Analysis of the Explanatory Variables of the Differences in Perceptions of Cyberbullying: A Role-Based-Model Approach.

PubMed

Fernández-Antelo, Inmaculada; Cuadrado-Gordillo, Isabel

2018-04-01

The controversies that exist regarding the delimitation of the cyberbullying construct demonstrate the need for further research focused on determining the criteria that shape the structure of the perceptions that adolescents have of this phenomenon and on seeking explanations of this behavior. The objectives of this study were to (a) construct possible explanatory models of the perception of cyberbullying from identifying and relating the criteria that form this construct and (b) analyze the influence of previous cyber victimization and cyber aggression experiences in the construction of explanatory models of the perception of cyberbullying. The sample consisted of 2,148 adolescents (49.1% girls; SD = 0.5) aged from 12 to 16 years ( M = 13.9 years; SD = 1.2). The results have shown that previous cyber victimization and cyber aggression experiences lead to major differences in the explanatory models to interpret cyber-abusive behavior as cyberbullying episodes, or as social relationship mechanisms, or as a revenge reaction. We note that the aggressors' explanatory model is based primarily on a strong reciprocal relationship between the imbalance of power and intentionality, that it functions as a link promoting indirect causal relationships of the anonymity and repetition factors with the cyberbullying construct. The victims' perceptual structure is based on three criteria-imbalance of power, intentionality, and publicity-where the key factor in this structure is the intention to harm. These results allow to design more effective measures of prevention and intervention closely tailored to addressing directly the factors that are considered to be predictors of risk.

How well can body size represent effects of the environment on demographic rates? Disentangling correlated explanatory variables.

PubMed

Brooks, Mollie E; Mugabo, Marianne; Rodgers, Gwendolen M; Benton, Timothy G; Ozgul, Arpat

2016-03-01

Demographic rates are shaped by the interaction of past and current environments that individuals in a population experience. Past environments shape individual states via selection and plasticity, and fitness-related traits (e.g. individual size) are commonly used in demographic analyses to represent the effect of past environments on demographic rates. We quantified how well the size of individuals captures the effects of a population's past and current environments on demographic rates in a well-studied experimental system of soil mites. We decomposed these interrelated sources of variation with a novel method of multiple regression that is useful for understanding nonlinear relationships between responses and multicollinear explanatory variables. We graphically present the results using area-proportional Venn diagrams. Our novel method was developed by combining existing methods and expanding upon them. We showed that the strength of size as a proxy for the past environment varied widely among vital rates. For instance, in this organism with an income breeding life history, the environment had more effect on reproduction than individual size, but with substantial overlap indicating that size encompassed some of the effects of the past environment on fecundity. This demonstrates that the strength of size as a proxy for the past environment can vary widely among life-history processes within a species, and this variation should be taken into consideration in trait-based demographic or individual-based approaches that focus on phenotypic traits as state variables. Furthermore, the strength of a proxy will depend on what state variable(s) and what demographic rate is being examined; that is, different measures of body size (e.g. length, volume, mass, fat stores) will be better or worse proxies for various life-history processes. © 2016 The Authors. Journal of Animal Ecology © 2016 British Ecological Society.

Meteorological influences on the interannual variability of meningitis incidence in northwest Nigeria.

NASA Astrophysics Data System (ADS)

Abdussalam, Auwal; Monaghan, Andrew; Dukic, Vanja; Hayden, Mary; Hopson, Thomas; Leckebusch, Gregor

2013-04-01

Northwest Nigeria is a region with high risk of bacterial meningitis. Since the first documented epidemic of meningitis in Nigeria in 1905, the disease has been endemic in the northern part of the country, with epidemics occurring regularly. In this study we examine the influence of climate on the interannual variability of meningitis incidence and epidemics. Monthly aggregate counts of clinically confirmed hospital-reported cases of meningitis were collected in northwest Nigeria for the 22-year period spanning 1990-2011. Several generalized linear statistical models were fit to the monthly meningitis counts, including generalized additive models. Explanatory variables included monthly records of temperatures, humidity, rainfall, wind speed, sunshine and dustiness from weather stations nearest to the hospitals, and a time series of polysaccharide vaccination efficacy. The effects of other confounding factors -- i.e., mainly non-climatic factors for which records were not available -- were estimated as a smooth, monthly-varying function of time in the generalized additive models. Results reveal that the most important explanatory climatic variables are mean maximum monthly temperature, relative humidity and dustiness. Accounting for confounding factors (e.g., social processes) in the generalized additive models explains more of the year-to-year variation of meningococcal disease compared to those generalized linear models that do not account for such factors. Promising results from several models that included only explanatory variables that preceded the meningitis case data by 1-month suggest there may be potential for prediction of meningitis in northwest Nigeria to aid decision makers on this time scale.

The use of generalised additive models (GAM) in dentistry.

PubMed

Helfenstein, U; Steiner, M; Menghini, G

1997-12-01

Ordinary multiple regression and logistic multiple regression are widely applied statistical methods which allow a researcher to 'explain' or 'predict' a response variable from a set of explanatory variables or predictors. In these models it is usually assumed that quantitative predictors such as age enter linearly into the model. During recent years these methods have been further developed to allow more flexibility in the way explanatory variables 'act' on a response variable. The methods are called 'generalised additive models' (GAM). The rigid linear terms characterising the association between response and predictors are replaced in an optimal way by flexible curved functions of the predictors (the 'profiles'). Plotting the 'profiles' allows the researcher to visualise easily the shape by which predictors 'act' over the whole range of values. The method facilitates detection of particular shapes such as 'bumps', 'U-shapes', 'J-shapes, 'threshold values' etc. Information about the shape of the association is not revealed by traditional methods. The shapes of the profiles may be checked by performing a Monte Carlo simulation ('bootstrapping'). After the presentation of the GAM a relevant case study is presented in order to demonstrate application and use of the method. The dependence of caries in primary teeth on a set of explanatory variables is investigated. Since GAMs may not be easily accessible to dentists, this article presents them in an introductory condensed form. It was thought that a nonmathematical summary and a worked example might encourage readers to consider the methods described. GAMs may be of great value to dentists in allowing visualisation of the shape by which predictors 'act' and obtaining a better understanding of the complex relationships between predictors and response.

Exploring the Wisdom Structure: Validation of the Spanish New Short Three-Dimensional Wisdom Scale (3D-WS) and Its Explanatory Power on Psychological Health-Related Variables.

PubMed

García-Campayo, Javier; Del Hoyo, Yolanda L; Barceló-Soler, Alberto; Navarro-Gil, Mayte; Borao, Luis; Giarin, Veronica; Tovar-Garcia, R Raziel; Montero-Marin, Jesus

2018-01-01

Introduction: Personal wisdom has demonstrated important implications for the health of individuals. The aim of the present study was to validate a Spanish version of the Three-Dimensional Wisdom Scale (3D-WS), exploring the structure of a possible general factor, and assessing its explanatory power on psychological health-related variables. Methods: A cross-sectional study design was used, with a total sample of 624 Spanish participants recruited on the Internet and randomly split into two halves. The following instruments were applied: 3D-WS, Purpose in Life (PIL), Multidimensional State Boredom Scale (MSBS), Positive and Negative Affect Scale (PANAS), and Difficulties in Emotion Regulation Scale (DERS). Factorial structures were analyzed through exploratory and confirmatory factor analysis (EFA and CFA), and the general factor was characterized by using bifactor models. The explanatory power of the 3D-WS was established by multiple regression. Results: The original long and short versions of the 3D-WS were not replicated in the first subsample using EFA, and there was a high rate of cross-loadings. Thus, a new short 3D-WS was proposed by ordering the original items according to factorial weights. This three-correlated-factor (reflective, cognitive, and affective) proposal was tested by means of CFA in the second subsample, with adequate psychometrics and invariance, and a good fit (χ 2 /df = 1.98; CFI = 0.946; RMSEA = 0.056; 90% CI = 0.040-0.072). A bifactor structure, in which the reflective trait of wisdom was integrated into a general factor (G-Reflective) improved the model fit (χ 2 /df = 1.85; CFI = 0.959; RMSEA = 0.052; 90% CI = 0.035-0.070). The explained common variance of G-Reflective was 0.53; therefore, the new short 3D-WS should not be considered essentially unidimensional. The new short 3D-WS showed positive relationships with the PIL and PANAS-positive, and negative associations with the MSBS, PANAS-negative and DERS, contributing to explain all

Causes of Job Turnover in the Public School Superintendency: An Explanatory Analysis in the Western United States

ERIC Educational Resources Information Center

Melver, Toby A.

2011-01-01

The purpose of this mixed-methods study was to determine the factors that affect public school superintendent turnover in five western states. An explanatory theory was developed to cover all of the possible variables and show the relationship between those variables. The questions that guided this research study were: (1) What environmental…

Environmental, morphological, and productive characterization of Sardinian goats and use of latent explanatory factors for population analysis.

PubMed

Vacca, G M; Paschino, P; Dettori, M L; Bergamaschi, M; Cipolat-Gotet, C; Bittante, G; Pazzola, M

2016-09-01

Dairy goat farming is practiced worldwide, within a range of different farming systems. Here we investigated the effects of environmental factors and morphology on milk traits of the Sardinian goat population. Sardinian goats are currently reared in Sardinia (Italy) in a low-input context, similar to many goat farming systems, especially in developing countries. Milk and morphological traits from 1,050 Sardinian goats from 42 farms were recorded. We observed a high variability regarding morphological traits, such as coat color, ear length and direction, horn presence, and udder shape. Such variability derived partly from the unplanned repeated crossbreeding of the native Sardinian goats with exotic breeds, especially Maltese goats. The farms located in the mountains were characterized by the traditional farming system and the lowest percentage of crossbred goats. Explanatory factors analysis was used to summarize the interrelated measured milk variables. The explanatory factor related to fat, protein, and energy content of milk (the "Quality" latent variable) explained about 30% of the variance of the whole data set of measured milk traits followed by the "Hygiene" (19%), "Production" (19%), and "Acidity" (11%) factors. The "Quality" and "Hygiene" factors were not affected by any of the farm classification items, whereas "Production" and "Acidity" were affected only by altitude and size of herds, respectively, indicating the adaptation of the local goat population to different environmental conditions. The use of latent explanatory factor analysis allowed us to clearly explain the large variability of milk traits, revealing that the Sardinian goat population cannot be divided into subpopulations based on milk attitude The factors, properly integrated with genetic data, may be useful tools in future selection programs.

Learned social hopelessness: the role of explanatory style in predicting social support during adolescence.

PubMed

Ciarrochi, Joseph; Heaven, Patrick C L

2008-12-01

Almost no research has examined the impact of explanatory style on social adjustment. We hypothesised that adolescents with a pessimistic style would be less likely to develop and maintain social support networks. Seven hundred and nineteen students (351 males and 366 females; 2 unknown; M(AGE) = 12.28, SD = .49) completed an anonymous survey in Grades 7 through 10. Explanatory style was assessed in Grades 7 and 9, sadness was assessed in Grades 7 through 10, and quantity and quality of social support was assessed in Grades 8, 9, and 10. Structural equation modelling was used to conduct cross-lagged panel analyses of the four waves of data. Pessimistic explanatory style predicted lower levels of social support, and lower social support from the family predicted higher levels of pessimistic explanatory style. Additional analyses suggested that the effects could not be explained by sadness or by assuming that pessimistic adolescents where less liked by their peers. Pessimistic adolescents feel unable to influence their social worlds in positive ways and consequently may not take actions to develop and maintain social support networks.

Explanatory models of psychosis amongst British South Asians.

PubMed

Bhikha, Aqeela; Farooq, Saeed; Chaudhry, Nasim; Naeem, Farooq; Husain, Nusrat

2015-08-01

A strong interest in the understanding, exploring, and extracting explanatory models of psychosis has recently arisen. Explanatory models (EMs) offer justifications and propose explanations when coping with and treating illnesses. Therefore, they may be important predictors of clinical outcome. Explanatory models of psychosis have been explored in many non-Western countries. However, very little research has examined EMs of psychosis in the UK. We therefore, aimed to elicit and describe explanatory models of psychosis amongst British South Asians, using both quantitative and qualitative methods. EMs of psychosis were examined using the Short Explanatory Model Interview (SEMI) in a cross-sectional sample of 45 patients. Most patients (55.5%) attributed their illness to supernatural causes. Few patients cited a biological (4.4%) cause. Majority of patients held dual EMs of psychosis (77.7%), combining prescribed medication and seeing a traditional healer as a treatment method. Duration of Untreated Psychosis (DUP) was not significantly associated with EMs of psychosis. The results suggest that patients hold multi-explanatory models in order to make sense of their illness and these stem from deep rooted traditional beliefs. This highlights the importance of educational intervention, culturally adapted psychological interventions and possibly working together with traditional healers in the UK to provide a positive support system. Further work is required in order to fully understand the relationship between EMs of psychosis and DUP. Copyright © 2015 Elsevier B.V. All rights reserved.

IRAS sky survey atlas: Explanatory supplement

NASA Technical Reports Server (NTRS)

Wheelock, S. L.; Gautier, T. N.; Chillemi, J.; Kester, D.; Mccallon, H.; Oken, C.; White, J.; Gregorich, D.; Boulanger, F.; Good, J.

1994-01-01

This Explanatory Supplement accompanies the IRAS Sky Survey Atlas (ISSA) and the ISSA Reject Set. The first ISSA release in 1991 covers completely the high ecliptic latitude sky, absolute value of beta is greater than 50 deg, with some coverage down to the absolute value of beta approx. equal to 40 deg. The second ISSA release in 1992 covers ecliptic latitudes of 50 deg greater than the absolute value of beta greater than 20 deg, with some coverage down to the absolute value of beta approx. equal to 13 deg. The remaining fields covering latitudes within 20 deg of the ecliptic plane are of reduced quality compared to the rest of the ISSA fields and therefore are released as a separate IPAC product, the ISSA Reject Set. The reduced quality is due to contamination by zodiacal emission residuals. Special care should be taken when using the ISSA Reject images. In addition to information on the ISSA images, some information is provided in this Explanatory Supplement on the IRAS Zodiacal History File (ZOHF), Version 3.0, which was described in the December 1988 release memo. The data described in this Supplement are available at the National Space Science Data Center (NSSDC) at the Goddard Space Flight Center. The interested reader is referred to the NSSDC for access to the IRAS Sky Survey Atlas (ISSA).

Tentative explanatory variable of lung dust concentration in gold miners exposed to crystalline silica.

PubMed

Dufresne, A; Loosereewanich, P; Bégin, R; Dion, C; Ecobichon, D; Muir, D C; Ritchie, A C; Perrault, G

1998-01-01

The first objective of the study was to investigate the relationships between quantitative lung mineral dust burdens, dust exposure history, and pathological fibrosis grading in silicotic workers. The second objective was to evaluate the association between particle size parameters, concentration of retained silica particles and the severity of the silicosis. Sixty-seven paraffin-embedded lung tissue samples of silicotic patients were analyzed. The cases of silicosis included 39 non-lung cancer patients and 28 patients with lung cancer. All of the cases were gold miners in the Province of Ontario, Canada. Particles, both angular and fibrous, were extracted from lung parenchyma by a bleach digestion method, mounted on copper microscopic grids by a carbon replica technique, and analyzed by transmission electron microscopy (TEM) and energy dispersive spectroscopy (EDS). Quartz concentration was also determined by X-ray diffraction (XRD) on a silver membrane filter after the extraction from the lung parenchyma. Total particles, silica, clay, and quartz also increase in concentration with increased age at death, although the trends are not statistically significant. Quartz concentration has a statistically significant correlation with the silicosis severity score (r = +0.45, p < 0.001), with the geometric mean concentration increasing from 2.24 micrograms/mg in the group having silicosis severity score less than 1 to 4.80 micrograms/mg in group with highest score. Quartz concentration is the only significant explanatory variable of the silicosis severity with a regression coefficient of +0.41 (p < 0.001). Among several dust exposure variables extracted from the work history of the miners, the calendar year of first exposure was the primary significant determinant of lung retained total particles, silica, and clay minerals, except for quartz. A statistically significant linear relationship between lung quartz concentration and silicosis severity in the gold miners was

Socioeconomic inequalities in mortality and repeated measurement of explanatory risk factors in a 25 years follow-up.

PubMed

Skalická, Věra; Ringdal, Kristen; Witvliet, Margot I

2015-01-01

Socioeconomic inequalities in mortality can be explained by different groups of risk factors. However, little is known whether repeated measurement of risk factors can provide better explanation of socioeconomic inequalities in health. Our study examines the extent to which relative educational and income inequalities in mortality might be explained by explanatory risk factors (behavioral, psychosocial, biomedical risk factors and employment) measured at two points in time, as compared to one measurement at baseline. From the Norwegian total county population-based HUNT Study (years 1984-86 and 1995-1997, respectively) 61 513 men and women aged 25-80 (82.5% of all enrolled) were followed-up for mortality in 25 years until 2009, employing a discrete time survival analysis. Socioeconomic inequalities in mortality were observed. As compared to their highest socioeconomic counterparts, the lowest educated men had an OR (odds ratio) of 1.41 (95% CI 1.29-1.55) and for the lowest income quartile OR = 1.59 (1.48-1.571), for women OR = 1.35 (1.17-1.55), and OR = 1.40 (1.28-1.52), respectively. Baseline explanatory variables attenuated the association between education and income with mortality by 54% and 54% in men, respectively, and by 69% and 18% in women. After entering time-varying variables, this attainment increased to 63% and 59% in men, respectively, and to 25% (income) in women, with no improvement in regard to education in women. Change in biomedical factors and employment did not amend the explanation. Addition of a second measurement for risk factors provided only a modest improvement in explaining educational and income inequalities in mortality in Norwegian men and women. Accounting for change in behavior provided the largest improvement in explained inequalities in mortality for both men and women, as compared to measurement at baseline. Psychosocial factors explained the largest share of income inequalities in mortality for men, but repeated measurement of

Information Sources as Explanatory Variables for the Belgian Health-Related Risk Perception of the Fukushima Nuclear Accident.

PubMed

Vyncke, Bart; Perko, Tanja; Van Gorp, Baldwin

2017-03-01

The media play an important role in risk communication, providing information about accidents, both nearby and far away. Each media source has its own presentation style, which could influence how the audience perceives the presented risk. This study investigates the explanatory power of 12 information sources (traditional media, new media, social media, and interpersonal communication) for the perceived risk posed by radiation released from the damaged Fukushima nuclear power plant on respondents' own health and that of the population in general. The analysis controlled for attitude toward nuclear energy, gender, education, satisfaction with the media coverage, and duration of attention paid to the coverage. The study uses a large empirical data set from a public opinion survey, which is representative for the Belgian population with respect to six sociodemographic variables. Results show that three information sources are significant regressors of perceived health-related risk of the nuclear accident: television, interpersonal communication, and the category of miscellaneous online sources. More favorable attitudes toward nuclear power, longer attention to the coverage, and higher satisfaction with the provided information lead to lower risk perception. Taken together, the results suggest that the media can indeed have a modest influence on how the audience perceives a risk. © 2016 Society for Risk Analysis.

Explanatory Power of Multi-scale Physical Descriptors in Modeling Benthic Indices Across Nested Ecoregions of the Pacific Northwest

NASA Astrophysics Data System (ADS)

Holburn, E. R.; Bledsoe, B. P.; Poff, N. L.; Cuhaciyan, C. O.

2005-05-01

Using over 300 R/EMAP sites in OR and WA, we examine the relative explanatory power of watershed, valley, and reach scale descriptors in modeling variation in benthic macroinvertebrate indices. Innovative metrics describing flow regime, geomorphic processes, and hydrologic-distance weighted watershed and valley characteristics are used in multiple regression and regression tree modeling to predict EPT richness, % EPT, EPT/C, and % Plecoptera. A nested design using seven ecoregions is employed to evaluate the influence of geographic scale and environmental heterogeneity on the explanatory power of individual and combined scales. Regression tree models are constructed to explain variability while identifying threshold responses and interactions. Cross-validated models demonstrate differences in the explanatory power associated with single-scale and multi-scale models as environmental heterogeneity is varied. Models explaining the greatest variability in biological indices result from multi-scale combinations of physical descriptors. Results also indicate that substantial variation in benthic macroinvertebrate response can be explained with process-based watershed and valley scale metrics derived exclusively from common geospatial data. This study outlines a general framework for identifying key processes driving macroinvertebrate assemblages across a range of scales and establishing the geographic extent at which various levels of physical description best explain biological variability. Such information can guide process-based stratification to avoid spurious comparison of dissimilar stream types in bioassessments and ensure that key environmental gradients are adequately represented in sampling designs.

Explanatory style, dispositional optimism, and reported parental behavior.

PubMed

Hjelle, L A; Busch, E A; Warren, J E

1996-12-01

The relationship between two cognitive personality constructs (explanatory style and dispositional optimism) and retrospective self-reports of maternal and paternal behavior were investigated. College students (62 men and 145 women) completed the Life Orientation Test, Attributional Style Questionnaire, and Parental Acceptance-Rejection Questionnaire in a single session. As predicted, dispositional optimism was positively correlated with reported maternal and paternal warmth/acceptance and negatively correlated with aggression/hostility, neglect/indifference, and undifferentiated rejection during middle childhood. Unexpectedly, explanatory style was found to be more strongly associated with retrospective reports of paternal as opposed to maternal behavior. The implications of these results for future research concerning the developmental antecedents of differences in explanatory style and dispositional optimism are discussed.

Interdisciplinary and Cross-Cultural Perspectives on Explanatory Coexistence.

PubMed

Watson-Jones, Rachel E; Busch, Justin T A; Legare, Cristine H

2015-10-01

Natural and supernatural explanations are used to interpret the same events in a number of predictable and universal ways. Yet little is known about how variation in diverse cultural ecologies influences how people integrate natural and supernatural explanations. Here, we examine explanatory coexistence in three existentially arousing domains of human thought: illness, death, and human origins using qualitative data from interviews conducted in Tanna, Vanuatu. Vanuatu, a Melanesian archipelago, provides a cultural context ideal for examining variation in explanatory coexistence due to the lack of industrialization and the relatively recent introduction of Christianity and Western education. We argue for the integration of interdisciplinary methodologies from cognitive science and anthropology to inform research on explanatory coexistence. Copyright © 2015 Cognitive Science Society, Inc.

Mechanisms of eyewitness suggestibility: tests of the explanatory role hypothesis.

PubMed

Rindal, Eric J; Chrobak, Quin M; Zaragoza, Maria S; Weihing, Caitlin A

2017-10-01

In a recent paper, Chrobak and Zaragoza (Journal of Experimental Psychology: General, 142(3), 827-844, 2013) proposed the explanatory role hypothesis, which posits that the likelihood of developing false memories for post-event suggestions is a function of the explanatory function the suggestion serves. In support of this hypothesis, they provided evidence that participant-witnesses were especially likely to develop false memories for their forced fabrications when their fabrications helped to explain outcomes they had witnessed. In three experiments, we test the generality of the explanatory role hypothesis as a mechanism of eyewitness suggestibility by assessing whether this hypothesis can predict suggestibility errors in (a) situations where the post-event suggestions are provided by the experimenter (as opposed to fabricated by the participant), and (b) across a variety of memory measures and measures of recollective experience. In support of the explanatory role hypothesis, participants were more likely to subsequently freely report (E1) and recollect the suggestions as part of the witnessed event (E2, source test) when the post-event suggestion helped to provide a causal explanation for a witnessed outcome than when it did not serve this explanatory role. Participants were also less likely to recollect the suggestions as part of the witnessed event (on measures of subjective experience) when their explanatory strength had been reduced by the presence of an alternative explanation that could explain the same outcome (E3, source test + warning). Collectively, the results provide strong evidence that the search for explanatory coherence influences people's tendency to misremember witnessing events that were only suggested to them.

Hill's Heuristics and Explanatory Coherentism in Epidemiology.

PubMed

Dammann, Olaf

2018-01-01

In this essay, I argue that Ted Poston's theory of explanatory coherentism is well-suited as a tool for causal explanation in the health sciences, particularly in epidemiology. Coherence has not only played a role in epidemiology for more than half a century as one of Hill's viewpoints, it can also provide background theory for the development of explanatory systems by integrating epidemiologic evidence with a diversity of other error-independent data. I propose that computational formalization of Hill's viewpoints in an explanatory coherentist framework would provide an excellent starting point for a formal epistemological (knowledge-theoretical) project designed to improve causal explanation in the health sciences. As an example, I briefly introduce Paul Thagard's ECHO system and offer my responses to possible objections to my proposal. © The Author(s) 2017. Published by Oxford University Press on behalf of the Johns Hopkins Bloomberg School of Public Health. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Joint perceptual decision-making: a case study in explanatory pluralism

PubMed Central

Abney, Drew H.; Dale, Rick; Yoshimi, Jeff; Kello, Chris T.; Tylén, Kristian; Fusaroli, Riccardo

2014-01-01

Traditionally different approaches to the study of cognition have been viewed as competing explanatory frameworks. An alternative view, explanatory pluralism, regards different approaches to the study of cognition as complementary ways of studying the same phenomenon, at specific temporal and spatial scales, using appropriate methodological tools. Explanatory pluralism has been often described abstractly, but has rarely been applied to concrete cases. We present a case study of explanatory pluralism. We discuss three separate ways of studying the same phenomenon: a perceptual decision-making task (Bahrami et al., 2010), where pairs of subjects share information to jointly individuate an oddball stimulus among a set of distractors. Each approach analyzed the same corpus but targeted different units of analysis at different levels of description: decision-making at the behavioral level, confidence sharing at the linguistic level, and acoustic energy at the physical level. We discuss the utility of explanatory pluralism for describing this complex, multiscale phenomenon, show ways in which this case study sheds new light on the concept of pluralism, and highlight good practices to critically assess and complement approaches. PMID:24795679

Explanatory style across the life span: evidence for stability over 52 years.

PubMed

Burns, M O; Seligman, M E

1989-03-01

Analyzed explanatory style across the life span. 30 Ss whose average age was 72 responded to questions about their current life and provided diaries or letters written in their youth, an average of 52 years earlier. A blind content analysis of explanatory style derived from these 2 sources revealed that explanatory style for negative events was stable throughout adult life (r = .54, p less than .002). In contrast, there appeared to be no stability of explanatory style for positive events between the same 2 time periods. These results suggest that explanatory style for negative events may persist across the life span and may constitute an enduring risk factor for depression, low achievement, and physical illness.

Treatment needs and predictive capacity of explanatory variables of oral disease in young athletes with an intellectual disability in Europe and Eurasia.

PubMed

Fernandez, C; Descamps, I; Fabjanska, K; Kaschke, I; Marks, L

2016-03-01

To evaluate the oral condition and treatment needs of young athletes with intellectual disability (ID) from 53 countries of Europe and Eurasia who participated in the Special Olympics European Games held in Antwerp, October 2014. A cross- sectional study was undertaken with data collected through standardised procedures from consenting athletes under 21 years of age. Oral hygiene habits, reports of oral pain and presence of gingival signs, sealants, untreated caries and missing teeth were recorded. Data analysis was performed in SPSS to produce descriptive statistics and explanatory variables for untreated decay, and gingival signs of disease were tested with Multilevel Generalized Linear Mixed Models. Five hundred three athletes participated in this study (mean age 17 yrs). Untreated decay was recorded in 33.4% of the participants and 38.7% of them had signs of gingival disease. Absence of untreated decay was associated with lower chances of gingival signs, while absence of sealants was related with higher chances of untreated decay. There is consistent evidence of persistent need for increased promotion of oral health, as well as preventive and restorative treatment in young athletes with ID in Europe and Eurasia. Due to the limited predictive capacity of the studied variables for oral disease, further studies including other related factors are needed.

Socioeconomic Inequalities in Mortality and Repeated Measurement of Explanatory Risk Factors in a 25 Years Follow-Up

PubMed Central

Skalická, Věra; Ringdal, Kristen; Witvliet, Margot I.

2015-01-01

Background Socioeconomic inequalities in mortality can be explained by different groups of risk factors. However, little is known whether repeated measurement of risk factors can provide better explanation of socioeconomic inequalities in health. Our study examines the extent to which relative educational and income inequalities in mortality might be explained by explanatory risk factors (behavioral, psychosocial, biomedical risk factors and employment) measured at two points in time, as compared to one measurement at baseline. Methods and Findings From the Norwegian total county population-based HUNT Study (years 1984–86 and 1995–1997, respectively) 61 513 men and women aged 25–80 (82.5% of all enrolled) were followed-up for mortality in 25 years until 2009, employing a discrete time survival analysis. Socioeconomic inequalities in mortality were observed. As compared to their highest socioeconomic counterparts, the lowest educated men had an OR (odds ratio) of 1.41 (95% CI 1.29–1.55) and for the lowest income quartile OR = 1.59 (1.48–1.571), for women OR = 1.35 (1.17–1.55), and OR = 1.40 (1.28–1.52), respectively. Baseline explanatory variables attenuated the association between education and income with mortality by 54% and 54% in men, respectively, and by 69% and 18% in women. After entering time-varying variables, this attainment increased to 63% and 59% in men, respectively, and to 25% (income) in women, with no improvement in regard to education in women. Change in biomedical factors and employment did not amend the explanation. Conclusions Addition of a second measurement for risk factors provided only a modest improvement in explaining educational and income inequalities in mortality in Norwegian men and women. Accounting for change in behavior provided the largest improvement in explained inequalities in mortality for both men and women, as compared to measurement at baseline. Psychosocial factors explained the largest share of income

Insight, psychopathology, explanatory models and outcome of schizophrenia in India: a prospective 5-year cohort study.

PubMed

Johnson, Shanthi; Sathyaseelan, Manoranjitham; Charles, Helen; Jeyaseelan, Visalakshi; Jacob, Kuruthukulangara Sebastian

2012-09-27

The sole focus of models of insight on bio-medical perspectives to the complete exclusion of local, non-medical and cultural constructs mandates review. This study attempted to investigate the impact of insight, psychopathology, explanatory models of illness on outcome of first episode schizophrenia. Patients diagnosed to have DSM IV schizophrenia (n = 131) were assessed prospectively for insight, psychopathology, explanatory models of illness at baseline, 6, 12 and 60 months using standard instruments. Multiple linear and logistic regression and generalized estimating equations (GEE) were employed to assess predictors of outcome. We could follow up 95 (72.5%) patients. Sixty-five of these patients (68.4%) achieved remission. There was a negative relationship between psychosis rating and insight scores. Urban residence, fluctuating course of the initial illness, and improvement in global functioning at 6 months and lower psychosis rating at 12 months were significantly related to remission at 5 years. Insight scores, number of non-medical explanatory models and individual explanatory models held during the later course of the illness were significantly associated with outcome. Analysis of longitudinal data using GEE showed that women, rural residence, insight scores and number of non-medical explanatory models of illness held were significantly associated with BPRS scores during the study period. Insight, the disease model and the number of non-medical model positively correlated with improvement in psychosis arguing for a complex interaction between the culture, context and illness variables. These finding argue that insight and explanatory models are secondary to psychopathology, course and outcome of the illness. The awareness of mental illness is a narrative act in which people make personal sense of the many challenges they face. The course and outcome of the illness, cultural context, acceptable cultural explanations and the prevalent social stigma

Regression Analysis of Stage Variability for West-Central Florida Lakes

USGS Publications Warehouse

Sacks, Laura A.; Ellison, Donald L.; Swancar, Amy

2008-01-01

The variability in a lake's stage depends upon many factors, including surface-water flows, meteorological conditions, and hydrogeologic characteristics near the lake. An understanding of the factors controlling lake-stage variability for a population of lakes may be helpful to water managers who set regulatory levels for lakes. The goal of this study is to determine whether lake-stage variability can be predicted using multiple linear regression and readily available lake and basin characteristics defined for each lake. Regressions were evaluated for a recent 10-year period (1996-2005) and for a historical 10-year period (1954-63). Ground-water pumping is considered to have affected stage at many of the 98 lakes included in the recent period analysis, and not to have affected stage at the 20 lakes included in the historical period analysis. For the recent period, regression models had coefficients of determination (R2) values ranging from 0.60 to 0.74, and up to five explanatory variables. Standard errors ranged from 21 to 37 percent of the average stage variability. Net leakage was the most important explanatory variable in regressions describing the full range and low range in stage variability for the recent period. The most important explanatory variable in the model predicting the high range in stage variability was the height over median lake stage at which surface-water outflow would occur. Other explanatory variables in final regression models for the recent period included the range in annual rainfall for the period and several variables related to local and regional hydrogeology: (1) ground-water pumping within 1 mile of each lake, (2) the amount of ground-water inflow (by category), (3) the head gradient between the lake and the Upper Floridan aquifer, and (4) the thickness of the intermediate confining unit. Many of the variables in final regression models are related to hydrogeologic characteristics, underscoring the importance of ground

An Explanatory Model of Self-Service on the Internet

NASA Astrophysics Data System (ADS)

Oliver, Dave; Livermore, Celia Romm; Farag, Neveen Awad

This chapter describes research that identifies and classifies the dimensions of self-service activity enabled through the Internet. Self-service is effected by organizations providing ways and means whereby customers perform tasks related to the procurement of goods and services. We describe how an instrument used to measure Internet-based self-service was developed, validated and applied. The results from applying the instrument to a large number of Web sites, covering a range of industries, countries and cultures, are analyzed and discussed. The study presents a model in which type of industry, level of technological development, income and cultural factors are proposed as explanatory variables for Web-based self-service. We conclude with an assessment of this program of research’s achievements so far.

Racialized customer service in restaurants: a quantitative assessment of the statistical discrimination explanatory framework.

PubMed

Brewster, Zachary W

2012-01-01

Despite popular claims that racism and discrimination are no longer salient issues in contemporary society, racial minorities continue to experience disparate treatment in everyday public interactions. The context of full-service restaurants is one such public setting wherein racial minority patrons, African Americans in particular, encounter racial prejudices and discriminate treatment. To further understand the causes of such discriminate treatment within the restaurant context, this article analyzes primary survey data derived from a community sample of servers (N = 200) to assess the explanatory power of one posited explanation—statistical discrimination. Taken as a whole, findings suggest that while a statistical discrimination framework toward understanding variability in servers’ discriminatory behaviors should not be disregarded, the framework’s explanatory utility is limited. Servers’ inferences about the potential profitability of waiting on customers across racial groups explain little of the overall variation in subjects’ self-reported discriminatory behaviors, thus suggesting that other factors not explored in this research are clearly operating and should be the focus of future inquires.

Determinants of Judgments of Explanatory Power: Credibility, Generality, and Statistical Relevance

PubMed Central

Colombo, Matteo; Bucher, Leandra; Sprenger, Jan

2017-01-01

Explanation is a central concept in human psychology. Drawing upon philosophical theories of explanation, psychologists have recently begun to examine the relationship between explanation, probability and causality. Our study advances this growing literature at the intersection of psychology and philosophy of science by systematically investigating how judgments of explanatory power are affected by (i) the prior credibility of an explanatory hypothesis, (ii) the causal framing of the hypothesis, (iii) the perceived generalizability of the explanation, and (iv) the relation of statistical relevance between hypothesis and evidence. Collectively, the results of our five experiments support the hypothesis that the prior credibility of a causal explanation plays a central role in explanatory reasoning: first, because of the presence of strong main effects on judgments of explanatory power, and second, because of the gate-keeping role it has for other factors. Highly credible explanations are not susceptible to causal framing effects, but they are sensitive to the effects of normatively relevant factors: the generalizability of an explanation, and its statistical relevance for the evidence. These results advance current literature in the philosophy and psychology of explanation in three ways. First, they yield a more nuanced understanding of the determinants of judgments of explanatory power, and the interaction between these factors. Second, they show the close relationship between prior beliefs and explanatory power. Third, they elucidate the nature of abductive reasoning. PMID:28928679

Determinants of Judgments of Explanatory Power: Credibility, Generality, and Statistical Relevance.

PubMed

Colombo, Matteo; Bucher, Leandra; Sprenger, Jan

2017-01-01

Explanation is a central concept in human psychology. Drawing upon philosophical theories of explanation, psychologists have recently begun to examine the relationship between explanation, probability and causality. Our study advances this growing literature at the intersection of psychology and philosophy of science by systematically investigating how judgments of explanatory power are affected by (i) the prior credibility of an explanatory hypothesis, (ii) the causal framing of the hypothesis, (iii) the perceived generalizability of the explanation, and (iv) the relation of statistical relevance between hypothesis and evidence. Collectively, the results of our five experiments support the hypothesis that the prior credibility of a causal explanation plays a central role in explanatory reasoning: first, because of the presence of strong main effects on judgments of explanatory power, and second, because of the gate-keeping role it has for other factors. Highly credible explanations are not susceptible to causal framing effects, but they are sensitive to the effects of normatively relevant factors: the generalizability of an explanation, and its statistical relevance for the evidence. These results advance current literature in the philosophy and psychology of explanation in three ways. First, they yield a more nuanced understanding of the determinants of judgments of explanatory power, and the interaction between these factors. Second, they show the close relationship between prior beliefs and explanatory power. Third, they elucidate the nature of abductive reasoning.

Examining Explanatory Style's Relationship to Efficacy and Burnout in Teachers

ERIC Educational Resources Information Center

Fineburg, Amy Cheek

2010-01-01

Explanatory style, the ways in which people explain both good and bad events (Seligman, 1998), shares theoretical components with teachers' sense of efficacy (Tshannon-Moran & Woolfolk-Hoy, 2001), which is how capable teachers feel about teaching. According to Bandura (1994), efficacy informs explanatory style, but this assertion does not…

Children with Autism Spectrum Disorder Have an Exceptional Explanatory Drive

ERIC Educational Resources Information Center

Rutherford, M. D.; Subiaul, Francys

2016-01-01

An "explanatory drive" motivates children to explain ambiguity. Individuals with autism spectrum disorders are interested in how systems work, but it is unknown whether they have an explanatory drive. We presented children with and without autism spectrum disorder unsolvable problems in a physical and in a social context and evaluated…

Modelling Analysis of Students' Processes of Generating Scientific Explanatory Hypotheses

ERIC Educational Resources Information Center

Park, Jongwon

2006-01-01

It has recently been determined that generating an explanatory hypothesis to explain a discrepant event is important for students' conceptual change. The purpose of this study is to investigate how students' generate new explanatory hypotheses. To achieve this goal, questions are used to identify students prior ideas related to electromagnetic…

Exploring the explaining quality of physics online explanatory videos

NASA Astrophysics Data System (ADS)

Kulgemeyer, Christoph; Peters, Cord H.

2016-11-01

Explaining skills are among the most important skills educators possess. Those skills have also been researched in recent years. During the same period, another medium has additionally emerged and become a popular source of information for learners: online explanatory videos, chiefly from the online video sharing website YouTube. Their content and explaining quality remain to this day mostly unmonitored, as well is their educational impact in formal contexts such as schools or universities. In this study, a framework for explaining quality, which has emerged from surveying explaining skills in expert-novice face-to-face dialogues, was used to explore the explaining quality of such videos (36 YouTube explanatory videos on Kepler’s laws and 15 videos on Newton’s third law). The framework consists of 45 categories derived from physics education research that deal with explanation techniques. YouTube provides its own ‘quality measures’ based on surface features including ‘likes’, views, and comments for each video. The question is whether or not these measures provide valid information for educators and students if they have to decide which video to use. We compared the explaining quality with those measures. Our results suggest that there is a correlation between explaining quality and only one of these measures: the number of content-related comments.

VARIABLE SELECTION IN NONPARAMETRIC ADDITIVE MODELS

PubMed Central

Huang, Jian; Horowitz, Joel L.; Wei, Fengrong

2010-01-01

We consider a nonparametric additive model of a conditional mean function in which the number of variables and additive components may be larger than the sample size but the number of nonzero additive components is “small” relative to the sample size. The statistical problem is to determine which additive components are nonzero. The additive components are approximated by truncated series expansions with B-spline bases. With this approximation, the problem of component selection becomes that of selecting the groups of coefficients in the expansion. We apply the adaptive group Lasso to select nonzero components, using the group Lasso to obtain an initial estimator and reduce the dimension of the problem. We give conditions under which the group Lasso selects a model whose number of components is comparable with the underlying model, and the adaptive group Lasso selects the nonzero components correctly with probability approaching one as the sample size increases and achieves the optimal rate of convergence. The results of Monte Carlo experiments show that the adaptive group Lasso procedure works well with samples of moderate size. A data example is used to illustrate the application of the proposed method. PMID:21127739

Uni- and multi-variable modelling of flood losses: experiences gained from the Secchia river inundation event.

NASA Astrophysics Data System (ADS)

Carisi, Francesca; Domeneghetti, Alessio; Kreibich, Heidi; Schröter, Kai; Castellarin, Attilio

2017-04-01

Flood risk is function of flood hazard and vulnerability, therefore its accurate assessment depends on a reliable quantification of both factors. The scientific literature proposes a number of objective and reliable methods for assessing flood hazard, yet it highlights a limited understanding of the fundamental damage processes. Loss modelling is associated with large uncertainty which is, among other factors, due to a lack of standard procedures; for instance, flood losses are often estimated based on damage models derived in completely different contexts (i.e. different countries or geographical regions) without checking its applicability, or by considering only one explanatory variable (i.e. typically water depth). We consider the Secchia river flood event of January 2014, when a sudden levee-breach caused the inundation of nearly 200 km2 in Northern Italy. In the aftermath of this event, local authorities collected flood loss data, together with additional information on affected private households and industrial activities (e.g. buildings surface and economic value, number of company's employees and others). Based on these data we implemented and compared a quadratic-regression damage function, with water depth as the only explanatory variable, and a multi-variable model that combines multiple regression trees and considers several explanatory variables (i.e. bagging decision trees). Our results show the importance of data collection revealing that (1) a simple quadratic regression damage function based on empirical data from the study area can be significantly more accurate than literature damage-models derived for a different context and (2) multi-variable modelling may outperform the uni-variable approach, yet it is more difficult to develop and apply due to a much higher demand of detailed data.

Older Men's Explanatory Model for Osteoporosis

ERIC Educational Resources Information Center

Solimeo, Samantha L.; Weber, Thomas J.; Gold, Deborah T.

2011-01-01

Purpose: To explore the nature of men's experiences of osteoporosis by developing an understanding of men's explanatory models. Design and Methods: This descriptive study invited community-residing male osteoporosis patients aged 50+ to participate in interviews about osteoporosis. Participants were recruited from a hospital-affiliated bone…

Bayesian Adaptive Lasso for Ordinal Regression with Latent Variables

ERIC Educational Resources Information Center

Feng, Xiang-Nan; Wu, Hao-Tian; Song, Xin-Yuan

2017-01-01

We consider an ordinal regression model with latent variables to investigate the effects of observable and latent explanatory variables on the ordinal responses of interest. Each latent variable is characterized by correlated observed variables through a confirmatory factor analysis model. We develop a Bayesian adaptive lasso procedure to conduct…

Explaining and Selecting Treatments for Autism: Parental Explanatory Models in Taiwan

ERIC Educational Resources Information Center

Shyu, Yea-Ing Lotus; Tsai, Jia-Ling; Tsai, Wen-Che

2010-01-01

Parental explanatory models about autism influence the type of therapy a child receives, the child's well-being, and the parents' own psychological adaptation. This qualitative study explored explanatory models used by parents of children with autism. In-depth interviews were conducted with 13 parents of children with autism from a medical center…

Pathological Left-Handedness: An Explanatory Model.

ERIC Educational Resources Information Center

Satz, Paul

Reported was an explanatory conceptual model for pathological left-handedness (PLH) and related hypotheses, some of which could not be tested empirically due to lack of information. The model was reported to provide an explanation for the relationship between handedness and specific learning disability, and handedness and cerebral dominance for…

Explanatory Supplement to the AllWISE Data Release Products

NASA Astrophysics Data System (ADS)

Cutri, R. M.; Wright, E. L.; Conrow, T.; Fowler, J. W.; Eisenhardt, P. R. M.; Grillmair, C.; Kirkpatrick, J. D.; Masci, F.; McCallon, H. L.; Wheelock, S. L.; Fajardo-Acosta, S.; Yan, L.; Benford, D.; Harbut, M.; Jarrett, T.; Lake, S.; Leisawitz, D.; Ressler, M. E.; Stanford, S. A.; Tsai, C. W.; Liu, F.; Helou, G.; Mainzer, A.; Gettings, D.; Gonzalez, A.; Hoffman, D.; Marsh, K. A.; Padgett, D.; Skrutskie, M. F.; Beck, R. P.; Papin, M.; Wittman, M.

2013-11-01

The AllWISE program builds upon the successful Wide-field Infrared Survey Explorer (WISE; Wright et al. 2010) mission by combining data from all WISE and NEOWISE (Mainzer et al. 2011) survey phases to form the most comprehensive view of the mid-infrared sky currently available. By combining the data from two complete sky coverage epochs in an advanced data processing system, AllWISE has generated new products that have enhanced photometric sensitivity and accuracy, and improved astrometric precision compared with the earlier WISE All-Sky Data Release. Exploiting the 6 month baseline between the WISE sky coverage epochs enables AllWISE to measure source motions for the first time, and to compute improved flux variability statistics. AllWISE data release products include: a Source Catalog that contains 4-band fluxes, positions, apparent motion measurements, and flux variability statistics for over 747 million objects detected at SNR>5 in the combined exposures; a Multiepoch Photometry Database containing over 42 billion time-tagged, single-exposure fluxes for each object detected on the combined exposures; and an Image Atlas of 18,240 4-band calibrated FITS images, depth-of-coverage and noise maps that cover the sky produced by coadding nearly 7.9 million single-exposure images from the cryogenic and post-cryogenic survey phases. The Explanatory Supplement to the AllWISE Data Release Products is a general guide for users of the AllWISE data. The Supplement contains detailed descriptions of the format and characteristics of the AllWISE data products, as well as a summary of cautionary notes that describe known limitations. The Supplement is an on-line document that is updated frequently to provide the most current information for users of the AllWISE data products. The Explanatory Supplement is maintained at: http://wise2.ipac.caltech.edu/docs/release/allwise/expsup/index.html AllWISE makes use of data from WISE, which is a joint project of the University of

How Robust Is Linear Regression with Dummy Variables?

ERIC Educational Resources Information Center

Blankmeyer, Eric

2006-01-01

Researchers in education and the social sciences make extensive use of linear regression models in which the dependent variable is continuous-valued while the explanatory variables are a combination of continuous-valued regressors and dummy variables. The dummies partition the sample into groups, some of which may contain only a few observations.…

Examining the Value of a Scaffolded Critique Framework to Promote Argumentative and Explanatory Writings Within an Argument-Based Inquiry Approach

NASA Astrophysics Data System (ADS)

Jang, Jeong-yoon; Hand, Brian

2017-12-01

This study investigated the value of using a scaffolded critique framework to promote two different types of writing—argumentative writing and explanatory writing—with different purposes within an argument-based inquiry approach known as the Science Writing Heuristic (SWH) approach. A quasi-experimental design with sixth and seventh grade students taught by two teachers was used. A total of 170 students participated in the study, with 87 in the control group (four classes) and 83 in the treatment group (four classes). All students used the SWH templates as an argumentative writing to guide their written work and completed these templates during the SWH investigations of each unit. After completing the SWH investigations, both groups of students were asked to complete the summary writing task as an explanatory writing at the end of each unit. All students' writing samples were scored using analytical frameworks developed for the study. The results indicated that the treatment group performed significantly better on the explanatory writing task than the control group. In addition, the results of the partial correlation suggested that there is a very strong significantly positive relationship between the argumentative writing and the explanatory writing.

How is the Ideal Gas Law Explanatory?

NASA Astrophysics Data System (ADS)

Woody, Andrea I.

2013-07-01

Using the ideal gas law as a comparative example, this essay reviews contemporary research in philosophy of science concerning scientific explanation. It outlines the inferential, causal, unification, and erotetic conceptions of explanation and discusses an alternative project, the functional perspective. In each case, the aim is to highlight insights from these investigations that are salient for pedagogical concerns. Perhaps most importantly, this essay argues that science teachers should be mindful of the normative and prescriptive components of explanatory discourse both in the classroom and in science more generally. Giving attention to this dimension of explanation not only will do justice to the nature of explanatory activity in science but also will support the development of robust reasoning skills in science students while helping them understand an important respect in which science is more than a straightforward collection of empirical facts, and consequently, science education involves more than simply learning them.

Explanatory chapter: introducing exogenous DNA into cells.

PubMed

Koontz, Laura

2013-01-01

The ability to efficiently introduce DNA into cells is essential for many experiments in biology. This is an explanatory chapter providing an overview of the various methods for introducing DNA into bacteria, yeast, and mammalian cells. Copyright © 2013 Elsevier Inc. All rights reserved.

Validation of an explanatory tool for data-fused displays for high-technology future aircraft

NASA Astrophysics Data System (ADS)

Fletcher, Georgina C. L.; Shanks, Craig R.; Selcon, Stephen J.

1996-05-01

As the number of sensor and data sources in the military cockpit increases, pilots will suffer high levels of workload which could result in reduced performance and the loss of situational awareness. A DRA research program has been investigating the use of data-fused displays in decision support and has developed and laboratory-tested an explanatory tool for displaying information in air combat scenarios. The tool has been designed to provide pictorial explanations of data that maintain situational awareness by involving the pilot in the hostile aircraft threat assessment task. This paper reports a study carried out to validate the success of the explanatory tool in a realistic flight simulation facility. Aircrew were asked to perform a threat assessment task, either with or without the explanatory tool providing information in the form of missile launch success zone envelopes, while concurrently flying a waypoint course within set flight parameters. The results showed that there was a significant improvement (p less than 0.01) in threat assessment accuracy of 30% when using the explanatory tool. This threat assessment performance advantage was achieved without a trade-off with flying task performance. Situational awareness measures showed no general differences between the explanatory and control conditions, but significant learning effects suggested that the explanatory tool makes the task initially more intuitive and hence less demanding on the pilots' attentional resources. The paper concludes that DRA's data-fused explanatory tool is successful at improving threat assessment accuracy in a realistic simulated flying environment, and briefly discusses the requirements for further research in the area.

Explanatory Unification by Proofs in School Mathematics

ERIC Educational Resources Information Center

Komatsu, Kotaro; Fujita, Taro; Jones, Keith; Naoki, Sue

2018-01-01

Kitcher's idea of 'explanatory unification', while originally proposed in the philosophy of science, may also be relevant to mathematics education, as a way of enhancing student thinking and achieving classroom activity that is closer to authentic mathematical practice. There is, however, no mathematics education research treating explanatory…

29 CFR 780.1001 - General explanatory statement.

Code of Federal Regulations, 2010 CFR

2010-07-01

... Employment of Home- workers in Making Wreaths; Exemption From Minimum Wage, Overtime Compensation, and Child... 29 Labor 3 2010-07-01 2010-07-01 false General explanatory statement. 780.1001 Section 780.1001 Labor Regulations Relating to Labor (Continued) WAGE AND HOUR DIVISION, DEPARTMENT OF LABOR STATEMENTS...

Soil Cd, Cr, Cu, Ni, Pb and Zn sorption and retention models using SVM: Variable selection and competitive model.

PubMed

González Costa, J J; Reigosa, M J; Matías, J M; Covelo, E F

2017-09-01

The aim of this study was to model the sorption and retention of Cd, Cu, Ni, Pb and Zn in soils. To that extent, the sorption and retention of these metals were studied and the soil characterization was performed separately. Multiple stepwise regression was used to produce multivariate models with linear techniques and with support vector machines, all of which included 15 explanatory variables characterizing soils. When the R-squared values are represented, two different groups are noticed. Cr, Cu and Pb sorption and retention show a higher R-squared; the most explanatory variables being humified organic matter, Al oxides and, in some cases, cation-exchange capacity (CEC). The other group of metals (Cd, Ni and Zn) shows a lower R-squared, and clays are the most explanatory variables, including a percentage of vermiculite and slime. In some cases, quartz, plagioclase or hematite percentages also show some explanatory capacity. Support Vector Machine (SVM) regression shows that the different models are not as regular as in multiple regression in terms of number of variables, the regression for nickel adsorption being the one with the highest number of variables in its optimal model. On the other hand, there are cases where the most explanatory variables are the same for two metals, as it happens with Cd and Cr adsorption. A similar adsorption mechanism is thus postulated. These patterns of the introduction of variables in the model allow us to create explainability sequences. Those which are the most similar to the selectivity sequences obtained by Covelo (2005) are Mn oxides in multiple regression and change capacity in SVM. Among all the variables, the only one that is explanatory for all the metals after applying the maximum parsimony principle is the percentage of sand in the retention process. In the competitive model arising from the aforementioned sequences, the most intense competitiveness for the adsorption and retention of different metals appears between

Exhaustive Search for Sparse Variable Selection in Linear Regression

NASA Astrophysics Data System (ADS)

Igarashi, Yasuhiko; Takenaka, Hikaru; Nakanishi-Ohno, Yoshinori; Uemura, Makoto; Ikeda, Shiro; Okada, Masato

2018-04-01

We propose a K-sparse exhaustive search (ES-K) method and a K-sparse approximate exhaustive search method (AES-K) for selecting variables in linear regression. With these methods, K-sparse combinations of variables are tested exhaustively assuming that the optimal combination of explanatory variables is K-sparse. By collecting the results of exhaustively computing ES-K, various approximate methods for selecting sparse variables can be summarized as density of states. With this density of states, we can compare different methods for selecting sparse variables such as relaxation and sampling. For large problems where the combinatorial explosion of explanatory variables is crucial, the AES-K method enables density of states to be effectively reconstructed by using the replica-exchange Monte Carlo method and the multiple histogram method. Applying the ES-K and AES-K methods to type Ia supernova data, we confirmed the conventional understanding in astronomy when an appropriate K is given beforehand. However, we found the difficulty to determine K from the data. Using virtual measurement and analysis, we argue that this is caused by data shortage.

Academic Judgment and Institutional Evaluation Made by Teachers According to Pupils' Explanatory Activity

ERIC Educational Resources Information Center

Jouffre, Stephane; Py, Jacques; Somat, Alain

2008-01-01

The influence of sixth-graders' explanatory activity was studied on their teachers' academic judgment. Concerning the pupils' explanatory activity, trait-related internal explanations were chosen more to explain positive events than negative ones, whereas the reverse was observed for effort/intention-related internal explanations. In response to…

Coping with Stress and Types of Burnout: Explanatory Power of Different Coping Strategies

PubMed Central

Montero-Marin, Jesus; Prado-Abril, Javier; Piva Demarzo, Marcelo Marcos; Gascon, Santiago; García-Campayo, Javier

2014-01-01

Background Burnout occurs when professionals use ineffective coping strategies to try to protect themselves from work-related stress. The dimensions of ‘overload’, ‘lack of development’ and ‘neglect’, belonging to the ‘frenetic’, ‘under-challenged’ and ‘worn-out’ subtypes, respectively, comprise a brief typological definition of burnout. The aim of the present study was to estimate the explanatory power of the different coping strategies on the development of burnout subtypes. Methods This was a cross-sectional survey with a random sample of university employees, stratified by occupation (n = 429). Multivariate linear regression models were constructed between the ‘Burnout Clinical Subtypes Questionnaire’, with its three dimensions –overload, lack of development and neglect– as dependent variables, and the ‘Coping Orientation for Problem Experiences’, with its fifteen dimensions, as independent variables. Adjusted multiple determination coefficients and beta coefficients were calculated to evaluate and compare the explanatory capacity of the different coping strategies. Results The ‘Coping Orientation for Problem Experiences’ subscales together explained 15% of the ‘overload’ (p<0.001), 9% of the ‘lack of development’ (p<0.001), and 21% of the ‘neglect’ (p<0.001). ‘Overload’ was mainly explained by ‘venting of emotions’ (Beta = 0.34; p<0.001); ‘lack of development’ by ‘cognitive avoidance’ (Beta = 0.21; p<0.001); and ‘neglect’ by ‘behavioural disengagement’ (Beta = 0.40; p<0.001). Other interesting associations were observed. Conclusions These findings further our understanding of the way in which the effectiveness of interventions for burnout may be improved, by influencing new treatments and preventive programmes using features of the strategies for handling stress in the workplace. PMID:24551223

Computer-mediated communication and interpersonal attraction: an experimental test of two explanatory hypotheses.

PubMed

Antheunis, Marjolijn L; Valkenburg, Patti M; Peter, Jochen

2007-12-01

The aims of this study were (a) to investigate the influence of computer-mediated communication (CMC) on interpersonal attraction and (b) to examine two underlying processes in the CMC-interpersonal attraction relationship. We identified two variables that may mediate the influence of CMC on interpersonal attraction: self-disclosure and direct questioning. Focusing on these potential mediating variables, we tested two explanatory hypotheses: the CMC-induced direct questioning hypothesis and the CMC-induced self-disclosure hypothesis. Eighty-one cross-sex dyads were randomly assigned to one of three experimental conditions: text-only CMC, visual CMC, and face-to-face communication. We did not find a direct effect of CMC on interpersonal attraction. However, we did find two positive indirect effects of text-only CMC on interpersonal attraction: text-only CMC stimulated both self-disclosure and direct questioning, both of which in turn enhanced interpersonal attraction. Results are discussed in light of uncertainty reduction theory and CMC theories.

Explanatory factors and predictors of fatigue in persons with rheumatoid arthritis: A longitudinal study.

PubMed

Feldthusen, Caroline; Grimby-Ekman, Anna; Forsblad-d'Elia, Helena; Jacobsson, Lennart; Mannerkorpi, Kaisa

2016-04-28

To investigate the impact of disease-related aspects on long-term variations in fatigue in persons with rheumatoid arthritis. Observational longitudinal study. Sixty-five persons with rheumatoid arthritis, age range 20-65 years, were invited to a clinical examination at 4 time-points during the 4 seasons. Outcome measures were: general fatigue rated on visual analogue scale (0-100) and aspects of fatigue assessed by the Bristol Rheumatoid Arthritis Fatigue Multidimensional Questionnaire. Disease-related variables were: disease activity (erythrocyte sedimentation rate), pain threshold (pressure algometer), physical capacity (six-minute walk test), pain (visual analogue scale (0-100)), depressive mood (Hospital Anxiety and Depression scale, depression subscale), personal factors (age, sex, body mass index) and season. Multivariable regression analysis, linear mixed effects models were applied. The strongest explanatory factors for all fatigue outcomes, when recorded at the same time-point as fatigue, were pain threshold and depressive mood. Self-reported pain was an explanatory factor for physical aspects of fatigue and body mass index contributed to explaining the consequences of fatigue on everyday living. For predicting later fatigue pain threshold and depressive mood were the strongest predictors. Pain threshold and depressive mood were the most important factors for fatigue in persons with rheumatoid arthritis.

Understanding burnout according to individual differences: ongoing explanatory power evaluation of two models for measuring burnout types

PubMed Central

2012-01-01

Background The classic determination of burnout is by means of the dimensions exhaustion, cynicism and inefficacy. A new definition of the syndrome is based on clinical subtypes, consisting of “frenetic” (involved, ambitious, overloaded), “underchallenged” (indifferent, bored, with lack of personal development) and “worn-out” (neglectful, unacknowledged, with little control). The dimensions of overload, lack of development and neglect form a shortened version of this perspective. The aims of this study were to estimate and to compare the explanatory power of both typological models, short and long, with the standard measurement. Methods This was a cross-sectional survey with a randomly sample of university employees (n=409). Multivariate linear regression models were constructed between the “Maslach Burnout Inventory General Survey” (MBI-GS) dimensions, as dependent variables, and the “Burnout Clinical Subtype Questionnaire” (BCSQ-36 and BCSQ-12) dimensions, as independent variables. Results The BCSQ-36 subscales together explained 53% of ‘exhaustion’ (p<0.001), 59% of ‘cynicism’ (p<0.001) and 37% of ‘efficacy’ (p<0.001), while BCSQ-12 subscales explained 44% of ‘exhaustion’ (p<0.001), 44% of ‘cynicism’ (p<0.001), and 30% of ‘efficacy’ (p<0.001). The difference in the explanatory power of both models was significant for ‘exhaustion’ (p<0.001), and for ‘cynicism’ (p<0.001) and ‘efficacy (p<0.001). Conclusions Both BCSQ-36 and BCSQ-12 demonstrate great explanatory power over the standard MBI-GS, while offering a useful characterization of the syndrome for the evaluation and design of interventions tailored to the characteristics of each individual. The BCSQ-36 may be very useful in mental health services, given that it provides a good deal of information, while the BCSQ-12 could be used as a screening measure in primary care consultations owing to its simplicity and functional nature. PMID:23110723

A Sensory Material Approach for Reducing Variability in Additively Manufactured Metal Parts.

PubMed

Franco, B E; Ma, J; Loveall, B; Tapia, G A; Karayagiz, K; Liu, J; Elwany, A; Arroyave, R; Karaman, I

2017-06-15

Despite the recent growth in interest for metal additive manufacturing (AM) in the biomedical and aerospace industries, variability in the performance, composition, and microstructure of AM parts remains a major impediment to its widespread adoption. The underlying physical mechanisms, which cause variability, as well as the scale and nature of variability are not well understood, and current methods are ineffective at capturing these details. Here, a Nickel-Titanium alloy is used as a sensory material in order to quantitatively, and rather rapidly, observe compositional and/or microstructural variability in selective laser melting manufactured parts; thereby providing a means to evaluate the role of process parameters on the variability. We perform detailed microstructural investigations using transmission electron microscopy at various locations to reveal the origins of microstructural variability in this sensory material. This approach helped reveal how reducing the distance between adjacent laser scans below a critical value greatly reduces both the in-sample and sample-to-sample variability. Microstructural investigations revealed that when the laser scan distance is wide, there is an inhomogeneity in subgrain size, precipitate distribution, and dislocation density in the microstructure, responsible for the observed variability. These results provide an important first step towards understanding the nature of variability in additively manufactured parts.

Adapting the concept of explanatory models of illness to the study of youth violence.

PubMed

Biering, Páll

2007-07-01

This study explores the feasibility of adapting Kleinman's concept of explanatory models of illness to the study of youth violence and is conducted within the hermeneutic tradition. Data were collected by interviewing 11 violent adolescents, their parents, and their caregivers. Four types of explanatory models representing the adolescent girls', the adolescent boys', the caregivers', and the parents' understanding of youth violence are found; they correspond sufficiently to Kleinman's concept and establish the feasibility of adapting it to the study of youth violence. The developmental nature of the parents' and adolescents' models makes it feasible to study them by means of hermeneutic methodology. There are some clinically significant discrepancies between the caregivers' and the clients' explanatory models; identifying such discrepancies is an essential step in the process of breaking down barriers to therapeutic communications. Violent adolescents should be encouraged to define their own explanatory models of violence through dialogue with their caregivers.

Explanatory models in patients with first episode depression: a study from north India.

PubMed

Grover, Sandeep; Kumar, Vineet; Chakrabarti, Subho; Hollikatti, Prabhakar; Singh, Pritpal; Tyagi, Shikha; Kulhara, Parmanand; Avasthi, Ajit

2012-09-01

The purpose of this work was to study the explanatory models of patients with first episode depression presenting to a tertiary care hospital located in North-western India. One hundred sixty four consecutive patients with diagnosis of first episode depression (except severe depression with psychotic symptoms) according to the International Classification of Diseases-10th Revision (ICD-10) and ≥18 years of age were evaluated for their explanatory models using the causal models section of Explanatory Model Interview Catalogue (EMIC). The most common explanations given were categorized into Karma-deed-heredity category (77.4%), followed by psychological explanations (62.2%), weakness (50%) and social causes (40.2%). Among the various specific causes the commonly reported explanations by at least one-fourth of the sample in decreasing order were: will of god (51.2%), fate/chance (40.9%), weakness of nerves (37.8%), general weakness (34.7%), bad deeds (26.2%), evil eye (24.4%) and family problems (21.9%). There was some influence of sociodemographic features on the explanations given by the patients. From the study, it can be concluded that patients with first episode depression have multiple explanatory models for their symptoms of depression which are slightly different than those reported in previous studies done from other parts of India. Understanding the multiple explanatory models for their symptoms of depression can have important treatment implications. Copyright © 2012 Elsevier B.V. All rights reserved.

Categorization and Analysis of Explanatory Writing in Mathematics

ERIC Educational Resources Information Center

Craig, Tracy S.

2011-01-01

The aim of this article is to present a scheme for coding and categorizing students' written explanations of mathematical problem-solving activities. The scheme was used successfully within a study project carried out to determine whether student problem-solving behaviour could be positively affected by writing explanatory strategies to…

A Pessimistic Explanatory Style is Prognostic for Poor Lung Cancer Survival

PubMed Central

Novotny, Paul; Colligan, Robert C.; Szydlo, Daniel W.; Clark, Matthew M.; Rausch, Sarah; Wampfler, Jason; Sloan, Jeff A.; Yang, Ping

2010-01-01

Background Several studies have demonstrated the importance of personality constructs on health behaviors and health status. Having a pessimistic outlook has been related to negative health behaviors and higher mortality. However, the construct has not been well explored in cancer populations. Methods Survival time of 534 adults, who were diagnosed with lung cancer and had a pessimistic explanatory style, was examined. The patients had completed the Minnesota Multiphasic Personality Inventory (MMPI) approximately 18.2 years prior to receiving their lung cancer diagnosis. MMPI Optimism-Pessimism (PSM) scores were divided into high (60 or more) and low scores (less than 60), and log-rank tests and Kaplan-Meier curves were used to determine survival differences. Multivariate Cox models were used for assessing prognostic values of pessimism along with other known predictors for lung cancer survival outcome. Booting strapping of the survival models was used as a sensitivity analysis. Results At the time of lung cancer diagnosis, patients were on average 67 years old; 48% were female; 85% had non-small cell lung cancer (NSCLC); 15% had small cell lung cancer (SCLC); 30% were stage I; 4% were stage II; 31% were stage III/limited; and 35% were stage IV/extensive. Patients who exhibited a non-pessimistic explanatory style survived approximately six months longer than patients classified as having a pessimistic explanatory style. Conclusion Among lung cancer patients, those having a pessimistic explanatory style experienced less favorable survival outcome, which may be related to cancer treatment decisions. Further research in this area is warranted. PMID:20139778

Attachment Security Balances Perspectives: Effects of Security Priming on Highly Optimistic and Pessimistic Explanatory Styles.

PubMed

Deng, Yanhe; Yan, Mengge; Chen, Henry; Sun, Xin; Zhang, Peng; Zeng, Xianglong; Liu, Xiangping; Lye, Yue

2016-01-01

Highly optimistic explanatory style (HOES) and highly pessimistic explanatory style (HPES) are two maladaptive ways to explain the world and may have roots in attachment insecurity. The current study aims to explore the effects of security priming - activating supportive representations of attachment security - on ameliorating these maladaptive explanatory styles. 57 participants with HOES and 57 participants with HPES were randomized into security priming and control conditions. Their scores of overall optimistic attribution were measured before and after priming. Security priming had a moderating effect: the security primed HOES group exhibited lower optimistic attribution, while the security primed HPES group evinced higher scores of optimistic attribution. Furthermore, the security primed HOES group attributed positive outcomes more externally, while the security primed HPES group attributed successful results more internally. The results support the application of security priming interventions on maladaptive explanatory styles. Its potential mechanism and directions for future study are also discussed.

Consumer-operated service program members' explanatory models of mental illness and recovery.

PubMed

Hoy, Janet M

2014-10-01

Incorporating individuals' understandings and explanations of mental illness into service delivery offers benefits relating to increased service relevance and meaning. Existing research delineates explanatory models of mental illness held by individuals in home, outpatient, and hospital-based contexts; research on models held by those in peer-support contexts is notably absent. In this article, I describe themes identified within and across explanatory models of mental illness and recovery held by mental health consumers (N = 24) at one peer center, referred to as a consumer-operated service center (COSP). Participants held explanatory models inclusive of both developmental stressors and biomedical causes, consistent with a stress-diathesis model (although no participant explicitly referenced such). Explicit incorporation of stress-diathesis constructs into programming at this COSP offers the potential of increasing service meaning and relevance. Identifying and incorporating shared meanings across individuals' understandings of mental illness likewise can increase relevance and meaning for particular subgroups of service users. © The Author(s) 2014.

Examining Explanatory Biases in Young Children's Biological Reasoning

ERIC Educational Resources Information Center

Legare, Cristine H.; Gelman, Susan A.

2014-01-01

Despite the well-established literature on explanation in early childhood, little is known about what constrains children's explanations. State change and negative outcomes were examined as potential explanatory biases in the domain of naïve biology, extending upon previous work in the domain of naïve physics. In two studies, preschool children…

Explanatory Model for Sound Amplification in a Stethoscope

ERIC Educational Resources Information Center

Eshach, H.; Volfson, A.

2015-01-01

In the present paper we suggest an original physical explanatory model that explains the mechanism of the sound amplification process in a stethoscope. We discuss the amplification of a single pulse, a continuous wave of certain frequency, and finally we address the resonant frequencies. It is our belief that this model may provide students with…

Explanatory Typologies as a Nested Strategy of Inquiry: Combining Cross-Case and Within-Case Analyses

ERIC Educational Resources Information Center

Møller, Jørgen; Skaaning, Svend-Erik

2017-01-01

Explanatory typologies have recently experienced a renaissance as a research strategy for constructing and assessing causal explanations. However, both the new methodological works on explanatory typologies and the way such typologies have been used in practice have been affected by two shortcomings. First, no elaborate procedures for assessing…

Attributional (Explanatory) Thinking about Failure in New Achievement Settings

ERIC Educational Resources Information Center

Perry, Raymond P.; Stupnisky, Robert H.; Daniels, Lia M.; Haynes, Tara L.

2008-01-01

Attributional (explanatory) thinking involves the appraisal of factors that contribute to performance and is instrumental to motivation and goal striving. Little is understood, however, concerning attributional thinking when multiple causes are involved in the transition to new achievement settings. Our study examined such complex attributional…

Conceptual Resources in Self-Developed Explanatory Models: The Importance of Integrating Conscious and Intuitive Knowledge

ERIC Educational Resources Information Center

Cheng, Meng-Fei; Brown, David E.

2010-01-01

This study explores the spontaneous explanatory models children construct, critique, and revise in the context of tasks in which children need to predict, observe, and explain phenomena involving magnetism. It further investigates what conceptual resources students use, and in what ways they use them, to construct explanatory models, and the…

Peak flow regression equations For small, ungaged streams in Maine: Comparing map-based to field-based variables

USGS Publications Warehouse

Lombard, Pamela J.; Hodgkins, Glenn A.

2015-01-01

Regression equations to estimate peak streamflows with 1- to 500-year recurrence intervals (annual exceedance probabilities from 99 to 0.2 percent, respectively) were developed for small, ungaged streams in Maine. Equations presented here are the best available equations for estimating peak flows at ungaged basins in Maine with drainage areas from 0.3 to 12 square miles (mi2). Previously developed equations continue to be the best available equations for estimating peak flows for basin areas greater than 12 mi2. New equations presented here are based on streamflow records at 40 U.S. Geological Survey streamgages with a minimum of 10 years of recorded peak flows between 1963 and 2012. Ordinary least-squares regression techniques were used to determine the best explanatory variables for the regression equations. Traditional map-based explanatory variables were compared to variables requiring field measurements. Two field-based variables—culvert rust lines and bankfull channel widths—either were not commonly found or did not explain enough of the variability in the peak flows to warrant inclusion in the equations. The best explanatory variables were drainage area and percent basin wetlands; values for these variables were determined with a geographic information system. Generalized least-squares regression was used with these two variables to determine the equation coefficients and estimates of accuracy for the final equations.

Explanatory models and distress in primary caregivers of patients with acute psychotic presentations: A study from South India.

PubMed

Joy, Deepa S; Manoranjitham, S D; Samuel, P; Jacob, K S

2017-11-01

Emotional distress among caregivers of people with mental illness is common, changes overtime and requires appropriate coping strategies to prevent long-term disability. Explanatory models, which underpin understanding of disease and illness, are crucial to coping. To study the association of explanatory models and distress among caregivers of people with acute psychotic illness. A total of 60 consecutive patients and their primary caregivers who presented to the Department of Psychiatry, Christian Medical College, Vellore, were recruited for the study. Positive and Negative Syndrome Scale (PANSS), Short Explanatory Model Interview (SEMI) and the General Health Questionnaire-12 (GHQ-12) were used to assess severity of psychosis, explanatory models of illness and emotional distress. Standard bivariate and multivariable statistics were employed. Majority of the caregivers simultaneously held multiple models of illness, which included medical and non-medical perspectives. The GHQ-12 score were significantly lower in people who held multiple explanatory models of illness when compared to the caregivers who believed single explanations. Explanatory models affect coping in caregivers of patients with acute psychotic presentations. There is a need to have a broad-based approach to recovery and care.

The variability puzzle in human memory.

PubMed

Kahana, Michael J; Aggarwal, Eash V; Phan, Tung D

2018-04-26

Memory performance exhibits a high level of variability from moment to moment. Much of this variability may reflect inadequately controlled experimental variables, such as word memorability, past practice and subject fatigue. Alternatively, stochastic variability in performance may largely reflect the efficiency of endogenous neural processes that govern memory function. To help adjudicate between these competing views, the authors conducted a multisession study in which subjects completed 552 trials of a delayed free-recall task. Applying a statistical model to predict variability in each subject's recall performance uncovered modest effects of word memorability, proactive interference, and other variables. In contrast to the limited explanatory power of these experimental variables, performance on the prior list strongly predicted current list recall. These findings suggest that endogenous factors underlying successful encoding and retrieval drive variability in performance. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

Avoiding and Correcting Bias in Score-Based Latent Variable Regression with Discrete Manifest Items

ERIC Educational Resources Information Center

Lu, Irene R. R.; Thomas, D. Roland

2008-01-01

This article considers models involving a single structural equation with latent explanatory and/or latent dependent variables where discrete items are used to measure the latent variables. Our primary focus is the use of scores as proxies for the latent variables and carrying out ordinary least squares (OLS) regression on such scores to estimate…

The Health Belief Model as an Explanatory Framework in Communication Research: Exploring Parallel, Serial, and Moderated Mediation

PubMed Central

Jones, Christina L.; Jensen, Jakob D.; Scherr, Courtney L.; Brown, Natasha R.; Christy, Katheryn; Weaver, Jeremy

2015-01-01

The Health Belief Model (HBM) posits that messages will achieve optimal behavior change if they successfully target perceived barriers, benefits, self-efficacy, and threat. While the model seems to be an ideal explanatory framework for communication research, theoretical limitations have limited its use in the field. Notably, variable ordering is currently undefined in the HBM. Thus, it is unclear whether constructs mediate relationships comparably (parallel mediation), in sequence (serial mediation), or in tandem with a moderator (moderated mediation). To investigate variable ordering, adults (N = 1,377) completed a survey in the aftermath of an 8-month flu vaccine campaign grounded in the HBM. Exposure to the campaign was positively related to vaccination behavior. Statistical evaluation supported a model where the indirect effect of exposure on behavior through perceived barriers and threat was moderated by self-efficacy (moderated mediation). Perceived barriers and benefits also formed a serial mediation chain. The results indicate that variable ordering in the Health Belief Model may be complex, may help to explain conflicting results of the past, and may be a good focus for future research. PMID:25010519

Explanatory Style in Patients with Rheumatoid Arthritis: An Unrecognized Predictor of Mortality

PubMed Central

Crowson, Aaron D.; Colligan, Robert C.; Matteson, Eric L.; Davis, John M.; Crowson, Cynthia S.

2016-01-01

Objective To determine whether pessimistic explanatory style altered the risk for and mortality of rheumatoid arthritis (RA) patients. Methods The study included subjects from a population-based cohort with incident RA and non-RA comparison cohort who completed the Minnesota Multiphasic Personality Inventory (MMPI). Results Among 148 RA and 135 non-RA subjects, pessimism was associated with development of rheumatoid factor positive (RF+) RA. Pessimism was associated with an increased risk of mortality (hazard ratio [HR]:2.88 with similar magnitude to RF+ (HR:2.28). Conclusion Pessimistic explanatory style was associated with an increased risk of developing RA and increased mortality rate in patients with RA. PMID:28148754

Explanatory Supplement to the Astronomical Almanac (3rd Edition)

NASA Astrophysics Data System (ADS)

Urban, Sean E.; Seidelmann, P. K.

2014-01-01

Publications and software from the the Astronomical Applications Department of the US Naval Observatory (USNO) are used throughout the world, not only in the Department of Defense for safe navigation, but by many people including other navigators, astronomers, aerospace engineers, and geodesists. Products such as The Nautical Almanac, The Astronomical Almanac, and the Multiyear Interactive Computer Almanac (MICA) are regarded as international standards. To maintain credibility, it is imperative that the methodologies employed and the data used are well documented. "The Explanatory Supplement to the Astronomical Almanac" (hereafter, "The ES") is a major source of such documentation. It is a comprehensive reference book on positional astronomy, covering the theories and algorithms used to produce The Astronomical Almanac, an annual publication produced jointly by the Nautical Almanac Office of USNO and Her Majesty's Nautical Almanac Office (HMNAO). The first edition of The ES appeared in 1961, and the second followed in 1992. Several major changes have taken place in fundamental astronomy since the second edition was published. Advances in radio observations allowed the celestial reference frame to be tied to extragalactic radio sources, thus the International Celestial Reference System replaced the FK5 system. The success of ESA's Hipparcos satellite dramatically altered observational astrometry. Improvements in Earth orientation observations lead to new precession and nutation theories. Additionally, a new positional paradigm, no longer tied to the ecliptic and equinox, was accepted. Largely because of these changes, staff at USNO and HMNAO decided the time was right for the next edition of The ES. The third edition is now available; it is a complete revision of the 1992 book. Along with subjects covered in the previous two editions, the book also contains descriptions of the major advancements in positional astronomy over the last 20 years, some of which are

Does IQ explain socio-economic differentials in total and cardiovascular disease mortality? Comparison with the explanatory power of traditional cardiovascular disease risk factors in the Vietnam Experience Study.

PubMed

Batty, G David; Shipley, Martin J; Dundas, Ruth; Macintyre, Sally; Der, Geoff; Mortensen, Laust H; Deary, Ian J

2009-08-01

The aim of this study was to examine the explanatory power of intelligence (IQ) compared with traditional cardiovascular disease (CVD) risk factors in the relationship of socio-economic disadvantage with total and CVD mortality, that is the extent to which IQ may account for the variance in this well-documented association. Cohort study of 4289 US male former military personnel with data on four widely used markers of socio-economic position (early adulthood and current income, occupational prestige, and education), IQ test scores (early adulthood and middle-age), a range of nine established CVD risk factors (systolic and diastolic blood pressure, total blood cholesterol, HDL cholesterol, body mass index, smoking, blood glucose, resting heart rate, and forced expiratory volume in 1 s), and later mortality. We used the relative index of inequality (RII) to quantify the relation between each index of socio-economic position and mortality. Fifteen years of mortality surveillance gave rise to 237 deaths (62 from CVD and 175 from 'other' causes). In age-adjusted analyses, as expected, each of the four indices of socio-economic position was inversely associated with total, CVD, and 'other' causes of mortality, such that elevated rates were evident in the most socio-economically disadvantaged men. When IQ in middle-age was introduced to the age-adjusted model, there was marked attenuation in the RII across the socio-economic predictors for total mortality (average 50% attenuation in RII), CVD (55%), and 'other' causes of death (49%). When the nine traditional risk factors were added to the age-adjusted model, the comparable reduction in RII was less marked than that seen after IQ adjustment: all-causes (40%), CVD (40%), and 'other' mortality (43%). Adding IQ to the latter model resulted in marked, additional explanatory power for all outcomes in comparison to the age-adjusted analyses: all-causes (63%), CVD (63%), and 'other' mortality (65%). When we utilized IQ in early

Decreasing Cloudiness Over China: An Updated Analysis Examining Additional Variables

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

Kaiser, D.P.

2000-01-14

As preparation of the IPCC's Third Assessment Report takes place, one of the many observed climate variables of key interest is cloud amount. For several nations of the world, there exist records of surface-observed cloud amount dating back to the middle of the 20th Century or earlier, offering valuable information on variations and trends. Studies using such databases include Sun and Groisman (1999) and Kaiser and Razuvaev (1995) for the former Soviet Union, Angel1 et al. (1984) for the United States, Henderson-Sellers (1986) for Europe, Jones and Henderson-Sellers (1992) for Australia, and Kaiser (1998) for China. The findings of Kaisermore » (1998) differ from the other studies in that much of China appears to have experienced decreased cloudiness over recent decades (1954-1994), whereas the other land regions for the most part show evidence of increasing cloud cover. This paper expands on Kaiser (1998) by analyzing trends in additional meteorological variables for Chi na [station pressure (p), water vapor pressure (e), and relative humidity (rh)] and extending the total cloud amount (N) analysis an additional two years (through 1996).« less

'Hypotheses, everywhere only hypotheses!': on some contexts of Dilthey's critique of explanatory psychology.

PubMed

Feest, Uljana

2007-03-01

In 1894, Wilhelm Dilthey published an article in which he formulated a critique of what he called 'explanatory psychology', contrasting it with his own conception of 'descriptive psychology'. Dilthey's descriptive psychology, in turn, was to provide the basis for Dilthey's specific philosophy of the human sciences (Geisteswissenschaften). In this paper, I contextualize Dilthey's critique of explanatory psychology. I show that while this critique comes across as very broad and sweeping, he in fact had specific opponents in mind, namely, scholars who, like him, attempted to theorize about the relationship between the individual and society, between psychology and the other human sciences. Dilthey's critique of explanatory psychology is the flipside of his critique of sociology, which he had already formulated. He challenged both because he felt that they gave the wrong kind of answer to the task of overcoming metaphysics within the human sciences. In particular, I identify the founders of Völkerpsychologie, Moritz Lazarus and Heymann Steinthal, and (more importantly) their student, Georg Simmel, as Dilthey's targets. I provide textual and historical evidence for this thesis.

Explanatory Supplement to the WISE All-Sky Release Products

NASA Technical Reports Server (NTRS)

2012-01-01

The Wide-field Infrared Survey Explorer (WISE; Wright et al. 2010) surveyed the entire sky at 3.4, 4.6, 12 and 22 microns in 2010, achieving 5-sigma point source sensitivities per band better than 0.08, 0.11, 1 and 6 mJy in unconfused regions on the ecliptic. The WISE All-Sky Data Release, conducted on March 14, 2012, incorporates all data taken during the full cryogenic mission phase, 7 January 2010 to 6 August 20l0,that were processed with improved calibrations and reduction algorithms. Release data products include: (1) an Atlas of 18,240 match-filtered, calibrated and coadded image sets; (2) a Source Catalog containing positions and four-band photometry for over 563 million objects, and (3) an Explanatory Supplement. Ancillary products include a Reject Table that contains 284 million detections that were not selected for the Source Catalog because they are low signal-to-noise ratio or spurious detections of image artifacts, an archive of over 1.5 million sets of calibrated WISE Single-exposure images, and a database of 9.4 billion source extractions from those single images, and moving object tracklets identified by the NEOWISE program (Mainzer et aI. 2011). The WISE All-Sky Data Release products supersede those from the WISE Preliminary Data Release (Cutri et al. 2011). The Explanatory Supplement to the WISE All-Sky Data Release Products is a general guide for users of the WISE data. The Supplement contains an overview of the WISE mission, facilities, and operations, a detailed description of WISE data processing algorithms, a guide to the content and formals of the image and tabular data products, and cautionary notes that describe known limitations of the All-Sky Release products. Instructions for accessing the WISE data products via the services of the NASA/IPAC Infrared Science Archive are provided. The Supplement also provides analyses of the achieved sky coverage, photometric and astrometric characteristics and completeness and reliability of the All

Explanatory Models of Illness: A Study of Within-Culture Variation

ERIC Educational Resources Information Center

Lynch, Elizabeth; Medin, Douglas

2006-01-01

The current studies explore causal models of heart attack and depression generated from American healers whom use distinct explanatory frameworks. Causal chains leading to two illnesses, heart attack and depression, were elicited from participant groups: registered nurses (RNs), energy healers, RN energy healers, and undergraduates. The…

Using Students' Explanatory Models as Sources of Feedback: Conceptualizing Ocean Acidification and Its Impacts

NASA Astrophysics Data System (ADS)

Sezen-Barrie, A.; Stapleton, M.; Wolfson, J.

2017-12-01

This qualitative study focuses on students evidence-based explanatory models on how ocean acidification impacts oysters. Explanatory models are the crucial components of scientific endeavors as it helps scientists explain how the natural world functions and the reasons for the ways it functions. Moreover, these models assemble individual practices to understand how they work together to reach clear conclusions through scientific investigations. Due to their critical roles in making sense of authentic science, recent studies in science education suggest that these models should be part of the curriculum aligned with new science standards, i.e. Next Generation Science Standards, which stress the importance of engaging students in scientific practices. By collecting data from 400 secondary school students in Maryland, we aim to respond to the question: How can we use secondary school students' explanatory models to provide students with constructive feedback for more comprehensive learning of ocean acidification (the related evidence, causes and impact)? The data were analyzed through discourse analysis method. We highlighted and coded students' inscriptions (e.g., drawings, writings, and representations) that are signs of students' understanding (or lack thereof) of ocean acidification. These signs included explanations of pH levels, drawings of oyster growth, and inclusions of relevant data. The findings showed that the explanatory models can be critical forms of feedback as they reveal a) students' alternative conceptions on how ocean acidification impacts oysters or how acidification works in general; b) students' interpretations of oceans' (non)connectedness to Earth system; c) the choice of scientific representations and their sources; and d) the way students' integrate evidence or data from the investigations. Our work tackles an understanding of one of the most vital signs of modern climatic changes. Recent scientific evidence shows that if the change in ocean

Combined Descriptive and Explanatory Information Improves Peers' Perceptions of Autism

ERIC Educational Resources Information Center

Campbell, Jonathan M.; Ferguson, Jane E.; Herzinger, Caitlin V.; Jackson, Jennie N.; Marino, Christine A.

2004-01-01

Authors examined the combined effects of descriptive and explanatory information on peers' perceptions and behavioral intentions toward an unfamiliar child with autism. Children (N=576; M age=10.06 years) were randomly assigned to view two videotapes of a boy engaging in typical and autistic behaviors receiving either descriptive (AUT-D) or…

Explanatory models concerning the effects of small-area characteristics on individual health.

PubMed

Voigtländer, Sven; Vogt, Verena; Mielck, Andreas; Razum, Oliver

2014-06-01

Material and social living conditions at the small-area level are assumed to have an effect on individual health. We review existing explanatory models concerning the effects of small-area characteristics on health and describe the gaps future research should try to fill. Systematic literature search for, and analysis of, studies that propose an explanatory model of the relationship between small-area characteristics and health. Fourteen studies met our inclusion criteria. Using various theoretical approaches, almost all of the models are based on a three-tier structure linking social inequalities (posited at the macro-level), small-area characteristics (posited at the meso-level) and individual health (micro-level). No study explicitly defines the geographical borders of the small-area context. The health impact of the small-area characteristics is explained by specific pathways involving mediating factors (psychological, behavioural, biological). These pathways tend to be seen as uni-directional; often, causality is implied. They may be modified by individual factors. A number of issues need more attention in research on explanatory models concerning small-area effects on health. Among them are the (geographical) definition of the small-area context; the systematic description of pathways comprising small-area contextual as well as compositional factors; questions of direction of association and causality; and the integration of a time dimension.

Explanatory model for sound amplification in a stethoscope

NASA Astrophysics Data System (ADS)

Eshach, H.; Volfson, A.

2015-01-01

In the present paper we suggest an original physical explanatory model that explains the mechanism of the sound amplification process in a stethoscope. We discuss the amplification of a single pulse, a continuous wave of certain frequency, and finally we address the resonant frequencies. It is our belief that this model may provide students with opportunities to not only better understand the amplification mechanism of a stethoscope, but also to strengthen their understanding of sound, pressure, waves, resonance modes, etc.

Divergent Explanatory Production (DEP): The Relationship between Resilience and Creativity

ERIC Educational Resources Information Center

Hernández, Óscar Sánchez; Méndez, Francisco Xavier; Garber, Judy

2015-01-01

Introduction: The aim of the study is to describe and analyze a new test and construct, Divergent Explanatory Production (DEP), defined as the ability to observe adverse situations from various points of view. At the theoretical level, it is a bridge between the reformulated model of learned helplessness (as a resilience model), and creative…

School District Information Technology Disaster Recovery Planning: An Explanatory Case Study

ERIC Educational Resources Information Center

Gray, Shaun L.

2017-01-01

Despite research and practitioner articles outlining the importance information technology disaster plans (ITDRPs) to organizational success, barriers have impeded the process of disaster preparation for Burlington County New Jersey school districts. The purpose of this explanatory qualitative case study was to understand how technology leader…

A regularized variable selection procedure in additive hazards model with stratified case-cohort design.

PubMed

Ni, Ai; Cai, Jianwen

2018-07-01

Case-cohort designs are commonly used in large epidemiological studies to reduce the cost associated with covariate measurement. In many such studies the number of covariates is very large. An efficient variable selection method is needed for case-cohort studies where the covariates are only observed in a subset of the sample. Current literature on this topic has been focused on the proportional hazards model. However, in many studies the additive hazards model is preferred over the proportional hazards model either because the proportional hazards assumption is violated or the additive hazards model provides more relevent information to the research question. Motivated by one such study, the Atherosclerosis Risk in Communities (ARIC) study, we investigate the properties of a regularized variable selection procedure in stratified case-cohort design under an additive hazards model with a diverging number of parameters. We establish the consistency and asymptotic normality of the penalized estimator and prove its oracle property. Simulation studies are conducted to assess the finite sample performance of the proposed method with a modified cross-validation tuning parameter selection methods. We apply the variable selection procedure to the ARIC study to demonstrate its practical use.

[Satisfaction with primary care nursing: use of measurement tools and explanatory factors].

PubMed

Martín-Fernández, J; Ariza-Cardiel, G; Rodríguez-Martínez, G; Gayo-Milla, M; Martínez-Gil, M; Alzola-Martín, C; Fernández-San Martín, M I

2015-01-01

This study aims to assess the psychometric properties of two measurement tools for patient satisfaction with nursing care in Primary Care, the satisfaction level, and the personal and consultation characteristics associated with its variability. Subjects randomly selected in 23 Health Care centres in the Community of Madrid were included. Satisfaction was measured by means of the AMABLE and Baker questionnaires, in which the psychometric properties were evaluated. Sociodemographic characteristics of the consultations, variables related to health status, and other related to the consultation process were collected. An explanatory model using Generalized Estimating Equations was constructed. The 662 subjects expressed a mean satisfaction of 4.95/5 (SD .25) with AMABLE, and 4.83/5 (SD .42) with the Baker questionnaire. AMABLE had a single dimension (Cronbach's alpha .85), and Baker three: professional care (mean 4.76, SD .48 Cronbach's alpha .74), depth of relationship (mean 3.76, SD 1.18, Cronbach's alpha .73), and perceived time (mean 4.42, SD .86, Cronbach's alpha .47). Ageing, a better perception of health status, and appointments arranged by nurses were associated with higher expressed satisfaction. Home care, hospital admissions, delayed consultation, extended family, or high family income were associated with lower satisfaction. Satisfaction with nurse consultations in Primary Care was very high, and varied depending on personal characteristics and on the type of consultation. The assessed tools allowed this outcome to be measured properly. Copyright © 2014 SECA. Published by Elsevier Espana. All rights reserved.

Against Explanatory Minimalism in Psychiatry.

PubMed

Thornton, Tim

2015-01-01

The idea that psychiatry contains, in principle, a series of levels of explanation has been criticized not only as empirically false but also, by Campbell, as unintelligible because it presupposes a discredited pre-Humean view of causation. Campbell's criticism is based on an interventionist-inspired denial that mechanisms and rational connections underpin physical and mental causation, respectively, and hence underpin levels of explanation. These claims echo some superficially similar remarks in Wittgenstein's Zettel. But attention to the context of Wittgenstein's remarks suggests a reason to reject explanatory minimalism in psychiatry and reinstate a Wittgensteinian notion of levels of explanation. Only in a context broader than the one provided by interventionism is that the ascription of propositional attitudes, even in the puzzling case of delusions, justified. Such a view, informed by Wittgenstein, can reconcile the idea that the ascription mental phenomena presupposes a particular level of explanation with the rejection of an a priori claim about its connection to a neurological level of explanation.

Parental Explanatory Models of Child's Intellectual Disability: A Q Methodology Study

ERIC Educational Resources Information Center

John, Aesha; Montgomery, Diane

2016-01-01

This study with families caring for an individual with an intellectual disability in a mid-sized Indian city explored the diverse explanatory models that parents constructed of causes, preferred treatment approaches and perceived social effects of their child's intellectual disability. Seventeen mothers and three fathers rank ordered 48 disability…

Explanatory Preferences Shape Learning and Inference.

PubMed

Lombrozo, Tania

2016-10-01

Explanations play an important role in learning and inference. People often learn by seeking explanations, and they assess the viability of hypotheses by considering how well they explain the data. An emerging body of work reveals that both children and adults have strong and systematic intuitions about what constitutes a good explanation, and that these explanatory preferences have a systematic impact on explanation-based processes. In particular, people favor explanations that are simple and broad, with the consequence that engaging in explanation can shape learning and inference by leading people to seek patterns and favor hypotheses that support broad and simple explanations. Given the prevalence of explanation in everyday cognition, understanding explanation is therefore crucial to understanding learning and inference. Copyright © 2016 Elsevier Ltd. All rights reserved.

Adult Learners' Knowledge of Fraction Addition and Subtraction

ERIC Educational Resources Information Center

Muckridge, Nicole A.

2017-01-01

The purpose of this study was to examine adult developmental mathematics (ADM) students' knowledge of fraction addition and subtraction as it relates to their demonstrated fraction schemes and ability to disembed in multiplicative contexts with whole numbers. The study was conducted using a mixed methods sequential explanatory design. In the first…

The Development and Application of the Explanatory Model of School Dysfunctions

ERIC Educational Resources Information Center

Bergman, Manfred Max; Bergman, Zinette; Gravett, Sarah

2011-01-01

This article develops the Explanatory Model of School Dysfunctions based on 80 essays of school principals and their representatives in Gauteng. It reveals the degree and kinds of school dysfunctions, as well as their interconnectedness with actors, networks, and domains. The model provides a basis for theory-based analyses of specific…

Developmental delays and dental caries in low-income preschoolers in the USA: a pilot cross-sectional study and preliminary explanatory model

PubMed Central

2013-01-01

Background Anecdotal evidence suggests that low-income preschoolers with developmental delays are at increased risk for dental caries and poor oral health, but there are no published studies based on empirical data. The purpose of this pilot study was two-fold: to examine the relationship between developmental delays and dental caries in low-income preschoolers and to present a preliminary explanatory model on the determinants of caries for enrollees in Head Start, a U.S. school readiness program for low-income preschool-aged children. Methods Data were collected on preschoolers ages 3–5 years at two Head Start centers in Washington, USA (N = 115). The predictor variable was developmental delay status (no/yes). The outcome variable was the prevalence of decayed, missing, and filled surfaces (dmfs) on primary teeth. We used multiple variable Poisson regression models to test the hypothesis that within a population of low-income preschoolers, those with developmental delays would have increased dmfs prevalence than those without developmental delays. Results Seventeen percent of preschoolers had a developmental delay and 51.3% of preschoolers had ≥1 dmfs. Preschoolers with developmental delays had a dmfs prevalence ratio that was 1.26 times as high as preschoolers without developmental delays (95% CI: 1.01, 1.58; P < .04). Other factors associated with increased dmfs prevalence ratios included: not having a dental home (P = .01); low caregiver education (P < .001); and living in a non-fluoridated community (P < .001). Conclusions Our pilot data suggest that developmental delays among low-income preschoolers are associated with increased primary tooth dmfs. Additional research is needed to further examine this relationship. Future interventions and policies should focus on caries prevention strategies within settings like Head Start classrooms that serve low-income preschool-aged children with additional targeted home- and community

Physicians' explanatory behaviours and legal liability in decided medical malpractice litigation cases in Japan.

PubMed

Hamasaki, Tomoko; Hagihara, Akihito

2011-04-21

A physician's duty to provide an adequate explanation to the patient is derived from the doctrine of informed consent and the physician's duty of disclosure. However, findings are extremely limited with respect to physicians' specific explanatory behaviours and what might be regarded as a breach of the physicians' duty to explain in an actual medical setting. This study sought to identify physicians' explanatory behaviours that may be related to the physicians' legal liability. We analysed legal decisions of medical malpractice cases between 1990 and 2009 in which the pivotal issue was the physician's duty to explain (366 cases). To identify factors related to the breach of the physician's duty to explain, an analysis was undertaken based on acknowledged breaches with regard to the physician's duty to explain to the patient according to court decisions. Additionally, to identify predictors of physicians' behaviours in breach of the duty to explain, logistic regression analysis was performed. When the physician's explanation was given before treatment or surgery (p = 0.006), when it was relevant or specific (p = 0.000), and when the patient's consent was obtained (p = 0.002), the explanation was less likely to be deemed inadequate or a breach of the physician's duty to explain. Patient factors related to physicians' legally problematic explanations were patient age and gender. One physician factor was related to legally problematic physician explanations, namely the number of physicians involved in the patient's treatment. These findings may be useful in improving physician-patient communication in the medical setting.

Physicians' explanatory behaviours and legal liability in decided medical malpractice litigation cases in Japan

PubMed Central

2011-01-01

Background A physician's duty to provide an adequate explanation to the patient is derived from the doctrine of informed consent and the physician's duty of disclosure. However, findings are extremely limited with respect to physicians' specific explanatory behaviours and what might be regarded as a breach of the physicians' duty to explain in an actual medical setting. This study sought to identify physicians' explanatory behaviours that may be related to the physicians' legal liability. Methods We analysed legal decisions of medical malpractice cases between 1990 and 2009 in which the pivotal issue was the physician's duty to explain (366 cases). To identify factors related to the breach of the physician's duty to explain, an analysis was undertaken based on acknowledged breaches with regard to the physician's duty to explain to the patient according to court decisions. Additionally, to identify predictors of physicians' behaviours in breach of the duty to explain, logistic regression analysis was performed. Results When the physician's explanation was given before treatment or surgery (p = 0.006), when it was relevant or specific (p = 0.000), and when the patient's consent was obtained (p = 0.002), the explanation was less likely to be deemed inadequate or a breach of the physician's duty to explain. Patient factors related to physicians' legally problematic explanations were patient age and gender. One physician factor was related to legally problematic physician explanations, namely the number of physicians involved in the patient's treatment. Conclusion These findings may be useful in improving physician-patient communication in the medical setting. PMID:21510891

`Quantum Mechanics' and `Scientific Explanation' An Explanatory Strategy Aiming at Providing `Understanding'

NASA Astrophysics Data System (ADS)

Hadzidaki, Pandora

2008-01-01

Empirical studies persistently indicate that the usual explanatory strategies used in quantum mechanics (QM) instruction fail, in general, to yield understanding. In this study, we propose an instructional intervention, which: (a) incorporates into its subject matter a critical comparison of QM scientific content with the fundamental epistemological and ontological commitments of the prominent philosophical theories of explanation, a weak form of which we meet in QM teaching; (b) illuminates the reasons of their failure in the quantum domain; and (c) implements an explanatory strategy highly inspired by the epistemological pathways through which, during the birth-process of QM, science has gradually reached understanding. This strategy, an inherent element of which is the meta-cognitive and meta-scientific thinking, aims at leading learners not only to an essential understanding of QM worldview, but to a deep insight into the ‘Nature of Science’ as well.

Towards a computational(ist) neurobiology of language: Correlational, integrated, and explanatory neurolinguistics*

PubMed Central

Poeppel, David

2014-01-01

We outline what an integrated approach to language research that connects experimental, theoretical, and neurobiological domains of inquiry would look like, and ask to what extent unification is possible across domains. At the center of the program is the idea that computational/representational (CR) theories of language must be used to investigate its neurobiological (NB) foundations. We consider different ways in which CR and NB might be connected. These are (1) A Correlational way, in which NB computation is correlated with the CR theory; (2) An Integrated way, in which NB data provide crucial evidence for choosing among CR theories; and (3) an Explanatory way, in which properties of NB explain why a CR theory is the way it is. We examine various questions concerning the prospects for Explanatory connections in particular, including to what extent it makes sense to say that NB could be specialized for particular computations. PMID:25914888

Towards a computational(ist) neurobiology of language: Correlational, integrated, and explanatory neurolinguistics.

PubMed

Embick, David; Poeppel, David

2015-05-01

We outline what an integrated approach to language research that connects experimental, theoretical, and neurobiological domains of inquiry would look like, and ask to what extent unification is possible across domains. At the center of the program is the idea that computational/representational (CR) theories of language must be used to investigate its neurobiological (NB) foundations. We consider different ways in which CR and NB might be connected. These are (1) A Correlational way, in which NB computation is correlated with the CR theory; (2) An Integrated way, in which NB data provide crucial evidence for choosing among CR theories; and (3) an Explanatory way, in which properties of NB explain why a CR theory is the way it is. We examine various questions concerning the prospects for Explanatory connections in particular, including to what extent it makes sense to say that NB could be specialized for particular computations.

Nitrogen deposition outweighs climatic variability in driving annual growth rate of canopy beech trees: Evidence from long-term growth reconstruction across a geographic gradient.

PubMed

Gentilesca, Tiziana; Rita, Angelo; Brunetti, Michele; Giammarchi, Francesco; Leonardi, Stefano; Magnani, Federico; van Noije, Twan; Tonon, Giustino; Borghetti, Marco

2018-07-01

In this study, we investigated the role of climatic variability and atmospheric nitrogen deposition in driving long-term tree growth in canopy beech trees along a geographic gradient in the montane belt of the Italian peninsula, from the Alps to the southern Apennines. We sampled dominant trees at different developmental stages (from young to mature tree cohorts, with tree ages spanning from 35 to 160 years) and used stem analysis to infer historic reconstruction of tree volume and dominant height. Annual growth volume (G V ) and height (G H ) variability were related to annual variability in model simulated atmospheric nitrogen deposition and site-specific climatic variables, (i.e. mean annual temperature, total annual precipitation, mean growing period temperature, total growing period precipitation, and standard precipitation evapotranspiration index) and atmospheric CO 2 concentration, including tree cambial age among growth predictors. Generalized additive models (GAM), linear mixed-effects models (LMM), and Bayesian regression models (BRM) were independently employed to assess explanatory variables. The main results from our study were as follows: (i) tree age was the main explanatory variable for long-term growth variability; (ii) GAM, LMM, and BRM results consistently indicated climatic variables and CO 2 effects on G V and G H were weak, therefore evidence of recent climatic variability influence on beech annual growth rates was limited in the montane belt of the Italian peninsula; (iii) instead, significant positive nitrogen deposition (N dep ) effects were repeatedly observed in G V and G H ; the positive effects of N dep on canopy height growth rates, which tended to level off at N dep values greater than approximately 1.0 g m -2  y -1 , were interpreted as positive impacts on forest stand above-ground net productivity at the selected study sites. © 2018 John Wiley & Sons Ltd.

Self-Explanation and Explanatory Feedback in Games: Individual Differences, Gameplay, and Learning

ERIC Educational Resources Information Center

Killingsworth, Stephen S.; Clark, Douglas B.; Adams, Deanne M.

2015-01-01

Previous research has demonstrated the efficacy of two explanation-based approaches for increasing learning in educational games. The first involves asking students to explain their answers (self-explanation) and the second involves providing correct explanations (explanatory feedback). This study (1) compared self-explanation and explanatory…

Learning Molecular Behaviour May Improve Student Explanatory Models of the Greenhouse Effect

ERIC Educational Resources Information Center

Harris, Sara E.; Gold, Anne U.

2018-01-01

We assessed undergraduates' representations of the greenhouse effect, based on student-generated concept sketches, before and after a 30-min constructivist lesson. Principal component analysis of features in student sketches revealed seven distinct and coherent explanatory models including a new "Molecular Details" model. After the…

Against Explanatory Minimalism in Psychiatry

PubMed Central

Thornton, Tim

2015-01-01

The idea that psychiatry contains, in principle, a series of levels of explanation has been criticized not only as empirically false but also, by Campbell, as unintelligible because it presupposes a discredited pre-Humean view of causation. Campbell’s criticism is based on an interventionist-inspired denial that mechanisms and rational connections underpin physical and mental causation, respectively, and hence underpin levels of explanation. These claims echo some superficially similar remarks in Wittgenstein’s Zettel. But attention to the context of Wittgenstein’s remarks suggests a reason to reject explanatory minimalism in psychiatry and reinstate a Wittgensteinian notion of levels of explanation. Only in a context broader than the one provided by interventionism is that the ascription of propositional attitudes, even in the puzzling case of delusions, justified. Such a view, informed by Wittgenstein, can reconcile the idea that the ascription mental phenomena presupposes a particular level of explanation with the rejection of an a priori claim about its connection to a neurological level of explanation. PMID:26696908

A tree-based statistical classification algorithm (CHAID) for identifying variables responsible for the occurrence of faecal indicator bacteria during waterworks operations

NASA Astrophysics Data System (ADS)

Bichler, Andrea; Neumaier, Arnold; Hofmann, Thilo

2014-11-01

Microbial contamination of groundwater used for drinking water can affect public health and is of major concern to local water authorities and water suppliers. Potential hazards need to be identified in order to protect raw water resources. We propose a non-parametric data mining technique for exploring the presence of total coliforms (TC) in a groundwater abstraction well and its relationship to readily available, continuous time series of hydrometric monitoring parameters (seven year records of precipitation, river water levels, and groundwater heads). The original monitoring parameters were used to create an extensive generic dataset of explanatory variables by considering different accumulation or averaging periods, as well as temporal offsets of the explanatory variables. A classification tree based on the Chi-Squared Automatic Interaction Detection (CHAID) recursive partitioning algorithm revealed statistically significant relationships between precipitation and the presence of TC in both a production well and a nearby monitoring well. Different secondary explanatory variables were identified for the two wells. Elevated water levels and short-term water table fluctuations in the nearby river were found to be associated with TC in the observation well. The presence of TC in the production well was found to relate to elevated groundwater heads and fluctuations in groundwater levels. The generic variables created proved useful for increasing significance levels. The tree-based model was used to predict the occurrence of TC on the basis of hydrometric variables.

Explanatory Versus Pragmatic Trials: An Essential Concept in Study Design and Interpretation.

PubMed

Merali, Zamir; Wilson, Jefferson R

2017-11-01

Randomized clinical trials often represent the highest level of clinical evidence available to evaluate the efficacy of an intervention in clinical medicine. Although the process of randomization serves to maximize internal validity, the external validity, or generalizability, of such studies depends on several factors determined at the design phase of the trial including eligibility criteria, study setting, and outcomes of interest. In general, explanatory trials are optimized to demonstrate the efficacy of an intervention in a highly selected patient group; however, findings from these studies may not be generalizable to the larger clinical problem. In contrast, pragmatic trials attempt to understand the real-world benefit of an intervention by incorporating design elements that allow for greater generalizability and clinical applicability of study results. In this article we describe the explanatory-pragmatic continuum for clinical trials in greater detail. Further, a well-accepted tool for grading trials on this continuum is described, and applied, to 2 recently published trials pertaining to the surgical management of lumbar degenerative spondylolisthesis.

Predictive and Explanatory Relationship Model between Procrastination, Motivation, Anxiety and Academic Achievement

ERIC Educational Resources Information Center

Akpur, Ugur

2017-01-01

Purpose: The purpose of this study is to determine the predictive and explanatory relationship model between procrastination, motivation, anxiety and academic achievement of university students. Research Methods: In this study, a causal research design was used. The study group consisted of 211 participants. In order to determine their motivation…

Variable selection with stepwise and best subset approaches

PubMed Central

2016-01-01

While purposeful selection is performed partly by software and partly by hand, the stepwise and best subset approaches are automatically performed by software. Two R functions stepAIC() and bestglm() are well designed for stepwise and best subset regression, respectively. The stepAIC() function begins with a full or null model, and methods for stepwise regression can be specified in the direction argument with character values “forward”, “backward” and “both”. The bestglm() function begins with a data frame containing explanatory variables and response variables. The response variable should be in the last column. Varieties of goodness-of-fit criteria can be specified in the IC argument. The Bayesian information criterion (BIC) usually results in more parsimonious model than the Akaike information criterion. PMID:27162786

Constructing and De-Constructing Cultural Values: An Explanatory Model of Teaching Behaviours.

ERIC Educational Resources Information Center

Boufoy-Bastick, Beatrice

This paper presents an explanatory model of cultural behaviors, which resulted from a 4-year ethnographic study of the different academic attainments in English of indigenous Fijians and the Indo-Fijians in the Fiji Islands. Fiji is a natural laboratory for investigating differential cultural behaviors because of these two culturally distinct main…

Incorporating additional tree and environmental variables in a lodgepole pine stem profile model

Treesearch

John C. Byrne

1993-01-01

A new variable-form segmented stem profile model is developed for lodgepole pine (Pinus contorta) trees from the northern Rocky Mountains of the United States. I improved estimates of stem diameter by predicting two of the model coefficients with linear equations using a measure of tree form, defined as a ratio of dbh and total height. Additional improvements were...

The Social Explanatory Styles Questionnaire: Assessing Moderators of Basic Social-Cognitive Phenomena Including Spontaneous Trait Inference, the Fundamental Attribution Error, and Moral Blame

PubMed Central

Gill, Michael J.; Andreychik, Michael R.

2014-01-01

Why is he poor? Why is she failing academically? Why is he so generous? Why is she so conscientious? Answers to such everyday questions—social explanations—have powerful effects on relationships at the interpersonal and societal levels. How do people select an explanation in particular cases? We suggest that, often, explanations are selected based on the individual's pre-existing general theories of social causality. More specifically, we suggest that over time individuals develop general beliefs regarding the causes of social events. We refer to these beliefs as social explanatory styles. Our goal in the present article is to offer and validate a measure of individual differences in social explanatory styles. Accordingly, we offer the Social Explanatory Styles Questionnaire (SESQ), which measures three independent dimensions of social explanatory style: Dispositionism, historicism, and controllability. Studies 1–3 examine basic psychometric properties of the SESQ and provide positive evidence regarding internal consistency, factor structure, and both convergent and divergent validity. Studies 4–6 examine predictive validity for each subscale: Does each explanatory dimension moderate an important phenomenon of social cognition? Results suggest that they do. In Study 4, we show that SESQ dispositionism moderates the tendency to make spontaneous trait inferences. In Study 5, we show that SESQ historicism moderates the tendency to commit the Fundamental Attribution Error. Finally, in Study 6 we show that SESQ controllability predicts polarization of moral blame judgments: Heightened blaming toward controllable stigmas (assimilation), and attenuated blaming toward uncontrollable stigmas (contrast). Decades of research suggest that explanatory style regarding the self is a powerful predictor of self-functioning. We think it is likely that social explanatory styles—perhaps comprising interactive combinations of the basic dimensions tapped by the SESQ—will be

Using explanatory crop models to develop simple tools for Advanced Life Support system studies

NASA Technical Reports Server (NTRS)

Cavazzoni, J.

2004-01-01

System-level analyses for Advanced Life Support require mathematical models for various processes, such as for biomass production and waste management, which would ideally be integrated into overall system models. Explanatory models (also referred to as mechanistic or process models) would provide the basis for a more robust system model, as these would be based on an understanding of specific processes. However, implementing such models at the system level may not always be practicable because of their complexity. For the area of biomass production, explanatory models were used to generate parameters and multivariable polynomial equations for basic models that are suitable for estimating the direction and magnitude of daily changes in canopy gas-exchange, harvest index, and production scheduling for both nominal and off-nominal growing conditions. c2004 COSPAR. Published by Elsevier Ltd. All rights reserved.

Interannual rainfall variability and SOM-based circulation classification

NASA Astrophysics Data System (ADS)

Wolski, Piotr; Jack, Christopher; Tadross, Mark; van Aardenne, Lisa; Lennard, Christopher

2018-01-01

Self-Organizing Maps (SOM) based classifications of synoptic circulation patterns are increasingly being used to interpret large-scale drivers of local climate variability, and as part of statistical downscaling methodologies. These applications rely on a basic premise of synoptic climatology, i.e. that local weather is conditioned by the large-scale circulation. While it is clear that this relationship holds in principle, the implications of its implementation through SOM-based classification, particularly at interannual and longer time scales, are not well recognized. Here we use a SOM to understand the interannual synoptic drivers of climate variability at two locations in the winter and summer rainfall regimes of South Africa. We quantify the portion of variance in seasonal rainfall totals that is explained by year to year differences in the synoptic circulation, as schematized by a SOM. We furthermore test how different spatial domain sizes and synoptic variables affect the ability of the SOM to capture the dominant synoptic drivers of interannual rainfall variability. Additionally, we identify systematic synoptic forcing that is not captured by the SOM classification. The results indicate that the frequency of synoptic states, as schematized by a relatively disaggregated SOM (7 × 9) of prognostic atmospheric variables, including specific humidity, air temperature and geostrophic winds, captures only 20-45% of interannual local rainfall variability, and that the residual variance contains a strong systematic component. Utilising a multivariate linear regression framework demonstrates that this residual variance can largely be explained using synoptic variables over a particular location; even though they are used in the development of the SOM their influence, however, diminishes with the size of the SOM spatial domain. The influence of the SOM domain size, the choice of SOM atmospheric variables and grid-point explanatory variables on the levels of explained

An Exploration of the Relationship between Optimistic Explanatory Style and Doctoral Study Completion

ERIC Educational Resources Information Center

Richards, Constance V. S.

2012-01-01

Few studies have explored the positive characteristics that motivate doctoral students to pursue and complete their degree; research has historically focused on doctoral student attrition. To fully understand doctoral student success, research must focus on factors that contribute to completion. Based on Seligman's theory of explanatory style,…

Technology Adoption in Secondary Mathematics Teaching in Kenya: An Explanatory Mixed Methods Study

ERIC Educational Resources Information Center

Kamau, Leonard Mwathi

2014-01-01

This study examined the factors related to technology adoption by secondary mathematics teachers in Nyandarua and Nairobi counties in the Republic of Kenya. Using a sequential explanatory mixed methods approach, I collected qualitative data from interviews and classroom observations of six teachers to better understand statistical results from the…

Explanatory models of diabetes in urban poor communities in Accra, Ghana.

PubMed

de-Graft Aikins, Ama; Awuah, Raphael Baffour; Pera, Tuula Anneli; Mendez, Montserrat; Ogedegbe, Gbenga

2015-01-01

The objective of the study was to examine explanatory models of diabetes and diabetes complications among urban poor Ghanaians living with diabetes and implications for developing secondary prevention strategies. Twenty adults with type 2 diabetes were recruited from three poor communities in Accra. Qualitative data were obtained using interviews that run between 40 and 90 minutes. The interviews were audio-taped, transcribed and analysed thematically, informed by the 'explanatory model of disease' concept. Respondents associated diabetes and its complications with diet, family history, lifestyle factors (smoking, excessive alcohol consumption and physical inactivity), psychological stress and supernatural factors (witchcraft and sorcery). These associations were informed by biomedical and cultural models of diabetes and disease. Subjective experience, through a process of 'body-listening,' constituted a third model on which respondents drew to theorise diabetes complications. Poverty was an important mediator of poor self-care practices, including treatment non-adherence. The biomedical model of diabetes was a major source of legitimate information for self-care practices. However, this was understood and applied through a complex framework of cultural theories of chronic disease, the biopsychological impact of everyday illness experience and the disempowering effects of poverty. An integrated biopsychosocial approach is proposed for diabetes intervention in this research community.

The explanatory structure of unexplainable events: Causal constraints on magical reasoning.

PubMed

Shtulman, Andrew; Morgan, Caitlin

2017-10-01

A common intuition, often captured in fiction, is that some impossible events (e.g., levitating a stone) are "more impossible" than others (e.g., levitating a feather). We investigated the source of this intuition, hypothesizing that graded notions of impossibility arise from explanatory considerations logically precluded by the violation at hand but still taken into account. Studies 1-4 involved college undergraduates (n = 357), and Study 5 involved preschool-aged children (n = 32). In Studies 1 and 2, participants saw pairs of magical spells that violated one of 18 causal principles-six physical, six biological, and six psychological-and were asked to indicate which spell would be more difficult to learn. Both spells violated the same causal principle but differed in their relation to a subsidiary principle. Participants' judgments of spell difficulty honored the subsidiary principle, even when participants were given the option of judging the two spells equally difficult. Study 3 replicated those effects with Likert-type ratings; Study 4 replicated them in an open-ended version of the task in which participants generated their own causal violations; and Study 5 replicated them with children. Taken together, these findings suggest that events that defy causal explanation are interpreted in terms of explanatory considerations that hold in the absence of such violations.

Strategies to Reduce the Negative Effects of Spoken Explanatory Text on Integrated Tasks

ERIC Educational Resources Information Center

Singh, Anne-Marie; Marcus, Nadine; Ayres, Paul

2017-01-01

Two experiments involving 125 grade-10 students learning about commerce investigated strategies to overcome the transient information effect caused by explanatory spoken text. The transient information effect occurs when learning is reduced as a result of information disappearing before the learner has time to adequately process it, or link it…

Exploring the post-genomic world: differing explanatory and manipulatory functions of post-genomic sciences.

PubMed

Holmes, Christina; Carlson, Siobhan M; McDonald, Fiona; Jones, Mavis; Graham, Janice

2016-01-02

Richard Lewontin proposed that the ability of a scientific field to create a narrative for public understanding garners it social relevance. This article applies Lewontin's conceptual framework of the functions of science (manipulatory and explanatory) to compare and explain the current differences in perceived societal relevance of genetics/genomics and proteomics. We provide three examples to illustrate the social relevance and strong cultural narrative of genetics/genomics for which no counterpart exists for proteomics. We argue that the major difference between genetics/genomics and proteomics is that genomics has a strong explanatory function, due to the strong cultural narrative of heredity. Based on qualitative interviews and observations of proteomics conferences, we suggest that the nature of proteins, lack of public understanding, and theoretical complexity exacerbates this difference for proteomics. Lewontin's framework suggests that social scientists may find that omics sciences affect social relations in different ways than past analyses of genetics.

The Role of Scientific Modeling Criteria in Advancing Students' Explanatory Ideas of Magnetism

ERIC Educational Resources Information Center

Cheng, Meng-Fei; Brown, David E.

2015-01-01

Student construction of models is a strong focus of current research and practice in science education. In order to study in detail the interactions between students' model generation and evaluation and their development of explanatory ideas to account for magnetic phenomena, a multi-session teaching experiment was conducted with a small number of…

Exploratory case study of students' main explanatory approaches to science concepts and their states of mental engagement

NASA Astrophysics Data System (ADS)

Nicdao-Quita, Maria Isabel T.

This study explored students' dominant ways of operating in science; the types of structuring that is evident, not in terms of ideas, but in terms of how the students think about, imagine, and relate to the physical processes. As the study progressed, the investigation of the students' ideas went beyond their prior knowledge; other significant dimensions emerged as these students interacted with the heating process. The students demonstrated rich and dynamic pictures of the heating process, and from these images, a larger picture of the mental entities and processes dominant in their understanding of the physical phenomenon. Four Filipino students studying in the United States were individually observed in their science classes, were visited at home, and were interviewed about water being heated. The analysis of each student's data led to the two constructs, the main explanatory approach and the students' states of mental engagement (SOME), while the student was cognitively and affectively connected with the phenomenon. The features of the main explanatory approach include an explanatory element and an affective element that pervade the students' thinking about the phenomenon. It is common to and dominant in students' thinking across time. It is the approach of the student taken as a holistic organization within the student when he or she starts dealing with the phenomenon. One of the assumptions behind dealing with the main explanatory approach is that it is much more connected with what kind of person the student is and with the state of mental engagement (SOME) the student is in. SOME refers to the personal energy of a student as he or she relates to and becomes involved with the physical process--there is absorption into the object of study. SOME is related to energizing the main explanatory approach. The interconnectedness of these two constructs can be viewed as a different level of abstraction or interpretation of the students' ways of thinking about the

Preliminary Evolutionary Explanations: A Basic Framework for Conceptual Change and Explanatory Coherence in Evolution

NASA Astrophysics Data System (ADS)

Kampourakis, Kostas; Zogza, Vasso

2009-10-01

This study aimed to explore secondary students’ explanations of evolutionary processes, and to determine how consistent these were, after a specific evolution instruction. In a previous study it was found that before instruction students provided different explanations for similar processes to tasks with different content. Hence, it seemed that the structure and the content of the task may have had an effect on students’ explanations. The tasks given to students demanded evolutionary explanations, in particular explanations for the origin of homologies and adaptations. Based on the conclusions from the previous study, we developed a teaching sequence in order to overcome students’ preconceptions, as well as to achieve conceptual change and explanatory coherence. Students were taught about fundamental biological concepts and the several levels of biological organization, as well as about the mechanisms of heredity and of the origin of genetic variation. Then, all these concepts were used to teach about evolution, by relating micro-concepts (e.g. genotypes) to macro-concepts (e.g. phenotypes). Moreover, during instruction students were brought to a conceptual conflict situation, where their intuitive explanations were challenged as emphasis was put on two concepts entirely opposed to their preconceptions: chance and unpredictability. From the explanations that students provided in the post-test it is concluded that conceptual change and explanatory coherence in evolution can be achieved to a certain degree by lower secondary school students through the suggested teaching sequence and the explanatory framework, which may form a basis for teaching further about evolution.

The role of patients' explanatory models and daily-lived experience in hypertension self-management.

PubMed

Bokhour, Barbara G; Cohn, Ellen S; Cortés, Dharma E; Solomon, Jeffrey L; Fix, Gemmae M; Elwy, A Rani; Mueller, Nora; Katz, Lois A; Haidet, Paul; Green, Alexander R; Borzecki, Ann M; Kressin, Nancy R

2012-12-01

Uncontrolled hypertension remains a significant problem for many patients. Few interventions to improve patients' hypertension self-management have had lasting effects. Previous work has focused largely on patients' beliefs as predictors of behavior, but little is understood about beliefs as they are embedded in patients' social contexts. This study aims to explore how patients' "explanatory models" of hypertension (understandings of the causes, mechanisms or pathophysiology, course of illness, symptoms and effects of treatment) and social context relate to their reported daily hypertension self-management behaviors. Semi-structured qualitative interviews with a diverse group of patients at two large urban Veterans Administration Medical centers. PARTICIPANTS (OR PATIENTS OR SUBJECTS): African-American, white and Latino Veterans Affairs (VA) primary care patients with uncontrolled blood pressure. We conducted thematic analysis using tools of grounded theory to identify key themes surrounding patients' explanatory models, social context and hypertension management behaviors. Patients' perceptions of the cause and course of hypertension, experiences of hypertension symptoms, and beliefs about the effectiveness of treatment were related to different hypertension self-management behaviors. Moreover, patients' daily-lived experiences, such as an isolated lifestyle, serious competing health problems, a lack of habits and routines, barriers to exercise and prioritizing lifestyle choices, also interfered with optimal hypertension self-management. Designing interventions to improve patients' hypertension self-management requires consideration of patients' explanatory models and their daily-lived experience. We propose a new conceptual model - the dynamic model of hypertension self-management behavior - which incorporates these key elements of patients' experiences.

ADPROCLUS: a graphical user interface for fitting additive profile clustering models to object by variable data matrices.

PubMed

Wilderjans, Tom F; Ceulemans, Eva; Van Mechelen, Iven; Depril, Dirk

2011-03-01

In many areas of psychology, one is interested in disclosing the underlying structural mechanisms that generated an object by variable data set. Often, based on theoretical or empirical arguments, it may be expected that these underlying mechanisms imply that the objects are grouped into clusters that are allowed to overlap (i.e., an object may belong to more than one cluster). In such cases, analyzing the data with Mirkin's additive profile clustering model may be appropriate. In this model: (1) each object may belong to no, one or several clusters, (2) there is a specific variable profile associated with each cluster, and (3) the scores of the objects on the variables can be reconstructed by adding the cluster-specific variable profiles of the clusters the object in question belongs to. Until now, however, no software program has been publicly available to perform an additive profile clustering analysis. For this purpose, in this article, the ADPROCLUS program, steered by a graphical user interface, is presented. We further illustrate its use by means of the analysis of a patient by symptom data matrix.

Explanatory and illustrative visualization of special and general relativity.

PubMed

Weiskopf, Daniel; Borchers, Marc; Ertl, Thomas; Falk, Martin; Fechtig, Oliver; Frank, Regine; Grave, Frank; King, Andreas; Kraus, Ute; Müller, Thomas; Nollert, Hans-Peter; Rica Mendez, Isabel; Ruder, Hanns; Schafhitzel, Tobias; Schär, Sonja; Zahn, Corvin; Zatloukal, Michael

2006-01-01

This paper describes methods for explanatory and illustrative visualizations used to communicate aspects of Einstein's theories of special and general relativity, their geometric structure, and of the related fields of cosmology and astrophysics. Our illustrations target a general audience of laypersons interested in relativity. We discuss visualization strategies, motivated by physics education and the didactics of mathematics, and describe what kind of visualization methods have proven to be useful for different types of media, such as still images in popular science magazines, film contributions to TV shows, oral presentations, or interactive museum installations. Our primary approach is to adopt an egocentric point of view: The recipients of a visualization participate in a visually enriched thought experiment that allows them to experience or explore a relativistic scenario. In addition, we often combine egocentric visualizations with more abstract illustrations based on an outside view in order to provide several presentations of the same phenomenon. Although our visualization tools often build upon existing methods and implementations, the underlying techniques have been improved by several novel technical contributions like image-based special relativistic rendering on GPUs, special relativistic 4D ray tracing for accelerating scene objects, an extension of general relativistic ray tracing to manifolds described by multiple charts, GPU-based interactive visualization of gravitational light deflection, as well as planetary terrain rendering. The usefulness and effectiveness of our visualizations are demonstrated by reporting on experiences with, and feedback from, recipients of visualizations and collaborators.

Hedonic price models with omitted variables and measurement errors: a constrained autoregression-structural equation modeling approach with application to urban Indonesia

NASA Astrophysics Data System (ADS)

Suparman, Yusep; Folmer, Henk; Oud, Johan H. L.

2014-01-01

Omitted variables and measurement errors in explanatory variables frequently occur in hedonic price models. Ignoring these problems leads to biased estimators. In this paper, we develop a constrained autoregression-structural equation model (ASEM) to handle both types of problems. Standard panel data models to handle omitted variables bias are based on the assumption that the omitted variables are time-invariant. ASEM allows handling of both time-varying and time-invariant omitted variables by constrained autoregression. In the case of measurement error, standard approaches require additional external information which is usually difficult to obtain. ASEM exploits the fact that panel data are repeatedly measured which allows decomposing the variance of a variable into the true variance and the variance due to measurement error. We apply ASEM to estimate a hedonic housing model for urban Indonesia. To get insight into the consequences of measurement error and omitted variables, we compare the ASEM estimates with the outcomes of (1) a standard SEM, which does not account for omitted variables, (2) a constrained autoregression model, which does not account for measurement error, and (3) a fixed effects hedonic model, which ignores measurement error and time-varying omitted variables. The differences between the ASEM estimates and the outcomes of the three alternative approaches are substantial.

Exploring the post-genomic world: differing explanatory and manipulatory functions of post-genomic sciences

PubMed Central

Holmes, Christina; Carlson, Siobhan M.; McDonald, Fiona; Jones, Mavis; Graham, Janice

2016-01-01

Richard Lewontin proposed that the ability of a scientific field to create a narrative for public understanding garners it social relevance. This article applies Lewontin's conceptual framework of the functions of science (manipulatory and explanatory) to compare and explain the current differences in perceived societal relevance of genetics/genomics and proteomics. We provide three examples to illustrate the social relevance and strong cultural narrative of genetics/genomics for which no counterpart exists for proteomics. We argue that the major difference between genetics/genomics and proteomics is that genomics has a strong explanatory function, due to the strong cultural narrative of heredity. Based on qualitative interviews and observations of proteomics conferences, we suggest that the nature of proteins, lack of public understanding, and theoretical complexity exacerbates this difference for proteomics. Lewontin's framework suggests that social scientists may find that omics sciences affect social relations in different ways than past analyses of genetics. PMID:27134568

Effect of several variables in the polymer toys additive migration to saliva.

PubMed

Noguerol-Cal, R; López-Vilariño, J M; González-Rodríguez, M V; Barral-Losada, L

2011-09-30

Capacity to migrate of a representative group of polymeric additives, dyes, antioxidants, hindered amine light stabilizers (HALS) or antistatics, from plastic toys to saliva was analyzed to protect children in their habits of sucking and biting. Most of target additives appear no-regulated in toys normative but adverse effects on human health of some of them have been demonstrated and their presence in others commercial articles normative has been included. In order to offer an effective and easy tool to perform these controls, migration tests by dynamic and static contact, followed by a preconcentration step by liquid-liquid extraction (LLE) and ultra performance liquid chromatographic analysis with ultraviolet-visible and evaporative light scattering detections (UPLC-UV/Vis-ELSD) have been optimized to evaluate the migrated amounts of the additives in saliva simulant. The detection limits of the migration methodologies were ranged from 8.68 × 10(-2) to 1.30 × 10(-3)mg migrated (L simulant)(-1). Influence of several variables on this mass transport, as time, temperature and friction, was also analyzed to achieve the most aggressive methodology to protect consumers. Migration of several studied additives, whose presence has been demonstrated in several purchased commercial toys, has been observed. Copyright © 2011 Elsevier B.V. All rights reserved.

Interpretation of tropospheric ozone variability in data with different vertical and temporal resolution

NASA Astrophysics Data System (ADS)

Petropavlovskikh, I. V.; Disterhoft, P.; Johnson, B. J.; Rieder, H. E.; Manney, G. L.; Daffer, W.

2012-12-01

This work attributes tropospheric ozone variability derived from the ground-based Dobson and Brewer Umkehr measurements and from ozone sonde data to local sources and transport. It assesses capability and limitations in both types of measurements that are often used to analyze long- and short-term variability in tropospheric ozone time series. We will address the natural and instrument-related contribution to the variability found in both Umkehr and sonde data. Validation of Umkehr methods is often done by intercomparisons against independent ozone measuring techniques such as ozone sounding. We will use ozone-sounding in its original and AK-smoothed vertical profiles for assessment of ozone inter-annual variability over Boulder, CO. We will discuss possible reasons for differences between different ozone measuring techniques and its effects on the derived ozone trends. Next to standard evaluation techniques we utilize a STL-decomposition method to address temporal variability and trends in the Boulder Umkehr data. Further, we apply a statistical modeling approach to the ozone data set to attribute ozone variability to individual driving forces associated with natural and anthropogenic causes. To this aim we follow earlier work applying a backward selection method (i.e., a stepwise elimination procedure out of a set of total 44 explanatory variables) to determine those explanatory variables which contribute most significantly to the observed variability. We will present also some results associated with completeness (sampling rate) of the existing data sets. We will also use MERRA (Modern-Era Retrospective analysis for Research and Applications) re-analysis results selected for Boulder location as a transfer function in understanding of the effects that the temporal sampling and vertical resolution bring into trend and ozone variability analysis. Analyzing intra-annual variability in ozone measurements over Boulder, CO, in relation to the upper tropospheric

Inconsistency prevents the valuable synergism of explanatory and pragmatic trails.

PubMed

Correia, Luis C L; Correia, Vitor C A; Souza, Thiago M B; Cerqueira, Antonio Maurício S; Alexandre, Felipe K B; Garcia, Guilherme; Ferreira, Felipe R M; Lopes, Fernanda O A

2018-05-01

To assess review articles on pragmatic trials in order to describe how authors define the aim of this type of study, how comprehensive methodological topics are covered, and which topics are most valued by authors. Review articles were selected from Medline Database, based on the expression "pragmatic trial" in the titles. Five trained medical students evaluated the articles, based on a list of 15 self-explanatory methodological topics. Each article was evaluated regarding topics covered. Baseline statements on the aim of pragmatic trials were derived. Among 22 articles identified, there was general agreement that the aim of a pragmatic trial is to evaluate if the intervention works under real-world conditions. The mean number of methodological topics addressed by each article was 7.6 ± 3.1. Only one article covered all 15 topics, three articles (14%) responded to at least 75% of topics and 13 articles (59%) mentioned at least 50% of the topics. The relative frequency each of the 15 topics was cited by articles had a mean of 50% ± 25%. No topic was addressed by all articles, only three (20%) were addressed by more than 75% of articles. There is agreement on the different aims of explanatory and pragmatic trials. But there is a large variation on methodological topics used to define a pragmatic trial, which led to inconsistency in defining the typical methodology of a pragmatic trial. © 2018 Chinese Cochrane Center, West China Hospital of Sichuan University and John Wiley & Sons Australia, Ltd.

Identifying the physical and anthropometric qualities explanatory of paddling adolescents.

PubMed

Sinclair, Wade H; Leicht, Anthony S; Eady, Troy W; Marshall, Nick J; Woods, Carl T

2017-12-01

This study aimed to identify the physical and/or anthropometric qualities explanatory of adolescent surf lifesavers participating in paddling activities. Cross-sectional observational study. A total of 53 (14-18years) male participants were recruited and classified into two groups; paddlers (n=30; actively participating in paddling), non-paddlers (n=23; not actively participating in paddling). All participants completed a testing battery that consisted of 16 physical (isometric strength and muscular endurance) and anthropometric (height, mass, segment lengths and breadths) assessments. Binary logistic regression models and receiver operating characteristic curves were built to identify the physical and/or anthropometric qualities most explanatory of paddling status (two levels: 1=paddlers, 0=non-paddlers). Significant between group differences were noted for 14 of the 16 assessments (P<0.05; d=0.59-1.29). However, it was the combination of horizontal shoulder abduction isometric strength, body mass, and sitting height that provided the greatest association with paddling status (Akaike Information Criterion=47.13). This full model successfully detected 87% and 70% of the paddlers and non-paddlers, respectively, with an area under the curve of 84.2%. These results indicate that there are distinctive physical and anthropometric qualities that may be advantageous for prospective paddling athletes to possess. Practitioners should integrate assessments of horizontal shoulder abduction isometric strength, body mass, and sitting height, as well as their subsequent cut-off thresholds, into talent detection programs focused toward the recognition of performance potential in paddling-oriented sports. Copyright © 2017 Sports Medicine Australia. Published by Elsevier Ltd. All rights reserved.

Improving Space Project Cost Estimating with Engineering Management Variables

NASA Technical Reports Server (NTRS)

Hamaker, Joseph W.; Roth, Axel (Technical Monitor)

2001-01-01

Current space project cost models attempt to predict space flight project cost via regression equations, which relate the cost of projects to technical performance metrics (e.g. weight, thrust, power, pointing accuracy, etc.). This paper examines the introduction of engineering management parameters to the set of explanatory variables. A number of specific engineering management variables are considered and exploratory regression analysis is performed to determine if there is statistical evidence for cost effects apart from technical aspects of the projects. It is concluded that there are other non-technical effects at work and that further research is warranted to determine if it can be shown that these cost effects are definitely related to engineering management.

The symmetry rule: a seven-year study of symptoms and explanatory labels among Gulf War veterans.

PubMed

Brewer, Noel T; Hallman, William K; Kipen, Howard M

2008-12-01

Noticing medical symptoms can cause one to search for explanatory labels such as "ate bad food" or even "exposed to anthrax," and perhaps these labels may cause new symptom reports. The present study examined whether there is empirical support for this symptom-label "symmetry rule." We interviewed veterans (N= 362) from the Gulf War Registry in 1995 and 2002 about their medical symptoms and about their exposure to war-related hazards and stressors. Health symptom reports were strongly correlated between the two time periods and showed relatively stable mean levels, whereas recall of war-related exposures was notably unstable. Veterans starting with fewer medical symptoms recalled fewer war-related exposures seven years later. Initial recollection of chemical and biological warfare exposure (but not other exposures) longitudinally predicted novel medical symptoms. The findings generally support the symmetry rule hypotheses, although the evidence for the label to symptom link was less strong. The findings account for some variability in symptoms and exposure recall over time, but they do not, on their own, account for the Gulf War veterans' elevated number of unexplained medical symptoms.

Input variable selection and calibration data selection for storm water quality regression models.

PubMed

Sun, Siao; Bertrand-Krajewski, Jean-Luc

2013-01-01

Storm water quality models are useful tools in storm water management. Interest has been growing in analyzing existing data for developing models for urban storm water quality evaluations. It is important to select appropriate model inputs when many candidate explanatory variables are available. Model calibration and verification are essential steps in any storm water quality modeling. This study investigates input variable selection and calibration data selection in storm water quality regression models. The two selection problems are mutually interacted. A procedure is developed in order to fulfil the two selection tasks in order. The procedure firstly selects model input variables using a cross validation method. An appropriate number of variables are identified as model inputs to ensure that a model is neither overfitted nor underfitted. Based on the model input selection results, calibration data selection is studied. Uncertainty of model performances due to calibration data selection is investigated with a random selection method. An approach using the cluster method is applied in order to enhance model calibration practice based on the principle of selecting representative data for calibration. The comparison between results from the cluster selection method and random selection shows that the former can significantly improve performances of calibrated models. It is found that the information content in calibration data is important in addition to the size of calibration data.

Explanatory characteristics for nutrient concentrations and loads in the Sava River Catchment and cross-regionally

NASA Astrophysics Data System (ADS)

Levi, L.; Cvetkovic, V.; Destouni, G.

2015-12-01

This study compiles estimates of waterborne nutrient concentrations and loads in the Sava River Catchment (SRC). Based on this compilation, we investigate hotspots of nutrient inputs and retention along the river, as well as concentration and load correlations with river discharge and various human drivers of excess nutrient inputs to the SRC. For cross-regional assessment and possible generalization, we also compare corresponding results between the SRC and the Baltic Sea Drainage Basin (BSDB). In the SRC, one small incremental subcatchment, which is located just downstream of Zagreb and has the highest population density among the SRC subcatchments, is identified as a major hotspot for net loading (input minus retention) of both total nitrogen (TN) and total phosphorus (TP) to the river and through it to downstream areas of the SRC. The other SRC subcatchments exhibit relatively similar characteristics with smaller net nutrient loading. The annual loads of both TN and TP along the Sava River exhibit dominant temporal variability with considerably higher correlation with annual river discharge (R2 = 0.51 and 0.28, respectively) than that of annual average nutrient concentrations (R2 = 0.0 versus discharge for both TN and TP). Nutrient concentrations exhibit instead dominant spatial variability with relatively high correlation with population density among the SRC subcatchments (R2=0.43-0.64). These SRC correlation characteristics compare well with corresponding ones for the BSDB, even though the two regions are quite different in their hydroclimatic, agricultural and wastewater treatment conditions. Such cross-regional consistency in dominant variability type and explanatory catchment characteristics may be a useful generalization basis, worthy of further investigation, for at least first-order estimation of nutrient concentration and load conditions in less data-rich regions.

Little Bayesians or Little Einsteins? Probability and Explanatory Virtue in Children's Inferences

ERIC Educational Resources Information Center

Johnston, Angie M.; Johnson, Samuel G. B.; Koven, Marissa L.; Keil, Frank C.

2017-01-01

Like scientists, children seek ways to explain causal systems in the world. But are children scientists in the strict Bayesian tradition of maximizing posterior probability? Or do they attend to other explanatory considerations, as laypeople and scientists--such as Einstein--do? Four experiments support the latter possibility. In particular, we…

Modeling the association between HR variability and illness in elite swimmers

PubMed Central

Hellard, Philippe; Guimaraes, Fanny; Avalos, Marta; Houel, Nicolas; Hausswirth, Christophe; Toussaint, Jean François

2011-01-01

Purpose To determine whether heart rate variability, an indirect measure of autonomic control, is associated with upper respiratory tract and pulmonary infections, muscular affections and all-type pathologies in elite swimmers. Methods Seven elite international and 11 national swimmers were followed weekly for two years. The indexes of cardiac autonomic regulation in supine and orthostatic position were assessed as explanatory variables by time-domain (SD1, SD2) and spectral analyses (high frequency- HF; 0.15 Hz-0.40Hz, low frequency-LF; 0.04-0.15 Hz and HF/LF ratio) of heart rate variability. Logistic mixed models described the relationship between the explanatory variables and the risk of upper respiratory tract and pulmonary infections, muscular affections and all-type pathologies. Results The risk of all-type pathologies was higher for national swimmers and in winter (p<0.01). An increase in the parasympathetic indexes (HF, SD1) in supine position assessed one week earlier was linked to a higher risk of upper respiratory tract and pulmonary infections (p<0.05), and to a higher risk of muscular affections (increase in HF, p<0.05). Multivariate analyses showed: (1) a higher all-type pathologies risk in winter, and for an increase in the total power of heart rate variability associated with a decline SD1 in supine position; (2) a higher all-type pathologies risk in winter associated with a decline in HF assessed one week earlier in orthostatic position; and (3) a higher risk of muscular affections in winter associated with a decrease SD1 and an increase LF in orthostatic position. Conclusion Swimmers’ health maintenance requires particular attention when autonomic balance shows a sudden increase in parasympathetic indices in supine position assessed one week earlier evolving toward sympathetic predominance in supine and orthostatic positions. PMID:21085039

Influence of Additive and Multiplicative Structure and Direction of Comparison on the Reversal Error

ERIC Educational Resources Information Center

González-Calero, José Antonio; Arnau, David; Laserna-Belenguer, Belén

2015-01-01

An empirical study has been carried out to evaluate the potential of word order matching and static comparison as explanatory models of reversal error. Data was collected from 214 undergraduate students who translated a set of additive and multiplicative comparisons expressed in Spanish into algebraic language. In these multiplicative comparisons…

Short-term favorable weather conditions are an important control of interannual variability in carbon and water fluxes

DOE PAGES

Zscheischler, Jakob; Fatichi, Simone; Wolf, Sebastian; ...

2016-08-08

Ecosystem models often perform poorly in reproducing interannual variability in carbon and water fluxes, resulting in considerable uncertainty when estimating the land-carbon sink. While many aggregated variables (growing season length, seasonal precipitation, or temperature) have been suggested as predictors for interannual variability in carbon fluxes, their explanatory power is limited and uncertainties remain as to their relative contributions. Recent results show that the annual count of hours where evapotranspiration (ET) is larger than its 95th percentile is strongly correlated with the annual variability of ET and gross primary production (GPP) in an ecosystem model. This suggests that the occurrence ofmore » favorable conditions has a strong influence on the annual carbon budget. Here we analyzed data from eight forest sites of the AmeriFlux network with at least 7 years of continuous measurements. We show that for ET and the carbon fluxes GPP, ecosystem respiration (RE), and net ecosystem production, counting the “most active hours/days” (i.e., hours/days when the flux exceeds a high percentile) correlates well with the respective annual sums, with correlation coefficients generally larger than 0.8. Phenological transitions have much weaker explanatory power. By exploiting the relationship between most active hours and interannual variability, we classify hours as most active or less active and largely explain interannual variability in ecosystem fluxes, particularly for GPP and RE. Our results suggest that a better understanding and modeling of the occurrence of large values in high-frequency ecosystem fluxes will result in a better understanding of interannual variability of these fluxes.« less

An instrumental variable random-coefficients model for binary outcomes

PubMed Central

Chesher, Andrew; Rosen, Adam M

2014-01-01

In this paper, we study a random-coefficients model for a binary outcome. We allow for the possibility that some or even all of the explanatory variables are arbitrarily correlated with the random coefficients, thus permitting endogeneity. We assume the existence of observed instrumental variables Z that are jointly independent with the random coefficients, although we place no structure on the joint determination of the endogenous variable X and instruments Z, as would be required for a control function approach. The model fits within the spectrum of generalized instrumental variable models, and we thus apply identification results from our previous studies of such models to the present context, demonstrating their use. Specifically, we characterize the identified set for the distribution of random coefficients in the binary response model with endogeneity via a collection of conditional moment inequalities, and we investigate the structure of these sets by way of numerical illustration. PMID:25798048

Phytoplankton dynamics of a subtropical reservoir controlled by the complex interplay among hydrological, abiotic, and biotic variables.

PubMed

Kuo, Yi-Ming; Wu, Jiunn-Tzong

2016-12-01

This study was conducted to identify the key factors related to the spatiotemporal variations in phytoplankton abundance in a subtropical reservoir from 2006 to 2010 and to assist in developing strategies for water quality management. Dynamic factor analysis (DFA), a dimension-reduction technique, was used to identify interactions between explanatory variables (i.e., environmental variables) and abundance (biovolume) of predominant phytoplankton classes. The optimal DFA model significantly described the dynamic changes in abundances of predominant phytoplankton groups (including dinoflagellates, diatoms, and green algae) at five monitoring sites. Water temperature, electrical conductivity, water level, nutrients (total phosphorus, NO 3 -N, and NH 3 -N), macro-zooplankton, and zooplankton were the key factors affecting the dynamics of aforementioned phytoplankton. Therefore, transformations of nutrients and reactions between water quality variables and aforementioned processes altered by hydrological conditions may also control the abundance dynamics of phytoplankton, which may represent common trends in the DFA model. The meandering shape of Shihmen Reservoir and its surrounding rivers caused a complex interplay between hydrological conditions and abiotic and biotic variables, resulting in phytoplankton abundance that could not be estimated using certain variables. Additional water quality and hydrological variables at surrounding rivers and monitoring plans should be executed a few days before and after reservoir operations and heavy storm, which would assist in developing site-specific preventive strategies to control phytoplankton abundance.

Conspicuous plumage colours are highly variable

PubMed Central

Szecsenyi, Beatrice; Nakagawa, Shinichi; Peters, Anne

2017-01-01

Elaborate ornamental traits are often under directional selection for greater elaboration, which in theory should deplete underlying genetic variation. Despite this, many ornamental traits appear to remain highly variable and how this essential variation is maintained is a key question in evolutionary biology. One way to address this question is to compare differences in intraspecific variability across different types of traits to determine whether high levels of variation are associated with specific trait characteristics. Here we assess intraspecific variation in more than 100 plumage colours across 55 bird species to test whether colour variability is linked to their level of elaboration (indicated by degree of sexual dichromatism and conspicuousness) or their condition dependence (indicated by mechanism of colour production). Conspicuous colours had the highest levels of variation and conspicuousness was the strongest predictor of variability, with high explanatory power. After accounting for this, there were no significant effects of sexual dichromatism or mechanisms of colour production. Conspicuous colours may entail higher production costs or may be more sensitive to disruptions during production. Alternatively, high variability could also be related to increased perceptual difficulties inherent to discriminating highly elaborate colours. Such psychophysical effects may constrain the exaggeration of animal colours. PMID:28100823

Conspicuous plumage colours are highly variable.

PubMed

Delhey, Kaspar; Szecsenyi, Beatrice; Nakagawa, Shinichi; Peters, Anne

2017-01-25

Elaborate ornamental traits are often under directional selection for greater elaboration, which in theory should deplete underlying genetic variation. Despite this, many ornamental traits appear to remain highly variable and how this essential variation is maintained is a key question in evolutionary biology. One way to address this question is to compare differences in intraspecific variability across different types of traits to determine whether high levels of variation are associated with specific trait characteristics. Here we assess intraspecific variation in more than 100 plumage colours across 55 bird species to test whether colour variability is linked to their level of elaboration (indicated by degree of sexual dichromatism and conspicuousness) or their condition dependence (indicated by mechanism of colour production). Conspicuous colours had the highest levels of variation and conspicuousness was the strongest predictor of variability, with high explanatory power. After accounting for this, there were no significant effects of sexual dichromatism or mechanisms of colour production. Conspicuous colours may entail higher production costs or may be more sensitive to disruptions during production. Alternatively, high variability could also be related to increased perceptual difficulties inherent to discriminating highly elaborate colours. Such psychophysical effects may constrain the exaggeration of animal colours. © 2017 The Author(s).

Learned Social Hopelessness: The Role of Explanatory Style in Predicting Social Support during Adolescence

ERIC Educational Resources Information Center

Ciarrochi, Joseph; Heaven, Patrick C. L.

2008-01-01

Background: Almost no research has examined the impact of explanatory style on social adjustment. We hypothesised that adolescents with a pessimistic style would be less likely to develop and maintain social support networks. Methods: Seven hundred and nineteen students (351 males and 366 females; 2 unknown; M[subscript AGE] = 12.28, SD = 0.49)…

Interparental Discord and Child Adjustment: Prospective Investigations of Emotional Security as an Explanatory Mechanism

ERIC Educational Resources Information Center

Cummings, E. Mark; Schermerhorn, Alice C.; Davies, Patrick T.; Goeke-Morey, Marcie C.; Cummings, Jennifer S.

2006-01-01

Advancing the process-oriented study of links between interparental discord and child adjustment, 2 multimethod prospective tests of emotional security as an explanatory mechanism are reported. On the basis of community samples, with waves spaced 2 years apart, Study 1 (113 boys and 113 girls, ages 9-18) identified emotional security as a mediator…

Narrative insight in psychosis: The relationship with spiritual and religious explanatory frameworks.

PubMed

Marriott, Michael R; Thompson, Andrew R; Cockshutt, Graham; Rowse, Georgina

2018-03-25

When considering psychosis, the concept of narrative insight has been offered as an alternative to clinical insight in determining individuals' responses to their difficulties, as it allows for a more holistic and person-centred framework to be embraced within professional practice. This study aims to explore the validity of the narrative insight construct within a group of people who have experienced psychosis. Inductive qualitative methods were used to explore how eight participants utilized spiritual or religious explanatory frameworks for their experiences of psychosis and to consider these in relation to the construct of narrative insight. Semi-structured interviews were undertaken with individuals who identified themselves as interested in spiritual or religious ideas and whose self-reported experiences which were identified as akin to psychosis by experienced academic clinicians. Transcriptions from these interviews were subject to interpretative phenomenological analysis within a broader research question; a selection of themes and data from the resultant phenomenological structure are explored here for their relevance to narrative insight. Participants discussed spiritual and biological explanations for their experiences and were able to hold alternative potential explanations alongside each other. They were reflective regarding the origins of their explanations and would describe a process of testing and proof in relation to them. These findings suggest that the narrative insight construct has the potential to be a valid approach to understanding experiences of psychosis, and challenge the dominance of the clinical insight construct within clinical practice. Clinicians should value the explanatory framework for experiences which are provided by individuals experiencing psychosis, and encourage them to develop a framework which is coherent to their own world view rather than predominantly pursuing a biomedical explanation. Assessments of psychosis should

Noise as an explanatory factor in work-related fatality reports

PubMed Central

Deshaies, Pierre; Martin, Richard; Belzile, Danny; Fortier, Pauline; Laroche, Chantal; Leroux, Tony; Nélisse, Hugues; Girard, Serge-André; Arcand, Robert; Poulin, Maurice; Picard, Michel

2015-01-01

Noise exposure in the workplace is a common reality in Québec, Canada as it is elsewhere. However, the extent to which noise acts as a causal or contributive factor in industrial work-related accidents has not been studied thoroughly despite its plausibility. This article aims to describe the importance or potential importance, during investigations looking into the specific causes of each work-related fatal accident, of noise as an explanatory factor. The written information contained in the accident reports pertaining to contextual and technical elements were used. The study used multiple case qualitative content analysis. This descriptive study was based on the content analysis of the 788 reports from the Commission de la santé et de la sécurité du travail du Québec [Workers’ Compensation Board (WCB)] investigating the fatal work-related accidents between 1990 and 2005. The study was descriptive (number and percentages). Noise was explicitly stated as one of the explanatory factors for the fatal outcome in 2.2% (17/788) of the fatal accidents, particularly when the work involved vehicular movement or the need to communicate between workers. Noise was not typically considered a unique cause in the accident, notably because the investigators considered that the accident would have probably occurred due to other risk factors (for example, disregard of safety rules, shortcomings in work methods, and inadequate training). Noise is an important risk factor when communication is involved in work. Since noise is ubiquitous and may also interfere with vigilance and other risk factors for accidents, it may be a much more important contributing factor to accidents than is currently recognized. PMID:26356371

Noise as an explanatory factor in work-related fatality reports.

PubMed

Deshaies, Pierre; Martin, Richard; Belzile, Danny; Fortier, Pauline; Laroche, Chantal; Leroux, Tony; Nélisse, Hugues; Girard, Serge-André; Arcand, Robert; Poulin, Maurice; Picard, Michel

2015-01-01

Noise exposure in the workplace is a common reality in Québec, Canada as it is elsewhere. However, the extent to which noise acts as a causal or contributive factor in industrial work-related accidents has not been studied thoroughly despite its plausibility. This article aims to describe the importance or potential importance, during investigations looking into the specific causes of each work-related fatal accident, of noise as an explanatory factor. The written information contained in the accident reports pertaining to contextual and technical elements were used. The study used multiple case qualitative content analysis. This descriptive study was based on the content analysis of the 788 reports from the Commission de la santé et de la sécurité du travail du Québec [Workers' Compensation Board (WCB)] investigating the fatal work-related accidents between 1990 and 2005. The study was descriptive (number and percentages). Noise was explicitly stated as one of the explanatory factors for the fatal outcome in 2.2% (17/788) of the fatal accidents, particularly when the work involved vehicular movement or the need to communicate between workers. Noise was not typically considered a unique cause in the accident, notably because the investigators considered that the accident would have probably occurred due to other risk factors (for example, disregard of safety rules, shortcomings in work methods, and inadequate training). Noise is an important risk factor when communication is involved in work. Since noise is ubiquitous and may also interfere with vigilance and other risk factors for accidents, it may be a much more important contributing factor to accidents than is currently recognized.

Explanatory models of addictive behaviour among native German, Russian-German, and Turkish youth.

PubMed

Penka, S; Heimann, H; Heinz, A; Schouler-Ocak, M

2008-01-01

In Germany, the public system of addiction treatment is used less by migrants with addictive disorders than by their non-migrant counterparts. To date, the literature has focused primarily on language, sociocultural factors, and residence status when discussing access barriers to this part of the health care system. However, little attention has been paid to cultural differences in explanatory models of addictive behaviour. This is surprising when we consider the important role played by popular knowledge in a population's perceptions of and responses to illnesses, including their causes, symptoms, and treatment. In the present study, we examined explanatory models of addictive behaviour and of mental disorders in 124 native German und Russian-German youth and compared these models to those observed in an earlier study of 144 German and Turkish youth. We employed the free listing technique German and to compile the terms that participating subjects used to describe addictive behaviour. Subsequently, we examined how a subset of our study population assigned these terms to the respective disorders by means of the pile sort method. Although the explanatory models used by the German and Russian-German youth in our study were surprisingly similar, those employed by Turkish youth did not make any fundamental distinction between illegal and legal drugs (e.g. alcohol and nicotine). German and Russian-German youth regarded eating disorders as "embarrassing" or "disgraceful", but Turkish youth did not. Unlike our German and Russian-German subjects, the Turkish youth did not classify eating disorders as being addictive in nature. Moreover, medical concepts crucial to a proper understanding of dependence disorders (e.g. the term "physical dependence") were characterised by almost half of our Turkish subjects as useless in describing addictions. These findings show that it is impossible to translate medical or everyday concepts of disease and treatment properly into a different

Parental explanatory models of ADHD: gender and cultural variations.

PubMed

Bussing, Regina; Gary, Faye A; Mills, Terry L; Garvan, Cynthia Wilson

2003-10-01

This study describes parents' explanatory models of Attention Deficit Hyperactivity Disorder (ADHD) and examines model variation by child characteristics. Children with ADHD (N = 182) were identified from a school district population of elementary school students. A reliable coding system was developed for parental responses obtained in ethnographic interviews in order to convert qualitative into numerical data for quantitative analysis. African-American parents were less likely to connect the school system to ADHD problem identification, expressed fewer worries about ADHD-related school problems, and voiced fewer preferences for school interventions than Caucasian parents, pointing to a potential disconnect with the school system. More African-American than Caucasian parents were unsure about potential causes of and treatments for ADHD, indicating a need for culturally appropriate parent education approaches.

Explanatory models and openness about dementia in migrant communities: A qualitative study among female family carers.

PubMed

van Wezel, Nienke; Francke, Anneke L; Kayan Acun, Emine; Devillé, Walter Ljm; van Grondelle, Nies J; Blom, Marco M

2016-06-15

The prevalence of dementia is increasing among people with a Turkish, Moroccan and Surinamese-Creole background. Because informal care is very important in these communities, it is pertinent to see what explanations female family carers have for dementia and whether they can discuss dementia openly within the community and the family. Forty-one individual interviews and six focus group interviews (n = 28) were held with female Turkish, Moroccan and Surinamese Creole family carers who are looking after a close relative with dementia, and who live in The Netherlands. Qualitative analysis has been carried out, supported by the software MaxQda. The dominant explanations of dementia given by the female family carers interviewed are in line with what Downs et al. describe as the explanatory models 'dementia as a normal ageing process' and 'dementia as a spiritual experience'. In addition, some female family carers gave explanations that were about an interplay between various factors. Turkish and Moroccan informal caregivers ascribe the causes of dementia relatively often to life events or personality traits, whereas Surinamese Creole caregivers frequently mention physical aspects, such as past dehydration. However, the explanatory model 'dementia as a neuropsychiatric condition', which is dominant in Western cultures, was rarely expressed by the informal caregivers. The female family carers generally talked openly about the dementia with their close family, whereas particularly in the Turkish and Moroccan communities open communication within the broader communities was often hampered, e.g. by feelings of shame. Female family carers of Turkish, Moroccan or Surinamese Creole backgrounds often consider dementia as a natural consequence of ageing, as a spiritual experience, and/or as an interplay between various factors. They feel they can talk openly about dementia within their close family, while outside the close family this is often more difficult. © The Author

Infection Elicited Autoimmunity and Myalgic Encephalomyelitis/Chronic Fatigue Syndrome: An Explanatory Model

PubMed Central

Blomberg, Jonas; Gottfries, Carl-Gerhard; Elfaitouri, Amal; Rizwan, Muhammad; Rosén, Anders

2018-01-01

Myalgic encephalomyelitis (ME) often also called chronic fatigue syndrome (ME/CFS) is a common, debilitating, disease of unknown origin. Although a subject of controversy and a considerable scientific literature, we think that a solid understanding of ME/CFS pathogenesis is emerging. In this study, we compiled recent findings and placed them in the context of the clinical picture and natural history of the disease. A pattern emerged, giving rise to an explanatory model. ME/CFS often starts after or during an infection. A logical explanation is that the infection initiates an autoreactive process, which affects several functions, including brain and energy metabolism. According to our model for ME/CFS pathogenesis, patients with a genetic predisposition and dysbiosis experience a gradual development of B cell clones prone to autoreactivity. Under normal circumstances these B cell offsprings would have led to tolerance. Subsequent exogenous microbial exposition (triggering) can lead to comorbidities such as fibromyalgia, thyroid disorder, and orthostatic hypotension. A decisive infectious trigger may then lead to immunization against autoantigens involved in aerobic energy production and/or hormone receptors and ion channel proteins, producing postexertional malaise and ME/CFS, affecting both muscle and brain. In principle, cloning and sequencing of immunoglobulin variable domains could reveal the evolution of pathogenic clones. Although evidence consistent with the model accumulated in recent years, there are several missing links in it. Hopefully, the hypothesis generates testable propositions that can augment the understanding of the pathogenesis of ME/CFS. PMID:29497420

Measuring change for a multidimensional test using a generalized explanatory longitudinal item response model.

PubMed

Cho, Sun-Joo; Athay, Michele; Preacher, Kristopher J

2013-05-01

Even though many educational and psychological tests are known to be multidimensional, little research has been done to address how to measure individual differences in change within an item response theory framework. In this paper, we suggest a generalized explanatory longitudinal item response model to measure individual differences in change. New longitudinal models for multidimensional tests and existing models for unidimensional tests are presented within this framework and implemented with software developed for generalized linear models. In addition to the measurement of change, the longitudinal models we present can also be used to explain individual differences in change scores for person groups (e.g., learning disabled students versus non-learning disabled students) and to model differences in item difficulties across item groups (e.g., number operation, measurement, and representation item groups in a mathematics test). An empirical example illustrates the use of the various models for measuring individual differences in change when there are person groups and multiple skill domains which lead to multidimensionality at a time point. © 2012 The British Psychological Society.

Examination of the Relation between TEOG Score of Turkish Revolution History and Kemalism Course and Reading Comprehension Skill (An Example of Explanatory Sequential Mixed Design)

ERIC Educational Resources Information Center

Yuvaci, Ibrahim; Demir, Selçuk Besir

2016-01-01

This paper is aimed to determine the relation between reading comprehension skill and TEOG success. In this research, a mixed research method, sequential explanatory mixed design, is utilized to examine the relation between reading comprehension skills and TEOG success of 8th grade students throughly. In explanatory sequential mixed design…

Parents' and Speech and Language Therapists' Explanatory Models of Language Development, Language Delay and Intervention

ERIC Educational Resources Information Center

Marshall, Julie; Goldbart, Juliet; Phillips, Julie

2007-01-01

Background: Parental and speech and language therapist (SLT) explanatory models may affect engagement with speech and language therapy, but there has been dearth of research in this area. This study investigated parents' and SLTs' views about language development, delay and intervention in pre-school children with language delay. Aims: The aims…

Why Do Adolescents Use Drugs? A Common Sense Explanatory Model from the Social Actor's Perspective

ERIC Educational Resources Information Center

Nuno-Gutierrez, Bertha Lidia; Rodriguez-Cerda, Oscar; Alvarez-Nemegyei, Jose

2006-01-01

Analysis was made of the common sense explanations of 60 Mexican teenage illicit drug users in rehabilitation to determine their drug use debut. The explanatory model was separated into three blocks, two of which contained common sense aspects: interaction between subject's plane and the collectivity; and relationship between subject's interior…

Accentuate the Positive: The Relationship between Positive Explanatory Style and Academic Achievement of Prospective Elementary Teachers

ERIC Educational Resources Information Center

Boyer, Wanda

2006-01-01

This research examines 480 current event-explanation units using the CAVE technique (Schulman, Castellon, & Seligman, 1989) to note the relationship between positive and negative explanatory style and achievement of prospective early childhood and upper elementary female teachers. This study found a significant positive relationship between…

The Symmetry Rule: A Seven-Year Study of Symptoms and Explanatory Labels Among GulfWar Veterans

PubMed Central

Brewer, Noel T.; Hallman, William K.; Kipen, Howard M.

2014-01-01

Noticing medical symptoms can cause one to search for explanatory labels such as “ate bad food” or even “exposed to anthrax,” and perhaps these labels may cause new symptom reports. The present study examined whether there is empirical support for this symptom-label “symmetry rule.” We interviewed veterans (N = 362) from the Gulf War Registry in 1995 and 2002 about their medical symptoms and about their exposure to war-related hazards and stressors. Health symptom reports were strongly correlated between the two time periods and showed relatively stable mean levels, whereas recall of war-related exposures was notably unstable. Veterans starting with fewer medical symptoms recalled fewer war-related exposures seven years later. Initial recollection of chemical and biological warfare exposure (but not other exposures) longitudinally predicted novel medical symptoms. The findings generally support the symmetry rule hypotheses, although the evidence for the label to symptom link was less strong. The findings account for some variability in symptoms and exposure recall over time, but they do not, on their own, account for the Gulf War veterans’ elevated number of unexplained medical symptoms. PMID:18795995

Explanatory pluralism: An unrewarding prediction error for free energy theorists.

PubMed

Colombo, Matteo; Wright, Cory

2017-03-01

Courtesy of its free energy formulation, the hierarchical predictive processing theory of the brain (PTB) is often claimed to be a grand unifying theory. To test this claim, we examine a central case: activity of mesocorticolimbic dopaminergic (DA) systems. After reviewing the three most prominent hypotheses of DA activity-the anhedonia, incentive salience, and reward prediction error hypotheses-we conclude that the evidence currently vindicates explanatory pluralism. This vindication implies that the grand unifying claims of advocates of PTB are unwarranted. More generally, we suggest that the form of scientific progress in the cognitive sciences is unlikely to be a single overarching grand unifying theory. Copyright © 2016 Elsevier Inc. All rights reserved.

Selection of relevant input variables in storm water quality modeling by multiobjective evolutionary polynomial regression paradigm

NASA Astrophysics Data System (ADS)

Creaco, E.; Berardi, L.; Sun, Siao; Giustolisi, O.; Savic, D.

2016-04-01

The growing availability of field data, from information and communication technologies (ICTs) in "smart" urban infrastructures, allows data modeling to understand complex phenomena and to support management decisions. Among the analyzed phenomena, those related to storm water quality modeling have recently been gaining interest in the scientific literature. Nonetheless, the large amount of available data poses the problem of selecting relevant variables to describe a phenomenon and enable robust data modeling. This paper presents a procedure for the selection of relevant input variables using the multiobjective evolutionary polynomial regression (EPR-MOGA) paradigm. The procedure is based on scrutinizing the explanatory variables that appear inside the set of EPR-MOGA symbolic model expressions of increasing complexity and goodness of fit to target output. The strategy also enables the selection to be validated by engineering judgement. In such context, the multiple case study extension of EPR-MOGA, called MCS-EPR-MOGA, is adopted. The application of the proposed procedure to modeling storm water quality parameters in two French catchments shows that it was able to significantly reduce the number of explanatory variables for successive analyses. Finally, the EPR-MOGA models obtained after the input selection are compared with those obtained by using the same technique without benefitting from input selection and with those obtained in previous works where other data-modeling techniques were used on the same data. The comparison highlights the effectiveness of both EPR-MOGA and the input selection procedure.

Categorization and analysis of explanatory writing in mathematics

NASA Astrophysics Data System (ADS)

Craig, Tracy S.

2011-10-01

The aim of this article is to present a scheme for coding and categorizing students' written explanations of mathematical problem-solving activities. The scheme was used successfully within a study project carried out to determine whether student problem-solving behaviour could be positively affected by writing explanatory strategies to mathematical problem-solving processes. The rationale for the study was the recognized importance of mathematical problem-solving, the widely acknowledged challenge of teaching problem-solving skills directly and the evidence in the literature that writing in mathematics provides a tool for learning. The study was carried out in a first-year mathematics course at the University of Cape Town, South Africa. Students' written submissions were categorized and analysed through use of an adaptation of a journal entry classification scheme. The scheme successfully observed positive changes over the experimental period in students' level of engagement with the mathematical material and with their stance towards knowledge.

Refinement of regression models to estimate real-time concentrations of contaminants in the Menomonee River drainage basin, southeast Wisconsin, 2008-11

USGS Publications Warehouse

Baldwin, Austin K.; Robertson, Dale M.; Saad, David A.; Magruder, Christopher

2013-01-01

In 2008, the U.S. Geological Survey and the Milwaukee Metropolitan Sewerage District initiated a study to develop regression models to estimate real-time concentrations and loads of chloride, suspended solids, phosphorus, and bacteria in streams near Milwaukee, Wisconsin. To collect monitoring data for calibration of models, water-quality sensors and automated samplers were installed at six sites in the Menomonee River drainage basin. The sensors continuously measured four potential explanatory variables: water temperature, specific conductance, dissolved oxygen, and turbidity. Discrete water-quality samples were collected and analyzed for five response variables: chloride, total suspended solids, total phosphorus, Escherichia coli bacteria, and fecal coliform bacteria. Using the first year of data, regression models were developed to continuously estimate the response variables on the basis of the continuously measured explanatory variables. Those models were published in a previous report. In this report, those models are refined using 2 years of additional data, and the relative improvement in model predictability is discussed. In addition, a set of regression models is presented for a new site in the Menomonee River Basin, Underwood Creek at Wauwatosa. The refined models use the same explanatory variables as the original models. The chloride models all used specific conductance as the explanatory variable, except for the model for the Little Menomonee River near Freistadt, which used both specific conductance and turbidity. Total suspended solids and total phosphorus models used turbidity as the only explanatory variable, and bacteria models used water temperature and turbidity as explanatory variables. An analysis of covariance (ANCOVA), used to compare the coefficients in the original models to those in the refined models calibrated using all of the data, showed that only 3 of the 25 original models changed significantly. Root-mean-squared errors (RMSEs

Perceived Problem-Solving Deficits and Suicidal Ideation: Evidence for the Explanatory Roles of Thwarted Belongingness and Perceived Burdensomeness in Five Samples.

PubMed

Chu, Carol; Walker, Kristin L; Stanley, Ian H; Hirsch, Jameson K; Greenberg, Jeffrey H; Rudd, M David; Joiner, Thomas E

2017-06-26

Perceived social problem-solving deficits are associated with suicide risk; however, little research has examined the mechanisms underlying this relationship. The interpersonal theory of suicide proposes 2 mechanisms in the pathogenesis of suicidal desire: intractable feelings of thwarted belongingness (TB) and perceived burdensomeness (PB). This study tested whether TB and PB serve as explanatory links in the relationship between perceived social problem-solving (SPS) deficits and suicidal thoughts and behaviors cross-sectionally and longitudinally. The specificity of TB and PB was evaluated by testing depression as a rival mediator. Self-report measures of perceived SPS deficits, TB, PB, suicidal ideation, and depression were administered in 5 adult samples: 336 and 105 undergraduates from 2 universities, 53 homeless individuals, 222 primary care patients, and 329 military members. Bias-corrected bootstrap mediation and meta-analyses were conducted to examine the magnitude of the direct and indirect effects, and the proposed mediation paths were tested using zero-inflated negative binomial regressions. Cross-sectionally, TB and PB were significant parallel mediators of the relationship between perceived SPS deficits and ideation, beyond depression. Longitudinally and beyond depression, in 1 study, both TB and PB emerged as significant explanatory factors, and in the other, only PB was a significant mediator. Findings supported the specificity of TB and PB: Depression and SPS deficits were not significant mediators. The relationship between perceived SPS deficits and ideation was explained by interpersonal theory variables, particularly PB. Findings support a novel application of the interpersonal theory, and bolster a growing compendium of literature implicating perceived SPS deficits in suicide risk. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

Extending the explanatory utility of the EPPM beyond fear-based persuasion.

PubMed

Lewis, Ioni; Watson, Barry; White, Katherine M

2013-01-01

In the 20 years since its inception, the Extended Parallel Process Model (EPPM) has attracted much empirical support. Currently, and unsurprisingly, given that is a model of fear-based persuasion, the EPPM's explanatory utility has been based only upon fear-based messages. However, an argument is put forth herein that draws upon existing evidence that the EPPM may be an efficacious framework for explaining the persuasive process and outcomes of emotion-based messages more broadly when such messages are addressing serious health topics. For the current study, four different types of emotional appeals were purposefully devised and included a fear-, an annoyance/agitation-, a pride-, and a humor-based message. All messages addressed the serious health issue of road safety, and in particular the risky behavior of speeding. Participants (n = 551) were exposed to only one of the four messages and subsequently provided responses within a survey. A series of 2 (threat: low, high) × 2 (efficacy: low, high) analysis of variance was conducted for each of the appeals based on the EPPM's message outcomes of acceptance and rejection. Support was found for the EPPM with a number of main effects of threat and efficacy emerging, reflecting that, irrespective of emotional appeal type, high levels of threat and efficacy enhanced message outcomes via maximizing acceptance and minimizing rejection. Theoretically, the findings provide support for the explanatory utility of the EPPM for emotion-based health messages more broadly. In an applied sense, the findings highlight the value of adopting the EPPM as a framework when devising and evaluating emotion-based health messages for serious health topics.

The Predictive Influence of Family and Community Demographic Variables on Grade 7 Student Achievement in Language Arts and Mathematics

ERIC Educational Resources Information Center

Wolfe, Adam

2016-01-01

This correlational, explanatory, longitudinal study sought to determine the combination of community and family-level demographic variables found in the 2010 U.S. Census data that most accurately predicted a New Jersey school district's percentage of students scoring proficient or above on the 2010, 2011, and 2012 NJ ASK 7 in Language Arts and…

CAVEing the MMPI for an Optimism-Pessimism Scale: Seligman's Attributional Model and the Assessment of Explanatory Style.

ERIC Educational Resources Information Center

Colligan, Robert C.; And Others

1994-01-01

Developed bipolar Minnesota Multiphasic Personality Inventory (MMPI) Optimism-Pessimism (PSM) scale based on results on Content Analysis of Verbatim Explanation applied to MMPI. Reliability and validity indices show that PSM scale is highly accurate and consistent with Seligman's theory that pessimistic explanatory style predicts increased…

Appreciative Accreditation: A Mixed Methods Explanatory Study of Appreciative Inquiry-Based Institutional Effectiveness Results in Higher Education

ERIC Educational Resources Information Center

Thibodeau, John

2011-01-01

This study examined the effects of using Appreciative Inquiry in accreditation and related institutional effectiveness activities within higher education. Using an explanatory participant-selection mixed methods approach, qualitative data from a series of interviews were used to explain the experiences of individuals identified from quantitative…

Use of generalised additive models to categorise continuous variables in clinical prediction

PubMed Central

2013-01-01

Background In medical practice many, essentially continuous, clinical parameters tend to be categorised by physicians for ease of decision-making. Indeed, categorisation is a common practice both in medical research and in the development of clinical prediction rules, particularly where the ensuing models are to be applied in daily clinical practice to support clinicians in the decision-making process. Since the number of categories into which a continuous predictor must be categorised depends partly on the relationship between the predictor and the outcome, the need for more than two categories must be borne in mind. Methods We propose a categorisation methodology for clinical-prediction models, using Generalised Additive Models (GAMs) with P-spline smoothers to determine the relationship between the continuous predictor and the outcome. The proposed method consists of creating at least one average-risk category along with high- and low-risk categories based on the GAM smooth function. We applied this methodology to a prospective cohort of patients with exacerbated chronic obstructive pulmonary disease. The predictors selected were respiratory rate and partial pressure of carbon dioxide in the blood (PCO2), and the response variable was poor evolution. An additive logistic regression model was used to show the relationship between the covariates and the dichotomous response variable. The proposed categorisation was compared to the continuous predictor as the best option, using the AIC and AUC evaluation parameters. The sample was divided into a derivation (60%) and validation (40%) samples. The first was used to obtain the cut points while the second was used to validate the proposed methodology. Results The three-category proposal for the respiratory rate was ≤ 20;(20,24];> 24, for which the following values were obtained: AIC=314.5 and AUC=0.638. The respective values for the continuous predictor were AIC=317.1 and AUC=0.634, with no statistically

A non-linear data mining parameter selection algorithm for continuous variables

PubMed Central

Razavi, Marianne; Brady, Sean

2017-01-01

In this article, we propose a new data mining algorithm, by which one can both capture the non-linearity in data and also find the best subset model. To produce an enhanced subset of the original variables, a preferred selection method should have the potential of adding a supplementary level of regression analysis that would capture complex relationships in the data via mathematical transformation of the predictors and exploration of synergistic effects of combined variables. The method that we present here has the potential to produce an optimal subset of variables, rendering the overall process of model selection more efficient. This algorithm introduces interpretable parameters by transforming the original inputs and also a faithful fit to the data. The core objective of this paper is to introduce a new estimation technique for the classical least square regression framework. This new automatic variable transformation and model selection method could offer an optimal and stable model that minimizes the mean square error and variability, while combining all possible subset selection methodology with the inclusion variable transformations and interactions. Moreover, this method controls multicollinearity, leading to an optimal set of explanatory variables. PMID:29131829

Continuous water-quality monitoring and regression analysis to estimate constituent concentrations and loads in the Sheyenne River, North Dakota, 1980-2006

USGS Publications Warehouse

Ryberg, Karen R.

2007-01-01

This report presents the results of a study by the U.S. Geological Survey, done in cooperation with the North Dakota State Water Commission, to estimate water-quality constituent concentrations at seven sites on the Sheyenne River, N. Dak. Regression analysis of water-quality data collected in 1980-2006 was used to estimate concentrations for hardness, dissolved solids, calcium, magnesium, sodium, and sulfate. The explanatory variables examined for the regression relations were continuously monitored streamflow, specific conductance, and water temperature. For the conditions observed in 1980-2006, streamflow was a significant explanatory variable for some constituents. Specific conductance was a significant explanatory variable for all of the constituents, and water temperature was not a statistically significant explanatory variable for any of the constituents in this study. The regression relations were evaluated using common measures of variability, including R2, the proportion of variability in the estimated constituent concentration explained by the explanatory variables and regression equation. R2 values ranged from 0.784 for calcium to 0.997 for dissolved solids. The regression relations also were evaluated by calculating the median relative percentage difference (RPD) between measured constituent concentration and the constituent concentration estimated by the regression equations. Median RPDs ranged from 1.7 for dissolved solids to 11.5 for sulfate. The regression relations also may be used to estimate daily constituent loads. The relations should be monitored for change over time, especially at sites 2 and 3 which have a short period of record. In addition, caution should be used when the Sheyenne River is affected by ice or when upstream sites are affected by isolated storm runoff. Almost all of the outliers and highly influential samples removed from the analysis were made during periods when the Sheyenne River might be affected by ice.

Design of an impact evaluation using a mixed methods model--an explanatory assessment of the effects of results-based financing mechanisms on maternal healthcare services in Malawi.

PubMed

Brenner, Stephan; Muula, Adamson S; Robyn, Paul Jacob; Bärnighausen, Till; Sarker, Malabika; Mathanga, Don P; Bossert, Thomas; De Allegri, Manuela

2014-04-22

. Combining a traditional quasi-experimental controlled pre- and post-test design with an explanatory mixed methods model permits an additional assessment of organizational and behavioral changes affecting complex processes. Through this impact evaluation approach, our design will not only create robust evidence measures for the outcome of interest, but also generate insights on how and why the investigated interventions produce certain intended and unintended effects and allows for a more in-depth evaluation approach.

The influences of canopy species and topographic variables on understory species diversity and composition in coniferous forests.

PubMed

Huo, Hong; Feng, Qi; Su, Yong-hong

2014-01-01

Understanding the factors that influence the distribution of understory vegetation is important for biological conservation and forest management. We compared understory species composition by multi-response permutation procedure and indicator species analysis between plots dominated by Qinghai spruce (Picea crassifolia Kom.) and Qilian juniper (Sabina przewalskii Kom.) in coniferous forests of the Qilian Mountains, northwestern China. Understory species composition differed markedly between the forest types. Many heliophilous species were significantly associated with juniper forest, while only one species was indicative of spruce forest. Using constrained ordination and the variation partitioning model, we quantitatively assessed the relative effects of two sets of explanatory variables on understory species composition. The results showed that topographic variables had higher explanatory power than did site conditions for understory plant distributions. However, a large amount of the variation in understory species composition remained unexplained. Forward selection revealed that understory species distributions were primarily affected by elevation and aspect. Juniper forest had higher species richness and α-diversity and lower β-diversity in the herb layer of the understory plant community than spruce forest, suggesting that the former may be more important in maintaining understory biodiversity and community stability in alpine coniferous forest ecosystems.

Robust best linear estimator for Cox regression with instrumental variables in whole cohort and surrogates with additive measurement error in calibration sample.

PubMed

Wang, Ching-Yun; Song, Xiao

2016-11-01

Biomedical researchers are often interested in estimating the effect of an environmental exposure in relation to a chronic disease endpoint. However, the exposure variable of interest may be measured with errors. In a subset of the whole cohort, a surrogate variable is available for the true unobserved exposure variable. The surrogate variable satisfies an additive measurement error model, but it may not have repeated measurements. The subset in which the surrogate variables are available is called a calibration sample. In addition to the surrogate variables that are available among the subjects in the calibration sample, we consider the situation when there is an instrumental variable available for all study subjects. An instrumental variable is correlated with the unobserved true exposure variable, and hence can be useful in the estimation of the regression coefficients. In this paper, we propose a nonparametric method for Cox regression using the observed data from the whole cohort. The nonparametric estimator is the best linear combination of a nonparametric correction estimator from the calibration sample and the difference of the naive estimators from the calibration sample and the whole cohort. The asymptotic distribution is derived, and the finite sample performance of the proposed estimator is examined via intensive simulation studies. The methods are applied to the Nutritional Biomarkers Study of the Women's Health Initiative. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Robust best linear estimator for Cox regression with instrumental variables in whole cohort and surrogates with additive measurement error in calibration sample

PubMed Central

Wang, Ching-Yun; Song, Xiao

2017-01-01

SUMMARY Biomedical researchers are often interested in estimating the effect of an environmental exposure in relation to a chronic disease endpoint. However, the exposure variable of interest may be measured with errors. In a subset of the whole cohort, a surrogate variable is available for the true unobserved exposure variable. The surrogate variable satisfies an additive measurement error model, but it may not have repeated measurements. The subset in which the surrogate variables are available is called a calibration sample. In addition to the surrogate variables that are available among the subjects in the calibration sample, we consider the situation when there is an instrumental variable available for all study subjects. An instrumental variable is correlated with the unobserved true exposure variable, and hence can be useful in the estimation of the regression coefficients. In this paper, we propose a nonparametric method for Cox regression using the observed data from the whole cohort. The nonparametric estimator is the best linear combination of a nonparametric correction estimator from the calibration sample and the difference of the naive estimators from the calibration sample and the whole cohort. The asymptotic distribution is derived, and the finite sample performance of the proposed estimator is examined via intensive simulation studies. The methods are applied to the Nutritional Biomarkers Study of the Women’s Health Initiative. PMID:27546625

Variables affecting learning in a simulation experience: a mixed methods study.

PubMed

Beischel, Kelly P

2013-02-01

The primary purpose of this study was to test a hypothesized model describing the direct effects of learning variables on anxiety and cognitive learning outcomes in a high-fidelity simulation (HFS) experience. The secondary purpose was to explain and explore student perceptions concerning the qualities and context of HFS affecting anxiety and learning. This study used a mixed methods quantitative-dominant explanatory design with concurrent qualitative data collection to examine variables affecting learning in undergraduate, beginning nursing students (N = 124). Being ready to learn, having a strong auditory-verbal learning style, and being prepared for simulation directly affected anxiety, whereas learning outcomes were directly affected by having strong auditory-verbal and hands-on learning styles. Anxiety did not quantitatively mediate cognitive learning outcomes as theorized, although students qualitatively reported debilitating levels of anxiety. This study advances nursing education science by providing evidence concerning variables affecting learning outcomes in HFS.

Evaluation of alternative model selection criteria in the analysis of unimodal response curves using CART

USGS Publications Warehouse

Ribic, C.A.; Miller, T.W.

1998-01-01

We investigated CART performance with a unimodal response curve for one continuous response and four continuous explanatory variables, where two variables were important (ie directly related to the response) and the other two were not. We explored performance under three relationship strengths and two explanatory variable conditions: equal importance and one variable four times as important as the other. We compared CART variable selection performance using three tree-selection rules ('minimum risk', 'minimum risk complexity', 'one standard error') to stepwise polynomial ordinary least squares (OLS) under four sample size conditions. The one-standard-error and minimum-risk-complexity methods performed about as well as stepwise OLS with large sample sizes when the relationship was strong. With weaker relationships, equally important explanatory variables and larger sample sizes, the one-standard-error and minimum-risk-complexity rules performed better than stepwise OLS. With weaker relationships and explanatory variables of unequal importance, tree-structured methods did not perform as well as stepwise OLS. Comparing performance within tree-structured methods, with a strong relationship and equally important explanatory variables, the one-standard-error-rule was more likely to choose the correct model than were the other tree-selection rules 1) with weaker relationships and equally important explanatory variables; and 2) under all relationship strengths when explanatory variables were of unequal importance and sample sizes were lower.

Child maltreatment among Asian Americans: characteristics and explanatory framework.

PubMed

Fuhua Zhai; Qin Gao

2009-05-01

This article systematically reviews the characteristics of child maltreatment among Asian Americans and provides a theoretical explanatory framework. The reported rate of child maltreatment among Asian Americans is disproportionately low. A high rate of physical abuse and low rates of neglect and sexual abuse are found among Asian American victims. Some protective factors (e.g., the emphasis on family harmony and reputation and the indulgence to infants and toddlers) may lead to low probability of child maltreatment among Asian Americans. Some others (e.g., parental authority and beliefs in physical punishment) may be risk factors of child maltreatment, especially physical abuse. Meanwhile, many other coexisting factors (e.g., children's obedience to parents and families' invisibility to authorities) may prohibit child maltreatment from being disclosed. Therefore, the overall low reported rate of child maltreatment among Asian Americans may be a combination of low incidence and underreporting. Implications for practice and research are discussed.

Spatiotemporal variability in wildfire patterns and analysis of the main drivers in Honduras using GIS and MODIS data

NASA Astrophysics Data System (ADS)

Valdez Vasquez, M. C.; Chen, C. F.

2017-12-01

Wildfires are unrestrained fires in an area of flammable vegetation and they are one of the most frequent disasters in Honduras during the dry season. During this period, anthropogenic activity combined with the harsh climatic conditions, dry vegetation and topographical variables, cause a large amount of wildfires. For this reason, there is a need to identify the drivers of wildfires and their susceptibility variations during the wildfire season. In this study, we combined the wildfire points during the 2010-2016 period every 8 days with a series of variables using the random forest (RF) algorithm. In addition to the wildfire points, we randomly generated a similar amount of background points that we use as pseudo-absence data. To represent the human imprint, we included proximity to different types of roads, trails, settlements and agriculture sites. Other variables included are the Moderate Resolution Imaging Spectra-radiometer (MODIS)-derived 8-day composites of land surface temperature (LST) and the normalized multi-band drought index (NMDI), derived from the MODIS surface reflectance data. We also included monthly average precipitation, solar radiation, and topographical variables. The exploratory analysis of the variables reveals that low precipitation combined with the low NMDI and accessibility to non-paved roads were the major drivers of wildfires during the early months of the dry season. During April, which is the peak of the dry season, the explanatory variables of relevance also included elevation and LST in addition to the proximity to paved and non-paved roads. During May, proximity to crops becomes relevant, in addition to the aforesaid variables. The average estimated area with high and very high wildfire susceptibility was 22% of the whole territory located mainly in the central and eastern regions, drifting towards the northeast areas during May. We validated the results using the area under the receiver operating characteristic (ROC) curve (AUC

Major histocompatibility complex harbors widespread genotypic variability of non-additive risk of rheumatoid arthritis including epistasis.

PubMed

Wei, Wen-Hua; Bowes, John; Plant, Darren; Viatte, Sebastien; Yarwood, Annie; Massey, Jonathan; Worthington, Jane; Eyre, Stephen

2016-04-25

Genotypic variability based genome-wide association studies (vGWASs) can identify potentially interacting loci without prior knowledge of the interacting factors. We report a two-stage approach to make vGWAS applicable to diseases: firstly using a mixed model approach to partition dichotomous phenotypes into additive risk and non-additive environmental residuals on the liability scale and secondly using the Levene's (Brown-Forsythe) test to assess equality of the residual variances across genotype groups per marker. We found widespread significant (P < 2.5e-05) vGWAS signals within the major histocompatibility complex (MHC) across all three study cohorts of rheumatoid arthritis. We further identified 10 epistatic interactions between the vGWAS signals independent of the MHC additive effects, each with a weak effect but jointly explained 1.9% of phenotypic variance. PTPN22 was also identified in the discovery cohort but replicated in only one independent cohort. Combining the three cohorts boosted power of vGWAS and additionally identified TYK2 and ANKRD55. Both PTPN22 and TYK2 had evidence of interactions reported elsewhere. We conclude that vGWAS can help discover interacting loci for complex diseases but require large samples to find additional signals.

'Individualism-collectivism' as an explanatory device for mental illness stigma.

PubMed

Papadopoulos, Chris; Foster, John; Caldwell, Kay

2013-06-01

The aim of this study is investigate whether the cross-cultural value paradigm 'individualism-collectivism' is a useful explanatory model for mental illness stigma on a cultural level. Using snowball sampling, a quantitative questionnaire survey of 305 individuals from four UK-based cultural groups (white-English, American, Greek/Greek Cypriot, and Chinese) was carried out. The questionnaire included the 'Community Attitudes to Mental Illness scale' and the 'vertical-horizontal individualism-collectivism scale'. The results revealed that the more stigmatizing a culture's mental illness attitudes are, the more likely collectivism effectively explains these attitudes. In contrast, the more positive a culture's mental illness attitudes, the more likely individualism effectively explains attitudes. We conclude that a consideration of the individualism-collectivism paradigm should be included in any future research aiming to provide a holistic understanding of the causes of mental illness stigma, particularly when the cultures stigmatization levels are particularly high or low.

Classification of natural and supernatural causes of mental distress. Development of a Mental Distress Explanatory Model Questionnaire.

PubMed

Eisenbruch, M

1990-11-01

This paper describes the background and development of a Mental Distress Explanatory Model Questionnaire designed to explore how people from different cultures explain mental distress. A 45-item questionnaire was developed with items derived from the Murdock et al. categories, with additional items covering western notions of physiological causation and stress. The questionnaire was administered to 261 people, mostly college students. Multi-dimensional scaling analysis shows four clusters of mental distress: a) stress; b) western physiological; c) nonwestern physiological; and d) supernatural. These clusters form two dimensions: western physiological vs. supernatural and impersonal vs. personalistic explanations. Natural and stress items are separated from supernatural and nonwestern physiological items along the first dimension. Brain damage, physical illness, and genetic defects have the greatest separation along the first dimension. Being hot, the body being out of balance, and wind currents passing through the body most strongly represent the non-western physiological category. The questionnaire has the potential to be used for community health screening and for monitoring patient care, as well as with students in the health sciences and with health practitioners.

Interparental Conflict and Children's School Adjustment: The Explanatory Role of Children's Internal Representations of Interparental and Parent-Child Relationships

ERIC Educational Resources Information Center

Sturge-Apple, Melissa L.; Davies, Patrick T.; Winter, Marcia A.; Cummings, E. Mark; Schermerhorn, Alice

2008-01-01

This study examined how children's insecure internal representations of interparental and parent-child relationships served as explanatory mechanisms in multiple pathways linking interparental conflict and parent emotional unavailability with the emotional and classroom engagement difficulties the children had in their adjustment to school. With…

Testing an explanatory model of nurses' intention to report adverse drug reactions in hospital settings.

PubMed

Angelis, Alessia De; Pancani, Luca; Steca, Patrizia; Colaceci, Sofia; Giusti, Angela; Tibaldi, Laura; Alvaro, Rosaria; Ausili, Davide; Vellone, Ercole

2017-05-01

To test an explanatory model of nurses' intention to report adverse drug reactions in hospital settings, based on the theory of planned behaviour. Under-reporting of adverse drug reactions is an important problem among nurses. A cross-sectional design was used. Data were collected with the adverse drug reporting nurses' questionnaire. Confirmatory factor analysis was performed to test the factor validity of the adverse drug reporting nurses' questionnaire, and structural equation modelling was used to test the explanatory model. The convenience sample comprised 500 Italian hospital nurses (mean age = 43.52). Confirmatory factor analysis supported the factor validity of the adverse drug reporting nurses' questionnaire. The structural equation modelling showed a good fit with the data. Nurses' intention to report adverse drug reactions was significantly predicted by attitudes, subjective norms and perceived behavioural control (R² = 0.16). The theory of planned behaviour effectively explained the mechanisms behind nurses' intention to report adverse drug reactions, showing how several factors come into play. In a scenario of organisational empowerment towards adverse drug reaction reporting, the major predictors of the intention to report are support for the decision to report adverse drug reactions from other health care practitioners, perceptions about the value of adverse drug reaction reporting and nurses' favourable self-assessment of their adverse drug reaction reporting skills. © 2017 John Wiley & Sons Ltd.

Azúcar y nervios: explanatory models and treatment experiences of Hispanics with diabetes and depression.

PubMed

Cabassa, Leopoldo J; Hansen, Marissa C; Palinkas, Lawrence A; Ell, Kathleen

2008-06-01

This study examined the explanatory models of depression, perceived relationships between diabetes and depression, and depression treatment experiences of low-income, Spanish-speaking, Hispanics with diabetes and depression. A purposive sample (n=19) was selected from participants enrolled in a randomized controlled trial conducted in Los Angeles, California (United States) testing the effectiveness of a health services quality improvement intervention. Four focus groups followed by 10 in-depth semi-structured qualitative interviews were conducted. Data were analyzed using the methodology of coding, consensus, co-occurrence, and comparison, an analytical strategy rooted in grounded theory. Depression was perceived as a serious condition linked to the accumulation of social stressors. Somatic and anxiety-like symptoms and the cultural idiom of nervios were central themes in low-income Hispanics' explanatory models of depression. The perceived reciprocal relationships between diabetes and depression highlighted the multiple pathways by which these two illnesses impact each other and support the integration of diabetes and depression treatments. Concerns about depression treatments included fears about the addictive and harmful properties of antidepressants, worries about taking too many pills, and the stigma attached to taking psychotropic medications. This study provides important insights about the cultural and social dynamics that shape low-income Hispanics' illness and treatment experiences and support the use of patient-centered approaches to reduce the morbidity and mortality associated with diabetes and depression.

Complex, dynamic combination of physical, chemical and nutritional variables controls spatio-temporal variation of sandy beach community structure.

PubMed

Ortega Cisneros, Kelly; Smit, Albertus J; Laudien, Jürgen; Schoeman, David S

2011-01-01

Sandy beach ecological theory states that physical features of the beach control macrobenthic community structure on all but the most dissipative beaches. However, few studies have simultaneously evaluated the relative importance of physical, chemical and biological factors as potential explanatory variables for meso-scale spatio-temporal patterns of intertidal community structure in these systems. Here, we investigate macroinfaunal community structure of a micro-tidal sandy beach that is located on an oligotrophic subtropical coast and is influenced by seasonal estuarine input. We repeatedly sampled biological and environmental variables at a series of beach transects arranged at increasing distances from the estuary mouth. Sampling took place over a period of five months, corresponding with the transition between the dry and wet season. This allowed assessment of biological-physical relationships across chemical and nutritional gradients associated with a range of estuarine inputs. Physical, chemical, and biological response variables, as well as measures of community structure, showed significant spatio-temporal patterns. In general, bivariate relationships between biological and environmental variables were rare and weak. However, multivariate correlation approaches identified a variety of environmental variables (i.e., sampling session, the C∶N ratio of particulate organic matter, dissolved inorganic nutrient concentrations, various size fractions of photopigment concentrations, salinity and, to a lesser extent, beach width and sediment kurtosis) that either alone or combined provided significant explanatory power for spatio-temporal patterns of macroinfaunal community structure. Overall, these results showed that the macrobenthic community on Mtunzini Beach was not structured primarily by physical factors, but instead by a complex and dynamic blend of nutritional, chemical and physical drivers. This emphasises the need to recognise ocean-exposed sandy

Complex, Dynamic Combination of Physical, Chemical and Nutritional Variables Controls Spatio-Temporal Variation of Sandy Beach Community Structure

PubMed Central

Ortega Cisneros, Kelly; Smit, Albertus J.; Laudien, Jürgen; Schoeman, David S.

2011-01-01

Sandy beach ecological theory states that physical features of the beach control macrobenthic community structure on all but the most dissipative beaches. However, few studies have simultaneously evaluated the relative importance of physical, chemical and biological factors as potential explanatory variables for meso-scale spatio-temporal patterns of intertidal community structure in these systems. Here, we investigate macroinfaunal community structure of a micro-tidal sandy beach that is located on an oligotrophic subtropical coast and is influenced by seasonal estuarine input. We repeatedly sampled biological and environmental variables at a series of beach transects arranged at increasing distances from the estuary mouth. Sampling took place over a period of five months, corresponding with the transition between the dry and wet season. This allowed assessment of biological-physical relationships across chemical and nutritional gradients associated with a range of estuarine inputs. Physical, chemical, and biological response variables, as well as measures of community structure, showed significant spatio-temporal patterns. In general, bivariate relationships between biological and environmental variables were rare and weak. However, multivariate correlation approaches identified a variety of environmental variables (i.e., sampling session, the C∶N ratio of particulate organic matter, dissolved inorganic nutrient concentrations, various size fractions of photopigment concentrations, salinity and, to a lesser extent, beach width and sediment kurtosis) that either alone or combined provided significant explanatory power for spatio-temporal patterns of macroinfaunal community structure. Overall, these results showed that the macrobenthic community on Mtunzini Beach was not structured primarily by physical factors, but instead by a complex and dynamic blend of nutritional, chemical and physical drivers. This emphasises the need to recognise ocean-exposed sandy

Multivariate dynamic Tobit models with lagged observed dependent variables: An effectiveness analysis of highway safety laws.

PubMed

Dong, Chunjiao; Xie, Kun; Zeng, Jin; Li, Xia

2018-04-01

Highway safety laws aim to influence driver behaviors so as to reduce the frequency and severity of crashes, and their outcomes. For one specific highway safety law, it would have different effects on the crashes across severities. Understanding such effects can help policy makers upgrade current laws and hence improve traffic safety. To investigate the effects of highway safety laws on crashes across severities, multivariate models are needed to account for the interdependency issues in crash counts across severities. Based on the characteristics of the dependent variables, multivariate dynamic Tobit (MVDT) models are proposed to analyze crash counts that are aggregated at the state level. Lagged observed dependent variables are incorporated into the MVDT models to account for potential temporal correlation issues in crash data. The state highway safety law related factors are used as the explanatory variables and socio-demographic and traffic factors are used as the control variables. Three models, a MVDT model with lagged observed dependent variables, a MVDT model with unobserved random variables, and a multivariate static Tobit (MVST) model are developed and compared. The results show that among the investigated models, the MVDT models with lagged observed dependent variables have the best goodness-of-fit. The findings indicate that, compared to the MVST, the MVDT models have better explanatory power and prediction accuracy. The MVDT model with lagged observed variables can better handle the stochasticity and dependency in the temporal evolution of the crash counts and the estimated values from the model are closer to the observed values. The results show that more lives could be saved if law enforcement agencies can make a sustained effort to educate the public about the importance of motorcyclists wearing helmets. Motor vehicle crash-related deaths, injuries, and property damages could be reduced if states enact laws for stricter text messaging rules, higher

A comparison of the physical and anthropometric qualities explanatory of talent in the elite junior Australian football development pathway.

PubMed

Woods, Carl T; Cripps, Ashley; Hopper, Luke; Joyce, Christopher

2017-07-01

To compare the physical and anthropometric qualities explanatory of talent at two developmental levels in junior Australian football (AF). Cross-sectional observational. From a total of 134 juniors, two developmental levels were categorised; U16 (n=50; 15.6±0.3 y), U18 (n=84; 17.4±0.5 y). Within these levels, two groups were a priori defined; talent identified (U16; n=25; 15.7±0.2 y; U18 n=42; 17.5±0.4 y), non-talent identified (U16; n=25; 15.6±0.4 y; U18; n=42; 17.3±0.6 y). Players completed seven physical and anthropometric assessments commonly utilised for talent identification in AF. Binary logistic regression models were built to identify the qualities most explanatory of talent at each level. A combination of standing height, dominant leg dynamic vertical jump height and 20m sprint time provided the most parsimonious explanation of talent at the U16 level (AICc=60.05). At the U18 level, it was a combination of body mass and 20m sprint time that provided the most parsimonious explanation of talent (AICc=111.27). Despite similarities, there appears to be distinctive differences in physical and anthropometric qualities explanatory of talent at the U16 and U18 level. Coaches may view physical and anthropometric qualities more (or less) favourably at different levels of the AF developmental pathway. Given these results, future work should implement a longitudinal design, as physical and/or anthropometric qualities may deteriorate (or emerge) as junior AF players develop. Copyright © 2016 Sports Medicine Australia. All rights reserved.

An Explanatory Model of Dating Violence Risk Factors in Spanish Adolescents.

PubMed

Aizpitarte, Alazne; Alonso-Arbiol, Itziar; Van de Vijver, Fons J R

2017-12-01

Dating violence is a serious public health issue that needs further understanding in terms of risk factors that may be involved in it. The main goal of this study was to test a mediational model of dating violence risk factors. The sample was composed of 477 secondary and college students from Spain (59% females). A dynamic developmental explanatory model considering aggressiveness, insecure attachment, interparental conflict, and peer dating violence was tested using a multigroup structural equation model. Aggressiveness partially mediated the relation between anxious attachment and dating violence and fully mediated the association between interparental conflict resolution and dating violence. Furthermore, perceived peer dating violence was a direct predictor of dating violence. Implications for prevention and intervention plans are discussed. © 2017 The Authors. Journal of Research on Adolescence © 2017 Society for Research on Adolescence.

A latent class distance association model for cross-classified data with a categorical response variable.

PubMed

Vera, José Fernando; de Rooij, Mark; Heiser, Willem J

2014-11-01

In this paper we propose a latent class distance association model for clustering in the predictor space of large contingency tables with a categorical response variable. The rows of such a table are characterized as profiles of a set of explanatory variables, while the columns represent a single outcome variable. In many cases such tables are sparse, with many zero entries, which makes traditional models problematic. By clustering the row profiles into a few specific classes and representing these together with the categories of the response variable in a low-dimensional Euclidean space using a distance association model, a parsimonious prediction model can be obtained. A generalized EM algorithm is proposed to estimate the model parameters and the adjusted Bayesian information criterion statistic is employed to test the number of mixture components and the dimensionality of the representation. An empirical example highlighting the advantages of the new approach and comparing it with traditional approaches is presented. © 2014 The British Psychological Society.

Focus on Success: An Explanatory Embedded Multiple-Case Study on How Youth Successfully Navigate Workforce Development Programs in Southern Nevada

ERIC Educational Resources Information Center

Villalobos, Ricardo

2017-01-01

This explanatory qualitative study investigated the perspectives of participant's and practitioner's perceived barriers to success and the necessary navigational expertise for overcoming the identified barriers. This multiple-case study research design examined three WIA out-of-school youth workforce development programs in Southern Nevada, with…

Temporal variability of gravity wave drag - vertical coupling and possible climate links

NASA Astrophysics Data System (ADS)

Miksovsky, Jiri; Sacha, Petr; Kuchar, Ales; Pisoft, Petr

2017-04-01

In the atmosphere, the internal gravity waves (IGW) are one of the fastest ways of natural information transfer in the vertical direction. Tropospheric changes that result in modification of sourcing, propagation or breaking conditions for IGWs almost immediately influence the distribution of gravity wave drag in the stratosphere. So far most of the related studies deal with IGW impacts higher in the upper stratospheric/mesospheric region and with the modulation of IGWs by planetary waves. This is most likely due to the fact that IGWs induce highest accelerations in the mesosphere and lower thermosphere region. However, the imposed drag force is much bigger in the stratosphere. In the presented analysis, we have assessed the relationship between the gravity wave activity in the stratosphere and other climatic phenomena through statistical techniques. Multivariable regression has been applied to investigate the IGW-related eastward and northward wind tendencies in the CMAM30-SD data, subject to the explanatory variables involving local circulation characteristics (derived from regional configuration of the thermobaric field) as well as the phases of the large-scale internal climate variability modes (ENSO, NAO, QBO). Our tests have highlighted several geographical areas with statistically significant responses of the orographic gravity waves effect to each of the variability modes under investigation; additional experiments have also indicated distinct signs of nonlinearity in some of the links uncovered. Furthermore, we have also applied composite analysis of displaced and split stratospheric polar vortex events (SPV) from CMAM30-SD to focus on how the strength and occurrence of the IGW hotspots can play a role in SPV occurrence and frequency.

The value of using seasonality and meteorological variables to model intra-urban PM2.5 variation

NASA Astrophysics Data System (ADS)

Olvera Alvarez, Hector A.; Myers, Orrin B.; Weigel, Margaret; Armijos, Rodrigo X.

2018-06-01

A yearlong air monitoring campaign was conducted to assess the impact of local temperature, relative humidity, and wind speed on the temporal and spatial variability of PM2.5 in El Paso, Texas. Monitoring was conducted at four sites purposely selected to capture the local traffic variability. Effects of meteorological events on seasonal PM2.5 variability were identified. For instance, in winter low-wind and low-temperature conditions were associated with high PM2.5 events that contributed to elevated seasonal PM2.5 levels. Similarly, in spring, high PM2.5 events were associated with high-wind and low-relative humidity conditions. Correlation coefficients between meteorological variables and PM2.5 fluctuated drastically across seasons. Specifically, it was observed that for most sites correlations between PM2.5 and meteorological variables either changed from positive to negative or dissolved depending on the season. Overall, the results suggest that mixed effects analysis with season and site as fixed factors and meteorological variables as covariates could increase the explanatory value of LUR models for PM2.5.

Developing a spatial-statistical model and map of historical malaria prevalence in Botswana using a staged variable selection procedure

PubMed Central

Craig, Marlies H; Sharp, Brian L; Mabaso, Musawenkosi LH; Kleinschmidt, Immo

2007-01-01

Background Several malaria risk maps have been developed in recent years, many from the prevalence of infection data collated by the MARA (Mapping Malaria Risk in Africa) project, and using various environmental data sets as predictors. Variable selection is a major obstacle due to analytical problems caused by over-fitting, confounding and non-independence in the data. Testing and comparing every combination of explanatory variables in a Bayesian spatial framework remains unfeasible for most researchers. The aim of this study was to develop a malaria risk map using a systematic and practicable variable selection process for spatial analysis and mapping of historical malaria risk in Botswana. Results Of 50 potential explanatory variables from eight environmental data themes, 42 were significantly associated with malaria prevalence in univariate logistic regression and were ranked by the Akaike Information Criterion. Those correlated with higher-ranking relatives of the same environmental theme, were temporarily excluded. The remaining 14 candidates were ranked by selection frequency after running automated step-wise selection procedures on 1000 bootstrap samples drawn from the data. A non-spatial multiple-variable model was developed through step-wise inclusion in order of selection frequency. Previously excluded variables were then re-evaluated for inclusion, using further step-wise bootstrap procedures, resulting in the exclusion of another variable. Finally a Bayesian geo-statistical model using Markov Chain Monte Carlo simulation was fitted to the data, resulting in a final model of three predictor variables, namely summer rainfall, mean annual temperature and altitude. Each was independently and significantly associated with malaria prevalence after allowing for spatial correlation. This model was used to predict malaria prevalence at unobserved locations, producing a smooth risk map for the whole country. Conclusion We have produced a highly plausible and

“Azúcar y Nervios: Explanatory Models and Treatment Experiences of Hispanics with Diabetes and Depression”

PubMed Central

Hansen, Marissa C; Palinkas, Lawrence A; Ell, Kathleen

2008-01-01

This study examined the explanatory models of depression, perceived relationships between diabetes and depression, and depression treatment experiences of low-income, Spanish-speaking, Hispanics with diabetes and depression. A purposive sample (n =19) was selected from participants enrolled in a randomized controlled trial conducted in Los Angeles, California (US) testing the effectiveness of a health services quality improvement intervention. Four focus groups followed by 10 in-depth semi-structured qualitative interviews were conducted. Data were analyzed using the methodology of coding, consensus, co-occurrence, and comparison, an analytical strategy rooted in grounded theory. Depression was perceived as a serious condition linked to the accumulation of social stressors. Somatic and anxiety-like symptoms and the cultural idiom of nervios were central themes in low-income Hispanics’ explanatory models of depression. The perceived reciprocal relationships between diabetes and depression highlighted the multiple pathways by which these two illnesses impact each other and support the integration of diabetes and depression treatments. Concerns about depression treatments included fears about the addictive and harmful properties of antidepressants, worries about taking too many pills, and the stigma attached to taking psychotropic medications. This study provides important insights about the cultural and social dynamics that shape low-income Hispanics’ illness and treatment experiences and support the use of patient-centered approaches to reduce the morbidity and mortality associated with diabetes and depression. PMID:18339466

An explanatory model for state Medicaid per capita prescription drug expenditures.

PubMed

Roy, Sanjoy; Madhavan, S Suresh

2012-01-01

Rising prescription drug expenditure is a growing concern for publicly funded drug benefit programs like Medicaid. To be able to contain drug expenditures in Medicaid, it is important that cause(s) for such increases are identified. This study attempts to establish an explanatory model for Medicaid prescription drugs expenditure based on the impacts of key influencers/predictors identified using a comprehensive framework of drug utilization. A modified Andersen's behavior model of health services utilization is employed to identify potential determinants of pharmaceutical expenditures in state Medicaid programs. Level of federal matching funds, access to primary care, severity of diseases, unemployment, and education levels were found to be key influencers of Medicaid prescription drug expenditure. Increases in all, except education levels, were found to result in increases in drug expenditures. Findings from this study could better inform intervention policies and cost-containment strategies for state Medicaid drug benefit programs.

Using a generalized additive model with autoregressive terms to study the effects of daily temperature on mortality.

PubMed

Yang, Lei; Qin, Guoyou; Zhao, Naiqing; Wang, Chunfang; Song, Guixiang

2012-10-30

Generalized Additive Model (GAM) provides a flexible and effective technique for modelling nonlinear time-series in studies of the health effects of environmental factors. However, GAM assumes that errors are mutually independent, while time series can be correlated in adjacent time points. Here, a GAM with Autoregressive terms (GAMAR) is introduced to fill this gap. Parameters in GAMAR are estimated by maximum partial likelihood using modified Newton's method, and the difference between GAM and GAMAR is demonstrated using two simulation studies and a real data example. GAMM is also compared to GAMAR in simulation study 1. In the simulation studies, the bias of the mean estimates from GAM and GAMAR are similar but GAMAR has better coverage and smaller relative error. While the results from GAMM are similar to GAMAR, the estimation procedure of GAMM is much slower than GAMAR. In the case study, the Pearson residuals from the GAM are correlated, while those from GAMAR are quite close to white noise. In addition, the estimates of the temperature effects are different between GAM and GAMAR. GAMAR incorporates both explanatory variables and AR terms so it can quantify the nonlinear impact of environmental factors on health outcome as well as the serial correlation between the observations. It can be a useful tool in environmental epidemiological studies.

Using a generalized additive model with autoregressive terms to study the effects of daily temperature on mortality

PubMed Central

2012-01-01

Background Generalized Additive Model (GAM) provides a flexible and effective technique for modelling nonlinear time-series in studies of the health effects of environmental factors. However, GAM assumes that errors are mutually independent, while time series can be correlated in adjacent time points. Here, a GAM with Autoregressive terms (GAMAR) is introduced to fill this gap. Methods Parameters in GAMAR are estimated by maximum partial likelihood using modified Newton’s method, and the difference between GAM and GAMAR is demonstrated using two simulation studies and a real data example. GAMM is also compared to GAMAR in simulation study 1. Results In the simulation studies, the bias of the mean estimates from GAM and GAMAR are similar but GAMAR has better coverage and smaller relative error. While the results from GAMM are similar to GAMAR, the estimation procedure of GAMM is much slower than GAMAR. In the case study, the Pearson residuals from the GAM are correlated, while those from GAMAR are quite close to white noise. In addition, the estimates of the temperature effects are different between GAM and GAMAR. Conclusions GAMAR incorporates both explanatory variables and AR terms so it can quantify the nonlinear impact of environmental factors on health outcome as well as the serial correlation between the observations. It can be a useful tool in environmental epidemiological studies. PMID:23110601

Examining the Value of a Scaffolded Critique Framework to Promote Argumentative and Explanatory Writings within an Argument-Based Inquiry Approach

ERIC Educational Resources Information Center

Jang, Jeong-yoon; Hand, Brian

2017-01-01

This study investigated the value of using a scaffolded critique framework to promote two different types of writing--argumentative writing and explanatory writing--with different purposes within an argument-based inquiry approach known as the Science Writing Heuristic (SWH) approach. A quasi-experimental design with sixth and seventh grade…

Locating the Social Origins of Mental Illness: The Explanatory Models of Mental Illness Among Clergy from Different Ethnic and Faith Backgrounds.

PubMed

Leavey, Gerard; Loewenthal, Kate; King, Michael

2016-10-01

Clergy have historically provided 'healing' through various spiritual and medical modalities and even in modern, developed welfare economies they may still be an important help-seeking resource. Partnerships between religion and psychiatry are regularly advocated, but there is scant research on clergy explanatory models of illness. This paper aimed to explore their relationship with psychiatry and to examine how clergy in various faith groups conceptualised mental health problems. In this qualitative study using in-depth interviews, these issues were explored with 32 practising clergy in the UK from a range of different Christian, Muslim and Jewish faith organisations and ethnic backgrounds. This paper presents findings related to clergy explanatory models of mental illness and, in particular, how the social factors involved in causation are tinged with spiritual influences and implications, and how the meanings of mental distress assume a social and moral significance in distinctive localised matters.

A comparison of data-driven groundwater vulnerability assessment methods

USGS Publications Warehouse

Sorichetta, Alessandro; Ballabio, Cristiano; Masetti, Marco; Robinson, Gilpin R.; Sterlacchini, Simone

2013-01-01

Increasing availability of geo-environmental data has promoted the use of statistical methods to assess groundwater vulnerability. Nitrate is a widespread anthropogenic contaminant in groundwater and its occurrence can be used to identify aquifer settings vulnerable to contamination. In this study, multivariate Weights of Evidence (WofE) and Logistic Regression (LR) methods, where the response variable is binary, were used to evaluate the role and importance of a number of explanatory variables associated with nitrate sources and occurrence in groundwater in the Milan District (central part of the Po Plain, Italy). The results of these models have been used to map the spatial variation of groundwater vulnerability to nitrate in the region, and we compare the similarities and differences of their spatial patterns and associated explanatory variables. We modify the standard WofE method used in previous groundwater vulnerability studies to a form analogous to that used in LR; this provides a framework to compare the results of both models and reduces the effect of sampling bias on the results of the standard WofE model. In addition, a nonlinear Generalized Additive Model has been used to extend the LR analysis. Both approaches improved discrimination of the standard WofE and LR models, as measured by the c-statistic. Groundwater vulnerability probability outputs, based on rank-order classification of the respective model results, were similar in spatial patterns and identified similar strong explanatory variables associated with nitrate source (population density as a proxy for sewage systems and septic sources) and nitrate occurrence (groundwater depth).

An Explanatory Mixed-Methods Approach to Tracing "Career Pathways" Policy in Virginia: How School Counselors and Student Demographics Influence Implementation Fidelity

ERIC Educational Resources Information Center

Ormsmith, Michael Isaac

2014-01-01

This explanatory mixed-methods policy analysis describes how school counselors' thoughts and attitudes contribute to the implementation fidelity of the Academic and Career Plan (ACP) policy in a suburban Virginia school division. A quantitative survey investigated counselor thoughts about the policy, implementation behaviors, and counselor ideas…

Sharpening method of satellite thermal image based on the geographical statistical model

NASA Astrophysics Data System (ADS)

Qi, Pengcheng; Hu, Shixiong; Zhang, Haijun; Guo, Guangmeng

2016-04-01

To improve the effectiveness of thermal sharpening in mountainous regions, paying more attention to the laws of land surface energy balance, a thermal sharpening method based on the geographical statistical model (GSM) is proposed. Explanatory variables were selected from the processes of land surface energy budget and thermal infrared electromagnetic radiation transmission, then high spatial resolution (57 m) raster layers were generated for these variables through spatially simulating or using other raster data as proxies. Based on this, the local adaptation statistical relationship between brightness temperature (BT) and the explanatory variables, i.e., the GSM, was built at 1026-m resolution using the method of multivariate adaptive regression splines. Finally, the GSM was applied to the high-resolution (57-m) explanatory variables; thus, the high-resolution (57-m) BT image was obtained. This method produced a sharpening result with low error and good visual effect. The method can avoid the blind choice of explanatory variables and remove the dependence on synchronous imagery at visible and near-infrared bands. The influences of the explanatory variable combination, sampling method, and the residual error correction on sharpening results were analyzed deliberately, and their influence mechanisms are reported herein.

Additional security features for optically variable foils

NASA Astrophysics Data System (ADS)

Marshall, Allan C.; Russo, Frank

1998-04-01

For thousands of years, man has exploited the attraction and radiance of pure gold to adorn articles of great significance. Today, designers decorate packaging with metallic gold foils to maintain the prestige of luxury items such as perfumes, chocolates, wine and whisky, and to add visible appeal and value to wide range of products. However, today's products do not call for the hand beaten gold leaf of the Ancient Egyptians, instead a rapid production technology exists which makes use of accurately coated thin polymer films and vacuum deposited metallic layers. Stamping Foils Technology is highly versatile since several different layers may be combined into one product, each providing a different function. Not only can a foil bring visual appeal to an article, it can provide physical and chemical resistance properties and also protect an article from human forms of interference, such as counterfeiting, copying or tampering. Stamping foils have proved to be a highly effective vehicle for applying optical devices to items requiring this type of protection. Credit cards, bank notes, personal identification documents and more recently high value packaged items such as software and perfumes are protected by optically variable devices applied using stamping foil technology.

Random parameter models for accident prediction on two-lane undivided highways in India.

PubMed

Dinu, R R; Veeraragavan, A

2011-02-01

Generalized linear modeling (GLM), with the assumption of Poisson or negative binomial error structure, has been widely employed in road accident modeling. A number of explanatory variables related to traffic, road geometry, and environment that contribute to accident occurrence have been identified and accident prediction models have been proposed. The accident prediction models reported in literature largely employ the fixed parameter modeling approach, where the magnitude of influence of an explanatory variable is considered to be fixed for any observation in the population. Similar models have been proposed for Indian highways too, which include additional variables representing traffic composition. The mixed traffic on Indian highways comes with a lot of variability within, ranging from difference in vehicle types to variability in driver behavior. This could result in variability in the effect of explanatory variables on accidents across locations. Random parameter models, which can capture some of such variability, are expected to be more appropriate for the Indian situation. The present study is an attempt to employ random parameter modeling for accident prediction on two-lane undivided rural highways in India. Three years of accident history, from nearly 200 km of highway segments, is used to calibrate and validate the models. The results of the analysis suggest that the model coefficients for traffic volume, proportion of cars, motorized two-wheelers and trucks in traffic, and driveway density and horizontal and vertical curvatures are randomly distributed across locations. The paper is concluded with a discussion on modeling results and the limitations of the present study. Copyright © 2010 Elsevier Ltd. All rights reserved.

Effect of climate variables on cocoa black pod incidence in Sabah using ARIMAX model

NASA Astrophysics Data System (ADS)

Ling Sheng Chang, Albert; Ramba, Haya; Mohd. Jaaffar, Ahmad Kamil; Kim Phin, Chong; Chong Mun, Ho

2016-06-01

Cocoa black pod disease is one of the major diseases affecting the cocoa production in Malaysia and also around the world. Studies have shown that the climate variables have influenced the cocoa black pod disease incidence and it is important to quantify the black pod disease variation due to the effect of climate variables. Application of time series analysis especially auto-regressive moving average (ARIMA) model has been widely used in economics study and can be used to quantify the effect of climate variables on black pod incidence to forecast the right time to control the incidence. However, ARIMA model does not capture some turning points in cocoa black pod incidence. In order to improve forecasting performance, other explanatory variables such as climate variables should be included into ARIMA model as ARIMAX model. Therefore, this paper is to study the effect of climate variables on the cocoa black pod disease incidence using ARIMAX model. The findings of the study showed ARIMAX model using MA(1) and relative humidity at lag 7 days, RHt - 7 gave better R square value compared to ARIMA model using MA(1) which could be used to forecast the black pod incidence to assist the farmers determine timely application of fungicide spraying and culture practices to control the black pod incidence.

Insight in psychosis: an independent predictor of outcome or an explanatory model of illness?

PubMed

Jacob, K S

2014-10-01

While the traditional view within psychiatry is that insight is independent of psychopathology and predicts the course and outcome of psychosis, recent data from India argues that insight is secondary to interaction between progression of illness on one hand and local culture and social environment on the other. The findings suggest that "insight" is an explanatory model (EM) and may reflect attempts at coping with the devastating effects of mental disorders. Most societies are pluralistic and offer multiple, divergent and contradictory explanations for illnesses. These belief systems interact with the trajectory of the person's illness to produce a unique personal understanding, often based on a set of complex and contradictory EMs. Like all EMs, insight provides meaning to explain and overcome challenges including disabling symptoms, persistent deficits, impaired social relations and difficult livelihood issues. The persistence of distress, impairment, disability and handicap, despite regular and optimal treatment, call for explanations, which go beyond the simplistic concept of disease. People tend to choose EMs, which are non-stigmatizing and which seem to help explain and rationalize their individual concerns. The frequent presence of multiple and often contradictory EMs, held simultaneously, suggest that they are pragmatic responses at coping. The results advocate a non-judgmental approach and broad based assessment of EMs of illness and their comparison with culturally appropriate beliefs, attributions and actions. The biomedical model of illness should be presented without dismissing patient beliefs or belittling local cultural explanations for illness. Clinical practice demands a negotiation of shared model of care and treatment plan between patient and physician perspectives. The diversity of patients, problems, beliefs and cultures mandates the need to educate, match, negotiate and integrate psychiatric and psychological frameworks and interventions. It

The role of environmental variables on Aedes albopictus biology and chikungunya epidemiology

PubMed Central

Waldock, Joanna; Chandra, Nastassya L; Lelieveld, Jos; Proestos, Yiannis; Michael, Edwin; Christophides, George; Parham, Paul E

2013-01-01

Aedes albopictus is a vector of dengue and chikungunya viruses in the field, along with around 24 additional arboviruses under laboratory conditions. As an invasive mosquito species, Ae. albopictus has been expanding in geographical range over the past 20 years, although the poleward extent of mosquito populations is limited by winter temperatures. Nonetheless, population densities depend on environmental conditions and since global climate change projections indicate increasing temperatures and altered patterns of rainfall, geographic distributions of previously tropical mosquito species may change. Although mathematical models can provide explanatory insight into observed patterns of disease prevalence in terms of epidemiological and entomological processes, understanding how environmental variables affect transmission is possible only with reliable model parameterisation, which, in turn, is obtained only through a thorough understanding of the relationship between mosquito biology and environmental variables. Thus, in order to assess the impact of climate change on mosquito population distribution and regions threatened by vector-borne disease, a detailed understanding (through a synthesis of current knowledge) of the relationship between climate, mosquito biology, and disease transmission is required, but this process has not yet been undertaken for Ae. albopictus. In this review, the impact of temperature, rainfall, and relative humidity on Ae. albopictus development and survival are considered. Existing Ae. albopictus populations across Europe are mapped with current climatic conditions, considering whether estimates of climatic cutoffs for Ae. albopictus are accurate, and suggesting that environmental thresholds must be calibrated according to the scale and resolution of climate model outputs and mosquito presence data. PMID:23916332

Influence of Climate Variability on US Regional Homicide Rates

NASA Astrophysics Data System (ADS)

Harp, R. D.; Karnauskas, K. B.

2017-12-01

Recent studies have found consistent evidence of a relationship between temperature and criminal behavior. However, despite agreement in the overall relationship, little progress has been made in distinguishing between two proposed explanatory theories. The General Affective Aggression Model (GAAM) suggests that high temperatures create periods of higher heat stress that enhance individual aggressiveness, whereas the Routine Activities Theory (RAT) theorizes that individuals are more likely to be outdoors interacting with others during periods of pleasant weather with a resulting increase in both interpersonal interactions and victim availability. Further, few studies have considered this relationship within the context of climate change in a quantitative manner. In an effort to distinguish between the two theories, and to examine the statistical relationships on a broader spatial scale than previously, we combined data from the Supplementary Homicide Report (SHR—compiled by the Federal Bureau of Investigation) and the North American Regional Reanalysis (NARR—compiled by the National Centers for Environmental Protection, a branch of the National Oceanic and Atmospheric Administration). US homicide data described by the SHR was compared with seven relevant observed climate variables (temperature, dew point, relative humidity, accumulated precipitation, accumulated snowfall, snow cover, and snow depth) provided by the NARR atmospheric reanalysis. Relationships between homicide rates and climate variables, as well as reveal regional spatial patterns will be presented and discussed, along with the implications due to future climate change. This research lays the groundwork for the refinement of estimates of an oft-overlooked climate change impact, which has previously been estimated to cause an additional 22,000 murders between 2010 and 2099, including providing important constraints for empirical models of future violent crime incidences in the face of global

Variability in in vitro fertilization outcomes of prepubertal goat oocytes explained by basic semen analyses.

PubMed

Palomo, M J; Quintanilla, R; Izquierdo, M D; Mogas, T; Paramio, M T

2016-12-01

This work analyses the changes that caprine spermatozoa undergo during in vitro fertilization (IVF) of in vitro matured prepubertal goat oocytes and their relationship with IVF outcome, in order to obtain an effective model that allows prediction of in vitro fertility on the basis of semen assessment. The evolution of several sperm parameters (motility, viability and acrosomal integrity) during IVF and their relationship with three IVF outcome criteria (total penetration, normal penetration and cleavage rates) were studied in a total of 56 IVF replicates. Moderate correlation coefficients between some sperm parameters and IVF outcome were observed. In addition, stepwise multiple regression analyses were conducted that considered three grouping of sperm parameters as potential explanatory variables of the three IVF outcome criteria. The proportion of IVF outcome variation that can be explained by the fitted models ranged from 0.62 to 0.86, depending upon the trait analysed and the variables considered. Seven out of 32 sperm parameters were selected as partial covariates in at least one of the nine multiple regression models. Among these, progressive sperm motility assessed immediately after swim-up, the percentage of dead sperm with intact acrosome and the incidence of acrosome reaction both determined just before the gamete co-culture, and finally the proportion of viable spermatozoa at 17 h post-insemination were the most frequently selected sperm parameters. Nevertheless, the predictive ability of these models must be confirmed in a larger sample size experiment.

Advancing complex explanatory conceptualizations of daily negative and positive affect: trigger and maintenance coping action patterns.

PubMed

Dunkley, David M; Ma, Denise; Lee, Ihno A; Preacher, Kristopher J; Zuroff, David C

2014-01-01

The present study addressed a fundamental gap between research and clinical work by advancing complex explanatory conceptualizations of coping action patterns that trigger and maintain daily negative affect and (low) positive affect. One hundred ninety-six community adults completed measures of perfectionism, and then 6 months later completed questionnaires at the end of the day for 14 consecutive days to provide simultaneous assessments of appraisals, coping, and affect across different stressful situations in everyday life. Multilevel structural equation modeling (MSEM) supported complex explanatory conceptualizations that demonstrated (a) disengagement trigger patterns consisting of several distinct appraisals (e.g., event stress) and coping strategies (e.g., avoidant coping) that commonly operate together across many different stressors when the typical individual experiences daily increases in negative affect and drops in positive affect; and (b) disengagement maintenance patterns composed of different appraisal and coping maintenance factors that, in combination, can explain why individuals with higher levels of self-critical perfectionism have persistent daily negative affect and low positive mood 6 months later. In parallel, engagement patterns (triggers and maintenance) composed of distinct appraisals (e.g., perceived social support) and coping strategies (e.g., problem-focused coping) were linked to compensatory experiences of daily positive affect. These findings demonstrate the promise of using daily diary methodologies and MSEM to promote a shared understanding between therapists and clients of trigger and maintenance coping action patterns that explain what precipitates and perpetuates clients' difficulties, which, in turn, can help achieve the 2 overarching therapy goals of reducing clients' distress and bolstering resilience. (c) 2014 APA, all rights reserved.

Analysis of low flows and selected methods for estimating low-flow characteristics at partial-record and ungaged stream sites in western Washington

USGS Publications Warehouse

Curran, Christopher A.; Eng, Ken; Konrad, Christopher P.

2012-01-01

Regional low-flow regression models for estimating Q7,10 at ungaged stream sites are developed from the records of daily discharge at 65 continuous gaging stations (including 22 discontinued gaging stations) for the purpose of evaluating explanatory variables. By incorporating the base-flow recession time constant τ as an explanatory variable in the regression model, the root-mean square error for estimating Q7,10 at ungaged sites can be lowered to 72 percent (for known values of τ), which is 42 percent less than if only basin area and mean annual precipitation are used as explanatory variables. If partial-record sites are included in the regression data set, τ must be estimated from pairs of discharge measurements made during continuous periods of declining low flows. Eight measurement pairs are optimal for estimating τ at partial-record sites, and result in a lowering of the root-mean square error by 25 percent. A low-flow survey strategy that includes paired measurements at partial-record sites requires additional effort and planning beyond a standard strategy, but could be used to enhance regional estimates of τ and potentially reduce the error of regional regression models for estimating low-flow characteristics at ungaged sites.

THE GJ1214 SUPER-EARTH SYSTEM: STELLAR VARIABILITY, NEW TRANSITS, AND A SEARCH FOR ADDITIONAL PLANETS

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

Berta, Zachory K.; Charbonneau, David; Bean, Jacob

2011-07-20

The super-Earth GJ1214b transits a nearby M dwarf that exhibits a 1% intrinsic variability in the near-infrared. Here, we analyze new observations to refine the physical properties of both the star and planet. We present three years of out-of-transit photometric monitoring of the stellar host GJ1214 from the MEarth Observatory and find the rotation period to be long, most likely an integer multiple of 53 days, suggesting low levels of magnetic activity and an old age for the system. We show that such variability will not pose significant problems to ongoing studies of the planet's atmosphere with transmission spectroscopy. Wemore » analyze two high-precision transit light curves from ESO's Very Large Telescope (VLT) along with seven others from the MEarth and Fred Lawrence Whipple Observatory 1.2 m telescopes, finding physical parameters for the planet that are consistent with previous work. The VLT light curves show tentative evidence for spot occultations during transit. Using two years of MEarth light curves, we place limits on additional transiting planets around GJ1214 with periods out to the habitable zone of the system. We also improve upon the previous photographic V-band estimate for the star, finding V = 14.71 {+-} 0.03.« less

Variable selection for distribution-free models for longitudinal zero-inflated count responses.

PubMed

Chen, Tian; Wu, Pan; Tang, Wan; Zhang, Hui; Feng, Changyong; Kowalski, Jeanne; Tu, Xin M

2016-07-20

Zero-inflated count outcomes arise quite often in research and practice. Parametric models such as the zero-inflated Poisson and zero-inflated negative binomial are widely used to model such responses. Like most parametric models, they are quite sensitive to departures from assumed distributions. Recently, new approaches have been proposed to provide distribution-free, or semi-parametric, alternatives. These methods extend the generalized estimating equations to provide robust inference for population mixtures defined by zero-inflated count outcomes. In this paper, we propose methods to extend smoothly clipped absolute deviation (SCAD)-based variable selection methods to these new models. Variable selection has been gaining popularity in modern clinical research studies, as determining differential treatment effects of interventions for different subgroups has become the norm, rather the exception, in the era of patent-centered outcome research. Such moderation analysis in general creates many explanatory variables in regression analysis, and the advantages of SCAD-based methods over their traditional counterparts render them a great choice for addressing this important and timely issues in clinical research. We illustrate the proposed approach with both simulated and real study data. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

Examining school effectiveness at the fourth grade: A hierarchical analysis of the Third International Mathematics and Science Study (TIMSS)

NASA Astrophysics Data System (ADS)

Stemler, Steven Edward

This study explored school effectiveness in mathematics and science at the fourth grade using data from IEA's Third International Mathematics and Science Study (TIMSS). Fourteen of the 26 countries participating in TIMSS at the fourth grade possessed sufficient between-school variability in mathematics achievement to justify the creation of explanatory models of school effectiveness while 13 countries possessed sufficient between-school variability in science achievement. Exploratory models were developed using variables drawn from student, teacher, and school questionnaires. The variables were chosen to represent the domains of student involvement, instructional methods, classroom organization, school climate, and school structure. Six explanatory models for each subject were analyzed using two-level hierarchical linear modeling (HLM) and were compared to models using only school mean SES as an explanatory variable. The amount of variability in student achievement in mathematics attributable to differences between schools ranged from 16% in Cyprus to 56% in Latvia, while the amount of between-school variance in science achievement ranged from 12% in Korea to 59% in Latvia. In general, about one-quarter of the variability in mathematics and science achievement was found to lie between schools. The research findings revealed that after adjusting for differences in student backgrounds across schools, the most effective schools in mathematics and science had students who reported seeing a positive relationship between hard work, belief in their own abilities, and achievement. In addition, more effective schools had students who reported less frequent use of computers and calculators in the classroom. These relationships were found to be stable across explanatory models, cultural contexts, and subject areas. This study has contributed a unique element to the literature by examining school effectiveness at the fourth grade across two subject areas and across 14

Explaining Participation: An Explanatory History of Select Gender Patterns in Undergraduate STEM

NASA Astrophysics Data System (ADS)

Mastroianni, Michael Pasquale

This explanatory study examines three focal periods in undergraduate STEM as related to the gender gap. Social, economic, and more general historical data are used to develop a clear and powerful explanation of baccalaureate trends in biology and engineering. Specifically, historical accounts are offered for 1) a ten-year period in undergraduate biology in which the number of baccalaureates awarded to men decreased 44 percent, while the number of baccalaureates awarded to women decreased one percent; 2) the start of a twenty-year period in which the number of bachelor's degrees awarded in the biological sciences increased 150 percent---from 36,068 degrees in 1989, to 90,003 bachelor's degrees in 2011; and 3) a ten year period in undergraduate engineering where female graduation rates septupled---this ten-year time period is the only instance of meaningful and noteworthy growth for women in undergraduate engineering over the past half century. Findings from each history reveal a common narrative underlying baccalaureate trends. Implications for undergraduate STEM are discussed.

Multiple Use One-Sided Hypotheses Testing in Univariate Linear Calibration

NASA Technical Reports Server (NTRS)

Krishnamoorthy, K.; Kulkarni, Pandurang M.; Mathew, Thomas

1996-01-01

Consider a normally distributed response variable, related to an explanatory variable through the simple linear regression model. Data obtained on the response variable, corresponding to known values of the explanatory variable (i.e., calibration data), are to be used for testing hypotheses concerning unknown values of the explanatory variable. We consider the problem of testing an unlimited sequence of one sided hypotheses concerning the explanatory variable, using the corresponding sequence of values of the response variable and the same set of calibration data. This is the situation of multiple use of the calibration data. The tests derived in this context are characterized by two types of uncertainties: one uncertainty associated with the sequence of values of the response variable, and a second uncertainty associated with the calibration data. We derive tests based on a condition that incorporates both of these uncertainties. The solution has practical applications in the decision limit problem. We illustrate our results using an example dealing with the estimation of blood alcohol concentration based on breath estimates of the alcohol concentration. In the example, the problem is to test if the unknown blood alcohol concentration of an individual exceeds a threshold that is safe for driving.

Phenology Analysis of Forest Vegetation to Environmental Variables during - and Post-Monsoon Seasons in Western Himalayan Region of India

NASA Astrophysics Data System (ADS)

Khare, S.; Latifi, H.; Ghosh, K.

2016-06-01

To assess the phenological changes in Moist Deciduous Forest (MDF) of western Himalayan region of India, we carried out NDVI time series analysis from 2013 to 2015 using Landsat 8 OLI data. We used the vegetation index differencing method to calculate the change in NDVI (NDVIchange) during pre and post monsoon seasons and these changes were used to assess the phenological behaviour of MDF by taking the effect of a set of environmental variables into account. To understand the effect of environmental variables on change in phenology, we designed a linear regression analysis with sample-based NDVIchange values as the response variable and elevation aspect, and Land Surface Temperature (LST) as explanatory variables. The Landsat-8 derived phenology transition stages were validated by calculating the phenology variation from Nov 2008 to April 2009 using Landsat-7 which has the same spatial resolution as Landsat-8. The Landsat-7 derived NDVI trajectories were plotted in accordance with MODIS derived phenology stages (from Nov 2008 to April 2009) of MDF. Results indicate that the Landsat -8 derived NDVI trajectories describing the phenology variation of MDF during spring, monsoon autumn and winter seasons agreed closely with Landsat-7 and MODIS derived phenology transition from Nov 2008 to April 2009. Furthermore, statistical analysis showed statistically significant correlations (p < 0.05) amongst the environmental variables and the NDVIchange between full greenness and maximum frequency stage of Onset of Greenness (OG) activity.. The major change in NDVI was observed in medium (600 to 650 m) and maximum (650 to 750 m) elevation areas. The change in LST showed also to be highly influential. The results of this study can be used for large scale monitoring of difficult-to-reach mountainous forests, with additional implications in biodiversity assessment. By means of a sufficient amount of available cloud-free imagery, detailed phenological trends across mountainous

Habitat connectivity and in-stream vegetation control temporal variability of benthic invertebrate communities.

PubMed

Huttunen, K-L; Mykrä, H; Oksanen, J; Astorga, A; Paavola, R; Muotka, T

2017-05-03

One of the key challenges to understanding patterns of β diversity is to disentangle deterministic patterns from stochastic ones. Stochastic processes may mask the influence of deterministic factors on community dynamics, hindering identification of the mechanisms causing variation in community composition. We studied temporal β diversity (among-year dissimilarity) of macroinvertebrate communities in near-pristine boreal streams across 14 years. To assess whether the observed β diversity deviates from that expected by chance, and to identify processes (deterministic vs. stochastic) through which different explanatory factors affect community variability, we used a null model approach. We observed that at the majority of sites temporal β diversity was low indicating high community stability. When stochastic variation was unaccounted for, connectivity was the only variable explaining temporal β diversity, with weakly connected sites exhibiting higher community variability through time. After accounting for stochastic effects, connectivity lost importance, suggesting that it was related to temporal β diversity via random colonization processes. Instead, β diversity was best explained by in-stream vegetation, community variability decreasing with increasing bryophyte cover. These results highlight the potential of stochastic factors to dampen the influence of deterministic processes, affecting our ability to understand and predict changes in biological communities through time.

Weather Variability, Tides, and Barmah Forest Virus Disease in the Gladstone Region, Australia

PubMed Central

Naish, Suchithra; Hu, Wenbiao; Nicholls, Neville; Mackenzie, John S.; McMichael, Anthony J.; Dale, Pat; Tong, Shilu

2006-01-01

In this study we examined the impact of weather variability and tides on the transmission of Barmah Forest virus (BFV) disease and developed a weather-based forecasting model for BFV disease in the Gladstone region, Australia. We used seasonal autoregressive integrated moving-average (SARIMA) models to determine the contribution of weather variables to BFV transmission after the time-series data of response and explanatory variables were made stationary through seasonal differencing. We obtained data on the monthly counts of BFV cases, weather variables (e.g., mean minimum and maximum temperature, total rainfall, and mean relative humidity), high and low tides, and the population size in the Gladstone region between January 1992 and December 2001 from the Queensland Department of Health, Australian Bureau of Meteorology, Queensland Department of Transport, and Australian Bureau of Statistics, respectively. The SARIMA model shows that the 5-month moving average of minimum temperature (β = 0.15, p-value < 0.001) was statistically significantly and positively associated with BFV disease, whereas high tide in the current month (β = −1.03, p-value = 0.04) was statistically significantly and inversely associated with it. However, no significant association was found for other variables. These results may be applied to forecast the occurrence of BFV disease and to use public health resources in BFV control and prevention. PMID:16675420

Weather variability, tides, and Barmah Forest virus disease in the Gladstone region, Australia.

PubMed

Naish, Suchithra; Hu, Wenbiao; Nicholls, Neville; Mackenzie, John S; McMichael, Anthony J; Dale, Pat; Tong, Shilu

2006-05-01

In this study we examined the impact of weather variability and tides on the transmission of Barmah Forest virus (BFV) disease and developed a weather-based forecasting model for BFV disease in the Gladstone region, Australia. We used seasonal autoregressive integrated moving-average (SARIMA) models to determine the contribution of weather variables to BFV transmission after the time-series data of response and explanatory variables were made stationary through seasonal differencing. We obtained data on the monthly counts of BFV cases, weather variables (e.g., mean minimum and maximum temperature, total rainfall, and mean relative humidity), high and low tides, and the population size in the Gladstone region between January 1992 and December 2001 from the Queensland Department of Health, Australian Bureau of Meteorology, Queensland Department of Transport, and Australian Bureau of Statistics, respectively. The SARIMA model shows that the 5-month moving average of minimum temperature (b=0.15, p-value<0.001) was statistically significantly and positively associated with BFV disease, whereas high tide in the current month (b=-1.03, p-value=0.04) was statistically significantly and inversely associated with it. However, no significant association was found for other variables. These results may be applied to forecast the occurrence of BFV disease and to use public health resources in BFV control and prevention.

The Variable Transition State in Polar Additions to Pi Bonds

ERIC Educational Resources Information Center

Weiss, Hilton M.

2010-01-01

A vast majority of polar additions of Bronsted acids to alkynes involve a termolecular transition state. With strong acids, considerable positive charge is developed on carbon and Markovnikov addition predominates. In less acidic solutions, however, the reaction is much slower and the transition state more closely resembles the olefinic product.…

The impact of flood variables on riparian vegetation

NASA Astrophysics Data System (ADS)

Dzubakova, Katarina; Molnar, Peter

2016-04-01

the most significant variables impacting vegetation response. Generally, maximal flood attributes had more significant impacts than integrated attributes over the flood duration. Additional explanatory variables in the model should account for vegetation heterogeneity, groundwater conditions and different effects of lateral and surface erosion.

Explanatory model of psychosis: impact on perception of self-stigma by patients in three sub-saharan African cities.

PubMed

Makanjuola, Victor; Esan, Yomi; Oladeji, Bibilola; Kola, Lola; Appiah-Poku, John; Harris, Benjamin; Othieno, Caleb; Price, Leshawndra; Seedat, Soraya; Gureje, Oye

2016-12-01

Most cultures in sub-Saharan Africa subscribe to the belief that the root cause of psychosis is supernatural. Individuals in the community who hold a religiomagical explanatory model of causation have been shown to exhibit more stigmatizing attitudes towards people with psychosis. Self-stigma among individuals with psychosis is less frequently studied. We used a mixed-method approach, consisting of key informant's interviews to elicit information on explanatory models of causation of psychosis and questionnaire assessment of internalized stigma with an adapted version of the Scale for Internalized Stigma of Mental Illness. Twenty-four, 31, and 30 subjects with recent experience of utilizing the service of traditional or faith healers for severe mental disorders in Ibadan (Nigeria), Kumasi (Ghana), and Nairobi (Kenya), respectively, were interviewed. About 44 % (42.1 %) of the Nigerian respondents had a high (severe) level of self-stigma with the respective proportions among Ghanaian and Kenyan respondents being 20.7 and 37.5 %. Compared with 4 out of a total of 12 respondents (33.3 %) who reported low self-stigma reported supernatural attribution, 14 out of 20 respondents (70 %) with the highest level of self-stigma reported supernatural attribution across the three sites. When low scorers ascribed supernatural causation, it was often with a religious focus. There is a greater tendency for persons with high levels of self-stigma than those with low levels to ascribe supernatural attribution to their experience of a severe mental health condition.

Genotypic variability-based genome-wide association study identifies non-additive loci HLA-C and IL12B for psoriasis.

PubMed

Wei, Wen-Hua; Massey, Jonathan; Worthington, Jane; Barton, Anne; Warren, Richard B

2018-03-01

Genome-wide association studies (GWASs) have identified a number of loci for psoriasis but largely ignored non-additive effects. We report a genotypic variability-based GWAS (vGWAS) that can prioritize non-additive loci without requiring prior knowledge of interaction types or interacting factors in two steps, using a mixed model to partition dichotomous phenotypes into an additive component and non-additive environmental residuals on the liability scale and then the Levene's (Brown-Forsythe) test to assess equality of the residual variances across genotype groups genome widely. The vGWAS identified two genome-wide significant (P < 5.0e-08) non-additive loci HLA-C and IL12B that were also genome-wide significant in an accompanying GWAS in the discovery cohort. Both loci were statistically replicated in vGWAS of an independent cohort with a small sample size. HLA-C and IL12B were reported in moderate gene-gene and/or gene-environment interactions in several occasions. We found a moderate interaction with age-of-onset of psoriasis, which was replicated indirectly. The vGWAS also revealed five suggestive loci (P < 6.76e-05) including FUT2 that was associated with psoriasis with environmental aspects triggered by virus infection and/or metabolic factors. Replication and functional investigation are needed to validate the suggestive vGWAS loci.

Notions such as "truth" or "correspondence to the objective world" play no role in explanatory accounts of perception.

PubMed

Mausfeld, Rainer

2015-12-01

Hoffman, Singh, and Prakash (Psychonomic Review and Bulletin, 2015, in press) intend to show that perceptions are evolutionarily tuned to fitness rather than to truth. I argue, partly in accordance with their objective, that issues of 'truth' or 'veridicality' have no place in explanatory accounts of perception theory, and rather belong to either ordinary discourse or to philosophy. I regard, however, their general presumption that the evolutionary development of core achievements of the human perceptual system would be primarily determined by aspects of fitness and adaption as unwarranted in light of the evidence available.

Forced Expiratory Volume in 1 Second Variability Helps Identify Patients with Cystic Fibrosis at Risk of Greater Loss of Lung Function.

PubMed

Morgan, Wayne J; VanDevanter, Donald R; Pasta, David J; Foreman, Aimee J; Wagener, Jeffrey S; Konstan, Michael W

2016-02-01

To evaluate several alternative measures of forced expiratory volume in 1 second percent predicted (FEV1 %pred) variability as potential predictors of future FEV1 %pred decline in patients with cystic fibrosis. We included 13,827 patients age ≥6 years from the Epidemiologic Study of Cystic Fibrosis 1994-2002 with ≥4 FEV1 %pred measurements spanning ≥366 days in both a 2-year baseline period and a 2-year follow-up period. We predicted change from best baseline FEV1 %pred to best follow-up FEV1 %pred and change from baseline to best in the second follow-up year by using multivariable regression stratified by 4 lung-disease stages. We assessed 5 measures of variability (some as deviations from the best and some as deviations from the trend line) both alone and after controlling for demographic and clinical factors and for the slope and level of FEV1 %pred. All 5 measures of FEV1 %pred variability were predictive, but the strongest predictor was median deviation from the best FEV1 %pred in the baseline period. The contribution to explanatory power (R(2)) was substantial and exceeded the total contribution of all other factors excluding the FEV1 %pred rate of decline. Adding the other variability measures provided minimal additional value. Median deviation from the best FEV1 %pred is a simple metric that markedly improves prediction of FEV1 %pred decline even after the inclusion of demographic and clinical characteristics and the FEV1 %pred rate of decline. The routine calculation of this variability measure could allow clinicians to better identify patients at risk and therefore in need of increased intervention. Copyright © 2016 Elsevier Inc. All rights reserved.

Continuous water-quality monitoring and regression analysis to estimate constituent concentrations and loads in the Red River of the North at Fargo and Grand Forks, North Dakota, 2003-12

USGS Publications Warehouse

Galloway, Joel M.

2014-01-01

The Red River of the North (hereafter referred to as “Red River”) Basin is an important hydrologic region where water is a valuable resource for the region’s economy. Continuous water-quality monitors have been operated by the U.S. Geological Survey, in cooperation with the North Dakota Department of Health, Minnesota Pollution Control Agency, City of Fargo, City of Moorhead, City of Grand Forks, and City of East Grand Forks at the Red River at Fargo, North Dakota, from 2003 through 2012 and at Grand Forks, N.Dak., from 2007 through 2012. The purpose of the monitoring was to provide a better understanding of the water-quality dynamics of the Red River and provide a way to track changes in water quality. Regression equations were developed that can be used to estimate concentrations and loads for dissolved solids, sulfate, chloride, nitrate plus nitrite, total phosphorus, and suspended sediment using explanatory variables such as streamflow, specific conductance, and turbidity. Specific conductance was determined to be a significant explanatory variable for estimating dissolved solids concentrations at the Red River at Fargo and Grand Forks. The regression equations provided good relations between dissolved solid concentrations and specific conductance for the Red River at Fargo and at Grand Forks, with adjusted coefficients of determination of 0.99 and 0.98, respectively. Specific conductance, log-transformed streamflow, and a seasonal component were statistically significant explanatory variables for estimating sulfate in the Red River at Fargo and Grand Forks. Regression equations provided good relations between sulfate concentrations and the explanatory variables, with adjusted coefficients of determination of 0.94 and 0.89, respectively. For the Red River at Fargo and Grand Forks, specific conductance, streamflow, and a seasonal component were statistically significant explanatory variables for estimating chloride. For the Red River at Grand Forks, a time

Prevalence of nutritional wasting in populations: building explanatory models using secondary data.

PubMed Central

Fernandez, Isabel D.; Himes, John H.; de Onis, Mercedes

2002-01-01

OBJECTIVE: To understand how social context affects the nutritional status of populations, as reflected by the prevalence of wasting in children under 5 years of age from Africa, Latin America, and Asia; to present a systematic way of building models for wasting prevalence, using a conceptual framework for the determinants of malnutrition; and to examine the feasibility of using readily available data collected over time to build models of wasting prevalence in populations. METHODS: Associations between prevalence of wasting and environmental variables were examined in the three regions. General linear mixed models were fitted using anthropometric survey data for countries within each region. FINDINGS: Low birth weight (LBW), measles incidence, and access to a safe water supply explained 64% of wasting variability in Asia. In Latin America, LBW and survey year explained 38%; in Africa, LBW, survey year, and adult literacy explained 7%. CONCLUSION: LBW emerged as a predictor of wasting prevalence in all three regions. Actions regarding women's rights may have an effect on the nutritional status of children since LBW seems to reflect several aspects of the conditions of women in society. Databases have to be made compatible with each other to facilitate integrated analysis for nutritional research and policy decision-making. In addition, the validity of the variables representing the conceptual framework should be improved. PMID:12075364

The Effect of Latent Binary Variables on the Uncertainty of the Prediction of a Dichotomous Outcome Using Logistic Regression Based Propensity Score Matching.

PubMed

Szekér, Szabolcs; Vathy-Fogarassy, Ágnes

2018-01-01

Logistic regression based propensity score matching is a widely used method in case-control studies to select the individuals of the control group. This method creates a suitable control group if all factors affecting the output variable are known. However, if relevant latent variables exist as well, which are not taken into account during the calculations, the quality of the control group is uncertain. In this paper, we present a statistics-based research in which we try to determine the relationship between the accuracy of the logistic regression model and the uncertainty of the dependent variable of the control group defined by propensity score matching. Our analyses show that there is a linear correlation between the fit of the logistic regression model and the uncertainty of the output variable. In certain cases, a latent binary explanatory variable can result in a relative error of up to 70% in the prediction of the outcome variable. The observed phenomenon calls the attention of analysts to an important point, which must be taken into account when deducting conclusions.

Effects of additional data on Bayesian clustering.

PubMed

Yamazaki, Keisuke

2017-10-01

Hierarchical probabilistic models, such as mixture models, are used for cluster analysis. These models have two types of variables: observable and latent. In cluster analysis, the latent variable is estimated, and it is expected that additional information will improve the accuracy of the estimation of the latent variable. Many proposed learning methods are able to use additional data; these include semi-supervised learning and transfer learning. However, from a statistical point of view, a complex probabilistic model that encompasses both the initial and additional data might be less accurate due to having a higher-dimensional parameter. The present paper presents a theoretical analysis of the accuracy of such a model and clarifies which factor has the greatest effect on its accuracy, the advantages of obtaining additional data, and the disadvantages of increasing the complexity. Copyright © 2017 Elsevier Ltd. All rights reserved.

Eating Disorders: Explanatory Variables in Caucasian and Hispanic College Women

ERIC Educational Resources Information Center

Aviña, Vanessa; Day, Susan X.

2016-01-01

The authors explored Hispanic and Caucasian college women's (N = 264) behavioral and attitudinal symptoms of eating disorders after controlling for body mass index and internalization of the thinness ideal, as well as the roles of ethnicity and ethnic identity in symptomatology. Correlational analysis, multivariate analysis of variance, and…

Fraying connections of caring women: an exemplar of including difference in the development of explanatory frameworks.

PubMed

Wuest, J

1997-01-01

While research exploring diverse groups enhances understanding of their unique perspectives and experiences, it also contributes to the exclusion of such groups from mainstream frameworks and solutions. The feminist grounded theory method allows for inclusion of marginalized groups through theoretical sensitivity to feminist theory and theoretical sampling. This paper demonstrates how this approach results in an explanatory framework that accounts for diverse realities in a study of women's caring. Fraying connections were identified as women's initial response to competing and changing caring demands. The range of dimensions and properties of fraying connections was identified through theoretical sampling guided by the emerging themes and theoretical sensitivity to issues of gender, culture, age, ability, class, and sexual orientation.

Distribution and relative abundance of humpback whales in relation to environmental variables in coastal British Columbia and adjacent waters

NASA Astrophysics Data System (ADS)

Dalla Rosa, Luciano; Ford, John K. B.; Trites, Andrew W.

2012-03-01

Humpback whales are common in feeding areas off British Columbia (BC) from spring to fall, and are widely distributed along the coast. Climate change and the increase in population size of North Pacific humpback whales may lead to increased anthropogenic impact and require a better understanding of species-habitat relationships. We investigated the distribution and relative abundance of humpback whales in relation to environmental variables and processes in BC waters using GIS and generalized additive models (GAMs). Six non-systematic cetacean surveys were conducted between 2004 and 2006. Whale encounter rates and environmental variables (oceanographic and remote sensing data) were recorded along transects divided into 4 km segments. A combined 3-year model and individual year models (two surveys each) were fitted with the mgcv R package. Model selection was based primarily on GCV scores. The explained deviance of our models ranged from 39% for the 3-year model to 76% for the 2004 model. Humpback whales were strongly associated with latitude and bathymetric features, including depth, slope and distance to the 100-m isobath. Distance to sea-surface-temperature fronts and salinity (climatology) were also constantly selected by the models. The shapes of smooth functions estimated for variables based on chlorophyll concentration or net primary productivity with different temporal resolutions and time lags were not consistent, even though higher numbers of whales seemed to be associated with higher primary productivity for some models. These and other selected explanatory variables may reflect areas of higher biological productivity that favor top predators. Our study confirms the presence of at least three important regions for humpback whales along the BC coast: south Dixon Entrance, middle and southwestern Hecate Strait and the area between La Perouse Bank and the southern edge of Juan de Fuca Canyon.

Additive Genetic Variability and the Bayesian Alphabet

PubMed Central

Gianola, Daniel; de los Campos, Gustavo; Hill, William G.; Manfredi, Eduardo; Fernando, Rohan

2009-01-01

The use of all available molecular markers in statistical models for prediction of quantitative traits has led to what could be termed a genomic-assisted selection paradigm in animal and plant breeding. This article provides a critical review of some theoretical and statistical concepts in the context of genomic-assisted genetic evaluation of animals and crops. First, relationships between the (Bayesian) variance of marker effects in some regression models and additive genetic variance are examined under standard assumptions. Second, the connection between marker genotypes and resemblance between relatives is explored, and linkages between a marker-based model and the infinitesimal model are reviewed. Third, issues associated with the use of Bayesian models for marker-assisted selection, with a focus on the role of the priors, are examined from a theoretical angle. The sensitivity of a Bayesian specification that has been proposed (called “Bayes A”) with respect to priors is illustrated with a simulation. Methods that can solve potential shortcomings of some of these Bayesian regression procedures are discussed briefly. PMID:19620397

Discrete factor approximations in simultaneous equation models: estimating the impact of a dummy endogenous variable on a continuous outcome.

PubMed

Mroz, T A

1999-10-01

This paper contains a Monte Carlo evaluation of estimators used to control for endogeneity of dummy explanatory variables in continuous outcome regression models. When the true model has bivariate normal disturbances, estimators using discrete factor approximations compare favorably to efficient estimators in terms of precision and bias; these approximation estimators dominate all the other estimators examined when the disturbances are non-normal. The experiments also indicate that one should liberally add points of support to the discrete factor distribution. The paper concludes with an application of the discrete factor approximation to the estimation of the impact of marriage on wages.

Baleen whale abundance and distribution in relation to environmental variables and prey density in the Eastern Bering Sea

NASA Astrophysics Data System (ADS)

Zerbini, Alexandre N.; Friday, Nancy A.; Palacios, Daniel M.; Waite, Janice M.; Ressler, Patrick H.; Rone, Brenda K.; Moore, Sue E.; Clapham, Phillip J.

2016-12-01

The Bering Sea is one of the most productive marine ecosystems in the world and an important habitat for various marine mammal species. Once abundant in this region, most baleen whale species were severely depleted by commercial whaling in the 19th and early 20th centuries. Since their protection in mid-20th century, baleen whale populations have been recovering and reoccupying their historical habitats. These species can consume large amounts of their prey and thus can modify the local structure of ecosystems. Characterizing the extent to which environmental conditions and prey density influence baleen whale abundance in the Eastern Bering Sea is essential to improve our understanding of ecosystem dynamics and to predict how these species might respond to ecosystem variability associated with climate changes. In this study, physiographic, oceanographic, and biological datasets from 2008 to 2010 were combined to model the habitat characteristics of fin whales, humpback whales, and minke whales in the EBS in early summer (June and July) using generalized additive models (GAMs). The explained deviances of the best-supported models were 54.9%, 20.6%, and 68.3% for minke, fin and humpback whales, respectively. Minke and fin whales had similar distribution patterns in the EBS but their abundance was predicted by different explanatory variables. Euphausiid and pollock biomasses, and depth were important predictors of minke whale numbers, while distance to shore, euphausiid biomass, distance to the 200 m isobath, and chlorophyll-a concentration better explained fin whale abundance. Humpback whales showed a preference for shallow, coastal waters north of the Alaska Peninsula. For this species, sea surface temperature, depth, chlorophyll-a concentration and euphausid biomass were important predictors of abundance. This study is the first to provide a habitat baseline for baleen whales in the EBS based on a quantitative assessment of the relationship between whale abundance

Obligatory Effort [Hishtadlut] as an Explanatory Model: A Critique of Reproductive Choice and Control.

PubMed

Teman, Elly; Ivry, Tsipy; Goren, Heela

2016-06-01

Studies on reproductive technologies often examine women's reproductive lives in terms of choice and control. Drawing on 48 accounts of procreative experiences of religiously devout Jewish women in Israel and the US, we examine their attitudes, understandings and experiences of pregnancy, reproductive technologies and prenatal testing. We suggest that the concept of hishtadlut-"obligatory effort"-works as an explanatory model that organizes Haredi women's reproductive careers and their negotiations of reproductive technologies. As an elastic category with negotiable and dynamic boundaries, hishtadlut gives ultra-orthodox Jewish women room for effort without the assumption of control; it allows them to exercise discretion in relation to medical issues without framing their efforts in terms of individual choice. Haredi women hold themselves responsible for making their obligatory effort and not for pregnancy outcomes. We suggest that an alternative paradigm to autonomous choice and control emerges from cosmological orders where reproductive duties constitute "obligatory choices."

Additive effects of mean temperature, temperature variability, and chlorothalonil to red-eyed treefrog (Agalychnis callidryas) larvae.

PubMed

Alza, Carissa M; Donnelly, Maureen A; Whitfield, Steven M

2016-12-01

Amphibian populations are declining globally, and multiple anthropogenic stressors, including contamination by pesticides and shifting climates, are driving these declines. Climate change may increase average temperatures or increase temperature variability, either of which may affect the susceptibility of nontarget organisms to contaminants. Eight-day ecotoxicological assays were conducted with red-eyed treefrog (Agalychnis callidryas) larvae to test for additive and interactive effects of exposure to the fungicide chlorothalonil, average temperature, and temperature variability on tadpole growth and survival. Egg masses were collected from seasonal ponds at La Selva Biological Station in Costa Rica, and tadpoles were exposed to a series of chlorothalonil concentrations across a range of ecologically relevant mean temperatures (23.4-27.3 °C) and daily temperature fluctuations (1.1-9.9 °C). Survival was measured each day, and tadpole growth was measured at the end of each trial. Concentrations of chlorothalonil ≥60 µg/L reduced survival, although survival was not affected by mean temperature or daily temperature range, and there were no synergistic interactions between chlorothalonil and temperature regime on survival. Chlorothalonil suppressed tadpole growth at relatively low concentrations (∼15 µg/L). There were impacts of both average temperature and daily temperature range on tadpole growth, although there were no synergistic interactions between temperature regimes and chlorothalonil. The results should inform efforts to manage ecosystems impacted by multiple large-scale anthropogenic stressors as well as methods for the design of ecologically appropriate toxicology trials. Environ Toxicol Chem 2016;35:2998-3004. © 2016 SETAC. © 2016 SETAC.

Intra-Site Variability in the Still Bay Fauna at Blombos Cave: Implications for Explanatory Models of the Middle Stone Age Cultural and Technological Evolution

PubMed Central

Discamps, Emmanuel; Henshilwood, Christopher Stuart

2015-01-01

To explain cultural and technological innovations in the Middle Stone Age (MSA) of southern Africa, scholars invoke several factors. A major question in this research theme is whether MSA technocomplexes are adapted to a particular set of environmental conditions and subsistence strategies or, on the contrary, to a wide range of different foraging behaviours. While faunal studies provide key information for addressing these factors, most analyses do not assess intra-technocomplex variability of faunal exploitation (i.e. variability within MSA phases). In this study, we assess the spatial variability of the Still Bay fauna in one phase (M1) of the Blombos Cave sequence. Analyses of taxonomic composition, taphonomic alterations and combustion patterns reveal important faunal variability both across space (lateral variation in the post-depositional history of the deposits, spatial organisation of combustion features) and over time (fine-scale diachronic changes throughout a single phase). Our results show how grouping material prior to zooarchaeological interpretations (e.g. by layer or phase) can induce a loss of information. Finally, we discuss how multiple independent subdivisions of archaeological sequences can improve our understanding of both the timing of different changes (for example in technology, culture, subsistence, environment) and how they may be inter-related. PMID:26658195

Intra-Site Variability in the Still Bay Fauna at Blombos Cave: Implications for Explanatory Models of the Middle Stone Age Cultural and Technological Evolution.

PubMed

Discamps, Emmanuel; Henshilwood, Christopher Stuart

2015-01-01

To explain cultural and technological innovations in the Middle Stone Age (MSA) of southern Africa, scholars invoke several factors. A major question in this research theme is whether MSA technocomplexes are adapted to a particular set of environmental conditions and subsistence strategies or, on the contrary, to a wide range of different foraging behaviours. While faunal studies provide key information for addressing these factors, most analyses do not assess intra-technocomplex variability of faunal exploitation (i.e. variability within MSA phases). In this study, we assess the spatial variability of the Still Bay fauna in one phase (M1) of the Blombos Cave sequence. Analyses of taxonomic composition, taphonomic alterations and combustion patterns reveal important faunal variability both across space (lateral variation in the post-depositional history of the deposits, spatial organisation of combustion features) and over time (fine-scale diachronic changes throughout a single phase). Our results show how grouping material prior to zooarchaeological interpretations (e.g. by layer or phase) can induce a loss of information. Finally, we discuss how multiple independent subdivisions of archaeological sequences can improve our understanding of both the timing of different changes (for example in technology, culture, subsistence, environment) and how they may be inter-related.

Using generalized additive mixed models to assess spatial, temporal, and hydrologic controls on bacteria and nitrate in a vulnerable agricultural aquifer.

PubMed

Mellor, Andrea F P; Cey, Edwin E

2015-11-01

The Abbotsford-Sumas aquifer (ASA) has a history of nitrate contamination from agricultural land use and manure application to soils, yet little is known about its microbial groundwater quality. The goal of this study was to investigate the spatiotemporal distribution of pathogen indicators (Escherichia coli [E. coli] and total coliform [TC]) and nitrate in groundwater, and their potential relation to hydrologic drivers. Sampling of 46 wells over an 11-month period confirmed elevated nitrate concentrations, with more than 50% of samples exceeding 10 mg-N/L. E. coli detections in groundwater were infrequent (4 of 385 total samples) and attributed mainly to surface water-groundwater connections along Fishtrap Creek, which tested positive for E. coli in every sampling event. TC was detected frequently in groundwater (70% of samples) across the ASA. Generalized additive mixed models (GAMMs) yielded valuable insights into relationships between TC or nitrate and a range of spatial, temporal, and hydrologic explanatory variables. Increased TC values over the wetter fall and winter period were most strongly related to groundwater temperatures and levels, while precipitation and well location were weaker (but still significant) predictors. In contrast, the moderate temporal variability in nitrate concentrations was not significantly related to hydrologic forcings. TC was relatively widespread across the ASA and spatial patterns could not be attributed solely to surface water connectivity. Varying nitrate concentrations across the ASA were significantly related to both well location and depth, likely due to spatially variable nitrogen loading and localized geochemical attenuation (i.e., denitrification). Vulnerability of the ASA to bacteria was clearly linked to hydrologic conditions, and was distinct from nitrate, such that a groundwater management strategy specifically for bacterial contaminants is warranted. Copyright © 2015 Elsevier B.V. All rights reserved.

Operator’s Manual for Variable Weight, Variable C.G. Helmet Simulator

DTIC Science & Technology

1981-09-01

fdoestify by block nufber) - A variable weight, variable CG helmet simulator has been designed to measure the effect of US Army headgear on muscle...any variable weights in the boxes, is 2.5 lb, slightly less than the weight of most quality crash helmets made by reputable manufacturers. The addition...of variable weights to the boxes can alter the center of gravity to simulate the effect of equipment attached to the out- side of a helmet. The

Phytoscreening with SPME: Variability Analysis.

PubMed

Limmer, Matt A; Burken, Joel G

2015-01-01

Phytoscreening has been demonstrated at a variety of sites over the past 15 years as a low-impact, sustainable tool in delineation of shallow groundwater contaminated with chlorinated solvents. Collection of tree cores is rapid and straightforward, but low concentrations in tree tissues requires sensitive analytics. Solid-phase microextraction (SPME) is amenable to the complex matrix while allowing for solvent-less extraction. Accurate quantification requires the absence of competitive sorption, examined here both in laboratory experiments and through comprehensive examination of field data. Analysis of approximately 2,000 trees at numerous field sites also allowed testing of the tree genus and diameter effects on measured tree contaminant concentrations. Collectively, while these variables were found to significantly affect site-adjusted perchloroethylene (PCE) concentrations, the explanatory power of these effects was small (adjusted R(2) = 0.031). 90th quantile chemical concentrations in trees were significantly reduced by increasing Henry's constant and increasing hydrophobicity. Analysis of replicate tree core data showed no correlation between replicate relative standard deviation (RSD) and wood type or tree diameter, with an overall median RSD of 30%. Collectively, these findings indicate SPME is an appropriate technique for sampling and analyzing chlorinated solvents in wood and that phytoscreening is robust against changes in tree type and diameter.

Reflecting on explanatory ability: A mechanism for detecting gaps in causal knowledge.

PubMed

Johnson, Dan R; Murphy, Meredith P; Messer, Riley M

2016-05-01

People frequently overestimate their understanding-with a particularly large blind-spot for gaps in their causal knowledge. We introduce a metacognitive approach to reducing overestimation, termed reflecting on explanatory ability (REA), which is briefly thinking about how well one could explain something in a mechanistic, step-by-step, causally connected manner. Nine experiments demonstrated that engaging in REA just before estimating one's understanding substantially reduced overestimation. Moreover, REA reduced overestimation with nearly the same potency as generating full explanations, but did so 20 times faster (although only for high complexity objects). REA substantially reduced overestimation by inducing participants to quickly evaluate an object's inherent causal complexity (Experiments 4-7). REA reduced overestimation by also fostering step-by-step, causally connected processing (Experiments 2 and 3). Alternative explanations for REA's effects were ruled out including a general conservatism account (Experiments 4 and 5) and a covert explanation account (Experiment 8). REA's overestimation-reduction effect generalized beyond objects (Experiments 1-8) to sociopolitical policies (Experiment 9). REA efficiently detects gaps in our causal knowledge with implications for improving self-directed learning, enhancing self-insight into vocational and academic abilities, and even reducing extremist attitudes. (c) 2016 APA, all rights reserved).

Making trials matter: pragmatic and explanatory trials and the problem of applicability

PubMed Central

Treweek, Shaun; Zwarenstein, Merrick

2009-01-01

Randomised controlled trials are the best research design for decisions about the effect of different interventions but randomisation does not, of itself, promote the applicability of a trial's results to situations other than the precise one in which the trial was done. While methodologists and trialists have rightly paid great attention to internal validity, much less has been given to applicability. This narrative review is aimed at those planning to conduct trials, and those aiming to use the information in them. It is intended to help the former group make their trials more widely useful and to help the latter group make more informed decisions about the wider use of existing trials. We review the differences between the design of most randomised trials (which have an explanatory attitude) and the design of trials more able to inform decision making (which have a pragmatic attitude) and discuss approaches used to assert applicability of trial results. If we want evidence from trials to be used in clinical practice and policy, trialists should make every effort to make their trial widely applicable, which means that more trials should be pragmatic in attitude. PMID:19493350

AIC identifies optimal representation of longitudinal dietary variables.

PubMed

VanBuren, John; Cavanaugh, Joseph; Marshall, Teresa; Warren, John; Levy, Steven M

2017-09-01

The Akaike Information Criterion (AIC) is a well-known tool for variable selection in multivariable modeling as well as a tool to help identify the optimal representation of explanatory variables. However, it has been discussed infrequently in the dental literature. The purpose of this paper is to demonstrate the use of AIC in determining the optimal representation of dietary variables in a longitudinal dental study. The Iowa Fluoride Study enrolled children at birth and dental examinations were conducted at ages 5, 9, 13, and 17. Decayed or filled surfaces (DFS) trend clusters were created based on age 13 DFS counts and age 13-17 DFS increments. Dietary intake data (water, milk, 100 percent-juice, and sugar sweetened beverages) were collected semiannually using a food frequency questionnaire. Multinomial logistic regression models were fit to predict DFS cluster membership (n=344). Multiple approaches could be used to represent the dietary data including averaging across all collected surveys or over different shorter time periods to capture age-specific trends or using the individual time points of dietary data. AIC helped identify the optimal representation. Averaging data for all four dietary variables for the whole period from age 9.0 to 17.0 provided a better representation in the multivariable full model (AIC=745.0) compared to other methods assessed in full models (AICs=750.6 for age 9 and 9-13 increment dietary measurements and AIC=762.3 for age 9, 13, and 17 individual measurements). The results illustrate that AIC can help researchers identify the optimal way to summarize information for inclusion in a statistical model. The method presented here can be used by researchers performing statistical modeling in dental research. This method provides an alternative approach for assessing the propriety of variable representation to significance-based procedures, which could potentially lead to improved research in the dental community. © 2017 American

Development of a neural-based forecasting tool to classify recreational water quality using fecal indicator organisms.

PubMed

Motamarri, Srinivas; Boccelli, Dominic L

2012-09-15

Users of recreational waters may be exposed to elevated pathogen levels through various point/non-point sources. Typical daily notifications rely on microbial analysis of indicator organisms (e.g., Escherichia coli) that require 18, or more, hours to provide an adequate response. Modeling approaches, such as multivariate linear regression (MLR) and artificial neural networks (ANN), have been utilized to provide quick predictions of microbial concentrations for classification purposes, but generally suffer from high false negative rates. This study introduces the use of learning vector quantization (LVQ)--a direct classification approach--for comparison with MLR and ANN approaches and integrates input selection for model development with respect to primary and secondary water quality standards within the Charles River Basin (Massachusetts, USA) using meteorologic, hydrologic, and microbial explanatory variables. Integrating input selection into model development showed that discharge variables were the most important explanatory variables while antecedent rainfall and time since previous events were also important. With respect to classification, all three models adequately represented the non-violated samples (>90%). The MLR approach had the highest false negative rates associated with classifying violated samples (41-62% vs 13-43% (ANN) and <16% (LVQ)) when using five or more explanatory variables. The ANN performance was more similar to LVQ when a larger number of explanatory variables were utilized, but the ANN performance degraded toward MLR performance as explanatory variables were removed. Overall, the use of LVQ as a direct classifier provided the best overall classification ability with respect to violated/non-violated samples for both standards. Copyright © 2012 Elsevier Ltd. All rights reserved.

Spatial regression analysis on 32 years of total column ozone data

NASA Astrophysics Data System (ADS)

Knibbe, J. S.; van der A, R. J.; de Laat, A. T. J.

2014-08-01

Multiple-regression analyses have been performed on 32 years of total ozone column data that was spatially gridded with a 1 × 1.5° resolution. The total ozone data consist of the MSR (Multi Sensor Reanalysis; 1979-2008) and 2 years of assimilated SCIAMACHY (SCanning Imaging Absorption spectroMeter for Atmospheric CHartographY) ozone data (2009-2010). The two-dimensionality in this data set allows us to perform the regressions locally and investigate spatial patterns of regression coefficients and their explanatory power. Seasonal dependencies of ozone on regressors are included in the analysis. A new physically oriented model is developed to parameterize stratospheric ozone. Ozone variations on nonseasonal timescales are parameterized by explanatory variables describing the solar cycle, stratospheric aerosols, the quasi-biennial oscillation (QBO), El Niño-Southern Oscillation (ENSO) and stratospheric alternative halogens which are parameterized by the effective equivalent stratospheric chlorine (EESC). For several explanatory variables, seasonally adjusted versions of these explanatory variables are constructed to account for the difference in their effect on ozone throughout the year. To account for seasonal variation in ozone, explanatory variables describing the polar vortex, geopotential height, potential vorticity and average day length are included. Results of this regression model are compared to that of a similar analysis based on a more commonly applied statistically oriented model. The physically oriented model provides spatial patterns in the regression results for each explanatory variable. The EESC has a significant depleting effect on ozone at mid- and high latitudes, the solar cycle affects ozone positively mostly in the Southern Hemisphere, stratospheric aerosols affect ozone negatively at high northern latitudes, the effect of QBO is positive and negative in the tropics and mid- to high latitudes, respectively, and ENSO affects ozone negatively

A novel variable selection approach that iteratively optimizes variable space using weighted binary matrix sampling.

PubMed

Deng, Bai-chuan; Yun, Yong-huan; Liang, Yi-zeng; Yi, Lun-zhao

2014-10-07

In this study, a new optimization algorithm called the Variable Iterative Space Shrinkage Approach (VISSA) that is based on the idea of model population analysis (MPA) is proposed for variable selection. Unlike most of the existing optimization methods for variable selection, VISSA statistically evaluates the performance of variable space in each step of optimization. Weighted binary matrix sampling (WBMS) is proposed to generate sub-models that span the variable subspace. Two rules are highlighted during the optimization procedure. First, the variable space shrinks in each step. Second, the new variable space outperforms the previous one. The second rule, which is rarely satisfied in most of the existing methods, is the core of the VISSA strategy. Compared with some promising variable selection methods such as competitive adaptive reweighted sampling (CARS), Monte Carlo uninformative variable elimination (MCUVE) and iteratively retaining informative variables (IRIV), VISSA showed better prediction ability for the calibration of NIR data. In addition, VISSA is user-friendly; only a few insensitive parameters are needed, and the program terminates automatically without any additional conditions. The Matlab codes for implementing VISSA are freely available on the website: https://sourceforge.net/projects/multivariateanalysis/files/VISSA/.

Using Qualitative Methods to Explore Lay Explanatory Models, Health-Seeking Behaviours and Self-Care Practices of Podoconiosis Patients in North-West Ethiopia

PubMed Central

Banks, Harrison S.; Tsegay, Girmay; Wubie, Moges; Tamiru, Abreham; Davey, Gail; Cooper, Max

2016-01-01

Background Podoconiosis (endemic non-filarial elephantiasis) is a chronic, non-infectious disease resulting from exposure of bare feet to red-clay soil in tropical highlands. This study examined lay beliefs about three under-researched aspects of podoconiosis patients’ care: explanatory models, health-seeking behaviours and self-care. Methods In-depth interviews and focus group discussions were undertaken with 34 participants (19 male, 15 female) between April-May 2015 at podoconiosis treatment centres across East and West Gojjam regions in north-west Ethiopia. Results Explanatory models for podoconiosis included contamination from blood, magic, soil or affected individuals. Belief in heredity or divine punishment often delayed clinic attendance. All participants had tried holy water treatment and some, holy soil. Herbal treatments were considered ineffectual, costly and appeared to promote fluid escape. Motivators for clinic attendance were failure of traditional treatments and severe or disabling symptoms. Patients did not report self-treatment with antibiotics. Self-care was hindered by water being unavailable or expensive and patient fatigue. Conclusion A pluralistic approach to podoconiosis self-treatment was discovered. Holy water is widely valued, though some patients prefer holy soil. Priests and traditional healers could help promote self-care and “signpost” patients to clinics. Change in behaviour and improving water access is key to self-care. PMID:27536772

Using Qualitative Methods to Explore Lay Explanatory Models, Health-Seeking Behaviours and Self-Care Practices of Podoconiosis Patients in North-West Ethiopia.

PubMed

Banks, Harrison S; Tsegay, Girmay; Wubie, Moges; Tamiru, Abreham; Davey, Gail; Cooper, Max

2016-08-01

Podoconiosis (endemic non-filarial elephantiasis) is a chronic, non-infectious disease resulting from exposure of bare feet to red-clay soil in tropical highlands. This study examined lay beliefs about three under-researched aspects of podoconiosis patients' care: explanatory models, health-seeking behaviours and self-care. In-depth interviews and focus group discussions were undertaken with 34 participants (19 male, 15 female) between April-May 2015 at podoconiosis treatment centres across East and West Gojjam regions in north-west Ethiopia. Explanatory models for podoconiosis included contamination from blood, magic, soil or affected individuals. Belief in heredity or divine punishment often delayed clinic attendance. All participants had tried holy water treatment and some, holy soil. Herbal treatments were considered ineffectual, costly and appeared to promote fluid escape. Motivators for clinic attendance were failure of traditional treatments and severe or disabling symptoms. Patients did not report self-treatment with antibiotics. Self-care was hindered by water being unavailable or expensive and patient fatigue. A pluralistic approach to podoconiosis self-treatment was discovered. Holy water is widely valued, though some patients prefer holy soil. Priests and traditional healers could help promote self-care and "signpost" patients to clinics. Change in behaviour and improving water access is key to self-care.

Variable spectra of active galaxies

NASA Technical Reports Server (NTRS)

Halpern, Jules P.

1988-01-01

The analysis of EXOSAT spectra of active galaxies are presented. The objects examined for X-ray spectral variability were MR 2251-178 and 3C 120. The results of these investigations are described, as well as additional results on X-ray spectral variability related to EXOSAT observations of active galaxies. Additionally, the dipping X-ray source 4U1624-49 was also investigated.

Predicting High Quality AFQT with Youth Attitude Tracking Study Data

DTIC Science & Technology

1991-12-01

for propensities. The history of the art of mental aptitude and psychological testing is long and convoluted. Names like Sir Francis Galton of England...Qualification Test . The explanatory variables reflect individual demographic, educational and labor market characteristics at the time of YATS interview. The...the fiftieth percentile on the Armed Forces Qualification Test . The explanatory variables reflect individual demographic, educational and labor market

The explanatory role of relationship power and control in domestic violence against women in Nicaragua: a feminist psychology analysis.

PubMed

Grose, Rose Grace; Grabe, Shelly

2014-08-01

This study offers a feminist psychology analysis of various aspects of relationship power and control and their relative explanatory contribution to understanding physical, psychological, and sexual violence against women. Findings from structured interviews with 345 women from rural Nicaragua (M age = 44) overwhelmingly demonstrate that measures of power and control reflecting interpersonal relationship dynamics have the strongest predictive power for explaining violence when compared in multivariate analyses to several of the more commonly used measures. These findings have implications for future research and the evaluation of interventions designed to decrease levels of violence against women. © The Author(s) 2014.

Who theorizes age? The "socio-demographic variables" device and age-period-cohort analysis in the rhetoric of survey research.

PubMed

Rughiniș, Cosima; Humă, Bogdana

2015-12-01

In this paper we argue that quantitative survey-based social research essentializes age, through specific rhetorical tools. We outline the device of 'socio-demographic variables' and we discuss its argumentative functions, looking at scientific survey-based analyses of adult scientific literacy, in the Public Understanding of Science research field. 'Socio-demographics' are virtually omnipresent in survey literature: they are, as a rule, used and discussed as bundles of independent variables, requiring little, if any, theoretical and measurement attention. 'Socio-demographics' are rhetorically effective through their common-sense richness of meaning and inferential power. We identify their main argumentation functions as 'structure building', 'pacification', and 'purification'. Socio-demographics are used to uphold causal vocabularies, supporting the transmutation of the descriptive statistical jargon of 'effects' and 'explained variance' into 'explanatory factors'. Age can also be studied statistically as a main variable of interest, through the age-period-cohort (APC) disambiguation technique. While this approach has generated interesting findings, it did not mitigate the reductionism that appears when treating age as a socio-demographic variable. By working with age as a 'socio-demographic variable', quantitative researchers convert it (inadvertently) into a quasi-biological feature, symmetrical, as regards analytical treatment, with pathogens in epidemiological research. Copyright © 2015 Elsevier Inc. All rights reserved.

Perceived Risks and Normative Beliefs as Explanatory Models for College Student Alcohol Involvement: An Assessment of a Campus with Conventional Alcohol Control Policies and Enforcement Practices

ERIC Educational Resources Information Center

Lewis, Todd F.; Thombs, Dennis L.

2005-01-01

The aim of this study was to conduct a multivariate assessment of college student drinking motivations at a campus with conventional alcohol control policies and enforcement practices, including the establishment and dissemination of alcohol policies and the use of warnings to arouse fear of sanctions. Two explanatory models were compared:…

Childhood trauma, antisocial personality typologies and recent violent acts among inpatient males with severe mental illness: exploring an explanatory pathway.

PubMed

Bruce, Matt; Laporte, Dionne

2015-03-01

Prevalence of childhood trauma is elevated among individuals with severe mental illness (SMI) compared to the general population and associated with poor prognosis, substance misuse, lower treatment compliance and violence. Antisocial personality disorder (ASPD) typologies (childhood vs adult onset) also represent possible mediating mechanisms to explain risk of violence among men with SMI. The current study aimed to explore an explanatory pathway linking childhood traumatic exposure, antisocial personality typologies and risk of violent behaviour among adult male inpatients with SMI. A total of 162 male inpatients with SMI were examined using a cross-sectional survey design. Information was extracted from medical files, interviews and official criminal records. Fifty-two participants (32.1%) reported experiencing a childhood trauma before 15. This group was 2.8 times more likely to engage in violent acts within the past 6months than those without such a history. Furthermore, those with childhood onset ASPD (early starters) were more likely to report childhood trauma and engage in violence compared to adult onset ASPD (late starters) and those without antisocial histories. Multivariate analyses revealed that early starter ASPD was the only variable that independently predicted violence and mediated the relationship between childhood trauma and recent violent acts. A significant subset of men reporting trauma and antisocial conduct from childhood (early starter ASPD) is at considerably elevated risk of engaging in violent behaviours. Assessment of antisocial typologies in men with SMI may assist effective and defensible case prioritisation, resource allocation and treatment planning. Copyright © 2014 Elsevier B.V. All rights reserved.

Use of real-time monitoring to predict concentrations of select constituents in the Menomonee River drainage basin, Southeast Wisconsin, 2008-9

USGS Publications Warehouse

Baldwin, Austin K.; Graczyk, David J.; Robertson, Dale M.; Saad, David A.; Magruder, Christopher

2012-01-01

The models to estimate chloride concentrations all used specific conductance as the explanatory variable, except for the model for the Little Menomonee River near Freistadt, which used both specific conductance and turbidity as explanatory variables. Adjusted R2 values for the chloride models ranged from 0.74 to 0.97. Models to estimate total suspended solids and total phosphorus used turbidity as the only explanatory variable. Adjusted R2 values ranged from 0.77 to 0.94 for the total suspended solids models and from 0.55 to 0.75 for the total phosphorus models. Models to estimate indicator bacteria used water temperature and turbidity as the explanatory variables, with adjusted R2 values from 0.54 to 0.69 for Escherichia coli bacteria models and from 0.54 to 0.74 for fecal coliform bacteria models. Dissolved oxygen was not used in any of the final models. These models may help managers measure the effects of land-use changes and improvement projects, establish total maximum daily loads, estimate important water-quality indicators such as bacteria concentrations, and enable informed decision making in the future.

Addition of simultaneous heat and solute transport and variable fluid viscosity to SEAWAT

USGS Publications Warehouse

Thorne, D.; Langevin, C.D.; Sukop, M.C.

2006-01-01

SEAWAT is a finite-difference computer code designed to simulate coupled variable-density ground water flow and solute transport. This paper describes a new version of SEAWAT that adds the ability to simultaneously model energy and solute transport. This is necessary for simulating the transport of heat and salinity in coastal aquifers for example. This work extends the equation of state for fluid density to vary as a function of temperature and/or solute concentration. The program has also been modified to represent the effects of variable fluid viscosity as a function of temperature and/or concentration. The viscosity mechanism is verified against an analytical solution, and a test of temperature-dependent viscosity is provided. Finally, the classic Henry-Hilleke problem is solved with the new code. ?? 2006 Elsevier Ltd. All rights reserved.

Improving the diagnosis related grouping model's ability to explain length of stay of elderly medical inpatients by incorporating function-linked variables.

PubMed

Sahadevan, S; Earnest, A; Koh, Y L; Lee, K M; Soh, C H; Ding, Y Y

2004-09-01

This study first aimed to determine the adequacy of the Diagnosis Related Grouping (DRG) model's ability to explain (1) the variance in the actual length of stay (LOS) of elderly medical inpatients and (2) the LOS difference in the same cohort between the departments of Geriatric Medicine (GRM) and General Medicine (GM). We then looked at how these explanatory abilities of the DRG changed when patients' function-linked variables (ignored by DRG) were incorporated into the model. Basic demographic data of a consecutively hospitalised cohort of elderly medical inpatients from GRM and GM, as well as their actual LOS, discharge DRG codes [with their corresponding trimmed average length of stay (ALOS)] and selected function-linked variables (including premorbid functional status, change in functional profile during hospitalisation and number of therapists seen) were recorded. Beginning with ALOS, function-linked variables that were significantly associated with LOS were then added into two multiple liner regression models so as to quantify how the functional dimension improved the DRGs' abilities to explain LOS variances and interdepartmental LOS differences. Forward selection procedure was employed to determine the final models. For the interdepartmental analysis, the study sample was restricted to patients who shared common DRG codes. 114 GRM and 118 GM patients were studied. Trimmed ALOS alone explained 8% of the actual LOS variance. With the addition of function-linked variables, the adjusted R2 of the final model increased to 28%. Due to common code restrictions, the data of 79 GRM and 78 GM patients were available for the analysis of interdepartmental LOS differences. At the unadjusted stage, the median stay of GRM patients was 4.3 days longer than GM's and with adjustments made for the DRGs, this difference was reduced to 3.9 days. Additionally adjusting for the patients' functional features diminished the interdepartmental LOS discrepancy even further, to 2

A site specific model and analysis of the neutral somatic mutation rate in whole-genome cancer data.

PubMed

Bertl, Johanna; Guo, Qianyun; Juul, Malene; Besenbacher, Søren; Nielsen, Morten Muhlig; Hornshøj, Henrik; Pedersen, Jakob Skou; Hobolth, Asger

2018-04-19

Detailed modelling of the neutral mutational process in cancer cells is crucial for identifying driver mutations and understanding the mutational mechanisms that act during cancer development. The neutral mutational process is very complex: whole-genome analyses have revealed that the mutation rate differs between cancer types, between patients and along the genome depending on the genetic and epigenetic context. Therefore, methods that predict the number of different types of mutations in regions or specific genomic elements must consider local genomic explanatory variables. A major drawback of most methods is the need to average the explanatory variables across the entire region or genomic element. This procedure is particularly problematic if the explanatory variable varies dramatically in the element under consideration. To take into account the fine scale of the explanatory variables, we model the probabilities of different types of mutations for each position in the genome by multinomial logistic regression. We analyse 505 cancer genomes from 14 different cancer types and compare the performance in predicting mutation rate for both regional based models and site-specific models. We show that for 1000 randomly selected genomic positions, the site-specific model predicts the mutation rate much better than regional based models. We use a forward selection procedure to identify the most important explanatory variables. The procedure identifies site-specific conservation (phyloP), replication timing, and expression level as the best predictors for the mutation rate. Finally, our model confirms and quantifies certain well-known mutational signatures. We find that our site-specific multinomial regression model outperforms the regional based models. The possibility of including genomic variables on different scales and patient specific variables makes it a versatile framework for studying different mutational mechanisms. Our model can serve as the neutral null model

From built environment to health inequalities: An explanatory framework based on evidence

PubMed Central

Gelormino, Elena; Melis, Giulia; Marietta, Cristina; Costa, Giuseppe

2015-01-01

Objective: The Health in All Policies strategy aims to engage every policy domain in health promotion. The more socially disadvantaged groups are usually more affected by potential negative impacts of policies if they are not health oriented. The built environment represents an important policy domain and, apart from its housing component, its impact on health inequalities is seldom assessed. Methods: A scoping review of evidence on the built environment and its health equity impact was carried out, searching both urban and medical literature since 2000 analysing socio-economic inequalities in relation to different components of the built environment. Results: The proposed explanatory framework assumes that key features of built environment (identified as density, functional mix and public spaces and services), may influence individual health through their impact on both natural environment and social context, as well as behaviours, and that these effects may be unequally distributed according to the social position of individuals. Conclusion: In general, the expected links proposed by the framework are well documented in the literature; however, evidence of their impact on health inequalities remains uncertain due to confounding factors, heterogeneity in study design, and difficulty to generalize evidence that is still very embedded to local contexts. PMID:26844145

Illness perceptions and explanatory models of viral hepatitis B & C among immigrants and refugees: a narrative systematic review.

PubMed

Owiti, John A; Greenhalgh, Trisha; Sweeney, Lorna; Foster, Graham R; Bhui, Kamaldeep S

2015-02-15

Hepatitis B and C (HBV, HCV) infections are associated with high morbidity and mortality. Many countries with traditionally low prevalence (such as UK) are now planning interventions (screening, vaccination, and treatment) of high-risk immigrants from countries with high prevalence. This review aimed to synthesise the evidence on immigrants' knowledge of HBV and HCV that might influence the uptake of clinical interventions. The review was also used to inform the design and successful delivery of a randomised controlled trial of targeted screening and treatment. Five databases (PubMed, CINHAL, SOCIOFILE, PsycINFO & Web of Science) were systematically searched, supplemented by reference tracking, searches of selected journals, and of relevant websites. We aimed to identify qualitative and quantitative studies that investigated knowledge of HBV and HCV among immigrants from high endemic areas to low endemic areas. Evidence, extracted according to a conceptual framework of Kleinman's explanatory model, was subjected to narrative synthesis. We adapted the PEN-3 model to categorise and analyse themes, and recommend strategies for interventions to influence help-seeking behaviour. We identified 51 publications including quantitative (n = 39), qualitative (n = 11), and mixed methods (n = 1) designs. Most of the quantitative studies included small samples and had heterogeneous methods and outcomes. The studies mainly concentrated on hepatitis B and ethnic groups of South East Asian immigrants residing in USA, Canada, and Australia. Many immigrants lacked adequate knowledge of aetiology, symptoms, transmission risk factors, prevention strategies, and treatment, of hepatitis HBV and HCV. Ethnicity, gender, better education, higher income, and English proficiency influenced variations in levels and forms of knowledge. Immigrants are vulnerable to HBV and HCV, and risk life-threatening complications from these infections because of poor knowledge and help

Agricultural disturbance response models for invertebrate and algal metrics from streams at two spatial scales within the U.S.

USGS Publications Warehouse

Waite, Ian R.

2014-01-01

As part of the USGS study of nutrient enrichment of streams in agricultural regions throughout the United States, about 30 sites within each of eight study areas were selected to capture a gradient of nutrient conditions. The objective was to develop watershed disturbance predictive models for macroinvertebrate and algal metrics at national and three regional landscape scales to obtain a better understanding of important explanatory variables. Explanatory variables in models were generated from landscape data, habitat, and chemistry. Instream nutrient concentration and variables assessing the amount of disturbance to the riparian zone (e.g., percent row crops or percent agriculture) were selected as most important explanatory variable in almost all boosted regression tree models regardless of landscape scale or assemblage. Frequently, TN and TP concentration and riparian agricultural land use variables showed a threshold type response at relatively low values to biotic metrics modeled. Some measure of habitat condition was also commonly selected in the final invertebrate models, though the variable(s) varied across regions. Results suggest national models tended to account for more general landscape/climate differences, while regional models incorporated both broad landscape scale and more specific local-scale variables.

Attitude Towards Physics and Additional Mathematics Achievement Towards Physics Achievement

ERIC Educational Resources Information Center

Veloo, Arsaythamby; Nor, Rahimah; Khalid, Rozalina

2015-01-01

The purpose of this research is to identify the difference in students' attitude towards Physics and Additional Mathematics achievement based on gender and relationship between attitudinal variables towards Physics and Additional Mathematics achievement with achievement in Physics. This research focused on six variables, which is attitude towards…

Revising explanatory models to accommodate anomalous genetic phenomena: Problem solving in the context of discovery

NASA Astrophysics Data System (ADS)

Hafner, Robert; Stewart, Jim

Past problem-solving research has provided a basis for helping students structure their knowledge and apply appropriate problem-solving strategies to solve problems for which their knowledge (or mental models) of scientific phenomena is adequate (model-using problem solving). This research examines how problem solving in the domain of Mendelian genetics proceeds in situations where solvers' mental models are insufficient to solve problems at hand (model-revising problem solving). Such situations require solvers to use existing models to recognize anomalous data and to revise those models to accommodate the data. The study was conducted in the context of 9-week high school genetics course and addressed: the heuristics charactenstic of successful model-revising problem solving: the nature of the model revisions, made by students as well as the nature of model development across problem types; and the basis upon which solvers decide that a revised model is sufficient (that t has both predictive and explanatory power).

Parents' explanatory models and hopes for outcomes of occupational therapy using a sensory integration approach.

PubMed

Cohn, Ellen S; Kramer, Jessica; Schub, Jamie A; May-Benson, Teresa

2014-01-01

PURPOSE. To describe parents' concerns and hopes for their children who would be receiving occupational therapy using a sensory integration approach. METHOD. Content analysis of 275 parental responses to three open-ended questions on developmental-sensory history intake forms. FINDINGS. Parents' descriptions of why they sought for their children were categorized into four overarching concerns about their children's challenges: self-regulation, interacting with peers, participating in skilled motor activities, and self-confidence. Parents often linked these concerns together, revealing explanatory models of how they make sense of potential relationships among their children's challenges and how these challenges affect occupational performance. Parents hoped occupational therapy would help their children develop self-understanding and frustration tolerance to self-regulate their behavior in socially acceptable ways. IMPLICATIONS. Assessment and intervention should explicitly focus on links among self-regulation, social participation, skills, and perceived competence to address parents' expectations. Copyright © 2014 by the American Occupational Therapy Association, Inc.

Environmental Drivers of Inter-annual Variability in Beaufort Sea Marine Fish Community Structure

NASA Astrophysics Data System (ADS)

Majewski, A.; Atchison, S.; Eert, J.; Dempsey, M.; MacPhee, S.; Michel, C.; Reist, J.

2016-02-01

The Beaufort Sea is a complex and dynamic system influenced by a wide suite of oceanic and riverine inputs that affect the ecosystem. Interactions within the resulting water masses are largely driven by factors such as precipitation, wind, and ice cover. Thus, the Beaufort Sea environment is highly variable in both space and time, and this variability is reflected in the habitats of biota. Inherent system variability must be factored into baselines designed to detect changes resulting from anthropogenic stressors and natural drivers. Between 2012 and 2014, Fisheries and Oceans Canada conducted the first baseline survey of offshore marine fishes, their habitats, and ecological relationships in the Canadian Beaufort Sea. In 2012, benthic trawling was conducted at 28 stations spanning 20-1000 m depths across shelf and slope habitats, and selected stations were re-sampled in 2013 and 2014. Concurrent sampling of oceanographic parameters and sediment composition was conducted at each station. We examine the stability of marine fish assemblages over a three-year period, and compare results for shelf stations to previous research to develop longer-term perspectives. Oceanographic (e.g., salinity), physical (e.g., depth and sediment grain size) and geographic (e.g., distance from shore) parameters, and proxies for local productivity (i.e., water-column and benthic chlorophyll) are explored as explanatory variables affecting fish community structure among years. Establishing knowledge baselines and understanding variability in the community structure and habitat associations of Beaufort Sea marine fishes will support mitigation and conservation efforts by enhancing our ability to predict, detect and monitor the effects of hydrocarbon development and climate change on this pivotal ecosystem component.

Benefits of treatment theory in the design of explanatory trials: cognitive treatment of illness perception in chronic low back pain rehabilitation as an illustrative example.

PubMed

Siemonsma, Petra C; Schröder, Carin D; Roorda, Leo D; Lettinga, Ant T

2010-02-01

Evidence-based treatment is not effective for all patients. Research must therefore be carried out to help clinicians to decide for whom and under what circumstances certain treatment is effective. Treatment theory can assist in designing research that will provide results on which clinical decision-making can be based. To illustrate how treatment theory can be helpful in the design of explanatory trials that assist clinical decision-making. The benefit of treatment theory was demonstrated by approaching the design of a clinical trial from two perspectives: one without the use of treatment theory and one with the explicit use of treatment theory. Evaluation of the effectiveness of cognitive treatment of illness perceptions for patients with chronic low back pain was used as an illustrative example. With treatment theory as the main focus, the intervention became the starting point for the design of an explanatory trial. Potentially relevant patient selection criteria, essential treatment components, the optimal choice of a control group and the selection of outcome measures were specified. This paper not only describes problems encountered in research on the effectiveness of treatment, but also ways in which to address these problems.

Explanatory models of adult patients with type 2 diabetes mellitus from urban centers of central Ethiopia.

PubMed

Habte, Bruck M; Kebede, Tedla; Fenta, Teferi G; Boon, Heather

2016-09-13

Type 2 diabetes, which is increasing as a public health problem in the low resource settings of Africa has been associated with the high prevalence of micro-vascular complications and increasing levels of macro-vascular complications. There is evidence from the developed world that understanding patient perceptions of chronic illness is important to design effective strategies for helping patients manage these conditions. This study utilized Kleinman's model to explore the illness perceptions of type 2 diabetes patients attending treatment in Addis Ababa and Butajira (Ethiopia) and better understand how they manage their illness. Qualitative interviews were conducted to elicit the explanatory models of purposively sampled type 2 diabetes patients attending treatment in three hospitals in central Ethiopia until saturation of key emerging themes was achieved. Analysis of interview transcripts was guided by Kleinman's model. A total of 39 participants, 24 from Addis Ababa and the rest from Butajira took part in the study. This study revealed that patients' explanatory models were informed by both the traditional and biomedical models with emotional distress evident in some of the participants. The traditional model seemed to reflect the strong religious and cultural influences for the majority of study participants. The findings also revealed that symptoms played significant roles in how patients viewed their illness including assessment of its severity. Most were uncertain about the cause of their illness, with those expressing certainty citing factors over which they believed they had little or no control. This may have contributed to the perceptions about the use of religious healing and traditional medicines in a complementary or alternative manner to the biomedical regimen which could affect their adherence to recommended regimens and their health outcomes. This study suggests the need for a strong diabetes care program that is sensitive to patients' experiences

Insight in Psychosis: An Indicator of Severity of Psychosis, an Explanatory Model of Illness, and a Coping Strategy

PubMed Central

Jacob, K. S.

2016-01-01

Recent studies related to insight, explanatory models (EMs) of illness and their relationship to outcome of psychosis are reviewed. The traditional argument that insight predicts outcome in psychosis is not supported by recent longitudinal data, which has been analyzed using multivariable statistics that adjust for severity and quality of illness. While all cognition will have a neurobiological representation, if “insight” is related to the primary psychotic process, then insight cannot be seen as an independent predictor of outcome but a part of the progression of illness. The evidence suggests insight, like all EMs, is belief which interacts with the trajectory of the person's illness and the local culture to produce a unique understanding of the illness for the particular individual and his/her family. PMID:27335513

EXPLANATORY MODELS OF HYPERTENSION AMONG NIGERIAN PATIENTS AT A UNIVERSITY TEACHING HOSPITAL

PubMed Central

Taylor, Kelly D.; Adedokun, Ayoade; Awobusuyi, Olugbenga; Adeniran, Peju; Onyia, Elochukwu; Ogedegbe, Gbenga

2013-01-01

Objective To elicit the explanatory models (EM) of hypertension among patients in a hospital-based primary care practice in Nigeria. Design Semi-structured in-depth individual interviews and focus groups were conducted with 62 hypertensive patients. Interviews and focus groups were audio-taped and transcribed verbatim. Data analysis was guided by phenomenology and content analysis using qualitative research software ATLAS.ti 5.0. Results Patients expressed four categories of EM of hypertension: 1) perceptions of hypertension, 2) consequences, 3) effect on daily life, and 4) perception of treatment. Focus group discussions and key informant interviews yielded a wide range of insights into the social and cultural factors influencing patients’ beliefs and health behavior. Participants were aware of the risks of hypertension. There was disagreement between participants’ own understanding of the serious nature of hypertension, the need for long-term treatment, and the desire to take medication long-term. Participants acknowledged the use of traditional medicine (e.g. teas and herbs) and healers. Different themes emerged for men versus women such that women often focused on family issues while men tended to discuss external stressors stemming from work as a cause of hypertension. Men were concerned with frequent urination, decreased libido and erectile dysfunction. Conclusion Knowledge gained will inform development of patient-centered treatment plans and targeted behavioral and educational interventions. PMID:23534506

Collaboration amongst clinical nursing leadership teams: a mixed-methods sequential explanatory study.

PubMed

Lamont, Scott; Brunero, Scott; Lyons, Sarah; Foster, Karlie; Perry, Lin

2015-11-01

To explore intra-professional collaboration amongst nursing leadership teams at a tertiary referral hospital in Sydney. Effective working within a wide network of alliances is critical to patient outcomes. An understanding of collaboration amongst nursing leadership teams is essential within this context. A sequential explanatory mixed-methods design was used. The Collaborative Behaviour scale was sent to 106 Nurse Unit Managers, Nurse Educators and Clinical Nurse Consultants to measure pairwise collaborative behaviours; two follow-up focus groups with 15 participants were conducted. Data were collected between May 2012 and May 2013. A thematic analysis of focus group data provided a detailed explanation of the questionnaire findings. The findings identified high collaboration between dyad groups. Two themes emerged from the thematic analysis: (1) professional role and expectations; with sub-themes of transparency and clarity of individual roles; and intra/interpersonal aspects of role functioning; and (2) organisational infrastructure and governance. These leadership teams can be effective and powerful vehicles for change and are central to optimum patient outcomes. Organisational strategic planning and evaluation can benefit from understanding how to promote collaborative behaviours in these nurse leaders. To date, little research has explored collaboration amongst nursing leadership teams. Successful collaboration may contribute to the efficient use of nursing resources; improve patient outcomes, and ultimately, nurse satisfaction and retention. © 2014 John Wiley & Sons Ltd.

Drivers for spatial variability in agricultural soil organic carbon stocks in Germany

NASA Astrophysics Data System (ADS)

Vos, Cora; Don, Axel; Hobley, Eleanor; Prietz, Roland; Heidkamp, Arne; Freibauer, Annette

2017-04-01

Soil organic carbon is one of the largest components of the global carbon cycle. It has recently gained importance in global efforts to mitigate climate change through carbon sequestration. In order to find locations suitable for carbon sequestration, and estimate the sequestration potential, however, it is necessary to understand the factors influencing the high spatial variability of soil organic carbon stocks. Due to numerous interacting factors that influence its dynamics, soil organic carbon stocks are difficult to predict. In the course of the German Agricultural Soil Inventory over 2500 agricultural sites were sampled and their soil organic carbon stocks determined. Data relating to more than 200 potential drivers of SOC stocks were compiled from laboratory measurements, farmer questionnaires and climate stations. The aims of this study were to 1) give an overview of soil organic carbon stocks in Germany's agricultural soils, 2) to quantify and explain the influence of explanatory variables on soil organic carbon stocks. Two different machine learning algorithms were used to identify the most important variables and multiple regression models were used to explore the influence of those variables. Models for predicting carbon stocks in different depth increments between 0-100 cm were developed, explaining up to 62% (validation, 98% calibration) of total variance. Land-use, land-use history, clay content and electrical conductivity were main predictors in the topsoil, while bedrock material, relief and electrical conductivity governed the variability of subsoil carbon stocks. We found 32% of all soils to be deeply anthropogenically transformed. The influence of climate related variables was surprisingly small (≤5% of explained variance), while site variables explained a large share of soil carbon variability (46-100% of explained variance), in particular in the subsoil. Thus, the understanding of SOC dynamics at regional scale requires a thorough description

Analysis of variability in additive manufactured open cell porous structures.

PubMed

Evans, Sam; Jones, Eric; Fox, Pete; Sutcliffe, Chris

2017-06-01

In this article, a novel method of analysing build consistency of additively manufactured open cell porous structures is presented. Conventionally, methods such as micro computed tomography or scanning electron microscopy imaging have been applied to the measurement of geometric properties of porous material; however, high costs and low speeds make them unsuitable for analysing high volumes of components. Recent advances in the image-based analysis of open cell structures have opened up the possibility of qualifying variation in manufacturing of porous material. Here, a photogrammetric method of measurement, employing image analysis to extract values for geometric properties, is used to investigate the variation between identically designed porous samples measuring changes in material thickness and pore size, both intra- and inter-build. Following the measurement of 125 samples, intra-build material thickness showed variation of ±12%, and pore size ±4% of the mean measured values across five builds. Inter-build material thickness and pore size showed mean ranges higher than those of intra-build, ±16% and ±6% of the mean material thickness and pore size, respectively. Acquired measurements created baseline variation values and demonstrated techniques suitable for tracking build deviation and inspecting additively manufactured porous structures to indicate unwanted process fluctuations.

Cancer family caregiver depression: are religion-related variables important?

PubMed

Williams, Anna-Leila; Dixon, Jane; Feinn, Richard; McCorkle, Ruth

2015-07-01

Prevalence estimates for clinical depression among cancer family caregivers (CFC) range upwards to 39%. Research inconsistently reports risk for CFC depressive symptoms when evaluating age, gender, ethnicity, or length of time as caregiver. The discrepant findings, coupled with emerging literature indicating religiosity may mitigate depression in some populations, led us to investigate religion-related variables to help predict CFC depressive symptoms. We conducted a cross-sectional study of 150 CFC. Explanatory variables included age, gender, spousal status, length of time as caregiver, attendance at religious services, and prayer. The outcome variable was the Center for Epidemiological Studies Depression Scale score. Compared with large national and state datasets, our sample has lower representation of individuals with no religious affiliation (10.7% vs. 16.1% national, p = 0.07 and 23.0% state, p = 0.001), higher rate of attendance at religious services (81.3% vs. 67.2% national, p < 0.001 and 30.0% state, p < 0.001), and higher rate of prayer (65.3% vs. 42.9% national, p < 0.001; no state data available). In unadjusted and adjusted models, prayer is not significantly associated with caregiver depressive symptoms or clinically significant depressive symptomology. Attendance at religious services is associated with depressive symptoms (p = 0.004) with an inversely linear trend (p = 0.002). The significant inverse association between attendance at religious services and depressive symptoms, despite no association between prayer and depressive symptoms, indicates that social or other factors may accompany attendance at religious services and contribute to the association. Clinicians can consider supporting a CFC's attendance at religious services as a potential preventive measure for depressive symptoms. Copyright © 2014 John Wiley & Sons, Ltd.

Nonparametric instrumental regression with non-convex constraints

NASA Astrophysics Data System (ADS)

Grasmair, M.; Scherzer, O.; Vanhems, A.

2013-03-01

This paper considers the nonparametric regression model with an additive error that is dependent on the explanatory variables. As is common in empirical studies in epidemiology and economics, it also supposes that valid instrumental variables are observed. A classical example in microeconomics considers the consumer demand function as a function of the price of goods and the income, both variables often considered as endogenous. In this framework, the economic theory also imposes shape restrictions on the demand function, such as integrability conditions. Motivated by this illustration in microeconomics, we study an estimator of a nonparametric constrained regression function using instrumental variables by means of Tikhonov regularization. We derive rates of convergence for the regularized model both in a deterministic and stochastic setting under the assumption that the true regression function satisfies a projected source condition including, because of the non-convexity of the imposed constraints, an additional smallness condition.

The role of climate and socioeconomic factors on the spatiotemporal variability of cholera in Nigeria

NASA Astrophysics Data System (ADS)

Abdussalam, Auwal; Thornes, John; Leckebusch, Gregor

2015-04-01

Nigeria has a number of climate-sensitive infectious diseases; one of the most important of these diseases that remains a threat to public health is cholera. This study investigates the influences of both meteorological and socioeconomic factors on the spatiotemporal variability of cholera in Nigeria. A stepwise multiple regression models are used to estimate the influence of the year-to-year variations of cholera cases and deaths for individual states in the country and as well for three groups of states that are classified based on annual rainfall amount. Specifically, seasonal mean maximum and minimum temperatures and annual rainfall totals were analysed with annual aggregate count of cholera cases and deaths, taking into account of the socioeconomic factors that are potentially enhancing vulnerability such as: absolute poverty, adult literacy, access to pipe borne water and population density. Result reveals that the most important explanatory meteorological and socioeconomic variables in explaining the spatiotemporal variability of the disease are rainfall totals, seasonal mean maximum temperature, absolute poverty, and accessibility to pipe borne water. The influences of socioeconomic factors appeared to be more pronounced in the northern part of the country, and vice-versa in the case of meteorological factors. Also, cross validated models output suggests a strong possibility of disease prediction, which will help authorities to put effective control measures in place which depend on prevention, and or efficient response.

Reproductive practices by patterns of marriage among Iranian women: study protocol for an explanatory sequential mixed methods design.

PubMed

Taghizadeh, Ziba; Vedadhir, Abouali; Behmanesh, Fereshteh; Ebadi, Abbas; Pourreza, Abulghasem; Abbasi-Shavazi, Mohammad Jalal

2015-09-18

Nowadays, nearly half of the world population lives in societies with low fertility or the below-replacement fertility. This potentially grounds the critical situation of reduction in the workforce and causes the aging of population due to an overall increase in life expectancy and standard of living. Hence, population and its transitions including the issue of fertility decline has become a topic of intense debate in the agenda-setting and policy-making processes in both the developed and developing countries. In this view, what can practically be done to respond to the fertility decline that entails effectively addressing the determinants of fertility change? In line with the literature, how people form their marriages or patterns of marriage is amongst influencing factors which potentially affect their reproductive practices as diverse societies recognize different conventions for marriage. This study is to examine women's reproductive practices by the various patterns of marriage using the explanatory sequential mixed methods design. This study has an explanatory sequential mixed methods design, the follow-up explanations variant model, with two strands. This design will be implemented in two distinct phases. In the first phase, a cross-sectional quantitative study will be done using a cluster sampling strategy on 850 married women 15-49 years old living in Babol city, Iran. In order to obtain a deeper understanding of the results of the quantitative phase, researchers will implement a qualitative research in the second phase of this study. This design will provide an explanation of the quantitative research results using the qualitative evidence. As patterns of marriage have implications for the status of women, their health and fertility, the result of this study can provide a rich source of information for the required health-related interventions and policies are required to put the demographic changes on the right track at micro and macro level and improve

Impact of managed care on physicians' decisions to manipulate reimbursement rules: an explanatory model.

PubMed

VanGeest, Jonathan; Weiner, Saul; Johnson, Timothy; Cummins, Deborah

2007-07-01

To develop and test an explanatory model of the impact of managed care on physicians' decisions to manipulate reimbursement rules for patients. A self-administered mailed questionnaire of a national random sample of 1124 practicing physicians in the USA. Structural equation modelling was used. The main outcome measure assessed whether or not physicians had manipulated reimbursement rules (such as exaggerated the severity of patients conditions, changed billing diagnoses, or reported signs or symptoms that the patients did not have) to help patients secure coverage for needed treatment or services. The response rate was 64% (n = 720). Physicians' decisions to manipulate reimbursement rules for patients are directly driven not only by ethical beliefs about gaming the system but also by requests from patients, the perception of insufficient time to deliver care, and the proportion of Medicaid patients. Covert advocacy is also the indirect result of utilization review hassles, primary care specialty, and practice environment. Managed care is not just a set of rules that physicians choose to follow or disobey, but an environment of competing pressures from patients, purchasers, and high workload. Reimbursement manipulation is a response to that environment, rather than simply a reflection of individual physicians' values.

An Explanatory Model of Poverty from the Perspective of Social Psychology and Human Rights.

PubMed

Pérez-Muñoz, Alfonso; Chacón, Fernando; Martínez Arias, Rosario

2015-12-09

Poverty is a social problem, entailing not only an economical perspective but above all a human and social issue. Poverty is promoted, justified and maintained by unique individuals and groups by means of our own attitudes, interests and behavior, as well as with our social structures and social relationships. From this interactive, psychosocial and sociostructural perspective, and also considering poverty as a denial of basic human rights (UNDP, 1998), we carried out a study with the primary objective to design and verify an Explanatory Model of Poverty. This research may helps to increase the validity of diagnostics and the effectiveness of interventions. Most of the hypotheses were accepted during the analysis and verification of the Model (p < .001), with data fitting the Model (CFI: 1 RMSEA: .025: LO90: 0 - HI90: .061. RMR: .008). These results, if replicated in new investigations, could have the following implications: (a) the need for a broad and comprehensive definition of poverty including its effects, processes and causes; (b) the need for everybody to accept the social responsibility in the prevention and solution to poverty; and (c) the need to conduct longitudinal interventions with scientific methodology and social participation.

An explanatory heuristic gives rise to the belief that words are well suited for their referents.

PubMed

Sutherland, Shelbie L; Cimpian, Andrei

2015-10-01

The mappings between the words of a language and their meanings are arbitrary. There is, for example, nothing inherently dog-like about the word dog. And yet, building on prior evidence (e.g., Brook, 1970; Piaget, 1967), the six studies reported here (N=1062) suggest that both children and (at least to some extent) adults see a special "fit" between objects and their names, as if names were particularly suitable or appropriate for the objects they denote. These studies also provide evidence for a novel proposal concerning the source of these nominal fit beliefs. Specifically, beliefs about nominal fit may be a byproduct of the heuristic processes that people use to make sense of the world more generally (Cimpian & Salomon, 2014a). In sum, the present studies provide new insights into how people conceive of language and demonstrate that these conceptions are rooted in the processes that underlie broader explanatory reasoning. Copyright © 2015 Elsevier B.V. All rights reserved.

Pro-anorexia, weight-loss drugs and the internet: an "anti-recovery" explanatory model of anorexia.

PubMed

Fox, Nick; Ward, Katie; O'Rourke, Alan

2005-11-01

This paper explores the online "pro-anorexia" underground, a movement that supports those with anorexia and adopts an "anti-recovery" perspective on the disease. While encouraging a "healthy" diet to sustain an anorexic way-of-life, the movement also recommends the radical use of weight-loss pharmaceuticals to pursue and maintain low body weight, in contrast to their conventional use to treat obesity. Using ethnographic and interview data collected from participants in the "Anagrrl" website and online forum, we analyse the pro-anorexia (or "pro-ana") movement in terms of its underlying "explanatory model" of the disease, and contrast it with medical, psychosocial, sociocultural and feminist models that encourage a "normalisation" of body shape and weight. We suggest that for participants in pro-ana, anorexia represents stability and control, and Anagrrl offers support and guidance for those who wish to remain in this "sanctuary". We discuss the pro-anorexia movement's use of the internet to facilitate resistance to medical and social theories of disease, and its subversion of pharmaceutical technologies.

Spatial analysis of participation in the Waterloo Residential Energy Efficiency Project

NASA Astrophysics Data System (ADS)

Song, Ge Bella

Researchers are in broad agreement that energy-conserving actions produce economic as well as energy savings. Household energy rating systems (HERS) have been established in many countries to inform households of their house's current energy performance and to help reduce their energy consumption and greenhouse gas emissions. In Canada, the national EnerGuide for Houses (EGH) program is delivered by many local delivery agents, including non-profit green community organizations. Waterloo Region Green Solutions is the local non-profit that offers the EGH residential energy evaluation service to local households. The purpose of this thesis is to explore the determinants of household's participation in the residential energy efficiency program (REEP) in Waterloo Region, to explain the relationship between the explanatory variables and REEP participation, and to propose ways to improve this kind of program. A spatial (trend) analysis was conducted within a geographic information system (GIS) to determine the spatial patterns of the REEP participation in Waterloo Region from 1999 to 2006. The impact of sources of information on participation and relationships between participation rates and explanatory variables were identified. GIS proved successful in presenting a visual interpretation of spatial patterns of the REEP participation. In general, the participating households tend to be clustered in urban areas and scattered in rural areas. Different sources of information played significant roles in reaching participants in different years. Moreover, there was a relationship between each explanatory variable and the REEP participation rates. Statistical analysis was applied to obtain a quantitative assessment of relationships between hypothesized explanatory variables and participation in the REEP. The Poisson regression model was used to determine the relationship between hypothesized explanatory variables and REEP participation at the CDA level. The results show that

Using Indirect Turbulence Measurements for Real-Time Parameter Estimation in Turbulent Air

NASA Technical Reports Server (NTRS)

Martos, Borja; Morelli, Eugene A.

2012-01-01

The use of indirect turbulence measurements for real-time estimation of parameters in a linear longitudinal dynamics model in atmospheric turbulence was studied. It is shown that measuring the atmospheric turbulence makes it possible to treat the turbulence as a measured explanatory variable in the parameter estimation problem. Commercial off-the-shelf sensors were researched and evaluated, then compared to air data booms. Sources of colored noise in the explanatory variables resulting from typical turbulence measurement techniques were identified and studied. A major source of colored noise in the explanatory variables was identified as frequency dependent upwash and time delay. The resulting upwash and time delay corrections were analyzed and compared to previous time shift dynamic modeling research. Simulation data as well as flight test data in atmospheric turbulence were used to verify the time delay behavior. Recommendations are given for follow on flight research and instrumentation.

Analysing Relationships Between Urban Land Use Fragmentation Metrics and Socio-Economic Variables

NASA Astrophysics Data System (ADS)

Sapena, M.; Ruiz, L. A.; Goerlich, F. J.

2016-06-01

Analysing urban regions is essential for their correct monitoring and planning. This is mainly accounted for the sharp increase of people living in urban areas, and consequently, the need to manage them. At the same time there has been a rise in the use of spatial and statistical datasets, such as the Urban Atlas, which offers high-resolution urban land use maps obtained from satellite imagery, and the Urban Audit, which provides statistics of European cities and their surroundings. In this study, we analyse the relations between urban fragmentation metrics derived from Land Use and Land Cover (LULC) data from the Urban Atlas dataset, and socio-economic data from the Urban Audit for the reference years 2006 and 2012. We conducted the analysis on a sample of sixty-eight Functional Urban Areas (FUAs). One-date and two-date based fragmentation indices were computed for each FUA, land use class and date. Correlation tests and principal component analysis were then applied to select the most representative indices. Finally, multiple regression models were tested to explore the prediction of socio-economic variables, using different combinations of land use metrics as explanatory variables, both at a given date and in a dynamic context. The outcomes show that demography, living conditions, labour, and transportation variables have a clear relation with the morphology of the FUAs. This methodology allows us to compare European FUAs in terms of the spatial distribution of the land use classes, their complexity, and their structural changes, as well as to preview and model different growth patterns and socio-economic indicators.

Dose-Response Calculator for ArcGIS

USGS Publications Warehouse

Hanser, Steven E.; Aldridge, Cameron L.; Leu, Matthias; Nielsen, Scott E.

2011-01-01

The Dose-Response Calculator for ArcGIS is a tool that extends the Environmental Systems Research Institute (ESRI) ArcGIS 10 Desktop application to aid with the visualization of relationships between two raster GIS datasets. A dose-response curve is a line graph commonly used in medical research to examine the effects of different dosage rates of a drug or chemical (for example, carcinogen) on an outcome of interest (for example, cell mutations) (Russell and others, 1982). Dose-response curves have recently been used in ecological studies to examine the influence of an explanatory dose variable (for example, percentage of habitat cover, distance to disturbance) on a predicted response (for example, survival, probability of occurrence, abundance) (Aldridge and others, 2008). These dose curves have been created by calculating the predicted response value from a statistical model at different levels of the explanatory dose variable while holding values of other explanatory variables constant. Curves (plots) developed using the Dose-Response Calculator overcome the need to hold variables constant by using values extracted from the predicted response surface of a spatially explicit statistical model fit in a GIS, which include the variation of all explanatory variables, to visualize the univariate response to the dose variable. Application of the Dose-Response Calculator can be extended beyond the assessment of statistical model predictions and may be used to visualize the relationship between any two raster GIS datasets (see example in tool instructions). This tool generates tabular data for use in further exploration of dose-response relationships and a graph of the dose-response curve.

Thwarted Belongingness as an Explanatory Link between Insomnia Symptoms and Suicidal Ideation: Findings from Three Samples of Military Service Members and Veterans

PubMed Central

Hom, Melanie A.; Chu, Carol; Schneider, Matthew E.; Lim, Ingrid C.; Hirsch, Jameson K.; Gutierrez, Peter M.; Joiner, Thomas E.

2017-01-01

Background Although insomnia has been identified as a robust predictor of suicidal ideation and behaviors, little is known about the mechanisms by which sleep disturbances confer risk for suicide. We investigated thwarted belongingness as an explanatory link between insomnia symptoms and suicidal ideation across three military service member and veteran samples. Methods Data were collected among United States military service members and veterans (N1=937, N2=3,386, N3=417) who completed self-report measures of insomnia symptoms, thwarted belongingness, suicidal ideation, and related psychiatric symptoms (e.g., anxiety, hopelessness). Bias-corrected bootstrap mediation analyses were utilized to examine the indirect effects of insomnia symptoms on suicidal ideation through thwarted belongingness, controlling for related psychiatric symptoms. Results Consistent with study hypotheses, thwarted belongingness significantly accounted for the relationship between insomnia and suicidal ideation across all three samples; however, insomnia symptoms did not significantly account for the relationship between thwarted belongingness and suicidal ideation, highlighting the specificity of our findings. Limitations This study utilized cross-sectional, self-report data. Conclusions Insomnia may confer suicide risk for military service members and veterans, in part, through the pathway of thwarted belongingness. Additional prospective studies are warranted to further delineate this model of risk. Our results offer a potential target for the therapeutic prevention of suicide, via the promotion of belongingness, among service members and veterans experiencing insomnia symptoms. PMID:27898373

Contribution of LFP dynamics to single-neuron spiking variability in motor cortex during movement execution

PubMed Central

Rule, Michael E.; Vargas-Irwin, Carlos; Donoghue, John P.; Truccolo, Wilson

2015-01-01

Understanding the sources of variability in single-neuron spiking responses is an important open problem for the theory of neural coding. This variability is thought to result primarily from spontaneous collective dynamics in neuronal networks. Here, we investigate how well collective dynamics reflected in motor cortex local field potentials (LFPs) can account for spiking variability during motor behavior. Neural activity was recorded via microelectrode arrays implanted in ventral and dorsal premotor and primary motor cortices of non-human primates performing naturalistic 3-D reaching and grasping actions. Point process models were used to quantify how well LFP features accounted for spiking variability not explained by the measured 3-D reach and grasp kinematics. LFP features included the instantaneous magnitude, phase and analytic-signal components of narrow band-pass filtered (δ,θ,α,β) LFPs, and analytic signal and amplitude envelope features in higher-frequency bands. Multiband LFP features predicted single-neuron spiking (1ms resolution) with substantial accuracy as assessed via ROC analysis. Notably, however, models including both LFP and kinematics features displayed marginal improvement over kinematics-only models. Furthermore, the small predictive information added by LFP features to kinematic models was redundant to information available in fast-timescale (<100 ms) spiking history. Overall, information in multiband LFP features, although predictive of single-neuron spiking during movement execution, was redundant to information available in movement parameters and spiking history. Our findings suggest that, during movement execution, collective dynamics reflected in motor cortex LFPs primarily relate to sensorimotor processes directly controlling movement output, adding little explanatory power to variability not accounted by movement parameters. PMID:26157365

Canonical Commonality Analysis.

ERIC Educational Resources Information Center

Leister, K. Dawn

Commonality analysis is a method of partitioning variance that has advantages over more traditional "OVA" methods. Commonality analysis indicates the amount of explanatory power that is "unique" to a given predictor variable and the amount of explanatory power that is "common" to or shared with at least one predictor…

Antarctic Meteorite Location and Mapping Project (AMLAMP): Antarctic meteorite location map series explanatory text and user's guide to AMLAMP data

NASA Technical Reports Server (NTRS)

Schutt, J.; Fessler, B.; Cassidy, W. A.

1993-01-01

This technical report is an update to LPI Technical Report 89-02, which contained data and information that was current to May 1987. Since that time approximately 4000 new meteorites have been collected, mapped, and characterized, mainly from the numerous ice fields in the Allan Hills-David Glacier region, from the Pecora Escarpment and Moulton Escarpment in the Thiel Mountains-Patuxent region, the Wisconsin Range region, and from the Beardmore region. Meteorite location maps for ice fields from these regions have been produced and are available. This report includes explanatory texts for the maps of new areas and provides information on updates of maps of the areas covered in LPI Technical Report 89-02. Sketch maps and description of locales that have been searched and have yielded single or few meteorites are also included. The meteorite listings for all the ice fields have been updated to include any classification changes and new meteorites recovered from ice fields in the Allan Hills-David Glacier region since 1987. The text has been reorganized and minor errors in the original report have been corrected. Computing capabilities have improved immensely since the early days of this project. Current software and hardware allow easy access to data over computer networks. With various commercial software packages, the data can be used many different ways, including database creation, statistics, and mapping. The databases, explanatory texts, and the plotter files used to produce the meteorite location maps are available through a computer network. Information on how to access AMLAMP data, its formats, and ways it can be used are given in the User's Guide to AMLAMP Data section. Meteorite location maps and thematic maps may be ordered from the Lunar and Planetary Institute. Ordering information is given in Appendix A.

Additional Samples: Where They Should Be Located

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

Pilger, G. G., E-mail: jfelipe@ufrgs.br; Costa, J. F. C. L.; Koppe, J. C.

2001-09-15

Information for mine planning requires to be close spaced, if compared to the grid used for exploration and resource assessment. The additional samples collected during quasimining usually are located in the same pattern of the original diamond drillholes net but closer spaced. This procedure is not the best in mathematical sense for selecting a location. The impact of an additional information to reduce the uncertainty about the parameter been modeled is not the same everywhere within the deposit. Some locations are more sensitive in reducing the local and global uncertainty than others. This study introduces a methodology to select additionalmore » sample locations based on stochastic simulation. The procedure takes into account data variability and their spatial location. Multiple equally probable models representing a geological attribute are generated via geostatistical simulation. These models share basically the same histogram and the same variogram obtained from the original data set. At each block belonging to the model a value is obtained from the n simulations and their combination allows one to access local variability. Variability is measured using an uncertainty index proposed. This index was used to map zones of high variability. A value extracted from a given simulation is added to the original data set from a zone identified as erratic in the previous maps. The process of adding samples and simulation is repeated and the benefit of the additional sample is evaluated. The benefit in terms of uncertainty reduction is measure locally and globally. The procedure showed to be robust and theoretically sound, mapping zones where the additional information is most beneficial. A case study in a coal mine using coal seam thickness illustrates the method.« less

Research of Water Level Prediction for a Continuous Flood due to Typhoons Based on a Machine Learning Method

NASA Astrophysics Data System (ADS)

Nakatsugawa, M.; Kobayashi, Y.; Okazaki, R.; Taniguchi, Y.

2017-12-01

This research aims to improve accuracy of water level prediction calculations for more effective river management. In August 2016, Hokkaido was visited by four typhoons, whose heavy rainfall caused severe flooding. In the Tokoro river basin of Eastern Hokkaido, the water level (WL) at the Kamikawazoe gauging station, which is at the lower reaches exceeded the design high-water level and the water rose to the highest level on record. To predict such flood conditions and mitigate disaster damage, it is necessary to improve the accuracy of prediction as well as to prolong the lead time (LT) required for disaster mitigation measures such as flood-fighting activities and evacuation actions by residents. There is the need to predict the river water level around the peak stage earlier and more accurately. Previous research dealing with WL prediction had proposed a method in which the WL at the lower reaches is estimated by the correlation with the WL at the upper reaches (hereinafter: "the water level correlation method"). Additionally, a runoff model-based method has been generally used in which the discharge is estimated by giving rainfall prediction data to a runoff model such as a storage function model and then the WL is estimated from that discharge by using a WL discharge rating curve (H-Q curve). In this research, an attempt was made to predict WL by applying the Random Forest (RF) method, which is a machine learning method that can estimate the contribution of explanatory variables. Furthermore, from the practical point of view, we investigated the prediction of WL based on a multiple correlation (MC) method involving factors using explanatory variables with high contribution in the RF method, and we examined the proper selection of explanatory variables and the extension of LT. The following results were found: 1) Based on the RF method tuned up by learning from previous floods, the WL for the abnormal flood case of August 2016 was properly predicted with a lead

An Update on Statistical Boosting in Biomedicine.

PubMed

Mayr, Andreas; Hofner, Benjamin; Waldmann, Elisabeth; Hepp, Tobias; Meyer, Sebastian; Gefeller, Olaf

2017-01-01

Statistical boosting algorithms have triggered a lot of research during the last decade. They combine a powerful machine learning approach with classical statistical modelling, offering various practical advantages like automated variable selection and implicit regularization of effect estimates. They are extremely flexible, as the underlying base-learners (regression functions defining the type of effect for the explanatory variables) can be combined with any kind of loss function (target function to be optimized, defining the type of regression setting). In this review article, we highlight the most recent methodological developments on statistical boosting regarding variable selection, functional regression, and advanced time-to-event modelling. Additionally, we provide a short overview on relevant applications of statistical boosting in biomedicine.

An outline of graphical Markov models in dentistry.

PubMed

Helfenstein, U; Steiner, M; Menghini, G

1999-12-01

In the usual multiple regression model there is one response variable and one block of several explanatory variables. In contrast, in reality there may be a block of several possibly interacting response variables one would like to explain. In addition, the explanatory variables may split into a sequence of several blocks, each block containing several interacting variables. The variables in the second block are explained by those in the first block; the variables in the third block by those in the first and the second block etc. During recent years methods have been developed allowing analysis of problems where the data set has the above complex structure. The models involved are called graphical models or graphical Markov models. The main result of an analysis is a picture, a conditional independence graph with precise statistical meaning, consisting of circles representing variables and lines or arrows representing significant conditional associations. The absence of a line between two circles signifies that the corresponding two variables are independent conditional on the presence of other variables in the model. An example from epidemiology is presented in order to demonstrate application and use of the models. The data set in the example has a complex structure consisting of successive blocks: the variable in the first block is year of investigation; the variables in the second block are age and gender; the variables in the third block are indices of calculus, gingivitis and mutans streptococci and the final response variables in the fourth block are different indices of caries. Since the statistical methods may not be easily accessible to dentists, this article presents them in an introductory form. Graphical models may be of great value to dentists in allowing analysis and visualisation of complex structured multivariate data sets consisting of a sequence of blocks of interacting variables and, in particular, several possibly interacting responses in the

Continuous-variable quantum homomorphic signature

NASA Astrophysics Data System (ADS)

Li, Ke; Shang, Tao; Liu, Jian-wei

2017-10-01

Quantum cryptography is believed to be unconditionally secure because its security is ensured by physical laws rather than computational complexity. According to spectrum characteristic, quantum information can be classified into two categories, namely discrete variables and continuous variables. Continuous-variable quantum protocols have gained much attention for their ability to transmit more information with lower cost. To verify the identities of different data sources in a quantum network, we propose a continuous-variable quantum homomorphic signature scheme. It is based on continuous-variable entanglement swapping and provides additive and subtractive homomorphism. Security analysis shows the proposed scheme is secure against replay, forgery and repudiation. Even under nonideal conditions, it supports effective verification within a certain verification threshold.

Operator’s Manual for Variable Weight, Variable C. G. Helmet Simulator,

DTIC Science & Technology

1981-09-01

A variabh weight, variable CG helmet simulator has been designed to measure the effect of US Army headgear on muscle loading and fatigue. The helmet...less than the weight of most quality crash helmets made by reputable manufacturers. The addition of variable weights to the boxes can alter the center...of gravity to simulate the effect of equipment attached to the out- side of a helmet. The helmet simulator has been calibrated for weights of 3.2, 4.0

The role of environmental variables in structuring landscape-scale species distributions in seafloor habitats.

PubMed

Kraan, Casper; Aarts, Geert; Van der Meer, Jaap; Piersma, Theunis

2010-06-01

Ongoing statistical sophistication allows a shift from describing species' spatial distributions toward statistically disentangling the possible roles of environmental variables in shaping species distributions. Based on a landscape-scale benthic survey in the Dutch Wadden Sea, we show the merits of spatially explicit generalized estimating equations (GEE). The intertidal macrozoobenthic species, Macoma balthica, Cerastoderma edule, Marenzelleria viridis, Scoloplos armiger, Corophium volutator, and Urothoe poseidonis served as test cases, with median grain-size and inundation time as typical environmental explanatory variables. GEEs outperformed spatially naive generalized linear models (GLMs), and removed much residual spatial structure, indicating the importance of median grain-size and inundation time in shaping landscape-scale species distributions in the intertidal. GEE regression coefficients were smaller than those attained with GLM, and GEE standard errors were larger. The best fitting GEE for each species was used to predict species' density in relation to median grain-size and inundation time. Although no drastic changes were noted compared to previous work that described habitat suitability for benthic fauna in the Wadden Sea, our predictions provided more detailed and unbiased estimates of the determinants of species-environment relationships. We conclude that spatial GEEs offer the necessary methodological advances to further steps toward linking pattern to process.

Multiple causes of nonstationarity in the Weihe annual low-flow series

NASA Astrophysics Data System (ADS)

Xiong, Bin; Xiong, Lihua; Chen, Jie; Xu, Chong-Yu; Li, Lingqi

2018-02-01

Under the background of global climate change and local anthropogenic activities, multiple driving forces have introduced various nonstationary components into low-flow series. This has led to a high demand on low-flow frequency analysis that considers nonstationary conditions for modeling. In this study, through a nonstationary frequency analysis framework with the generalized linear model (GLM) to consider time-varying distribution parameters, the multiple explanatory variables were incorporated to explain the variation in low-flow distribution parameters. These variables are comprised of the three indices of human activities (HAs; i.e., population, POP; irrigation area, IAR; and gross domestic product, GDP) and the eight measuring indices of the climate and catchment conditions (i.e., total precipitation P, mean frequency of precipitation events λ, temperature T, potential evapotranspiration (EP), climate aridity index AIEP, base-flow index (BFI), recession constant K and the recession-related aridity index AIK). This framework was applied to model the annual minimum flow series of both Huaxian and Xianyang gauging stations in the Weihe River, China (also known as the Wei He River). The results from stepwise regression for the optimal explanatory variables show that the variables related to irrigation, recession, temperature and precipitation play an important role in modeling. Specifically, analysis of annual minimum 30-day flow in Huaxian shows that the nonstationary distribution model with any one of all explanatory variables is better than the one without explanatory variables, the nonstationary gamma distribution model with four optimal variables is the best model and AIK is of the highest relative importance among these four variables, followed by IAR, BFI and AIEP. We conclude that the incorporation of multiple indices related to low-flow generation permits tracing various driving forces. The established link in nonstationary analysis will be beneficial

Efficacy of generic allometric equations for estimating biomass: a test in Japanese natural forests.

PubMed

Ishihara, Masae I; Utsugi, Hajime; Tanouchi, Hiroyuki; Aiba, Masahiro; Kurokawa, Hiroko; Onoda, Yusuke; Nagano, Masahiro; Umehara, Toru; Ando, Makoto; Miyata, Rie; Hiura, Tsutom

2015-07-01

Accurate estimation of tree and forest biomass is key to evaluating forest ecosystem functions and the global carbon cycle. Allometric equations that estimate tree biomass from a set of predictors, such as stem diameter and tree height, are commonly used. Most allometric equations are site specific, usually developed from a small number of trees harvested in a small area, and are either species specific or ignore interspecific differences in allometry. Due to lack of site-specific allometries, local equations are often applied to sites for which they were not originally developed (foreign sites), sometimes leading to large errors in biomass estimates. In this study, we developed generic allometric equations for aboveground biomass and component (stem, branch, leaf, and root) biomass using large, compiled data sets of 1203 harvested trees belonging to 102 species (60 deciduous angiosperm, 32 evergreen angiosperm, and 10 evergreen gymnosperm species) from 70 boreal, temperate, and subtropical natural forests in Japan. The best generic equations provided better biomass estimates than did local equations that were applied to foreign sites. The best generic equations included explanatory variables that represent interspecific differences in allometry in addition to stem diameter, reducing error by 4-12% compared to the generic equations that did not include the interspecific difference. Different explanatory variables were selected for different components. For aboveground and stem biomass, the best generic equations had species-specific wood specific gravity as an explanatory variable. For branch, leaf, and root biomass, the best equations had functional types (deciduous angiosperm, evergreen angiosperm, and evergreen gymnosperm) instead of functional traits (wood specific gravity or leaf mass per area), suggesting importance of other traits in addition to these traits, such as canopy and root architecture. Inclusion of tree height in addition to stem diameter improved

Improved algorithms for estimating Total Alkalinity in Northern Gulf of Mexico

NASA Astrophysics Data System (ADS)

Devkota, M.; Dash, P.

2017-12-01

Ocean Acidification (OA) is one of the serious challenges that have significant impacts on ocean. About 25% of anthropologically generated CO2 is absorbed by the oceans which decreases average ocean pH. This change has critical impacts on marine species, ocean ecology, and associated economics. 35 years of observation concluded that the rate of alteration in OA parameters varies geographically with higher variations in the northern Gulf of Mexico (N-GoM). Several studies have suggested that the Mississippi River affects the carbon dynamics of the N-GoM coastal ecosystem significantly. Total Alkalinity (TA) algorithms developed for major ocean basins produce inaccurate estimations in this region. Hence, a local algorithm to estimate TA is the need for this region, which would incorporate the local effects of oceanographic processes and complex spatial influences. In situ data collected in N-GoM region during the GOMECC-I and II cruises, and GISR Cruises (G-1, 3, 5) from 2007 to 2013 were assimilated and used to calculate the efficiency of the existing TA algorithm that uses Sea Surface Temperature (SST) and Sea Surface Salinity (SSS) as explanatory variables. To improve this algorithm, firstly, statistical analyses were performed to improve the coefficients and the functional form of this algorithm. Then, chlorophyll a (Chl-a) was included as an additional explanatory variable in the multiple linear regression approach in addition to SST and SSS. Based on the average concentration of Chl-a for last 15 years, the N-GoM was divided into two regions, and two separate algorithms were developed for each region. Finally, to address spatial non-stationarity, a Geographically Weighted Regression (GWR) algorithm was developed. The existing TA algorithm resulted considerable algorithm bias with a larger bias in the coastal waters. Chl-a as an additional explanatory variable reduced the bias in the residuals and improved the algorithm efficiency. Chl-a worked as a proxy for

Lexicography and Mathematics Learning: A Case Study of "Variable."

ERIC Educational Resources Information Center

Frawley, William

1992-01-01

Lexicography is shown to offer some useful new tools to researchers in mathematics education. The paper examines the relationship between the sublanguage of mathematics and the acquisition of mathematical knowledge, and also the use of definitions in research and curriculum design. An Explanatory Combinatorial Dictionary is advocated for improving…

A Middle-Range Explanatory Theory of Self-Management Behavior for Collaborative Research and Practice.

PubMed

Blok, Amanda C

2017-04-01

To report an analysis of the concept of self-management behaviors. Self-management behaviors are typically associated with disease management, with frequent use by nurse researchers related to chronic illness management and by international health organizations for development of disease management interventions. A concept analysis was conducted within the context of Orem's self-care framework. Walker and Avant's eight-step concept analysis approach guided the analysis. Academic databases were searched for relevant literature including CIHAHL, Cochrane Databases of Systematic Reviews and Register of Controlled Trials, MEDLINE, PsycARTICLES and PsycINFO, and SocINDEX. Literature using the term "self-management behavior" and published between April 2001 and March 2015 was analyzed for attributes, antecedents, and consequences. A total of 189 journal articles were reviewed. Self-management behaviors are defined as proactive actions related to lifestyle, a problem, planning, collaborating, and mental support, as well as reactive actions related to a circumstantial change, to achieve a goal influenced by the antecedents of physical, psychological, socioeconomic, and cultural characteristics, as well as collaborative and received support. The theoretical definition and middle-range explanatory theory of self-management behaviors will guide future collaborative research and clinical practice for disease management. © 2016 Wiley Periodicals, Inc.

14 CFR 25.1533 - Additional operating limitations.

Code of Federal Regulations, 2010 CFR

2010-01-01

... and wet), and runway gradients) for smooth, hard-surfaced runways. Additionally, at the option of the... for variable factors (such as altitude, temperature, wind, and runway gradients) are those at which...

Controlled but not cured: Structural processes and explanatory models of Chagas disease in tropical Bolivia.

PubMed

Forsyth, Colin

2015-11-01

Dressler (2001:456) characterizes medical anthropology as divided between two poles: the constructivist, which focuses on the "meaning and significance that events have for people," and the structuralist, which emphasizes socioeconomic processes and relationships. This study synthesizes structuralist and constructivist perspectives by investigating how structural processes impact explanatory models of Chagas disease in a highly endemic area. The research took place from March-June 2013 through the Centro Medico Humberto Parra, a non-profit clinic servicing low income populations in Palacios, Bolivia and surrounding communities. Semistructured interviews (n = 68) and consensus analysis questionnaires (n = 48) were administered to people dealing with Chagas disease. In the interview narratives, respondents link Chagas disease with experiences of marginalization and rural poverty, and describe multilayered impediments to accessing treatment. They often view the disease as incurable, but this reflects inconsistent messages from the biomedical system. The consensus analysis results show strong agreement on knowledge of the vector, ethnomedical treatment, and structural factors related to Chagas disease. In interpreting Chagas disease, respondents account for the structural factors which place them at risk and impede access to care. Copyright © 2015 Elsevier Ltd. All rights reserved.

Dopaminergic modulation of hemodynamic signal variability and the functional connectome during cognitive performance.

PubMed

Alavash, Mohsen; Lim, Sung-Joo; Thiel, Christiane; Sehm, Bernhard; Deserno, Lorenz; Obleser, Jonas

2018-05-15

Dopamine underlies important aspects of cognition, and has been suggested to boost cognitive performance. However, how dopamine modulates the large-scale cortical dynamics during cognitive performance has remained elusive. Using functional MRI during a working memory task in healthy young human listeners, we investigated the effect of levodopa (l-dopa) on two aspects of cortical dynamics, blood oxygen-level-dependent (BOLD) signal variability and the functional connectome of large-scale cortical networks. We here show that enhanced dopaminergic signaling modulates the two potentially interrelated aspects of large-scale cortical dynamics during cognitive performance, and the degree of these modulations is able to explain inter-individual differences in l-dopa-induced behavioral benefits. Relative to placebo, l-dopa increased BOLD signal variability in task-relevant temporal, inferior frontal, parietal and cingulate regions. On the connectome level, however, l-dopa diminished functional integration across temporal and cingulo-opercular regions. This hypo-integration was expressed as a reduction in network efficiency and modularity in more than two thirds of the participants and to different degrees. Hypo-integration co-occurred with relative hyper-connectivity in paracentral lobule and precuneus, as well as posterior putamen. Both, l-dopa-induced BOLD signal variability modulation and functional connectome modulations proved predictive of an individual's l-dopa-induced benefits in behavioral performance, namely response speed and perceptual sensitivity. Lastly, l-dopa-induced modulations of BOLD signal variability were correlated with l-dopa-induced modulation of nodal connectivity and network efficiency. Our findings underline the role of dopamine in maintaining the dynamic range of, and communication between, cortical systems, and their explanatory power for inter-individual differences in benefits from dopamine during cognitive performance. Copyright © 2018

Statistical summary of selected physical, chemical, and toxicity characteristics and estimates of annual constituent loads in urban stormwater, Maricopa County, Arizona

USGS Publications Warehouse

Fossum, Kenneth D.; O'Day, Christie M.; Wilson, Barbara J.; Monical, Jim E.

2001-01-01

Stormwater and streamflow in Maricopa County were monitored to (1) describe the physical, chemical, and toxicity characteristics of stormwater from areas having different land uses, (2) describe the physical, chemical, and toxicity characteristics of streamflow from areas that receive urban stormwater, and (3) estimate constituent loads in stormwater. Urban stormwater and streamflow had similar ranges in most constituent concentrations. The mean concentration of dissolved solids in urban stormwater was lower than in streamflow from the Salt River and Indian Bend Wash. Urban stormwater, however, had a greater chemical oxygen demand and higher concentrations of most nutrients. Mean seasonal loads and mean annual loads of 11 constituents and volumes of runoff were estimated for municipalities in the metropolitan Phoenix area, Arizona, by adjusting regional regression equations of loads. This adjustment procedure uses the original regional regression equation and additional explanatory variables that were not included in the original equation. The adjusted equations had standard errors that ranged from 161 to 196 percent. The large standard errors of the prediction result from the large variability of the constituent concentration data used in the regression analysis. Adjustment procedures produced unsatisfactory results for nine of the regressions?suspended solids, dissolved solids, total phosphorus, dissolved phosphorus, total recoverable cadmium, total recoverable copper, total recoverable lead, total recoverable zinc, and storm runoff. These equations had no consistent direction of bias and no other additional explanatory variables correlated with the observed loads. A stepwise-multiple regression or a three-variable regression (total storm rainfall, drainage area, and impervious area) and local data were used to develop local regression equations for these nine constituents. These equations had standard errors from 15 to 183 percent.

Logistic regression modeling to assess groundwater vulnerability to contamination in Hawaii, USA.

PubMed

Mair, Alan; El-Kadi, Aly I

2013-10-01

Capture zone analysis combined with a subjective susceptibility index is currently used in Hawaii to assess vulnerability to contamination of drinking water sources derived from groundwater. In this study, we developed an alternative objective approach that combines well capture zones with multiple-variable logistic regression (LR) modeling and applied it to the highly-utilized Pearl Harbor and Honolulu aquifers on the island of Oahu, Hawaii. Input for the LR models utilized explanatory variables based on hydrogeology, land use, and well geometry/location. A suite of 11 target contaminants detected in the region, including elevated nitrate (>1 mg/L), four chlorinated solvents, four agricultural fumigants, and two pesticides, was used to develop the models. We then tested the ability of the new approach to accurately separate groups of wells with low and high vulnerability, and the suitability of nitrate as an indicator of other types of contamination. Our results produced contaminant-specific LR models that accurately identified groups of wells with the lowest/highest reported detections and the lowest/highest nitrate concentrations. Current and former agricultural land uses were identified as significant explanatory variables for eight of the 11 target contaminants, while elevated nitrate was a significant variable for five contaminants. The utility of the combined approach is contingent on the availability of hydrologic and chemical monitoring data for calibrating groundwater and LR models. Application of the approach using a reference site with sufficient data could help identify key variables in areas with similar hydrogeology and land use but limited data. In addition, elevated nitrate may also be a suitable indicator of groundwater contamination in areas with limited data. The objective LR modeling approach developed in this study is flexible enough to address a wide range of contaminants and represents a suitable addition to the current subjective approach

Logistic regression modeling to assess groundwater vulnerability to contamination in Hawaii, USA

NASA Astrophysics Data System (ADS)

Mair, Alan; El-Kadi, Aly I.

2013-10-01

Capture zone analysis combined with a subjective susceptibility index is currently used in Hawaii to assess vulnerability to contamination of drinking water sources derived from groundwater. In this study, we developed an alternative objective approach that combines well capture zones with multiple-variable logistic regression (LR) modeling and applied it to the highly-utilized Pearl Harbor and Honolulu aquifers on the island of Oahu, Hawaii. Input for the LR models utilized explanatory variables based on hydrogeology, land use, and well geometry/location. A suite of 11 target contaminants detected in the region, including elevated nitrate (> 1 mg/L), four chlorinated solvents, four agricultural fumigants, and two pesticides, was used to develop the models. We then tested the ability of the new approach to accurately separate groups of wells with low and high vulnerability, and the suitability of nitrate as an indicator of other types of contamination. Our results produced contaminant-specific LR models that accurately identified groups of wells with the lowest/highest reported detections and the lowest/highest nitrate concentrations. Current and former agricultural land uses were identified as significant explanatory variables for eight of the 11 target contaminants, while elevated nitrate was a significant variable for five contaminants. The utility of the combined approach is contingent on the availability of hydrologic and chemical monitoring data for calibrating groundwater and LR models. Application of the approach using a reference site with sufficient data could help identify key variables in areas with similar hydrogeology and land use but limited data. In addition, elevated nitrate may also be a suitable indicator of groundwater contamination in areas with limited data. The objective LR modeling approach developed in this study is flexible enough to address a wide range of contaminants and represents a suitable addition to the current subjective approach.

A systematic review of explanatory factors of barriers and facilitators to improving asthma management in South Asian children

PubMed Central

2014-01-01

Background South Asian children with asthma are less likely to receive prescriptions and more likely to suffer uncontrolled symptoms and acute asthma admissions compared with White British children. Understanding barriers are therefore vital in addressing health inequalities. We undertook a systematic review identifying explanatory factors for barriers and facilitators to asthma management in South Asian children. South Asians were defined as individuals of Indian, Pakistani or Bangladeshi descent. Methods Data Sources - Medline, HMIC, EMBASE, ASSIA, Web of Science, BNI, CINAHL, PsycINFO, OpenSIGLE, CRD, Scopus, NHS Evidence, Cochrane Library, Campbell Collaboration, RCPCH, ATS, ERS, Asthma UK, Google Scholar & Asthma Guidelines (BTS, GINA, ATS, Monash, NAEPP, Singapore & New Zealand) to August 2013. Inclusion Criteria – Qualitative, quantitative or mixed methods research with primary focus on identifying explanations for barriers and/or facilitators to asthma management in South Asian children aged 0–18 years with diagnosed/suspected asthma and/or carers and/or healthcare professionals. Data Extraction – Three authors independently reviewed, selected & extracted eligible articles with disagreements resolved by research team discussion. Results 15 studies encompassing 25,755 children, 18,483 parents/carers and 239 healthcare professionals were included. Barriers and explanatory factors identified were: 1. Lack of asthma knowledge in families and healthcare professionals. 2. Under-use of preventer medications. 3. Non-acceptance/denial of asthma. 4. Over-reliance on Emergency Department management. 5. Communication problems. 6. Non-adherence to medication. 7. Use of complementary therapies. Little facilitators regarding asthma management were identified. Conclusions Several key issues were identified as likely to be ethnic-specific to South Asian families, rather than a reflection of minority status: impact of parental and professional knowledge and beliefs

Risky online behaviors among adolescents: Longitudinal relations among problematic Internet use, cyberbullying perpetration, and meeting strangers online.

PubMed

Gámez-Guadix, Manuel; Borrajo, Erika; Almendros, Carmen

2016-03-01

Background and aims This study aims to analyze the cross-sectional and longitudinal relationship between three major risky online behaviors during adolescence: problematic Internet use, cyberbullying perpetration, and meeting strangers online. An additional objective was to study the role of impulsivity-irresponsibility as a possible explanatory variable of the relationships between these risky online behaviors. Methods The study sample was 888 adolescents that completed self-report measures at time 1 and time 2 with an interval of 6 months. Results The findings showed a significant cross-sectional relationship between the risky online behaviors analyzed. At the longitudinal level, problematic Internet use at time 1 predicted an increase in the perpetration of cyberbullying and meeting strangers online at time 2. Furthermore, meeting strangers online increased the likelihood of cyberbullying perpetration at time 2. Finally, when impulsivity-irresponsibility was included in the model as an explanatory variable, the relationships previously found remained significant. Discussion These results extend traditional problem behavior theory during adolescence, also supporting a relationship between different risky behaviors in cyberspace. In addition, findings highlighted the role of problematic Internet use, which increased the chances of developing cyberbullying perpetration and meeting strangers online over time. However, the results suggest a limited role of impulsivity-irresponsibility as an explicative mechanism. Conclusions The findings suggest that various online risk activities ought to be addressed together when planning assessment, prevention and intervention efforts.

Analysis of variables affecting unemployment rate and detecting for cluster in West Java, Central Java, and East Java in 2012

NASA Astrophysics Data System (ADS)

Samuel, Putra A.; Widyaningsih, Yekti; Lestari, Dian

2016-02-01

The objective of this study is modeling the Unemployment Rate (UR) in West Java, Central Java, and East Java, with rate of disease, infant mortality rate, educational level, population size, proportion of married people, and GDRP as the explanatory variables. Spatial factors are also considered in the modeling since the closer the distance, the higher the correlation. This study uses the secondary data from BPS (Badan Pusat Statistik). The data will be analyzed using Moran I test, to obtain the information about spatial dependence, and using Spatial Autoregressive modeling to obtain the information, which variables are significant affecting UR and how great the influence of the spatial factors. The result is, variables proportion of married people, rate of disease, and population size are related significantly to UR. In all three regions, the Hotspot of unemployed will also be detected districts/cities using Spatial Scan Statistics Method. The results are 22 districts/cities as a regional group with the highest unemployed (Most likely cluster) in the study area; 2 districts/cities as a regional group with the highest unemployed in West Java; 1 district/city as a regional groups with the highest unemployed in Central Java; 15 districts/cities as a regional group with the highest unemployed in East Java.

Thwarted belongingness as an explanatory link between insomnia symptoms and suicidal ideation: Findings from three samples of military service members and veterans.

PubMed

Hom, Melanie A; Chu, Carol; Schneider, Matthew E; Lim, Ingrid C; Hirsch, Jameson K; Gutierrez, Peter M; Joiner, Thomas E

2017-02-01

Although insomnia has been identified as a robust predictor of suicidal ideation and behaviors, little is known about the mechanisms by which sleep disturbances confer risk for suicide. We investigated thwarted belongingness as an explanatory link between insomnia symptoms and suicidal ideation across three military service member and veteran samples. Data were collected among United States military service members and veterans (N 1 =937, N 2 =3,386, N 3 =417) who completed self-report measures of insomnia symptoms, thwarted belongingness, suicidal ideation, and related psychiatric symptoms (e.g., anxiety, hopelessness). Bias-corrected bootstrap mediation analyses were utilized to examine the indirect effects of insomnia symptoms on suicidal ideation through thwarted belongingness, controlling for related psychiatric symptoms. Consistent with study hypotheses, thwarted belongingness significantly accounted for the relationship between insomnia and suicidal ideation across all three samples; however, insomnia symptoms did not significantly account for the relationship between thwarted belongingness and suicidal ideation, highlighting the specificity of our findings. This study utilized cross-sectional self-report data. Insomnia may confer suicide risk for military service members and veterans, in part, through the pathway of thwarted belongingness. Additional prospective studies are warranted to further delineate this model of risk. Our results offer a potential therapeutic target for the prevention of suicide, via the promotion of belongingness, among service members and veterans experiencing insomnia symptoms. Copyright © 2016 Elsevier B.V. All rights reserved.

Continuous water-quality monitoring and regression analysis to estimate constituent concentrations and loads in the Red River of the North, Fargo, North Dakota, 2003-05

USGS Publications Warehouse

Ryberg, Karen R.

2006-01-01

This report presents the results of a study by the U.S. Geological Survey, done in cooperation with the Bureau of Reclamation, U.S. Department of the Interior, to estimate water-quality constituent concentrations in the Red River of the North at Fargo, North Dakota. Regression analysis of water-quality data collected in 2003-05 was used to estimate concentrations and loads for alkalinity, dissolved solids, sulfate, chloride, total nitrite plus nitrate, total nitrogen, total phosphorus, and suspended sediment. The explanatory variables examined for regression relation were continuously monitored physical properties of water-streamflow, specific conductance, pH, water temperature, turbidity, and dissolved oxygen. For the conditions observed in 2003-05, streamflow was a significant explanatory variable for all estimated constituents except dissolved solids. pH, water temperature, and dissolved oxygen were not statistically significant explanatory variables for any of the constituents in this study. Specific conductance was a significant explanatory variable for alkalinity, dissolved solids, sulfate, and chloride. Turbidity was a significant explanatory variable for total phosphorus and suspended sediment. For the nutrients, total nitrite plus nitrate, total nitrogen, and total phosphorus, cosine and sine functions of time also were used to explain the seasonality in constituent concentrations. The regression equations were evaluated using common measures of variability, including R2, or the proportion of variability in the estimated constituent explained by the regression equation. R2 values ranged from 0.703 for total nitrogen concentration to 0.990 for dissolved-solids concentration. The regression equations also were evaluated by calculating the median relative percentage difference (RPD) between measured constituent concentration and the constituent concentration estimated by the regression equations. Median RPDs ranged from 1.1 for dissolved solids to 35.2 for

When monoclonal antibodies are not monospecific: Hybridomas frequently express additional functional variable regions

PubMed Central

Bradbury, Andrew R. M.; Trinklein, Nathan D.; Wilkinson, Ian C.; Tandon, Atul K.; Anderson, Stephen; Bladen, Catherine L.; Jones, Brittany; Aldred, Shelley Force; Bestagno, Marco; Burrone, Oscar; Maynard, Jennifer; Ferrara, Fortunato; Görnemann, Janina; Glanville, Jacob; Wolf, Philipp; Frenzel, Andre; Wong, Julin; Koh, Xin Yu; Eng, Hui-Yan; Lane, David; Lefranc, Marie-Paule; Clark, Mike

2018-01-01

ABSTRACT Monoclonal antibodies are commonly assumed to be monospecific, but anecdotal studies have reported genetic diversity in antibody heavy chain and light chain genes found within individual hybridomas. As the prevalence of such diversity has never been explored, we analyzed 185 random hybridomas, in a large multicenter dataset. The hybridomas analyzed were not biased towards those with cloning difficulties or known to have additional chains. Of the hybridomas we evaluated, 126 (68.1%) contained no additional productive chains, while the remaining 59 (31.9%) contained one or more additional productive heavy or light chains. The expression of additional chains degraded properties of the antibodies, including specificity, binding signal and/or signal-to-noise ratio, as determined by enzyme-linked immunosorbent assay and immunohistochemistry. The most abundant mRNA transcripts found in a hybridoma cell line did not necessarily encode the antibody chains providing the correct specificity. Consequently, when cloning antibody genes, functional validation of all possible VH and VL combinations is required to identify those with the highest affinity and lowest cross-reactivity. These findings, reflecting the current state of hybridomas used in research, reiterate the importance of using sequence-defined recombinant antibodies for research or diagnostic use. PMID:29485921

Input Variability Facilitates Unguided Subcategory Learning in Adults

PubMed Central

Eidsvåg, Sunniva Sørhus; Austad, Margit; Asbjørnsen, Arve E.

2015-01-01

Purpose This experiment investigated whether input variability would affect initial learning of noun gender subcategories in an unfamiliar, natural language (Russian), as it is known to assist learning of other grammatical forms. Method Forty adults (20 men, 20 women) were familiarized with examples of masculine and feminine Russian words. Half of the participants were familiarized with 32 different root words in a high-variability condition. The other half were familiarized with 16 different root words, each repeated twice for a total of 32 presentations in a high-repetition condition. Participants were tested on untrained members of the category to assess generalization. Familiarization and testing was completed 2 additional times. Results Only participants in the high-variability group showed evidence of learning after an initial period of familiarization. Participants in the high-repetition group were able to learn after additional input. Both groups benefited when words included 2 cues to gender compared to a single cue. Conclusions The results demonstrate that the degree of input variability can influence learners' ability to generalize a grammatical subcategory (noun gender) from a natural language. In addition, the presence of multiple cues to linguistic subcategory facilitated learning independent of variability condition. PMID:25680081

Input Variability Facilitates Unguided Subcategory Learning in Adults.

PubMed

Eidsvåg, Sunniva Sørhus; Austad, Margit; Plante, Elena; Asbjørnsen, Arve E

2015-06-01

This experiment investigated whether input variability would affect initial learning of noun gender subcategories in an unfamiliar, natural language (Russian), as it is known to assist learning of other grammatical forms. Forty adults (20 men, 20 women) were familiarized with examples of masculine and feminine Russian words. Half of the participants were familiarized with 32 different root words in a high-variability condition. The other half were familiarized with 16 different root words, each repeated twice for a total of 32 presentations in a high-repetition condition. Participants were tested on untrained members of the category to assess generalization. Familiarization and testing was completed 2 additional times. Only participants in the high-variability group showed evidence of learning after an initial period of familiarization. Participants in the high-repetition group were able to learn after additional input. Both groups benefited when words included 2 cues to gender compared to a single cue. The results demonstrate that the degree of input variability can influence learners' ability to generalize a grammatical subcategory (noun gender) from a natural language. In addition, the presence of multiple cues to linguistic subcategory facilitated learning independent of variability condition.

The SU(2) action-angle variables

NASA Technical Reports Server (NTRS)

Ellinas, Demosthenes

1993-01-01

Operator angle-action variables are studied in the frame of the SU(2) algebra, and their eigenstates and coherent states are discussed. The quantum mechanical addition of action-angle variables is shown to lead to a noncommutative Hopf algebra. The group contraction is used to make the connection with the harmonic oscillator.

Explanatory Models of Genetics and Genetic Risk among a Selected Group of Students.

PubMed

Goltz, Heather Honoré; Bergman, Margo; Goodson, Patricia

2016-01-01

This exploratory qualitative study focuses on how college students conceptualize genetics and genetic risk, concepts essential for genetic literacy (GL) and genetic numeracy (GN), components of overall health literacy (HL). HL is dependent on both the background knowledge and culture of a patient, and lower HL is linked to increased morbidity and mortality for a number of chronic health conditions (e.g., diabetes and cancer). A purposive sample of 86 students from three Southwestern universities participated in eight focus groups. The sample ranged in age from 18 to 54 years, and comprised primarily of female (67.4%), single (74.4%), and non-White (57%) participants, none of whom were genetics/biology majors. A holistic-content approach revealed broad categories concerning participants' explanatory models (EMs) of genetics and genetic risk. Participants' EMs were grounded in highly contextualized narratives that only partially overlapped with biomedical models. While higher education levels should be associated with predominately knowledge-based EM of genetic risk, this study shows that even in well-educated populations cultural factors can dominate. Study findings reveal gaps in how this sample of young adults obtains, processes, and understands genetic/genomic concepts. Future studies should assess how individuals with low GL and GN obtain and process genetics and genetic risk information and incorporate this information into health decision making. Future work should also address the interaction of communication between health educators, providers, and genetic counselors, to increase patient understanding of genetic risk.

Symbolic dynamics marker of heart rate variability combined with clinical variables enhance obstructive sleep apnea screening

NASA Astrophysics Data System (ADS)

Ravelo-García, A. G.; Saavedra-Santana, P.; Juliá-Serdá, G.; Navarro-Mesa, J. L.; Navarro-Esteva, J.; Álvarez-López, X.; Gapelyuk, A.; Penzel, T.; Wessel, N.

2014-06-01

Many sleep centres try to perform a reduced portable test in order to decrease the number of overnight polysomnographies that are expensive, time-consuming, and disturbing. With some limitations, heart rate variability (HRV) has been useful in this task. The aim of this investigation was to evaluate if inclusion of symbolic dynamics variables to a logistic regression model integrating clinical and physical variables, can improve the detection of subjects for further polysomnographies. To our knowledge, this is the first contribution that innovates in that strategy. A group of 133 patients has been referred to the sleep center for suspected sleep apnea. Clinical assessment of the patients consisted of a sleep related questionnaire and a physical examination. The clinical variables related to apnea and selected in the statistical model were age (p < 10-3), neck circumference (p < 10-3), score on a questionnaire scale intended to quantify daytime sleepiness (p < 10-3), and intensity of snoring (p < 10-3). The validation of this model demonstrated an increase in classification performance when a variable based on non-linear dynamics of HRV (p < 0.01) was used additionally to the other variables. For diagnostic rule based only on clinical and physical variables, the corresponding area under the receiver operating characteristic (ROC) curve was 0.907 (95% confidence interval (CI) = 0.848, 0.967), (sensitivity 87.10% and specificity 80%). For the model including the average of a symbolic dynamic variable, the area under the ROC curve was increased to 0.941 (95% = 0.897, 0.985), (sensitivity 88.71% and specificity 82.86%). In conclusion, symbolic dynamics, coupled with significant clinical and physical variables can help to prioritize polysomnographies in patients with a high probability of apnea. In addition, the processing of the HRV is a well established low cost and robust technique.

Large interannual variability in net ecosystem carbon dioxide exchange of a disturbed temperate peatland.

PubMed

Aslan-Sungur, Guler; Lee, Xuhui; Evrendilek, Fatih; Karakaya, Nusret

2016-06-01

Peatland ecosystems play an important role in the global carbon (C) cycle as significant C sinks. However, human-induced disturbances can turn these sinks into sources of atmospheric CO2. Long-term measurements are needed to understand seasonal and interannual variability of net ecosystem CO2 exchange (NEE) and effects of hydrological conditions and their disturbances on C fluxes. Continuous eddy-covariance measurements of NEE were conducted between August 2010 and April 2014 at Yenicaga temperate peatland (Turkey), which was drained for agricultural usage and for peat mining until 2009. Annual NEE during the three full years of measurement indicated that the peatland acted as a CO2 source with large interannual variability, at rates of 246, 244 and 663 g Cm(-2)yr(-1) for 2011, 2012, and 2013 respectively, except for June 2011, and May to July 2012. The emission strengths were comparable to those found for severely disturbed tropical peatlands. The peak CO2 emissions occurred in the dry summer of 2013 when water table level (WTL) was below a threshold value of -60 cm and soil water content (SCW) below a threshold value of 70% by volume. Water availability index was found to have a stronger explanatory power for variations in monthly ecosystem respiration (ER) than the traditional water status indicators (SCW and WTL). Air temperature, evapotranspiration and vapor pressure deficient were the most significant variables strongly correlated with NEE and its component fluxes of gross primary production and ER. Copyright © 2016 Elsevier B.V. All rights reserved.

Eliminating Survivor Bias in Two-stage Instrumental Variable Estimators.

PubMed

Vansteelandt, Stijn; Walter, Stefan; Tchetgen Tchetgen, Eric

2018-07-01

Mendelian randomization studies commonly focus on elderly populations. This makes the instrumental variables analysis of such studies sensitive to survivor bias, a type of selection bias. A particular concern is that the instrumental variable conditions, even when valid for the source population, may be violated for the selective population of individuals who survive the onset of the study. This is potentially very damaging because Mendelian randomization studies are known to be sensitive to bias due to even minor violations of the instrumental variable conditions. Interestingly, the instrumental variable conditions continue to hold within certain risk sets of individuals who are still alive at a given age when the instrument and unmeasured confounders exert additive effects on the exposure, and moreover, the exposure and unmeasured confounders exert additive effects on the hazard of death. In this article, we will exploit this property to derive a two-stage instrumental variable estimator for the effect of exposure on mortality, which is insulated against the above described selection bias under these additivity assumptions.

Estimating historical groundwater levels based on relations with hydrologic and meteorological variables in the U.S. glacial aquifer system

NASA Astrophysics Data System (ADS)

Dudley, R. W.; Hodgkins, G. A.; Nielsen, M. G.; Qi, S. L.

2018-07-01

A number of previous studies have examined relations between groundwater levels and hydrologic and meteorological variables over parts of the glacial aquifer system, but systematic analyses across the entire U.S. glacial aquifer system are lacking. We tested correlations between monthly groundwater levels measured at 1043 wells in the U.S. glacial aquifer system considered to be minimally influenced by human disturbance and selected hydrologic and meteorological variables with the goal of extending historical groundwater records where there were strong correlations. Groundwater levels in the East region correlated most strongly with short-term (1 and 3 month) averages of hydrologic and meteorological variables, while those in the Central and West Central regions yielded stronger correlations with hydrologic and meteorological variables averaged over longer time intervals (6-12 months). Variables strongly correlated with high and low annual groundwater levels were identified as candidate records for use in statistical linear models as a means to fill in and extend historical high and low groundwater levels respectively. Overall, 37.4% of study wells meeting data criteria had successful models for high and (or) low groundwater levels; these wells shared characteristics of relatively higher local precipitation, higher local land-surface slope, lower amounts of clay within the surficial sediments, and higher base-flow index. Streamflow and base flow served as explanatory variables in about two thirds of both high- and low-groundwater-level models in all three regions, and generally yielded more and better models compared to precipitation and Palmer Drought Severity Index. The use of variables such as streamflow with substantially longer and more complete records than those of groundwater wells provide a means for placing contemporary groundwater levels in a longer historical context and can support site-specific analyses such as groundwater modeling.

Factors affecting plant species composition of hedgerows: relative importance and hierarchy

NASA Astrophysics Data System (ADS)

Deckers, Bart; Hermy, Martin; Muys, Bart

2004-07-01

Although there has been a clear quantitative and qualitative decline in traditional hedgerow network landscapes during last century, hedgerows are crucial for the conservation of rural biodiversity, functioning as an important habitat, refuge and corridor for numerous species. To safeguard this conservation function, insight in the basic organizing principles of hedgerow plant communities is needed. The vegetation composition of 511 individual hedgerows situated within an ancient hedgerow network landscape in Flanders, Belgium was recorded, in combination with a wide range of explanatory variables, including a selection of spatial variables. Non-parametric statistics in combination with multivariate data analysis techniques were used to study the effect of individual explanatory variables. Next, variables were grouped in five distinct subsets and the relative importance of these variable groups was assessed by two related variation partitioning techniques, partial regression and partial canonical correspondence analysis, taking into account explicitly the existence of intercorrelations between variables of different factor groups. Most explanatory variables affected significantly hedgerow species richness and composition. Multivariate analysis showed that, besides adjacent land use, hedgerow management, soil conditions, hedgerow type and origin, the role of other factors such as hedge dimensions, intactness, etc., could certainly not be neglected. Furthermore, both methods revealed the same overall ranking of the five distinct factor groups. Besides a predominant impact of abiotic environmental conditions, it was found that management variables and structural aspects have a relatively larger influence on the distribution of plant species in hedgerows than their historical background or spatial configuration.

How do Small Groups Promote Behaviour Change? An Integrative Conceptual Review of Explanatory Mechanisms.

PubMed

Borek, Aleksandra J; Abraham, Charles

2018-03-01

Small groups are used to promote health, well-being, and personal change by altering members' perceptions, beliefs, expectations, and behaviour patterns. An extensive cross-disciplinary literature has articulated and tested theories explaining how such groups develop, function, and facilitate change. Yet these theoretical understandings are rarely applied in the development, description, and evaluation of health-promotion, group-based, behaviour-change interventions. Medline database, library catalogues, search engines, specific journals and reference lists were searched for relevant texts. Texts were reviewed for explanatory concepts or theories describing change processes in groups, which were integrated into the developing conceptual structure. This was designed to be a parsimonious conceptual framework that could be applied to design and delivery. Five categories of interacting processes and concepts were identified and defined: (1) group development processes, (2) dynamic group processes, (3) social change processes, (4) personal change processes, and (5) group design and operating parameters. Each of these categories encompasses a variety of theorised mechanisms explaining individual change in small groups. The final conceptual model, together with the design issues and practical recommendations derived from it, provides a practical basis for linking research and theory explaining group functioning to optimal design of group-based, behaviour-change interventions. © 2018 The Authors. Applied Psychology: Health and Well-Being published by John Wiley & Sons Ltd on behalf of International Association of Applied Psychology.

The power of videogame-like experiences for explanatory storytelling in science, education, and healthcare.

NASA Astrophysics Data System (ADS)

Sarno, D. A.; Hayes, J.

2016-12-01

In the last forty years, videogames have gone from a dot bouncing between two lines ("PONG", 1972), to sprawling $150 million enterprises that teams of hundreds work on for years, with fully-developed, novelistic stories and graphics that can be arrestingly realistic and engrossing. Video games - and now virtual reality - conjure superhero sagas, alien wars, and historic battlefields. Yet the game industry has given little thought to using this powerful storytelling medium to explain the many wondrous facets of regular old reality. The techniques and technologies of game design are offering an ever-more potent tool for explaining the processes of science. Want to explain fracking to someone unfamiliar with its strange mechanics? We did - we built a game-like graphic that asks learners to frack a well themselves, on an iPad. They use their fingergs to drill the well, inject the water and solvents, and gather the resulting oil and gas - not to mention seeing the potential environmental ramifications. How about explaining heart or brain surgery on a 3-month old child? Or showing students how a nerve cell works by allowing them to fly into it and build the proteins that enable the nerve to fire? We've done all these, and are continuing to add new dimensions to immersive teaching and explanatory storytelling. We'll share insights we've gathered along the way.

Realist explanatory theory building method for social epidemiology: a protocol for a mixed method multilevel study of neighbourhood context and postnatal depression.

PubMed

Eastwood, John G; Jalaludin, Bin B; Kemp, Lynn A

2014-01-01

A recent criticism of social epidemiological studies, and multi-level studies in particular has been a paucity of theory. We will present here the protocol for a study that aims to build a theory of the social epidemiology of maternal depression. We use a critical realist approach which is trans-disciplinary, encompassing both quantitative and qualitative traditions, and that assumes both ontological and hierarchical stratification of reality. We describe a critical realist Explanatory Theory Building Method comprising of an: 1) emergent phase, 2) construction phase, and 3) confirmatory phase. A concurrent triangulated mixed method multilevel cross-sectional study design is described. The Emergent Phase uses: interviews, focus groups, exploratory data analysis, exploratory factor analysis, regression, and multilevel Bayesian spatial data analysis to detect and describe phenomena. Abductive and retroductive reasoning will be applied to: categorical principal component analysis, exploratory factor analysis, regression, coding of concepts and categories, constant comparative analysis, drawing of conceptual networks, and situational analysis to generate theoretical concepts. The Theory Construction Phase will include: 1) defining stratified levels; 2) analytic resolution; 3) abductive reasoning; 4) comparative analysis (triangulation); 5) retroduction; 6) postulate and proposition development; 7) comparison and assessment of theories; and 8) conceptual frameworks and model development. The strength of the critical realist methodology described is the extent to which this paradigm is able to support the epistemological, ontological, axiological, methodological and rhetorical positions of both quantitative and qualitative research in the field of social epidemiology. The extensive multilevel Bayesian studies, intensive qualitative studies, latent variable theory, abductive triangulation, and Inference to Best Explanation provide a strong foundation for Theory

Metacognitive judgments of repetition and variability effects in natural concept learning: evidence for variability neglect.

PubMed

Wahlheim, Christopher N; Finn, Bridgid; Jacoby, Larry L

2012-07-01

In four experiments, we examined the effects of repetitions and variability on the learning of bird families and metacognitive awareness of such effects. Of particular interest was the accuracy of, and bases for, predictions regarding classification of novel bird species, referred to as category learning judgments (CLJs). Participants studied birds in high repetitions and high variability conditions. These conditions differed in the number of presentations of each bird (repetitions) and the number of unique species from each family (variability). After study, participants made CLJs for each family and were then tested. Results from a classification test revealed repetition benefits for studied species and variability benefits for novel species. In contrast with performance, CLJs did not reflect the benefits of variability. Results showed that CLJs were susceptible to accessibility-based metacognitive illusions produced by additional repetitions of studied items.

[Different explanatory models for addictive behavior in Turkish and German youths in Germany: significance for prevention and treatment].

PubMed

Penka, S; Krieg, S; Hunner, Ch; Heinz, A

2003-07-01

Due to cultural and social barriers, immigrants seldom frequent centers for information, counseling, and treatment of addictive disorders. We examine cultural differences in the explanatory models of addictive behavior among Turkish and German youths in Germany with statistical devices that map the concepts associated with problems of addiction. Relevant differences were found between the disorder concepts of Turkish and German youth. German but not Turkish youths classified eating disorders among severe addictive disorders and associated them with embarrassment and shame. Concerning substance abuse, German but not Turkish youths clearly differentiated between illegal drug abuse and the abuse of alcohol and nicotine. Nearly half of all Turkish youths rejected central medical concepts such as "physical dependence" or "reduced control of substance intake" as completely inadequate to characterize problems of addictive behavior. Preventive information programs must consider these differences and use concepts that are accepted and clearly associated with addictive behavior by immigrant populations.

Long-term change in a behavioural trait: truncated spawning distribution and demography in Northeast Arctic cod

PubMed Central

Opdal, Anders Frugård; Jørgensen, Christian

2015-01-01

Harvesting may be a potent driver of demographic change and contemporary evolution, which both may have great impacts on animal populations. Research has focused on changes in phenotypic traits that are easily quantifiable and for which time series exist, such as size, age, sex, or gonad size, whereas potential changes in behavioural traits have been under-studied. Here, we analyse potential drivers of long-term changes in a behavioural trait for the Northeast Arctic stock of Atlantic cod Gadus morhua, namely choice of spawning location. For 104 years (1866–1969), commercial catches were recorded annually and reported by county along the Norwegian coast. During this time period, spawning ground distribution has fluctuated with a trend towards more northerly spawning. Spawning location is analysed against a suite of explanatory factors including climate, fishing pressure, density dependence, and demography. We find that demography (age or age at maturation) had the highest explanatory power for variation in spawning location, while climate had a limited effect below statistical significance. As to potential mechanisms, some effects of climate may act through demography, and explanatory variables for demography may also have absorbed direct evolutionary change in migration distance for which proxies were unavailable. Despite these caveats, we argue that fishing mortality, either through demographic or evolutionary change, has served as an effective driver for changing spawning locations in cod, and that additional explanatory factors related to climate add no significant information. PMID:25336028

Modeling Effects of Temperature, Soil, Moisture, Nutrition and Variety As Determinants of Severity of Pythium Damping-Off and Root Disease in Subterranean Clover

PubMed Central

You, Ming P.; Rensing, Kelly; Renton, Michael; Barbetti, Martin J.

2017-01-01

Subterranean clover (Trifolium subterraneum) is a critical pasture legume in Mediterranean regions of southern Australia and elsewhere, including Mediterranean-type climatic regions in Africa, Asia, Australia, Europe, North America, and South America. Pythium damping-off and root disease caused by Pythium irregulare is a significant threat to subterranean clover in Australia and a study was conducted to define how environmental factors (viz. temperature, soil type, moisture and nutrition) as well as variety, influence the extent of damping-off and root disease as well as subterranean clover productivity under challenge by this pathogen. Relationships were statistically modeled using linear and generalized linear models and boosted regression trees. Modeling found complex relationships between explanatory variables and the extent of Pythium damping-off and root rot. Linear modeling identified high-level (4 or 5-way) significant interactions for each dependent variable (dry shoot and root weight, emergence, tap and lateral root disease index). Furthermore, all explanatory variables (temperature, soil, moisture, nutrition, variety) were found significant as part of some interaction within these models. A significant five-way interaction between all explanatory variables was found for both dry shoot and root dry weights, and a four way interaction between temperature, soil, moisture, and nutrition was found for both tap and lateral root disease index. A second approach to modeling using boosted regression trees provided support for and helped clarify the complex nature of the relationships found in linear models. All explanatory variables showed at least 5% relative influence on each of the five dependent variables. All models indicated differences due to soil type, with the sand-based soil having either higher weights, greater emergence, or lower disease indices; while lowest weights and less emergence, as well as higher disease indices, were found for loam soil and

Health inequalities in Germany: do regional-level variables explain differentials in cardiovascular risk?

PubMed Central

Breckenkamp, Juergen; Mielck, Andreas; Razum, Oliver

2007-01-01

Background Socioeconomic status is a predictor not only of mortality, but also of cardiovascular risk and morbidity. An ongoing debate in the field of social inequalities and health focuses on two questions: 1) Is individual health status associated with individual income as well as with income inequality at the aggregate (e. g. regional) level? 2) If there is such an association, does it operate via a psychosocial pathway (e.g. stress) or via a "neo-materialistic" pathway (e.g. systematic under-investment in societal infrastructures)? For the first time in Germany, we here investigate the association between cardiovascular health status and income inequality at the area level, controlling for individual socio-economic status. Methods Individual-level explanatory variables (age, socio-economic status) and outcome data (body mass index, blood pressure, cholesterol level) as well as the regional-level variable (proportion of relative poverty) were taken from the baseline survey of the German Cardiovascular Prevention Study, a cross-sectional, community-based, multi-center intervention study, comprising six socio-economically diverse intervention regions, each with about 1800 participants aged 25–69 years. Multilevel modeling was used to examine the effects of individual and regional level variables. Results Regional effects are small compared to individual effects for all risk factors analyzed. Most of the total variance is explained at the individual level. Only for diastolic blood pressure in men and for cholesterol in both men and women is a statistically significant effect visible at the regional level. Conclusion Our analysis does not support the assumption that in Germany cardiovascular risk factors were to a large extent associated with income inequality at regional level. PMID:17603918

[An explanatory model of behavior toward mental illness].

PubMed

García-Sílberman, Sarah

2002-01-01

To evaluate a theoretical model designed to explain behaviors toward mental illness, considering some variables related to the construct. A survey was conducted in 1996 on mental disorder beliefs, attitudes, and behavioral intentions. The sample population was stratified by socioeconomic status, age, and gender. Study subjects were 800 individuals from Mexico City's general population. A data collection instrument was constructed and validated, consisting of 120 Likert-type items with five options each. Data were coded and analyzed with the software package SPSS. Internal consistency of the scales was assessed using Cronbach's alpha and construct validity with factorial analysis. Student's t test and ANOVA were used to compare the groups in the different strata. The model allowed to confirm the predictive capacity of the causal chain connecting beliefs, attitudes, and intentions; nevertheless, other study variables did not contribute to explain it, and behavior was scarcely influenced by intentions, depending mainly on experimented necessity. Study findings constitute a basis to understand the attitudes of shame and fear usually related to mental illnesses, to plan efficient actions aimed at modifying them, and to design programs to promote mental health. The English version of this paper is available at: http://www.insp.mx/salud/index.html.

[Multilevel analysis of the technical efficiency of hospitals in the Spanish National Health System by property and type of management].

PubMed

Pérez-Romero, Carmen; Ortega-Díaz, M Isabel; Ocaña-Riola, Ricardo; Martín-Martín, José Jesús

2018-05-11

To analyze technical efficiency by type of property and management of general hospitals in the Spanish National Health System (2010-2012) and identify hospital and regional explanatory variables. 230 hospitals were analyzed combining data envelopment analysis and fixed effects multilevel linear models. Data envelopment analysis measured overall, technical and scale efficiency, and the analysis of explanatory factors was performed using multilevel models. The average rate of overall technical efficiency of hospitals without legal personality is lower than hospitals with legal personality (0.691 and 0.876 in 2012). There is a significant variability in efficiency under variable returns (TE) by direct, indirect and mixed forms of management. The 29% of the variability in TE es attributable to the Region. Legal personality increased the TE of the hospitals by 11.14 points. On the other hand, most of the forms of management (different to those of the traditional hospitals) increased TE in varying percentages. At regional level, according to the model considered, insularity and average annual income per household are explanatory variables of TE. Having legal personality favours technical efficiency. The regulatory and management framework of hospitals, more than public or private ownership, seem to explain technical efficiency. Regional characteristics explain the variability in TE. Copyright © 2018 SESPAS. Publicado por Elsevier España, S.L.U. All rights reserved.

The effect of modeled absolute timing variability and relative timing variability on observational learning.

PubMed

Grierson, Lawrence E M; Roberts, James W; Welsher, Arthur M

2017-05-01

There is much evidence to suggest that skill learning is enhanced by skill observation. Recent research on this phenomenon indicates a benefit of observing variable/erred demonstrations. In this study, we explore whether it is variability within the relative organization or absolute parameterization of a movement that facilitates skill learning through observation. To do so, participants were randomly allocated into groups that observed a model with no variability, absolute timing variability, relative timing variability, or variability in both absolute and relative timing. All participants performed a four-segment movement pattern with specific absolute and relative timing goals prior to and following the observational intervention, as well as in a 24h retention test and transfers tests that featured new relative and absolute timing goals. Absolute timing error indicated that all groups initially acquired the absolute timing, maintained their performance at 24h retention, and exhibited performance deterioration in both transfer tests. Relative timing error revealed that the observation of no variability and relative timing variability produced greater performance at the post-test, 24h retention and relative timing transfer tests, but for the no variability group, deteriorated at absolute timing transfer test. The results suggest that the learning of absolute timing following observation unfolds irrespective of model variability. However, the learning of relative timing benefits from holding the absolute features constant, while the observation of no variability partially fails in transfer. We suggest learning by observing no variability and variable/erred models unfolds via similar neural mechanisms, although the latter benefits from the additional coding of information pertaining to movements that require a correction. Copyright © 2017 Elsevier B.V. All rights reserved.

Parents' help-seeking behaviours during acute childhood illness at home: A contribution to explanatory theory.

PubMed

Neill, Sarah J; Jones, Caroline H D; Lakhanpaul, Monica; Roland, Damian T; Thompson, Matthew J

2016-03-01

Uncertainty and anxiety surround parents' decisions to seek medical help for an acutely ill child. Consultation rates for children are rising, yet little is known about factors that influence parents' help-seeking behaviours. We used focus groups and interviews to examine how 27 parents of children under five years, from a range of socioeconomic groups in the East Midlands of England, use information to make decisions during acute childhood illness at home. This article reports findings elucidating factors that influence help-seeking behaviours. Parents reported that decision-making during acute childhood illness was influenced by a range of personal, social and health service factors. Principal among these was parents' concern to do the right thing for their child. Their ability to assess the severity of the illness was influenced by knowledge and experience of childhood illness. When parents were unable to access their general practitioner (GP), feared criticism from or had lost trust in their GP, some parents reported using services elsewhere such as Accident and Emergency. These findings contribute to explanatory theory concerning parents' help-seeking behaviours. Professional and political solutions have not reduced demand; therefore, collaborative approaches involving the public and professionals are now needed to improve parents' access to information. © The Author(s) 2014.

Barriers and Explanatory Mechanisms of Delays in the Patient and Diagnosis Intervals of Care for Breast Cancer in Mexico.

PubMed

Unger-Saldaña, Karla; Ventosa-Santaulària, Daniel; Miranda, Alfonso; Verduzco-Bustos, Guillermo

2018-04-01

Most breast cancer patients in low- and middle-income settings are diagnosed at advanced stages due to lengthy intervals of care. This study aimed to understand the mechanisms through which delays occur in the patient interval and diagnosis interval of care. We conducted a cross-sectional survey including 886 patients referred to four major public cancer hospitals in Mexico City. Based in a conceptual model of help-seeking behavior, a path analysis strategy was used to identify the relationships between explanatory factors of patient delay and diagnosis delay. The patient and the diagnosis intervals were greater than 3 months in 20% and 65% of participants, respectively. We present explanatory models for each interval and the interrelationship between the associated factors. The patient interval was longer among women who were single, interpreted their symptoms as not worrisome, concealed symptoms, and perceived a lack of financial resources and the difficulty of missing a day of work as barriers to seek care. These barriers were more commonly perceived among patients who were younger, had lower socioeconomic status, and lived outside of Mexico City. The diagnosis interval was longer among those who used several different health services prior to the cancer hospital and perceived medical errors in these services. More health services were used among those who perceived errors and long waiting times for appointments, and who first consulted private services. Our findings support the relevance of strengthening early cancer diagnosis strategies, especially the improvement of quality of primary care and expedited referral routes to cancer services. This study's findings suggest that policy in low- and middle-income countries (LMICs) should be directed toward reducing delays in diagnosis, before the implementation of mammography screening programs. The results suggest several factors susceptible to early diagnosis interventions. To reduce patient delays, the usually

End-Point Variability Is Not Noise in Saccade Adaptation

PubMed Central

Herman, James P.; Cloud, C. Phillip; Wallman, Josh

2013-01-01

When each of many saccades is made to overshoot its target, amplitude gradually decreases in a form of motor learning called saccade adaptation. Overshoot is induced experimentally by a secondary, backwards intrasaccadic target step (ISS) triggered by the primary saccade. Surprisingly, however, no study has compared the effectiveness of different sizes of ISS in driving adaptation by systematically varying ISS amplitude across different sessions. Additionally, very few studies have examined the feasibility of adaptation with relatively small ISSs. In order to best understand saccade adaptation at a fundamental level, we addressed these two points in an experiment using a range of small, fixed ISS values (from 0° to 1° after a 10° primary target step). We found that significant adaptation occurred across subjects with an ISS as small as 0.25°. Interestingly, though only adaptation in response to 0.25° ISSs appeared to be complete (the magnitude of change in saccade amplitude was comparable to size of the ISS), further analysis revealed that a comparable proportion of the ISS was compensated for across conditions. Finally, we found that ISS size alone was sufficient to explain the magnitude of adaptation we observed; additional factors did not significantly improve explanatory power. Overall, our findings suggest that current assumptions regarding the computation of saccadic error may need to be revisited. PMID:23555763

A Study of Effects of MultiCollinearity in the Multivariable Analysis

PubMed Central

Yoo, Wonsuk; Mayberry, Robert; Bae, Sejong; Singh, Karan; (Peter) He, Qinghua; Lillard, James W.

2015-01-01

A multivariable analysis is the most popular approach when investigating associations between risk factors and disease. However, efficiency of multivariable analysis highly depends on correlation structure among predictive variables. When the covariates in the model are not independent one another, collinearity/multicollinearity problems arise in the analysis, which leads to biased estimation. This work aims to perform a simulation study with various scenarios of different collinearity structures to investigate the effects of collinearity under various correlation structures amongst predictive and explanatory variables and to compare these results with existing guidelines to decide harmful collinearity. Three correlation scenarios among predictor variables are considered: (1) bivariate collinear structure as the most simple collinearity case, (2) multivariate collinear structure where an explanatory variable is correlated with two other covariates, (3) a more realistic scenario when an independent variable can be expressed by various functions including the other variables. PMID:25664257

A Study of Effects of MultiCollinearity in the Multivariable Analysis.

PubMed

Yoo, Wonsuk; Mayberry, Robert; Bae, Sejong; Singh, Karan; Peter He, Qinghua; Lillard, James W

2014-10-01

A multivariable analysis is the most popular approach when investigating associations between risk factors and disease. However, efficiency of multivariable analysis highly depends on correlation structure among predictive variables. When the covariates in the model are not independent one another, collinearity/multicollinearity problems arise in the analysis, which leads to biased estimation. This work aims to perform a simulation study with various scenarios of different collinearity structures to investigate the effects of collinearity under various correlation structures amongst predictive and explanatory variables and to compare these results with existing guidelines to decide harmful collinearity. Three correlation scenarios among predictor variables are considered: (1) bivariate collinear structure as the most simple collinearity case, (2) multivariate collinear structure where an explanatory variable is correlated with two other covariates, (3) a more realistic scenario when an independent variable can be expressed by various functions including the other variables.

Modeling the role of environmental variables on the population dynamics of the malaria vector Anopheles gambiae sensu stricto

PubMed Central

2012-01-01

Background The impact of weather and climate on malaria transmission has attracted considerable attention in recent years, yet uncertainties around future disease trends under climate change remain. Mathematical models provide powerful tools for addressing such questions and understanding the implications for interventions and eradication strategies, but these require realistic modeling of the vector population dynamics and its response to environmental variables. Methods Published and unpublished field and experimental data are used to develop new formulations for modeling the relationships between key aspects of vector ecology and environmental variables. These relationships are integrated within a validated deterministic model of Anopheles gambiae s.s. population dynamics to provide a valuable tool for understanding vector response to biotic and abiotic variables. Results A novel, parsimonious framework for assessing the effects of rainfall, cloudiness, wind speed, desiccation, temperature, relative humidity and density-dependence on vector abundance is developed, allowing ease of construction, analysis, and integration into malaria transmission models. Model validation shows good agreement with longitudinal vector abundance data from Tanzania, suggesting that recent malaria reductions in certain areas of Africa could be due to changing environmental conditions affecting vector populations. Conclusions Mathematical models provide a powerful, explanatory means of understanding the role of environmental variables on mosquito populations and hence for predicting future malaria transmission under global change. The framework developed provides a valuable advance in this respect, but also highlights key research gaps that need to be resolved if we are to better understand future malaria risk in vulnerable communities. PMID:22877154

Understanding First Generation College Student Experiences and Interaction with Belongingness, Identity, and Social Capital: An Explanatory Mixed Method Study

NASA Astrophysics Data System (ADS)

Boone, Hank Joseph Reyes

This master's thesis is a mixed method explanatory study focusing on First Generation College student's (FGS) engineering degree experiences. Constructs used to understand their experiences were future time perspective, belongingness, engineering identity, social capital, and social identity complexity. An upper level engineering students' communications class was surveyed at a western land grant institution. Analysis showed FGS had more engineering belongingness than peers having at least one parent graduate college. The qualitative population was then upper level engineering FGS who reported high belongingness. Data showed the five interview participants communicated belongingness in terms of engineering identity. They became an engineer when they had experiences using engineering knowledge. Participants often accessed parents and family to make academic and career decisions, but some accessed more individuals (i.e. professors, engineers, peers). Lastly, participants appeared to compartmentalize their FGS identity to outside the engineering classroom while they formed their engineering identity through the degree program.

[Academic performance in first year medical students: an explanatory multivariate model].

PubMed

Urrutia Aguilar, María Esther; Ortiz León, Silvia; Fouilloux Morales, Claudia; Ponce Rosas, Efrén Raúl; Guevara Guzmán, Rosalinda

2014-12-01

Current education is focused in intellectual, affective, and ethical aspects, thus acknowledging their significance in students´ metacognition. Nowadays, it is known that an adequate and motivating environment together with a positive attitude towards studies is fundamental to induce learning. Medical students are under multiple stressful, academic, personal, and vocational situations. To identify psychosocial, vocational, and academic variables of 2010-2011 first year medical students at UNAM that may help predict their academic performance. Academic surveys of psychological and vocational factors were applied; an academic follow-up was carried out to obtain a multivariate model. The data were analyzed considering descriptive, comparative, correlative, and predictive statistics. The main variables that affect students´ academic performance are related to previous knowledge and to psychological variables. The results show the significance of implementing institutional programs to support students throughout their college adaptation.

Speed and Cardiac Recovery Variables Predict the Probability of Elimination in Equine Endurance Events

PubMed Central

Younes, Mohamed; Robert, Céline; Cottin, François; Barrey, Eric

2015-01-01

Nearly 50% of the horses participating in endurance events are eliminated at a veterinary examination (a vet gate). Detecting unfit horses before a health problem occurs and treatment is required is a challenge for veterinarians but is essential for improving equine welfare. We hypothesized that it would be possible to detect unfit horses earlier in the event by measuring heart rate recovery variables. Hence, the objective of the present study was to compute logistic regressions of heart rate, cardiac recovery time and average speed data recorded at the previous vet gate (n-1) and thus predict the probability of elimination during successive phases (n and following) in endurance events. Speed and heart rate data were extracted from an electronic database of endurance events (80–160 km in length) organized in four countries. Overall, 39% of the horses that started an event were eliminated—mostly due to lameness (64%) or metabolic disorders (15%). For each vet gate, logistic regressions of explanatory variables (average speed, cardiac recovery time and heart rate measured at the previous vet gate) and categorical variables (age and/or event distance) were computed to estimate the probability of elimination. The predictive logistic regressions for vet gates 2 to 5 correctly classified between 62% and 86% of the eliminated horses. The robustness of these results was confirmed by high areas under the receiving operating characteristic curves (0.68–0.84). Overall, a horse has a 70% chance of being eliminated at the next gate if its cardiac recovery time is longer than 11 min at vet gate 1 or 2, or longer than 13 min at vet gates 3 or 4. Heart rate recovery and average speed variables measured at the previous vet gate(s) enabled us to predict elimination at the following vet gate. These variables should be checked at each veterinary examination, in order to detect unfit horses as early as possible. Our predictive method may help to improve equine welfare and ethical

Speed and Cardiac Recovery Variables Predict the Probability of Elimination in Equine Endurance Events.

PubMed

Younes, Mohamed; Robert, Céline; Cottin, François; Barrey, Eric

2015-01-01

Nearly 50% of the horses participating in endurance events are eliminated at a veterinary examination (a vet gate). Detecting unfit horses before a health problem occurs and treatment is required is a challenge for veterinarians but is essential for improving equine welfare. We hypothesized that it would be possible to detect unfit horses earlier in the event by measuring heart rate recovery variables. Hence, the objective of the present study was to compute logistic regressions of heart rate, cardiac recovery time and average speed data recorded at the previous vet gate (n-1) and thus predict the probability of elimination during successive phases (n and following) in endurance events. Speed and heart rate data were extracted from an electronic database of endurance events (80-160 km in length) organized in four countries. Overall, 39% of the horses that started an event were eliminated--mostly due to lameness (64%) or metabolic disorders (15%). For each vet gate, logistic regressions of explanatory variables (average speed, cardiac recovery time and heart rate measured at the previous vet gate) and categorical variables (age and/or event distance) were computed to estimate the probability of elimination. The predictive logistic regressions for vet gates 2 to 5 correctly classified between 62% and 86% of the eliminated horses. The robustness of these results was confirmed by high areas under the receiving operating characteristic curves (0.68-0.84). Overall, a horse has a 70% chance of being eliminated at the next gate if its cardiac recovery time is longer than 11 min at vet gate 1 or 2, or longer than 13 min at vet gates 3 or 4. Heart rate recovery and average speed variables measured at the previous vet gate(s) enabled us to predict elimination at the following vet gate. These variables should be checked at each veterinary examination, in order to detect unfit horses as early as possible. Our predictive method may help to improve equine welfare and ethical

More on Darwin's illness: comment on the final diagnosis of Charles Darwin.

PubMed

Sheehan, William; Meller, William H; Thurber, Steven

2008-06-20

Without the possibility of confirmatory exhumation, diagnostic inferences about Darwin's illness must remain speculative. A diagnosis of Darwin's aggregate symptoms must account for not only gastrointestinal distress but also his predominant and excessive retching and the conglomerate of other heterogeneous symptoms. We opine that Crohn's disease, posited as the 'final diagnosis', is not sufficient for subsuming his pleiomorphic symptomatology. An additional proposal is outlined that may help to explain his presentation with heterogeneous symptoms. It incorporates constitutional vulnerabilities, psychosomatic influences and Pavlovian conditioning as explanatory variables.

An explanatory model for the concept of mental health in Iranian youth

PubMed Central

Chinekesh, Ahdieh; Hosseini, Seyed Ali; Mohammadi, Farahnaz; Motlagh, Mohammad Esmael; Baradaran Eftekhari, Monir; Djalalinia, Shirin; Ardalan, Gelayol

2018-01-01

Background: Mental health is considered as an integral and essential component of overall health. Its determinants and related factors are one of the most important research priorities, especially in adolescents and young people. Using a qualitative approach, the present study aimed to identify factors affecting the mental health of youth in Iran. Methods: In 2017, following content analysis principles, and using semi-structured in-depth interviews, we conducted a qualitative study exploring the opinions of young people about mental health. A targeted sampling method was used, and participants were young volunteers aged 18 to 30 who were selected from Tehran province, Iran. Inclusion criteria for participants was willingness to participate in the study, and ability to express their experiences. Data collection was done with individual in-depth interviews. According to the explanatory model, the interviews were directed toward the concept of mental health and path of causality and auxiliary behaviors. Results: 21 young adults participated, who met the study inclusion criteria, of whom 12 participants were male. Their mean age was 24.4 ± 0.41 years and their education varied from primary school to Master’s degree. Mental health was considered as mental well-being and a sense of satisfaction and efficacy, not only the presence of a disease or mental disorder. Based on the opinions of the interviewees, three factors of personal characteristics, family and society are involved in mental health. Individual factors were associated with behavioral and physical problems. One of the most important issues was revealed as tensions in societal and family conflicts. Economic problems and unemployment of young people were also extracted from the social factor. Conclusion: In Iran, social factors such as jobs for the unemployed and job security are considered as important determinants in the mental health of young people. PMID:29560255

Vocational Teacher Stress and the Educational System.

ERIC Educational Resources Information Center

Adams, Elaine; Heath-Camp, Betty; Camp, William G.

1999-01-01

A multiple regression analysis of data from 235 secondary vocational teachers in Virginia found that educational system-related variables explained most teacher stress. The most important explanatory variables were task stress and role overload. (SK)

The use of process models to inform and improve statistical models of nitrate occurrence, Great Miami River Basin, southwestern Ohio

USGS Publications Warehouse

Walter, Donald A.; Starn, J. Jeffrey

2013-01-01

in estimated variables for circular buffers and contributing recharge areas of existing public-supply and network wells in the Great Miami River Basin. Large differences in areaweighted mean environmental variables are observed at the basin scale, determined by using the network of uniformly spaced hypothetical wells; the differences have a spatial pattern that generally is similar to spatial patterns in the underlying STATSGO data. Generally, the largest differences were observed for area-weighted nitrogen-application rate from county and national land-use data; the basin-scale differences ranged from -1,600 (indicating a larger value from within the volume-equivalent contributing recharge area) to 1,900 kilograms per year (kg/yr); the range in the underlying spatial data was from 0 to 2,200 kg/yr. Silt content, alfisol content, and nitrogen-application rate are defined by the underlying spatial data and are external to the groundwater system; however, depth to water is an environmental variable that can be estimated in more detail and, presumably, in a more physically based manner using a groundwater-flow model than using the spatial data. Model-calculated depths to water within circular buffers in the Great Miami River Basin differed substantially from values derived from the spatial data and had a much larger range. Differences in estimates of area-weighted spatial variables result in corresponding differences in predictions of nitrate occurrence in the aquifer. In addition to the factors affecting contributing recharge areas and estimated explanatory variables, differences in predictions also are a function of the specific set of explanatory variables used and the fitted slope coefficients in a given model. For models that predicted the probability of exceeding 1 and 4 milligrams per liter as nitrogen (mg/L as N), predicted probabilities using variables estimated from circular buffers and contributing recharge areas generally were correlated but differed

Adaptive Variability in Skilled Human Movements

NASA Astrophysics Data System (ADS)

Kudo, Kazutoshi; Ohtsuki, Tatsuyuki

Human movements are produced in variable external/internal environments. Because of this variability, the same motor command can result in quite different movement patterns. Therefore, to produce skilled movements humans must coordinate the variability, not try to exclude it. In addition, because human movements are produced in redundant and complex systems, a combination of variability should be observed in different anatomical/physiological levels. In this paper, we introduce our research about human movement variability that shows remarkable coordination among components, and between organism and environment. We also introduce nonlinear dynamical models that can describe a variety of movements as a self-organization of a dynamical system, because the dynamical systems approach is a major candidate to understand the principle underlying organization of varying systems with huge degrees-of-freedom.

Role Variables VS. Contextual Variables in the Theory of Didactic Systems

NASA Astrophysics Data System (ADS)

Alberti, Monica; Cirina, Lucia; Paoli, Francesco

Partisans of the constructivist approach to mathematics education, such as Brousseau or Chevallard, developed an accurate theoretical framework in which didactical systems are viewed in a systemic perspective. What they somewhat fail to draw, however, is a sharp distinction between role variables - concerning the roles played in the didactical interaction by the individual elements of the system (Student-Teacher-Knowledge) - and contextual variables - concerning the action on the learning process of the system as a whole. Our research in progress on 2nd graders' word problem solving strategies applies the previous dichotomy to class management strategies adopted by teachers. Partial evidence collected so far points to the tentative conclusion according to which, contextual variables being equal, differences in teaching styles and methods may deeply reshape the role component of didactical systems. If we take into careful account this distinction, we can shed additional light into some hitherto unexplained phenomena observed in the literature.

Black string corrections in variable tension braneworld scenarios

NASA Astrophysics Data System (ADS)

Da Rocha, Roldão; Hoff da Silva, J. M.

2012-02-01

Braneworld models with variable tension are investigated, and the corrections on the black string horizon along the extra dimension are provided. Such corrections are encrypted in additional terms involving the covariant derivatives of the variable tension on the brane, providing profound consequences concerning the black string horizon variation along the extra dimension, near the brane. The black string horizon behavior is shown to be drastically modified by the terms corrected by the brane variable tension. In particular, a model motivated by the phenomenological interesting case regarding Eötvös branes is investigated. It forthwith provides further physical features regarding variable tension braneworld scenarios, heretofore concealed in all previous analysis in the literature. All precedent analysis considered uniquely the expansion of the metric up to the second order along the extra dimension, which is able to evince solely the brane variable tension absolute value. Notwithstanding, the expansion terms aftermath, further accomplished in this paper from the third order on, elicits the successive covariant derivatives of the brane variable tension, and their respective coupling with the extrinsic curvature, the Weyl tensor, and the Riemann and Ricci tensors, as well as the scalar curvature. Such additional terms are shown to provide sudden modifications in the black string horizon in a variable tension braneworld scenario.

Effectiveness of the Touch Math Technique in Teaching Basic Addition to Children with Autism

ERIC Educational Resources Information Center

Yikmis, Ahmet

2016-01-01

This study aims to reveal whether the touch math technique is effective in teaching basic addition to children with autism. The dependent variable of this study is the children's skills to solve addition problems correctly, whereas teaching with the touch math technique is the independent variable. Among the single-subject research models, a…

Modeling Linguistic Variables With Regression Models: Addressing Non-Gaussian Distributions, Non-independent Observations, and Non-linear Predictors With Random Effects and Generalized Additive Models for Location, Scale, and Shape

PubMed Central

Coupé, Christophe

2018-01-01

As statistical approaches are getting increasingly used in linguistics, attention must be paid to the choice of methods and algorithms used. This is especially true since they require assumptions to be satisfied to provide valid results, and because scientific articles still often fall short of reporting whether such assumptions are met. Progress is being, however, made in various directions, one of them being the introduction of techniques able to model data that cannot be properly analyzed with simpler linear regression models. We report recent advances in statistical modeling in linguistics. We first describe linear mixed-effects regression models (LMM), which address grouping of observations, and generalized linear mixed-effects models (GLMM), which offer a family of distributions for the dependent variable. Generalized additive models (GAM) are then introduced, which allow modeling non-linear parametric or non-parametric relationships between the dependent variable and the predictors. We then highlight the possibilities offered by generalized additive models for location, scale, and shape (GAMLSS). We explain how they make it possible to go beyond common distributions, such as Gaussian or Poisson, and offer the appropriate inferential framework to account for ‘difficult’ variables such as count data with strong overdispersion. We also demonstrate how they offer interesting perspectives on data when not only the mean of the dependent variable is modeled, but also its variance, skewness, and kurtosis. As an illustration, the case of phonemic inventory size is analyzed throughout the article. For over 1,500 languages, we consider as predictors the number of speakers, the distance from Africa, an estimation of the intensity of language contact, and linguistic relationships. We discuss the use of random effects to account for genealogical relationships, the choice of appropriate distributions to model count data, and non-linear relationships. Relying on GAMLSS

Modeling Linguistic Variables With Regression Models: Addressing Non-Gaussian Distributions, Non-independent Observations, and Non-linear Predictors With Random Effects and Generalized Additive Models for Location, Scale, and Shape.

PubMed

Coupé, Christophe

2018-01-01

As statistical approaches are getting increasingly used in linguistics, attention must be paid to the choice of methods and algorithms used. This is especially true since they require assumptions to be satisfied to provide valid results, and because scientific articles still often fall short of reporting whether such assumptions are met. Progress is being, however, made in various directions, one of them being the introduction of techniques able to model data that cannot be properly analyzed with simpler linear regression models. We report recent advances in statistical modeling in linguistics. We first describe linear mixed-effects regression models (LMM), which address grouping of observations, and generalized linear mixed-effects models (GLMM), which offer a family of distributions for the dependent variable. Generalized additive models (GAM) are then introduced, which allow modeling non-linear parametric or non-parametric relationships between the dependent variable and the predictors. We then highlight the possibilities offered by generalized additive models for location, scale, and shape (GAMLSS). We explain how they make it possible to go beyond common distributions, such as Gaussian or Poisson, and offer the appropriate inferential framework to account for 'difficult' variables such as count data with strong overdispersion. We also demonstrate how they offer interesting perspectives on data when not only the mean of the dependent variable is modeled, but also its variance, skewness, and kurtosis. As an illustration, the case of phonemic inventory size is analyzed throughout the article. For over 1,500 languages, we consider as predictors the number of speakers, the distance from Africa, an estimation of the intensity of language contact, and linguistic relationships. We discuss the use of random effects to account for genealogical relationships, the choice of appropriate distributions to model count data, and non-linear relationships. Relying on GAMLSS, we

Parental Depressive Symptoms and Adolescent Adjustment: A Prospective Test of an Explanatory Model for the Role of Marital Conflict

PubMed Central

Cummings, E. Mark; Cheung, Rebecca Y. M.; Koss, Kalsea; Davies, Patrick T.

2014-01-01

Despite calls for process-oriented models for child maladjustment due to heightened marital conflict in the context of parental depressive symptoms, few longitudinal tests of the mechanisms underlying these relations have been conducted. Addressing this gap, the present study examined multiple factors longitudinally that link parental depressive symptoms to adolescent adjustment problems, building on a conceptual model informed by emotional security theory (EST). Participants were 320 families (158 boys, 162 girls), including mothers and fathers, who took part when their children were in kindergarten (T1), second (T2), seventh (T3), eighth (T4) and ninth (T5) grades. Parental depressive symptoms (T1) were related to changes in adolescents’ externalizing and internalizing symptoms (T5), as mediated by parents’ negative emotional expressiveness (T2), marital conflict (T3), and emotional insecurity (T4). Evidence was thus advanced for emotional insecurity as an explanatory process in the context of parental depressive symptoms. PMID:24652484

Empirical spatial econometric modelling of small scale neighbourhood

NASA Astrophysics Data System (ADS)

Gerkman, Linda

2012-07-01

The aim of the paper is to model small scale neighbourhood in a house price model by implementing the newest methodology in spatial econometrics. A common problem when modelling house prices is that in practice it is seldom possible to obtain all the desired variables. Especially variables capturing the small scale neighbourhood conditions are hard to find. If there are important explanatory variables missing from the model, the omitted variables are spatially autocorrelated and they are correlated with the explanatory variables included in the model, it can be shown that a spatial Durbin model is motivated. In the empirical application on new house price data from Helsinki in Finland, we find the motivation for a spatial Durbin model, we estimate the model and interpret the estimates for the summary measures of impacts. By the analysis we show that the model structure makes it possible to model and find small scale neighbourhood effects, when we know that they exist, but we are lacking proper variables to measure them.

Risky online behaviors among adolescents: Longitudinal relations among problematic Internet use, cyberbullying perpetration, and meeting strangers online

PubMed Central

Gámez-Guadix, Manuel; Borrajo, Erika; Almendros, Carmen

2016-01-01

Background and aims This study aims to analyze the cross-sectional and longitudinal relationship between three major risky online behaviors during adolescence: problematic Internet use, cyberbullying perpetration, and meeting strangers online. An additional objective was to study the role of impulsivity–irresponsibility as a possible explanatory variable of the relationships between these risky online behaviors. Methods The study sample was 888 adolescents that completed self-report measures at time 1 and time 2 with an interval of 6 months. Results The findings showed a significant cross-sectional relationship between the risky online behaviors analyzed. At the longitudinal level, problematic Internet use at time 1 predicted an increase in the perpetration of cyberbullying and meeting strangers online at time 2. Furthermore, meeting strangers online increased the likelihood of cyberbullying perpetration at time 2. Finally, when impulsivity–irresponsibility was included in the model as an explanatory variable, the relationships previously found remained significant. Discussion These results extend traditional problem behavior theory during adolescence, also supporting a relationship between different risky behaviors in cyberspace. In addition, findings highlighted the role of problematic Internet use, which increased the chances of developing cyberbullying perpetration and meeting strangers online over time. However, the results suggest a limited role of impulsivity–irresponsibility as an explicative mechanism. Conclusions The findings suggest that various online risk activities ought to be addressed together when planning assessment, prevention and intervention efforts. PMID:28092196

Direction dependence analysis: A framework to test the direction of effects in linear models with an implementation in SPSS.

PubMed

Wiedermann, Wolfgang; Li, Xintong

2018-04-16

In nonexperimental data, at least three possible explanations exist for the association of two variables x and y: (1) x is the cause of y, (2) y is the cause of x, or (3) an unmeasured confounder is present. Statistical tests that identify which of the three explanatory models fits best would be a useful adjunct to the use of theory alone. The present article introduces one such statistical method, direction dependence analysis (DDA), which assesses the relative plausibility of the three explanatory models on the basis of higher-moment information about the variables (i.e., skewness and kurtosis). DDA involves the evaluation of three properties of the data: (1) the observed distributions of the variables, (2) the residual distributions of the competing models, and (3) the independence properties of the predictors and residuals of the competing models. When the observed variables are nonnormally distributed, we show that DDA components can be used to uniquely identify each explanatory model. Statistical inference methods for model selection are presented, and macros to implement DDA in SPSS are provided. An empirical example is given to illustrate the approach. Conceptual and empirical considerations are discussed for best-practice applications in psychological data, and sample size recommendations based on previous simulation studies are provided.

Body Fat Percentage Prediction Using Intelligent Hybrid Approaches

PubMed Central

Shao, Yuehjen E.

2014-01-01

Excess of body fat often leads to obesity. Obesity is typically associated with serious medical diseases, such as cancer, heart disease, and diabetes. Accordingly, knowing the body fat is an extremely important issue since it affects everyone's health. Although there are several ways to measure the body fat percentage (BFP), the accurate methods are often associated with hassle and/or high costs. Traditional single-stage approaches may use certain body measurements or explanatory variables to predict the BFP. Diverging from existing approaches, this study proposes new intelligent hybrid approaches to obtain fewer explanatory variables, and the proposed forecasting models are able to effectively predict the BFP. The proposed hybrid models consist of multiple regression (MR), artificial neural network (ANN), multivariate adaptive regression splines (MARS), and support vector regression (SVR) techniques. The first stage of the modeling includes the use of MR and MARS to obtain fewer but more important sets of explanatory variables. In the second stage, the remaining important variables are served as inputs for the other forecasting methods. A real dataset was used to demonstrate the development of the proposed hybrid models. The prediction results revealed that the proposed hybrid schemes outperformed the typical, single-stage forecasting models. PMID:24723804

Independent contrasts and PGLS regression estimators are equivalent.

PubMed

Blomberg, Simon P; Lefevre, James G; Wells, Jessie A; Waterhouse, Mary

2012-05-01

We prove that the slope parameter of the ordinary least squares regression of phylogenetically independent contrasts (PICs) conducted through the origin is identical to the slope parameter of the method of generalized least squares (GLSs) regression under a Brownian motion model of evolution. This equivalence has several implications: 1. Understanding the structure of the linear model for GLS regression provides insight into when and why phylogeny is important in comparative studies. 2. The limitations of the PIC regression analysis are the same as the limitations of the GLS model. In particular, phylogenetic covariance applies only to the response variable in the regression and the explanatory variable should be regarded as fixed. Calculation of PICs for explanatory variables should be treated as a mathematical idiosyncrasy of the PIC regression algorithm. 3. Since the GLS estimator is the best linear unbiased estimator (BLUE), the slope parameter estimated using PICs is also BLUE. 4. If the slope is estimated using different branch lengths for the explanatory and response variables in the PIC algorithm, the estimator is no longer the BLUE, so this is not recommended. Finally, we discuss whether or not and how to accommodate phylogenetic covariance in regression analyses, particularly in relation to the problem of phylogenetic uncertainty. This discussion is from both frequentist and Bayesian perspectives.

Seasonally adjusted birth frequencies follow the Poisson distribution.

PubMed

Barra, Mathias; Lindstrøm, Jonas C; Adams, Samantha S; Augestad, Liv A

2015-12-15

Variations in birth frequencies have an impact on activity planning in maternity wards. Previous studies of this phenomenon have commonly included elective births. A Danish study of spontaneous births found that birth frequencies were well modelled by a Poisson process. Somewhat unexpectedly, there were also weekly variations in the frequency of spontaneous births. Another study claimed that birth frequencies follow the Benford distribution. Our objective was to test these results. We analysed 50,017 spontaneous births at Akershus University Hospital in the period 1999-2014. To investigate the Poisson distribution of these births, we plotted their variance over a sliding average. We specified various Poisson regression models, with the number of births on a given day as the outcome variable. The explanatory variables included various combinations of years, months, days of the week and the digit sum of the date. The relationship between the variance and the average fits well with an underlying Poisson process. A Benford distribution was disproved by a goodness-of-fit test (p < 0.01). The fundamental model with year and month as explanatory variables is significantly improved (p < 0.001) by adding day of the week as an explanatory variable. Altogether 7.5% more children are born on Tuesdays than on Sundays. The digit sum of the date is non-significant as an explanatory variable (p = 0.23), nor does it increase the explained variance. INERPRETATION: Spontaneous births are well modelled by a time-dependent Poisson process when monthly and day-of-the-week variation is included. The frequency is highest in summer towards June and July, Friday and Tuesday stand out as particularly busy days, and the activity level is at its lowest during weekends.

A FORTRAN program for multivariate survival analysis on the personal computer.

PubMed

Mulder, P G

1988-01-01

In this paper a FORTRAN program is presented for multivariate survival or life table regression analysis in a competing risks' situation. The relevant failure rate (for example, a particular disease or mortality rate) is modelled as a log-linear function of a vector of (possibly time-dependent) explanatory variables. The explanatory variables may also include the variable time itself, which is useful for parameterizing piecewise exponential time-to-failure distributions in a Gompertz-like or Weibull-like way as a more efficient alternative to Cox's proportional hazards model. Maximum likelihood estimates of the coefficients of the log-linear relationship are obtained from the iterative Newton-Raphson method. The program runs on a personal computer under DOS; running time is quite acceptable, even for large samples.

Variable conductance heat pipe technology

NASA Technical Reports Server (NTRS)

Marcus, B. D.; Edwards, D. K.; Anderson, W. T.

1973-01-01

Research and development programs in variable conductance heat pipe technology were conducted. The treatment has been comprehensive, involving theoretical and/or experimental studies in hydrostatics, hydrodynamics, heat transfer into and out of the pipe, fluid selection, and materials compatibility, in addition to the principal subject of variable conductance control techniques. Efforts were not limited to analytical work and laboratory experimentation, but extended to the development, fabrication and test of spacecraft hardware, culminating in the successful flight of the Ames Heat Pipe Experiment on the OAO-C spacecraft.

Mosaic, self-similarity logic, and biological attraction principles: three explanatory instruments in biology.

PubMed

Agnati, Luigi F; Baluska, Frantisek; Barlow, Peter W; Guidolin, Diego

2009-11-01

From a structural standpoint, living organisms are organized like a nest of Russian matryoshka dolls, in which structures are buried within one another. From a temporal point of view, this type of organization is the result of a history comprised of a set of time backcloths which have accompanied the passage of living matter from its origins up to the present day. The aim of the present paper is to indicate a possible course of this 'passage through time, and suggest how today's complexity has been reached by living organisms. This investigation will employ three conceptual tools, namely the Mosaic, Self-Similarity Logic, and the Biological Attraction principles. Self-Similarity Logic indicates the self-consistency by which elements of a living system interact, irrespective of the spatiotemporal level under consideration. The term Mosaic indicates how, from the same set of elements assembled according to different patterns, it is possible to arrive at completely different constructions: hence, each system becomes endowed with different emergent properties. The Biological Attraction principle states that there is an inherent drive for association and merging of compatible elements at all levels of biological complexity. By analogy with the gravitation law in physics, biological attraction is based on the evidence that each living organism creates an attractive field around itself. This field acts as a sphere of influence that actively attracts similar fields of other biological systems, thereby modifying salient features of the interacting organisms. Three specific organizational levels of living matter, namely the molecular, cellular, and supracellular levels, have been considered in order to analyse and illustrate the interpretative as well as the predictive roles of each of these three explanatory principles.

Relating brain signal variability to knowledge representation.

PubMed

Heisz, Jennifer J; Shedden, Judith M; McIntosh, Anthony R

2012-11-15

We assessed the hypothesis that brain signal variability is a reflection of functional network reconfiguration during memory processing. In the present experiments, we use multiscale entropy to capture the variability of human electroencephalogram (EEG) while manipulating the knowledge representation associated with faces stored in memory. Across two experiments, we observed increased variability as a function of greater knowledge representation. In Experiment 1, individuals with greater familiarity for a group of famous faces displayed more brain signal variability. In Experiment 2, brain signal variability increased with learning after multiple experimental exposures to previously unfamiliar faces. The results demonstrate that variability increases with face familiarity; cognitive processes during the perception of familiar stimuli may engage a broader network of regions, which manifests as higher complexity/variability in spatial and temporal domains. In addition, effects of repetition suppression on brain signal variability were observed, and the pattern of results is consistent with a selectivity model of neural adaptation. Crown Copyright © 2012. Published by Elsevier Inc. All rights reserved.

Processes Understanding of Decadal Climate Variability

NASA Astrophysics Data System (ADS)

Prömmel, Kerstin; Cubasch, Ulrich

2016-04-01

The realistic representation of decadal climate variability in the models is essential for the quality of decadal climate predictions. Therefore, the understanding of those processes leading to decadal climate variability needs to be improved. Several of these processes are already included in climate models but their importance has not yet completely been clarified. The simulation of other processes requires sometimes a higher resolution of the model or an extension by additional subsystems. This is addressed within one module of the German research program "MiKlip II - Decadal Climate Predictions" (http://www.fona-miklip.de/en/) with a focus on the following processes. Stratospheric processes and their impact on the troposphere are analysed regarding the climate response to aerosol perturbations caused by volcanic eruptions and the stratospheric decadal variability due to solar forcing, climate change and ozone recovery. To account for the interaction between changing ozone concentrations and climate a computationally efficient ozone chemistry module is developed and implemented in the MiKlip prediction system. The ocean variability and air-sea interaction are analysed with a special focus on the reduction of the North Atlantic cold bias. In addition, the predictability of the oceanic carbon uptake with a special emphasis on the underlying mechanism is investigated. This addresses a combination of physical, biological and chemical processes.

Decision-making and evaluation of science causal claims: Effects of goals on uses of evidence and explanatory mechanism

NASA Astrophysics Data System (ADS)

Wong, Jacqueline Yin Sang

2015-10-01

Evidence and explanatory mechanism are central to scientific practices. Using such information could also inform decisions about issues in which science can play some role, from policy issues like climate change to personal issues like vaccination. While research suggests that people tend to focus on non-science considerations when making science-related decisions, there is also evidence that people can reason very productively with evidence and mechanism. This study examines how the goals participants pursue when reading a science report influences how they attend to information about causal mechanism and evidence. Two hundred and seventeen high school students were asked either to evaluate the truth of a scientific claim, to make a personal decision based on the claim, or to make a social policy decision based on the claim using an online task-based survey. All three groups of participants attended to evidence and mechanism, but participants with different goals requested different types of information and were influenced by evidence and mechanism for different reasons. The findings suggest that goals influence how participants use evidence and mechanism.

Coping resources as explanatory factors of stress reactions during missile attacks: comparing Jewish and Arab adolescents in Israel.

PubMed

Braun-Lewensohn, Orna; Sagy, Shifra

2011-06-01

The aim of this study was to explore coping resources as explanatory factors in reducing emotional distress of adolescents in an acute stress situation. We compared two ethnic groups-Jewish and Arab-Bedouin Israelis-during intensive missile attacks in January 2009. Data were gathered from 138 Israeli-Jews and 84 Israeli-Arab Bedouins, 12-18 years old, who filled out self reported questionnaires among which state anxiety, state anger, and psychological distress (SPD) were measures of emotional distress, and sense of coherence (SOC) and hope index served as measures of coping resources. Findings indicated no differences between the two groups on state anxiety, SPD and hope levels. Arab Bedouins reported higher levels of state anger and lower levels of sense of coherence. The coping resources, however, explained the stress reactions differently among the two groups. While SOC made a major contribution in explaining stress reactions among Jewish adolescents, hope index explained stress reactions only for the Arab group. The findings are discussed against the background of the salutogenic theory and the cultural differences between the two ethnic groups.

How relevant is environmental quality to per capita health expenditures? Empirical evidence from panel of developing countries.

PubMed

Yahaya, Adamu; Nor, Norashidah Mohamed; Habibullah, Muzafar Shah; Ghani, Judhiana Abd; Noor, Zaleha Mohd

2016-01-01

Developing countries have witnessed economic growth as their GDP keeps increasing steadily over the years. The growth led to higher energy consumption which eventually leads to increase in air pollutions that pose a danger to human health. People's healthcare demand, in turn, increase due to the changes in the socioeconomic life and improvement in the health technology. This study is an attempt to investigate the impact of environmental quality on per capital health expenditure in 125 developing countries within a panel cointegration framework from 1995 to 2012. We found out that a long-run relationship exists between per capita health expenditure and all explanatory variables as they were panel cointegrated. The explanatory variables were found to be statistically significant in explaining the per capita health expenditure. The result further revealed that CO2 has the highest explanatory power on the per capita health expenditure. The impact of the explanatory power of the variables is greater in the long-run compared to the short-run. Based on this result, we conclude that environmental quality is a powerful determinant of health expenditure in developing countries. Therefore, developing countries should as a matter of health care policy give provision of healthy air a priority via effective policy implementation on environmental management and control measures to lessen the pressure on health care expenditure. Moreover more environmental proxies with alternative methods should be considered in the future research.

The Southern Hemisphere Additional Ozonesondes (SHADOZ) 1998-2002 Tropical Ozone Climatology. 3; Instrumentation and Station-to-Station Variability

NASA Technical Reports Server (NTRS)

Thompson, Anne M.; Witte, Jacqueline C.; Smit, Herman G. J.; Oltmans, Samuel J.; Johnson, Bryan J.; Kirchhoff, Volker W. J. H.; Schmidlin, Francis J.

2004-01-01

Abstract: Since 1998 the Southern Hemisphere ADditional OZonesondes (SHADOZ) project has collected more than 2000 ozone profiles from a dozen tropical and subtropical sites using balloon-borne electrochemical concentration cell (ECC) ozonesondes. The data (with accompanying pressure-temperature-humidity soundings) are archived. Analysis of ozonesonde imprecision within the SHADOZ dataset revealed that variations in ozonesonde technique could lead to station-to-station biases in the measurements. In this paper imprecisions and accuracy in the SHADOZ dataset are examined in light of new data. When SHADOZ total ozone column amounts are compared to version 8 TOMS (2004 release), discrepancies between sonde and satellite datasets decline 1-2 percentage points on average, compared to version 7 TOMS. Variability among stations is evaluated using total ozone normalized to TOMS and results of laboratory tests on ozonesondes (JOSE-2O00, Julich Ozonesonde Intercomparison Experiment). Ozone deviations from a standard instrument in the JOSE flight simulation chamber resemble those of SHADOZ station data relative to a SHADOZ-defined climatological reference. Certain systematic variations in SHADOZ ozone profiles are accounted for by differences in solution composition, data processing and instrument (manufacturer). Instrument bias leads to a greater ozone measurement above 25 km over Nairobi and to lower total column ozone at three Pacific sites compared to other SHADOZ stations at 0-20 deg.S.

Nutrition as an important mediator of the impact of background variables on outcome in middle childhood

PubMed Central

Kitsao-Wekulo, Patricia; Holding, Penny; Taylor, H. Gerry; Abubakar, Amina; Kvalsvig, Jane; Connolly, Kevin

2013-01-01

Adequate nutrition is fundamental to the development of a child's full potential. However, the extent to which malnutrition affects developmental and cognitive outcomes in the midst of co-occurring risk factors remains largely understudied. We sought to establish if the effects of nutritional status varied according to diverse background characteristics as well as to compare the relative strength of the effects of poor nutritional status on language skills, motor abilities, and cognitive functioning at school age. This cross-sectional study was conducted among school-age boys and girls resident in Kilifi District in Kenya. We hypothesized that the effects of area of residence, school attendance, household wealth, age and gender on child outcomes are experienced directly and indirectly through child nutritional status. The use of structural equation modeling (SEM) allowed the disaggregation of the total effect of the explanatory variables into direct effects (effects that go directly from one variable to another) and indirect effects. Each of the models tested for the four child outcomes had a good fit. However, the effects on verbal memory apart from being weaker than for the other outcomes, were not mediated through nutritional status. School attendance was the most influential predictor of nutritional status and child outcomes. The estimated models demonstrated the continued importance of child nutritional status at school-age. PMID:24298246

Measurement variability error for estimates of volume change

Treesearch

James A. Westfall; Paul L. Patterson

2007-01-01

Using quality assurance data, measurement variability distributions were developed for attributes that affect tree volume prediction. Random deviations from the measurement variability distributions were applied to 19381 remeasured sample trees in Maine. The additional error due to measurement variation and measurement bias was estimated via a simulation study for...

Long-term change in a behavioural trait: truncated spawning distribution and demography in Northeast Arctic cod.

PubMed

Opdal, Anders Frugård; Jørgensen, Christian

2015-04-01

Harvesting may be a potent driver of demographic change and contemporary evolution, which both may have great impacts on animal populations. Research has focused on changes in phenotypic traits that are easily quantifiable and for which time series exist, such as size, age, sex, or gonad size, whereas potential changes in behavioural traits have been under-studied. Here, we analyse potential drivers of long-term changes in a behavioural trait for the Northeast Arctic stock of Atlantic cod Gadus morhua, namely choice of spawning location. For 104 years (1866-1969), commercial catches were recorded annually and reported by county along the Norwegian coast. During this time period, spawning ground distribution has fluctuated with a trend towards more northerly spawning. Spawning location is analysed against a suite of explanatory factors including climate, fishing pressure, density dependence, and demography. We find that demography (age or age at maturation) had the highest explanatory power for variation in spawning location, while climate had a limited effect below statistical significance. As to potential mechanisms, some effects of climate may act through demography, and explanatory variables for demography may also have absorbed direct evolutionary change in migration distance for which proxies were unavailable. Despite these caveats, we argue that fishing mortality, either through demographic or evolutionary change, has served as an effective driver for changing spawning locations in cod, and that additional explanatory factors related to climate add no significant information. © 2014 The Authors. Global Change Biology Published by John Wiley & Sons Ltd.

Explanatory model of help-seeking and coping mechanisms among depressed women in three ethnic groups of Fars, Kurdish, and Turkish in Iran.

PubMed

Dejman, Masoumeh; Ekblad, Solvig; Forouzan, Ameneh-Setareh; Baradaran-Eftekhari, Monir; Malekafzali, Hossein

2008-07-01

As one of the most prevalent diseases globally and as an important cause of disability, depressive disorders are responsible for as many as one in every five visits to primary care doctors. Cultural variations in clinical presentation, sometimes make it difficult to recognize the disorder resulting in patients not being diagnosed and not receiving appropriate treatment. To address this issue, we conducted a qualitative pilot study on three ethnic groups including Fars, Kurdish, and Turkish in Iran to test the use of qualitative methods in exploring the explanatory models of help-seeking and coping with depression (without psychotic feature) among Iranian women. A qualitative study design was used based on an explanatory model of illness framework. Individual interviews were conducted with key informant (n=6), and depressed female patients (n=6). A hypothetical case vignette was also used in focus group discussions and individual interviews with lay people (three focus groups including 25 participants and six individual interviews; n=31). There were a few differences regarding help-seeking and coping mechanisms among the three ethnic groups studied. The most striking differences were in the area of treatment. Non-psychotic depressive disorder in all ethnicities was related to an external stressor, and symptoms of illness were viewed as a response to an event in the social world. Coping mechanisms involved two strategies: (1) solving problems by seeking social support from family and neighbors, religious practice, and engaging in pleasurable activities, and (2) seeking medical support from psychologists and family counselors. The Fars group was far more likely to recommend professional treatment and visiting psychiatrists whereas the other two ethnic groups (i.e., Turks and Kurds) preferred to consult family counselors, psychologists or other alternative care providers, and traditional healers. The study has educational and clinical implications. Cultural reframing

Impact of advanced monitoring variables on intraoperative clinical decision-making: an international survey.

PubMed

Joosten, Alexandre; Desebbe, Olivier; Suehiro, Koichi; Essiet, Mfonobong; Alexander, Brenton; Ricks, Cameron; Rinehart, Joseph; Faraoni, David; Cecconi, Maurizio; Van der Linden, Philippe; Cannesson, Maxime

2017-02-01

To assess the relationship between the addition of advanced monitoring variables and changes in clinical decision-making. A 15-questions survey was anonymously emailed to international experts and physician members of five anesthesia societies which focused on assessing treatment decisions of clinicians during three realistic clinical scenarios measured at two distinct time points. The first is when typical case information and basic monitoring (T1) were provided, and then once again after the addition of advanced monitoring variables (T2). We hypothesized that the addition of advanced variables would increase the incidence of an optimal therapeutic decision (a priori defined as the answer with the highest percentage of expert agreement) and decrease the variability among the physician's suggested treatments. The survey was completed by 18 experts and 839 physicians. Overall, adding advanced monitoring did not significantly increase physician response accuracy, with the least substantial changes noted on questions related to volume expansion or vasopressor administration. Moreover, advanced monitoring data did not significantly decrease the high level of initial practice variability in physician suggested treatments (P = 0.13), in contrast to the low variability observed within the expert group (P = 0.039). Additionally, 5-10 years of practice (P < 0.0001) and a cardiovascular subspecialty (P = 0.048) were both physician characteristics associated with a higher rate of optimal therapeutic decisions. The addition of advanced variables was of limited benefit for most physicians, further indicating the need for more in depth education on the clinical value and technical understanding of such variables.

What variables should be considered in allocating Primary health care Pharmaceutical budgets to districts in Uganda?

PubMed

Mujasi, Paschal N; Puig-Junoy, Jaume

2015-01-01

A key policy question for the government of Uganda is how to equitably allocate primary health care pharmaceutical budgets to districts. This paper seeks to identify variables influencing current primary health care pharmaceutical expenditure and their usefulness in allocating prospective pharmaceutical budgets to districts. This was a cross sectional, retrospective observational study using secondary administrative data. We collected data on the value of pharmaceuticals procured by primary health care facilities in each district from National Medical Stores for the financial year 2011/2012. The dependent variable was expressed as per capita district pharmaceutical expenditure. By reviewing literature we identified 26 potential explanatory variables. They include supply, need and demand, and health system organization variables that may influence the demand and supply of health services and the corresponding pharmaceutical expenditure. We collected secondary data for these variables for all the districts in Uganda (n = 112). We performed econometric analysis to estimate parameters of various regression models. There is a significant correlation between per capita district pharmaceutical expenditure and total district population, rural poverty, access to drinking water and outpatient department (OPD) per capita utilisation.(P < 0.01). The percentage of health centre IIIs (HC III) among each district's health facilities is significantly correlated with per capita pharmaceutical expenditure (P < 0.05). OPD per capita utilisation has a relatively strong correlation with per capita pharmaceutical expenditure (r = 0.498); all the other significant factors are weakly correlated with per capita pharmaceutical expenditure (r < 0.5). From several iterations of an initially developed model, the proposed final model for explaining per capita pharmaceutical expenditure explains about 53% of the variation in pharmaceutical expenditure among districts in

Partition Coefficients of Organics between Water and Carbon Dioxide Revisited: Correlation with Solute Molecular Descriptors and Solvent Cohesive Properties.

PubMed

Roth, Michal

2016-12-06

High-pressure phase behavior of systems containing water, carbon dioxide and organics has been important in several environment- and energy-related fields including carbon capture and storage, CO 2 sequestration and CO 2 -assisted enhanced oil recovery. Here, partition coefficients (K-factors) of organic solutes between water and supercritical carbon dioxide have been correlated with extended linear solvation energy relationships (LSERs). In addition to the Abraham molecular descriptors of the solutes, the explanatory variables also include the logarithm of solute vapor pressure, the solubility parameters of carbon dioxide and water, and the internal pressure of water. This is the first attempt to include also the properties of water as explanatory variables in LSER correlations of K-factor data in CO 2 -water-organic systems. Increasing values of the solute hydrogen bond acidity, the solute hydrogen bond basicity, the solute dipolarity/polarizability, the internal pressure of water and the solubility parameter of water all tend to reduce the K-factor, that is, to favor the solute partitioning to the water-rich phase. On the contrary, increasing values of the solute characteristic volume, the solute vapor pressure and the solubility parameter of CO 2 tend to raise the K-factor, that is, to favor the solute partitioning to the CO 2 -rich phase.

Socio-demographic, health, and tinnitus related variables affecting tinnitus severity.

PubMed

Hoekstra, Carlijn E L; Wesdorp, Francina M; van Zanten, Gijsbert A

2014-01-01

Tinnitus is a highly prevalent symptom with potential severe morbidity. Fortunately, only a small proportion of the population experience problems due to their tinnitus in such a degree that it adversely affects their quality of life (clinically significant tinnitus). It is not known why these individuals develop more burden from tinnitus. It seems likely that the severity of tinnitus can be influenced by different factors, such as socio-demographic or tinnitus characteristics or additional health complaints. It remains unclear from the current literature as to what are the main independent variables that have a bearing on tinnitus severity. This study addresses this problem by investigating variables previously described in the literature as well as additional variables. The aim of this study is to identify socio-demographic, health, and tinnitus variables that independently relate to tinnitus severity the most. This is a retrospective cohort study performed at the Tinnitus Care Group of the University Medical Center, Utrecht, in 309 consecutively seen chronic tinnitus patients. At this care group, patients are examined according to a structured diagnostic protocol, including history-taking by an otorhinolaryngologist and audiologist, physical examination, and audiometry. Based on results from previous research and theoretical considerations, a subset of data acquired through this diagnostic protocol were selected and used in this study. Univariate and multivariate correlations with tinnitus severity were investigated for 28 socio-demographic, health, and tinnitus variables. Tinnitus severity was measured with the Tinnitus Questionnaire (TQ) and the Tinnitus Handicap Inventory (THI). Eighteen variables related univariately with the TQ and 16 variables related univariately with the THI. Among these, 14 variables related univariately with both the TQ and the THI. Multivariate analyses showed three variables with an independent significant effect on both the TQ and

Deconstructed transverse mass variables

DOE PAGES

Ismail, Ahmed; Schwienhorst, Reinhard; Virzi, Joseph S.; ...

2015-04-02

Traditional searches for R-parity conserving natural supersymmetry (SUSY) require large transverse mass and missing energy cuts to separate the signal from large backgrounds. SUSY models with compressed spectra inherently produce signal events with small amounts of missing energy that are hard to explore. We use this difficulty to motivate the construction of "deconstructed" transverse mass variables which are designed preserve information on both the norm and direction of the missing momentum. Here, we demonstrate the effectiveness of these variables in searches for the pair production of supersymmetric top-quark partners which subsequently decay into a final state with an isolated lepton,more » jets and missing energy. We show that the use of deconstructed transverse mass variables extends the accessible compressed spectra parameter space beyond the region probed by traditional methods. The parameter space can further be expanded to neutralino masses that are larger than the difference between the stop and top masses. In addition, we also discuss how these variables allow for novel searches of single stop production, in order to directly probe unconstrained stealth stops in the small stop-and neutralino-mass regime. We also demonstrate the utility of these variables for generic gluino and stop searches in all-hadronic final states. Overall, we demonstrate that deconstructed transverse variables are essential to any search wanting to maximize signal separation from the background when the signal has undetected particles in the final state.« less

Year-class formation of upper St. Lawrence River northern pike

USGS Publications Warehouse

Smith, B.M.; Farrell, J.M.; Underwood, H.B.; Smith, S.J.

2007-01-01

Variables associated with year-class formation in upper St. Lawrence River northern pike Esox lucius were examined to explore population trends. A partial least-squares (PLS) regression model (PLS 1) was used to relate a year-class strength index (YCSI; 1974-1997) to explanatory variables associated with spawning and nursery areas (seasonal water level and temperature and their variability, number of ice days, and last day of ice presence). A second model (PLS 2) incorporated four additional ecological variables: potential predators (abundance of double-crested cormorants Phalacrocorax auritus and yellow perch Perca flavescens), female northern pike biomass (as a measure of stock-recruitment effects), and total phosphorus (productivity). Trends in adult northern pike catch revealed a decline (1981-2005), and year-class strength was positively related to catch per unit effort (CPUE; R2 = 0.58). The YCSI exceeded the 23-year mean in only 2 of the last 10 years. Cyclic patterns in the YCSI time series (along with strong year-classes every 4-6 years) were apparent, as was a dampening effect of amplitude beginning around 1990. The PLS 1 model explained over 50% of variation in both explanatory variables and the dependent variable, YCSI first-order moving-average residuals. Variables retained (N = 10; Wold's statistic ??? 0.8) included negative YCSI associations with high summer water levels, high variability in spring and fall water levels, and variability in fall water temperature. The YCSI exhibited positive associations with high spring, summer, and fall water temperature, variability in spring temperature, and high winter and spring water level. The PLS 2 model led to positive YCSI associations with phosphorus and yellow perch CPUE and a negative correlation with double-crested cormorant abundance. Environmental variables (water level and temperature) are hypothesized to regulate northern pike YCSI cycles, and dampening in YCSI magnitude may be related to a

Incomes, Attitudes, and Occurrences of Invasive Species: An Application to Signal Crayfish in Sweden

NASA Astrophysics Data System (ADS)

Gren, Ing-Marie; Campos, Monica; Edsman, Lennart; Bohman, Patrik

2009-02-01

This article analyzes and carries out an econometric test of the explanatory power of economic and attitude variables for occurrences of the nonnative signal crayfish in Swedish waters. Signal crayfish are a carrier of plague which threatens the native noble crayfish with extinction. Crayfish are associated with recreational and cultural traditions in Sweden, which may run against environmental preferences for preserving native species. Econometric analysis is carried out using panel data at the municipality level with economic factors and attitudes as explanatory variables, which are derived from a simple dynamic harvesting model. A log-normal model is used for the regression analysis, and the results indicate significant impacts on occurrences of waters with signal crayfish of changes in both economic and attitude variables. Variables reflecting environmental and recreational preferences have unexpected signs, where the former variable has a positive and the latter a negative impact on occurrences of waters with signal crayfish. These effects are, however, counteracted by their respective interaction effect with income.

Unravelling the spirits’ message: a study of help-seeking steps and explanatory models among patients suffering from spirit possession in Uganda

PubMed Central

2014-01-01

As in many cultures, also in Uganda spirit possession is a common idiom of distress associated with traumatic experiences. In the DSM-IV and -5, possession trance disorders can be classified as dissociative disorders. Dissociation in Western countries is associated with complicated, time-consuming and costly therapies. Patients with spirit possession in SW Uganda, however, often report partial or full recovery after treatment by traditional healers. The aim of this study is to explore how the development of symptoms concomitant help-seeking steps, and explanatory models (EM) eventually contributed to healing of patients with spirit possession in SW Uganda. Illness narratives of 119 patients with spirit possession referred by traditional healers were analysed using a mixed-method approach. Treatments of two-thirds of the patients were unsuccessful when first seeking help in the medical sector. Their initially physical symptoms subsequently developed into dissociative possession symptoms. After an average of two help-seeking steps, patients reached a healing place where 99% of them found satisfactory EM and effective healing. During healing sessions, possessing agents were summoned to identify themselves and underlying problems were addressed. Often-mentioned explanations were the following: neglect of rituals and of responsibilities towards relatives and inheritance, the call to become a healer, witchcraft, grief, and land conflicts. The results demonstrate that traditional healing processes of spirit possession can play a role in restoring connections with the supra-, inter-, intra-, and extra-human worlds. It does not always seem necessary to address individual traumatic experiences per se, which is in line with other research in this field. The study leads to additional perspectives on treatment of trauma-related dissociation in Western countries and on developing effective mental health services in low -and middle-income countries. PMID:24940355

Unravelling the spirits' message: a study of help-seeking steps and explanatory models among patients suffering from spirit possession in Uganda.

PubMed

van Duijl, Marjolein; Kleijn, Wim; de Jong, Joop

2014-01-01

As in many cultures, also in Uganda spirit possession is a common idiom of distress associated with traumatic experiences. In the DSM-IV and -5, possession trance disorders can be classified as dissociative disorders. Dissociation in Western countries is associated with complicated, time-consuming and costly therapies. Patients with spirit possession in SW Uganda, however, often report partial or full recovery after treatment by traditional healers. The aim of this study is to explore how the development of symptoms concomitant help-seeking steps, and explanatory models (EM) eventually contributed to healing of patients with spirit possession in SW Uganda. Illness narratives of 119 patients with spirit possession referred by traditional healers were analysed using a mixed-method approach. Treatments of two-thirds of the patients were unsuccessful when first seeking help in the medical sector. Their initially physical symptoms subsequently developed into dissociative possession symptoms. After an average of two help-seeking steps, patients reached a healing place where 99% of them found satisfactory EM and effective healing. During healing sessions, possessing agents were summoned to identify themselves and underlying problems were addressed. Often-mentioned explanations were the following: neglect of rituals and of responsibilities towards relatives and inheritance, the call to become a healer, witchcraft, grief, and land conflicts. The results demonstrate that traditional healing processes of spirit possession can play a role in restoring connections with the supra-, inter-, intra-, and extra-human worlds. It does not always seem necessary to address individual traumatic experiences per se, which is in line with other research in this field. The study leads to additional perspectives on treatment of trauma-related dissociation in Western countries and on developing effective mental health services in low -and middle-income countries.

Effects of poor asthma control, insomnia, anxiety and depression on quality of life in young asthmatics.

PubMed

Sundbom, Fredrik; Malinovschi, Andrei; Lindberg, Eva; Alving, Kjell; Janson, Christer

2016-01-01

Asthma-related quality of life has previously been shown to be associated with asthma control. The aims of the present study were to further analyze this correlation, identify other variables with impact on asthma-related quality of life and investigate the covariance among these variables. Information was retrieved from a cohort of 369 patients, aged 12-35, with physician-diagnosed asthma requiring anti-inflammatory treatment for at least 3 months per year. Questionnaire data [including the mini-Asthma Quality of Life Questionnaire (mAQLQ), asthma control test (ACT) and Hospital Anxiety and Depression Scale (HADS)], quality of sleep, lung function data and blood samples were analyzed. Linear regression models with the mAQLQ score as the dependent scalar variable were calculated. ACT was the single variable that had the highest explanatory value for the mAQLQ score (51.5%). High explanatory power was also observed for anxiety and depression (17.0%) and insomnia (14.1%). The population was divided into groups depending on the presence of anxiety and depression, uncontrolled asthma and insomnia. The group that reported none of these conditions had the highest mean mAQLQ score (6.3 units), whereas the group reporting all of these conditions had the lowest mAQLQ score (3.8 units). The ACT score was the single most important variable in predicting asthma-related quality of life. Combining the ACT score with the data on insomnia, anxiety and depression showed considerable additive effects of the conditions. Hence, we recommend the routine use of the ACT and careful attention to symptoms of insomnia, anxiety or depression in the clinical evaluation of asthma-related quality of life.

A successful backward step correlates with hip flexion moment of supporting limb in elderly people.

PubMed

Takeuchi, Yahiko

2018-01-01

The objective of this study was to determine the positional relationship between the center of mass (COM) and the center of pressure (COP) at the time of step landing, and to examine their relationship with the joint moments exerted by the supporting limb, with regard to factors of the successful backward step response. The study population comprised 8 community-dwelling elderly people that were observed to take successive multi steps after the landing of a backward stepping. Using a motion capture system and force plate, we measured the COM, COP and COM-COP deviation distance on landing during backward stepping. In addition, we measured the moment of the supporting limb joint during backward stepping. The multi-step data were compared with data from instances when only one step was taken (single-step). Variables that differed significantly between the single- and multi-step data were used as objective variables and the joint moments of the supporting limb were used as explanatory variables in single regression analyses. The COM-COP deviation in the anteroposterior was significantly larger in the single-step. A regression analysis with COM-COP deviation as the objective variable obtained a significant regression equation in the hip flexion moment (R2 = 0.74). The hip flexion moment of supporting limb was shown to be a significant explanatory variable in both the PS and SS phases for the relationship with COM-COP distance. This study found that to create an appropriate backward step response after an external disturbance (i.e. the ability to stop after 1 step), posterior braking of the COM by a hip flexion moment are important during the single-limbed standing phase.

The role of mass media in adolescents' sexual behaviors: exploring the explanatory value of the three-step self-objectification process.

PubMed

Vandenbosch, Laura; Eggermont, Steven

2015-04-01

This longitudinal study (N = 730) explored whether the three-step process of self-objectification (internalization of appearance ideals, valuing appearance over competence, and body surveillance) could explain the influence of sexual media messages on adolescents' sexual behaviors. A structural equation model showed that reading sexualizing magazines (Time 1) was related to the internalization of appearance ideals and valuing appearance over competence (Time 2). In turn, the internalization of appearance ideals was positively associated with body surveillance and valuing appearance over competence (all at Time 2). Valuing appearance over competence was also positively associated with body surveillance (all at Time 2). Lastly, body surveillance (Time 2) positively related to the initiation of French kissing (Time 3) whereas valuing appearance over competence (Time 2) positively related to the initiation of sexual intercourse (Time 3). No significant relationship was observed for intimate touching. The discussion focused on the explanatory role of self-objectification in media effects on adolescents' sexual behaviors.

Learning genetic inquiry through the use, revision, and justification of explanatory models

NASA Astrophysics Data System (ADS)

Cartier, Jennifer Lorraine

Central to the process of inquiry in science is the construction and assessment of models that can be used to explain (and in some cases, predict) natural phenomena. This dissertation is a qualitative study of student learning in a high school biology course that was designed to give students opportunities to learn about genetic inquiry in part by providing them with authentic experiences doing inquiry in the discipline. With the aid of a computer program that generates populations of "fruit flies", the students in this class worked in groups structured like scientific communities to build, revise, and defend explanatory models for various inheritance phenomena. Analysis of the ways in which the first cohort of students assessed their inheritance models revealed that all students assessed models based upon empirical fit (data/model match). However, in contrast to the practice of scientists and despite explicit instruction, students did not consistently apply conceptual assessment criteria to their models. That is, they didn't seek consistency between underlying concepts or processes in their models and those of other important genetic models, such as meiosis. This is perhaps in part because they lacked an understanding of models as conceptual rather than physical entities. Subsequently, the genetics curriculum was altered in order to create more opportunities for students to address epistemological issues associated with model assessment throughout the course. The second cohort of students' understanding of models changed over the nine-week period: initially the majority of students equated scientific models with "proof" (generally physical) of "theories"; at the end of the course, most students demonstrated understanding of the conceptual nature of scientific models and the need to justify such knowledge according to both its empirical utility and conceptual consistency. Through model construction and assessment (i.e. scientific inquiry), students were able to

Explaining the sense of family coherence among husbands and wives: the Israeli case.

PubMed

Kulik, Liat

2009-12-01

This study examined variables belonging to the family environment that explain the sense of family coherence among husbands (n = 133) and wives (n = 133) in Israel. Specifically, the explanatory variables tested were spousal power relations (as expressed in equality in the division of household labor and decision making), and perceived family conflict. In general, the sense of family coherence among spouses was found to be high. Perceived family conflict contributed to explaining the sense of family coherence for both husbands and wives. Equality in the division of household labor and in decision making had a greater impact on husbands than wives. Family coherence correlated negatively with age for husbands and positively with income for wives. The explanatory variables had a greater impact on the sense of family coherence among husbands than among wives.

Some difficulties and inconsistencies when using habit strength and reasoned action variables in models of metered household water conservation.

PubMed

Jorgensen, Bradley S; Martin, John F; Pearce, Meryl; Willis, Eileen

2013-01-30

Research employing household water consumption data has sought to test models of water demand and conservation using variables from attitude theory. A significant, albeit unrecognised, challenge has been that attitude models describe individual-level motivations while consumption data is recorded at the household level thereby creating inconsistency between units of theory and measurement. This study employs structural equation modelling and moderated regression techniques to addresses the level of analysis problem, and tests hypotheses by isolating effects on water conservation in single-person households. Furthermore, the results question the explanatory utility of habit strength, perceived behavioural control, and intentions for understanding metered water conservation in single-person households. For example, evidence that intentions predict water conservation or that they interact with habit strength in single-person households was contrary to theoretical expectations. On the other hand, habit strength, self-reports of past water conservation, and perceived behavioural control were good predictors of intentions to conserve water. Copyright © 2012 Elsevier Ltd. All rights reserved.

An Integrated Method to Analyze Farm Vulnerability to Climatic and Economic Variability According to Farm Configurations and Farmers' Adaptations.

PubMed

Martin, Guillaume; Magne, Marie-Angélina; Cristobal, Magali San

2017-01-01

The need to adapt to decrease farm vulnerability to adverse contextual events has been extensively discussed on a theoretical basis. We developed an integrated and operational method to assess farm vulnerability to multiple and interacting contextual changes and explain how this vulnerability can best be reduced according to farm configurations and farmers' technical adaptations over time. Our method considers farm vulnerability as a function of the raw measurements of vulnerability variables (e.g., economic efficiency of production), the slope of the linear regression of these measurements over time, and the residuals of this linear regression. The last two are extracted from linear mixed models considering a random regression coefficient (an intercept common to all farms), a global trend (a slope common to all farms), a random deviation from the general mean for each farm, and a random deviation from the general trend for each farm. Among all possible combinations, the lowest farm vulnerability is obtained through a combination of high values of measurements, a stable or increasing trend and low variability for all vulnerability variables considered. Our method enables relating the measurements, trends and residuals of vulnerability variables to explanatory variables that illustrate farm exposure to climatic and economic variability, initial farm configurations and farmers' technical adaptations over time. We applied our method to 19 cattle (beef, dairy, and mixed) farms over the period 2008-2013. Selected vulnerability variables, i.e., farm productivity and economic efficiency, varied greatly among cattle farms and across years, with means ranging from 43.0 to 270.0 kg protein/ha and 29.4-66.0% efficiency, respectively. No farm had a high level, stable or increasing trend and low residuals for both farm productivity and economic efficiency of production. Thus, the least vulnerable farms represented a compromise among measurement value, trend, and variability of

An Integrated Method to Analyze Farm Vulnerability to Climatic and Economic Variability According to Farm Configurations and Farmers’ Adaptations

PubMed Central

Martin, Guillaume; Magne, Marie-Angélina; Cristobal, Magali San

2017-01-01

The need to adapt to decrease farm vulnerability to adverse contextual events has been extensively discussed on a theoretical basis. We developed an integrated and operational method to assess farm vulnerability to multiple and interacting contextual changes and explain how this vulnerability can best be reduced according to farm configurations and farmers’ technical adaptations over time. Our method considers farm vulnerability as a function of the raw measurements of vulnerability variables (e.g., economic efficiency of production), the slope of the linear regression of these measurements over time, and the residuals of this linear regression. The last two are extracted from linear mixed models considering a random regression coefficient (an intercept common to all farms), a global trend (a slope common to all farms), a random deviation from the general mean for each farm, and a random deviation from the general trend for each farm. Among all possible combinations, the lowest farm vulnerability is obtained through a combination of high values of measurements, a stable or increasing trend and low variability for all vulnerability variables considered. Our method enables relating the measurements, trends and residuals of vulnerability variables to explanatory variables that illustrate farm exposure to climatic and economic variability, initial farm configurations and farmers’ technical adaptations over time. We applied our method to 19 cattle (beef, dairy, and mixed) farms over the period 2008–2013. Selected vulnerability variables, i.e., farm productivity and economic efficiency, varied greatly among cattle farms and across years, with means ranging from 43.0 to 270.0 kg protein/ha and 29.4–66.0% efficiency, respectively. No farm had a high level, stable or increasing trend and low residuals for both farm productivity and economic efficiency of production. Thus, the least vulnerable farms represented a compromise among measurement value, trend, and

Quantitative predictions of streamflow variability in the Susquehanna River Basin

NASA Astrophysics Data System (ADS)

Alexander, R.; Boyer, E. W.; Leonard, L. N.; Duffy, C.; Schwarz, G. E.; Smith, R. A.

2012-12-01

Hydrologic researchers and water managers have increasingly sought an improved understanding of the major processes that control fluxes of water and solutes across diverse environmental settings and large spatial scales. Regional analyses of observed streamflow data have led to advances in our knowledge of relations among land use, climate, and streamflow, with methodologies ranging from statistical assessments of multiple monitoring sites to the regionalization of the parameters of catchment-scale mechanistic simulation models. However, gaps remain in our understanding of the best ways to transfer the knowledge of hydrologic response and governing processes among locations, including methods for regionalizing streamflow measurements and model predictions. We developed an approach to predict variations in streamflow using the SPARROW (SPAtially Referenced Regression On Watershed attributes) modeling infrastructure, with mechanistic functions, mass conservation constraints, and statistical estimation of regional and sub-regional parameters. We used the model to predict discharge in the Susquehanna River Basin (SRB) under varying hydrological regimes that are representative of contemporary flow conditions. The resulting basin-scale water balance describes mean monthly flows in stream reaches throughout the entire SRB (represented at a 1:100,000 scale using the National Hydrologic Data network), with water supply and demand components that are inclusive of a range of hydrologic, climatic, and cultural properties (e.g., precipitation, evapotranspiration, soil and groundwater storage, runoff, baseflow, water use). We compare alternative models of varying complexity that reflect differences in the number and types of explanatory variables and functional expressions as well as spatial and temporal variability in the model parameters. Statistical estimation of the models reveals the levels of complexity that can be uniquely identified, subject to the information content

Breastfeeding and the risk of childhood asthma: A two-stage instrumental variable analysis to address endogeneity.

PubMed

Sharma, Nivita D

2017-09-01

Several explanations for the inconsistent results on the effects of breastfeeding on childhood asthma have been suggested. The purpose of this study was to investigate one unexplored explanation, which is the presence of a potential endogenous relationship between breastfeeding and childhood asthma. Endogeneity exists when an explanatory variable is correlated with the error term for reasons such as selection bias, reverse causality, and unmeasured confounders. Unadjusted endogeneity will bias the effect of breastfeeding on childhood asthma. To investigate potential endogeneity, a cross-sectional study of breastfeeding practices and incidence of childhood asthma in 87 pediatric patients in Georgia, the USA, was conducted using generalized linear modeling and a two-stage instrumental variable analysis. First, the relationship between breastfeeding and childhood asthma was analyzed without considering endogeneity. Second, tests for presence of endogeneity were performed and having detected endogeneity between breastfeeding and childhood asthma, a two-stage instrumental variable analysis was performed. The first stage of this analysis estimated the duration of breastfeeding and the second-stage estimated the risk of childhood asthma. When endogeneity was not taken into account, duration of breastfeeding was found to significantly increase the risk of childhood asthma (relative risk ratio [RR]=2.020, 95% confidence interval [CI]: [1.143-3.570]). After adjusting for endogeneity, duration of breastfeeding significantly reduced the risk of childhood asthma (RR=0.003, 95% CI: [0.000-0.240]). The findings suggest that researchers should consider evaluating how the presence of endogeneity could affect the relationship between duration of breastfeeding and the risk of childhood asthma. © 2017 EAACI and John Wiley and Sons A/S. Published by John Wiley and Sons Ltd.

Variable & Recode Definitions - SEER Documentation

Cancer.gov

Resources that define variables and provide documentation for reporting using SEER and related datasets. Choose from SEER coding and staging manuals plus instructions for recoding behavior, site, stage, cause of death, insurance, and several additional topics. Also guidance on months survived, calculating Hispanic mortality, and site-specific surgery.

Marital Conflict in Early Childhood and Adolescent Disordered Eating: Emotional Insecurity about the Marital Relationship as an Explanatory Mechanism

PubMed Central

George, Melissa W.; Fairchild, Amanda J.; Cummings, E. Mark; Davies, Patrick T.

2017-01-01

Disordered eating behaviors, including frequent dieting, unhealthy weight control behaviors (e.g., vomiting and skipping meals for weight loss) and binge eating are prevalent among adolescents. While negative, conflict-ridden family environments have long been implicated as problematic and a contributing factor to the development of disordered eating, few studies have examined the influence of marital conflict exposure in childhood to understand the development of these behaviors in adolescence. The current study investigates the impact of marital conflict, children’s emotional insecurity about the marital relationship, and disordered eating behaviors in early adolescence in a prospective, longitudinal study of a community sample of 236 families in Midwest and Northeast regions of the U.S. Full structural mediation analyses utilizing robust latent constructs of marital conflict and emotional insecurity about the marital relationship, support children’s emotional insecurity as an explanatory mechanism for the influence of marital conflict on adolescent disordered eating behaviors. Findings are discussed with important implications for the long-term impact of marital conflict and the development of disordered eating in adolescence. PMID:25113902

Marital conflict in early childhood and adolescent disordered eating: emotional insecurity about the marital relationship as an explanatory mechanism.

PubMed

George, Melissa W; Fairchild, Amanda J; Mark Cummings, E; Davies, Patrick T

2014-12-01

Disordered eating behaviors, including frequent dieting, unhealthy weight control behaviors (e.g., vomiting and skipping meals for weight loss) and binge eating are prevalent among adolescents. While negative, conflict-ridden family environments have long been implicated as problematic and a contributing factor to the development of disordered eating, few studies have examined the influence of marital conflict exposure in childhood to understand the development of these behaviors in adolescence. The current study investigates the impact of marital conflict, children's emotional insecurity about the marital relationship, and disordered eating behaviors in early adolescence in a prospective, longitudinal study of a community sample of 236 families in Midwest and Northeast regions of the U.S. Full structural mediation analyses utilizing robust latent constructs of marital conflict and emotional insecurity about the marital relationship, support children's emotional insecurity as an explanatory mechanism for the influence of marital conflict on adolescent disordered eating behaviors. Findings are discussed with important implications for the long-term impact of marital conflict and the development of disordered eating in adolescence. Copyright © 2014 Elsevier Ltd. All rights reserved.

Why don't segregated Roma do more for their health? An explanatory framework from an ethnographic study in Slovakia.

PubMed

Belak, Andrej; Madarasova Geckova, Andrea; van Dijk, Jitse P; Reijneveld, Sijmen A

2018-06-16

The health status of segregated Roma is poor. To understand why segregated Roma engage in health-endangering practices, we explored their nonadherence to clinical and public health recommendations. We examined one segregated Roma settlement of 260 inhabitants in Slovakia. To obtain qualitative data on local-level mechanisms supporting Roma nonadherence, we combined ethnography and systematic interviewing over 10 years. We then performed a qualitative content analysis based on sociological and public health theories. Our explanatory framework summarizes how the nonadherence of local Roma was supported by an interlocked system of seven mechanisms, controlled by and operating through both local Roma and non-Roma. These regard the Roma situation of poverty, segregation and substandard infrastructure; the Roma socialization into their situation; the Roma-perceived value of Roma alternative practices; the exclusionary non-Roma and self-exclusionary Roma ideologies; the discrimination, racism and dysfunctional support towards Roma by non-Roma; and drawbacks in adherence. Non-Roma ideologies, internalized by Roma into a racialized ethnic identity through socialization, and drawbacks in adherence might present powerful, yet neglected, mechanisms supporting segregated Roma nonadherence.

The effects of spatial autoregressive dependencies on inference in ordinary least squares: a geometric approach

NASA Astrophysics Data System (ADS)

Smith, Tony E.; Lee, Ka Lok

2012-01-01

There is a common belief that the presence of residual spatial autocorrelation in ordinary least squares (OLS) regression leads to inflated significance levels in beta coefficients and, in particular, inflated levels relative to the more efficient spatial error model (SEM). However, our simulations show that this is not always the case. Hence, the purpose of this paper is to examine this question from a geometric viewpoint. The key idea is to characterize the OLS test statistic in terms of angle cosines and examine the geometric implications of this characterization. Our first result is to show that if the explanatory variables in the regression exhibit no spatial autocorrelation, then the distribution of test statistics for individual beta coefficients in OLS is independent of any spatial autocorrelation in the error term. Hence, inferences about betas exhibit all the optimality properties of the classic uncorrelated error case. However, a second more important series of results show that if spatial autocorrelation is present in both the dependent and explanatory variables, then the conventional wisdom is correct. In particular, even when an explanatory variable is statistically independent of the dependent variable, such joint spatial dependencies tend to produce "spurious correlation" that results in over-rejection of the null hypothesis. The underlying geometric nature of this problem is clarified by illustrative examples. The paper concludes with a brief discussion of some possible remedies for this problem.

The effect of topography on arctic-alpine aboveground biomass and NDVI patterns

NASA Astrophysics Data System (ADS)

Riihimäki, Henri; Heiskanen, Janne; Luoto, Miska

2017-04-01

Topography is a key factor affecting numerous environmental phenomena, including Arctic and alpine aboveground biomass (AGB) distribution. Digital Elevation Model (DEM) is a source of topographic information which can be linked to local growing conditions. Here, we investigated the effect of DEM derived variables, namely elevation, topographic position, radiation and wetness on AGB and Normalized Difference Vegetation Index (NDVI) in a Fennoscandian forest-alpine tundra ecotone. Boosted regression trees were used to derive non-parametric response curves and relative influences of the explanatory variables. Elevation and potential incoming solar radiation were the most important explanatory variables for both AGB and NDVI. In the NDVI models, the response curves were smooth compared with AGB models. This might be caused by large contribution of field and shrub layer to NDVI, especially at the treeline. Furthermore, radiation and elevation had a significant interaction, showing that the highest NDVI and biomass values are found from low-elevation, high-radiation sites, typically on the south-southwest facing valley slopes. Topographic wetness had minor influence on AGB and NDVI. Topographic position had generally weak effects on AGB and NDVI, although protected topographic position seemed to be more favorable below the treeline. The explanatory power of the topographic variables, particularly elevation and radiation demonstrates that DEM-derived land surface parameters can be used for exploring biomass distribution resulting from landform control on local growing conditions.

Modeling the cardiovascular system using a nonlinear additive autoregressive model with exogenous input

NASA Astrophysics Data System (ADS)

Riedl, M.; Suhrbier, A.; Malberg, H.; Penzel, T.; Bretthauer, G.; Kurths, J.; Wessel, N.

2008-07-01

The parameters of heart rate variability and blood pressure variability have proved to be useful analytical tools in cardiovascular physics and medicine. Model-based analysis of these variabilities additionally leads to new prognostic information about mechanisms behind regulations in the cardiovascular system. In this paper, we analyze the complex interaction between heart rate, systolic blood pressure, and respiration by nonparametric fitted nonlinear additive autoregressive models with external inputs. Therefore, we consider measurements of healthy persons and patients suffering from obstructive sleep apnea syndrome (OSAS), with and without hypertension. It is shown that the proposed nonlinear models are capable of describing short-term fluctuations in heart rate as well as systolic blood pressure significantly better than similar linear ones, which confirms the assumption of nonlinear controlled heart rate and blood pressure. Furthermore, the comparison of the nonlinear and linear approaches reveals that the heart rate and blood pressure variability in healthy subjects is caused by a higher level of noise as well as nonlinearity than in patients suffering from OSAS. The residue analysis points at a further source of heart rate and blood pressure variability in healthy subjects, in addition to heart rate, systolic blood pressure, and respiration. Comparison of the nonlinear models within and among the different groups of subjects suggests the ability to discriminate the cohorts that could lead to a stratification of hypertension risk in OSAS patients.

A New Variable Weighting and Selection Procedure for K-Means Cluster Analysis

ERIC Educational Resources Information Center

Steinley, Douglas; Brusco, Michael J.

2008-01-01

A variance-to-range ratio variable weighting procedure is proposed. We show how this weighting method is theoretically grounded in the inherent variability found in data exhibiting cluster structure. In addition, a variable selection procedure is proposed to operate in conjunction with the variable weighting technique. The performances of these…

Infrared spectroscopic monitoring of urea addition to oriented strandboard resins

Treesearch

Chi-Leung So; Thomas L. Eberhardt; Ernest Hsu; Brian K. Via; Chung Y. Hse

2007-01-01

One of the variables in phenol formaldehyde adhesive resin formulation is the addition of urea, which allows the resin manufacturer to manipulate both product functionality and cost. Nitrogen content can be used as a measure of the level of urea addition because most of the nitrogen present is derived from urea added at the end of the preparation process. Nitrogen...

The Catalina Surveys Southern periodic variable star catalogue

NASA Astrophysics Data System (ADS)

Drake, A. J.; Djorgovski, S. G.; Catelan, M.; Graham, M. J.; Mahabal, A. A.; Larson, S.; Christensen, E.; Torrealba, G.; Beshore, E.; McNaught, R. H.; Garradd, G.; Belokurov, V.; Koposov, S. E.

2017-08-01

Here, we present the results from our analysis of 6 yr of optical photometry taken by the Siding Spring Survey (SSS). This completes a search for periodic variable stars within the 30 000 deg2 of the sky covered by the Catalina Surveys. The current analysis covers 81 million sources with declinations between -20° and -75° with median magnitudes in the range 11 < V < 19.5. We find approximately 34 000 new periodic variable stars in addition to the ˜9000 RR Lyrae that we previously discovered in SSS data. This brings the total number of periodic variables identified in Catalina data to ˜110 000. The new SSS periodic variable stars mainly consist of eclipsing binaries, RR Lyrae, LPVs, RS CVn stars, δ Scutis, and Anomalous Cepheids. By cross-matching these variable stars with those from prior surveys, we find that ˜90 per cent of the sources are new discoveries and recover ˜95 per cent of the known periodic variables in the survey region. For the known sources, we find excellent agreement between our catalogue and prior values of luminosity, period, and amplitude. However, we find many variable stars that had previously been misclassified. Examining the distribution of RR Lyrae, we find a population associated with the Large Magellanic Cloud (LMC) that extends more than 20° from its centre confirming recent evidence for the existence of a very extended stellar halo in the LMC. By combining SSS photometry with Dark Energy Survey data, we identify additional LMC halo RR Lyrae, thus confirming the significance of the population.

Real-time predictive seasonal influenza model in Catalonia, Spain

PubMed Central

Basile, Luca; Oviedo de la Fuente, Manuel; Torner, Nuria; Martínez, Ana; Jané, Mireia

2018-01-01

Influenza surveillance is critical to monitoring the situation during epidemic seasons and predictive mathematic models may aid the early detection of epidemic patterns. The objective of this study was to design a real-time spatial predictive model of ILI (Influenza Like Illness) incidence rate in Catalonia using one- and two-week forecasts. The available data sources used to select explanatory variables to include in the model were the statutory reporting disease system and the sentinel surveillance system in Catalonia for influenza incidence rates, the official climate service in Catalonia for meteorological data, laboratory data and Google Flu Trend. Time series for every explanatory variable with data from the last 4 seasons (from 2010–2011 to 2013–2014) was created. A pilot test was conducted during the 2014–2015 season to select the explanatory variables to be included in the model and the type of model to be applied. During the 2015–2016 season a real-time model was applied weekly, obtaining the intensity level and predicted incidence rates with 95% confidence levels one and two weeks away for each health region. At the end of the season, the confidence interval success rate (CISR) and intensity level success rate (ILSR) were analysed. For the 2015–2016 season a CISR of 85.3% at one week and 87.1% at two weeks and an ILSR of 82.9% and 82% were observed, respectively. The model described is a useful tool although it is hard to evaluate due to uncertainty. The accuracy of prediction at one and two weeks was above 80% globally, but was lower during the peak epidemic period. In order to improve the predictive power, new explanatory variables should be included. PMID:29513710

Linking the Observation of Essential Variables to Societal Benefits

NASA Astrophysics Data System (ADS)

Sylak-Glassman, E.

2017-12-01

Different scientific communities have established sets of commonly agreed upon essential variables to help coordinate data collection in a variety of Earth observation areas. As an example, the World Meteorological Organization Global Climate Observing System has identified 50 Essential Climate Variables (ECVs), such as sea-surface temperature and carbon dioxide, which are required to monitoring the climate and detect and attribute climate change. In addition to supporting climate science, measuring these ECVs deliver many types of societal benefits, ranging from disaster mitigation to agricultural productivity to human health. While communicating the value in maintaining and improving observational records for these variables has been a challenge, quantifying how the measurement of these ECVs results in the delivery of many different societal benefits may help support their continued measurement. The 2016 National Earth Observation Assessment (EOA 2016) quantified the impact of individual Earth observation systems, sensors, networks, and surveys (or Earth observation systems, for short) on the achievement of 217 Federal objectives in 13 societal benefit areas (SBAs). This study will demonstrate the use of the EOA 2016 dataset to show the different Federal objectives and SBAs that are impacted by the Earth observation systems used to measure ECVs. Describing how the measurements from these Earth observation systems are used not only to maintain the climate record but also to meet additional Federal objectives may help articulate the continued measurement of the ECVs. This study will act as a pilot for the use of the EOA 2016 dataset to map between the measurements required to observe additional sets of variables, such as the Essential Ocean Variables and Essential Biodiversity Variables, and the ability to achieve a variety of societal benefits.

Variable dynamic testbed vehicle : safety plan

DOT National Transportation Integrated Search

1997-02-01

This safety document covers the entire safety process from inception to delivery of the Variable Dynamic Testbed Vehicle. In addition to addressing the process of safety on the vehicle , it should provide a basis on which to build future safety proce...

Waist Circumference Adjusted for Body Mass Index and Intra-Abdominal Fat Mass

PubMed Central

Berentzen, Tina Landsvig; Ängquist, Lars; Kotronen, Anna; Borra, Ronald; Yki-Järvinen, Hannele; Iozzo, Patricia; Parkkola, Riitta; Nuutila, Pirjo; Ross, Robert; Allison, David B.; Heymsfield, Steven B.; Overvad, Kim; Sørensen, Thorkild I. A.; Jakobsen, Marianne Uhre

2012-01-01

Background The association between waist circumference (WC) and mortality is particularly strong and direct when adjusted for body mass index (BMI). One conceivable explanation for this association is that WC adjusted for BMI is a better predictor of the presumably most harmful intra-abdominal fat mass (IAFM) than WC alone. We studied the prediction of abdominal subcutaneous fat mass (ASFM) and IAFM by WC alone and by addition of BMI as an explanatory factor. Methodology/Principal Findings WC, BMI and magnetic resonance imaging data from 742 men and women who participated in clinical studies in Canada and Finland were pooled. Total adjusted squared multiple correlation coefficients (R2) of ASFM and IAFM were calculated from multiple linear regression models with WC and BMI as explanatory variables. Mean BMI and WC of the participants in the pooled sample were 30 kg/m2 and 102 cm, respectively. WC explained 29% of the variance in ASFM and 51% of the variance in IAFM. Addition of BMI to WC added 28% to the variance explained in ASFM, but only 1% to the variance explained in IAFM. Results in subgroups stratified by study center, sex, age, obesity level and type 2 diabetes status were not systematically different. Conclusion/Significance The prediction of IAFM by WC is not improved by addition of BMI. PMID:22384179

New ways to analyze word generation performance in brain injury: A systematic review and meta-analysis of additional performance measures.

PubMed

Thiele, Kristina; Quinting, Jana Marie; Stenneken, Prisca

2016-09-01

The investigation of word generation performance is an accepted, widely used, and well-established method for examining cognitive, language, or communication impairment due to brain damage. The performance measure traditionally applied in the investigation of word generation is the number of correct responses. Previous studies, however, have suggested that this measure does not capture all potentially relevant aspects of word generation performance and hence its underlying processes, so that its analytical and explanatory power of word generation performance might be rather limited. Therefore, additional qualitative or quantitative performance measures have been introduced to gain information that goes beyond the deficit and allows for therapeutic implications. We undertook a systematic review and meta-analysis of original research that focused on the application of additional measures of word generation performance in adult clinical populations with acquired brain injury. Word generation tasks are an integral part of many different tests, but only few use additional performance measures in addition to the number of correct responses in the analysis of word generation performance. Additional measures, which showed increased or similar diagnostic utility relative to the traditional performance measure, regarded clustering and switching, error types, and temporal characteristics. The potential of additional performance measures is not yet fully exhausted in patients with brain injury. The temporal measure of response latencies in particular is not adequately represented, though it may be a reliable measure especially for identifying subtle impairments. Unfortunately, there is no general consensus as of yet on which additional measures are best suited to characterizing word generation performance. Further research is needed to specify the additional parameters that are best qualified for identifying and characterizing impaired word generation performance.

A Bayesian additive model for understanding public transport usage in special events.

PubMed

Rodrigues, Filipe; Borysov, Stanislav; Ribeiro, Bernardete; Pereira, Francisco

2016-12-02

Public special events, like sports games, concerts and festivals are well known to create disruptions in transportation systems, often catching the operators by surprise. Although these are usually planned well in advance, their impact is difficult to predict, even when organisers and transportation operators coordinate. The problem highly increases when several events happen concurrently. To solve these problems, costly processes, heavily reliant on manual search and personal experience, are usual practice in large cities like Singapore, London or Tokyo. This paper presents a Bayesian additive model with Gaussian process components that combines smart card records from public transport with context information about events that is continuously mined from the Web. We develop an efficient approximate inference algorithm using expectation propagation, which allows us to predict the total number of public transportation trips to the special event areas, thereby contributing to a more adaptive transportation system. Furthermore, for multiple concurrent event scenarios, the proposed algorithm is able to disaggregate gross trip counts into their most likely components related to specific events and routine behavior. Using real data from Singapore, we show that the presented model outperforms the best baseline model by up to 26% in R2 and also has explanatory power for its individual components.

Selecting a Variable for Predicting the Diagnosis of PTB Patients From Comparison of Chest X-ray Images

NASA Astrophysics Data System (ADS)

Mohd. Rijal, Omar; Mohd. Noor, Norliza; Teng, Shee Lee

A statistical method of comparing two digital chest radiographs for Pulmonary Tuberculosis (PTB) patients has been proposed. After applying appropriate image registration procedures, a selected subset of each image is converted to an image histogram (or box plot). Comparing two chest X-ray images is equivalent to the direct comparison of the two corresponding histograms. From each histogram, eleven percentiles (of image intensity) are calculated. The number of percentiles that shift to the left (NLSP) when second image is compared to the first has been shown to be an indicator of patients` progress. In this study, the values of NLSP is to be compared with the actual diagnosis (Y) of several medical practitioners. A logistic regression model is used to study the relationship between NLSP and Y. This study showed that NLSP may be used as an alternative or second opinion for Y. The proposed regression model also show that important explanatory variables such as outcomes of sputum test (Z) and degree of image registration (W) may be omitted when estimating Y-values.

A Systematic Search for Short-term Variability of EGRET Sources

NASA Technical Reports Server (NTRS)

Wallace, P. M.; Griffis, N. J.; Bertsch, D. L.; Hartman, R. C.; Thompson, D. J.; Kniffen, D. A.; Bloom, S. D.

2000-01-01

The 3rd EGRET Catalog of High-energy Gamma-ray Sources contains 170 unidentified sources, and there is great interest in the nature of these sources. One means of determining source class is the study of flux variability on time scales of days; pulsars are believed to be stable on these time scales while blazers are known to be highly variable. In addition, previous work has demonstrated that 3EG J0241-6103 and 3EG J1837-0606 are candidates for a new gamma-ray source class. These sources near the Galactic plane display transient behavior but cannot be associated with any known blazers. Although, many instances of flaring AGN have been reported, the EGRET database has not been systematically searched for occurrences of short-timescale (approximately 1 day) variability. These considerations have led us to conduct a systematic search for short-term variability in EGRET data, covering all viewing periods through proposal cycle 4. Six 3EG catalog sources are reported here to display variability on short time scales; four of them are unidentified. In addition, three non-catalog variable sources are discussed.

Mutilating Data and Discarding Variance: The Dangers of Dichotomizing Continuous Variables.

ERIC Educational Resources Information Center

Kroff, Michael W.

This paper reviews issues involved in converting continuous variables to nominal variables to be used in the OVA techniques. The literature dealing with the dangers of dichotomizing continuous variables is reviewed. First, the assumptions invoked by OVA analyses are reviewed in addition to concerns regarding the loss of variance and a reduction in…

Iterative Strain-Gage Balance Calibration Data Analysis for Extended Independent Variable Sets

NASA Technical Reports Server (NTRS)

Ulbrich, Norbert Manfred

2011-01-01

A new method was developed that makes it possible to use an extended set of independent calibration variables for an iterative analysis of wind tunnel strain gage balance calibration data. The new method permits the application of the iterative analysis method whenever the total number of balance loads and other independent calibration variables is greater than the total number of measured strain gage outputs. Iteration equations used by the iterative analysis method have the limitation that the number of independent and dependent variables must match. The new method circumvents this limitation. It simply adds a missing dependent variable to the original data set by using an additional independent variable also as an additional dependent variable. Then, the desired solution of the regression analysis problem can be obtained that fits each gage output as a function of both the original and additional independent calibration variables. The final regression coefficients can be converted to data reduction matrix coefficients because the missing dependent variables were added to the data set without changing the regression analysis result for each gage output. Therefore, the new method still supports the application of the two load iteration equation choices that the iterative method traditionally uses for the prediction of balance loads during a wind tunnel test. An example is discussed in the paper that illustrates the application of the new method to a realistic simulation of temperature dependent calibration data set of a six component balance.

Geographic trends in prostate cancer mortality: an application of spatial smoothers and the need for adjustment.

PubMed

Kafadar, K

1997-01-01

Prostate cancer mortality among whites and nonwhites in U.S. counties are analyzed for geographic effects. To better visualize geographical effects, the data are smoothed with a bivariate smoother using age-specific rates. Among nonwhites, an important explanatory variable is the proportion of African Americans. A relationship between the mortality rate and this variable is derived, and the data are adjusted for this variable using this relationship. When the rates are adjusted for age only, among whites there is a north-south gradient: rates are higher in the north, lower in the south. Among nonwhites, the gradient runs east to west: higher in the east, lower in the west. The latter gradient disappears when the rates are further adjusted for African Americans. The study reveals the importance of both smoothing the data to visualize patterns in geography and adjusting the data for an important variable to identify underlying patterns. The additional adjustment permits the identification of other areas of the country with elevated or depressed rates.

Variables Affecting Proficiency in English as a Second Language

ERIC Educational Resources Information Center

Santana, Josefina C.; García-Santillán, Arturo; Escalera-Chávez, Milka Elena

2017-01-01

This study explores different variables leading to proficiency in English as a second language. Level of English on a placement exam taken upon entering a private university in Mexico was correlated to several variables. Additionally, participants (N = 218) were asked their perception of their own proficiency. A linear regression and a one-factor…

Pupil Control Ideology and the Salience of Teacher Characteristics

ERIC Educational Resources Information Center

Smyth, W. J.

1977-01-01

The explanatory power of the combined biographical variables of teacher age, experience, sex, organizational status, and academic qualifications for variances in pupil control ideology (PCI) is seriously questioned, since as little as 6 percent of PCI variance may be explained by reference to these particular variables. (Author)

Progress with variable cycle engines

NASA Technical Reports Server (NTRS)

Westmoreland, J. S.

1980-01-01

The evaluation of components of an advanced propulsion system for a future supersonic cruise vehicle is discussed. These components, a high performance duct burner for thrust augmentation and a low jet noise coannular exhaust nozzle, are part of the variable stream control engine. An experimental test program involving both isolated component and complete engine tests was conducted for the high performance, low emissions duct burner with excellent results. Nozzle model tests were completed which substantiate the inherent jet noise benefit associated with the unique velocity profile possible of a coannular exhaust nozzle system on a variable stream control engine. Additional nozzle model performance tests have established high thrust efficiency levels at takeoff and supersonic cruise for this nozzle system. Large scale testing of these two critical components is conducted using an F100 engine as the testbed for simulating the variable stream control engine.

Generic Feature Selection with Short Fat Data

PubMed Central

Clarke, B.; Chu, J.-H.

2014-01-01

SUMMARY Consider a regression problem in which there are many more explanatory variables than data points, i.e., p ≫ n. Essentially, without reducing the number of variables inference is impossible. So, we group the p explanatory variables into blocks by clustering, evaluate statistics on the blocks and then regress the response on these statistics under a penalized error criterion to obtain estimates of the regression coefficients. We examine the performance of this approach for a variety of choices of n, p, classes of statistics, clustering algorithms, penalty terms, and data types. When n is not large, the discrimination over number of statistics is weak, but computations suggest regressing on approximately [n/K] statistics where K is the number of blocks formed by a clustering algorithm. Small deviations from this are observed when the blocks of variables are of very different sizes. Larger deviations are observed when the penalty term is an Lq norm with high enough q. PMID:25346546

Agricultural losses related to frost events: use of the 850 hPa level temperature as an explanatory variable of the damage cost

NASA Astrophysics Data System (ADS)

Papagiannaki, K.; Lagouvardos, K.; Kotroni, V.; Papagiannakis, G.

2014-09-01

The objective of this study is the analysis of damaging frost events in agriculture, by examining the relationship between the daily minimum temperature in the lower atmosphere (at an isobaric level of 850 hPa) and crop production losses. Furthermore, the study suggests a methodological approach for estimating agriculture risk due to frost events, with the aim of estimating the short-term probability and magnitude of frost-related financial losses for different levels of 850 hPa temperature. Compared with near-surface temperature forecasts, temperature forecasts at the level of 850 hPa are less influenced by varying weather conditions or by local topographical features; thus, they constitute a more consistent indicator of the forthcoming weather conditions. The analysis of the daily monetary compensations for insured crop losses caused by weather events in Greece shows that, during the period 1999-2011, frost caused more damage to crop production than any other meteorological phenomenon. Two regions of different geographical latitudes are examined further, to account for the differences in the temperature ranges developed within their ecological environment. Using a series of linear and logistic regressions, we found that minimum temperature (at an 850 hPa level), grouped into three categories according to its magnitude, and seasonality, are significant variables when trying to explain crop damage costs, as well as to predict and quantify the likelihood and magnitude of damaging frost events.

Beyond imperviousness: A statistical approach to identifying functional differences between development morphologies on variable source area-type response in urbanized watersheds

NASA Astrophysics Data System (ADS)

Lim, T. C.

2016-12-01

Empirical evidence has shown linkages between urbanization, hydrological regime change, and degradation of water quality and aquatic habitat. Percent imperviousness, has long been suggested as the dominant source of these negative changes. However, recent research identifying alternative pathways of runoff production at the watershed scale have called into question percent impervious surface area's primacy in urban runoff production compared to other aspects of urbanization including change in vegetative cover, imported water and water leakages, and the presence of drainage infrastructure. In this research I show how a robust statistical methodology can detect evidence of variable source area (VSA)-type hydrologic response associated with incremental hydraulic connectivity in watersheds. I then use logistic regression to explore how evidence of VSA-type response relates to the physical and meterological characteristics of the watershed. I find that impervious surface area is highly correlated with development, but does not add significant explanatory power beyond percent developed in predicting VSA-type response. Other aspects of development morphology, including percent developed open space and type of drainage infrastructure also do not add to the explanatory power of undeveloped land in predicting VSA-type response. Within only developed areas, the effect of developed open space was found to be more similar to that of total impervious area than to undeveloped land. These findings were consistent when tested across a national cross-section of urbanized watersheds, a higher resolution dataset of Baltimore Metropolitan Area watersheds, and a subsample of watersheds confirmed not to be served by combined sewer systems. These findings suggest that land development policies that focus on lot coverage should be revisited, and more focus should be placed on preserving native vegetation and soil conditions alongside development.

The Role of Auxiliary Variables in Deterministic and Deterministic-Stochastic Spatial Models of Air Temperature in Poland

NASA Astrophysics Data System (ADS)

Szymanowski, Mariusz; Kryza, Maciej

2017-02-01

Our study examines the role of auxiliary variables in the process of spatial modelling and mapping of climatological elements, with air temperature in Poland used as an example. The multivariable algorithms are the most frequently applied for spatialization of air temperature, and their results in many studies are proved to be better in comparison to those obtained by various one-dimensional techniques. In most of the previous studies, two main strategies were used to perform multidimensional spatial interpolation of air temperature. First, it was accepted that all variables significantly correlated with air temperature should be incorporated into the model. Second, it was assumed that the more spatial variation of air temperature was deterministically explained, the better was the quality of spatial interpolation. The main goal of the paper was to examine both above-mentioned assumptions. The analysis was performed using data from 250 meteorological stations and for 69 air temperature cases aggregated on different levels: from daily means to 10-year annual mean. Two cases were considered for detailed analysis. The set of potential auxiliary variables covered 11 environmental predictors of air temperature. Another purpose of the study was to compare the results of interpolation given by various multivariable methods using the same set of explanatory variables. Two regression models: multiple linear (MLR) and geographically weighted (GWR) method, as well as their extensions to the regression-kriging form, MLRK and GWRK, respectively, were examined. Stepwise regression was used to select variables for the individual models and the cross-validation method was used to validate the results with a special attention paid to statistically significant improvement of the model using the mean absolute error (MAE) criterion. The main results of this study led to rejection of both assumptions considered. Usually, including more than two or three of the most significantly

Using case study within a sequential explanatory design to evaluate the impact of specialist and advanced practice roles on clinical outcomes: the SCAPE study.

PubMed

Lalor, Joan G; Casey, Dympna; Elliott, Naomi; Coyne, Imelda; Comiskey, Catherine; Higgins, Agnes; Murphy, Kathy; Devane, Declan; Begley, Cecily

2013-04-08

The role of the clinical nurse/midwife specialist and advanced nurse/midwife practitioner is complex not least because of the diversity in how the roles are operationalised across health settings and within multidisciplinary teams. This aim of this paper is to use The SCAPE Study: Specialist Clinical and Advanced Practitioner Evaluation in Ireland to illustrate how case study was used to strengthen a Sequential Explanatory Design. In Phase 1, clinicians identified indicators of specialist and advanced practice which were then used to guide the instrumental case study design which formed the second phase of the larger study. Phase 2 used matched case studies to evaluate the effectiveness of specialist and advanced practitioners on clinical outcomes for service users. Data were collected through observation, documentary analysis, and interviews. Observations were made of 23 Clinical Specialists or Advanced Practitioners, and 23 matched clinicians in similar matched non-postholding sites, while they delivered care. Forty-one service users, 41 clinicians, and 23 Directors of Nursing or Midwifery were interviewed, and 279 service users completed a survey based on the components of CS and AP practice identified in Phase 1. A coding framework, and the generation of cross tabulation matrices in NVivo, was used to make explicit how the outcome measures were confirmed and validated from multiple sources. This strengthened the potential to examine single cases that seemed 'different', and allowed for cases to be redefined. Phase 3 involved interviews with policy-makers to set the findings in context. Case study is a powerful research strategy to use within sequential explanatory mixed method designs, and adds completeness to the exploration of complex issues in clinical practice. The design is flexible, allowing the use of multiple data collection methods from both qualitative and quantitative paradigms. Multiple approaches to data collection are needed to evaluate the impact

Human influence on California fire regimes.

PubMed

Syphard, Alexandra D; Radeloff, Volker C; Keeley, Jon E; Hawbaker, Todd J; Clayton, Murray K; Stewart, Susan I; Hammer, Roger B

2007-07-01

Periodic wildfire maintains the integrity and species composition of many ecosystems, including the mediterranean-climate shrublands of California. However, human activities alter natural fire regimes, which can lead to cascading ecological effects. Increased human ignitions at the wildland-urban interface (WUI) have recently gained attention, but fire activity and risk are typically estimated using only biophysical variables. Our goal was to determine how humans influence fire in California and to examine whether this influence was linear, by relating contemporary (2000) and historic (1960-2000) fire data to both human and biophysical variables. Data for the human variables included fine-resolution maps of the WUI produced using housing density and land cover data. Interface WUI, where development abuts wildland vegetation, was differentiated from intermix WUI, where development intermingles with wildland vegetation. Additional explanatory variables included distance to WUI, population density, road density, vegetation type, and ecoregion. All data were summarized at the county level and analyzed using bivariate and multiple regression methods. We found highly significant relationships between humans and fire on the contemporary landscape, and our models explained fire frequency (R2 = 0.72) better than area burned (R2 = 0.50). Population density, intermix WUI, and distance to WUI explained the most variability in fire frequency, suggesting that the spatial pattern of development may be an important variable to consider when estimating fire risk. We found nonlinear effects such that fire frequency and area burned were highest at intermediate levels of human activity, but declined beyond certain thresholds. Human activities also explained change in fire frequency and area burned (1960-2000), but our models had greater explanatory power during the years 1960-1980, when there was more dramatic change in fire frequency. Understanding wildfire as a function of the

Human influence on California fire regimes

USGS Publications Warehouse

Syphard, A.D.; Radeloff, V.C.; Keeley, J.E.; Hawbaker, T.J.; Clayton, M.K.; Stewart, S.I.; Hammer, R.B.

2007-01-01

Periodic wildfire maintains the integrity and species composition of many ecosystems, including the mediterranean-climate shrublands of California. However, human activities alter natural fire regimes, which can lead to cascading ecological effects. Increased human ignitions at the wildland-urban interface (WUI) have recently gained attention, but fire activity and risk are typically estimated using only biophysical variables. Our goal was to determine how humans influence fire in California and to examine whether this influence was linear, by relating contemporary (2000) and historic (1960-2000) fire data to both human and biophysical variables. Data for the human variables included fine-resolution maps of the WUI produced using housing density and land cover data. Interface WUI, where development abuts wildland vegetation, was differentiated from intermix WUI, where development intermingles with wildland vegetation. Additional explanatory variables included distance to WUI, population density, road density, vegetation type, and ecoregion. All data were summarized at the county level and analyzed using bivariate and multiple regression methods. We found highly significant relationships between humans and fire on the contemporary landscape, and our models explained fire frequency (R2 = 0.72) better than area burned (R2 = 0.50). Population density, intermix WUI, and distance to WUI explained the most variability in fire frequency, suggesting that the spatial pattern of development may be an important variable to consider when estimating fire risk. We found nonlinear effects such that fire frequency and area burned were highest at intermediate levels of human activity, but declined beyond certain thresholds. Human activities also explained change in fire frequency and area burned (1960-2000), but our models had greater explanatory power during the years 1960-1980, when there was more dramatic change in fire frequency. Understanding wildfire as a function of the

An Instrumental Variable Probit (IVP) analysis on depressed mood in Korea: the impact of gender differences and other socio-economic factors.

PubMed

Gitto, Lara; Noh, Yong-Hwan; Andrés, Antonio Rodríguez

2015-04-16

Depression is a mental health state whose frequency has been increasing in modern societies. It imposes a great burden, because of the strong impact on people's quality of life and happiness. Depression can be reliably diagnosed and treated in primary care: if more people could get effective treatments earlier, the costs related to depression would be reversed. The aim of this study was to examine the influence of socio-economic factors and gender on depressed mood, focusing on Korea. In fact, in spite of the great amount of empirical studies carried out for other countries, few epidemiological studies have examined the socio-economic determinants of depression in Korea and they were either limited to samples of employed women or did not control for individual health status. Moreover, as the likely data endogeneity (i.e. the possibility of correlation between the dependent variable and the error term as a result of autocorrelation or simultaneity, such as, in this case, the depressed mood due to health factors that, in turn might be caused by depression), might bias the results, the present study proposes an empirical approach, based on instrumental variables, to deal with this problem. Data for the year 2008 from the Korea National Health and Nutrition Examination Survey (KNHANES) were employed. About seven thousands of people (N= 6,751, of which 43% were males and 57% females), aged from 19 to 75 years old, were included in the sample considered in the analysis. In order to take into account the possible endogeneity of some explanatory variables, two Instrumental Variables Probit (IVP) regressions were estimated; the variables for which instrumental equations were estimated were related to the participation of women to the workforce and to good health, as reported by people in the sample. Explanatory variables were related to age, gender, family factors (such as the number of family members and marital status) and socio-economic factors (such as education

An Instrumental Variable Probit (IVP) analysis on depressed mood in Korea: the impact of gender differences and other socio-economic factors

PubMed Central

Gitto, Lara; Noh, Yong-Hwan; Andrés, Antonio Rodríguez

2015-01-01

Background: Depression is a mental health state whose frequency has been increasing in modern societies. It imposes a great burden, because of the strong impact on people’s quality of life and happiness. Depression can be reliably diagnosed and treated in primary care: if more people could get effective treatments earlier, the costs related to depression would be reversed. The aim of this study was to examine the influence of socio-economic factors and gender on depressed mood, focusing on Korea. In fact, in spite of the great amount of empirical studies carried out for other countries, few epidemiological studies have examined the socio-economic determinants of depression in Korea and they were either limited to samples of employed women or did not control for individual health status. Moreover, as the likely data endogeneity (i.e. the possibility of correlation between the dependent variable and the error term as a result of autocorrelation or simultaneity, such as, in this case, the depressed mood due to health factors that, in turn might be caused by depression), might bias the results, the present study proposes an empirical approach, based on instrumental variables, to deal with this problem. Methods: Data for the year 2008 from the Korea National Health and Nutrition Examination Survey (KNHANES) were employed. About seven thousands of people (N= 6,751, of which 43% were males and 57% females), aged from 19 to 75 years old, were included in the sample considered in the analysis. In order to take into account the possible endogeneity of some explanatory variables, two Instrumental Variables Probit (IVP) regressions were estimated; the variables for which instrumental equations were estimated were related to the participation of women to the workforce and to good health, as reported by people in the sample. Explanatory variables were related to age, gender, family factors (such as the number of family members and marital status) and socio-economic factors

Development of a QTL-environment-based predictive model for node addition rate in common bean.

PubMed

Zhang, Li; Gezan, Salvador A; Eduardo Vallejos, C; Jones, James W; Boote, Kenneth J; Clavijo-Michelangeli, Jose A; Bhakta, Mehul; Osorno, Juan M; Rao, Idupulapati; Beebe, Stephen; Roman-Paoli, Elvin; Gonzalez, Abiezer; Beaver, James; Ricaurte, Jaumer; Colbert, Raphael; Correll, Melanie J

2017-05-01

This work reports the effects of the genetic makeup, the environment and the genotype by environment interactions for node addition rate in an RIL population of common bean. This information was used to build a predictive model for node addition rate. To select a plant genotype that will thrive in targeted environments it is critical to understand the genotype by environment interaction (GEI). In this study, multi-environment QTL analysis was used to characterize node addition rate (NAR, node day - 1 ) on the main stem of the common bean (Phaseolus vulgaris L). This analysis was carried out with field data of 171 recombinant inbred lines that were grown at five sites (Florida, Puerto Rico, 2 sites in Colombia, and North Dakota). Four QTLs (Nar1, Nar2, Nar3 and Nar4) were identified, one of which had significant QTL by environment interactions (QEI), that is, Nar2 with temperature. Temperature was identified as the main environmental factor affecting NAR while day length and solar radiation played a minor role. Integration of sites as covariates into a QTL mixed site-effect model, and further replacing the site component with explanatory environmental covariates (i.e., temperature, day length and solar radiation) yielded a model that explained 73% of the phenotypic variation for NAR with root mean square error of 16.25% of the mean. The QTL consistency and stability was examined through a tenfold cross validation with different sets of genotypes and these four QTLs were always detected with 50-90% probability. The final model was evaluated using leave-one-site-out method to assess the influence of site on node addition rate. These analyses provided a quantitative measure of the effects on NAR of common beans exerted by the genetic makeup, the environment and their interactions.

Using generalized additive (mixed) models to analyze single case designs.

PubMed

Shadish, William R; Zuur, Alain F; Sullivan, Kristynn J

2014-04-01

This article shows how to apply generalized additive models and generalized additive mixed models to single-case design data. These models excel at detecting the functional form between two variables (often called trend), that is, whether trend exists, and if it does, what its shape is (e.g., linear and nonlinear). In many respects, however, these models are also an ideal vehicle for analyzing single-case designs because they can consider level, trend, variability, overlap, immediacy of effect, and phase consistency that single-case design researchers examine when interpreting a functional relation. We show how these models can be implemented in a wide variety of ways to test whether treatment is effective, whether cases differ from each other, whether treatment effects vary over cases, and whether trend varies over cases. We illustrate diagnostic statistics and graphs, and we discuss overdispersion of data in detail, with examples of quasibinomial models for overdispersed data, including how to compute dispersion and quasi-AIC fit indices in generalized additive models. We show how generalized additive mixed models can be used to estimate autoregressive models and random effects and discuss the limitations of the mixed models compared to generalized additive models. We provide extensive annotated syntax for doing all these analyses in the free computer program R. Copyright © 2013 Society for the Study of School Psychology. Published by Elsevier Ltd. All rights reserved.

Estimating and testing interactions when explanatory variables are subject to non-classical measurement error.

PubMed

Murad, Havi; Kipnis, Victor; Freedman, Laurence S

2016-10-01

Assessing interactions in linear regression models when covariates have measurement error (ME) is complex.We previously described regression calibration (RC) methods that yield consistent estimators and standard errors for interaction coefficients of normally distributed covariates having classical ME. Here we extend normal based RC (NBRC) and linear RC (LRC) methods to a non-classical ME model, and describe more efficient versions that combine estimates from the main study and internal sub-study. We apply these methods to data from the Observing Protein and Energy Nutrition (OPEN) study. Using simulations we show that (i) for normally distributed covariates efficient NBRC and LRC were nearly unbiased and performed well with sub-study size ≥200; (ii) efficient NBRC had lower MSE than efficient LRC; (iii) the naïve test for a single interaction had type I error probability close to the nominal significance level, whereas efficient NBRC and LRC were slightly anti-conservative but more powerful; (iv) for markedly non-normal covariates, efficient LRC yielded less biased estimators with smaller variance than efficient NBRC. Our simulations suggest that it is preferable to use: (i) efficient NBRC for estimating and testing interaction effects of normally distributed covariates and (ii) efficient LRC for estimating and testing interactions for markedly non-normal covariates. © The Author(s) 2013.

Psychopathology in people with epilepsy and intellectual disability; an investigation of potential explanatory variables.

PubMed

Espie, C A; Watkins, J; Curtice, L; Espie, A; Duncan, R; Ryan, J A; Brodie, M J; Mantala, K; Sterrick, M

2003-11-01

There are few studies on epilepsy and psychopathology in people with intellectual disability (mental retardation) despite epilepsy prevalence rates that are thirty times higher than in the general population. The aims of this study, therefore, were to identify reliable, epilepsy-specific predictors of psychiatric and behavioural disorder in these patients, and to investigate reliable predictors of carer stress. A database of 685 patients was compiled, from which 250 were randomly selected. Structured interviews were completed on 186 of these 250 patients (74%) (108 men, 78 women; mean age (SD) 35.5 (10.1)) comprising descriptive, clinical and functional components, and validated measures of psychopathology for which comparative data were available. Logistic and linear regression methods were used to identify predictors. One-third of patients with epilepsy and intellectual disability met criteria for possible psychiatric disorder, particularly affective/neurotic disorder; twice the comparison rates for intellectual disability alone. Behavioural problem levels, however, were lower than population norms. Regression models explaining modest amounts of variance (R(2)< or =24%) suggested certain seizure phenomena (greater seizure severity, more seizures in past month, lesser tendency to loss of consciousness during seizures) as particular risk factors for psychiatric disorder. General disability factors such as level of intellectual, sensory or motor disability and side effects of medication, however, contributed more to explaining behavioural problems. Around half of the family carers reported significant stress, and one-third exhibited clinically significant anxiety symptoms. Younger carers were more stressed, and side effects from patients' medication also contributed to carer stress. Although epilepsy in itself may be a risk factor for psychopathology in a minority of people with intellectual disability, some epilepsy-specific factors may predict psychiatric disorder. Behavioural problems need to be considered separately from psychiatric disorder because general factors, more closely associated with disability, are stronger predictors of their occurrence.

'Food Sticking in My Throat': Videofluoroscopic Evaluation of a Common Symptom.

PubMed

Madhavan, Aarthi; Carnaby, Giselle D; Crary, Michael A

2015-06-01

Prevalence of the symptom of food 'sticking' during swallowing has been reported to range from 5 to 50%, depending on the assessment setting. However, limited objective evidence has emerged to clarify factors that contribute to this symptom. Three hundred and fifteen patient records from an outpatient dysphagia clinic were reviewed to identify patients with symptoms of 'food sticking in the throat.' Corresponding videofluoroscopic swallowing studies for patients with this complaint were reviewed for the following variables: accuracy of symptom localization, identification and characteristics (anatomic, physiologic) of an explanatory cause for the symptom, and the specific swallowed material that identified the explanatory cause. One hundred and forty one patients (45%) were identified with a complaint of food 'sticking' in their throat during swallowing. Prevalence of explanatory findings on fluoroscopy was 76% (107/141). Eighty five percent (91/107) of explanatory causes were physiologic in nature, while 15% (16/107) were anatomic. The majority of explanatory causes were identified in the esophagus (71%). Symptom localization was more accurate when the explanatory cause was anatomic versus physiologic (75 vs. 18%). A non-masticated marshmallow presented with the highest diagnostic yield in identification of explanatory causes (71%). Patients complaining of 'food sticking in the throat' are likely to present with esophageal irregularities. Thus, imaging studies of swallowing function should include the esophagus. A range of materials, including a non-masticated marshmallow, is helpful in determining the location and characteristics of swallowing deficits contributing to this symptom.

The 1998-2000 SHADOZ (Southern Hemisphere ADditional OZonesondes) Tropical Ozone Climatology. 2; Stratospheric and Tropospheric Ozone Variability and the Zonal Wave-One

NASA Technical Reports Server (NTRS)

Thompson, Anne M.; Witte, Jacquelyn C.; Oltmans, Samuel J.; Schmidlin, Francis J.; Logan, Jennifer A.; Fujiwara, Masatomo; Kirchhoff, Volker W. J. H.; Posny, Francoise; Coetzee, Gert J. R.; Hoegger, Bruno;

Racial disparities in self-rated health: Trends, explanatory factors, and the changing role of socio-demographics

PubMed Central

Beck, Audrey N.; Finch, Brian K.; Lin, Shih-Fan; Hummer, Robert A.; Masters, Ryan K.

2014-01-01

This paper uses data from the U.S. National Health Interview Surveys (N = 1,513,097) to describe and explain temporal patterns in black-white health disparities with models that simultaneously consider the unique effects of age, period, and cohort. First, we employ cross-classified random effects age–period–cohort (APC) models to document black-white disparities in self-rated health across temporal dimensions. Second, we use decomposition techniques to shed light on the extent to which socio-economic shifts in cohort composition explain the age and period adjusted racial health disparities across successive birth cohorts. Third, we examine the extent to which exogenous conditions at the time of birth help explain the racial disparities across successive cohorts. Results show that black-white disparities are wider among the pre-1935 cohorts for women, falling thereafter; disparities for men exhibit a similar pattern but exhibit narrowing among cohorts born earlier in the century. Differences in socioeconomic composition consistently contribute to racial health disparities across cohorts; notably, marital status differences by race emerge as an increasingly important explanatory factor in more recent cohorts for women whereas employment differences by race emerge as increasingly salient in more recent cohorts for men. Finally, our cohort characteristics models suggest that cohort economic conditions at the time of birth (percent large family, farm or Southern birth) help explain racial disparities in health for both men and women. PMID:24581075

Factors influencing storm-generated suspended-sediment concentrations and loads in four basins of contrasting land use, humid-tropical Puerto Rico

Treesearch

A. C. Gellis; NO-VALUE

2013-01-01

The significant characteristics controlling the variability in storm-generated suspended-sediment loads and concentrations were analyzed for four basins of differing land use (forest, pasture, cropland, and urbanizing) in humid-tropical Puerto Rico. Statistical analysis involved stepwise regression on factor scores. The explanatory variables were attributes of flow,...

Longitudinal Course of Risk for Parental Post-Adoption Depression

PubMed Central

Foli, Karen J.; South, Susan C.; Lim, Eunjung; Hebdon, Megan

2016-01-01

Objective To determine whether the Postpartum Depression Predictors Inventory-Revised (PDPI-R) could be used to reveal distinct classes of adoptive parents across time. Design Longitudinal data were collected via online surveys at 4-6 weeks pre-placement, 4-6 weeks post-placement, and 5-6 months post-placement. Setting Participants were primarily clients of the largest adoption agency in the United States. Participants Participants included 127 adoptive parents (68 mothers and 59 fathers). Methods We applied a latent class growth analysis to the PDPI-R and conducted mixed effects modeling of class, time, and class×time interaction for the following categories of explanatory variables: parental expectations; interpersonal variables; psychological symptoms; and life orientation. Results Four latent trajectory classes were found. Class 1 (55% of sample) showed a stably low level of PDPI-R scores over time. Class 2 (32%) reported mean scores below the cut-off points at all three time points. Class 3 (8%) started at an intermediate level and increased after post-placement, but decreased at 5-6 months post-placement. Class 4 (5%) had high mean scores at all three time points. Significant main effects were found for almost all explanatory variables for class and for several variables for time. Significant interactions between class and time were found for expectations about the child and amount of love and ambivalence in parent's intimate relationship. Conclusion Findings may assist nurses to be alert to trajectories of risk for post-adoption depression. Additional factors, not included in the PDPI-R, to determine risk for post-adoption depression may be needed for adoptive parents. PMID:26874267

The explanatory models of depression in low income countries: listening to women in India.

PubMed

Pereira, Bernadette; Andrew, Gracy; Pednekar, Sulochana; Pai, Reshma; Pelto, Pertti; Patel, Vikram

2007-09-01

Women, and persons facing social and economic disadvantage, are at greater risk for depressive disorders. Our objective was to describe the explanatory models of illness in depressed women, in particular, their idioms of distress, and their views of their social circumstances and how this related to their illness. We carried out a qualitative investigation nested in a population based cohort study of women's mental and reproductive health in Goa, India. We purposively sampled women who were ever-married and who had been found to be suffering from a depressive disorder on the basis of a structured diagnostic interview. In-depth interviews were carried out about six months apart exploring stressors in women's lives, a typical day in their recent lives, and their illness narratives (idioms of distress, causal models, impact of illness, help-seeking). 35 women consented to participate in the study, 28 completing both interviews. Women gave expression to their problems primarily through somatic complaints, typically a variety of body aches, autonomic symptoms, gynecological symptoms and sleep problems. There was frequent mention of overall "weakness" and tiredness. Economic difficulties and difficulties with interpersonal relationships (particularly related to marital relationships) were the most common causal models. However, women rarely considered biomedical concepts, for example, the notion that they may suffer from an illness or that their complaints were due to a biochemical disturbance in the brain. Despite the lack of a biomedical concept, most of the participants had sought medical help, typically for reproductive and somatic complaints. We recommend the use of somatic idioms as the defining clinical features, and a broader, psychosocial model for understanding the aetiology and conceptualization of the clinical syndrome of depression for public health interventions and mental health promotion in the Indian context.

Explanatory Pluralism and the (Dis)Unity of Science: The Argument from Incompatible Counterfactual Consequences

PubMed Central

Gijsbers, Victor

2016-01-01

What is the relationship between different sciences or research approaches that deal with the same phenomena, for instance, with the phenomena of the human mind? Answers to this question range from a monist perspective according to which one of these approaches is privileged over the others, through an integrationist perspective according to which they must strive to form a unity greater than the sum of its parts, to an isolationist perspective according to which each of them has its own autonomous sphere of validity. In order to assess these perspectives in this article, I discuss the debates about the unity of science and about explanatory pluralism. The most pressing issue turns out to be the choice between the integrative and the isolationist perspective: the question is whether the integrative tendencies in science should be fully indulged in or whether they should be held in check by acknowledging that a certain amount of isolation is necessary. I argue that the issue can be further distilled into the question of whether two true explanations of the same fact can ever fail to be combinable into one single explanation. I show that this can indeed be the case, namely, when the explanations have incompatible counterfactual consequences, something that is often the case when we try to combine explanations from different sciences or research approaches. These approaches thus embody perspectives on the world that are to a certain extent autonomous. This leads to the conclusion that although interdisciplinarity may have many advantages, we should not take the project of integration too far. At the end of the day, the different research approaches with their different perspectives and insights must remain precisely that: different and somewhat disunified. PMID:27014099

Explanatory Pluralism and the (Dis)Unity of Science: The Argument from Incompatible Counterfactual Consequences.

PubMed

Gijsbers, Victor

2016-01-01

What is the relationship between different sciences or research approaches that deal with the same phenomena, for instance, with the phenomena of the human mind? Answers to this question range from a monist perspective according to which one of these approaches is privileged over the others, through an integrationist perspective according to which they must strive to form a unity greater than the sum of its parts, to an isolationist perspective according to which each of them has its own autonomous sphere of validity. In order to assess these perspectives in this article, I discuss the debates about the unity of science and about explanatory pluralism. The most pressing issue turns out to be the choice between the integrative and the isolationist perspective: the question is whether the integrative tendencies in science should be fully indulged in or whether they should be held in check by acknowledging that a certain amount of isolation is necessary. I argue that the issue can be further distilled into the question of whether two true explanations of the same fact can ever fail to be combinable into one single explanation. I show that this can indeed be the case, namely, when the explanations have incompatible counterfactual consequences, something that is often the case when we try to combine explanations from different sciences or research approaches. These approaches thus embody perspectives on the world that are to a certain extent autonomous. This leads to the conclusion that although interdisciplinarity may have many advantages, we should not take the project of integration too far. At the end of the day, the different research approaches with their different perspectives and insights must remain precisely that: different and somewhat disunified.

An explanatory model of community pharmacists' support in the secondary prevention of cardiovascular disease.

PubMed

Puspitasari, Hanni P; Costa, Daniel S J; Aslani, Parisa; Krass, Ines

2016-01-01

Community pharmacists have faced ongoing challenges in the delivery of clinical pharmacy services. Various attitudinal and environmental factors have been found to be associated with the provision of general clinical pharmacy services or services which focus on a specific condition, including cardiovascular disease (CVD). However, the interrelationship and relative influence of explanatory factors has not been investigated. To develop a model illustrating influences on CVD support provision by community pharmacists. Mail surveys were sent to a random sample of 1350 Australian community pharmacies to investigate determinants of CVD support provision. A theoretical model modified from the Theory of Planned Behavior (TPB) was used as a framework for the survey instrument. Structural equation modeling was used to determine how pharmacists' attitudes and environmental factors influence CVD support. A response rate of 15.8% (209/1320) was obtained. The model for CVD support provision by community pharmacists demonstrated good fit: χ(2)/df = 1.403, RMSEA = 0.047 (90% CI = 0.031-0.062), CFI = 0.962, TLI = 0.955 and WRMR = 0.838. Factors found to predict CVD support included: two attitudinal latent factors ("subjective norms of pharmacists' role in CVD support" and "pharmacists' perceived responsibilities in CVD support") and environmental factors i.e. pharmacy infrastructure (documentation and a private area), workload, location; government funded pharmacy practice programs; and pharmacists' involvement with Continuing Professional Development and attendance at CVD courses. Pharmacists' attitudes appeared to be the strongest predictor of CVD support provision. The TPB framework was useful in identifying "subjective norms" and "pharmacists' beliefs" as key constructs of community pharmacists' attitudes. Community pharmacies would be able to provide such an advanced clinical service if they strongly believed that this was an acknowledged part of their scope of practice, had

The Use of Dialectical Behavior Therapy (DBT) in Music Therapy: A Sequential Explanatory Study.

PubMed

Chwalek, Carolyn M; McKinney, Cathy H

2015-01-01

There are published examples of how dialectical behavior therapy (DBT) and music therapy are effectively being used as separate therapies in the treatment of individuals with a variety of mental health disorders. However, research examining DBT-informed music therapy is limited. The purpose of this study was to determine whether music therapists working in mental health settings are implementing components of DBT in their work, and if so, how and why; and if not, why not and what is their level of interest in such work. We used a sequential explanatory mixed-methods research design implemented in two phases. Phase 1 was a quantitative survey of board-certified music therapists (n=260). Due to a low survey response rate (18%), and to enhance the validity of the findings, Phase 2, an embedded qualitative procedure in the form of interviews with clinicians experienced in the DBT approach, was added to the study. Both survey and interviews inquired about DBT training, use of DBT-informed music therapy, music therapy experiences used to address DBT skills, and experiences of implementing DBT-informed music therapy. Respondents indicating they implement DBT-informed music therapy (38.3%) are using components and adaptations of the standard DBT protocol. Advantages of implementing DBT-informed music therapy were identified, and more than half of the respondents who do not implement DBT in their music therapy practice also perceived this work as at least somewhat important. Disadvantages were also identified and support the need for further research. Components of DBT are used in music therapy and are valued, but there is a lack of empirical evidence to inform, refine, and guide practice. © the American Music Therapy Association 2015. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Variability of a "force signature" during windmill softball pitching and relationship between discrete force variables and pitch velocity.

PubMed

Nimphius, Sophia; McGuigan, Michael R; Suchomel, Timothy J; Newton, Robert U

2016-06-01

This study assessed reliability of discrete ground reaction force (GRF) variables over multiple pitching trials, investigated the relationships between discrete GRF variables and pitch velocity (PV) and assessed the variability of the "force signature" or continuous force-time curve during the pitching motion of windmill softball pitchers. Intraclass correlation coefficient (ICC) for all discrete variables was high (0.86-0.99) while the coefficient of variance (CV) was low (1.4-5.2%). Two discrete variables were significantly correlated to PV; second vertical peak force (r(5)=0.81, p=0.03) and time between peak forces (r(5)=-0.79; p=0.03). High ICCs and low CVs support the reliability of discrete GRF and PV variables over multiple trials and significant correlations indicate there is a relationship between the ability to produce force and the timing of this force production with PV. The mean of all pitchers' curve-average standard deviation of their continuous force-time curves demonstrated low variability (CV=4.4%) indicating a repeatable and identifiable "force signature" pattern during this motion. As such, the continuous force-time curve in addition to discrete GRF variables should be examined in future research as a potential method to monitor or explain changes in pitching performance. Copyright © 2016 Elsevier B.V. All rights reserved.

Estimating and Modelling Bias of the Hierarchical Partitioning Public-Domain Software: Implications in Environmental Management and Conservation

PubMed Central

Olea, Pedro P.; Mateo-Tomás, Patricia; de Frutos, Ángel

2010-01-01

Background Hierarchical partitioning (HP) is an analytical method of multiple regression that identifies the most likely causal factors while alleviating multicollinearity problems. Its use is increasing in ecology and conservation by its usefulness for complementing multiple regression analysis. A public-domain software “hier.part package” has been developed for running HP in R software. Its authors highlight a “minor rounding error” for hierarchies constructed from >9 variables, however potential bias by using this module has not yet been examined. Knowing this bias is pivotal because, for example, the ranking obtained in HP is being used as a criterion for establishing priorities of conservation. Methodology/Principal Findings Using numerical simulations and two real examples, we assessed the robustness of this HP module in relation to the order the variables have in the analysis. Results indicated a considerable effect of the variable order on the amount of independent variance explained by predictors for models with >9 explanatory variables. For these models the nominal ranking of importance of the predictors changed with variable order, i.e. predictors declared important by its contribution in explaining the response variable frequently changed to be either most or less important with other variable orders. The probability of changing position of a variable was best explained by the difference in independent explanatory power between that variable and the previous one in the nominal ranking of importance. The lesser is this difference, the more likely is the change of position. Conclusions/Significance HP should be applied with caution when more than 9 explanatory variables are used to know ranking of covariate importance. The explained variance is not a useful parameter to use in models with more than 9 independent variables. The inconsistency in the results obtained by HP should be considered in future studies as well as in those already published

The Facilitators and Barriers to Nurses’ Participation in Continuing Education Programs: A Mixed Method Explanatory Sequential Study

PubMed Central

Shahhosseini, Zohreh; Hamzehgardeshi, Zeinab

2015-01-01

Background: Since several factors affect nurses’ participation in Continuing Education, and that nurses’ Continuing Education affects patients’ and community health status, it is essential to know facilitators and barriers of participation in Continuing Education programs and plan accordingly. This mixed approach study aimed to investigate the facilitators and barriers of nurses’ participation, to explore nurses’ perception of the most common facilitators and barriers. Methods: An explanatory sequential mixed methods design with follow up explanations variant were used, and it involved collecting quantitative data (361 nurses) first and then explaining the quantitative results with in-depth interviews during a qualitative study. Results: The results showed that the mean score of facilitators to nurses’ participation in Continuing Education was significantly higher than the mean score of barriers (61.99±10.85 versus 51.17±12.83; p<0.001, t=12.23). The highest mean score of facilitators of nurses’ participation in Continuing Education was related to “Update my knowledge”. By reviewing the handwritings in qualitative phase, two main levels of updating information and professional skills were extracted as the most common facilitators and lack of support as the most common barrier to nurses’ participation in continuing education program. Conclusion: According to important role Continuing Education on professional skills, nurse managers should facilitate the nurse’ participation in the Continues Education. PMID:25948439

The facilitators and barriers to nurses' participation in continuing education programs: a mixed method explanatory sequential study.

PubMed

Shahhosseini, Zohreh; Hamzehgardeshi, Zeinab

2014-11-30

Since several factors affect nurses' participation in Continuing Education, and that nurses' Continuing Education affects patients' and community health status, it is essential to know facilitators and barriers of participation in Continuing Education programs and plan accordingly. This mixed approach study aimed to investigate the facilitators and barriers of nurses' participation, to explore nurses' perception of the most common facilitators and barriers. An explanatory sequential mixed methods design with follow up explanations variant were used, and it involved collecting quantitative data (361 nurses) first and then explaining the quantitative results with in-depth interviews during a qualitative study. The results showed that the mean score of facilitators to nurses' participation in Continuing Education was significantly higher than the mean score of barriers (61.99 ± 10.85 versus 51.17 ± 12.83; p<0.001, t=12.23). The highest mean score of facilitators of nurses' participation in Continuing Education was related to "Update my knowledge". By reviewing the handwritings in qualitative phase, two main levels of updating information and professional skills were extracted as the most common facilitators and lack of support as the most common barrier to nurses' participation in continuing education program. According to important role Continuing Education on professional skills, nurse managers should facilitate the nurse' participation in the Continues Education.

Agricultural losses related to frost events: use of the 850 hPa level temperature as an explanatory variable of the damage cost

NASA Astrophysics Data System (ADS)

Papagiannaki, K.; Lagouvardos, K.; Kotroni, V.; Papagiannakis, G.

2014-01-01

The objective of this study is to analyze frost damaging events in agriculture, by examining the relationship between the daily minimum temperature at the lower atmosphere (at the pressure level of 850 hPa) and crop production losses. Furthermore, the study suggests a methodological approach for estimating agriculture risk due to frost events, with the aim to estimate the short-term probability and magnitude of frost-related financial losses for different levels of 850 hPa temperature. Compared with near surface temperature forecasts, temperature forecast at the level of 850 hPa is less influenced by varying weather conditions, as well as by local topographical features, thus it constitutes a more consistent indicator of the forthcoming weather conditions. The analysis of the daily monetary compensations for insured crop losses caused by weather events in Greece, during the period 1999-2011, shows that frost is the major meteorological phenomenon with adverse effects on crop productivity in the largest part of the country. Two regions of different geographical latitude are further examined, to account for the differences in the temperature ranges developed within their ecological environment. Using a series of linear and logistic regressions, we found that minimum temperature (at 850 hPa level), grouped in three categories according to its magnitude, and seasonality are significant variables when trying to explain crop damage costs, as well as to predict and quantify the likelihood and magnitude of frost damaging events.

Additive schemes for certain operator-differential equations

NASA Astrophysics Data System (ADS)

Vabishchevich, P. N.

2010-12-01

Unconditionally stable finite difference schemes for the time approximation of first-order operator-differential systems with self-adjoint operators are constructed. Such systems arise in many applied problems, for example, in connection with nonstationary problems for the system of Stokes (Navier-Stokes) equations. Stability conditions in the corresponding Hilbert spaces for two-level weighted operator-difference schemes are obtained. Additive (splitting) schemes are proposed that involve the solution of simple problems at each time step. The results are used to construct splitting schemes with respect to spatial variables for nonstationary Navier-Stokes equations for incompressible fluid. The capabilities of additive schemes are illustrated using a two-dimensional model problem as an example.

Long-term variability in sugarcane bagasse feedstock compositional methods: Sources and magnitude of analytical variability

DOE PAGES

Templeton, David W.; Sluiter, Justin B.; Sluiter, Amie; ...

2016-10-18

In an effort to find economical, carbon-neutral transportation fuels, biomass feedstock compositional analysis methods are used to monitor, compare, and improve biofuel conversion processes. These methods are empirical, and the analytical variability seen in the feedstock compositional data propagates into variability in the conversion yields, component balances, mass balances, and ultimately the minimum ethanol selling price (MESP). We report the average composition and standard deviations of 119 individually extracted National Institute of Standards and Technology (NIST) bagasse [Reference Material (RM) 8491] run by seven analysts over 7 years. Two additional datasets, using bulk-extracted bagasse (containing 58 and 291 replicates each),more » were examined to separate out the effects of batch, analyst, sugar recovery standard calculation method, and extractions from the total analytical variability seen in the individually extracted dataset. We believe this is the world's largest NIST bagasse compositional analysis dataset and it provides unique insight into the long-term analytical variability. Understanding the long-term variability of the feedstock analysis will help determine the minimum difference that can be detected in yield, mass balance, and efficiency calculations. The long-term data show consistent bagasse component values through time and by different analysts. This suggests that the standard compositional analysis methods were performed consistently and that the bagasse RM itself remained unchanged during this time period. The long-term variability seen here is generally higher than short-term variabilities. It is worth noting that the effect of short-term or long-term feedstock compositional variability on MESP is small, about $0.03 per gallon. The long-term analysis variabilities reported here are plausible minimum values for these methods, though not necessarily average or expected variabilities. We must emphasize the importance of training and

Long-term variability in sugarcane bagasse feedstock compositional methods: Sources and magnitude of analytical variability

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

Templeton, David W.; Sluiter, Justin B.; Sluiter, Amie

In an effort to find economical, carbon-neutral transportation fuels, biomass feedstock compositional analysis methods are used to monitor, compare, and improve biofuel conversion processes. These methods are empirical, and the analytical variability seen in the feedstock compositional data propagates into variability in the conversion yields, component balances, mass balances, and ultimately the minimum ethanol selling price (MESP). We report the average composition and standard deviations of 119 individually extracted National Institute of Standards and Technology (NIST) bagasse [Reference Material (RM) 8491] run by seven analysts over 7 years. Two additional datasets, using bulk-extracted bagasse (containing 58 and 291 replicates each),more » were examined to separate out the effects of batch, analyst, sugar recovery standard calculation method, and extractions from the total analytical variability seen in the individually extracted dataset. We believe this is the world's largest NIST bagasse compositional analysis dataset and it provides unique insight into the long-term analytical variability. Understanding the long-term variability of the feedstock analysis will help determine the minimum difference that can be detected in yield, mass balance, and efficiency calculations. The long-term data show consistent bagasse component values through time and by different analysts. This suggests that the standard compositional analysis methods were performed consistently and that the bagasse RM itself remained unchanged during this time period. The long-term variability seen here is generally higher than short-term variabilities. It is worth noting that the effect of short-term or long-term feedstock compositional variability on MESP is small, about $0.03 per gallon. The long-term analysis variabilities reported here are plausible minimum values for these methods, though not necessarily average or expected variabilities. We must emphasize the importance of training and

Should Age at Diagnosis Be Included as an Additional Variable in the Risk of Recurrence Classification System in Patients with Differentiated Thyroid Cancer.

PubMed

Pitoia, Fabián; Jerkovich, Fernando; Smulever, Anabella; Brenta, Gabriela; Bueno, Fernanda; Cross, Graciela

2017-07-01

To evaluate the influence of age at diagnosis on the frequency of structural incomplete response (SIR) according to the modified risk of recurrence (RR) staging system from the American Thyroid Association guidelines. We performed a retrospective analysis of 268 patients with differentiated thyroid cancer (DTC) followed up for at least 3 years after initial treatment (total thyroidectomy and remnant ablation). The median follow-up in the whole cohort was 74.3 months (range: 36.1-317.9) and the median age at diagnosis was 45.9 years (range: 18-87). The association between age at diagnosis and the initial and final response to treatment was assessed with analysis of variance (ANOVA). Patients were also divided into several groups considering age younger and older than 40, 50, and 60 years. Age at diagnosis was not associated with either an initial or final statistically significant different SIR to treatment ( p = 0.14 and p = 0.58, respectively). Additionally, we did not find any statistically significant differences when the percentages of SIR considering the classification of RR were compared between different groups of patients by using several age cutoffs. When patients are correctly risk stratified, it seems that age at diagnosis is not involved in the frequency of having a SIR at the initial evaluation or at the final follow-up, so it should not be included as an additional variable to be considered in the RR classifications.

Should Age at Diagnosis Be Included as an Additional Variable in the Risk of Recurrence Classification System in Patients with Differentiated Thyroid Cancer

PubMed Central

Pitoia, Fabián; Jerkovich, Fernando; Smulever, Anabella; Brenta, Gabriela; Bueno, Fernanda; Cross, Graciela

2017-01-01

Objective To evaluate the influence of age at diagnosis on the frequency of structural incomplete response (SIR) according to the modified risk of recurrence (RR) staging system from the American Thyroid Association guidelines. Patients and Methods We performed a retrospective analysis of 268 patients with differentiated thyroid cancer (DTC) followed up for at least 3 years after initial treatment (total thyroidectomy and remnant ablation). The median follow-up in the whole cohort was 74.3 months (range: 36.1-317.9) and the median age at diagnosis was 45.9 years (range: 18-87). The association between age at diagnosis and the initial and final response to treatment was assessed with analysis of variance (ANOVA). Patients were also divided into several groups considering age younger and older than 40, 50, and 60 years. Results Age at diagnosis was not associated with either an initial or final statistically significant different SIR to treatment (p = 0.14 and p = 0.58, respectively). Additionally, we did not find any statistically significant differences when the percentages of SIR considering the classification of RR were compared between different groups of patients by using several age cutoffs. Conclusions When patients are correctly risk stratified, it seems that age at diagnosis is not involved in the frequency of having a SIR at the initial evaluation or at the final follow-up, so it should not be included as an additional variable to be considered in the RR classifications. PMID:28785543

Temporal and spatial variability of global water balance

USGS Publications Warehouse

McCabe, Gregory J.; Wolock, David M.

2013-01-01

An analysis of simulated global water-balance components (precipitation [P], actual evapotranspiration [AET], runoff [R], and potential evapotranspiration [PET]) for the past century indicates that P has been the primary driver of variability in R. Additionally, since about 2000, there have been increases in P, AET, R, and PET for most of the globe. The increases in R during 2000 through 2009 have occurred despite unprecedented increases in PET. The increases in R are the result of substantial increases in P during the cool Northern Hemisphere months (i.e. October through March) when PET increases were relatively small; the largest PET increases occurred during the warm Northern Hemisphere months (April through September). Additionally, for the 2000 through 2009 period, the latitudinal distribution of P departures appears to co-vary with the mean P departures from 16 climate model projections of the latitudinal response of P to warming, except in the high latitudes. Finally, changes in water-balance variables appear large from the perspective of departures from the long-term means. However, when put into the context of the magnitudes of the raw water balance variable values, there appears to have been little change in any of the water-balance variables over the past century on a global or hemispheric scale.

Poisson Regression Analysis of Illness and Injury Surveillance Data

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

Frome E.L., Watkins J.P., Ellis E.D.

2012-12-12

The Department of Energy (DOE) uses illness and injury surveillance to monitor morbidity and assess the overall health of the work force. Data collected from each participating site include health events and a roster file with demographic information. The source data files are maintained in a relational data base, and are used to obtain stratified tables of health event counts and person time at risk that serve as the starting point for Poisson regression analysis. The explanatory variables that define these tables are age, gender, occupational group, and time. Typical response variables of interest are the number of absences duemore » to illness or injury, i.e., the response variable is a count. Poisson regression methods are used to describe the effect of the explanatory variables on the health event rates using a log-linear main effects model. Results of fitting the main effects model are summarized in a tabular and graphical form and interpretation of model parameters is provided. An analysis of deviance table is used to evaluate the importance of each of the explanatory variables on the event rate of interest and to determine if interaction terms should be considered in the analysis. Although Poisson regression methods are widely used in the analysis of count data, there are situations in which over-dispersion occurs. This could be due to lack-of-fit of the regression model, extra-Poisson variation, or both. A score test statistic and regression diagnostics are used to identify over-dispersion. A quasi-likelihood method of moments procedure is used to evaluate and adjust for extra-Poisson variation when necessary. Two examples are presented using respiratory disease absence rates at two DOE sites to illustrate the methods and interpretation of the results. In the first example the Poisson main effects model is adequate. In the second example the score test indicates considerable over-dispersion and a more detailed analysis attributes the over-dispersion to

Dropouts in Two-Year Colleges: Better Prediction with the Use of Moderator Subgroups.

ERIC Educational Resources Information Center

Capoor, Madan; Eagle, Norman

Failure to identify and account for the effect of moderator variables is an important reason for the low explanatory power of much educational research. Pre-existing subgroups such as sex, ethnicity, and curriculum offer an easily identifiable and theoretically meaningful source of moderator variables. Tests for intercept and slope differences in…

A Test of the Big Fish in a Little Pond Hypothesis: An Investigation into the Feelings of Seven-Year-Old Pupils in School.

ERIC Educational Resources Information Center

Tymms, Peter

2001-01-01

The feelings (self-concepts and attitudes) of 21,000 British 7-year-olds toward math, reading, and school were investigated using multivariate multilevel models. The most important explanatory variables were the teacher and pupils' academic level. Other variables (age, sex, and first language) were weakly connected to attitude measures. (Contains…

Determinants of Crime in Virginia: An Empirical Analysis

ERIC Educational Resources Information Center

Ali, Abdiweli M.; Peek, Willam

2009-01-01

This paper is an empirical analysis of the determinants of crime in Virginia. Over a dozen explanatory variables that current literature suggests as important determinants of crime are collected. The data is from 1970 to 2000. These include economic, fiscal, demographic, political, and social variables. The regression results indicate that crime…

Variables Associated with Grade R English Additional Language Acquisition in Multilingual Rural Mpumalanga Schools

ERIC Educational Resources Information Center

Moodley, P.; Kritzinger, A.; Vinck, B.

2016-01-01

In a previous study Moodley, Kritzinger and Vinck (2014) found that formal English Additional Language (EAL) instruction contributed significantly better to listening and speaking skills in Grade R learners, than did a play-based approach. The finding in multilingual rural Mpumalanga schools was in agreement with numerous studies elsewhere.…

Impact of Turbine Modulation on Variable-Cycle Engine Performance. Phase 4. Additional Hardware Design and Fabrication, Engine Modification, and Altitude Test. Part 3 B

DTIC Science & Technology

1974-12-01

urbofan engine performance. An AiKesearch Model TFE731 -2 Turbofan Engine was modified to incorporate production-type variable-geometry hardware...reliability was shown for the variable- geometry components. The TFE731 , modified to include variable geometry, proved to be an inexpensive...Atm at a Met Thrust of 3300 LBF 929 85 Variable-Cycle Engine TFE731 Exhaust-Nozzle Performance 948 86 Analytical Model Comparisons, Aerodynamic

Supersonic propulsion technology. [variable cycle engines

NASA Technical Reports Server (NTRS)

Powers, A. G.; Coltrin, R. E.; Stitt, L. E.; Weber, R. J.; Whitlow, J. B., Jr.

1979-01-01

Propulsion concepts for commercial supersonic transports are discussed. It is concluded that variable cycle engines, together with advanced supersonic inlets and low noise coannular nozzles, provide good operating performance for both supersonic and subsonic flight. In addition, they are reasonably quiet during takeoff and landing and have acceptable exhaust emissions.

Relations among Functional Systems in Behavior Analysis

PubMed Central

Thompson, Travis

2007-01-01

This paper proposes that an organism's integrated repertoire of operant behavior has the status of a biological system, similar to other biological systems, like the nervous, cardiovascular, or immune systems. Evidence from a number of sources indicates that the distinctions between biological and behavioral events is often misleading, engendering counterproductive explanatory controversy. A good deal of what is viewed as biological (often thought to be inaccessible or hypothetical) can become publicly measurable variables using currently available and developing technologies. Moreover, such endogenous variables can serve as establishing operations, discriminative stimuli, conjoint mediating events, and maintaining consequences within a functional analysis of behavior and need not lead to reductionistic explanation. I suggest that explanatory misunderstandings often arise from conflating different levels of analysis and that behavior analysis can extend its reach by identifying variables operating within a functional analysis that also serve functions in other biological systems. PMID:17575907

Application of response surface methodology in optimization of lactic acid fermentation of radish: effect of addition of salt, additives and growth stimulators.

PubMed

Joshi, V K; Chauhan, Arjun; Devi, Sarita; Kumar, Vikas

2015-08-01

Lactic acid fermentation of radish was conducted using various additive and growth stimulators such as salt (2 %-3 %), lactose, MgSO4 + MnSO4 and Mustard (1 %, 1.5 % and 2 %) to optimize the process. Response surface methodology (Design expert, Trial version 8.0.5.2) was applied to the experimental data for the optimization of process variables in lactic acid fermentation of radish. Out of various treatments studied, only the treatments having ground mustard had an appreciable effect on lactic acid fermentation. Both linear and quadratic terms of the variables studied had a significant effect on the responses studied. The interactions between the variables were found to contribute to the response at a significant level. The best results were obtained in the treatment with 2.5 % salt, 1.5 % lactose, 1.5 % (MgSO4 + MnSO4) and 1.5 % mustard. These optimized concentrations increased titrable acidity and LAB count, but lowered pH. The second-order polynomial regression model determined that the highest titrable acidity (1.69), lowest pH (2.49) and maximum LAB count (10 × 10(8) cfu/ml) would be obtained at these concentrations of additives. Among 30 runs conducted, run 2 has got the optimum concentration of salt- 2.5 %, lactose- 1.5 %, MgSO4 + MnSO4- 1.5 % and mustard- 1.5 % for lactic acid fermentation of radish. The values for different additives and growth stimulators optimized in this study could successfully be employed for the lactic acid fermentation of radish as a postharvest reduction tool and for product development.

Pilot Preferences on Displayed Aircraft Control Variables

NASA Technical Reports Server (NTRS)

Trujillo, Anna C.; Gregory, Irene M.

2013-01-01

The experiments described here explored how pilots want available maneuver authority information transmitted and how this information affects pilots before and after an aircraft failure. The aircraft dynamic variables relative to flight performance were narrowed to energy management variables. A survey was conducted to determine what these variables should be. Survey results indicated that bank angle, vertical velocity, and airspeed were the preferred variables. Based on this, two displays were designed to inform the pilot of available maneuver envelope expressed as bank angle, vertical velocity, and airspeed. These displays were used in an experiment involving control surface failures. Results indicate the displayed limitations in bank angle, vertical velocity, and airspeed were helpful to the pilots during aircraft surface failures. However, the additional information did lead to a slight increase in workload, a small decrease in perceived aircraft flying qualities, and no effect on aircraft situation awareness.

Variable pixel size ionospheric tomography

NASA Astrophysics Data System (ADS)

Zheng, Dunyong; Zheng, Hongwei; Wang, Yanjun; Nie, Wenfeng; Li, Chaokui; Ao, Minsi; Hu, Wusheng; Zhou, Wei

2017-06-01

A novel ionospheric tomography technique based on variable pixel size was developed for the tomographic reconstruction of the ionospheric electron density (IED) distribution. In variable pixel size computerized ionospheric tomography (VPSCIT) model, the IED distribution is parameterized by a decomposition of the lower and upper ionosphere with different pixel sizes. Thus, the lower and upper IED distribution may be very differently determined by the available data. The variable pixel size ionospheric tomography and constant pixel size tomography are similar in most other aspects. There are some differences between two kinds of models with constant and variable pixel size respectively, one is that the segments of GPS signal pay should be assigned to the different kinds of pixel in inversion; the other is smoothness constraint factor need to make the appropriate modified where the pixel change in size. For a real dataset, the variable pixel size method distinguishes different electron density distribution zones better than the constant pixel size method. Furthermore, it can be non-chided that when the effort is spent to identify the regions in a model with best data coverage. The variable pixel size method can not only greatly improve the efficiency of inversion, but also produce IED images with high fidelity which are the same as a used uniform pixel size method. In addition, variable pixel size tomography can reduce the underdetermined problem in an ill-posed inverse problem when the data coverage is irregular or less by adjusting quantitative proportion of pixels with different sizes. In comparison with constant pixel size tomography models, the variable pixel size ionospheric tomography technique achieved relatively good results in a numerical simulation. A careful validation of the reliability and superiority of variable pixel size ionospheric tomography was performed. Finally, according to the results of the statistical analysis and quantitative comparison, the

Insight in psychosis: Standards, science, ethics and value judgment.

PubMed

Jacob, K S

2017-06-01

The clinical assessment of insight solely employs biomedical perspectives and criteria to the complete exclusion of context and culture and to the disregard of values and value judgments. The aim of this discussion article is to examine recent research from India on insight and explanatory models in psychosis and re-examine the framework of assessment, diagnosis and management of insight and explanatory models. Recent research from India on insight in psychosis and explanatory models is reviewed. Recent research, which has used longitudinal data and adjusted for pretreatment variables, suggests that insight and explanatory models of illness at baseline do not predict course, outcome and treatment response in schizophrenia, which seem to be dependent on the severity and quality of the psychosis. It supports the view that people with psychosis simultaneously hold multiple and contradictory explanatory models of illness, which change over time and with the trajectory of the illness. It suggests that insight, like all explanatory models, is a narrative of the person's reality and a coping strategy to handle with the varied impact of the illness. This article argues that the assessment of insight necessarily involves value entailments, commitments and consequences. It supports a need for a broad-based approach to assess awareness, attribution and action related to mental illness and to acknowledge the role of values and value judgment in the evaluation of insight in psychosis.

The Association between Sleep Disturbances and Depression among Firefighters: Emotion Dysregulation as an Explanatory Factor

PubMed Central

Hom, Melanie A.; Stanley, Ian H.; Rogers, Megan L.; Tzoneva, Mirela; Bernert, Rebecca A.; Joiner, Thomas E.

2016-01-01

Study Objectives: To investigate emotion regulation difficulties in association with self-reported insomnia symptoms, nightmares, and depression symptoms in a sample of current and retired firefighters. Methods: A total of 880 current and retired United States firefighters completed a web-based survey of firefighter behavioral health. Self-report measures included the Center for Epidemiologic Studies Depression Scale, Insomnia Severity Index, PTSD Checklist, and Difficulties in Emotion Regulation Scale. Results: A notable portion of participants reported clinically significant depression symptoms (39.6%) and insomnia symptoms (52.7%), as well as nightmare problems (19.2%), each of which demonstrated a strong association with emotion regulation difficulties (rs = 0.56–0.80). Bootstrapped mediation analyses revealed that the indirect effects of overall emotion regulation difficulties were significant both for the relationship between insomnia and depression (95% CI: 0.385–0.566) and nightmares and depression (95% CI: 1.445–2.365). Limited access to emotion regulation strategies emerged as the strongest, significant indirect effect for both relationships (insomnia 95% CI: 0.136–0.335; nightmares 95% CI: 0.887–1.931). Conclusions: Findings extend previous affective neuroscience research by providing evidence that insomnia and nightmares may influence depression symptoms specifically through the pathway of explicit emotion regulation difficulties. Sleep disturbances may impair the ability to access and leverage emotion regulation strategies effectively, thus conferring risk for negative affect and depression. Citation: Hom MA, Stanley IH, Rogers ML, Tzoneva M, Bernert RA, Joiner TE. The association between sleep disturbances and depression among firefighters: emotion dysregulation as an explanatory factor. J Clin Sleep Med 2016;12(2):235–245. PMID:26350604

Linking environmental variability to population and community dynamics: Chapter 7

USGS Publications Warehouse

Pantel, Jelena H.; Pendleton, Daniel E.; Walters, Annika W.; Rogers, Lauren A.

2014-01-01

Linking population and community responses to environmental variability lies at the heart of ecology, yet methodological approaches vary and existence of broad patterns spanning taxonomic groups remains unclear. We review the characteristics of environmental and biological variability. Classic approaches to link environmental variability to population and community variability are discussed as are the importance of biotic factors such as life history and community interactions. In addition to classic approaches, newer techniques such as information theory and artificial neural networks are reviewed. The establishment and expansion of observing networks will provide new long-term ecological time-series data, and with it, opportunities to incorporate environmental variability into research. This review can help guide future research in the field of ecological and environmental variability.

Bayesian Group Bridge for Bi-level Variable Selection.

PubMed

Mallick, Himel; Yi, Nengjun

2017-06-01

A Bayesian bi-level variable selection method (BAGB: Bayesian Analysis of Group Bridge) is developed for regularized regression and classification. This new development is motivated by grouped data, where generic variables can be divided into multiple groups, with variables in the same group being mechanistically related or statistically correlated. As an alternative to frequentist group variable selection methods, BAGB incorporates structural information among predictors through a group-wise shrinkage prior. Posterior computation proceeds via an efficient MCMC algorithm. In addition to the usual ease-of-interpretation of hierarchical linear models, the Bayesian formulation produces valid standard errors, a feature that is notably absent in the frequentist framework. Empirical evidence of the attractiveness of the method is illustrated by extensive Monte Carlo simulations and real data analysis. Finally, several extensions of this new approach are presented, providing a unified framework for bi-level variable selection in general models with flexible penalties.

[Variability in nursing workload within Swiss Diagnosis Related Groups].

PubMed

Baumberger, Dieter; Bürgin, Reto; Bartholomeyczik, Sabine

2014-04-01