constraints entailed in the common pathway model. Implications for the substantive interpretation of the Big Five are discussed.

The influence of local- and landscape-level factors on wetland breeding birds in the Prairie Pothole Region of North and South Dakota

USGS Publications Warehouse

Igl, Lawrence D.; Shaffer, Jill A.; Johnson, Douglas H.; Buhl, Deborah A.

2017-08-17

We examined the relationship between local- (wetland) and landscape-level factors and breeding bird abundances on 1,190 depressional wetlands in the Prairie Pothole Region of North and South Dakota during the breeding seasons in 1995–97. The surveyed wetlands were selected from five wetland classes (alkali, permanent, semipermanent, seasonal, or temporary), two wetland types (natural or restored), and two landowner groups (private or Federal). We recorded 133 species of birds in the surveyed wetlands during the 3 years. We analyzed the nine most common (or focal) species (that is, species that were present in 25 percent or more of the 1,190 wetlands): the Red-winged Blackbird (Agelaius phoeniceus), Blue-winged Teal (Anas discors), Mallard (Anas platyrhynchos), American Coot (Fulica americana), Gadwall (Anas strepera), Common Yellowthroat (Geothlypis trichas), Yellow-headed Blackbird (Xanthocephalus xanthocephalus), Northern Shoveler (Anas clypeata), and Savannah Sparrow (Passerculus sandwichensis). Our results emphasize the ecological value of all wetland classes, natural and restored wetlands, and publicly and privately owned wetlands in this region, including wetlands that are generally smaller and shallower (that is, temporary and seasonal wetlands) and thus most vulnerable to drainage. Blue-winged Teal, Northern Shoveler, Gadwall, Common Yellowthroat, and Red-winged Blackbird had higher abundances on Federal than on private wetlands. Abundances differed among wetland classes for seven of the nine focal species: Blue-winged Teal, Northern Shoveler, Mallard, American Coot, Common Yellowthroat, Yellow-headed Blackbird, Red-winged Blackbird. American Coot had higher abundances on restored wetlands than on natural wetlands overall, and Gadwall and Common Yellowthroat had higher abundances on private restored wetlands than on private natural wetlands. The Common Yellowthroat was the only species that had higher abundances on restored private wetlands than on restored Federal wetlands. After adjusting for wetland size and the date and location of the surveys, our results demonstrated that incorporating wetland- and landscape-level factors in models can improve our ability to predict abundances of wetland birds in this region. The top model for eight of the nine focal species included wetland- and landscape-level factors, whereas the best model for Blue-winged Teal included only wetland-level attributes. Although local factors (for example, percent open water or emergent vegetation) in individual wetlands are important factors for some wetland breeding birds, it is important that natural resource managers consider landscape-level factors beyond the local factors in their conservation plans for wetland birds.

The Geometric Relationship Between Holland's Personality Typology and the Vocational Preference Inventory

ERIC Educational Resources Information Center

Wakefield, James A., Jr.; Doughtie, Eugene B.

1973-01-01

Holland's Vocational Preference Inventory was administered to 373 undergraduates. The 11 scales of the inventory were intercorrelated and factor analyzed. Six common factors were obtained. The placement of the six personality types in six-dimensional space by factor analysis corresponded closely to Holland's model. (Author)

SCL-90-R emotional distress ratings in substance use and impulse control disorders: One-factor, oblique first-order, higher-order, and bi-factor models compared.

PubMed

Arrindell, Willem A; Urbán, Róbert; Carrozzino, Danilo; Bech, Per; Demetrovics, Zsolt; Roozen, Hendrik G

2017-09-01

To fully understand the dimensionality of an instrument in a certain population, rival bi-factor models should be routinely examined and tested against oblique first-order and higher-order structures. The present study is among the very few studies that have carried out such a comparison in relation to the Symptom Checklist-90-R. In doing so, it utilized a sample comprising 2593 patients with substance use and impulse control disorders. The study also included a test of a one-dimensional model of general psychological distress. Oblique first-order factors were based on the original a priori 9-dimensional model advanced by Derogatis (1977); and on an 8-dimensional model proposed by Arrindell and Ettema (2003)-Agoraphobia, Anxiety, Depression, Somatization, Cognitive-performance deficits, Interpersonal sensitivity and mistrust, Acting-out hostility, and Sleep difficulties. Taking individual symptoms as input, three higher-order models were tested with at the second-order levels either (1) General psychological distress; (2) 'Panic with agoraphobia', 'Depression' and 'Extra-punitive behavior'; or (3) 'Irritable-hostile depression' and 'Panic with agoraphobia'. In line with previous studies, no support was found for the one-factor model. Bi-factor models were found to fit the dataset best relative to the oblique first-order and higher-order models. However, oblique first-order and higher-order factor models also fit the data fairly well in absolute terms. Higher-order solution (2) provided support for R.F. Krueger's empirical model of psychopathology which distinguishes between fear, distress, and externalizing factors (Krueger, 1999). The higher-order model (3), which combines externalizing and distress factors (Irritable-hostile depression), fit the data numerically equally well. Overall, findings were interpreted as supporting the hypothesis that the prevalent forms of symptomatology addressed have both important common and unique features. Proposals were made to improve the Depression subscale as its scores represent more of a very common construct as is measured with the severity (total) scale than of a specific measure that purports to measure what it should assess-symptoms of depression. Copyright © 2017 Elsevier Ireland Ltd. All rights reserved.

The Issue of Power in the Identification of "g" with Lower-Order Factors

ERIC Educational Resources Information Center

Matzke, Dora; Dolan, Conor V.; Molenaar, Dylan

2010-01-01

In higher order factor models, general intelligence (g) is often found to correlate perfectly with lower-order common factors, suggesting that g and some well-defined cognitive ability, such as working memory, may be identical. However, the results of studies that addressed the equivalence of g and lower-order factors are inconsistent. We suggest…

FACTOR 9.2: A Comprehensive Program for Fitting Exploratory and Semiconfirmatory Factor Analysis and IRT Models

ERIC Educational Resources Information Center

Lorenzo-Seva, Urbano; Ferrando, Pere J.

2013-01-01

FACTOR 9.2 was developed for three reasons. First, exploratory factor analysis (FA) is still an active field of research although most recent developments have not been incorporated into available programs. Second, there is now renewed interest in semiconfirmatory (SC) solutions as suitable approaches to the complex structures are commonly found…

Applying the Common Sense Model to Understand Representations of Arsenic Contaminated Well Water

PubMed Central

Severtson, Dolores J.; Baumann, Linda C.; Brown, Roger L.

2015-01-01

Theory-based research is needed to understand how people respond to environmental health risk information. The common sense model of self-regulation and the mental models approach propose that information shapes individual’s personal understandings that influence their decisions and actions. We compare these frameworks and explain how the common sense model (CSM) was applied to describe and measure mental representations of arsenic contaminated well water. Educational information, key informant interviews, and environmental risk literature were used to develop survey items to measure dimensions of cognitive representations (identity, cause, timeline, consequences, control) and emotional representations. Surveys mailed to 1067 private well users with moderate and elevated arsenic levels yielded an 84% response rate (n=897). Exploratory and confirmatory factor analyses of data from the elevated arsenic group identified a factor structure that retained the CSM representational structure and was consistent across moderate and elevated arsenic groups. The CSM has utility for describing and measuring representations of environmental health risks thus supporting its application to environmental health risk communication research. PMID:18726811

Quantifying traditional Chinese medicine patterns using modern test theory: an example of functional constipation.

PubMed

Shen, Minxue; Cui, Yuanwu; Hu, Ming; Xu, Linyong

2017-01-13

The study aimed to validate a scale to assess the severity of "Yin deficiency, intestine heat" pattern of functional constipation based on the modern test theory. Pooled longitudinal data of 237 patients with "Yin deficiency, intestine heat" pattern of constipation from a prospective cohort study were used to validate the scale. Exploratory factor analysis was used to examine the common factors of items. A multidimensional item response model was used to assess the scale with the presence of multidimensionality. The Cronbach's alpha ranged from 0.79 to 0.89, and the split-half reliability ranged from 0.67 to 0.79 at different measurements. Exploratory factor analysis identified two common factors, and all items had cross factor loadings. Bidimensional model had better goodness of fit than the unidimensional model. Multidimensional item response model showed that the all items had moderate to high discrimination parameters. Parameters indicated that the first latent trait signified intestine heat, while the second trait characterized Yin deficiency. Information function showed that items demonstrated highest discrimination power among patients with moderate to high level of disease severity. Multidimensional item response theory provides a useful and rational approach in validating scales for assessing the severity of patterns in traditional Chinese medicine.

Heterogeneity in the development of proactive and reactive aggression in childhood: Common and specific genetic - environmental factors

PubMed Central

Lacourse, Eric; Brendgen, Mara; Vitaro, Frank; Dionne, Ginette; Tremblay, Richard Ernest; Boivin, Michel

2017-01-01

Background Few studies are grounded in a developmental framework to study proactive and reactive aggression. Furthermore, although distinctive correlates, predictors and outcomes have been highlighted, proactive and reactive aggression are substantially correlated. To our knowledge, no empirical study has examined the communality of genetic and environmental underpinning of the development of both subtypes of aggression. The current study investigated the communality and specificity of genetic-environmental factors related to heterogeneity in proactive and reactive aggression’s development throughout childhood. Methods Participants were 223 monozygotic and 332 dizygotic pairs. Teacher reports of aggression were obtained at 6, 7, 9, 10 and 12 years of age. Joint development of both phenotypes were analyzed through a multivariate latent growth curve model. Set point, differentiation, and genetic maturation/environmental modulation hypotheses were tested using a biometric decomposition of intercepts and slopes. Results Common genetic factors accounted for 64% of the total variation of proactive and reactive aggression’s intercepts. Two other sets of uncorrelated genetic factors accounted for reactive aggression’s intercept (17%) on the one hand, and for proactive (43%) and reactive (13%) aggression’s slopes on the other. Common shared environmental factors were associated with proactive aggression’s intercept (21%) and slope (26%) and uncorrelated shared environmental factors were also associated with reactive aggression’s slope (14%). Common nonshared environmental factors explained most of the remaining variability of proactive and reactive aggression slopes. Conclusions A genetic differentiation hypothesis common to both phenotypes was supported by common genetic factors associated with the developmental heterogeneity of proactive and reactive aggression in childhood. A genetic maturation hypothesis common to both phenotypes, albeit stronger for proactive aggression, was supported by common genetic factors associated with proactive and reactive aggression slopes. A shared environment set point hypothesis for proactive aggression was supported by shared environmental factors associated with proactive aggression baseline and slope. Although there are many common features to proactive and reactive aggression, the current research underscores the advantages of differentiating them when studying aggression. PMID:29211810

Confirmatory Factor Analysis of the Combined Social Phobia Scale and Social Interaction Anxiety Scale: Support for a Bifactor Model.

PubMed

Gomez, Rapson; Watson, Shaun D

2017-01-01

For the Social Phobia Scale (SPS) and the Social Interaction Anxiety Scale (SIAS) together, this study examined support for a bifactor model, and also the internal consistency reliability and external validity of the factors in this model. Participants ( N = 526) were adults from the general community who completed the SPS and SIAS. Confirmatory factor analysis (CFA) of their ratings indicated good support for the bifactor model. For this model, the loadings for all but six items were higher on the general factor than the specific factors. The three positively worded items had negligible loadings on the general factor. The general factor explained most of the common variance in the SPS and SIAS, and demonstrated good model-based internal consistency reliability (omega hierarchical) and a strong association with fear of negative evaluation and extraversion. The practical implications of the findings for the utilization of the SPS and SIAS, and the theoretical and clinical implications for social anxiety are discussed.

Confirmatory Factor Analysis of the Combined Social Phobia Scale and Social Interaction Anxiety Scale: Support for a Bifactor Model

PubMed Central

Gomez, Rapson; Watson, Shaun D.

2017-01-01

For the Social Phobia Scale (SPS) and the Social Interaction Anxiety Scale (SIAS) together, this study examined support for a bifactor model, and also the internal consistency reliability and external validity of the factors in this model. Participants (N = 526) were adults from the general community who completed the SPS and SIAS. Confirmatory factor analysis (CFA) of their ratings indicated good support for the bifactor model. For this model, the loadings for all but six items were higher on the general factor than the specific factors. The three positively worded items had negligible loadings on the general factor. The general factor explained most of the common variance in the SPS and SIAS, and demonstrated good model-based internal consistency reliability (omega hierarchical) and a strong association with fear of negative evaluation and extraversion. The practical implications of the findings for the utilization of the SPS and SIAS, and the theoretical and clinical implications for social anxiety are discussed. PMID:28210232

Modeling greenhouse gas emissions from dairy farms

USDA-ARS?s Scientific Manuscript database

Evaluation and mitigation of greenhouse gas emissions from dairy farms requires a comprehensive approach that integrates the impacts and interactions of all important sources and sinks. This approach requires some form of modeling. Types of models commonly used include empirical emission factors, pr...

The Structure of Working Memory in Young Children and Its Relation to Intelligence

PubMed Central

Gray, Shelley; Green, Samuel; Alt, Mary; Hogan, Tiffany P.; Kuo, Trudy; Brinkley, Shara; Cowan, Nelson

2016-01-01

This study investigated the structure of working memory in young school-age children by testing the fit of three competing theoretical models using a wide variety of tasks. The best fitting models were then used to assess the relationship between working memory and nonverbal measures of fluid reasoning (Gf) and visual processing (Gv) intelligence. One hundred sixty-eight English-speaking 7–9 year olds with typical development, from three states, participated. Results showed that Cowan’s three-factor embedded processes model fit the data slightly better than Baddeley and Hitch’s (1974) three-factor model (specified according to Baddeley, 1986) and decisively better than Baddeley’s (2000) four-factor model that included an episodic buffer. The focus of attention factor in Cowan’s model was a significant predictor of Gf and Gv. The results suggest that the focus of attention, rather than storage, drives the relationship between working memory, Gf, and Gv in young school-age children. Our results do not rule out the Baddeley and Hitch model, but they place constraints on both it and Cowan’s model. A common attentional component is needed for feature binding, running digit span, and visual short-term memory tasks; phonological storage is separate, as is a component of central executive processing involved in task manipulation. The results contribute to a zeitgeist in which working memory models are coming together on common ground (cf. Cowan, Saults, & Blume, 2014; Hu, Allen, Baddeley, & Hitch, 2016). PMID:27990060

Cloud immersion building shielding factors for US residential structures.

PubMed

Dickson, E D; Hamby, D M

2014-12-01

This paper presents validated building shielding factors designed for contemporary US housing-stock under an idealized, yet realistic, exposure scenario within a semi-infinite cloud of radioactive material. The building shielding factors are intended for use in emergency planning and level three probabilistic risk assessments for a variety of postulated radiological events in which a realistic assessment is necessary to better understand the potential risks for accident mitigation and emergency response planning. Factors are calculated from detailed computational housing-units models using the general-purpose Monte Carlo N-Particle computational code, MCNP5, and are benchmarked from a series of narrow- and broad-beam measurements analyzing the shielding effectiveness of ten common general-purpose construction materials and ten shielding models representing the primary weather barriers (walls and roofs) of likely US housing-stock. Each model was designed to scale based on common residential construction practices and include, to the extent practical, all structurally significant components important for shielding against ionizing radiation. Calculations were performed for floor-specific locations as well as for computing a weighted-average representative building shielding factor for single- and multi-story detached homes, both with and without basement, as well for single-wide manufactured housing-units.

Some Statistics for Assessing Person-Fit Based on Continuous-Response Models

ERIC Educational Resources Information Center

Ferrando, Pere Joan

2010-01-01

This article proposes several statistics for assessing individual fit based on two unidimensional models for continuous responses: linear factor analysis and Samejima's continuous response model. Both models are approached using a common framework based on underlying response variables and are formulated at the individual level as fixed regression…

Is the notion of central fatigue based on a solid foundation?

PubMed

Contessa, Paola; Puleo, Alessio; De Luca, Carlo J

2016-02-01

Exercise-induced muscle fatigue has been shown to be the consequence of peripheral factors that impair muscle fiber contractile mechanisms. Central factors arising within the central nervous system have also been hypothesized to induce muscle fatigue, but no direct empirical evidence that is causally associated to reduction of muscle force-generating capability has yet been reported. We developed a simulation model to investigate whether peripheral factors of muscle fatigue are sufficient to explain the muscle force behavior observed during empirical studies of fatiguing voluntary contractions, which is commonly attributed to central factors. Peripheral factors of muscle fatigue were included in the model as a time-dependent decrease in the amplitude of the motor unit force twitches. Our simulation study indicated that the force behavior commonly attributed to central fatigue could be explained solely by peripheral factors during simulated fatiguing submaximal voluntary contractions. It also revealed important flaws regarding the use of the interpolated twitch response from electrical stimulation of the muscle as a means for assessing central fatigue. Our analysis does not directly refute the concept of central fatigue. However, it raises important concerns about the manner in which it is measured and about the interpretation of the commonly accepted causes of central fatigue and questions the very need for the existence of central fatigue. Copyright © 2016 the American Physiological Society.

Changes in soil respiration across a chronosequence of tallgrass prairie reconstructions

Treesearch

Ryan M. Maher; Heidi Asbjornsen; Randall K. Kolka; Cynthia A. Cambardella; James W. Raich

2010-01-01

Close relationships among climatic factors and soil respiration (Rs) are commonly reported. However, variation in Rs across the landscape is compounded by site-specific differences that impede the development of spatially explicit models. Among factors that influence R

Interdisciplinary Research: Performance and Policy Issues.

ERIC Educational Resources Information Center

Rossini, Frederick A.; Porter, Alan L.

1981-01-01

Successful interdisciplinary research performance, it is suggested, depends on such structural and process factors as leadership, team characteristics, study bounding, iteration, communication patterns, and epistemological factors. Appropriate frameworks for socially organizing the development of knowledge such as common group learning, modeling,…

Using a latent variable model with non-constant factor loadings to examine PM2.5 constituents related to secondary inorganic aerosols.

PubMed

Zhang, Zhenzhen; O'Neill, Marie S; Sánchez, Brisa N

2016-04-01

Factor analysis is a commonly used method of modelling correlated multivariate exposure data. Typically, the measurement model is assumed to have constant factor loadings. However, from our preliminary analyses of the Environmental Protection Agency's (EPA's) PM 2.5 fine speciation data, we have observed that the factor loadings for four constituents change considerably in stratified analyses. Since invariance of factor loadings is a prerequisite for valid comparison of the underlying latent variables, we propose a factor model that includes non-constant factor loadings that change over time and space using P-spline penalized with the generalized cross-validation (GCV) criterion. The model is implemented using the Expectation-Maximization (EM) algorithm and we select the multiple spline smoothing parameters by minimizing the GCV criterion with Newton's method during each iteration of the EM algorithm. The algorithm is applied to a one-factor model that includes four constituents. Through bootstrap confidence bands, we find that the factor loading for total nitrate changes across seasons and geographic regions.

A single factor underlies the metabolic syndrome: a confirmatory factor analysis.

PubMed

Pladevall, Manel; Singal, Bonita; Williams, L Keoki; Brotons, Carlos; Guyer, Heidi; Sadurni, Josep; Falces, Carles; Serrano-Rios, Manuel; Gabriel, Rafael; Shaw, Jonathan E; Zimmet, Paul Z; Haffner, Steven

2006-01-01

Confirmatory factor analysis (CFA) was used to test the hypothesis that the components of the metabolic syndrome are manifestations of a single common factor. Three different datasets were used to test and validate the model. The Spanish and Mauritian studies included 207 men and 203 women and 1,411 men and 1,650 women, respectively. A third analytical dataset including 847 men was obtained from a previously published CFA of a U.S. population. The one-factor model included the metabolic syndrome core components (central obesity, insulin resistance, blood pressure, and lipid measurements). We also tested an expanded one-factor model that included uric acid and leptin levels. Finally, we used CFA to compare the goodness of fit of one-factor models with the fit of two previously published four-factor models. The simplest one-factor model showed the best goodness-of-fit indexes (comparative fit index 1, root mean-square error of approximation 0.00). Comparisons of one-factor with four-factor models in the three datasets favored the one-factor model structure. The selection of variables to represent the different metabolic syndrome components and model specification explained why previous exploratory and confirmatory factor analysis, respectively, failed to identify a single factor for the metabolic syndrome. These analyses support the current clinical definition of the metabolic syndrome, as well as the existence of a single factor that links all of the core components.

Heterogeneity in the Effect of Common Shocks on Healthcare Expenditure Growth.

PubMed

Hauck, Katharina; Zhang, Xiaohui

2016-09-01

Healthcare expenditure growth is affected by important unobserved common shocks such as technological innovation, changes in sociological factors, shifts in preferences, and the epidemiology of diseases. While common factors impact in principle all countries, their effect is likely to differ across countries. To allow for unobserved heterogeneity in the effects of common shocks, we estimate a panel data model of healthcare expenditure growth in 34 OECD countries over the years 1980 to 2012, where the usual fixed or random effects are replaced by a multifactor error structure. We address model uncertainty with Bayesian model averaging, to identify a small set of robust expenditure drivers from 43 potential candidates. We establish 16 significant drivers of healthcare expenditure growth, including growth in GDP per capita and in insurance premiums, changes in financing arrangements and some institutional characteristics, expenditures on pharmaceuticals, population ageing, costs of health administration, and inpatient care. Our approach allows us to provide robust evidence to policy makers on the drivers that were most strongly associated with the growth in healthcare expenditures over the past 32 years. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

Confirmatory factor analysis reveals a latent cognitive structure common to bipolar disorder, schizophrenia, and normal controls.

PubMed

Schretlen, David J; Peña, Javier; Aretouli, Eleni; Orue, Izaskun; Cascella, Nicola G; Pearlson, Godfrey D; Ojeda, Natalia

2013-06-01

We sought to determine whether a single hypothesized latent factor structure would characterize cognitive functioning in three distinct groups. We assessed 576 adults (340 community controls, 126 adults with bipolar disorder, and 110 adults with schizophrenia) using 15 measures derived from nine cognitive tests. Confirmatory factor analysis (CFA) was conducted to examine the fit of a hypothesized six-factor model. The hypothesized factors included attention, psychomotor speed, verbal memory, visual memory, ideational fluency, and executive functioning. The six-factor model provided an excellent fit for all three groups [for community controls, root mean square error of approximation (RMSEA) <0.048 and comparative fit index (CFI) = 0.99; for adults with bipolar disorder, RMSEA = 0.071 and CFI = 0.99; and for adults with schizophrenia, RMSEA = 0.06 and CFI = 0.98]. Alternate models that combined fluency with processing speed or verbal and visual memory reduced the goodness of fit. Multi-group CFA results supported factor invariance across the three groups. Confirmatory factor analysis supported a single six-factor structure of cognitive functioning among patients with schizophrenia or bipolar disorder and community controls. While the three groups clearly differ in level of performance, they share a common underlying architecture of information processing abilities. These cognitive factors could provide useful targets for clinical trials of treatments that aim to enhance information processing in persons with neurological and neuropsychiatric disorders. © 2013 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Risk and protective factors in the clinical rehabilitation of chronic back pain

PubMed Central

Wippert, Pia-Maria; Fliesser, Michael; Krause, Matthias

2017-01-01

Objectives Chronic back pain (CBP) can lead to disability and burden. In addition to its medical causes, its development is influenced by psychosocial risk factors, the so-called flag factors, which are categorized and integrated into many treatment guidelines. Currently, most studies investigate single flag factors, which limit the estimation of individual factor significance in the development of chronic pain. Furthermore, factors concerning patients’ lifestyle, biography and treatment history are often neglected. Therefore, the objectives of the present study are to identify commonly neglected factors of CBP and integrate them into an analysis model comparing their significance with established flag factors. Methods A total of 24 patients and therapists were cross-sectionally interviewed to identify commonly neglected factors of CBP. Subsequently, the impact of these factors was surveyed in a longitudinal study. In two rehabilitation clinics, CBP patients (n = 145) were examined before and 6 months after a 3-week inpatient rehabilitation. Outcome variables, chronification factor pain experience (CF-PE) and chronification factor disability (CF-D), were ascertained with confirmatory factor analysis (CFA) of standardized questionnaires. Predictors were evaluated using stepwise calculations of simple and multiple regression models. Results Through interviews, medical history, iatrogenic factors, poor compliance, critical life events (LEs), social support (SS) type and effort–reward were identified as commonly neglected factors. However, only the final three held significance in comparison to established factors such as depression and pain-related cognitions. Longitudinally, lifestyle factors found to influence future pain were initial pain, physically demanding work, nicotine consumption, gender and rehabilitation clinic. LEs were unexpectedly found to be a strong predictor of future pain, as were the protective factors, reward at work and perceived SS. Discussion These findings shed insight regarding often overlooked factors in the development of CBP, suggesting that more detailed operationalization and superordinate frameworks would be beneficial to further research. Conclusion In particular, LEs should be taken into account in future research. Protective factors should be integrated in therapeutic settings. PMID:28740424

Factoring vs linear modeling in rate estimation: a simulation study of relative accuracy.

PubMed

Maldonado, G; Greenland, S

1998-07-01

A common strategy for modeling dose-response in epidemiology is to transform ordered exposures and covariates into sets of dichotomous indicator variables (that is, to factor the variables). Factoring tends to increase estimation variance, but it also tends to decrease bias and thus may increase or decrease total accuracy. We conducted a simulation study to examine the impact of factoring on the accuracy of rate estimation. Factored and unfactored Poisson regression models were fit to follow-up study datasets that were randomly generated from 37,500 population model forms that ranged from subadditive to supramultiplicative. In the situations we examined, factoring sometimes substantially improved accuracy relative to fitting the corresponding unfactored model, sometimes substantially decreased accuracy, and sometimes made little difference. The difference in accuracy between factored and unfactored models depended in a complicated fashion on the difference between the true and fitted model forms, the strength of exposure and covariate effects in the population, and the study size. It may be difficult in practice to predict when factoring is increasing or decreasing accuracy. We recommend, therefore, that the strategy of factoring variables be supplemented with other strategies for modeling dose-response.

Theoretical Insight Into the Empirical Tortuosity-Connectivity Factor in the Burdine-Brooks-Corey Water Relative Permeability Model

NASA Astrophysics Data System (ADS)

Ghanbarian, Behzad; Ioannidis, Marios A.; Hunt, Allen G.

2017-12-01

A model commonly applied to the estimation of water relative permeability krw in porous media is the Burdine-Brooks-Corey model, which relies on a simplified picture of pores as a bundle of noninterconnected capillary tubes. In this model, the empirical tortuosity-connectivity factor is assumed to be a power law function of effective saturation with an exponent (μ) commonly set equal to 2 in the literature. Invoking critical path analysis and using percolation theory, we relate the tortuosity-connectivity exponent μ to the critical scaling exponent t of percolation that characterizes the power law behavior of the saturation-dependent electrical conductivity of porous media. We also discuss the cause of the nonuniversality of μ in terms of the nonuniversality of t and compare model estimations with water relative permeability from experiments. The comparison supports determining μ from the electrical conductivity scaling exponent t, but also highlights limitations of the model.

Percent Mammographic Density and Dense Area as Risk Factors for Breast Cancer.

PubMed

Rauh, C; Hack, C C; Häberle, L; Hein, A; Engel, A; Schrauder, M G; Fasching, P A; Jud, S M; Ekici, A B; Loehberg, C R; Meier-Meitinger, M; Ozan, S; Schulz-Wendtland, R; Uder, M; Hartmann, A; Wachter, D L; Beckmann, M W; Heusinger, K

2012-08-01

Purpose: Mammographic characteristics are known to be correlated to breast cancer risk. Percent mammographic density (PMD), as assessed by computer-assisted methods, is an established risk factor for breast cancer. Along with this assessment the absolute dense area (DA) of the breast is reported as well. Aim of this study was to assess the predictive value of DA concerning breast cancer risk in addition to other risk factors and in addition to PMD. Methods: We conducted a case control study with hospital-based patients with a diagnosis of invasive breast cancer and healthy women as controls. A total of 561 patients and 376 controls with available mammographic density were included into this study. We describe the differences concerning the common risk factors BMI, parital status, use of hormone replacement therapy (HRT) and menopause between cases and controls and estimate the odds ratios for PMD and DA, adjusted for the mentioned risk factors. Furthermore we compare the prediction models with each other to find out whether the addition of DA improves the model. Results: Mammographic density and DA were highly correlated with each other. Both variables were as well correlated to the commonly known risk factors with an expected direction and strength, however PMD (ρ = -0.56) was stronger correlated to BMI than DA (ρ = -0.11). The group of women within the highest quartil of PMD had an OR of 2.12 (95 % CI: 1.25-3.62). This could not be seen for the fourth quartile concerning DA. However the assessment of breast cancer risk could be improved by including DA in a prediction model in addition to common risk factors and PMD. Conclusions: The inclusion of the parameter DA into a prediction model for breast cancer in addition to established risk factors and PMD could improve the breast cancer risk assessment. As DA is measured together with PMD in the process of computer-assisted assessment of PMD it might be considered to include it as one additional breast cancer risk factor that is obtained from breast imaging.

Operationalising caseload midwifery in the Australian public maternity system: Findings from a national cross-sectional survey of maternity managers.

PubMed

Dawson, Kate; Forster, Della A; McLachlan, Helen L; Newton, Michelle S

2018-06-01

Despite high-level evidence of the benefits of caseload midwifery for women and babies, little is known about specific practice arrangements, organisational barriers and facilitators, nor about workforce requirements of caseload. This paper explores how caseload models across Australia operate. A national cross-sectional, online survey of maternity managers in public maternity hospitals with birthing services was undertaken. Only services with a caseload model are included in the analysis. Of 253 eligible hospitals, 149 (63%) responded, of whom 44 (31%) had a caseload model. Operationalisation of caseload varied across the country. Most commonly, caseload midwives were required to work more than 0.5 EFT, have more than one year of experience and have the skills across the whole scope of practice. On average, midwives took a caseload of 35-40 women when full time, with reduced caseloads if caring for women at higher risk. Leave coverage was complex and often ad-hoc. Duration of home-based postnatal care varied and most commonly provided to six weeks. Women's access to caseload care was impacted by many factors with geographical location and obstetric risk being most common. Introducing, managing and operationalising caseload midwifery care is complex. Factors which may affect the expansion and availability of the model are multi-faceted and include staffing and model inclusion guidelines. Coverage of leave is a factor which appears particularly challenging and needs more focus. Copyright © 2017 Australian College of Midwives. Published by Elsevier Ltd. All rights reserved.

The conceptualization and measurement of cognitive reserve using common proxy indicators: Testing some tenable reflective and formative models.

PubMed

Ikanga, Jean; Hill, Elizabeth M; MacDonald, Douglas A

2017-02-01

The examination of cognitive reserve (CR) literature reveals a lack of consensus regarding conceptualization and pervasive problems with its measurement. This study aimed at examining the conceptual nature of CR through the analysis of reflective and formative models using eight proxies commonly employed in the CR literature. We hypothesized that all CR proxies would significantly contribute to a one-factor reflective model and that educational and occupational attainment would produce the strongest loadings on a single CR factor. The sample consisted of 149 participants (82 male/67 female), with 18.1 average years of education and ages of 45-99 years. Participants were assessed for eight proxies of CR (parent socioeconomic status, intellectual functioning, level of education, health literacy, occupational prestige, life leisure activities, physical activities, and spiritual and religious activities). Primary statistical analyses consisted of confirmatory factor analysis (CFA) to test reflective models and structural equation modeling (SEM) to evaluate multiple indicators multiple causes (MIMIC) models. CFA did not produce compelling support for a unitary CR construct when using all eight of our CR proxy variables in a reflective model but fairly cogent evidence for a one-factor model with four variable proxies. A second three-factor reflective model based upon an exploratory principal components analysis of the eight proxies was tested using CFA. Though all eight indicators significantly loaded on their assigned factors, evidence in support of overall model fit was mixed. Based upon the results involving the three-factor reflective model, two alternative formative models were developed and evaluated. While some support was obtained for both, the model in which the formative influences were specified as latent variables appeared to best account for the contributions of all eight proxies to the CR construct. While the findings provide partial support for our hypothesis regarding CR as a one-dimensional reflective construct, the results strongly suggest that the construct is more complex than what can be captured in a reflective model alone. There is a need for theory to better identify and differentiate formative from reflective indicators and to articulate the mechanisms by which CR develops and operates.

Coordinate Conversion Technique for OTH Backscatter Radar

DTIC Science & Technology

1977-05-01

obliquity of the earth’s equator (=23.0󈧓), A is the mean longitude of the sun measured in the ecliptic counterclockwise from the first point of...MODEL FOR Fo-LAYER CORRECTION FACTORS-VERTICAL IO NO GRAM 11. MODEL FOR Fg-LAYER CORRECTION FACTORS- OBLIQUE IO NO GRAM 12. ELEMENTS OF COMMON BLOCK...simulation in (1) to a given oblique ionogram generate range gradient factors to apply to f F9 and I\\1(3000)F„ to force agreement; (3) from the

Identifying environmental variables explaining genotype-by-environment interaction for body weight of rainbow trout (Onchorynchus mykiss): reaction norm and factor analytic models.

PubMed

Sae-Lim, Panya; Komen, Hans; Kause, Antti; Mulder, Han A

2014-02-26

Identifying the relevant environmental variables that cause GxE interaction is often difficult when they cannot be experimentally manipulated. Two statistical approaches can be applied to address this question. When data on candidate environmental variables are available, GxE interaction can be quantified as a function of specific environmental variables using a reaction norm model. Alternatively, a factor analytic model can be used to identify the latent common factor that explains GxE interaction. This factor can be correlated with known environmental variables to identify those that are relevant. Previously, we reported a significant GxE interaction for body weight at harvest in rainbow trout reared on three continents. Here we explore their possible causes. Reaction norm and factor analytic models were used to identify which environmental variables (age at harvest, water temperature, oxygen, and photoperiod) may have caused the observed GxE interaction. Data on body weight at harvest was recorded on 8976 offspring reared in various locations: (1) a breeding environment in the USA (nucleus), (2) a recirculating aquaculture system in the Freshwater Institute in West Virginia, USA, (3) a high-altitude farm in Peru, and (4) a low-water temperature farm in Germany. Akaike and Bayesian information criteria were used to compare models. The combination of days to harvest multiplied with daily temperature (Day*Degree) and photoperiod were identified by the reaction norm model as the environmental variables responsible for the GxE interaction. The latent common factor that was identified by the factor analytic model showed the highest correlation with Day*Degree. Day*Degree and photoperiod were the environmental variables that differed most between Peru and other environments. Akaike and Bayesian information criteria indicated that the factor analytical model was more parsimonious than the reaction norm model. Day*Degree and photoperiod were identified as environmental variables responsible for the strong GxE interaction for body weight at harvest in rainbow trout across four environments. Both the reaction norm and the factor analytic models can help identify the environmental variables responsible for GxE interaction. A factor analytic model is preferred over a reaction norm model when limited information on differences in environmental variables between farms is available.

Identifying environmental variables explaining genotype-by-environment interaction for body weight of rainbow trout (Onchorynchus mykiss): reaction norm and factor analytic models

PubMed Central

2014-01-01

Background Identifying the relevant environmental variables that cause GxE interaction is often difficult when they cannot be experimentally manipulated. Two statistical approaches can be applied to address this question. When data on candidate environmental variables are available, GxE interaction can be quantified as a function of specific environmental variables using a reaction norm model. Alternatively, a factor analytic model can be used to identify the latent common factor that explains GxE interaction. This factor can be correlated with known environmental variables to identify those that are relevant. Previously, we reported a significant GxE interaction for body weight at harvest in rainbow trout reared on three continents. Here we explore their possible causes. Methods Reaction norm and factor analytic models were used to identify which environmental variables (age at harvest, water temperature, oxygen, and photoperiod) may have caused the observed GxE interaction. Data on body weight at harvest was recorded on 8976 offspring reared in various locations: (1) a breeding environment in the USA (nucleus), (2) a recirculating aquaculture system in the Freshwater Institute in West Virginia, USA, (3) a high-altitude farm in Peru, and (4) a low-water temperature farm in Germany. Akaike and Bayesian information criteria were used to compare models. Results The combination of days to harvest multiplied with daily temperature (Day*Degree) and photoperiod were identified by the reaction norm model as the environmental variables responsible for the GxE interaction. The latent common factor that was identified by the factor analytic model showed the highest correlation with Day*Degree. Day*Degree and photoperiod were the environmental variables that differed most between Peru and other environments. Akaike and Bayesian information criteria indicated that the factor analytical model was more parsimonious than the reaction norm model. Conclusions Day*Degree and photoperiod were identified as environmental variables responsible for the strong GxE interaction for body weight at harvest in rainbow trout across four environments. Both the reaction norm and the factor analytic models can help identify the environmental variables responsible for GxE interaction. A factor analytic model is preferred over a reaction norm model when limited information on differences in environmental variables between farms is available. PMID:24571451

Generalized Structured Component Analysis with Uniqueness Terms for Accommodating Measurement Error

PubMed Central

Hwang, Heungsun; Takane, Yoshio; Jung, Kwanghee

2017-01-01

Generalized structured component analysis (GSCA) is a component-based approach to structural equation modeling (SEM), where latent variables are approximated by weighted composites of indicators. It has no formal mechanism to incorporate errors in indicators, which in turn renders components prone to the errors as well. We propose to extend GSCA to account for errors in indicators explicitly. This extension, called GSCAM, considers both common and unique parts of indicators, as postulated in common factor analysis, and estimates a weighted composite of indicators with their unique parts removed. Adding such unique parts or uniqueness terms serves to account for measurement errors in indicators in a manner similar to common factor analysis. Simulation studies are conducted to compare parameter recovery of GSCAM and existing methods. These methods are also applied to fit a substantively well-established model to real data. PMID:29270146

Genetic and environmental influences on female sexual orientation, childhood gender typicality and adult gender identity.

PubMed

Burri, Andrea; Cherkas, Lynn; Spector, Timothy; Rahman, Qazi

2011-01-01

Human sexual orientation is influenced by genetic and non-shared environmental factors as are two important psychological correlates--childhood gender typicality (CGT) and adult gender identity (AGI). However, researchers have been unable to resolve the genetic and non-genetic components that contribute to the covariation between these traits, particularly in women. Here we performed a multivariate genetic analysis in a large sample of British female twins (N = 4,426) who completed a questionnaire assessing sexual attraction, CGT and AGI. Univariate genetic models indicated modest genetic influences on sexual attraction (25%), AGI (11%) and CGT (31%). For the multivariate analyses, a common pathway model best fitted the data. This indicated that a single latent variable influenced by a genetic component and common non-shared environmental component explained the association between the three traits but there was substantial measurement error. These findings highlight common developmental factors affecting differences in sexual orientation.

Extracting the Evaluations of Stereotypes: Bi-factor Model of the Stereotype Content Structure

PubMed Central

Sayans-Jiménez, Pablo; Cuadrado, Isabel; Rojas, Antonio J.; Barrada, Juan R.

2017-01-01

Stereotype dimensions—competence, morality and sociability—are fundamental to studying the perception of other groups. These dimensions have shown moderate/high positive correlations with each other that do not reflect the theoretical expectations. The explanation for this (e.g., halo effect) undervalues the utility of the shared variance identified. In contrast, in this work we propose that this common variance could represent the global evaluation of the perceived group. Bi-factor models are proposed to improve the internal structure and to take advantage of the information representing the shared variance among dimensions. Bi-factor models were compared with first order models and other alternative models in three large samples (300–309 participants). The relationships among the global and specific bi-factor dimensions with a global evaluation dimension (measured through a semantic differential) were estimated. The results support the use of bi-factor models rather than first order models (and other alternative models). Bi-factor models also show a greater utility to directly and more easily explore the stereotype content including its evaluative content. PMID:29085313

Genetic architecture of the Delis-Kaplan Executive Function System Trail Making Test: evidence for distinct genetic influences on executive function.

PubMed

Vasilopoulos, Terrie; Franz, Carol E; Panizzon, Matthew S; Xian, Hong; Grant, Michael D; Lyons, Michael J; Toomey, Rosemary; Jacobson, Kristen C; Kremen, William S

2012-03-01

To examine how genes and environments contribute to relationships among Trail Making Test (TMT) conditions and the extent to which these conditions have unique genetic and environmental influences. Participants included 1,237 middle-aged male twins from the Vietnam Era Twin Study of Aging. The Delis-Kaplan Executive Function System TMT included visual searching, number and letter sequencing, and set-shifting components. Phenotypic correlations among TMT conditions ranged from 0.29 to 0.60, and genes accounted for the majority (58-84%) of each correlation. Overall heritability ranged from 0.34 to 0.62 across conditions. Phenotypic factor analysis suggested a single factor. In contrast, genetic models revealed a single common genetic factor but also unique genetic influences separate from the common factor. Genetic variance (i.e., heritability) of number and letter sequencing was completely explained by the common genetic factor while unique genetic influences separate from the common factor accounted for 57% and 21% of the heritabilities of visual search and set shifting, respectively. After accounting for general cognitive ability, unique genetic influences accounted for 64% and 31% of those heritabilities. A common genetic factor, most likely representing a combination of speed and sequencing, accounted for most of the correlation among TMT 1-4. Distinct genetic factors, however, accounted for a portion of variance in visual scanning and set shifting. Thus, although traditional phenotypic shared variance analysis techniques suggest only one general factor underlying different neuropsychological functions in nonpatient populations, examining the genetic underpinnings of cognitive processes with twin analysis can uncover more complex etiological processes.

Childhood separation anxiety disorder and adult onset panic attacks share a common genetic diathesis.

PubMed

Roberson-Nay, Roxann; Eaves, Lindon J; Hettema, John M; Kendler, Kenneth S; Silberg, Judy L

2012-04-01

Childhood separation anxiety disorder (SAD) is hypothesized to share etiologic roots with panic disorder. The aim of this study was to estimate the genetic and environmental sources of covariance between childhood SAD and adult onset panic attacks (AOPA), with the primary goal to determine whether these two phenotypes share a common genetic diathesis. Participants included parents and their monozygotic or dizygotic twins (n = 1,437 twin pairs) participating in the Virginia Twin Study of Adolescent Behavioral Development and those twins who later completed the Young Adult Follow-Up (YAFU). The Child and Adolescent Psychiatric Assessment was completed at three waves during childhood/adolescence followed by the Structured Clinical Interview for DSM-III-R at the YAFU. Two separate, bivariate Cholesky models were fit to childhood diagnoses of SAD and overanxious disorder (OAD), respectively, and their relation with AOPA; a trivariate Cholesky model also examined the collective influence of childhood SAD and OAD on AOPA. In the best-fitting bivariate model, the covariation between SAD and AOPA was accounted for by genetic and unique environmental factors only, with the genetic factor associated with childhood SAD explaining significant variance in AOPA. Environmental risk factors were not significantly shared between SAD and AOPA. By contrast, the genetic factor associated with childhood OAD did not contribute significantly to AOPA. Results of the trivariate Cholesky reaffirmed outcomes of bivariate models. These data indicate that childhood SAD and AOPA share a common genetic diathesis that is not observed for childhood OAD, strongly supporting the hypothesis of a specific genetic etiologic link between the two phenotypes. © 2012 Wiley Periodicals, Inc.

Model Fit and Item Factor Analysis: Overfactoring, Underfactoring, and a Program to Guide Interpretation.

PubMed

Clark, D Angus; Bowles, Ryan P

2018-04-23

In exploratory item factor analysis (IFA), researchers may use model fit statistics and commonly invoked fit thresholds to help determine the dimensionality of an assessment. However, these indices and thresholds may mislead as they were developed in a confirmatory framework for models with continuous, not categorical, indicators. The present study used Monte Carlo simulation methods to investigate the ability of popular model fit statistics (chi-square, root mean square error of approximation, the comparative fit index, and the Tucker-Lewis index) and their standard cutoff values to detect the optimal number of latent dimensions underlying sets of dichotomous items. Models were fit to data generated from three-factor population structures that varied in factor loading magnitude, factor intercorrelation magnitude, number of indicators, and whether cross loadings or minor factors were included. The effectiveness of the thresholds varied across fit statistics, and was conditional on many features of the underlying model. Together, results suggest that conventional fit thresholds offer questionable utility in the context of IFA.

A dynamic factor model of the evaluation of the financial crisis in Turkey.

PubMed

Sezgin, F; Kinay, B

2010-01-01

Factor analysis has been widely used in economics and finance in situations where a relatively large number of variables are believed to be driven by few common causes of variation. Dynamic factor analysis (DFA) which is a combination of factor and time series analysis, involves autocorrelation matrices calculated from multivariate time series. Dynamic factor models were traditionally used to construct economic indicators, macroeconomic analysis, business cycles and forecasting. In recent years, dynamic factor models have become more popular in empirical macroeconomics. They have more advantages than other methods in various respects. Factor models can for instance cope with many variables without running into scarce degrees of freedom problems often faced in regression-based analysis. In this study, a model which determines the effect of the global crisis on Turkey is proposed. The main aim of the paper is to analyze how several macroeconomic quantities show an alteration before the evolution of the crisis and to decide if a crisis can be forecasted or not.

Moving in Parallel Toward a Modern Modeling Epistemology: Bayes Factors and Frequentist Modeling Methods.

PubMed

Rodgers, Joseph Lee

2016-01-01

The Bayesian-frequentist debate typically portrays these statistical perspectives as opposing views. However, both Bayesian and frequentist statisticians have expanded their epistemological basis away from a singular focus on the null hypothesis, to a broader perspective involving the development and comparison of competing statistical/mathematical models. For frequentists, statistical developments such as structural equation modeling and multilevel modeling have facilitated this transition. For Bayesians, the Bayes factor has facilitated this transition. The Bayes factor is treated in articles within this issue of Multivariate Behavioral Research. The current presentation provides brief commentary on those articles and more extended discussion of the transition toward a modern modeling epistemology. In certain respects, Bayesians and frequentists share common goals.

Common genetic factors among sexual orientation, gender nonconformity, and number of sex partners in female twins: implications for the evolution of homosexuality.

PubMed

Burri, Andrea; Spector, Tim; Rahman, Qazi

2015-04-01

Homosexuality is a stable population-level trait in humans that lowers direct fitness and yet is substantially heritable, resulting in a so-called Darwinian "paradox." Evolutionary models have proposed that polymorphic genes influencing homosexuality confer a reproductive benefit to heterosexual carriers, thus offsetting the fitness costs associated with persistent homosexuality. This benefit may consist of a "sex typicality" intermediate phenotype. However, there are few empirical tests of this hypothesis using genetically informative data in humans. This study aimed to test the hypothesis that common genetic factors can explain the association between measures of sex typicality, mating success, and homosexuality in a Western (British) sample of female twins. Here, we used data from 996 female twins (498 twin pairs) comprising 242 full dizygotic pairs and 256 full monozygotic pairs (mean age 56.8) and 1,555 individuals whose co-twin did not participate. Measures of sexual orientation, sex typicality (recalled childhood gender nonconformity), and mating success (number of lifetime sexual partners) were completed. Variables were subject to multivariate variance component analysis. We found that masculine women are more likely to be nonheterosexual, report more sexual partners, and, when heterosexual, also report more sexual partners. Multivariate twin modeling showed that common genetic factors explained the relationship between sexual orientation, sex typicality, and mating success through a shared latent factor. Our findings suggest that genetic factors responsible for nonheterosexuality are shared with genetic factors responsible for the number of lifetime sexual partners via a latent sex typicality phenotype in human females. These results may have implications for evolutionary models of homosexuality but are limited by potential mediating variables (such as personality traits) and measurement issues. © 2015 International Society for Sexual Medicine.

An Assessment of the Dimensionality and Factorial Structure of the Revised Paranormal Belief Scale

PubMed Central

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

2017-01-01

Since its introduction, the Revised Paranormal Belief Scale (RPBS) has developed into a principal measure of belief in the paranormal. Accordingly, the RPBS regularly appears within parapsychological research. Despite common usage, academic debates continue to focus on the factorial structure of the RPBS and its psychometric integrity. Using an aggregated heterogeneous sample (N = 3,764), the present study tested the fit of 10 factorial models encompassing variants of the most commonly proposed solutions (seven, five, two, and one-factor) plus new bifactor alternatives. A comparison of competing models revealed a seven-factor bifactor solution possessed superior data-model fit (CFI = 0.945, TLI = 0.933, IFI = 0.945, SRMR = 0.046, RMSEA = 0.058), containing strong factor loadings for a general factor and weaker, albeit acceptable, factor loadings for seven subfactors. This indicated that belief in the paranormal, as measured by the RPBS, is best characterized as a single overarching construct, comprising several related, but conceptually independent subfactors. Furthermore, women reported significantly higher paranormal belief scores than men, and tests of invariance indicated that mean differences in gender are unlikely to reflect measurement bias. Results indicate that despite concerns about the content and psychometric integrity of the RPBS the measure functions well at both a global and seven-factor level. Indeed, the original seven-factors contaminate alternative solutions. PMID:29018398

An Assessment of the Dimensionality and Factorial Structure of the Revised Paranormal Belief Scale.

PubMed

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

2017-01-01

Since its introduction, the Revised Paranormal Belief Scale (RPBS) has developed into a principal measure of belief in the paranormal. Accordingly, the RPBS regularly appears within parapsychological research. Despite common usage, academic debates continue to focus on the factorial structure of the RPBS and its psychometric integrity. Using an aggregated heterogeneous sample ( N = 3,764), the present study tested the fit of 10 factorial models encompassing variants of the most commonly proposed solutions (seven, five, two, and one-factor) plus new bifactor alternatives. A comparison of competing models revealed a seven-factor bifactor solution possessed superior data-model fit (CFI = 0.945, TLI = 0.933, IFI = 0.945, SRMR = 0.046, RMSEA = 0.058), containing strong factor loadings for a general factor and weaker, albeit acceptable, factor loadings for seven subfactors. This indicated that belief in the paranormal, as measured by the RPBS, is best characterized as a single overarching construct, comprising several related, but conceptually independent subfactors. Furthermore, women reported significantly higher paranormal belief scores than men, and tests of invariance indicated that mean differences in gender are unlikely to reflect measurement bias. Results indicate that despite concerns about the content and psychometric integrity of the RPBS the measure functions well at both a global and seven-factor level. Indeed, the original seven-factors contaminate alternative solutions.

A population-based Swedish Twin and Sibling Study of cannabis, stimulant and sedative abuse in men.

PubMed

Kendler, Kenneth S; Ohlsson, Henrik; Maes, Hermine H; Sundquist, Kristina; Lichtenstein, Paul; Sundquist, Jan

2015-04-01

Prior studies, utilizing interview-based assessments, suggest that most of the genetic risk factors for drug abuse (DA) are non-specific with a minority acting specifically on risk for abuse of particular psychoactive substance classes. We seek to replicate these findings using objective national registry data. We examined abuse of cannabis, stimulants (including cocaine) and sedatives ascertained from national Swedish registers in male-male monozygotic (1720 pairs) and dizygotic twins (1219 pairs) combined with near-age full siblings (76,457 pairs) to provide sufficient power. Modeling was performed using Mx. A common pathway model fitted better than an independent pathway model. The latent liability to DA was highly heritable but also influenced by shared environment. Cannabis, stimulant and sedative abuse all loaded strongly on the common factor. Estimates for the total heritability for the three forms of substance abuse ranged from 64 to 70%. Between 75 and 90% of that genetic risk was non-specific, coming from the common factor with the remainder deriving from substance specific genetic risk factors. By contrast, all of the shared environmental effects, which accounted for 18-20% of the variance in liability, were non-specific. In accord with prior studies based on personal interviews, the large preponderance of genetic risk factors for abuse of specific classes of psychoactive substance are non-specific. These results suggest that genetic variation in the primary sites of action of the psychoactive drugs, which differ widely across most drug classes, play a minor role in human individual differences in risk for DA. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

A Linear Variable-[theta] Model for Measuring Individual Differences in Response Precision

ERIC Educational Resources Information Center

Ferrando, Pere J.

2011-01-01

Models for measuring individual response precision have been proposed for binary and graded responses. However, more continuous formats are quite common in personality measurement and are usually analyzed with the linear factor analysis model. This study extends the general Gaussian person-fluctuation model to the continuous-response case and…

Coincident Detection Significance in Multimessenger Astronomy

NASA Astrophysics Data System (ADS)

Ashton, G.; Burns, E.; Dal Canton, T.; Dent, T.; Eggenstein, H.-B.; Nielsen, A. B.; Prix, R.; Was, M.; Zhu, S. J.

2018-06-01

We derive a Bayesian criterion for assessing whether signals observed in two separate data sets originate from a common source. The Bayes factor for a common versus unrelated origin of signals includes an overlap integral of the posterior distributions over the common-source parameters. Focusing on multimessenger gravitational-wave astronomy, we apply the method to the spatial and temporal association of independent gravitational-wave and electromagnetic (or neutrino) observations. As an example, we consider the coincidence between the recently discovered gravitational-wave signal GW170817 from a binary neutron star merger and the gamma-ray burst GRB 170817A: we find that the common-source model is enormously favored over a model describing them as unrelated signals.

Postmodernism, Therapeutic Common Factors, and Innovation: Contemporary Influences Shaping a More Efficient and Effective Model of School Counseling

ERIC Educational Resources Information Center

Klein, James F.; Gee, Corrie R.

2006-01-01

School counseling lacks clarity. This confusion is the result of competing models and confusing standards, domains, and competencies. This article offers a simplified model of school counseling entitled the "Six 'C' Model" (i.e., Care, Collaboration, Champion, Challenge, Courage, and Commitment). The interactive model is informed by the…

Risk Factors for Unidirectional and Bidirectional Intimate Partner Violence among Young Adults

ERIC Educational Resources Information Center

Renner, Lynette M.; Whitney, Stephen D.

2012-01-01

Objective: The purpose of this study was to identify common and unique risk factors for intimate partner violence (IPV) among young adults in relationships. Guided by two models of IPV, the same set of risk factors was used to examine outcomes of unidirectional (perpetration or victimization) and bidirectional (reciprocal) IPV separately for males…

An improved model to predict bandwidth enhancement in an inductively tuned common source amplifier.

PubMed

Reza, Ashif; Misra, Anuraag; Das, Parnika

2016-05-01

This paper presents an improved model for the prediction of bandwidth enhancement factor (BWEF) in an inductively tuned common source amplifier. In this model, we have included the effect of drain-source channel resistance of field effect transistor along with load inductance and output capacitance on BWEF of the amplifier. A frequency domain analysis of the model is performed and a closed-form expression is derived for BWEF of the amplifier. A prototype common source amplifier is designed and tested. The BWEF of amplifier is obtained from the measured frequency response as a function of drain current and load inductance. In the present work, we have clearly demonstrated that inclusion of drain-source channel resistance in the proposed model helps to estimate the BWEF, which is accurate to less than 5% as compared to the measured results.

Global self-esteem and method effects: competing factor structures, longitudinal invariance, and response styles in adolescents.

PubMed

Urbán, Róbert; Szigeti, Réka; Kökönyei, Gyöngyi; Demetrovics, Zsolt

2014-06-01

The Rosenberg Self-Esteem Scale (RSES) is a widely used measure for assessing self-esteem, but its factor structure is debated. Our goals were to compare 10 alternative models for the RSES and to quantify and predict the method effects. This sample involves two waves (N =2,513 9th-grade and 2,370 10th-grade students) from five waves of a school-based longitudinal study. The RSES was administered in each wave. The global self-esteem factor with two latent method factors yielded the best fit to the data. The global factor explained a large amount of the common variance (61% and 46%); however, a relatively large proportion of the common variance was attributed to the negative method factor (34 % and 41%), and a small proportion of the common variance was explained by the positive method factor (5% and 13%). We conceptualized the method effect as a response style and found that being a girl and having a higher number of depressive symptoms were associated with both low self-esteem and negative response style, as measured by the negative method factor. Our study supported the one global self-esteem construct and quantified the method effects in adolescents.

Global self-esteem and method effects: competing factor structures, longitudinal invariance and response styles in adolescents

PubMed Central

Urbán, Róbert; Szigeti, Réka; Kökönyei, Gyöngyi; Demetrovics, Zsolt

2013-01-01

The Rosenberg Self-Esteem Scale (RSES) is a widely used measure for assessing self-esteem, but its factor structure is debated. Our goals were to compare 10 alternative models for RSES; and to quantify and predict the method effects. This sample involves two waves (N=2513 ninth-grade and 2370 tenth-grade students) from five waves of a school-based longitudinal study. RSES was administered in each wave. The global self-esteem factor with two latent method factors yielded the best fit to the data. The global factor explained large amount of the common variance (61% and 46%); however, a relatively large proportion of the common variance was attributed to the negative method factor (34 % and 41%), and a small proportion of the common variance was explained by the positive method factor (5% and 13%). We conceptualized the method effect as a response style, and found that being a girl and having higher number of depressive symptoms were associated with both low self-esteem and negative response style measured by the negative method factor. Our study supported the one global self-esteem construct and quantified the method effects in adolescents. PMID:24061931

Building a Values-Informed Mental Model for New Orleans Climate Risk Management.

PubMed

Bessette, Douglas L; Mayer, Lauren A; Cwik, Bryan; Vezér, Martin; Keller, Klaus; Lempert, Robert J; Tuana, Nancy

2017-10-01

Individuals use values to frame their beliefs and simplify their understanding when confronted with complex and uncertain situations. The high complexity and deep uncertainty involved in climate risk management (CRM) lead to individuals' values likely being coupled to and contributing to their understanding of specific climate risk factors and management strategies. Most mental model approaches, however, which are commonly used to inform our understanding of people's beliefs, ignore values. In response, we developed a "Values-informed Mental Model" research approach, or ViMM, to elicit individuals' values alongside their beliefs and determine which values people use to understand and assess specific climate risk factors and CRM strategies. Our results show that participants consistently used one of three values to frame their understanding of risk factors and CRM strategies in New Orleans: (1) fostering a healthy economy, wealth, and job creation, (2) protecting and promoting healthy ecosystems and biodiversity, and (3) preserving New Orleans' unique culture, traditions, and historically significant neighborhoods. While the first value frame is common in analyses of CRM strategies, the latter two are often ignored, despite their mirroring commonly accepted pillars of sustainability. Other values like distributive justice and fairness were prioritized differently depending on the risk factor or strategy being discussed. These results suggest that the ViMM method could be a critical first step in CRM decision-support processes and may encourage adoption of CRM strategies more in line with stakeholders' values. © 2017 Society for Risk Analysis.

Sediment Acoustics: Wideband Model, Reflection Loss and Ambient Noise Inversion

DTIC Science & Technology

2009-09-30

between 1 and 10 kHz. The model is also capable of explaining the apparent discrepancy between the data and the Kramers- Kronig relationship (K-K...of in-situ measurements of sediment sound speed and attenuation from SAX99, SAX04 and SW06 with the commonly used Kramers- Kronig equation (black...inverse quality factor. The data is overlaid by the Kramers- Kronig estimate of sound speed from measured attenuation, by both the commonly used equation

Examining age-related shared variance between face cognition, vision, and self-reported physical health: a test of the common cause hypothesis for social cognition

PubMed Central

Olderbak, Sally; Hildebrandt, Andrea; Wilhelm, Oliver

2015-01-01

The shared decline in cognitive abilities, sensory functions (e.g., vision and hearing), and physical health with increasing age is well documented with some research attributing this shared age-related decline to a single common cause (e.g., aging brain). We evaluate the extent to which the common cause hypothesis predicts associations between vision and physical health with social cognition abilities specifically face perception and face memory. Based on a sample of 443 adults (17–88 years old), we test a series of structural equation models, including Multiple Indicator Multiple Cause (MIMIC) models, and estimate the extent to which vision and self-reported physical health are related to face perception and face memory through a common factor, before and after controlling for their fluid cognitive component and the linear effects of age. Results suggest significant shared variance amongst these constructs, with a common factor explaining some, but not all, of the shared age-related variance. Also, we found that the relations of face perception, but not face memory, with vision and physical health could be completely explained by fluid cognition. Overall, results suggest that a single common cause explains most, but not all age-related shared variance with domain specific aging mechanisms evident. PMID:26321998

The Mindful Attention Awareness Scale: Further Examination of Dimensionality, Reliability, and Concurrent Validity Estimates.

PubMed

Osman, Augustine; Lamis, Dorian A; Bagge, Courtney L; Freedenthal, Stacey; Barnes, Sean M

2016-01-01

We examined the factor structure and psychometric properties of the Mindful Attention Awareness Scale (MAAS) in a sample of 810 undergraduate students. Using common exploratory factor analysis (EFA), we obtained evidence for a 1-factor solution (41.84% common variance). To confirm unidimensionality of the 15-item MAAS, we conducted a 1-factor confirmatory factor analysis (CFA). Results of the EFA and CFA, respectively, provided support for a unidimensional model. Using differential item functioning analysis methods within item response theory modeling (IRT-based DIF), we found that individuals with high and low levels of nonattachment responded similarly to the MAAS items. Following a detailed item analysis, we proposed a 5-item short version of the instrument and present descriptive statistics and composite score reliability for the short and full versions of the MAAS. Finally, correlation analyses showed that scores on the full and short versions of the MAAS were associated with measures assessing related constructs. The 5-item MAAS is as useful as the original MAAS in enhancing our understanding of the mindfulness construct.

Quantifying the Strength of General Factors in Psychopathology: A Comparison of CFA with Maximum Likelihood Estimation, BSEM, and ESEM/EFA Bifactor Approaches.

PubMed

Murray, Aja Louise; Booth, Tom; Eisner, Manuel; Obsuth, Ingrid; Ribeaud, Denis

2018-05-22

Whether or not importance should be placed on an all-encompassing general factor of psychopathology (or p factor) in classifying, researching, diagnosing, and treating psychiatric disorders depends (among other issues) on the extent to which comorbidity is symptom-general rather than staying largely within the confines of narrower transdiagnostic factors such as internalizing and externalizing. In this study, we compared three methods of estimating p factor strength. We compared omega hierarchical and explained common variance calculated from confirmatory factor analysis (CFA) bifactor models with maximum likelihood (ML) estimation, from exploratory structural equation modeling/exploratory factor analysis models with a bifactor rotation, and from Bayesian structural equation modeling (BSEM) bifactor models. Our simulation results suggested that BSEM with small variance priors on secondary loadings might be the preferred option. However, CFA with ML also performed well provided secondary loadings were modeled. We provide two empirical examples of applying the three methodologies using a normative sample of youth (z-proso, n = 1,286) and a university counseling sample (n = 359).

Common Sense Illness Beliefs of Diabetes among At-Risk Latino College Students

PubMed Central

Santos, Silvia J.; Hurtado-Ortiz, Maria T.; Lewis, Laurenne; Ramirez-Garcia, Julia

2017-01-01

This study examined the validity of the Implicit Model of Illness Questionnaire (IMIQ - Schiaffino & Cea, 1995) when used with Latino college students (n = 156; 34% male, 66% female) who are at-risk for developing diabetes due to family history of this disease. An exploratory principal-axis factor analysis yielded four significant factors – curability, personal responsibility, symptom variability/seriousness, and personal attributions – which accounted for 35% of variance and reflected a psychosocial-biomedical common sense perspective of diabetes. Factor-based analyses revealed differences in diabetes illness beliefs based on students’ age, generational status, acculturation orientation, and disease experience of the afflicted relative. PMID:29056849

Risk factors for gambling and substance use among recent college students.

PubMed

Caldeira, Kimberly M; Arria, Amelia M; O'Grady, Kevin E; Vincent, Kathryn B; Robertson, Carl; Welsh, Christopher J

2017-10-01

While it is well known that substance use and gambling overlap, the degree to which this overlap can be explained by shared risk factors has not been fully explored. This study aimed to identify common and unique risk factors for gambling and substance use among young adults. Young adults (n=1,019) in a longitudinal study since college entry were interviewed annually. Past-year frequency of seven gambling activities was assessed once (Year 5). Structural equation models evaluated suspected risk factors in two models, one for gambling with substance use as an intermediary variable, and one for substance use with gambling as the intermediary variable. Sixty percent gambled; 6% gambled weekly or more. Examination of the two structural models supported the existence of significant paths (a) from two of the five substance use variables (alcohol, drugs) to gambling frequency, and (b) from gambling frequency to all five substance use variables. Every risk factor associated with gambling was also associated with one or more substance use variables. Risk factors common to gambling and substance use were sex, race/ethnicity, extracurricular involvement (fraternity/sorority, athletics), impulsive sensation-seeking, and behavioral dysregulation. Risk factors unique to substance use were conduct problems, anxiety, and parent's history of alcohol and mental health problems. Gambling and substance use are interrelated, but with incomplete overlap in their respective risk factors. Results underscore the need for longitudinal research to elucidate their distinct etiologies. Copyright © 2017 Elsevier B.V. All rights reserved.

Developmental Trajectories in Toddlers’ Self-restraint Predict Individual Differences in Executive Functions 14 Years Later: A Behavioral Genetic Analysis

PubMed Central

Friedman, Naomi P.; Miyake, Akira; Robinson, JoAnn L.; Hewitt, John K.

2011-01-01

We examined whether self-restraint in early childhood predicted individual differences in three executive functions (EFs; inhibiting prepotent responses, updating working memory, and shifting task sets) in late adolescence in a sample of ~950 twins. At ages 14, 20, 24, and 36 months, the children were shown an attractive toy and told not to touch it for 30 seconds. Latency to touch the toy increased with age, and latent class growth modeling distinguished two groups of children that differed in their latencies to touch the toy at all 4 time points. Using confirmatory factor analysis, the three EFs (measured with latent variables at age 17 years) were decomposed into a Common EF factor (isomorphic to response inhibition ability) and two factors specific to updating and shifting, respectively. Less restrained children had significantly lower scores on the Common EF factor, equivalent scores on the Updating-specific factor, and higher scores on the Shifting-specific factor than the more restrained children. The less restrained group also had lower IQ scores, but this effect was entirely mediated by the EF components. Twin models indicated that the associations were primarily genetic in origin for the Common EF variable but split between genetics and nonshared environment for the Shifting-specific variable. These results suggest a biological relation between individual differences in self-restraint and EFs, one that begins early in life and persists into late adolescence. PMID:21668099

Modeling genetic and environmental factors to increase heritability and ease the identification of candidate genes for birth weight: a twin study.

PubMed

Gielen, M; Lindsey, P J; Derom, C; Smeets, H J M; Souren, N Y; Paulussen, A D C; Derom, R; Nijhuis, J G

2008-01-01

Heritability estimates of birth weight have been inconsistent. Possible explanations are heritability changes during gestational age or the influence of covariates (e.g. chorionicity). The aim of this study was to model birth weights of twins across gestational age and to quantify the genetic and environmental components. We intended to reduce the common environmental variance to increase heritability and thereby the chance of identifying candidate genes influencing the genetic variance of birth weight. Perinatal data were obtained from 4232 live-born twin pairs from the East Flanders Prospective Twin Survey, Belgium. Heritability of birth weights across gestational ages was estimated using a non-linear multivariate Gaussian regression with covariates in the means model and in covariance structure. Maternal, twin-specific, and placental factors were considered as covariates. Heritability of birth weight decreased during gestation from 25 to 42 weeks. However, adjusting for covariates increased the heritability over this time period, with the highest heritability for first-born twins of multipara with separate placentas, who were staying alive (from 52% at 25 weeks to 30% at 42 weeks). Twin-specific factors revealed latent genetic components, whereas placental factors explained common and unique environmental factors. The number of placentas and site of the insertion of the umbilical cord masked the effect of chorionicity. Modeling genetic and environmental factors leads to a better estimate of their role in growth during gestation. For birth weight, mainly environmental factors were explained, resulting in an increase of the heritability and thereby the chance of finding genes influencing birth weight in linkage and association studies.

Characterisation of soil microtopography effects on runoff and soil erosion rates under simulated rainfall

USDA-ARS?s Scientific Manuscript database

Soil surface roughness is commonly identified as one of the dominant factors governing runoff and interrill erosion. Yet, because of difficulties in acquiring the data, most studies pay little attention to soil surface roughness. This is particularly true for soil erosion models which commonly don't...

Contaminant deposition building shielding factors for US residential structures.

PubMed

Dickson, Elijah; Hamby, David; Eckerman, Keith

2017-10-10

This paper presents validated building shielding factors designed for contemporary US housing-stock under an idealized, yet realistic, exposure scenario from contaminant deposition on the roof and surrounding surfaces. The building shielding factors are intended for use in emergency planning and level three probabilistic risk assessments for a variety of postulated radiological events in which a realistic assessment is necessary to better understand the potential risks for accident mitigation and emergency response planning. Factors are calculated from detailed computational housing-units models using the general-purpose Monte Carlo N-Particle computational code, MCNP5, and are benchmarked from a series of narrow- and broad-beam measurements analyzing the shielding effectiveness of ten common general-purpose construction materials and ten shielding models representing the primary weather barriers (walls and roofs) of likely US housing-stock. Each model was designed to scale based on common residential construction practices and include, to the extent practical, all structurally significant components important for shielding against ionizing radiation. Calculations were performed for floor-specific locations from contaminant deposition on the roof and surrounding ground as well as for computing a weighted-average representative building shielding factor for single- and multi-story detached homes, both with and without basement as well for single-wide manufactured housing-unit. © 2017 IOP Publishing Ltd.

Contaminant deposition building shielding factors for US residential structures.

PubMed

Dickson, E D; Hamby, D M; Eckerman, K F

2015-06-01

This paper presents validated building shielding factors designed for contemporary US housing-stock under an idealized, yet realistic, exposure scenario from contaminant deposition on the roof and surrounding surfaces. The building shielding factors are intended for use in emergency planning and level three probabilistic risk assessments for a variety of postulated radiological events in which a realistic assessment is necessary to better understand the potential risks for accident mitigation and emergency response planning. Factors are calculated from detailed computational housing-units models using the general-purpose Monte Carlo N-Particle computational code, MCNP5, and are benchmarked from a series of narrow- and broad-beam measurements analyzing the shielding effectiveness of ten common general-purpose construction materials and ten shielding models representing the primary weather barriers (walls and roofs) of likely US housing-stock. Each model was designed to scale based on common residential construction practices and include, to the extent practical, all structurally significant components important for shielding against ionizing radiation. Calculations were performed for floor-specific locations from contaminant deposition on the roof and surrounding ground as well as for computing a weighted-average representative building shielding factor for single- and multi-story detached homes, both with and without basement as well for single-wide manufactured housing-unit.

Multi-level multi-task learning for modeling cross-scale interactions in nested geospatial data

USGS Publications Warehouse

Yuan, Shuai; Zhou, Jiayu; Tan, Pang-Ning; Fergus, Emi; Wagner, Tyler; Sorrano, Patricia

2017-01-01

Predictive modeling of nested geospatial data is a challenging problem as the models must take into account potential interactions among variables defined at different spatial scales. These cross-scale interactions, as they are commonly known, are particularly important to understand relationships among ecological properties at macroscales. In this paper, we present a novel, multi-level multi-task learning framework for modeling nested geospatial data in the lake ecology domain. Specifically, we consider region-specific models to predict lake water quality from multi-scaled factors. Our framework enables distinct models to be developed for each region using both its local and regional information. The framework also allows information to be shared among the region-specific models through their common set of latent factors. Such information sharing helps to create more robust models especially for regions with limited or no training data. In addition, the framework can automatically determine cross-scale interactions between the regional variables and the local variables that are nested within them. Our experimental results show that the proposed framework outperforms all the baseline methods in at least 64% of the regions for 3 out of 4 lake water quality datasets evaluated in this study. Furthermore, the latent factors can be clustered to obtain a new set of regions that is more aligned with the response variables than the original regions that were defined a priori from the ecology domain.

The psychology of doing nothing: forms of decision avoidance result from reason and emotion.

PubMed

Anderson, Christopher J

2003-01-01

Several independent lines of research bear on the question of why individuals avoid decisions by postponing them, failing to act, or accepting the status quo. This review relates findings across several different disciplines and uncovers 4 decision avoidance effects that offer insight into this common but troubling behavior: choice deferral, status quo bias, omission bias, and inaction inertia. These findings are related by common antecedents and consequences in a rational-emotional model of the factors that predispose humans to do nothing. Prominent components of the model include cost-benefit calculations, anticipated regret, and selection difficulty. Other factors affecting decision avoidance through these key components, such as anticipatory negative emotions, decision strategies, counterfactual thinking, and preference uncertainty, are also discussed.

Genetic Architecture of the Delis-Kaplan Executive Function System Trail Making Test: Evidence for Distinct Genetic Influences on Executive Function

PubMed Central

Vasilopoulos, Terrie; Franz, Carol E.; Panizzon, Matthew S.; Xian, Hong; Grant, Michael D.; Lyons, Michael J; Toomey, Rosemary; Jacobson, Kristen C.; Kremen, William S.

2012-01-01

Objective To examine how genes and environments contribute to relationships among Trail Making test conditions and the extent to which these conditions have unique genetic and environmental influences. Method Participants included 1237 middle-aged male twins from the Vietnam-Era Twin Study of Aging (VESTA). The Delis-Kaplan Executive Function System Trail Making test included visual searching, number and letter sequencing, and set-shifting components. Results Phenotypic correlations among Trails conditions ranged from 0.29 – 0.60, and genes accounted for the majority (58–84%) of each correlation. Overall heritability ranged from 0.34 to 0.62 across conditions. Phenotypic factor analysis suggested a single factor. In contrast, genetic models revealed a single common genetic factor but also unique genetic influences separate from the common factor. Genetic variance (i.e., heritability) of number and letter sequencing was completely explained by the common genetic factor while unique genetic influences separate from the common factor accounted for 57% and 21% of the heritabilities of visual search and set-shifting, respectively. After accounting for general cognitive ability, unique genetic influences accounted for 64% and 31% of those heritabilities. Conclusions A common genetic factor, most likely representing a combination of speed and sequencing accounted for most of the correlation among Trails 1–4. Distinct genetic factors, however, accounted for a portion of variance in visual scanning and set-shifting. Thus, although traditional phenotypic shared variance analysis techniques suggest only one general factor underlying different neuropsychological functions in non-patient populations, examining the genetic underpinnings of cognitive processes with twin analysis can uncover more complex etiological processes. PMID:22201299

Exploring the Full-Information Bifactor Model in Vertical Scaling with Construct Shift

ERIC Educational Resources Information Center

Li, Ying; Lissitz, Robert W.

2012-01-01

To address the lack of attention to construct shift in item response theory (IRT) vertical scaling, a multigroup, bifactor model was proposed to model the common dimension for all grades and the grade-specific dimensions. Bifactor model estimation accuracy was evaluated through a simulation study with manipulated factors of percentage of common…

Partner alcohol use, violence and women’s mental health: population-based survey in India

PubMed Central

Nayak, Madhabika B.; Patel, Vikram; Bond, Jason C.; Greenfield, Thomas K.

2010-01-01

Background The relationship between partner alcohol use and violence as risk factors for poor mental health in women is unclear. Aims To describe partner-related and other psychosocial risk factors for common mental disorders in women and examine interrelationships between these factors. Method Data are reported on 821 women aged 18–49 years from a larger population study in north Goa, India. Logistic regression models evaluated the risks for women’s common mental disorders and tested for mediation effects in the relationship between partner alcohol use and these disorders. Results Excessive partner alcohol use increased the risk for common mental disorders two- to threefold. Partner violence and alcohol-related problems each partially mediated the association between partner excessive alcohol use and these mental disorders. Women’s own violence-related attitudes were also independently associated with them. Conclusions Partner alcohol use, partner violence and women’s violence-related attitudes must be addressed to prevent and treat common mental disorders in women. PMID:20194540

Urinary tract infectivity or R strains of Escherichia coli carrying various virulence factors.

PubMed

Kétyi, I; Naumann, G; Nimmich, W

1983-01-01

The virulence factors of Escherichia coli supposed to act in urinary tract infections were studied on R strains in a suckling mouse model. The production of alpha-(diffusible-) haemolysin or the possession of antigen K1 enhanced the virulence significantly, while the type 1 (common) fimbriae failed to do so. An isogenic motile and non-motile pair of E. coli did not show any difference in infectivity in the model. The adhesins, the diffusible haemolysin, and the acidic polysaccharide K antigens (K1) are definitely additive virulence factors in the model. This is in good agreement with the experience of clinical bacteriology.

An in-depth review of photovoltaic system performance models

NASA Technical Reports Server (NTRS)

Smith, J. H.; Reiter, L. R.

1984-01-01

The features, strong points and shortcomings of 10 numerical models commonly applied to assessing photovoltaic performance are discussed. The models range in capabilities from first-order approximations to full circuit level descriptions. Account is taken, at times, of the cell and module characteristics, the orientation and geometry, array-level factors, the power-conditioning equipment, the overall plant performance, O and M effects, and site-specific factors. Areas of improvement and/or necessary extensions are identified for several of the models. Although the simplicity of a model was found not necessarily to affect the accuracy of the data generated, the use of any one model was dependent on the application.

Recurrent personality dimensions in inclusive lexical studies: indications for a big six structure.

PubMed

Saucier, Gerard

2009-10-01

Previous evidence for both the Big Five and the alternative six-factor model has been drawn from lexical studies with relatively narrow selections of attributes. This study examined factors from previous lexical studies using a wider selection of attributes in 7 languages (Chinese, English, Filipino, Greek, Hebrew, Spanish, and Turkish) and found 6 recurrent factors, each with common conceptual content across most of the studies. The previous narrow-selection-based six-factor model outperformed the Big Five in capturing the content of the 6 recurrent wideband factors. Adjective markers of the 6 recurrent wideband factors showed substantial incremental prediction of important criterion variables over and above the Big Five. Correspondence between wideband 6 and narrowband 6 factors indicate they are variants of a "Big Six" model that is more general across variable-selection procedures and may be more general across languages and populations.

When What You See Isn’t What You Get: How Viewshed Analysis is Impacted by Digital Surface Model (DSM) Resolution

EPA Science Inventory

A key factor for improving models of ecosystem benefits is the availability of high quality spatial data. High resolution LIDAR data are now commonly available and can be used to produce more accurate model outputs. However, increased resolution leads to higher computer resource...

Compensatory changes in CYP expression in three different toxicology mouse models: CAR-null, Cyp3a-null, and Cyp2b9/10/13-null mice

EPA Science Inventory

Targeted mutant models are common in mechanistic toxicology experiments investigating the absorption, metabolism, distribution, or elimination (ADME) of chemicals from individuals. Key models include those for xenosensing transcription factors and cytochrome P450s (CYP). Here we ...

The Superskills Model: A Supervisory Microskill Competency Training Model

ERIC Educational Resources Information Center

Destler, Dusty

2017-01-01

Streamlined supervision frameworks are needed to enhance and progress the practice and training of supervisors. This author proposes the SuperSkills Model (SSM), grounded in the practice of microskills and supervision common factors, with a focus on the development and foundational learning of supervisors-in-training. The SSM worksheet prompts for…

A "Common Factors" Approach to Developing Culturally Tailored HIV Prevention Interventions.

PubMed

Owczarzak, Jill; Phillips, Sarah D; Filippova, Olga; Alpatova, Polina; Mazhnaya, Alyona; Zub, Tatyana; Aleksanyan, Ruzanna

2016-06-01

The current dominant model of HIV prevention intervention dissemination involves packaging interventions developed in one context, training providers to implement that specific intervention, and evaluating the extent to which providers implement it with fidelity. Research shows that providers rarely implement these programs with fidelity due to perceived incompatibility, resource constraints, and preference for locally generated solutions. In this study, we used the concept of "common factors," or broad constructs shared by most evidence-based HIV prevention interventions, to train service providers to develop their own programs. We recruited eight Ukrainian HIV prevention organizations from regions with HIV epidemics concentrated among people who inject drugs. We trained staff to identify HIV risk behaviors and determinants, construct behavior change logic models, and develop and manualize an intervention. We systematically reviewed each manual to assess intervention format and content and determine whether the program met intervention criteria as taught during training. All agencies developed programs that reflected common factors of effective behavior change HIV prevention interventions. Each agency's program targeted a unique population that reflected local HIV epidemiology. All programs incorporated diverse pedagogical strategies that focused on skill-building, goal-setting, communication, and empowerment. Agencies struggled to limit information dissemination and the overall scope and length of their programs. We conclude that training service providers to develop their own programs based on common elements of effective behavior change interventions can potentially transform existing processes of program development, implementation, and capacity building. Expanding this model will require committed training and support resources. © 2015 Society for Public Health Education.

First order error corrections in common introductory physics experiments

NASA Astrophysics Data System (ADS)

Beckey, Jacob; Baker, Andrew; Aravind, Vasudeva; Clarion Team

As a part of introductory physics courses, students perform different standard lab experiments. Almost all of these experiments are prone to errors owing to factors like friction, misalignment of equipment, air drag, etc. Usually these types of errors are ignored by students and not much thought is paid to the source of these errors. However, paying attention to these factors that give rise to errors help students make better physics models and understand physical phenomena behind experiments in more detail. In this work, we explore common causes of errors in introductory physics experiment and suggest changes that will mitigate the errors, or suggest models that take the sources of these errors into consideration. This work helps students build better and refined physical models and understand physics concepts in greater detail. We thank Clarion University undergraduate student grant for financial support involving this project.

Aging Trajectories in Different Body Systems Share Common Environmental Etiology: The Healthy Aging Twin Study (HATS).

PubMed

Moayyeri, Alireza; Hart, Deborah J; Snieder, Harold; Hammond, Christopher J; Spector, Timothy D; Steves, Claire J

2016-02-01

Little is known about the extent to which aging trajectories of different body systems share common sources of variance. We here present a large twin study investigating the trajectories of change in five systems: cardiovascular, respiratory, skeletal, morphometric, and metabolic. Longitudinal clinical data were collected on 3,508 female twins in the TwinsUK registry (complete pairs:740 monozygotic (MZ), 986 dizygotic (DZ), mean age at entry 48.9 ± 10.4, range 18-75 years; mean follow-up 10.2 ± 2.8 years, range 4-17.8 years). Panel data on multiple age-related variables were used to estimate biological ages for each individual at each time point, in linear mixed effects models. A weighted average approach was used to combine variables within predefined body system groups. Aging trajectories for each system in each individual were then constructed using linear modeling. Multivariate structural equation modeling of these aging trajectories showed low genetic effects (heritability), ranging from 2% in metabolic aging to 22% in cardiovascular aging. However, we found a significant effect of shared environmental factors on the variations in aging trajectories in cardiovascular (54%), skeletal (34%), morphometric (53%), and metabolic systems (53%). The remainder was due to environmental factors unique to each individual plus error. Multivariate Cholesky decomposition showed that among aging trajectories for various body systems there were significant and substantial correlations between the unique environmental latent factors as well as shared environmental factors. However, there was no evidence for a single common factor for aging. This study, the first of its kind in aging, suggests that diverse organ systems share non-genetic sources of variance for aging trajectories. Confirmatory studies are needed using population-based twin cohorts and alternative methods of handling missing data.

The structure of psychopathology in adolescence and its common personality and cognitive correlates.

PubMed

Castellanos-Ryan, Natalie; Brière, Frederic N; O'Leary-Barrett, Maeve; Banaschewski, Tobias; Bokde, Arun; Bromberg, Uli; Büchel, Christian; Flor, Herta; Frouin, Vincent; Gallinat, Juergen; Garavan, Hugh; Martinot, Jean-Luc; Nees, Frauke; Paus, Tomas; Pausova, Zdenka; Rietschel, Marcella; Smolka, Michael N; Robbins, Trevor W; Whelan, Robert; Schumann, Gunter; Conrod, Patricia

2016-11-01

The traditional view that mental disorders are distinct, categorical disorders has been challenged by evidence that disorders are highly comorbid and exist on a continuum (e.g., Caspi et al., 2014; Tackett et al., 2013). The first objective of this study was to use structural equation modeling to model the structure of psychopathology in an adolescent community-based sample (N = 2,144) including conduct disorder, attention-deficit/hyperactivity disorder (ADHD), oppositional-defiant disorder (ODD), obsessive-compulsive disorder, eating disorders, substance use, anxiety, depression, phobias, and other emotional symptoms, assessed at 16 years. The second objective was to identify common personality and cognitive correlates of psychopathology, assessed at 14 years. Results showed that psychopathology at 16 years fit 2 bifactor models equally well: (a) a bifactor model, reflecting a general psychopathology factor, as well as specific externalizing (representing mainly substance misuse and low ADHD) and internalizing factors; and (b) a bifactor model with a general psychopathology factor and 3 specific externalizing (representing mainly ADHD and ODD), substance use and internalizing factors. The general psychopathology factor was related to high disinhibition/impulsivity, low agreeableness, high neuroticism and hopelessness, high delay-discounting, poor response inhibition and low performance IQ. Substance use was specifically related to high novelty-seeking, sensation-seeking, extraversion, high verbal IQ, and risk-taking. Internalizing psychopathology was specifically related to high neuroticism, hopelessness and anxiety-sensitivity, low novelty-seeking and extraversion, and an attentional bias toward negatively valenced verbal stimuli. Findings reveal several nonspecific or transdiagnostic personality and cognitive factors that may be targeted in new interventions to potentially prevent the development of multiple psychopathologies. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

The Structure of Psychopathology in Adolescence and Its Common Personality and Cognitive Correlates

PubMed Central

2016-01-01

The traditional view that mental disorders are distinct, categorical disorders has been challenged by evidence that disorders are highly comorbid and exist on a continuum (e.g., Caspi et al., 2014; Tackett et al., 2013). The first objective of this study was to use structural equation modeling to model the structure of psychopathology in an adolescent community-based sample (N = 2,144) including conduct disorder, attention-deficit/hyperactivity disorder (ADHD), oppositional-defiant disorder (ODD), obsessive–compulsive disorder, eating disorders, substance use, anxiety, depression, phobias, and other emotional symptoms, assessed at 16 years. The second objective was to identify common personality and cognitive correlates of psychopathology, assessed at 14 years. Results showed that psychopathology at 16 years fit 2 bifactor models equally well: (a) a bifactor model, reflecting a general psychopathology factor, as well as specific externalizing (representing mainly substance misuse and low ADHD) and internalizing factors; and (b) a bifactor model with a general psychopathology factor and 3 specific externalizing (representing mainly ADHD and ODD), substance use and internalizing factors. The general psychopathology factor was related to high disinhibition/impulsivity, low agreeableness, high neuroticism and hopelessness, high delay-discounting, poor response inhibition and low performance IQ. Substance use was specifically related to high novelty-seeking, sensation-seeking, extraversion, high verbal IQ, and risk-taking. Internalizing psychopathology was specifically related to high neuroticism, hopelessness and anxiety-sensitivity, low novelty-seeking and extraversion, and an attentional bias toward negatively valenced verbal stimuli. Findings reveal several nonspecific or transdiagnostic personality and cognitive factors that may be targeted in new interventions to potentially prevent the development of multiple psychopathologies. PMID:27819466

Econometrics and Psychometrics: A Survey of Communalities

ERIC Educational Resources Information Center

Goldberger, Arthur S.

1971-01-01

Several themes which are common to both econometrics and psychometrics are surveyed. The themes are illustrated by reference to permanent income hypotheses, simultaneous equation models, adaptive expectations and partial adjustment schemes, and by reference to test score theory, factor analysis, and time-series models. (Author)

An Analysis of Machine- and Human-Analytics in Classification.

PubMed

Tam, Gary K L; Kothari, Vivek; Chen, Min

2017-01-01

In this work, we present a study that traces the technical and cognitive processes in two visual analytics applications to a common theoretic model of soft knowledge that may be added into a visual analytics process for constructing a decision-tree model. Both case studies involved the development of classification models based on the "bag of features" approach. Both compared a visual analytics approach using parallel coordinates with a machine-learning approach using information theory. Both found that the visual analytics approach had some advantages over the machine learning approach, especially when sparse datasets were used as the ground truth. We examine various possible factors that may have contributed to such advantages, and collect empirical evidence for supporting the observation and reasoning of these factors. We propose an information-theoretic model as a common theoretic basis to explain the phenomena exhibited in these two case studies. Together we provide interconnected empirical and theoretical evidence to support the usefulness of visual analytics.

Structure of the Wechsler Intelligence Scale for Children--Fourth Edition among a national sample of referred students.

PubMed

Watkins, Marley W

2010-12-01

The structure of the Wechsler Intelligence Scale for Children-Fourth Edition (WISC-IV; D. Wechsler, 2003a) was analyzed via confirmatory factor analysis among a national sample of 355 students referred for psychoeducational evaluation by 93 school psychologists from 35 states. The structure of the WISC-IV core battery was best represented by four first-order factors as per D. Wechsler (2003b), plus a general intelligence factor in a direct hierarchical model. The general factor was the predominate source of variation among WISC-IV subtests, accounting for 48% of the total variance and 75% of the common variance. The largest 1st-order factor, Processing Speed, only accounted for 6.1% total and 9.5% common variance. Given these explanatory contributions, recommendations favoring interpretation of the 1st-order factor scores over the general intelligence score appear to be misguided.

Common duckweed (Lemna minor) is a versatile high-throughput infection model for the Burkholderia cepacia complex and other pathogenic bacteria.

PubMed

Thomson, Euan L S; Dennis, Jonathan J

2013-01-01

Members of the Burkholderia cepacia complex (Bcc) have emerged in recent decades as problematic pulmonary pathogens of cystic fibrosis (CF) patients, with severe infections progressing to acute necrotizing pneumonia and sepsis. This study presents evidence that Lemna minor (Common duckweed) is useful as a plant model for the Bcc infectious process, and has potential as a model system for bacterial pathogenesis in general. To investigate the relationship between Bcc virulence in duckweed and Galleria mellonella (Greater wax moth) larvae, a previously established Bcc infection model, a duckweed survival assay was developed and used to determine LD50 values. A strong correlation (R(2) = 0.81) was found between the strains' virulence ranks in the two infection models, suggesting conserved pathways in these vastly different hosts. To broaden the application of the duckweed model, enteropathogenic Escherichia coli (EPEC) and five isogenic mutants with previously established LD50 values in the larval model were tested against duckweed, and a strong correlation (R(2) = 0.93) was found between their raw LD50 values. Potential virulence factors in B. cenocepacia K56-2 were identified using a high-throughput screen against single duckweed plants. In addition to the previously characterized antifungal compound (AFC) cluster genes, several uncharacterized genes were discovered including a novel lysR regulator, a histidine biosynthesis gene hisG, and a gene located near the gene encoding the recently characterized virulence factor SuhB(Bc). Finally, to demonstrate the utility of this model in therapeutic applications, duckweed was rescued from Bcc infection by treating with bacteriophage at 6-h intervals. It was observed that phage application became ineffective at a timepoint that coincided with a sharp increase in bacterial invasion of plant tissue. These results indicate that common duckweed can serve as an effective infection model for the investigation of bacterial virulence factors and therapeutic strategies to combat them.

Common Duckweed (Lemna minor) Is a Versatile High-Throughput Infection Model For the Burkholderia cepacia Complex and Other Pathogenic Bacteria

PubMed Central

Thomson, Euan L. S.; Dennis, Jonathan J.

2013-01-01

Members of the Burkholderia cepacia complex (Bcc) have emerged in recent decades as problematic pulmonary pathogens of cystic fibrosis (CF) patients, with severe infections progressing to acute necrotizing pneumonia and sepsis. This study presents evidence that Lemna minor (Common duckweed) is useful as a plant model for the Bcc infectious process, and has potential as a model system for bacterial pathogenesis in general. To investigate the relationship between Bcc virulence in duckweed and Galleria mellonella (Greater wax moth) larvae, a previously established Bcc infection model, a duckweed survival assay was developed and used to determine LD50 values. A strong correlation (R2 = 0.81) was found between the strains’ virulence ranks in the two infection models, suggesting conserved pathways in these vastly different hosts. To broaden the application of the duckweed model, enteropathogenic Escherichia coli (EPEC) and five isogenic mutants with previously established LD50 values in the larval model were tested against duckweed, and a strong correlation (R2 = 0.93) was found between their raw LD50 values. Potential virulence factors in B. cenocepacia K56-2 were identified using a high-throughput screen against single duckweed plants. In addition to the previously characterized antifungal compound (AFC) cluster genes, several uncharacterized genes were discovered including a novel lysR regulator, a histidine biosynthesis gene hisG, and a gene located near the gene encoding the recently characterized virulence factor SuhBBc. Finally, to demonstrate the utility of this model in therapeutic applications, duckweed was rescued from Bcc infection by treating with bacteriophage at 6-h intervals. It was observed that phage application became ineffective at a timepoint that coincided with a sharp increase in bacterial invasion of plant tissue. These results indicate that common duckweed can serve as an effective infection model for the investigation of bacterial virulence factors and therapeutic strategies to combat them. PMID:24223216

A New Perspective: The Common Factors Model as a Foundation for Social Work Practice Education

ERIC Educational Resources Information Center

Cameron, Mark; Keenan, Elizabeth King

2009-01-01

Foundation social work practice education is critical to the preparation of BSW practitioners for professional practice and the establishment of a theoretical and skill base upon which graduate students may build competencies in the advanced curriculum. Issues in the foundation practice curriculum may hinder this development. The common factors…

Arab-Levantine personality structure: A psycholexical study of modern standard Arabic in Lebanon, Syria, Jordan, and the West Bank.

PubMed

Zeinoun, Pia; Daouk-Öyry, Lina; Choueiri, Lina; van de Vijver, Fons J R

2018-06-01

The debate of whether personality traits are universal or culture-specific has been informed by psycholexical (or lexical) studies conducted in tens of languages and cultures. We contribute to this debate through a series of studies in which we investigated personality descriptors in Modern Standard Arabic, the variety of Arabic that is presumably common to about 26 countries and native to more than 200 million people. We identified an appropriate source of personality descriptors, extracted them, and systematically reduced them to 167 personality traits that are common, are not redundant with each other, and are familiar and commonly understood in Lebanon, Syria, Jordan, and the West Bank (Palestinian territories). We then analyzed self- and peer ratings (N = 806) and identified a six-factor solution comprising Morality (I), Conscientiousness (II), Positive Emotionality (III), Dominance (IV), Agreeableness/Righteousness (V), and Emotional Stability (VI) without replicating an Openness factor. The factors were narrower or broader variants of factors found in the Big Five and HEXACO models. Conceptual and methodological considerations may have impacted the factor structure. © 2017 Wiley Periodicals, Inc.

Broad Bandwidth or High Fidelity? Evidence from the Structure of Genetic and Environmental Effects on the Facets of the Five Factor Model

PubMed Central

Briley, Daniel A.; Tucker-Drob, Elliot M.

2017-01-01

The Five Factor Model (FFM) of personality is well-established at the phenotypic level, but much less is known about the coherence of the genetic and environmental influences within each personality domain. Univariate behavioral genetic analyses have consistently found the influence of additive genes and nonshared environment on multiple personality facets, but the extent to which genetic and environmental influences on specific facets reflect more general influences on higher order factors is less clear. We applied a multivariate quantitative-genetic approach to scores on the CPI-Big Five facets for 490 monozygotic and 317 dizygotic twins who took part in the National Merit Twin Study. Our results revealed a complex genetic structure for facets composing all five factors, with both domain-general and facet-specific genetic and environmental influences. Models that required common genetic and environmental influences on each facet to occur by way of effects on a higher order trait did not fit as well as models allowing for common genetic and environmental effects to act directly on the facets for three of the Big Five domains. These results add to the growing body of literature indicating that important variation in personality occurs at the facet level which may be overshadowed by aggregating to the trait level. Research at the facet level, rather than the factor level, is likely to have pragmatic advantages in future research on the genetics of personality. PMID:22695681

Low Impact of Traditional Risk Factors on Carotid Intima-Media Thickness: The ELSA-Brasil Cohort.

PubMed

Santos, Itamar S; Alencar, Airlane P; Rundek, Tatjana; Goulart, Alessandra C; Barreto, Sandhi M; Pereira, Alexandre C; Benseñor, Isabela M; Lotufo, Paulo A

2015-09-01

There is little information about how much traditional cardiovascular risk factors explain common carotid artery intima-media thickness (CCA-IMT) variance. We aimed to study to which extent CCA-IMT values are determined by traditional risk factors and which commonly used measurements of blood pressure, glucose metabolism, lipid profile, and adiposity contribute the most to this determination in the Brazilian Longitudinal Study of Adult Health (ELSA-Brasil) cohort baseline. We analyzed 9792 individuals with complete data and CCA-IMT measurements. We built multiple linear regression models using mean left and right CCA-IMT as the dependent variable. All models were stratified by sex. We also analyzed individuals stratified by 10-year coronary heart disease risk and, in separate, those with no traditional risk factors. Main models' R(2) varied between 0.141 and 0.373. The major part of the explained variance in CCA-IMT was because of age and race. Indicators of blood pressure, lipid profile, and adiposity that most frequently composed the best models were pulse pressure, low-density lipoprotein/high-density lipoprotein ratio, and neck circumference. The association between neck circumference and CCA-IMT persisted significant even after further adjustment for vessel sizes and body mass index. Indicators of glucose metabolism had smaller contribution. We found that >60% of CCA-IMT were not explained by demographic and traditional cardiovascular risk factors, which highlights the need to study novel risk factors. Pulse pressure, low-density lipoprotein/high-density lipoprotein ratio, and neck circumference were the most consistent contributors. © 2015 American Heart Association, Inc.

Determining Smoking Cessation Related Information, Motivation, and Behavioral Skills among Opiate Dependent Smokers in Methadone Treatment.

PubMed

Cooperman, Nina A; Richter, Kimber P; Bernstein, Steven L; Steinberg, Marc L; Williams, Jill M

2015-04-01

Over 80% of people in methadone treatment smoke cigarettes, and existing smoking cessation interventions have been minimally effective. To develop an Information-Motivation-Behavioral Skills (IMB) Model of behavior change based smoking cessation intervention for methadone maintained smokers, we examined smoking cessation related IMB factors in this population. Current or former smokers in methadone treatment (n = 35) participated in focus groups. Ten methadone clinic counselors participated in an individual interview. A content analysis was conducted using deductive and inductive approaches. Commonly known IMB factors related to smoking cessation were described. These factors included: the health effects of smoking and treatment options for quitting (information); pregnancy and cost of cigarettes (motivators); and coping with emotions, finding social support, and pharmacotherapy adherence (behavioral skills). IMB factors specific to methadone maintained smokers were also described. These factors included: the relationship between quitting smoking and drug relapse (information), the belief that smoking is the same as using drugs (motivator); and coping with methadone clinic culture and applying skills used to quit drugs to quitting smoking (behavioral skills). IMB strengths and deficits varied by individual. Methadone maintained smokers could benefit from research on an IMB Model based smoking cessation intervention that is individualized, addresses IMB factors common among all smokers, and also addresses IMB factors unique to this population.

Genetic and Environmental Influences on Female Sexual Orientation, Childhood Gender Typicality and Adult Gender Identity

PubMed Central

Burri, Andrea; Cherkas, Lynn; Spector, Timothy; Rahman, Qazi

2011-01-01

Background Human sexual orientation is influenced by genetic and non-shared environmental factors as are two important psychological correlates – childhood gender typicality (CGT) and adult gender identity (AGI). However, researchers have been unable to resolve the genetic and non-genetic components that contribute to the covariation between these traits, particularly in women. Methodology/Principal Findings Here we performed a multivariate genetic analysis in a large sample of British female twins (N = 4,426) who completed a questionnaire assessing sexual attraction, CGT and AGI. Univariate genetic models indicated modest genetic influences on sexual attraction (25%), AGI (11%) and CGT (31%). For the multivariate analyses, a common pathway model best fitted the data. Conclusions/Significance This indicated that a single latent variable influenced by a genetic component and common non-shared environmental component explained the association between the three traits but there was substantial measurement error. These findings highlight common developmental factors affecting differences in sexual orientation. PMID:21760939

Factor structure of the Wechsler Intelligence Scale for Children-Fifth Edition: Exploratory factor analyses with the 16 primary and secondary subtests.

PubMed

Canivez, Gary L; Watkins, Marley W; Dombrowski, Stefan C

2016-08-01

The factor structure of the 16 Primary and Secondary subtests of the Wechsler Intelligence Scale for Children-Fifth Edition (WISC-V; Wechsler, 2014a) standardization sample was examined with exploratory factor analytic methods (EFA) not included in the WISC-V Technical and Interpretive Manual (Wechsler, 2014b). Factor extraction criteria suggested 1 to 4 factors and results favored 4 first-order factors. When this structure was transformed with the Schmid and Leiman (1957) orthogonalization procedure, the hierarchical g-factor accounted for large portions of total and common variance while the 4 first-order factors accounted for small portions of total and common variance; rendering interpretation at the factor index level less appropriate. Although the publisher favored a 5-factor model where the Perceptual Reasoning factor was split into separate Visual Spatial and Fluid Reasoning dimensions, no evidence for 5 factors was found. It was concluded that the WISC-V provides strong measurement of general intelligence and clinical interpretation should be primarily, if not exclusively, at that level. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

Modeling and Forecasting Mortality With Economic Growth: A Multipopulation Approach.

PubMed

Boonen, Tim J; Li, Hong

2017-10-01

Research on mortality modeling of multiple populations focuses mainly on extrapolating past mortality trends and summarizing these trends by one or more common latent factors. This article proposes a multipopulation stochastic mortality model that uses the explanatory power of economic growth. In particular, we extend the Li and Lee model (Li and Lee 2005) by including economic growth, represented by the real gross domestic product (GDP) per capita, to capture the common mortality trend for a group of populations with similar socioeconomic conditions. We find that our proposed model provides a better in-sample fit and an out-of-sample forecast performance. Moreover, it generates lower (higher) forecasted period life expectancy for countries with high (low) GDP per capita than the Li and Lee model.

Vitamin D insufficiency and subclinical atherosclerosis in non-diabetic males living with HIV.

PubMed

Portilla, Joaquín; Moreno-Pérez, Oscar; Serna-Candel, Carmen; Escoín, Corina; Alfayate, Rocio; Reus, Sergio; Merino, Esperanza; Boix, Vicente; Giner, Livia; Sánchez-Payá, José; Picó, Antonio

2014-01-01

Vitamin D insufficiency (VDI) has been associated with increased cardiovascular risk in the non-HIV population. This study evaluates the relationship among serum 25-hydroxyvitamin D [25(OH)D] levels, cardiovascular risk factors, adipokines, antiviral therapy (ART) and subclinical atherosclerosis in HIV-infected males. A cross-sectional study in ambulatory care was made in non-diabetic patients living with HIV. VDI was defined as 25(OH)D serum levels <75 nmol/L. Fasting lipids, glucose, inflammatory markers (tumour necrosis factor-α, interleukin-6, high-sensitivity C-reactive protein) and endothelial markers (plasminogen activator inhibitor-1, or PAI-I) were measured. The common carotid artery intima-media thickness (C-IMT) was determined. A multivariate logistic regression analysis was made to identify factors associated with the presence of VDI, while multivariate linear regression analysis was used to identify factors associated with common C-IMT. Eighty-nine patients were included (age 42 ± 8 years), 18.9% were in CDC (US Centers for Disease Control and Prevention) stage C and 75 were on ART. VDI was associated with ART exposure, sedentary lifestyle, higher triglycerides levels and PAI-I. In univariate analysis, VDI was associated with greater common C-IMT. The multivariate linear regression model, adjusted by confounding factors, revealed an independent association between common C-IMT and patient age, time of exposure to protease inhibitors (PIs) and impaired fasting glucose (IFG). In contrast, there were no independent associations between common C-IMT and VDI or inflammatory and endothelial markers. VDI was not independently associated with subclinical atherosclerosis in non-diabetic males living with HIV. Older age, a longer exposure to PIs, and IFG were independent factors associated with common C-IMT in this population.

Community Epidemiology of Risk and Adolescent Substance Use: Practical Questions for Enhancing Prevention

PubMed Central

2012-01-01

To promote an effective approach to prevention, the community diagnosis model helps communities systematically assess and prioritize risk factors to guide the selection of preventive interventions. This increasingly widely used model relies primarily on individual-level research that links risk and protective factors to substance use outcomes. I discuss common assumptions in the translation of such research concerning the definition of risk factor elevation; the equivalence, independence, and stability of relations between risk factors and problem behaviors; and community differences in risk factors and risk factor–problem behavior relations. Exploring these assumptions could improve understanding of the relations of risk factors and substance use within and across communities and enhance the efficacy of the community diagnosis model. This approach can also be applied to other areas of public health where individual and community levels of risk and outcomes intersect. PMID:22390508

The factor structure of the 12-item general health questionnaire (GHQ-12) in young Chinese civil servants.

PubMed

Liang, Ying; Wang, Lei; Yin, Xican

2016-09-26

The 12-item General Health Questionnaire (GHQ-12) is a commonly used screening instrument for measuring mental disorders. However, few studies have measured the mental health of Chinese professionals or explored the factor structure of the GHQ-12 through investigations of young Chinese civil servants. This study analyses the factor structure of the GHQ-12 on young Chinese civil servants. Respondents include 1051 participants from six cities in eastern China. Exploratory Factor Analysis (EFA) is used to identify the potential factor structure of the GHQ-12. Confirmatory Factor Analysis (CFA) models of previous studies are referred to for model fitting. The results indicate the GHQ-12 has very good reliability and validity. All ten CFA models are well fitted with the actual data. All the ten models are feasible and fit the data equally well. The Chinese version of the GHQ-12 is suitable for professional groups and can serve as a screening tool to detect anxiety and psychiatric disorders.

Collegial Support and Community with Trust in Swedish and Danish dentistry.

PubMed

Berthelsen, Hanne; Söderfeldt, Björn; Harris, Rebecca; Pejtersen, Jan Hyld; Bergström, Kamilla; Hjalmers, Karin; Ordell, Sven

2011-11-01

The aim of the study was to better understand the associations between work factors and professional support among dentists (Collegial Support) as well as the sense of being part of a work community characterized by trust (Community with Trust). A questionnaire was sent to 1835 general dental practitioners, randomly selected from the members of dental associations in Sweden and Denmark in 2008. The response rate was 68%. Two models with the outcome variables Collegial Support and being part of a Community with Trust were built using multiple hierarchical linear regression. Demographic background factors, work factors, managerial factors and factors relating to objectives and to values characterizing climate of the practice were all introduced as blocks into the models. A different pattern emerged for Collegial Support than for Community with Trust, indicating different underlying mechanisms. The main results were: (I) Female, married/cohabitant, collegial network outside the practice, common breaks, formalized managerial education of leader and a climate characterized by professional values, which were positively associated with Collegial Support, while number of years as a dentist and being managerially responsible were negatively associated. (II) Common breaks, decision authority and a climate characterized by professional values were positively associated with Community with Trust. A professionally-oriented practice climate and having common breaks at work were strongly associated with both outcome variables. The study underlined the importance of managing dentistry in a way which respects the professional ethos of dentists.

HIGH DIMENSIONAL COVARIANCE MATRIX ESTIMATION IN APPROXIMATE FACTOR MODELS.

PubMed

Fan, Jianqing; Liao, Yuan; Mincheva, Martina

2011-01-01

The variance covariance matrix plays a central role in the inferential theories of high dimensional factor models in finance and economics. Popular regularization methods of directly exploiting sparsity are not directly applicable to many financial problems. Classical methods of estimating the covariance matrices are based on the strict factor models, assuming independent idiosyncratic components. This assumption, however, is restrictive in practical applications. By assuming sparse error covariance matrix, we allow the presence of the cross-sectional correlation even after taking out common factors, and it enables us to combine the merits of both methods. We estimate the sparse covariance using the adaptive thresholding technique as in Cai and Liu (2011), taking into account the fact that direct observations of the idiosyncratic components are unavailable. The impact of high dimensionality on the covariance matrix estimation based on the factor structure is then studied.

Monte Carlo simulations of the gamma-ray exposure rates of common rocks

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

Haber, Daniel A.; Malchow, Russell L.; Burnley, Pamela C.

Monte Carlo simulations have been performed to model the gamma ray emission and attenuation properties of common rocks. In geologic materials, 40K, 238U, and 232Th are responsible for most gamma ray production. If the concentration of these radioelements and attenuation factors such as degree of water saturation are known, an estimate of the gamma-ray exposure rate can be made. The results show that there are no significant differences in gamma-ray screening between major rock types. If the total number of radionuclide atoms are held constant then the major controlling factor is density of the rock. Finally, the thickness of regolithmore » or soil overlying rock can be estimated by modeling the exposure rate if the radionuclide contents of both materials are known.« less

Monte Carlo simulations of the gamma-ray exposure rates of common rocks

DOE PAGES

Haber, Daniel A.; Malchow, Russell L.; Burnley, Pamela C.

2016-11-24

Monte Carlo simulations have been performed to model the gamma ray emission and attenuation properties of common rocks. In geologic materials, 40K, 238U, and 232Th are responsible for most gamma ray production. If the concentration of these radioelements and attenuation factors such as degree of water saturation are known, an estimate of the gamma-ray exposure rate can be made. The results show that there are no significant differences in gamma-ray screening between major rock types. If the total number of radionuclide atoms are held constant then the major controlling factor is density of the rock. Lastly, the thickness of regolithmore » or soil overlying rock can be estimated by modeling the exposure rate if the radionuclide contents of both materials are known.« less

Monte Carlo simulations of the gamma-ray exposure rates of common rocks

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

Haber, Daniel A.; Malchow, Russell L.; Burnley, Pamela C.

Monte Carlo simulations have been performed to model the gamma ray emission and attenuation properties of common rocks. In geologic materials, 40K, 238U, and 232Th are responsible for most gamma ray production. If the concentration of these radioelements and attenuation factors such as degree of water saturation are known, an estimate of the gamma-ray exposure rate can be made. The results show that there are no significant differences in gamma-ray screening between major rock types. If the total number of radionuclide atoms are held constant then the major controlling factor is density of the rock. Lastly, the thickness of regolithmore » or soil overlying rock can be estimated by modeling the exposure rate if the radionuclide contents of both materials are known.« less

A Model for Predicting Integrated Man-Machine System Reliability: Model Logic and Description

DTIC Science & Technology

1974-11-01

3. Fatigue buildup curve. The common requirement of all tests on the Dynamic Strength factor is for the muscles involved to propel, support, or...move the body repeatedly or to support it continuously over time. The tests of our Static Strength factor emphasize the lifting power of the muscles ...or the pounds of pressure which the muscles can exert. ... In contrast to Dynamic Strength the force exerted is against external objects, rather

Evaluating the Factor Validity of the Children's Organizational Skills Scale in Youth with ADHD.

PubMed

Molitor, Stephen J; Langberg, Joshua M; Evans, Steven W; Dvorsky, Melissa R; Bourchtein, Elizaveta; Eddy, Laura D; Smith, Zoe R; Oddo, Lauren E

2017-06-01

Children and adolescents with ADHD often have difficulties with organization, time management, and planning (OTMP) skills, and these skills are a common target of intervention. A limited array of tools for measuring these abilities in youth is available, and one of the most prominent measures is the Children's Organizational Skills Scale (COSS). Although the COSS fills an important need, a replication of the COSS factor structure outside of initial measure development has not been conducted in any population. Given that the COSS is frequently used in ADHD research, the current study evaluated the factor structure of the parent-rated COSS in a sample ( N = 619) of adolescents with ADHD. Results indicated that the original factor structure could be replicated, although the use of item parcels appeared to affect model fit statistics. An alternative bi-factor model was also tested that did not require the use of parcels, with results suggesting similar model fit in comparison to the original factor structure. Exploratory validity tests indicated that the domain-general factor of the bi-factor model appears related to broad executive functioning abilities.

Carotid artery intima-media complex thickening in patients with relatively long-surviving type 1 diabetes mellitus.

PubMed

Distiller, Larry A; Joffe, Barry I; Melville, Vanessa; Welman, Tania; Distiller, Greg B

2006-01-01

The factors responsible for premature coronary atherosclerosis in patients with type 1 diabetes are ill defined. We therefore assessed carotid intima-media complex thickness (IMT) in relatively long-surviving patients with type 1 diabetes as a marker of atherosclerosis and correlated this with traditional risk factors. Cross-sectional study of 148 patients with relatively long-surviving (>18 years) type 1 diabetes (76 men and 72 women) attending the Centre for Diabetes and Endocrinology, Johannesburg. The mean common carotid artery IMT and presence or absence of plaque was evaluated by high-resolution B-mode ultrasound. Their median age was 48 years and duration of diabetes 26 years (range 18-59 years). Traditional risk factors (age, duration of diabetes, glycemic control, hypertension, smoking and lipoprotein concentrations) were recorded. Three response variables were defined and modeled. Standard multiple regression was used for a continuous IMT variable, logistic regression for the presence/absence of plaque and ordinal logistic regression to model three categories of "risk." The median common carotid IMT was 0.62 mm (range 0.44-1.23 mm) with plaque detected in 28 cases. The multiple regression model found significant associations between IMT and current age (P=.001), duration of diabetes (P=.033), BMI (P=.008) and diagnosed hypertension (P=.046) with HDL showing a protective effect (P=.022). Current age (P=.001) and diagnosed hypertension (P=.004), smoking (P=.008) and retinopathy (P=.033) were significant in the logistic regression model. Current age was also significant in the ordinal logistic regression model (P<.001), as was total cholesterol/HDL ratio (P<.001) and mean HbA(1c) concentration (P=.073). The major factors influencing common carotid IMT in patients with relatively long-surviving type 1 diabetes are age, duration of diabetes, existing hypertension and HDL (protective) with a relatively minor role ascribed to relatively long-standing glycemic control.

Stress Intensity Factors for Cracking Metal Structures under Rapid Thermal Loading. Volume 2. Theoretical Background

DTIC Science & Technology

1989-08-01

thermal pulse loadings. The work couples a Green’s function integration technique for transient thermal stresses with the well-known influence ... function approach for calculating stress intensity factors. A total of seven most commonly used crack models were investigated in this study. A computer

The Adolescent Substance Use Risk Continuum: A Cultural, Strengths-Based Approach to Case Conceptualization

ERIC Educational Resources Information Center

Miller, Alexis; Cook, Jennifer M.

2017-01-01

Many theories are used to conceptualize adolescent substance use, yet none adequately assist mental health professionals in assessing adolescents' strengths and risk factors while incorporating cultural factors. The authors reviewed common adolescent substance abuse theories and their strengths and limitations, and offer a new model to…

A Class of Factor Analysis Estimation Procedures with Common Asymptotic Sampling Properties

ERIC Educational Resources Information Center

Swain, A. J.

1975-01-01

Considers a class of estimation procedures for the factor model. The procedures are shown to yield estimates possessing the same asymptotic sampling properties as those from estimation by maximum likelihood or generalized last squares, both special members of the class. General expressions for the derivatives needed for Newton-Raphson…

Structure of Preschool Phonological Sensitivity: Overlapping Sensitivity to Rhyme, Words, Syllables, and Phonemes.

ERIC Educational Resources Information Center

Anthony, Jason L.; Lonigan, Christopher J.; Burgess, Stephen R.; Driscoll, Kimberly; Phillips, Beth M.; Cantor, Brenlee G.

2002-01-01

This study examined relations among sensitivity to words, syllables, rhymes, and phonemes in older and younger preschoolers. Confirmatory factor analyses found that a one-factor model best explained the date from both groups of children. Only variance common to all phonological sensitivity skills was related to print knowledge and rudimentary…

Reliability of Summed Item Scores Using Structural Equation Modeling: An Alternative to Coefficient Alpha

ERIC Educational Resources Information Center

Green, Samuel B.; Yang, Yanyun

2009-01-01

A method is presented for estimating reliability using structural equation modeling (SEM) that allows for nonlinearity between factors and item scores. Assuming the focus is on consistency of summed item scores, this method for estimating reliability is preferred to those based on linear SEM models and to the most commonly reported estimate of…

Systems Impact: Issues and Trends in Improving School Outcomes for All Learners through Multitier Instructional Models

ERIC Educational Resources Information Center

Chard, David J.

2013-01-01

The majority of school districts implementing response to intervention use a systemwide, multitier model of delivery. This article describes the common features of multitier models and discusses the emerging evidence of their effectiveness. In addition, specific factors that schools should consider to enhance effective implementation of systemic,…

Curve of Factors Model: A Latent Growth Modeling Approach for Educational Research

ERIC Educational Resources Information Center

Isiordia, Marilu; Ferrer, Emilio

2018-01-01

A first-order latent growth model assesses change in an unobserved construct from a single score and is commonly used across different domains of educational research. However, examining change using a set of multiple response scores (e.g., scale items) affords researchers several methodological benefits not possible when using a single score. A…

The Abuse Intervention Model: A Pragmatic Approach to Intervention for Elder Mistreatment.

PubMed

Mosqueda, Laura; Burnight, Kerry; Gironda, Melanie W; Moore, Alison A; Robinson, Jehni; Olsen, Bonnie

2016-09-01

Ten percent of older adults experience elder mistreatment, and it is much more common in older adults with dementia. It is associated with higher rates of psychological distress, hospitalization, and death and, in the United States, costs billions of dollars each year. Although elder mistreatment is relatively common and costly, it is estimated that fewer than 10% of instances of elder mistreatment are reported. Given these data, there is a great need for research on interventions to mitigate elder mistreatment and for a practical model or framework to use in approaching such interventions. Although many theories have been proposed, adapted, and applied to understand elder mistreatment, there has not been a simple, coherent framework of known risk factors of the victim, perpetrator, and environment that applies to all types of abuse. This article presents a new model to examine the multidimensional and complex relationships between risk factors. Theories of elder mistreatment, research on risk factors for elder mistreatment, and 10 years of experience of faculty and staff at an Elder Abuse Forensics Center who have investigated more than 1,000 cases of elder mistreatment inform this model. It is hoped that this model, the Abuse Intervention Model, will be used to study and intervene in elder mistreatment. © 2016, Copyright the Authors Journal compilation © 2016, The American Geriatrics Society.

Calculating the nutrient composition of recipes with computers.

PubMed

Powers, P M; Hoover, L W

1989-02-01

The objective of this research project was to compare the nutrient values computed by four commonly used computerized recipe calculation methods. The four methods compared were the yield factor, retention factor, summing, and simplified retention factor methods. Two versions of the summing method were modeled. Four pork entrée recipes were selected for analysis: roast pork, pork and noodle casserole, pan-broiled pork chops, and pork chops with vegetables. Assumptions were made about changes expected to occur in the ingredients during preparation and cooking. Models were designed to simulate the algorithms of the calculation methods using a microcomputer spreadsheet software package. Identical results were generated in the yield factor, retention factor, and summing-cooked models for roast pork. The retention factor and summing-cooked models also produced identical results for the recipe for pan-broiled pork chops. The summing-raw model gave the highest value for water in all four recipes and the lowest values for most of the other nutrients. A superior method or methods was not identified. However, on the basis of the capabilities provided with the yield factor and retention factor methods, more serious consideration of these two methods is recommended.

Effects of spatial disturbance on common loon nest site selection and territory success

USGS Publications Warehouse

McCarthy, K.P.; DeStefano, S.

2011-01-01

The common loon (Gavia immer) breeds during the summer on northern lakes and water bodies that are also often desirable areas for aquatic recreation and human habitation. In northern New England, we assessed how the spatial nature of disturbance affects common loon nest site selection and territory success. We found through classification and regression analysis that distance to and density of disturbance factors can be used to classify observed nest site locations versus random points, suggesting that these factors affect loon nest site selection (model 1: Correct classification = 75%, null = 50%, K = 0.507, P < 0.001; model 2: Correct classification = 78%, null = 50%, K = 0.551, P < 0.001). However, in an exploratory analysis, we were unable to show a relation between spatial disturbance variables and breeding success (P = 0.595, R 2 = 0.436), possibly because breeding success was so low during the breeding seasons of 2007-2008. We suggest that by selecting nest site locations that avoid disturbance factors, loons thereby limit the effect that disturbance will have on their breeding success. Still, disturbance may force loons to use sub-optimal nesting habitat, limiting the available number of territories, and overall productivity. We advise that management efforts focus on limiting disturbance factors to allow breeding pairs access to the best nesting territories, relieving disturbance pressures that may force sub-optimal nest placement. ?? 2011 The Wildlife Society.

Schizophrenia and Depression Co-Morbidity: What We have Learned from Animal Models

PubMed Central

Samsom, James N.; Wong, Albert H. C.

2015-01-01

Patients with schizophrenia are at an increased risk for the development of depression. Overlap in the symptoms and genetic risk factors between the two disorders suggests a common etiological mechanism may underlie the presentation of comorbid depression in schizophrenia. Understanding these shared mechanisms will be important in informing the development of new treatments. Rodent models are powerful tools for understanding gene function as it relates to behavior. Examining rodent models relevant to both schizophrenia and depression reveals a number of common mechanisms. Current models which demonstrate endophenotypes of both schizophrenia and depression are reviewed here, including models of CUB and SUSHI multiple domains 1, PDZ and LIM domain 5, glutamate Delta 1 receptor, diabetic db/db mice, neuropeptide Y, disrupted in schizophrenia 1, and its interacting partners, reelin, maternal immune activation, and social isolation. Neurotransmission, brain connectivity, the immune system, the environment, and metabolism emerge as potential common mechanisms linking these models and potentially explaining comorbid depression in schizophrenia. PMID:25762938

Three-and-a-half-factor model? The genetic and environmental structure of the CBCL/6-18 internalizing grouping.

PubMed

Franić, Sanja; Dolan, Conor V; Borsboom, Denny; van Beijsterveldt, Catherina E M; Boomsma, Dorret I

2014-05-01

In the present article, multivariate genetic item analyses were employed to address questions regarding the ontology and the genetic and environmental etiology of the Anxious/Depressed, Withdrawn, and Somatic Complaints syndrome dimensions of the Internalizing grouping of the Child Behavior Checklist/6-18 (CBCL/6-18). Using common and independent pathway genetic factor modeling, it was examined whether these syndrome dimensions can be ascribed a realist ontology. Subsequently, the structures of the genetic and environmental influences giving rise to the observed symptom covariation were examined. Maternal ratings of a population-based sample of 17,511 Dutch twins of mean age 7.4 (SD = 0.4) on the items of the Internalizing grouping of the Dutch CBCL/6-18 were analyzed. Applications of common and independent pathway modeling demonstrated that the Internalizing syndrome dimensions may be better understood as a composite of unconstrained genetic and environmental influences than as causally relevant entities generating the observed symptom covariation. Furthermore, the results indicate a common genetic basis for anxiety, depression, and withdrawn behavior, with the distinction between these syndromes being driven by the individual-specific environment. Implications for the substantive interpretation of these syndrome dimensions are discussed.

Transfer Factors for Contaminant Uptake by Fruit and Nut Trees

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

Napier, Bruce A.; Fellows, Robert J.; Minc, Leah D.

Transfer of radionuclides from soils into plants is one of the key mechanisms for long-term contamination of the human food chain. Nearly all computer models that address soil-to-plant uptake of radionuclides use empirically-derived transfer factors to address this process. Essentially all available soil-to-plant transfer factors are based on measurements in annual crops. Because very few measurements are available for tree fruits, samples were taken of alfalfa and oats and the stems, leaves, and fruits and nuts of almond, apple, apricot, carob, fig, grape, nectarine, pecan, pistachio (natural and grafted), and pomegranate, along with local surface soil. The samples were dried,more » ground, weighed, and analyzed for trace constituents through a combination of induction-coupled plasma mass spectrometry and instrumental neutron activation analysis for a wide range of naturally-occurring elements. Analysis results are presented and converted to soil-to-plant transfer factors. These are compared to commonly used and internationally recommended values. Those determined for annual crops are very similar to commonly-used values; those determined for tree fruits show interesting differences. Most macro- and micronutrients are slightly reduced in fruits; non-essential elements are reduced further. These findings may be used in existing computer models and may allow development of tree-fruit-specific transfer models.« less

Groundwater salinity in a floodplain forest impacted by saltwater intrusion

NASA Astrophysics Data System (ADS)

Kaplan, David A.; Muñoz-Carpena, Rafael

2014-11-01

Coastal wetlands occupy a delicate position at the intersection of fresh and saline waters. Changing climate and watershed hydrology can lead to saltwater intrusion into historically freshwater systems, causing plant mortality and loss of freshwater habitat. Understanding the hydrological functioning of tidally influenced floodplain forests is essential for advancing ecosystem protection and restoration goals, however finding direct relationships between hydrological inputs and floodplain hydrology is complicated by interactions between surface water, groundwater, and atmospheric fluxes in variably saturated soils with heterogeneous vegetation and topography. Thus, an alternative method for identifying common trends and causal factors is required. Dynamic factor analysis (DFA), a time series dimension reduction technique, models temporal variation in observed data as linear combinations of common trends, which represent unexplained common variability, and explanatory variables. DFA was applied to model shallow groundwater salinity in the forested floodplain wetlands of the Loxahatchee River (Florida, USA), where altered watershed hydrology has led to changing hydroperiod and salinity regimes and undesired vegetative changes. Long-term, high-resolution groundwater salinity datasets revealed dynamics over seasonal and yearly time periods as well as over tidal cycles and storm events. DFA identified shared trends among salinity time series and a full dynamic factor model simulated observed series well (overall coefficient of efficiency, Ceff = 0.85; 0.52 ≤ Ceff ≤ 0.99). A reduced multilinear model based solely on explanatory variables identified in the DFA had fair to good results (Ceff = 0.58; 0.38 ≤ Ceff ≤ 0.75) and may be used to assess the effects of restoration and management scenarios on shallow groundwater salinity in the Loxahatchee River floodplain.

Formative Constructs Implemented via Common Factors

ERIC Educational Resources Information Center

Treiblmaier, Horst; Bentler, Peter M.; Mair, Patrick

2011-01-01

Recently there has been a renewed interest in formative measurement and its role in properly specified models. Formative measurement models are difficult to identify, and hence to estimate and test. Existing solutions to the identification problem are shown to not adequately represent the formative constructs of interest. We propose a new two-step…

A CONCEPTUAL MODEL FOR EVALUATING RELATIVE POTENCY DATA FOR USE IN ECOLOGICAL RISK ASSESSMENTS

EPA Science Inventory

For chemicals with a common mechanism of toxicity, relative potency factors (RPFs) allow dose and exposure measures to be normalized to an equivalent toxicity amount of a model chemical... In ecological risk assessments the large number of possible target species, variety of expo...

Premature atherosclerosis in pediatric systemic lupus erythematosus: risk factors for increased carotid intima-media thickness in the atherosclerosis prevention in pediatric lupus erythematosus cohort.

PubMed

Schanberg, Laura E; Sandborg, Christy; Barnhart, Huiman X; Ardoin, Stacy P; Yow, Eric; Evans, Gregory W; Mieszkalski, Kelly L; Ilowite, Norman T; Eberhard, Anne; Levy, Deborah M; Kimura, Yukiko; von Scheven, Emily; Silverman, Earl; Bowyer, Suzanne L; Punaro, Lynn; Singer, Nora G; Sherry, David D; McCurdy, Deborah; Klein-Gitelman, Marissa; Wallace, Carol; Silver, Richard; Wagner-Weiner, Linda; Higgins, Gloria C; Brunner, Hermine I; Jung, Lawrence; Soep, Jennifer B; Reed, Ann

2009-05-01

To evaluate risk factors for subclinical atherosclerosis in a population of patients with pediatric systemic lupus erythematosus (SLE). In a prospective multicenter study, a cohort of 221 patients underwent baseline measurements of carotid intima-media thickness (CIMT) as part of the Atherosclerosis Prevention in Pediatric Lupus Erythematosus (APPLE) trial. SLE disease measures, medications, and traditional risk factors for atherosclerosis were assessed. A standardized protocol was used to assess the thickness of the bilateral common carotid arteries and the mean maximal IMT of 12 segments. Univariable analysis identified potential associations with CIMT, which were examined in multivariable linear regression modeling. Based on the mean-mean common or the mean-max CIMT as the dependent variable, univariable analysis showed significant associations of the following variables with increased CIMT: increasing age, longer SLE duration, minority status, higher body mass index (BMI), male sex, increased creatinine clearance, higher lipoprotein(a) level, proteinuria, azathioprine treatment, and prednisone dose. In multivariable modeling, both azathioprine use (P=0.005 for the mean-mean model and P=0.102 for the mean-max model) and male sex (P<0.001) were associated with increases in the mean-max CIMT. A moderate dosage of prednisone (0.15-0.4 mg/kg/day) was associated with decreases in the mean-max CIMT (P=0.024), while high-dose and low-dose prednisone were associated with increases in the mean-mean common CIMT (P=0.021) and the mean-max CIMT (P=0.064), respectively. BMI (P<0.001) and creatinine clearance (P=0.031) remained associated with increased mean-mean common CIMT, while increasing age (P<0.001) and increasing lipoprotein(a) level (P=0.005) were associated with increased mean-max CIMT. Traditional as well as nontraditional risk factors were associated with increased CIMT in this cohort of patients in the APPLE trial. Azathioprine treatment was associated with increased CIMT. The relationship between CIMT and prednisone dose may not be linear.

Similarity Assessment of Land Surface Model Outputs in the North American Land Data Assimilation System

NASA Astrophysics Data System (ADS)

Kumar, Sujay V.; Wang, Shugong; Mocko, David M.; Peters-Lidard, Christa D.; Xia, Youlong

2017-11-01

Multimodel ensembles are often used to produce ensemble mean estimates that tend to have increased simulation skill over any individual model output. If multimodel outputs are too similar, an individual LSM would add little additional information to the multimodel ensemble, whereas if the models are too dissimilar, it may be indicative of systematic errors in their formulations or configurations. The article presents a formal similarity assessment of the North American Land Data Assimilation System (NLDAS) multimodel ensemble outputs to assess their utility to the ensemble, using a confirmatory factor analysis. Outputs from four NLDAS Phase 2 models currently running in operations at NOAA/NCEP and four new/upgraded models that are under consideration for the next phase of NLDAS are employed in this study. The results show that the runoff estimates from the LSMs were most dissimilar whereas the models showed greater similarity for root zone soil moisture, snow water equivalent, and terrestrial water storage. Generally, the NLDAS operational models showed weaker association with the common factor of the ensemble and the newer versions of the LSMs showed stronger association with the common factor, with the model similarity increasing at longer time scales. Trade-offs between the similarity metrics and accuracy measures indicated that the NLDAS operational models demonstrate a larger span in the similarity-accuracy space compared to the new LSMs. The results of the article indicate that simultaneous consideration of model similarity and accuracy at the relevant time scales is necessary in the development of multimodel ensemble.

Cognitive Abilities Explain Wording Effects in the Rosenberg Self-Esteem Scale.

PubMed

Gnambs, Timo; Schroeders, Ulrich

2017-12-01

There is consensus that the 10 items of the Rosenberg Self-Esteem Scale (RSES) reflect wording effects resulting from positively and negatively keyed items. The present study examined the effects of cognitive abilities on the factor structure of the RSES with a novel, nonparametric latent variable technique called local structural equation models. In a nationally representative German large-scale assessment including 12,437 students competing measurement models for the RSES were compared: a bifactor model with a common factor and a specific factor for all negatively worded items had an optimal fit. Local structural equation models showed that the unidimensionality of the scale increased with higher levels of reading competence and reasoning, while the proportion of variance attributed to the negatively keyed items declined. Wording effects on the factor structure of the RSES seem to represent a response style artifact associated with cognitive abilities.

Geospatial Analysis Tool Kit for Regional Climate Datasets (GATOR) : An Open-source Tool to Compute Climate Statistic GIS Layers from Argonne Climate Modeling Results

DTIC Science & Technology

2017-08-01

This large repository of climate model results for North America (Wang and Kotamarthi 2013, 2014, 2015) is stored in Network Common Data Form (NetCDF...Network Common Data Form (NetCDF). UCAR/Unidata Program Center, Boulder, CO. Available at: http://www.unidata.ucar.edu/software/netcdf. Accessed on 6/20...emissions diverge from each other regarding fossil fuel use, technology, and other socioeconomic factors. As a result, the estimated emissions for each of

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

Michel, D. T.; Maximov, A. V.; Short, R. W.

The fraction of laser energy converted into hot electrons by the two-plasmon-decay instability is found to have different overlapped intensity thresholds for various configurations on the Omega Laser Facility [T. R. Boehly et al., Opt. Commun. 133, 495 (1997); J. H. Kelly et al., J. Phys. IV 133, 75 (2006)]. A factor-of-2 difference in the overlapped intensity threshold is observed between two- and four-beam configurations. The overlapped intensity threshold increases by a factor of 2 between the 4- and 18-beam configurations and by a factor of 3 between the 4- and 60-beam configurations. This is explained by a linear common-wavemore » model where multiple laser beams drive a common electron-plasma wave in a wavevector region that bisects the laser beams (resonant common-wave region in k-space). These experimental results indicate that the hot-electron threshold depends on the hydrodynamic parameters at the quarter-critical density surface, the configuration of the laser beams, and the sum of the intensity of the beams that share the same angle with the common-wave vector.« less

Minimum-complexity helicopter simulation math model

NASA Technical Reports Server (NTRS)

Heffley, Robert K.; Mnich, Marc A.

1988-01-01

An example of a minimal complexity simulation helicopter math model is presented. Motivating factors are the computational delays, cost, and inflexibility of the very sophisticated math models now in common use. A helicopter model form is given which addresses each of these factors and provides better engineering understanding of the specific handling qualities features which are apparent to the simulator pilot. The technical approach begins with specification of features which are to be modeled, followed by a build up of individual vehicle components and definition of equations. Model matching and estimation procedures are given which enable the modeling of specific helicopters from basic data sources such as flight manuals. Checkout procedures are given which provide for total model validation. A number of possible model extensions and refinement are discussed. Math model computer programs are defined and listed.

Agent based models for wealth distribution with preference in interaction

NASA Astrophysics Data System (ADS)

Goswami, Sanchari; Sen, Parongama

2014-12-01

We propose a set of conservative models in which agents exchange wealth with a preference in the choice of interacting agents in different ways. The common feature in all the models is that the temporary values of financial status of agents is a deciding factor for interaction. Other factors which may play important role are past interactions and wealth possessed by individuals. Wealth distribution, network properties and activity are the main quantities which have been studied. Evidence of phase transitions and other interesting features are presented. The results show that certain observations of the real economic system can be reproduced by the models.

HIGH DIMENSIONAL COVARIANCE MATRIX ESTIMATION IN APPROXIMATE FACTOR MODELS

PubMed Central

Fan, Jianqing; Liao, Yuan; Mincheva, Martina

2012-01-01

The variance covariance matrix plays a central role in the inferential theories of high dimensional factor models in finance and economics. Popular regularization methods of directly exploiting sparsity are not directly applicable to many financial problems. Classical methods of estimating the covariance matrices are based on the strict factor models, assuming independent idiosyncratic components. This assumption, however, is restrictive in practical applications. By assuming sparse error covariance matrix, we allow the presence of the cross-sectional correlation even after taking out common factors, and it enables us to combine the merits of both methods. We estimate the sparse covariance using the adaptive thresholding technique as in Cai and Liu (2011), taking into account the fact that direct observations of the idiosyncratic components are unavailable. The impact of high dimensionality on the covariance matrix estimation based on the factor structure is then studied. PMID:22661790

Neglect the Structure of Multitrait-Multimethod Data at Your Peril: Implications for Associations with External Variables

ERIC Educational Resources Information Center

Castro-Schilo, Laura; Widaman, Keith F.; Grimm, Kevin J.

2013-01-01

In 1959, Campbell and Fiske introduced the use of multitrait-multimethod (MTMM) matrices in psychology, and for the past 4 decades confirmatory factor analysis (CFA) has commonly been used to analyze MTMM data. However, researchers do not always fit CFA models when MTMM data are available; when CFA modeling is used, multiple models are available…

Increased susceptibility to atrial fibrillation secondary to atrial fibrosis in transgenic goats expressing transforming growth factor - B1

USDA-ARS?s Scientific Manuscript database

Atrial fibrillation (AF) is the most common sustained cardiac arrhythmia in people with significant morbidity and mortality. There is a strong association between atrial fibrosis and AF. Transforming growth factor B1 (TGF-B1) is an essential mediator of atrial fibrosis in animal models and human pat...

Improved methods for the measurement and modeling of PV module and system performance for all operating conditions

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

King, D.L.

1995-11-01

The objective of this work was to develop improved performance model for modules and systems for for all operating conditions for use in module specifications, system and BOS component design, and system rating or monitoring. The approach taken was to identify and quantify the influence of dominant factors of solar irradiance, cell temperature, angle-of-incidence; and solar spectrum; use outdoor test procedures to separate the effects of electrical, thermal, and optical performance; use fundamental cell characteristics to improve analysis; and combine factors in simple model using the common variables.

Surface structural ion adsorption modeling of competitive binding of oxyanions by metal (hydr)oxides

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

Hiemstra, T.; Riemsdijk, W.H. van

1999-02-01

An important challenge in surface complexation models (SCM) is to connect the molecular microscopic reality to macroscopic adsorption phenomena. This study elucidates the primary factor controlling the adsorption process by analyzing the adsorption and competition of PO{sub 4}, AsO{sub 4}, and SeO{sub 3}. The authors show that the structure of the surface-complex acting in the dominant electrostatic field can be ascertained as the primary controlling adsorption factor. The surface species of arsenate are identical with those of phosphate and the adsorption behavior is very similar. On the basis of the selenite adsorption, The authors show that the commonly used 1pKmore » models are incapable to incorporate in the adsorption modeling the correct bidentate binding mechanism found by spectroscopy. The use of the bidentate mechanism leads to a proton-oxyanion ratio and corresponding pH dependence that are too large. The inappropriate intrinsic charge attribution to the primary surface groups and the condensation of the inner sphere surface complex to a point charge are responsible for this behavior of commonly used 2pK models. Both key factors are differently defined in the charge distributed multi-site complexation (CD-MUSIC) model and are based in this model on a surface structural approach. The CD-MUSIC model can successfully describe the macroscopic adsorption phenomena using the surface speciation and binding mechanisms as found by spectroscopy. The model is also able to predict the anion competition well. The charge distribution in the interface is in agreement with the observed structure of surface complexes.« less

Adolescent emotionality and effortful control: Core latent constructs and links to psychopathology and functioning

PubMed Central

Snyder, Hannah R.; Gulley, Lauren D.; Bijttebier, Patricia; Hartman, Catharina A.; Oldehinkel, Albertine J.; Mezulis, Amy; Young, Jami F.; Hankin, Benjamin L.

2015-01-01

Temperament is associated with important outcomes in adolescence, including academic and interpersonal functioning and psychopathology. Rothbart’s temperament model is among the most well-studied and supported approaches to adolescent temperament, and contains three main components: positive emotionality (PE), negative emotionality (NE), and effortful control (EC). However, the latent factor structure of Rothbart’s temperament measure for adolescents, the Early Adolescent Temperament Questionnaire Revised (EATQ-R, Ellis & Rothbart, 2001) has not been definitively established. To address this problem and investigate links between adolescent temperament and functioning, we used confirmatory factor analysis to examine the latent constructs of the EATQ-R in a large combined sample. For EC and NE, bifactor models consisting of a common factor plus specific factors for some sub-facets of each component fit best, providing a more nuanced understanding of these temperament dimensions. The nature of the PE construct in the EATQ-R is less clear. Models replicated in a hold-out dataset. The common components of high NE and low EC where broadly associated with increased psychopathology symptoms, and poor interpersonal and school functioning, while specific components of NE were further associated with corresponding specific components of psychopathology. Further questioning the construct validity of PE as measured by the EATQ-R, PE factors did not correlate with construct validity measures in a way consistent with theories of PE. Bringing consistency to the way the EATQ-R is modeled and using purer latent variables has the potential to advance the field in understanding links between dimensions of temperament and important outcomes of adolescent development. PMID:26011660

Adolescent emotionality and effortful control: Core latent constructs and links to psychopathology and functioning.

PubMed

Snyder, Hannah R; Gulley, Lauren D; Bijttebier, Patricia; Hartman, Catharina A; Oldehinkel, Albertine J; Mezulis, Amy; Young, Jami F; Hankin, Benjamin L

2015-12-01

Temperament is associated with important outcomes in adolescence, including academic and interpersonal functioning and psychopathology. Rothbart's temperament model is among the most well-studied and supported approaches to adolescent temperament, and contains 3 main components: positive emotionality (PE), negative emotionality (NE), and effortful control (EC). However, the latent factor structure of Rothbart's temperament measure for adolescents, the Early Adolescent Temperament Questionnaire Revised (EATQ-R; Ellis & Rothbart, 2001) has not been definitively established. To address this problem and investigate links between adolescent temperament and functioning, we used confirmatory factor analysis to examine the latent constructs of the EATQ-R in a large combined sample. For EC and NE, bifactor models consisting of a common factor plus specific factors for some subfacets of each component fit best, providing a more nuanced understanding of these temperament dimensions. The nature of the PE construct in the EATQ-R is less clear. Models replicated in a hold-out dataset. The common components of high NE and low EC where broadly associated with increased psychopathology symptoms, and poor interpersonal and school functioning, while specific components of NE were further associated with corresponding specific components of psychopathology. Further questioning the construct validity of PE as measured by the EATQ-R, PE factors did not correlate with construct validity measures in a way consistent with theories of PE. Bringing consistency to the way the EATQ-R is modeled and using purer latent variables has the potential to advance the field in understanding links between dimensions of temperament and important outcomes of adolescent development. (c) 2015 APA, all rights reserved).

The Pathogenesis of Nonalcoholic Fatty Liver Disease: Interplay between Diet, Gut Microbiota, and Genetic Background

PubMed Central

Marsh, Sharon; Hu, Junbo; Feng, Wenke

2016-01-01

Nonalcoholic fatty liver disease (NAFLD) is the most common chronic liver disease in the world, and it comprises a spectrum of hepatic abnormalities from simple hepatic steatosis to steatohepatitis, fibrosis, cirrhosis, and liver cancer. While the pathogenesis of NAFLD remains incompletely understood, a multihit model has been proposed that accommodates causal factors from a variety of sources, including intestinal and adipose proinflammatory stimuli acting on the liver simultaneously. Prior cellular and molecular studies of patient and animal models have characterized several common pathogenic mechanisms of NAFLD, including proinflammation cytokines, lipotoxicity, oxidative stress, and endoplasmic reticulum stress. In recent years, gut microbiota has gained much attention, and dysbiosis is recognized as a crucial factor in NAFLD. Moreover, several genetic variants have been identified through genome-wide association studies, particularly rs738409 (Ile748Met) in PNPLA3 and rs58542926 (Glu167Lys) in TM6SF2, which are critical risk alleles of the disease. Although a high-fat diet and inactive lifestyles are typical risk factors for NAFLD, the interplay between diet, gut microbiota, and genetic background is believed to be more important in the development and progression of NAFLD. This review summarizes the common pathogenic mechanisms, the gut microbiota relevant mechanisms, and the major genetic variants leading to NAFLD and its progression. PMID:27247565

Small Heat Shock Proteins Are Novel Common Determinants of Alcohol and Nicotine Sensitivity in Caenorhabditis elegans

PubMed Central

Johnson, James R.; Rajamanoharan, Dayani; McCue, Hannah V.; Rankin, Kim

2016-01-01

Addiction to drugs is strongly determined by multiple genetic factors. Alcohol and nicotine produce distinct pharmacological effects within the nervous system through discrete molecular targets; yet, data from family and twin analyses support the existence of common genetic factors for addiction in general. The mechanisms underlying addiction, however, are poorly described and common genetic factors for alcohol and nicotine remain unidentified. We investigated the role that the heat shock transcription factor, HSF-1, and its downstream effectors played as common genetic modulators of sensitivity to addictive substances. Using Caenorhabditis elegans, an exemplary model organism with substance dose-dependent responses similar to mammals, we demonstrate that HSF-1 altered sensitivity to both alcohol and nicotine. Using a combination of a targeted RNAi screen of downstream factors and transgenic approaches we identified that these effects were contingent upon the constitutive neuronal expression of HSP-16.48, a small heat shock protein (HSP) homolog of human α-crystallin. Furthermore we demonstrated that the function of HSP-16.48 in drug sensitivity surprisingly was independent of chaperone activity during the heat shock stress response. Instead we identified a distinct domain within the N-terminal region of the HSP-16.48 protein that specified its function in comparison to related small HSPs. Our findings establish and characterize a novel genetic determinant underlying sensitivity to diverse addictive substances. PMID:26773049

Partial Least Squares with Structured Output for Modelling the Metabolomics Data Obtained from Complex Experimental Designs: A Study into the Y-Block Coding.

PubMed

Xu, Yun; Muhamadali, Howbeer; Sayqal, Ali; Dixon, Neil; Goodacre, Royston

2016-10-28

Partial least squares (PLS) is one of the most commonly used supervised modelling approaches for analysing multivariate metabolomics data. PLS is typically employed as either a regression model (PLS-R) or a classification model (PLS-DA). However, in metabolomics studies it is common to investigate multiple, potentially interacting, factors simultaneously following a specific experimental design. Such data often cannot be considered as a "pure" regression or a classification problem. Nevertheless, these data have often still been treated as a regression or classification problem and this could lead to ambiguous results. In this study, we investigated the feasibility of designing a hybrid target matrix Y that better reflects the experimental design than simple regression or binary class membership coding commonly used in PLS modelling. The new design of Y coding was based on the same principle used by structural modelling in machine learning techniques. Two real metabolomics datasets were used as examples to illustrate how the new Y coding can improve the interpretability of the PLS model compared to classic regression/classification coding.

A general psychopathology factor in early adolescence.

PubMed

Patalay, Praveetha; Fonagy, Peter; Deighton, Jessica; Belsky, Jay; Vostanis, Panos; Wolpert, Miranda

2015-07-01

Recently, a general psychopathology dimension reflecting common aspects among disorders has been identified in adults. This has not yet been considered in children and adolescents, where the focus has been on externalising and internalising dimensions. To examine the existence, correlates and predictive value of a general psychopathology dimension in young people. Alternative factor models were estimated using self-reports of symptoms in a large community-based sample aged 11-13.5 years (N = 23 477), and resulting dimensions were assessed in terms of associations with external correlates and future functioning. Both a traditional two-factor model and a bi-factor model with a general psychopathology bi-factor fitted the data well. The general psychopathology bi-factor best predicted future psychopathology and academic attainment. Associations with correlates and factor loadings are discussed. A general psychopathology factor, which is equal across genders, can be identified in young people. Its associations with correlates and future functioning indicate that investigating this factor can increase our understanding of the aetiology, risk and correlates of psychopathology. © The Royal College of Psychiatrists 2015.

Associations between five-factor model of the Positive and Negative Syndrome Scale and plasma levels of monoamine metabolite in patients with schizophrenia.

PubMed

Watanabe, Kenya; Miura, Itaru; Kanno-Nozaki, Keiko; Horikoshi, Sho; Mashiko, Hirobumi; Niwa, Shin-Ichi; Yabe, Hirooki

2015-12-15

The five-factor model of the Positive and Negative Syndrome Scale (PANSS) for schizophrenia symptoms is the most common multiple-factor model used in analyses; its use may improve evaluation of symptoms in schizophrenia patients. Plasma monoamine metabolite levels are possible indicators of clinical symptoms or response to antipsychotics in schizophrenia. We investigated the association between five-factor model components and plasma monoamine metabolites levels to explore the model's biological basis. Plasma levels of homovanillic acid (HVA), 3-methoxy-4-hydroxyphenylglycol (MHPG), and 5-hydroxyindoleacetic acid (5-HIAA) were measured using high-performance liquid chromatography in 65 Japanese patients with schizophrenia. Significant negative correlation between plasma 5-HIAA levels and the depression/anxiety component was found. Furthermore, significant positive correlation was found between plasma MHPG levels and the excitement component. Plasma HVA levels were not correlated with any five-factor model component. These results suggest that the five-factor model of the PANSS may have a biological basis, and may be useful for elucidating the psychopathology of schizophrenia. Assessment using the five-factor model may enable understanding of monoaminergic dysfunction, possibly allowing more appropriate medication selection. Further studies of a larger number of first-episode schizophrenia patients are needed to confirm and extend these results. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

The epidemiology of pelvic floor disorders and childbirth: an update

PubMed Central

Hallock, Jennifer L.; Handa, Victoria L.

2015-01-01

SYNOPSIS Using a life span model, this article presents new scientific findings regarding risk factors for pelvic floor disorders (PFDs), with a focus on the role of childbirth in the development of single or multiple co-existing PFDs. Phase I of the life span model includes predisposing factors such as genetic predisposition and race. Phase II of the model includes inciting factors such as obstetric events. Prolapse, urinary incontinence (UI) and fecal incontinence (FI) are more common among vaginally parous women, although the impact of vaginal delivery on risk of FI is less dramatic than for prolapse and UI. Finally, Phase III includes intervening factors such as age and obesity. Both age and obesity are associated with prevalence of PFDs. The prevention and treatment of obesity is an important component to PFD prevention. PMID:26880504

Replication and extension of a hierarchical model of social anxiety and depression: fear of positive evaluation as a key unique factor in social anxiety.

PubMed

Weeks, Justin W

2015-01-01

Wang, Hsu, Chiu, and Liang (2012, Journal of Anxiety Disorders, 26, 215-224) recently proposed a hierarchical model of social interaction anxiety and depression to account for both the commonalities and distinctions between these conditions. In the present paper, this model was extended to more broadly encompass the symptoms of social anxiety disorder, and replicated in a large unselected, undergraduate sample (n = 585). Structural equation modeling (SEM) and hierarchical regression analyses were employed. Negative affect and positive affect were conceptualized as general factors shared by social anxiety and depression; fear of negative evaluation (FNE) and disqualification of positive social outcomes were operationalized as specific factors, and fear of positive evaluation (FPE) was operationalized as a factor unique to social anxiety. This extended hierarchical model explicates structural relationships among these factors, in which the higher-level, general factors (i.e., high negative affect and low positive affect) represent vulnerability markers of both social anxiety and depression, and the lower-level factors (i.e., FNE, disqualification of positive social outcomes, and FPE) are the dimensions of specific cognitive features. Results from SEM and hierarchical regression analyses converged in support of the extended model. FPE is further supported as a key symptom that differentiates social anxiety from depression.

Confirmatory Factor Analysis of Ordinal Variables with Misspecified Models

ERIC Educational Resources Information Center

Yang-Wallentin, Fan; Joreskog, Karl G.; Luo, Hao

2010-01-01

Ordinal variables are common in many empirical investigations in the social and behavioral sciences. Researchers often apply the maximum likelihood method to fit structural equation models to ordinal data. This assumes that the observed measures have normal distributions, which is not the case when the variables are ordinal. A better approach is…

Model Based Usability Heuristics for Constructivist E-Learning

ERIC Educational Resources Information Center

Katre, Dinesh S.

2007-01-01

Many e-learning applications and games have been studied to identify the common interaction models of constructivist learning, namely: 1. Move the object to appropriate location; 2. Place objects in appropriate order and location(s); 3. Click to identify; 4. Change the variable factors to observe the effects; and 5. System personification and…

Assessing Measurement Equivalence in Ordered-Categorical Data

ERIC Educational Resources Information Center

Elosua, Paula

2011-01-01

Assessing measurement equivalence in the framework of the common factor linear models (CFL) is known as factorial invariance. This methodology is used to evaluate the equivalence among the parameters of a measurement model among different groups. However, when dichotomous, Likert, or ordered responses are used, one of the assumptions of the CFL is…

Individual Differences in Components of Reaction Time Distributions and Their Relations to Working Memory and Intelligence

ERIC Educational Resources Information Center

Schmiedek, Florian; Oberauer, Klaus; Wilhelm, Oliver; Suss, Heinz-Martin; Wittmann, Werner W.

2007-01-01

The authors bring together approaches from cognitive and individual differences psychology to model characteristics of reaction time distributions beyond measures of central tendency. Ex-Gaussian distributions and a diffusion model approach are used to describe individuals' reaction time data. The authors identified common latent factors for each…

Toward a Common Structure in Demographic Educational Modeling and Simulation: A Complex Systems Approach

ERIC Educational Resources Information Center

Guevara, Porfirio

2014-01-01

This article identifies elements and connections that seem to be relevant to explain persistent aggregate behavioral patterns in educational systems when using complex dynamical systems modeling and simulation approaches. Several studies have shown what factors are at play in educational fields, but confusion still remains about the underlying…

Energy risk in the arbitrage pricing model: an empirical and theoretical study

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

Bremer, M.A.

1986-01-01

This dissertation empirically explores the Arbitrage Pricing Theory in the context of energy risk for securities over the 1960s, 1970s, and early 1980s. Starting from a general multifactor pricing model, the paper develops a two factor model based on a market-like factor and an energy factor. This model is then tested on portfolios of securities grouped according to industrial classification using several econometric techniques designed to overcome some of the more serious estimation problems common to these models. The paper concludes that energy risk is priced in the 1970s and possibly even in the 1960s. Energy risk is found tomore » be priced in the sense that investors who hold assets subjected to energy risk are paid for this risk. The classic version of the Capital Asset Pricing Model which posits the market as the single priced factor is rejected in favor of the Arbitrage Pricing Theory or multi-beta versions of the Capital Asset Pricing Model. The study introduces some original econometric methodology to carry out empirical tests.« less

Life-style factors and hand eczema.

PubMed

Anveden Berglind, I; Alderling, M; Meding, B

2011-09-01

Previous knowledge of the impact of certain life-style factors on hand eczema is scanty. To investigate a possible association between hand eczema and life-style factors such as obesity, physical exercise, stress, smoking and alcohol consumption. In a cross-sectional public health survey in Stockholm, Sweden, 27,994 (58%) randomly chosen individuals aged 18-64 years completed a postal questionnaire regarding physical and mental health, social relations, economic status and work. Of these, 27,793 individuals responded to the question regarding hand eczema and were included in the present study. The association between life-style factors and hand eczema was analysed by prevalence proportion ratios (PPR), using a generalized linear model. Hand eczema was more common among individuals who reported high stress levels, PPR 1·326 (95% CI 1·303-1·350). There was also a positive dose-response relationship between hand eczema and stress. Hand eczema was less common among individuals reporting high physical exercise, and most apparent in women, PPR 0·781 (95% CI 0·770-0·792). Men who reported high alcohol intake reported hand eczema less often, PPR 0·958 (95% CI 0·930-0·987). Obese individuals reported hand eczema more commonly, PPR 1·204 (95% CI 1·174-1·234). There was a slight increase of hand eczema among smokers, PPR 1·025 (95% CI 1·006-1·044). Hand eczema was more common in individuals who reported stress, obesity and smoking. In individuals who reported high physical exercise levels hand eczema was less common. As there appears to be an association between life-style factors and hand eczema it is important to consider life-style factors in clinical practice. © 2011 The Authors. BJD © 2011 British Association of Dermatologists.

Common Cause Failure Modeling in Space Launch Vehicles

NASA Technical Reports Server (NTRS)

Hark, Frank; Ring, Rob; Novack, Steven D.; Britton, Paul

2015-01-01

Common Cause Failures (CCFs) are a known and documented phenomenon that defeats system redundancy. CCFs are a set of dependent type of failures that can be caused for example by system environments, manufacturing, transportation, storage, maintenance, and assembly. Since there are many factors that contribute to CCFs, they can be reduced, but are difficult to eliminate entirely. Furthermore, failure databases sometimes fail to differentiate between independent and dependent CCF. Because common cause failure data is limited in the aerospace industry, the Probabilistic Risk Assessment (PRA) Team at Bastion Technology Inc. is estimating CCF risk using generic data collected by the Nuclear Regulatory Commission (NRC). Consequently, common cause risk estimates based on this database, when applied to other industry applications, are highly uncertain. Therefore, it is important to account for a range of values for independent and CCF risk and to communicate the uncertainty to decision makers. There is an existing methodology for reducing CCF risk during design, which includes a checklist of 40+ factors grouped into eight categories. Using this checklist, an approach to produce a beta factor estimate is being investigated that quantitatively relates these factors. In this example, the checklist will be tailored to space launch vehicles, a quantitative approach will be described, and an example of the method will be presented.

Risk factors associated with iatrogenic opioid and benzodiazepine withdrawal in critically ill pediatric patients: a systematic review and conceptual model.

PubMed

Best, Kaitlin M; Boullata, Joseph I; Curley, Martha A Q

2015-02-01

Analgesia and sedation are common therapies in pediatric critical care, and rapid titration of these medications is associated with iatrogenic withdrawal syndrome. We performed a systematic review of the literature to identify all common and salient risk factors associated with iatrogenic withdrawal syndrome and build a conceptual model of iatrogenic withdrawal syndrome risk in critically ill pediatric patients. Multiple databases, including PubMed/Medline, EMBASE, CINAHL, and the Cochrane Central Registry of Clinical Trials, were searched using relevant terms from January 1, 1980, to August 1, 2014. Articles were included if they were published in English and discussed iatrogenic withdrawal syndrome following either opioid or benzodiazepine therapy in children in acute or intensive care settings. Articles were excluded if subjects were neonates born to opioid- or benzodiazepine-dependent mothers, children diagnosed as substance abusers, or subjects with cancer-related pain; if data about opioid or benzodiazepine treatment were not specified; or if primary data were not reported. In total, 1,395 articles were evaluated, 33 of which met the inclusion criteria. To facilitate analysis, all opioid and/or benzodiazepine doses were converted to morphine or midazolam equivalents, respectively. A table of evidence was developed for qualitative analysis of common themes, providing a framework for the construction of a conceptual model. The strongest risk factors associated with iatrogenic withdrawal syndrome include duration of therapy and cumulative dose. Additionally, evidence exists linking patient, process, and system factors in the development of iatrogenic withdrawal syndrome. Most articles were prospective observational or interventional studies. Given the state of existing evidence, well-designed prospective studies are required to better characterize iatrogenic withdrawal syndrome in critically ill pediatric patients. This review provides data to support the construction of a conceptual model of iatrogenic withdrawal syndrome risk that, if supported, could be useful in guiding future research.

Class Enumeration and Parameter Recovery of Growth Mixture Modeling and Second-Order Growth Mixture Modeling in the Presence of Measurement Noninvariance between Latent Classes

PubMed Central

Kim, Eun Sook; Wang, Yan

2017-01-01

Population heterogeneity in growth trajectories can be detected with growth mixture modeling (GMM). It is common that researchers compute composite scores of repeated measures and use them as multiple indicators of growth factors (baseline performance and growth) assuming measurement invariance between latent classes. Considering that the assumption of measurement invariance does not always hold, we investigate the impact of measurement noninvariance on class enumeration and parameter recovery in GMM through a Monte Carlo simulation study (Study 1). In Study 2, we examine the class enumeration and parameter recovery of the second-order growth mixture modeling (SOGMM) that incorporates measurement models at the first order level. Thus, SOGMM estimates growth trajectory parameters with reliable sources of variance, that is, common factor variance of repeated measures and allows heterogeneity in measurement parameters between latent classes. The class enumeration rates are examined with information criteria such as AIC, BIC, sample-size adjusted BIC, and hierarchical BIC under various simulation conditions. The results of Study 1 showed that the parameter estimates of baseline performance and growth factor means were biased to the degree of measurement noninvariance even when the correct number of latent classes was extracted. In Study 2, the class enumeration accuracy of SOGMM depended on information criteria, class separation, and sample size. The estimates of baseline performance and growth factor mean differences between classes were generally unbiased but the size of measurement noninvariance was underestimated. Overall, SOGMM is advantageous in that it yields unbiased estimates of growth trajectory parameters and more accurate class enumeration compared to GMM by incorporating measurement models. PMID:28928691

Effects of spatial disturbance on common loon nest site selection and territory success

USGS Publications Warehouse

McCarthy, Kyle P.; DeStefano, Stephen

2011-01-01

The common loon (Gavia immer) breeds during the summer on northern lakes and water bodies that are also often desirable areas for aquatic recreation and human habitation. In northern New England, we assessed how the spatial nature of disturbance affects common loon nest site selection and territory success. We found through classification and regression analysis that distance to and density of disturbance factors can be used to classify observed nest site locations versus random points, suggesting that these factors affect loon nest site selection (model 1: Correct classification = 75%, null = 50%, K = 0.507, P < 0.001; model 2: Correct classification = 78%, null = 50%, K = 0.551, P < 0.001). However, in an exploratory analysis, we were unable to show a relation between spatial disturbance variables and breeding success (P = 0.595, R2 = 0.436), possibly because breeding success was so low during the breeding seasons of 2007–2008. We suggest that by selecting nest site locations that avoid disturbance factors, loons thereby limit the effect that disturbance will have on their breeding success. Still, disturbance may force loons to use sub-optimal nesting habitat, limiting the available number of territories, and overall productivity. We advise that management efforts focus on limiting disturbance factors to allow breeding pairs access to the best nesting territories, relieving disturbance pressures that may force sub-optimal nest placement.

Groundwater salinity in a floodplain forest impacted by saltwater intrusion.

PubMed

Kaplan, David A; Muñoz-Carpena, Rafael

2014-11-15

Coastal wetlands occupy a delicate position at the intersection of fresh and saline waters. Changing climate and watershed hydrology can lead to saltwater intrusion into historically freshwater systems, causing plant mortality and loss of freshwater habitat. Understanding the hydrological functioning of tidally influenced floodplain forests is essential for advancing ecosystem protection and restoration goals, however finding direct relationships between hydrological inputs and floodplain hydrology is complicated by interactions between surface water, groundwater, and atmospheric fluxes in variably saturated soils with heterogeneous vegetation and topography. Thus, an alternative method for identifying common trends and causal factors is required. Dynamic factor analysis (DFA), a time series dimension reduction technique, models temporal variation in observed data as linear combinations of common trends, which represent unexplained common variability, and explanatory variables. DFA was applied to model shallow groundwater salinity in the forested floodplain wetlands of the Loxahatchee River (Florida, USA), where altered watershed hydrology has led to changing hydroperiod and salinity regimes and undesired vegetative changes. Long-term, high-resolution groundwater salinity datasets revealed dynamics over seasonal and yearly time periods as well as over tidal cycles and storm events. DFA identified shared trends among salinity time series and a full dynamic factor model simulated observed series well (overall coefficient of efficiency, Ceff=0.85; 0.52≤Ceff≤0.99). A reduced multilinear model based solely on explanatory variables identified in the DFA had fair to good results (Ceff=0.58; 0.38≤Ceff≤0.75) and may be used to assess the effects of restoration and management scenarios on shallow groundwater salinity in the Loxahatchee River floodplain. Copyright © 2014 Elsevier B.V. All rights reserved.

Using Dynamic Multi-Task Non-Negative Matrix Factorization to Detect the Evolution of User Preferences in Collaborative Filtering

PubMed Central

Ju, Bin; Qian, Yuntao; Ye, Minchao; Ni, Rong; Zhu, Chenxi

2015-01-01

Predicting what items will be selected by a target user in the future is an important function for recommendation systems. Matrix factorization techniques have been shown to achieve good performance on temporal rating-type data, but little is known about temporal item selection data. In this paper, we developed a unified model that combines Multi-task Non-negative Matrix Factorization and Linear Dynamical Systems to capture the evolution of user preferences. Specifically, user and item features are projected into latent factor space by factoring co-occurrence matrices into a common basis item-factor matrix and multiple factor-user matrices. Moreover, we represented both within and between relationships of multiple factor-user matrices using a state transition matrix to capture the changes in user preferences over time. The experiments show that our proposed algorithm outperforms the other algorithms on two real datasets, which were extracted from Netflix movies and Last.fm music. Furthermore, our model provides a novel dynamic topic model for tracking the evolution of the behavior of a user over time. PMID:26270539

Using Dynamic Multi-Task Non-Negative Matrix Factorization to Detect the Evolution of User Preferences in Collaborative Filtering.

PubMed

Ju, Bin; Qian, Yuntao; Ye, Minchao; Ni, Rong; Zhu, Chenxi

2015-01-01

Predicting what items will be selected by a target user in the future is an important function for recommendation systems. Matrix factorization techniques have been shown to achieve good performance on temporal rating-type data, but little is known about temporal item selection data. In this paper, we developed a unified model that combines Multi-task Non-negative Matrix Factorization and Linear Dynamical Systems to capture the evolution of user preferences. Specifically, user and item features are projected into latent factor space by factoring co-occurrence matrices into a common basis item-factor matrix and multiple factor-user matrices. Moreover, we represented both within and between relationships of multiple factor-user matrices using a state transition matrix to capture the changes in user preferences over time. The experiments show that our proposed algorithm outperforms the other algorithms on two real datasets, which were extracted from Netflix movies and Last.fm music. Furthermore, our model provides a novel dynamic topic model for tracking the evolution of the behavior of a user over time.

Comparison of Factor Simplicity Indices for Dichotomous Data: DETECT R, Bentler's Simplicity Index, and the Loading Simplicity Index

ERIC Educational Resources Information Center

Finch, Holmes; Stage, Alan Kirk; Monahan, Patrick

2008-01-01

A primary assumption underlying several of the common methods for modeling item response data is unidimensionality, that is, test items tap into only one latent trait. This assumption can be assessed several ways, using nonlinear factor analysis and DETECT, a method based on the item conditional covariances. When multidimensionality is identified,…

The Modeling of Factors That Influence Coast Guard Manpower Requirements

DTIC Science & Technology

2014-12-01

applications, and common data warehouses needed to fully develop an effective and efficient manpower requirements engineering and management program. The... manpower requirements determination ensures a ready force, and safe and effective mission execution. Shortage or excess of manpower is the catalyst...FACTORS THAT INFLUENCE COAST GUARD MANPOWER REQUIREMENTS by Kara M. Lavin December 2014 Thesis Advisor: Ronald E. Giachetti Co-Advisor

The X-Factor: an evaluation of common methods used to analyse major inter-segment kinematics during the golf swing.

PubMed

Brown, Susan J; Selbie, W Scott; Wallace, Eric S

2013-01-01

A common biomechanical feature of a golf swing, described in various ways in the literature, is the interaction between the thorax and pelvis, often termed the X-Factor. There is no consistent method used within golf biomechanics literature however to calculate these segment interactions. The purpose of this study was to examine X-factor data calculated using three reported methods in order to determine the similarity or otherwise of the data calculated using each method. A twelve-camera three-dimensional motion capture system was used to capture the driver swings of 19 participants and a subject specific three-dimensional biomechanical model was created with the position and orientation of each model estimated using a global optimisation algorithm. Comparison of the X-Factor methods showed significant differences for events during the swing (P < 0.05). Data for each kinematic measure were derived as a times series for all three methods and regression analysis of these data showed that whilst one method could be successfully mapped to another, the mappings between methods are subject dependent (P <0.05). Findings suggest that a consistent methodology considering the X-Factor from a joint angle approach is most insightful in describing a golf swing.

Genetics, gene expression and bioinformatics of the pituitary gland.

PubMed

Davis, Shannon W; Potok, Mary Anne; Brinkmeier, Michelle L; Carninci, Piero; Lyons, Robert H; MacDonald, James W; Fleming, Michelle T; Mortensen, Amanda H; Egashira, Noboru; Ghosh, Debashis; Steel, Karen P; Osamura, Robert Y; Hayashizaki, Yoshihide; Camper, Sally A

2009-04-01

Genetic cases of congenital pituitary hormone deficiency are common and many are caused by transcription factor defects. Mouse models with orthologous mutations are invaluable for uncovering the molecular mechanisms that lead to problems in organ development and typical patient characteristics. We are using mutant mice defective in the transcription factors PROP1 and POU1F1 for gene expression profiling to identify target genes for these critical transcription factors and candidates for cases of pituitary hormone deficiency of unknown aetiology. These studies reveal critical roles for Wnt signalling pathways, including the TCF/LEF transcription factors and interacting proteins of the groucho family, bone morphogenetic protein antagonists and targets of notch signalling. Current studies are investigating the roles of novel homeobox genes and pathways that regulate the transition from proliferation to differentiation, cell adhesion and cell migration. Pituitary adenomas are a common human health problem, yet most cases are sporadic, necessitating alternative approaches to traditional Mendelian genetic studies. Mouse models of adenoma formation offer the opportunity for gene expression profiling during progressive stages of hyperplasia, adenoma and tumorigenesis. This approach holds promise for the identification of relevant pathways and candidate genes as risk factors for adenoma formation, understanding mechanisms of progression, and identifying drug targets and clinically relevant biomarkers. Copyright 2009 S. Karger AG, Basel.

Genetics, Gene Expression and Bioinformatics of the Pituitary Gland

PubMed Central

Davis, Shannon W; Potok, Mary Anne; Brinkmeier, Michelle L; Carninci, Piero; Lyons, Robert H; MacDonald, James W.; Fleming, Michelle T; Mortensen, Amanda H; Egashira, Noboru; Ghosh, Debashis; Steel, Karen P.; Osamura, Robert Y; Hayashizaki, Yoshihide; Camper, Sally A

2011-01-01

Genetic cases of congenital pituitary hormone deficiency are common and many are caused by transcription factor defects. Mouse models with orthologous mutations are invaluable for uncovering the molecular mechanisms that lead to problems in organ development and typical patient characteristics. We are using mutant mice defective in the transcription factors PROP1 and POU1F1 for gene expression profiling to identify target genes for these critical transcription factors and candidates for cases of pituitary hormone deficiency of unknown etiology. These studies reveal critical roles for Wnt signalling pathways including the TCF/LEF transcription factors and interacting proteins of the groucho family, bone morphogenetic proteins antagonists, and targets of notch signalling. Current studies are investigating roles of novel homeobox genes and pathways that regulate the transition from proliferation to differentiation, cell adhesion and cell migration. Pituitary adenomas are a common human health problem, yet most cases are sporadic, necessitating alternative approaches to traditional Mendelian genetic studies. Mouse models of adenoma formation offer the opportunity for gene expression profiling during progressive stages of hyperplasia, adenoma and tumorigenesis. This approach holds promise for identification of relevant pathways and candidate genes as risk factors for adenoma formation, understanding mechanisms of progression, and identifying drug targets and clinically relevant biomarkers. PMID:19407506

Platelet-derived growth factor receptors differentially inform intertumoral and intratumoral heterogeneity

PubMed Central

Kim, Youngmi; Kim, Eunhee; Wu, Qiulian; Guryanova, Olga; Hitomi, Masahiro; Lathia, Justin D.; Serwanski, David; Sloan, Andrew E.; Weil, Robert J.; Lee, Jeongwu; Nishiyama, Akiko; Bao, Shideng; Hjelmeland, Anita B.; Rich, Jeremy N.

2012-01-01

Growth factor-mediated proliferation and self-renewal maintain tissue-specific stem cells and are frequently dysregulated in cancers. Platelet-derived growth factor (PDGF) ligands and receptors (PDGFRs) are commonly overexpressed in gliomas and initiate tumors, as proven in genetically engineered models. While PDGFRα alterations inform intertumoral heterogeneity toward a proneural glioblastoma (GBM) subtype, we interrogated the role of PDGFRs in intratumoral GBM heterogeneity. We found that PDGFRα is expressed only in a subset of GBMs, while PDGFRβ is more commonly expressed in tumors but is preferentially expressed by self-renewing tumorigenic GBM stem cells (GSCs). Genetic or pharmacological targeting of PDGFRβ (but not PDGFRα) attenuated GSC self-renewal, survival, tumor growth, and invasion. PDGFRβ inhibition decreased activation of the cancer stem cell signaling node STAT3, while constitutively active STAT3 rescued the loss of GSC self-renewal caused by PDGFRβ targeting. In silico survival analysis demonstrated that PDGFRB informed poor prognosis, while PDGFRA was a positive prognostic factor. Our results may explain mixed clinical responses of anti-PDGFR-based approaches and suggest the need for integration of models of cancer as an organ system into development of cancer therapies. PMID:22661233

The mathematical limits of genetic prediction for complex chronic disease.

PubMed

Keyes, Katherine M; Smith, George Davey; Koenen, Karestan C; Galea, Sandro

2015-06-01

Attempts at predicting individual risk of disease based on common germline genetic variation have largely been disappointing. The present paper formalises why genetic prediction at the individual level is and will continue to have limited utility given the aetiological architecture of most common complex diseases. Data were simulated on one million populations with 10 000 individuals in each populations with varying prevalences of a genetic risk factor, an interacting environmental factor and the background rate of disease. The determinant risk ratio and risk difference magnitude for the association between a gene variant and disease is a function of the prevalence of the interacting factors that activate the gene, and the background rate of disease. The risk ratio and total excess cases due to the genetic factor increase as the prevalence of interacting factors increase, and decrease as the background rate of disease increases. Germline genetic variations have high predictive capacity for individual disease only under conditions of high heritability of particular genetic sequences, plausible only under rare variant hypotheses. Under a model of common germline genetic variants that interact with other genes and/or environmental factors in order to cause disease, the predictive capacity of common genetic variants is determined by the prevalence of the factors that interact with the variant and the background rate. A focus on estimating genetic associations for the purpose of prediction without explicitly grounding such work in an understanding of modifiable (including environmentally influenced) factors will be limited in its ability to yield important insights about the risk of disease. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.

Aggression and Rule-breaking: Heritability and stability of antisocial behavior problems in childhood and adolescence

PubMed Central

Niv, Sharon; Tuvblad, Catherine; Raine, Adrian; Baker, Laura A.

2013-01-01

Purpose This twin study examined the structure of genetic and environmental influences on aggression and rule-breaking in order to examine change and stability across the span of childhood to mid-adolescence. Methods Behavioral assessments were conducted at two time points: age 9–10 years and 14–15 years. Using behavioral genetics biometric modeling, the longitudinal structure of influences was investigated. Results Aggression and rule-breaking were found to be influenced by a latent common factor of antisocial behavior (ASB) within each wave of data collection. The childhood-age common factor of ASB was influenced by 41% genetics, 40% shared environment and 19% nonshared environment. In adolescence, 41% of influences on the common factor were novel and entirely genetic, while the remainder of influences were stable across time. Additionally, both aggression and rule-breaking within each wave were found to have unique influences not common across subscales or across waves, highlighting specificity of influences on different problem behaviors at both ages. Conclusions This research sheds light on the commonality of influences on etiology of different forms of antisocial behavior, and suggests future directions for research into intervention for antisocial behavior problems in youth, such as investigation of adolescence-specific environmental influences on the development of antisocial behavior problems. PMID:24347737

Common carotid intima-media thickness does not add to Framingham risk score in individuals with diabetes mellitus: the USE-IMT initiative.

PubMed

den Ruijter, H M; Peters, S A E; Groenewegen, K A; Anderson, T J; Britton, A R; Dekker, J M; Engström, G; Eijkemans, M J; Evans, G W; de Graaf, J; Grobbee, D E; Hedblad, B; Hofman, A; Holewijn, S; Ikeda, A; Kavousi, M; Kitagawa, K; Kitamura, A; Koffijberg, H; Ikram, M A; Lonn, E M; Lorenz, M W; Mathiesen, E B; Nijpels, G; Okazaki, S; O'Leary, D H; Polak, J F; Price, J F; Robertson, C; Rembold, C M; Rosvall, M; Rundek, T; Salonen, J T; Sitzer, M; Stehouwer, C D A; Witteman, J C; Moons, K G; Bots, M L

2013-07-01

The aim of this work was to investigate whether measurement of the mean common carotid intima-media thickness (CIMT) improves cardiovascular risk prediction in individuals with diabetes. We performed a subanalysis among 4,220 individuals with diabetes in a large ongoing individual participant data meta-analysis involving 56,194 subjects from 17 population-based cohorts worldwide. We first refitted the risk factors of the Framingham heart risk score on the individuals without previous cardiovascular disease (baseline model) and then expanded this model with the mean common CIMT (CIMT model). The absolute 10 year risk for developing a myocardial infarction or stroke was estimated from both models. In individuals with diabetes we compared discrimination and calibration of the two models. Reclassification of individuals with diabetes was based on allocation to another cardiovascular risk category when mean common CIMT was added. During a median follow-up of 8.7 years, 684 first-time cardiovascular events occurred among the population with diabetes. The C statistic was 0.67 for the Framingham model and 0.68 for the CIMT model. The absolute 10 year risk for developing a myocardial infarction or stroke was 16% in both models. There was no net reclassification improvement with the addition of mean common CIMT (1.7%; 95% CI -1.8, 3.8). There were no differences in the results between men and women. There is no improvement in risk prediction in individuals with diabetes when measurement of the mean common CIMT is added to the Framingham risk score. Therefore, this measurement is not recommended for improving individual cardiovascular risk stratification in individuals with diabetes.

The developmental association between eating disorders symptoms and symptoms of depression and anxiety in juvenile twin girls.

PubMed

Silberg, Judy L; Bulik, Cynthia M

2005-12-01

We investigated the role of genetic and environmental factors in the developmental association among symptoms of eating disorders, depression, and anxiety syndromes in 8-13-year-old and 14-17-year-old twin girls. Multivariate genetic models were fitted to child-reported longitudinal symptom data gathered from clinical interview on 408 MZ and 198 DZ female twin pairs from the Virginia Twin Study of Adolescent Behavioural Development (VTSABD). Model-fitting revealed distinct etiological patterns underlying the association among symptoms of eating disorders, depression, overanxious disorder (OAD), and separation anxiety disorder (SAD) during the course of development: 1) a common genetic factor influencing liability to all symptoms - of early and later OAD, depression, SAD, and eating symptoms; 2) a distinct genetic factor specifically indexing liability to early eating disorders symptoms; 3) a shared environmental factor specifically influencing early depression and early eating disorders symptoms; and 4) a common environmental factor affecting liability to symptoms of later eating disorders and both early and later separation anxiety. These results suggest a pervasive genetic effect that influences liability to symptoms of over-anxiety, separation anxiety, depression, and eating disorder throughout development, a shared environmental influence on later adolescent eating problems and persistent separation anxiety, genetic influences specific to early eating disorders symptoms, and a shared environmental factor influencing symptoms of early eating and depression.

Reliability of IGBT in a STATCOM for Harmonic Compensation and Power Factor Correction

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

Gopi Reddy, Lakshmi Reddy; Tolbert, Leon M; Ozpineci, Burak

With smart grid integration, there is a need to characterize reliability of a power system by including reliability of power semiconductors in grid related applications. In this paper, the reliability of IGBTs in a STATCOM application is presented for two different applications, power factor correction and harmonic elimination. The STATCOM model is developed in EMTP, and analytical equations for average conduction losses in an IGBT and a diode are derived and compared with experimental data. A commonly used reliability model is used to predict reliability of IGBT.

Occupant behavior models: A critical review of implementation and representation approaches in building performance simulation programs

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

Hong, Tianzhen; Chen, Yixing; Belafi, Zsofia

Occupant behavior (OB) in buildings is a leading factor influencing energy use in buildings. Quantifying this influence requires the integration of OB models with building performance simulation (BPS). This study reviews approaches to representing and implementing OB models in today’s popular BPS programs, and discusses weaknesses and strengths of these approaches and key issues in integrating of OB models with BPS programs. Two of the key findings are: (1) a common data model is needed to standardize the representation of OB models, enabling their flexibility and exchange among BPS programs and user applications; the data model can be implemented usingmore » a standard syntax (e.g., in the form of XML schema), and (2) a modular software implementation of OB models, such as functional mock-up units for co-simulation, adopting the common data model, has advantages in providing a robust and interoperable integration with multiple BPS programs. Such common OB model representation and implementation approaches help standardize the input structures of OB models, enable collaborative development of a shared library of OB models, and allow for rapid and widespread integration of OB models with BPS programs to improve the simulation of occupant behavior and quantification of their impact on building performance.« less

Occupant behavior models: A critical review of implementation and representation approaches in building performance simulation programs

DOE PAGES

Hong, Tianzhen; Chen, Yixing; Belafi, Zsofia; ...

2017-07-27

Occupant behavior (OB) in buildings is a leading factor influencing energy use in buildings. Quantifying this influence requires the integration of OB models with building performance simulation (BPS). This study reviews approaches to representing and implementing OB models in today’s popular BPS programs, and discusses weaknesses and strengths of these approaches and key issues in integrating of OB models with BPS programs. Two of the key findings are: (1) a common data model is needed to standardize the representation of OB models, enabling their flexibility and exchange among BPS programs and user applications; the data model can be implemented usingmore » a standard syntax (e.g., in the form of XML schema), and (2) a modular software implementation of OB models, such as functional mock-up units for co-simulation, adopting the common data model, has advantages in providing a robust and interoperable integration with multiple BPS programs. Such common OB model representation and implementation approaches help standardize the input structures of OB models, enable collaborative development of a shared library of OB models, and allow for rapid and widespread integration of OB models with BPS programs to improve the simulation of occupant behavior and quantification of their impact on building performance.« less

Rodent Hypoxia–Ischemia Models for Cerebral Palsy Research: A Systematic Review

PubMed Central

Rumajogee, Prakasham; Bregman, Tatiana; Miller, Steven P.; Yager, Jerome Y.; Fehlings, Michael G.

2016-01-01

Cerebral palsy (CP) is a complex multifactorial disorder, affecting approximately 2.5–3/1000 live term births, and up to 22/1000 prematurely born babies. CP results from injury to the developing brain incurred before, during, or after birth. The most common form of this condition, spastic CP, is primarily associated with injury to the cerebral cortex and subcortical white matter as well as the deep gray matter. The major etiological factors of spastic CP are hypoxia/ischemia (HI), occurring during the last third of pregnancy and around birth age. In addition, inflammation has been found to be an important factor contributing to brain injury, especially in term infants. Other factors, including genetics, are gaining importance. The classic Rice–Vannucci HI model (in which 7-day-old rat pups undergo unilateral ligation of the common carotid artery followed by exposure to 8% oxygen hypoxic air) is a model of neonatal stroke that has greatly contributed to CP research. In this model, brain damage resembles that observed in severe CP cases. This model, and its numerous adaptations, allows one to finely tune the injury parameters to mimic, and therefore study, many of the pathophysiological processes and conditions observed in human patients. Investigators can recreate the HI and inflammation, which cause brain damage and subsequent motor and cognitive deficits. This model further enables the examination of potential approaches to achieve neural repair and regeneration. In the present review, we compare and discuss the advantages, limitations, and the translational value for CP research of HI models of perinatal brain injury. PMID:27199883

Developing probabilistic models to predict amphibian site occupancy in a patchy landscape

Treesearch

R. A. Knapp; K.R. Matthews; H. K. Preisler; R. Jellison

2003-01-01

Abstract. Human-caused fragmentation of habitats is threatening an increasing number of animal and plant species, making an understanding of the factors influencing patch occupancy ever more important. The overall goal of the current study was to develop probabilistic models of patch occupancy for the mountain yellow-legged frog (Rana muscosa). This once-common species...

Using Multigroup Confirmatory Factor Analysis to Test Measurement Invariance in Raters: A Clinical Skills Examination Application

ERIC Educational Resources Information Center

Kahraman, Nilufer; Brown, Crystal B.

2015-01-01

Psychometric models based on structural equation modeling framework are commonly used in many multiple-choice test settings to assess measurement invariance of test items across examinee subpopulations. The premise of the current article is that they may also be useful in the context of performance assessment tests to test measurement invariance…

Bifactor latent structure of attention-deficit/hyperactivity disorder (ADHD)/oppositional defiant disorder (ODD) symptoms and first-order latent structure of sluggish cognitive tempo symptoms.

PubMed

Lee, SoYean; Burns, G Leonard; Beauchaine, Theodore P; Becker, Stephen P

2016-08-01

The objective was to determine if the latent structure of attention-deficit/hyperactivity disorder (ADHD) and oppositional defiant disorder (ODD) symptoms is best explained by a general disruptive behavior factor along with specific inattention (IN), hyperactivity/impulsivity (HI), and ODD factors (a bifactor model) whereas the latent structure of sluggish cognitive tempo (SCT) symptoms is best explained by a first-order factor independent of the bifactor model of ADHD/ODD. Parents' (n = 703) and teachers' (n = 366) ratings of SCT, ADHD-IN, ADHD-HI, and ODD symptoms on the Child and Adolescent Disruptive Behavior Inventory (CADBI) in a community sample of children (ages 5-13; 55% girls) were used to evaluate 4 models of symptom organization. Results indicated that a bifactor model of ADHD/ODD symptoms, in conjunction with a separate first-order SCT factor, was the best model for both parent and teacher ratings. The first-order SCT factor showed discriminant validity with the general disruptive behavior and specific IN factors in the bifactor model. In addition, higher scores on the SCT factor predicted greater academic and social impairment, even after controlling for the general disruptive behavior and 3 specific factors. Consistent with predictions from the trait-impulsivity etiological model of externalizing liability, a single, general disruptive behavior factor accounted for nearly all common variance in ADHD/ODD symptoms, whereas SCT symptoms represented a factor different from the general disruptive behavior and specific IN factor. These results provide additional support for distinguishing between SCT and ADHD-IN. The study also demonstrates how etiological models can be used to predict specific latent structures of symptom organization. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

Structural equation modeling in environmental risk assessment.

PubMed

Buncher, C R; Succop, P A; Dietrich, K N

1991-01-01

Environmental epidemiology requires effective models that take individual observations of environmental factors and connect them into meaningful patterns. Single-factor relationships have given way to multivariable analyses; simple additive models have been augmented by multiplicative (logistic) models. Each of these steps has produced greater enlightenment and understanding. Models that allow for factors causing outputs that can affect later outputs with putative causation working at several different time points (e.g., linkage) are not commonly used in the environmental literature. Structural equation models are a class of covariance structure models that have been used extensively in economics/business and social science but are still little used in the realm of biostatistics. Path analysis in genetic studies is one simplified form of this class of models. We have been using these models in a study of the health and development of infants who have been exposed to lead in utero and in the postnatal home environment. These models require as input the directionality of the relationship and then produce fitted models for multiple inputs causing each factor and the opportunity to have outputs serve as input variables into the next phase of the simultaneously fitted model. Some examples of these models from our research are presented to increase familiarity with this class of models. Use of these models can provide insight into the effect of changing an environmental factor when assessing risk. The usual cautions concerning believing a model, believing causation has been proven, and the assumptions that are required for each model are operative.

Bluetongue virus spread in Europe is a consequence of climatic, landscape and vertebrate host factors as revealed by phylogeographic inference

PubMed Central

Palmarini, Massimo; Mertens, Peter

2017-01-01

Spatio-temporal patterns of the spread of infectious diseases are commonly driven by environmental and ecological factors. This is particularly true for vector-borne diseases because vector populations can be strongly affected by host distribution as well as by climatic and landscape variables. Here, we aim to identify environmental drivers for bluetongue virus (BTV), the causative agent of a major vector-borne disease of ruminants that has emerged multiple times in Europe in recent decades. In order to determine the importance of climatic, landscape and host-related factors affecting BTV diffusion across Europe, we fitted different phylogeographic models to a dataset of 113 time-stamped and geo-referenced BTV genomes, representing multiple strains and serotypes. Diffusion models using continuous space revealed that terrestrial habitat below 300 m altitude, wind direction and higher livestock densities were associated with faster BTV movement. Results of discrete phylogeographic analysis involving generalized linear models broadly supported these findings, but varied considerably with the level of spatial partitioning. Contrary to common perception, we found no evidence for average temperature having a positive effect on BTV diffusion, though both methodological and biological reasons could be responsible for this result. Our study provides important insights into the drivers of BTV transmission at the landscape scale that could inform predictive models of viral spread and have implications for designing control strategies. PMID:29021180

Beyond Negative Affectivity: A Hierarchical Model of Global and Transdiagnostic Vulnerabilities for Emotional Disorders.

PubMed

Paulus, Daniel J; Talkovsky, Alexander M; Heggeness, Luke F; Norton, Peter J

2015-01-01

Negative affectivity (NA) has been linked to anxiety and depression (DEP). Identifying the common factors between anxiety and DEP is important when explaining their overlap and comorbidity. However, general factors such as NA tend to have differential relationships with different disorders, suggesting the need to identify mediators in order to explicate these relationships. The current study tests a theoretically and empirically derived hierarchical model of emotional disorders including both a general factor (NA) and transdiagnostic risk factors [anxiety sensitivity (AS) and intolerance of uncertainty (IoU)] using structural equation modeling. AS was tested as a mid-level factor between NA and panic disorder/agoraphobia, while IoU was tested as a mid-level factor between NA and social phobia, generalized anxiety disorder, obsessive-compulsive disorder, and DEP. Data from 642 clinical outpatients with a heterogeneous presentation of emotional disorders were available for analysis. The hierarchical model fits the data adequately. Moreover, while a simplified model removing AS and IoU fits the data well, it resulted in a significant loss of information for all latent disorder constructs. Data were unavailable to estimate post-traumatic stress disorder or specific phobias. Future work will need to extend to other emotional disorders. This study demonstrates the importance of both general factors that link disorders together and semi-specific transdiagnostic factors partially explaining their heterogeneity. Including these mid-level factors in hierarchical models of psychopathology can help account for additional variance and help to clarify the relationship between disorder constructs and NA.

Crowding Out in an Integrated World Capital Market

DTIC Science & Technology

1993-06-16

some authors to conclude that the idea of Ricardian equivalence should be resurrected. The results of the models equating investment demand to desired...investment is ultimately manifested. How interest rates are affected by deficits and other factors, such as real money supply, is where the models ...the ISLM model is either accurate or appropriate, it is the one which is most commonly used by journalists, politicians, business people and

Evidence for the Trait-Impulsivity Etiological Model in a Clinical Sample: Bifactor Structure and Its Relation to Impairment and Environmental Risk.

PubMed

Rodenacker, Klaas; Hautmann, Christopher; Görtz-Dorten, Anja; Döpfner, Manfred

2018-05-01

The trait-impulsivity etiological model assumes that a general factor (trait-impulsivity) underlies attention-deficit/hyperactivity disorder (ADHD), oppositional defiant disorder (ODD), and other externalizing disorders. We investigated the plausibility of this assumption by testing the factor structure of ADHD and ODD in a bifactor framework for a clinical sample of 1420 children between 6 and 18 years of age (M = 9.99, SD = 3.34; 85% male). Further, the trait-impulsivity etiological model assumes that ODD emerges only if environmental risk factors are present. Our results support the validity of the trait-impulsivity etiological model, as they confirm that ADHD and ODD share a strong general factor of disruptive behavior (DB) in this clinical sample. Furthermore, unlike the subdimensions of ADHD, we found that the specific ODD factor explained as much true score variance as the general DB factor. This suggests that a common scale of ADHD and ODD may prove to be as important as a separate ODD subscale to assess externalizing problems in school-age children. However, all other subscales of ADHD may not explain sufficient true score variance once the impact of the general DB factor has been taken into consideration. In accordance with the trait-impulsivity model, we also showed that all factors, but predominantly the general factor and specific inattention factor, predicted parent-rated impairment, and that predominantly ODD and impulsivity are predicted by environmental risk factors.

Solar energy market penetration models - Science or number mysticism

NASA Technical Reports Server (NTRS)

Warren, E. H., Jr.

1980-01-01

The forecast market potential of a solar technology is an important factor determining its R&D funding. Since solar energy market penetration models are the method used to forecast market potential, they have a pivotal role in a solar technology's development. This paper critiques the applicability of the most common solar energy market penetration models. It is argued that the assumptions underlying the foundations of rigorously developed models, or the absence of a reasonable foundation for the remaining models, restrict their applicability.

The Factor Structure of the Aggression Questionnaire With Violent Offenders.

PubMed

Pettersen, Cathrine; Nunes, Kevin L; Cortoni, Franca

2018-05-01

The Buss-Perry Aggression Questionnaire (AQ) is a self-report measure of aggressiveness commonly employed in nonforensic and forensic settings and is included in violent offender pre- and posttreatment assessment batteries. The aim of the current study was to assess the fit of the four-factor model of the AQ with violent offenders ( N = 271), a population for which the factor structure of the English version of the AQ has not previously been examined. Confirmatory factor analyses did not yield support for the four-factor model of the original 29-item AQ. Acceptable fit was obtained with the 12-item short form, but careful examination of the relationships between the latent factors revealed that the four subscales of the AQ may not represent distinct aspects of aggressiveness. Our findings call into question whether the AQ optimally measures trait aggressiveness among violent offenders.

A Systematic Review of the Factors Influencing Ethnic Minority Women's Cervical Cancer Screening Behavior: From Intrapersonal to Policy Level.

PubMed

Chan, Dorothy N S; So, Winnie K W

Cervical cancer can be prevented by effective screening using Papanicolaou tests, but the utilization rate is lower among ethnic minorities than in the general population. Understanding the factors influencing minorities' use of such screening can aid the design of an appropriate intervention to increase their uptake rate. The aims of this study were to examine the factors that influence ethnic minority women in using cervical cancer screening and the similarities and differences in associated factors across different groups and to explore the interrelationships between the factors identified. A literature search was conducted using Ovid MEDLINE, Cumulative Index to Nursing and Allied Health Literature Plus, Scopus, PsycINFO, and PubMed. Furthermore, 1390 articles were retrieved, of which 24 met the inclusion criteria. Critical appraisal was performed by means of a quality assessment tool. The findings were summarized in tabular and narrative forms. The findings showed that certain factors commonly affected ethnic minority women's screening behavior, including knowledge, attitude and perceptions, physician's recommendation, quality of care and service, language, and acculturation. Culture-related factors, religion, and acculturation exhibited close interrelationships with the attitude and perceptions factor, resulting in behavioral change. The review sheds light on how common or unique are the factors across ethnic minorities and how these factors interact to influence behavior. Further studies are warranted to develop and test empirically a comprehensive model leading to a better understanding of the interrelationships between multiple factors. The model should be useful in informing policy makers about appropriate resource allocation and in guiding the development of culturally relevant programs to increase screening uptake.

Study on characteristics of the aperture-averaging factor of atmospheric scintillation in terrestrial optical wireless communication

NASA Astrophysics Data System (ADS)

Shen, Hong; Liu, Wen-xing; Zhou, Xue-yun; Zhou, Li-ling; Yu, Long-Kun

2018-02-01

In order to thoroughly understand the characteristics of the aperture-averaging effect of atmospheric scintillation in terrestrial optical wireless communication and provide references for engineering design and performance evaluation of the optics system employed in the atmosphere, we have theoretically deduced the generally analytic expression of the aperture-averaging factor of atmospheric scintillation, and numerically investigated characteristics of the apertureaveraging factor under different propagation conditions. The limitations of the current commonly used approximate calculation formula of aperture-averaging factor have been discussed, and the results showed that the current calculation formula is not applicable for the small receiving aperture under non-uniform turbulence link. Numerical calculation has showed that aperture-averaging factor of atmospheric scintillation presented an exponential decline model for the small receiving aperture under non-uniform turbulent link, and the general expression of the model was given. This model has certain guiding significance for evaluating the aperture-averaging effect in the terrestrial optical wireless communication.

Functional and structural insights into novel DREB1A transcription factors in common wheat (Triticum aestivum L.): A molecular modeling approach.

PubMed

Kumar, Anuj; Kumar, Sanjay; Kumar, Upendra; Suravajhala, Prashanth; Gajula, M N V Prasad

2016-10-01

Triticum aestivum L. known as common wheat is one of the most important cereal crops feeding a large and growing population. Various environmental stress factors including drought, high salinity and heat etc. adversely affect wheat production in a significant manner. Dehydration-responsive element-binding (DREB1A) factors, a class of transcription factors (TF) play an important role in combating drought stress. It is known that DREB1A specifically interacts with the dehydration responsive elements (DRE/CRT) inducing expression of genes involved in environmental stress tolerance in plants. Despite its critical interplay in plants, the structural and functional aspects of DREB1A TF in wheat remain unresolved. Previous studies showed that wheat DREBs (DREB1 and DREB2) were isolated using various methods including yeast two-hybrid screens but no extensive structural models were reported. In this study, we made an extensive in silico study to gain insight into DREB1A TF and reported the location of novel DREB1A in wheat chromosomes. We inferred the three-dimensional structural model of DREB1A using homology modelling and further evaluated them using molecular dynamics(MD) simulations yielding refined modelled structures. Our biochemical function predictions suggested that the wheat DREB1A orthologs have similar biochemical functions and pathways to that of AtDREB1A. In conclusion, the current study presents a structural perspective of wheat DREB1A and helps in understanding the molecular basis for the mechanism of DREB1A in response to environmental stress. Copyright © 2016 Elsevier Ltd. All rights reserved.

Plants as models for the study of human pathogenesis.

PubMed

Guttman, David S

2004-05-01

There are many common disease mechanisms used by bacterial pathogens of plants and humans. They use common means of attachment, secretion and genetic regulation. They share many virulence factors, such as extracellular polysaccharides and some type III secreted effectors. Plant and human innate immune systems also share many similarities. Many of these shared bacterial virulence mechanisms are homologous, but even more appear to have independently converged on a common function. This combination of homologous and analogous systems reveals conserved and critical steps in the disease process. Given these similarities, and the many experimental advantages of plant biology, including ease of replication, stringent genetic and reproductive control, and high throughput with low cost, it is proposed that plants would make excellent models for the study of human pathogenesis.

Bifactor Modeling of the Positive and Negative Syndrome Scale: Generalized Psychosis Spans Schizoaffective, Bipolar, and Schizophrenia Diagnoses.

PubMed

Anderson, Ariana E; Marder, Stephen; Reise, Steven P; Savitz, Adam; Salvadore, Giacomo; Fu, Dong Jing; Li, Qingqin; Turkoz, Ibrahim; Han, Carol; Bilder, Robert M

2018-02-06

Common genetic variation spans schizophrenia, schizoaffective and bipolar disorders, but historically, these syndromes have been distinguished categorically. A symptom dimension shared across these syndromes, if such a general factor exists, might provide a clearer target for understanding and treating mental illnesses that share core biological bases. We tested the hypothesis that a bifactor model of the Positive and Negative Syndrome Scale (PANSS), containing 1 general factor and 5 specific factors (positive, negative, disorganized, excited, anxiety), explains the cross-diagnostic structure of symptoms better than the traditional 5-factor model, and examined the extent to which a general factor reflects the overall severity of symptoms spanning diagnoses in 5094 total patients with a diagnosis of schizophrenia, schizoaffective, and bipolar disorder. The bifactor model provided superior fit across diagnoses, and was closer to the "true" model, compared to the traditional 5-factor model (Vuong test; P < .001). The general factor included high loadings on 28 of the 30 PANSS items, omitting symptoms associated with the excitement and anxiety/depression domains. The general factor had highest total loadings on symptoms that are often associated with the positive and disorganization syndromes, but there were also substantial loadings on the negative syndrome thus leading to the interpretation of this factor as reflecting generalized psychosis. A bifactor model derived from the PANSS can provide a stronger framework for measuring cross-diagnostic psychopathology than a 5-factor model, and includes a generalized psychosis dimension shared at least across schizophrenia, schizoaffective, and bipolar disorder. © The Author(s) 2018. Published by Oxford University Press on behalf of the Maryland Psychiatric Research Center. All rights reserved. For permissions, please email: journals.permissions@oup.com

Tailored Testing Theory and Practice: A Basic Model, Normal Ogive Submodels, and Tailored Testing Algorithms

DTIC Science & Technology

1983-08-01

ACCESSION NO «• TITLE (and Sublltle) TAILORED TESTING THEORY AND PRACTICE: A BASIC MODEL , NORMAL OGIVE SUBMODELS, AND TAILORED TESTING ALGORITHMS 7...single common-factor model , the author derives the two- and three-parametir normal ogfve il’^irTr^ functions as submodels. For both of these...PAOEfWiwi Dmia Bnfnd) NPRDC TR 83-32 AUGUST 1983 TAILORED TESTING THEORY AND PRACTICE: A BASIC MODEL , NORMAL OGIVE SUBMODELS, AND TAILORED TESTING

Carotid intima media thickness and plaques can predict the occurrence of ischemic cerebrovascular events.

PubMed

Prati, Patrizio; Tosetto, Alberto; Vanuzzo, Diego; Bader, Giovanni; Casaroli, Marco; Canciani, Luigi; Castellani, Sergio; Touboul, Pierre-Jean

2008-09-01

The clinical usefulness of noninvasive measurement of carotid intima media thickness and plaque visualization in the general population is still uncertain. We evaluated the age-specific incidence rates of cerebrovascular events in a cohort of 1348 subjects randomly taken from the census list of San Daniele Township and followed for a mean period of 12.7 years. The association among common carotid intima media thickness, measured at baseline, arterial risk factors, and incidence of ischemic cerebrovascular events was modeled using Poisson regression. The predictive ability of common carotid intima media thickness over arterial risk factors (summarized in the Framingham Stroke Risk Score) was evaluated by receiver operating characteristic curve analysis. During the follow-up, 115 subjects developed nonfatal ischemic stroke, transient ischemic attack, or vascular death, which were the predefined study end points. After adjustment for age and sex, hypertension, diabetes, common carotid intima media thickness above 1 mm, and carotid plaques were all independent risk factors for development of vascular events. Inclusion of carotid findings (presence of common carotid intima media thickness above 1 mm or carotid plaques) resulted in a predictive power higher than Framingham Stroke Risk Score alone only on for those subjects with a Framingham Stroke Risk Score over 20%. Although common carotid intima media thickness and presence of carotid plaques are known to be risk factors for the development of vascular events and to be independent from the conventional risk factors summarized in the Framingham Stroke Risk Score, their contribution to individual risk prediction is limited. Further studies will be required to address the role of carotid ultrasonography in the primary prevention of high-risk subjects.

A Basic Bivariate Structure of Personality Attributes Evident Across Nine Languages.

PubMed

Saucier, Gerard; Thalmayer, Amber Gayle; Payne, Doris L; Carlson, Robert; Sanogo, Lamine; Ole-Kotikash, Leonard; Church, A Timothy; Katigbak, Marcia S; Somer, Oya; Szarota, Piotr; Szirmák, Zsofia; Zhou, Xinyue

2014-02-01

Here, two studies seek to characterize a parsimonious common-denominator personality structure with optimal cross-cultural replicability. Personality differences are observed in all human populations and cultures, but lexicons for personality attributes contain so many distinctions that parsimony is lacking. Models stipulating the most important attributes have been formulated by experts or by empirical studies drawing on experience in a very limited range of cultures. Factor analyses of personality lexicons of nine languages of diverse provenance (Chinese, Korean, Filipino, Turkish, Greek, Polish, Hungarian, Maasai, and Senoufo) were examined, and their common structure was compared to that of several prominent models in psychology. A parsimonious bivariate model showed evidence of substantial convergence and ubiquity across cultures. Analyses involving key markers of these dimensions in English indicate that they are broad dimensions involving the overlapping content of the interpersonal circumplex, models of communion and agency, and morality/warmth and competence. These "Big Two" dimensions-Social Self-Regulation and Dynamism-provide a common-denominator model involving the two most crucial axes of personality variation, ubiquitous across cultures. The Big Two might serve as an umbrella model serving to link diverse theoretical models and associated research literatures. © 2013 Wiley Periodicals, Inc.

Development and validation of a prediction algorithm for the onset of common mental disorders in a working population.

PubMed

Fernandez, Ana; Salvador-Carulla, Luis; Choi, Isabella; Calvo, Rafael; Harvey, Samuel B; Glozier, Nicholas

2018-01-01

Common mental disorders are the most common reason for long-term sickness absence in most developed countries. Prediction algorithms for the onset of common mental disorders may help target indicated work-based prevention interventions. We aimed to develop and validate a risk algorithm to predict the onset of common mental disorders at 12 months in a working population. We conducted a secondary analysis of the Household, Income and Labour Dynamics in Australia Survey, a longitudinal, nationally representative household panel in Australia. Data from the 6189 working participants who did not meet the criteria for a common mental disorders at baseline were non-randomly split into training and validation databases, based on state of residence. Common mental disorders were assessed with the mental component score of 36-Item Short Form Health Survey questionnaire (score ⩽45). Risk algorithms were constructed following recommendations made by the Transparent Reporting of a multivariable prediction model for Prevention Or Diagnosis statement. Different risk factors were identified among women and men for the final risk algorithms. In the training data, the model for women had a C-index of 0.73 and effect size (Hedges' g) of 0.91. In men, the C-index was 0.76 and the effect size was 1.06. In the validation data, the C-index was 0.66 for women and 0.73 for men, with positive predictive values of 0.28 and 0.26, respectively Conclusion: It is possible to develop an algorithm with good discrimination for the onset identifying overall and modifiable risks of common mental disorders among working men. Such models have the potential to change the way that prevention of common mental disorders at the workplace is conducted, but different models may be required for women.

An investigation of PTSD's core dimensions and relations with anxiety and depression.

PubMed

Byllesby, Brianna M; Durham, Tory A; Forbes, David; Armour, Cherie; Elhai, Jon D

2016-03-01

Posttraumatic stress disorder (PTSD) is highly comorbid with anxiety and depressive disorders, which is suggestive of shared variance or common underlying dimensions. The purpose of the present study was to examine the relationship between the latent factors of PTSD with the constructs of anxiety and depression in order to increase understanding of the co-occurrence of these disorders. Data were collected from a nonclinical sample of 186 trauma-exposed participants using the PTSD Checklist and Hospital Anxiety and Depression Scale. Confirmatory factor analyses were conducted to determine model fit comparing 3 PTSD factor structure models, followed by Wald tests comparing the relationships between PTSD factors and the core dimensions of anxiety and depression. In model comparisons, the 5-factor dysphoric arousal model of PTSD provided the best fit for the data, compared to the emotional numbing and dysphoria models of PTSD. Compared to anxious arousal, the dysphoric arousal and numbing factors of PTSD were more related to depression severity. Numbing, anxious arousal, and dysphoric arousal were not differentially related to the latent anxiety factor. The underlying factors of PTSD contain aspects of the core dimensions of both anxiety and depression. The heterogeneity of PTSD's associations with anxiety and depressive constructs requires additional empirical exploration because clarification regarding these relationships will impact diagnostic classification as well as clinical practice. (c) 2016 APA, all rights reserved).

The Structure of Personality Disorders in Individuals with Posttraumatic Stress Disorder

PubMed Central

Wolf, Erika J.; Miller, Mark W.; Brown, Timothy A.

2015-01-01

Research on the structure of personality disorders (PDs) has relied primarily on exploratory analyses to evaluate trait-based models of the factors underlying the covariation of these disorders. This study used confirmatory factor analysis to evaluate whether a model that included both PD traits and a general personality dysfunction factor would account for the comorbidity of the PDs better than a trait-only model. It also examined if the internalizing/externalizing model of psychopathology, developed previously through research on the structure of Axis I disorders, might similarly account for the covariation of the Axis II disorders in a sample of 245 veterans and non-veterans with posttraumatic stress disorder. Results indicated that the best fitting model was a modified bifactor structure composed of nine lower-order common factors. These factors indexed pathology ranging from aggression to dependency, with the correlations among them accounted for by higher-order Internalizing and Externalizing factors. Further, a general factor, reflecting a construct that we termed boundary disturbance, accounted for additional variance and covariance across nearly all the indicators. The Internalizing, Externalizing, and Boundary Disturbance factors evidenced differential associations with trauma-related covariates. These findings suggest continuity in the underlying structure of psychopathology across DSM-IV Axes I & II and provide empirical evidence of a pervasive, core disturbance in the boundary between self and other across the PDs. PMID:22448802

Construct validity of the Wechsler Intelligence Scale for Children - Fourth UK Edition with a referred Irish sample: Wechsler and Cattell-Horn-Carroll model comparisons with 15 subtests.

PubMed

Canivez, Gary L; Watkins, Marley W; Good, Rebecca; James, Kate; James, Trevor

2017-09-01

Irish educational psychologists frequently use the Wechsler Intelligence Scale for Children - Fourth UK Edition (WISC-IV UK ; Wechsler, 2004, Wechsler Intelligence Scale for Children-Fourth UK Edition, London, UK, Harcourt Assessment) in clinical assessments of children with learning difficulties. Unfortunately, reliability and validity studies of the WISC-IV UK standardization sample have not yet been reported. Watkins et al. (2013, International Journal of School and Educational Psychology, 1, 102) found support for a bifactor structure with a large sample (N = 794) of Irish children who were administered the 10 WISC-IV UK core subtests in clinical assessments of learning difficulties and dominance of general intelligence. Because only 10 subtests were available, Cattell-Horn-Carroll (CHC; McGrew, 1997, 2005, Contemporary intellectual assessment: Theories, tests, and issues, New York, NY: Guilford; Schneider & McGrew, 2012, Contemporary intellectual assessment: Theories, tests, and issues, New York, NY, Guilford Press) models could not be tested and compared. The present study utilized confirmatory factor analyses to test the latent factor structure of the WISC-IV UK with a sample of 245 Irish children administered all 15 WISC-IV UK subtests in evaluations assessing learning difficulties in order to examine CHC- and Wechsler-based models. One through five, oblique first-order factor models and higher order versus bifactor models were examined and compared using CFA. Meaningful differences in fit statistics were not observed between the Wechsler and CHC representations of higher-order or bifactor models. In all four structures, general intelligence accounted for the largest portions of explained common variance, whereas group factors accounted for small to miniscule portions of explained common variance. Omega-hierarchical subscale coefficients indicated that unit-weighted composites that would be generated by WISC-IV UK group factors (Wechsler or CHC) would contain little unique variance and thus be of little value. These results were similar to those from other investigations, further demonstrating the replication of the WISC-IV factor structure across cultures and the importance of focusing primary interpretation on the FSIQ. © 2017 The British Psychological Society.

A Bottom-Up Approach to Understanding Protein Layer Formation at Solid-Liquid Interfaces

PubMed Central

Kastantin, Mark; Langdon, Blake B.; Schwartz, Daniel K.

2014-01-01

A common goal across different fields (e.g. separations, biosensors, biomaterials, pharmaceuticals) is to understand how protein behavior at solid-liquid interfaces is affected by environmental conditions. Temperature, pH, ionic strength, and the chemical and physical properties of the solid surface, among many factors, can control microscopic protein dynamics (e.g. adsorption, desorption, diffusion, aggregation) that contribute to macroscopic properties like time-dependent total protein surface coverage and protein structure. These relationships are typically studied through a top-down approach in which macroscopic observations are explained using analytical models that are based upon reasonable, but not universally true, simplifying assumptions about microscopic protein dynamics. Conclusions connecting microscopic dynamics to environmental factors can be heavily biased by potentially incorrect assumptions. In contrast, more complicated models avoid several of the common assumptions but require many parameters that have overlapping effects on predictions of macroscopic, average protein properties. Consequently, these models are poorly suited for the top-down approach. Because the sophistication incorporated into these models may ultimately prove essential to understanding interfacial protein behavior, this article proposes a bottom-up approach in which direct observations of microscopic protein dynamics specify parameters in complicated models, which then generate macroscopic predictions to compare with experiment. In this framework, single-molecule tracking has proven capable of making direct measurements of microscopic protein dynamics, but must be complemented by modeling to combine and extrapolate many independent microscopic observations to the macro-scale. The bottom-up approach is expected to better connect environmental factors to macroscopic protein behavior, thereby guiding rational choices that promote desirable protein behaviors. PMID:24484895

Overall Preference of Running Shoes Can Be Predicted by Suitable Perception Factors Using a Multiple Regression Model.

PubMed

Tay, Cheryl Sihui; Sterzing, Thorsten; Lim, Chen Yen; Ding, Rui; Kong, Pui Wah

2017-05-01

This study examined (a) the strength of four individual footwear perception factors to influence the overall preference of running shoes and (b) whether these perception factors satisfied the nonmulticollinear assumption in a regression model. Running footwear must fulfill multiple functional criteria to satisfy its potential users. Footwear perception factors, such as fit and cushioning, are commonly used to guide shoe design and development, but it is unclear whether running-footwear users are able to differentiate one factor from another. One hundred casual runners assessed four running shoes on a 15-cm visual analogue scale for four footwear perception factors (fit, cushioning, arch support, and stability) as well as for overall preference during a treadmill running protocol. Diagnostic tests showed an absence of multicollinearity between factors, where values for tolerance ranged from .36 to .72, corresponding to variance inflation factors of 2.8 to 1.4. The multiple regression model of these four footwear perception variables accounted for 77.7% to 81.6% of variance in overall preference, with each factor explaining a unique part of the total variance. Casual runners were able to rate each footwear perception factor separately, thus assigning each factor a true potential to improve overall preference for the users. The results also support the use of a multiple regression model of footwear perception factors to predict overall running shoe preference. Regression modeling is a useful tool for running-shoe manufacturers to more precisely evaluate how individual factors contribute to the subjective assessment of running footwear.

An investigation of the factor structure of the beck depression inventory-II in anorexia nervosa.

PubMed

Fuss, Samantha; Trottier, Kathryn; Carter, Jacqueline

2015-01-01

Symptoms of depression frequently co-occur with eating disorders and have been associated with negative outcomes. Self-report measures such as the Beck Depression Inventory-II (BDI-II) are commonly used to assess for the presence of depressive symptoms in eating disorders, but the instrument's factor structure in this population has not been examined. The purposes of this study were to explore the factor structure of the BDI-II in a sample of individuals (N = 437) with anorexia nervosa undergoing inpatient treatment and to examine changes in depressive symptoms on each of the identified factors following a course of treatment for anorexia nervosa in order to provide evidence supporting the construct validity of the measure. Exploratory factor analysis revealed that a three-factor model reflected the best fit for the data. Confirmatory factor analysis was used to validate this model against competing models and the three-factor model exhibited strong model fit characteristics. BDI-II scores were significantly reduced on all three factors following inpatient treatment, which supported the construct validity of the scale. The BDI-II appears to be reliable in this population, and the factor structure identified through this analysis may offer predictive utility for identifying individuals who may have more difficulty achieving weight restoration in the context of inpatient treatment. Copyright © 2014 John Wiley & Sons, Ltd and Eating Disorders Association. Copyright © 2014 John Wiley & Sons, Ltd and Eating Disorders Association.

Multiple factors affect a population of Agassiz's desert tortoise (Gopherus agassizii) in the Northwestern Mojave Desert

USGS Publications Warehouse

Berry, Kristin H.; Yee, Julie L.; Coble, Ashley A.; Perry, William M.; Shields, Timothy A.

2013-01-01

Numerous factors have contributed to declines in populations of the federally threatened Agassiz's Desert Tortoise (Gopherus agassizii) and continue to limit recovery. In 2010, we surveyed a low-density population on a military test facility in the northwestern Mojave Desert of California, USA, to evaluate population status and identify potential factors contributing to distribution and low densities. Estimated densities of live tortoises ranged spatially from 1.2/km2 to 15.1/km2. Although only one death of a breeding-age tortoise was recorded for the 4-yr period prior to the survey, remains of 16 juvenile and immature tortoises were found, and most showed signs of predation by Common Ravens (Corvus corax) and mammals. Predation may have limited recruitment of young tortoises into the adult size classes. To evaluate the relative importance of different types of impacts to tortoises, we developed predictive models for spatially explicit densities of tortoise sign and live tortoises using topography (i.e., slope), predators (Common Raven, signs of mammalian predators), and anthropogenic impacts (distances from paved road and denuded areas, density of ordnance fragments) as covariates. Models suggest that densities of tortoise sign increased with slope and signs of mammalian predators and decreased with Common Ravens, while also varying based on interaction effects involving these predictors as well as distances from paved roads, denuded areas, and ordnance. Similarly, densities of live tortoises varied by interaction effects among distances to denuded areas and paved roads, density of ordnance fragments, and slope. Thus multiple factors predict the densities and distribution of this population.

Cumulative impact of common genetic variants and other risk factors on colorectal cancer risk in 42,103 individuals

PubMed Central

Dunlop, Malcolm G.; Tenesa, Albert; Farrington, Susan M.; Ballereau, Stephane; Brewster, David H.; Pharoah, Paul DP.; Schafmayer, Clemens; Hampe, Jochen; Völzke, Henry; Chang-Claude, Jenny; Hoffmeister, Michael; Brenner, Hermann; von Holst, Susanna; Picelli, Simone; Lindblom, Annika; Jenkins, Mark A.; Hopper, John L.; Casey, Graham; Duggan, David; Newcomb, Polly; Abulí, Anna; Bessa, Xavier; Ruiz-Ponte, Clara; Castellví-Bel, Sergi; Niittymäki, Iina; Tuupanen, Sari; Karhu, Auli; Aaltonen, Lauri; Zanke, Brent W.; Hudson, Thomas J.; Gallinger, Steven; Barclay, Ella; Martin, Lynn; Gorman, Maggie; Carvajal-Carmona, Luis; Walther, Axel; Kerr, David; Lubbe, Steven; Broderick, Peter; Chandler, Ian; Pittman, Alan; Penegar, Steven; Campbell, Harry; Tomlinson, Ian; Houlston, Richard S.

2016-01-01

Objective Colorectal cancer (CRC) has a substantial heritable component. Common genetic variation has been shown to contribute to CRC risk. In a large, multi-population study, we set out to assess the feasibility of CRC risk prediction using common genetic variant data, combined with other risk factors. We built a risk prediction model and applied it to the Scottish population using available data. Design Nine populations of European descent were studied to develop and validate colorectal cancer risk prediction models. Binary logistic regression was used to assess the combined effect of age, gender, family history (FH) and genotypes at 10 susceptibility loci that individually only modestly influence colorectal cancer risk. Risk models were generated from case-control data incorporating genotypes alone (n=39,266), and in combination with gender, age and family history (n=11,324). Model discriminatory performance was assessed using 10-fold internal cross-validation and externally using 4,187 independent samples. 10-year absolute risk was estimated by modelling genotype and FH with age- and gender-specific population risks. Results Median number of risk alleles was greater in cases than controls (10 vs 9, p<2.2×10−16), confirmed in external validation sets (Sweden p=1.2×10−6, Finland p=2×10−5). Mean per-allele increase in risk was 9% (OR 1.09; 95% CI 1.05–1.13). Discriminative performance was poor across the risk spectrum (area under curve (AUC) for genotypes alone - 0.57; AUC for genotype/age/gender/FH - 0.59). However, modelling genotype data, FH, age and gender with Scottish population data shows the practicalities of identifying a subgroup with >5% predicted 10-year absolute risk. Conclusion We show that genotype data provides additional information that complements age, gender and FH as risk factors. However, individualized genetic risk prediction is not currently feasible. Nonetheless, the modelling exercise suggests public health potential, since it is possible to stratify the population into CRC risk categories, thereby informing targeted prevention and surveillance. PMID:22490517

The structure of common emotion regulation strategies: A meta-analytic examination.

PubMed

Naragon-Gainey, Kristin; McMahon, Tierney P; Chacko, Thomas P

2017-04-01

Emotion regulation has been examined extensively with regard to important outcomes, including psychological and physical health. However, the literature includes many different emotion regulation strategies but little examination of how they relate to one another, making it difficult to interpret and synthesize findings. The goal of this meta-analysis was to examine the underlying structure of common emotion regulation strategies (i.e., acceptance, behavioral avoidance, distraction, experiential avoidance, expressive suppression, mindfulness, problem solving, reappraisal, rumination, worry), and to evaluate this structure in light of theoretical models of emotion regulation. We also examined how distress tolerance-an important emotion regulation ability -relates to strategy use. We conducted meta-analyses estimating the correlations between emotion regulation strategies (based on 331 samples and 670 effect sizes), as well as between distress tolerance and strategies. The resulting meta-analytic correlation matrix was submitted to confirmatory and exploratory factor analyses. None of the confirmatory models, based on prior theory, was an acceptable fit to the data. Exploratory factor analysis suggested that 3 underlying factors best characterized these data. Two factors-labeled Disengagement and Aversive Cognitive Perseveration-emerged as strongly correlated but distinct factors, with the latter consisting of putatively maladaptive strategies. The third factor, Adaptive Engagement, was a less unified factor and weakly related to the other 2 factors. Distress tolerance was most closely associated with low levels of repetitive negative thought and experiential avoidance, and high levels of acceptance and mindfulness. We discuss the theoretical implications of these findings and applications to emotion regulation assessment. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

Heritability of the Number of Teeth in Middle-Aged and Older Danish Twins.

PubMed

Kurushima, Y; Silventoinen, K; Dokkedal, U; Skytthe, A; Mucci, L A; Christensen, K; Hjelmborg, J V B

2017-12-01

Tooth loss is a common health concern in older adults. We aimed to estimate the relative contributions of genetic and environmental factors to the variation in the number of teeth in middle-aged and older populations using a population-based cohort of Danish twins. The study included 5,269 Danish middle-aged or older twins who provided data on the number of teeth at baseline by structured interviews. The data were analyzed using univariate liability threshold modeling, stratified by sex and age, to estimate familial risk of tooth loss as well as estimates of heritability. In the whole cohorts, 23% of participants were edentate and 53% had retained 20 or more teeth. A statistical model including additive genetic factors and environmental factors partly shared by co-twins and partly unique to each individual twin gave the best statistical fit for the number of teeth in both age categories as well as in men and women. Overall, additive genetic factors explained 36% (95% confidence interval [CI]: 23% to 49%), common environmental factors 20% (95% CI: 9% to 31%), and unique environmental factors 44% (95% CI: 40% to 48%) of the total variation of the number of teeth. This study indicates that a substantial part of the variation in tooth loss is explained by genetic as well as environmental factors shared by co-twins. Our results implied that family background importantly affects tooth loss in both the middle-aged and the older populations. Family history is thus an important factor to take into account in dental health care.

An improved canopy wind model for predicting wind adjustment factors and wildland fire behavior

Treesearch

W. J. Massman; J. M. Forthofer; M. A. Finney

2017-01-01

The ability to rapidly estimate wind speed beneath a forest canopy or near the ground surface in any vegetation is critical to practical wildland fire behavior models. The common metric of this wind speed is the "mid-flame" wind speed, UMF. However, the existing approach for estimating UMF has some significant shortcomings. These include the assumptions that...

A Parent-Child Interactional Model of Social Anxiety Disorder in Youth

ERIC Educational Resources Information Center

Ollendick, Thomas H.; Benoit, Kristy E.

2012-01-01

In this paper, one of the most common disorders of childhood and adolescence, social anxiety disorder (SAD), is examined to illustrate the complex and delicate interplay between parent and child factors that can result in normal development gone awry. Our parent-child model of SAD posits a host of variables that converge to occasion the onset and…

Development of Rail Temperature Prediction Model : Research Results

DOT National Transportation Integrated Search

2008-06-01

Preventing track buckling is important to the railroad industry's goal of operational safety. It is a common practice for railroads to impose slow orders during hot weather when the risk of track buckling is high. Numerous factors affect track buckli...

Prediction versus aetiology: common pitfalls and how to avoid them.

PubMed

van Diepen, Merel; Ramspek, Chava L; Jager, Kitty J; Zoccali, Carmine; Dekker, Friedo W

2017-04-01

Prediction research is a distinct field of epidemiologic research, which should be clearly separated from aetiological research. Both prediction and aetiology make use of multivariable modelling, but the underlying research aim and interpretation of results are very different. Aetiology aims at uncovering the causal effect of a specific risk factor on an outcome, adjusting for confounding factors that are selected based on pre-existing knowledge of causal relations. In contrast, prediction aims at accurately predicting the risk of an outcome using multiple predictors collectively, where the final prediction model is usually based on statistically significant, but not necessarily causal, associations in the data at hand.In both scientific and clinical practice, however, the two are often confused, resulting in poor-quality publications with limited interpretability and applicability. A major problem is the frequently encountered aetiological interpretation of prediction results, where individual variables in a prediction model are attributed causal meaning. This article stresses the differences in use and interpretation of aetiological and prediction studies, and gives examples of common pitfalls. © The Author 2017. Published by Oxford University Press on behalf of ERA-EDTA. All rights reserved.

Effects of natural and human factors on groundwater quality of basin-fill aquifers in the southwestern United States-conceptual models for selected contaminants

USGS Publications Warehouse

Bexfield, Laura M.; Thiros, Susan A.; Anning, David W.; Huntington, Jena M.; McKinney, Tim S.

2011-01-01

As part of the U.S. Geological Survey National Water-Quality Assessment (NAWQA) Program, the Southwest Principal Aquifers (SWPA) study is building a better understanding of the factors that affect water quality in basin-fill aquifers in the Southwestern United States. The SWPA study area includes four principal aquifers of the United States: the Basin and Range basin-fill aquifers in California, Nevada, Utah, and Arizona; the Rio Grande aquifer system in New Mexico and Colorado; and the California Coastal Basin and Central Valley aquifer systems in California. Similarities in the hydrogeology, land- and water-use practices, and water-quality issues for alluvial basins within the study area allow for regional analysis through synthesis of the baseline knowledge of groundwater-quality conditions in basins previously studied by the NAWQA Program. Resulting improvements in the understanding of the sources, movement, and fate of contaminants are assisting in the development of tools used to assess aquifer susceptibility and vulnerability.This report synthesizes previously published information about the groundwater systems and water quality of 15 information-rich basin-fill aquifers (SWPA case-study basins) into conceptual models of the primary natural and human factors commonly affecting groundwater quality with respect to selected contaminants, thereby helping to build a regional understanding of the susceptibility and vulnerability of basin-fill aquifers to those contaminants. Four relatively common contaminants (dissolved solids, nitrate, arsenic, and uranium) and two contaminant classes (volatile organic compounds (VOCs) and pesticide compounds) were investigated for sources and controls affecting their occurrence and distribution above specified levels of concern in groundwater of the case-study basins. Conceptual models of factors that are important to aquifer vulnerability with respect to those contaminants and contaminant classes were subsequently formed. The conceptual models are intended in part to provide a foundation for subsequent development of regional-scale statistical models that relate specific constituent concentrations or occurrence in groundwater to natural and human factors.

Hydrochemical analysis of groundwater using a tree-based model

NASA Astrophysics Data System (ADS)

Litaor, M. Iggy; Brielmann, H.; Reichmann, O.; Shenker, M.

2010-06-01

SummaryHydrochemical indices are commonly used to ascertain aquifer characteristics, salinity problems, anthropogenic inputs and resource management, among others. This study was conducted to test the applicability of a binary decision tree model to aquifer evaluation using hydrochemical indices as input. The main advantage of the tree-based model compared to other commonly used statistical procedures such as cluster and factor analyses is the ability to classify groundwater samples with assigned probability and the reduction of a large data set into a few significant variables without creating new factors. We tested the model using data sets collected from headwater springs of the Jordan River, Israel. The model evaluation consisted of several levels of complexity, from simple separation between the calcium-magnesium-bicarbonate water type of karstic aquifers to the more challenging separation of calcium-sodium-bicarbonate water type flowing through perched and regional basaltic aquifers. In all cases, the model assigned measures for goodness of fit in the form of misclassification errors and singled out the most significant variable in the analysis. The model proceeded through a sequence of partitions providing insight into different possible pathways and changing lithology. The model results were extremely useful in constraining the interpretation of geological heterogeneity and constructing a conceptual flow model for a given aquifer. The tree model clearly identified the hydrochemical indices that were excluded from the analysis, thus providing information that can lead to a decrease in the number of routinely analyzed variables and a significant reduction in laboratory cost.

Indirect estimation of emission factors for phosphate surface mining using air dispersion modeling.

PubMed

Tartakovsky, Dmitry; Stern, Eli; Broday, David M

2016-06-15

To date, phosphate surface mining suffers from lack of reliable emission factors. Due to complete absence of data to derive emissions factors, we developed a methodology for estimating them indirectly by studying a range of possible emission factors for surface phosphate mining operations and comparing AERMOD calculated concentrations to concentrations measured around the mine. We applied this approach for the Khneifiss phosphate mine, Syria, and the Al-Hassa and Al-Abyad phosphate mines, Jordan. The work accounts for numerous model unknowns and parameter uncertainties by applying prudent assumptions concerning the parameter values. Our results suggest that the net mining operations (bulldozing, grading and dragline) contribute rather little to ambient TSP concentrations in comparison to phosphate processing and transport. Based on our results, the common practice of deriving the emission rates for phosphate mining operations from the US EPA emission factors for surface coal mining or from the default emission factor of the EEA seems to be reasonable. Yet, since multiple factors affect dispersion from surface phosphate mines, a range of emission factors, rather than only a single value, was found to satisfy the model performance. Copyright © 2016 Elsevier B.V. All rights reserved.

SCA with rotation to distinguish common and distinctive information in linked data.

PubMed

Schouteden, Martijn; Van Deun, Katrijn; Pattyn, Sven; Van Mechelen, Iven

2013-09-01

Often data are collected that consist of different blocks that all contain information about the same entities (e.g., items, persons, or situations). In order to unveil both information that is common to all data blocks and information that is distinctive for one or a few of them, an integrated analysis of the whole of all data blocks may be most useful. Interesting classes of methods for such an approach are simultaneous-component and multigroup factor analysis methods. These methods yield dimensions underlying the data at hand. Unfortunately, however, in the results from such analyses, common and distinctive types of information are mixed up. This article proposes a novel method to disentangle the two kinds of information, by making use of the rotational freedom of component and factor models. We illustrate this method with data from a cross-cultural study of emotions.

Narcissistic Personality Disorder and the Structure of Common Mental Disorders.

PubMed

Eaton, Nicholas R; Rodriguez-Seijas, Craig; Krueger, Robert F; Campbell, W Keith; Grant, Bridget F; Hasin, Deborah S

2017-08-01

Narcissistic personality disorder (NPD) shows high rates of comorbidity with mood, anxiety, substance use, and other personality disorders. Previous bivariate comorbidity investigations have left NPD multivariate comorbidity patterns poorly understood. Structural psychopathology research suggests that two transdiagnostic factors, internalizing (with distress and fear subfactors) and externalizing, account for comorbidity among common mental disorders. NPD has rarely been evaluated within this framework, with studies producing equivocal results. We investigated how NPD related to other mental disorders in the internalizing-externalizing model using diagnoses from a nationally representative sample (N = 34,653). NPD was best conceptualized as a distress disorder. NPD variance accounted for by transdiagnostic factors was modest, suggesting its variance is largely unique in the context of other common mental disorders. Results clarify NPD multivariate comorbidity, suggest avenues for classification and clinical endeavors, and highlight the need to understand vulnerable and grandiose narcissism subtypes' comorbidity patterns and structural relations.

The effect of fatigue driving on injury severity considering the endogeneity.

PubMed

Li, Yanyan; Yamamoto, Toshiyuki; Zhang, Guangnan

2018-02-01

Fatigue driving is one of the most risky driving-related behaviors and represented a significant social and economic cost to the community. Several studies have already examined the relationship between fatigue driving behavior and traffic injury severity from different aspects. However, fatigue driving and injury severity in traffic crash may share some common influential factors. Ignoring the impact of these common factors will lead to endogeneity problem and result in biased parameter estimation. Based on 38,564 crash records during 2006-2011 in Guangdong province, China, we apply a bivariate endogenous binary-ordered probit model to examine the relationship between fatigue driving and injury severity considering endogeneity of fatigue driving. We also explore the difference of influential factors between commercial and non-commercial vehicle drivers. This study identifies several common observed influential factors of fatigue driving propensity and fatal injury propensity and reveals a substantial and significant negative correlation of unobserved factors between them. The influence of fatigue driving on injury severity is significantly underestimated if the endogeneity of fatigue driving on fatal injury propensity is ignored. Factors such as vehicle insurance and road types not only affect fatal injury propensity, but also fatigue driving propensity. The findings in this study can help better understand how those factors affect fatigue driving and injury severity, and contributes to more efficient policy for preventing the harmfulness of fatigue-related crashes. Copyright © 2017 National Safety Council and Elsevier Ltd. All rights reserved.

Mapping Common Aphasia Assessments to Underlying Cognitive Processes and Their Neural Substrates.

PubMed

Lacey, Elizabeth H; Skipper-Kallal, Laura M; Xing, Shihui; Fama, Mackenzie E; Turkeltaub, Peter E

2017-05-01

Understanding the relationships between clinical tests, the processes they measure, and the brain networks underlying them, is critical in order for clinicians to move beyond aphasia syndrome classification toward specification of individual language process impairments. To understand the cognitive, language, and neuroanatomical factors underlying scores of commonly used aphasia tests. Twenty-five behavioral tests were administered to a group of 38 chronic left hemisphere stroke survivors and a high-resolution magnetic resonance image was obtained. Test scores were entered into a principal components analysis to extract the latent variables (factors) measured by the tests. Multivariate lesion-symptom mapping was used to localize lesions associated with the factor scores. The principal components analysis yielded 4 dissociable factors, which we labeled Word Finding/Fluency, Comprehension, Phonology/Working Memory Capacity, and Executive Function. While many tests loaded onto the factors in predictable ways, some relied heavily on factors not commonly associated with the tests. Lesion symptom mapping demonstrated discrete brain structures associated with each factor, including frontal, temporal, and parietal areas extending beyond the classical language network. Specific functions mapped onto brain anatomy largely in correspondence with modern neural models of language processing. An extensive clinical aphasia assessment identifies 4 independent language functions, relying on discrete parts of the left middle cerebral artery territory. A better understanding of the processes underlying cognitive tests and the link between lesion and behavior may lead to improved aphasia diagnosis, and may yield treatments better targeted to an individual's specific pattern of deficits and preserved abilities.

Multiple, but not traditional risk factors predict mortality in older people: the Concord Health and Ageing in Men Project.

PubMed

Hirani, Vasant; Naganathan, Vasi; Blyth, Fiona; Le Couteur, David G; Gnjidic, Danijela; Stanaway, Fiona F; Seibel, Markus J; Waite, Louise M; Handelsman, David J; Cumming, Robert G

2014-01-01

This study aims to identify the common risk factors for mortality in community-dwelling older men. A prospective population-based study was conducted with a median of 6.7 years of follow-up. Participants included 1705 men aged ≥70 years at baseline (2005-2007) living in the community in Sydney, Australia. Demographic information, lifestyle factors, health status, self-reported history of diseases, physical performance measures, blood pressure, height and weight, disability (activities of daily living (ADL) and instrumental ADLs, instrumental ADLs (IADLs)), cognitive status, depressive symptoms and blood analyte measures were considered. Cox regression analyses were conducted to model predictors delete time until of mortality. During follow-up, 461 men (27 %) died. Using Cox proportional hazards model, significant predictors of delete time to time to mortality included in the final model (p < 0.05) were older age, body mass index < 20 kg m(2), high white cell count, anaemia, low albumin, current smoking, history of cancer, history of myocardial infarction, history of congestive heart failure, depressive symptoms and ADL and IADL disability and impaired chair stands. We found that overweight and obesity and/or being a lifelong non-drinker of alcohol were protective against mortality. Compared to men with less than or equal to one risk factor, the hazard ratio in men with three risk factors was 2.5; with four risk factors, it was 4.0; with five risk factors, it was 4.9; and for six or more risk factors, it was 11.4, respectively. We have identified common risk factors that predict mortality that may be useful in making clinical decisions among older people living in the community. Our findings suggest that, in primary care, screening and management of multiple risk factors are important to consider for extending survival, rather than simply considering individual risk factors in isolation. Some of the "traditional" risk factors for mortality in a younger population, including high blood pressure, hypercholesterolaemia, overweight and obesity and diabetes, were not independent predictors of mortality in this population of older men.

Eating traits questionnaires as a continuum of a single concept. Uncontrolled eating.

PubMed

Vainik, Uku; Neseliler, Selin; Konstabel, Kenn; Fellows, Lesley K; Dagher, Alain

2015-07-01

Research on eating behaviour has identified several potentially relevant eating-related traits captured by different questionnaires. Often, these questionnaires predict Body Mass Index (BMI), but the relationship between them has not been explicitly studied. We studied the unity and diversity of questionnaires capturing five common eating-related traits: Power of Food, Eating Impulsivity, emotional eating, Disinhibition, and binge eating in women from Estonia (n = 740) and Canada (n = 456). Using bifactor analysis, we showed that a) these questionnaires are largely explained by a single factor, and b) relative to this shared factor, only some questionnaires offered additional variance in predicting BMI. Hence, these questionnaires seemed to characterise a common factor, which we label Uncontrolled Eating. Item Response Theory techniques were then applied to demonstrate that c) within this common factor, the questionnaires could be placed on a continuum of Uncontrolled Eating. That is, Eating Impulsivity focused on the milder degree, Power of Food Scale, emotional eating scales, and Disinhibition on intermediate degrees, and the Binge Eating Scale on the most severe degrees of Uncontrolled Eating. In sum, evidence from two samples showed that questionnaires capturing five common BMI-related traits largely reflected the same underlying latent trait - Uncontrolled Eating. In Estonia, some questionnaires focused on different severities of this common construct, supporting a continuum model of Uncontrolled Eating. These findings provide a starting point for developing better questionnaires of the neurobehavioural correlates of obesity, and provide a unifying perspective from which to view the existing literature. R scripts and data used for the analysis are provided. Copyright © 2015 Elsevier Ltd. All rights reserved.

Understanding compliance issues for daily self-injectable treatment in ambulatory care settings

PubMed Central

Brod, Meryl; Rousculp, Matthew; Cameron, Ann

2008-01-01

Background The challenge of understanding factors influencing compliance with injectable treatments is critical as injectable biologics/medications become more common. Objective Understanding compliance issues for long term self-injectable treatments, using a chronic condition (osteoporosis) as a model. Research design A qualitative study to generate hypotheses regarding compliance issues for self-injectable treatments. Semi-structured interview guides were developed and data collected from patients and clinical experts. Findings were analyzed for common themes and a conceptual model of the compliance impact of self-injectable treatments generated. Subjects Six physicians (Rheumatology, Internal Medicine, and Endocrinology) and 22 patients (14% never began treatment, 23% had filled at least one prescription but discontinued treatment, and 63% were currently on treatment) were interviewed. Results Physician and patient factors influenced the compliance process at four distinct time-points: pre-treatment, time treatment recommended, short-term, and long-term. Physician factors that influenced patients’ persistence were knowledge about treatment, patient-training resources, and clinical profile/efficacy evaluations. For patients, motivation level, physician message, and clinical profile were key. Logistical issues, minor side effects and injection site issues influenced adherence but not persistence. Conclusions Compliance is a multifactorial, dynamic process. Both physician and patient factors influence compliance at different points in the process. PMID:19920953

Maximize, minimize or target - optimization for a fitted response from a designed experiment

DOE PAGES

Anderson-Cook, Christine Michaela; Cao, Yongtao; Lu, Lu

2016-04-01

One of the common goals of running and analyzing a designed experiment is to find a location in the design space that optimizes the response of interest. Depending on the goal of the experiment, we may seek to maximize or minimize the response, or set the process to hit a particular target value. After the designed experiment, a response model is fitted and the optimal settings of the input factors are obtained based on the estimated response model. Furthermore, the suggested optimal settings of the input factors are then used in the production environment.

Factor Structure and Convergent Validity of the Stress Index for Parents of Adolescents (SIPA) in Adolescents With ADHD.

PubMed

Eadeh, Hana-May; Langberg, Joshua M; Molitor, Stephen J; Behrhorst, Katie; Smith, Zoe R; Evans, Steven W

2018-02-01

Parenting stress is common in families with an adolescent with attention-deficit/hyperactivity disorder (ADHD). The Stress Index for Parents of Adolescents (SIPA) was developed to assess parenting stress but has not been validated outside of the original development work. This study examined the factor structure and sources of convergent validity of the SIPA in a sample of adolescents diagnosed with ADHD ( M age = 12.3, N = 327) and their caregivers. Three first-order models, two bifactor models, and one higher order model were evaluated; none met overall model fit criteria but the first-order nine-factor model displayed the best fit. Convergent validity was also assessed and the SIPA adolescent domain was moderately correlated with measures of family impairment and conflict after accounting for ADHD symptom severity. Implications of these findings for use of the SIPA in ADHD samples are discussed along with directions for future research focused on parent stress and ADHD.

Revisiting the Paraquat-Induced Sporadic Parkinson's Disease-Like Model.

PubMed

Bastías-Candia, Sussy; Zolezzi, Juan M; Inestrosa, Nibaldo C

2018-06-03

Parkinson's disease (PD) is a major neurodegenerative disorder that affects 1-2% of the total global population. Despite its high prevalence and publication of several studies focused on understanding its pathology, an effective treatment that stops and/or reverses the damage to dopaminergic neurons is unavailable. Similar to other neurodegenerative disorders, PD etiology may be linked to several factors, including genetic susceptibility and environmental elements. Regarding environmental factors, several neurotoxic pollutants, including 6-hydroxydopamine (6-OHDA) and 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP), have been identified. Moreover, some pesticides/herbicides, such as rotenone, paraquat (PQ), maneb (MB), and mancozeb (MZ), cause neurotoxicity and induce a PD-like pathology. Based on these findings, several in vitro and in vivo PD-like models have been developed to understand the pathophysiology of PD and evaluate different therapeutic strategies to fight dopaminergic neurodegeneration. 6-OHDA and MPTP are common models used in PD research, and pesticide-based approaches have become secondary models of study. However, some herbicides, such as PQ, are commonly used by farming laborers in developing countries. Thus, the present review summarizes the relevant scientific background regarding the use and effects of chronic exposure to PQ in the context of PD. Similarly, we discuss the relevance of PD-like models developed using this agrochemical compound.

Estimating the Diets of Animals Using Stable Isotopes and a Comprehensive Bayesian Mixing Model

PubMed Central

Hopkins, John B.; Ferguson, Jake M.

2012-01-01

Using stable isotope mixing models (SIMMs) as a tool to investigate the foraging ecology of animals is gaining popularity among researchers. As a result, statistical methods are rapidly evolving and numerous models have been produced to estimate the diets of animals—each with their benefits and their limitations. Deciding which SIMM to use is contingent on factors such as the consumer of interest, its food sources, sample size, the familiarity a user has with a particular framework for statistical analysis, or the level of inference the researcher desires to make (e.g., population- or individual-level). In this paper, we provide a review of commonly used SIMM models and describe a comprehensive SIMM that includes all features commonly used in SIMM analysis and two new features. We used data collected in Yosemite National Park to demonstrate IsotopeR's ability to estimate dietary parameters. We then examined the importance of each feature in the model and compared our results to inferences from commonly used SIMMs. IsotopeR's user interface (in R) will provide researchers a user-friendly tool for SIMM analysis. The model is also applicable for use in paleontology, archaeology, and forensic studies as well as estimating pollution inputs. PMID:22235246

Affecting Factors of Secondhand Smoke Exposure in Korea: Focused on Different Exposure Locations.

PubMed

Sun, Li Yuan; Cheong, Hae Kwan; Lee, Eun Whan; Kang, Kyeong Jin; Park, Jae Hyun

2016-09-01

Exposure to secondhand smoke (SHS) not only can cause serious illness, but is also an economic and social burden. Contextual and individual factors of non-smoker exposure to SHS depend on location. However, studies focusing on this subject are lacking. In this study, we described and compared the factors related to SHS exposure according to location in Korea. Regarding individual factors related to SHS exposure, a common individual variable model and location-specific variable model was used to evaluate SHS exposure at home/work/public locations based on sex. In common individual variables, such as age, and smoking status showed different relationships with SHS exposure in different locations. Among home-related variables, housing type and family with a single father and unmarried children showed the strongest positive relationships with SHS exposure in both males and females. In the workplace, service and sales workers, blue-collar workers, and manual laborers showed the strongest positive association with SHS exposure in males and females. For multilevel analysis in public places, only SHS exposure in females was positively related with cancer screening rate. Exposure to SHS in public places showed a positive relationship with drinking rate and single-parent family in males and females. The problem of SHS embodies social policies and interactions between individuals and social contextual factors. Policy makers should consider the contextual factors of specific locations and regional and individual context, along with differences between males and females, to develop effective strategies for reducing SHS exposure.

Determining Smoking Cessation Related Information, Motivation, and Behavioral Skills among Opiate Dependent Smokers in Methadone Treatment

PubMed Central

Cooperman, Nina A.; Richter, Kimber P.; Bernstein, Steven L.; Steinberg, Marc L.; Williams, Jill M.

2015-01-01

Background Over 80% of people in methadone treatment smoke cigarettes, and existing smoking cessation interventions have been minimally effective. Objective To develop an Information-Motivation-Behavioral Skills (IMB) Model of behavior change based smoking cessation intervention for methadone maintained smokers, we examined smoking cessation related information, motivation, and behavioral skills in this population. Methods Current or former smokers in methadone treatment (n=35) participated in focus groups. Ten methadone clinic counselors participated in an individual interview. A content analysis was conducted using deductive and inductive approaches. Results Commonly known information, motivation, and behavioral skills factors related to smoking cessation were described. These factors included: the health effects of smoking and treatment options for quitting (information); pregnancy and cost of cigarettes (motivators); and coping with emotions, finding social support, and pharmacotherapy adherence (behavioral skills). Information, motivation, and behavioral skills factors specific to methadone maintained smokers were also described. These factors included: the relationship between quitting smoking and drug relapse (information), the belief that smoking is the same as using drugs (motivator); and coping with methadone clinic culture and applying skills used to quit drugs to quitting smoking (behavioral skills). Information, motivation, and behavioral skills strengths and deficits varied by individual. Conclusions Methadone maintained smokers could benefit from research on an IMB Model based smoking cessation intervention that is individualized, addresses IMB factors common among all smokers, and also addresses IMB factors unique to this population. PMID:25559697

A comparison of linear and nonlinear statistical techniques in performance attribution.

PubMed

Chan, N H; Genovese, C R

2001-01-01

Performance attribution is usually conducted under the linear framework of multifactor models. Although commonly used by practitioners in finance, linear multifactor models are known to be less than satisfactory in many situations. After a brief survey of nonlinear methods, nonlinear statistical techniques are applied to performance attribution of a portfolio constructed from a fixed universe of stocks using factors derived from some commonly used cross sectional linear multifactor models. By rebalancing this portfolio monthly, the cumulative returns for procedures based on standard linear multifactor model and three nonlinear techniques-model selection, additive models, and neural networks-are calculated and compared. It is found that the first two nonlinear techniques, especially in combination, outperform the standard linear model. The results in the neural-network case are inconclusive because of the great variety of possible models. Although these methods are more complicated and may require some tuning, toolboxes are developed and suggestions on calibration are proposed. This paper demonstrates the usefulness of modern nonlinear statistical techniques in performance attribution.

The Schizotypal Personality Questionnaire-Brief lacks measurement invariance across three countries.

PubMed

Liu, Shujuan; Mellor, David; Ling, Mathew; Saiz, José L; Vinet, Eugenia V; Xu, Xiaoyan; Renati, Solomon; Byrne, Linda K

2017-12-01

The Schizotypal Personality Questionnaire-Brief (SPQ-B) is a commonly-used tool for measuring schizotypal personality traits and due to its wide application, its cross-cultural validity is of interest. Previous studies suggest that the SPQ-B either has a three- or four-factor structure, but the majority of studies have been conducted in Western contexts and little is known about the psychometric properties of the scale in other populations. In this study factorial invariance testing across three cultural contexts-Australia, China and Chile was conducted. In total, 729 young adults (Mean age = 23.99 years, SD = 9.87 years) participated. Invariance testing did not support the four-factor model across three countries. Confirmatory Factor Analyses revealed that neither the four- nor three-factor model had strong fit in any of the settings. However, in comparison with other competing models, the four-factor model showed the best for the Australian sample, while the three-factor model was the most reasonable for both Chinese and Chilean samples. The reliability of the SPQ-B scores, estimated with Omega, ranged from 0.86 to 0.91. These findings suggest that the SPQ-B factors are not consistent across different cultural groups. We suggest that these differences could be attributed to potential confounding cultural and translation issues. Copyright © 2017 Elsevier B.V. All rights reserved.

Bone fracture healing in mechanobiological modeling: A review of principles and methods.

PubMed

Ghiasi, Mohammad S; Chen, Jason; Vaziri, Ashkan; Rodriguez, Edward K; Nazarian, Ara

2017-06-01

Bone fracture is a very common body injury. The healing process is physiologically complex, involving both biological and mechanical aspects. Following a fracture, cell migration, cell/tissue differentiation, tissue synthesis, and cytokine and growth factor release occur, regulated by the mechanical environment. Over the past decade, bone healing simulation and modeling has been employed to understand its details and mechanisms, to investigate specific clinical questions, and to design healing strategies. The goal of this effort is to review the history and the most recent work in bone healing simulations with an emphasis on both biological and mechanical properties. Therefore, we provide a brief review of the biology of bone fracture repair, followed by an outline of the key growth factors and mechanical factors influencing it. We then compare different methodologies of bone healing simulation, including conceptual modeling (qualitative modeling of bone healing to understand the general mechanisms), biological modeling (considering only the biological factors and processes), and mechanobiological modeling (considering both biological aspects and mechanical environment). Finally we evaluate different components and clinical applications of bone healing simulation such as mechanical stimuli, phases of bone healing, and angiogenesis.

SPATIAL EXPLICIT POPULATION MODELS FOR RISK ASSESSMENT: COMMON LOONS AND MERCURY AS A CASE STUDY

EPA Science Inventory

Factors that significantly impact population dynamics, such as resource availability and exposure to stressors, frequently vary over space and thereby determine the heterogeneous spatial distributions of organisms. Considering this fact, the US Environmental Protection Agency's ...

SUSCEPTIBILITY TO OZONE-INDUCED INJURY AND ANTIOXIDANT COMPENSATION IN RAT MODELS OF CARDIOVASCULAR DISEASE

EPA Science Inventory

Increased oxidative stress and compromised antioxidant status are common pathologic factors of cardiovascular diseases (CVD). It is hypothesized that individuals with chronic CVD are more susceptible to environmental exposures due to underlying oxidative stress. To determine the ...

Organisational Factors of Occupational Accidents with Movement Disturbance (OAMD) and Prevention

PubMed Central

LECLERCQ, Sylvie

2014-01-01

Workplace design and upkeep, or human factors, are frequently advanced for explaining so-called Occupational Slip, Trip and Fall Accidents (OSTFAs). Despite scientific progress, these accidents, and more broadly Occupational Accidents with Movement Disturbance (OAMDs), are also commonly considered to be “simple”. This paper aims to stimulate changes in such perceptions by focusing on organisational factors that often combine with other accident factors to cause movement disturbance and injury in work situations. These factors frequently lead to arbitration between production and safety, which involves implementation of controls by workers. These controls can lead to greater worker exposure to OAMD risk. We propose a model that focuses on such controls to account specifically for the need to confront production and safety logics within a company and to enhance the potential for appropriate prevention action. These are then integrated into the set of controls highlighted by work organisation model developed by the NIOSH. PMID:25345425

What distinguishes individual stocks from the index?

NASA Astrophysics Data System (ADS)

Wagner, F.; Milaković, M.; Alfarano, S.

2010-01-01

Stochastic volatility models decompose the time series of financial returns into the product of a volatility factor and an iid noise factor. Assuming a slow dynamic for the volatility factor, we show via nonparametric tests that both the index as well as its individual stocks share a common volatility factor. While the noise component is Gaussian for the index, individual stock returns turn out to require a leptokurtic noise. Thus we propose a two-component model for stocks, given by the sum of Gaussian noise, which reflects market-wide fluctuations, and Laplacian noise, which incorporates firm-specific factors such as firm profitability or growth performance, both of which are known to be Laplacian distributed. In the case of purely Gaussian noise, the chi-squared probability for the density of individual stock returns is typically on the order of 10-20, while it increases to values of O(1) by adding the Laplace component.

Evidence for the Discriminant Validity of the Revised Social Anhedonia Scale From Social Anxiety.

PubMed

Cicero, David C; Krieg, Alexander; Becker, Theresa M; Kerns, John G

2016-10-01

Social anhedonia and social anxiety are two constructs with similar behaviors including avoidance of and withdrawal from social situations. In three studies, the current research aimed to test whether social anhedonia could be discriminated from social anxiety using the most common measure of social anhedonia, the Revised Social Anhedonia Scale (RSAS). In Study 1, an item-level factor analysis of the RSAS found two factors: Social Apathy/Aversion and Social Withdrawal. In Study 2, this two-factor structure was confirmed in a separate sample. In Study 3, a model with social anhedonia and anxiety scale scores loading on separate factors fit better than a model with social anhedonia and anxiety loading on a single factor. Social anhedonia and anxiety displayed differential associations with negative schizotypy and emotion processing. Findings suggest that the RSAS is successful in measuring social anhedonia distinct from social anxiety. © The Author(s) 2015.

Common Factor Mechanisms in Clinical Practice and Their Relationship with Outcome.

PubMed

Gaitan-Sierra, Carolina; Hyland, Michael E

2015-01-01

This study investigates three common factor mechanisms that could affect outcome in clinical practice: response expectancy, the affective expectation model and motivational concordance. Clients attending a gestalt therapy clinic (30 clients), a sophrology (therapeutic technique) clinic (33 clients) and a homeopathy clinic (31 clients) completed measures of expectancy and the Positive Affect and Negative Affect Schedule (PANAS) before their first session. After 1 month, they completed PANAS and measures of intrinsic motivation, perceived effort and empowerment. Expectancy was not associated with better outcome and was no different between treatments. Although some of the 54 clients who endorsed highest expectations showed substantial improvement, others did not: 19 had no change or deteriorated in positive affect, and 18 had the same result for negative affect. Intrinsic motivation independently predicted changes in negative affect (β = -0.23). Intrinsic motivation (β = 0.24), effort (β = 0.23) and empowerment (β = 0.20) independently predicted positive affect change. Expectancy (β = -0.17) negatively affected changes in positive affect. Clients found gestalt and sophrology to be more intrinsically motivating, empowering and effortful compared with homeopathy. Greater improvement in mood was found for sophrology and gestalt than for homeopathy clients. These findings are inconsistent with response expectancy as a common factor mechanism in clinical practice. The results support motivational concordance (outcome influenced by the intrinsic enjoyment of the therapy) and the affective expectation model (high expectations can lead for some clients to worse outcome). When expectancy correlates with outcome in some other studies, this may be due to confound between expectancy and intrinsic enjoyment. Common factors play an important role in outcome. Intrinsic enjoyment of a therapeutic treatment is associated with better outcome. Active engagement with a therapeutic treatment improves outcome. Unrealistic expectations about a therapeutic treatment can have a negative impact on outcome. Copyright © 2014 John Wiley & Sons, Ltd.

Can Optimism, Pessimism, Hope, Treatment Credibility and Treatment Expectancy Be Distinguished in Patients Undergoing Total Hip and Total Knee Arthroplasty?

PubMed Central

Haanstra, Tsjitske M.; Tilbury, Claire; Kamper, Steven J.; Tordoir, Rutger L.; Vliet Vlieland, Thea P. M.; Nelissen, Rob G. H. H.; Cuijpers, Pim; de Vet, Henrica C. W.; Dekker, Joost; Knol, Dirk L.; Ostelo, Raymond W.

2015-01-01

Objectives The constructs optimism, pessimism, hope, treatment credibility and treatment expectancy are associated with outcomes of medical treatment. While these constructs are grounded in different theoretical models, they nonetheless show some conceptual overlap. The purpose of this study was to examine whether currently available measurement instruments for these constructs capture the conceptual differences between these constructs within a treatment setting. Methods Patients undergoing Total Hip and Total Knee Arthroplasty (THA and TKA) (Total N = 361; 182 THA; 179 TKA), completed the Life Orientation Test-Revised for optimism and pessimism, the Hope Scale, the Credibility Expectancy Questionnaire for treatment credibility and treatment expectancy. Confirmatory factor analysis was used to examine whether the instruments measure distinct constructs. Four theory-driven models with one, two, four and five latent factors were evaluated using multiple fit indices and Δχ2 tests, followed by some posthoc models. Results The results of the theory driven confirmatory factor analysis showed that a five factor model in which all constructs loaded on separate factors yielded the most optimal and satisfactory fit. Posthoc, a bifactor model in which (besides the 5 separate factors) a general factor is hypothesized accounting for the commonality of the items showed a significantly better fit than the five factor model. All specific factors, except for the hope factor, showed to explain a substantial amount of variance beyond the general factor. Conclusion Based on our primary analyses we conclude that optimism, pessimism, hope, treatment credibility and treatment expectancy are distinguishable in THA and TKA patients. Postdoc, we determined that all constructs, except hope, showed substantial specific variance, while also sharing some general variance. PMID:26214176

Can Optimism, Pessimism, Hope, Treatment Credibility and Treatment Expectancy Be Distinguished in Patients Undergoing Total Hip and Total Knee Arthroplasty?

PubMed

Haanstra, Tsjitske M; Tilbury, Claire; Kamper, Steven J; Tordoir, Rutger L; Vliet Vlieland, Thea P M; Nelissen, Rob G H H; Cuijpers, Pim; de Vet, Henrica C W; Dekker, Joost; Knol, Dirk L; Ostelo, Raymond W

2015-01-01

The constructs optimism, pessimism, hope, treatment credibility and treatment expectancy are associated with outcomes of medical treatment. While these constructs are grounded in different theoretical models, they nonetheless show some conceptual overlap. The purpose of this study was to examine whether currently available measurement instruments for these constructs capture the conceptual differences between these constructs within a treatment setting. Patients undergoing Total Hip and Total Knee Arthroplasty (THA and TKA) (Total N = 361; 182 THA; 179 TKA), completed the Life Orientation Test-Revised for optimism and pessimism, the Hope Scale, the Credibility Expectancy Questionnaire for treatment credibility and treatment expectancy. Confirmatory factor analysis was used to examine whether the instruments measure distinct constructs. Four theory-driven models with one, two, four and five latent factors were evaluated using multiple fit indices and Δχ2 tests, followed by some posthoc models. The results of the theory driven confirmatory factor analysis showed that a five factor model in which all constructs loaded on separate factors yielded the most optimal and satisfactory fit. Posthoc, a bifactor model in which (besides the 5 separate factors) a general factor is hypothesized accounting for the commonality of the items showed a significantly better fit than the five factor model. All specific factors, except for the hope factor, showed to explain a substantial amount of variance beyond the general factor. Based on our primary analyses we conclude that optimism, pessimism, hope, treatment credibility and treatment expectancy are distinguishable in THA and TKA patients. Postdoc, we determined that all constructs, except hope, showed substantial specific variance, while also sharing some general variance.

Dimensions of service quality in healthcare: a systematic review of literature.

PubMed

Fatima, Iram; Humayun, Ayesha; Iqbal, Usman; Shafiq, Muhammad

2018-06-13

Various dimensions of healthcare service quality were used and discussed in literature across the globe. This study presents an updated meaningful review of the extensive research that has been conducted on measuring dimensions of healthcare service quality. Systematic review method in current study is based on PRISMA guidelines. We searched for literature using databases such as Google, Google Scholar, PubMed and Social Science, Citation Index. In this study, we screened 1921 identified papers using search terms/phrases. Snowball strategies were adopted to extract published articles from January 1997 till December 2016. Two-hundred and fourteen papers were identified as relevant for data extraction; completed by two researchers, double checked by the other two to develop agreement in discrepancies. In total, 74 studies fulfilled our pre-defined inclusion and exclusion criteria for data analysis. Service quality is mainly measured as technical and functional, incorporating many sub-dimensions. We synthesized the information about dimensions of healthcare service quality with reference to developed and developing countries. 'Tangibility' is found to be the most common contributing factor whereas 'SERVQUAL' as the most commonly used model to measure healthcare service quality. There are core dimensions of healthcare service quality that are commonly found in all models used in current reviewed studies. We found a little difference in these core dimensions while focusing dimensions in both developed and developing countries, as mostly SERVQUAL is being used as the basic model to either generate a new one or to add further contextual dimensions. The current study ranked the contributing factors based on their frequency in literature. Based on these priorities, if factors are addressed irrespective of any context, may lead to contribute to improve healthcare quality and may provide an important information for evidence-informed decision-making.

Lower Bounds to the Reliabilities of Factor Score Estimators.

PubMed

Hessen, David J

2016-10-06

Under the general common factor model, the reliabilities of factor score estimators might be of more interest than the reliability of the total score (the unweighted sum of item scores). In this paper, lower bounds to the reliabilities of Thurstone's factor score estimators, Bartlett's factor score estimators, and McDonald's factor score estimators are derived and conditions are given under which these lower bounds are equal. The relative performance of the derived lower bounds is studied using classic example data sets. The results show that estimates of the lower bounds to the reliabilities of Thurstone's factor score estimators are greater than or equal to the estimates of the lower bounds to the reliabilities of Bartlett's and McDonald's factor score estimators.

Ethnic diversity in the genetics of venous thromboembolism.

PubMed

Tang, Liang; Hu, Yu

2015-11-01

Genetic susceptibility is considered as a crucial factor for the development of venous thromboembolism (VTE). Epidemiologic and genetic studies have revealed clear disparities in the incidence of VTE and the distribution of genetic factors for VTE in populations stratified by ethnicity worldwide. While gain-of-function polymorphisms in the procoagulant genes are common inherited factors in European-origin populations, the most prevalent molecular basis for venous thrombosis in Asians is confirmed to be dysfunctional variants in the anticoagulant genes. With the breakthrough of genomic technologies, a set of novel common alleles and rare mutations associated with VTE have also been identified, in different ethnic groups. Several putative pathways contributing to the pathogenesis of thrombophilia in populations of African-ancestry are largely unknown, as current knowledge of hereditary and acquired risk factors do not fully explain the highest risk of VTE in Black groups. In-depth studies across diverse ethnic populations are needed to unravel the whole genetics of VTE, which will help developing individual risk prediction models and strategies to minimise VTE in all populations.

Complementary exploratory and confirmatory factor analyses of the French WISC-V: Analyses based on the standardization sample.

PubMed

Lecerf, Thierry; Canivez, Gary L

2018-06-01

Interpretation of the French Wechsler Intelligence Scale for Children-Fifth Edition (French WISC-V; Wechsler, 2016a) is based on a 5-factor model including Verbal Comprehension (VC), Visual Spatial (VS), Fluid Reasoning (FR), Working Memory (WM), and Processing Speed (PS). Evidence for the French WISC-V factorial structure was established exclusively through confirmatory factor analyses (CFAs). However, as recommended by Carroll (1995); Reise (2012), and Brown (2015), factorial structure should derive from both exploratory factor analysis (EFA) and CFA. The first goal of this study was to examine the factorial structure of the French WISC-V using EFA. The 15 French WISC-V primary and secondary subtest scaled scores intercorrelation matrix was used and factor extraction criteria suggested from 1 to 4 factors. To disentangle the contribution of first- and second-order factors, the Schmid and Leiman (1957) orthogonalization transformation (SLT) was applied. Overall, no EFA evidence for 5 factors was found. Results indicated that the g factor accounted for about 67% of the common variance and that the contributions of the first-order factors were weak (3.6 to 11.9%). CFA was used to test numerous alternative models. Results indicated that bifactor models produced better fit to these data than higher-order models. Consistent with previous studies, findings suggested dominance of the general intelligence factor and that users should thus emphasize the Full Scale IQ (FSIQ) when interpreting the French WISC-V. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

[Establishment and evaluation of extracorporeal circulation model in rats].

PubMed

Xie, Xiao-Jun; Tao, Kai-Yu; Tang, Meng-Lin; Du, Lei; An, Qi; Lin, Ke; Gan, Chang-Ping; Chen, You-Wen; Luo, Shu-Hua

2012-09-01

To establish an extracorporeal circulation (ECC) rat model, and evaluate the inflammatory response and organ injury induced in the model. SD rats were anesthetized and cannulated from right common carotid artery to left femoral vein to establish the bypass of extracorporeal circulation. Then the rats were randomly divided into ECC group and sham group. The rats in ECC group were subjected to extracorporeal circulation for 2 hours and then rest for 2 hours, while the rats in sham group were only observed for 4 hours without extracorporeal circulation. After that, blood routine examination, blood gas analysis, the measurement of pro-inflammatory factors in bronchoalveolar lavage fluid and lung tissue were performed to evaluate the lung injury induced by ECC. Circulating endothelial cells were also calculated by flow cytometry to assess the vascular endothelial injury. At 2 hours after ECC, red blood cell counts in both groups kept normal, while leukocyte and neutrophil counts, plasmatic tumor necrosis factor-a level and neutrophil elastase level, circulating endothelial cells in the rats of ECC group were significantly higher than those in sham group. Tumor necrosis factor-alpha in bronchoalveolar lavage fluid and water content in lung of the ECC rats were also significantly higher, while the oxygenation index was significantly lower. Neutrophil infiltration was also observed in lung tissues with increased thickness of alveolar membrane in ECC group. The ECC model established from right common carotid artery to left femoral vein in our study can successfully induce systemic inflammatory response, and acute lung injury associated with inflammation.

Sexual function in women in rural Tamil Nadu: disease, dysfunction, distress and norms.

PubMed

Viswanathan, Shonima; Prasad, Jasmine; Jacob, K S; Kuruvilla, Anju

2014-01-01

We examined the nature, prevalence and explanatory models of sexual concerns and dysfunction among women in rural Tamil Nadu. Married women between 18 and 65 years of age, from randomly selected villages in Kaniyambadi block, Vellore district, Tamil Nadu, were chosen by stratified sampling technique. Sexual functioning was assessed using the Female Sexual Function Index (FSFI). The modified Short Explanatory Model Interview (SEMI) was used to assess beliefs about sexual concerns and the General Health Questionnaire-12 (GHQ-12) was used to screen for common mental disorders. Sociodemographic variables and other risk factors were also assessed. Most of the women (277; 98.2%) contacted agreed to participate in the study. The prevalence of sexual dysfunction, based on the cut-off score on the FSFI, was 64.3%. However, only a minority of women considered it a problem (4.7%), expressed dissatisfaction (5.8%) or sought medical help (2.5%). The most common explanatory models offered for sexual problems included an unhappy marriage,stress and physical problems. Factors associated with lower FSFI included older age, illiteracy, as well as medical illness and sexual and marital factors such as menopause, poor quality of marital relationship, history of physical abuse and lack of privacy. The diagnosis of female sexual dysfunction needs to be nuanced and based on the broader personal and social context. Our findings argue that there is a need to use models that employ personal, local and contextual standards in assessing complex behaviours such as sexual function. Copyright 2014, NMJI.

Validating the Malheur model for predicting ponderosa pine post-fire mortality using 24 fires in the Pacific Northwest, USA

Treesearch

Walter G. Thies; Douglas J. Westlind

2012-01-01

Fires, whether intentionally or accidentally set, commonly occur in western interior forests of the US. Following fire, managers need the ability to predict mortality of individual trees based on easily observed characteristics. Previously, a two-factor model using crown scorch and bole scorch proportions was developed with data from 3415 trees for predicting the...

Genetic and Environmental Influences on Pubertal Development: Longitudinal Data from Finnish Twins at Ages 11 and 14

ERIC Educational Resources Information Center

Mustanski, Brian S.; Viken, Richard J.; Kaprio, Jaakko; Pulkkinen, Lea; Rose, Richard J.

2004-01-01

To study sources of individual differences in pubertal development, the authors fit a sex-limitation common factor model to data reported, at ages 11 and 14 years, by 1,891 twin pairs on items that comprise the Pubertal Development Scale (PDS; A. C. Petersen, L. Crockett, M. Richards, & A. Boxer, 1988). The model divides variation into a general…

Teacher Professional Development and Student Achievement: Analysis of Trends from Grade 8 TIMSS 2003, 2007 and 2011 Math Data for the Kingdom of Bahrain

ERIC Educational Resources Information Center

Ajjawi, Samah

2015-01-01

It is a common knowledge that student achievement is a product of multiple individual and environmental factors. The literature developed various models to organize and explain the relationship between some of these variables and student learning which translates into student achievement. Yet, no comprehensive model is able to capture all possible…

[Protection and bidirectional effect of rhubarb anthraquinone and tannins for rats' liver].

PubMed

Qin, Lu-shan; Zhao, Hai-ping; Zhao, Yan-ling; Ma, Zhi-jiel; Zeng, Ling-na; Zhang, Ya-ming; Zhang, Ping; Yan, Dan; Bai, Zhao-fang; Li, Yue; Hao, Qing-xiu; Zhao, Kui-jun; Wang, Jia-bo; Xiao, Xiao-he

2014-06-01

To compare the bidirectional effect of rhubarb total anthraquinone (TA) and total tannins (TT) on rats' liver. One hundred rats were randomly divided into 10 groups, i.e., the blank group, the model group, the blank + high dose TA group, the blank +low dose TA group, the blank + high dose TT group, the blank + low dose TT group, the model + high dose TA group, the model + low dose TA group, the model +high dose TT group, and the model + low dose TT group, 10 in each group. The carbon tetrachloride (CCI4) was used to prepare the acute liver injury rat model. TA and TT of rhubarb (at 5.40 g crude drugs/kg and 14.69 g crude drugs/kg) were intragastrically administrated to rats in all groups except the blank group and the model group, once daily for 6 successive days.The general state of rats, biochemical indices such as alanine aminotransferase (ALT), aspartate aminotransferase (AST), alkaline phosphatase (ALP), laminin (LN), hyaluronic acid (HA), transforming growth factor beta1 (TGF-beta1), as well pathological results of rat liver tissues. Finally the protection laws of TA and TT for rats' liver were analyzed using factor analysis. Compared with the blank control group, all biochemical indices increased in the blank group (P < 0.05, P < 0.01). HA also increased in the blank + high dose TA group; AST, ALT, and HA also increased in the blank +high dose TT group (P < 0.05). Compared with the model group, AST, ALT, ALP, HA, and TGF-beta1 significantly decreased in the model + low dose TA group, the model + high dose TA group, the model + low dose TT group (P < 0.05, P < 0.01). Serum AST, ALT, and ALP also decreased in the model + high dose TT group (P < 0.05, P < 0.01). Pathological results showed that mild swollen liver cells in the model + high dose TA group. Fatty degeneration and fragmental necrosis around the central veins occurred in the blank + high dose TA group. The pathological injury was inproved in the model +low dose TA group. Two common factors, liver fibrosis and liver cell injury, were extracted by using factor analysis. TA showed stronger improvement of the two common factors than TT. Rhubarb TA and TT showed protective and harmful effects on rats' liver. At an equivalent dosage, TA had better liver protection than TT. High dose TT played a role in liver injury to some extent.

Psychological Language on Twitter Predicts County-Level Heart Disease Mortality

PubMed Central

Eichstaedt, Johannes C.; Schwartz, Hansen Andrew; Kern, Margaret L.; Park, Gregory; Labarthe, Darwin R.; Merchant, Raina M.; Jha, Sneha; Agrawal, Megha; Dziurzynski, Lukasz A.; Sap, Maarten; Weeg, Christopher; Larson, Emily E.; Ungar, Lyle H.; Seligman, Martin E. P.

2015-01-01

Hostility and chronic stress are known risk factors for heart disease, but they are costly to assess on a large scale. We used language expressed on Twitter to characterize community-level psychological correlates of age-adjusted mortality from atherosclerotic heart disease (AHD). Language patterns reflecting negative social relationships, disengagement, and negative emotions—especially anger—emerged as risk factors; positive emotions and psychological engagement emerged as protective factors. Most correlations remained significant after controlling for income and education. A cross-sectional regression model based only on Twitter language predicted AHD mortality significantly better than did a model that combined 10 common demographic, socioeconomic, and health risk factors, including smoking, diabetes, hypertension, and obesity. Capturing community psychological characteristics through social media is feasible, and these characteristics are strong markers of cardiovascular mortality at the community level. PMID:25605707

Psychological language on Twitter predicts county-level heart disease mortality.

PubMed

Eichstaedt, Johannes C; Schwartz, Hansen Andrew; Kern, Margaret L; Park, Gregory; Labarthe, Darwin R; Merchant, Raina M; Jha, Sneha; Agrawal, Megha; Dziurzynski, Lukasz A; Sap, Maarten; Weeg, Christopher; Larson, Emily E; Ungar, Lyle H; Seligman, Martin E P

2015-02-01

Hostility and chronic stress are known risk factors for heart disease, but they are costly to assess on a large scale. We used language expressed on Twitter to characterize community-level psychological correlates of age-adjusted mortality from atherosclerotic heart disease (AHD). Language patterns reflecting negative social relationships, disengagement, and negative emotions-especially anger-emerged as risk factors; positive emotions and psychological engagement emerged as protective factors. Most correlations remained significant after controlling for income and education. A cross-sectional regression model based only on Twitter language predicted AHD mortality significantly better than did a model that combined 10 common demographic, socioeconomic, and health risk factors, including smoking, diabetes, hypertension, and obesity. Capturing community psychological characteristics through social media is feasible, and these characteristics are strong markers of cardiovascular mortality at the community level. © The Author(s) 2014.

CO2 fluxes and ecosystem dynamics at five European treeless peatlands - merging data and process oriented modelling

NASA Astrophysics Data System (ADS)

Metzger, C.; Jansson, P.-E.; Lohila, A.; Aurela, M.; Eickenscheidt, T.; Belelli-Marchesini, L.; Dinsmore, K. J.; Drewer, J.; van Huissteden, J.; Drösler, M.

2014-06-01

The carbon dioxide (CO2) exchange of five different peatland systems across Europe with a wide gradient in landuse intensity, water table depth, soil fertility and climate was simulated with the process oriented CoupModel. The aim of the study was to find out to what extent CO2 fluxes measured at different sites, can be explained by common processes and parameters implemented in the model. The CoupModel was calibrated to fit measured CO2 fluxes, soil temperature, snow depth and leaf area index (LAI) and resulting differences in model parameters were analysed. Finding site independent model parameters would mean that differences in the measured fluxes could be explained solely by model input data: water table, meteorological data, management and soil inventory data. The model, utilizing a site independent configuration for most of the parameters, captured seasonal variability in the major fluxes well. Parameters that differed between sites included the rate of soil organic decomposition, photosynthetic efficiency, and regulation of the mobile carbon (C) pool from senescence to shooting in the next year. The largest difference between sites was the rate coefficient for heterotrophic respiration. Setting it to a common value would lead to underestimation of mean total respiration by a factor of 2.8 up to an overestimation by a factor of 4. Despite testing a wide range of different responses to soil water and temperature, heterotrophic respiration rates were consistently lowest on formerly drained sites and highest on the managed sites. Substrate decomposability, pH and vegetation characteristics are possible explanations for the differences in decomposition rates. Applying common parameter values for the timing of plant shooting and senescence, and a minimum temperature for photosynthesis, had only a minor effect on model performance, even though the gradient in site latitude ranged from 48° N (South-Germany) to 68° N (northern Finland). This was also true for common parameters defining the moisture and temperature response for decomposition. CoupModel is able to describe measured fluxes at different sites or under different conditions, providing that the rate of soil organic decomposition, photosynthetic efficiency, and the regulation of the mobile carbon (C) pool are estimated from available information on specific soil conditions, vegetation and management of the ecosystems.

A Comparative Study of Workplace Bullying Among Public and Private Employees in Europe.

PubMed

Ariza-Montes, Antonio; Leal-Rodríguez, Antonio L; Leal-Millán, Antonio G

2015-06-01

Workplace bullying emerges from a set of individual, organizational, and contextual factors. The purpose of this article is hence to identify the influence of these factors among public and private employees. The study is carried out as a statistical-empirical cross-sectional study. The database used was obtained from the 5th European Working Conditions Survey 2010. The results reveal a common core with respect to the factors that determine workplace bullying. Despite this common base that integrates both models, the distinctive features of the harassed employee within the public sector deal with age, full-time work, the greater nighttime associated with certain public service professions, and a lower level of motivation. The present work summarizes a set of implications and proposes that, under normal conditions, workplace bullying could be reduced if job demands are limited and job resources are increased.

Single nucleotide polymorphisms associated with coronary heart disease predict incident ischemic stroke in the atherosclerosis risk in communities study.

PubMed

Morrison, Alanna C; Bare, Lance A; Luke, May M; Pankow, James S; Mosley, Thomas H; Devlin, James J; Willerson, James T; Boerwinkle, Eric

2008-01-01

Ischemic stroke and coronary heart disease (CHD) may share genetic factors contributing to a common etiology. This study investigates whether 51 single nucleotide polymorphisms (SNPs) associated with CHD in multiple antecedent studies are associated with incident ischemic stroke in the Atherosclerosis Risk in Communities (ARIC) study. From the multiethnic ARIC cohort of 14,215 individuals, 495 validated ischemic strokes were identified. Cox proportional hazards models, adjusted for age and gender, identified three SNPs in Whites and two SNPs in Blacks associated with incident stroke (p

Creative style, personality, and artistic endeavor.

PubMed

Gelade, Garry A

2002-08-01

Research has shown that creative style, as measured by the Kirton Adaption-Innovation Inventory (KAI; M. J. Kirton, 1976), is correlated with more than 30 different personality traits. In this article, the author demonstrates that many of these correlations can be understood within the framework of the Five-Factor Model of personality and shows that the predominant correlates of creative style are personality indicators in the domains of the factors Conscientiousness, Openness to Experience, and, to a lesser extent, Extraversion. These findings provide a basis for comparing the personality traits associated with creative style and occupational creativity. High scorers on the KAI (innovators) differ from both average and creative scientists but have personality characteristics similar to those of artists. This finding suggests that the artistic personality may be more common than is generally supposed and that common factors might underlie both artistic endeavor and creative style.

A murine model of acute myeloid leukemia with Evi1 overexpression and autocrine stimulation by an intracellular form of GM-CSF in DA-3 cells.

PubMed

Cardona, Maria E; Simonson, Oscar E; Oprea, Iulian I; Moreno, Pedro M D; Silva-Lara, Maria F; Mohamed, Abdalla J; Christensson, Birger; Gahrton, Gösta; Dilber, M Sirac; Smith, C I Edvard; Arteaga, H Jose

2016-01-01

The poor treatment response of acute myeloid leukemia (AML) overexpressing high-risk oncogenes such as EVI1, demands specific animal models for new treatment evaluations. Evi1 is a common site of activating integrations in murine leukemia virus (MLV)-induced AML and in retroviral and lentiviral gene-modified HCS. Still, a model of overt AML induced by Evi1 has not been generated. Cell lines from MLV-induced AML are growth factor-dependent and non-transplantable. Hence, for the leukemia maintenance in the infected animals, a growth factor source such as chronic immune response has been suggested. We have investigated whether these leukemias are transplantable if provided with growth factors. We show that the Evi1(+)DA-3 cells modified to express an intracellular form of GM-CSF, acquired growth factor independence and transplantability and caused an overt leukemia in syngeneic hosts, without increasing serum GM-CSF levels. We propose this as a general approach for modeling different forms of high-risk human AML using similar cell lines.

The Challenge of Understanding Cerebral White Matter Injury in the Premature Infant

PubMed Central

Elitt, Christopher M.; Rosenberg, Paul A.

2014-01-01

White matter injury in the premature infant leads to motor and more commonly behavioral and cognitive problems that are a tremendous burden to society. While there has been much progress in understanding unique vulnerabilities of developing oligodendrocytes over the past 30 years, there remain no proven therapies for the premature infant beyond supportive care. The lack of translational progress may be partially explained by the challenge of developing relevant animal models when the etiology remains unclear, as is the case in this disorder. There has been an emphasis on hypoxia-ischemia and infection/inflammation as upstream etiologies, but less consideration of other contributory factors. This review highlights the evolution of white matter pathology in the premature infant, discusses the prevailing proposed etiologies, critically analyzes a sampling of common animal models and provides detailed support for our hypothesis that nutritional and hormonal deprivation may be additional factors playing critical and overlooked roles in white matter pathology in the premature infant. PMID:24838063

A unifying framework of the demand for transnational medical travel.

PubMed

Osterle, August; Johnson, Tricia; Delgado, Jose

2013-01-01

Transnational medical travel has gained attention recently as a strategy for patients to obtain care that is higher quality, costs less, or offers improved access relative to care provided within their home countries. This article examines institutional environments in the European Union and United States that influence transnational medical travel, describes the conceptual model of demand for medical travel, and illustrates individual dimensions in the conceptual model of medical travel using a series of case studies. The conceptual model of medical travel is predicated on Andersen's behavioral model of health services. Transnational medical travel is a heterogeneous phenomenon that is influenced by a number of patient-related factors and by the institutional environment in which the patient resides. While cost, access, and quality are commonly cited factors that influence a patient's decision regarding where to seek care, multiple factors may simultaneously influence the decision about the destination for care, including culture, social factors, and the institutional environment. The conceptual framework addresses the patient-related factors that influence where a patient seeks care. This framework can help researchers and regulatory bodies to evaluate the opportunities and the risks of transnational medical travel and help providers and governments to develop international patient programs.

The prosocial personality and its facets: genetic and environmental architecture of mother-reported behavior of 7-year-old twins

PubMed Central

Knafo-Noam, Ariel; Uzefovsky, Florina; Israel, Salomon; Davidov, Maayan; Zahn-Waxler, Caroyln

2015-01-01

Children vary markedly in their tendency to behave prosocially, and recent research has implicated both genetic and environmental factors in this variability. Yet, little is known about the extent to which different aspects of prosociality constitute a single dimension (the prosocial personality), and to the extent they are intercorrelated, whether these aspects share their genetic and environmental origins. As part of the Longitudinal Israeli Study of Twins (LIST), mothers of 183 monozygotic (MZ) and dizygotic (DZ) 7-year-old twin pairs (51.6% male) reported regarding their children’s prosociality using questionnaires. Five prosociality facets (sharing, social concern, kindness, helping, and empathic concern) were identified. All five facets intercorrelated positively (r > 0.39) suggesting a single-factor structure to the data, consistent with the theoretical idea of a single prosociality trait. Higher MZ than DZ twin correlations indicated genetic contributions to each prosociality facet. A common-factor-common-pathway multivariate model estimated high (69%) heritability for the common prosociality factor, with the non-shared environment and error accounting for the remaining variance. For each facet, unique genetic and environmental contributions were identified as well. The results point to the presence of a broad prosociality phenotype, largely affected by genetics; whereas additional genetic and environmental factors contribute to different aspects of prosociality, such as helping and sharing. PMID:25762952

Robust Bayesian linear regression with application to an analysis of the CODATA values for the Planck constant

NASA Astrophysics Data System (ADS)

Wübbeler, Gerd; Bodnar, Olha; Elster, Clemens

2018-02-01

Weighted least-squares estimation is commonly applied in metrology to fit models to measurements that are accompanied with quoted uncertainties. The weights are chosen in dependence on the quoted uncertainties. However, when data and model are inconsistent in view of the quoted uncertainties, this procedure does not yield adequate results. When it can be assumed that all uncertainties ought to be rescaled by a common factor, weighted least-squares estimation may still be used, provided that a simple correction of the uncertainty obtained for the estimated model is applied. We show that these uncertainties and credible intervals are robust, as they do not rely on the assumption of a Gaussian distribution of the data. Hence, common software for weighted least-squares estimation may still safely be employed in such a case, followed by a simple modification of the uncertainties obtained by that software. We also provide means of checking the assumptions of such an approach. The Bayesian regression procedure is applied to analyze the CODATA values for the Planck constant published over the past decades in terms of three different models: a constant model, a straight line model and a spline model. Our results indicate that the CODATA values may not have yet stabilized.

Prevalence of Common Mental Disorders and Associated Factors among People with Glaucoma Attending Outpatient Clinic at Menelik II Referral Hospital, Addis Ababa, Ethiopia.

PubMed

Bedasso, Kufa; Bedaso, Asres; Feyera, Fetuma; Gebeyehu, Abebaw; Yohannis, Zegeye

2016-01-01

The burden of blindness from glaucoma is high. Therefore, people suffering from a serious eye disease such as glaucoma, which can lead to blindness, usually have an emotional disturbance on the patient. Untreated psychiatric illness is associated with increased morbidity and increased costs of care. This study aimed to assess prevalence of common mental disorders and associated factors among people with Glaucoma attending Menelik II referral hospital, Addis Ababa, Ethiopia, 2014. Institution based Cross-sectional study design was conducted in the Department of Ophthalmology Menelik II Referral Hospital from April 10 to May 15, 2014. 423 participants who had undergone through investigation, examination and diagnosed as patients of glaucoma were selected randomly from the glaucoma clinic. Data were collected through face to face interview using Self Reporting Questionnaire consisted of 20 items. Study subjects who scored ≥11 from SRQ-20 were considered as having common mental disorders. Bivariate and multivariable logistic regression analysis with 95% CI were done and variables with P<0.05 in the final model were identified as independent factors associated with common mental disorders. Four hundred five patients with glaucoma were included in our study with response rate of 95.7% and 64.5% were males. The average age was 59±13.37 years. Common mental disorders were observed in 23.2% of Glaucoma patients. It is quite obvious that levels of CMDs were high among patients with glaucoma. There was a significant association between age, sex, chronic physical illness, income and duration of illness at P < 0.05. Symptoms of common mental disorders were the commonest comorbidities among patients with glaucoma. It will be better to assess and treat Common mental disorders as a separate illness in patients with glaucoma.

A combined model of human erythropoiesis and granulopoiesis under growth factor and chemotherapy treatment

PubMed Central

2014-01-01

Background Haematotoxicity of conventional chemotherapies often results in delays of treatment or reduction of chemotherapy dose. To ameliorate these side-effects, patients are routinely treated with blood transfusions or haematopoietic growth factors such as erythropoietin (EPO) or granulocyte colony-stimulating factor (G-CSF). For the latter ones, pharmaceutical derivatives are available, which differ in absorption kinetics, pharmacokinetic and -dynamic properties. Due to the complex interaction of cytotoxic effects of chemotherapy and the stimulating effects of different growth factor derivatives, optimal treatment is a non-trivial task. In the past, we developed mathematical models of thrombopoiesis, granulopoiesis and erythropoiesis under chemotherapy and growth-factor applications which can be used to perform clinically relevant predictions regarding the feasibility of chemotherapy schedules and cytopenia prophylaxis with haematopoietic growth factors. However, interactions of lineages and growth-factors were ignored so far. Results To close this gap, we constructed a hybrid model of human granulopoiesis and erythropoiesis under conventional chemotherapy, G-CSF and EPO applications. This was achieved by combining our single lineage models of human erythropoiesis and granulopoiesis with a common stem cell model. G-CSF effects on erythropoiesis were also implemented. Pharmacodynamic models are based on ordinary differential equations describing proliferation and maturation of haematopoietic cells. The system is regulated by feedback loops partly mediated by endogenous and exogenous EPO and G-CSF. Chemotherapy is modelled by depletion of cells. Unknown model parameters were determined by fitting the model predictions to time series data of blood counts and cytokine profiles. Data were extracted from literature or received from cooperating clinical study groups. Our model explains dynamics of mature blood cells and cytokines after growth-factor applications in healthy volunteers. Moreover, we modelled 15 different chemotherapeutic drugs by estimating their bone marrow toxicity. Taking into account different growth-factor schedules, this adds up to 33 different chemotherapy regimens explained by the model. Conclusions We conclude that we established a comprehensive biomathematical model to explain the dynamics of granulopoiesis and erythropoiesis under combined chemotherapy, G-CSF, and EPO applications. We demonstrate how it can be used to make predictions regarding haematotoxicity of yet untested chemotherapy and growth-factor schedules. PMID:24886056

Examining the association of abortion history and current mental health: A reanalysis of the National Comorbidity Survey using a common-risk-factors model.

PubMed

Steinberg, Julia R; Finer, Lawrence B

2011-01-01

Using the US National Comorbidity Survey (NCS), Coleman, Coyle, Shuping, and Rue (2009) published an analysis indicating that compared to women who had never had an abortion, women who had reported an abortion were at an increased risk of several anxiety, mood, and substance use disorders. Here, we show that those results are not replicable. That is, using the same data, sample, and codes as indicated by those authors, it is not possible to replicate the simple bivariate statistics testing the relationship of ever having had an abortion to each mental health disorder when no factors were controlled for in analyses (Table 2 in Coleman et al., 2009). Furthermore, among women with prior pregnancies in the NCS, we investigated whether having zero, one, or multiple abortions (abortion history) was associated with having a mood, anxiety, or substance use disorder at the time of the interview. In doing this, we tested two competing frameworks: the abortion-as-trauma versus the common-risk-factors approach. Our results support the latter framework. In the bivariate context when no other factors were included in models, abortion history was not related to having a mood disorder, but it was related to having an anxiety or substance use disorder. When prior mental health and violence experience were controlled in our models, no significant relation was found between abortion history and anxiety disorders. When these same risk factors and other background factors were controlled, women who had multiple abortions remained at an increased risk of having a substance use disorder compared to women who had no abortions, likely because we were unable to control for other risk factors associated with having an abortion and substance use. Policy, practice, and research should focus on assisting women at greatest risk of having unintended pregnancies and having poor mental health-those with violence in their lives and prior mental health problems. Copyright © 2010 Elsevier Ltd. All rights reserved.

Genome-Wide Investigation of WRKY Transcription Factors Involved in Terminal Drought Stress Response in Common Bean

PubMed Central

Wu, Jing; Chen, Jibao; Wang, Lanfen; Wang, Shumin

2017-01-01

WRKY transcription factor plays a key role in drought stress. However, the characteristics of the WRKY gene family in the common bean (Phaseolus vulgaris L.) are unknown. In this study, we identified 88 complete WRKY proteins from the draft genome sequence of the “G19833” common bean. The predicted genes were non-randomly distributed in all chromosomes. Basic information, amino acid motifs, phylogenetic tree and the expression patterns of PvWRKY genes were analyzed, and the proteins were classified into groups 1, 2, and 3. Group 2 was further divided into five subgroups: 2a, 2b, 2c, 2d, and 2e. Finally, we detected 19 WRKY genes that were responsive to drought stress using qRT-PCR; 11 were down-regulated, and 8 were up-regulated under drought stress. This study comprehensively examines WRKY proteins in the common bean, a model food legume, and it provides a foundation for the functional characterization of the WRKY family and opportunities for understanding the mechanisms of drought stress tolerance in this plant. PMID:28386267

Genome-Wide Investigation of WRKY Transcription Factors Involved in Terminal Drought Stress Response in Common Bean.

PubMed

Wu, Jing; Chen, Jibao; Wang, Lanfen; Wang, Shumin

2017-01-01

WRKY transcription factor plays a key role in drought stress. However, the characteristics of the WRKY gene family in the common bean ( Phaseolus vulgaris L.) are unknown. In this study, we identified 88 complete WRKY proteins from the draft genome sequence of the "G19833" common bean. The predicted genes were non-randomly distributed in all chromosomes. Basic information, amino acid motifs, phylogenetic tree and the expression patterns of PvWRKY genes were analyzed, and the proteins were classified into groups 1, 2, and 3. Group 2 was further divided into five subgroups: 2a, 2b, 2c, 2d, and 2e. Finally, we detected 19 WRKY genes that were responsive to drought stress using qRT-PCR; 11 were down-regulated, and 8 were up-regulated under drought stress. This study comprehensively examines WRKY proteins in the common bean, a model food legume, and it provides a foundation for the functional characterization of the WRKY family and opportunities for understanding the mechanisms of drought stress tolerance in this plant.

GENETIC AND ENVIRONMENTAL EFFECTS ON BODY MASS INDEX DURING ADOLESCENCE: A PROSPECTIVE STUDY AMONG FINNISH TWINS

PubMed Central

Lajunen, Hanna-Reetta; Kaprio, Jaakko; Keski-Rahkonen, Anna; Rose, Richard J.; Pulkkinen, Lea; Rissanen, Aila; Silventoinen, Karri

2009-01-01

Objective To study genetic and environmental factors affecting body mass index (BMI) and BMI phenotypic correlations across adolescence. Design Prospective, population-based, twin cohort study. Subjects and methods We used twin modeling in 2413 monozygotic and same-sex and opposite-sex dizygotic Finnish twin pairs born in 1983–1987 and assessed by self-report questionnaires at 11–12, 14, and 17 years. Results Heritability of BMI was estimated to be 0.58–0.69 among 11–12- and 14-year-old boys and girls, 0.83 among 17-year-old boys and 0.74 among girls. Common environmental effects shared by siblings were 0.15–0.24 among 11–12- and 14-year-old boys and girls but no longer discernible at 17 y. Unique environmental effects were 0.15–0.23. Additive genetic factors explained 90–96% of the BMI phenotypic correlations across adolescence, whereas unique environmental factors explained the rest. Common environment had no effect on BMI phenotypic correlations. Conclusions The genetic contribution to BMI is strong during adolescence, and it mainly explains BMI phenotypic correlations across adolescence. Common environmental factors have an effect on BMI during early adolescence, but that effect disappears by late adolescence. PMID:19337205

Psychometric properties of a suicide screen for adjudicated youth in residential care.

PubMed

Langhinrichsen-Rohling, Jennifer; Hudson, Kenneth; Lamis, Dorian A; Carr, Nicole

2012-04-01

There is a need to efficiently and effectively screen adjudicated youth residing within the juvenile justice system for suicide proneness. Accordingly, in the current study, the psychometric properties of the Life Attitude Schedule: Short Form (LAS:S), a 24-item risk assessment for suicide proneness, were assessed using data from adjudicated youth residing in an alternative sentencing facility (n = 130). As predicted, statistically significant correlations were obtained between total LAS:S suicide proneness scores and reports of recent suicide ideation and hopelessness. Contrary to expectation, the previously reported 2-factor model for the LAS:S, with Factor 1 representing physical unhealthiness and Factor 2 representing psychological death, poorly fit the data. In adjudicated youth, we found that a single factor model derived from the 4 LAS:S subscales produced a better fit to the data than the 2-factor model. The death-related, self-related, injury-related, and negative health-related behaviors contained on the LAS:S shared common variance in these youth. A clinical implication is that practitioners can effectively use the total LAS:S score when screening adjudicated youth for suicide proneness.

Applicability of the Social Development Model to Urban Ethnic Minority Youth: Examining the Relationship between External Constraints, Family Socialization, and Problem Behaviors

PubMed Central

Choi, Yoonsun; Harachi, Tracy W.; Gillmore, Mary Rogers; Catalano, Richard F.

2011-01-01

The development of preventive interventions targeting adolescent problem behaviors requires a thorough understanding of risk and protective factors for such behaviors. However, few studies examine whether different cultural and ethnic groups share these factors. This study is an attempt to fill a gap in research by examining similarities and differences in risk factors across racial and ethnic groups. The social development model has shown promise in organizing predictors of problem behaviors. This article investigates whether a version of that model can be generalized to youth in different racial and ethnic groups (N = 2,055, age range from 11 to 15), including African American (n = 478), Asian Pacific Islander (API) American (n = 491), multiracial (n = 442), and European American (n = 644) youth. The results demonstrate that common risk factors can be applied to adolescents, regardless of their race and ethnicity. The findings also demonstrate that there are racial and ethnic differences in the magnitudes of relationships among factors that affect problem behaviors. Further study is warranted to develop a better understanding of these differential magnitudes. PMID:21625351

Dimensions of Credibility in Models and Simulations

NASA Technical Reports Server (NTRS)

Steele, Martin J.

2008-01-01

Based on the National Aeronautics and Space Administration's (NASA's) work in developing a standard for models and simulations (M&S), the subject of credibility in M&S became a distinct focus. This is an indirect result from the Space Shuttle Columbia Accident Investigation Board (CAIB), which eventually resulted in an action, among others, to improve the rigor in NASA's M&S practices. The focus of this action came to mean a standardized method for assessing and reporting results from any type of M&S. As is typical in the standards development process, this necessarily developed into defming a common terminology base, common documentation requirements (especially for M&S used in critical decision making), and a method for assessing the credibility of M&S results. What surfaced in the development of the NASA Standard was the various dimensions credibility to consider when accepting the results from any model or simulation analysis. The eight generally relevant factors of credibility chosen in the NASA Standard proved only one aspect in the dimensionality of M&S credibility. At the next level of detail, the full comprehension of some of the factors requires an understanding along a couple of dimensions as well. Included in this discussion are the prerequisites for the appropriate use of a given M&S, the choice of factors in credibility assessment with their inherent dimensionality, and minimum requirements for fully reporting M&S results.

A review of vulnerability and risks for schizophrenia: Beyond the two hit hypothesis

PubMed Central

Davis, Justin; Eyre, Harris; Jacka, Felice N; Dodd, Seetal; Dean, Olivia; McEwen, Sarah; Debnath, Monojit; McGrath, John; Maes, Michael; Amminger, Paul; McGorry, Patrick D; Pantelis, Christos; Berk, Michael

2016-01-01

Schizophrenia risk has often been conceptualized using a model which requires two hits in order to generate the clinical phenotype—the first as an early priming in a genetically predisposed individual and the second a likely environmental insult. The aim of this paper was to review the literature and reformulate this binary risk-vulnerability model. We sourced the data for this narrative review from the electronic database PUBMED. Our search terms were not limited by language or date of publication. The development of schizophrenia may be driven by genetic vulnerability interacting with multiple vulnerability factors including lowered prenatal vitamin D exposure, viral infections, smoking intelligence quotient, social cognition cannabis use, social defeat, nutrition and childhood trauma. It is likely that these genetic risks, environmental risks and vulnerability factors are cumulative and interactive with each other and with critical periods of neurodevelopmental vulnerability. The development of schizophrenia is likely to be more complex and nuanced than the binary two hit model originally proposed nearly thirty years ago. Risk appears influenced by a more complex process involving genetic risk interfacing with multiple potentially interacting hits and vulnerability factors occurring at key periods of neurodevelopmental activity, which culminate in the expression of disease state. These risks are common across a number of neuropsychiatric and medical disorders, which might inform common preventive and intervention strategies across non-communicable disorders. PMID:27073049

New evidence on the validity of the Arnett Caregiver Interaction Scale: Results from the Early Childhood Longitudinal Study-Birth Cohort

PubMed Central

Colwell, Nicole; Gordon, Rachel A.; Fujimoto, Ken; Kaestner, Robert; Korenman, Sanders

2013-01-01

The Arnett Caregiver Interaction Scale (CIS) has been widely used in research studies to measure the quality of caregiver–child interactions. The scale was modeled on a well-established theory of parenting, but there are few psychometric studies of its validity. We applied factor analyses and item response theory methods to assess the psychometric properties of the Arnett CIS in a national sample of toddlers in home-based care and preschoolers in center-based care from the Early Childhood Longitudinal Study-Birth Cohort. We found that a bifactor structure (one common factor and a second set of specific factors) best fits the data. In the Arnett CIS, the bifactor model distinguishes a common substantive dimension from two methodological dimensions (for positively and negatively oriented items). Despite the good fit of this model, the items are skewed (most teachers/caregivers display positive interactions with children) and, as a result, the Arnett CIS is not well suited to distinguish between caregivers who are “highly” versus “moderately” positive in their interactions with children, according to the items on the scale. Regression-adjusted associations between the Arnett CIS and child outcomes are small, especially for preschoolers in centers. We encourage future scale development work on measures of child care quality by early childhood scholars. PMID:24058264

Models for randomly distributed nanoscopic domains on spherical vesicles

NASA Astrophysics Data System (ADS)

Anghel, Vinicius N. P.; Bolmatov, Dima; Katsaras, John

2018-06-01

The existence of lipid domains in the plasma membrane of biological systems has proven controversial, primarily due to their nanoscopic size—a length scale difficult to interrogate with most commonly used experimental techniques. Scattering techniques have recently proven capable of studying nanoscopic lipid domains populating spherical vesicles. However, the development of analytical methods able of predicting and analyzing domain pair correlations from such experiments has not kept pace. Here, we developed models for the random distribution of monodisperse, circular nanoscopic domains averaged on the surface of a spherical vesicle. Specifically, the models take into account (i) intradomain correlations corresponding to form factors and interdomain correlations corresponding to pair distribution functions, and (ii) the analytical computation of interdomain correlations for cases of two and three domains on a spherical vesicle. In the case of more than three domains, these correlations are treated either by Monte Carlo simulations or by spherical analogs of the Ornstein-Zernike and Percus-Yevick (PY) equations. Importantly, the spherical analog of the PY equation works best in the case of nanoscopic size domains, a length scale that is mostly inaccessible by experimental approaches such as, for example, fluorescent techniques and optical microscopies. The analytical form factors and structure factors of nanoscopic domains populating a spherical vesicle provide a new and important framework for the quantitative analysis of experimental data from commonly studied phase-separated vesicles used in a wide range of biophysical studies.

The Genetic Covariation between Fear Conditioning and Self-Report Fears

PubMed Central

Hettema, John M.; Annas, Peter; Neale, Michael C.; Fredrikson, Mats; Sci, Dr Med; Kendler, Kenneth S.

2008-01-01

Background Fear conditioning is a traditional model for the acquisition of phobias, while behavioral therapies utilize processes underlying extinction to treat phobic and other anxiety disorders. Furthermore, fear conditioning has been proposed as an endophenotype for genetic studies of anxiety disorders. While prior studies have demonstrated that fear conditioning and self-report fears are heritable, no studies have determined whether they share a common genetic basis. Methods We obtained fear conditioning data from 173 twin pairs from the Swedish Twin Registry who also provided self-report ratings of 16 common fears. Using multivariate structural equation modeling, we analyzed factor-derived scores for the subjective fear ratings together with the electrophysiologic skin conductance responses during habituation, acquisition, and extinction to determine the extent of their genetic covariation. Results Phenotypic correlations between experimental and self-report fear measures were modest and, and counter-intuitively, negative; that is, subjects who reported themselves as more fearful had smaller electrophysiologic responses. Best-fit models estimated a significant (negative) genetic correlation between them, although genetic factors underlying fear conditioning accounted for only 9% of individual differences in self-report fears. Conclusions Experimentally-derived fear conditioning measures share only a small portion of the genetic factors underlying individual differences in subjective fears, cautioning against relying too heavily on the former as an endophenotype for genetic studies of phobic disorders. PMID:17698042

Measuring student engagement among elementary students: pilot of the Student Engagement Instrument--Elementary Version.

PubMed

Carter, Chandra P; Reschly, Amy L; Lovelace, Matthew D; Appleton, James J; Thompson, Dianne

2012-06-01

Early school withdrawal, commonly referred to as dropout, is associated with a plethora of negative outcomes for students, schools, and society. Student engagement, however, presents as a promising theoretical model and cornerstone of school completion interventions. The purpose of the present study was to validate the Student Engagement Instrument-Elementary Version (SEI-E). The psychometric properties of this measure were assessed based on the responses of an ethnically diverse sample of 1,943 students from an urban locale. Exploratory and confirmatory factor analyses indicated that the 4-factor model of student engagement provided the best fit for the current data, which is divergent from previous SEI studies suggesting 5- and 6-factor models. Discussion and implications of these findings are presented in the context of student engagement and dropout prevention. (PsycINFO Database Record (c) 2012 APA, all rights reserved).

Multi-Collinearity Based Model Selection for Landslide Susceptibility Mapping: A Case Study from Ulus District of Karabuk, Turkey

NASA Astrophysics Data System (ADS)

Sahin, E. K.; Colkesen, I., , Dr; Kavzoglu, T.

2017-12-01

Identification of localities prone to landslide areas plays an important role for emergency planning, disaster management and recovery planning. Due to its great importance for disaster management, producing accurate and up-to-date landslide susceptibility maps is essential for hazard mitigation purpose and regional planning. The main objective of the present study was to apply multi-collinearity based model selection approach for the production of a landslide susceptibility map of Ulus district of Karabuk, Turkey. It is a fact that data do not contain enough information to describe the problem under consideration when the factors are highly correlated with each other. In such cases, choosing a subset of the original features will often lead to better performance. This paper presents multi-collinearity based model selection approach to deal with the high correlation within the dataset. Two collinearity diagnostic factors (Tolerance (TOL) and the Variance Inflation Factor (VIF)) are commonly used to identify multi-collinearity. Values of VIF that exceed 10.0 and TOL values less than 1.0 are often regarded as indicating multi-collinearity. Five causative factors (slope length, curvature, plan curvature, profile curvature and topographical roughness index) were found highly correlated with each other among 15 factors available for the study area. As a result, the five correlated factors were removed from the model estimation, and performances of the models including the remaining 10 factors (aspect, drainage density, elevation, lithology, land use/land cover, NDVI, slope, sediment transport index, topographical position index and topographical wetness index) were evaluated using logistic regression. The performance of prediction model constructed with 10 factors was compared to that of 15-factor model. The prediction performance of two susceptibility maps was evaluated by overall accuracy and the area under the ROC curve (AUC) values. Results showed that overall accuracy and AUC was calculated as 77.15% and 96.62% respectively for the model with 10 selected factors whilst they were estimated as 73.45% and 89.45% respectively for the model with all factors. It is clear that the multi-collinearity based model outperformed the conventional model in the mapping of landslide susceptibility.

What determines the spectrum of protein native state structures?

PubMed

Lezon, Timothy R; Banavar, Jayanth R; Lesk, Arthur M; Maritan, Amos

2006-05-01

We present a brief summary of the key factors underlying protein structure, as developed in the investigations of Pauling, Ramachandran, and Rose. We then outline a simplified physical model of proteins that focuses on geometry and symmetry. Although this model superficially appears unrelated to the detailed chemical descriptions commonly applied to proteins, we show that it captures the essential elements of the chemistry and provides a unified framework for understanding the common characteristics of folded proteins. We suggest that the spectrum of protein native state structures is determined by geometry and symmetry and the role of the sequence is to choose its native state structure from this predetermined menu. 2006 Wiley-Liss, Inc.

Developing a model for agile supply: an empirical study from Iranian pharmaceutical supply chain.

PubMed

Rajabzadeh Ghatari, Ali; Mehralian, Gholamhossein; Zarenezhad, Forouzandeh; Rasekh, Hamid Reza

2013-01-01

Agility is the fundamental characteristic of a supply chain needed for survival in turbulent markets, where environmental forces create additional uncertainty resulting in higher risk in the supply chain management. In addition, agility helps providing the right product, at the right time to the consumer. The main goal of this research is therefore to promote supplier selection in pharmaceutical industry according to the formative basic factors. Moreover, this paper can configure its supply network to achieve the agile supply chain. The present article analyzes the supply part of supply chain based on SCOR model, used to assess agile supply chains by highlighting their specific characteristics and applicability in providing the active pharmaceutical ingredient (API). This methodology provides an analytical modeling; the model enables potential suppliers to be assessed against the multiple criteria using both quantitative and qualitative measures. In addition, for making priority of critical factors, TOPSIS algorithm has been used as a common technique of MADM model. Finally, several factors such as delivery speed, planning and reorder segmentation, trust development and material quantity adjustment are identified and prioritized as critical factors for being agile in supply of API.

Developing a Model for Agile Supply: an Empirical Study from Iranian Pharmaceutical Supply Chain

PubMed Central

Rajabzadeh Ghatari, Ali; Mehralian, Gholamhossein; Zarenezhad, Forouzandeh; Rasekh, Hamid Reza

2013-01-01

Agility is the fundamental characteristic of a supply chain needed for survival in turbulent markets, where environmental forces create additional uncertainty resulting in higher risk in the supply chain management. In addition, agility helps providing the right product, at the right time to the consumer. The main goal of this research is therefore to promote supplier selection in pharmaceutical industry according to the formative basic factors. Moreover, this paper can configure its supply network to achieve the agile supply chain. The present article analyzes the supply part of supply chain based on SCOR model, used to assess agile supply chains by highlighting their specific characteristics and applicability in providing the active pharmaceutical ingredient (API). This methodology provides an analytical modeling; the model enables potential suppliers to be assessed against the multiple criteria using both quantitative and qualitative measures. In addition, for making priority of critical factors, TOPSIS algorithm has been used as a common technique of MADM model. Finally, several factors such as delivery speed, planning and reorder segmentation, trust development and material quantity adjustment are identified and prioritized as critical factors for being agile in supply of API. PMID:24250689

Soil Erosion map of Europe based on high resolution input datasets

NASA Astrophysics Data System (ADS)

Panagos, Panos; Borrelli, Pasquale; Meusburger, Katrin; Ballabio, Cristiano; Alewell, Christine

2015-04-01

Modelling soil erosion in European Union is of major importance for agro-environmental policies. Soil erosion estimates are important inputs for the Common Agricultural Policy (CAP) and the implementation of the Soil Thematic Strategy. Using the findings of a recent pan-European data collection through the EIONET network, it was concluded that most Member States are applying the empirical Revised Universal Soil Loss Equation (RUSLE) for the modelling soil erosion at National level. This model was chosen for the pan-European soil erosion risk assessment and it is based on 6 input factors. Compared to past approaches, each of the factors is modelled using the latest pan-European datasets, expertise and data from Member states and high resolution remote sensing data. The soil erodibility (K-factor) is modelled using the recently published LUCAS topsoil database with 20,000 point measurements and incorporating the surface stone cover which can reduce K-factor by 15%. The rainfall erosivity dataset (R-factor) has been implemented using high temporal resolution rainfall data from more than 1,500 precipitation stations well distributed in Europe. The cover-management (C-factor) incorporates crop statistics and management practices such as cover crops, tillage practices and plant residuals. The slope length and steepness (combined LS-factor) is based on the first ever 25m Digital Elevation Model (DEM) of Europe. Finally, the support practices (P-factor) is modelled for first time at this scale taking into account the 270,000 LUCAS earth observations and the Good Agricultural and Environmental Condition (GAEC) that farmers have to follow in Europe. The high resolution input layers produce the final soil erosion risk map at 100m resolution and allow policy makers to run future land use, management and climate change scenarios.

Creating Welcoming Spaces for Lesbian, Gay, Bisexual, and Transgender (LGBT) Patients: An Evaluation of the Health Care Environment.

PubMed

McClain, Zachary; Hawkins, Linda A; Yehia, Baligh R

2016-01-01

Health outcomes are affected by patient, provider, and environmental factors. Previous studies have evaluated patient-level factors; few focusing on environment. Safe clinical spaces are important for lesbian, gay, bisexual, and transgender (LGBT) communities. This study evaluates current models of LGBT health care delivery, identifies strengths and weaknesses, and makes recommendations for LGBT spaces. Models are divided into LGBT-specific and LGBT-embedded care delivery. Advantages to both models exist, and they provide LGBT patients different options of healthcare. Yet certain commonalities must be met: a clean and confidential system. Once met, LGBT-competent environments and providers can advocate for appropriate care for LGBT communities, creating environments where they would want to seek care.

Mapping common aphasia assessments to underlying cognitive processes and their neural substrates

PubMed Central

Lacey, Elizabeth H.; Skipper-Kallal, LM; Xing, S; Fama, ME; Turkeltaub, PE

2017-01-01

Background Understanding the relationships between clinical tests, the processes they measure, and the brain networks underlying them, is critical in order for clinicians to move beyond aphasia syndrome classification toward specification of individual language process impairments. Objective To understand the cognitive, language, and neuroanatomical factors underlying scores of commonly used aphasia tests. Methods 25 behavioral tests were administered to a group of 38 chronic left hemisphere stroke survivors and a high resolution MRI was obtained. Test scores were entered into a principal components analysis to extract the latent variables (factors) measured by the tests. Multivariate lesion-symptom mapping was used to localize lesions associated with the factor scores. Results The principal components analysis yielded four dissociable factors, which we labeled Word Finding/Fluency, Comprehension, Phonology/Working Memory Capacity, and Executive Function. While many tests loaded onto the factors in predictable ways, some relied heavily on factors not commonly associated with the tests. Lesion symptom mapping demonstrated discrete brain structures associated with each factor, including frontal, temporal, and parietal areas extending beyond the classical language network. Specific functions mapped onto brain anatomy largely in correspondence with modern neural models of language processing. Conclusions An extensive clinical aphasia assessment identifies four independent language functions, relying on discrete parts of the left middle cerebral artery territory. A better understanding of the processes underlying cognitive tests and the link between lesion and behavior may lead to improved aphasia diagnosis, and may yield treatments better targeted to an individual’s specific pattern of deficits and preserved abilities. PMID:28135902

An analytical model for pressure of volume fractured tight oil reservoir with horizontal well

NASA Astrophysics Data System (ADS)

Feng, Qihong; Dou, Kaiwen; Zhang, Xianmin; Xing, Xiangdong; Xia, Tian

2017-05-01

The property of tight oil reservoir is worse than common reservoir that we usually seen before, the porosity and permeability is low, the diffusion is very complex. Therefore, the ordinary depletion method is useless here. The volume fracture breaks through the conventional EOR mechanism, which set the target by amplifying the contact area of fracture and reservoir so as to improving the production of every single well. In order to forecast the production effectively, we use the traditional dual-porosity model, build an analytical model for production of volume fractured tight oil reservoir with horizontal well, and get the analytical solution in Laplace domain. Then we construct the log-log plot of dimensionless pressure and time by stiffest conversion. After that, we discuss the influential factors of pressure. Several factors like cross flow, skin factors and threshold pressure gradient was analyzed in the article. This model provides a useful method for tight oil production forecast and it has certain guiding significance for the production capacity prediction and dynamic analysis.

On the importance of controlling for effort in analysis of count survey data: Modeling population change from Christmas Bird Count data

USGS Publications Warehouse

Link, W.A.; Sauer, J.R.; Helbig, Andreas J.; Flade, Martin

1999-01-01

Count survey data are commonly used for estimating temporal and spatial patterns of population change. Since count surveys are not censuses, counts can be influenced by 'nuisance factors' related to the probability of detecting animals but unrelated to the actual population size. The effects of systematic changes in these factors can be confounded with patterns of population change. Thus, valid analysis of count survey data requires the identification of nuisance factors and flexible models for their effects. We illustrate using data from the Christmas Bird Count (CBC), a midwinter survey of bird populations in North America. CBC survey effort has substantially increased in recent years, suggesting that unadjusted counts may overstate population growth (or understate declines). We describe a flexible family of models for the effect of effort, that includes models in which increasing effort leads to diminishing returns in terms of the number of birds counted.

Advanced Psychotherapy Training: Psychotherapy Scholars' Track, and the Apprenticeship Model

ERIC Educational Resources Information Center

Feinstein, Robert E.; Yager, Joel

2013-01-01

Background/Objective: Guided by ACGME's requirements, psychiatric residency training in psychotherapy currently focuses on teaching school-specific forms of psychotherapy (i.e., cognitive-behavioral, supportive, and psychodynamic psychotherapy). On the basis of a literature review of common factors affecting psychotherapy outcomes and…

Biomagnification of higher brominated PBDE congeners in an urban terrestrial food web in north China based on field observation of prey deliveries.

PubMed

Yu, Le-Huan; Luo, Xiao-Jun; Wu, Jiang-Ping; Liu, Li-Yu; Song, Jie; Sun, Quan-Hui; Zhang, Xiu-Lan; Chen, Da; Mai, Bi-Xian

2011-06-15

As an important group of brominated flame retardants, polybrominated diphenyl ethers (PBDEs) persist in the wildlife food webs. However, the biomagnification of PBDEs has not been adequately studied in the terrestrial food webs. In this study, a terrestrial food web composed of common kestrels, sparrows, rats, grasshoppers, and dragonflies in the urban environment from northern China was obtained. A field prey delivery study, reinforced by δ¹³C and δ¹⁵N analyses, indicates that sparrows are the primary prey items of common kestrels. Concentrations of PBDEs were in the following order: common kestrel > sparrow > rat > grasshopper and dragonfly with BDE-209 as the dominant congener. Biomagnification factors (BMFs) were calculated as the ratio between the lipid normalized concentrations in the predator and prey. The highest BMF (6.9) was determined for BDE-153 in sparrow/common kestrel food chain. Other higher brominated congeners, such as BDE-202, -203, -154, -183, -197, and -209, were also biomagnified in this terrestrial food chain with BMF of 1.3-4.7. BDE-47, -99, and -100 were found to be biodiluted from sparrow to common kestrel (BMFs < 1). Measured BMF values for BDE-153, -47, -99, and -100 were consistent with predicted values from a nonsteady-state model in American kestrels from another study. Retention factors and metabolism of BDE congeners may be confounding factors influencing the measured BMFs in this current study.

Estimating Escherichia coli loads in streams based on various physical, chemical, and biological factors

PubMed Central

Dwivedi, Dipankar; Mohanty, Binayak P.; Lesikar, Bruce J.

2013-01-01

Microbes have been identified as a major contaminant of water resources. Escherichia coli (E. coli) is a commonly used indicator organism. It is well recognized that the fate of E. coli in surface water systems is governed by multiple physical, chemical, and biological factors. The aim of this work is to provide insight into the physical, chemical, and biological factors along with their interactions that are critical in the estimation of E. coli loads in surface streams. There are various models to predict E. coli loads in streams, but they tend to be system or site specific or overly complex without enhancing our understanding of these factors. Hence, based on available data, a Bayesian Neural Network (BNN) is presented for estimating E. coli loads based on physical, chemical, and biological factors in streams. The BNN has the dual advantage of overcoming the absence of quality data (with regards to consistency in data) and determination of mechanistic model parameters by employing a probabilistic framework. This study evaluates whether the BNN model can be an effective alternative tool to mechanistic models for E. coli loads estimation in streams. For this purpose, a comparison with a traditional model (LOADEST, USGS) is conducted. The models are compared for estimated E. coli loads based on available water quality data in Plum Creek, Texas. All the model efficiency measures suggest that overall E. coli loads estimations by the BNN model are better than the E. coli loads estimations by the LOADEST model on all the three occasions (three-fold cross validation). Thirteen factors were used for estimating E. coli loads with the exhaustive feature selection technique, which indicated that six of thirteen factors are important for estimating E. coli loads. Physical factors included temperature and dissolved oxygen; chemical factors include phosphate and ammonia; biological factors include suspended solids and chlorophyll. The results highlight that the LOADEST model estimates E. coli loads better in the smaller ranges, whereas the BNN model estimates E. coli loads better in the higher ranges. Hence, the BNN model can be used to design targeted monitoring programs and implement regulatory standards through TMDL programs. PMID:24511166

Attention-deficit/hyperactivity disorder dimensionality: the reliable 'g' and the elusive 's' dimensions.

PubMed

Wagner, Flávia; Martel, Michelle M; Cogo-Moreira, Hugo; Maia, Carlos Renato Moreira; Pan, Pedro Mario; Rohde, Luis Augusto; Salum, Giovanni Abrahão

2016-01-01

The best structural model for attention-deficit/hyperactivity disorder (ADHD) symptoms remains a matter of debate. The objective of this study is to test the fit and factor reliability of competing models of the dimensional structure of ADHD symptoms in a sample of randomly selected and high-risk children and pre-adolescents from Brazil. Our sample comprised 2512 children aged 6-12 years from 57 schools in Brazil. The ADHD symptoms were assessed using parent report on the development and well-being assessment (DAWBA). Fit indexes from confirmatory factor analysis were used to test unidimensional, correlated, and bifactor models of ADHD, the latter including "g" ADHD and "s" symptom domain factors. Reliability of all models was measured with omega coefficients. A bifactor model with one general factor and three specific factors (inattention, hyperactivity, impulsivity) exhibited the best fit to the data, according to fit indices, as well as the most consistent factor loadings. However, based on omega reliability statistics, the specific inattention, hyperactivity, and impulsivity dimensions provided very little reliable information after accounting for the reliable general ADHD factor. Our study presents some psychometric evidence that ADHD specific ("s") factors might be unreliable after taking common ("g" factor) variance into account. These results are in accordance with the lack of longitudinal stability among subtypes, the absence of dimension-specific molecular genetic findings and non-specific effects of treatment strategies. Therefore, researchers and clinicians might most effectively rely on the "g" ADHD to characterize ADHD dimensional phenotype, based on currently available symptom items.

Bifactor structure of the Wechsler Preschool and Primary Scale of Intelligence--Fourth Edition.

PubMed

Watkins, Marley W; Beaujean, A Alexander

2014-03-01

The Wechsler Preschool and Primary Scale of Intelligence--Fourth Edition (WPPSI-IV; Wechsler, 2012) represents a substantial departure from its predecessor, including omission of 4 subtests, addition of 5 new subtests, and modification of the contents of the 5 retained subtests. Wechsler (2012) explicitly assumed a higher-order structure with general intelligence (g) as the second-order factor that explained all the covariation of several first-order factors but failed to consider a bifactor model. The WPPSI-IV normative sample contains 1,700 children aged 2 years and 6 months through 7 years and 7 months, bifurcated into 2 age groups: 2:6-3:11 year olds (n = 600) and 4:0-7:7 year olds (n = 1,100). This study applied confirmatory factor analysis to the WPPSI-IV normative sample data to test the fit of a bifactor model and to determine the reliability of the resulting factors. The bifactor model fit the WPPSI-IV normative sample data as well as or better than the higher-order models favored by Wechsler (2012). In the bifactor model, the general factor accounted for more variance in every subtest than did its corresponding domain-specific factor and the general factor accounted for more total and common variance than all domain-specific factors combined. Further, the domain-specific factors exhibited poor reliability independent of g (i.e., ωh coefficients of .05 to .33). These results suggest that only the general intelligence dimension was sufficiently robust and precise for clinical use. PsycINFO Database Record (c) 2014 APA, all rights reserved.

A novel genomic signature with translational significance for human idiopathic pulmonary fibrosis.

PubMed

Bauer, Yasmina; Tedrow, John; de Bernard, Simon; Birker-Robaczewska, Magdalena; Gibson, Kevin F; Guardela, Brenda Juan; Hess, Patrick; Klenk, Axel; Lindell, Kathleen O; Poirey, Sylvie; Renault, Bérengère; Rey, Markus; Weber, Edgar; Nayler, Oliver; Kaminski, Naftali

2015-02-01

The bleomycin-induced rodent lung fibrosis model is commonly used to study mechanisms of lung fibrosis and to test potential therapeutic interventions, despite the well recognized dissimilarities to human idiopathic pulmonary fibrosis (IPF). Therefore, in this study, we sought to identify genomic commonalities between the gene expression profiles from 100 IPF lungs and 108 control lungs that were obtained from the Lung Tissue Research Consortium, and rat lungs harvested at Days 3, 7, 14, 21, 28, 42, and 56 after bleomycin instillation. Surprisingly, the highest gene expression similarity between bleomycin-treated rat and IPF lungs was observed at Day 7. At this point of maximal rat-human commonality, we identified a novel set of 12 disease-relevant translational gene markers (C6, CTHRC1, CTSE, FHL2, GAL, GREM1, LCN2, MMP7, NELL1, PCSK1, PLA2G2A, and SLC2A5) that was able to separate almost all patients with IPF from control subjects in our cohort and in two additional IPF/control cohorts (GSE10667 and GSE24206). Furthermore, in combination with diffusing capacity of carbon monoxide measurements, four members of the translational gene marker set contributed to stratify patients with IPF according to disease severity. Significantly, pirfenidone attenuated the expression change of one (CTHRC1) translational gene marker in the bleomycin-induced lung fibrosis model, in transforming growth factor-β1-treated primary human lung fibroblasts and transforming growth factor-β1-treated human epithelial A549 cells. Our results suggest that a strategy focused on rodent model-human disease commonalities may identify genes that could be used to predict the pharmacological impact of therapeutic interventions, and thus facilitate the development of novel treatments for this devastating lung disease.

Landslide susceptibility modeling applying machine learning methods: A case study from Longju in the Three Gorges Reservoir area, China

NASA Astrophysics Data System (ADS)

Zhou, Chao; Yin, Kunlong; Cao, Ying; Ahmed, Bayes; Li, Yuanyao; Catani, Filippo; Pourghasemi, Hamid Reza

2018-03-01

Landslide is a common natural hazard and responsible for extensive damage and losses in mountainous areas. In this study, Longju in the Three Gorges Reservoir area in China was taken as a case study for landslide susceptibility assessment in order to develop effective risk prevention and mitigation strategies. To begin, 202 landslides were identified, including 95 colluvial landslides and 107 rockfalls. Twelve landslide causal factor maps were prepared initially, and the relationship between these factors and each landslide type was analyzed using the information value model. Later, the unimportant factors were selected and eliminated using the information gain ratio technique. The landslide locations were randomly divided into two groups: 70% for training and 30% for verifying. Two machine learning models: the support vector machine (SVM) and artificial neural network (ANN), and a multivariate statistical model: the logistic regression (LR), were applied for landslide susceptibility modeling (LSM) for each type. The LSM index maps, obtained from combining the assessment results of the two landslide types, were classified into five levels. The performance of the LSMs was evaluated using the receiver operating characteristics curve and Friedman test. Results show that the elimination of noise-generating factors and the separated modeling of each landslide type have significantly increased the prediction accuracy. The machine learning models outperformed the multivariate statistical model and SVM model was found ideal for the case study area.

The impact of race on metabolic disease risk factors in women with and without posttraumatic stress disorder.

PubMed

Dedert, Eric A; Harper, Leia A; Calhoun, Patrick S; Dennis, Michelle F; Beckham, Jean C

2013-03-01

The literature on PTSD and metabolic disease risk factors has been limited by lacking investigation of the potential influence of commonly comorbid disorders and the role of race. In this study data were provided by a sample of 134 women (63 PTSD and 71 without PTSD). Separate sets of models examining associations of psychiatric disorder classifications with metabolic disease risk factors were used. Each model included race (African American or Caucasian), psychiatric disorder, and their interaction. There was an interaction of race and PTSD on body mass index, abdominal obesity, and triglycerides. While PTSD was not generally associated with deleterious health effects in African American participants, PTSD was related to worse metabolic disease risk factors in Caucasians. MDD was associated with metabolic disease risk factors, but there were no interactions with race. Results support the importance of race in the relationship between PTSD and metabolic disease risk factors. Future research would benefit from analysis of cultural factors to explain how race might influence metabolic disease risk factors in PTSD.

Estimating site occupancy and abundance using indirect detection indices

USGS Publications Warehouse

Stanley, T.R.; Royle, J. Andrew

2005-01-01

Knowledge of factors influencing animal distribution and abundance is essential in many areas of ecological research, management, and policy-making. Because common methods for modeling and estimating abundance (e.g., capture-recapture, distance sampling) are sometimes not practical for large areas or elusive species, indices are sometimes used as surrogate measures of abundance. We present an extension of the Royle and Nichols (2003) generalization of the MacKenzie et al. (2002) site-occupancy model that incorporates length of the sampling interval into the, model for detection probability. As a result, we obtain a modeling framework that shows how useful information can be extracted from a class of index methods we call indirect detection indices (IDIs). Examples of IDIs include scent station, tracking tube, snow track, tracking plate, and hair snare surveys. Our model is maximum likelihood, and it can be used to estimate site occupancy and model factors influencing patterns of occupancy and abundance in space. Under certain circumstances, it can also be used to estimate abundance. We evaluated model properties using Monte Carlo simulations and illustrate the method with tracking tube and scent station data. We believe this model will be a useful tool for determining factors that influence animal distribution and abundance.

A Concept of Constructing a Common Information Space for High Tech Programs Using Information Analytical Systems

NASA Astrophysics Data System (ADS)

Zakharova, Alexandra A.; Kolegova, Olga A.; Nekrasova, Maria E.

2016-04-01

The paper deals with the issues in program management used for engineering innovative products. The existing project management tools were analyzed. The aim is to develop a decision support system that takes into account the features of program management used for high-tech products: research intensity, a high level of technical risks, unpredictable results due to the impact of various external factors, availability of several implementing agencies. The need for involving experts and using intelligent techniques for information processing is demonstrated. A conceptual model of common information space to support communication between members of the collaboration on high-tech programs has been developed. The structure and objectives of the information analysis system “Geokhod” were formulated with the purpose to implement the conceptual model of common information space in the program “Development and production of new class mining equipment - “Geokhod”.

Common Psychiatric Disorders and Caffeine Use, Tolerance, and Withdrawal: An Examination of Shared Genetic and Environmental Effects

PubMed Central

Bergin, Jocilyn E.; Kendler, Kenneth S.

2012-01-01

Background Previous studies examined caffeine use and caffeine dependence and risk for the symptoms, or diagnosis, of psychiatric disorders. The current study aimed to determine if generalized anxiety disorder (GAD), panic disorder, phobias, major depressive disorder (MDD), anorexia nervosa (AN), or bulimia nervosa (BN) shared common genetic or environmental factors with caffeine use, caffeine tolerance, or caffeine withdrawal. Method Using 2,270 women from the Virginia Adult Twin Study of Psychiatric and Substance Use Disorders, bivariate Cholesky decomposition models were used to determine if any of the psychiatric disorders shared genetic or environmental factors with caffeine use phenotypes. Results GAD, phobias, and MDD shared genetic factors with caffeine use, with genetic correlations estimated to be 0.48, 0.25, and 0.38, respectively. Removal of the shared genetic and environmental parameter for phobias and caffeine use resulted in a significantly worse fitting model. MDD shared unique environmental factors (environmental correlation = 0.23) with caffeine tolerance; the genetic correlation between AN and caffeine tolerance and BN and caffeine tolerance were 0.64 and 0.49, respectively. Removal of the genetic and environmental correlation parameters resulted in significantly worse fitting models for GAD, phobias, MDD, AN, and BN, which suggested that there was significant shared liability between each of these phenotypes and caffeine tolerance. GAD had modest genetic correlations with caffeine tolerance, 0.24, and caffeine withdrawal, 0.35. Conclusions There was suggestive evidence of shared genetic and environmental liability between psychiatric disorders and caffeine phenotypes. This might inform us about the etiology of the comorbidity between these phenotypes. PMID:22854069

Common psychiatric disorders and caffeine use, tolerance, and withdrawal: an examination of shared genetic and environmental effects.

PubMed

Bergin, Jocilyn E; Kendler, Kenneth S

2012-08-01

Previous studies examined caffeine use and caffeine dependence and risk for the symptoms, or diagnosis, of psychiatric disorders. The current study aimed to determine if generalized anxiety disorder (GAD), panic disorder, phobias, major depressive disorder (MDD), anorexia nervosa (AN), or bulimia nervosa (BN) shared common genetic or environmental factors with caffeine use, caffeine tolerance, or caffeine withdrawal. Using 2,270 women from the Virginia Adult Twin Study of Psychiatric and Substance Use Disorders, bivariate Cholesky decomposition models were used to determine if any of the psychiatric disorders shared genetic or environmental factors with caffeine use phenotypes. GAD, phobias, and MDD shared genetic factors with caffeine use, with genetic correlations estimated to be 0.48, 0.25, and 0.38, respectively. Removal of the shared genetic and environmental parameter for phobias and caffeine use resulted in a significantly worse fitting model. MDD shared unique environmental factors (environmental correlation=0.23) with caffeine tolerance; the genetic correlation between AN and caffeine tolerance and BN and caffeine tolerance were 0.64 and 0.49, respectively. Removal of the genetic and environmental correlation parameters resulted in significantly worse fitting models for GAD, phobias, MDD, AN, and BN, which suggested that there was significant shared liability between each of these phenotypes and caffeine tolerance. GAD had modest genetic correlations with caffeine tolerance, 0.24, and caffeine withdrawal, 0.35. There was suggestive evidence of shared genetic and environmental liability between psychiatric disorders and caffeine phenotypes. This might inform us about the etiology of the comorbidity between these phenotypes.

Factor Structure and Psychometric Properties of the Posttraumatic Stress Disorder (PTSD) Checklist and DSM-5 PTSD Symptom Set in a Long-Term Postearthquake Cohort in Armenia.

PubMed

Demirchyan, Anahit; Goenjian, Armen K; Khachadourian, Vahe

2015-10-01

Psychometric properties of the Armenian-language posttraumatic stress disorder (PTSD) Checklist-Civilian version (PCL-C) and the DSM-5 PTSD symptom set were examined in a long-term cohort of earthquake survivors. In 2012, 725 survivors completed the instruments. Item-/scale-level analysis and confirmatory factor analysis (CFA) were performed for both scales. In addition, exploratory factor analysis (EFA) was conducted for DSM-5 symptoms. Also, the differential internal versus external specificity of PTSD symptom clusters taken from the most supported PTSD structural models was examined. Both scales had Cronbach's alpha greater than .9. CFA of PCL-C structure demonstrated an excellent fit by a four-factor (reexperiencing, avoidance, numbing, and hyperarousal) model known as numbing model; however, a superior fit was achieved by a five-factor model (Elhai et al.). EFA yielded a five-factor structure for DSM-5 symptoms with the aforementioned four domains plus a negative state domain. This model achieved an acceptable fit during CFA, whereas the DSM-5 criteria-based model did not. The Armenian-language PCL-C was recommended as a valid PTSD screening tool. The study findings provided support to the proposed new classification of common mental disorders, where PTSD, depression, and generalized anxiety are grouped together as a subclass of distress disorders. Recommendations were made to further improve the PTSD diagnostic criteria. © The Author(s) 2014.

Study on Misalignment Angle Compensation during Scale Factor Matching for Two Pairs of Accelerometers in a Gravity Gradient Instrument

PubMed Central

Huang, Xiangqing; Deng, Zhongguang; Xie, Yafei; Fan, Ji; Hu, Chenyuan

2018-01-01

A method for automatic compensation of misalignment angles during matching the scale factors of two pairs of the accelerometers in developing the rotating accelerometer gravity gradient instrument (GGI) is proposed and demonstrated in this paper. The purpose of automatic scale factor matching of the four accelerometers in GGI is to suppress the common mode acceleration of the moving-based platforms. However, taking the full model equation of the accelerometer into consideration, the other two orthogonal axes which is the pendulous axis and the output axis, will also sense the common mode acceleration and reduce the suppression performance. The coefficients from the two axes to the output are δO and δP respectively, called the misalignment angles. The angle δO, coupling with the acceleration along the pendulous axis perpendicular to the rotational plane, will not be modulated by the rotation and gives little contribution to the scale factors matching. On the other hand, because of coupling with the acceleration along the centripetal direction in the rotating plane, the angle δP would produce a component with 90 degrees phase delay relative to the scale factor component. Hence, the δP component coincides exactly with the sensitive direction of the orthogonal accelerometers. To improve the common mode acceleration rejection, the misalignment angle δP is compensated by injecting a trimming current, which is proportional to the output of an orthogonal accelerometer, into the torque coil of the accelerometer during the scale factor matching. The experimental results show that the common linear acceleration suppression achieved three orders after the scale factors balance and five orders after the misalignment angles compensation, which is almost down to the noise level of the used accelerometers of 1~2 × 10−7 g/√Hz (1 g ≈ 9.8 m/s2). PMID:29670021

Study on Misalignment Angle Compensation during Scale Factor Matching for Two Pairs of Accelerometers in a Gravity Gradient Instrument.

PubMed

Huang, Xiangqing; Deng, Zhongguang; Xie, Yafei; Fan, Ji; Hu, Chenyuan; Tu, Liangcheng

2018-04-18

A method for automatic compensation of misalignment angles during matching the scale factors of two pairs of the accelerometers in developing the rotating accelerometer gravity gradient instrument (GGI) is proposed and demonstrated in this paper. The purpose of automatic scale factor matching of the four accelerometers in GGI is to suppress the common mode acceleration of the moving-based platforms. However, taking the full model equation of the accelerometer into consideration, the other two orthogonal axes which is the pendulous axis and the output axis, will also sense the common mode acceleration and reduce the suppression performance. The coefficients from the two axes to the output are δ O and δ P respectively, called the misalignment angles. The angle δ O , coupling with the acceleration along the pendulous axis perpendicular to the rotational plane, will not be modulated by the rotation and gives little contribution to the scale factors matching. On the other hand, because of coupling with the acceleration along the centripetal direction in the rotating plane, the angle δ P would produce a component with 90 degrees phase delay relative to the scale factor component. Hence, the δ P component coincides exactly with the sensitive direction of the orthogonal accelerometers. To improve the common mode acceleration rejection, the misalignment angle δ P is compensated by injecting a trimming current, which is proportional to the output of an orthogonal accelerometer, into the torque coil of the accelerometer during the scale factor matching. The experimental results show that the common linear acceleration suppression achieved three orders after the scale factors balance and five orders after the misalignment angles compensation, which is almost down to the noise level of the used accelerometers of 1~2 × 10 −7 g/√Hz (1 g ≈ 9.8 m/s²).

Modelling the factor structure of the Child Depression Inventory in a population of apparently healthy adolescents in Nigeria.

PubMed

Olorunju, Samson Bamidele; Akpa, Onoja Matthew; Afolabi, Rotimi Felix

2018-01-01

Childhood and adolescent depression is common and often persists into adulthood with negative implications for school performances, peer relationship and behavioural functioning. The Child Depression Inventory (CDI) has been used to assess depression among adolescents in many countries including Nigeria but it is uncertain if the theoretical structure of CDI appropriately fits the experiences of adolescents in Nigeria. This study assessed varying theoretical modelling structure of the CDI in a population of apparently healthy adolescents in Benue state, Nigeria. Data was extracted on CDI scale and demographic information from a total of 1, 963 adolescents (aged 10-19 years), who participated in a state wide study assessing adolescent psychosocial functioning. In addition to descriptive statistics and reliability tests, Exploratory Factor Analysis (EFA) and Confirmatory Factor analysis (CFA) were used to model the underlying factor structure and its adequacy. The suggested new model was compared with existing CDI models as well as the CDI's original theoretical model. A model is considered better, if it has minimum Root Mean Square Error of Approximation (RMSEA<0.05), Minimum value of Discrepancy (CMIN/DF<3.0) and Akaike information criteria. All analyses were performed at 95% confidence level, using the version 21 of AMOS and the R software. Participants were 14.7±2.1 years and mostly male (54.3%), from Monogamous homes (67.9%) and lived in urban areas (52.2%). The measure of the overall internal consistency of the 2-factor CDI was α = 0.84. The 2-factor model had the minimum RMSEA (0.044), CMIN/DF (2.87) and least AIC (1037.996) compared to the other five CDI models. The child depression inventory has a 2-factor structure in a non-clinical general population of adolescents in Nigeria. Future use of the CDI in related setting may consider the 2-factor model.

Internal structure of the Community Assessment of Psychic Experiences-Positive (CAPE-P15) scale: Evidence for a general factor.

PubMed

Núñez, D; Arias, V; Vogel, E; Gómez, L

2015-07-01

Psychotic-like experiences (PLEs) are prevalent in the general population and are associated with poor mental health and a higher risk of psychiatric disorders. The Community Assessment of Psychic Experiences-Positive (CAPE-P15) scale is a self-screening questionnaire to address subclinical positive psychotic symptoms (PPEs) in community contexts. Although its psychometric properties seem to be adequate to screen PLEs, further research is needed to evaluate certain validity aspects, particularly its internal structure and its functioning in different populations. To uncover the optimal factor structure of the CAPE-P15 scale in adolescents aged 13 to 18 years using factorial analysis methods suitable to manage categorical variables. A sample of 727 students from six secondary public schools and 245 university students completed the CAPE-P15. The dimensionality of the CAPE-P15 was tested through exploratory structural equation models (ESEMs). Based on the ESEM results, we conducted a confirmatory factor analysis (CFA) to contrast two factorial structures that potentially underlie the symptoms described by the scale: a) three correlated factors and b) a hierarchical model composed of a general PLE factor plus three specific factors (persecutory ideation, bizarre experiences, and perceptual abnormalities). The underlying structure of PLEs assessed by the CAPE-P15 is consistent with both multidimensional and hierarchical solutions. However, the latter show the best fit. Our findings reveal the existence of a strong general factor underlying scale scores. Compared with the specific factors, the general factor explains most of the common variance observed in subjects' responses. The findings suggest that the factor structure of subthreshold psychotic experiences addressed by the CAPE-P15 can be adequately represented by a general factor and three separable specific traits, supporting the hypothesis according to which there might be a common source underlying PLEs. Copyright © 2015 Elsevier B.V. All rights reserved.

Decision Support Model to Optimize Site Characterization Activities Taken in Compliance with the Comprehensive Environmental Response Compensation and Liability Act

DTIC Science & Technology

1995-12-01

Contingency Plan ............................... 10 Table 2: Summary of Inhalation Emission Factors (K) for Equation ( 1 ...surveys for exposure factors commonly used in risk assessment (EPA, 1989a: 1 - 1 ). Exposure can take place via three possible routes, the inhalation ...Equation ( 1 ) calculates the dose for the inhalation route (USEPA, 1991 a:51-52; USEPA, 1989b:6-44). Dose - (C)(IRXETXEFXED) (K)(BWXAT) where C

Understanding the factors that influence breast reconstruction decision making in Australian women.

PubMed

Somogyi, Ron Barry; Webb, Angela; Baghdikian, Nairy; Stephenson, John; Edward, Karen-Leigh; Morrison, Wayne

2015-04-01

Breast reconstruction is safe and improves quality of life. Despite this, many women do not undergo breast reconstruction and the reasons for this are poorly understood. This study aims to identify the factors that influence a woman's decision whether or not to have breast reconstruction and to better understand their attitudes toward reconstruction. An online survey was distributed to breast cancer patients from Breast Cancer Network Australia. Results were tabulated, described qualitatively and analyzed for significance using a multiple logistic regression model. 501 mastectomy patients completed surveys, of which 62% had undergone breast reconstruction. Factors that positively influenced likelihood of reconstruction included lower age, bilateral mastectomy, access to private hospitals, decreased home/work responsibilities, increased level of home support and early discussion of reconstructive options. Most common reasons for avoiding reconstruction included "I don't feel the need" and "I don't want more surgery". The most commonly sited sources of reconstruction information came from the breast surgeon followed by the plastic surgeon then the breast cancer nurse and the most influential of these was the plastic surgeon. A model using factors easily obtained on clinical history can be used to understand likelihood of reconstruction. This knowledge may help identify barriers to reconstruction, ultimately improving the clinicians' ability to appropriately educate mastectomy patients and ensure effective decision making around breast reconstruction. Copyright © 2014 Elsevier Ltd. All rights reserved.

Common and gender specific factors associated with one-year mortality in nursing home residents.

PubMed

Kiely, Dan K; Flacker, Jonathan M

2002-01-01

To identify common and gender-specific factors associated with mortality in two distinct nursing home (NH) populations: newly admitted (NA), and long-stay (LS) residents. A retrospective cohort study. NH facilities in the state of New York. A total of 59,080 NA female and 28,080 NA male NH residents, and 24,260 LS female and 8,928 LS male NH residents evaluated between June 1994 and December 1997 who were at least 65 years of age. Minimum Data Set information including measures of health, functional, cognitive, psychological, and social status. Multivariate proportional hazards regression results indicate that in NA residents, use of feeding tubes, bowel incontinence, and refuses fluids were associated with mortality in women only, whereas fever was associated with mortality in men only. Cancer and congestive heart failure (CHF) were more strongly associated with mortality in women than men. In LS residents, deterioration in communication, refuses fluids, use of indwelling catheters, and deterioration in cognition were associated with mortality in women but not men. Bedfast most of the time, use of new medications, and a balance problem were associated with mortality in men but not women. Shortness-of-breath was more strongly associated with mortality in women than men. In both NA and LS residents, although men and women share many common factors associated with mortality, each gender has some unique factors associated with mortality. Furthermore, the strength of some common factors is significantly different across genders. These readily available data could be useful in making medical decisions and advance directive planning, and in the development of quality improvement initiatives and mortality prediction models.

Return to Work After Lumbar Microdiscectomy - Personalizing Approach Through Predictive Modeling.

PubMed

Papić, Monika; Brdar, Sanja; Papić, Vladimir; Lončar-Turukalo, Tatjana

2016-01-01

Lumbar disc herniation (LDH) is the most common disease among working population requiring surgical intervention. This study aims to predict the return to work after operative treatment of LDH based on the observational study including 153 patients. The classification problem was approached using decision trees (DT), support vector machines (SVM) and multilayer perception (MLP) combined with RELIEF algorithm for feature selection. MLP provided best recall of 0.86 for the class of patients not returning to work, which combined with the selected features enables early identification and personalized targeted interventions towards subjects at risk of prolonged disability. The predictive modeling indicated at the most decisive risk factors in prolongation of work absence: psychosocial factors, mobility of the spine and structural changes of facet joints and professional factors including standing, sitting and microclimate.

Scaling behavior in the dynamics of citations to scientific journals

NASA Astrophysics Data System (ADS)

Picoli, S., Jr.; Mendes, R. S.; Malacarne, L. C.; Lenzi, E. K.

2006-08-01

We analyze a database comprising the impact factor (citations per recent items published) of scientific journals for a 13-year period (1992 2004). We find that i) the distribution of impact factors follows asymptotic power law behavior, ii) the distribution of annual logarithmic growth rates has an exponential form, and iii) the width of this distribution decays with the impact factor as a power law with exponent β simeq 0.22. The results ii) and iii) are surprising similar to those observed in the growth dynamics of organizations with complex internal structure suggesting the existence of common mechanisms underlying the dynamics of these systems. We propose a general model for such systems, an extension of the simplest model for firm growth, and compare their predictions with our empirical results.

Risks, Risk Factors, and Outcomes Associated with Phone and Internet Sexting Among University Students in the United States.

PubMed

Dir, Allyson L; Cyders, Melissa A

2015-08-01

Sexting, defined as the exchange of sexually suggestive pictures or messages via mobile phone or social networking sites (SNS), has received media attention for its prevalence and associated negative outcomes; however, research has not yet fully established risk factors for and resulting outcomes from sexting behaviors. The current study was the first empirical test of a causal path model in males and females, in which impulsivity-related traits and expectancies influence sexual behaviors through phone and SNS sexting. We also examined prevalence and perceived likelihood of common negative outcomes associated with sexting. Multiple regression and structural equation modeling (SEM) statistics were conducted on two independent undergraduate samples (n = 611 and 255). The best fitting SEM model (RMSEA = 0.04, CFI = 0.96, TLI = 0.94, and χ(2) = 176.06, df = 75, p < .001) demonstrated a significant indirect effect of sensation seeking on phone sexting behaviors through sex-related sexting expectancies and a significant indirect effect of sensation seeking on sexual hookup behaviors through phone sexting behaviors (b = 0.06, p = .03), but only for females. Reverse mediations and mediation with SNS were not significant. Negative outcomes were rare: sexts being spread to others was the most common negative sexting experience (n = 21, 12 %). This study suggests the viability of personality and expectancies affecting sexual hookup behaviors through engagement in sexting behaviors. It also suggests that although direct negative outcomes associated with sexting are thought to be common, they were rare in the current sample.

Resilience and risk for alcohol use disorders: A Swedish twin study

PubMed Central

Long, E.C.; Lönn, S.L.; Ji, J.; Lichtenstein, P.; Sundquist, J.; Sundquist, K.; Kendler, K.S.

2016-01-01

Background Resilience has been shown to be protective against alcohol use disorders (AUD), but the magnitude and nature of the relationship between these two phenotypes is not clear. The aim of this study is to examine the strength of this relationship and the degree to which it results from common genetic or common environmental influences. Methods Resilience was assessed on a nine-point scale during a personal interview in 1,653,721 Swedish men aged 17–25 years. AUD was identified based on Swedish medical, legal, and pharmacy registries. The magnitude of the relationship between resilience and AUD was examined using logistic regression. The extent to which the relationship arises from common genetic or common environmental factors was examined using a bivariate Cholesky decomposition model. Results The five single items that comprised the resilience assessment (social maturity, interest, psychological energy, home environment, and emotional control) all reduced risk for subsequent AUD, with social maturity showing the strongest effect. The linear effect by logistic regression showed that a one-point increase on the resilience scale was associated with a 29% decrease in odds of AUD. The Cholesky decomposition model demonstrated that the resilience-AUD relationship was largely attributable to overlapping genetic and shared environmental factors (57% and 36%, respectively). Conclusion Resilience is strongly associated with a reduction in risk for AUD. This relationship appears to be the result of overlapping genetic and shared environmental influences that impact resilience and risk of AUD, rather than a directly causal relationship. PMID:27918840

Combining PubMed knowledge and EHR data to develop a weighted bayesian network for pancreatic cancer prediction.

PubMed

Zhao, Di; Weng, Chunhua

2011-10-01

In this paper, we propose a novel method that combines PubMed knowledge and Electronic Health Records to develop a weighted Bayesian Network Inference (BNI) model for pancreatic cancer prediction. We selected 20 common risk factors associated with pancreatic cancer and used PubMed knowledge to weigh the risk factors. A keyword-based algorithm was developed to extract and classify PubMed abstracts into three categories that represented positive, negative, or neutral associations between each risk factor and pancreatic cancer. Then we designed a weighted BNI model by adding the normalized weights into a conventional BNI model. We used this model to extract the EHR values for patients with or without pancreatic cancer, which then enabled us to calculate the prior probabilities for the 20 risk factors in the BNI. The software iDiagnosis was designed to use this weighted BNI model for predicting pancreatic cancer. In an evaluation using a case-control dataset, the weighted BNI model significantly outperformed the conventional BNI and two other classifiers (k-Nearest Neighbor and Support Vector Machine). We conclude that the weighted BNI using PubMed knowledge and EHR data shows remarkable accuracy improvement over existing representative methods for pancreatic cancer prediction. Copyright © 2011 Elsevier Inc. All rights reserved.

Combining PubMed Knowledge and EHR Data to Develop a Weighted Bayesian Network for Pancreatic Cancer Prediction

PubMed Central

Zhao, Di; Weng, Chunhua

2011-01-01

In this paper, we propose a novel method that combines PubMed knowledge and Electronic Health Records to develop a weighted Bayesian Network Inference (BNI) model for pancreatic cancer prediction. We selected 20 common risk factors associated with pancreatic cancer and used PubMed knowledge to weigh the risk factors. A keyword-based algorithm was developed to extract and classify PubMed abstracts into three categories that represented positive, negative, or neutral associations between each risk factor and pancreatic cancer. Then we designed a weighted BNI model by adding the normalized weights into a conventional BNI model. We used this model to extract the EHR values for patients with or without pancreatic cancer, which then enabled us to calculate the prior probabilities for the 20 risk factors in the BNI. The software iDiagnosis was designed to use this weighted BNI model for predicting pancreatic cancer. In an evaluation using a case-control dataset, the weighted BNI model significantly outperformed the conventional BNI and two other classifiers (k-Nearest Neighbor and Support Vector Machine). We conclude that the weighted BNI using PubMed knowledge and EHR data shows remarkable accuracy improvement over existing representative methods for pancreatic cancer prediction. PMID:21642013

The High Affinity Iron Permease is a Key Virulence Factor Required for Rhizopus oryzae Pathogenesis

USDA-ARS?s Scientific Manuscript database

Rhizopus oryzae is the most common cause of mucormycosis, an angioinvasive fungal infection that causes a >/=50% mortality rate despite first-line therapy. Clinical and animal model data clearly demonstrate that the presence of elevated available serum iron predisposes the host to mucormycosis. Th...

Multidimensional Measurement of Situational Interest in Physical Education: Application of Bifactor Exploratory Structural Equation Modeling

ERIC Educational Resources Information Center

Garn, Alex C.

2017-01-01

Multidimensional measurement is a common theme in motivation research because many constructs are conceptualized as having an overarching general factor (e.g., situational interest) and specific dimensions (e.g., attention demand, challenge, exploration intention, instant enjoyment, novelty). This review addresses current issues associated with…

EVALUATION OF DNA CHIPS (MICROARRAYS) FOR DETERMINING VIRULENCE FACTOR ACTIVITY RELATIONSHIPS (VFARS)

EPA Science Inventory

Computational toxicology is a rapid approach to screening for toxic effects and looking for common outcomes that can result in predictive models. The long term project will result in the development of a database of mRNA responses to known water-borne pathogens. An understanding...

A "Common Factors" Approach to Developing Culturally Tailored HIV Prevention Interventions

ERIC Educational Resources Information Center

Owczarzak, Jill; Phillips, Sarah D.; Filippova, Olga; Alpatova, Polina; Mazhnaya, Alyona; Zub, Tatyana; Aleksanyan, Ruzanna

2016-01-01

The current dominant model of HIV prevention intervention dissemination involves packaging interventions developed in one context, training providers to implement that specific intervention, and evaluating the extent to which providers implement it with fidelity. Research shows that providers rarely implement these programs with fidelity due to…

Community College Student Success: What Institutional Characteristics Make a Difference?

ERIC Educational Resources Information Center

Calcagno, Juan Carlos; Bailey, Thomas; Jenkins, Davis; Kienzl, Gregory; Leinbach, Timothy

2008-01-01

Most of the models developed to examine student persistence and attainment in postsecondary education largely fail to account for the influence of institutional factors, particularly when attendance is observed at multiple institutions. Multi-institutional attendance is common for students who begin at a community college, but until now an…

Animal Models in Cardiovascular Research: Hypertension and Atherosclerosis

PubMed Central

Ng, Chun-Yi; Jaarin, Kamsiah

2015-01-01

Hypertension and atherosclerosis are among the most common causes of mortality in both developed and developing countries. Experimental animal models of hypertension and atherosclerosis have become a valuable tool for providing information on etiology, pathophysiology, and complications of the disease and on the efficacy and mechanism of action of various drugs and compounds used in treatment. An animal model has been developed to study hypertension and atherosclerosis for several reasons. Compared to human models, an animal model is easily manageable, as compounding effects of dietary and environmental factors can be controlled. Blood vessels and cardiac tissue samples can be taken for detailed experimental and biomolecular examination. Choice of animal model is often determined by the research aim, as well as financial and technical factors. A thorough understanding of the animal models used and complete analysis must be validated so that the data can be extrapolated to humans. In conclusion, animal models for hypertension and atherosclerosis are invaluable in improving our understanding of cardiovascular disease and developing new pharmacological therapies. PMID:26064920

Predictors of formal home health care use in elderly patients after hospitalization.

PubMed

Solomon, D H; Wagner, D R; Marenberg, M E; Acampora, D; Cooney, L M; Inouye, S K

1993-09-01

To prospectively study the incidence of and risk factors for home health care (HHC) use in a cohort of elderly medical and surgical patients discharged from acute care. Although HHC is commonly received by patients in this group, its predictors have not been well studied. Prospective cohort study. Medical and surgical wards at a university teaching hospital, followed by 23 Medicare-certified HHC agencies in the study catchment area. 226 medical and surgical patients aged 70 years and older immediately after discharge from acute care. HHC initiated within 14 days after hospital discharge, measured by direct review of HHC agency records. The incidence of HHC initiated within 2 weeks post-discharge was 75/226 (34%). The median duration of service was 30 days (range 3-483) with a median of 3 visits per week. Four independent predictors of HHC were identified through multivariate analysis: educational level < or = 12 years (relative risk (RR) 3.3; 95% confidence interval (CI) 1.6 to 6.6); less accessible social support (RR, 1.7; CI 0.9 to 3.1); impairment in at least one instrumental activity of daily living (RR, 1.9; CI, 1.0, 3.4); and prior HHC use (RR, 2.1; CI, 1.2 to 3.6). Risk strata were created by adding one point for each risk factor present: with 0-1 risk factors, 8% used HHC; with two risk factors, 28%; with three risk factors, 45%, with four risk factors, 76%. This trend was statistically significant (P < 0.001). HHC use is common among elderly patients after discharge from acute care. A simple predictive model based on four risk factors can be used on admission to predict HHC use. This model may be useful for discharge planning and health care utilization planning for the elderly population.

Extracts of Bauhinia championii (Benth.) Benth. attenuate the inflammatory response in a rat model of collagen-induced arthritis

PubMed Central

XU, WEI; HUANG, MINGQING; ZHANG, YUQIN; LI, HUANG; ZHENG, HAIYIN; YU, LISHUANG; CHU, KEDAN; LIN, YU; CHEN, LIDIAN

2016-01-01

Rheumatoid arthritis is considered a serious public health problem, which is commonly treated with traditional Chinese or herbal medicine. The present study evaluated the effects of Bauhinia championii (Benth.) Benth. extraction (BCBE) on a type II collagen-induced arthritis (CIA) rat model. Wistar rats with CIA received either 125 or 500 mg/kg BCBE, after which, paw swelling was markedly suppressed compared with in the model group. In addition, BCBE significantly ameliorated pathological joint alterations, including synovial hyperplasia, and cartilage and bone destruction. The protein and mRNA expression levels of interleukin (IL)-6, IL-8, tumor necrosis factor-α and nuclear factor-κB in synovial tissue were determined by immunohistochemical staining, western blot analysis and reverse transcription-polymerase chain reaction. The results demonstrated that the expression levels of these factors were significantly downregulated in the BCBE-treated group compared with in the model group. These results indicated that BCBE may exert an inhibitory effect on the CIA rat model, and its therapeutic potential is associated with its anti-inflammatory action. PMID:27035125

Modelling the pre-assessment learning effects of assessment: evidence in the validity chain.

PubMed

Cilliers, Francois J; Schuwirth, Lambert W T; van der Vleuten, Cees P M

2012-11-01

We previously developed a model of the pre-assessment learning effects of consequential assessment and started to validate it. The model comprises assessment factors, mechanism factors and learning effects. The purpose of this study was to continue the validation process. For stringency, we focused on a subset of assessment factor-learning effect associations that featured least commonly in a baseline qualitative study. Our aims were to determine whether these uncommon associations were operational in a broader but similar population to that in which the model was initially derived. A cross-sectional survey of 361 senior medical students at one medical school was undertaken using a purpose-made questionnaire based on a grounded theory and comprising pairs of written situational tests. In each pair, the manifestation of an assessment factor was varied. The frequencies at which learning effects were selected were compared for each item pair, using an adjusted alpha to assign significance. The frequencies at which mechanism factors were selected were calculated. There were significant differences in the learning effect selected between the two scenarios of an item pair for 13 of this subset of 21 uncommon associations, even when a p-value of < 0.00625 was considered to indicate significance. Three mechanism factors were operational in most scenarios: agency; response efficacy, and response value. For a subset of uncommon associations in the model, the role of most assessment factor-learning effect associations and the mechanism factors involved were supported in a broader but similar population to that in which the model was derived. Although model validation is an ongoing process, these results move the model one step closer to the stage of usefully informing interventions. Results illustrate how factors not typically included in studies of the learning effects of assessment could confound the results of interventions aimed at using assessment to influence learning. © Blackwell Publishing Ltd 2012.

Dimensionality of DSM-5 posttraumatic stress disorder and its association with suicide attempts: results from the National Epidemiologic Survey on Alcohol and Related Conditions-III.

PubMed

Chen, Chiung M; Yoon, Young-Hee; Harford, Thomas C; Grant, Bridget F

2017-06-01

Emerging confirmatory factor analytic (CFA) studies suggest that posttraumatic stress disorder (PTSD) as defined by the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (DSM-5) is best characterized by seven factors, including re-experiencing, avoidance, negative affect, anhedonia, externalizing behaviors, and anxious and dysphoric arousal. The seven factors, however, have been found to be highly correlated, suggesting that one general factor may exist to explain the overall correlations among symptoms. Using data from the National Epidemiologic Survey on Alcohol and Related Conditions-III, a large, national survey of 36,309 U.S. adults ages 18 and older, this study proposed and tested an exploratory bifactor hybrid model for DSM-5 PTSD symptoms. The model posited one general and seven specific latent factors, whose associations with suicide attempts and mediating psychiatric disorders were used to validate the PTSD dimensionality. The exploratory bifactor hybrid model fitted the data extremely well, outperforming the 7-factor CFA hybrid model and other competing CFA models. The general factor was found to be the single dominant latent trait that explained most of the common variance (~76%) and showed significant, positive associations with suicide attempts and mediating psychiatric disorders, offering support to the concurrent validity of the PTSD construct. The identification of the primary latent trait of PTSD confirms PTSD as an independent psychiatric disorder and helps define PTSD severity in clinical practice and for etiologic research. The accurate specification of PTSD factor structure has implications for treatment efforts and the prevention of suicidal behaviors.

Research on the relationship between the elements and pharmacological activities in velvet antler using factor analysis and cluster analysis

NASA Astrophysics Data System (ADS)

Zhou, Libing

2017-04-01

Velvet antler has certain effect on improving the body's immune cells and the regulation of immune system function, nervous system, anti-stress, anti-aging and osteoporosis. It has medicinal applications to treat a wide range of diseases such as tissue wound healing, anti-tumor, cardiovascular disease, et al. Therefore, the research on the relationship between pharmacological activities and elements in velvet antler is of great significance. The objective of this study was to comprehensively evaluate 15 kinds of elements in different varieties of velvet antlers and study on the relationship between the elements and traditional Chinese medicine efficacy for the human. The factor analysis and the factor cluster analysis methods were used to analyze the data of elements in the sika velvet antler, cervus elaphus linnaeus, flower horse hybrid velvet antler, apiti (elk) velvet antler, male reindeer velvet antler and find out the relationship between 15 kinds of elements including Ca, P, Mg, Na, K, Fe, Cu, Mn, Al, Ba, Co, Sr, Cr, Zn and Ni. Combining with MATLAB2010 and SPSS software, the chemometrics methods were made on the relationship between the elements in velvet antler and the pharmacological activities. The first commonality factor F1 had greater load on the indexes of Ca, P, Mg, Co, Sr and Ni, and the second commonality factor F2 had greater load on the indexes of K, Mn, Zn and Cr, and the third commonality factor F3 had greater load on the indexes of Na, Cu and Ba, and the fourth commonality factor F4 had greater load on the indexes of Fe and Al. 15 kinds of elements in velvet antler in the order were elk velvet antler>flower horse hybrid velvet antler>cervus elaphus linnaeus>sika velvet antler>male reindeer velvet antler. Based on the factor analysis and the factor cluster analysis, a model for evaluating traditional Chinese medicine quality was constructed. These studies provide the scientific base and theoretical foundation for the future large-scale rational relation development of velvet antler resources as well as the relationship between the elements and traditional Chinese medicine efficacy for the human.

Understanding factors that influence participation in physical activity among people with a neuromusculoskeletal condition: a review of qualitative studies.

PubMed

Newitt, Rosemarie; Barnett, Fiona; Crowe, Melissa

2016-01-01

This review aims to describe the factors that influence participation in physical activity (PA) in people with neuromusculoskeletal (NMS) conditions. A systematic search of six databases was conducted. Articles were included if the study qualitatively explored factors that influence participation in PA by individuals with a NMS condition. Fifteen peer-reviewed articles published between 2003 and 2013 were analysed for common themes and critically appraised. Results were categorised using the International Classification of Functioning, Disability and Health framework. The most common demotivators reported for the three areas of functioning, body function and structures, activities and participation were lack of walking balance, muscle weakness, pain, stiffness, bladder and blower problems, depression, thermoregulation and fear of injury. Fluctuating symptoms and fatigue were mentioned as demotivators in all of the progressive conditions. Maintaining independence, function and weight, and the prevention of secondary conditions were the leading motivators reported in this domain. Most common environmental barriers include accessibility, costs, transport and insufficient information and knowledge from health professionals. Social support is a consistent determinate of PA and is reported as a facilitator in every study. The most common personal demotivators include lack of motivation, feelings of self-consciousness and embarrassment in public, anxiety, frustration and anger. Personal motivators include goal setting and achieving, enjoyment, feeling good, feeling "normal", motivation and optimism, redefining self and escapism from everyday boundaries. Individuals with NMS conditions report complex common barriers, facilitators, demotivators and motivators to participation in PA. The way these factors influence participation in PA is unique to the individual; therefore, it is necessary to adopt an individually tailored approach when designing interventions. Individuals with neuromusculoskeletal conditions report common factors that influence participation in physical activity. It is the characteristics, attitude and beliefs of an individual that determine the way in which these factors influence participation in physical activity. Health professionals should be guided by the International Classification of Functioning, Disability and Health framework when assessing individuals, as the model will ensure all major factors of interest with regard to disability and physical activity behaviour are considered. Interventions to promote participation in physical activity in people with neuromusculoskeletal conditions require an individual approach that facilitates the assessment and management of an individual's barriers to physical activity. A multi-disciplinary approach may be required to address factors that influence participation in physical activity. Health professionals must be informed about other areas of expertise and draw on this when necessary.

Freshwater wetlands: fertile grounds for the invasive Phragmites australis in a climate change context

PubMed Central

Tougas-Tellier, Marie-Andrée; Morin, Jean; Hatin, Daniel; Lavoie, Claude

2015-01-01

Climate change will likely affect flooding regimes, which have a large influence on the functioning of freshwater riparian wetlands. Low water levels predicted for several fluvial systems make wetlands especially vulnerable to the spread of invaders, such as the common reed (Phragmites australis), one of the most invasive species in North America. We developed a model to map the distribution of potential germination grounds of the common reed in freshwater wetlands of the St. Lawrence River (Québec, Canada) under current climate conditions and used this model to predict their future distribution under two climate change scenarios simulated for 2050. We gathered historical and recent (remote sensing) data on the distribution of common reed stands for model calibration and validation purposes, then determined the parameters controlling the species establishment by seed. A two-dimensional model and the identified parameters were used to simulate the current (2010) and future (2050) distribution of germination grounds. Common reed stands are not widespread along the St. Lawrence River (212 ha), but our model suggests that current climate conditions are already conducive to considerable further expansion (>16,000 ha). Climate change may also exacerbate the expansion, particularly if river water levels drop, which will expose large bare areas propitious to seed germination. This phenomenon may be particularly important in one sector of the river, where existing common reed stands could increase their areas by a factor of 100, potentially creating the most extensive reedbed complex in North America. After colonizing salt and brackishwater marshes, the common reed could considerably expand into the freshwater marshes of North America which cover several million hectares. The effects of common reed expansion on biodiversity are difficult to predict, but likely to be highly deleterious given the competitiveness of the invader and the biological richness of freshwater wetlands. PMID:26380675

Common Cause Case Study: An Estimated Probability of Four Solid Rocket Booster Hold-down Post Stud Hang-ups

NASA Technical Reports Server (NTRS)

Cross, Robert

2005-01-01

Until Solid Rocket Motor ignition, the Space Shuttle is mated to the Mobil Launch Platform in part via eight (8) Solid Rocket Booster (SRB) hold-down bolts. The bolts are fractured using redundant pyrotechnics, and are designed to drop through a hold-down post on the Mobile Launch Platform before the Space Shuttle begins movement. The Space Shuttle program has experienced numerous failures where a bolt has "hung-up." That is, it did not clear the hold-down post before liftoff and was caught by the SRBs. This places an additional structural load on the vehicle that was not included in the original certification requirements. The Space Shuttle is currently being certified to withstand the loads induced by up to three (3) of eight (8) SRB hold-down post studs experiencing a "hang-up." The results af loads analyses performed for four (4) stud-hang ups indicate that the internal vehicle loads exceed current structural certification limits at several locations. To determine the risk to the vehicle from four (4) stud hang-ups, the likelihood of the scenario occurring must first be evaluated. Prior to the analysis discussed in this paper, the likelihood of occurrence had been estimated assuming that the stud hang-ups were completely independent events. That is, it was assumed that no common causes or factors existed between the individual stud hang-up events. A review of the data associated with the hang-up events, showed that a common factor (timing skew) was present. This paper summarizes a revised likelihood evaluation performed for the four (4) stud hang-ups case considering that there are common factors associated with the stud hang-ups. The results show that explicitly (i.e. not using standard common cause methodologies such as beta factor or Multiple Greek Letter modeling) taking into account the common factor of timing skew results in an increase in the estimated likelihood of four (4) stud hang-ups of an order of magnitude over the independent failure case.

Common Cause Case Study: An Estimated Probability of Four Solid Rocket Booster Hold-Down Post Stud Hang-ups

NASA Technical Reports Server (NTRS)

Cross, Robert

2005-01-01

Until Solid Rocket Motor ignition, the Space Shuttle is mated to the Mobil Launch Platform in part via eight (8) Solid Rocket Booster (SRB) hold-down bolts. The bolts are fractured using redundant pyrotechnics, and are designed to drop through a hold-down post on the Mobile Launch Platform before the Space Shuttle begins movement. The Space Shuttle program has experienced numerous failures where a bolt has hung up. That is, it did not clear the hold-down post before liftoff and was caught by the SRBs. This places an additional structural load on the vehicle that was not included in the original certification requirements. The Space Shuttle is currently being certified to withstand the loads induced by up to three (3) of eight (8) SRB hold-down experiencing a "hang-up". The results of loads analyses performed for (4) stud hang-ups indicate that the internal vehicle loads exceed current structural certification limits at several locations. To determine the risk to the vehicle from four (4) stud hang-ups, the likelihood of the scenario occurring must first be evaluated. Prior to the analysis discussed in this paper, the likelihood of occurrence had been estimated assuming that the stud hang-ups were completely independent events. That is, it was assumed that no common causes or factors existed between the individual stud hang-up events. A review of the data associated with the hang-up events, showed that a common factor (timing skew) was present. This paper summarizes a revised likelihood evaluation performed for the four (4) stud hang-ups case considering that there are common factors associated with the stud hang-ups. The results show that explicitly (i.e. not using standard common cause methodologies such as beta factor or Multiple Greek Letter modeling) taking into account the common factor of timing skew results in an increase in the estimated likelihood of four (4) stud hang-ups of an order of magnitude over the independent failure case.

Using Fault Trees to Advance Understanding of Diagnostic Errors.

PubMed

Rogith, Deevakar; Iyengar, M Sriram; Singh, Hardeep

2017-11-01

Diagnostic errors annually affect at least 5% of adults in the outpatient setting in the United States. Formal analytic techniques are only infrequently used to understand them, in part because of the complexity of diagnostic processes and clinical work flows involved. In this article, diagnostic errors were modeled using fault tree analysis (FTA), a form of root cause analysis that has been successfully used in other high-complexity, high-risk contexts. How factors contributing to diagnostic errors can be systematically modeled by FTA to inform error understanding and error prevention is demonstrated. A team of three experts reviewed 10 published cases of diagnostic error and constructed fault trees. The fault trees were modeled according to currently available conceptual frameworks characterizing diagnostic error. The 10 trees were then synthesized into a single fault tree to identify common contributing factors and pathways leading to diagnostic error. FTA is a visual, structured, deductive approach that depicts the temporal sequence of events and their interactions in a formal logical hierarchy. The visual FTA enables easier understanding of causative processes and cognitive and system factors, as well as rapid identification of common pathways and interactions in a unified fashion. In addition, it enables calculation of empirical estimates for causative pathways. Thus, fault trees might provide a useful framework for both quantitative and qualitative analysis of diagnostic errors. Future directions include establishing validity and reliability by modeling a wider range of error cases, conducting quantitative evaluations, and undertaking deeper exploration of other FTA capabilities. Copyright © 2017 The Joint Commission. Published by Elsevier Inc. All rights reserved.

Is Clostridium difficile infection a risk factor for subsequent bloodstream infection?

PubMed

Ulrich, Robert J; Santhosh, Kavitha; Mogle, Jill A; Young, Vincent B; Rao, Krishna

2017-12-01

Clostridium difficile infection (CDI) is a common nosocomial diarrheal illness increasingly associated with mortality in United States. The underlying factors and mechanisms behind the recent increases in morbidity from CDI have not been fully elucidated. Murine models suggest a mucosal barrier breakdown leads to bacterial translocation and subsequent bloodstream infection (BSI). This study tests the hypothesis that CDI is associated with subsequent BSI in humans. We conducted a retrospective cohort study on 1132 inpatients hospitalized >72 h with available stool test results for toxigenic C. difficile. The primary outcome was BSI following CDI. Secondary outcomes included 30-day mortality, colectomy, readmission, and ICU admission. Unadjusted and adjusted logistic regression models were developed. CDI occurred in 570 of 1132 patients (50.4%). BSI occurred in 86 (7.6%) patients. Enterococcus (14%) and Klebsiella (14%) species were the most common organisms. Patients with BSI had higher comorbidity scores and were more likely to be male, on immunosuppression, critically ill, and have a central venous catheter in place. Of the patients with BSI, 36 (42%) had CDI. CDI was not associated with subsequent BSI (OR 0.69; 95% CI 0.44-1.08; P = 0.103) in unadjusted analysis. In multivariable modeling, CDI appeared protective against subsequent BSI (OR 0.57; 95% CI 0.34-0.96; P = 0.036). Interaction modeling suggests a complicated relationship among CDI, BSI, antibiotic exposure, and central venous catheter use. In this cohort of inpatients that underwent testing for CDI, CDI was not a risk factor for developing subsequent BSI. Copyright © 2017 Elsevier Ltd. All rights reserved.

Integrative Families and Systems Treatment: A Middle Path toward Integrating Common and Specific Factors in Evidence-Based Family Therapy

ERIC Educational Resources Information Center

Fraser, J. Scott; Solovey, Andrew D.; Grove, David; Lee, Mo Yee; Greene, Gilbert J.

2012-01-01

A moderate common factors approach is proposed as a synthesis or middle path to integrate common and specific factors in evidence-based approaches to high-risk youth and families. The debate in family therapy between common and specific factors camps is reviewed and followed by suggestions from the literature for synthesis and creative flexibility…

Acute Diarrheal Syndromic Surveillance

PubMed Central

Kam, H.J.; Choi, S.; Cho, J.P.; Min, Y.G.; Park, R.W.

2010-01-01

Objective In an effort to identify and characterize the environmental factors that affect the number of patients with acute diarrheal (AD) syndrome, we developed and tested two regional surveillance models including holiday and weather information in addition to visitor records, at emergency medical facilities in the Seoul metropolitan area of Korea. Methods With 1,328,686 emergency department visitor records from the National Emergency Department Information system (NEDIS) and the holiday and weather information, two seasonal ARIMA models were constructed: (1) The simple model (only with total patient number), (2) the environmental factor-added model. The stationary R-squared was utilized as an in-sample model goodness-of-fit statistic for the constructed models, and the cumulative mean of the Mean Absolute Percentage Error (MAPE) was used to measure post-sample forecast accuracy over the next 1 month. Results The (1,0,1)(0,1,1)7 ARIMA model resulted in an adequate model fit for the daily number of AD patient visits over 12 months for both cases. Among various features, the total number of patient visits was selected as a commonly influential independent variable. Additionally, for the environmental factor-added model, holidays and daily precipitation were selected as features that statistically significantly affected model fitting. Stationary R-squared values were changed in a range of 0.651-0.828 (simple), and 0.805-0.844 (environmental factor-added) with p<0.05. In terms of prediction, the MAPE values changed within 0.090-0.120 and 0.089-0.114, respectively. Conclusion The environmental factor-added model yielded better MAPE values. Holiday and weather information appear to be crucial for the construction of an accurate syndromic surveillance model for AD, in addition to the visitor and assessment records. PMID:23616829

Construct validity of the five factor borderline inventory.

PubMed

DeShong, Hilary L; Lengel, Gregory J; Sauer-Zavala, Shannon E; O'Meara, Madison; Mullins-Sweatt, Stephanie N

2015-06-01

The Five Factor Borderline Inventory (FFBI) is a new self-report measure developed to assess traits of borderline personality disorder (BPD) from the perspective of the Five Factor Model of general personality. The current study sought to first replicate initial validity findings for the FFBI and then to further validate the FFBI with predispositional risk factors of the biosocial theory of BPD and with commonly associated features of BPD (e.g., depression, low self-esteem) utilizing two samples of young adults (N = 87; 85) who have engaged in nonsuicidal self-injury. The FFBI showed strong convergent and discriminant validity across two measures of the Five Factor Model and also correlated strongly with measures of impulsivity, emotion dysregulation, and BPD. The FFBI also related to two measures of early childhood emotional vulnerability and parental invalidation and measures of depression, anxiety, and self-esteem. Overall, the results provide support for the FFBI as a measure of BPD. © The Author(s) 2014.

Chronic cerebral hypoperfusion: a key mechanism leading to vascular cognitive impairment and dementia. Closing the translational gap between rodent models and human vascular cognitive impairment and dementia.

PubMed

Duncombe, Jessica; Kitamura, Akihiro; Hase, Yoshiki; Ihara, Masafumi; Kalaria, Raj N; Horsburgh, Karen

2017-10-01

Increasing evidence suggests that vascular risk factors contribute to neurodegeneration, cognitive impairment and dementia. While there is considerable overlap between features of vascular cognitive impairment and dementia (VCID) and Alzheimer's disease (AD), it appears that cerebral hypoperfusion is the common underlying pathophysiological mechanism which is a major contributor to cognitive decline and degenerative processes leading to dementia. Sustained cerebral hypoperfusion is suggested to be the cause of white matter attenuation, a key feature common to both AD and dementia associated with cerebral small vessel disease (SVD). White matter changes increase the risk for stroke, dementia and disability. A major gap has been the lack of mechanistic insights into the evolution and progress of VCID. However, this gap is closing with the recent refinement of rodent models which replicate chronic cerebral hypoperfusion. In this review, we discuss the relevance and advantages of these models in elucidating the pathogenesis of VCID and explore the interplay between hypoperfusion and the deposition of amyloid β (Aβ) protein, as it relates to AD. We use examples of our recent investigations to illustrate the utility of the model in preclinical testing of candidate drugs and lifestyle factors. We propose that the use of such models is necessary for tackling the urgently needed translational gap from preclinical models to clinical treatments. © 2017 The Author(s). Published by Portland Press Limited on behalf of the Biochemical Society.

Learning topic models by belief propagation.

PubMed

Zeng, Jia; Cheung, William K; Liu, Jiming

2013-05-01

Latent Dirichlet allocation (LDA) is an important hierarchical Bayesian model for probabilistic topic modeling, which attracts worldwide interest and touches on many important applications in text mining, computer vision and computational biology. This paper represents the collapsed LDA as a factor graph, which enables the classic loopy belief propagation (BP) algorithm for approximate inference and parameter estimation. Although two commonly used approximate inference methods, such as variational Bayes (VB) and collapsed Gibbs sampling (GS), have gained great success in learning LDA, the proposed BP is competitive in both speed and accuracy, as validated by encouraging experimental results on four large-scale document datasets. Furthermore, the BP algorithm has the potential to become a generic scheme for learning variants of LDA-based topic models in the collapsed space. To this end, we show how to learn two typical variants of LDA-based topic models, such as author-topic models (ATM) and relational topic models (RTM), using BP based on the factor graph representations.

A heteroscedastic generalized linear model with a non-normal speed factor for responses and response times.

PubMed

Molenaar, Dylan; Bolsinova, Maria

2017-05-01

In generalized linear modelling of responses and response times, the observed response time variables are commonly transformed to make their distribution approximately normal. A normal distribution for the transformed response times is desirable as it justifies the linearity and homoscedasticity assumptions in the underlying linear model. Past research has, however, shown that the transformed response times are not always normal. Models have been developed to accommodate this violation. In the present study, we propose a modelling approach for responses and response times to test and model non-normality in the transformed response times. Most importantly, we distinguish between non-normality due to heteroscedastic residual variances, and non-normality due to a skewed speed factor. In a simulation study, we establish parameter recovery and the power to separate both effects. In addition, we apply the model to a real data set. © 2017 The Authors. British Journal of Mathematical and Statistical Psychology published by John Wiley & Sons Ltd on behalf of British Psychological Society.

Global isostatic geoid anomalies for plate and boundary layer models of the lithosphere

NASA Technical Reports Server (NTRS)

Hager, B. H.

1981-01-01

Commonly used one dimensional geoid models predict that the isostatic geoid anomaly over old ocean basins for the boundary layer thermal model of the lithosphere is a factor of two greater than that for the plate model. Calculations presented, using the spherical analogues of the plate and boundary layer thermal models, show that for the actual global distribution of plate ages, one dimensional models are not accurate and a spherical, fully three dimensional treatment is necessary. The maximum difference in geoid heights predicted for the two models is only about two meters. The thermal structure of old lithosphere is unlikely to be resolvable using global geoid anomalies. Stripping the effects of plate aging and a hypothetical uniform, 35 km, isostatically-compensated continental crust from the observed geoid emphasizes that the largest-amplitude geoid anomaly is the geoid low of almost 120 m over West Antarctica, a factor of two greater than the low of 60 m over Ceylon.

Genetic and environmental influences on growth from late childhood to adulthood: a longitudinal study of two Finnish twin cohorts.

PubMed

Jelenkovic, Aline; Ortega-Alonso, Alfredo; Rose, Richard J; Kaprio, Jaakko; Rebato, Esther; Silventoinen, Karri

2011-01-01

Human growth is a complex process that remains insufficiently understood. We aimed to analyze genetic and environmental influences on growth from late childhood to early adulthood. Two cohorts of monozygotic and dizygotic (same sex and opposite sex) Finnish twin pairs were studied longitudinally using self-reported height at 11-12, 14, and 17 years and adult age (FinnTwin12) and at 16, 17, and 18 years and adult age (FinnTwin16). Univariate and multivariate variance component models for twin data were used. From childhood to adulthood, genetic differences explained 72-81% of the variation of height in boys and 65-86% in girls. Environmental factors common to co-twins explained 5-23% of the variation of height, with the residual variation explained by environmental factors unique to each twin individual. Common environmental factors affecting height were highly correlated between the analyzed ages (0.72-0.99 and 0.91-1.00 for boys and girls, respectively). Genetic (0.58-0.99 and 0.70-0.99, respectively) and unique environmental factors (0.32-0.78 and 0.54-0.82, respectively) affecting height at different ages were more weakly, but still substantially, correlated. The genetic contribution to height is strong during adolescence. The high genetic correlations detected across the ages encourage further efforts to identify genes affecting growth. Common and unique environmental factors affecting height during adolescence are also important, and further studies are necessary to identify their nature and test whether they interact with genetic factors. Copyright © 2011 Wiley-Liss, Inc.

Controls on the distribution and isotopic composition of helium in deep ground-water flows

USGS Publications Warehouse

Zhao, X.; Fritzel, T.L.B.; Quinodoz, H.A.M.; Bethke, C.M.; Torgersen, T.

1998-01-01

The distribution and isotopic composition of helium in sedimentary basins can be used to interpret the ages of very old ground waters. The piston-flow model commonly used in such interpretation, how ever, does not account for several important factors and as such works well only in very simple flow regimes. In this study of helium transport in a hypothetical sedimentary basin, we develop a numerical model that accounts for the magnitude and distribution of the basal helium flux, hydrodynamic dispersion, and complexities in flow regimes such as subregional flow cells. The modeling shows that these factors exert strong controls on the helium distribution and isotopic composition. The simulations may provide a basis for more accurate interpretations of observed helium concentrations and isotopic ratios in sedimentary basins.

The Unknown Hydrogen Exosphere: Space Weather Implications

NASA Astrophysics Data System (ADS)

Krall, J.; Glocer, A.; Fok, M.-C.; Nossal, S. M.; Huba, J. D.

2018-03-01

Recent studies suggest that the hydrogen (H) density in the exosphere and geocorona might differ from previously assumed values by factors as large as 2. We use the SAMI3 (Sami3 is Also a Model of the Ionosphere) and Comprehensive Inner Magnetosphere-Ionosphere models to evaluate scenarios where the hydrogen density is reduced or enhanced, by a factor of 2, relative to values given by commonly used empirical models. We show that the rate of plasmasphere refilling following a geomagnetic storm varies nearly linearly with the hydrogen density. We also show that the ring current associated with a geomagnetic storm decays more rapidly when H is increased. With respect to these two space weather effects, increased exosphere hydrogen density is associated with reduced threats to space assets during and following a geomagnetic storm.

Human attribute concepts: relative ubiquity across twelve mutually isolated languages.

PubMed

Saucier, Gerard; Thalmayer, Amber Gayle; Bel-Bahar, Tarik S

2014-07-01

It has been unclear which human-attribute concepts are most universal across languages. To identify common-denominator concepts, we used dictionaries for 12 mutually isolated languages-Maasai, Supyire Senoufo, Khoekhoe, Afar, Mara Chin, Hmong, Wik-Mungkan, Enga, Fijian, Inuktitut, Hopi, and Kuna-representing diverse cultural characteristics and language families, from multiple continents. A composite list of every person-descriptive term in each lexicon was closely examined to determine the content (in terms of English translation) most ubiquitous across languages. Study 1 identified 28 single-word concepts used to describe persons in all 12 languages, as well as 41 additional terms found in 11 of 12. Results indicated that attribute concepts related to morality and competence appear to be as cross-culturally ubiquitous as basic-emotion concepts. Formulations of universal-attribute concepts from Osgood and Wierzbicka were well-supported. Study 2 compared lexically based personality models on the relative ubiquity of key associated terms, finding that 1- and 2-dimensional models draw on markedly more ubiquitous terms than do 5- or 6-factor models. We suggest that ubiquitous attributes reflect common cultural as well as common biological processes.

A sensitivity study of the effects of evaporation/condensation accommodation coefficients on transient heat pipe modeling

NASA Astrophysics Data System (ADS)

Hall, Michael L.; Doster, J. Michael

1990-03-01

The dynamic behavior of liquid metal heat pipe models is strongly influenced by the choice of evaporation and condensation modeling techniques. Classic kinetic theory descriptions of the evaporation and condensation processes are often inadequate for real situations; empirical accommodation coefficients are commonly utilized to reflect nonideal mass transfer rates. The complex geometries and flow fields found in proposed heat pipe systems cause considerable deviation from the classical models. the THROHPUT code, which has been described in previous works, was developed to model transient liquid metal heat pipe behavior from frozen startup conditions to steady state full power operation. It is used here to evaluate the sensitivity of transient liquid metal heat pipe models to the choice of evaporation and condensation accommodation coefficients. Comparisons are made with experimental liquid metal heat pipe data. It is found that heat pipe behavior can be predicted with the proper choice of the accommodation coefficients. However, the common assumption of spatially constant accommodation coefficients is found to be a limiting factor in the model.

Shared Genetics and Couple-Associated Environment Are Major Contributors to the Risk of Both Clinical and Self-Declared Depression.

PubMed

Zeng, Yanni; Navarro, Pau; Xia, Charley; Amador, Carmen; Fernandez-Pujals, Ana M; Thomson, Pippa A; Campbell, Archie; Nagy, Reka; Clarke, Toni-Kim; Hafferty, Jonathan D; Smith, Blair H; Hocking, Lynne J; Padmanabhan, Sandosh; Hayward, Caroline; MacIntyre, Donald J; Porteous, David J; Haley, Chris S; McIntosh, Andrew M

2016-12-01

Both genetic and environmental factors contribute to risk of depression, but estimates of their relative contributions are limited. Commonalities between clinically-assessed major depressive disorder (MDD) and self-declared depression (SDD) are also unclear. Using data from a large Scottish family-based cohort (GS:SFHS, N=19,994), we estimated the genetic and environmental variance components for MDD and SDD. The components representing the genetic effect associated with genome-wide common genetic variants (SNP heritability), the additional pedigree-associated genetic effect and non-genetic effects associated with common environments were estimated in a linear mixed model (LMM). Both MDD and SDD had significant contributions from components representing the effect from common genetic variants, the additional genetic effect associated with the pedigree and the common environmental effect shared by couples. The estimate of correlation between SDD and MDD was high (r=1.00, se=0.20) for common-variant-associated genetic effect and lower for the additional genetic effect from the pedigree (r=0.57, se=0.08) and the couple-shared environmental effect (r=0.53, se=0.22). Both genetics and couple-shared environmental effects were major factors influencing liability to depression. SDD may provide a scalable alternative to MDD in studies seeking to identify common risk variants. Rarer variants and environmental effects may however differ substantially according to different definitions of depression. Copyright © 2016 The Authors. Published by Elsevier B.V. All rights reserved.

The Development of the General Factor of Psychopathology 'p Factor' Through Childhood and Adolescence.

PubMed

Murray, Aja Louise; Eisner, Manuel; Ribeaud, Denis

2016-11-01

Recent studies have suggested that the structure of psychopathology may be usefully represented in terms of a general factor of psychopathology (p-factor) capturing variance common to a broad range of symptoms transcending diagnostic domains in addition to specific factors capturing variance common to smaller subsets of more closely related symptoms. Little is known about how the general co-morbidity captured by this p-factor develops and whether general co-morbidity increases or decreases over childhood and adolescence. We evaluated two competing hypotheses: 1) dynamic mutualism which predicts growth in general co-morbidity and associated p-factor strength over time and 2) p-differentiation which predicts that manifestations of liabilities towards psychopathology become increasingly specific over time. Data came from the Zurich Project on the Social Development of Children and Youths (z-proso), a longitudinal study of a normative sample (approx. 50 % male) measured at 8 time points from ages 7 to 15. We operationalised general co-morbidity as p-factor strength in a bi-factor model and used omega hierarchical to track how this changed over development. In contrast to the predictions of both dynamic mutualism and p-differentiation, p-factor strength remained relatively constant over the studied period suggesting that such processes do not govern the interplay between psychopathological symptoms during this phase of development. Future research should focus on earlier phases of development and on factors that maintain the consistency of symptom-general covariation across this period.

Introducing the Postsecondary Instructional Practices Survey (PIPS): A Concise, Interdisciplinary, and Easy-to-Score Survey.

PubMed

Walter, Emily M; Henderson, Charles R; Beach, Andrea L; Williams, Cody T

Researchers, administrators, and policy makers need valid and reliable information about teaching practices. The Postsecondary Instructional Practices Survey (PIPS) is designed to measure the instructional practices of postsecondary instructors from any discipline. The PIPS has 24 instructional practice statements and nine demographic questions. Users calculate PIPS scores by an intuitive proportion-based scoring convention. Factor analyses from 72 departments at four institutions (N = 891) support a 2- or 5-factor solution for the PIPS; both models include all 24 instructional practice items and have good model fit statistics. Factors in the 2-factor model include (a) instructor-centered practices, nine items; and (b) student-centered practices, 13 items. Factors in the 5-factor model include (a) student-student interactions, six items; (b) content delivery, four items; (c) formative assessment, five items; (d) student-content engagement, five items; and (e) summative assessment, four items. In this article, we describe our development and validation processes, provide scoring conventions and outputs for results, and describe wider applications of the instrument. © 2016 E. M. Walter et al. CBE—Life Sciences Education © 2016 The American Society for Cell Biology. This article is distributed by The American Society for Cell Biology under license from the author(s). It is available to the public under an Attribution–Noncommercial–Share Alike 3.0 Unported Creative Commons License (http://creativecommons.org/licenses/by-nc-sa/3.0).

A novel co-occurrence-based approach to predict pure associative and semantic priming.

PubMed

Roelke, Andre; Franke, Nicole; Biemann, Chris; Radach, Ralph; Jacobs, Arthur M; Hofmann, Markus J

2018-03-15

The theoretical "difficulty in separating association strength from [semantic] feature overlap" has resulted in inconsistent findings of either the presence or absence of "pure" associative priming in recent literature (Hutchison, 2003, Psychonomic Bulletin & Review, 10(4), p. 787). The present study used co-occurrence statistics of words in sentences to provide a full factorial manipulation of direct association (strong/no) and the number of common associates (many/no) of the prime and target words. These common associates were proposed to serve as semantic features for a recent interactive activation model of semantic processing (i.e., the associative read-out model; Hofmann & Jacobs, 2014). With stimulus onset asynchrony (SOA) as an additional factor, our findings indicate that associative and semantic priming are indeed dissociable. Moreover, the effect of direct association was strongest at a long SOA (1,000 ms), while many common associates facilitated lexical decisions primarily at a short SOA (200 ms). This response pattern is consistent with previous performance-based accounts and suggests that associative and semantic priming can be evoked by computationally determined direct and common associations.

Adolescence as a period of vulnerability and intervention in schizophrenia: Insights from the MAM model.

PubMed

Gomes, Felipe V; Rincón-Cortés, Millie; Grace, Anthony A

2016-11-01

Adolescence is a time of extensive neuroanatomical, functional and chemical reorganization of the brain, which parallels substantial maturational changes in behavior and cognition. Environmental factors that impinge on the timing of these developmental factors, including stress and drug exposure, increase the risk for psychiatric disorders. Indeed, antecedents to affective and psychotic disorders, which have clinical and pathophysiological overlap, are commonly associated with risk factors during adolescence that predispose to these disorders. In the context of schizophrenia, psychosis typically begins in late adolescence/early adulthood, which has been replicated by animal models. Rats exposed during gestational day (GD) 17 to the mitotoxin methylazoxymethanol acetate (MAM) exhibit behavioral, pharmacological, and anatomical characteristics consistent with an animal model of schizophrenia. Here we provide an overview of adolescent changes within the dopamine system and the PFC and review recent findings regarding the effects of stress and cannabis exposure during the peripubertal period as risk factors for the emergence of schizophrenia-like deficits. Finally, we discuss peripubertal interventions appearing to circumvent the emergence of adult schizophrenia-like deficits. Copyright © 2016 Elsevier Ltd. All rights reserved.

Clinical models are inaccurate in predicting bile duct stones in situ for patients with gallbladder.

PubMed

Topal, B; Fieuws, S; Tomczyk, K; Aerts, R; Van Steenbergen, W; Verslype, C; Penninckx, F

2009-01-01

The probability that a patient has common bile duct stones (CBDS) is a key factor in determining diagnostic and treatment strategies. This prospective cohort study evaluated the accuracy of clinical models in predicting CBDS for patients who will undergo cholecystectomy for lithiasis. From October 2005 until September 2006, 335 consecutive patients with symptoms of gallstone disease underwent cholecystectomy. Statistical analysis was performed on prospective patient data obtained at the time of first presentation to the hospital. Demonstrable CBDS at the time of endoscopic retrograde cholangiopancreatography (ERCP) or intraoperative cholangiography (IOC) was considered the gold standard for the presence of CBDS. Common bile duct stones were demonstrated in 53 patients. For 35 patients, ERCP was performed, with successful stone clearance in 24 of 30 patients who had proven CBDS. In 29 patients, IOC showed CBDS, which were managed successfully via laparoscopic common bile duct exploration, with stone extraction at the time of cholecystectomy. Prospective validation of the existing model for CBDS resulted in a predictive accuracy rate of 73%. The new model showed a predictive accuracy rate of 79%. Clinical models are inaccurate in predicting CBDS in patients with cholelithiasis. Management strategies should be based on the local availability of therapeutic expertise.

Victimization, Suicidal Ideation, and Alcohol Use From Age 13 to 15 Years: Support for the Self-Medication Model

PubMed Central

Marschall-Lévesque, Shawn; Castellanos-Ryan, Natalie; Parent, Sophie; Renaud, Johanne; Vitaro, Frank; Boivin, Michel; Tremblay, Richard E.; Séguin, Jean R.

2017-01-01

Purpose Recent years have seen increased coverage of adolescent victimization and suicide. Both adolescent peer victimization and substance use have been associated with suicidal ideation, with evidence suggesting that all three factors are interrelated. There are at least four models which can explain the associations between these factors (i.e., self-medication, secondary mental disorder, bidirectional, and common factor). However, none of them is being empirically supported as the dominant model because few longitudinal studies have explored the association between these factors. Methods The present study compared longitudinal paths of all four models simultaneously using a cross-lagged model. This was done using self-reported measures of peer victimization, suicidal ideation, and alcohol use at age 13, 14, and 15 years in a longitudinal sample of 238 adolescents. Results All three variables were moderately stable across time. Significant cross-lagged associations were found, showing that frequent peer victimization at age 13 years was associated with higher odds of having suicidal ideation at age 14 years (odds ratio, 1.82; p < .05). In turn, presence of suicidal ideation at age 14 years was significantly associated with higher alcohol use frequency at age 15 years (β = .13; p < .05). Conclusions Results support previous literature suggesting that peer victimization predates alcohol use and extends it by showing clear directionality between suicidal ideation and alcohol use over 1 year, supporting the self-medication model. Clarifying the empirical basis of these underlying models could allow for earlier prevention strategies, by targeting the risk factor that appears the earliest in the model. PMID:27914973

The Tripartite Model of Risk Perception (TRIRISK): Distinguishing Deliberative, Affective, and Experiential Components of Perceived Risk.

PubMed

Ferrer, Rebecca A; Klein, William M P; Persoskie, Alexander; Avishai-Yitshak, Aya; Sheeran, Paschal

2016-10-01

Although risk perception is a key predictor in health behavior theories, current conceptions of risk comprise only one (deliberative) or two (deliberative vs. affective/experiential) dimensions. This research tested a tripartite model that distinguishes among deliberative, affective, and experiential components of risk perception. In two studies, and in relation to three common diseases (cancer, heart disease, diabetes), we used confirmatory factor analyses to examine the factor structure of the tripartite risk perception (TRIRISK) model and compared the fit of the TRIRISK model to dual-factor and single-factor models. In a third study, we assessed concurrent validity by examining the impact of cancer diagnosis on (a) levels of deliberative, affective, and experiential risk perception, and (b) the strength of relations among risk components, and tested predictive validity by assessing relations with behavioral intentions to prevent cancer. The tripartite factor structure was supported, producing better model fit across diseases (studies 1 and 2). Inter-correlations among the components were significantly smaller among participants who had been diagnosed with cancer, suggesting that affected populations make finer-grained distinctions among risk perceptions (study 3). Moreover, all three risk perception components predicted unique variance in intentions to engage in preventive behavior (study 3). The TRIRISK model offers both a novel conceptualization of health-related risk perceptions, and new measures that enhance predictive validity beyond that engendered by unidimensional and bidimensional models. The present findings have implications for the ways in which risk perceptions are targeted in health behavior change interventions, health communications, and decision aids.

Ion penetration depth in the plant cell wall

NASA Astrophysics Data System (ADS)

Yu, L. D.; Vilaithong, T.; Phanchaisri, B.; Apavatjrut, P.; Anuntalabhochai, S.; Evans, P.; Brown, I. G.

2003-05-01

This study investigates the depth of ion penetration in plant cell wall material. Based on the biological structure of the plant cell wall, a physical model is proposed which assumes that the wall is composed of randomly orientated layers of cylindrical microfibrils made from cellulose molecules of C 6H 12O 6. With this model, we have determined numerical factors for ion implantation in the plant cell wall to correct values calculated from conventional ion implantation programs. Using these correction factors, it is possible to apply common ion implantation programs to estimate the ion penetration depth in the cell for bioengineering purposes. These estimates are compared with measured data from experiments and good agreement is achieved.

Internal validity of an anxiety disorder screening instrument across five ethnic groups.

PubMed

Ritsher, Jennifer Boyd; Struening, Elmer L; Hellman, Fred; Guardino, Mary

2002-08-30

We tested the factor structure of the National Anxiety Disorder Screening Day instrument (n=14860) within five ethnic groups (White, Black, Hispanic, Asian, Native American). Conducted yearly across the US, the screening is meant to detect five common anxiety syndromes. Factor analyses often fail to confirm the validity of assessment tools' structures, and this is especially likely for minority ethnic groups. If symptoms cluster differently across ethnic groups, criteria for conventional DSM-IV disorders are less likely to be met, leaving significant distress unlabeled and under-detected in minority groups. Exploratory and confirmatory factor analyses established that the items clustered into the six expected factors (one for each disorder plus agoraphobia). This six-factor model fit the data very well for Whites and not significantly worse for each other group. However, small areas of the model did not appear to fit as well for some groups. After taking these areas into account, the data still clearly suggest more prevalent PTSD symptoms in the Black, Hispanic and Native American groups in our sample. Additional studies are warranted to examine the model's external validity, generalizability to more culturally distinct groups, and overlap with other culture-specific syndromes.

Beyond the big five: the Dark Triad and the supernumerary personality inventory.

PubMed

Veselka, Livia; Schermer, Julie Aitken; Vernon, Philip A

2011-04-01

The Dark Triad of personality, comprising Machiavellianism, narcissism, and psychopathy, was investigated in relation to the Supernumerary Personality Inventory (SPI) traits, because both sets of variables are predominantly distinct from the Big Five model of personality. Correlational and principal factor analyses were conducted to assess the relations between the Dark Triad and SPI traits. Multivariate behavioral genetic model-fitting analyses were also conducted to determine the correlated genetic and/or environmental underpinnings of the observed phenotypic correlations. Participants were 358 monozygotic and 98 same-sex dizygotic adult twin pairs from North America. As predicted, results revealed significant correlations between the Dark Triad and most SPI traits, and these correlations were primarily attributable to common genetic and non-shared environmental factors, except in the case of Machiavellianism, where shared environmental effects emerged. Three correlated factors were extracted during joint factor analysis of the Dark Triad and SPI traits, as well as a heritable general factor of personality - results that clarified the structure of the Dark Triad construct. It is concluded that the Dark Triad represents an exploitative and antisocial construct that extends beyond the Big Five model and shares a theoretical space with the SPI traits.

Prediction of cadmium enrichment in reclaimed coastal soils by classification and regression tree

NASA Astrophysics Data System (ADS)

Ru, Feng; Yin, Aijing; Jin, Jiaxin; Zhang, Xiuying; Yang, Xiaohui; Zhang, Ming; Gao, Chao

2016-08-01

Reclamation of coastal land is one of the most common ways to obtain land resources in China. However, it has long been acknowledged that the artificial interference with coastal land has disadvantageous effects, such as heavy metal contamination. This study aimed to develop a prediction model for cadmium enrichment levels and assess the importance of affecting factors in typical reclaimed land in Eastern China (DFCL: Dafeng Coastal Land). Two hundred and twenty seven surficial soil/sediment samples were collected and analyzed to identify the enrichment levels of cadmium and the possible affecting factors in soils and sediments. The classification and regression tree (CART) model was applied in this study to predict cadmium enrichment levels. The prediction results showed that cadmium enrichment levels assessed by the CART model had an accuracy of 78.0%. The CART model could extract more information on factors affecting the environmental behavior of cadmium than correlation analysis. The integration of correlation analysis and the CART model showed that fertilizer application and organic carbon accumulation were the most important factors affecting soil/sediment cadmium enrichment levels, followed by particle size effects (Al2O3, TFe2O3 and SiO2), contents of Cl and S, surrounding construction areas and reclamation history.

Urban heat island effect: A systematic review of spatio-temporal factors, data, methods, and mitigation measures

NASA Astrophysics Data System (ADS)

Deilami, Kaveh; Kamruzzaman, Md.; Liu, Yan

2018-05-01

Despite research on urban heat island (UHI) effect has increased exponentially over the last few decades, a systematic review of factors contributing to UHI effect has scarcely been reported in the literature. This paper provides a systematic and overarching review of different spatial and temporal factors affecting the UHI effect. UHI is a phenomenon when urban areas experience a higher temperature than their surrounding non-urban areas and is considered as a critical factor contributing to global warming, heat related mortalities, and unpredictable climatic changes. Therefore, there is a pressing need to identify the spatio-temporal factors that contribute to (or mitigate) the UHI effect in order to develop a thorough understanding of their causal mechanism so that these are addressed through urban planning policies. This paper systematically identified 75 eligible studies on UHI effect and reviews the nature and type of satellite images used, the techniques applied to classify land cover/use changes, the models to assess the link between spatio-temporal factors and UHI effect, and the effects of these factors on UHI. The review results show that: a) 54% of the studies used Landsat TM images for modelling the UHI effect followed by Landsat ETM (34%), and MODIS (28%); b) land cover indices (46%), followed by supervised classification (17%) were the dominant methods to derive land cover/use changes associated with UHI effect; c) ordinary least square regression is the most commonly applied method (68%) to investigate the link between different spatio-temporal factors and the UHI effect followed by comparative analysis (33%); and d) the most common factors affecting the UHI effect as reported in the reviewed studies, include vegetation cover (44%), season (33%), built-up area (28%), day/night (25%), population density (14%), water body (12%) together with others. This research discusses the findings in policy terms and provides directions for future research.

Experimentally Derived δ13C and δ15N Discrimination Factors for Gray Wolves and the Impact of Prior Information in Bayesian Mixing Models

PubMed Central

Bucci, Melanie E.; Callahan, Peggy; Koprowski, John L.; Polfus, Jean L.; Krausman, Paul R.

2015-01-01

Stable isotope analysis of diet has become a common tool in conservation research. However, the multiple sources of uncertainty inherent in this analysis framework involve consequences that have not been thoroughly addressed. Uncertainty arises from the choice of trophic discrimination factors, and for Bayesian stable isotope mixing models (SIMMs), the specification of prior information; the combined effect of these aspects has not been explicitly tested. We used a captive feeding study of gray wolves (Canis lupus) to determine the first experimentally-derived trophic discrimination factors of C and N for this large carnivore of broad conservation interest. Using the estimated diet in our controlled system and data from a published study on wild wolves and their prey in Montana, USA, we then investigated the simultaneous effect of discrimination factors and prior information on diet reconstruction with Bayesian SIMMs. Discrimination factors for gray wolves and their prey were 1.97‰ for δ13C and 3.04‰ for δ15N. Specifying wolf discrimination factors, as opposed to the commonly used red fox (Vulpes vulpes) factors, made little practical difference to estimates of wolf diet, but prior information had a strong effect on bias, precision, and accuracy of posterior estimates. Without specifying prior information in our Bayesian SIMM, it was not possible to produce SIMM posteriors statistically similar to the estimated diet in our controlled study or the diet of wild wolves. Our study demonstrates the critical effect of prior information on estimates of animal diets using Bayesian SIMMs, and suggests species-specific trophic discrimination factors are of secondary importance. When using stable isotope analysis to inform conservation decisions researchers should understand the limits of their data. It may be difficult to obtain useful information from SIMMs if informative priors are omitted and species-specific discrimination factors are unavailable. PMID:25803664

Experimentally derived δ¹³C and δ¹⁵N discrimination factors for gray wolves and the impact of prior information in Bayesian mixing models.

PubMed

Derbridge, Jonathan J; Merkle, Jerod A; Bucci, Melanie E; Callahan, Peggy; Koprowski, John L; Polfus, Jean L; Krausman, Paul R

2015-01-01

Stable isotope analysis of diet has become a common tool in conservation research. However, the multiple sources of uncertainty inherent in this analysis framework involve consequences that have not been thoroughly addressed. Uncertainty arises from the choice of trophic discrimination factors, and for Bayesian stable isotope mixing models (SIMMs), the specification of prior information; the combined effect of these aspects has not been explicitly tested. We used a captive feeding study of gray wolves (Canis lupus) to determine the first experimentally-derived trophic discrimination factors of C and N for this large carnivore of broad conservation interest. Using the estimated diet in our controlled system and data from a published study on wild wolves and their prey in Montana, USA, we then investigated the simultaneous effect of discrimination factors and prior information on diet reconstruction with Bayesian SIMMs. Discrimination factors for gray wolves and their prey were 1.97‰ for δ13C and 3.04‰ for δ15N. Specifying wolf discrimination factors, as opposed to the commonly used red fox (Vulpes vulpes) factors, made little practical difference to estimates of wolf diet, but prior information had a strong effect on bias, precision, and accuracy of posterior estimates. Without specifying prior information in our Bayesian SIMM, it was not possible to produce SIMM posteriors statistically similar to the estimated diet in our controlled study or the diet of wild wolves. Our study demonstrates the critical effect of prior information on estimates of animal diets using Bayesian SIMMs, and suggests species-specific trophic discrimination factors are of secondary importance. When using stable isotope analysis to inform conservation decisions researchers should understand the limits of their data. It may be difficult to obtain useful information from SIMMs if informative priors are omitted and species-specific discrimination factors are unavailable.

The Role of Education in Reinforcing the Group Model in Japanese Society.

ERIC Educational Resources Information Center

Collins, Kevin

Many attempts have been made to explain how modern Japan has, with speed and minimal stress, become competitive with Western nations in terms of military strength and industrial productivity. One factor commonly mentioned is the "groupishness," the collective orientation,that is basic to Japanese society. Some research has suggested that…

A Cross-Cultural Study of CKCM Efficacy in an Undergraduate Chemistry Classroom

ERIC Educational Resources Information Center

Çalik, Muammer; Cobern, William W.

2017-01-01

The aim of this study was to cross-culturally investigate the instructional efficacy of the Common Knowledge Construction Model (CKCM) with college students learning about "factors affecting solubility" focusing on students' conceptual understanding, attitudes and scientific habits of mind. Even though the CKCM is a decade old, there has…

Tests of Measurement Invariance without Subgroups: A Generalization of Classical Methods

ERIC Educational Resources Information Center

Merkle, Edgar C.; Zeileis, Achim

2013-01-01

The issue of measurement invariance commonly arises in factor-analytic contexts, with methods for assessment including likelihood ratio tests, Lagrange multiplier tests, and Wald tests. These tests all require advance definition of the number of groups, group membership, and offending model parameters. In this paper, we study tests of measurement…

Using Nonlinear Programming in International Trade Theory: The Factor-Proportions Model

ERIC Educational Resources Information Center

Gilbert, John

2004-01-01

Students at all levels benefit from a multi-faceted approach to learning abstract material. The most commonly used technique in teaching the pure theory of international trade is a combination of geometry and algebraic derivations. Numerical simulation can provide a valuable third support to these approaches. The author describes a simple…

Differential Ability Scales-II Prediction of Reading Performance: Global Scores Are Not Enough

ERIC Educational Resources Information Center

Elliott, Colin D.; Hale, James B.; Fiorello, Catherine A.; Dorvil, Cledicianne; Moldovan, Jaime

2010-01-01

This study investigated the effects of broad cognitive abilities derived from the Cattell-Horn-Carroll (CHC) taxonomy, together with the effect of the general factor ("g"), on Wechsler Individual Achievement Test, Second Edition (WIAT-II) reading achievement. Structural equation modeling (SEM) and commonality analyses were applied to the…

Recruitment dynamics in complex life cycles. [of organisms living in marine rocky zone

NASA Technical Reports Server (NTRS)

Roughgarden, Jonathan; Possingham, Hugh; Gaines, Steven

1988-01-01

Factors affecting marine population fluctuations are discussed with particular attention given to a common barnacle species of the Pacific coast of North America. It is shown how models combining larval circulation with adult interactions can potentially forecast population fluctuations. These findings demonstrate how processes in different ecological habitats are coupled.

Statistical Power for a Simultaneous Test of Factorial and Predictive Invariance

ERIC Educational Resources Information Center

Olivera-Aguilar, Margarita; Millsap, Roger E.

2013-01-01

A common finding in studies of differential prediction across groups is that although regression slopes are the same or similar across groups, group differences exist in regression intercepts. Building on earlier work by Birnbaum (1979), Millsap (1998) presented an invariant factor model that would explain such intercept differences as arising due…

An Investigation of the Sampling Distribution of the Congruence Coefficient.

ERIC Educational Resources Information Center

Broadbooks, Wendy J.; Elmore, Patricia B.

This study developed and investigated an empirical sampling distribution of the congruence coefficient. The effects of sample size, number of variables, and population value of the congruence coefficient on the sampling distribution of the congruence coefficient were examined. Sample data were generated on the basis of the common factor model and…

Ribosomal DNA replication fork barrier and HOT1 recombination hot spot: shared sequences but independent activities.

PubMed

Ward, T R; Hoang, M L; Prusty, R; Lau, C K; Keil, R L; Fangman, W L; Brewer, B J

2000-07-01

In the ribosomal DNA of Saccharomyces cerevisiae, sequences in the nontranscribed spacer 3' of the 35S ribosomal RNA gene are important to the polar arrest of replication forks at a site called the replication fork barrier (RFB) and also to the cis-acting, mitotic hyperrecombination site called HOT1. We have found that the RFB and HOT1 activity share some but not all of their essential sequences. Many of the mutations that reduce HOT1 recombination also decrease or eliminate fork arrest at one of two closely spaced RFB sites, RFB1 and RFB2. A simple model for the juxtaposition of RFB and HOT1 sequences is that the breakage of strands in replication forks arrested at RFB stimulates recombination. Contrary to this model, we show here that HOT1-stimulated recombination does not require the arrest of forks at the RFB. Therefore, while HOT1 activity is independent of replication fork arrest, HOT1 and RFB require some common sequences, suggesting the existence of a common trans-acting factor(s).

"Staying safe" - a narrative review of falls prevention in people with Parkinson's - "PDSAFE".

PubMed

Hulbert, Sophia; Rochester, Lynn; Nieuwboer, Alice; Goodwin, Vicki; Fitton, Carolyn; Chivers-Seymour, Kim; Ashburn, Ann

2018-05-18

Parkinson's disease demonstrates a spectrum of motor and non-motor symptoms. Falling is common and disabling. Current medical management shows minimal impact to reduce falls or fall-related risk factors, such as deficits in gait, strength, and postural instability. Despite evidence supporting rehabilitation in reducing fall risk factors, the most appropriate intervention to reduce overall fall rate remains inconclusive. This article aims to 1) synthesise current evidence and conceptual models of falls rehabilitation in Parkinson's in a narrative review; and based on this evidence, 2) introduce the treatment protocol used in the falls prevention and multi-centre clinical trial "PDSAFE". Search of four bibliographic databases using the terms "Parkinson*" and "Fall*" combined with each of the following; "Rehab*, Balanc*, Strength*, Strateg*and Exercis*" and a framework for narrative review was followed. A total of 3557 papers were identified, 416 were selected for review. The majority report the impact of rehabilitation on isolated fall risk factors. Twelve directly measure the impact on overall fall rate. Results were used to construct a narrative review with conceptual discussion based on the "International Classification of Functioning", leading to presentation of the "PDSAFE" intervention protocol. Evidence suggests training single, fall risk factors may not affect overall fall rate. Combining with behavioural and strategy training in a functional, personalised multi-dimensional model, addressing all components of the "International Classification of Functioning" is likely to provide a greater influence on falls reduction. "PDSAFE" is a multi-dimensional, physiotherapist delivered, individually tailored, progressive, home-based programme. It is designed with a strong evidence-based approach and illustrates a model for the clinical delivery of the conceptual theory discussed. Implications for Rehabilitation Parkinson's disease demonstrates a spectrum of motor and non-motor symptoms, where falling is common and disabling. Current medical and surgical management have minimal impact on falls, rehabilitation of falls risk factors has strong evidence but the most appropriate intervention to reduce overall fall rate remains inconclusive. Addressing all components of the International Classification of Function in a multifactorial model when designing falls rehabilitation interventions may be more effective at reducing fall rates in people with Parkinson's than treating isolated risk factors. The clinical model for falls rehabilitation in people with Parkinson's should be multi-dimensional.

Variance composition, measurement invariance by gender, and construct validity of the Femininity Ideology Scale-Short Form.

PubMed

Levant, Ronald F; Alto, Kathleen M; McKelvey, Daniel K; Richmond, Katherine A; McDermott, Ryon C

2017-11-01

The current study extended prior work on the Femininity Ideology Scale (FIS), a multidimensional measure of traditional femininity ideology (TFI), in several ways. First, we conducted exploratory factor and bifactor analyses, which revealed a general TFI factor and 3 specific factors: dependence/deference, purity, and emotionality/traditional roles. Second, based on these results we developed the 12-item FIS-Short Form (FIS-SF). Third, we assessed the FIS-SF using confirmatory factor analysis on a separate sample, finding that the items loaded on the general factor and 3 specific factors as hypothesized, and that the bifactor model fit better than common factors and unidimensional models. Fourth, model-based reliability estimates tentatively support the use of raw scores to represent the general TFI factor and the emotionality/traditional roles specific factor, but the other 2 specific factors are best measured using SEM or by ipsatizing their scores. Fifth, we assessed measurement invariance across 2 gender groups, finding evidence for configural invariance for all factors, and for partial metric invariance for the specific factors. Sixth, we found evidence for the convergent construct validity of the FIS-SF general factor and the emotionality/traditional roles specific factors by examining relationships with the latent variables of several constructs in the nomological network. The results are discussed in relationship to prior literature, future research directions, applications to counseling practice, and limitations. Data (N = 1,472, 907 women, 565 men, 530 people of color) were from community and college participants who responded to an online survey. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

Path analysis of risk factors leading to premature birth.

PubMed

Fields, S J; Livshits, G; Sirotta, L; Merlob, P

1996-01-01

The present study tested whether various sociodemographic, anthropometric, behavioral, and medical/physiological factors act in a direct or indirect manner on the risk of prematurity using path analysis on a sample of Israeli births. The path model shows that medical complications, primarily toxemia, chorioammionitis, and a previous low birth weight delivery directly and significantly act on the risk of prematurity as do low maternal pregnancy weight gain and ethnicity. Other medical complications, including chronic hypertension, preclampsia, and placental abruption, although significantly correlated with prematurity, act indirectly on prematurity through toxemia. The model further shows that the commonly accepted sociodemographic, anthropometric, and behavioral risk factors act by modifying the development of medical complications that lead to prematurity as opposed to having a direct effect on premature delivery. © 1996 Wiley-Liss, Inc. Copyright © 1996 Wiley-Liss, Inc.

Stress-intensity factors for a wide range of semi-elliptical surface cracks in finite-thickness plates

NASA Technical Reports Server (NTRS)

Raju, I. S.; Newman, J. C., Jr.

1979-01-01

Surface cracks are among the more common flaws in aircraft and pressure vessel components. Several calculations of stress-intensity factors for semi-elliptical surface cracks subjected to tension have appeared in the literature. However, some of these solutions are in disagreement by 50-100%. In this paper, stress-intensity factors for shallow and deep semi-elliptical surface cracks in plates subjected to tension are presented. To verify the accuracy of the three-dimensional finite-element models employed, convergence was studied by varying the number of degrees of freedom in the models from 1500 to 6900. The 6900 degrees of freedom used here were more than twice the number used in previously reported solutions. Also, the stress-intensity variations in the boundary-layer region at the intersection of the crack with the free surface were investigated.

The road traffic crashes as a neglected public health concern; an observational study from Iranian population.

PubMed

Bakhtiyari, Mahmood; Delpisheh, Ali; Monfared, Ayad Bahadori; Kazemi-Galougahi, Mohammad Hassan; Mehmandar, Mohammad Reza; Riahi, Mohammad; Salehi, Masoud; Mansournia, Mohammad Ali

2015-01-01

Traffic crashes are multifactorial events caused by human factors, technical issues, and environmental conditions. The present study aimed to determine the role of human factors in traffic crashes in Iran using the proportional odds regression model. The database of all traffic crashes in Iran in 2010 (n = 592, 168) registered through the "COM.114" police forms was investigated. Human risk factors leading to traffic crashes were determined and the odds ratio (OR) of each risk factor was estimated using an ordinal regression model and adjusted for potential confounding factors such as age, gender, and lighting status within and outside of cities. The drivers' mean age ± standard deviation was 34.1 ± 14.0 years. The most prevalent risk factors leading to death within cities were disregarding traffic rules and regulations (45%), driver rushing (31%), and alcohol consumption (12.3%). Using the proportional odds regression model, alcohol consumption was the most significant human risk factor in traffic crashes within cities (OR = 6.5, 95% confidence interval [CI], 4.88-8.65) and outside of cities (OR = 1.73, 95% CI, 1.22-3.29). Public health strategies and preventive policies should be focused on more common human risk factors such as disregarding traffic rules and regulations, drivers' rushing, and alcohol consumption due to their greater population attributable fraction and more intuitive impacts on society.

Triggers for Autism: Genetic and Environmental Factors

PubMed Central

Matsuzaki, Hideo; Iwata, Keiko; Manabe, Takayuki; Mori, Norio

2012-01-01

This report reviews the research on the factors that cause autism. In several studies, these factors have been verified by reproducing them in autistic animal models. Clinical research has demonstrated that genetic and environmental factors play a major role in the development of autism. However, most cases are idiopathic, and no single factor can explain the trends in the pathology and prevalence of autism. At the time of this writing, autism is viewed more as a multi-factorial disorder. However, the existence of an unknown factor that may be common in all autistic cases cannot be ruled out. It is hoped that future biological studies of autism will help construct a new theory that can interpret the pathology of autism in a coherent manner. To achieve this, large-scale epidemiological research is essential. PMID:23650465

Modeling the structure of the attitudes and belief scale 2 using CFA and bifactor approaches: Toward the development of an abbreviated version.

PubMed

Hyland, Philip; Shevlin, Mark; Adamson, Gary; Boduszek, Daniel

2014-01-01

The Attitudes and Belief Scale-2 (ABS-2: DiGiuseppe, Leaf, Exner, & Robin, 1988. The development of a measure of rational/irrational thinking. Paper presented at the World Congress of Behavior Therapy, Edinburg, Scotland.) is a 72-item self-report measure of evaluative rational and irrational beliefs widely used in Rational Emotive Behavior Therapy research contexts. However, little psychometric evidence exists regarding the measure's underlying factor structure. Furthermore, given the length of the ABS-2 there is a need for an abbreviated version that can be administered when there are time demands on the researcher, such as in clinical settings. This study sought to examine a series of theoretical models hypothesized to represent the latent structure of the ABS-2 within an alternative models framework using traditional confirmatory factor analysis as well as utilizing a bifactor modeling approach. Furthermore, this study also sought to develop a psychometrically sound abbreviated version of the ABS-2. Three hundred and thirteen (N = 313) active emergency service personnel completed the ABS-2. Results indicated that for each model, the application of bifactor modeling procedures improved model fit statistics, and a novel eight-factor intercorrelated solution was identified as the best fitting model of the ABS-2. However, the observed fit indices failed to satisfy commonly accepted standards. A 24-item abbreviated version was thus constructed and an intercorrelated eight-factor solution yielded satisfactory model fit statistics. Current results support the use of a bifactor modeling approach to determining the factor structure of the ABS-2. Furthermore, results provide empirical support for the psychometric properties of the newly developed abbreviated version.

Body weight concerns: Cross-national study and identification of factors related to eating disorders.

PubMed

Silva, Wanderson Roberto da; Santana, Moema de Souza; Maroco, João; Maloa, Benvindo Felismino Samuel; Campos, Juliana Alvares Duarte Bonini

2017-01-01

Body weight concerns are common among individuals with eating disorders, and this construct can be assessed using psychometric instruments. The Weight Concerns Scale (WCS) is commonly used to assess body weight concerns. To evaluate the psychometric properties of the WCS with Brazilian, Portuguese, and Mozambican female college students; to estimate body weight concerns; and to identify factors related to eating disorders. Confirmatory factor analysis was performed. Factorial, convergent, concurrent, and divergent validity, as well as reliability, were assessed. Cross-national invariance was tested by means of multigroup analysis. Structural models were tested using the WCS as the dependent variable, while demographic and academic variables and body mass index were used as independent variables. Logistic models were tested to estimate the likelihood of eating disorders being developed in specific groups. Participants were 2,068 female students. The psychometric properties of the WCS were adequate for the Portuguese sample; however, for the Brazilian and Mozambican samples, it was necessary to correlate the errors of two items to improve model fit. The WCS did not show cross-national invariance. The variables "thoughts about dropping out of college," "medication use because of studies," "medication and supplements use for body change," "body mass index," "socioeconomic status," "age," and "performance in course" were significant predictors of body weight concerns. Overall, 24.4% (95% confidence interval = 22.9-26.7) of the students were likely to develop eating disorders. Students under 21 years old, who use medication and supplements for body change, and who were classified as overweight/obese have increased likelihood of developing eating disorders. The WCS showed good psychometric properties with Brazilian, Portuguese, and Mozambican students; however, it did not show cross-national invariance. We identified important aspects for investigating body weight concerns and factors related to eating disorders.

Design Evaluation of Wind Turbine Spline Couplings Using an Analytical Model: Preprint

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

Guo, Y.; Keller, J.; Wallen, R.

2015-02-01

Articulated splines are commonly used in the planetary stage of wind turbine gearboxes for transmitting the driving torque and improving load sharing. Direct measurement of spline loads and performance is extremely challenging because of limited accessibility. This paper presents an analytical model for the analysis of articulated spline coupling designs. For a given torque and shaft misalignment, this analytical model quickly yields insights into relationships between the spline design parameters and resulting loads; bending, contact, and shear stresses; and safety factors considering various heat treatment methods. Comparisons of this analytical model against previously published computational approaches are also presented.

Convergence of circuit dysfunction in ASD: a common bridge between diverse genetic and environmental risk factors and common clinical electrophysiology.

PubMed

Port, Russell G; Gandal, Michael J; Roberts, Timothy P L; Siegel, Steven J; Carlson, Gregory C

2014-01-01

Most recent estimates indicate that 1 in 68 children are affected by an autism spectrum disorder (ASD). Though decades of research have uncovered much about these disorders, the pathological mechanism remains unknown. Hampering efforts is the seeming inability to integrate findings over the micro to macro scales of study, from changes in molecular, synaptic and cellular function to large-scale brain dysfunction impacting sensory, communicative, motor and cognitive activity. In this review, we describe how studies focusing on neuronal circuit function provide unique context for identifying common neurobiological disease mechanisms of ASD. We discuss how recent EEG and MEG studies in subjects with ASD have repeatedly shown alterations in ensemble population recordings (both in simple evoked related potential latencies and specific frequency subcomponents). Because these disease-associated electrophysiological abnormalities have been recapitulated in rodent models, studying circuit differences in these models may provide access to abnormal circuit function found in ASD. We then identify emerging in vivo and ex vivo techniques, focusing on how these assays can characterize circuit level dysfunction and determine if these abnormalities underlie abnormal clinical electrophysiology. Such circuit level study in animal models may help us understand how diverse genetic and environmental risks can produce a common set of EEG, MEG and anatomical abnormalities found in ASD.

Delayed onset of lactogenesis among first-time mothers is related to maternal obesity and factors associated with ineffective breastfeeding.

PubMed

Nommsen-Rivers, Laurie A; Chantry, Caroline J; Peerson, Janet M; Cohen, Roberta J; Dewey, Kathryn G

2010-09-01

Delayed onset of lactogenesis (OL) is most common in primiparas and increases the risk of excess neonatal weight loss, formula supplementation, and early weaning. We examined variables associated with delayed OL among first-time mothers who delivered at term and initiated breastfeeding (n = 431). We conducted in-person interviews during pregnancy and at days 0, 3, and 7 postpartum and extracted obstetric and newborn information from medical records. We defined OL as delayed if it occurred after 72 h and used chi-square analysis to examine its association with potential risk factors across 6 dimensions: 1) prenatal characteristics, 2) maternal anthropometric characteristics, 3) labor and delivery experience, 4) newborn characteristics, 5) maternal postpartum factors, and 6) infant feeding variables. We examined independent associations by using multivariable logistic regression analysis. Median OL was 68.9 h postpartum; 44% of mothers experienced delayed OL. We observed significant bivariate associations between delayed OL and variables in all 6 dimensions (P < 0.05). In a multivariate model adjusted for prenatal feeding intentions, independent risk factors for delayed OL were maternal age > or =30 y, body mass index in the overweight or obese range, birth weight >3600 g, absence of nipple discomfort between 0-3 d postpartum, and infant failing to "breastfeed well" > or =2 times in the first 24 h. Postpartum edema was significant in an alternate model excluding body mass index (P < 0.05). The risk factors for delayed OL are multidimensional. Public health and obstetric and maternity care interventions are needed to address what has become an alarmingly common problem among primiparas.

Back-neck pain and symptoms of anxiety and depression: a population-based twin study.

PubMed

Reichborn-Kjennerud, T; Stoltenberg, C; Tambs, K; Roysamb, E; Kringlen, E; Torgersen, S; Harris, J R

2002-08-01

Clinical and epidemiological studies have shown an association between anxiety and depression and pain in the back and neck. The nature of this relationship is not clear. This study aimed to investigate the extent to which common genetic and environmental aetiological factors contribute to the covariance between symptoms of anxiety and depression and back-neck pain. Measures of back-neck pain and symptoms of anxiety and depression were part of a self-report questionnaire sent in 1992 to twins born in Norway between 1967 and 1974 (3996 pairs). Structural equation modelling was applied to determine to what extent back-neck pain and symptoms of anxiety and depression share genetic and environmental liability factors. The phenotypic correlation between symptoms of anxiety and depression and back-neck pain was 0.31. Individual differences in both anxiety and depression and back-neck pain were best accounted for by additive genetic and individual environmental factors. Heritability estimates were 0.53 and 0.30 respectively. For back-neck pain, however, a model specifying only shared- and individual environmental effects could not be rejected. Bivariate analyses revealed that the correlation between back-neck pain and symptoms of anxiety and depression was best explained by additive genetic and individual environmental factors. Genetic factors affecting both phenotypes accounted for 60% of the covariation. There were no significant sex differences. The results support previous findings of a moderate association between back-neck pain and symptoms of anxiety and depression, and suggest that this association is primarily due to common genetic effects.

Genetic and Environmental Influences on Depressive Symptoms in Chinese Adolescents

PubMed Central

Chen, Jie; Li, Xinying; Natsuaki, Misaki N.; Leve, Leslie D.; Harold, Gordon T.

2016-01-01

Adolescent depression is common and has become a major public health concern in China, yet little research has examined the etiology of depression in Chinese adolescents. In the present study, genetic and environmental influences on Chinese adolescent depressive symptoms were investigated in 1181 twin pairs residing in Beijing, China (ages 11 to 19 years). Child- and parent-versions of the Children’s Depression Inventory (CDI) were used to measure adolescents’ depressive symptoms. For self-reports, genetic factors, shared environmental factors, and non-shared environmental factors accounted for 50%, 5%, and 45% of the variation in depressive symptoms, respectively; for parent-reports, genetic factors, shared environmental factors, and non-shared environmental factors accounted for 51%, 18%, and 31% of the variation, respectively. These estimates are generally consistent with previous findings in Western adolescents, supporting the cross-cultural generalizability of etiological model of adolescent depression. Neither qualitative nor quantitative sex differences were found in the etiological model. Future studies are needed to investigate how genes and environments work together (gene-environment interaction, gene-environment correlation) to influence depression in Chinese adolescents. PMID:24311200

Genetic and environmental influences on depressive symptoms in Chinese adolescents.

PubMed

Chen, Jie; Li, Xinying; Natsuaki, Misaki N; Leve, Leslie D; Harold, Gordon T

2014-01-01

Adolescent depression is common and has become a major public health concern in China, yet little research has examined the etiology of depression in Chinese adolescents. In the present study, genetic and environmental influences on Chinese adolescent depressive symptoms were investigated in 1,181 twin pairs residing in Beijing, China (ages 11-19 years). Child- and parent-versions of the children's depression inventory were used to measure adolescents' depressive symptoms. For self-reports, genetic factors, shared environmental factors, and non-shared environmental factors accounted for 50, 5, and 45 % of the variation in depressive symptoms, respectively; for parent-reports, genetic factors, shared environmental factors, and non-shared environmental factors accounted for 51, 18, and 31 % of the variation, respectively. These estimates are generally consistent with previous findings in Western adolescents, supporting the cross-cultural generalizability of etiological model of adolescent depression. Neither qualitative nor quantitative sex differences were found in the etiological model. Future studies are needed to investigate how genes and environments work together (gene-environment interaction, gene-environment correlation) to influence depression in Chinese adolescents.

Risk forewarning model for rice grain Cd pollution based on Bayes theory.

PubMed

Wu, Bo; Guo, Shuhai; Zhang, Lingyan; Li, Fengmei

2018-03-15

Cadmium (Cd) pollution of rice grain caused by Cd-contaminated soils is a common problem in southwest and central south China. In this study, utilizing the advantages of the Bayes classification statistical method, we established a risk forewarning model for rice grain Cd pollution, and put forward two parameters (the prior probability factor and data variability factor). The sensitivity analysis of the model parameters illustrated that sample size and standard deviation influenced the accuracy and applicable range of the model. The accuracy of the model was improved by the self-renewal of the model through adding the posterior data into the priori data. Furthermore, this method can be used to predict the risk probability of rice grain Cd pollution under similar soil environment, tillage and rice varietal conditions. The Bayes approach thus represents a feasible method for risk forewarning of heavy metals pollution of agricultural products caused by contaminated soils. Copyright © 2017 Elsevier B.V. All rights reserved.

A simple model of space radiation damage in GaAs solar cells

NASA Technical Reports Server (NTRS)

Wilson, J. W.; Stith, J. J.; Stock, L. V.

1983-01-01

A simple model is derived for the radiation damage of shallow junction gallium arsenide (GaAs) solar cells. Reasonable agreement is found between the model and specific experimental studies of radiation effects with electron and proton beams. In particular, the extreme sensitivity of the cell to protons stopping near the cell junction is predicted by the model. The equivalent fluence concept is of questionable validity for monoenergetic proton beams. Angular factors are quite important in establishing the cell sensitivity to incident particle types and energies. A fluence of isotropic incidence 1 MeV electrons (assuming infinite backing) is equivalent to four times the fluence of normal incidence 1 MeV electrons. Spectral factors common to the space radiations are considered, and cover glass thickness required to minimize the initial damage for a typical cell configuration is calculated. Rough equivalence between the geosynchronous environment and an equivalent 1 MeV electron fluence (normal incidence) is established.

Bifactor model of WISC-IV: Applicability and measurement invariance in low and normal IQ groups.

PubMed

Gomez, Rapson; Vance, Alasdair; Watson, Shaun

2017-07-01

This study examined the applicability and measurement invariance of the bifactor model of the 10 Wechsler Intelligence Scale for Children-Fourth Edition (WISC-IV) core subtests in groups of children and adolescents (age range from 6 to 16 years) with low (IQ ≤79; N = 229; % male = 75.9) and normal (IQ ≥80; N = 816; % male = 75.0) IQ scores. Results supported this model in both groups, and there was good support for measurement invariance for this model across these groups. For all participants together, the omega hierarchical and explained common variance (ECV) values were high for the general factor and low to negligible for the specific factors. Together, the findings favor the use of the Full Scale IQ (FSIQ) scores of the WISC-IV, but not the subscale index scores. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

Validity of the Eating Attitude Test among Exercisers.

PubMed

Lane, Helen J; Lane, Andrew M; Matheson, Hilary

2004-12-01

Theory testing and construct measurement are inextricably linked. To date, no published research has looked at the factorial validity of an existing eating attitude inventory for use with exercisers. The Eating Attitude Test (EAT) is a 26-item measure that yields a single index of disordered eating attitudes. The original factor analysis showed three interrelated factors: Dieting behavior (13-items), oral control (7-items), and bulimia nervosa-food preoccupation (6-items). The primary purpose of the study was to examine the factorial validity of the EAT among a sample of exercisers. The second purpose was to investigate relationships between eating attitudes scores and selected psychological constructs. In stage one, 598 regular exercisers completed the EAT. Confirmatory factor analysis (CFA) was used to test the single-factor, a three-factor model, and a four-factor model, which distinguished bulimia from food pre-occupation. CFA of the single-factor model (RCFI = 0.66, RMSEA = 0.10), the three-factor-model (RCFI = 0.74; RMSEA = 0.09) showed poor model fit. There was marginal fit for the 4-factor model (RCFI = 0.91, RMSEA = 0.06). Results indicated five-items showed poor factor loadings. After these 5-items were discarded, the three models were re-analyzed. CFA results indicated that the single-factor model (RCFI = 0.76, RMSEA = 0.10) and three-factor model (RCFI = 0.82, RMSEA = 0.08) showed poor fit. CFA results for the four-factor model showed acceptable fit indices (RCFI = 0.98, RMSEA = 0.06). Stage two explored relationships between EAT scores, mood, self-esteem, and motivational indices toward exercise in terms of self-determination, enjoyment and competence. Correlation results indicated that depressed mood scores positively correlated with bulimia and dieting scores. Further, dieting was inversely related with self-determination toward exercising. Collectively, findings suggest that a 21-item four-factor model shows promising validity coefficients among exercise participants, and that future research is needed to investigate eating attitudes among samples of exercisers. Key PointsValidity of psychometric measures should be thoroughly investigated. Researchers should not assume that a scale validation on one sample will show the same validity coefficients in a different population.The Eating Attitude Test is a commonly used scale. The present study shows a revised 21-item scale was suitable for exercisers.Researchers using the Eating Attitude Test should use subscales of Dieting, Oral control, Food pre-occupation, and Bulimia.Future research should involve qualitative techniques and interview exercise participants to explore the nature of eating attitudes.

The Dunedin Dementia Risk Awareness Project: a convenience sample of general practitioners.

PubMed

Barak, Yoram; Rapsey, Charlene; Fridman, Dana; Scott, Kate

2018-05-04

Recent recommendations of US and UK governmental and academic agencies suggest that up to 35% of dementia cases are preventable. We aimed to appraise general practitioners' (GPs) awareness of risk and protective factors associated with dementia and their intentions to act within the context of the Health Beliefs Model. We canvassed degree of dementia awareness, using the modified Lifestyle for Brain Health (LIBRA) scale among a convenience sample of local GPs. Thirty-five GPs, mean age 56.7 + 6.8 years (range: 43-72) participated. There were 19 women and 16 men, all New Zealand European. Genetics was the most commonly cited risk for dementia and exercise the most commonly cited protective factor. More than 80% of participants correctly identified 8/12 LIBRA factors. Factors not identified were: renal dysfunction, obesity, Mediterranean diet and high cognitive activity. The majority of participants felt they were at risk of suffering from dementia, that lifestyle changes will help reduce their risk and wished to start these changes soon. GPs are knowledgeable about dementia risk and protective factors. They reported optimism in their ability to modify their own risk factors through lifestyle interventions. This places GPs in a unique position to help disseminate this knowledge to their clients.

The five and seven factors personality models: differences and similitude between the TCI-R, NEO-FFI-R and ZKPQ-50-CC.

PubMed

Aluja, Anton; Blanch, Angel

2011-11-01

The present study tests the relationships between the three frequently used personality models evaluated by the Temperament Character Inventory-Revised (TCI-R), Neuroticism Extraversion Openness Five Factor Inventory - Revised (NEO-FFI-R) and Zuckerman-Kuhlman Personality Questionnaire-50- Cross-Cultural (ZKPQ-50-CC). The results were obtained with a sample of 928 volunteer subjects from the general population aged between 17 and 28 years old. Frequency distributions and alpha reliabilities with the three instruments were acceptable. Correlational and factorial analyses showed that several scales in the three instruments share an appreciable amount of common variance. Five factors emerged from principal components analysis. The first factor was integrated by A (Agreeableness), Co (Cooperativeness) and Agg-Host (Aggressiveness-Hostility), with secondary loadings in C (Conscientiousness) and SD (Self-directiveness) from other factors. The second factor was composed by N (Neuroticism), N-Anx (Neuroticism-Anxiety), HA (Harm Avoidance) and SD (Self-directiveness). The third factor was integrated by Sy (Sociability), E (Extraversion), RD (Reward Dependence), ImpSS (Impulsive Sensation Seeking) and NS (novelty Seeking). The fourth factor was integrated by Ps (Persistence), Act (Activity), and C, whereas the fifth and last factor was composed by O (Openness) and ST (Self- Transcendence). Confirmatory factor analyses indicate that the scales in each model are highly interrelated and define the specified latent dimension well. Similarities and differences between these three instruments are further discussed.

Co-occurrence of behavioral risk factors of common non-communicable diseases among urban slum dwellers in Nairobi, Kenya.

PubMed

Haregu, Tilahun Nigatu; Oti, Samuel; Egondi, Thaddaeus; Kyobutungi, Catherine

2015-01-01

The four common non-communicable diseases (NCDs) account for 80% of NCD-related deaths worldwide. The four NCDs share four common risk factors. As most of the existing evidence on the common NCD risk factors is based on analysis of a single factor at a time, there is a need to investigate the co-occurrence of the common NCD risk factors, particularly in an urban slum setting in sub-Saharan Africa. To determine the prevalence of co-occurrence of the four common NCDs risk factors among urban slum dwellers in Nairobi, Kenya. This analysis was based on the data collected as part of a cross-sectional survey to assess linkages among socio-economic status, perceived personal risk, and risk factors for cardiovascular and NCDs in a population of slum dwellers in Nairobi, Kenya, in 2008-2009. A total of 5,190 study subjects were included in the analysis. After selecting relevant variables for common NCD risk factors, we computed the prevalence of all possible combinations of the four common NCD risk factors. The analysis was disaggregated by relevant background variables. The weighted prevalences of unhealthy diet, insufficient physical activity, harmful use of alcohol, and tobacco use were found to be 57.2, 14.4, 10.1, and 12.4%, respectively. Nearly 72% of the study participants had at least one of the four NCD risk factors. About 52% of the study population had any one of the four NCD risk factors. About one-fifth (19.8%) had co-occurrence of NCD risk factors. Close to one in six individuals (17.6%) had two NCD risk factors, while only 2.2% had three or four NCD risk factors. One out of five of people in the urban slum settings of Nairobi had co-occurrence of NCD risk factors. Both comprehensive and differentiated approaches are needed for effective NCD prevention and control in these settings.

Exploratory factor analysis of the 12-item Functional Assessment of Chronic Illness Therapy-Spiritual Well-Being Scale in people newly diagnosed with advanced cancer.

PubMed

Bai, Mei; Dixon, Jane K

2014-01-01

The purpose of this study was to reexamine the factor pattern of the 12-item Functional Assessment of Chronic Illness Therapy-Spiritual Well-Being Scale (FACIT-Sp-12) using exploratory factor analysis in people newly diagnosed with advanced cancer. Principal components analysis (PCA) and 3 common factor analysis methods were used to explore the factor pattern of the FACIT-Sp-12. Factorial validity was assessed in association with quality of life (QOL). Principal factor analysis (PFA), iterative PFA, and maximum likelihood suggested retrieving 3 factors: Peace, Meaning, and Faith. Both Peace and Meaning positively related to QOL, whereas only Peace uniquely contributed to QOL. This study supported the 3-factor model of the FACIT-Sp-12. Suggestions for revision of items and further validation of the identified factor pattern were provided.

Intermolecular orbital interaction in π systems

NASA Astrophysics Data System (ADS)

Zhao, Rundong; Zhang, Rui-Qin

2018-04-01

Intermolecular interactions, in regard to which people tend to emphasise the noncovalent van der Waals (vdW) forces when conducting investigations throughout chemistry, can influence the structure, stability and function of molecules and materials. Despite the ubiquitous nature of vdW interactions, a simplified electrostatic model has been popularly adopted to explain common intermolecular interactions, especially those existing in π-involved systems. However, this classical model has come under fire in revealing specific issues such as substituent effects, due to its roughness; and it has been followed in past decades by sundry explanations which sometimes bring in nebulous descriptions. In this account, we try to summarise and present a unified model for describing and analysing the binding mechanism of such systems from the viewpoint of energy decomposition. We also emphasise a commonly ignored factor - orbital interaction, pointing out that the noncovalent intermolecular orbital interactions actually exhibit similar bonding and antibonding phenomena as those in covalent bonds.

Analysis of the influence of advanced materials for aerospace products R&D and manufacturing cost

NASA Astrophysics Data System (ADS)

Shen, A. W.; Guo, J. L.; Wang, Z. J.

2015-12-01

In this paper, we pointed out the deficiency of traditional cost estimation model about aerospace products Research & Development (R&D) and manufacturing based on analyzing the widely use of advanced materials in aviation products. Then we put up with the estimating formulas of cost factor, which representing the influences of advanced materials on the labor cost rate and manufacturing materials cost rate. The values ranges of the common advanced materials such as composite materials, titanium alloy are present in the labor and materials two aspects. Finally, we estimate the R&D and manufacturing cost of F/A-18, F/A- 22, B-1B and B-2 aircraft based on the common DAPCA IV model and the modified model proposed by this paper. The calculation results show that the calculation precision improved greatly by the proposed method which considering advanced materials. So we can know the proposed method is scientific and reasonable.

A multilevel model for comorbid outcomes: obesity and diabetes in the US.

PubMed

Congdon, Peter

2010-02-01

Multilevel models are overwhelmingly applied to single health outcomes, but when two or more health conditions are closely related, it is important that contextual variation in their joint prevalence (e.g., variations over different geographic settings) is considered. A multinomial multilevel logit regression approach for analysing joint prevalence is proposed here that includes subject level risk factors (e.g., age, race, education) while also taking account of geographic context. Data from a US population health survey (the 2007 Behavioral Risk Factor Surveillance System or BRFSS) are used to illustrate the method, with a six category multinomial outcome defined by diabetic status and weight category (obese, overweight, normal). The influence of geographic context is partly represented by known geographic variables (e.g., county poverty), and partly by a model for latent area influences. In particular, a shared latent variable (common factor) approach is proposed to measure the impact of unobserved area influences on joint weight and diabetes status, with the latent variable being spatially structured to reflect geographic clustering in risk.

Effect of Poisson's loss factor of rubbery material on underwater sound absorption of anechoic coatings

NASA Astrophysics Data System (ADS)

Zhong, Jie; Zhao, Honggang; Yang, Haibin; Yin, Jianfei; Wen, Jihong

2018-06-01

Rubbery coatings embedded with air cavities are commonly used on underwater structures to reduce reflection of incoming sound waves. In this paper, the relationships between Poisson's and modulus loss factors of rubbery materials are theoretically derived, the different effects of the tiny Poisson's loss factor on characterizing the loss factors of shear and longitudinal moduli are revealed. Given complex Young's modulus and dynamic Poisson's ratio, it is found that the shear loss factor has almost invisible variation with the Poisson's loss factor and is very close to the loss factor of Young's modulus, while the longitudinal loss factor almost linearly decreases with the increase of Poisson's loss factor. Then, a finite element (FE) model is used to investigate the effect of the tiny Poisson's loss factor, which is generally neglected in some FE models, on the underwater sound absorption of rubbery coatings. Results show that the tiny Poisson's loss factor has a significant effect on the sound absorption of homogeneous coatings within the concerned frequency range, while it has both frequency- and structure-dependent influence on the sound absorption of inhomogeneous coatings with embedded air cavities. Given the material parameters and cavity dimensions, more obvious effect can be observed for the rubbery coating with a larger lattice constant and/or a thicker cover layer.

A Study to Identify Those Variables Which Contribute to the Utilization of Wellness Clinic Services by Active Duty Army Family Members

DTIC Science & Technology

1985-07-01

utilization of organizational assets. The marketing mix model consisting of the four key vari- ables of price, promotion, product, and place, is commonly...minimal marketing efforts may bring significant increases in useage. The author included some specific recommendations for marketing the Wellness Clinic. 12...care This five factor model indicates that the two major approa- ches to analyzing preventive health care consumer decisionmaking, marketing and health

Compressional and shear-wave velocity versus depth relations for common rock types in northern California

USGS Publications Warehouse

Brocher, T.M.

2008-01-01

This article presents new empirical compressional and shear-wave velocity (Vp and Vs) versus depth relationships for the most common rock types in northern California. Vp versus depth relations were developed from borehole, laboratory, seismic refraction and tomography, and density measurements, and were converted to Vs versus depth relations using new empirical relations between Vp and Vs. The relations proposed here account for increasing overburden pressure but not for variations in other factors that can influence velocity over short distance scales, such as lithology, consolidation, induration, porosity, and stratigraphic age. Standard deviations of the misfits predicted by these relations thus provide a measure of the importance of the variability in Vp and Vs caused by these other factors. Because gabbros, greenstones, basalts, and other mafic rocks have a different Vp and Vs relationship than sedimentary and granitic rocks, the differences in Vs between these rock types at depths below 6 or 7 km are generally small. The new relations were used to derive the 2005 U.S. Geological Survey seismic velocity model for northern California employed in the broadband strong motion simulations of the 1989 Loma Prieta and 1906 San Francisco earthquakes; initial tests of the model indicate that the Vp model generally compares favorably to regional seismic tomography models but that the Vp and Vs values proposed for the Franciscan Complex may be about 5% too high.

Maternal pre-pregnancy weight and externalising behaviour problems in preschool children: a UK-based twin study.

PubMed

Antoniou, Evangelia E; Fowler, Tom; Reed, Keith; Southwood, Taunton R; McCleery, Joseph P; Zeegers, Maurice P

2014-10-14

To estimate the heritability of child behaviour problems and investigate the association between maternal pre-pregnancy overweight and child behaviour problems in a genetically sensitive design. Observational cross-sectional study. The Twins and Multiple Births Association Heritability Study (TAMBAHS) is an online UK-wide volunteer-based study investigating the development of twins from birth until 5 years of age. A total of 443 (16% of the initial registered members) mothers answered questions on pre-pregnancy weight and their twins' internalising and externalising problems using the Child Behavior Checklist and correcting for important covariates including gestational age, twins' birth weight, age and sex, mother's educational level and smoking (before, during and after pregnancy). The heritability of behaviour problems and their association with maternal pre-pregnancy weight. The genetic analysis suggested that genetic and common environmental factors account for most of the variation in externalising disorders (an ACE model was the most parsimonious with genetic factors (A) explaining 46% (95% CI 33% to 60%) of the variance, common environment (C) explaining 42% (95% CI 27% to 54%) and non-shared environmental factors (E) explaining 13% (95% CI 10% to 16%) of the variance. For internalising problems, a CE model was the most parsimonious model with the common environment explaining 51% (95% CI 44% to 58%) of the variance and non-shared environment explaining 49% (95% CI 42% to 56%) of the variance. Moreover, the regression analysis results suggested that children of overweight mothers showed a trend (OR=1.10, 95% CI 0.58% to 2.06) towards being more aggressive and exhibit externalising behaviours compared to children of normal weight mothers. Maternal pre-pregnancy weight may play a role in children's aggressive behaviour. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.

Testing Group Mean Differences of Latent Variables in Multilevel Data Using Multiple-Group Multilevel CFA and Multilevel MIMIC Modeling.

PubMed

Kim, Eun Sook; Cao, Chunhua

2015-01-01

Considering that group comparisons are common in social science, we examined two latent group mean testing methods when groups of interest were either at the between or within level of multilevel data: multiple-group multilevel confirmatory factor analysis (MG ML CFA) and multilevel multiple-indicators multiple-causes modeling (ML MIMIC). The performance of these methods were investigated through three Monte Carlo studies. In Studies 1 and 2, either factor variances or residual variances were manipulated to be heterogeneous between groups. In Study 3, which focused on within-level multiple-group analysis, six different model specifications were considered depending on how to model the intra-class group correlation (i.e., correlation between random effect factors for groups within cluster). The results of simulations generally supported the adequacy of MG ML CFA and ML MIMIC for multiple-group analysis with multilevel data. The two methods did not show any notable difference in the latent group mean testing across three studies. Finally, a demonstration with real data and guidelines in selecting an appropriate approach to multilevel multiple-group analysis are provided.

Risk Estimation Modeling and Feasibility Testing for a Mobile eHealth Intervention for Binge Drinking Among Young People: The D-ARIANNA (Digital-Alcohol RIsk Alertness Notifying Network for Adolescents and young adults) Project.

PubMed

Carrà, Giuseppe; Crocamo, Cristina; Schivalocchi, Alessandro; Bartoli, Francesco; Carretta, Daniele; Brambilla, Giulia; Clerici, Massimo

2015-01-01

Binge drinking is common among young people but often relevant risk factors are not recognized. eHealth apps, attractive for young people, may be useful to enhance awareness of this problem. We aimed at developing a current risk estimation model for binge drinking, incorporated into an eHealth app--D-ARIANNA (Digital-Alcohol RIsk Alertness Notifying Network for Adolescents and young adults)--for young people. A longitudinal approach with phase 1 (risk estimation), phase 2 (design), and phase 3 (feasibility) was followed. Risk/protective factors identified from the literature were used to develop a current risk estimation model for binge drinking. Relevant odds ratios were subsequently pooled through meta-analytic techniques with a random-effects model, deriving weighted estimates to be introduced in a final model. A set of questions, matching identified risk factors, were nested in a questionnaire and assessed for wording, content, and acceptability in focus groups involving 110 adolescents and young adults. Ten risk factors (5 modifiable) and 2 protective factors showed significant associations with binge drinking and were included in the model. Their weighted coefficients ranged between -0.71 (school proficiency) and 1.90 (cannabis use). The model, nested in an eHealth app questionnaire, provides in percent an overall current risk score, accompanied by appropriate images. Factors that mostly contribute are shown in summary messages. Minor changes have been realized after focus groups review. Most of the subjects (74%) regarded the eHealth app as helpful to assess binge drinking risk. We could produce an evidence-based eHealth app for young people, evaluating current risk for binge drinking. Its effectiveness will be tested in a large trial.

[Precipitating factors in patients with repetitive exacerbation of chronic left heart failure].

PubMed

Sasaki, T; Yanagitani, Y; Kubo, T; Matsuo, H; Miyatake, K

1998-04-01

The precipitating factors of repetitive exacerbation were investigated in 110 consecutive patients with chronic left heart failure admitted due to acute exacerbation more than twice to the medical emergency ward of National Cardiovascular Center from January, 1992 to December, 1996. The controls were 189 consecutive patients with chronic left heart failure admitted to the ward due to acute exacerbation only once during the same period. Excessive intake of water or sodium, overwork and infection were common precipitating factors in the first decompensation of left heart failure, but the former two factors became less common with repeated admission. Patient mistakes such as excessive intake of water or sodium, overwork and noncompliance with medications, and new onset arrhythmias were common precipitating factors in patients (n = 13) admitted to the ward more than four times. Infection was a common precipitating factor (63%) in patients with a time interval between readmission and the last discharge of longer than 2 years. Despite repeated admission, infection was a common precipitating factor in patients with valvular heart disease (n = 31), patient mistakes were common in heart disease with left ventricular hypertrophy (n = 20), and infection and new onset arrhythmias were common in dilated cardiomyopathy (n = 28) and old myocardial infarction (n = 31). Patient mistakes and new onset arrhythmias were the common factors that led to repetitive exacerbation of left heart failure, and precipitating factors were characterized by the etiology of left heart failure.

Factors Determining Success in Youth Judokas

PubMed Central

Krstulović, Saša; Caput, Petra Đapić

2017-01-01

Abstract The aim of this study was to compare two models of determining factors for success in judo. The first model (Model A) included testing motor abilities of high-level Croatian judokas in the cadet age category. The sample in Model A consisted of 71 male and female judokas aged 16 ± 0.6 years who were divided into four subsamples according to sex and weight category. The second model (Model B) consisted of interviewing 40 top-level judo experts on the importance of motor abilities for cadets’ success in judo. According to Model A, the greatest impact on the criterion variable of success in males and females of heavier weight categories were variables assessing maximum strength, coordination and jumping ability. In the lighter weight male categories, the highest correlation with the criterion variable of success was the variable assessing agility. However, in the lighter weight female categories, the greatest impact on success had the variable assessing muscular endurance. In Model B, specific endurance was crucial for success in judo, while flexibility was the least important, regardless of sex and weight category. Spearman’s rank correlation coefficients showed that there were no significant correlations in the results obtained in Models A and B for all observed subsamples. Although no significant correlations between the factors for success obtained through Models A and B were found, common determinants of success, regardless of the applied model, were identified. PMID:28469759

Comparison of Survival Models for Analyzing Prognostic Factors in Gastric Cancer Patients

PubMed

Habibi, Danial; Rafiei, Mohammad; Chehrei, Ali; Shayan, Zahra; Tafaqodi, Soheil

2018-03-27

Objective: There are a number of models for determining risk factors for survival of patients with gastric cancer. This study was conducted to select the model showing the best fit with available data. Methods: Cox regression and parametric models (Exponential, Weibull, Gompertz, Log normal, Log logistic and Generalized Gamma) were utilized in unadjusted and adjusted forms to detect factors influencing mortality of patients. Comparisons were made with Akaike Information Criterion (AIC) by using STATA 13 and R 3.1.3 softwares. Results: The results of this study indicated that all parametric models outperform the Cox regression model. The Log normal, Log logistic and Generalized Gamma provided the best performance in terms of AIC values (179.2, 179.4 and 181.1, respectively). On unadjusted analysis, the results of the Cox regression and parametric models indicated stage, grade, largest diameter of metastatic nest, largest diameter of LM, number of involved lymph nodes and the largest ratio of metastatic nests to lymph nodes, to be variables influencing the survival of patients with gastric cancer. On adjusted analysis, according to the best model (log normal), grade was found as the significant variable. Conclusion: The results suggested that all parametric models outperform the Cox model. The log normal model provides the best fit and is a good substitute for Cox regression. Creative Commons Attribution License

An Integrated and Interdisciplinary Model for Predicting the Risk of Injury and Death in Future Earthquakes.

PubMed

Shapira, Stav; Novack, Lena; Bar-Dayan, Yaron; Aharonson-Daniel, Limor

2016-01-01

A comprehensive technique for earthquake-related casualty estimation remains an unmet challenge. This study aims to integrate risk factors related to characteristics of the exposed population and to the built environment in order to improve communities' preparedness and response capabilities and to mitigate future consequences. An innovative model was formulated based on a widely used loss estimation model (HAZUS) by integrating four human-related risk factors (age, gender, physical disability and socioeconomic status) that were identified through a systematic review and meta-analysis of epidemiological data. The common effect measures of these factors were calculated and entered to the existing model's algorithm using logistic regression equations. Sensitivity analysis was performed by conducting a casualty estimation simulation in a high-vulnerability risk area in Israel. the integrated model outcomes indicated an increase in the total number of casualties compared with the prediction of the traditional model; with regard to specific injury levels an increase was demonstrated in the number of expected fatalities and in the severely and moderately injured, and a decrease was noted in the lightly injured. Urban areas with higher populations at risk rates were found more vulnerable in this regard. The proposed model offers a novel approach that allows quantification of the combined impact of human-related and structural factors on the results of earthquake casualty modelling. Investing efforts in reducing human vulnerability and increasing resilience prior to an occurrence of an earthquake could lead to a possible decrease in the expected number of casualties.

Association of socio-economic, gender and health factors with common mental disorders in women: a population-based study of 5703 married rural women in India.

PubMed

Shidhaye, Rahul; Patel, Vikram

2010-12-01

There are few population-based studies from low- and middle-income countries that have described the association of socio-economic, gender and health factors with common mental disorders (CMDs) in rural women. Population-based study of currently married rural women in the age group of 15-39 years. The baseline data are from the National Family Health Survey-II conducted in 1998. A follow-up study was conducted 4 years later in 2002-03. The outcome of CMD was assessed using the 12-item General Health Questionnaire (GHQ-12). Due to the hierarchical nature and complex survey design, data were analysed using mixed-effect logistic regression with random intercept model. A total of 5703 women (representing 83.5% of eligible women) completed follow-up. The outcome of CMD was observed in 609 women (10.7%, 95% confidence interval 9.8-11.6). The following factors were independently associated with the outcome of CMD in the final multivariable model: higher age, low education, low standard of living, recent intimate partner violence (IPV), husband's unsatisfactory reaction to dowry, husband's alcohol use and women's own tobacco use. Socio-economic and gender disadvantage factors are independently associated with CMDs in this population of women. Strategies that address structural determinants, for example to promote women's education and reduce their exposure to IPV, may reduce the burden of CMDs in women.

Musculoskeletal complaints, anxiety-depression symptoms, and neuroticism: A study of middle-aged twins.

PubMed

Vassend, Olav; Røysamb, Espen; Nielsen, Christopher Sivert; Czajkowski, Nikolai Olavi

2017-08-01

Musculoskeletal (MS) complaints are reported commonly, but the extent to which such complaints reflect the severity of site-specific pathology or a more generalized susceptibility to feel pain/discomfort is uncertain. Both site-specific and more widespread MS conditions have been shown to be linked to anxiety and depression, but the nature of this relationship is poorly understood. In the present study the role of neuroticism as a shared risk factor that may possibly explain the co-occurrence between anxiety-depression and MS complaints was investigated. The sample consisted of 746 monozygotic and 770 dizygotic twins in the age group of 50-65 years (M = 57.11, SD = 4.5). Using Cholesky modeling, genetic and environmental influences on neuroticism, anxiety-depression and MS symptoms, and the associations among these phenotypes were determined. A single factor accounted for about 50% of the overall variance in MS symptom reporting. The best-fitting biometric model included sex-specific additive genetic and individual-specific environmental effects. All 3 phenotypes were strongly influenced by genetic factors, heritability (h2) = 0.41-0.56. Furthermore, while there was a considerable overlap in genetic risk factors among the 3 phenotypes, a substantial proportion of the genetic risk shared between MS complaints and anxiety-depression was independent of neuroticism. Evidence for a common underlying susceptibility to report MS symptoms, genetically linked to both neuroticism and anxiety-depression symptoms, was found. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

Scan Order in Gibbs Sampling: Models in Which it Matters and Bounds on How Much.

PubMed

He, Bryan; De Sa, Christopher; Mitliagkas, Ioannis; Ré, Christopher

2016-01-01

Gibbs sampling is a Markov Chain Monte Carlo sampling technique that iteratively samples variables from their conditional distributions. There are two common scan orders for the variables: random scan and systematic scan. Due to the benefits of locality in hardware, systematic scan is commonly used, even though most statistical guarantees are only for random scan. While it has been conjectured that the mixing times of random scan and systematic scan do not differ by more than a logarithmic factor, we show by counterexample that this is not the case, and we prove that that the mixing times do not differ by more than a polynomial factor under mild conditions. To prove these relative bounds, we introduce a method of augmenting the state space to study systematic scan using conductance.

Scan Order in Gibbs Sampling: Models in Which it Matters and Bounds on How Much

PubMed Central

He, Bryan; De Sa, Christopher; Mitliagkas, Ioannis; Ré, Christopher

2016-01-01

Gibbs sampling is a Markov Chain Monte Carlo sampling technique that iteratively samples variables from their conditional distributions. There are two common scan orders for the variables: random scan and systematic scan. Due to the benefits of locality in hardware, systematic scan is commonly used, even though most statistical guarantees are only for random scan. While it has been conjectured that the mixing times of random scan and systematic scan do not differ by more than a logarithmic factor, we show by counterexample that this is not the case, and we prove that that the mixing times do not differ by more than a polynomial factor under mild conditions. To prove these relative bounds, we introduce a method of augmenting the state space to study systematic scan using conductance. PMID:28344429

Prevalence of Common Mental Disorders and Associated Factors among People with Glaucoma Attending Outpatient Clinic at Menelik II Referral Hospital, Addis Ababa, Ethiopia

PubMed Central

Bedasso, Kufa; Feyera, Fetuma; Gebeyehu, Abebaw; Yohannis, Zegeye

2016-01-01

Background The burden of blindness from glaucoma is high. Therefore, people suffering from a serious eye disease such as glaucoma, which can lead to blindness, usually have an emotional disturbance on the patient. Untreated psychiatric illness is associated with increased morbidity and increased costs of care. Objective This study aimed to assess prevalence of common mental disorders and associated factors among people with Glaucoma attending Menelik II referral hospital, Addis Ababa, Ethiopia, 2014. Methods Institution based Cross-sectional study design was conducted in the Department of Ophthalmology Menelik II Referral Hospital from April 10 to May 15, 2014. 423 participants who had undergone through investigation, examination and diagnosed as patients of glaucoma were selected randomly from the glaucoma clinic. Data were collected through face to face interview using Self Reporting Questionnaire consisted of 20 items. Study subjects who scored ≥11 from SRQ-20 were considered as having common mental disorders. Bivariate and multivariable logistic regression analysis with 95% CI were done and variables with P<0.05 in the final model were identified as independent factors associated with common mental disorders. Results Four hundred five patients with glaucoma were included in our study with response rate of 95.7% and 64.5% were males. The average age was 59±13.37 years. Common mental disorders were observed in 23.2% of Glaucoma patients. It is quite obvious that levels of CMDs were high among patients with glaucoma. There was a significant association between age, sex, chronic physical illness, income and duration of illness at P < 0.05. Conclusion and Recommendation Symptoms of common mental disorders were the commonest comorbidities among patients with glaucoma. It will be better to assess and treat Common mental disorders as a separate illness in patients with glaucoma. PMID:27584147

Learn good from bad: Effects of good and bad neighbors in spatial prisoners' dilemma games

NASA Astrophysics Data System (ADS)

Lu, Peng

2015-10-01

Cooperation is vital for the human society and this study focuses on how to promote cooperation. In our stratification model, there exist three classes: two minorities are elites who are prone to cooperate and scoundrels who are born to defect; one majority is the class of common people. Agents of these three classes interact with each other on a square lattice. Commons' cooperation and its factors are investigated. Contradicting our common sense, it indicates that elites play a negative role while scoundrels play a positive one in promoting commons' cooperation. Besides, effects of good and bad neighbors vary with temptation. When the temptation is smaller the positive effect is able to overcome the negative effect, but the later prevails when the temptation is larger. It concludes that common people are more prone to cooperate in harsh environment with bad neighbors, and a better environment with good neighbors merely leads to laziness and free riding of commons.

Communication: Is a coarse-grained model for water sufficient to compute Kapitza conductance on non-polar surfaces?

PubMed

Ardham, Vikram Reddy; Leroy, Frédéric

2017-10-21

Coarse-grained models have increasingly been used in large-scale particle-based simulations. However, due to their lack of degrees of freedom, it is a priori unlikely that they straightforwardly represent thermal properties with the same accuracy as their atomistic counterparts. We take a first step in addressing the impact of liquid coarse-graining on interfacial heat conduction by showing that an atomistic and a coarse-grained model of water may yield similar values of the Kapitza conductance on few-layer graphene with interactions ranging from hydrophobic to mildly hydrophilic. By design the water models employed yield similar liquid layer structures on the graphene surfaces. Moreover, they share common vibration properties close to the surfaces and thus couple with the vibrations of graphene in a similar way. These common properties explain why they yield similar Kapitza conductance values despite their bulk thermal conductivity differing by more than a factor of two.

Moving across scales: Challenges and opportunities in upscaling carbon fluxes

NASA Astrophysics Data System (ADS)

Naithani, K. J.

2016-12-01

Light use efficiency (LUE) type models are commonly used to upscale terrestrial C fluxes and estimate regional and global C budgets. Model parameters are often estimated for each land cover type (LCT) using flux observations from one or more eddy covariance towers, and then spatially extrapolated by integrating land cover, meteorological, and remotely sensed data. Decisions regarding the type of input data (spatial resolution of land cover data, spatial and temporal length of flux data), representation of landscape structure (land use vs. disturbance regime), and the type of modeling framework (common risk vs. hierarchical) all influence the estimates CO2 fluxes and the associated uncertainties, but are rarely considered together. This work presents a synthesis of past and present efforts for upscaling CO2 fluxes and associated uncertainties in the ChEAS (Chequamegon Ecosystem Atmosphere Study) region in northern Wisconsin and the Upper Peninsula of Michigan. This work highlights two key future research needs. First, the characterization of uncertainties due to all of the abovementioned factors reflects only a (hopefully relevant) subset the overall uncertainties. Second, interactions among these factors are likely critical, but are poorly represented by the tower network at landscape scales. Yet, results indicate significant spatial and temporal heterogeneity of uncertainty in CO2 fluxes which can inform carbon management efforts and prioritize data needs.

Mathematical modeling of atopic dermatitis reveals "double-switch" mechanisms underlying 4 common disease phenotypes.

PubMed

Domínguez-Hüttinger, Elisa; Christodoulides, Panayiotis; Miyauchi, Kosuke; Irvine, Alan D; Okada-Hatakeyama, Mariko; Kubo, Masato; Tanaka, Reiko J

2017-06-01

The skin barrier acts as the first line of defense against constant exposure to biological, microbial, physical, and chemical environmental stressors. Dynamic interplay between defects in the skin barrier, dysfunctional immune responses, and environmental stressors are major factors in the development of atopic dermatitis (AD). A systems biology modeling approach can yield significant insights into these complex and dynamic processes through integration of prior biological data. We sought to develop a multiscale mathematical model of AD pathogenesis that describes the dynamic interplay between the skin barrier, environmental stress, and immune dysregulation and use it to achieve a coherent mechanistic understanding of the onset, progression, and prevention of AD. We mathematically investigated synergistic effects of known genetic and environmental risk factors on the dynamic onset and progression of the AD phenotype, from a mostly asymptomatic mild phenotype to a severe treatment-resistant form. Our model analysis identified a "double switch," with 2 concatenated bistable switches, as a key network motif that dictates AD pathogenesis: the first switch is responsible for the reversible onset of inflammation, and the second switch is triggered by long-lasting or frequent activation of the first switch, causing irreversible onset of systemic T H 2 sensitization and worsening of AD symptoms. Our mathematical analysis of the bistable switch predicts that genetic risk factors decrease the threshold of environmental stressors to trigger systemic T H 2 sensitization. This analysis predicts and explains 4 common clinical AD phenotypes from a mild and reversible phenotype through to severe and recalcitrant disease and provides a mechanistic explanation for clinically demonstrated preventive effects of emollient treatments against development of AD. Copyright © 2016 The Authors. Published by Elsevier Inc. All rights reserved.

A Gaussian random field model for similarity-based smoothing in Bayesian disease mapping.

PubMed

Baptista, Helena; Mendes, Jorge M; MacNab, Ying C; Xavier, Miguel; Caldas-de-Almeida, José

2016-08-01

Conditionally specified Gaussian Markov random field (GMRF) models with adjacency-based neighbourhood weight matrix, commonly known as neighbourhood-based GMRF models, have been the mainstream approach to spatial smoothing in Bayesian disease mapping. In the present paper, we propose a conditionally specified Gaussian random field (GRF) model with a similarity-based non-spatial weight matrix to facilitate non-spatial smoothing in Bayesian disease mapping. The model, named similarity-based GRF, is motivated for modelling disease mapping data in situations where the underlying small area relative risks and the associated determinant factors do not vary systematically in space, and the similarity is defined by "similarity" with respect to the associated disease determinant factors. The neighbourhood-based GMRF and the similarity-based GRF are compared and accessed via a simulation study and by two case studies, using new data on alcohol abuse in Portugal collected by the World Mental Health Survey Initiative and the well-known lip cancer data in Scotland. In the presence of disease data with no evidence of positive spatial correlation, the simulation study showed a consistent gain in efficiency from the similarity-based GRF, compared with the adjacency-based GMRF with the determinant risk factors as covariate. This new approach broadens the scope of the existing conditional autocorrelation models. © The Author(s) 2016.

The genetic and environmental etiology of antisocial behavior from childhood to emerging adulthood.

PubMed

Tuvblad, Catherine; Narusyte, Jurgita; Grann, Martin; Sarnecki, Jerzy; Lichtenstein, Paul

2011-09-01

Previous research suggests that both genetic and environmental influences are important for antisocial behavior across the life span, even though the prevalence and incidence of antisocial behavior varies considerably across ages. However, little is known of how genetic and environmental effects influence the development of antisocial behavior. A total of 2,600 male and female twins from the population-based Swedish Twin Registry were included in the present study. Antisocial behavior was measured on four occasions, when twins were 8-9, 13-14, 16-17, and 19-20 years old. Longitudinal analyses of the data were conducted using structural equation modeling. The stability of antisocial behavior over time was explained by a common latent persistent antisocial behavior factor. A common genetic influence accounted for 67% of the total variance in this latent factor, the shared environment explained 26%, and the remaining 7% was due to the non-shared environment. Significant age-specific shared environmental factors were found at ages 13-14 years, suggesting that common experiences (e.g., peers) are important for antisocial behavior at this age. Results from this study show that genetic as well as shared environmental influences are important in antisocial behavior that persists from childhood to emerging adulthood.

Dynamic factor analysis for estimating ground water arsenic trends.

PubMed

Kuo, Yi-Ming; Chang, Fi-John

2010-01-01

Drinking ground water containing high arsenic (As) concentrations has been associated with blackfoot disease and the occurrence of cancer along the southwestern coast of Taiwan. As a result, 28 ground water observation wells were installed to monitor the ground water quality in this area. Dynamic factor analysis (DFA) is used to identify common trends that represent unexplained variability in ground water As concentrations of decommissioned wells and to investigate whether explanatory variables (total organic carbon [TOC], As, alkalinity, ground water elevation, and rainfall) affect the temporal variation in ground water As concentration. The results of the DFA show that rainfall dilutes As concentration in areas under aquacultural and agricultural use. Different combinations of geochemical variables (As, alkalinity, and TOC) of nearby monitoring wells affected the As concentrations of the most decommissioned wells. Model performance was acceptable for 11 wells (coefficient of efficiency >0.50), which represents 52% (11/21) of the decommissioned wells. Based on DFA results, we infer that surface water recharge may be effective for diluting the As concentration, especially in the areas that are relatively far from the coastline. We demonstrate that DFA can effectively identify the important factors and common effects representing unexplained variability common to decommissioned wells on As variation in ground water and extrapolate information from existing monitoring wells to the nearby decommissioned wells.

Associations between motor timing, music practice, and intelligence studied in a large sample of twins.

PubMed

Ullén, Fredrik; Mosing, Miriam A; Madison, Guy

2015-03-01

Music performance depends critically on precise processing of time. A common model behavior in studies of motor timing is isochronous serial interval production (ISIP), that is, hand/finger movements with a regular beat. ISIP accuracy is related to both music practice and intelligence. Here we present a study of these associations in a large twin cohort, demonstrating that the effects of music practice and intelligence on motor timing are additive, with no significant multiplicative (interaction) effect. Furthermore, the association between music practice and motor timing was analyzed with the use of a co-twin control design using intrapair differences. These analyses revealed that the phenotypic association disappeared when all genetic and common environmental factors were controlled. This suggests that the observed association may not reflect a causal effect of music practice on ISIP performance but rather reflect common influences (e.g., genetic effects) on both outcomes. The relevance of these findings for models of practice and expert performance is discussed. © 2014 New York Academy of Sciences.

Neuroinflammatory Mechanisms of Connective Tissue Fibrosis: Targeting Neurogenic and Mast Cell Contributions

PubMed Central

Monument, Michael J.; Hart, David A.; Salo, Paul T.; Befus, A. Dean; Hildebrand, Kevin A.

2015-01-01

Significance: The pathogenesis of fibrogenic wound and connective tissue healing is complex and incompletely understood. Common observations across a vast array of human and animal models of fibroproliferative conditions suggest neuroinflammatory mechanisms are important upstream fibrogenic events. Recent Advances: As detailed in this review, mast cell hyperplasia is a common observation in fibrotic tissue. Recent investigations in human and preclinical models of hypertrophic wound healing and post-traumatic joint fibrosis provides evidence that fibrogenesis is governed by a maladaptive neuropeptide-mast cell-myofibroblast signaling pathway. Critical Issues: The blockade and manipulation of these factors is providing promising evidence that if timed correctly, the fibrogenic process can be appropriately regulated. Clinically, abnormal fibrogenic healing responses are not ubiquitous to all patients and the identification of those at-risk remains an area of priority. Future Directions: Ultimately, an integrated appreciation of the common pathobiology shared by many fibrogenic connective tissue conditions may provide a scientific framework to facilitate the development of novel antifibrotic prevention and treatment strategies. PMID:25785237

Medical teams and the standard of care in negligence.

PubMed

Sappideen, Carolyn

2015-09-01

Medical teams are essential to the delivery of modern, patient-centred health care in hospitals. A collective model of responsibility envisaged by team care is inconsistent with common law tort liability which focuses on the individual rather than the team. There is no basis upon which a team can be liable as a collective at common law. Nor does the common law'countenance liability for the conduct of other team members absent some form of agency, vicarious liability or non-delegable duty. Despite the barriers to the adoption of a team standard of care in negligence, there is scope for team factors to have a role in determining the standard of care so that being a team player is part and parcel of what it is to be a competent professional. If this is the case, the skill set, and the standard of care expected of the individual professional, includes skills based on team models of communication, cross-monitoring and trust.

Modelling the pre-assessment learning effects of assessment: evidence in the validity chain

PubMed Central

Cilliers, Francois J; Schuwirth, Lambert W T; van der Vleuten, Cees P M

2012-01-01

OBJECTIVES We previously developed a model of the pre-assessment learning effects of consequential assessment and started to validate it. The model comprises assessment factors, mechanism factors and learning effects. The purpose of this study was to continue the validation process. For stringency, we focused on a subset of assessment factor–learning effect associations that featured least commonly in a baseline qualitative study. Our aims were to determine whether these uncommon associations were operational in a broader but similar population to that in which the model was initially derived. METHODS A cross-sectional survey of 361 senior medical students at one medical school was undertaken using a purpose-made questionnaire based on a grounded theory and comprising pairs of written situational tests. In each pair, the manifestation of an assessment factor was varied. The frequencies at which learning effects were selected were compared for each item pair, using an adjusted alpha to assign significance. The frequencies at which mechanism factors were selected were calculated. RESULTS There were significant differences in the learning effect selected between the two scenarios of an item pair for 13 of this subset of 21 uncommon associations, even when a p-value of < 0.00625 was considered to indicate significance. Three mechanism factors were operational in most scenarios: agency; response efficacy, and response value. CONCLUSIONS For a subset of uncommon associations in the model, the role of most assessment factor–learning effect associations and the mechanism factors involved were supported in a broader but similar population to that in which the model was derived. Although model validation is an ongoing process, these results move the model one step closer to the stage of usefully informing interventions. Results illustrate how factors not typically included in studies of the learning effects of assessment could confound the results of interventions aimed at using assessment to influence learning. Discuss ideas arising from this article at ‘http://www.mededuc.com discuss’ PMID:23078685

Factor analysis of submicron particle size distributions near a major United States-Canada trade bridge.

PubMed

Ogulei, David; Hopke, Philip K; Ferro, Andrea R; Jaques, Peter A

2007-02-01

A factor analytic model has been applied to resolve and apportion particles based on submicron particle size distributions downwind of a United States-Canada bridge in Buffalo, NY. The sites chosen for this study were located at gradually increasing distances downwind of the bridge complex. Seven independent factors were resolved, including four factors that were common to all of the five sites considered. The common factors were generally characterized by the existence of two or more number and surface area modes. The seven factors resolved were identified as follows: fresh tail-pipe diesel exhaust, local/street diesel traffic, aged/evolved diesel particles, spark-ignition gasoline emissions, background urban emissions, heavy-duty diesel agglomerates, and secondary/transported material. Submicron (<0.5 microm) and ultrafine (<0.1 microm) particle emissions downwind of the bridge were dominated by commercial diesel truck emissions. Thus, this study obtained size distinction between fresh versus aged vehicle exhaust and spark-ignition versus diesel emissions based on the measured high time-resolution particle number concentrations. Because this study mainly used particles <300 nm in diameter, some sources that would usually exhibit number modes >100 nm were not resolved. Also, the resolved profiles suggested that the major number mode for fresh tailpipe diesel exhaust might exist below the detection limit of the spectrometer used. The average particle number contributions from the resolved factors were highest closest to the bridge.

Evolving hard problems: Generating human genetics datasets with a complex etiology.

PubMed

Himmelstein, Daniel S; Greene, Casey S; Moore, Jason H

2011-07-07

A goal of human genetics is to discover genetic factors that influence individuals' susceptibility to common diseases. Most common diseases are thought to result from the joint failure of two or more interacting components instead of single component failures. This greatly complicates both the task of selecting informative genetic variants and the task of modeling interactions between them. We and others have previously developed algorithms to detect and model the relationships between these genetic factors and disease. Previously these methods have been evaluated with datasets simulated according to pre-defined genetic models. Here we develop and evaluate a model free evolution strategy to generate datasets which display a complex relationship between individual genotype and disease susceptibility. We show that this model free approach is capable of generating a diverse array of datasets with distinct gene-disease relationships for an arbitrary interaction order and sample size. We specifically generate eight-hundred Pareto fronts; one for each independent run of our algorithm. In each run the predictiveness of single genetic variation and pairs of genetic variants have been minimized, while the predictiveness of third, fourth, or fifth-order combinations is maximized. Two hundred runs of the algorithm are further dedicated to creating datasets with predictive four or five order interactions and minimized lower-level effects. This method and the resulting datasets will allow the capabilities of novel methods to be tested without pre-specified genetic models. This allows researchers to evaluate which methods will succeed on human genetics problems where the model is not known in advance. We further make freely available to the community the entire Pareto-optimal front of datasets from each run so that novel methods may be rigorously evaluated. These 76,600 datasets are available from http://discovery.dartmouth.edu/model_free_data/.

Dynamic factor analysis of long-term growth trends of the intertidal seagrass Thalassia hemprichii in southern Taiwan

NASA Astrophysics Data System (ADS)

Kuo, Yi-Ming; Lin, Hsing-Juh

2010-01-01

We examined environmental factors which are most responsible for the 8-year temporal dynamics of the intertidal seagrass Thalassia hemprichii in southern Taiwan. A dynamic factor analysis (DFA), a dimension-reduction technique, was applied to identify common trends in a multivariate time series and the relationships between this series and interacting environmental variables. The results of dynamic factor models (DFMs) showed that the leaf growth rate of the seagrass was mainly influenced by salinity (Sal), tidal range (TR), turbidity ( K), and a common trend representing an unexplained variability in the observed time series. Sal was the primary variable that explained the temporal dynamics of the leaf growth rate compared to TR and K. K and TR had larger influences on the leaf growth rate in low- than in high-elevation beds. In addition to K, TR, and Sal, UV-B radiation (UV-B), sediment depth (SD), and a common trend accounted for long-term temporal variations of the above-ground biomass. Thus, K, TR, Sal, UV-B, and SD are the predominant environmental variables that described temporal growth variations of the intertidal seagrass T. hemprichii in southern Taiwan. In addition to environmental variables, human activities may be contributing to negative impacts on the seagrass beds; this human interference may have been responsible for the unexplained common trend in the DFMs. Due to successfully applying the DFA to analyze complicated ecological and environmental data in this study, important environmental variables and impacts of human activities along the coast should be taken into account when managing a coastal environment for the conservation of intertidal seagrass beds.

Five Factor Model personality disorder scales: An introduction to a special section on assessment of maladaptive variants of the five factor model.

PubMed

Bagby, R Michael; Widiger, Thomas A

2018-01-01

The Five-Factor Model (FFM) is a dimensional model of general personality structure, consisting of the domains of neuroticism (or emotional instability), extraversion versus introversion, openness (or unconventionality), agreeableness versus antagonism, and conscientiousness (or constraint). The FFM is arguably the most commonly researched dimensional model of general personality structure. However, a notable limitation of existing measures of the FFM has been a lack of coverage of its maladaptive variants. A series of self-report inventories has been developed to assess for the maladaptive personality traits that define Diagnostic and Statistical Manual of Mental Disorders (fifth edition; DSM-5) Section II personality disorders (American Psychiatric Association [APA], 2013) from the perspective of the FFM. In this paper, we provide an introduction to this Special Section, presenting the rationale and empirical support for these measures and placing them in the historical context of the recent revision to the APA diagnostic manual. This introduction is followed by 5 papers that provide further empirical support for these measures and address current issues within the personality assessment literature. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

Event-based rainfall-runoff modelling of the Kelantan River Basin

NASA Astrophysics Data System (ADS)

Basarudin, Z.; Adnan, N. A.; Latif, A. R. A.; Tahir, W.; Syafiqah, N.

2014-02-01

Flood is one of the most common natural disasters in Malaysia. According to hydrologists there are many causes that contribute to flood events. The two most dominant factors are the meteorology factor (i.e climate change) and change in land use. These two factors contributed to floods in recent decade especially in the monsoonal catchment such as Malaysia. This paper intends to quantify the influence of rainfall during extreme rainfall events on the hydrological model in the Kelantan River catchment. Therefore, two dynamic inputs were used in the study: rainfall and river discharge. The extreme flood events in 2008 and 2004 were compared based on rainfall data for both years. The events were modeled via a semi-distributed HEC-HMS hydrological model. Land use change was not incorporated in the study because the study only tries to quantify rainfall changes during these two events to simulate the discharge and runoff value. Therefore, the land use data representing the year 2004 were used as inputs in the 2008 runoff model. The study managed to demonstrate that rainfall change has a significant impact to determine the peak discharge and runoff depth for the study area.

Centenarian Rates and Life Expectancy Related to the Death Rates of Multiple Sclerosis, Asthma, and Rheumatoid Arthritis and the Incidence of Type 1 Diabetes in Children.

PubMed

Lens-Pechakova, Lilia S

2016-02-01

The autoimmune diseases are among the 10 leading causes of death for women and the number two cause of chronic illness in America as well as a predisposing factor for cardiovascular diseases and cancer. Patients of some autoimmune diseases have shown a shorter life span and are a model of accelerated immunosenescence. Conversely, centenarians are used as a model of successful aging and have shown several immune parameters that are better preserved and lower levels of autoantibodies. The study reported here focused on clarifying the connection between longevity and some autoimmune and allergic diseases in 29 developed Organisation for Economic Co-operation and Development (OECD) countries, because multidisciplinary analyses of the accelerated or delayed aging data could show a distinct relationship pattern, help to identify common factors, and determine new important factors that contribute to longevity and healthy aging. The relationships between the mortality rates data of multiple sclerosis (MS), rheumatoid arthritis (RA), asthma, the incidence of type 1 diabetes (T1D) from one side and centenarian rates (two sets) as well as life expectancy data from the other side were assessed using regression models and Pearson correlation coefficients. The data obtained correspond to an inverse linear correlation with different degrees of linearity. This is the first observation of a clear tendency of diminishing centenarian rates or life expectancy in countries having higher death rates of asthma, MS, and RA and a higher incidence of T1D in children. The conclusion is that most probably there are common mechanistic pathways and factors affecting the above diseases and at the same time but in the opposite direction the processes of longevity. Further study, comparing genetic data, mechanistic pathways, and other factors connected to autoimmune diseases with those of longevity could clarify the processes involved, so as to promote longevity and limit the expansion of those diseases in the younger and older population.

[Work stress, common mental disorders and Work Ability Index among call center workers of an Italian company].

PubMed

Conway, Paul Maurice; Campanini, Paolo; Punzi, Silvia; Fichera, Giuseppe Paolo; Camerino, Donatella; Francioli, Laura; Neri, Luca; Costa, Giovanni

2013-01-01

To test three hypotheses in an Italian sample of call center workers: higher levels of perceived work stress are associated with more frequent common mental disorders (GHQ-12) and a lower Work Ability Index; combining the Job Strain (JS) and Effort/Reward Imbalance (ERI) models increases explained variance in health over and above either model when applied separately; compared with outbound operators, inbound call handlers are expected to report a lower health status,which is due to a more intense exposure to task-related work stress factors in the latter. A multi-center cross-sectional study, conducted by means of interviews and self-administered questionnaires. Call handlers working in the Italian branch of a telecommunication multinational company. In all, 1,106 permanent workers were examined (35.9%of the total target population, 98.9% response rate). The majority were women (76.5%);mean age was 33.3 (SD: 3.9) and company seniority 8.0 (SD: 2.1). Nearly 60% worked as inbound call handlers, about one third as outbound operators. Work stress was measured with the well-known JS and ERI models. Three exposure levels (based on tertiles) were identified for each scale. Common mental disorders were measured with the GHQ-12 questionnaire. Subjects with a GHQ-12 score 4 were classified as "cases". The Work Ability Index (WAI) was used to evaluate work ability. Being in the "poor" or "moderate" categories of the WAI indicated a low work ability status. Cronbach's alphas were 0.70 for all scales. Multivariate Poisson regressions showed that both models were linked to more frequent common mental disorders and a lower WAI. Moreover, combined models demonstrated an advantage in terms of explained variance in health. Finally, performing inbound call handling was associated with a lower WAI in comparison with engaging in outbound activities. Mediation analyses showed that such association is explained by the higher levels of psychological job demands and Job Strain experienced by inbound operators. Our results highlight the relevance of work stress as a risk factor for lower psychological health, and especially for a poorer WAI among call center workers. The combined use of the two models increases completeness of work stress assessment in this sector.The higher levels of work stress and the lower WAI observed among inbound operators are due to objectively less favourable task-related characteristics.

Interacting factors associated with Low antibiotic prescribing for respiratory tract infections in primary health care - a mixed methods study in Sweden.

PubMed

Strandberg, Eva Lena; Brorsson, Annika; André, Malin; Gröndal, Hedvig; Mölstad, Sigvard; Hedin, Katarina

2016-07-18

Prescribing of antibiotics for common infections varies widely, and there is no medical explanation. Systematic reviews have highlighted factors that may influence antibiotic prescribing and that this is a complex process. It is unclear how factors interact and how the primary care organization affects diagnostic procedures and antibiotic prescribing. Therefore, we sought to explore and understand interactions between factors influencing antibiotic prescribing for respiratory tract infections in primary care. Our mixed methods design was guided by the Triangulation Design Model according to Creswell. Quantitative and qualitative data were collected in parallel. Quantitative data were collected by prescription statistics, questionnaires to patients, and general practitioners' audit registrations. Qualitative data were collected through observations and semi-structured interviews. From the analysis of the data from the different sources an overall theme emerged: A common practice in the primary health care centre is crucial for low antibiotic prescribing in line with guidelines. Several factors contribute to a common practice, such as promoting management and leadership, internalized guidelines including inter-professional discussions, the general practitioner's diagnostic process, nurse triage, and patient expectation. These factors were closely related and influenced each other. The results showed that knowledge must be internalized and guidelines need to be normative for the group as well as for every individual. Low prescribing is associated with adapted and transformed guidelines within all staff, not only general practitioners. Nurses' triage and self-care advice played an important role. Encouragement from the management level stimulated inter-professional discussions about antibiotic prescribing. Informal opinion moulders talking about antibiotic prescribing was supported by the managers. Finally, continuous professional development activities were encouraged for up-to-date knowledge.

New models of hemostasis.

PubMed

McMichael, Maureen

2012-05-01

Hemostasis is an essential protective mechanism that depends on a delicate balance of procoagulant and anticoagulant processes. The waterfall/cascade models of coagulation are useful for understanding several essential steps of coagulation in vitro. These have resulted in the creation of the plasma-based tests used commonly and the ability to identify deficiencies in the extrinsic, intrinsic, and common pathways of coagulation. The model was also essential in elucidating the role of several of the inhibitors of coagulation and is currently used to demonstrate coagulation as it occurs in plasma in a static environment that is devoid of endothelial interactions. The intrinsic pathway originally described by these models does not appear to be essential for in vivo hemostasis but may play a role in pathologic thrombosis. The waterfall/cascade models' lack of cellular elements sets the stage for the cell-based model of coagulation. The cell-based model of blood coagulation, which includes the varied, complicated network of factors necessary for appropriate in vivo coagulation to occur, was the next step in the evolution of our understanding of coagulation. Recently, researchers have focused on real-time, in vivo models of hemostasis and this research reveals unexpected phenomena. Copyright © 2012 Elsevier Inc. All rights reserved.

Shared molecular networks in orofacial and neural tube development.

PubMed

Kousa, Youssef A; Mansour, Tamer A; Seada, Haitham; Matoo, Samaneh; Schutte, Brian C

2017-01-30

Single genetic variants can affect multiple tissues during development. Thus it is possible that disruption of shared gene regulatory networks might underlie syndromic presentations. In this study, we explore this idea through examination of two critical developmental programs that control orofacial and neural tube development and identify shared regulatory factors and networks. Identification of these networks has the potential to yield additional candidate genes for poorly understood developmental disorders and assist in modeling and perhaps managing risk factors to prevent morbidly and mortality. We reviewed the literature to identify genes common between orofacial and neural tube defects and development. We then conducted a bioinformatic analysis to identify shared molecular targets and pathways in the development of these tissues. Finally, we examine publicly available RNA-Seq data to identify which of these genes are expressed in both tissues during development. We identify common regulatory factors in orofacial and neural tube development. Pathway enrichment analysis shows that folate, cancer and hedgehog signaling pathways are shared in neural tube and orofacial development. Developing neural tissues differentially express mouse exencephaly and cleft palate genes, whereas developing orofacial tissues were enriched for both clefting and neural tube defect genes. These data suggest that key developmental factors and pathways are shared between orofacial and neural tube defects. We conclude that it might be most beneficial to focus on common regulatory factors and pathways to better understand pathology and develop preventative measures for these birth defects. Birth Defects Research 109:169-179, 2017. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

Examining the influence of link function misspecification in conventional regression models for developing crash modification factors.

PubMed

Wu, Lingtao; Lord, Dominique

2017-05-01

This study further examined the use of regression models for developing crash modification factors (CMFs), specifically focusing on the misspecification in the link function. The primary objectives were to validate the accuracy of CMFs derived from the commonly used regression models (i.e., generalized linear models or GLMs with additive linear link functions) when some of the variables have nonlinear relationships and quantify the amount of bias as a function of the nonlinearity. Using the concept of artificial realistic data, various linear and nonlinear crash modification functions (CM-Functions) were assumed for three variables. Crash counts were randomly generated based on these CM-Functions. CMFs were then derived from regression models for three different scenarios. The results were compared with the assumed true values. The main findings are summarized as follows: (1) when some variables have nonlinear relationships with crash risk, the CMFs for these variables derived from the commonly used GLMs are all biased, especially around areas away from the baseline conditions (e.g., boundary areas); (2) with the increase in nonlinearity (i.e., nonlinear relationship becomes stronger), the bias becomes more significant; (3) the quality of CMFs for other variables having linear relationships can be influenced when mixed with those having nonlinear relationships, but the accuracy may still be acceptable; and (4) the misuse of the link function for one or more variables can also lead to biased estimates for other parameters. This study raised the importance of the link function when using regression models for developing CMFs. Copyright © 2017 Elsevier Ltd. All rights reserved.

Unlocking Ft: Modeling thermodynamic controls and isotope fractionation factors in nutrient limited environments

NASA Astrophysics Data System (ADS)

Druhan, J. L.; Giannetta, M.; Sanford, R. A.

2017-12-01

In recent years, reactive transport principles have expanded from early applications, largely based in contaminant hydrology, to a wide range of biologically mediated redox environments including marine sedimentary diagenesis, terrestrial metal ore deposits, soils, and critical zone weathering profiles. A common observation across this diversity of systems is that they often function under energetically limited conditions in comparison to those typical of contaminated aquifers subject to engineered remediation techniques. As a result, the kinetic rate expressions traditionally employed within reactive transport frameworks to simulate microbially mediated redox transformations have required modification. This was recognized in a series of seminal papers by Jin and Bethke (2005, 2007) in which the authors expanded upon a Monod rate law to include a thermodynamic potential factor `Ft' which exerts a limitation on the overall rate based on the thermodynamic driving force of the electron transfer reaction. This new rate expression is now commonly implemented within many of the major reactive transport software packages, though appropriate application has yet to be thoroughly demonstrated. Notably, the characteristically large partitioning of stable isotopes during microbially mediated reactions, which is extensively utilized to identify and quantify these redox transformations, has yet to be simulated under conditions in which the Ft term may be expected to exert a significant mass dependent influence. Here, we develop a series of simplified simulations for the microbially mediated reduction of sulfate based on the datasets reported by Jin and Bethke, and apply appropriate mass-bias within the Ft term to consider the extent to which the resulting isotopic fractionation is consistent with that observed in energetically limited systems. We show that the Ft term can exert a significant influence on the observed fractionation factor under common environmental conditions, resulting in model behavior which is, in effect, a microbial redox analog to the variable observed fractionation factor resulting from a transition state theory rate law as derived by DePaolo (2011).

Prevalence of self-reported asthma in urban and rural areas of Turkey.

PubMed

Ekici, Aydanur; Ekici, Mehmet; Kocyigit, Pinar; Karlidag, Ali

2012-06-01

The risk factors for asthma in rural and urban population of Turkey are not well known. In this study we examined the effects of risk factors on the prevalence of asthma in adults living in rural and urban areas using data from a representative sample. Parents and grandparents of students from 20 randomly selected primary schools in urban and rural areas of Kirikkale, Turkey, were asked about respiratory diseases using the respiratory questionnaire, which were returned to us by their children. Out of 13,225 parents and grandparents of primary school students 12,270 returned the questionnaires, for an overall response rate of 92.7%. The prevalence of asthma was more common in adults living in rural areas than in urban areas (10.8% vs. 6.2%, p < .0001, respectively). Asthma was more prevalent in women exposed to biomass smoke than those who were not exposed to it in rural areas (14.8% vs. 6.6%, p = .0001, respectively). Frequent childhood respiratory infections were more common in adults living in rural areas than in urban areas (18.2% vs. 10.9%, p < .0001, respectively). Exposure to biomass smoke and frequent childhood respiratory infections were associated with an increased risk of asthma, after adjusting for possible confounding factors in the logistic model for rural subjects. Chronic rhinitis (p = .0001) and frequent childhood respiratory infections (p = .0001) were associated with an increased risk of asthma, after adjusting for possible confounding factors in the logistic model for urban subjects. The prevalence of asthma in adults living in the rural areas of the Kirikkale Region in Central Turkey was significantly higher than that in the urban population. Exposure to biomass smoke and childhood respiratory infections were more common in adults living in rural areas. The higher rate of asthma in adults living in rural areas may be due to a higher frequency of childhood respiratory infections and exposure to biomass smoke.

Protective factors associated with fewer multiple problem behaviors among homeless/runaway youth.

PubMed

Lightfoot, Marguerita; Stein, Judith A; Tevendale, Heather; Preston, Kathleen

2011-01-01

Although homeless youth exhibit numerous problem behaviors, protective factors that can be targeted and modified by prevention programs to decrease the likelihood of involvement in risky behaviors are less apparent. The current study tested a model of protective factors for multiple problem behavior in a sample of 474 homeless youth (42% girls; 83% minority) ages 12 to 24 years. Higher levels of problem solving and planning skills were strongly related to lower levels of multiple problem behaviors in homeless youth, suggesting both the positive impact of preexisting personal assets of these youth and important programmatic targets for further building their resilience and decreasing problem behaviors. Indirect relationships between the background factors of self-esteem and social support and multiple problem behaviors were significantly mediated through protective skills. The model suggests that helping youth enhance their skills in goal setting, decision making, and self-reliant coping could lessen a variety of problem behaviors commonly found among homeless youth.

Protective Factors Associated with Fewer Multiple Problem Behaviors Among Homeless/Runaway Youth

PubMed Central

Lightfoot, Marguerita; Stein, Judith A.; Tevendale, Heather; Preston, Kathleen

2015-01-01

Although homeless youth exhibit numerous problem behaviors, protective factors that can be targeted and modified by prevention programs to decrease the likelihood of involvement in risky behaviors are less apparent. The current study tested a model of protective factors for multiple problem behavior in a sample of 474 homeless youth (42% girls; 83% minority) ages 12 to 24 years. Higher levels of problem solving and planning skills were strongly related to lower levels of multiple problem behaviors in homeless youth, suggesting both the positive impact of preexisting personal assets of these youth and important programmatic targets for further building their resilience and decreasing problem behaviors. Indirect relationships between the background factors of self-esteem and social support and multiple problem behaviors were significantly mediated through protective skills. The model suggests that helping youth enhance their skills in goal setting, decision making, and self-reliant coping could lessen a variety of problem behaviors commonly found among homeless youth. PMID:22023279

Retinopathy of prematurity: molecular pathology and therapeutic strategies.

PubMed

Mechoulam, Hadas; Pierce, Eric A

2003-01-01

Retinopathy of prematurity (ROP) is an ischemia-induced proliferative retinopathy, which affects premature infants with low birth weight. It is a leading cause of visual impairment and blindness in children, and shares pathophysiological characteristics with other common ocular diseases such as diabetic retinopathy, central vein occlusion, and age-related macular degeneration. Pathologically similar inherited diseases such as Norrie disease suggest a possible genetic component in the susceptibility to ROP. The process of retinal neovascularization in ROP and in animal models of oxygen-induced retinopathy is complex, and involves angiogenic factors, such as vascular endothelial growth factor, and basement membrane components. Potential medical therapies for ROP, including modulators of angiogenic factors, inhibitors of basement membrane changes, endogenous inhibitors such as pigment epithelium derived factor, and anti-inflammatory drugs, have shown efficacy against neovascularization in several animal models. Some of these therapies are in clinical trials now for diabetic retinopathy and age-related macular degeneration, and in the future may prove efficacious for the treatment of ROP.

Developmental Associations Between Adolescent Alcohol Use and Dating Aggression

PubMed Central

Reyes, H. Luz McNaughton; Foshee, Vangie A.; Bauer, Daniel J.; Ennett, Susan T.

2012-01-01

While numerous studies have established a link between alcohol use and partner violence in adulthood, little research has examined this relation during adolescence. The current study used multivariate growth models to examine relations between alcohol use and dating aggression across grades 8 through 12 controlling for shared risk factors (common causes) that predict both behaviors. Associations between trajectories of alcohol use and dating aggression were reduced substantially when common causes were controlled. Concurrent associations between the two behaviors were significant across nearly all grades but no evidence was found for prospective connections from prior alcohol use to subsequent dating aggression or vice versa. Findings suggest that prevention efforts should target common causes of alcohol use and dating aggression. PMID:23589667

A multivariate decision tree analysis of biophysical factors in tropical forest fire occurrence

Treesearch

Rey S. Ofren; Edward Harvey

2000-01-01

A multivariate decision tree model was used to quantify the relative importance of complex hierarchical relationships between biophysical variables and the occurrence of tropical forest fires. The study site is the Huai Kha Kbaeng wildlife sanctuary, a World Heritage Site in northwestern Thailand where annual fires are common and particularly destructive. Thematic...

Self-Reported Use of Different Forms of Aggression in Late Adolescence and Emerging Adulthood

ERIC Educational Resources Information Center

Verona, Edelyn; Sadeh, Naomi; Case, Steve M.; Reed, Americus, II; Bhattacharjee, Amit

2008-01-01

Two studies investigated the psychometric properties of a self-report measure of commonly recognized forms of aggression (FOA) that could be used to efficiently gather aggression data in large samples. EFA and CFA in Study 1 suggested that a five-factor model (Physical, Property, Verbal, Relational, and Passive-Rational) best represented the data…

And never the twain shall meet? Integrating revenue cycle and supply chain functions.

PubMed

Matjucha, Karen A; Chung, Bianca

2008-09-01

Four initial steps to implementing a profit and loss management model are: Identify the supplies clinicians are using. Empower stakeholders to remove items that are not commonly used. Reduce factors driving wasted product. Review the chargemaster to ensure that supplies used in selected procedures are represented. Strategically set prices that optimize maximum allowable reimbursement.

Cognitive Vulnerability-Stress Model of Depression during Adolescence: Investigating Depressive Symptom Specificity in a Multi-Wave Prospective Study

ERIC Educational Resources Information Center

Hankin, Benjamin L.

2008-01-01

Depression commonly co-occurs with anxiety and externalizing problems. Etiological factors from a central cognitive theory of depression, the Hopelessness Theory (Abramson et al. "Psychological Review," 96, 358-372, 1989), were examined to evaluate whether a negative inferential style about cause, consequence, and self interacted with stressors…

Human Factors in Command-and-Control System Procurement,

DTIC Science & Technology

1985-12-01

more common terms, whether workload is too high. Generally, workload is a concept that is open to many intepretations . From a modeller’s viewpoint...solution, according to Meister and Farr (1966). may be to provide designers with better means of analysing conceptual systems. The goals of this report are thus closely aligned with that philosophy. DATE FILMED

Resilience, Syndemic Factors, and Serosorting Behaviors among HIV-Positive and HIV-Negative Substance-Using MSM

ERIC Educational Resources Information Center

Kurtz, Steven P.; Buttram, Mance E.; Surratt, Hilary L.; Stall, Ronald D.

2012-01-01

Serosorting is commonly employed by MSM to reduce HIV risk. We hypothesize that MSM perceive serosorting to be effective, and that serosorting is predicted by resilience and inversely related to syndemic characteristics. Surveys included 504 substance-using MSM. Logistic regression models examined syndemic and resilience predictors of serosorting,…

Response surface model for the reduction of Salmonella biofilm on stainless steel with lactic acid, ethanol and chlorine as controlling factors

USDA-ARS?s Scientific Manuscript database

Bacterial colonization and biofilm formation on food contact surfaces can be sources of contamination of processed foods and poses a serious threat to health. Since chlorine- or ethanol-based disinfection is commonly used in the food industry and kitchens, a disinfectant containing chlorine (Cl), et...

Cultural Predictors of Physical and Mental Health Status among Mexican American Women: A Mediation Model

PubMed Central

Dinh, Khanh T.; Castro, Felipe González; Tein, Jenn-Yun; Kim, Su Yeong

2016-01-01

This study, using secondary data analysis, examined a mediation model of acculturation and ethnic pride as predictors of physical and mental health outcomes in a sample of 561 Mexican American women. Factors postulated as mediators were family support and religiosity. Systematic across-group comparison analyses were conducted to examine sources of differences in the mediation model between immigrant and non-immigrant women. The results partially supported the hypothesized mediation model, indicating that family support, but not religiosity, was a significant mediator in the relationship between ethnic pride and mental health problems. In addition, as differences between immigrant and non-immigrant women were observed only in the variables means, but not in the factor loadings or regression paths, the model tested may capture a common psychosocial process that affects these women and their health outcomes. Overall, this study offers important implications for future research and the design of intervention programs for Mexican American women. PMID:19130212

Animal models for assessment of infection and inflammation: contributions to elucidating the pathophysiology of sudden infant death syndrome.

PubMed

Blood-Siegfried, Jane

2015-01-01

Sudden infant death syndrome (SIDS) is still not well understood. It is defined as the sudden and unexpected death of an infant without a definitive cause. There are numerous hypotheses about the etiology of SIDS but the exact cause or causes have never been pinpointed. Examination of theoretical pathologies might only be possible in animal models. Development of these models requires consideration of the environmental and/or developmental risk factors often associated with SIDS, as they need to explain how the risk factors could contribute to the cause of death. These models were initially developed in common laboratory animals to test various hypotheses to explain these infant deaths - guinea pig, piglet, mouse, neonatal rabbit, and neonatal rat. Currently, there are growing numbers of researchers using genetically altered animals to examine specific areas of interest. This review describes the different systems and models developed to examine the diverse hypotheses for the cause of SIDS and their potential for defining a causal mechanism or mechanisms.

Evaluation of factors important in modeling plasma concentrations of tetracycline hydrochloride administered in water in swine.

PubMed

Mason, Sharon E; Almond, Glen W; Riviere, Jim E; Baynes, Ronald E

2012-10-01

To model the plasma tetracycline concentrations in swine (Sus scrofa domestica) treated with medication administered in water and determine the factors that contribute to the most accurate predictions of measured plasma drug concentrations. Plasma tetracycline concentrations measured in blood samples from 3 populations of swine. Data from previous studies provided plasma tetracycline concentrations that were measured in blood samples collected from 1 swine population at 0, 4, 8, 12, 24, 32, 48, 56, 72, 80, 96, and 104 hours and from 2 swine populations at 0, 12, 24, 48, and 72 hours hours during administration of tetracycline hydrochloride dissolved in water. A 1-compartment pharmacostatistical model was used to analyze 5 potential covariate schemes and determine factors most important in predicting the plasma concentrations of tetracycline in swine. 2 models most accurately predicted the tetracycline plasma concentrations in the 3 populations of swine. Factors of importance were body weight or age of pig, ambient temperature, concentration of tetracycline in water, and water use per unit of time. The factors found to be of importance, combined with knowledge of the individual pharmacokinetic and chemical properties of medications currently approved for administration in water, may be useful in more prudent administration of approved medications administered to swine. Factors found to be important in pharmacostatistical models may allow prediction of plasma concentrations of tetracycline or other commonly used medications administered in water. The ability to predict in vivo concentrations of medication in a population of food animals can be combined with bacterial minimum inhibitory concentrations to decrease the risk of developing antimicrobial resistance.