Dimensional structure of DSM-5 posttraumatic stress symptoms: support for a hybrid Anhedonia and Externalizing Behaviors model.

PubMed

Armour, Cherie; Tsai, Jack; Durham, Tory A; Charak, Ruby; Biehn, Tracey L; Elhai, Jon D; Pietrzak, Robert H

2015-02-01

Several revisions to the symptom clusters of posttraumatic stress disorder (PTSD) have been made in the 5th edition of the Diagnostic and Statistical Manual of Mental Disorders (DSM-5). Central to the focus of this study was the revision of PTSD's tripartite structure in DSM-IV into four symptom clusters in DSM-5. Emerging confirmatory factor analytic (CFA) studies have suggested that DSM-5 PTSD symptoms may be best represented by one of two 6-factor models: (1) an Externalizing Behaviors model characterized by a factor which combines the irritability/anger and self-destructive/reckless behavior items; and (2) an Anhedonia model characterized by items of loss of interest, detachment, and restricted affect. The current study conducted CFAs of DSM-5 PTSD symptoms assessed using the PTSD Checklist for DSM-5 (PCL-5) in two independent and diverse trauma-exposed samples of a nationally representative sample of 1484 U.S. veterans and a sample of 497 Midwestern U.S. university undergraduate students. Relative fits of the DSM-5 model, the DSM-5 Dysphoria model, the DSM-5 Dysphoric Arousal model, the two 6-factor models, and a newly proposed 7-factor Hybrid model, which consolidates the two 6-factor models, were evaluated. Results revealed that, in both samples, both 6-factor models provided significantly better fit than the 4-factor DSM-5 model, the DSM-5 Dysphoria model and the DSM-5 Dysphoric Arousal model. Further, the 7-factor Hybrid model, which incorporates key features of both 6-factor models and is comprised of re-experiencing, avoidance, negative affect, anhedonia, externalizing behaviors, and anxious and dysphoric arousal symptom clusters, provided superior fit to the data in both samples. Results are discussed in light of theoretical and empirical support for the latent structure of DSM-5 PTSD symptoms. Copyright © 2014 Elsevier Ltd. All rights reserved.

User acceptance of mobile commerce: an empirical study in Macau

NASA Astrophysics Data System (ADS)

Lai, Ivan K. W.; Lai, Donny C. F.

2014-06-01

This study aims to examine the positive and negative factors that can significantly explain user acceptance of mobile commerce (m-commerce) in Macau. A technology acceptance model for m-commerce with five factors is constructed. The proposed model is tested using data collected from 219 respondents. Confirmatory factor analysis is performed to examine the reliability and validity of the model, and structural equation modelling is performed to access the relationship between behaviour intention and each factor. The acceptance of m-commerce is influenced by factors including performance expectancy, social influence, facilitating conditions and privacy concern; while effort expectancy is insignificant in this case. The results of the study are useful for m-commerce service providers to adjust their strategies for promoting m-commerce services. This study contributes to the practice by providing a user technology acceptance model for m-commerce that can be used as a foundation for future research.

A confirmatory factor analysis of the Impact of Event Scale using a sample of World War II and Korean War veterans.

PubMed

Shevlin, M; Hunt, N; Robbins, I

2000-12-01

This study assessed the factor structure of the Impact of Event Scale (IES), a measure of intrusion and avoidance, using a sample of World War II and Korean War veterans who had experienced combat 40-50 years earlier. A series of 3 confirmatory factor analytic models were specified and estimated using LISREL 8.3. Model 1 specified a 1-factor model. Model 2 specified a correlated 2-factor model. Model 3 specified a 2-factor model with additional cross-factor loadings for Items 2 and 12. Model 3 was found to fit the data. In addition, this model was found to be a better explanation of the data than the other models. Also in addition, the correlations between the Intrusion and Avoidance factors and the 4 subscales of the 28-item General Health Questionnaire were examined to determine the distinctiveness of the two IES factors.

Factors affecting smartphone adoption for accessing information in medical settings.

PubMed

Tahamtan, Iman; Pajouhanfar, Sara; Sedghi, Shahram; Azad, Mohsen; Roudbari, Masoud

2017-06-01

This study aimed to acquire knowledge about the factors affecting smartphone adoption for accessing information in medical settings in Iranian Hospitals. A qualitative and quantitative approach was used to conduct this study. Semi-structured interviews were conducted with 21 medical residents and interns in 2013 to identify determinant factors for smartphone adoption. Afterwards, nine relationships were hypothesised. We developed a questionnaire to test these hypotheses and to evaluate the importance of each factor. Structural equation modelling was used to analyse the causal relations between model parameters and to accurately identify determinant factors. Eight factors were identified in the qualitative phase of the study, including perceived usefulness, perceived ease of use, training, internal environment, personal experience, social impacts, observability and job related characteristics. Among the studied factors, perceived usefulness, personal experience and job related characteristics were significantly associated with attitude to use a smartphone which accounted for 64% of the variance in attitude. Perceived usefulness had the strongest impact on attitude to use a smartphone. The factors that emerged from interviews were consistent with the Technology Acceptance Model (TAM) and some previous studies. TAM is a reliable model for understanding the factors of smartphone acceptance in medical settings. © 2017 Health Libraries Group.

The Effects of Autocorrelation on the Curve-of-Factors Growth Model

ERIC Educational Resources Information Center

Murphy, Daniel L.; Beretvas, S. Natasha; Pituch, Keenan A.

2011-01-01

This simulation study examined the performance of the curve-of-factors model (COFM) when autocorrelation and growth processes were present in the first-level factor structure. In addition to the standard curve-of factors growth model, 2 new models were examined: one COFM that included a first-order autoregressive autocorrelation parameter, and a…

Interaction in Balanced Cross Nested Designs

NASA Astrophysics Data System (ADS)

Ramos, Paulo; Mexia, João T.; Carvalho, Francisco; Covas, Ricardo

2011-09-01

Commutative Jordan Algebras, CJA, are used in the study of mixed models obtained, through crossing and nesting, from simpler ones. In the study of cross nested models the interaction between nested factors have been systematically discarded. However this can constitutes an artificial simplification of the models. We point out that, when two crossed factors interact, such interaction is symmetric, both factors playing in it equivalent roles, while when two nested factors interact, the interaction is determined by the nesting factor. These interactions will be called interactions with nesting. In this work we present a coherent formulation of the algebraic structure of models enabling the choice of families of interactions between cross and nested factors using binary operations on CJA.

The structural invariance of the Temporal Experience of Pleasure Scale across time and culture.

PubMed

Li, Zhi; Shi, Hai-Song; Elis, Ori; Yang, Zhuo-Ya; Wang, Ya; Lui, Simon S Y; Cheung, Eric F C; Kring, Ann M; Chan, Raymond C K

2018-06-01

The Temporal Experience of Pleasure Scale (TEPS) is a self-report instrument that assesses pleasure experience. Initial scale development and validation in the United States yielded a two-factor solution comprising anticipatory and consummatory pleasure. However, a four-factor model that further parsed anticipatory and consummatory pleasure experience into abstract and contextual components was a better model fit in China. In this study, we tested both models using confirmatory factor analysis in an American and a Chinese sample and examined the configural measurement invariance of both models across culture. We also examined the temporal stability of the four-factor model in the Chinese sample. The results indicated that the four-factor model of the TEPS was a better fit than the two-factor model in the Chinese sample. In contrast, both models fit the American sample, which also included many Asian American participants. The four-factor model fit both the Asian American and Chinese samples equally well. Finally, the four-factor model demonstrated good measurement and structural invariance across culture and time, suggesting that this model may be applicable in both cross-cultural and longitudinal studies. © 2018 The Institute of Psychology, Chinese Academy of Sciences and John Wiley & Sons Australia, Ltd.

Theoretical implementation of prior knowledge in the design of a multi-scale prosthesis satisfaction questionnaire.

PubMed

Schürmann, Tim; Beckerle, Philipp; Preller, Julia; Vogt, Joachim; Christ, Oliver

2016-12-19

In product development for lower limb prosthetic devices, a set of special criteria needs to be met. Prosthetic devices have a direct impact on the rehabilitation process after an amputation with both perceived technological and psychological aspects playing an important role. However, available psychometric questionnaires fail to consider the important links between these two dimensions. In this article a probabilistic latent trait model is proposed with seven technical and psychological factors which measure satisfaction with the prosthesis. The results of a first study are used to determine the basic parameters of the statistical model. These distributions represent hypotheses about factor loadings between manifest items and latent factors of the proposed psychometric questionnaire. A study was conducted and analyzed to form hypotheses for the prior distributions of the questionnaire's measurement model. An expert agreement study conducted on 22 experts was used to determine the prior distribution of item-factor loadings in the model. Model parameters that had to be specified as part of the measurement model were informed prior distributions on the item-factor loadings. For the current 70 items in the questionnaire, each factor loading was set to represent the certainty with which experts had assigned the items to their respective factors. Considering only the measurement model and not the structural model of the questionnaire, 70 out of 217 informed prior distributions on parameters were set. The use of preliminary studies to set prior distributions in latent trait models, while being a relatively new approach in psychological research, provides helpful information towards the design of a seven factor questionnaire that means to identify relations between technical and psychological factors in prosthetic product design and rehabilitation medicine.

Factor structure of parent and teacher ratings of the ODD symptoms for Malaysian primary school children.

PubMed

Gomez, Rapson

2017-02-01

This present study used confirmatory factor analysis (CFA) to examine the applicability of one-, two- three- and second order Oppositional Defiant Disorder (ODD) factor models, proposed in previous studies, in a group of Malaysian primary school children. These models were primarily based on parent reports. In the current study, parent and teacher ratings of the ODD symptoms were obtained for 934 children. For both groups of respondents, the findings showing some support for all models examined, with most support for a second order model with Burke et al. (2010) three factors (oppositional, antagonistic, and negative affect) as the primary factors. The diagnostic implications of the findings are discussed. Copyright © 2016 Elsevier B.V. All rights reserved.

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

PubMed

Saucier, Gerard

2009-10-01

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

Bifactor Models Show a Superior Model Fit: Examination of the Factorial Validity of Parent-Reported and Self-Reported Symptoms of Attention-Deficit/Hyperactivity Disorders in Children and Adolescents.

PubMed

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

2016-01-01

Various studies have demonstrated that bifactor models yield better solutions than models with correlated factors. However, the kind of bifactor model that is most appropriate is yet to be examined. The current study is the first to test bifactor models across the full age range (11-18 years) of adolescents using self-reports, and the first to test bifactor models with German subjects and German questionnaires. The study sample included children and adolescents aged between 6 and 18 years recruited from a German clinical sample (n = 1,081) and a German community sample (n = 642). To examine the factorial validity, we compared unidimensional, correlated factors and higher-order and bifactor models and further tested a modified incomplete bifactor model for measurement invariance. Bifactor models displayed superior model fit statistics compared to correlated factor models or second-order models. However, a more parsimonious incomplete bifactor model with only 2 specific factors (inattention and impulsivity) showed a good model fit and a better factor structure than the other bifactor models. Scalar measurement invariance was given in most group comparisons. An incomplete bifactor model would suggest that the specific inattention and impulsivity factors represent entities separable from the general attention-deficit/hyperactivity disorder construct and might, therefore, give way to a new approach to subtyping of children beyond and above attention-deficit/hyperactivity disorder. © 2016 S. Karger AG, Basel.

Quantitative Analysis of Intra Urban Growth Modeling using socio economic agents by combining cellular automata model with agent based model

NASA Astrophysics Data System (ADS)

Singh, V. K.; Jha, A. K.; Gupta, K.; Srivastav, S. K.

2017-12-01

Recent studies indicate that there is a significant improvement in the urban land use dynamics through modeling at finer spatial resolutions. Geo-computational models such as cellular automata and agent based model have given evident proof regarding the quantification of the urban growth pattern with urban boundary. In recent studies, socio- economic factors such as demography, education rate, household density, parcel price of the current year, distance to road, school, hospital, commercial centers and police station are considered to the major factors influencing the Land Use Land Cover (LULC) pattern of the city. These factors have unidirectional approach to land use pattern which makes it difficult to analyze the spatial aspects of model results both quantitatively and qualitatively. In this study, cellular automata model is combined with generic model known as Agent Based Model to evaluate the impact of socio economic factors on land use pattern. For this purpose, Dehradun an Indian city is selected as a case study. Socio economic factors were collected from field survey, Census of India, Directorate of economic census, Uttarakhand, India. A 3X3 simulating window is used to consider the impact on LULC. Cellular automata model results are examined for the identification of hot spot areas within the urban area and agent based model will be using logistic based regression approach where it will identify the correlation between each factor on LULC and classify the available area into low density, medium density, high density residential or commercial area. In the modeling phase, transition rule, neighborhood effect, cell change factors are used to improve the representation of built-up classes. Significant improvement is observed in the built-up classes from 84 % to 89 %. However after incorporating agent based model with cellular automata model the accuracy improved from 89 % to 94 % in 3 classes of urban i.e. low density, medium density and commercial classes. Sensitivity study of the model indicated that southern and south-west part of the city have shown improvement and small patches of growth are also observed in the north western part of the city.The study highlights the growing importance of socio economic factors and geo-computational modeling approach on changing LULC of newly growing cities of modern India.

Factors influencing a problem-based learning implementation: A case study of IT courses

NASA Astrophysics Data System (ADS)

Darus, Norida Muhd; Mohd, Haslina; Baharom, Fauziah; Saip, Mohamed Ali; Puteh, Nurnasran; Marzuki @ Matt, Zaharin; Husain, Mohd Zabidin; Yasin, Azman

2016-08-01

IT students must be trained to work efficiently as teamwork. One of the techniques that can be used to train them is through Problem-Based Learning (PBL) approach. The PBL implementation can be influenced by various factors depending on the ultimate goal of the study. This study is focusing on the IT students' perception of the PBL implementation. The student's perception is important to ensure the successfulness of the PBL implementation. Therefore, it is important to identify the factors that might influence the implementation of PBL of IT courses. This study aims to identify some catalyst factors that may influence the PBL implementation of IT courses. The study involved three (3) main phases: identifying PBL implementation factors, constructing a PBL model, and PBL model validation using statistical analysis. Four main factors are identified: PBL Characteristics, PBL Course Assessment, PBL Practices, and PBL Perception. Based on these four factors, a PBL model is constructed. Then, based on the proposed PBL model, four hypotheses are formulated and analyzed to validate the model. All hypotheses are significantly acceptable. The result shows that the PBL Characteristics and PBL Course Assessment factors are significantly influenced the PBL Practices and indirectly influenced the Students' Perception of the PBL Implementation for IT courses. This PBL model can assist decision makers in enhancing the PBL teaching and learning strategy for IT courses. It is also can be tested to other courses in the future.

Implicit theories of a desire for fame.

PubMed

Maltby, John; Day, Liz; Giles, David; Gillett, Raphael; Quick, Marianne; Langcaster-James, Honey; Linley, P Alex

2008-05-01

The aim of the present studies was to generate implicit theories of a desire for fame among the general population. In Study 1, we were able to develop a nine-factor analytic model of conceptions of the desire to be famous that initially comprised nine separate factors; ambition, meaning derived through comparison with others, psychologically vulnerable, attention seeking, conceitedness, social access, altruistic, positive affect, and glamour. Analysis that sought to examine replicability among these factors suggested that three factors (altruistic, positive affect, and glamour) neither display factor congruence nor display adequate internal reliability. A second study examined the validity of these factors in predicting profiles of individuals who may desire fame. The findings from this study suggested that two of the nine factors (positive affect and altruism) could not be considered strong factors within the model. Overall, the findings suggest that implicit theories of a desire for fame comprise six factors. The discussion focuses on how an implicit model of a desire for fame might progress into formal theories of a desire for fame.

The High Five: Associations of the Five Positive Factors with the Big Five and Well-being.

PubMed

Cosentino, Alejandro C; Castro Solano, Alejandro

2017-01-01

The study of individual differences in positive characteristics has mainly focused on moral traits. The objectives of this research were to study individual differences in positive characteristics from the point of view of the layperson, including non-moral individual characteristics, and to generate a replicable model of positive factors. Three studies based on a lexical approach were conducted. The first study generated a corpus of words which resulted in a refined list of socially shared positive characteristics. The second study produced a five-factor model of positive characteristics: erudition, peace, cheerfulness, honesty, and tenacity. The third study confirmed the model with a different sample. The five-positive-factor model not only showed positive associations with emotional, psychological and social well-being, but it also accounted for the variance beyond that accounted for by the Big Five factors in predicting these well-being dimensions. In addition, the presence of convergent and divergent validity of the five positive factors is shown with relation to the Values-in-Action (VIA) classification of character strengths proposed by Peterson and Seligman (2004).

The High Five: Associations of the Five Positive Factors with the Big Five and Well-being

PubMed Central

Cosentino, Alejandro C.; Castro Solano, Alejandro

2017-01-01

The study of individual differences in positive characteristics has mainly focused on moral traits. The objectives of this research were to study individual differences in positive characteristics from the point of view of the layperson, including non-moral individual characteristics, and to generate a replicable model of positive factors. Three studies based on a lexical approach were conducted. The first study generated a corpus of words which resulted in a refined list of socially shared positive characteristics. The second study produced a five-factor model of positive characteristics: erudition, peace, cheerfulness, honesty, and tenacity. The third study confirmed the model with a different sample. The five-positive-factor model not only showed positive associations with emotional, psychological and social well-being, but it also accounted for the variance beyond that accounted for by the Big Five factors in predicting these well-being dimensions. In addition, the presence of convergent and divergent validity of the five positive factors is shown with relation to the Values-in-Action (VIA) classification of character strengths proposed by Peterson and Seligman (2004). PMID:28790947

[Psychosocial factors at work and cardiovascular diseases: contribution of the Effort-Reward Imbalance model].

PubMed

Niedhammer, I; Siegrist, J

1998-11-01

The effect of psychosocial factors at work on health, especially cardiovascular health, has given rise to growing concern in occupational epidemiology over the last few years. Two theoretical models, Karasek's model and the Effort-Reward Imbalance model, have been developed to evaluate psychosocial factors at work within specific conceptual frameworks in an attempt to take into account the serious methodological difficulties inherent in the evaluation of such factors. Karasek's model, the most widely used model, measures three factors: psychological demands, decision latitude and social support at work. Many studies have shown the predictive effects of these factors on cardiovascular diseases independently of well-known cardiovascular risk factors. More recently, the Effort-Reward Imbalance model takes into account the role of individual coping characteristics which was neglected in the Karasek model. The effort-reward imbalance model focuses on the reciprocity of exchange in occupational life where high-cost/low-gain conditions are considered particularly stressful. Three dimensions of rewards are distinguished: money, esteem and gratifications in terms of promotion prospects and job security. Some studies already support that high-effort/low reward-conditions are predictive of cardiovascular diseases.

A Multi-Domain Model of Risk Factors for ODD Symptoms in a Community Sample of 4-Year-Olds

ERIC Educational Resources Information Center

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

2012-01-01

Few studies have been designed to assess the pathways by which risk factors are associated with symptoms of psychopathology across multiple domains, including contextual factors, parental depression, parenting, and child characteristics. The present study examines a cross-sectional model of risk factors for symptoms of Oppositional Defiant…

Quantitative analysis of factors that affect oil pipeline network accident based on Bayesian networks: A case study in China

NASA Astrophysics Data System (ADS)

Zhang, Chao; Qin, Ting Xin; Huang, Shuai; Wu, Jian Song; Meng, Xin Yan

2018-06-01

Some factors can affect the consequences of oil pipeline accident and their effects should be analyzed to improve emergency preparation and emergency response. Although there are some qualitative analysis models of risk factors' effects, the quantitative analysis model still should be researched. In this study, we introduce a Bayesian network (BN) model of risk factors' effects analysis in an oil pipeline accident case that happened in China. The incident evolution diagram is built to identify the risk factors. And the BN model is built based on the deployment rule for factor nodes in BN and the expert knowledge by Dempster-Shafer evidence theory. Then the probabilities of incident consequences and risk factors' effects can be calculated. The most likely consequences given by this model are consilient with the case. Meanwhile, the quantitative estimations of risk factors' effects may provide a theoretical basis to take optimal risk treatment measures for oil pipeline management, which can be used in emergency preparation and emergency response.

The Social Anxiety and Depression Life Interference—24 Inventory: Classical and modern psychometric evaluations

PubMed Central

Berzins, Tiffany L.; Garcia, Antonio F.; Acosta, Melina; Osman, Augustine

2017-01-01

Two instrument validation studies broadened the research literature exploring the factor structure, internal consistency reliability, and concurrent validity of scores on the Social Anxiety and Depression Life Interference—24 Inventory (SADLI-24; Osman, Bagge, Freedenthal, Guiterrez, & Emmerich, 2011). Study 1 (N = 1065) was undertaken to concurrently appraise three competing factor models for the instrument: a unidimensional model, a two-factor oblique model and a bifactor model. The bifactor model provided the best fit to the study sample data. Study 2 (N = 220) extended the results from Study 1 with an investigation of the convergent and discriminant validity for the bifactor model of the SADLI-24 with multiple regression analyses and scale-level exploratory structural equation modeling. This project yields data that augments the initial instrument development investigations for the target measure. PMID:28781401

Exploratory and Confirmatory Factor Analysis of the Career Decision-Making Difficulties Questionnaire

PubMed Central

Farrokhi, Farahman; Mahdavi, Ali; Moradi, Samad

2012-01-01

Objective The present study aimed at validating the structure of Career Decision-making Difficulties Questionnaire (CDDQ). Methods Five hundred and eleven undergraduate students took part in this research; from these participants, 63 males and 200 females took part in the first study, and 63 males and 185 females completed the survey for the second study. Results The results of exploratory factor analysis (EFA) indicated strong support for the three-factor structure, consisting of lack of information about the self, inconsistent information, lack of information and lack of readiness factors. A confirmatory factor analysis was run with the second sample using structural equation modeling. As expected, the three-factor solution provided a better fit to the data than the alternative models. Conclusion CDDQ was recommended to be used for college students in this study due to the fact that this instrument measures all three aspects of the model. Future research is needed to learn whether this model would fit other different samples. PMID:22952549

Factor structure of a conceptual model of oral health tested among 65-year olds in Norway and Sweden.

PubMed

Astrøm, Anne Nordrehaug; Ekbäck, Gunnar; Ordell, Sven

2010-04-01

No studies have tested oral health-related quality of life models in dentate older adults across different populations. To test the factor structure of oral health outcomes within Gilbert's conceptual model among 65-year olds in Sweden and Norway. It was hypothesized that responses to 14 observed indicators could be explained by three correlated factors, symptom status, functional limitations and oral disadvantages, that each observed oral health indicator would associate more strongly with the factor it is supposed to measure than with competing factors and that the proposed 3-factor structure would possess satisfactory cross-national stability with 65-year olds in Norway and Sweden. In 2007, 6078 Swedish- and 4062 Norwegian adults borne in 1942 completed mailed questionnaires including oral symptoms, functional limitations and the eight item Oral Impacts on Daily Performances inventory. Model generation analysis was restricted to the Norwegian study group and the model achieved was tested without modifications in Swedish 65-year olds. A modified 3-factor solution with cross-loadings, improved the fit to the data compared with a 2-factor- and the initially proposed 3-factor model among the Norwegian [comparative fit index (CFI) = 0.97] and Swedish (CFI = 0.98) participants. All factor loadings for the modified 3-factor model were in the expected direction and were statistically significant at CR > 1. Multiple group confirmatory factor analyses, with Norwegian and Swedish data simultaneously revealed acceptable fit for the unconstrained model (CFI = 0.97), whereas unconstrained and constrained models were statistically significant different in nested model comparison. Within construct validity of Gilbert's model was supported with Norwegian and Swedish 65-year olds, indicating that the 14-item questionnaire reflected three constructs; symptom status, functional limitation and oral disadvantage. Measurement invariance was confirmed at the level of factor structure, suggesting that the 3-factor model is comparable to some extent across 65-year olds in Norway and Sweden.

Components of Mathematics Anxiety: Factor Modeling of the MARS30-Brief

PubMed Central

Pletzer, Belinda; Wood, Guilherme; Scherndl, Thomas; Kerschbaum, Hubert H.; Nuerk, Hans-Christoph

2016-01-01

Mathematics anxiety involves feelings of tension, discomfort, high arousal, and physiological reactivity interfering with number manipulation and mathematical problem solving. Several factor analytic models indicate that mathematics anxiety is rather a multidimensional than unique construct. However, the factor structure of mathematics anxiety has not been fully clarified by now. This issue shall be addressed in the current study. The Mathematics Anxiety Rating Scale (MARS) is a reliable measure of mathematics anxiety (Richardson and Suinn, 1972), for which several reduced forms have been developed. Most recently, a shortened version of the MARS (MARS30-brief) with comparable reliability was published. Different studies suggest that mathematics anxiety involves up to seven different factors. Here we examined the factor structure of the MARS30-brief by means of confirmatory factor analysis. The best model fit was obtained by a six-factor model, dismembering the known two general factors “Mathematical Test Anxiety” (MTA) and “Numerical Anxiety” (NA) in three factors each. However, a more parsimonious 5-factor model with two sub-factors for MTA and three for NA fitted the data comparably well. Factors were differentially susceptible to sex differences and differences between majors. Measurement invariance for sex was established. PMID:26924996

Components of Mathematics Anxiety: Factor Modeling of the MARS30-Brief.

PubMed

Pletzer, Belinda; Wood, Guilherme; Scherndl, Thomas; Kerschbaum, Hubert H; Nuerk, Hans-Christoph

2016-01-01

Mathematics anxiety involves feelings of tension, discomfort, high arousal, and physiological reactivity interfering with number manipulation and mathematical problem solving. Several factor analytic models indicate that mathematics anxiety is rather a multidimensional than unique construct. However, the factor structure of mathematics anxiety has not been fully clarified by now. This issue shall be addressed in the current study. The Mathematics Anxiety Rating Scale (MARS) is a reliable measure of mathematics anxiety (Richardson and Suinn, 1972), for which several reduced forms have been developed. Most recently, a shortened version of the MARS (MARS30-brief) with comparable reliability was published. Different studies suggest that mathematics anxiety involves up to seven different factors. Here we examined the factor structure of the MARS30-brief by means of confirmatory factor analysis. The best model fit was obtained by a six-factor model, dismembering the known two general factors "Mathematical Test Anxiety" (MTA) and "Numerical Anxiety" (NA) in three factors each. However, a more parsimonious 5-factor model with two sub-factors for MTA and three for NA fitted the data comparably well. Factors were differentially susceptible to sex differences and differences between majors. Measurement invariance for sex was established.

Determining factors influencing survival of breast cancer by fuzzy logistic regression model.

PubMed

Nikbakht, Roya; Bahrampour, Abbas

2017-01-01

Fuzzy logistic regression model can be used for determining influential factors of disease. This study explores the important factors of actual predictive survival factors of breast cancer's patients. We used breast cancer data which collected by cancer registry of Kerman University of Medical Sciences during the period of 2000-2007. The variables such as morphology, grade, age, and treatments (surgery, radiotherapy, and chemotherapy) were applied in the fuzzy logistic regression model. Performance of model was determined in terms of mean degree of membership (MDM). The study results showed that almost 41% of patients were in neoplasm and malignant group and more than two-third of them were still alive after 5-year follow-up. Based on the fuzzy logistic model, the most important factors influencing survival were chemotherapy, morphology, and radiotherapy, respectively. Furthermore, the MDM criteria show that the fuzzy logistic regression have a good fit on the data (MDM = 0.86). Fuzzy logistic regression model showed that chemotherapy is more important than radiotherapy in survival of patients with breast cancer. In addition, another ability of this model is calculating possibilistic odds of survival in cancer patients. The results of this study can be applied in clinical research. Furthermore, there are few studies which applied the fuzzy logistic models. Furthermore, we recommend using this model in various research areas.

Recent development of risk-prediction models for incident hypertension: An updated systematic review

PubMed Central

Xiao, Lei; Liu, Ya; Wang, Zuoguang; Li, Chuang; Jin, Yongxin; Zhao, Qiong

2017-01-01

Background Hypertension is a leading global health threat and a major cardiovascular disease. Since clinical interventions are effective in delaying the disease progression from prehypertension to hypertension, diagnostic prediction models to identify patient populations at high risk for hypertension are imperative. Methods Both PubMed and Embase databases were searched for eligible reports of either prediction models or risk scores of hypertension. The study data were collected, including risk factors, statistic methods, characteristics of study design and participants, performance measurement, etc. Results From the searched literature, 26 studies reporting 48 prediction models were selected. Among them, 20 reports studied the established models using traditional risk factors, such as body mass index (BMI), age, smoking, blood pressure (BP) level, parental history of hypertension, and biochemical factors, whereas 6 reports used genetic risk score (GRS) as the prediction factor. AUC ranged from 0.64 to 0.97, and C-statistic ranged from 60% to 90%. Conclusions The traditional models are still the predominant risk prediction models for hypertension, but recently, more models have begun to incorporate genetic factors as part of their model predictors. However, these genetic predictors need to be well selected. The current reported models have acceptable to good discrimination and calibration ability, but whether the models can be applied in clinical practice still needs more validation and adjustment. PMID:29084293

Examining the ethnoracial invariance of a bifactor model of anxiety sensitivity and the incremental validity of the physical domain-specific factor in a primary-care patient sample.

PubMed

Fergus, Thomas A; Kelley, Lance P; Griggs, Jackson O

2017-10-01

There is growing support for a bifactor conceptualization of the Anxiety Sensitivity Index-3 (ASI-3; Taylor et al., 2007), consisting of a General factor and 3 domain-specific factors (i.e., Physical, Cognitive, Social). Earlier studies supporting a bifactor model of the ASI-3 used samples that consisted of predominantly White respondents. In addition, extant research has yet to support the incremental validity of the Physical domain-specific factor while controlling for the General factor. The present study is an examination of a bifactor model of the ASI-3 and the measurement invariance of that model among an ethnoracially diverse sample of primary-care patients (N = 533). Results from multiple-group confirmatory factor analysis supported the configural and metric/scalar invariance of the bifactor model of the ASI-3 across self-identifying Black, Latino, and White respondents. The Physical domain-specific factor accounted for unique variance in an index of health anxiety beyond the General factor. These results provide support for the generalizability of a bifactor model of the ASI-3 across 3 ethnoracial groups, as well as indication of the incremental explanatory power of the Physical domain-specific factor. Study implications are discussed. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

Beyond factor analysis: Multidimensionality and the Parkinson's Disease Sleep Scale-Revised.

PubMed

Pushpanathan, Maria E; Loftus, Andrea M; Gasson, Natalie; Thomas, Meghan G; Timms, Caitlin F; Olaithe, Michelle; Bucks, Romola S

2018-01-01

Many studies have sought to describe the relationship between sleep disturbance and cognition in Parkinson's disease (PD). The Parkinson's Disease Sleep Scale (PDSS) and its variants (the Parkinson's disease Sleep Scale-Revised; PDSS-R, and the Parkinson's Disease Sleep Scale-2; PDSS-2) quantify a range of symptoms impacting sleep in only 15 items. However, data from these scales may be problematic as included items have considerable conceptual breadth, and there may be overlap in the constructs assessed. Multidimensional measurement models, accounting for the tendency for items to measure multiple constructs, may be useful more accurately to model variance than traditional confirmatory factor analysis. In the present study, we tested the hypothesis that a multidimensional model (a bifactor model) is more appropriate than traditional factor analysis for data generated by these types of scales, using data collected using the PDSS-R as an exemplar. 166 participants diagnosed with idiopathic PD participated in this study. Using PDSS-R data, we compared three models: a unidimensional model; a 3-factor model consisting of sub-factors measuring insomnia, motor symptoms and obstructive sleep apnoea (OSA) and REM sleep behaviour disorder (RBD) symptoms; and, a confirmatory bifactor model with both a general factor and the same three sub-factors. Only the confirmatory bifactor model achieved satisfactory model fit, suggesting that PDSS-R data are multidimensional. There were differential associations between factor scores and patient characteristics, suggesting that some PDSS-R items, but not others, are influenced by mood and personality in addition to sleep symptoms. Multidimensional measurement models may also be a helpful tool in the PDSS and the PDSS-2 scales and may improve the sensitivity of these instruments.

Investigation of the factor structure of spirituality and religiosity in Iranian Shiite university students.

PubMed

Joshanloo, Mohsen

2012-01-01

One of the important challenges facing psychologists of religion pertains to the definition of religiosity and spirituality. One way of understanding the connection between these two concepts is to suppose that one of them is a subset of the other. Another useful and sensitive way, however, is to view spirituality and religiosity as overlapping constructs, sharing some characteristics but also retaining nonshared features. Empirical studies examining the factor structure of spirituality and religiosity are scant and almost all of them come from Western culture. These factor analytic studies generally confirm that religiosity and spirituality can best be described in terms of two distinct yet correlated factors. To date, no study has investigated the relationship between these two constructs in Islamic cultures. To redress this imbalance, confirmatory factor analysis was used to examine the factor structure of religiosity and spirituality in two Iranian Shiite samples using an extensive set of scales (including Santa Clara Strength of Religious Faith, Spiritual Involvement and Beliefs Scale - Revised, Spiritual Meaning Scale, and Spiritual Transcendence Scale). Two hypothetical models were tested: a model that viewed spirituality and religiosity as correlated but separate constructs and a model that combined the indicators of religiosity and spirituality into a single construct. In keeping with the results obtained in Western cultures, results of confirmatory factor analyses, conducted in Study 1 (N=225) and Study 2 (N=288), revealed that a two-factor model fitted the data better than a single-factor model. Implications of the results are discussed, as are study limitations and directions for further research.

Psychometric Properties of the “Sport Motivation Scale (SMS)” Adapted to Physical Education

PubMed Central

Granero-Gallegos, Antonio; Baena-Extremera, Antonio; Gómez-López, Manuel; Sánchez-Fuentes, José Antonio; Abraldes, J. Arturo

2014-01-01

The aim of this study was to investigate the factor structure of a Spanish version of the Sport Motivation Scale adapted to physical education. A second aim was to test which one of three hypothesized models (three, five and seven-factor) provided best model fit. 758 Spanish high school students completed the Sport Motivation Scale adapted for Physical Education and also completed the Learning and Performance Orientation in Physical Education Classes Questionnaire. We examined the factor structure of each model using confirmatory factor analysis and also assessed internal consistency and convergent validity. The results showed that all three models in Spanish produce good indicators of fitness, but we suggest using the seven-factor model (χ2/gl = 2.73; ECVI = 1.38) as it produces better values when adapted to physical education, that five-factor model (χ2/gl = 2.82; ECVI = 1.44) and three-factor model (χ2/gl = 3.02; ECVI = 1.53). Key Points Physical education research conducted in Spain has used the version of SMS designed to assess motivation in sport, but validity reliability and validity results in physical education have not been reported. Results of the present study lend support to the factorial validity and internal reliability of three alternative factor structures (3, 5, and 7 factors) of SMS adapted to Physical Education in Spanish. Although all three models in Spanish produce good indicators of fitness, but we suggest using the seven-factor model. PMID:25435772

Exploratory Study of Factors Influencing Job-Related Stress in Japanese Psychiatric Nurses

PubMed Central

Yada, Hironori; Lu, Xi; Omori, Hisamitsu; Abe, Hiroshi; Matsuo, Hisae; Ishida, Yasushi; Katoh, Takahiko

2015-01-01

This study explored the factor structure of psychiatric nurses' job-related stress and examined the specificity of the related stressors using the job stressor scale of the Brief Job Stress Questionnaire (BJSQ). The stressor scale of the BJSQ was administered to 296 nurses and assistant nurses. Answers were examined statistically. Exploratory factor analysis was performed to identify factor structures; two factors (overload and job environment) were valid. Confirmatory factor analysis was conducted to examine the two-factor structure and found 11 items with factor loadings of >0.40 (model 1), 13 items with factor loadings from 0.30 to <0.40 (model 2), and 17 items with factor loadings from 0.20 to <0.30 (model 3) for one factor; model 1 demonstrated the highest goodness of fit. Then, we observed that the two-factor structure (model 1) showed a higher goodness of fit than the original six-factor structure. This differed from subscales based on general workers' job-related stressors, suggesting that the factor structure of psychiatric nurses' job-related stressors is specific. Further steps may be necessary to reduce job-related stress specifically related to overload including attention to many needs of patients and job environment including complex ethical dilemmas in psychiatric nursing. PMID:25922763

Exploratory study of factors influencing job-related stress in Japanese psychiatric nurses.

PubMed

Yada, Hironori; Lu, Xi; Omori, Hisamitsu; Abe, Hiroshi; Matsuo, Hisae; Ishida, Yasushi; Katoh, Takahiko

2015-01-01

This study explored the factor structure of psychiatric nurses' job-related stress and examined the specificity of the related stressors using the job stressor scale of the Brief Job Stress Questionnaire (BJSQ). The stressor scale of the BJSQ was administered to 296 nurses and assistant nurses. Answers were examined statistically. Exploratory factor analysis was performed to identify factor structures; two factors (overload and job environment) were valid. Confirmatory factor analysis was conducted to examine the two-factor structure and found 11 items with factor loadings of >0.40 (model 1), 13 items with factor loadings from 0.30 to <0.40 (model 2), and 17 items with factor loadings from 0.20 to <0.30 (model 3) for one factor; model 1 demonstrated the highest goodness of fit. Then, we observed that the two-factor structure (model 1) showed a higher goodness of fit than the original six-factor structure. This differed from subscales based on general workers' job-related stressors, suggesting that the factor structure of psychiatric nurses' job-related stressors is specific. Further steps may be necessary to reduce job-related stress specifically related to overload including attention to many needs of patients and job environment including complex ethical dilemmas in psychiatric nursing.

Major psychological factors affecting acceptance of gene-recombination technology.

PubMed

Tanaka, Yutaka

2004-12-01

The purpose of this study was to verify the validity of a causal model that was made to predict the acceptance of gene-recombination technology. A structural equation model was used as a causal model. First of all, based on preceding studies, the factors of perceived risk, perceived benefit, and trust were set up as important psychological factors determining acceptance of gene-recombination technology in the structural equation model. An additional factor, "sense of bioethics," which I consider to be important for acceptance of biotechnology, was added to the model. Based on previous studies, trust was set up to have an indirect influence on the acceptance of gene-recombination technology through perceived risk and perceived benefit in the model. Participants were 231 undergraduate students in Japan who answered a questionnaire with a 5-point bipolar scale. The results indicated that the proposed model fits the data well, and showed that acceptance of gene-recombination technology is explained largely by four factors, that is, perceived risk, perceived benefit, trust, and sense of bioethics, whether the technology is applied to plants, animals, or human beings. However, the relative importance of the four factors was found to vary depending on whether the gene-recombination technology was applied to plants, animals, or human beings. Specifically, the factor of sense of bioethics is the most important factor in acceptance of plant gene-recombination technology and animal gene-recombination technology, and the factors of trust and perceived risk are the most important factors in acceptance of human being gene-recombination technology.

Applying a Social-Ecological Framework to Factors Related to Nicotine Replacement Therapy for Adolescent Smoking Cessation.

PubMed

King, Jessica L; Merten, Julie W; Wong, Tzu-Jung; Pomeranz, Jamie L

2018-06-01

This systematic review synthesizes factors related to nicotine replacement therapy (NRT) use among adolescents seeking to quit smoking, using the social-ecological model as a guiding framework. Searches of PubMED, ProQuest, EBSCOhost, and ERIC were conducted in July 2016. Original studies of cigarette smokers younger than 18 years that discussed NRT were included. Two reviewers individually extracted study purpose, sample, design, and results. Factors were categorized by social-ecological model level and summarized. A total of 103 907 articles were identified during initial search. After narrowing to peer-reviewed articles in English and eliminating reviews and adult-only studies, we reviewed 51 articles. These 51 articles identified factors from studies at each level of the social-ecological model: intrapersonal ( k = 20), interpersonal ( k = 2), organizational ( k = 7), community ( k = 11), and public policy ( k = 14). Findings provide insight into the applicability of NRT for adolescent smoking cessation, and factors by social-ecological model level highlight areas for additional research. Future adolescent NRT studies should assess factors at the interpersonal, organizational, and community levels, as well as the interactions between levels.

Substance and Artifact in the Higher-Order Factors of the Big Five

PubMed Central

McCrae, Robert R.; Jang, Kerry L.; Ando, Juko; Ono, Yutaka; Yamagata, Shinji; Riemann, Rainer; Angleitner, Alois; Spinath, Frank M.

2018-01-01

J. M. Digman (1997) proposed that the Big Five personality traits showed a higher-order structure with 2 factors he labeled α and β. These factors have been alternatively interpreted as heritable components of personality or as artifacts of evaluative bias. Using structural equation modeling, the authors reanalyzed data from a cross-national twin study and from American cross-observer studies and analyzed new multimethod data from a German twin study. In all analyses, artifact models outperformed substance models by root-mean-square error of approximation criteria, but models combining both artifact and substance were slightly better. These findings suggest that the search for the biological basis of personality traits may be more profitably focused on the 5 factors themselves and their specific facets, especially in monomethod studies. PMID:18665712

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

PubMed

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

2017-09-01

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

Factor Structure of a Multidimensional Gender Identity Scale in a Sample of Chinese Elementary School Children

PubMed Central

Yu, Lu; Xie, Dong; Shek, Daniel T. L.

2012-01-01

This study examined the factor structure of a scale based on the four-dimensional gender identity model (Egan and Perry, 2001) in 726 Chinese elementary school students. Exploratory factor analyses suggested a three-factor model, two of which corresponded to “Felt Pressure” and “Intergroup Bias” in the original model. The third factor “Gender Compatibility” appeared to be a combination of “Gender Typicality” and “Gender Contentment” in the original model. Follow-up confirmatory factor analysis (CFA) indicated that, relative to the initial four-factor structure, the three-factor model fits the current Chinese sample better. These results are discussed in light of cross-cultural similarities and differences in development of gender identity. PMID:22701363

Assessing posttraumatic stress disorder's latent structure in elderly bereaved European trauma survivors: evidence for a five-factor dysphoric and anxious arousal model.

PubMed

Armour, Cherie; O'Connor, Maja; Elklit, Ask; Elhai, Jon D

2013-10-01

The three-factor structure of posttraumatic stress disorder (PTSD) specified by the Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition, is not supported in the empirical literature. Two alternative four-factor models have received a wealth of empirical support. However, a consensus regarding which is superior has not been reached. A recent five-factor model has been shown to provide superior fit over the existing four-factor models. The present study investigated the fit of the five-factor model against the existing four-factor models and assessed the resultant factors' association with depression in a bereaved European trauma sample (N = 325). The participants were assessed for PTSD via the Harvard Trauma Questionnaire and depression via the Beck Depression Inventory. The five-factor model provided superior fit to the data compared with the existing four-factor models. In the dysphoric arousal model, depression was equally related to both dysphoric arousal and emotional numbing, whereas depression was more related to dysphoric arousal than to anxious arousal.

Mining geographic variations of Plasmodium vivax for active surveillance: a case study in China.

PubMed

Shi, Benyun; Tan, Qi; Zhou, Xiao-Nong; Liu, Jiming

2015-05-27

Geographic variations of an infectious disease characterize the spatial differentiation of disease incidences caused by various impact factors, such as environmental, demographic, and socioeconomic factors. Some factors may directly determine the force of infection of the disease (namely, explicit factors), while many other factors may indirectly affect the number of disease incidences via certain unmeasurable processes (namely, implicit factors). In this study, the impact of heterogeneous factors on geographic variations of Plasmodium vivax incidences is systematically investigate in Tengchong, Yunnan province, China. A space-time model that resembles a P. vivax transmission model and a hidden time-dependent process, is presented by taking into consideration both explicit and implicit factors. Specifically, the transmission model is built upon relevant demographic, environmental, and biophysical factors to describe the local infections of P. vivax. While the hidden time-dependent process is assessed by several socioeconomic factors to account for the imported cases of P. vivax. To quantitatively assess the impact of heterogeneous factors on geographic variations of P. vivax infections, a Markov chain Monte Carlo (MCMC) simulation method is developed to estimate the model parameters by fitting the space-time model to the reported spatial-temporal disease incidences. Since there is no ground-truth information available, the performance of the MCMC method is first evaluated against a synthetic dataset. The results show that the model parameters can be well estimated using the proposed MCMC method. Then, the proposed model is applied to investigate the geographic variations of P. vivax incidences among all 18 towns in Tengchong, Yunnan province, China. Based on the geographic variations, the 18 towns can be further classify into five groups with similar socioeconomic causality for P. vivax incidences. Although this study focuses mainly on the transmission of P. vivax, the proposed space-time model is general and can readily be extended to investigate geographic variations of other diseases. Practically, such a computational model will offer new insights into active surveillance and strategic planning for disease surveillance and control.

[Does the GHQ-12 scoring system affect its factor structure? An exploratory study of Ibero American students].

PubMed

Urzúa, Alfonso; Caqueo-Urízar, Alejandra; Bargsted, Mariana; Irarrázaval, Matías

2015-06-01

This study aimed to evaluate whether the scoring system of the General Health Questionnaire (GHQ-12) alters the instrument's factor structure. The method considered 1,972 university students from nine Ibero American countries. Modeling was performed with structural equations for 1, 2, and 3 latent factors. The mechanism for scoring the questions was analyzed within each type of structure. The results indicate that models with 2 and 3 factors show better goodness-of-fit. In relation to scoring mechanisms, procedure 0-1-1-1 for models with 2 and 3 factors showed the best fit. In conclusion, there appears to be a relationship between the response format and the number of factors identified in the instrument's structure. The model with the best fit was 3-factor 0-1-1-1-formatted, but 0-1-2-3 has acceptable and more stable indicators and provides a better format for two- and three-dimensional models.

Testing the psychometric properties of the Environmental Attitudes Inventory on undergraduate students in the Arab context: A test-retest approach.

PubMed

AlMenhali, Entesar Ali; Khalid, Khalizani; Iyanna, Shilpa

2018-01-01

The Environmental Attitudes Inventory (EAI) was developed to evaluate the multidimensional nature of environmental attitudes; however, it is based on a dataset from outside the Arab context. This study reinvestigated the construct validity of the EAI with a new dataset and confirmed the feasibility of applying it in the Arab context. One hundred and forty-eight subjects in Study 1 and 130 in Study 2 provided valid responses. An exploratory factor analysis (EFA) was used to extract a new factor structure in Study 1, and confirmatory factor analysis (CFA) was performed in Study 2. Both studies generated a seven-factor model, and the model fit was discussed for both the studies. Study 2 exhibited satisfactory model fit indices compared to Study 1. Factor loading values of a few items in Study 1 affected the reliability values and average variance extracted values, which demonstrated low discriminant validity. Based on the results of the EFA and CFA, this study showed sufficient model fit and suggested the feasibility of applying the EAI in the Arab context with a good construct validity and internal consistency.

Testing the psychometric properties of the Environmental Attitudes Inventory on undergraduate students in the Arab context: A test-retest approach

PubMed Central

2018-01-01

The Environmental Attitudes Inventory (EAI) was developed to evaluate the multidimensional nature of environmental attitudes; however, it is based on a dataset from outside the Arab context. This study reinvestigated the construct validity of the EAI with a new dataset and confirmed the feasibility of applying it in the Arab context. One hundred and forty-eight subjects in Study 1 and 130 in Study 2 provided valid responses. An exploratory factor analysis (EFA) was used to extract a new factor structure in Study 1, and confirmatory factor analysis (CFA) was performed in Study 2. Both studies generated a seven-factor model, and the model fit was discussed for both the studies. Study 2 exhibited satisfactory model fit indices compared to Study 1. Factor loading values of a few items in Study 1 affected the reliability values and average variance extracted values, which demonstrated low discriminant validity. Based on the results of the EFA and CFA, this study showed sufficient model fit and suggested the feasibility of applying the EAI in the Arab context with a good construct validity and internal consistency. PMID:29758021

Adverse effects of psychosocial work factors on blood pressure: systematic review of studies on demand-control-support and effort-reward imbalance models.

PubMed

Gilbert-Ouimet, Mahée; Trudel, Xavier; Brisson, Chantal; Milot, Alain; Vézina, Michel

2014-03-01

A growing body of research has investigated the adverse effects of psychosocial work factors on blood pressure (BP) elevation. There is now a clear need for an up-to-date, critical synthesis of reliable findings on this topic. This systematic review aimed to evaluate the adverse effects of psychosocial work factors of both the demand-control-support (DCS) and effort-reward imbalance (ERI) models on BP among men and women, according to the methodological quality of the studies. To be eligible, studies had to: (i) evaluate at least one psychosocial work factor, (ii) evaluate BP or hypertension, (iii) comprise ≥100 workers, (iv) be written in English or French, and (v) be published in a peer-reviewed journal. A total of 74 studies were included. Of these, 64 examined the DCS model, and 12 looked at the ERI model, with 2 studies considering both models. Approximately half the studies observed a significant adverse effect of psychosocial work factors on BP. A more consistent effect was observed, however, among men than women. For job strain, a more consistent effect was also observed in studies of higher methodological quality, ie, studies using a prospective design and ambulatory BP measures. A more consistent adverse effect of psychosocial work factors was observed among men than women and in studies of higher methodological quality. These findings contribute to the current effort of primary prevention of cardiovascular disease by documenting the psychosocial etiology of elevated BP, a major cardiovascular risk factor.

The contribution of an animal model toward uncovering biological risk factors for PTSD.

PubMed

Cohen, Hagit; Matar, Michael A; Richter-Levin, Gal; Zohar, Joseph

2006-07-01

Clinical studies of posttraumatic stress disorder (PTSD) have elicited proposed risk factors for developing PTSD in the aftermath of stress exposure. Generally, these risk factors have arisen from retrospective analysis of premorbid characteristics of study populations. A valid animal model of PTSD can complement clinical studies and help to elucidate issues, such as the contribution of proposed risk factors, in ways which are not practicable in the clinical arena. Important qualities of animal models include the possibility to conduct controlled prospective studies, easy access to postmortem brains, and the availability of genetically manipulated subjects, which can be tailored to specific needs. When these qualities are further complemented by an approach which defines phenomenologic criteria to address the variance in individual response pattern and magnitude, enabling the animal subjects to be classified into definable groups for focused study, the model acquires added validity. This article presents an overview of a series of studies in such an animal model which examine the contribution of two proposed risk factors and the value of two early postexposure pharmacological manipulations on the prevalence rates of subjects displaying an extreme magnitude of behavioral response to a predator stress paradigm.

Confirmatory Factor Analysis of the Minnesota Nicotine Withdrawal Scale

PubMed Central

Toll, Benjamin A.; O’Malley, Stephanie S.; McKee, Sherry A.; Salovey, Peter; Krishnan-Sarin, Suchitra

2008-01-01

The authors examined the factor structure of the Minnesota Nicotine Withdrawal Scale (MNWS) using confirmatory factor analysis in clinical research samples of smokers trying to quit (n = 723). Three confirmatory factor analytic models, based on previous research, were tested with each of the 3 study samples at multiple points in time. A unidimensional model including all 8 MNWS items was found to be the best explanation of the data. This model produced fair to good internal consistency estimates. Additionally, these data revealed that craving should be included in the total score of the MNWS. Factor scores derived from this single-factor, 8-item model showed that increases in withdrawal were associated with poor smoking outcome for 2 of the clinical studies. Confirmatory factor analyses of change scores showed that the MNWS symptoms cohere as a syndrome over time. Future investigators should report a total score using all of the items from the MNWS. PMID:17563141

Analyzing musculoskeletal neck pain, measured as present pain and periods of pain, with three different regression models: a cohort study.

PubMed

Grimby-Ekman, Anna; Andersson, Eva M; Hagberg, Mats

2009-06-19

In the literature there are discussions on the choice of outcome and the need for more longitudinal studies of musculoskeletal disorders. The general aim of this longitudinal study was to analyze musculoskeletal neck pain, in a group of young adults. Specific aims were to determine whether psychosocial factors, computer use, high work/study demands, and lifestyle are long-term or short-term factors for musculoskeletal neck pain, and whether these factors are important for developing or ongoing musculoskeletal neck pain. Three regression models were used to analyze the different outcomes. Pain at present was analyzed with a marginal logistic model, for number of years with pain a Poisson regression model was used and for developing and ongoing pain a logistic model was used. Presented results are odds ratios and proportion ratios (logistic models) and rate ratios (Poisson model). The material consisted of web-based questionnaires answered by 1204 Swedish university students from a prospective cohort recruited in 2002. Perceived stress was a risk factor for pain at present (PR = 1.6), for developing pain (PR = 1.7) and for number of years with pain (RR = 1.3). High work/study demands was associated with pain at present (PR = 1.6); and with number of years with pain when the demands negatively affect home life (RR = 1.3). Computer use pattern (number of times/week with a computer session > or = 4 h, without break) was a risk factor for developing pain (PR = 1.7), but also associated with pain at present (PR = 1.4) and number of years with pain (RR = 1.2). Among life style factors smoking (PR = 1.8) was found to be associated to pain at present. The difference between men and women in prevalence of musculoskeletal pain was confirmed in this study. It was smallest for the outcome ongoing pain (PR = 1.4) compared to pain at present (PR = 2.4) and developing pain (PR = 2.5). By using different regression models different aspects of neck pain pattern could be addressed and the risk factors impact on pain pattern was identified. Short-term risk factors were perceived stress, high work/study demands and computer use pattern (break pattern). Those were also long-term risk factors. For developing pain perceived stress and computer use pattern were risk factors.

Analyzing musculoskeletal neck pain, measured as present pain and periods of pain, with three different regression models: a cohort study

PubMed Central

Grimby-Ekman, Anna; Andersson, Eva M; Hagberg, Mats

2009-01-01

Background In the literature there are discussions on the choice of outcome and the need for more longitudinal studies of musculoskeletal disorders. The general aim of this longitudinal study was to analyze musculoskeletal neck pain, in a group of young adults. Specific aims were to determine whether psychosocial factors, computer use, high work/study demands, and lifestyle are long-term or short-term factors for musculoskeletal neck pain, and whether these factors are important for developing or ongoing musculoskeletal neck pain. Methods Three regression models were used to analyze the different outcomes. Pain at present was analyzed with a marginal logistic model, for number of years with pain a Poisson regression model was used and for developing and ongoing pain a logistic model was used. Presented results are odds ratios and proportion ratios (logistic models) and rate ratios (Poisson model). The material consisted of web-based questionnaires answered by 1204 Swedish university students from a prospective cohort recruited in 2002. Results Perceived stress was a risk factor for pain at present (PR = 1.6), for developing pain (PR = 1.7) and for number of years with pain (RR = 1.3). High work/study demands was associated with pain at present (PR = 1.6); and with number of years with pain when the demands negatively affect home life (RR = 1.3). Computer use pattern (number of times/week with a computer session ≥ 4 h, without break) was a risk factor for developing pain (PR = 1.7), but also associated with pain at present (PR = 1.4) and number of years with pain (RR = 1.2). Among life style factors smoking (PR = 1.8) was found to be associated to pain at present. The difference between men and women in prevalence of musculoskeletal pain was confirmed in this study. It was smallest for the outcome ongoing pain (PR = 1.4) compared to pain at present (PR = 2.4) and developing pain (PR = 2.5). Conclusion By using different regression models different aspects of neck pain pattern could be addressed and the risk factors impact on pain pattern was identified. Short-term risk factors were perceived stress, high work/study demands and computer use pattern (break pattern). Those were also long-term risk factors. For developing pain perceived stress and computer use pattern were risk factors. PMID:19545386

Extracurricular activity participation moderates impact of family and school factors on adolescents' disruptive behavioural problems.

PubMed

Driessens, Corine M E F

2015-11-11

The prevalence of problem behaviours among British adolescents has increased in the past decades. Following Erikson's psychosocial developmental theory and Bronfenbrenner's developmental ecological model, it was hypothesized that youth problem behaviour is shaped in part by social environment. The aim of this project was to explore potential protective factors within the social environment of British youth's for the presentation of disruptive behavioural problems. This study used secondary data from the Longitudinal Study of Young People in England, a cohort study of secondary school students. These data were analysed with generalized estimation equations to take the correlation between the longitudinal observations into account. Three models were built. The first model determined the effect of family, school, and extracurricular setting on presentation of disruptive behavioural problems. The second model expanded the first model by assuming extracurricular activities as protective factors that moderated the interaction between family and school factors with disruptive behavioural problems. The third model described the effect of prior disruptive behaviour on current disruptive behaviour. Associations were found between school factors, family factors, involvement in extracurricular activities and presence of disruptive behavioural problems. Results from the second generalized estimating equation (GEE) logistic regression models indicated that extracurricular activities buffered the impact of school and family factors on the presence of disruptive behavioural problems. For instance, participation in sports activities decreased the effect of bullying on psychological distress. Results from the third model indicated that prior acts of disruptive behaviour reinforced current disruptive behaviour. This study supports Erikson's psychosocial developmental theory and Bronfenbrenner's developmental ecological model; social environment did influence the presence of disruptive behavioural problems for British adolescents. The potential of extracurricular activities to intervention strategies addressing disruptive behavioural problems of adolescents is discussed.

Study of Factors Preventing Children from Enrolment in Primary School in the Republic of Honduras: Analysis Using Structural Equation Modelling

ERIC Educational Resources Information Center

Ashida, Akemi

2015-01-01

Studies have investigated factors that impede enrolment in Honduras. However, they have not analysed individual factors as a whole or identified the relationships among them. This study used longitudinal data for 1971 children who entered primary schools from 1986 to 2000, and employed structural equation modelling to examine the factors…

Systematics of g factors of 2{sub 1}{sup +} states in even-even nuclei from Gd to Pt: A microscopic description by the projected shell model

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

Bian, Bao-An; Institute of Low Energy Nuclear Physics, Beijing Normal University, Beijing 100875; Di, Yao-Min

2007-01-15

The systematics of g factor of the first excited 2{sup +} state vs neutron number N is studied by the projected shell model. The study covers the even-even nuclei of all isotopic chains from Gd to Pt. g factors are calculated by using the many-body wave functions that well reproduce the energy levels and B(E2)s of the ground-state bands. For Gd to W isotopes the characteristic feature of the g factor data along an isotopic chain is described by the present model. Deficiency of the model in the g factor description for the heavier Os and Pt isotopes is discussed.

Confirming the Multidimensionality of Psychologically Controlling Parenting among Chinese-American Mothers: Love Withdrawal, Guilt Induction, and Shaming.

PubMed

Cheah, Charissa; Yu, Jing; Hart, Craig; Sun, Shuyan; Olsen, Joseph

2015-05-01

Despite the theoretical conceptualization of parental psychological control as a multidimensional construct, the majority of previous studies have examined psychological control as a unidimensional scale. Moreover, the conceptualization of shaming and its associations with love withdrawal and guilt induction are unclear. The current study aimed to fill these gaps by evaluating the latent factor structure underlying 18 items from Olsen et al. (2002) that were conceptually relevant to love withdrawal, guilt induction, and shaming practices in a sample of 169 mothers of Chinese-American preschoolers. A multidimensional three-factor model and bi-factor model were specified based on our formulated operational definitions for the three dimensions of psychological control. Both models were found to be superior to the unidimensional model. In addition, results from the bi-factor model and an additional second-order factor model indicated that psychological control is essentially empirically isomorphic with guilt induction. Although love withdrawal and shaming factors were also fairly strong indicators of psychological control, each exhibited important additional unique variability and mutual distinctiveness. Implications for the conceptualization of love withdrawal, guilt induction, and shaming as well as directions for future studies are discussed.

Confirming the Multidimensionality of Psychologically Controlling Parenting among Chinese-American Mothers: Love Withdrawal, Guilt Induction, and Shaming

PubMed Central

Cheah, Charissa; Yu, Jing; Hart, Craig; Sun, Shuyan; Olsen, Joseph

2014-01-01

Despite the theoretical conceptualization of parental psychological control as a multidimensional construct, the majority of previous studies have examined psychological control as a unidimensional scale. Moreover, the conceptualization of shaming and its associations with love withdrawal and guilt induction are unclear. The current study aimed to fill these gaps by evaluating the latent factor structure underlying 18 items from Olsen et al. (2002) that were conceptually relevant to love withdrawal, guilt induction, and shaming practices in a sample of 169 mothers of Chinese-American preschoolers. A multidimensional three-factor model and bi-factor model were specified based on our formulated operational definitions for the three dimensions of psychological control. Both models were found to be superior to the unidimensional model. In addition, results from the bi-factor model and an additional second-order factor model indicated that psychological control is essentially empirically isomorphic with guilt induction. Although love withdrawal and shaming factors were also fairly strong indicators of psychological control, each exhibited important additional unique variability and mutual distinctiveness. Implications for the conceptualization of love withdrawal, guilt induction, and shaming as well as directions for future studies are discussed. PMID:26052168

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

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

Measuring striving for understanding and learning value of geometry: a validity study

NASA Astrophysics Data System (ADS)

Ubuz, Behiye; Aydınyer, Yurdagül

2017-11-01

The current study aimed to construct a questionnaire that measures students' personality traits related to striving for understanding and learning value of geometry and then examine its psychometric properties. Through the use of multiple methods on two independent samples of 402 and 521 middle school students, two studies were performed to address this issue to provide support for its validity. In Study 1, exploratory factor analysis indicated the two-factor model. In Study 2, confirmatory factor analysis indicated the better fit of two-factor model compared to one or three-factor model. Convergent and discriminant validity evidence provided insight into the distinctiveness of the two factors. Subgroup validity evidence revealed gender differences for striving for understanding geometry trait favouring girls and grade level differences for learning value of geometry trait favouring the sixth- and seventh-grade students. Predictive validity evidence demonstrated that the striving for understanding geometry trait but not learning value of geometry trait was significantly correlated with prior mathematics achievement. In both studies, each factor and the entire questionnaire showed satisfactory reliability. In conclusion, the questionnaire was psychometrically sound.

Confirmatory factor analysis of the PTSD Checklist and the Clinician-Administered PTSD Scale in disaster workers exposed to the World Trade Center Ground Zero.

PubMed

Palmieri, Patrick A; Weathers, Frank W; Difede, JoAnn; King, Dainel W

2007-05-01

Although posttraumatic stress disorder (PTSD) factor analytic research has yielded little support for the DSM-IV 3-factor model of reexperiencing, avoidance, and hyperarousal symptoms, no clear consensus regarding alternative models has emerged. One possible explanation is differential instrumentation across studies. In the present study, the authors used confirmatory factor analysis to compare a self-report measure, the PTSD Checklist (PCL), and a structured clinical interview, the Clinician-Administered PTSD Scale (CAPS), in 2,960 utility workers exposed to the World Trade Center Ground Zero site. Although two 4-factor models fit adequately for each measure, the latent structure of the PCL was slightly better represented by correlated reexperiencing, avoidance, dysphoria, and hyperarousal factors, whereas that of the CAPS was slightly better represented by correlated reexperiencing, avoidance, emotional numbing, and hyperarousal factors. After accounting for method variance, the model specifying dysphoria as a distinct factor achieved slightly better fit. Patterns of correlations with external variables provided additional support for the dysphoria model. Implications regarding the underlying structure of PTSD are discussed.

[Factor structure validity of the social capital scale used at baseline in the ELSA-Brasil study].

PubMed

Souto, Ester Paiva; Vasconcelos, Ana Glória Godoi; Chor, Dora; Reichenheim, Michael E; Griep, Rosane Härter

2016-07-21

This study aims to analyze the factor structure of the Brazilian version of the Resource Generator (RG) scale, using baseline data from the Brazilian Longitudinal Health Study in Adults (ELSA-Brasil). Cross-validation was performed in three random subsamples. Exploratory factor analysis using exploratory structural equation models was conducted in the first two subsamples to diagnose the factor structure, and confirmatory factor analysis was used in the third to corroborate the model defined by the exploratory analyses. Based on the 31 initial items, the model with the best fit included 25 items distributed across three dimensions. They all presented satisfactory convergent validity (values greater than 0.50 for the extracted variance) and precision (values greater than 0.70 for compound reliability). All factor correlations were below 0.85, indicating full discriminative factor validity. The RG scale presents acceptable psychometric properties and can be used in populations with similar characteristics.

Confirmatory factor analysis of the Center for Epidemiologic Studies – Depression Scale in Black and White dementia caregivers

PubMed Central

Flynn Longmire, Crystal V.; Knight, Bob G.

2012-01-01

Objectives In order to better understand if measurement problems underlie the inconsistent findings that exist regarding differences in depression levels between Black and White caregivers, this study examined the factor structure and invariance of the Center for Epidemiologic Studies-Depression scale (CES-D). Method A confirmatory factor analysis of the 20-item CES-D was performed on a sample of 167 Black and 214 White family caregivers of older adults with dementia from Los Angeles County. Results The relationships between the 20 items and the four factors, as well as the relationships among each of the factors, were equivalent across both caregiver groups, indicating that the four-factor model fit the data for both racial groups. Conclusion These findings offer further evidence that the standard four-factor model is the best fitting model for the CES-D and is invariant across racial groups. PMID:21069602

Confirmatory factor analysis of the Center for Epidemiologic Studies-Depression Scale in black and white dementia caregivers.

PubMed

Flynn Longmire, Crystal V; Knight, Bob G

2010-11-01

In order to better understand if measurement problems underlie the inconsistent findings that exist regarding differences in depression levels between Black and White caregivers, this study examined the factor structure and invariance of the Center for Epidemiologic Studies-Depression (CES-D) Scale. A confirmatory factor analysis of the 20-item CES-D was performed on a sample of 167 Black and 214 White family caregivers of older adults with dementia from Los Angeles County. The relationships between the 20 items and the four factors, as well as the relationships among each of the factors, were equivalent across both caregiver groups, indicating that the four-factor model fit the data for both the racial groups. These findings offer further evidence that the standard four-factor model is the best fitting model for the CES-D and is invariant across racial groups.

Modeling the effects of study abroad programs on college students

Treesearch

Alvin H. Yu; Garry E. Chick; Duarte B. Morais; Chung-Hsien Lin

2009-01-01

This study explored the possibility of modeling the effects of a study abroad program on students from a university in the northeastern United States. A program effect model was proposed after conducting an extensive literature review and empirically examining a sample of 265 participants in 2005. Exploratory factor analysis (EFA), confirmatory factor analysis (CFA),...

Structural Model of psychological risk and protective factors affecting on quality of life in patients with coronary heart disease: A psychocardiology model

PubMed Central

Nekouei, Zohreh Khayyam; Yousefy, Alireza; Doost, Hamid Taher Neshat; Manshaee, Gholamreza; Sadeghei, Masoumeh

2014-01-01

Background: Conducted researches show that psychological factors may have a very important role in the etiology, continuity and consequences of coronary heart diseases. This study has drawn the psychological risk and protective factors and their effects in patients with coronary heart diseases (CHD) in a structural model. It aims to determine the structural relations between psychological risk and protective factors with quality of life in patients with coronary heart disease. Materials and Methods: The present cross-sectional and correlational studies were conducted using structural equation modeling. The study sample included 398 patients of coronary heart disease in the university referral Hospital, as well as other city health care centers in Isfahan city. They were selected based on random sampling method. Then, in case, they were executed the following questionnaires: Coping with stressful situations (CISS- 21), life orientation (LOT-10), general self-efficacy (GSE-10), depression, anxiety and stress (DASS-21), perceived stress (PSS-14), multidimensional social support (MSPSS-12), alexithymia (TAS-20), spiritual intelligence (SQ-23) and quality of life (WHOQOL-26). Results: The results showed that protective and risk factors could affect the quality of life in patients with CHD with factor loadings of 0.35 and −0.60, respectively. Moreover, based on the values of the framework of the model such as relative chi-square (CMIN/DF = 3.25), the Comparative Fit Index (CFI = 0.93), the Parsimony Comparative Fit Index (PCFI = 0.68), the Root Mean Square Error of Approximation (RMSEA = 0.07) and details of the model (significance of the relationships) it has been confirmed that the psychocardiological structural model of the study is the good fitting model. Conclusion: This study was among the first to research the different psychological risk and protective factors of coronary heart diseases in the form of a structural model. The results of this study have emphasized the necessity of noticing the psychological factors in primary prevention by preventive programs and in secondary prevention by rehabilitation centers to improve the quality of life of the people with heart diseases. PMID:24778660

Hierarchical and coupling model of factors influencing vessel traffic flow.

PubMed

Liu, Zhao; Liu, Jingxian; Li, Huanhuan; Li, Zongzhi; Tan, Zhirong; Liu, Ryan Wen; Liu, Yi

2017-01-01

Understanding the characteristics of vessel traffic flow is crucial in maintaining navigation safety, efficiency, and overall waterway transportation management. Factors influencing vessel traffic flow possess diverse features such as hierarchy, uncertainty, nonlinearity, complexity, and interdependency. To reveal the impact mechanism of the factors influencing vessel traffic flow, a hierarchical model and a coupling model are proposed in this study based on the interpretative structural modeling method. The hierarchical model explains the hierarchies and relationships of the factors using a graph. The coupling model provides a quantitative method that explores interaction effects of factors using a coupling coefficient. The coupling coefficient is obtained by determining the quantitative indicators of the factors and their weights. Thereafter, the data obtained from Port of Tianjin is used to verify the proposed coupling model. The results show that the hierarchical model of the factors influencing vessel traffic flow can explain the level, structure, and interaction effect of the factors; the coupling model is efficient in analyzing factors influencing traffic volumes. The proposed method can be used for analyzing increases in vessel traffic flow in waterway transportation system.

Hierarchical and coupling model of factors influencing vessel traffic flow

PubMed Central

Liu, Jingxian; Li, Huanhuan; Li, Zongzhi; Tan, Zhirong; Liu, Ryan Wen; Liu, Yi

2017-01-01

Understanding the characteristics of vessel traffic flow is crucial in maintaining navigation safety, efficiency, and overall waterway transportation management. Factors influencing vessel traffic flow possess diverse features such as hierarchy, uncertainty, nonlinearity, complexity, and interdependency. To reveal the impact mechanism of the factors influencing vessel traffic flow, a hierarchical model and a coupling model are proposed in this study based on the interpretative structural modeling method. The hierarchical model explains the hierarchies and relationships of the factors using a graph. The coupling model provides a quantitative method that explores interaction effects of factors using a coupling coefficient. The coupling coefficient is obtained by determining the quantitative indicators of the factors and their weights. Thereafter, the data obtained from Port of Tianjin is used to verify the proposed coupling model. The results show that the hierarchical model of the factors influencing vessel traffic flow can explain the level, structure, and interaction effect of the factors; the coupling model is efficient in analyzing factors influencing traffic volumes. The proposed method can be used for analyzing increases in vessel traffic flow in waterway transportation system. PMID:28414747

Evidence for a unique PTSD construct represented by PTSD's D1-D3 symptoms.

PubMed

Elhai, Jon D; Biehn, Tracey L; Armour, Cherie; Klopper, Jessica J; Frueh, B Christopher; Palmieri, Patrick A

2011-04-01

Two models of posttraumatic stress disorder (PTSD) have received the most empirical support in confirmatory factor analytic studies: King, Leskin, King, and Weathers' (1998) Emotional Numbing model of reexperiencing, avoidance, emotional numbing and hyperarousal; and Simms, Watson, and Doebbeling's (2002) Dysphoria model of reexperiencing, avoidance, dysphoria and hyperarousal. These models only differ in placement of three PTSD symptoms: sleep problems (D1), irritability (D2), and concentration problems (D3). In the present study, we recruited 252 women victims of domestic violence and tested whether there is empirical support to separate these three PTSD symptoms into a fifth factor, while retaining the Emotional Numbing and Dysphoria models' remaining four factors. Confirmatory factor analytic findings demonstrated that separating the three symptoms into a separate factor significantly enhanced model fit for the Emotional Numbing and Dysphoria models. These three symptoms may represent a unique latent construct. Implications are discussed. Copyright © 2010 Elsevier Ltd. All rights reserved.

Monitoring hand, foot and mouth disease by combining search engine query data and meteorological factors.

PubMed

Huang, Da-Cang; Wang, Jin-Feng

2018-01-15

Hand, foot and mouth disease (HFMD) has been recognized as a significant public health threat and poses a tremendous challenge to disease control departments. To date, the relationship between meteorological factors and HFMD has been documented, and public interest of disease has been proven to be trackable from the Internet. However, no study has explored the combination of these two factors in the monitoring of HFMD. Therefore, the main aim of this study was to develop an effective monitoring model of HFMD in Guangzhou, China by utilizing historical HFMD cases, Internet-based search engine query data and meteorological factors. To this end, a case study was conducted in Guangzhou, using a network-based generalized additive model (GAM) including all factors related to HFMD. Three other models were also constructed using some of the variables for comparison. The results suggested that the model showed the best estimating ability when considering all of the related factors. Copyright © 2017 Elsevier B.V. All rights reserved.

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

PubMed

Liang, Ying; Wang, Lei; Yin, Xican

2016-09-26

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

Using Ryff's scales of psychological well-being in adolescents in mainland China.

PubMed

Gao, Jie; McLellan, Ros

2018-04-20

Psychological well-being in adolescence has always been a focus of public attention and academic research. Ryff's six-factor model of psychological well-being potentially provides a comprehensive theoretical framework for investigating positive functioning of adolescents. However, previous studies reported inconsistent findings of the reliability and validity of Ryff's Scales of Psychological Well-being (SPWB). The present study aimed to explore whether Ryff's six-factor model of psychological well-being could be applied in Chinese adolescents. The Scales of Psychological Well-being (SPWB) were adapted for assessing the psychological well-being of adolescents in mainland China. 772 adolescents (365 boys to 401 girls, 6 missing gender data, mean age = 13.65) completed the adapted 33-item SPWB. The data was used to examine the reliability and construct validity of the adapted SPWB. Results showed that five of the six sub-scales had acceptable internal consistency of items, except the sub-scale of autonomy. The factorial structure of the SPWB was not as clear-cut as the theoretical framework suggested. Among the models under examination, the six-factor model had better model fit than the hierarchical model and the one-factor model. However, the goodness-of-fit of the six-factor model was hardly acceptable. High factor correlations were identified between the sub-scales of environmental mastery, purpose in life and personal growth. Findings of the present study echoed a number of previous studies which reported inadequate reliability and validity of Ryff's scales. Given the evidence, it was suggested that future adolescent studies should seek to develop more age-specific and context-appropriate items for a better operationalisation of Ryff's theoretical model of psychological well-being.

The Dual-Factor Model of Mental Health: Further Study of the Determinants of Group Differences

ERIC Educational Resources Information Center

Lyons, Michael D.; Huebner, E. Scott; Hills, Kimberly J.; Shinkareva, Svetlana V.

2012-01-01

Consistent with a positive psychology framework, this study examined the contributions of personality, environmental, and perceived social support variables in classifying adolescents using Greenspoon and Saklofske's Dual-Factor model of mental health. This model incorporates information about positive subjective well-being (SWB), along with…

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

PubMed

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

2006-01-01

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

Two-vehicle injury severity models based on integration of pavement management and traffic engineering factors.

PubMed

Jiang, Ximiao; Huang, Baoshan; Yan, Xuedong; Zaretzki, Russell L; Richards, Stephen

2013-01-01

The severity of traffic-related injuries has been studied by many researchers in recent decades. However, the evaluation of many factors is still in dispute and, until this point, few studies have taken into account pavement management factors as points of interest. The objective of this article is to evaluate the combined influences of pavement management factors and traditional traffic engineering factors on the injury severity of 2-vehicle crashes. This study examines 2-vehicle rear-end, sideswipe, and angle collisions that occurred on Tennessee state routes from 2004 to 2008. Both the traditional ordered probit (OP) model and Bayesian ordered probit (BOP) model with weak informative prior were fitted for each collision type. The performances of these models were evaluated based on the parameter estimates and deviances. The results indicated that pavement management factors played identical roles in all 3 collision types. Pavement serviceability produces significant positive effects on the severity of injuries. The pavement distress index (PDI), rutting depth (RD), and rutting depth difference between right and left wheels (RD_df) were not significant in any of these 3 collision types. The effects of traffic engineering factors varied across collision types, except that a few were consistently significant in all 3 collision types, such as annual average daily traffic (AADT), rural-urban location, speed limit, peaking hour, and light condition. The findings of this study indicated that improved pavement quality does not necessarily lessen the severity of injuries when a 2-vehicle crash occurs. The effects of traffic engineering factors are not universal but vary by the type of crash. The study also found that the BOP model with a weak informative prior can be used as an alternative but was not superior to the traditional OP model in terms of overall performance.

Reliability and Validity Evidence for Achievement Goal Models in High School Physical Education Settings

ERIC Educational Resources Information Center

Guan, Jianmin; McBride, Ron; Xiang, Ping

2007-01-01

Although empirical research in academic areas provides support for both a 3-factor as well as a 4-factor achievement goal model, both models were proposed and tested with a collegiate sample. Little is known about the generalizability of either model with high school level samples. This study was designed to examine whether the 3-factor model…

Factor Structure of the Wechsler Intelligence Scale for Children: Fourth Edition in Children with ADHD.

PubMed

Thaler, Nicholas S; Barchard, Kimberly A; Parke, Elyse; Jones, W Paul; Etcoff, Lewis M; Allen, Daniel N

2015-12-01

Recent evidence suggests that the factor structure of the Wechsler Intelligence Scale for Children-Fourth Edition (WISC-IV) is better explained by a five-factor model rather than the four-factor model in the standardization sample. The current study examined the WISC-IV's factor structure in a sample of children with ADHD. Participants included 314 children and adolescents who were diagnosed with ADHD. Confirmatory factor analysis was conducted on the 10 core subtests of the WISC-IV, and three models were examined including two based on Cattell-Horn-Carroll (CHC) theory. A five-factor model consisting of Gc, Gf, Gv, Gsm, and Gs factors provided the best fit for the data. The Perceptual Reasoning factor identified in the original four-factor model split into the two CHC factors, Gf and Gv, and cross-loaded the Symbol Search subtest onto the Gv factor. A five-factor model based on CHC theory provided superior fit for the WISC-IV in children with ADHD, as has been found with the standardization sample. © The Author(s) 2012.

Bayesian structural equation modeling: a more flexible representation of substantive theory.

PubMed

Muthén, Bengt; Asparouhov, Tihomir

2012-09-01

This article proposes a new approach to factor analysis and structural equation modeling using Bayesian analysis. The new approach replaces parameter specifications of exact zeros with approximate zeros based on informative, small-variance priors. It is argued that this produces an analysis that better reflects substantive theories. The proposed Bayesian approach is particularly beneficial in applications where parameters are added to a conventional model such that a nonidentified model is obtained if maximum-likelihood estimation is applied. This approach is useful for measurement aspects of latent variable modeling, such as with confirmatory factor analysis, and the measurement part of structural equation modeling. Two application areas are studied, cross-loadings and residual correlations in confirmatory factor analysis. An example using a full structural equation model is also presented, showing an efficient way to find model misspecification. The approach encompasses 3 elements: model testing using posterior predictive checking, model estimation, and model modification. Monte Carlo simulations and real data are analyzed using Mplus. The real-data analyses use data from Holzinger and Swineford's (1939) classic mental abilities study, Big Five personality factor data from a British survey, and science achievement data from the National Educational Longitudinal Study of 1988.

Food hygiene practices and its associated factors among model and non model households in Abobo district, southwestern Ethiopia: Comparative cross-sectional study.

PubMed

Okugn, Akoma; Woldeyohannes, Demelash

2018-01-01

In developing country most of human infectious diseases are caused by eating contaminated food. Estimated nine out ten of the diarrheal disease is attributable to the environment and associated with risk factors of poor food hygiene practice. Understanding the risk of eating unsafe food is the major concern to prevent and control food borne diseases. The main goal of this study was to assessing food hygiene practices and its associated factors among model and non model households at Abobo district. This study was conducted from 18 October 2013 to 13 June 2014. A community-based comparative cross-sectional study design was used. Pretested structured questionnaire was used to collect data. A total of 1247 households (417 model and 830 non model households) were included in the study from Abobo district. Bivariate and multivariate logistic regression analysis was used to identify factors associated with outcome variable. The study revealed that good food hygiene practice was 51%, of which 79% were model and 36.70% were non model households. Type of household [AOR: 2.07, 95% CI: (1.32-3.39)], sex of household head [AOR: 1.63, 95% CI: (1.06-2.48)], Availability of liquid wastes disposal pit [AOR: 2.23, 95% CI: (1.39,3.63)], Knowledge of liquid waste to cause diseases [AOR: 1.95, 95% (1.23,3.08)], and availability of functional hand washing facility [AOR: 3.61, 95% CI: (1.86-7.02)] were the factors associated with food handling practices. This study revealed that good food handling practice is low among model and non model households. While type of household (model versus non model households), sex, knowledge of solid waste to cause diseases, availability of functional hand washing facility, and availability of liquid wastes disposal pit were the factors associated with outcome variable. Health extension workers should play a great role in educating households regarding food hygiene practices to improve their knowledge and practices of the food hygiene.

Dynamic Factor Analysis of Nonstationary Multivariate Time Series.

ERIC Educational Resources Information Center

Molenaar, Peter C. M.; And Others

1992-01-01

The dynamic factor model proposed by P. C. Molenaar (1985) is exhibited, and a dynamic nonstationary factor model (DNFM) is constructed with latent factor series that have time-varying mean functions. The use of a DNFM is illustrated using data from a television viewing habits study. (SLD)

Alternative models of DSM-5 PTSD: Examining diagnostic implications.

PubMed

Murphy, Siobhan; Hansen, Maj; Elklit, Ask; Yong Chen, Yoke; Raudzah Ghazali, Siti; Shevlin, Mark

2018-04-01

The factor structure of DSM-5 posttraumatic stress disorder (PTSD) has been extensively debated with evidence supporting the recently proposed seven-factor Hybrid model. However, despite myriad studies examining PTSD symptom structure few have assessed the diagnostic implications of these proposed models. This study aimed to generate PTSD prevalence estimates derived from the 7 alternative factor models and assess whether pre-established risk factors associated with PTSD (e.g., transportation accidents and sexual victimisation) produce consistent risk estimates. Seven alternative models were estimated within a confirmatory factor analytic framework using the PTSD Checklist for DSM-5 (PCL-5). Data were analysed from a Malaysian adolescent community sample (n = 481) of which 61.7% were female, with a mean age of 17.03 years. The results indicated that all models provided satisfactory model fit with statistical superiority for the Externalising Behaviours and seven-factor Hybrid models. The PTSD prevalence estimates varied substantially ranging from 21.8% for the DSM-5 model to 10.0% for the Hybrid model. Estimates of risk associated with PTSD were inconsistent across the alternative models, with substantial variation emerging for sexual victimisation. These findings have important implications for research and practice and highlight that more research attention is needed to examine the diagnostic implications emerging from the alternative models of PTSD. Copyright © 2017 Elsevier B.V. All rights reserved.

Perceived game realism: a test of three alternative models.

PubMed

Ribbens, Wannes

2013-01-01

Perceived realism is considered a key concept in explaining the mental processing of media messages and the societal impact of media. Despite its importance, little is known about its conceptualization and dimensional structure, especially with regard to digital games. The aim of this study was to test a six-factor model of perceived game realism comprised of simulational realism, freedom of choice, perceptual pervasiveness, social realism, authenticity, and character involvement and to assess it against an alternative single- and five-factor model. Data were collected from 380 male digital game users who judged the realism of the first-person shooter Half-Life 2 based upon their previous experience with the game. Confirmatory factor analysis was applied to investigate which model fits the data best. The results support the six-factor model over the single- and five-factor solutions. The study contributes to our knowledge of perceived game realism by further developing its conceptualization and measurement.

Psychometric properties and Confirmatory structure of the Strengths and difficulties questionnaire in a sample of adolescents in Nigeria.

PubMed

Akpa, Onoja M; Afolabi, Rotimi F; Fowobaje, Kayode R

Though the SDQ has been used in selected studies in Nigeria, its theoretical structure has not been fully and appropriately investigated in the setting. The present study employs Exploratory Factor Analysis (EFA) and Confirmatory Factor Analysis (CFA) to investigate the theoretical structure of the self-reported version of the SDQ in a sample of adolescents in Benue state, Nigeria. A total of 1,244 adolescents from different categories of secondary schools in Makurdi and Vandekya Local government areas of Benue state participated in the study. Preliminary data analyses were performed using descriptive statistics while the theoretical structure of the SDQ was assessed using EFA and CFA. Model fits were assessed using Chi-square test and other fit indices at 5% significance level. Participants were 14.19±2.45 (Vandekya) and 14.19±2.45 (Makurdi) years old. Results of the EFA and CFA revealed a 3-factor oblique model as the best model for the sample of adolescents studied ( χ 2 / df =2.20, p<0.001) with all fit indices yielding better results. A correlated 3-factor model fits the present data better than the 5-factor theoretical model of the SDQ. The use of the original 5-factor model of the SDQ in the present setting should be interpreted with caution.

Assessing a dysphoric arousal model of acute stress disorder symptoms in a clinical sample of rape and bank robbery victims

PubMed Central

Hansen, Maj; Armour, Cherie; Elklit, Ask

2012-01-01

Background Since the introduction of Acute Stress Disorder (ASD) into the 4th edition of the Diagnostic and Statistical Manual of Mental Disorders (DSM-IV) research has focused on the ability of ASD to predict PTSD rather than focusing on addressing ASD's underlying latent structure. The few existing confirmatory factor analytic (CFA) studies of ASD have failed to reach a clear consensus regarding ASD's underlying dimensionality. Although, the discrepancy in the results may be due to varying ASD prevalence rates, it remains possible that the model capturing the latent structure of ASD has not yet been put forward. One such model may be a replication of a new five-factor model of PTSD, which separates the arousal symptom cluster into Dysphoric and Anxious Arousal. Given the pending DSM-5, uncovering ASD's latent structure is more pertinent than ever. Objective Using CFA, four different models of the latent structure of ASD were specified and tested: the proposed DSM-5 model, the DSM-IV model, a three factor model, and a five factor model separating the arousal symptom cluster. Method The analyses were based on a combined sample of rape and bank robbery victims, who all met the diagnostic criteria for ASD (N = 404) using the Acute Stress Disorder Scale. Results The results showed that the five factor model provided the best fit to the data. Conclusions The results of the present study suggest that the dimensionality of ASD may be best characterized as a five factor structure which separates dysphoric and anxious arousal items into two separate factors, akin to recent research on PTSD's latent structure. Thus, the current study adds to the debate about how ASD should be conceptualized in the pending DSM-5. PMID:22893845

Assessing a dysphoric arousal model of acute stress disorder symptoms in a clinical sample of rape and bank robbery victims.

PubMed

Hansen, Maj; Armour, Cherie; Elklit, Ask

2012-01-01

Since the introduction of Acute Stress Disorder (ASD) into the 4th edition of the Diagnostic and Statistical Manual of Mental Disorders (DSM-IV) research has focused on the ability of ASD to predict PTSD rather than focusing on addressing ASD's underlying latent structure. The few existing confirmatory factor analytic (CFA) studies of ASD have failed to reach a clear consensus regarding ASD's underlying dimensionality. Although, the discrepancy in the results may be due to varying ASD prevalence rates, it remains possible that the model capturing the latent structure of ASD has not yet been put forward. One such model may be a replication of a new five-factor model of PTSD, which separates the arousal symptom cluster into Dysphoric and Anxious Arousal. Given the pending DSM-5, uncovering ASD's latent structure is more pertinent than ever. USING CFA, FOUR DIFFERENT MODELS OF THE LATENT STRUCTURE OF ASD WERE SPECIFIED AND TESTED: the proposed DSM-5 model, the DSM-IV model, a three factor model, and a five factor model separating the arousal symptom cluster. The analyses were based on a combined sample of rape and bank robbery victims, who all met the diagnostic criteria for ASD (N = 404) using the Acute Stress Disorder Scale. The results showed that the five factor model provided the best fit to the data. The results of the present study suggest that the dimensionality of ASD may be best characterized as a five factor structure which separates dysphoric and anxious arousal items into two separate factors, akin to recent research on PTSD's latent structure. Thus, the current study adds to the debate about how ASD should be conceptualized in the pending DSM-5.

Protective Factors for Children of Alcoholics: Parenting, Family Environment, Child Personality, and Contextual Supports.

ERIC Educational Resources Information Center

Jordan, Lisa C.; Chassin, Laurie

The purposes of this study were to identify factors that would ameliorate the risk for substance abuse problems among children of alcoholics (COA), and to explore mechanisms of protection, particularly the Stress-Buffering model. Protective factors for children of alcoholics were examined in a controlled study (N=386). Three possible models are…

Dimensionality of the 9-item Utrecht Work Engagement Scale revisited: A Bayesian structural equation modeling approach.

PubMed

Fong, Ted C T; Ho, Rainbow T H

2015-01-01

The aim of this study was to reexamine the dimensionality of the widely used 9-item Utrecht Work Engagement Scale using the maximum likelihood (ML) approach and Bayesian structural equation modeling (BSEM) approach. Three measurement models (1-factor, 3-factor, and bi-factor models) were evaluated in two split samples of 1,112 health-care workers using confirmatory factor analysis and BSEM, which specified small-variance informative priors for cross-loadings and residual covariances. Model fit and comparisons were evaluated by posterior predictive p-value (PPP), deviance information criterion, and Bayesian information criterion (BIC). None of the three ML-based models showed an adequate fit to the data. The use of informative priors for cross-loadings did not improve the PPP for the models. The 1-factor BSEM model with approximately zero residual covariances displayed a good fit (PPP>0.10) to both samples and a substantially lower BIC than its 3-factor and bi-factor counterparts. The BSEM results demonstrate empirical support for the 1-factor model as a parsimonious and reasonable representation of work engagement.

Heterogeneity in the Latent Structure of PTSD Symptoms among Canadian Veterans

ERIC Educational Resources Information Center

Naifeh, James A.; Richardson, J. Don; Del Ben, Kevin S.; Elhai, Jon D.

2010-01-01

The current study used factor mixture modeling to identify heterogeneity (i.e., latent classes) in 2 well-supported models of posttraumatic stress disorder's (PTSD) factor structure. Data were analyzed from a clinical sample of 405 Canadian veterans evaluated for PTSD. Results were consistent with our hypotheses. Each PTSD factor model was best…

A comparative study of mixture cure models with covariate

NASA Astrophysics Data System (ADS)

Leng, Oh Yit; Khalid, Zarina Mohd

2017-05-01

In survival analysis, the survival time is assumed to follow a non-negative distribution, such as the exponential, Weibull, and log-normal distributions. In some cases, the survival time is influenced by some observed factors. The absence of these observed factors may cause an inaccurate estimation in the survival function. Therefore, a survival model which incorporates the influences of observed factors is more appropriate to be used in such cases. These observed factors are included in the survival model as covariates. Besides that, there are cases where a group of individuals who are cured, that is, not experiencing the event of interest. Ignoring the cure fraction may lead to overestimate in estimating the survival function. Thus, a mixture cure model is more suitable to be employed in modelling survival data with the presence of a cure fraction. In this study, three mixture cure survival models are used to analyse survival data with a covariate and a cure fraction. The first model includes covariate in the parameterization of the susceptible individuals survival function, the second model allows the cure fraction to depend on covariate, and the third model incorporates covariate in both cure fraction and survival function of susceptible individuals. This study aims to compare the performance of these models via a simulation approach. Therefore, in this study, survival data with varying sample sizes and cure fractions are simulated and the survival time is assumed to follow the Weibull distribution. The simulated data are then modelled using the three mixture cure survival models. The results show that the three mixture cure models are more appropriate to be used in modelling survival data with the presence of cure fraction and an observed factor.

A systematic literature review of PTSD's latent structure in the Diagnostic and Statistical Manual of Mental Disorders: DSM-IV to DSM-5.

PubMed

Armour, Cherie; Műllerová, Jana; Elhai, Jon D

2016-03-01

The factor structure of posttraumatic stress disorder (PTSD) has been widely researched, but consensus regarding the exact number and nature of factors is yet to be reached. The aim of the current study was to systematically review the extant literature on PTSD's latent structure in the Diagnostic and Statistical Manual of Mental Disorders (DSM) in order to identify the best-fitting model. One hundred and twelve research papers published after 1994 using confirmatory factor analysis and DSM-based measures of PTSD were included in the review. In the DSM-IV literature, four-factor models received substantial support, but the five-factor Dysphoric arousal model demonstrated the best fit, regardless of gender, measurement instrument or trauma type. The recently proposed DSM-5 PTSD model was found to be a good representation of PTSD's latent structure, but studies analysing the six- and seven-factor models suggest that the DSM-5 PTSD factor structure may need further alterations. Copyright © 2015 Elsevier Ltd. All rights reserved.

The Impact of Sample Size and Other Factors When Estimating Multilevel Logistic Models

ERIC Educational Resources Information Center

Schoeneberger, Jason A.

2016-01-01

The design of research studies utilizing binary multilevel models must necessarily incorporate knowledge of multiple factors, including estimation method, variance component size, or number of predictors, in addition to sample sizes. This Monte Carlo study examined the performance of random effect binary outcome multilevel models under varying…

Maturity of hospital information systems: Most important influencing factors.

PubMed

Vidal Carvalho, João; Rocha, Álvaro; Abreu, António

2017-07-01

Maturity models facilitate organizational management, including information systems management, with hospital organizations no exception. This article puts forth a study carried out with a group of experts in the field of hospital information systems management with a view to identifying the main influencing factors to be included in an encompassing maturity model for hospital information systems management. This study is based on the results of a literature review, which identified maturity models in the health field and relevant influencing factors. The development of this model is justified to the extent that the available maturity models for the hospital information systems management field reveal multiple limitations, including lack of detail, absence of tools to determine their maturity and lack of characterization for stages of maturity structured by different influencing factors.

Spatial Resolution Effects of Digital Terrain Models on Landslide Susceptibility Analysis

NASA Astrophysics Data System (ADS)

Chang, K. T.; Dou, J.; Chang, Y.; Kuo, C. P.; Xu, K. M.; Liu, J. K.

2016-06-01

The purposes of this study are to identify the maximum number of correlated factors for landslide susceptibility mapping and to evaluate landslide susceptibility at Sihjhong river catchment in the southern Taiwan, integrating two techniques, namely certainty factor (CF) and artificial neural network (ANN). The landslide inventory data of the Central Geological Survey (CGS, MOEA) in 2004-2014 and two digital elevation model (DEM) datasets including a 5-meter LiDAR DEM and a 30-meter Aster DEM were prepared. We collected thirteen possible landslide-conditioning factors. Considering the multi-collinearity and factor redundancy, we applied the CF approach to optimize these thirteen conditioning factors. We hypothesize that if the CF values of the thematic factor layers are positive, it implies that these conditioning factors have a positive relationship with the landslide occurrence. Therefore, based on this assumption and positive CF values, seven conditioning factors including slope angle, slope aspect, elevation, terrain roughness index (TRI), terrain position index (TPI), total curvature, and lithology have been selected for further analysis. The results showed that the optimized-factors model provides a better accuracy for predicting landslide susceptibility in the study area. In conclusion, the optimized-factors model is suggested for selecting relative factors of landslide occurrence.

FACTORS INFLUENCING THE DESIGN OF BIOACCUMULATION FACTOR AND BIOTA-SEDIMENT ACCUMULATION FACTOR FIELD STUDIES

EPA Science Inventory

General guidance for designing field studies to measure bioaccumulation factors (BAFs) and biota-sediment accumulation factors (BSAFs) is not available. To develop such guidance, a series of modeling simulations were performed to evaluate the underlying factors and principles th...

An Early Model for Value and Sustainability in Health Information Exchanges: Qualitative Study.

PubMed

Feldman, Sue S

2018-04-30

The primary value relative to health information exchange has been seen in terms of cost savings relative to laboratory and radiology testing, emergency department expenditures, and admissions. However, models are needed to statistically quantify value and sustainability and better understand the dependent and mediating factors that contribute to value and sustainability. The purpose of this study was to provide a basis for early model development for health information exchange value and sustainability. A qualitative study was conducted with 21 interviews of eHealth Exchange participants across 10 organizations. Using a grounded theory approach and 3.0 as a relative frequency threshold, 5 main categories and 16 subcategories emerged. This study identifies 3 core current perceived value factors and 5 potential perceived value factors-how interviewees predict health information exchanges may evolve as there are more participants. These value factors were used as the foundation for early model development for sustainability of health information exchange. Using the value factors from the interviews, the study provides the basis for early model development for health information exchange value and sustainability. This basis includes factors from the research: fostering consumer engagement; establishing a provider directory; quantifying use, cost, and clinical outcomes; ensuring data integrity through patient matching; and increasing awareness, usefulness, interoperability, and sustainability of eHealth Exchange. ©Sue S Feldman. Originally published in JMIR Medical Informatics (http://medinform.jmir.org), 30.04.2018.

Cross-cultural confirmation of bi-factor models of a symptom distress measure: Symptom Checklist-90-Revised in clinical samples.

PubMed

Urbán, Róbert; Arrindell, Willem A; Demetrovics, Zsolt; Unoka, Zsolt; Timman, Reinier

2016-05-30

Four decades have elapsed since the introduction for clinical and research purposes of the Symptom Checklist-90(-R). Yet, its underlying dimensional structure has not been clearly delineated. A shift has been observed in the methods utilized-from predominantly exploratory factor analytic in nature in the first two decades or so to different confirmatory methods in recent years. A need remains to search for a structure that remains invariant across samples and nations. In that context, the present study attempted to replicate and extend recent findings yielded in a Hungarian general population sample (N=2,874) with two psychiatric patient samples from Hungary (N=972) and The Netherlands (N=1,902). In doing so, four models were contrasted: the one-factor model, Derogatis' nine factor model, a second-ordered factor model, and a bi-factor model. The bi-factor model was shown to yield the closest fit to the data in both countries. Further studies are needed to determine the stable number and kind of subscale scores that reflect the specific (primary) symptoms best, that is, those subscales with minimal shared variance with the overall general psychological distress dimension. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Model invariance across genders of the Broad Autism Phenotype Questionnaire.

PubMed

Broderick, Neill; Wade, Jordan L; Meyer, J Patrick; Hull, Michael; Reeve, Ronald E

2015-10-01

ASD is one of the most heritable neuropsychiatric disorders, though comprehensive genetic liability remains elusive. To facilitate genetic research, researchers employ the concept of the broad autism phenotype (BAP), a milder presentation of traits in undiagnosed relatives. Research suggests that the BAP Questionnaire (BAPQ) demonstrates psychometric properties superior to other self-report measures. To examine evidence regarding validity of the BAPQ, the current study used confirmatory factor analysis to test the assumption of model invariance across genders. Results of the current study upheld model invariance at each level of parameter constraint; however, model fit indices suggested limited goodness-of-fit between the proposed model and the sample. Exploratory analyses investigated alternate factor structure models but ultimately supported the proposed three-factor structure model.

Machine learning methods reveal the temporal pattern of dengue incidence using meteorological factors in metropolitan Manila, Philippines.

PubMed

Carvajal, Thaddeus M; Viacrusis, Katherine M; Hernandez, Lara Fides T; Ho, Howell T; Amalin, Divina M; Watanabe, Kozo

2018-04-17

Several studies have applied ecological factors such as meteorological variables to develop models and accurately predict the temporal pattern of dengue incidence or occurrence. With the vast amount of studies that investigated this premise, the modeling approaches differ from each study and only use a single statistical technique. It raises the question of whether which technique would be robust and reliable. Hence, our study aims to compare the predictive accuracy of the temporal pattern of Dengue incidence in Metropolitan Manila as influenced by meteorological factors from four modeling techniques, (a) General Additive Modeling, (b) Seasonal Autoregressive Integrated Moving Average with exogenous variables (c) Random Forest and (d) Gradient Boosting. Dengue incidence and meteorological data (flood, precipitation, temperature, southern oscillation index, relative humidity, wind speed and direction) of Metropolitan Manila from January 1, 2009 - December 31, 2013 were obtained from respective government agencies. Two types of datasets were used in the analysis; observed meteorological factors (MF) and its corresponding delayed or lagged effect (LG). After which, these datasets were subjected to the four modeling techniques. The predictive accuracy and variable importance of each modeling technique were calculated and evaluated. Among the statistical modeling techniques, Random Forest showed the best predictive accuracy. Moreover, the delayed or lag effects of the meteorological variables was shown to be the best dataset to use for such purpose. Thus, the model of Random Forest with delayed meteorological effects (RF-LG) was deemed the best among all assessed models. Relative humidity was shown to be the top-most important meteorological factor in the best model. The study exhibited that there are indeed different predictive outcomes generated from each statistical modeling technique and it further revealed that the Random forest model with delayed meteorological effects to be the best in predicting the temporal pattern of Dengue incidence in Metropolitan Manila. It is also noteworthy that the study also identified relative humidity as an important meteorological factor along with rainfall and temperature that can influence this temporal pattern.

Factor Structure and Psychometric Properties of English and Spanish Versions of the Edinburgh Postnatal Depression Scale Among Hispanic Women in a Primary Care Setting

PubMed Central

Hartley, Chelsey M.; Barroso, Nicole; Rey, Yasmin; Pettit, Jeremy W.; Bagner, Daniel M.

2015-01-01

Background Although a number of studies have examined the factor structure of the Edinburgh Postnatal Depression Scale (EPDS) in predominately White or African American samples, no published research has reported on the factor structure among Hispanic women who reside in the United States. Objective The current study examined the factor structure of the EPDS among Hispanic mothers in the United States. Method Among 220 Hispanic women, drawn from a pediatric primary care setting, with an infant aged 0 to 10 months, 6 structural models guided by the empirical literature were evaluated using confirmatory factor analysis. Results Results supported a 2-factor model of depression and anxiety as the best fitting model. Multigroup models supported the factorial invariance across women who completed the EDPS in English and Spanish. Conclusion These findings provide initial support for the 2-factor structure of the EPDS among Hispanic women in the United States. PMID:24807217

Factor structure and psychometric properties of english and spanish versions of the edinburgh postnatal depression scale among Hispanic women in a primary care setting.

PubMed

Hartley, Chelsey M; Barroso, Nicole; Rey, Yasmin; Pettit, Jeremy W; Bagner, Daniel M

2014-12-01

Although a number of studies have examined the factor structure of the Edinburgh Postnatal Depression Scale (EPDS) in predominately White or African American samples, no published research has reported on the factor structure among Hispanic women who reside in the United States. The current study examined the factor structure of the EPDS among Hispanic mothers in the United States. Among 220 Hispanic women, drawn from a pediatric primary care setting, with an infant aged 0 to 10 months, 6 structural models guided by the empirical literature were evaluated using confirmatory factor analysis. Results supported a 2-factor model of depression and anxiety as the best fitting model. Multigroup models supported the factorial invariance across women who completed the EDPS in English and Spanish. These findings provide initial support for the 2-factor structure of the EPDS among Hispanic women in the United States. © 2014 Wiley Periodicals, Inc.

Statistical Modeling Reveals the Effect of Absolute Humidity on Dengue in Singapore

PubMed Central

Xu, Hai-Yan; Fu, Xiuju; Lee, Lionel Kim Hock; Ma, Stefan; Goh, Kee Tai; Wong, Jiancheng; Habibullah, Mohamed Salahuddin; Lee, Gary Kee Khoon; Lim, Tian Kuay; Tambyah, Paul Anantharajah; Lim, Chin Leong; Ng, Lee Ching

2014-01-01

Weather factors are widely studied for their effects on indicating dengue incidence trends. However, these studies have been limited due to the complex epidemiology of dengue, which involves dynamic interplay of multiple factors such as herd immunity within a population, distinct serotypes of the virus, environmental factors and intervention programs. In this study, we investigate the impact of weather factors on dengue in Singapore, considering the disease epidemiology and profile of virus serotypes. A Poisson regression combined with Distributed Lag Non-linear Model (DLNM) was used to evaluate and compare the impact of weekly Absolute Humidity (AH) and other weather factors (mean temperature, minimum temperature, maximum temperature, rainfall, relative humidity and wind speed) on dengue incidence from 2001 to 2009. The same analysis was also performed on three sub-periods, defined by predominant circulating serotypes. The performance of DLNM regression models were then evaluated through the Akaike's Information Criterion. From the correlation and DLNM regression modeling analyses of the studied period, AH was found to be a better predictor for modeling dengue incidence than the other unique weather variables. Whilst mean temperature (MeanT) also showed significant correlation with dengue incidence, the relationship between AH or MeanT and dengue incidence, however, varied in the three sub-periods. Our results showed that AH had a more stable impact on dengue incidence than temperature when virological factors were taken into consideration. AH appeared to be the most consistent factor in modeling dengue incidence in Singapore. Considering the changes in dominant serotypes, the improvements in vector control programs and the inconsistent weather patterns observed in the sub-periods, the impact of weather on dengue is modulated by these other factors. Future studies on the impact of climate change on dengue need to take all the other contributing factors into consideration in order to make meaningful public policy recommendations. PMID:24786517

Statistical modeling reveals the effect of absolute humidity on dengue in Singapore.

PubMed

Xu, Hai-Yan; Fu, Xiuju; Lee, Lionel Kim Hock; Ma, Stefan; Goh, Kee Tai; Wong, Jiancheng; Habibullah, Mohamed Salahuddin; Lee, Gary Kee Khoon; Lim, Tian Kuay; Tambyah, Paul Anantharajah; Lim, Chin Leong; Ng, Lee Ching

2014-05-01

Weather factors are widely studied for their effects on indicating dengue incidence trends. However, these studies have been limited due to the complex epidemiology of dengue, which involves dynamic interplay of multiple factors such as herd immunity within a population, distinct serotypes of the virus, environmental factors and intervention programs. In this study, we investigate the impact of weather factors on dengue in Singapore, considering the disease epidemiology and profile of virus serotypes. A Poisson regression combined with Distributed Lag Non-linear Model (DLNM) was used to evaluate and compare the impact of weekly Absolute Humidity (AH) and other weather factors (mean temperature, minimum temperature, maximum temperature, rainfall, relative humidity and wind speed) on dengue incidence from 2001 to 2009. The same analysis was also performed on three sub-periods, defined by predominant circulating serotypes. The performance of DLNM regression models were then evaluated through the Akaike's Information Criterion. From the correlation and DLNM regression modeling analyses of the studied period, AH was found to be a better predictor for modeling dengue incidence than the other unique weather variables. Whilst mean temperature (MeanT) also showed significant correlation with dengue incidence, the relationship between AH or MeanT and dengue incidence, however, varied in the three sub-periods. Our results showed that AH had a more stable impact on dengue incidence than temperature when virological factors were taken into consideration. AH appeared to be the most consistent factor in modeling dengue incidence in Singapore. Considering the changes in dominant serotypes, the improvements in vector control programs and the inconsistent weather patterns observed in the sub-periods, the impact of weather on dengue is modulated by these other factors. Future studies on the impact of climate change on dengue need to take all the other contributing factors into consideration in order to make meaningful public policy recommendations.

Factor analysis and multiple regression between topography and precipitation on Jeju Island, Korea

NASA Astrophysics Data System (ADS)

Um, Myoung-Jin; Yun, Hyeseon; Jeong, Chang-Sam; Heo, Jun-Haeng

2011-11-01

SummaryIn this study, new factors that influence precipitation were extracted from geographic variables using factor analysis, which allow for an accurate estimation of orographic precipitation. Correlation analysis was also used to examine the relationship between nine topographic variables from digital elevation models (DEMs) and the precipitation in Jeju Island. In addition, a spatial analysis was performed in order to verify the validity of the regression model. From the results of the correlation analysis, it was found that all of the topographic variables had a positive correlation with the precipitation. The relations between the variables also changed in accordance with a change in the precipitation duration. However, upon examining the correlation matrix, no significant relationship between the latitude and the aspect was found. According to the factor analysis, eight topographic variables (latitude being the exception) were found to have a direct influence on the precipitation. Three factors were then extracted from the eight topographic variables. By directly comparing the multiple regression model with the factors (model 1) to the multiple regression model with the topographic variables (model 3), it was found that model 1 did not violate the limits of statistical significance and multicollinearity. As such, model 1 was considered to be appropriate for estimating the precipitation when taking into account the topography. In the study of model 1, the multiple regression model using factor analysis was found to be the best method for estimating the orographic precipitation on Jeju Island.

An assessment of the construct distinctiveness of stress arousal and burnout.

PubMed

Smith, Kenneth J; Davy, Jeanette A; Everly, George S

2006-10-01

This study examined the construct and discriminant validity of stress arousal and burnout as measured on the Stress Arousal Scale and the multidimensional role-specific version of the Maslach Burnout Inventory, respectively. The analyses utilized data from 148 individuals randomly selected from a database of 563 respondents to a larger study. The sample responded to a survey sent to members of the American Institute of Certified Public Accountants (AICPA). Sample size used in this study fell within Loehlin's 1992 prescription that for confirmatory factor analysis with two to four factors, a minimum of 100 to 200 cases should be collected. Forty-six respondents indicated that they were partners, principals, or sole practitioners in accounting firms, and 103 indicated that they were staff members (juniors, seniors, or managers). Latent variables were first constructed for the stress arousal and burnout factors. Confirmatory factor analysis was then conducted on the scale data to assess whether the factors would load on their respective underlying theoretical constructs. Finally, a nested model constraining stress arousal and burnout to load on one underlying construct was tested against the hypothesized two-factor model. The results indicated good model fit for the two-factor model and a significant loss of fit for the one-factor model, thus providing strong support for the conceptualization of stress arousal and burnout as distinct constructs.

The Four-Factor Model of Depressive Symptoms in Dementia Caregivers: A Structural Equation Model of Ethnic Differences

PubMed Central

Roth, David L.; Ackerman, Michelle L.; Okonkwo, Ozioma C.; Burgio, Louis D.

2008-01-01

Previous studies have suggested that 4 latent constructs (depressed affect, well-being, interpersonal problems, somatic symptoms) underlie the item responses on the Center for Epidemiological Studies Depression (CES-D) Scale. This instrument has been widely used in dementia caregiving research, but the fit of this multifactor model and the explanatory contributions of multifactor models have not been sufficiently examined for caregiving samples. The authors subjected CES-D data (N = 1,183) from the initial Resources for Enhancing Alzheimer’s Caregiver Health Study to confirmatory factor analysis methods and found that the 4-factor model provided excellent fit to the observed data. Invariance analyses suggested only minimal item-loading differences across race subgroups and supported the validity of race comparisons on the latent factors. Significant race differences were found on 3 of the 4 latent factors both before and after controlling for demographic covariates. African Americans reported less depressed affect and better well-being than White caregivers, who reported better well-being and fewer interpersonal problems than Hispanic caregivers. These findings clarify and extend previous studies of race differences in depression among diverse samples of dementia caregivers. PMID:18808246

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

PubMed

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

2018-01-17

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

Analysis of Korean Students' International Mobility by 2-D Model: Driving Force Factor and Directional Factor

ERIC Educational Resources Information Center

Park, Elisa L.

2009-01-01

The purpose of this study is to understand the dynamics of Korean students' international mobility to study abroad by using the 2-D Model. The first D, "the driving force factor," explains how and what components of the dissatisfaction with domestic higher education perceived by Korean students drives students' outward mobility to seek…

Do the Teacher and School Factors of the Dynamic Model Affect High- and Low-Achieving Student Groups to the Same Extent? A Cross-Country Study

ERIC Educational Resources Information Center

Vanlaar, Gudrun; Kyriakides, Leonidas; Panayiotou, Anastasia; Vandecandelaere, Machteld; McMahon, Léan; De Fraine, Bieke; Van Damme, Jan

2016-01-01

Background: The dynamic model of educational effectiveness (DMEE) is a comprehensive theoretical framework including factors that are important for school learning, based on consistent findings within educational effectiveness research. Purpose: This study investigates the impact of teacher and school factors of DMEE on mathematics and science…

A Dual-Driver Model of Retention and Turnover in the Direct Care Workforce

ERIC Educational Resources Information Center

Mittal, Vikas; Rosen, Jules; Leana, Carrie

2009-01-01

Purpose: The purpose of this study was to understand the factors associated with turnover and retention of direct care workers. We hypothesize that a dual-driver model that includes individual factors, on-the-job factors, off-the-job factors, and contextual factors can be used to distinguish between reasons for direct care workforces (DCWs)…

Antibiotic Resistances in Livestock: A Comparative Approach to Identify an Appropriate Regression Model for Count Data

PubMed Central

Hüls, Anke; Frömke, Cornelia; Ickstadt, Katja; Hille, Katja; Hering, Johanna; von Münchhausen, Christiane; Hartmann, Maria; Kreienbrock, Lothar

2017-01-01

Antimicrobial resistance in livestock is a matter of general concern. To develop hygiene measures and methods for resistance prevention and control, epidemiological studies on a population level are needed to detect factors associated with antimicrobial resistance in livestock holdings. In general, regression models are used to describe these relationships between environmental factors and resistance outcome. Besides the study design, the correlation structures of the different outcomes of antibiotic resistance and structural zero measurements on the resistance outcome as well as on the exposure side are challenges for the epidemiological model building process. The use of appropriate regression models that acknowledge these complexities is essential to assure valid epidemiological interpretations. The aims of this paper are (i) to explain the model building process comparing several competing models for count data (negative binomial model, quasi-Poisson model, zero-inflated model, and hurdle model) and (ii) to compare these models using data from a cross-sectional study on antibiotic resistance in animal husbandry. These goals are essential to evaluate which model is most suitable to identify potential prevention measures. The dataset used as an example in our analyses was generated initially to study the prevalence and associated factors for the appearance of cefotaxime-resistant Escherichia coli in 48 German fattening pig farms. For each farm, the outcome was the count of samples with resistant bacteria. There was almost no overdispersion and only moderate evidence of excess zeros in the data. Our analyses show that it is essential to evaluate regression models in studies analyzing the relationship between environmental factors and antibiotic resistances in livestock. After model comparison based on evaluation of model predictions, Akaike information criterion, and Pearson residuals, here the hurdle model was judged to be the most appropriate model. PMID:28620609

Procedures and models for estimating preconstruction costs of highway projects.

DOT National Transportation Integrated Search

2012-07-01

This study presents data driven and component based PE cost prediction models by utilizing critical factors retrieved from ten years of historical project data obtained from ODOT roadway division. The study used factor analysis of covariance and corr...

Learning with Interactive Whiteboards: Determining the Factors on Promoting Interactive Whiteboards to Students by Technology Acceptance Model

ERIC Educational Resources Information Center

Kilic, Eylem; Güler, Çetin; Çelik, H. Eray; Tatli, Cemal

2015-01-01

Purpose: The purpose of this study is to investigate the factors which might affect the intention to use interactive whiteboards (IWBs) by university students, using Technology Acceptance Model by the structural equation modeling approach. The following hypothesis guided the current study: H1. There is a positive relationship between IWB…

Modeling of Individual and Organizational Factors Affecting Traumatic Occupational Injuries Based on the Structural Equation Modeling: A Case Study in Large Construction Industries.

PubMed

Mohammadfam, Iraj; Soltanzadeh, Ahmad; Moghimbeigi, Abbas; Akbarzadeh, Mehdi

2016-09-01

Individual and organizational factors are the factors influencing traumatic occupational injuries. The aim of the present study was the short path analysis of the severity of occupational injuries based on individual and organizational factors. The present cross-sectional analytical study was implemented on traumatic occupational injuries within a ten-year timeframe in 13 large Iranian construction industries. Modeling and data analysis were done using the structural equation modeling (SEM) approach and the IBM SPSS AMOS statistical software version 22.0, respectively. The mean age and working experience of the injured workers were 28.03 ± 5.33 and 4.53 ± 3.82 years, respectively. The portions of construction and installation activities of traumatic occupational injuries were 64.4% and 18.1%, respectively. The SEM findings showed that the individual, organizational and accident type factors significantly were considered as effective factors on occupational injuries' severity (P < 0.05). Path analysis of occupational injuries based on the SEM reveals that individual and organizational factors and their indicator variables are very influential on the severity of traumatic occupational injuries. So, these should be considered to reduce occupational accidents' severity in large construction industries.

Indigenous Chinese Personality Constructs: Is the Five-Factor Model Complete?

ERIC Educational Resources Information Center

Cheung, Fanny M.; Leung, Kwok; Zhang, Jian-Xin; Sun, Hai-Fa; Gan, Yi-Qun; Song, Wei-Zhen; Xie, Dong

2001-01-01

Three studies involving Chinese respondents from China and Hong Kong and diverse respondents from Hawaii compared the Chinese Personality Assessment Inventory factor structure with the Revised NEO Personality Inventory (NEO-PI-R) and NEO-Five Factor Inventory. Results supported the universality of the five-factor model, the validity of NEO-PI-R,…

Posttraumatic stress disorder symptom structure in Chinese adolescents exposed to a deadly earthquake.

PubMed

Wang, Li; Long, Di; Li, Zhongquan; Armour, Cherie

2011-07-01

This present study examined the structure of posttraumatic stress disorder (PTSD) symptoms in a large sample of Chinese adolescents exposed to a deadly earthquake. A total of 2,800 middle school students aged 12 to 18 years participated in the study 6 months after the "Wenchuan Earthquake". Results of confirmatory factor analysis indicated that a five-factor intercorrelated model composed of intrusion, avoidance, numbing, dysphoric arousal, and anxious arousal, fit data significantly better than both the four-factor numbing model King et al. (Psychological Assessment 10:90-96, 1998) and the four-factor dysphoria model Simms et al. (Journal of Abnormal Psychology 111:637-647, 2002). Further examination of the external convergent and discriminant validity revealed that except for the dysphoric arousal factor, the remaining four PTSD factors yielded significantly different correlations with external measures of anxiety vs. depression. The findings add to the limited literature on the factor structure of PTSD in youths and on the five-factor PTSD model. In addition, they provide more detail into the latent psychopathological processes of PTSD, and inform the forthcoming DSM-5.

The factor structure of posttraumatic stress disorder: a literature update, critique of methodology, and agenda for future research.

PubMed

Elhai, Jon D; Palmieri, Patrick A

2011-08-01

We present an update of recent literature (since 2007) exploring the factor structure of posttraumatic stress disorder (PTSD) symptom measures. Research supporting a four-factor emotional numbing model and a four-factor dysphoria model is presented, with these models fitting better than all other models examined. Variables accounting for factor structure differences are reviewed, including PTSD query instructions, type of PTSD measure, extent of trauma exposure, ethnicity, and timing of administration. Methodological and statistical limitations with recent studies are presented. Finally, a research agenda and recommendations are offered to push this research area forward, including suggestions to validate PTSD’s factors against external measures of psychopathology, test moderators of factor structure, and examine heterogeneity of symptom presentations based on factor structure examination.

Use of Cox's Cure Model to Establish Clinical Determinants of Long-Term Disease-Free Survival in Neoadjuvant-Chemotherapy-Treated Breast Cancer Patients without Pathologic Complete Response.

PubMed

Asano, Junichi; Hirakawa, Akihiro; Hamada, Chikuma; Yonemori, Kan; Hirata, Taizo; Shimizu, Chikako; Tamura, Kenji; Fujiwara, Yasuhiro

2013-01-01

In prognostic studies for breast cancer patients treated with neoadjuvant chemotherapy (NAC), the ordinary Cox proportional-hazards (PH) model has been often used to identify prognostic factors for disease-free survival (DFS). This model assumes that all patients eventually experience relapse or death. However, a subset of NAC-treated breast cancer patients never experience these events during long-term follow-up (>10 years) and may be considered clinically "cured." Clinical factors associated with cure have not been studied adequately. Because the ordinary Cox PH model cannot be used to identify such clinical factors, we used the Cox PH cure model, a recently developed statistical method. This model includes both a logistic regression component for the cure rate and a Cox regression component for the hazard for uncured patients. The purpose of this study was to identify the clinical factors associated with cure and the variables associated with the time to recurrence or death in NAC-treated breast cancer patients without a pathologic complete response, by using the Cox PH cure model. We found that hormone receptor status, clinical response, human epidermal growth factor receptor 2 status, histological grade, and the number of lymph node metastases were associated with cure.

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

Almus, F.E.; Rao, L.V.; Fleck, R.A.

An umbilical vein model was designed in which washed vein segments are filled with a reaction mixture containing factor VIIa, Ca(+)+, and a substrate, either 3H-factor IX or 3H-factor X. The vein wall provides the tissue factor (TF) for factor VIIa/TF complexes that activate the substrates as measured by activation peptide release. The model was developed to study TF induced on venous endothelium in situ. However, unlike previous studies with TF expressed on cultured umbilical vein endothelial cells, factors IX and X were activated without first having to expose the vein wall to a perturbing stimulus. Histologic studies revealed thatmore » washing the vein and mixing the reaction mixture before subsampling had disrupted the endothelium. Immunostaining with anti-TF antibodies revealed no staining of endothelium but intense staining in extensions of Wharton's jelly penetrating fenestrations of the muscularis media of the vein. Thus, the model provided data on factor VIIa/TF formed, not on endothelium, but within the mucoid connective tissue of Wharton's jelly. It is known that factor VIIa/TF formed with TF in suspension or with TF expressed on the surface of cultured cells activates factor X more rapidly than factor IX. In contrast, in the umbilical vein model, when each substrate was present in an 88 nmol/L concentration, factors IX and X were activated at equivalent rates (mean activation rate for factor IX, 18.8 +/- 3.6 nmol/L/h; for factor X, 17.8 +/- 2.9 nmol/L/h; n = 9 paired vein segments). These data strengthen the evidence that factor VIIa/TF activation of factor IX represents a key initial reaction of coagulation in tissues. These results also show that data obtained with factor VIIa/TF complexes formed on the surface of cultured cells need not hold for factor VIIa/TF complexes formed in extracellular matrix.« less

The Tripartite Model of Risk Perception (TRIRISK): Distinguishing Deliberative, Affective, and Experiential Components of Perceived Risk.

PubMed

Ferrer, Rebecca A; Klein, William M P; Persoskie, Alexander; Avishai-Yitshak, Aya; Sheeran, Paschal

2016-10-01

Although risk perception is a key predictor in health behavior theories, current conceptions of risk comprise only one (deliberative) or two (deliberative vs. affective/experiential) dimensions. This research tested a tripartite model that distinguishes among deliberative, affective, and experiential components of risk perception. In two studies, and in relation to three common diseases (cancer, heart disease, diabetes), we used confirmatory factor analyses to examine the factor structure of the tripartite risk perception (TRIRISK) model and compared the fit of the TRIRISK model to dual-factor and single-factor models. In a third study, we assessed concurrent validity by examining the impact of cancer diagnosis on (a) levels of deliberative, affective, and experiential risk perception, and (b) the strength of relations among risk components, and tested predictive validity by assessing relations with behavioral intentions to prevent cancer. The tripartite factor structure was supported, producing better model fit across diseases (studies 1 and 2). Inter-correlations among the components were significantly smaller among participants who had been diagnosed with cancer, suggesting that affected populations make finer-grained distinctions among risk perceptions (study 3). Moreover, all three risk perception components predicted unique variance in intentions to engage in preventive behavior (study 3). The TRIRISK model offers both a novel conceptualization of health-related risk perceptions, and new measures that enhance predictive validity beyond that engendered by unidimensional and bidimensional models. The present findings have implications for the ways in which risk perceptions are targeted in health behavior change interventions, health communications, and decision aids.

Moderating Factors of Video-Modeling with Other as Model: A Meta-Analysis of Single-Case Studies

ERIC Educational Resources Information Center

Mason, Rose A.; Ganz, Jennifer B.; Parker, Richard I.; Burke, Mack D.; Camargo, Siglia P.

2012-01-01

Video modeling with other as model (VMO) is a more practical method for implementing video-based modeling techniques, such as video self-modeling, which requires significantly more editing. Despite this, identification of contextual factors such as participant characteristics and targeted outcomes that moderate the effectiveness of VMO has not…

Reliability and validity of general health questionnaire (GHQ-12) for male tannery workers: a study carried out in Kanpur, India.

PubMed

Kashyap, Gyan Chandra; Singh, Shri Kant

2017-03-21

The purpose of this study was to test the reliability, validity and factor structure of GHQ-12 questionnaire on male tannery workers of India. We have tested three different factor models of the GHQ-12. This paper used primary data obtained from a cross-sectional household study of tannery workers from Jajmau area of the city of Kanpur in northern India, which was conducted during January-June, 2015, as part of a doctoral program. The study covered 286 tannery workers from the study area. An interview schedule containing GHQ-12 was used for tannery workers who had completed at least 1 year at their present occupation preceding the survey. To test reliability, Cronbach's alpha test was used. The convergent test was used for validity. Confirmatory factor analysis was used to compare three factor structures for the GHQ-12. A total of 286 samples were analyzed in this study. The mean age of the tannery workers in this study was 38 years (SD = 1.42). We found the alpha coefficient to be 0.93 for the complete sample. The value of alpha represents the acceptable internal consistency for all the groups. Each item of scale showed almost the same internal consistency of 0.93 for the male tannery workers. The correlation between factor 1 (Anxiety and Depression) and factor 2 (Social Dysfunction) was 0.92. The correlation between factor 1 (Anxiety and Depression) and factor 3 (Loss of confidence) was the highest 0.98. Comparative fit index (CFI) estimate best-fitted for model-III that gave the CFI value 0.97. The SRMR indicator gave the lowest value 0.031 for the model-III. The findings suggest that the Hindi version of GHQ-12 is a reliable and valid tool for measuring psychological distress in male tannery workers of Kanpur city, India. Study found that the model proposed by the Graetz was the best fitted model for the data.

Relationship between stress-related psychosocial work factors and suboptimal health among Chinese medical staff: a cross-sectional study.

PubMed

Liang, Ying-Zhi; Chu, Xi; Meng, Shi-Jiao; Zhang, Jie; Wu, Li-Juan; Yan, Yu-Xiang

2018-03-06

The study aimed to develop and validate a model to measure psychosocial factors at work among medical staff in China based on confirmatory factor analysis (CFA). The second aim of the current study was to clarify the association between stress-related psychosocial work factors and suboptimal health status. The cross-sectional study was conducted using clustered sampling method. Xuanwu Hospital, a 3A grade hospital in Beijing. Nine hundred and fourteen medical staff aged over 40 years were sampled. Seven hundred and ninety-seven valid questionnaires were collected and used for further analyses. The sample included 94% of the Han population. The Copenhagen Psychosocial Questionnaire (COPSOQ) and the Suboptimal Health Status Questionnaires-25 were used to assess the psychosocial factors at work and suboptimal health status, respectively. CFA was conducted to establish the evaluating method of COPSOQ. A multivariate logistic regression model was used to estimate the relationship between suboptimal health status and stress-related psychosocial work factors among Chinese medical staff. There was a strong correlation among the five dimensions of COPSOQ based on the first-order factor model. Then, we established two second-order factors including negative and positive psychosocial work stress factors to evaluate psychosocial factors at work, and the second-order factor model fit well. The high score in negative (OR (95% CI)=1.47 (1.34 to 1.62), P<0.001) and positive (OR (95% CI)=0.96 (0.94 to 0.98), P<0.001) psychosocial work factors increased and decreased the risk of suboptimal health, respectively. This relationship remained statistically significant after adjusting for confounders and when using different cut-offs of suboptimal health status. Among medical staff, the second-order factor model was a suitable method to evaluate the COPSOQ. The negative and positive psychosocial work stress factors might be the risk and protective factors of suboptimal health, respectively. Moreover, negative psychosocial work stress was the most associated factor to predict suboptimal health. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2018. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

Relationship between stress-related psychosocial work factors and suboptimal health among Chinese medical staff: a cross-sectional study

PubMed Central

Meng, Shi-Jiao; Zhang, Jie; Wu, Li-Juan; Yan, Yu-Xiang

2018-01-01

Objectives The study aimed to develop and validate a model to measure psychosocial factors at work among medical staff in China based on confirmatory factor analysis (CFA). The second aim of the current study was to clarify the association between stress-related psychosocial work factors and suboptimal health status. Design The cross-sectional study was conducted using clustered sampling method. Setting Xuanwu Hospital, a 3A grade hospital in Beijing. Participants Nine hundred and fourteen medical staff aged over 40 years were sampled. Seven hundred and ninety-seven valid questionnaires were collected and used for further analyses. The sample included 94% of the Han population. Main outcome measures The Copenhagen Psychosocial Questionnaire (COPSOQ) and the Suboptimal Health Status Questionnaires-25 were used to assess the psychosocial factors at work and suboptimal health status, respectively. CFA was conducted to establish the evaluating method of COPSOQ. A multivariate logistic regression model was used to estimate the relationship between suboptimal health status and stress-related psychosocial work factors among Chinese medical staff. Results There was a strong correlation among the five dimensions of COPSOQ based on the first-order factor model. Then, we established two second-order factors including negative and positive psychosocial work stress factors to evaluate psychosocial factors at work, and the second-order factor model fit well. The high score in negative (OR (95% CI)=1.47 (1.34 to 1.62), P<0.001) and positive (OR (95% CI)=0.96 (0.94 to 0.98), P<0.001) psychosocial work factors increased and decreased the risk of suboptimal health, respectively. This relationship remained statistically significant after adjusting for confounders and when using different cut-offs of suboptimal health status. Conclusions Among medical staff, the second-order factor model was a suitable method to evaluate the COPSOQ. The negative and positive psychosocial work stress factors might be the risk and protective factors of suboptimal health, respectively. Moreover, negative psychosocial work stress was the most associated factor to predict suboptimal health. PMID:29511008

Perception of competence in middle school physical education: instrument development and validation.

PubMed

Scrabis-Fletcher, Kristin; Silverman, Stephen

2010-03-01

Perception of Competence (POC) has been studied extensively in physical activity (PA) research with similar instruments adapted for physical education (PE) research. Such instruments do not account for the unique PE learning environment. Therefore, an instrument was developed and the scores validated to measure POC in middle school PE. A multiphase design was used consisting of an intensive theoretical review, elicitation study, prepilot study, pilot study, content validation study, and final validation study (N=1281). Data analysis included a multistep iterative process to identify the best model fit. A three-factor model for POC was tested and resulted in root mean square error of approximation = .09, root mean square residual = .07, goodness offit index = .90, and adjusted goodness offit index = .86 values in the acceptable range (Hu & Bentler, 1999). A two-factor model was also tested and resulted in a good fit (two-factor fit indexes values = .05, .03, .98, .97, respectively). The results of this study suggest that an instrument using a three- or two-factor model provides reliable and valid scores ofPOC measurement in middle school PE.

Forms of ethnic prejudice: assessing the dimensionality of a Spanish-language version of the Blatant and Subtle Prejudice Scale.

PubMed

Cárdenas Castro, Manuel

2010-02-01

The main purpose of this study was to investigate the dimensionality of a Spanish-language version of the Blatant and Subtle Prejudice Scale via exploratory (EFA) and confirmatory factor analysis (CFA). No research has confirmed the hypothesized factor structure in Latin American countries. Using data from a random and probability survey in population of the northern area of Chile (N= 896), four models were specified: single factor model (global prejudice factor), correlated two-factor model (subtle and blatant prejudice), correlated two-factor second-order model, and single-factor second-order model. The findings indicated that the two-factor second-order model had the best fit. The corresponding alpha coefficients were .82 (subtle prejudice) and .76 (blatant prejudice). Lastly, differences were examined between , , and regarding their feelings toward immigrants, their feelings about their beliefs concerning the state aid received by these out-groups, and their feelings about their beliefs regarding future policies for them.

Modelling the pre-assessment learning effects of assessment: evidence in the validity chain.

PubMed

Cilliers, Francois J; Schuwirth, Lambert W T; van der Vleuten, Cees P M

2012-11-01

We previously developed a model of the pre-assessment learning effects of consequential assessment and started to validate it. The model comprises assessment factors, mechanism factors and learning effects. The purpose of this study was to continue the validation process. For stringency, we focused on a subset of assessment factor-learning effect associations that featured least commonly in a baseline qualitative study. Our aims were to determine whether these uncommon associations were operational in a broader but similar population to that in which the model was initially derived. A cross-sectional survey of 361 senior medical students at one medical school was undertaken using a purpose-made questionnaire based on a grounded theory and comprising pairs of written situational tests. In each pair, the manifestation of an assessment factor was varied. The frequencies at which learning effects were selected were compared for each item pair, using an adjusted alpha to assign significance. The frequencies at which mechanism factors were selected were calculated. There were significant differences in the learning effect selected between the two scenarios of an item pair for 13 of this subset of 21 uncommon associations, even when a p-value of < 0.00625 was considered to indicate significance. Three mechanism factors were operational in most scenarios: agency; response efficacy, and response value. For a subset of uncommon associations in the model, the role of most assessment factor-learning effect associations and the mechanism factors involved were supported in a broader but similar population to that in which the model was derived. Although model validation is an ongoing process, these results move the model one step closer to the stage of usefully informing interventions. Results illustrate how factors not typically included in studies of the learning effects of assessment could confound the results of interventions aimed at using assessment to influence learning. © Blackwell Publishing Ltd 2012.

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

PubMed Central

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

2014-01-01

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

Reproductive Risk Factors and Coronary Heart Disease in the Women’s Health Initiative Observational Study

PubMed Central

Parikh, Nisha I.; Jeppson, Rebecca P.; Berger, Jeffrey S.; Eaton, Charles B.; Kroenke, Candyce H.; LeBlanc, Erin S.; Lewis, Cora E.; Loucks, Eric B.; Parker, Donna R.; Rillamas-Sun, Eileen; Ryckman, Kelli K; Waring, Molly E.; Schenken, Robert S.; Johnson, Karen C; Edstedt-Bonamy, Anna-Karin; Allison, Matthew A.; Howard, Barbara V.

2016-01-01

Background Reproductive factors provide an early window into a woman’s coronary heart disease (CHD) risk, however their contribution to CHD risk stratification is uncertain. Methods and Results In the Women’s Health Initiative Observational Study, we constructed Cox proportional hazards models for CHD including age, pregnancy status, number of live births, age at menarche, menstrual irregularity, age at first birth, stillbirths, miscarriages, infertility ≥ 1 year, infertility cause, and breastfeeding. We next added each candidate reproductive factor to an established CHD risk factor model. A final model was then constructed with significant reproductive factors added to established CHD risk factors. Improvement in C-statistic, net reclassification index (or NRI with risk categories of <5%, 5–<10%, and ≥10% 10-year risk of CHD) and integrated discriminatory index (IDI) were assessed. Among 72,982 women [n=4607 CHD events, median follow-up=12.0 (IQR=8.3–13.7) years, mean (SD) age 63.2 (7.2) years], an age-adjusted reproductive risk factor model had a C-statistic of 0.675 for CHD. In a model adjusted for established CHD risk factors, younger age at first birth, number of still births, number of miscarriages and lack of breastfeeding were positively associated with CHD. Reproductive factors modestly improved model discrimination (C-statistic increased from 0.726 to 0.730; IDI=0.0013, p-value < 0.0001). Net reclassification for women with events was not improved (NRI events=0.007, p-value=0.18); and for women without events was marginally improved (NRI non-events=0.002, p-value=0.04) Conclusions Key reproductive factors are associated with CHD independently of established CHD risk factors, very modestly improve model discrimination and do not materially improve net reclassification. PMID:27143682

Item-level and subscale-level factoring of Biggs' Learning Process Questionnaire (LPQ) in a mainland Chinese sample.

PubMed

Sachs, J; Gao, L

2000-09-01

The learning process questionnaire (LPQ) has been the source of intensive cross-cultural study. However, an item-level factor analysis of all the LPQ items simultaneously has never been reported. Rather, items within each subscale have been factor analysed to establish subscale unidimensionality and justify the use of composite subscale scores. It was of major interest to see if the six logically constructed items groups of the LPQ would be supported by empirical evidence. Additionally, it was of interest to compare the consistency of the reliability and correlational structure of the LPQ subscales in our study with those of previous cross-cultural studies. Confirmatory factor analysis was used to fit the six-factor item level model and to fit five representative subscale level factor models. A total of 1070 students between the ages of 15 to 18 years was drawn from a representative selection of 29 classes from within 15 secondary schools in Guangzhou, China. Males and females were almost equally represented. The six-factor item level model of the LPQ seemed to fit reasonably well, thus supporting the six dimensional structure of the LPQ and justifying the use of composite subscale scores for each LPQ dimension. However, the reliability of many of these subscales was low. Furthermore, only two subscale-level factor models showed marginally acceptable fit. Substantive considerations supported an oblique three-factor model. Because the LPQ subscales often show low internal consistency reliability, experimental and correlational studies that have used these subscales as dependent measures have been disappointing. It is suggested that some LPQ items should be revised and other items added to improve the inventory's overall psychometric properties.

Relationship between oral health-related knowledge, attitudes and behavior among 15-16-year-old adolescents: a structural equation modeling approach.

PubMed

Tolvanen, Mimmi; Lahti, Satu; Miettunen, Jouko; Hausen, Hannu

2012-03-01

The aim of this study was to confirm the previously observed attitudinal factor structure related to behavioral change and the knowledge-attitude-behavior model on dental health and hygiene among adolescents. The study population consisted of all 8(th) and 9(th) graders (15-16 years) who started the 2004-2005 school year in Rauma, Finland (n = 827). Data on knowledge, attitudes, toothbrushing and using fluoride toothpaste were gathered by questionnaires. Hypothesized structure included four attitudinal factors related to dental health and hygiene: 'importance of toothbrushing when participating in social situations' (F1), 'importance of toothbrushing for health-related reasons and better appearance' (F2), 'being concerned about developing caries lesions' (F3) and 'importance of toothbrushing for feeling accepted' (F4). Structural equation modeling (SEM) was used to test the hypothesized model: pathways lead from knowledge to behavior both directly and via attitudes. The hypothesized model was also modified by removing non-significant pathways and studying the inter-relationships between attitudes. A confirmatory factor analysis revealed that factor F4 had to be removed. In the final model, knowledge influenced behavior directly and via two attitude factors, F1 and F2, which were inter-related. 'Concern about developing caries lesions' was a background factor influencing only knowledge. The final factor structure and SEM model were acceptable-to-good fit. Knowledge had a smaller effect on behavior than on attitudes. Our results support theories about the causal knowledge-attitudes-behavior chain, also for adolescents' oral health-related behaviors.

Modelling impulsive factors for electronics and restaurant coupons’ e-store display

NASA Astrophysics Data System (ADS)

Ariningsih, P. K.; Nainggolan, M.; Sandy, I. A.

2018-04-01

In many times, the increment of e-store visitors does not followed by sales increment. Most purchases through e-commerce are impulsive buying, however only small amount of study is available to understand impulsive factors of e-store display. This paper suggests a preliminary concept on understanding the impulsive factors in Electronics and Restaurant Coupons e-store display, which are two among few popular group products sold through e-commerce. By conducting literature study and survey, 31 attributes were identified as impulsive factors in electronics e-store display and 20 attributes were identified as impulsive factors for restaurant coupon e-store. The attributes were then grouped into comprehensive impulsive factors by factor analysis. Each group of impulsive attributes were generated into 3 factors. Accessibility Factors and Trust Factors appeared for each group products. The other factors are Internal Factors for electronics e-store and Marketing factors for restaurant coupons e-store. Structural Equation Model of the impulsive factors was developed for each type of e-store, which stated the covariance between Trust Factors and Accessibility Factors. Based on preliminary model, Internal Factor and Trust Factor are influencing impulsive buying in electronics store. Special factor for electronics e-store is Internal Factor, while for restaurant coupons e-store is Marketing Factor.

PTSD's latent structure in Malaysian tsunami victims: assessing the newly proposed Dysphoric Arousal model.

PubMed

Armour, Cherie; Raudzah Ghazali, Siti; Elklit, Ask

2013-03-30

The underlying latent structure of Posttraumatic Stress Disorder (PTSD) is widely researched. However, despite a plethora of factor analytic studies, no single model has consistently been shown as superior to alternative models. The two most often supported models are the Emotional Numbing and the Dysphoria models. However, a recently proposed five-factor Dysphoric Arousal model has been gathering support over and above existing models. Data for the current study were gathered from Malaysian Tsunami survivors (N=250). Three competing models (Emotional Numbing/Dysphoria/Dysphoric Arousal) were specified and estimated using Confirmatory Factor Analysis (CFA). The Dysphoria model provided superior fit to the data compared to the Emotional Numbing model. However, using chi-square difference tests, the Dysphoric Arousal model showed a superior fit compared to both the Emotional Numbing and Dysphoria models. In conclusion, the current results suggest that the Dysphoric Arousal model better represents PTSD's latent structure and that items measuring sleeping difficulties, irritability/anger and concentration difficulties form a separate, unique PTSD factor. These results are discussed in relation to the role of Hyperarousal in PTSD's on-going symptom maintenance and in relation to the DSM-5. Copyright © 2012 Elsevier Ireland Ltd. All rights reserved.

Modeling the Relationship between Safety Climate and Safety Performance in a Developing Construction Industry: A Cross-Cultural Validation Study

PubMed Central

Zahoor, Hafiz; Chan, Albert P. C.; Utama, Wahyudi P.; Gao, Ran; Zafar, Irfan

2017-01-01

This study attempts to validate a safety performance (SP) measurement model in the cross-cultural setting of a developing country. In addition, it highlights the variations in investigating the relationship between safety climate (SC) factors and SP indicators. The data were collected from forty under-construction multi-storey building projects in Pakistan. Based on the results of exploratory factor analysis, a SP measurement model was hypothesized. It was tested and validated by conducting confirmatory factor analysis on calibration and validation sub-samples respectively. The study confirmed the significant positive impact of SC on safety compliance and safety participation, and negative impact on number of self-reported accidents/injuries. However, number of near-misses could not be retained in the final SP model because it attained a lower standardized path coefficient value. Moreover, instead of safety participation, safety compliance established a stronger impact on SP. The study uncovered safety enforcement and promotion as a novel SC factor, whereas safety rules and work practices was identified as the most neglected factor. The study contributed to the body of knowledge by unveiling the deviations in existing dimensions of SC and SP. The refined model is expected to concisely measure the SP in the Pakistani construction industry, however, caution must be exercised while generalizing the study results to other developing countries. PMID:28350366

Modeling the Relationship between Safety Climate and Safety Performance in a Developing Construction Industry: A Cross-Cultural Validation Study.

PubMed

Zahoor, Hafiz; Chan, Albert P C; Utama, Wahyudi P; Gao, Ran; Zafar, Irfan

2017-03-28

This study attempts to validate a safety performance (SP) measurement model in the cross-cultural setting of a developing country. In addition, it highlights the variations in investigating the relationship between safety climate (SC) factors and SP indicators. The data were collected from forty under-construction multi-storey building projects in Pakistan. Based on the results of exploratory factor analysis, a SP measurement model was hypothesized. It was tested and validated by conducting confirmatory factor analysis on calibration and validation sub-samples respectively. The study confirmed the significant positive impact of SC on safety compliance and safety participation , and negative impact on number of self-reported accidents/injuries . However, number of near-misses could not be retained in the final SP model because it attained a lower standardized path coefficient value. Moreover, instead of safety participation , safety compliance established a stronger impact on SP. The study uncovered safety enforcement and promotion as a novel SC factor, whereas safety rules and work practices was identified as the most neglected factor. The study contributed to the body of knowledge by unveiling the deviations in existing dimensions of SC and SP. The refined model is expected to concisely measure the SP in the Pakistani construction industry, however, caution must be exercised while generalizing the study results to other developing countries.

Factor structure and internal reliability of an exercise health belief model scale in a Mexican population.

PubMed

Villar, Oscar Armando Esparza-Del; Montañez-Alvarado, Priscila; Gutiérrez-Vega, Marisela; Carrillo-Saucedo, Irene Concepción; Gurrola-Peña, Gloria Margarita; Ruvalcaba-Romero, Norma Alicia; García-Sánchez, María Dolores; Ochoa-Alcaraz, Sergio Gabriel

2017-03-01

Mexico is one of the countries with the highest rates of overweight and obesity around the world, with 68.8% of men and 73% of women reporting both. This is a public health problem since there are several health related consequences of not exercising, like having cardiovascular diseases or some types of cancers. All of these problems can be prevented by promoting exercise, so it is important to evaluate models of health behaviors to achieve this goal. Among several models the Health Belief Model is one of the most studied models to promote health related behaviors. This study validates the first exercise scale based on the Health Belief Model (HBM) in Mexicans with the objective of studying and analyzing this model in Mexico. Items for the scale called the Exercise Health Belief Model Scale (EHBMS) were developed by a health research team, then the items were applied to a sample of 746 participants, male and female, from five cities in Mexico. The factor structure of the items was analyzed with an exploratory factor analysis and the internal reliability with Cronbach's alpha. The exploratory factor analysis reported the expected factor structure based in the HBM. The KMO index (0.92) and the Barlett's sphericity test (p < 0.01) indicated an adequate and normally distributed sample. Items had adequate factor loadings, ranging from 0.31 to 0.92, and the internal consistencies of the factors were also acceptable, with alpha values ranging from 0.67 to 0.91. The EHBMS is a validated scale that can be used to measure exercise based on the HBM in Mexican populations.

Examining the Reliability and Validity of Clinician Ratings on the Five-Factor Model Score Sheet

ERIC Educational Resources Information Center

Few, Lauren R.; Miller, Joshua D.; Morse, Jennifer Q.; Yaggi, Kirsten E.; Reynolds, Sarah K.; Pilkonis, Paul A.

2010-01-01

Despite substantial research use, measures of the five-factor model (FFM) are infrequently used in clinical settings due, in part, to issues related to administration time and a reluctance to use self-report instruments. The current study examines the reliability and validity of the Five-Factor Model Score Sheet (FFMSS), which is a 30-item…

Structural equation modeling in environmental risk assessment.

PubMed

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

1991-01-01

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

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

PubMed

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

2017-07-01

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

Bayes Factor Covariance Testing in Item Response Models.

PubMed

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

2017-12-01

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

Confirmatory factor analysis of the Oral Health Impact Profile.

PubMed

John, M T; Feuerstahler, L; Waller, N; Baba, K; Larsson, P; Celebić, A; Kende, D; Rener-Sitar, K; Reissmann, D R

2014-09-01

Previous exploratory analyses suggest that the Oral Health Impact Profile (OHIP) consists of four correlated dimensions and that individual differences in OHIP total scores reflect an underlying higher-order factor. The aim of this report is to corroborate these findings in the Dimensions of Oral Health-Related Quality of Life (DOQ) Project, an international study of general population subjects and prosthodontic patients. Using the project's Validation Sample (n = 5022), we conducted confirmatory factor analyses in a sample of 4993 subjects with sufficiently complete data. In particular, we compared the psychometric performance of three models: a unidimensional model, a four-factor model and a bifactor model that included one general factor and four group factors. Using model-fit criteria and factor interpretability as guides, the four-factor model was deemed best in terms of strong item loadings, model fit (RMSEA = 0·05, CFI = 0·99) and interpretability. These results corroborate our previous findings that four highly correlated factors - which we have named Oral Function, Oro-facial Pain, Oro-facial Appearance and Psychosocial Impact - can be reliably extracted from the OHIP item pool. However, the good fit of the unidimensional model and the high interfactor correlations in the four-factor solution suggest that OHRQoL can also be sufficiently described with one score. © 2014 John Wiley & Sons Ltd.

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

PubMed

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

2016-01-01

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

Predictive models and prognostic factors for upper tract urothelial carcinoma: a comprehensive review of the literature.

PubMed

Mbeutcha, Aurélie; Mathieu, Romain; Rouprêt, Morgan; Gust, Kilian M; Briganti, Alberto; Karakiewicz, Pierre I; Shariat, Shahrokh F

2016-10-01

In the context of customized patient care for upper tract urothelial carcinoma (UTUC), decision-making could be facilitated by risk assessment and prediction tools. The aim of this study was to provide a critical overview of existing predictive models and to review emerging promising prognostic factors for UTUC. A literature search of articles published in English from January 2000 to June 2016 was performed using PubMed. Studies on risk group stratification models and predictive tools in UTUC were selected, together with studies on predictive factors and biomarkers associated with advanced-stage UTUC and oncological outcomes after surgery. Various predictive tools have been described for advanced-stage UTUC assessment, disease recurrence and cancer-specific survival (CSS). Most of these models are based on well-established prognostic factors such as tumor stage, grade and lymph node (LN) metastasis, but some also integrate newly described prognostic factors and biomarkers. These new prediction tools seem to reach a high level of accuracy, but they lack external validation and decision-making analysis. The combinations of patient-, pathology- and surgery-related factors together with novel biomarkers have led to promising predictive tools for oncological outcomes in UTUC. However, external validation of these predictive models is a prerequisite before their introduction into daily practice. New models predicting response to therapy are urgently needed to allow accurate and safe individualized management in this heterogeneous disease.

Confirmatory factor analysis of the Eating Disorder Examination-Questionnaire: A comparison of five factor solutions across vegan and omnivore participants.

PubMed

Heiss, Sydney; Boswell, James F; Hormes, Julia M

2018-05-01

The Eating Disorder Examination-Questionnaire (EDE-Q) is a valid and reliable measure of eating-related pathology, but its factor structure has proven difficult to replicate. Given differences in dietary patterns in vegans compared to omnivores, proper measurement of eating disorder symptoms is especially important in studies of animal product avoiders. This study compared goodness-of-fit of five alternative models of the EDE-Q in vegans (i.e., individuals refraining from all animal products, n = 318) and omnivores (i.e., individuals not restricting intake of animal products, n = 200). Confirmatory factor analyses were used to compare fit indices of the original four-factor model of the EDE-Q, along with alternative three-, two-, full one-, and brief one-factor models. No model provided adequate fit of the data in either sample of respondents. The fit of the brief one-factor model was the closest to acceptable in omnivores, but did not perform as well in vegans. Indicators of fit were comparable in vegans and omnivores across all other models. Our data confirm difficulties in replicating the proposed factor structure of the EDE-Q, including in vegans. More research is needed to determine the suitability of the EDE-Q for quantifying eating behaviors, including in those abstaining from animal products. © 2018 Wiley Periodicals, Inc.

Improved performance of epidemiologic and genetic risk models for rheumatoid arthritis serologic phenotypes using family history

PubMed Central

Sparks, Jeffrey A.; Chen, Chia-Yen; Jiang, Xia; Askling, Johan; Hiraki, Linda T.; Malspeis, Susan; Klareskog, Lars; Alfredsson, Lars; Costenbader, Karen H.; Karlson, Elizabeth W.

2014-01-01

Objective To develop and validate rheumatoid arthritis (RA) risk models based on family history, epidemiologic factors, and known genetic risk factors. Methods We developed and validated models for RA based on known RA risk factors, among women in two cohorts: the Nurses’ Health Study (NHS, 381 RA cases and 410 controls) and the Epidemiological Investigation of RA (EIRA, 1244 RA cases and 971 controls). Model discrimination was evaluated using the area under the receiver operating characteristic curve (AUC) in logistic regression models for the study population and for those with positive family history. The joint effect of family history with genetics, smoking, and body mass index (BMI) was evaluated using logistic regression models to estimate odds ratios (OR) for RA. Results The complete model including family history, epidemiologic risk factors, and genetics demonstrated AUCs of 0.74 for seropositive RA in NHS and 0.77 for anti-citrullinated protein antibody (ACPA)-positive RA in EIRA. Among women with positive family history, discrimination was excellent for complete models for seropositive RA in NHS (AUC 0.82) and ACPA-positive RA in EIRA (AUC 0.83). Positive family history, high genetic susceptibility, smoking, and increased BMI had an OR of 21.73 for ACPA-positive RA. Conclusions We developed models for seropositive and seronegative RA phenotypes based on family history, epidemiologic and genetic factors. Among those with positive family history, models utilizing epidemiologic and genetic factors were highly discriminatory for seropositive and seronegative RA. Assessing epidemiological and genetic factors among those with positive family history may identify individuals suitable for RA prevention strategies. PMID:24685909

Generalized ghost pilgrim dark energy in F(T,TG) cosmology

NASA Astrophysics Data System (ADS)

Sharif, M.; Nazir, Kanwal

2016-07-01

This paper is devoted to study the generalized ghost pilgrim dark energy (PDE) model in F(T,TG) gravity with flat Friedmann-Robertson-Walker (FRW) universe. In this scenario, we reconstruct F(T,TG) models and evaluate the corresponding equation of state (EoS) parameter for different choices of the scale factors. We assume power-law scale factor, scale factor for unification of two phases, intermediate and bouncing scale factor. We study the behavior of reconstructed models and EoS parameters graphically. It is found that all the reconstructed models show decreasing behavior for PDE parameter u = -2. On the other hand, the EoS parameter indicates transition from dust-like matter to phantom era for all choices of the scale factor except intermediate for which this is less than - 1. We conclude that all the results are in agreement with PDE phenomenon.

Empirical evidence for an invariant three-factor structure of the Parental Bonding Instrument in six European countries.

PubMed

Heider, Dirk; Matschinger, Herbert; Bernert, Sebastian; Vilagut, Gemma; Martínez-Alonso, Montserrat; Dietrich, Sandra; Angermeyer, Matthias C

2005-06-30

The objective of the present study was to test the Parental Bonding Instrument's (PBI) three-factor structure (care, overprotection, and authoritarianism) found by [Cox, B.J., Enns, M.W., Clara, I.P. 2000, The Parental Bonding Instrument: confirmatory evidence for a three-factor model in a psychiatric clinical sample and in the National Comorbidity Survey, Social Psychiatry and Psychiatric Epidemiology 35 (2000) 353-357.] on an eight-item short form of the scale. A total of 8813 respondents from the six European countries participating in the ESEMeD project (Belgium, France, Germany, Italy, The Netherlands, and Spain) completed either the PBI-paternal or the PBI-maternal scale. Maximum likelihood confirmatory factor analysis was used to compare the original factor model of Cox et al. with a three-factor solution that emerged from an exploration of the structure with principal component factor analysis. When gender and age subgroups, as well as different countries, were taken into account, the accuracy of the model was confirmed. The fit indices for the new model indicated a generally better model fit than the ones for the model originally developed by Cox et al. Further efforts should be directed to the modeling of the dimension authoritarianism. The results provide the opportunity to estimate the influence of the extracted factors on mental disorders in different countries. The application of the short form of the PBI seems suitable primarily for large epidemiological studies.

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

PubMed

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

2017-12-01

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

A multilateral modelling of Youth Soccer Performance Index (YSPI)

NASA Astrophysics Data System (ADS)

Bisyri Husin Musawi Maliki, Ahmad; Razali Abdullah, Mohamad; Juahir, Hafizan; Abdullah, Farhana; Ain Shahirah Abdullah, Nurul; Muazu Musa, Rabiu; Musliha Mat-Rasid, Siti; Adnan, Aleesha; Azura Kosni, Norlaila; Muhamad, Wan Siti Amalina Wan; Afiqah Mohamad Nasir, Nur

2018-04-01

This study aims to identify the most dominant factors that influencing performance of soccer player and to predict group performance for soccer players. A total of 184 of youth soccer players from Malaysia sport school and six soccer academy encompasses as respondence of the study. Exploratory factor analysis (EFA) and Confirmatory factor analysis (CFA) were computed to identify the most dominant factors whereas reducing the initial 26 parameters with recommended >0.5 of factor loading. Meanwhile, prediction of the soccer performance was predicted by regression model. CFA revealed that sit and reach, vertical jump, VO2max, age, weight, height, sitting height, calf circumference (cc), medial upper arm circumference (muac), maturation, bicep, triceps, subscapular, suprailiac, 5M, 10M, and 20M speed were the most dominant factors. Further index analysis forming Youth Soccer Performance Index (YSPI) resulting by categorizing three groups namely, high, moderate, and low. The regression model for this study was significant set as p < 0.001 and R2 is 0.8222 which explained that the model contributed a total of 82% prediction ability to predict the whole set of the variables. The significant parameters in contributing prediction of YSPI are discussed. As a conclusion, the precision of the prediction models by integrating a multilateral factor reflecting for predicting potential soccer player and hopefully can create a competitive soccer games.

Global sensitivity analysis of a filtration model for submerged anaerobic membrane bioreactors (AnMBR).

PubMed

Robles, A; Ruano, M V; Ribes, J; Seco, A; Ferrer, J

2014-04-01

The results of a global sensitivity analysis of a filtration model for submerged anaerobic MBRs (AnMBRs) are assessed in this paper. This study aimed to (1) identify the less- (or non-) influential factors of the model in order to facilitate model calibration and (2) validate the modelling approach (i.e. to determine the need for each of the proposed factors to be included in the model). The sensitivity analysis was conducted using a revised version of the Morris screening method. The dynamic simulations were conducted using long-term data obtained from an AnMBR plant fitted with industrial-scale hollow-fibre membranes. Of the 14 factors in the model, six were identified as influential, i.e. those calibrated using off-line protocols. A dynamic calibration (based on optimisation algorithms) of these influential factors was conducted. The resulting estimated model factors accurately predicted membrane performance. Copyright © 2014 Elsevier Ltd. All rights reserved.

Vulnerability and Resilience in Women with Arthritis: Test of a Two-Factor Model

ERIC Educational Resources Information Center

Smith, Bruce W.; Zautra, Alex J.

2008-01-01

The purpose of this study was to test a 2-factor model of affective health in women with rheumatoid arthritis (RA; n = 82) or osteoarthritis (OA; n = 88). Positive and negative social interactions and affect were assessed for 11 consecutive weeks. For each participant, Vulnerability and Resilience factors were created from factor analyses of…

Landslide susceptibility modeling applying machine learning methods: A case study from Longju in the Three Gorges Reservoir area, China

NASA Astrophysics Data System (ADS)

Zhou, Chao; Yin, Kunlong; Cao, Ying; Ahmed, Bayes; Li, Yuanyao; Catani, Filippo; Pourghasemi, Hamid Reza

2018-03-01

Landslide is a common natural hazard and responsible for extensive damage and losses in mountainous areas. In this study, Longju in the Three Gorges Reservoir area in China was taken as a case study for landslide susceptibility assessment in order to develop effective risk prevention and mitigation strategies. To begin, 202 landslides were identified, including 95 colluvial landslides and 107 rockfalls. Twelve landslide causal factor maps were prepared initially, and the relationship between these factors and each landslide type was analyzed using the information value model. Later, the unimportant factors were selected and eliminated using the information gain ratio technique. The landslide locations were randomly divided into two groups: 70% for training and 30% for verifying. Two machine learning models: the support vector machine (SVM) and artificial neural network (ANN), and a multivariate statistical model: the logistic regression (LR), were applied for landslide susceptibility modeling (LSM) for each type. The LSM index maps, obtained from combining the assessment results of the two landslide types, were classified into five levels. The performance of the LSMs was evaluated using the receiver operating characteristics curve and Friedman test. Results show that the elimination of noise-generating factors and the separated modeling of each landslide type have significantly increased the prediction accuracy. The machine learning models outperformed the multivariate statistical model and SVM model was found ideal for the case study area.

The Role of Readiness Factors in E-Learning Outcomes: An Empirical Study

ERIC Educational Resources Information Center

Keramati, Abbas; Afshari-Mofrad, Masoud; Kamrani, Ali

2011-01-01

Although many researchers have studied different factors which affect E-Learning outcomes, there is little research on assessment of the intervening role of readiness factors in E-Learning outcomes. This study proposes a conceptual model to determine the role of readiness factors in the relationship between E-Learning factors and E-Learning…

Latent Variable Modeling of Brain Gray Matter Volume and Psychopathy in Incarcerated Offenders

PubMed Central

Baskin-Sommers, Arielle R.; Neumann, Craig S.; Cope, Lora M.; Kiehl, Kent A.

2016-01-01

Advanced statistical modeling has become a prominent feature in psychological science and can be a useful approach for representing the neural architecture linked to psychopathology. Psychopathy, a disorder characterized by dysfunction in interpersonal-affective and impulsive-antisocial domains, is associated with widespread neural abnormalities. Several imaging studies suggest that underlying structural deficits in paralimbic regions are associated with psychopathy. While these studies are useful, they make assumptions about the organization of the brain and its relevance to individuals displaying psychopathic features. Capitalizing on statistical modeling, the present study (N=254) used latent variable methods to examine the structure of gray matter volume in male offenders, and assessed the latent relations between psychopathy and gray matter factors reflecting paralimbic and non-paralimbic regions. Results revealed good fit for a four-factor gray matter paralimbic model and these first-order factors were accounted for by a super-ordinate paralimbic ‘system’ factor. Moreover, a super-ordinate psychopathy factor significantly predicted the paralimbic, but not the non-paralimbic factor. The latent variable paralimbic model, specifically linked with psychopathy, goes beyond understanding of single brain regions within the system and provides evidence for psychopathy-related gray matter volume reductions in the paralimbic system as a whole. PMID:27269123

Depressive symptoms following natural disaster in Korea: psychometric properties of the Center for Epidemiologic Studies Depression Scale.

PubMed

Cho, Sungkun; Cho, Yongrae

2017-11-28

Depressive symptoms have been recognized as one of the most frequent complaints among natural disaster survivors. One of the most frequently used self-report measures of depressive symptoms is the Center for Epidemiologic Studies Depression Scale (CES-D). To our knowledge, no study has yet examined the factor structure, reliability, and validity of the CES-D in a sample of natural disaster survivors. Thus, the present study investigated the factor structure, reliability, and validity of a Korean language version of the CES-D (KCES-D) for natural disaster survivors. We utilized two archived datasets collected independently for two different periods in 2008 in the same region of Korea (n = 192 for sample 1; n = 148 for sample 2). Participants were survivors of torrential rains in the mid-eastern region of the Korean peninsula. For analysis, Samples 1 and 2 were merged (N = 340). Confirmatory factor analysis was performed to evaluate the one-factor model, the four-factor model, and the bi-factor models, as well as the second-order factor model. Composite reliability was computed to examine the internal consistency of the KCES-D total and subscale scores. Finally, Pearson's r was computed to examine the relationship between the KCES-D and the trauma-related measures. The four-factor model provided the best fit to the data among the alternatives. The KCES-D showed adequate internal consistency, except for the 'interpersonal difficulties' subscale. Also regarding concurrent validity, weak to moderate positive correlations were observed between the KCES-D and the trauma-related measures. The results support the four-factor model and indicate that the KCES-D has adequate psychometric properties for natural disaster survivors. If these findings are further confirmed, the KCES-D can be used as a useful, rapid, and inexpensive screening tool for assessing depressive symptoms in natural disaster survivors.

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

PubMed

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

2015-01-01

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

The utility of the bifactor model in understanding unique components of anxiety sensitivity in a South Korean sample.

PubMed

Ebesutani, Chad; Kim, Mirihae; Park, Hee-Hoon

2016-08-01

The present study was the first to examine the applicability of the bifactor structure underlying the Anxiety Sensitivity Index-3 (ASI-3) in an East Asian (South Korean) sample and to determine which factors in the bifactor model were significantly associated with anxiety, depression, and negative affect. Using a sample of 289 South Korean university students, we compared (a) the original 3-factor AS model, (b) a 3-group bifactor AS model, and (c) a 2-group bifactor AS model (with only the physical and social concern group factors present). Results revealed that the 2-group bifactor AS model fit the ASI-3 data the best. Relatedly, although all ASI-3 items loaded on the general AS factor, the Cognitive Concern group factor was not defined in the bifactor model and may therefore need to be omitted in order to accurately model AS when conducting factor analysis and structural equation modeling (SEM) in cross cultural contexts. SEM results also revealed that the general AS factor was the only factor from the 2-group bifactor model that significantly predicted anxiety, depression, and negative affect. Implications and importance of this new bifactor structure of Anxiety Sensitivity in East Asian samples are discussed. Copyright © 2016 Elsevier B.V. All rights reserved.

The classification of body dysmorphic disorder symptoms in male and female adolescents.

PubMed

Schneider, Sophie C; Baillie, Andrew J; Mond, Jonathan; Turner, Cynthia M; Hudson, Jennifer L

2018-01-01

Body dysmorphic disorder (BDD) was categorised in DSM-5 within the newly created 'obsessive-compulsive and related disorders' chapter, however this classification remains subject to debate. Confirmatory factor analysis was used to test competing models of the co-occurrence of symptoms of BDD, obsessive-compulsive disorder, unipolar depression, anxiety, and eating disorders in a community sample of adolescents, and to explore potential sex differences in these models. Self-report questionnaires assessing disorder symptoms were completed by 3149 Australian adolescents. The fit of correlated factor models was calculated separately in males and females, and measurement invariance testing compared parameters of the best-fitting model between males and females. All theoretical models of the classification of BDD had poor fit to the data. Good fit was found for a novel model where BDD symptoms formed a distinct latent factor, correlated with affective disorder and eating disorder latent factors. Metric non-invariance was found between males and females, and the majority of factor loadings differed between males and females. Correlations between some latent factors also differed by sex. Only cross-sectional data were collected, and the study did not assess a broad range of DSM-5 defined eating disorder symptoms or other disorders in the DSM-5 obsessive-compulsive and related disorders chapter. This study is the first to statistically evaluate competing models of BDD classification. The findings highlight the unique features of BDD and its associations with affective and eating disorders. Future studies examining the classification of BDD should consider developmental and sex differences in their models. Copyright © 2017. Published by Elsevier B.V.

Financial Distress Prediction Using Discrete-time Hazard Model and Rating Transition Matrix Approach

NASA Astrophysics Data System (ADS)

Tsai, Bi-Huei; Chang, Chih-Huei

2009-08-01

Previous studies used constant cut-off indicator to distinguish distressed firms from non-distressed ones in the one-stage prediction models. However, distressed cut-off indicator must shift according to economic prosperity, rather than remains fixed all the time. This study focuses on Taiwanese listed firms and develops financial distress prediction models based upon the two-stage method. First, this study employs the firm-specific financial ratio and market factors to measure the probability of financial distress based on the discrete-time hazard models. Second, this paper further focuses on macroeconomic factors and applies rating transition matrix approach to determine the distressed cut-off indicator. The prediction models are developed by using the training sample from 1987 to 2004, and their levels of accuracy are compared with the test sample from 2005 to 2007. As for the one-stage prediction model, the model in incorporation with macroeconomic factors does not perform better than that without macroeconomic factors. This suggests that the accuracy is not improved for one-stage models which pool the firm-specific and macroeconomic factors together. In regards to the two stage models, the negative credit cycle index implies the worse economic status during the test period, so the distressed cut-off point is adjusted to increase based on such negative credit cycle index. After the two-stage models employ such adjusted cut-off point to discriminate the distressed firms from non-distressed ones, their error of misclassification becomes lower than that of one-stage ones. The two-stage models presented in this paper have incremental usefulness in predicting financial distress.

Source Apportionment Using Positive Matrix Factorization on Daily Measurements of Inorganic and Organic Speciated PM2.5

PubMed Central

Dutton, Steven J.; Vedal, Sverre; Piedrahita, Ricardo; Milford, Jana B.; Miller, Shelly L.; Hannigan, Michael P.

2012-01-01

Particulate matter less than 2.5 microns in diameter (PM2.5) has been linked with a wide range of adverse health effects. Determination of the sources of PM2.5 most responsible for these health effects could lead to improved understanding of the mechanisms of such effects and more targeted regulation. This has provided the impetus for the Denver Aerosol Sources and Health (DASH) study, a multi-year source apportionment and health effects study relying on detailed inorganic and organic PM2.5 speciation measurements. In this study, PM2.5 source apportionment is performed by coupling positive matrix factorization (PMF) with daily speciated PM2.5 measurements including inorganic ions, elemental carbon (EC) and organic carbon (OC), and organic molecular markers. A qualitative comparison is made between two models, PMF2 and ME2, commonly used for solving the PMF problem. Many previous studies have incorporated chemical mass balance (CMB) for organic molecular marker source apportionment on limited data sets, but the DASH data set is large enough to use multivariate factor analysis techniques such as PMF. Sensitivity of the PMF2 and ME2 models to the selection of speciated PM2.5 components and model input parameters was investigated in depth. A combination of diagnostics was used to select an optimum, 7-factor model using one complete year of daily data with pointwise measurement uncertainties. The factors included 1) a wintertime/methoxyphenol factor, 2) an EC/sterane factor, 3) a nitrate/polycyclic aromatic hydrocarbon (PAH) factor, 4) a summertime/selective aliphatic factor, 5) an n-alkane factor, 6) a middle oxygenated PAH/alkanoic acid factor and 7) an inorganic ion factor. These seven factors were qualitatively linked with known PM2.5 emission sources with varying degrees of confidence. Mass apportionment using the 7-factor model revealed the contribution of each factor to the mass of OC, EC, nitrate and sulfate. On an annual basis, the majority of OC and EC mass was associated with the summertime/selective aliphatic factor and the EC/sterane factor, respectively, while nitrate and sulfate mass were both dominated by the inorganic ion factor. This apportionment was found to vary substantially by season. Several of the factors identified in this study agree well with similar assessments conducted in St. Louis, MO and Pittsburgh, PA using PMF and organic molecular markers. PMID:22768005

Statistical analysis of whole-body absorption depending on anatomical human characteristics at a frequency of 2.1 GHz.

PubMed

Habachi, A El; Conil, E; Hadjem, A; Vazquez, E; Wong, M F; Gati, A; Fleury, G; Wiart, J

2010-04-07

In this paper, we propose identification of the morphological factors that may impact the whole-body averaged specific absorption rate (WBSAR). This study is conducted for the case of exposure to a front plane wave at a 2100 MHz frequency carrier. This study is based on the development of different regression models for estimating the WBSAR as a function of morphological factors. For this purpose, a database of 12 anatomical human models (phantoms) has been considered. Also, 18 supplementary phantoms obtained using the morphing technique were generated to build the required relation. This paper presents three models based on external morphological factors such as the body surface area, the body mass index or the body mass. These models show good results in estimating the WBSAR (<10%) for families obtained by the morphing technique, but these are still less accurate (30%) when applied to different original phantoms. This study stresses the importance of the internal morphological factors such as muscle and fat proportions in characterization of the WBSAR. The regression models are then improved using internal morphological factors with an estimation error of approximately 10% on the WBSAR. Finally, this study is suitable for establishing the statistical distribution of the WBSAR for a given population characterized by its morphology.

Statistical analysis of whole-body absorption depending on anatomical human characteristics at a frequency of 2.1 GHz

NASA Astrophysics Data System (ADS)

El Habachi, A.; Conil, E.; Hadjem, A.; Vazquez, E.; Wong, M. F.; Gati, A.; Fleury, G.; Wiart, J.

2010-04-01

In this paper, we propose identification of the morphological factors that may impact the whole-body averaged specific absorption rate (WBSAR). This study is conducted for the case of exposure to a front plane wave at a 2100 MHz frequency carrier. This study is based on the development of different regression models for estimating the WBSAR as a function of morphological factors. For this purpose, a database of 12 anatomical human models (phantoms) has been considered. Also, 18 supplementary phantoms obtained using the morphing technique were generated to build the required relation. This paper presents three models based on external morphological factors such as the body surface area, the body mass index or the body mass. These models show good results in estimating the WBSAR (<10%) for families obtained by the morphing technique, but these are still less accurate (30%) when applied to different original phantoms. This study stresses the importance of the internal morphological factors such as muscle and fat proportions in characterization of the WBSAR. The regression models are then improved using internal morphological factors with an estimation error of approximately 10% on the WBSAR. Finally, this study is suitable for establishing the statistical distribution of the WBSAR for a given population characterized by its morphology.

Using Factor Mixture Models to Evaluate the Type A/B Classification of Alcohol Use Disorders in a Heterogeneous Treatment Sample

PubMed Central

Hildebrandt, Tom; Epstein, Elizabeth E.; Sysko, Robyn; Bux, Donald A.

2017-01-01

Background The type A/B classification model for alcohol use disorders (AUDs) has received considerable empirical support. However, few studies examine the underlying latent structure of this subtyping model, which has been challenged as a dichotomization of a single drinking severity dimension. Type B, relative to type A, alcoholics represent those with early age of onset, greater familial risk, and worse outcomes from alcohol use. Method We examined the latent structure of the type A/B model using categorical, dimensional, and factor mixture models in a mixed gender community treatment-seeking sample of adults with an AUD. Results Factor analytic models identified 2-factors (drinking severity/externalizing psychopathology and internalizing psychopathology) underlying the type A/B indicators. A factor mixture model with 2-dimensions and 3-classes emerged as the best overall fitting model. The classes reflected a type A class and two type B classes (B1 and B2) that differed on the respective level of drinking severity/externalizing pathology and internalizing pathology. Type B1 had a greater prevalence of women and more internalizing pathology and B2 had a greater prevalence of men and more drinking severity/externalizing pathology. The 2-factor, 3-class model also exhibited predictive validity by explaining significant variance in 12-month drinking and drug use outcomes. Conclusions The model identified in the current study may provide a basis for examining different sources of heterogeneity in the course and outcome of AUDs. PMID:28247423

High-Dimensional Sparse Factor Modeling: Applications in Gene Expression Genomics

PubMed Central

Carvalho, Carlos M.; Chang, Jeffrey; Lucas, Joseph E.; Nevins, Joseph R.; Wang, Quanli; West, Mike

2010-01-01

We describe studies in molecular profiling and biological pathway analysis that use sparse latent factor and regression models for microarray gene expression data. We discuss breast cancer applications and key aspects of the modeling and computational methodology. Our case studies aim to investigate and characterize heterogeneity of structure related to specific oncogenic pathways, as well as links between aggregate patterns in gene expression profiles and clinical biomarkers. Based on the metaphor of statistically derived “factors” as representing biological “subpathway” structure, we explore the decomposition of fitted sparse factor models into pathway subcomponents and investigate how these components overlay multiple aspects of known biological activity. Our methodology is based on sparsity modeling of multivariate regression, ANOVA, and latent factor models, as well as a class of models that combines all components. Hierarchical sparsity priors address questions of dimension reduction and multiple comparisons, as well as scalability of the methodology. The models include practically relevant non-Gaussian/nonparametric components for latent structure, underlying often quite complex non-Gaussianity in multivariate expression patterns. Model search and fitting are addressed through stochastic simulation and evolutionary stochastic search methods that are exemplified in the oncogenic pathway studies. Supplementary supporting material provides more details of the applications, as well as examples of the use of freely available software tools for implementing the methodology. PMID:21218139

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

PubMed

Gomez, Rapson; Watson, Shaun D

2017-01-01

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

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

PubMed Central

Gomez, Rapson; Watson, Shaun D.

2017-01-01

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

Assessing the latent structure of DSM-5 PTSD among Chinese adolescents after the Ya'an earthquake.

PubMed

Zhou, Xiao; Wu, Xinchun; Zhen, Rui

2017-08-01

To examine the underlying substructure of DSM-5 PTSD in an adolescent sample, this study used a confirmatory factor analysis alternative model approach to assess 813 adolescents two and a half years after the Ya'an earthquake. Participants completed the PTSD Checklist for DSM-5, the Center for Epidemiologic Studies Depression Scale for Children, and the Screen for Child Anxiety Related Emotional Disorders. The results found that the seven-factor hybrid PTSD model entailing intrusion, avoidance, negative affect, anhedonia, externalizing behaviors, anxious arousal, and dysphoric arousal had significantly better fit indices than other alternative models. Depression and anxiety displayed high correlations with the seven-factor model. The findings suggested that the seven-factor model was more applicable to adolescents following the earthquake, and may carry important implications for further clinical practice and research on posttraumatic stress symptomatology. Copyright © 2017 Elsevier Ireland Ltd. All rights reserved.

Dental Students' Perceptions of Risk Factors for Musculoskeletal Disorders: Adapting the Job Factors Questionnaire for Dentistry.

PubMed

Presoto, Cristina D; Wajngarten, Danielle; Domingos, Patrícia A S; Campos, Juliana A D B; Garcia, Patrícia P N S

2018-01-01

The aims of this study were to adapt the Job Factors Questionnaire to the field of dentistry, evaluate its psychometric properties, evaluate dental students' perceptions of work/study risk factors for musculoskeletal disorders, and determine the influence of gender and academic level on those perceptions. All 580 students enrolled in two Brazilian dental schools in 2015 were invited to participate in the study. A three-factor structure (Repetitiveness, Work Posture, and External Factors) was tested through confirmatory factor analysis. Convergent validity was estimated using the average variance extracted (AVE), discriminant validity was based on the correlational analysis of the factors, and reliability was assessed. A causal model was created using structural equation modeling to evaluate the influence of gender and academic level on students' perceptions. A total of 480 students completed the questionnaire for an 83% response rate. The responding students' average age was 21.6 years (SD=2.98), and 74.8% were women. Higher scores were observed on the Work Posture factor items. The refined model presented proper fit to the studied sample. Convergent validity was compromised only for External Factors (AVE=0.47), and discriminant validity was compromised for Work Posture and External Factors (r 2 =0.69). Reliability was adequate. Academic level did not have a significant impact on the factors, but the women students exhibited greater perception. Overall, the adaptation resulted in a useful instrument for assessing perceptions of risk factors for musculoskeletal disorders. Gender was found to significantly influence all three factors, with women showing greater perception of the risk factors.

Mind the Gap! A Multilevel Analysis of Factors Related to Variation in Published Cost-Effectiveness Estimates within and between Countries.

PubMed

Boehler, Christian E H; Lord, Joanne

2016-01-01

Published cost-effectiveness estimates can vary considerably, both within and between countries. Despite extensive discussion, little is known empirically about factors relating to these variations. To use multilevel statistical modeling to integrate cost-effectiveness estimates from published economic evaluations to investigate potential causes of variation. Cost-effectiveness studies of statins for cardiovascular disease prevention were identified by systematic review. Estimates of incremental costs and effects were extracted from reported base case, sensitivity, and subgroup analyses, with estimates grouped in studies and in countries. Three bivariate models were developed: a cross-classified model to accommodate data from multinational studies, a hierarchical model with multinational data allocated to a single category at country level, and a hierarchical model excluding multinational data. Covariates at different levels were drawn from a long list of factors suggested in the literature. We found 67 studies reporting 2094 cost-effectiveness estimates relating to 23 countries (6 studies reporting for more than 1 country). Data and study-level covariates included patient characteristics, intervention and comparator cost, and some study methods (e.g., discount rates and time horizon). After adjusting for these factors, the proportion of variation attributable to countries was negligible in the cross-classified model but moderate in the hierarchical models (14%-19% of total variance). Country-level variables that improved the fit of the hierarchical models included measures of income and health care finance, health care resources, and population risks. Our analysis suggested that variability in published cost-effectiveness estimates is related more to differences in study methods than to differences in national context. Multinational studies were associated with much lower country-level variation than single-country studies. These findings are for a single clinical question and may be atypical. © The Author(s) 2015.

An ontology for factors affecting tuberculosis treatment adherence behavior in sub-Saharan Africa.

PubMed

Ogundele, Olukunle Ayodeji; Moodley, Deshendran; Pillay, Anban W; Seebregts, Christopher J

2016-01-01

Adherence behavior is a complex phenomenon influenced by diverse personal, cultural, and socioeconomic factors that may vary between communities in different regions. Understanding the factors that influence adherence behavior is essential in predicting which individuals and communities are at risk of nonadherence. This is necessary for supporting resource allocation and intervention planning in disease control programs. Currently, there is no known concrete and unambiguous computational representation of factors that influence tuberculosis (TB) treatment adherence behavior that is useful for prediction. This study developed a computer-based conceptual model for capturing and structuring knowledge about the factors that influence TB treatment adherence behavior in sub-Saharan Africa (SSA). An extensive review of existing categorization systems in the literature was used to develop a conceptual model that captured scientific knowledge about TB adherence behavior in SSA. The model was formalized as an ontology using the web ontology language. The ontology was then evaluated for its comprehensiveness and applicability in building predictive models. The outcome of the study is a novel ontology-based approach for curating and structuring scientific knowledge of adherence behavior in patients with TB in SSA. The ontology takes an evidence-based approach by explicitly linking factors to published clinical studies. Factors are structured around five dimensions: factor type, type of effect, regional variation, cross-dependencies between factors, and treatment phase. The ontology is flexible and extendable and provides new insights into the nature of and interrelationship between factors that influence TB adherence.

An ontology for factors affecting tuberculosis treatment adherence behavior in sub-Saharan Africa

PubMed Central

Ogundele, Olukunle Ayodeji; Moodley, Deshendran; Pillay, Anban W; Seebregts, Christopher J

2016-01-01

Purpose Adherence behavior is a complex phenomenon influenced by diverse personal, cultural, and socioeconomic factors that may vary between communities in different regions. Understanding the factors that influence adherence behavior is essential in predicting which individuals and communities are at risk of nonadherence. This is necessary for supporting resource allocation and intervention planning in disease control programs. Currently, there is no known concrete and unambiguous computational representation of factors that influence tuberculosis (TB) treatment adherence behavior that is useful for prediction. This study developed a computer-based conceptual model for capturing and structuring knowledge about the factors that influence TB treatment adherence behavior in sub-Saharan Africa (SSA). Methods An extensive review of existing categorization systems in the literature was used to develop a conceptual model that captured scientific knowledge about TB adherence behavior in SSA. The model was formalized as an ontology using the web ontology language. The ontology was then evaluated for its comprehensiveness and applicability in building predictive models. Conclusion The outcome of the study is a novel ontology-based approach for curating and structuring scientific knowledge of adherence behavior in patients with TB in SSA. The ontology takes an evidence-based approach by explicitly linking factors to published clinical studies. Factors are structured around five dimensions: factor type, type of effect, regional variation, cross-dependencies between factors, and treatment phase. The ontology is flexible and extendable and provides new insights into the nature of and interrelationship between factors that influence TB adherence. PMID:27175067

The Factors That Influence Bureaucracy and Professionalism in Schools: A Grounded Theory Study

ERIC Educational Resources Information Center

Koybasi, Fatma; Ugurlu, Celal Teyyar

2017-01-01

The aim of this study is to identify the factors that influence the interaction between bureaucracy and professionalism in schools and to develop a model of bureaucracy-professionalism interaction. This is a qualitative study carried out in grounded theory model. The study group consisted of 10 male and 10 female teachers who were working in Sivas…

Patient- and cohort-specific dose and risk estimation for abdominopelvic CT: a study based on 100 patients

NASA Astrophysics Data System (ADS)

Tian, Xiaoyu; Li, Xiang; Segars, W. Paul; Frush, Donald P.; Samei, Ehsan

2012-03-01

The purpose of this work was twofold: (a) to estimate patient- and cohort-specific radiation dose and cancer risk index for abdominopelvic computer tomography (CT) scans; (b) to evaluate the effects of patient anatomical characteristics (size, age, and gender) and CT scanner model on dose and risk conversion coefficients. The study included 100 patient models (42 pediatric models, 58 adult models) and multi-detector array CT scanners from two commercial manufacturers (LightSpeed VCT, GE Healthcare; SOMATOM Definition Flash, Siemens Healthcare). A previously-validated Monte Carlo program was used to simulate organ dose for each patient model and each scanner, from which DLP-normalized-effective dose (k factor) and DLP-normalized-risk index values (q factor) were derived. The k factor showed exponential decrease with increasing patient size. For a given gender, q factor showed exponential decrease with both increasing patient size and patient age. The discrepancies in k and q factors across scanners were on average 8% and 15%, respectively. This study demonstrates the feasibility of estimating patient-specific organ dose and cohort-specific effective dose and risk index in abdominopelvic CT requiring only the knowledge of patient size, gender, and age.

An Early Model for Value and Sustainability in Health Information Exchanges: Qualitative Study

PubMed Central

2018-01-01

Background The primary value relative to health information exchange has been seen in terms of cost savings relative to laboratory and radiology testing, emergency department expenditures, and admissions. However, models are needed to statistically quantify value and sustainability and better understand the dependent and mediating factors that contribute to value and sustainability. Objective The purpose of this study was to provide a basis for early model development for health information exchange value and sustainability. Methods A qualitative study was conducted with 21 interviews of eHealth Exchange participants across 10 organizations. Using a grounded theory approach and 3.0 as a relative frequency threshold, 5 main categories and 16 subcategories emerged. Results This study identifies 3 core current perceived value factors and 5 potential perceived value factors—how interviewees predict health information exchanges may evolve as there are more participants. These value factors were used as the foundation for early model development for sustainability of health information exchange. Conclusions Using the value factors from the interviews, the study provides the basis for early model development for health information exchange value and sustainability. This basis includes factors from the research: fostering consumer engagement; establishing a provider directory; quantifying use, cost, and clinical outcomes; ensuring data integrity through patient matching; and increasing awareness, usefulness, interoperability, and sustainability of eHealth Exchange. PMID:29712623

How do various maize crop models vary in their responses to climate change factors?

USDA-ARS?s Scientific Manuscript database

Potential consequences of climate change on crop production can be studied using mechanistic crop simulation models. While a broad variety of maize simulation models exist, it is not known whether different models give similar grain yield responses to changes in climatic factors, or whether they agr...

The HEXACO and Five-Factor Models of Personality in Relation to RIASEC Vocational Interests

ERIC Educational Resources Information Center

McKay, Derek A.; Tokar, David M.

2012-01-01

The current study extended the empirical research on the overlap of vocational interests and personality by (a) testing hypothesized relations between RIASEC interests and the personality dimensions of the HEXACO model, and (b) exploring the HEXACO personality model's predictive advantage over the five-factor model (FFM) in capturing RIASEC…

Evaluating Individual Students' Perceptions of Instructional Quality: An Investigation of their Factor Structure, Measurement Invariance, and Relations to Educational Outcomes.

PubMed

Scherer, Ronny; Nilsen, Trude; Jansen, Malte

2016-01-01

Students' perceptions of instructional quality are among the most important criteria for evaluating teaching effectiveness. The present study evaluates different latent variable modeling approaches (confirmatory factor analysis, exploratory structural equation modeling, and bifactor modeling), which are used to describe these individual perceptions with respect to their factor structure, measurement invariance, and the relations to selected educational outcomes (achievement, self-concept, and motivation in mathematics). On the basis of the Programme for International Student Assessment (PISA) 2012 large-scale data sets of Australia, Canada, and the USA (N = 26,746 students), we find support for the distinction between three factors of individual students' perceptions and full measurement invariance across countries for all modeling approaches. In this regard, bifactor exploratory structural equation modeling outperformed alternative approaches with respect to model fit. Our findings reveal significant relations to the educational outcomes. This study synthesizes different modeling approaches of individual students' perceptions of instructional quality and provides insights into the nature of these perceptions from an individual differences perspective. Implications for the measurement and modeling of individually perceived instructional quality are discussed.

Does information available at admission for delivery improve prediction of vaginal birth after cesarean?

PubMed Central

Grobman, William A.; Lai, Yinglei; Landon, Mark B.; Spong, Catherine Y.; Leveno, Kenneth J.; Rouse, Dwight J.; Varner, Michael W.; Moawad, Atef H.; Simhan, Hyagriv N.; Harper, Margaret; Wapner, Ronald J.; Sorokin, Yoram; Miodovnik, Menachem; Carpenter, Marshall; O'sullivan, Mary J.; Sibai, Baha M.; Langer, Oded; Thorp, John M.; Ramin, Susan M.; Mercer, Brian M.

2010-01-01

Objective To construct a predictive model for vaginal birth after cesarean (VBAC) that combines factors that can be ascertained only as the pregnancy progresses with those known at initiation of prenatal care. Study design Using multivariable modeling, we constructed a predictive model for VBAC that included patient factors known at the initial prenatal visit as well as those that only became evident as the pregancy progressed to the admission for delivery. Results 9616 women were analyzed. The regression equation for VBAC success included multiple factors that could not be known at the first prenatal visit. The area under the curve for this model was significantly greater (P < .001) than that of a model that included only factors available at the first prenatal visit. Conclusion A prediction model for VBAC success that incorporates factors that can be ascertained only as the pregnancy progresses adds to the predictive accuracy of a model that uses only factors available at a first prenatal visit. PMID:19813165

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

PubMed Central

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

2017-01-01

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

Modeling of Individual and Organizational Factors Affecting Traumatic Occupational Injuries Based on the Structural Equation Modeling: A Case Study in Large Construction Industries

PubMed Central

Mohammadfam, Iraj; Soltanzadeh, Ahmad; Moghimbeigi, Abbas; Akbarzadeh, Mehdi

2016-01-01

Background Individual and organizational factors are the factors influencing traumatic occupational injuries. Objectives The aim of the present study was the short path analysis of the severity of occupational injuries based on individual and organizational factors. Materials and Methods The present cross-sectional analytical study was implemented on traumatic occupational injuries within a ten-year timeframe in 13 large Iranian construction industries. Modeling and data analysis were done using the structural equation modeling (SEM) approach and the IBM SPSS AMOS statistical software version 22.0, respectively. Results The mean age and working experience of the injured workers were 28.03 ± 5.33 and 4.53 ± 3.82 years, respectively. The portions of construction and installation activities of traumatic occupational injuries were 64.4% and 18.1%, respectively. The SEM findings showed that the individual, organizational and accident type factors significantly were considered as effective factors on occupational injuries’ severity (P < 0.05). Conclusions Path analysis of occupational injuries based on the SEM reveals that individual and organizational factors and their indicator variables are very influential on the severity of traumatic occupational injuries. So, these should be considered to reduce occupational accidents’ severity in large construction industries. PMID:27800465

Examining the Factor Structure and Hierarchical Nature of the Quality of Life Construct

ERIC Educational Resources Information Center

Wang, Mian; Schalock, Robert L.; Verdugo, Miguel A.; Jenaro, Christina

2010-01-01

There is considerable debate in the area of individual quality of life research regarding the factor structure and hierarchical nature of the quality of life construct. Our purpose in this study was to test via structural equation modeling an a priori quality of life model consisting of eight first-order factors and one second-order factor. Data…

Family Risk and Resiliency Factors, Substance Use, and the Drug Resistance Process in Adolescence.

ERIC Educational Resources Information Center

Moon, Dreama G.; Jackson, Kristina M.; Hecht, Michael L.

2000-01-01

Study tests two models to compare the effects of risk and resiliency across gender and ethnicity. Results support the model in which risk and resiliency are discrete sets of factors and demonstrate that overall resiliency factors play a larger role than risk factors in substance use and drug resistance processes. Gender proved to be an important…

Measuring the effects of socioeconomic factors on mental health among migrants in urban China: a multiple indicators multiple causes model.

PubMed

Guan, Ming

2017-01-01

Since 1978, rural-urban migrants mainly contribute Chinese urbanization. The purpose of this paper is to examine the effects of socioeconomic factors on mental health of them. Their mental health was measured by 12-item general health questionnaire (GHQ-12). The study sample comprised 5925 migrants obtained from the 2009 rural-to-urban migrants survey (RUMiC). The relationships among the instruments were assessed by the correlation analysis. The one-factor (overall items), two-factor (positive vs. negative items), and model conducted by principal component analysis were tested in the confirmatory factor analysis (CFA). On the basis of three CFA models, the three multiple indicators multiple causes (MIMIC) models with age, gender, marriage, ethnicity, and employment were constructed to investigate the concurrent associations between socioeconomic factors and GHQ-12. Of the sample, only 1.94% were of ethnic origin and mean age was 31.63 (SD = ±10.43) years. The one-factor, two-factor, and three-factor structure (i.e. semi-positive/negative/independent usefulness) had good model fits in the CFA analysis and gave order (i.e. 2 factor>3 factor>1 factor), which suggests that the three models can be used to assess psychological symptoms of migrants in urban China. All MIMIC models had acceptable fit and gave order (i.e. one-dimensional model>two-dimensional model>three-dimensional model). There were weak associations of socioeconomic factors with mental health among migrants in urban China. Policy discussion suggested that improvement of socioeconomic status of rural-urban migrants and mental health systems in urban China should be highlighted and strengthened.

Examining the integrity of measurement of cognitive abilities in the prediction of achievement: Comparisons and contrasts across variables from higher-order and bifactor models.

PubMed

Benson, Nicholas F; Kranzler, John H; Floyd, Randy G

2016-10-01

Prior research examining cognitive ability and academic achievement relations have been based on different theoretical models, have employed both latent variables as well as observed variables, and have used a variety of analytic methods. Not surprisingly, results have been inconsistent across studies. The aims of this study were to (a) examine how relations between psychometric g, Cattell-Horn-Carroll (CHC) broad abilities, and academic achievement differ across higher-order and bifactor models; (b) examine how well various types of observed scores corresponded with latent variables; and (c) compare two types of observed scores (i.e., refined and non-refined factor scores) as predictors of academic achievement. Results suggest that cognitive-achievement relations vary across theoretical models and that both types of factor scores tend to correspond well with the models on which they are based. However, orthogonal refined factor scores (derived from a bifactor model) have the advantage of controlling for multicollinearity arising from the measurement of psychometric g across all measures of cognitive abilities. Results indicate that the refined factor scores provide more precise representations of their targeted constructs than non-refined factor scores and maintain close correspondence with the cognitive-achievement relations observed for latent variables. Thus, we argue that orthogonal refined factor scores provide more accurate representations of the relations between CHC broad abilities and achievement outcomes than non-refined scores do. Further, the use of refined factor scores addresses calls for the application of scores based on latent variable models. Copyright © 2016 Society for the Study of School Psychology. Published by Elsevier Ltd. All rights reserved.

Testing a cognitive model to predict posttraumatic stress disorder following childbirth.

PubMed

King, Lydia; McKenzie-McHarg, Kirstie; Horsch, Antje

2017-01-14

One third of women describes their childbirth as traumatic and between 0.8 and 6.9% goes on to develop posttraumatic stress disorder (PTSD). The cognitive model of PTSD has been shown to be applicable to a range of trauma samples. However, childbirth is qualitatively different to other trauma types and special consideration needs to be taken when applying it to this population. Previous studies have investigated some cognitive variables in isolation but no study has so far looked at all the key processes described in the cognitive model. This study therefore aimed to investigate whether theoretically-derived variables of the cognitive model explain unique variance in postnatal PTSD symptoms when key demographic, obstetric and clinical risk factors are controlled for. One-hundred and fifty-seven women who were between 1 and 12 months post-partum (M = 6.5 months) completed validated questionnaires assessing PTSD and depressive symptoms, childbirth experience, postnatal social support, trauma memory, peritraumatic processing, negative appraisals, dysfunctional cognitive and behavioural strategies and obstetric as well as demographic risk factors in an online survey. A PTSD screening questionnaire suggested that 5.7% of the sample might fulfil diagnostic criteria for PTSD. Overall, risk factors alone predicted 43% of variance in PTSD symptoms and cognitive behavioural factors alone predicted 72.7%. A final model including both risk factors and cognitive behavioural factors explained 73.7% of the variance in PTSD symptoms, 37.1% of which was unique variance predicted by cognitive factors. All variables derived from Ehlers and Clark's cognitive model significantly explained variance in PTSD symptoms following childbirth, even when clinical, demographic and obstetric were controlled for. Our findings suggest that the CBT model is applicable and useful as a way of understanding and informing the treatment of PTSD following childbirth.

Factor Structure of the Penn State Worry Questionnaire: Examination of a Method Factor

ERIC Educational Resources Information Center

Hazlett-Stevens, Holly; Ullman, Jodie B.; Craske, Michelle G.

2004-01-01

The Penn State Worry Questionnaire (PSWQ) was originally designed as a unifactorial measure of pathological trait worry. However, recent studies supported a two-factor solution with positively worded items loading on the first factor and reverse-scored items loading on a second factor. The current study compared this two-factor model to a negative…

Individual and Situational Factors Associated with Social Barriers for Persons with Mobility Impairment

ERIC Educational Resources Information Center

McCaughey, Tiffany

2009-01-01

Decades of research have examined factors involved in complex, and sometimes stressful, interpersonal interactions between individuals with and without disabilities. The present study applies structural equation modeling to test an integrative model of individual and situational factors affecting encounters between able-bodied college students and…

Determinants of Standard Errors of MLEs in Confirmatory Factor Analysis

ERIC Educational Resources Information Center

Yuan, Ke-Hai; Cheng, Ying; Zhang, Wei

2010-01-01

This paper studies changes of standard errors (SE) of the normal-distribution-based maximum likelihood estimates (MLE) for confirmatory factor models as model parameters vary. Using logical analysis, simplified formulas and numerical verification, monotonic relationships between SEs and factor loadings as well as unique variances are found.…

Application of GA-SVM method with parameter optimization for landslide development prediction

NASA Astrophysics Data System (ADS)

Li, X. Z.; Kong, J. M.

2013-10-01

Prediction of landslide development process is always a hot issue in landslide research. So far, many methods for landslide displacement series prediction have been proposed. Support vector machine (SVM) has been proved to be a novel algorithm with good performance. However, the performance strongly depends on the right selection of the parameters (C and γ) of SVM model. In this study, we presented an application of GA-SVM method with parameter optimization in landslide displacement rate prediction. We selected a typical large-scale landslide in some hydro - electrical engineering area of Southwest China as a case. On the basis of analyzing the basic characteristics and monitoring data of the landslide, a single-factor GA-SVM model and a multi-factor GA-SVM model of the landslide were built. Moreover, the models were compared with single-factor and multi-factor SVM models of the landslide. The results show that, the four models have high prediction accuracies, but the accuracies of GA-SVM models are slightly higher than those of SVM models and the accuracies of multi-factor models are slightly higher than those of single-factor models for the landslide prediction. The accuracy of the multi-factor GA-SVM models is the highest, with the smallest RSME of 0.0009 and the biggest RI of 0.9992.

The Synergistic Effect of Affective Factors on Student Learning Outcomes

ERIC Educational Resources Information Center

Jack, Brady Michael; Lin, Huann-shyang; Yore, Larry D.

2014-01-01

This study investigates how affective and self-related factors impact participation in science learning and environmental awareness and responsibility. Using PISA 2006 datasets from Taiwan and Canada having similar level of science competency, the model for this study verifies and expands an earlier model by examining the relationships among…

Non-Linear Modeling of Growth Prerequisites in a Finnish Polytechnic Institution of Higher Education

ERIC Educational Resources Information Center

Nokelainen, Petri; Ruohotie, Pekka

2009-01-01

Purpose: This study aims to examine the factors of growth-oriented atmosphere in a Finnish polytechnic institution of higher education with categorical exploratory factor analysis, multidimensional scaling and Bayesian unsupervised model-based visualization. Design/methodology/approach: This study was designed to examine employee perceptions of…

Adolescent Problem Behavior in Navi Mumbai: An Exploratory Study of Psychosocial Risk and Protection

ERIC Educational Resources Information Center

Solomon, R. J.

2007-01-01

Background: A conceptual framework about protective factors (models protection, controls protection, support protection) and risk factors (models risk, opportunity risk, vulnerability risk) was employed to articulate the content of five psychosocial contexts of adolescent life--individual, family, peers, school, and neighborhood--in a study of…

Teacher Behavior and Student Outcomes: Results of a European Study

ERIC Educational Resources Information Center

Panayiotou, Anastasia; Kyriakides, Leonidas; Creemers, Bert P. M.; McMahon, Léan; Vanlaar, Gudrun; Pfeifer, Michael; Rekalidou, Galini; Bren, Matevž

2014-01-01

This study investigates the extent to which the factors included in the dynamic model of educational effectiveness are associated with student achievement gains in six different European countries. At classroom level, the dynamic model refers to eight factors relating to teacher behavior in the classroom: orientation, structuring, questioning,…

Psychometric Properties of the Serbian Version of the Maslach Burnout Inventory-Human Services Survey: A Validation Study among Anesthesiologists from Belgrade Teaching Hospitals

PubMed Central

Matejić, Bojana; Milenović, Miodrag; Kisić Tepavčević, Darija; Simić, Dušica; Pekmezović, Tatjana; Worley, Jody A.

2015-01-01

We report findings from a validation study of the translated and culturally adapted Serbian version of Maslach Burnout Inventory-Human Services Survey (MBI-HSS), for a sample of anesthesiologists working in the tertiary healthcare. The results showed the sufficient overall reliability (Cronbach's α = 0.72) of the scores (items 1–22). The results of Bartlett's test of sphericity (χ 2 = 1983.75, df = 231, p < 0.001) and Kaiser-Meyer-Olkin measure of sampling adequacy (0.866) provided solid justification for factor analysis. In order to increase sensitivity of this questionnaire, we performed unfitted factor analysis model (eigenvalue greater than 1) which enabled us to extract the most suitable factor structure for our study instrument. The exploratory factor analysis model revealed five factors with eigenvalues greater than 1.0, explaining 62.0% of cumulative variance. Velicer's MAP test has supported five-factor model with the smallest average squared correlation of 0,184. This study indicated that Serbian version of the MBI-HSS is a reliable and valid instrument to measure burnout among a population of anesthesiologists. Results confirmed strong psychometric characteristics of the study instrument, with recommendations for interpretation of two new factors that may be unique to the Serbian version of the MBI-HSS. PMID:26090517

Psychometric Properties of the Serbian Version of the Maslach Burnout Inventory-Human Services Survey: A Validation Study among Anesthesiologists from Belgrade Teaching Hospitals.

PubMed

Matejić, Bojana; Milenović, Miodrag; Kisić Tepavčević, Darija; Simić, Dušica; Pekmezović, Tatjana; Worley, Jody A

2015-01-01

We report findings from a validation study of the translated and culturally adapted Serbian version of Maslach Burnout Inventory-Human Services Survey (MBI-HSS), for a sample of anesthesiologists working in the tertiary healthcare. The results showed the sufficient overall reliability (Cronbach's α = 0.72) of the scores (items 1-22). The results of Bartlett's test of sphericity (χ(2) = 1983.75, df = 231, p < 0.001) and Kaiser-Meyer-Olkin measure of sampling adequacy (0.866) provided solid justification for factor analysis. In order to increase sensitivity of this questionnaire, we performed unfitted factor analysis model (eigenvalue greater than 1) which enabled us to extract the most suitable factor structure for our study instrument. The exploratory factor analysis model revealed five factors with eigenvalues greater than 1.0, explaining 62.0% of cumulative variance. Velicer's MAP test has supported five-factor model with the smallest average squared correlation of 0,184. This study indicated that Serbian version of the MBI-HSS is a reliable and valid instrument to measure burnout among a population of anesthesiologists. Results confirmed strong psychometric characteristics of the study instrument, with recommendations for interpretation of two new factors that may be unique to the Serbian version of the MBI-HSS.

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

PubMed

Zahnd, Whitney E; McLafferty, Sara L

2017-11-01

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

Application of zero-inflated poisson mixed models in prognostic factors of hepatitis C.

PubMed

Akbarzadeh Baghban, Alireza; Pourhoseingholi, Asma; Zayeri, Farid; Jafari, Ali Akbar; Alavian, Seyed Moayed

2013-01-01

In recent years, hepatitis C virus (HCV) infection represents a major public health problem. Evaluation of risk factors is one of the solutions which help protect people from the infection. This study aims to employ zero-inflated Poisson mixed models to evaluate prognostic factors of hepatitis C. The data was collected from a longitudinal study during 2005-2010. First, mixed Poisson regression (PR) model was fitted to the data. Then, a mixed zero-inflated Poisson model was fitted with compound Poisson random effects. For evaluating the performance of the proposed mixed model, standard errors of estimators were compared. The results obtained from mixed PR showed that genotype 3 and treatment protocol were statistically significant. Results of zero-inflated Poisson mixed model showed that age, sex, genotypes 2 and 3, the treatment protocol, and having risk factors had significant effects on viral load of HCV patients. Of these two models, the estimators of zero-inflated Poisson mixed model had the minimum standard errors. The results showed that a mixed zero-inflated Poisson model was the almost best fit. The proposed model can capture serial dependence, additional overdispersion, and excess zeros in the longitudinal count data.

Epistemic belief structures within introductory astronomy

NASA Astrophysics Data System (ADS)

Johnson, Keith; Willoughby, Shannon D.

2018-06-01

The reliability and validity of inventories should be verified in multiple ways. Although the epistemological beliefs about the physical science survey (EBAPS) has been deemed to be reliable and valid by the authors, the axes or factor structure proposed by the authors has not been independently checked. Using data from a study sample we discussed in previous publications, we performed exploratory factor analysis on 1,258 post-test EBAPS surveys. The students in the sample were from an introductory Astronomy course at a mid-sized western university. Inspection suggested the use of either a three-factor model or a five-factor model. Each of the factors is interpreted and discussed, and the factors are compared to the axes proposed by the authors of the EBAPS. We find that the five-factor model extrapolated from our data partially overlaps with the model put forth by the authors of the EBAPS, and that many of the questions did not load onto any factors.

Factorial invariance of posttraumatic stress disorder symptoms across three veteran samples.

PubMed

McDonald, Scott D; Beckham, Jean C; Morey, Rajendra; Marx, Christine; Tupler, Larry A; Calhoun, Patrick S

2008-06-01

Research generally supports a 4-factor structure of posttraumatic stress disorder (PTSD) symptoms. However, few studies have established factor invariance by comparing multiple groups. This study examined PTSD symptom structure using the Davidson Trauma Scale (DTS) across three veteran samples: treatment-seeking Vietnam-era veterans, treatment-seeking post-Vietnam-era veterans, and Operation Enduring Freedom/Operation Iraqi Freedom (OEF/OIF) veteran research participants. Confirmatory factor analyses of DTS items demonstrated that a 4-factor structural model of the DTS (reexperiencing, avoidance, numbing, and hyperarousal) was superior to five alternate models, including the conventional 3-factor model proposed by the Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition (DSM-IV; American Psychiatric Association, 1994). Results supported factor invariance across the three veteran cohorts, suggesting that cross-group comparisons are interpretable. Implications and applications for DSM-IV nosology and the validity of symptom measures are discussed.

The HEXACO Honesty-Humility, Agreeableness, and Emotionality factors: a review of research and theory.

PubMed

Ashton, Michael C; Lee, Kibeom; de Vries, Reinout E

2014-05-01

We review research and theory on the HEXACO personality dimensions of Honesty-Humility (H), Agreeableness (A), and Emotionality (E), with particular attention to the following topics: (1) the origins of the HEXACO model in lexical studies of personality structure, and the content of the H, A, and E factors in those studies; (2) the operationalization of the H, A, and E factors in the HEXACO Personality Inventory-Revised; (3) the construct validity of self-reports on scales measuring the H factor; (4) the theoretical distinction between H and A; (5) similarity and assumed similarity between social partners in personality, with a focus on H and A; (6) the extent to which H (and A and E) variance is represented in instruments assessing the "Five-Factor Model" of personality; and (7) the relative validity of scales assessing the HEXACO and Five-Factor Model dimensions in predicting criteria conceptually relevant to H, A, and E.

The contributions of human factors on human error in Malaysia aviation maintenance industries

NASA Astrophysics Data System (ADS)

Padil, H.; Said, M. N.; Azizan, A.

2018-05-01

Aviation maintenance is a multitasking activity in which individuals perform varied tasks under constant pressure to meet deadlines as well as challenging work conditions. These situational characteristics combined with human factors can lead to various types of human related errors. The primary objective of this research is to develop a structural relationship model that incorporates human factors, organizational factors, and their impact on human errors in aviation maintenance. Towards that end, a questionnaire was developed which was administered to Malaysian aviation maintenance professionals. Structural Equation Modelling (SEM) approach was used in this study utilizing AMOS software. Results showed that there were a significant relationship of human factors on human errors and were tested in the model. Human factors had a partial effect on organizational factors while organizational factors had a direct and positive impact on human errors. It was also revealed that organizational factors contributed to human errors when coupled with human factors construct. This study has contributed to the advancement of knowledge on human factors effecting safety and has provided guidelines for improving human factors performance relating to aviation maintenance activities and could be used as a reference for improving safety performance in the Malaysian aviation maintenance companies.

Factorial invariance of pediatric patient self-reported fatigue across age and gender: a multigroup confirmatory factor analysis approach utilizing the PedsQL™ Multidimensional Fatigue Scale.

PubMed

Varni, James W; Beaujean, A Alexander; Limbers, Christine A

2013-11-01

In order to compare multidimensional fatigue research findings across age and gender subpopulations, it is important to demonstrate measurement invariance, that is, that the items from an instrument have equivalent meaning across the groups studied. This study examined the factorial invariance of the 18-item PedsQL™ Multidimensional Fatigue Scale items across age and gender and tested a bifactor model. Multigroup confirmatory factor analysis (MG-CFA) was performed specifying a three-factor model across three age groups (5-7, 8-12, and 13-18 years) and gender. MG-CFA models were proposed in order to compare the factor structure, metric, scalar, and error variance across age groups and gender. The analyses were based on 837 children and adolescents recruited from general pediatric clinics, subspecialty clinics, and hospitals in which children were being seen for well-child checks, mild acute illness, or chronic illness care. A bifactor model of the items with one general factor influencing all the items and three domain-specific factors representing the General, Sleep/Rest, and Cognitive Fatigue domains fit the data better than oblique factor models. Based on the multiple measures of model fit, configural, metric, and scalar invariance were found for almost all items across the age and gender groups, as was invariance in the factor covariances. The PedsQL™ Multidimensional Fatigue Scale demonstrated strict factorial invariance for child and adolescent self-report across gender and strong factorial invariance across age subpopulations. The findings support an equivalent three-factor structure across the age and gender groups studied. Based on these data, it can be concluded that pediatric patients across the groups interpreted the items in a similar manner regardless of their age or gender, supporting the multidimensional factor structure interpretation of the PedsQL™ Multidimensional Fatigue Scale.

Hospital survey on patient safety culture: psychometric analysis on a Scottish sample.

PubMed

Sarac, Cakil; Flin, Rhona; Mearns, Kathryn; Jackson, Jeanette

2011-10-01

To investigate the psychometric properties of the Hospital Survey on Patient Safety Culture on a Scottish NHS data set. The data were collected from 1969 clinical staff (estimated 22% response rate) from one acute hospital from each of seven Scottish Health boards. Using a split-half validation technique, the data were randomly split; an exploratory factor analysis was conducted on the calibration data set, and confirmatory factor analyses were conducted on the validation data set to investigate and check the original US model fit in a Scottish sample. Following the split-half validation technique, exploratory factor analysis results showed a 10-factor optimal measurement model. The confirmatory factor analyses were then performed to compare the model fit of two competing models (10-factor alternative model vs 12-factor original model). An S-B scaled χ(2) square difference test demonstrated that the original 12-factor model performed significantly better in a Scottish sample. Furthermore, reliability analyses of each component yielded satisfactory results. The mean scores on the climate dimensions in the Scottish sample were comparable with those found in other European countries. This study provided evidence that the original 12-factor structure of the Hospital Survey on Patient Safety Culture scale has been replicated in this Scottish sample. Therefore, no modifications are required to the original 12-factor model, which is suggested for use, since it would allow researchers the possibility of cross-national comparisons.

Improved performance of epidemiologic and genetic risk models for rheumatoid arthritis serologic phenotypes using family history.

PubMed

Sparks, Jeffrey A; Chen, Chia-Yen; Jiang, Xia; Askling, Johan; Hiraki, Linda T; Malspeis, Susan; Klareskog, Lars; Alfredsson, Lars; Costenbader, Karen H; Karlson, Elizabeth W

2015-08-01

To develop and validate rheumatoid arthritis (RA) risk models based on family history, epidemiologic factors and known genetic risk factors. We developed and validated models for RA based on known RA risk factors, among women in two cohorts: the Nurses' Health Study (NHS, 381 RA cases and 410 controls) and the Epidemiological Investigation of RA (EIRA, 1244 RA cases and 971 controls). Model discrimination was evaluated using the area under the receiver operating characteristic curve (AUC) in logistic regression models for the study population and for those with positive family history. The joint effect of family history with genetics, smoking and body mass index (BMI) was evaluated using logistic regression models to estimate ORs for RA. The complete model including family history, epidemiologic risk factors and genetics demonstrated AUCs of 0.74 for seropositive RA in NHS and 0.77 for anti-citrullinated protein antibody (ACPA)-positive RA in EIRA. Among women with positive family history, discrimination was excellent for complete models for seropositive RA in NHS (AUC 0.82) and ACPA-positive RA in EIRA (AUC 0.83). Positive family history, high genetic susceptibility, smoking and increased BMI had an OR of 21.73 for ACPA-positive RA. We developed models for seropositive and seronegative RA phenotypes based on family history, epidemiological and genetic factors. Among those with positive family history, models using epidemiologic and genetic factors were highly discriminatory for seropositive and seronegative RA. Assessing epidemiological and genetic factors among those with positive family history may identify individuals suitable for RA prevention strategies. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.

Latent structures of female sexual functioning.

PubMed

Carvalho, Joana; Vieira, Armando Luís; Nobre, Pedro

2012-08-01

For the last three decades, male and female sexual responses have been conceptualized as similar, based on separated and sequential phases as proposed by the models of Masters and Johnson (1966) and Kaplan (1979) model. However, there is a growing debate around the need to conceptualize female sexual response and the classification of sexual dysfunction in women, in view of the upcoming editions of the DSM and ICD. The aim of this study was to test, using structural equation modeling, five conceptual, alternative models of female sexual function, using a sample of women with sexual difficulties and a sample of women without sexual problems. A total of 1993 Portuguese women participated in the study and completed a modified version of the Female Sexual Function Index. Findings suggested a four-factor solution as the model that best fit the data regarding women presenting sexual difficulties: (1) desire/arousal; (2) lubrication; (3) orgasm; (4) pain/vaginismus. In relation to sexually healthy women, the best model was a five-factor solution comprising of (1) desire; (2) arousal; (3) lubrication; (4) orgasm; and (5) pain/vaginismus. Discriminant validity between factors was supported, suggesting that these dimensions measure distinct phenomena. Model fit to the data significantly decreased in both samples, as models began to successively consider greater levels of overlap among phases of sexual function, towards a single-factor solution. By suggesting the overlap between pain and vaginismus, results partially support the new classification that is currently being discussed regarding DSM-5. Additionally, results on the relationship between sexual desire and arousal were inconclusive as sexually healthy women were better characterized by a five-factor model that considered the structural independence among these factors, whereas women with sexual difficulties better fit with a four-factor model merging sexual desire and subjective sexual arousal.

[Confirmatory factor analysis of the short French version of the Center for Epidemiological Studies of Depression Scale (CES-D10) in adolescents].

PubMed

Cartierre, N; Coulon, N; Demerval, R

2011-09-01

Screening depressivity among adolescents is a key public health priority. In order to measure the severity of depressive symptomatology, a four-dimensional 20 items scale called "Center for Epidemiological Studies-Depression Scale" (CES-D) was developed. A shorter 10-item version was developed and validated (Andresen et al.). For this brief version, several authors supported a two-factor structure - Negative and Positive affect - but the relationship between the two reversed-worded items of the Positive affect factor could be better accounted for by correlated errors. The aim of this study is triple: firstly to test a French version of the CES-D10 among adolescents; secondly to test the relevance of a one-dimensional structure by considering error correlation for Positive affect items; finally to examine the extent to which this structural model is invariant across gender. The sample was composed of 269 French middle school adolescents (139 girls and 130 boys, mean age: 13.8, SD=0.65). Confirmatory Factorial Analyses (CFA) using the LISREL 8.52 were conducted in order to assess the adjustment to the data of three factor models: a one-factor model, a two-factor model (Positive and Negative affect) and a one-factor model with specification of correlated errors between the two reverse-worded items. Then, multigroup analysis was conducted to test the scale invariance for girls and boys. Internal consistency of the CES-D10 was satisfying for the adolescent sample (α=0.75). The best fitting model is the one-factor model with correlated errors between the two items of the previous Positive affect factor (χ(2)/dl=2.50; GFI=0.939; CFI=0.894; RMSEA=0.076). This model presented a better statistical fit to the data than the one-factor model without error correlation: χ(2)(diff) (1)=22.14, p<0.001. Then, the one-factor model with correlated errors was analyzed across separate samples of girls and boys. The model explains the data somewhat better for boys than for girls. The model's overall χ(2)(68) without equality constraints from the multigroup analysis was 107.98. The χ(2)(89) statistic for the model with equality-constrained factor loadings was 121.31. The change in the overall Chi(2) is not statistically significant. This result implies that the model is, therefore, invariant across gender. The mean scores were higher for girls than boys: 9.69 versus 7.19; t(267)=4.13, p<0.001. To conclude, and waiting for further research using the French version of the CES-D10 for adolescents, it appears that this short scale is generally acceptable and can be a useful tool for both research and practice. The scale invariance across gender has been demonstrated but the invariance across age must be tested too. Copyright © 2011 L’Encéphale, Paris. Published by Elsevier Masson SAS. All rights reserved.

Bem Sex Role Inventory Validation in the International Mobility in Aging Study.

PubMed

Ahmed, Tamer; Vafaei, Afshin; Belanger, Emmanuelle; Phillips, Susan P; Zunzunegui, Maria-Victoria

2016-09-01

This study investigated the measurement structure of the Bem Sex Role Inventory (BSRI) with different factor analysis methods. Most previous studies on validity applied exploratory factor analysis (EFA) to examine the BSRI. We aimed to assess the psychometric properties and construct validity of the 12-item short-form BSRI in a sample administered to 1,995 older adults from wave 1 of the International Mobility in Aging Study (IMIAS). We used Cronbach's alpha to assess internal consistency reliability and confirmatory factor analysis (CFA) to assess psychometric properties. EFA revealed a three-factor model, further confirmed by CFA and compared with the original two-factor structure model. Results revealed that a two-factor solution (instrumentality-expressiveness) has satisfactory construct validity and superior fit to data compared to the three-factor solution. The two-factor solution confirms expected gender differences in older adults. The 12-item BSRI provides a brief, psychometrically sound, and reliable instrument in international samples of older adults.

An alternative method for centrifugal compressor loading factor modelling

NASA Astrophysics Data System (ADS)

Galerkin, Y.; Drozdov, A.; Rekstin, A.; Soldatova, K.

2017-08-01

The loading factor at design point is calculated by one or other empirical formula in classical design methods. Performance modelling as a whole is out of consideration. Test data of compressor stages demonstrates that loading factor versus flow coefficient at the impeller exit has a linear character independent of compressibility. Known Universal Modelling Method exploits this fact. Two points define the function - loading factor at design point and at zero flow rate. The proper formulae include empirical coefficients. A good modelling result is possible if the choice of coefficients is based on experience and close analogs. Earlier Y. Galerkin and K. Soldatova had proposed to define loading factor performance by the angle of its inclination to the ordinate axis and by the loading factor at zero flow rate. Simple and definite equations with four geometry parameters were proposed for loading factor performance calculated for inviscid flow. The authors of this publication have studied the test performance of thirteen stages of different types. The equations are proposed with universal empirical coefficients. The calculation error lies in the range of plus to minus 1,5%. The alternative model of a loading factor performance modelling is included in new versions of the Universal Modelling Method.

Factor structure of overall autobiographical memory usage: the directive, self and social functions revisited.

PubMed

Rasmussen, Anne S; Habermas, Tilmann

2011-08-01

According to theory, autobiographical memory serves three broad functions of overall usage: directive, self, and social. However, there is evidence to suggest that the tripartite model may be better conceptualised in terms of a four-factor model with two social functions. In the present study we examined the two models in Danish and German samples, using the Thinking About Life Experiences Questionnaire (TALE; Bluck, Alea, Habermas, & Rubin, 2005), which measures the overall usage of the three functions generalised across concrete memories. Confirmatory factor analysis supported the four-factor model and rejected the theoretical three-factor model in both samples. The results are discussed in relation to cultural differences in overall autobiographical memory usage as well as sharing versus non-sharing aspects of social remembering.

A cross-validation study of the TGMD-2: The case of an adolescent population.

PubMed

Issartel, Johann; McGrane, Bronagh; Fletcher, Richard; O'Brien, Wesley; Powell, Danielle; Belton, Sarahjane

2017-05-01

This study proposes an extension of a widely used test evaluating fundamental movement skills proficiency to an adolescent population, with a specific emphasis on validity and reliability for this older age group. Cross-sectional observational study. A total of 844 participants (n=456 male, 12.03±0.49) participated in this study. The 12 fundamental movement skills of the TGMD-2 were assessed. Inter-rater reliability was examined to ensure a minimum of 95% consistency between coders. Confirmatory factor analysis was undertaken with a one-factor model (all 12 skills) and two-factor model (6 locomotor skills and 6 object-control skills) as proposed by Ulrich et al. (2000). The model fit was examined using χ 2 , TLI, CFI and RMSEA. Test-retest reliability was carried out with a subsample of 35 participants. The test-retest reliability reached Intraclass Correlation Coefficient of 0.78 (locomotor), 0.76 (object related) and 0.91 (gross motor skill proficiency). The confirmatory factor analysis did not display a good fit for either the one-factor or two-factor model due to a really low contribution of several skills. A reduction in the number of skills to just seven (run, gallop, hop, horizontal jump, bounce, kick and roll) revealed an overall good fit by TLI, CFI and RMSEA measures. The proposed new model offers the possibility of longitudinal studies to track the maturation of fundamental movement skills across the child and adolescent spectrum, while also giving researchers a valid assessment to tool to evaluate adolescent fundamental movement skills proficiency level. Copyright © 2016 Sports Medicine Australia. All rights reserved.

Dimensional structure of DSM-5 posttraumatic stress disorder symptoms: results from the National Health and Resilience in Veterans Study.

PubMed

Tsai, Jack; Harpaz-Rotem, Ilan; Armour, Cherie; Southwick, Steven M; Krystal, John H; Pietrzak, Robert H

2015-05-01

To evaluate the prevalence of DSM-5 posttraumatic stress disorder (PTSD) and factor structure of PTSD symptomatology in a nationally representative sample of US veterans and examine how PTSD symptom clusters are related to depression, anxiety, suicidal ideation, hostility, physical and mental health-related functioning, and quality of life. Data were analyzed from the National Health and Resilience in Veterans Study, a nationally representative survey of 1,484 US veterans conducted from September through October 2013. Confirmatory factor analyses were conducted to evaluate the factor structure of PTSD symptoms, and structural equation models were constructed to examine the association between PTSD symptom clusters and external correlates. 12.0% of veterans screened positive for lifetime PTSD and 5.2% for past-month PTSD. A 5-factor dysphoric arousal model and a newly proposed 6-factor model both fit the data significantly better than the 4-factor model of DSM-5. The 6-factor model fit the data best in the full sample, as well as in subsamples of female veterans and veterans with lifetime PTSD. The emotional numbing symptom cluster was more strongly related to depression (P < .001) and worse mental health-related functioning (P < .001) than other symptom clusters, while the externalizing behavior symptom cluster was more strongly related to hostility (P < .001). A total of 5.2% of US veterans screened positive for past-month DSM-5 PTSD. A 6-factor model of DSM-5 PTSD symptoms, which builds on extant models and includes a sixth externalizing behavior factor, provides the best dimensional representation of DSM-5 PTSD symptom clusters and demonstrates validity in assessing health outcomes of interest in this population. © Copyright 2015 Physicians Postgraduate Press, Inc.

Construct validity of the Beck Hopelessness Scale (BHS) among university students: A multitrait-multimethod approach.

PubMed

Boduszek, Daniel; Dhingra, Katie

2016-10-01

There is considerable debate about the underlying factor structure of the Beck Hopelessness Scale (BHS) in the literature. An established view is that it reflects a unitary or bidimensional construct in nonclinical samples. There are, however, reasons to reconsider this conceptualization. Based on previous factor analytic findings from both clinical and nonclinical studies, the aim of the present study was to compare 16 competing models of the BHS in a large university student sample (N = 1, 733). Sixteen distinct factor models were specified and tested using conventional confirmatory factor analytic techniques, along with confirmatory bifactor modeling. A 3-factor solution with 2 method effects (i.e., a multitrait-multimethod model) provided the best fit to the data. The reliability of this conceptualization was supported by McDonald's coefficient omega and the differential relationships exhibited between the 3 hopelessness factors ("feelings about the future," "loss of motivation," and "future expectations") and measures of goal disengagement, brooding rumination, suicide ideation, and suicide attempt history. The results provide statistical support for a 3-trait and 2-method factor model, and hence the 3 dimensions of hopelessness theorized by Beck. The theoretical and methodological implications of these findings are discussed. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

Development of the Internet addiction scale based on the Internet Gaming Disorder criteria suggested in DSM-5.

PubMed

Cho, Hyun; Kwon, Min; Choi, Ji-Hye; Lee, Sang-Kyu; Choi, Jung Seok; Choi, Sam-Wook; Kim, Dai-Jin

2014-09-01

This study was conducted to develop and validate a standardized self-diagnostic Internet addiction (IA) scale based on the diagnosis criteria for Internet Gaming Disorder (IGD) in the Diagnostic and Statistical Manual of Mental Disorder, 5th edition (DSM-5). Items based on the IGD diagnosis criteria were developed using items of the previous Internet addiction scales. Data were collected from a community sample. The data were divided into two sets, and confirmatory factor analysis (CFA) was performed repeatedly. The model was modified after discussion with professionals based on the first CFA results, after which the second CFA was performed. The internal consistency reliability was generally good. The items that showed significantly low correlation values based on the item-total correlation of each factor were excluded. After the first CFA was performed, some factors and items were excluded. Seven factors and 26 items were prepared for the final model. The second CFA results showed good general factor loading, Squared Multiple Correlation (SMC) and model fit. The model fit of the final model was good, but some factors were very highly correlated. It is recommended that some of the factors be refined through further studies. Copyright © 2014. Published by Elsevier Ltd.

Cross-validation of an employee safety climate model in Malaysia.

PubMed

Bahari, Siti Fatimah; Clarke, Sharon

2013-06-01

Whilst substantial research has investigated the nature of safety climate, and its importance as a leading indicator of organisational safety, much of this research has been conducted with Western industrial samples. The current study focuses on the cross-validation of a safety climate model in the non-Western industrial context of Malaysian manufacturing. The first-order factorial validity of Cheyne et al.'s (1998) [Cheyne, A., Cox, S., Oliver, A., Tomas, J.M., 1998. Modelling safety climate in the prediction of levels of safety activity. Work and Stress, 12(3), 255-271] model was tested, using confirmatory factor analysis, in a Malaysian sample. Results showed that the model fit indices were below accepted levels, indicating that the original Cheyne et al. (1998) safety climate model was not supported. An alternative three-factor model was developed using exploratory factor analysis. Although these findings are not consistent with previously reported cross-validation studies, we argue that previous studies have focused on validation across Western samples, and that the current study demonstrates the need to take account of cultural factors in the development of safety climate models intended for use in non-Western contexts. The results have important implications for the transferability of existing safety climate models across cultures (for example, in global organisations) and highlight the need for future research to examine cross-cultural issues in relation to safety climate. Copyright © 2013 National Safety Council and Elsevier Ltd. All rights reserved.

Reducing weapon-carrying among urban American Indian young people.

PubMed

Bearinger, Linda H; Pettingell, Sandra L; Resnick, Michael D; Potthoff, Sandra J

2010-07-01

To examine the likelihood of weapon-carrying among urban American Indian young people, given the presence of salient risk and protective factors. The study used data from a confidential, self-report Urban Indian Youth Health Survey with 200 forced-choice items examining risk and protective factors and social, contextual, and demographic information. Between 1995 and 1998, 569 American Indian youths, aged 9-15 years, completed surveys administered in public schools and an after-school program. Using logistic regression, probability profiles compared the likelihood of weapon-carrying, given the combinations of salient risk and protective factors. In the final models, weapon-carrying was associated significantly with one risk factor (substance use) and two protective factors (school connectedness, perceiving peers as having prosocial behavior attitudes/norms). With one risk factor and two protective factors, in various combinations in the models, the likelihood of weapon carrying ranged from 4% (with two protective factors and no risk factor in the model) to 80% of youth (with the risk factor and no protective factors in the model). Even in the presence of the risk factor, the two protective factors decreased the likelihood of weapon-carrying to 25%. This analysis highlights the importance of protective factors in comprehensive assessments and interventions for vulnerable youth. In that the risk factor and two protective factors significantly related to weapon-carrying are amenable to intervention at both individual and population-focused levels, study findings offer a guide for prioritizing strategies for decreasing weapon-carrying among urban American Indian young people. Copyright (c) 2010 Society for Adolescent Health and Medicine. Published by Elsevier Inc. All rights reserved.

Factor structure of DSM-5 PTSD symptoms in trauma-exposed adolescents: Examining stability across time.

PubMed

Wang, Li; Cao, Xing; Cao, Chengqi; Fang, Ruojiao; Yang, Haibo; Elhai, Jon D

2017-12-01

This study investigated the latent structure of DSM-5 PTSD symptoms using two-wave longitudinal data collected from a sample of adolescents exposed to an explosion accident. Two waves of surveys were conducted approximately 3 and 8 months after the accident, respectively. A total of 836 students completed the baseline survey, and 762 students completed the follow-up survey. The results of confirmatory factor analyses(CFA) indicated that a seven-factor hybrid model composed of intrusion, avoidance, negative affect, anhedonia, externalizing behaviors, anxious arousal and dysphoric arousal factors yielded significantly better data fit at both waves than the other models including the DSM-5 four-factor model, the six-factor anhedonia and externalizing behaviors models. Furthermore, the results of CFA invariance tests supported the longitudinal invariance of the model. Implications and limitations in terms of these results are discussed. Copyright © 2017 Elsevier Ltd. All rights reserved.

Validity of the Eating Attitude Test among Exercisers.

PubMed

Lane, Helen J; Lane, Andrew M; Matheson, Hilary

2004-12-01

Theory testing and construct measurement are inextricably linked. To date, no published research has looked at the factorial validity of an existing eating attitude inventory for use with exercisers. The Eating Attitude Test (EAT) is a 26-item measure that yields a single index of disordered eating attitudes. The original factor analysis showed three interrelated factors: Dieting behavior (13-items), oral control (7-items), and bulimia nervosa-food preoccupation (6-items). The primary purpose of the study was to examine the factorial validity of the EAT among a sample of exercisers. The second purpose was to investigate relationships between eating attitudes scores and selected psychological constructs. In stage one, 598 regular exercisers completed the EAT. Confirmatory factor analysis (CFA) was used to test the single-factor, a three-factor model, and a four-factor model, which distinguished bulimia from food pre-occupation. CFA of the single-factor model (RCFI = 0.66, RMSEA = 0.10), the three-factor-model (RCFI = 0.74; RMSEA = 0.09) showed poor model fit. There was marginal fit for the 4-factor model (RCFI = 0.91, RMSEA = 0.06). Results indicated five-items showed poor factor loadings. After these 5-items were discarded, the three models were re-analyzed. CFA results indicated that the single-factor model (RCFI = 0.76, RMSEA = 0.10) and three-factor model (RCFI = 0.82, RMSEA = 0.08) showed poor fit. CFA results for the four-factor model showed acceptable fit indices (RCFI = 0.98, RMSEA = 0.06). Stage two explored relationships between EAT scores, mood, self-esteem, and motivational indices toward exercise in terms of self-determination, enjoyment and competence. Correlation results indicated that depressed mood scores positively correlated with bulimia and dieting scores. Further, dieting was inversely related with self-determination toward exercising. Collectively, findings suggest that a 21-item four-factor model shows promising validity coefficients among exercise participants, and that future research is needed to investigate eating attitudes among samples of exercisers. Key PointsValidity of psychometric measures should be thoroughly investigated. Researchers should not assume that a scale validation on one sample will show the same validity coefficients in a different population.The Eating Attitude Test is a commonly used scale. The present study shows a revised 21-item scale was suitable for exercisers.Researchers using the Eating Attitude Test should use subscales of Dieting, Oral control, Food pre-occupation, and Bulimia.Future research should involve qualitative techniques and interview exercise participants to explore the nature of eating attitudes.

Confirmatory factorial analysis of the children´s attraction to physical activity scale (capa).

PubMed

Seabra, A C; Maia, J A; Parker, M; Seabra, A; Brustad, R; Fonseca, A M

2015-03-27

Attraction to physical activity (PA) is an important contributor to children´s intrinsic motivation to engage in games, and sports. Previous studies have supported the utility of the children´s attraction to PA scale (CAPA) (Brustad, 1996) but the validity of this measure for use in Portugal has not been established. The purpose of this study was to cross-validate the shorter version of the CAPA scale in the Portuguese cultural context. A sample of 342 children (8--10 years of age) was used. Confirmatory factor analyses using EQS software ( version 6.1) tested t hree competing measurement models: a single--factor model, a five factor model, and a second order factor model. The single--factor model and the second order model showed a poor fit to the data. It was found that a five-factor model similar to the original one revealed good fit to the data (S--B χ 2 (67) =94.27,p=0.02; NNFI=0.93; CFI=0.95; RMSEA=0.04; 90%CI=0.02;0.05). The results indicated that the CAPA scale is valid and appropriate for use in the Portuguese cultural context. The availability of a valid scale to evaluate attraction to PA at schools should provide improved opportunities for better assessment and understanding of children´s involvement in PA.

Attitudes toward psychotropic medications among patients with chronic psychiatric disorders and their family caregivers

PubMed Central

Grover, Sandeep; Chakrabarti, Subho; Sharma, Aarti; Tyagi, Shikha

2014-01-01

Aim: To examine attitudes towards psychotropic medications among patients with chronic psychiatric disorders as well as their family caregivers by using factor analysis. Materials and Methods: The study included 200 patients and their family caregivers with chronic psychiatric disorders who are attending the psychiatry outpatient services. A self-designed 18-item self-rated questionnaire was used to evaluate the attitude toward psychotropics and factor analysis was done to study the different models of attitudes. Results: In general both patients and caregivers had positive attitude toward the psychotropic medications and there was no significant difference between the patients and caregivers on the various items of the questionnaire assessing the attitude. Factor analysis of the questionnaire indicated that either two-factor or four-factor models explained the attitude of the patients and caregivers. In the two-factor model there was one positive and one negative attitude factor, whereas the four-factor model comprised of two positive and two negative attitude factors. The four-factor model of attitudes provided a more comprehensive solution to how attitudes might be formed among patients and their family caregivers. Factors one and four in the four-factor solution still reflected positive attitudes, but appeared to portray a risk-benefit approach, in which benefits such as the efficacy of psychotropic medications in treating mental illnesses and preventing relapse, and medications being better than other options were being contrasted with the risks of side effects and permanent damage or harm. Conclusion: Attitudes of patients with chronic psychiatric disorders and their caregivers toward psychotropic medications appear to be shaped by factors such as perceived efficacy or benefit from medicines, the necessity for taking treatment and concerns such as side effects, harm or expense. PMID:25288840

Spatial variability of the effect of air pollution on term birth weight: evaluating influential factors using Bayesian hierarchical models.

PubMed

Li, Lianfa; Laurent, Olivier; Wu, Jun

2016-02-05

Epidemiological studies suggest that air pollution is adversely associated with pregnancy outcomes. Such associations may be modified by spatially-varying factors including socio-demographic characteristics, land-use patterns and unaccounted exposures. Yet, few studies have systematically investigated the impact of these factors on spatial variability of the air pollution's effects. This study aimed to examine spatial variability of the effects of air pollution on term birth weight across Census tracts and the influence of tract-level factors on such variability. We obtained over 900,000 birth records from 2001 to 2008 in Los Angeles County, California, USA. Air pollution exposure was modeled at individual level for nitrogen dioxide (NO2) and nitrogen oxides (NOx) using spatiotemporal models. Two-stage Bayesian hierarchical non-linear models were developed to (1) quantify the associations between air pollution exposure and term birth weight within each tract; and (2) examine the socio-demographic, land-use, and exposure-related factors contributing to the between-tract variability of the associations between air pollution and term birth weight. Higher air pollution exposure was associated with lower term birth weight (average posterior effects: -14.7 (95 % CI: -19.8, -9.7) g per 10 ppb increment in NO2 and -6.9 (95 % CI: -12.9, -0.9) g per 10 ppb increment in NOx). The variation of the association across Census tracts was significantly influenced by the tract-level socio-demographic, exposure-related and land-use factors. Our models captured the complex non-linear relationship between these factors and the associations between air pollution and term birth weight: we observed the thresholds from which the influence of the tract-level factors was markedly exacerbated or attenuated. Exacerbating factors might reflect additional exposure to environmental insults or lower socio-economic status with higher vulnerability, whereas attenuating factors might indicate reduced exposure or higher socioeconomic status with lower vulnerability. Our Bayesian models effectively combined a priori knowledge with training data to infer the posterior association of air pollution with term birth weight and to evaluate the influence of the tract-level factors on spatial variability of such association. This study contributes new findings about non-linear influences of socio-demographic factors, land-use patterns, and unaccounted exposures on spatial variability of the effects of air pollution.

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

ERIC Educational Resources Information Center

Finch, Holmes

2010-01-01

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

Comparison of emission factors for road traffic from a tunnel study (Gubrist tunnel, Switzerland) and from emission modeling

NASA Astrophysics Data System (ADS)

John, Christian; Friedrich, Rainer; Staehelin, Johannes; Schläpfer, Kurt; Stahel, Werner A.

The emission factors of NO x, VOC and CO of a road tunnel study performed in September 1993 in the Gubrist tunnel, close to Zürich (Switzerland) are compared with results of emission calculations based on recent results of dynamometric test measurements. The emission calculations are carried out with a traffic emission model taking into account the detailed composition of the vehicle fleet in the tunnel, the average speed and the gradient of the road and the special aerodynamics in a tunnel. With the exception of NO x emission factors for heavy duty vehicles no evidence for a discrepancy between the results of the tunnel study and the emission modeling was found. The measured emission factors of individual hydrocarbons of light duty vehicles were in good agreement with the expectations for most components.

The role of Patient Health Engagement Model (PHE-model) in affecting patient activation and medication adherence: A structural equation model

PubMed Central

Graffigna, Guendalina; Bonanomi, Andrea

2017-01-01

Background Increasing bodies of scientific research today examines the factors and interventions affecting patients’ ability to self-manage and adhere to treatment. Patient activation is considered the most reliable indicator of patients’ ability to manage health autonomously. Only a few studies have tried to assess the role of psychosocial factors in promoting patient activation. A more systematic modeling of the psychosocial factors explaining the variance of patient activation is needed. Objective To test the hypothesized effect of patient activation on medication adherence; to test the the hypothesized effects of positive emotions and of the quality of the patient/doctor relationship on patient activation; and to test the hypothesized mediating effect of Patient Health Engagement (PHE-model) in this pathway. Material and methods This cross-sectional study involved 352 Italian-speaking adult chronic patients. The survey included measures of i) patient activation (Patient Activation Measure 13 –short form); ii) Patient Health Engagement model (Patient Health Engagement Scale); iii) patient adherence (4 item-Morinsky Medication Adherence Scale); iv) the quality of the patients’ emotional feelings (Manikin Self Assessment Scale); v) the quality of the patient/doctor relationship (Health Care Climate Questionnaire). Structural equation modeling was used to test the hypotheses proposed. Results According to the theoretical model we hypothesized, research results confirmed that patients’ activation significantly affects their reported medication adherence. Moreover, psychosocial factors, such as the patients’ quality of the emotional feelings and the quality of the patient/doctor relationship were demonstrated to be factors affecting the level of patient activation. Finally, the mediation effect of the Patient Health Engagement model was confirmed by the analysis. Conclusions Consistently with the results of previous studies, these findings demonstrate that the Patient Health Engagement Model is a critical factor in enhancing the quality of care. The Patient Health Engagement Model might acts as a mechanism to increase patient activation and adherence. PMID:28654686

The role of Patient Health Engagement Model (PHE-model) in affecting patient activation and medication adherence: A structural equation model.

PubMed

Graffigna, Guendalina; Barello, Serena; Bonanomi, Andrea

2017-01-01

Increasing bodies of scientific research today examines the factors and interventions affecting patients' ability to self-manage and adhere to treatment. Patient activation is considered the most reliable indicator of patients' ability to manage health autonomously. Only a few studies have tried to assess the role of psychosocial factors in promoting patient activation. A more systematic modeling of the psychosocial factors explaining the variance of patient activation is needed. To test the hypothesized effect of patient activation on medication adherence; to test the the hypothesized effects of positive emotions and of the quality of the patient/doctor relationship on patient activation; and to test the hypothesized mediating effect of Patient Health Engagement (PHE-model) in this pathway. This cross-sectional study involved 352 Italian-speaking adult chronic patients. The survey included measures of i) patient activation (Patient Activation Measure 13 -short form); ii) Patient Health Engagement model (Patient Health Engagement Scale); iii) patient adherence (4 item-Morinsky Medication Adherence Scale); iv) the quality of the patients' emotional feelings (Manikin Self Assessment Scale); v) the quality of the patient/doctor relationship (Health Care Climate Questionnaire). Structural equation modeling was used to test the hypotheses proposed. According to the theoretical model we hypothesized, research results confirmed that patients' activation significantly affects their reported medication adherence. Moreover, psychosocial factors, such as the patients' quality of the emotional feelings and the quality of the patient/doctor relationship were demonstrated to be factors affecting the level of patient activation. Finally, the mediation effect of the Patient Health Engagement model was confirmed by the analysis. Consistently with the results of previous studies, these findings demonstrate that the Patient Health Engagement Model is a critical factor in enhancing the quality of care. The Patient Health Engagement Model might acts as a mechanism to increase patient activation and adherence.

Dietary Factors Modulate Helicobacter-Associated Gastric Cancer in Rodent Models

PubMed Central

Fox, James G.; Wang, Timothy C.

2014-01-01

Since its discovery in 1982, the global importance of H. pylori-induced disease, particularly in developing countries, remains high. The use of rodent models particularly mice, and the unanticipated usefulness of the gerbil to study H. pylori pathogenesis have been used extensively to study the interactions of the host, the pathogen and the environmental conditions influencing the outcome of persistent H. pylori infection. Dietary factors in humans are increasingly recognized as being important factors in modulating progression and severity of H. pylori-induced gastric cancer. Studies using rodent models to verify and help explain mechanisms whereby various dietary ingredients impact disease outcome should continue to be extremely productive. PMID:24301796

Brief Report: Bifactor Modeling of General vs. Specific Factors of Religiousness Differentially Predicting Substance Use Risk in Adolescence

PubMed Central

Kim-Spoon, Jungmeen; Longo, Gregory S.; Holmes, Christopher J.

2015-01-01

Religiousness is important to adolescents in the U.S., and the significant link between high religiousness and low substance use is well known. There is a debate between multidimensional and unidimensional perspectives of religiousness (Gorsuch, 1984); yet, no empirical study has tested this hierarchical model of religiousness related to adolescent health outcomes. The current study presents the first attempt to test a bifactor model of religiousness related to substance use among adolescents (N = 220, 45% female). Our bifactor model using structural equation modeling suggested the multidimensional nature of religiousness as well as the presence of a superordinate general religiousness factor directly explaining the covariation among the specific factors including organizational and personal religiousness and religious social support. The general religiousness factor was inversely related to substance use. After accounting for the contribution of the general religiousness factor, high organizational religiousness related to low substance use, whereas personal religiousness and religious support were positively related to substance use. The findings present the first evidence that supports hierarchical structures of adolescent religiousness that contribute differentially to adolescent substance use. PMID:26043168

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

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

Bremer, M.A.

1986-01-01

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

An Empirical Comparison of Competing Factor Structures for the Repeatable Battery for the Assessment of Neuropsychological Status: A Project FRONTIER Study†

PubMed Central

Torrence, Nicole D.; John, Samantha E.; Gavett, Brandon E.; O'Bryant, Sid E.

2016-01-01

The original factor structure of the Repeatable Battery for the Assessment of Neuropsychological Status (RBANS) has received little empirical support, but at least eight alternative factor structures have been identified in the literature. The current study used confirmatory factor analysis to compare the original RBANS model with eight alternatives, which were adjusted to include a general factor. Participant data were obtained from Project FRONTIER, an epidemiological study of rural health, and comprised 341 adults (229 women, 112 men) with mean age of 61.2 years (SD = 12.1) and mean education of 12.4 years (SD = 3.3). A bifactor version of the model proposed by Duff and colleagues provided the best fit to the data (CFI = 0.98; root-mean-squared error of approximation = 0.07), but required further modification to produce appropriate factor loadings. The results support the inclusion of a general factor and provide partial replication of the Duff and colleagues RBANS model. PMID:26429558

Differences in within- and between-person factor structure of positive and negative affect: analysis of two intensive measurement studies using multilevel structural equation modeling.

PubMed

Rush, Jonathan; Hofer, Scott M

2014-06-01

The Positive and Negative Affect Schedule (PANAS) is a widely used measure of emotional experience. The factor structure of the PANAS has been examined predominantly with cross-sectional designs, which fails to disaggregate within-person variation from between-person differences. There is still uncertainty as to the factor structure of positive and negative affect and whether they constitute 2 distinct independent factors. The present study examined the within-person and between-person factor structure of the PANAS in 2 independent samples that reported daily affect over 7 and 14 occasions, respectively. Results from multilevel confirmatory factor analyses revealed that a 2-factor structure at both the within-person and between-person levels, with correlated specific factors for overlapping items, provided good model fit. The best-fitting solution was one where within-person factors of positive and negative affect were inversely correlated, but between-person factors were independent. The structure was further validated through multilevel structural equation modeling examining the effects of cognitive interference, daily stress, physical symptoms, and physical activity on positive and negative affect factors.

Assessing Cognitive and Affective Empathy Through the Interpersonal Reactivity Index: An Argument Against a Two-Factor Model.

PubMed

Chrysikou, Evangelia G; Thompson, W Jake

2016-12-01

One aspect of higher order social cognition is empathy, a psychological construct comprising a cognitive (recognizing emotions) and an affective (responding to emotions) component. The complex nature of empathy complicates the accurate measurement of these components. The most widely used measure of empathy is the Interpersonal Reactivity Index (IRI). However, the factor structure of the IRI as it is predominantly used in the psychological literature differs from Davis's original four-factor model in that it arbitrarily combines the subscales to form two factors: cognitive and affective empathy. This two-factor model of the IRI, although popular, has yet to be examined for psychometric support. In the current study, we examine, for the first time, the validity of this alternative model. A confirmatory factor analysis showed poor model fit for this two-factor structure. Additional analyses offered support for the original four-factor model, as well as a hierarchical model for the scale. In line with previous findings, females scored higher on the IRI than males. Our findings indicate that the IRI, as it is currently used in the literature, does not accurately measure cognitive and affective empathy and highlight the advantages of using the original four-factor structure of the scale for empathy assessments. © The Author(s) 2015.

Factors Affecting Study-Related Burnout among Finnish University Students: Teaching-Learning Environment, Achievement Motivation and the Meaning of Life

ERIC Educational Resources Information Center

Meriläinen, Matti

2014-01-01

This study of a large sample (n = 3035) examined relationships between study-related burnout and components of the teaching-learning environment, achievement motivation and the perceived meaning of life. The overall model, tested with structural equation modelling, revealed that the factor of the teaching-learning environment correlated with both…

Research on investment decisions model of trans-regional transmission network based on the theory of NPV

NASA Astrophysics Data System (ADS)

Zai, Wenjiao; Wang, Bo; Liu, Jichun; Shi, Haobo; Zeng, Pingliang

2018-02-01

The investment decision model of trans-regional transmission network in the context of Global Energy Internet was studied in this paper. The key factors affecting the trans-regional transmission network investment income: the income tax rate, the loan interest rate, the expected return on investment of the investment subject, the per capita GDP and so on were considered in the transmission network investment income model. First, according to the principle of system dynamics, the causality diagram of key factors was constructed. Then, the dynamic model of transmission investment decision was established. A case study of the power transmission network between China and Mongolia, through the simulation of the system dynamic model, the influence of the above key factors on the investment returns was analyzed, and the feasibility and effectiveness of the model was proved.

Behavior of Holographic Ricci Dark Energy in Scalar Gauss-Bonnet Gravity for Different Choices of the Scale Factor

NASA Astrophysics Data System (ADS)

Pasqua, Antonio; Chattopadhyay, Surajit; Khurshudyan, Martiros; Aly, Ayman A.

2014-09-01

In this paper, we studied the cosmological application of the interacting Ricci Dark Energy (RDE) model in the framework of the scalar Gauss-Bonnet modified gravity model. We studied the properties of the reconstructed potential , the Strong Energy Condition (SEC), the Weak Energy Condition (WEC) and the deceleration parameter q for three different models of scale factor, i.e. the emergent, the intermediate and the logamediate one. We obtained that , for the emergent scenario, has a decreasing behavior, while, for the logamediate scenario, the potential start with an increasing behavior then, for later times, it shows a slowly decreasing behavior. Finally, for the intermediate scenario, the potential has an initial increasing behavior, then for a time of t≈1.2, it starts to decrease. We also found that both SEC and WEC are violated for all the three scale factors considered. Finally, studying the plots of q, we derived that an accelerated universe can be achieved for the three models of scale factor considered.

Exploring Factors that Affect Purchase Intention of Athletic Team Merchandise

ERIC Educational Resources Information Center

Lee, Donghun; Trail, Galen T.; Lee, Cindy; Schoenstedt, Linda J.

2013-01-01

The purpose of this study was to test a structural model to determine which psychosocial constructs affected the purchase intention of athletic team merchandise (ATM). Results from the analyses indicated that the twelve-factor ATM model fit the data from collegiate athletic events well, explaining the various impact factors that lead to purchase…

Spatial Dependence and Heterogeneity in Bayesian Factor Analysis: A Cross-National Investigation of Schwartz Values

ERIC Educational Resources Information Center

Stakhovych, Stanislav; Bijmolt, Tammo H. A.; Wedel, Michel

2012-01-01

In this article, we present a Bayesian spatial factor analysis model. We extend previous work on confirmatory factor analysis by including geographically distributed latent variables and accounting for heterogeneity and spatial autocorrelation. The simulation study shows excellent recovery of the model parameters and demonstrates the consequences…

Organizational Learning and Product Design Management: Towards a Theoretical Model.

ERIC Educational Resources Information Center

Chiva-Gomez, Ricardo; Camison-Zornoza, Cesar; Lapiedra-Alcami, Rafael

2003-01-01

Case studies of four Spanish ceramics companies were used to construct a theoretical model of 14 factors essential to organizational learning. One set of factors is related to the conceptual-analytical phase of the product design process and the other to the creative-technical phase. All factors contributed to efficient product design management…

The Value Range of Contact Stiffness Factor between Pile and Soil Based on Penalty Function

NASA Astrophysics Data System (ADS)

Chen, Sandy H. L.; Wu, Xinliu

2018-03-01

The value range of contact stiffness factor based on penalty function is studied when we use finite element software ANSYS to analyze contact problems, take single pile and soil of a certain project for example, the normal contact between pile and soil is analyzed with 2D simplified model in horizontal load. The study shows that when adopting linear elastic model to simulate soil, the maximum contact pressure and penetration approach steady value as the contact stiffness factor increases. The reasonable value range of contact stiffness factor reduces as the underlying element thickness decreases, but the rule reverses when refers to the soil stiffness. If choose DP model to simulate soil, the stiffness factor should be magnified 100 times compares to the elastic model regardless of the soil bears small force and still in elastic deformation stage or into the plastic deformation stage. When the soil bears big force and into plastic deformation stage, the value range of stiffness factor relates to the plastic strain range of the soil, and reduces as the horizontal load increases.

Gender differences in the factor structure of posttraumatic stress disorder symptoms in war-exposed adolescents.

PubMed

Armour, Cherie; Elhai, Jon D; Layne, Christopher M; Shevlin, Mark; Duraković-Belko, Elvira; Djapo, Nermin; Pynoos, Robert S

2011-05-01

DSM-IV's three-factor model of posttraumatic stress disorder (PTSD) is rarely empirically supported, whereas other four-factor models (King et al., 1998; Simms, Watson, & Doebbeling, 2002) have proven to be better representations of PTSD's latent structure. To date, a clear consensus as to which model provides the best representation of PTSD's underlying dimensions has yet to be reached. The current study investigated whether gender is associated with factor structure differences using the King et al. (1998) model of reexperiencing, avoidance, numbing, and hyperarousal PTSD symptoms. Participants were war-exposed Bosnian secondary/high school boys and girls (N=1572) assessed nearly two years after the 1992-1995 Bosnian conflict. Confirmatory factor analytic tests of measurement invariance across PTSD model parameters revealed many significant sex-linked differences. Implications regarding the potential role of gender as a moderator of the King et al. (1998) model's factor structure are discussed. Copyright © 2011 Elsevier Ltd. All rights reserved.

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

PubMed

Clark, D Angus; Bowles, Ryan P

2018-04-23

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

Modeling the factors affecting unsafe behavior in the construction industry from safety supervisors' perspective.

PubMed

Khosravi, Yahya; Asilian-Mahabadi, Hassan; Hajizadeh, Ebrahim; Hassanzadeh-Rangi, Narmin; Bastani, Hamid; Khavanin, Ali; Mortazavi, Seyed Bagher

2014-01-01

There can be little doubt that the construction is the most hazardous industry in the worldwide. This study was designed to modeling the factors affecting unsafe behavior from the perspective of safety supervisors. The qualitative research was conducted to extract a conceptual model. A structural model was then developed based on a questionnaire survey (n=266) by two stage Structural Equation Model (SEM) approach. An excellent confirmed 12-factors structure explained about 62% of variances unsafe behavior in the construction industry. A good fit structural model indicated that safety climate factors were positively correlated with safety individual factors (P<0.001) and workplace safety condition (P<0.001). The workplace safety condition was found to play a strong mediating role in linking the safety climate and construction workers' engagement in safe or unsafe behavior. In order to improve construction safety performance, more focus on the workplace condition is required.

The WRKY transcription factor family in Brachypodium distachyon.

PubMed

Tripathi, Prateek; Rabara, Roel C; Langum, Tanner J; Boken, Ashley K; Rushton, Deena L; Boomsma, Darius D; Rinerson, Charles I; Rabara, Jennifer; Reese, R Neil; Chen, Xianfeng; Rohila, Jai S; Rushton, Paul J

2012-06-22

A complete assembled genome sequence of wheat is not yet available. Therefore, model plant systems for wheat are very valuable. Brachypodium distachyon (Brachypodium) is such a system. The WRKY family of transcription factors is one of the most important families of plant transcriptional regulators with members regulating important agronomic traits. Studies of WRKY transcription factors in Brachypodium and wheat therefore promise to lead to new strategies for wheat improvement. We have identified and manually curated the WRKY transcription factor family from Brachypodium using a pipeline designed to identify all potential WRKY genes. 86 WRKY transcription factors were found, a total higher than all other current databases. We therefore propose that our numbering system (BdWRKY1-BdWRKY86) becomes the standard nomenclature. In the JGI v1.0 assembly of Brachypodium with the MIPS/JGI v1.0 annotation, nine of the transcription factors have no gene model and eleven gene models are probably incorrectly predicted. In total, twenty WRKY transcription factors (23.3%) do not appear to have accurate gene models. To facilitate use of our data, we have produced The Database of Brachypodium distachyon WRKY Transcription Factors. Each WRKY transcription factor has a gene page that includes predicted protein domains from MEME analyses. These conserved protein domains reflect possible input and output domains in signaling. The database also contains a BLAST search function where a large dataset of WRKY transcription factors, published genes, and an extensive set of wheat ESTs can be searched. We also produced a phylogram containing the WRKY transcription factor families from Brachypodium, rice, Arabidopsis, soybean, and Physcomitrella patens, together with published WRKY transcription factors from wheat. This phylogenetic tree provides evidence for orthologues, co-orthologues, and paralogues of Brachypodium WRKY transcription factors. The description of the WRKY transcription factor family in Brachypodium that we report here provides a framework for functional genomics studies in an important model system. Our database is a resource for both Brachypodium and wheat studies and ultimately projects aimed at improving wheat through manipulation of WRKY transcription factors.

The WRKY transcription factor family in Brachypodium distachyon

PubMed Central

2012-01-01

Background A complete assembled genome sequence of wheat is not yet available. Therefore, model plant systems for wheat are very valuable. Brachypodium distachyon (Brachypodium) is such a system. The WRKY family of transcription factors is one of the most important families of plant transcriptional regulators with members regulating important agronomic traits. Studies of WRKY transcription factors in Brachypodium and wheat therefore promise to lead to new strategies for wheat improvement. Results We have identified and manually curated the WRKY transcription factor family from Brachypodium using a pipeline designed to identify all potential WRKY genes. 86 WRKY transcription factors were found, a total higher than all other current databases. We therefore propose that our numbering system (BdWRKY1-BdWRKY86) becomes the standard nomenclature. In the JGI v1.0 assembly of Brachypodium with the MIPS/JGI v1.0 annotation, nine of the transcription factors have no gene model and eleven gene models are probably incorrectly predicted. In total, twenty WRKY transcription factors (23.3%) do not appear to have accurate gene models. To facilitate use of our data, we have produced The Database of Brachypodium distachyon WRKY Transcription Factors. Each WRKY transcription factor has a gene page that includes predicted protein domains from MEME analyses. These conserved protein domains reflect possible input and output domains in signaling. The database also contains a BLAST search function where a large dataset of WRKY transcription factors, published genes, and an extensive set of wheat ESTs can be searched. We also produced a phylogram containing the WRKY transcription factor families from Brachypodium, rice, Arabidopsis, soybean, and Physcomitrella patens, together with published WRKY transcription factors from wheat. This phylogenetic tree provides evidence for orthologues, co-orthologues, and paralogues of Brachypodium WRKY transcription factors. Conclusions The description of the WRKY transcription factor family in Brachypodium that we report here provides a framework for functional genomics studies in an important model system. Our database is a resource for both Brachypodium and wheat studies and ultimately projects aimed at improving wheat through manipulation of WRKY transcription factors. PMID:22726208

Spatial econometric analysis of factors influencing regional energy efficiency in China.

PubMed

Song, Malin; Chen, Yu; An, Qingxian

2018-05-01

Increased environmental pollution and energy consumption caused by the country's rapid development has raised considerable public concern, and has become the focus of the government and public. This study employs the super-efficiency slack-based model-data envelopment analysis (SBM-DEA) to measure the total factor energy efficiency of 30 provinces in China. The estimation model for the spatial interaction intensity of regional total factor energy efficiency is based on Wilson's maximum entropy model. The model is used to analyze the factors that affect the potential value of total factor energy efficiency using spatial dynamic panel data for 30 provinces during 2000-2014. The study found that there are differences and spatial correlations of energy efficiency among provinces and regions in China. The energy efficiency in the eastern, central, and western regions fluctuated significantly, and was mainly because of significant energy efficiency impacts on influences of industrial structure, energy intensity, and technological progress. This research is of great significance to China's energy efficiency and regional coordinated development.

Evaluations of the psychometric properties of the Recovery-Stress Questionnaire for Athletes among a sample of young French table tennis players.

PubMed

Martinent, Guillaume; Decret, Jean-Claude; Isoard-Gautheur, Sandrine; Filaire, Edith; Ferrand, Claude

2014-04-01

This study used confirmatory factor analyses (CFAs) among a sample of young French table tennis players to test: (a) original 19-factor structure, (b) 14-factor structure recently suggested in literature, and (c) hierarchical factor structure of the Recovery-Stress Questionnaire for Athletes (RESTQ-Sport). 148 table tennis players completed the RESTQ-Sport and other self-report questionnaires between one to five occasions with a delay of 1 mo. between each completion. Results of CFAs showed: (a) evidence for relative superiority of the original model in comparison to an alternative model recently proposed in literature, (b) a good fit of the data for the 67-item 17-factor model of the RESTQ-Sport, and (c) an acceptable fit of the data for the hierarchical model of the RESTQ-Sport. Correlations between RESTQ-Sport subscales and burnout and motivation subscales also provided evidence for criterion-related validity of the RESTQ-Sport. This study provided support for reliability and validity of the RESTQ-Sport.

A Confirmatory Factor Analysis of the Structure of Statistics Anxiety Measure: An examination of four alternative models

PubMed Central

Vahedi, Shahram; Farrokhi, Farahman

2011-01-01

Objective The aim of this study is to explore the confirmatory factor analysis results of the Persian adaptation of Statistics Anxiety Measure (SAM), proposed by Earp. Method The validity and reliability assessments of the scale were performed on 298 college students chosen randomly from Tabriz University in Iran. Confirmatory factor analysis (CFA) was carried out to determine the factor structures of the Persian adaptation of SAM. Results As expected, the second order model provided a better fit to the data than the three alternative models. Conclusions Hence, SAM provides an equally valid measure for use among college students. The study both expands and adds support to the existing body of math anxiety literature. PMID:22952530

Eating disorders and non-suicidal self-injury: Structural equation modelling of a conceptual model.

PubMed

Vieira, Ana Isabel; Machado, Bárbara C; Moreira, Célia S; Machado, Paulo P P; Brandão, Isabel; Roma-Torres, António; Gonçalves, Sónia

2018-06-14

Evidence suggests several risk factors for both eating disorders (ED) and nonsuicidal self-injury (NSSI), but the relationships between these factors are not well understood. Considering our previous work and a conceptual model, this cross-sectional study aimed to assess the relationships among distal and proximal factors for the presence of NSSI in ED. We assessed 245 ED patients with the Oxford Risk Factor Interview for ED. Structural equation modelling revealed that both distal and proximal factors were related to the presence of NSSI in ED, disclosing a mediating role of the proximal factors. Stressful life events mediated the relationship between childhood sexual abuse, peer aggression, and both ED and NSSI. Childhood physical abuse was related to ED and NSSI via substance use, negative self-evaluation, and suicide attempts. Findings provided support for the conceptual model and highlight the possible mechanisms by which psychosocial factors may lead to ED and NSSI. Copyright © 2018 John Wiley & Sons, Ltd and Eating Disorders Association.

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

PubMed

Sezgin, F; Kinay, B

2010-01-01

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

Development of database of real-world diesel vehicle emission factors for China.

PubMed

Shen, Xianbao; Yao, Zhiliang; Zhang, Qiang; Wagner, David Vance; Huo, Hong; Zhang, Yingzhi; Zheng, Bo; He, Kebin

2015-05-01

A database of real-world diesel vehicle emission factors, based on type and technology, has been developed following tests on more than 300 diesel vehicles in China using a portable emission measurement system. The database provides better understanding of diesel vehicle emissions under actual driving conditions. We found that although new regulations have reduced real-world emission levels of diesel trucks and buses significantly for most pollutants in China, NOx emissions have been inadequately controlled by the current standards, especially for diesel buses, because of bad driving conditions in the real world. We also compared the emission factors in the database with those calculated by emission factor models and used in inventory studies. The emission factors derived from COPERT (Computer Programmer to calculate Emissions from Road Transport) and MOBILE may both underestimate real emission factors, whereas the updated COPERT and PART5 (Highway Vehicle Particulate Emission Modeling Software) models may overestimate emission factors in China. Real-world measurement results and emission factors used in recent emission inventory studies are inconsistent, which has led to inaccurate estimates of emissions from diesel trucks and buses over recent years. This suggests that emission factors derived from European or US-based models will not truly represent real-world emissions in China. Therefore, it is useful and necessary to conduct systematic real-world measurements of vehicle emissions in China in order to obtain the optimum inputs for emission inventory models. Copyright © 2015. Published by Elsevier B.V.

Modelling the factor structure of the Child Depression Inventory in a population of apparently healthy adolescents in Nigeria.

PubMed

Olorunju, Samson Bamidele; Akpa, Onoja Matthew; Afolabi, Rotimi Felix

2018-01-01

Childhood and adolescent depression is common and often persists into adulthood with negative implications for school performances, peer relationship and behavioural functioning. The Child Depression Inventory (CDI) has been used to assess depression among adolescents in many countries including Nigeria but it is uncertain if the theoretical structure of CDI appropriately fits the experiences of adolescents in Nigeria. This study assessed varying theoretical modelling structure of the CDI in a population of apparently healthy adolescents in Benue state, Nigeria. Data was extracted on CDI scale and demographic information from a total of 1, 963 adolescents (aged 10-19 years), who participated in a state wide study assessing adolescent psychosocial functioning. In addition to descriptive statistics and reliability tests, Exploratory Factor Analysis (EFA) and Confirmatory Factor analysis (CFA) were used to model the underlying factor structure and its adequacy. The suggested new model was compared with existing CDI models as well as the CDI's original theoretical model. A model is considered better, if it has minimum Root Mean Square Error of Approximation (RMSEA<0.05), Minimum value of Discrepancy (CMIN/DF<3.0) and Akaike information criteria. All analyses were performed at 95% confidence level, using the version 21 of AMOS and the R software. Participants were 14.7±2.1 years and mostly male (54.3%), from Monogamous homes (67.9%) and lived in urban areas (52.2%). The measure of the overall internal consistency of the 2-factor CDI was α = 0.84. The 2-factor model had the minimum RMSEA (0.044), CMIN/DF (2.87) and least AIC (1037.996) compared to the other five CDI models. The child depression inventory has a 2-factor structure in a non-clinical general population of adolescents in Nigeria. Future use of the CDI in related setting may consider the 2-factor model.

TheInternational Index of Erectile Function (IIEF-15): psychometric properties of the Portuguese version.

PubMed

Quinta Gomes, Ana Luísa; Nobre, Pedro

2012-01-01

The International Index of Erectile Function (IIEF) is a brief, reliable, and multidimensional scale for assessing sexual function in men in both research and clinical trials. The objective of the present study was to determine the psychometric properties of the Portuguese version of the IIEF. A total of 1,363 Portuguese men participated in this study (a clinical sample of 37 men and a community sample of 1,326 men). All participants completed a questionnaire regarding demographic information and the IIEF. Principal component analysis using varimax rotation indicated a two-factor structure explaining approximately 55% of the total variance (one factor encompassing erection and orgasmic function domains of the original IIEF, and a second factor corresponding to sexual desire, intercourse, and overall satisfaction). The differentiated factor structure with five separate domains of sexual function was not replicated in the Portuguese version. The two-factor model and the original five-factor model of male sexual function were assessed with confirmatory factor analysis (CFA), and overall acceptable fits were demonstrated for both models. However, despite a non-optimal performance, CFA provided a better support for the five-factor solution as the model that best fitted the data. An important lack of discriminant validity evidenced by high intercorrelations among dimensions was detected in both models, suggesting a substantial overlap among factors. Reliability studies showed good internal consistency for the five subscales, and test-retest reliability analysis supported the stability of the measure over time. Discriminant validity confirmed the ability of both subscales to differentiate men with erectile dysfunction from matched controls. Results suggested that the Portuguese version of the IIEF has adequate psychometric properties, and its use is recommended for clinical and research purposes. Further studies are needed in order to elucidate the association among dimensions of male sexual function and, ultimately, to offer a clearer conceptualization of male's sexual response. © 2011 International Society for Sexual Medicine.

Characterizing executive functioning in older special populations: from cognitively elite to cognitively impaired.

PubMed

de Frias, Cindy M; Dixon, Roger A; Strauss, Esther

2009-11-01

The authors examined the structure and invariance of executive functions (EF) across (a) a continuum of cognitive status in 3 groups of older adults (cognitively elite [CE], cognitively normal [CN], and cognitively impaired [CI]) and (b) a 3-year longitudinal interval. Using latent variable analyses (LISREL 8.80), the authors tested 3-factor models ("Inhibition": Hayling [Burgess & Shallice, 1997], Stroop [Regard, 1981]; "Shifting": Brixton [Burgess & Shallice, 1997], Color Trails [D'Elia et al., 1996]; and "Updating": Reading and Computational Span [Salthouse & Babcock, 1991]) and 1-factor models within each group. Participants (initial N = 570; 53-90 years) were from the Victoria Longitudinal Study (Sample 3, Waves 1 and 2). Cross-sectionally, the authors observed a 3-factor EF structure especially for the CE group and 1-factor solutions for all 3 groups. Longitudinally, temporal invariance was supported for the 3-factor model (CE and CN groups) and the 1-factor model (CI and CN groups). Subgroups with higher cognitive status and greater 3-year stability performed better on EF factors than corresponding groups with lower cognitive status and less stability. Studies of EF structure, performance, dedifferentiation, and dysfunction will benefit from considering initial cognitive status and longitudinal stability.

Developmental and Individual Differences in Chinese Writing

PubMed Central

Guan, Connie Qun; Ye, Feifei; Wagner, Richard K.; Meng, Wanjin

2015-01-01

The goal of the present study was to examine the generalizability of a model of the underlying dimensions of written composition across writing systems (Chinese Mandarin vs. English) and level of writing skill. A five-factor model of writing originally developed from analyses of 1st and 4th grade English writing samples was applied to Chinese writing samples obtained from 4th and 7th grade students. Confirmatory factor analysis was used to compare the fits of alternative models of written composition. The results suggest that the five-factor model of written composition generalizes to Chinese writing samples and applies to both less skilled (Grade 4) and more skilled (Grade 7) writing, with differences in factor means between grades that vary in magnitude across factors. PMID:26038631

Psychometric properties of the Intrinsic Motivation Inventory in a competitive sport setting: a confirmatory factor analysis.

PubMed

McAuley, E; Duncan, T; Tammen, V V

1989-03-01

The present study was designed to assess selected psychometric properties of the Intrinsic Motivation Inventory (IMI) (Ryan, 1982), a multidimensional measure of subjects' experience with regard to experimental tasks. Subjects (N = 116) competed in a basketball free-throw shooting game, following which they completed the IMI. The LISREL VI computer program was employed to conduct a confirmatory factor analysis to assess the tenability of a five factor hierarchical model representing four first-order factors or dimensions and a second-order general factor representing intrinsic motivation. Indices of model acceptability tentatively suggest that the sport data adequately fit the hypothesized five factor hierarchical model. Alternative models were tested but did not result in significant improvements in the goodness-of-fit indices, suggesting the proposed model to be the most accurate of the models tested. Coefficient alphas for the four dimensions and the overall scale indicated adequate reliability. The results are discussed with regard to the importance of accurate assessment of psychological constructs and the use of linear structural equations in confirming the factor structures of measures.

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

PubMed

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

2018-05-22

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

A designed screening study with prespecified combinations of factor settings

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

Anderson-cook, Christine M; Robinson, Timothy J

2009-01-01

In many applications, the experimenter has limited options about what factor combinations can be chosen for a designed study. Consider a screening study for a production process involving five input factors whose levels have been previously established. The goal of the study is to understand the effect of each factor on the response, a variable that is expensive to measure and results in destruction of the part. From an inventory of available parts with known factor values, we wish to identify a best collection of factor combinations with which to estimate the factor effects. Though the observational nature of themore » study cannot establish a causal relationship involving the response and the factors, the study can increase understanding of the underlying process. The study can also help determine where investment should be made to control input factors during production that will maximally influence the response. Because the factor combinations are observational, the chosen model matrix will be nonorthogonal and will not allow independent estimation of factor effects. In this manuscript we borrow principles from design of experiments to suggest an 'optimal' selection of factor combinations. Specifically, we consider precision of model parameter estimates, the issue of replication, and abilities to detect lack of fit and to estimate two-factor interactions. Through an example, we present strategies for selecting a subset of factor combinations that simultaneously balance multiple objectives, conduct a limited sensitivity analysis, and provide practical guidance for implementing our techniques across a variety of quality engineering disciplines.« less

The Five-Factor Model of Personality and Its Relationship to Cognitive Style (Rush and Prudence) and Academic Achievement among a Sample of Students

ERIC Educational Resources Information Center

Barakat, Asia; Othman, Afaf

2015-01-01

The present study aims to identify the relationship between the five-factor model of personality and its relationship to cognitive style (rush and prudence) and academic achievement among a sample of students. The study is based on descriptive approach for studying the relationship between the variables of the study, results and analysis. The…

Factors influencing antibiotic prescribing in long-term care facilities: a qualitative in-depth study.

PubMed

van Buul, Laura W; van der Steen, Jenny T; Doncker, Sarah M M M; Achterberg, Wilco P; Schellevis, François G; Veenhuizen, Ruth B; Hertogh, Cees M P M

2014-12-16

Insight into factors that influence antibiotic prescribing is crucial when developing interventions aimed at a more rational use of antibiotics. We examined factors that influence antibiotic prescribing in long-term care facilities, and present a conceptual model that integrates these factors. Semi-structured qualitative interviews were conducted with physicians (n = 13) and nursing staff (n = 13) in five nursing homes and two residential care homes in the central-west region of the Netherlands. An iterative analysis was applied to interviews with physicians to identify and categorize factors that influence antibiotic prescribing, and to integrate these into a conceptual model. This conceptual model was triangulated with the perspectives of nursing staff. The analysis resulted in the identification of six categories of factors that can influence the antibiotic prescribing decision: the clinical situation, advance care plans, utilization of diagnostic resources, physicians' perceived risks, influence of others, and influence of the environment. Each category comprises several factors that may influence the decision to prescribe or not prescribe antibiotics directly (e.g. pressure of patients' family leading to antibiotic prescribing) or indirectly via influence on other factors (e.g. unfamiliarity with patients resulting in a higher physician perceived risk of non-treatment, in turn resulting in a higher tendency to prescribe antibiotics). Our interview study shows that several non-rational factors may affect antibiotic prescribing decision making in long-term care facilities, suggesting opportunities to reduce inappropriate antibiotic use. We developed a conceptual model that integrates the identified categories of influencing factors and shows the relationships between those categories. This model may be used as a practical tool in long-term care facilities to identify local factors potentially leading to inappropriate prescribing, and to subsequently intervene at the level of those factors to promote appropriate antibiotic prescribing.

Modelling the pre-assessment learning effects of assessment: evidence in the validity chain

PubMed Central

Cilliers, Francois J; Schuwirth, Lambert W T; van der Vleuten, Cees P M

2012-01-01

OBJECTIVES We previously developed a model of the pre-assessment learning effects of consequential assessment and started to validate it. The model comprises assessment factors, mechanism factors and learning effects. The purpose of this study was to continue the validation process. For stringency, we focused on a subset of assessment factor–learning effect associations that featured least commonly in a baseline qualitative study. Our aims were to determine whether these uncommon associations were operational in a broader but similar population to that in which the model was initially derived. METHODS A cross-sectional survey of 361 senior medical students at one medical school was undertaken using a purpose-made questionnaire based on a grounded theory and comprising pairs of written situational tests. In each pair, the manifestation of an assessment factor was varied. The frequencies at which learning effects were selected were compared for each item pair, using an adjusted alpha to assign significance. The frequencies at which mechanism factors were selected were calculated. RESULTS There were significant differences in the learning effect selected between the two scenarios of an item pair for 13 of this subset of 21 uncommon associations, even when a p-value of < 0.00625 was considered to indicate significance. Three mechanism factors were operational in most scenarios: agency; response efficacy, and response value. CONCLUSIONS For a subset of uncommon associations in the model, the role of most assessment factor–learning effect associations and the mechanism factors involved were supported in a broader but similar population to that in which the model was derived. Although model validation is an ongoing process, these results move the model one step closer to the stage of usefully informing interventions. Results illustrate how factors not typically included in studies of the learning effects of assessment could confound the results of interventions aimed at using assessment to influence learning. Discuss ideas arising from this article at ‘http://www.mededuc.com discuss’ PMID:23078685

[A prediction model for internet game addiction in adolescents: using a decision tree analysis].

PubMed

Kim, Ki Sook; Kim, Kyung Hee

2010-06-01

This study was designed to build a theoretical frame to provide practical help to prevent and manage adolescent internet game addiction by developing a prediction model through a comprehensive analysis of related factors. The participants were 1,318 students studying in elementary, middle, and high schools in Seoul and Gyeonggi Province, Korea. Collected data were analyzed using the SPSS program. Decision Tree Analysis using the Clementine program was applied to build an optimum and significant prediction model to predict internet game addiction related to various factors, especially parent related factors. From the data analyses, the prediction model for factors related to internet game addiction presented with 5 pathways. Causative factors included gender, type of school, siblings, economic status, religion, time spent alone, gaming place, payment to Internet café, frequency, duration, parent's ability to use internet, occupation (mother), trust (father), expectations regarding adolescent's study (mother), supervising (both parents), rearing attitude (both parents). The results suggest preventive and managerial nursing programs for specific groups by path. Use of this predictive model can expand the role of school nurses, not only in counseling addicted adolescents but also, in developing and carrying out programs with parents and approaching adolescents individually through databases and computer programming.

IMPACT OF OBESITY ON DEVELOPMENT AND PROGRESSION OF MAMMARY TUMORS IN PRECLINICAL MODELS OF BREAST CANCER

PubMed Central

Cleary, Margot P.

2013-01-01

Overweight and/or obesity are known risk factors for postmenopausal breast cancer. More recently increased body weight has also been associated with poor prognosis for both pre- and postmenopausal breast cancer. This relationship has primarily been identified through epidemiological studies. Additional information from in vitro studies has also been produced in attempts to delineate mechanisms of action for the association of obesity and body weight and breast cancer. This approach has identified potential growth factors such as insulin, leptin, estrogen and IGF-I which are reported to be modulated by body weight changes. However, in vitro studies are limited in scope and frequently use non-physiological concentrations of growth factors, while long follow-up is needed for human studies. Preclinical animal models provide an intermediary approach to investigate the impact of body weight and potential growth factors on mammary/breast tumor development and progression. Here results of a number of studies addressing this issue are presented. In the majority of the studies either genetically-obese or diet-induced obese rodent models have been used to investigate spontaneous, transgenic and carcinogen-induced mammary tumor development. To study tumor progression the major focus has been allograft studies in mice with either genetic or dietary-induced obesity. In general, obesity has been demonstrated to shorten mammary tumor latency and to impact tumor pathology. However, in rodents with defects in leptin and other growth factors the impact of obesity is not as straightforward. Future studies using more physiologically relevant obesity models and clearly distinguishing diet composition from body weight effects will be important in continuing to understand the factors associated with body weight’s impact on the mammary/breast cancer development and progression. PMID:24122258

Mars approach for global sensitivity analysis of differential equation models with applications to dynamics of influenza infection.

PubMed

Lee, Yeonok; Wu, Hulin

2012-01-01

Differential equation models are widely used for the study of natural phenomena in many fields. The study usually involves unknown factors such as initial conditions and/or parameters. It is important to investigate the impact of unknown factors (parameters and initial conditions) on model outputs in order to better understand the system the model represents. Apportioning the uncertainty (variation) of output variables of a model according to the input factors is referred to as sensitivity analysis. In this paper, we focus on the global sensitivity analysis of ordinary differential equation (ODE) models over a time period using the multivariate adaptive regression spline (MARS) as a meta model based on the concept of the variance of conditional expectation (VCE). We suggest to evaluate the VCE analytically using the MARS model structure of univariate tensor-product functions which is more computationally efficient. Our simulation studies show that the MARS model approach performs very well and helps to significantly reduce the computational cost. We present an application example of sensitivity analysis of ODE models for influenza infection to further illustrate the usefulness of the proposed method.

State Effect of Traumatic Experience on Personality Structure

PubMed Central

Lee, Hong-seock; Lee, Sang-Kyu; Lee, Heung-Pyo

2012-01-01

Objective Personality is defined as the trait-like qualities of a person. However, it has been recently suggested that the state effect of a situation leads to changes in scores on personality assessments. We predicted that traumatic experiences would induce changes not only in personality scores but also in the factor structures of personality assessments. Methods MethodsaaWe conducted a cross-sectional, case-controlled study using two data sets: a traumatized adolescent sample (n=71) and a non-traumatized adolescent sample (n=296). Personality factor structures were compared between the two samples using exploratory factor analyses for 25 lower-ordered subscales of the Temperament and Character Inventory (TCI). In the non-traumatized sample, evaluation of the scree plot suggested a five-factor solution supporting TCI's original seven-factor model. Results The traumatized sample showed a three-factor structure representing a biological factor, a social factor and an existential factor. This decrease in number of personality factors was caused by strengthened correlations among personality subscales related to coping with traumatic situations. Cloninger's psychobiological model of personality (i.e., temperament-character) was adequate in capturing personality traits of non-traumatized adolescents, but the tripartite view of existential psychology (i.e., body-mind-spirit) clearly corresponded to the factor structure of the traumatized adolescents. Conclusion The three-factor solution of the present traumatized group is consistent with the tripartite model of personality (i.e., body-mind-spirit), while the five-factor solution of the non-traumatized group corresponds to Cloninger's seven-factor model. This is the first study to describe the state effects of traumatic experiences on personality structure. PMID:23251200

Confirmatory factor analysis applied to the Force Concept Inventory

NASA Astrophysics Data System (ADS)

Eaton, Philip; Willoughby, Shannon D.

2018-06-01

In 1995, Huffman and Heller used exploratory factor analysis to draw into question the factors of the Force Concept Inventory (FCI). Since then several papers have been published examining the factors of the FCI on larger sets of student responses and understandable factors were extracted as a result. However, none of these proposed factor models have been verified to not be unique to their original sample through the use of independent sets of data. This paper seeks to confirm the factor models proposed by Scott et al. in 2012, and Hestenes et al. in 1992, as well as another expert model proposed within this study through the use of confirmatory factor analysis (CFA) and a sample of 20 822 postinstruction student responses to the FCI. Upon application of CFA using the full sample, all three models were found to fit the data with acceptable global fit statistics. However, when CFA was performed using these models on smaller sample sizes the models proposed by Scott et al. and Eaton and Willoughby were found to be far more stable than the model proposed by Hestenes et al. The goodness of fit of these models to the data suggests that the FCI can be scored on factors that are not unique to a single class. These scores could then be used to comment on how instruction methods effect the performance of students along a single factor and more in-depth analyses of curriculum changes may be possible as a result.

The estimation of uniaxial compressive strength conversion factor of trona and interbeds from point load tests and numerical modeling

NASA Astrophysics Data System (ADS)

Ozturk, H.; Altinpinar, M.

2017-07-01

The point load (PL) test is generally used for estimation of uniaxial compressive strength (UCS) of rocks because of its economic advantages and simplicity in testing. If the PL index of a specimen is known, the UCS can be estimated using conversion factors. Several conversion factors have been proposed by various researchers and they are dependent upon the rock type. In the literature, conversion factors on different sedimentary, igneous and metamorphic rocks can be found, but no study exists on trona. In this study, laboratory UCS and field PL tests were carried out on trona and interbeds of volcano-sedimentary rocks. Based on these tests, PL to UCS conversion factors of trona and interbeds are proposed. The tests were modeled numerically using a distinct element method (DEM) software, particle flow code (PFC), in an attempt to guide researchers having various types of modeling problems (excavation, cavern design, hydraulic fracturing, etc.) of the abovementioned rock types. Average PFC parallel bond contact model micro properties for the trona and interbeds were determined within this study so that future researchers can use them to avoid the rigorous PFC calibration procedure. It was observed that PFC overestimates the tensile strength of the rocks by a factor that ranges from 22 to 106.

The Development and Psychometric Validation of an Arabic-Language Version of the Pain Catastrophizing Scale

PubMed Central

Fares, Souha

2017-01-01

Context. The Pain Catastrophizing Scale (PCS) is the most widely used measure of pain-specific catastrophizing. Objectives. The purpose of the present study was to develop and psychometrically evaluate an Arabic-language version of the PCS. Methods. In Study 1, 150 adult chronic nonmalignant pain patients seeking treatment at a hospital setting completed the PCS-A and a number of self-report measures assessing clinical parameters of pain, symptoms of depression, and quality of life. Study 2 employed a cold pressor pain task to examine the PCS-A in a sample of 44 healthy university students. Results. Exploratory factor analyses suggested a two-factor structure. Confirmatory factor analysis comparing the 2-factor model, Sullivan's original 3-factor model, and a 1-factor model based on the total score all provided adequate fit to the data. Cronbach's alpha coefficients across all models met or exceeded accepted standards of reliability. Catastrophizing was associated with higher levels of depression and increased pain intensity and interference. Catastrophizing predicted decreased quality of life, even after controlling for the contribution of gender, employment, depression, and pain interference. PCS-A scores were positively correlated with heightened experimental pain severity and decreased pain tolerance. Conclusion. The present results provide strong support for the psychometric properties of the PCS-A. PMID:28190958

Multiscale Spatial Assessment of Determinant Factors of Land Use Change: Study at Urban Area of Yogyakarta

NASA Astrophysics Data System (ADS)

Susilo, Bowo

2017-12-01

Studies of land use change have been undertaken by different researchers using various methods. Among those methods, modelling is widely utilized. Modelling land use change required several components remarked as model variables. Those represent any conditions or factors which considered relevant or have some degree of correlation to the changes of land use. Variables which have significant correlation to land use change are referred as determinant factors or driving forces. Those factors as well as changes of land use are distributed across space and therefore referred as spatial determinant factors. The main objective of the research was to examine land use change and its determinant factors. Area and location of land use change were analysed based on three different years of land use maps, which are 1993, 2000 and 2007. Spatial and temporal analysis were performed which emphasize to the influence of scale to both of analysis’s. Urban area of Yogyakarta was selected as study area. Study area covered three different districts (kabupaten), involving 20 sub districts and totally consists of 74 villages. Result of this study shows that during 14 years periods (1993 to 2007), there were about 1,460 hectares of land use change had been taken place. Dominant type of land use change is agricultural to residential. The uses of different spatial and temporal scale in analysis were able to reveal different factors related to land use change. In general, factors influencing the quantities of land use change in the study area were population growth and the availability of land. The use of data with different spatial resolution can reveal the presence of various factors associated with the location of the change. Locations of land use change were influenced or determined by accessibility factors.

A Test of an Integrative Model Using Social Factors and Personality Traits: Prediction on the Delinquency of South Korean Youth.

PubMed

Yun, Minwoo; Kim, Eunyoung; Park, Woong-Sub

2017-08-01

To more fully comprehend juvenile delinquency, it is necessary to take an integrative approach, with consideration of both personality traits of social risk factors. Many scholars argue the necessity and strength of integrative approach on the ground that juvenile delinquency is an outcome of interplay of individual and social factors. The present study examines the general applicability of an integrative model of personal traits and social risk factors to youth delinquency in the South Korean context. The empirical results show that the delinquency predictors in the current South Korean sample are closely aligned to Loeber and Farrington's theoretical propositions and that found in Western nations. Perhaps this is because South Korea has undergone rapid Westernization for the last decades. Because the correlates in this sample and Western theoretical propositions and studies overlap, an integrative model of personality trait and social risk factors is indeed generally applicable to South Korea. This finding also depicts the extent of Westernization in the South Korean society at least among adolescents. Limitations of the present study and directions for the future study are discussed.

The effects of cumulative risks and promotive factors on urban adolescent alcohol and other drug use: a longitudinal study of resiliency.

PubMed

Ostaszewski, Krzysztof; Zimmerman, Marc A

2006-12-01

Resiliency theory provides a conceptual framework for studying why some youth exposed to risk factors do not develop the negative behaviors they predict. The purpose of this study was to test compensatory and protective models of resiliency in a longitudinal sample of urban adolescents (80% African American). The data were from Years 1 (9th grade) and 4 (12th grade). The study examined effects of cumulative risk and promotive factors on adolescent polydrug use including alcohol, tobacco and marijuana. Cumulative measures of risk/promotive factors represented individual characteristics, peer influence, and parental/familial influences. After controlling for demographics, results of multiple regression of polydrug use support the compensatory model of resiliency both cross-sectionally and longitudinally. Promotive factors were also found to have compensatory effects on change in adolescent polydrug use. The protective model of resiliency evidenced cross-sectionally was not supported in longitudinal analysis. The findings support resiliency theory and the use of cumulative risk/promotive measures in resiliency research. Implications focused on utilizing multiple assets and resources in prevention programming are discussed.

FACTORS INFLUENCING THE DESIGN OF BIOACCUMULATION FACTOR AND BIOTA-SEDIMENT ACCUMULATION FACTOR FIELD STUDIES

EPA Science Inventory

A series of modeling simulations were performed to develop an understanding of the underlying factors and principles involved in developing field sampling designs for measuring bioaccumulation factors (BAFs) and biota-sediment accumulation factors (BSAFs. These simulations reveal...

Application of the PRECEDE model to understanding mental health promoting behaviors in Hong Kong.

PubMed

Mo, Phoenix K H; Mak, Winnie W S

2008-08-01

The burdens related to mental illness have been increasingly recognized in many countries. Nevertheless, research in positive mental health behaviors remains scarce. This study utilizes the Predisposing, Reinforcing, and Enabling Causes in Education Diagnosis and Evaluation (PRECEDE) model to identify factors associated with mental health promoting behaviors and to examine the effects of these behaviors on mental well-being and quality of life among 941 adults in Hong Kong. Structural equation modeling shows that sense of coherence (predisposing factor), social support (reinforcing factor), and daily hassles (enabling factor) are significantly related to mental health promoting behaviors, which are associated with mental well-being and quality of life. Results of bootstrap analyses confirm the mediating role of mental health promoting behaviors on well-being and quality of life. The study supports the application of the PRECEDE model in understanding mental health promoting behaviors and demonstrates its relationships with well-being and quality of life.

Proof of factorization using background field method of QCD

NASA Astrophysics Data System (ADS)

Nayak, Gouranga C.

2010-02-01

Factorization theorem plays the central role at high energy colliders to study standard model and beyond standard model physics. The proof of factorization theorem is given by Collins, Soper and Sterman to all orders in perturbation theory by using diagrammatic approach. One might wonder if one can obtain the proof of factorization theorem through symmetry considerations at the lagrangian level. In this paper we provide such a proof.

Proof of factorization using background field method of QCD

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

Nayak, Gouranga C.

Factorization theorem plays the central role at high energy colliders to study standard model and beyond standard model physics. The proof of factorization theorem is given by Collins, Soper and Sterman to all orders in perturbation theory by using diagrammatic approach. One might wonder if one can obtain the proof of factorization theorem through symmetry considerations at the lagrangian level. In this paper we provide such a proof.

Analysis of Food Hub Commerce and Participation Using Agent-Based Modeling: Integrating Financial and Social Drivers.

PubMed

Krejci, Caroline C; Stone, Richard T; Dorneich, Michael C; Gilbert, Stephen B

2016-02-01

Factors influencing long-term viability of an intermediated regional food supply network (food hub) were modeled using agent-based modeling techniques informed by interview data gathered from food hub participants. Previous analyses of food hub dynamics focused primarily on financial drivers rather than social factors and have not used mathematical models. Based on qualitative and quantitative data gathered from 22 customers and 11 vendors at a midwestern food hub, an agent-based model (ABM) was created with distinct consumer personas characterizing the range of consumer priorities. A comparison study determined if the ABM behaved differently than a model based on traditional economic assumptions. Further simulation studies assessed the effect of changes in parameters, such as producer reliability and the consumer profiles, on long-term food hub sustainability. The persona-based ABM model produced different and more resilient results than the more traditional way of modeling consumers. Reduced producer reliability significantly reduced trade; in some instances, a modest reduction in reliability threatened the sustainability of the system. Finally, a modest increase in price-driven consumers at the outset of the simulation quickly resulted in those consumers becoming a majority of the overall customer base. Results suggest that social factors, such as desire to support the community, can be more important than financial factors. An ABM of food hub dynamics, based on human factors data gathered from the field, can be a useful tool for policy decisions. Similar approaches can be used for modeling customer dynamics with other sustainable organizations. © 2015, Human Factors and Ergonomics Society.

Prognostic factors for risk stratification of adult cancer patients with chemotherapy-induced febrile neutropenia: a systematic review and meta-analysis.

PubMed

Lee, Yee Mei; Lang, Dora; Lockwood, Craig

Increasing numbers of studies identify new prognostic factors for categorising chemotherapy-induced febrile neutropenia adult cancer patients into high- or low-risk groups for adverse outcomes. These groupings are used to tailor therapy according to level of risk. However many emerging factors with prognostic significance remain controversial, being based on single studies only. A systematic review was conducted to determine the strength of association of all identified factors associated with the outcomes of chemotherapy-induced febrile neutropenia patients. The participants included were adults of 15 years old and above, with a cancer diagnosis and who underwent cancer treatment.The review focused on clinical factors and their association with the outcomes of cancer patients with chemotherapy-induced febrile neutropenia at presentation of fever.All quantitative studies published in English which investigated clinical factors for risk stratification of adult cancer patients with chemotherapy-induced febrile neutropenia were considered.The primary outcome of interest was to identify the clinical factors for risk stratification of adult cancer patients with chemotherapy-induced febrile neutropenia. Electronic databases searched from their respective inception date up to December 2011 include MEDLINE, EMBASE, CINAHL, Cochrane Central Register of Controlled Trials (CENTRAL), Web of Science, Science-Direct, Scopus and Mednar. The quality of the included studies was subjected to assessment by two independent reviewers. The standardised critical appraisal tool from the Joanna Briggs Institute Meta-Analysis of Statistics Assessment and Review Instrument (JBI-MAStARI) was used to assess the following criteria: representativeness of study population; clearly defined prognostic factors and outcomes; whether potential confounders were addressed and appropriate statistical analysis was undertaken for the study design. Data extraction was performed using a modified version of the standardised extraction tool from the JBI-MAStARI. Prognostic factors and the accompanying odds ratio reported for the significance of these factors that were identified by multivariate regression, were extracted from each included study. Studies results were pooled in statistical meta-analysis using Review Manager 5.1. Where statistical pooling was not possible, the findings were presented in narrative form. Seven studies (four prospective cohort and three retrospective cohort) investigating 22 factors in total were included. Fixed effects meta-analysis showed: hypotension [OR=1.66, 95%CI, 1.14-2.41, p=0.008] and thrombocytopenia [OR=3.92, 95%CI, 2.19-7.01, p<0.00001)] were associated with high-risk of adverse outcomes for febrile neutropenia. Other factors that were statistically significant from single studies included: age of patients, clinical presentation at fever onset, presence or absence of co-morbidities, infections, duration and severity of neutropenia state. Five prognostic factors failed to demonstrate an association between the variables and the outcomes measured and they include: presence of pneumonia, total febrile days, median days to fever, recovery from neutropenia and presence of moderate clinical symptoms in association with Gram-negative bacteraemia. Despite the overall limitations identified in the included studies, this review has provided a synthesis of the best available evidence for the prognostic factors used in risk stratification of febrile neutropenia patients. However, the dynamic aspects of prognostic model development, validation and utilisation have not been addressed adequately thus far. Given the findings of this review, it is timely to address these issues and improve the utilisation of prognostic models in the management of febrile neutropenia patients. The identified factors are similar to the factors in current prognostic models. However, additional factors that were reported to be statistically significant in this review (thrombocytopenia, presence of central venous catheter, and duration and severity of neutropenia) have not previously been included in prognostic models. This review has found these factors may improve the performance of current models by adding or replacing some of the factors. The role of risk stratification of chemotherapy-induced febrile neutropenia patients continues to evolve as the practice of risk-based therapy has been demonstrated to be beneficial to patients, clinicians and health care organisations. Further research to identify new factors /markers is needed to develop a new model which is reliable and accurate for these patients, regardless of cancer types. A robust and well-validated prognostic model is the key to enhance patient safety in the risk-based management of cancer patients with chemotherapy-induced febrile neutropenia.

Correlation of causal factors that influence construction safety performance: A model.

PubMed

Rodrigues, F; Coutinho, A; Cardoso, C

2015-01-01

The construction sector has presented positive development regarding the decrease in occupational accident rates in recent years. Regardless, the construction sector stands out systematically from other industries due to its high number of fatalities. The aim of this paper is to deeply understand the causality of construction accidents from the early design phase through a model. This study reviewed several research papers presenting various analytical models that correlate the contributing factors to occupational accidents in this sector. This study also analysed different construction projects and conducted a survey of design and site supervision teams. This paper proposes a model developed from the analysis of existing ones, which correlates the causal factors through all the construction phases. It was concluded that effective risk prevention can only be achieved by a global correlation of causal factors including not only production ones but also client requirements, financial climate, design team competence, project and risk management, financial capacity, health and safety policy and early planning. Accordingly, a model is proposed.

Evaluating Individual Students' Perceptions of Instructional Quality: An Investigation of their Factor Structure, Measurement Invariance, and Relations to Educational Outcomes

PubMed Central

Scherer, Ronny; Nilsen, Trude; Jansen, Malte

2016-01-01

Students' perceptions of instructional quality are among the most important criteria for evaluating teaching effectiveness. The present study evaluates different latent variable modeling approaches (confirmatory factor analysis, exploratory structural equation modeling, and bifactor modeling), which are used to describe these individual perceptions with respect to their factor structure, measurement invariance, and the relations to selected educational outcomes (achievement, self-concept, and motivation in mathematics). On the basis of the Programme for International Student Assessment (PISA) 2012 large-scale data sets of Australia, Canada, and the USA (N = 26,746 students), we find support for the distinction between three factors of individual students' perceptions and full measurement invariance across countries for all modeling approaches. In this regard, bifactor exploratory structural equation modeling outperformed alternative approaches with respect to model fit. Our findings reveal significant relations to the educational outcomes. This study synthesizes different modeling approaches of individual students' perceptions of instructional quality and provides insights into the nature of these perceptions from an individual differences perspective. Implications for the measurement and modeling of individually perceived instructional quality are discussed. PMID:26903917

Assessing the specificity of posttraumatic stress disorder's dysphoric items within the dysphoria model.

PubMed

Armour, Cherie; Shevlin, Mark

2013-10-01

The factor structure of posttraumatic stress disorder (PTSD) currently used by the Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition (DSM-IV), has received limited support. A four-factor dysphoria model is widely supported. However, the dysphoria factor of this model has been hailed as a nonspecific factor of PTSD. The present study investigated the specificity of the dysphoria factor within the dysphoria model by conducting a confirmatory factor analysis while statistically controlling for the variance attributable to depression. The sample consisted of 429 individuals who met the diagnostic criteria for PTSD in the National Comorbidity Survey. The results concluded that there was no significant attenuation in any of the PTSD items. This finding is pertinent given several proposals for the removal of dysphoric items from the diagnostic criteria set of PTSD in the upcoming DSM-5.

Anthropometric data reduction using confirmatory factor analysis.

PubMed

Rohani, Jafri Mohd; Olusegun, Akanbi Gabriel; Rani, Mat Rebi Abdul

2014-01-01

The unavailability of anthropometric data especially in developing countries has remained a limiting factor towards the design of learning facilities with sufficient ergonomic consideration. Attempts to use anthropometric data from developed countries have led to provision of school facilities unfit for the users. The purpose of this paper is to use factor analysis to investigate the suitability of the collected anthropometric data as a database for school design in Nigerian tertiary institutions. Anthropometric data were collected from 288 male students in a Federal Polytechnic in North-West of Nigeria. Their age is between 18-25 years. Nine vertical anthropometric dimensions related to heights were collected using the conventional traditional equipment. Exploratory factor analysis was used to categorize the variables into a model consisting of two factors. Thereafter, confirmatory factor analysis was used to investigate the fit of the data to the proposed model. A just identified model, made of two factors, each with three variables was developed. The variables within the model accounted for 81% of the total variation of the entire data. The model was found to demonstrate adequate validity and reliability. Various measuring indices were used to verify that the model fits the data properly. The final model reveals that stature height and eye height sitting were the most stable variables for designs that have to do with standing and sitting construct. The study has shown the application of factor analysis in anthropometric data analysis. The study highlighted the relevance of these statistical tools to investigate variability among anthropometric data involving diverse population, which has not been widely used for analyzing previous anthropometric data. The collected data is therefore suitable for use while designing for Nigerian students.

[Psychosocial work factors and self-reported health in the French national SUMER survey].

PubMed

Lesuffleur, Thomas; Chastang, Jean-François; Cavet, Marine; Niedhammer, Isabelle

2015-01-01

This study was designed to investigate the associations between psychosocial work factors, using well-known theoretical models and emerging concepts, and self-reported health in the national population of French employees. This study was based on the data of the French national representative SUMER 2010 survey. The sample included 46,962 employees, 26,883 men and 20,079 women, with an 87% participation rate. Self-reported health was measured by means of a single question and was analysed as a binary variable. Psychosocial work factors included factors related to job strain and effort-reward imbalance models, workplace violence and working hours. Associations between psychosocial work factors and self-reported health were studied using weighted logistic regression models adjusted for covariates (age, occupation, economic activity, and other types of occupational exposure). Low decision latitude (skill discretion and decision authority), high psychological demands, low social support (from supervisors for men), low reward (low esteem and low job promotion for both genders and job insecurity for men), bullying and verbal abuse for both genders were associated with self-reported health. This study emphasizes the role of psychosocial work factors as risk factors for poor self-reported health and suggests that the implementation of preventive measures to reduce exposure to psychosocial work factors should be an objective for the improvement of health at work.

Factorial Validity and Invariance Assessment of a Short Version of the Recalled Childhood Gender Identity/Role Questionnaire.

PubMed

Veale, Jaimie F

2016-04-01

Recalled childhood gender role/identity is a construct that is related to sexual orientation, abuse, and psychological health. The purpose of this study was to assess the factorial validity of a short version of Zucker et al.'s (2006) "Recalled Childhood Gender Identity/Gender Role Questionnaire" using confirmatory factor analysis and to test the stability of the factor structure across groups (measurement invariance). Six items of the questionnaire were completed online by 1929 participants from a variety of gender identity and sexual orientation groups. Models of the six items loading onto one factor had poor fit for the data. Items were removed for having a large proportion of error variance. Among birth-assigned females, a five-item model had good fit for the data, but there was evidence for differences in scale's factor structure across gender identity, age, level of education, and country groups. Among birth-assigned males, the resulting four-item model did not account for all of the relationship between variables, and modeling for this resulted in a model that was almost saturated. This model also had evidence of measurement variance across gender identity and sexual orientation groups. The models had good reliability and factor score determinacy. These findings suggest that results of previous studies that have assessed recalled childhood gender role/identity may have been susceptible to construct bias due to measurement variance across these groups. Future studies should assess measurement invariance between groups they are comparing, and if it is not found the issue can be addressed by removing variant indicators and/or applying a partial invariance model.

Impact of Lead Time and Safety Factor in Mixed Inventory Models with Backorder Discounts

NASA Astrophysics Data System (ADS)

Lo, Ming-Cheng; Chao-Hsien Pan, Jason; Lin, Kai-Cing; Hsu, Jia-Wei

This study investigates the impact of safety factor on the continuous review inventory model involving controllable lead time with mixture of backorder discount and partial lost sales. The objective is to minimize the expected total annual cost with respect to order quantity, backorder price discount, safety factor and lead time. A model with normal demand is also discussed. Numerical examples are presented to illustrate the procedures of the algorithms and the effects of parameters on the result of the proposed models are analyzed.

Risk factors for lower extremity injuries among half marathon and marathon runners of the Lage Landen Marathon Eindhoven 2012: A prospective cohort study in the Netherlands.

PubMed

van Poppel, D; de Koning, J; Verhagen, A P; Scholten-Peeters, G G M

2016-02-01

To determine risk factors for running injuries during the Lage Landen Marathon Eindhoven 2012. Prospective cohort study. Population-based study. This study included 943 runners. Running injuries after the Lage Landen Marathon. Sociodemographic and training-related factors as well as lifestyle factors were considered as potential risk factors and assessed in a questionnaire 1 month before the running event. The association between potential risk factors and injuries was determined, per running distance separately, using univariate and multivariate logistic regression analysis. In total, 154 respondents sustained a running injury. Among the marathon runners, in the univariate model, body mass index ≥ 26 kg/m(2), ≤ 5 years of running experience, and often performing interval training, were significantly associated with running injuries, whereas in the multivariate model only ≤ 5 years of running experience and not performing interval training on a regular basis were significantly associated with running injuries. Among marathon runners, no multivariate model could be created because of the low number of injuries and participants. This study indicates that interval training on a regular basis may be recommended to marathon runners to reduce the risk of injury. © 2015 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Reading component skills of learners in adult basic education.

PubMed

MacArthur, Charles A; Konold, Timothy R; Glutting, Joseph J; Alamprese, Judith A

2010-01-01

The purposes of this study were to investigate the reliability and construct validity of measures of reading component skills with a sample of adult basic education (ABE) learners, including both native and nonnative English speakers, and to describe the performance of those learners on the measures. Investigation of measures of reading components is needed because available measures were neither developed for nor normed on ABE populations or with nonnative speakers of English. The study included 486 students, 334 born or educated in the United States (native) and 152 not born or educated in the United States (nonnative) but who spoke English well enough to participate in English reading classes. All students had scores on 11 measures covering five constructs: decoding, word recognition, spelling, fluency, and comprehension. Confirmatory factor analysis (CFA) was used to test three models: a two-factor model with print and meaning factors; a three-factor model that separated out a fluency factor; and a five-factor model based on the hypothesized constructs. The five-factor model fit best. In addition, the CFA model fit both native and nonnative populations equally well without modification, showing that the tests measure the same constructs with the same accuracy for both groups. Group comparisons found no difference between the native and nonnative samples on word recognition, but the native sample scored higher on fluency and comprehension and lower on decoding than did the nonnative sample. Students with self-reported learning disabilities scored lower on all reading components. Differences by age and gender were also analyzed.

Factor Structure of the Counselor Burnout Inventory in a Sample of Sexual Offender and Sexual Abuse Therapists

ERIC Educational Resources Information Center

Lee, Jayoung; Wallace, Sam; Puig, Ana; Choi, Bo Young; Nam, Suk Kyung; Lee, Sang Min

2010-01-01

This study empirically tested and compared three different models of factor structure with a sample of therapists working with sexual offenders, survivors of sexual abuse, or both. Results indicated that a modified five-factor model was the most appropriate. Practical implications for sexual offender/abuse survivor therapists are discussed.…

Jordanian Pre-Service Teachers' and Technology Integration: A Human Resource Development Approach

ERIC Educational Resources Information Center

Al-Ruz, Jamal Abu; Khasawneh, Samer

2011-01-01

The purpose of this study was to test a model in which technology integration of pre-service teachers was predicted by a number of university-based and school-based factors. Initially, factors affecting technology integration were identified, and a research-based path model was developed to explain causal relationships between these factors. The…

The Internal Structure of Positive and Negative Affect: A Confirmatory Factor Analysis of the PANAS

ERIC Educational Resources Information Center

Tuccitto, Daniel E.; Giacobbi, Peter R., Jr.; Leite, Walter L.

2010-01-01

This study tested five confirmatory factor analytic (CFA) models of the Positive Affect Negative Affect Schedule (PANAS) to provide validity evidence based on its internal structure. A sample of 223 club sport athletes indicated their emotions during the past week. Results revealed that an orthogonal two-factor CFA model, specifying error…

An investigation into the psychometric properties of the Hospital Anxiety and Depression Scale in patients with breast cancer

PubMed Central

Rodgers, Jacqui; Martin, Colin R; Morse, Rachel C; Kendell, Kate; Verrill, Mark

2005-01-01

Background To determine the psychometric properties of the Hospital Anxiety and Depression Scale (HADS) in patients with breast cancer and determine the suitability of the instrument for use with this clinical group. Methods A cross-sectional design was used. The study used a pooled data set from three breast cancer clinical groups. The dependent variables were HADS anxiety and depression sub-scale scores. Exploratory and confirmatory factor analyses were conducted on the HADS to determine its psychometric properties in 110 patients with breast cancer. Seven models were tested to determine model fit to the data. Results Both factor analysis methods indicated that three-factor models provided a better fit to the data compared to two-factor (anxiety and depression) models for breast cancer patients. Clark and Watson's three factor tripartite and three factor hierarchical models provided the best fit. Conclusion The underlying factor structure of the HADS in breast cancer patients comprises three distinct, but correlated factors, negative affectivity, autonomic anxiety and anhedonic depression. The clinical utility of the HADS in screening for anxiety and depression in breast cancer patients may be enhanced by using a modified scoring procedure based on a three-factor model of psychological distress. This proposed alternate scoring method involving regressing autonomic anxiety and anhedonic depression factors onto the third factor (negative affectivity) requires further investigation in order to establish its efficacy. PMID:16018801

Validating the 11-Item Revised University of California Los Angeles Scale to Assess Loneliness Among Older Adults: An Evaluation of Factor Structure and Other Measurement Properties.

PubMed

Lee, Joonyup; Cagle, John G

2017-11-01

To examine the measurement properties and factor structure of the short version of the Revised University of California Los Angeles (R-UCLA) loneliness scale from the Health and Retirement Study (HRS). Based on data from 3,706 HRS participants aged 65 + who completed the 2012 wave of the HRS and its Psychosocial Supplement, the measurement properties and factorability of the R-UCLA were examined by conducting an exploratory factor analysis (EFA) and the confirmatory factor analysis (CFA) on randomly split halves. The average score for the 11-item loneliness scale was 16.4 (standard deviation: 4.5). An evaluation of the internal consistency produced a Cronbach's α of 0.87. Results from the EFA showed that two- and three-factor models were appropriate. However, based on the results of the CFA, only a two-factor model was determined to be suitable because there was a very high correlation between two factors identified in the three-factor model, available social connections and sense of belonging. This study provides important data on the properties of the 11-item R-UCLA scale by identifying a two-factor model of loneliness: feeling isolated and available social connections. Our findings suggest the 11-item R-UCLA has good factorability and internal reliability. Copyright © 2017 American Association for Geriatric Psychiatry. Published by Elsevier Inc. All rights reserved.

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

PubMed

Lecerf, Thierry; Canivez, Gary L

2018-06-01

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

Bayesian Exploratory Factor Analysis

PubMed Central

Conti, Gabriella; Frühwirth-Schnatter, Sylvia; Heckman, James J.; Piatek, Rémi

2014-01-01

This paper develops and applies a Bayesian approach to Exploratory Factor Analysis that improves on ad hoc classical approaches. Our framework relies on dedicated factor models and simultaneously determines the number of factors, the allocation of each measurement to a unique factor, and the corresponding factor loadings. Classical identification criteria are applied and integrated into our Bayesian procedure to generate models that are stable and clearly interpretable. A Monte Carlo study confirms the validity of the approach. The method is used to produce interpretable low dimensional aggregates from a high dimensional set of psychological measurements. PMID:25431517

Determinants of sick-leave duration: a tool for managers?

PubMed

Flach, Peter A; Krol, Boudien; Groothoff, Johan W

2008-09-01

To provide managers with tools to manage episodes of sick-leave of their employees, the influence of factors such as age, gender, duration of tenure, working full-time or part-time, cause and history of sick-leave, salary and education on sick-leave duration was studied. In a cross-sectional study, data derived from the 2005 sick-leave files of a Dutch university were examined. Odds ratios of the single risk factors were calculated for short spells (or=91 days) of sick-leave. Next, these factors were studied in multiple regression models. Age, gender, duration of employment, cause and history of sick-leave, salary and membership of scientific staff, studied as single factors, have a significant influence on sick-leave duration. In multiple models, this influence remains for gender, salary, age, and history and cause of sick-leave. Only in medium or long spells and regarding the risk for a long or an extended spell do the predictive values of models consisting of psychological factors, work-related factors, salary and gender become reasonable. The predictive value of the risk factors used in this study is limited, and varies with the duration of the sick-leave spell. Only the risk for an extended spell of sick-leave as compared to a medium or long spell is reasonably predicted. Factors contributing to this risk may be used as tools in decision-making.

Comprehensive manual handling limits for lowering, pushing, pulling and carrying activities.

PubMed

Shoaf, C; Genaidy, A; Karwowski, W; Waters, T; Christensen, D

1997-11-01

The objective of this study was to develop a set of mathematical models for manual lowering, pushing, pulling and carrying activities that would result in establishing load capacity limits to protect the lower back against occupational low-back disorders. In order to establish safe guidelines, a three-stage process was used. First, psychophysical data was used to generate the models' discounting factors and recommended load capacities. Second, biomechanical analysis was used to refine the recommended load capacities. Third, physiological criteria were used to validate the models' discounting factors. Both task and personal factors were considered in the models' development. When compared to the results from prior psychophysical research for these activities, the developed load capacity values are lower than previously established limits. The results of this study allowed the authors to validate the hypothesis proposed and tested by Karwowski (1983) that states that the combination of physiological and biomechanical stresses should lead to the overall measure of task acceptability or the psychophysical stress. This study also found that some of the discounting factors for the task frequency parameters recommended in the prior psychophysical research should not be used as several of the high frequency factors violated physiological limits.

Dimensional analysis of depressive, anxious and somatic symptoms presented by primary care patients and their relationship with ICD-11 PHC proposed diagnoses.

PubMed

Ziebold, Carolina; Goldberg, David P; Reed, Geoffrey M; Minhas, Fareed; Razzaque, Bushra; Fortes, Sandra; Robles, Rebeca; Lam, Tai Pong; Bobes, Julio; Iglesias, Celso; Cogo-Moreira, Hugo; García, José Ángel; Mari, Jair J

2018-06-04

A study conducted as part of the development of the Eleventh International Classification of Mental Disorders for Primary Health Care (ICD-11 PHC) provided an opportunity to test the relationships among depressive, anxious and somatic symptoms in PHC. Primary care physicians participating in the ICD-11 PHC field studies in five countries selected patients who presented with somatic symptoms not explained by known physical pathology by applying a 29-item screening on somatic complaints that were under study for bodily stress disorder. Patients were interviewed using the Clinical Interview Schedule-Revised and assessed using two five-item scales that measure depressive and anxious symptoms. Structural models of anxious-depressive symptoms and somatic complaints were tested using a bi-factor approach. A total of 797 patients completed the study procedures. Two bi-factor models fit the data well: Model 1 had all symptoms loaded on a general factor, along with one of three specific depression, anxiety and somatic factors [x2 (627) = 741.016, p < 0.0011, RMSEA = 0.015, CFI = 0.911, TLI = 0.9]. Model 2 had a general factor and two specific anxious depression and somatic factors [x2 (627) = 663.065, p = 0.1543, RMSEA = 0.008, CFI = 0.954, TLI = 0.948]. These data along with those of previous studies suggest that depressive, anxious and somatic symptoms are largely different presentations of a common latent phenomenon. This study provides support for the ICD-11 PHC conceptualization of mood disturbance, especially anxious depression, as central among patients who present multiple somatic symptoms.

Seasonal Variation and Ecosystem Dependence of Emission Factors for Selected Trace Gases and PM2.5 for Southern African Savanna Fires

NASA Technical Reports Server (NTRS)

Korontzi, S.; Ward, D. E.; Susott, R. A.; Yokelson, R. J.; Justice, C. O.; Hobbs, P. V.; Smithwick, E. A. H.; Hao, W. M.

2003-01-01

In this paper we present the first early dry season (early June-early August) emission factor measurements for carbon dioxide (CO2), carbon monoxide (CO), methane (Ca), nonmethane hydrocarbons (NMHC), and particulates with a diameter less than 2.5 microns (pM2.5) for southern African grassland and woodland fires. Seasonal emission factors for grassland fires correlate linearly with the proportion of green grass, used as a surrogate for the fuel moisture content, and are higher for products of incomplete combustion in the early part of the dry season compared with later in the dry season. Models of emission factors for NMHC and PM(sub 2.5) versus modified combustion efficiency (MCE) are statistically different in grassland compared with woodland ecosystems. We compare predictions based on the integration of emissions factors from this study, from the southern African Fire-Atmosphere Research Initiative 1992 (SAFARI-92), and from SAFARI-2000 with those based on the smaller set of ecosystem-specific emission factors to estimate the effects of using regional-average rather than ecosystem-specific emission factors. We also test the validity of using the SAFARI-92 models for emission factors versus MCE to predict the early dry season emission factors measured in this study. The comparison indicates that the largest discrepancies occur at the low end (0.907) and high end (0.972) of MCE values measured in this study. Finally, we combine our models of MCE versus proportion of green grass for grassland fires with emission factors versus MCE for selected oxygenated volatile organic compounds measured in the SAFARI-2000 campaign to derive the first seasonal emission factors for these compounds. The results of this study demonstrate that seasonal variations in savanna fire emissions are important and should be considered in modeling emissions at regional to continental scales.

Global Quantitative Modeling of Chromatin Factor Interactions

PubMed Central

Zhou, Jian; Troyanskaya, Olga G.

2014-01-01

Chromatin is the driver of gene regulation, yet understanding the molecular interactions underlying chromatin factor combinatorial patterns (or the “chromatin codes”) remains a fundamental challenge in chromatin biology. Here we developed a global modeling framework that leverages chromatin profiling data to produce a systems-level view of the macromolecular complex of chromatin. Our model ultilizes maximum entropy modeling with regularization-based structure learning to statistically dissect dependencies between chromatin factors and produce an accurate probability distribution of chromatin code. Our unsupervised quantitative model, trained on genome-wide chromatin profiles of 73 histone marks and chromatin proteins from modENCODE, enabled making various data-driven inferences about chromatin profiles and interactions. We provided a highly accurate predictor of chromatin factor pairwise interactions validated by known experimental evidence, and for the first time enabled higher-order interaction prediction. Our predictions can thus help guide future experimental studies. The model can also serve as an inference engine for predicting unknown chromatin profiles — we demonstrated that with this approach we can leverage data from well-characterized cell types to help understand less-studied cell type or conditions. PMID:24675896

Modeling and projection of dengue fever cases in Guangzhou based on variation of weather factors.

PubMed

Li, Chenlu; Wang, Xiaofeng; Wu, Xiaoxu; Liu, Jianing; Ji, Duoying; Du, Juan

2017-12-15

Dengue fever is one of the most serious vector-borne infectious diseases, especially in Guangzhou, China. Dengue viruses and their vectors Aedes albopictus are sensitive to climate change primarily in relation to weather factors. Previous research has mainly focused on identifying the relationship between climate factors and dengue cases, or developing dengue case models with some non-climate factors. However, there has been little research addressing the modeling and projection of dengue cases only from the perspective of climate change. This study considered this topic using long time series data (1998-2014). First, sensitive weather factors were identified through meta-analysis that included literature review screening, lagged analysis, and collinear analysis. Then, key factors that included monthly average temperature at a lag of two months, and monthly average relative humidity and monthly average precipitation at lags of three months were determined. Second, time series Poisson analysis was used with the generalized additive model approach to develop a dengue model based on key weather factors for January 1998 to December 2012. Data from January 2013 to July 2014 were used to validate that the model was reliable and reasonable. Finally, future weather data (January 2020 to December 2070) were input into the model to project the occurrence of dengue cases under different climate scenarios (RCP 2.6 and RCP 8.5). Longer time series analysis and scientifically selected weather variables were used to develop a dengue model to ensure reliability. The projections suggested that seasonal disease control (especially in summer and fall) and mitigation of greenhouse gas emissions could help reduce the incidence of dengue fever. The results of this study hope to provide a scientifically theoretical basis for the prevention and control of dengue fever in Guangzhou. Copyright © 2017 Elsevier B.V. All rights reserved.

Exploration of the factor structure of the Kirton Adaption-Innovation Inventory using bootstrapping estimation.

PubMed

Im, Subin; Min, Soonhong

2013-04-01

Exploratory factor analyses of the Kirton Adaption-Innovation Inventory (KAI), which serves to measure individual cognitive styles, generally indicate three factors: sufficiency of originality, efficiency, and rule/group conformity. In contrast, a 2005 study by Im and Hu using confirmatory factor analysis supported a four-factor structure, dividing the sufficiency of originality dimension into two subdimensions, idea generation and preference for change. This study extends Im and Hu's (2005) study of a derived version of the KAI by providing additional evidence of the four-factor structure. Specifically, the authors test the robustness of the parameter estimates to the violation of normality assumptions in the sample using bootstrap methods. A bias-corrected confidence interval bootstrapping procedure conducted among a sample of 356 participants--members of the Arkansas Household Research Panel, with middle SES and average age of 55.6 yr. (SD = 13.9)--showed that the four-factor model with two subdimensions of sufficiency of originality fits the data significantly better than the three-factor model in non-normality conditions.

The effects of Wechsler Intelligence Scale for Children-Fourth Edition cognitive abilities on math achievement.

PubMed

Parkin, Jason R; Beaujean, A Alexander

2012-02-01

This study used structural equation modeling to examine the effect of Stratum III (i.e., general intelligence) and Stratum II (i.e., Comprehension-Knowledge, Fluid Reasoning, Short-Term Memory, Processing Speed, and Visual Processing) factors of the Cattell-Horn-Carroll (CHC) cognitive abilities, as operationalized by the Wechsler Intelligence Scale for Children, Fourth Edition (WISC-IV; Wechsler, 2003a) subtests, on Quantitative Knowledge, as operationalized by the Wechsler Individual Achievement Test, Second Edition (WIAT-II; Wechsler, 2002) subtests. Participants came from the WISC-IV/WIAT-II linking sample (n=550). We compared models that predicted Quantitative Knowledge using only Stratum III factors, only Stratum II factors, and both Stratum III and Stratum II factors. Results indicated that the model with only the Stratum III factor predicting Quantitative Knowledge best fit the data. Copyright © 2011 Society for the Study of School Psychology. Published by Elsevier Ltd. All rights reserved.

Modeling the Factors Associated with Children's Mental Health Difficulties in Primary School: A Multilevel Study

ERIC Educational Resources Information Center

Humphrey, Neil; Wigelsworth, Michael

2012-01-01

The current study explores some of the factors associated with children's mental health difficulties in primary school. Multilevel modeling with data from 628 children from 36 schools was used to determine how much variation in mental health difficulties exists between and within schools, and to identify characteristics at the school and…

Academic Risk Factors and Deficits of Learned Hopelessness: A Longitudinal Study of Hong Kong Secondary School Students

ERIC Educational Resources Information Center

Au, Raymond C. P.; Watkins, David A.; Hattie, John A. C.

2010-01-01

The aim of the present study is to explore a causal model of academic achievement and learning-related personal variables by testing the nature of relationships between learned hopelessness, its risk factors and hopelessness deficits as proposed in major theories in this area. The model investigates affective-motivational characteristics of…

Validation of a Four-Factor Model of Career Indecision

ERIC Educational Resources Information Center

Brown, Steven D.; Hacker, Jason; Abrams, Matthew; Carr, Andrea; Rector, Christopher; Lamp, Kristen; Telander, Kyle; Siena, Anne

2012-01-01

Two studies were designed to explore whether a meta-analytically derived four-factor model of career indecision (Brown & Rector, 2008) could be replicated at the primary and secondary data levels. In the first study, an initial pool of 167 items was written based on 35 different instruments whose scores had loaded saliently on at least one…

Factors Contributing to Research Team Effectiveness: Testing a Model of Team Effectiveness in an Academic Setting

ERIC Educational Resources Information Center

Omar, Zoharah; Ahmad, Aminah

2014-01-01

Following the classic systems model of inputs, processes, and outputs, this study examined the influence of three input factors, team climate, work overload, and team leadership, on research project team effectiveness as measured by publication productivity, team member satisfaction, and job frustration. This study also examined the mediating…

Development of Writing: Key Components of Written Language

ERIC Educational Resources Information Center

Kantor, Patricia Thatcher

2012-01-01

This study utilized confirmatory factor analyses and latent change score analyses to model individual and developmental differences in a longitudinal study of children's writing. Participants were 158 children who completed a writing sample each year from 1st through 4th grade. At all four time points, a four-factor model of writing provided…

Estimation of the cure rate in Iranian breast cancer patients.

PubMed

Rahimzadeh, Mitra; Baghestani, Ahmad Reza; Gohari, Mahmood Reza; Pourhoseingholi, Mohamad Amin

2014-01-01

Although the Cox's proportional hazard model is the popular approach for survival analysis to investigate significant risk factors of cancer patient survival, it is not appropriate in the case of log-term disease free survival. Recently, cure rate models have been introduced to distinguish between clinical determinants of cure and variables associated with the time to event of interest. The aim of this study was to use a cure rate model to determine the clinical associated factors for cure rates of patients with breast cancer (BC). This prospective cohort study covered 305 patients with BC, admitted at Shahid Faiazbakhsh Hospital, Tehran, during 2006 to 2008 and followed until April 2012. Cases of patient death were confirmed by telephone contact. For data analysis, a non-mixed cure rate model with Poisson distribution and negative binomial distribution were employed. All analyses were carried out using a developed Macro in WinBugs. Deviance information criteria (DIC) were employed to find the best model. The overall 1-year, 3-year and 5-year relative survival rates were 97%, 89% and 74%. Metastasis and stage of BC were the significant factors, but age was significant only in negative binomial model. The DIC also showed that the negative binomial model had a better fit. This study indicated that, metastasis and stage of BC were identified as the clinical criteria for cure rates. There are limited studies on BC survival which employed these cure rate models to identify the clinical factors associated with cure. These models are better than Cox, in the case of long-term survival.

Data assimilation for groundwater flow modelling using Unbiased Ensemble Square Root Filter: Case study in Guantao, North China Plain

NASA Astrophysics Data System (ADS)

Li, N.; Kinzelbach, W.; Li, H.; Li, W.; Chen, F.; Wang, L.

2017-12-01

Data assimilation techniques are widely used in hydrology to improve the reliability of hydrological models and to reduce model predictive uncertainties. This provides critical information for decision makers in water resources management. This study aims to evaluate a data assimilation system for the Guantao groundwater flow model coupled with a one-dimensional soil column simulation (Hydrus 1D) using an Unbiased Ensemble Square Root Filter (UnEnSRF) originating from the Ensemble Kalman Filter (EnKF) to update parameters and states, separately or simultaneously. To simplify the coupling between unsaturated and saturated zone, a linear relationship obtained from analyzing inputs to and outputs from Hydrus 1D is applied in the data assimilation process. Unlike EnKF, the UnEnSRF updates parameter ensemble mean and ensemble perturbations separately. In order to keep the ensemble filter working well during the data assimilation, two factors are introduced in the study. One is called damping factor to dampen the update amplitude of the posterior ensemble mean to avoid nonrealistic values. The other is called inflation factor to relax the posterior ensemble perturbations close to prior to avoid filter inbreeding problems. The sensitivities of the two factors are studied and their favorable values for the Guantao model are determined. The appropriate observation error and ensemble size were also determined to facilitate the further analysis. This study demonstrated that the data assimilation of both model parameters and states gives a smaller model prediction error but with larger uncertainty while the data assimilation of only model states provides a smaller predictive uncertainty but with a larger model prediction error. Data assimilation in a groundwater flow model will improve model prediction and at the same time make the model converge to the true parameters, which provides a successful base for applications in real time modelling or real time controlling strategies in groundwater resources management.

Biotic and abiotic factors predicting the global distribution and population density of an invasive large mammal

PubMed Central

Lewis, Jesse S.; Farnsworth, Matthew L.; Burdett, Chris L.; Theobald, David M.; Gray, Miranda; Miller, Ryan S.

2017-01-01

Biotic and abiotic factors are increasingly acknowledged to synergistically shape broad-scale species distributions. However, the relative importance of biotic and abiotic factors in predicting species distributions is unclear. In particular, biotic factors, such as predation and vegetation, including those resulting from anthropogenic land-use change, are underrepresented in species distribution modeling, but could improve model predictions. Using generalized linear models and model selection techniques, we used 129 estimates of population density of wild pigs (Sus scrofa) from 5 continents to evaluate the relative importance, magnitude, and direction of biotic and abiotic factors in predicting population density of an invasive large mammal with a global distribution. Incorporating diverse biotic factors, including agriculture, vegetation cover, and large carnivore richness, into species distribution modeling substantially improved model fit and predictions. Abiotic factors, including precipitation and potential evapotranspiration, were also important predictors. The predictive map of population density revealed wide-ranging potential for an invasive large mammal to expand its distribution globally. This information can be used to proactively create conservation/management plans to control future invasions. Our study demonstrates that the ongoing paradigm shift, which recognizes that both biotic and abiotic factors shape species distributions across broad scales, can be advanced by incorporating diverse biotic factors. PMID:28276519

Mind the Gap! A Multilevel Analysis of Factors Related to Variation in Published Cost-Effectiveness Estimates within and between Countries

PubMed Central

Boehler, Christian E. H.; Lord, Joanne

2016-01-01

Background. Published cost-effectiveness estimates can vary considerably, both within and between countries. Despite extensive discussion, little is known empirically about factors relating to these variations. Objectives. To use multilevel statistical modeling to integrate cost-effectiveness estimates from published economic evaluations to investigate potential causes of variation. Methods. Cost-effectiveness studies of statins for cardiovascular disease prevention were identified by systematic review. Estimates of incremental costs and effects were extracted from reported base case, sensitivity, and subgroup analyses, with estimates grouped in studies and in countries. Three bivariate models were developed: a cross-classified model to accommodate data from multinational studies, a hierarchical model with multinational data allocated to a single category at country level, and a hierarchical model excluding multinational data. Covariates at different levels were drawn from a long list of factors suggested in the literature. Results. We found 67 studies reporting 2094 cost-effectiveness estimates relating to 23 countries (6 studies reporting for more than 1 country). Data and study-level covariates included patient characteristics, intervention and comparator cost, and some study methods (e.g., discount rates and time horizon). After adjusting for these factors, the proportion of variation attributable to countries was negligible in the cross-classified model but moderate in the hierarchical models (14%−19% of total variance). Country-level variables that improved the fit of the hierarchical models included measures of income and health care finance, health care resources, and population risks. Conclusions. Our analysis suggested that variability in published cost-effectiveness estimates is related more to differences in study methods than to differences in national context. Multinational studies were associated with much lower country-level variation than single-country studies. These findings are for a single clinical question and may be atypical. PMID:25878194

Using agent-based modeling to study multiple risk factors and multiple health outcomes at multiple levels.

PubMed

Yang, Yong

2017-11-01

Most health studies focus on one health outcome and examine the influence of one or multiple risk factors. However, in reality, various pathways, interactions, and associations exist not only between risk factors and health outcomes but also among the risk factors and among health outcomes. The advance of system science methods, Big Data, and accumulated knowledge allows us to examine how multiple risk factors influence multiple health outcomes at multiple levels (termed a 3M study). Using the study of neighborhood environment and health as an example, I elaborate on the significance of 3M studies. 3M studies may lead to a significantly deeper understanding of the dynamic interactions among risk factors and outcomes and could help us design better interventions that may be of particular relevance for upstream interventions. Agent-based modeling (ABM) is a promising method in the 3M study, although its potentials are far from being fully explored. Future challenges include the gap of epidemiologic knowledge and evidence, lack of empirical data sources, and the technical challenges of ABM. © 2017 New York Academy of Sciences.

Understanding Group/Party Affiliation Using Social Networks and Agent-Based Modeling

NASA Technical Reports Server (NTRS)

Campbell, Kenyth

2012-01-01

The dynamics of group affiliation and group dispersion is a concept that is most often studied in order for political candidates to better understand the most efficient way to conduct their campaigns. While political campaigning in the United States is a very hot topic that most politicians analyze and study, the concept of group/party affiliation presents its own area of study that producers very interesting results. One tool for examining party affiliation on a large scale is agent-based modeling (ABM), a paradigm in the modeling and simulation (M&S) field perfectly suited for aggregating individual behaviors to observe large swaths of a population. For this study agent based modeling was used in order to look at a community of agents and determine what factors can affect the group/party affiliation patterns that are present. In the agent-based model that was used for this experiment many factors were present but two main factors were used to determine the results. The results of this study show that it is possible to use agent-based modeling to explore group/party affiliation and construct a model that can mimic real world events. More importantly, the model in the study allows for the results found in a smaller community to be translated into larger experiments to determine if the results will remain present on a much larger scale.

The Benefits of Including Clinical Factors in Rectal Normal Tissue Complication Probability Modeling After Radiotherapy for Prostate Cancer

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

Defraene, Gilles, E-mail: gilles.defraene@uzleuven.be; Van den Bergh, Laura; Al-Mamgani, Abrahim

2012-03-01

Purpose: To study the impact of clinical predisposing factors on rectal normal tissue complication probability modeling using the updated results of the Dutch prostate dose-escalation trial. Methods and Materials: Toxicity data of 512 patients (conformally treated to 68 Gy [n = 284] and 78 Gy [n = 228]) with complete follow-up at 3 years after radiotherapy were studied. Scored end points were rectal bleeding, high stool frequency, and fecal incontinence. Two traditional dose-based models (Lyman-Kutcher-Burman (LKB) and Relative Seriality (RS) and a logistic model were fitted using a maximum likelihood approach. Furthermore, these model fits were improved by including themore » most significant clinical factors. The area under the receiver operating characteristic curve (AUC) was used to compare the discriminating ability of all fits. Results: Including clinical factors significantly increased the predictive power of the models for all end points. In the optimal LKB, RS, and logistic models for rectal bleeding and fecal incontinence, the first significant (p = 0.011-0.013) clinical factor was 'previous abdominal surgery.' As second significant (p = 0.012-0.016) factor, 'cardiac history' was included in all three rectal bleeding fits, whereas including 'diabetes' was significant (p = 0.039-0.048) in fecal incontinence modeling but only in the LKB and logistic models. High stool frequency fits only benefitted significantly (p = 0.003-0.006) from the inclusion of the baseline toxicity score. For all models rectal bleeding fits had the highest AUC (0.77) where it was 0.63 and 0.68 for high stool frequency and fecal incontinence, respectively. LKB and logistic model fits resulted in similar values for the volume parameter. The steepness parameter was somewhat higher in the logistic model, also resulting in a slightly lower D{sub 50}. Anal wall DVHs were used for fecal incontinence, whereas anorectal wall dose best described the other two endpoints. Conclusions: Comparable prediction models were obtained with LKB, RS, and logistic NTCP models. Including clinical factors improved the predictive power of all models significantly.« less

Conceptual design and analysis of a dynamic scale model of the Space Station Freedom

NASA Technical Reports Server (NTRS)

Davis, D. A.; Gronet, M. J.; Tan, M. K.; Thorne, J.

1994-01-01

This report documents the conceptual design study performed to evaluate design options for a subscale dynamic test model which could be used to investigate the expected on-orbit structural dynamic characteristics of the Space Station Freedom early build configurations. The baseline option was a 'near-replica' model of the SSF SC-7 pre-integrated truss configuration. The approach used to develop conceptual design options involved three sets of studies: evaluation of the full-scale design and analysis databases, conducting scale factor trade studies, and performing design sensitivity studies. The scale factor trade study was conducted to develop a fundamental understanding of the key scaling parameters that drive design, performance and cost of a SSF dynamic scale model. Four scale model options were estimated: 1/4, 1/5, 1/7, and 1/10 scale. Prototype hardware was fabricated to assess producibility issues. Based on the results of the study, a 1/4-scale size is recommended based on the increased model fidelity associated with a larger scale factor. A design sensitivity study was performed to identify critical hardware component properties that drive dynamic performance. A total of 118 component properties were identified which require high-fidelity replication. Lower fidelity dynamic similarity scaling can be used for non-critical components.

Confirmatory factor analysis of the Child Oral Health Impact Profile (Korean version).

PubMed

Cho, Young Il; Lee, Soonmook; Patton, Lauren L; Kim, Hae-Young

2016-04-01

Empirical support for the factor structure of the Child Oral Health Impact Profile (COHIP) has not been fully established. The purposes of this study were to evaluate the factor structure of the Korean version of the COHIP (COHIP-K) empirically using confirmatory factor analysis (CFA) based on the theoretical framework and then to assess whether any of the factors in the structure could be grouped into a simpler single second-order factor. Data were collected through self-reported COHIP-K responses from a representative community sample of 2,236 Korean children, 8-15 yr of age. Because a large inter-factor correlation of 0.92 was estimated in the original five-factor structure, the two strongly correlated factors were combined into one factor, resulting in a four-factor structure. The revised four-factor model showed a reasonable fit with appropriate inter-factor correlations. Additionally, the second-order model with four sub-factors was reasonable with sufficient fit and showed equal fit to the revised four-factor model. A cross-validation procedure confirmed the appropriateness of the findings. Our analysis empirically supported a four-factor structure of COHIP-K, a summarized second-order model, and the use of an integrated summary COHIP score. © 2016 Eur J Oral Sci.

Modeling conflict : research methods, quantitative modeling, and lessons learned.

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

Rexroth, Paul E.; Malczynski, Leonard A.; Hendrickson, Gerald A.

2004-09-01

This study investigates the factors that lead countries into conflict. Specifically, political, social and economic factors may offer insight as to how prone a country (or set of countries) may be for inter-country or intra-country conflict. Largely methodological in scope, this study examines the literature for quantitative models that address or attempt to model conflict both in the past, and for future insight. The analysis concentrates specifically on the system dynamics paradigm, not the political science mainstream approaches of econometrics and game theory. The application of this paradigm builds upon the most sophisticated attempt at modeling conflict as a resultmore » of system level interactions. This study presents the modeling efforts built on limited data and working literature paradigms, and recommendations for future attempts at modeling conflict.« less

General principles of institutional risks influence on pension systems

NASA Astrophysics Data System (ADS)

Nepp, A. N.; Shilkov, A. A.; Sheveleva, A. Y.; Mamedbakov, M. R.

2016-12-01

This paper examines the tools used to study the influence of institutional factors on investment returns. The research object are the tools used in the evaluation of institutional risks in the pension system, in particular, the correlation model of factors impacting on the `anti-director' index, econometric estimates combining the different determinants of savings, the model of endogenous institutional change, etc. Research work focusing on issues of institutional factors affecting pension systems (authored by La Porta, Guiso, Gianetti, El-Mekkaouide Freitas, Neyapti B., and others) is reviewed. The model is examined in terms of the impact of institutional risks on pension systems, especially with regard to the funded part. The study identified the following factors that affect financial institutions, including pension institutions: management quality, regulation quality, rule of law, political stability, and corruption control.

Risk factors for pressure ulcer development in critically Ill patients: a conceptual model to guide research.

PubMed

Benoit, Richard; Mion, Lorraine

2012-08-01

This paper presents a proposed conceptual model to guide research on pressure ulcer risk in critically ill patients, who are at high risk for pressure ulcer development. However, no conceptual model exists that guides risk assessment in this population. Results from a review of prospective studies were evaluated for design quality and level of statistical reporting. Multivariate findings from studies having high or medium design quality by the National Institute of Health and Clinical Excellence standards were conceptually grouped. The conceptual groupings were integrated into Braden and Bergstrom's (Braden and Bergstrom [1987] Rehabilitation Nursing, 12, 8-12, 16) conceptual model, retaining their original constructs and augmenting their concept of intrinsic factors for tissue tolerance. The model could enhance consistency in research on pressure ulcer risk factors. Copyright © 2012 Wiley Periodicals, Inc.

A structural equation modelling approach examining the pathways between safety climate, behaviour performance and workplace slipping

PubMed Central

Swedler, David I; Verma, Santosh K; Huang, Yueng-Hsiang; Lombardi, David A; Chang, Wen-Ruey; Brennan, Melayne; Courtney, Theodore K

2015-01-01

Objective Safety climate has previously been associated with increasing safe workplace behaviours and decreasing occupational injuries. This study seeks to understand the structural relationship between employees’ perceptions of safety climate, performing a safety behaviour (ie, wearing slip-resistant shoes) and risk of slipping in the setting of limited-service restaurants. Methods At baseline, we surveyed 349 employees at 30 restaurants for their perceptions of their safety training and management commitment to safety as well as demographic data. Safety performance was identified as wearing slip-resistant shoes, as measured by direct observation by the study team. We then prospectively collected participants’ hours worked and number of slips weekly for the next 12 weeks. Using a confirmatory factor analysis, we modelled safety climate as a higher order factor composed of previously identified training and management commitment factors. Results The 349 study participants experienced 1075 slips during the 12-week follow-up. Confirmatory factor analysis supported modelling safety climate as a higher order factor composed of safety training and management commitment. In a structural equation model, safety climate indirectly affected prospective risk of slipping through safety performance, but no direct relationship between safety climate and slips was evident. Conclusions Results suggest that safety climate can reduce workplace slips through performance of a safety behaviour as well as suggesting a potential causal mechanism through which safety climate can reduce workplace injuries. Safety climate can be modelled as a higher order factor composed of safety training and management commitment. PMID:25710968

Development and Examination of a Family Triadic Measure to Examine Quality of Life Family Congruence in Nursing Home Residents and Two Family Members.

PubMed

Aalgaard Kelly, Gina

2015-01-01

Objective: The overall purpose of this study was to propose and test a conceptual model and apply family analyses methods to understand quality of life family congruence in the nursing home setting. Method: Secondary data for this study were from a larger study, titled Measurement, Indicators and Improvement of the Quality of Life (QOL) in Nursing Homes . Research literature, family systems theory and human ecological assumptions, fostered the conceptual model empirically testing quality of life family congruence. Results: The study results supported a model examining nursing home residents and two family members on quality of life family congruence. Specifically, family intergenerational dynamic factors, resident personal and social-psychological factors, and nursing home family input factors were examined to identify differences in quality of life family congruence among triad families. Discussion: Formal family involvement and resident cognitive functioning were found as the two most influential factors to quality of life family congruence (QOLFC).

Development and Examination of a Family Triadic Measure to Examine Quality of Life Family Congruence in Nursing Home Residents and Two Family Members

PubMed Central

Aalgaard Kelly, Gina

2015-01-01

Objective: The overall purpose of this study was to propose and test a conceptual model and apply family analyses methods to understand quality of life family congruence in the nursing home setting. Method: Secondary data for this study were from a larger study, titled Measurement, Indicators and Improvement of the Quality of Life (QOL) in Nursing Homes. Research literature, family systems theory and human ecological assumptions, fostered the conceptual model empirically testing quality of life family congruence. Results: The study results supported a model examining nursing home residents and two family members on quality of life family congruence. Specifically, family intergenerational dynamic factors, resident personal and social-psychological factors, and nursing home family input factors were examined to identify differences in quality of life family congruence among triad families. Discussion: Formal family involvement and resident cognitive functioning were found as the two most influential factors to quality of life family congruence (QOLFC). PMID:28138474

Psychosocial work factors and social inequalities in psychological distress: a population-based study.

PubMed

Duchaine, Caroline S; Ndjaboué, Ruth; Levesque, Manon; Vézina, Michel; Trudel, Xavier; Gilbert-Ouimet, Mahée; Dionne, Clermont E; Mâsse, Benoît; Pearce, Neil; Brisson, Chantal

2017-01-18

Mental health problems (MHP) are the leading cause of disability worldwide. The inverse association between socioeconomic position (SEP) and MHP has been well documented. There is prospective evidence that factors from the work environment, including adverse psychosocial work factors, could contribute to the development of MHP including psychological distress. However, the contribution of psychosocial work factors to social inequalities in MHP remains unclear. This study evaluates the contribution of psychosocial work factors from two highly supported models, the Demand-Control-Support (DCS) and the Effort-Reward Imbalance (ERI) models to SEP inequalities of psychological distress in men and women from a population-based sample of Quebec workers. Data were collected during a survey on working conditions, health and safety at work. SEP was evaluated using education, occupation and household income. Psychosocial work factors and psychological distress were assessed using validated instruments. Mean differences (MD) in the score of psychological distress were estimated separately for men and women. Low education level and low household income were associated with psychological distress among men (MD, 0.56 (95% CI 0.06; 1.05) and 1.26 (95% CI 0.79; 1.73) respectively). In men, the contribution of psychosocial work factors from the DCS and the ERI models to the association between household income and psychological distress ranged from 9% to 24%. No clear inequalities were observed among women. These results suggest that psychosocial work factors from the DCS and the ERI models contribute to explain a part of social inequalities in psychological distress among men. Psychosocial factors at work are frequent and modifiable. The present study supports the relevance of targeting these factors for the primary prevention of MHP and for health policies aiming to reduce social inequalities in mental health.

Applying spatial regression to evaluate risk factors for microbiological contamination of urban groundwater sources in Juba, South Sudan

NASA Astrophysics Data System (ADS)

Engström, Emma; Mörtberg, Ulla; Karlström, Anders; Mangold, Mikael

2017-06-01

This study developed methodology for statistically assessing groundwater contamination mechanisms. It focused on microbial water pollution in low-income regions. Risk factors for faecal contamination of groundwater-fed drinking-water sources were evaluated in a case study in Juba, South Sudan. The study was based on counts of thermotolerant coliforms in water samples from 129 sources, collected by the humanitarian aid organisation Médecins Sans Frontières in 2010. The factors included hydrogeological settings, land use and socio-economic characteristics. The results showed that the residuals of a conventional probit regression model had a significant positive spatial autocorrelation (Moran's I = 3.05, I-stat = 9.28); therefore, a spatial model was developed that had better goodness-of-fit to the observations. The most significant factor in this model ( p-value 0.005) was the distance from a water source to the nearest Tukul area, an area with informal settlements that lack sanitation services. It is thus recommended that future remediation and monitoring efforts in the city be concentrated in such low-income regions. The spatial model differed from the conventional approach: in contrast with the latter case, lowland topography was not significant at the 5% level, as the p-value was 0.074 in the spatial model and 0.040 in the traditional model. This study showed that statistical risk-factor assessments of groundwater contamination need to consider spatial interactions when the water sources are located close to each other. Future studies might further investigate the cut-off distance that reflects spatial autocorrelation. Particularly, these results advise research on urban groundwater quality.

[Confirmative study of a French version of the Exercise Dependence Scale-revised with a French population].

PubMed

Allegre, B; Therme, P

2008-10-01

Since the first writings on excessive exercise, there has been an increased interest in exercise dependence. One of the major consequences of this increased interest has been the development of several definitions and measures of exercise dependence. The work of Veale [Does primary exercise dependence really exist? In: Annet J, Cripps B, Steinberg H, editors. Exercise addiction: Motivation for participation in sport and exercise.Leicester, UK: Br Psychol Soc; 1995. p. 1-5.] provides an advance for the definition and measure of exercise dependence. These studies have adapted the DSM-IV criteria for substance dependence to measure exercise dependence. The Exercise Dependence Scale-Revised is based on these diagnostic criteria, which are: tolerance; withdrawal effects; intention effect; lack of control; time; reductions in other activities; continuance. Confirmatory factor analyses of EDS-R provided support to present a measurement model (21 items loaded in seven factors) of EDS-R (Comparative Fit Index=0.97; Root mean Square Error of Approximation=0.05; Tucker-Lewis Index=0.96). The aim of this study was to examine the psychometric properties of a French version of the EDS-R [Factorial validity and psychometric examination of the exercise dependence scale-revised. Meas Phys Educ Exerc Sci 2004;8(4):183-201.] to test the stability of the seven-factor model of the original version with a French population. A total of 516 half-marathoners ranged in age from 17 to 74 years old (Mean age=39.02 years, ET=10.64), with 402 men (77.9%) and 114 women (22.1%) participated in the study. The principal component analysis results in a six-factor structure, which accounts for 68.60% of the total variance. Because principal component analysis presents a six-factor structure differing from the original seven-factor structure, two models were tested, using confirmatory factor analysis. The first model is the seven-factor model of the original version of the EDS-R and the second is the model produced by the principal component analysis. The results of confirmatory factor analysis presented the original model (with a seven-factor structure) as a good model and fit indices were good (X(2)/ddl=2.89, Root Mean Square Error of Approximation (RMSEA)=0.061, Expected Cross Validation Index (ECVI)=1.20, Goodness-of-Fit Index (GFI)=0.92, Comparative Fit Index (CFI)=0.94, Standardized Root Mean Square (SRMS)=0.048). These results showed that the French version of EDS-R has an identical factor structure to the original. Therefore, the French version of EDS-R was an acceptable scale to measure exercise dependence and can be used on a French population.

Longitudinal tests of competing factor structures for the Rosenberg Self-Esteem Scale: traits, ephemeral artifacts, and stable response styles.

PubMed

Marsh, Herbert W; Scalas, L Francesca; Nagengast, Benjamin

2010-06-01

Self-esteem, typically measured by the Rosenberg Self-Esteem Scale (RSE), is one of the most widely studied constructs in psychology. Nevertheless, there is broad agreement that a simple unidimensional factor model, consistent with the original design and typical application in applied research, does not provide an adequate explanation of RSE responses. However, there is no clear agreement about what alternative model is most appropriate-or even a clear rationale for how to test competing interpretations. Three alternative interpretations exist: (a) 2 substantively important trait factors (positive and negative self-esteem), (b) 1 trait factor and ephemeral method artifacts associated with positively or negatively worded items, or (c) 1 trait factor and stable response-style method factors associated with item wording. We have posited 8 alternative models and structural equation model tests based on longitudinal data (4 waves of data across 8 years with a large, representative sample of adolescents). Longitudinal models provide no support for the unidimensional model, undermine support for the 2-factor model, and clearly refute claims that wording effects are ephemeral, but they provide good support for models positing 1 substantive (self-esteem) factor and response-style method factors that are stable over time. This longitudinal methodological approach has not only resolved these long-standing issues in self-esteem research but also has broad applicability to most psychological assessments based on self-reports with a mix of positively and negatively worded items.

Bayesian inference of the number of factors in gene-expression analysis: application to human virus challenge studies.

PubMed

Chen, Bo; Chen, Minhua; Paisley, John; Zaas, Aimee; Woods, Christopher; Ginsburg, Geoffrey S; Hero, Alfred; Lucas, Joseph; Dunson, David; Carin, Lawrence

2010-11-09

Nonparametric Bayesian techniques have been developed recently to extend the sophistication of factor models, allowing one to infer the number of appropriate factors from the observed data. We consider such techniques for sparse factor analysis, with application to gene-expression data from three virus challenge studies. Particular attention is placed on employing the Beta Process (BP), the Indian Buffet Process (IBP), and related sparseness-promoting techniques to infer a proper number of factors. The posterior density function on the model parameters is computed using Gibbs sampling and variational Bayesian (VB) analysis. Time-evolving gene-expression data are considered for respiratory syncytial virus (RSV), Rhino virus, and influenza, using blood samples from healthy human subjects. These data were acquired in three challenge studies, each executed after receiving institutional review board (IRB) approval from Duke University. Comparisons are made between several alternative means of per-forming nonparametric factor analysis on these data, with comparisons as well to sparse-PCA and Penalized Matrix Decomposition (PMD), closely related non-Bayesian approaches. Applying the Beta Process to the factor scores, or to the singular values of a pseudo-SVD construction, the proposed algorithms infer the number of factors in gene-expression data. For real data the "true" number of factors is unknown; in our simulations we consider a range of noise variances, and the proposed Bayesian models inferred the number of factors accurately relative to other methods in the literature, such as sparse-PCA and PMD. We have also identified a "pan-viral" factor of importance for each of the three viruses considered in this study. We have identified a set of genes associated with this pan-viral factor, of interest for early detection of such viruses based upon the host response, as quantified via gene-expression data.

Job strain (demands and control model) as a predictor of cardiovascular risk factors among petrochemical personnel

PubMed Central

Habibi, Ehsanollah; Poorabdian, Siamak; Shakerian, Mahnaz

2015-01-01

Background: One of the practical models for the assessment of stressful working conditions due to job strain is job demand and control model, which explains how physical and psychological adverse consequences, including cardiovascular risk factors can be established due to high work demands (the amount of workload, in addition to time limitations to complete that work) and low control of the worker on his/her work (lack of decision making) in the workplace. The aim of this study was to investigate how certain cardiovascular risk factors (including body mass index [BMI], heart rate, blood pressure, cholesterol and smoking) and the job demand and job control are related to each other. Materials and Methods: This prospective cohort study was conducted on 500 workers of the petrochemical industry in south of Iran, 2009. The study population was selected using simple random statistical method. They completed job demand and control questionnaire. The cardiovascular risk factors data was extracted from the workers hygiene profiles. Chi-square (χ2) test and hypothesis test (η) were used to assess the possible relationship between different quantified variables, individual demographic and cardiovascular risk factors. Results: The results of this study revealed that a significant relationship can be found between job demand control model and cardiovascular risk factors. Chi-square test result for the heart rate showed the highest (χ2 = 145.078) relationship, the corresponding results for smoking and BMI were χ2 = 85.652 and χ2 = 30.941, respectively. Subsequently, hypothesis testing results for cholesterol and hypertension was 0.469 and 0.684, respectively. Discussion: Job strain is likely to be associated with an increased risk of cardiovascular risk factors among male staff in a petrochemical company in Iran. The parameters illustrated in the Job demands and control model can act as acceptable predictors for the probability of job stress occurrence followed by showing a high trend of CVD risk factors. PMID:25861661

Latent class analysis of factors that influence weekday and weekend single-vehicle crash severities.

PubMed

Adanu, Emmanuel Kofi; Hainen, Alexander; Jones, Steven

2018-04-01

This paper investigates factors that influence the severity of single-vehicle crashes that happen on weekdays and weekends. Crash data from 2012 to 2016 for the State of Alabama was used for this study. Latent class logit models were developed as alternative to the frequently used random parameters models to account for unobserved heterogeneity across crash-severity observations. Exploration of the data revealed that a high proportion of severe injury injury crashes happened on weekends. The study examined whether single-vehicle crash contributing factors differ between weekdays and weekends. The model estimation results indicate a significant association of severe injury crashes to risk factors such as driver unemployment, driving with invalid license, no seatbelt use, fatigue, driving under influence, old age, and driving on county roads for both weekdays and weekends. Research findings show a strong link between human factors and the occurrence of severe injury single-vehicle crashes, as it has been observed that many of the factors associated with severe-injury outcome are driver behavior related. To illustrate the significance of the findings of this study, a third model using the combined data was developed to explore the merit of using sub-populations of the data for improved and detailed segmentation of the crash-severity factors. It has also been shown that generally, the factors that influence single-vehicle crash injury outcomes were not very different between weekdays and weekends. The findings of this study show the importance of investigating sub-populations of data to reveal complex relationships that should be understood as a necessary step in targeted countermeasure application. Copyright © 2018 Elsevier Ltd. All rights reserved.

The use of the bi-factor model to test the uni-dimensionality of a battery of reasoning tests.

PubMed

Primi, Ricardo; Rocha da Silva, Marjorie Cristina; Rodrigues, Priscila; Muniz, Monalisa; Almeida, Leandro S

2013-02-01

The Battery of Reasoning Tests 5 (BPR-5) aims to assess the reasoning ability of individuals, using sub-tests with different formats and contents that require basic processes of inductive and deductive reasoning for their resolution. The BPR has three sequential forms: BPR-5i (for children from first to fifth grade), BPR-5 - Form A (for children from sixth to eighth grade) and BPR-5 - form B (for high school and undergraduate students). The present study analysed 412 questionnaires concerning BPR-5i, 603 questionnaires concerning BPR-5 - Form A and 1748 questionnaires concerning BPR-5 - Form B. The main goal was to test the uni-dimensionality of the battery and its tests in relation to items using the bi-factor model. Results suggest that the g factor loadings (extracted by the uni-dimensional model) do not change when the data is adjusted for a more flexible multi-factor model (bi-factor model). A general reasoning factor underlying different contents items is supported.

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

PubMed

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

2016-01-01

The best structural model for attention-deficit/hyperactivity disorder (ADHD) symptoms remains a matter of debate. The objective of this study is to test the fit and factor reliability of competing models of the dimensional structure of ADHD symptoms in a sample of randomly selected and high-risk children and pre-adolescents from Brazil. Our sample comprised 2512 children aged 6-12 years from 57 schools in Brazil. The ADHD symptoms were assessed using parent report on the development and well-being assessment (DAWBA). Fit indexes from confirmatory factor analysis were used to test unidimensional, correlated, and bifactor models of ADHD, the latter including "g" ADHD and "s" symptom domain factors. Reliability of all models was measured with omega coefficients. A bifactor model with one general factor and three specific factors (inattention, hyperactivity, impulsivity) exhibited the best fit to the data, according to fit indices, as well as the most consistent factor loadings. However, based on omega reliability statistics, the specific inattention, hyperactivity, and impulsivity dimensions provided very little reliable information after accounting for the reliable general ADHD factor. Our study presents some psychometric evidence that ADHD specific ("s") factors might be unreliable after taking common ("g" factor) variance into account. These results are in accordance with the lack of longitudinal stability among subtypes, the absence of dimension-specific molecular genetic findings and non-specific effects of treatment strategies. Therefore, researchers and clinicians might most effectively rely on the "g" ADHD to characterize ADHD dimensional phenotype, based on currently available symptom items.

Factor structure of the Childhood Autism Rating Scale as per DSM-5.

PubMed

Park, Eun-Young; Kim, Joungmin

2016-02-01

The DSM-5 recently proposed new diagnostic criteria for autism spectrum disorder (ASD). Although many new or updated tools have been developed since the DSM-IV was published in 1994, the Childhood Autism Rating Scale (CARS) has been used consistently in ASD diagnosis and research due to its technical adequacy, cost-effectiveness, and practicality. Additionally, items in the CARS did not alter following the release of the revised DSM-IV because the CARS factor structure was found to be consistent with the revised criteria after factor analysis. For that reason, in this study confirmatory factor analysis was used to identify the factor structure of the CARS. Participants (n = 150) consisted of children with an ASD diagnosis or who met the criteria for broader autism or emotional/behavior disorder with comorbid disorders such as attention-deficit hyperactivity disorder, bipolar disorder, intellectual or developmental disabilities. Previous studies used one-, two-, and four-factor models, all of which we examined to confirm the best-fit model on confirmatory factor analysis. Appropriate comparative fit indices and root mean square errors were obtained for all four models. The two-factor model, based on DSM-5 criteria, was the most valid and reliable. The inter-item consistency of the CARS was 0.926 and demonstrated adequate reliability, thereby supporting the validity and reliability of the two-factor model of CARS. Although CARS was developed prior to the introduction of DSM-5, its psychometric properties, conceptual relevance, and flexible administration procedures support its continued role as a screening device in the diagnostic decision-making process. © 2015 Japan Pediatric Society.

Developing a dimensional model for successful cognitive and emotional aging.

PubMed

Vahia, Ipsit V; Thompson, Wesley K; Depp, Colin A; Allison, Matthew; Jeste, Dilip V

2012-04-01

There is currently a lack of consensus on the definition of successful aging (SA) and existing implementations have omitted constructs associated with SA. We used empirical methods to develop a dimensional model of SA that incorporates a wider range of associated variables, and we examined the relationship among these components using factor analysis and Bayesian Belief Nets. We administered a successful aging questionnaire comprising several standardized measures related to SA to a sample of 1948 older women enrolled in the San Diego site of the Women's Health Initiative study. The SA-related variables we included in the model were self-rated successful aging, depression severity, physical and emotional functioning, optimism, resilience, attitude towards own aging, self-efficacy, and cognitive ability. After adjusting for age, education and income, we fitted an exploratory factor analysis model to the SA-related variables and then, in order to address relationships among these factors, we computed a Bayesian Belief Net (BBN) using rotated factor scores. The SA-related variables loaded onto five factors. Based on the loading, we labeled the factors as follows: self-rated successful aging, cognition, psychosocial protective factors, physical functioning, and emotional functioning. In the BBN, self-rated successful aging emerged as the primary downstream factor and exhibited significant partial correlations with psychosocial protective factors, physical/general status and mental/emotional status but not with cognitive ability. Our study represents a step forward in developing a dimensional model of SA. Our findings also point to a potential role for psychiatry in improving successful aging by managing depressive symptoms and developing psychosocial interventions to improve self-efficacy, resilience, and optimism.

Examining General and Specific Factors in the Dimensionality of Oral Language and Reading in 4th–10th Grades

PubMed Central

Foorman, Barbara R.; Koon, Sharon; Petscher, Yaacov; Mitchell, Alison; Truckenmiller, Adrea

2015-01-01

The objective of this study was to explore dimensions of oral language and reading and their influence on reading comprehension in a relatively understudied population—adolescent readers in 4th through 10th grades. The current study employed latent variable modeling of decoding fluency, vocabulary, syntax, and reading comprehension so as to represent these constructs with minimal error and to examine whether residual variance unaccounted for by oral language can be captured by specific factors of syntax and vocabulary. A 1-, 3-, 4-, and bifactor model were tested with 1,792 students in 18 schools in 2 large urban districts in the Southeast. Students were individually administered measures of expressive and receptive vocabulary, syntax, and decoding fluency in mid-year. At the end of the year students took the state reading test as well as a group-administered, norm-referenced test of reading comprehension. The bifactor model fit the data best in all 7 grades and explained 72% to 99% of the variance in reading comprehension. The specific factors of syntax and vocabulary explained significant unique variance in reading comprehension in 1 grade each. The decoding fluency factor was significantly correlated with the reading comprehension and oral language factors in all grades, but, in the presence of the oral language factor, was not significantly associated with the reading comprehension factor. Results support a bifactor model of lexical knowledge rather than the 3-factor model of the Simple View of Reading, with the vast amount of variance in reading comprehension explained by a general oral language factor. PMID:26346839

Understanding clinician attitudes towards implementation of guided self-help cognitive behaviour therapy for those who hear distressing voices: using factor analysis to test normalisation process theory.

PubMed

Hazell, Cassie M; Strauss, Clara; Hayward, Mark; Cavanagh, Kate

2017-07-24

The Normalisation Process Theory (NPT) has been used to understand the implementation of physical health care interventions. The current study aims to apply the NPT model to a secondary mental health context, and test the model using exploratory factor analysis. This study will consider the implementation of a brief cognitive behaviour therapy for psychosis (CBTp) intervention. Mental health clinicians were asked to complete a NPT-based questionnaire on the implementation of a brief CBTp intervention. All clinicians had experience of either working with the target client group or were able to deliver psychological therapies. In total, 201 clinicians completed the questionnaire. The results of the exploratory factor analysis found partial support for the NPT model, as three of the NPT factors were extracted: (1) coherence, (2) cognitive participation, and (3) reflexive monitoring. We did not find support for the fourth NPT factor (collective action). All scales showed strong internal consistency. Secondary analysis of these factors showed clinicians to generally support the implementation of the brief CBTp intervention. This study provides strong evidence for the validity of the three NPT factors extracted. Further research is needed to determine whether participants' level of seniority moderates factor extraction, whether this factor structure can be generalised to other healthcare settings, and whether pre-implementation attitudes predict actual implementation outcomes.

Using a Market Ratio Factor in Faculty Salary Equity Studies. AIR Professional File. Number 103, Spring 2007

ERIC Educational Resources Information Center

Luna, Andrew L.

2007-01-01

The purpose of this study was to determine if a market ratio factor was a better predictor of faculty salaries than the use of k-1 dummy variables representing the various disciplines. This study used two multiple regression analyses to develop an explanatory model to determine which model might best explain faculty salaries. A total of 20 out of…

A Time Series Analysis: Weather Factors, Human Migration and Malaria Cases in Endemic Area of Purworejo, Indonesia, 2005–2014

PubMed Central

REJEKI, Dwi Sarwani Sri; NURHAYATI, Nunung; AJI, Budi; MURHANDARWATI, E. Elsa Herdiana; KUSNANTO, Hari

2018-01-01

Background: Climatic and weather factors become important determinants of vector-borne diseases transmission like malaria. This study aimed to prove relationships between weather factors with considering human migration and previous case findings and malaria cases in endemic areas in Purworejo during 2005–2014. Methods: This study employed ecological time series analysis by using monthly data. The independent variables were the maximum temperature, minimum temperature, maximum humidity, minimum humidity, precipitation, human migration, and previous malaria cases, while the dependent variable was positive malaria cases. Three models of count data regression analysis i.e. Poisson model, quasi-Poisson model, and negative binomial model were applied to measure the relationship. The least Akaike Information Criteria (AIC) value was also performed to find the best model. Negative binomial regression analysis was considered as the best model. Results: The model showed that humidity (lag 2), precipitation (lag 3), precipitation (lag 12), migration (lag1) and previous malaria cases (lag 12) had a significant relationship with malaria cases. Conclusion: Weather, migration and previous malaria cases factors need to be considered as prominent indicators for the increase of malaria case projection. PMID:29900134

Brief report: Bifactor modeling of general vs. specific factors of religiousness differentially predicting substance use risk in adolescence.

PubMed

Kim-Spoon, Jungmeen; Longo, Gregory S; Holmes, Christopher J

2015-08-01

Religiousness is important to adolescents in the U.S., and the significant link between high religiousness and low substance use is well known. There is a debate between multidimensional and unidimensional perspectives of religiousness (Gorsuch, 1984); yet, no empirical study has tested this hierarchical model of religiousness related to adolescent health outcomes. The current study presents the first attempt to test a bifactor model of religiousness related to substance use among adolescents (N = 220, 45% female). Our bifactor model using structural equation modeling suggested the multidimensional nature of religiousness as well as the presence of a superordinate general religiousness factor directly explaining the covariation among the specific factors including organizational and personal religiousness and religious social support. The general religiousness factor was inversely related to substance use. After accounting for the contribution of the general religiousness factor, high organizational religiousness related to low substance use, whereas personal religiousness and religious support were positively related to substance use. The findings present the first evidence that supports hierarchical structures of adolescent religiousness that contribute differentially to adolescent substance use. Copyright © 2015 The Foundation for Professionals in Services for Adolescents. Published by Elsevier Ltd. All rights reserved.

The relationship between patient data and pooled clinical management decisions.

PubMed

Ludbrook, G I; O'Loughlin, E J; Corcoran, T B; Grant, C

2013-01-01

A strong relationship between patient data and preoperative clinical decisions could potentially be used to support clinical decisions in preoperative management. The aim of this exploratory study was to determine the relationship between key patient data and pooled clinical opinions on management. In a previous study, panels of anaesthetists compared the quality of computer-assisted patient health assessments with outpatient consultations and made decisions on the need for preoperative tests, no preoperative outpatient assessment, possible postoperative intensive care unit/high dependency unit requirements and aspiration prophylaxis. In the current study, the relationship between patient data and these decisions was examined using binomial logistic regression analysis. Backward stepwise regression was used to identify independent predictors of each decision (at P >0.15), which were then incorporated into a predictive model. The number of factors related to each decision varied: blood picture (four factors), biochemistry (six factors), coagulation studies (three factors), electrocardiography (eight factors), chest X-ray (seven factors), preoperative outpatient assessment (17 factors), intensive care unit requirement (eight factors) and aspiration prophylaxis (one factor). The factor types also varied, but included surgical complexity, age, gender, number of medications or comorbidities, body mass index, hypertension, central nervous system condition, heart disease, sleep apnoea, smoking, persistent pain and stroke. Models based on these relationships usually demonstrated good sensitivity and specificity, with receiver operating characteristics in the following areas under curve: blood picture (0.75), biochemistry (0.86), coagulation studies (0.71), electrocardiography (0.90), chest X-ray (0.85), outpatient assessment (0.85), postoperative intensive care unit requirement (0.88) and aspiration prophylaxis (0.85). These initial results suggest modelling of patient data may have utility supporting clinicians' preoperative decisions.

Factor Analysis of Drawings: Application to college student models of the greenhouse effect

NASA Astrophysics Data System (ADS)

Libarkin, Julie C.; Thomas, Stephen R.; Ording, Gabriel

2015-09-01

Exploratory factor analysis was used to identify models underlying drawings of the greenhouse effect made by over 200 entering university freshmen. Initial content analysis allowed deconstruction of drawings into salient features, with grouping of these features via factor analysis. A resulting 4-factor solution explains 62% of the data variance, suggesting that 4 archetype models of the greenhouse effect dominate thinking within this population. Factor scores, indicating the extent to which each student's drawing aligned with representative models, were compared to performance on conceptual understanding and attitudes measures, demographics, and non-cognitive features of drawings. Student drawings were also compared to drawings made by scientists to ascertain the extent to which models reflect more sophisticated and accurate models. Results indicate that student and scientist drawings share some similarities, most notably the presence of some features of the most sophisticated non-scientific model held among the study population. Prior knowledge, prior attitudes, gender, and non-cognitive components are also predictive of an individual student's model. This work presents a new technique for analyzing drawings, with general implications for the use of drawings in investigating student conceptions.

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

PubMed

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

2016-10-01

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

Is the Factor Observed in Investigations on the Item-Position Effect Actually the Difficulty Factor?

PubMed

Schweizer, Karl; Troche, Stefan

2018-02-01

In confirmatory factor analysis quite similar models of measurement serve the detection of the difficulty factor and the factor due to the item-position effect. The item-position effect refers to the increasing dependency among the responses to successively presented items of a test whereas the difficulty factor is ascribed to the wide range of item difficulties. The similarity of the models of measurement hampers the dissociation of these factors. Since the item-position effect should theoretically be independent of the item difficulties, the statistical ex post manipulation of the difficulties should enable the discrimination of the two types of factors. This method was investigated in two studies. In the first study, Advanced Progressive Matrices (APM) data of 300 participants were investigated. As expected, the factor thought to be due to the item-position effect was observed. In the second study, using data simulated to show the major characteristics of the APM data, the wide range of items with various difficulties was set to zero to reduce the likelihood of detecting the difficulty factor. Despite this reduction, however, the factor now identified as item-position factor, was observed in virtually all simulated datasets.

Dimensions and categories: the "big five" factors and the DSM personality disorders.

PubMed

Morey, L C; Gunderson, J; Quigley, B D; Lyons, M

2000-09-01

The five-factor model of personality, which has been widely studied in personality psychology, has been hypothesized to have specific relevance for DSM-defined personality disorders. To evaluate hypothesized relationships of the five-factor model of personality to personality disorders, 144 patients with personality disorders (diagnosed via a structured interview) completed an inventory to assess the five-factor model. Results indicated that the majority of the personality disorders can be differentiated in theoretically predictable ways using the five-factor model of personality. However, while the personality disorders as a whole appear to be differentiable from normal personality functioning on the five factors, the patterns are quite similar across the disorders, a finding that may provide some insight into the general nature of personality pathology but may also suggest problems with discriminant validity. Third, it does not appear that considering disorders as special combinations of features (as might be expected in some categorical models) is more informative than considering them as the sum of certain features (as might be expected in a dimensional model).

Towards a Four-Dimensional Model of Burnout: A Multigroup Factor-Analytic Study Including Depersonalization and Cynicism

ERIC Educational Resources Information Center

Salanova, Marisa; Llorens, Susana; Garcia-Renedo, Monica; Burriel, Raul; Breso, Edgar; Schaufeli, Wilmar B.

2005-01-01

This article investigated whether cynicism and depersonalization are two different dimensions of burnout or whether they may be collapsed into one construct of mental distance. Using confirmatory factor analyses in two samples of teachers (n = 483) and blue-collar workers (n = 474), a superior fit was found for the four-factor model that contained…

Exploring the Latent Structure of the Luria Model for the KABC-II at School Age: Further Insights from Confirmatory Factor Analysis

ERIC Educational Resources Information Center

McGill, Ryan J.

2017-01-01

The present study examined the factor structure of the Luria interpretive model for the Kaufman Assessment Battery for Children-Second Edition (KABC-II) with normative sample participants aged 7-18 (N = 2,025) using confirmatory factor analysis with maximum-likelihood estimation. For the eight subtest Luria configuration, an alternative…

WISC-IV and Clinical Validation of the Four- and Five-Factor Interpretative Approaches

ERIC Educational Resources Information Center

Weiss, Lawrence G.; Keith, Timothy Z.; Zhu, Jianjun; Chen, Hsinyi

2013-01-01

The purpose of this study was to determine the constructs measured by the WISC-IV and the consistency of measurement across large normative and clinical samples. Competing higher order four- and five-factor models were analyzed using the WISC-IV normative sample and clinical subjects. The four-factor solution is the model published with the test…

Factor Structure of the Torrance Tests of Creative Thinking Verbal Form B in a Spanish-Speaking Population

ERIC Educational Resources Information Center

Krumm, Gabriela; Aranguren, María; Arán Filippetti, Vanessa; Lemos, Viviana

2016-01-01

The objective of this study was to compare, through a Confirmatory Factor Analysis, two different theoretical models that explain the operationalized creativity construct with the Verbal Torrance Tests of Creative Thinking (TTCT), Form B. Model 1 is represented by six factors which correspond to each activity and its respective indicators while…

Modeling Vascularized Bone Regeneration Within a Porous Biodegradable CaP Scaffold Loaded with Growth Factors

PubMed Central

Sun, X; Kang, Y; Bao, J; Zhang, Y; Yang, Y; Zhou, X

2013-01-01

Osteogenetic microenvironment is a complex constitution in which extracellular matrix (ECM) molecules, stem cells and growth factors each interact to direct the coordinate regulation of bone tissue development. Importantly, angiogenesis improvement and revascularization are critical for osteogenesis during bone tissue regeneration processes. In this study, we developed a three-dimensional (3D) multi-scale system model to study cell response to growth factors released from a 3D biodegradable porous calcium phosphate (CaP) scaffold. Our model reconstructed the 3D bone regeneration system and examined the effects of pore size and porosity on bone formation and angiogenesis. The results suggested that scaffold porosity played a more dominant role in affecting bone formation and angiogenesis compared with pore size, while the pore size could be controlled to tailor the growth factor release rate and release fraction. Furthermore, a combination of gradient VEGF with BMP2 and Wnt released from the multi-layer scaffold promoted angiogenesis and bone formation more readily than single growth factors. These results demonstrated that the developed model can be potentially applied to predict vascularized bone regeneration with specific scaffold and growth factors. PMID:23566802

Factorial Validity of the ADHD Adult Symptom Rating Scale in a French Community Sample: Results From the ChiP-ARD Study.

PubMed

Morin, Alexandre J S; Tran, Antoine; Caci, Hervé

2016-06-01

Recent publications reported that a bifactor model better represented the underlying structure of ADHD than classical models, at least in youth. The Adult ADHD Symptoms Rating Scale (ASRS) has been translated into many languages, but a single study compared its structure in adults across Diagnostic and Statistical Manual of Mental Disorders (4th ed.; DSM-IV) and International Classification of Diseases (ICD-10) classifications. We investigated the factor structure, reliability, and measurement invariance of the ASRS among a community sample of 1,171 adults. Results support a bifactor model, including one general ADHD factor and three specific Inattention, Hyperactivity, and Impulsivity factors corresponding to ICD-10, albeit the Impulsivity specific factor was weakly defined. Results also support the complete measurement invariance of this model across gender and age groups, and that men have higher scores than women on the ADHD G-factor but lower scores on all three S-factors. Results suggest that a total ASRS-ADHD score is meaningful, reliable, and valid in adults. (J. of Att. Dis. 2016; 20(6) 530-541). © The Author(s) 2013.

Influence of Psychosocial Factors and Habitual Behavior in Temporomandibular Disorder–Related Symptoms in a Working Population in Japan

PubMed Central

Nishiyama, Akira; Kino, Koji; Sugisaki, Masashi; Tsukagoshi, Kaori

2012-01-01

Background: The symptoms of temporomandibular disorders (TMD) are directly influenced by numerous factors, and it is thought that additional factors exert indirect influences. However, the relationships between TMD-related symptoms (TRS) and these contributing factors are largely unknown. Thus, the goal of the present study was to investigate influences on TRS in a working population by determining the prevalence of TRS, analyzing contributing factors, and determining their relative influences on TRS. Materials and Methods: The study subjects were 2203 adults who worked for a single company. Subjects completed a questionnaire assessing TRS, psychosocial factors (stress, anxiety, depressed mood, and chronic fatigue), tooth-contacting habit, and sleep bruxism-related morning symptoms, using a 5-point numeric rating scale. Our analysis proceeded in 2 phases. First, all variables of the descriptor were divided into parts by using an exploratory factor analysis. Second, this factorial structure was verified by using a confirmatory factor analysis with structural equation modeling. Results: Of 2203 employees, 362 reported experiencing TRS (16.4%). Structural equation modeling generated a final model with a goodness of fit index of 0.991, an adjusted goodness of fit index of 0.984, and a root mean square error of approximately 0.021. These indices indicate a strong structural model. The standardized path coefficients for “habitual behavioral factors and TRS,” “psychosocial factors and habitual behavioral factors,” “psychosocial factors and TRS,” and “gender and habitual behavior factors” were 0.48, 0.38, 0.14, and 0.18, respectively. Conclusions: Habitual behavioral factors exert a stronger effect on TRS than do psychosocial factors. PMID:23346261

E-Learning and Social Media Motivation Factor Model

ERIC Educational Resources Information Center

Rosli, Mohd Shafie; Saleh, Nor Shela; Aris, Baharuddin; Ahmad, Maizah Hura; Sejzi, Abbas Abjoli; Shamsudin, Nur Amalina

2016-01-01

The aims of this study are to probe into the motivational factors toward the usage of e-learning and social media among educational technology postgraduate students in the Faculty of Education, Universiti Teknologi Malaysia. This study had involved 70 respondents via the means of a questionnaire. Four factors have been studied, named, the factor…

Factor structure and validation of the Attentional Control Scale.

PubMed

Judah, Matt R; Grant, DeMond M; Mills, Adam C; Lechner, William V

2014-04-01

The Attentional Control Scale (ACS; Derryberry & Reed, 2002) has been used to assess executive control over attention in numerous studies, but no published data have examined the factor structure of the English version. The current studies addressed this need and tested the predictive and convergent validity of the ACS subscales. In Study 1, exploratory factor analysis yielded a two-factor model with Focusing and Shifting subscales. In Study 2, confirmatory factor analysis supported this model and suggested superior fit compared to the factor structure of the Icelandic version (Ólafsson et al., 2011). Study 3 examined correlations between the ACS subscales and measures of working memory, anxiety, and cognitive control. Study 4 examined correlations between the subscales and reaction times on a mixed-antisaccade task, revealing positive correlations for antisaccade performance and prosaccade latency with Focusing scores and between switch trial performance and Shifting scores. Additionally, the findings partially supported unique relationships between Focusing and trait anxiety and between Shifting and depression that have been noted in recent research. Although the results generally support the validity of the ACS, additional research using performance-based tasks is needed.

An Exploratory Study of Pre-Admission Predictors of Hardiness and Retention for United States Military Academy Cadets Using Regression Modeling

DTIC Science & Technology

2013-06-01

Character in Sports Index CV Cross Validation FAS Faculty Appraisal Score FFM Five-Factor Model, also known as the “Big Five” GAM... FFM ). USMA does not allow personality testing as a selection tool. However, perhaps we may discover whether pre-admission information can predict...characteristic, and personality factors as described by the Five Factor Model ( FFM ) to determine their effect on one’s academic performance at USMA (Clark

Animal Models of Hemophilia

PubMed Central

Sabatino, Denise E.; Nichols, Timothy C.; Merricks, Elizabeth; Bellinger, Dwight A.; Herzog, Roland W.; Monahan, Paul E.

2013-01-01

The X-linked bleeding disorder hemophilia is caused by mutations in coagulation factor VIII (hemophilia A) or factor IX (hemophilia B). Unless prophylactic treatment is provided, patients with severe disease (less than 1% clotting activity) typically experience frequent spontaneous bleeds. Current treatment is largely based on intravenous infusion of recombinant or plasma-derived coagulation factor concentrate. More effective factor products are being developed. Moreover, gene therapies for sustained correction of hemophilia are showing much promise in pre-clinical studies and in clinical trials. These advances in molecular medicine heavily depend on availability of well-characterized small and large animal models of hemophilia, primarily hemophilia mice and dogs. Experiments in these animals represent important early and intermediate steps of translational research aimed at development of better and safer treatments for hemophilia, such a protein and gene therapies or immune tolerance protocols. While murine models are excellent for studies of large groups of animals using genetically defined strains, canine models are important for testing scale-up and for longer-term follow-up as well as for studies that require larger blood volumes. PMID:22137432

Factor Structure, Reliability and Measurement Invariance of the Alberta Context Tool and the Conceptual Research Utilization Scale, for German Residential Long Term Care

PubMed Central

Hoben, Matthias; Estabrooks, Carole A.; Squires, Janet E.; Behrens, Johann

2016-01-01

We translated the Canadian residential long term care versions of the Alberta Context Tool (ACT) and the Conceptual Research Utilization (CRU) Scale into German, to study the association between organizational context factors and research utilization in German nursing homes. The rigorous translation process was based on best practice guidelines for tool translation, and we previously published methods and results of this process in two papers. Both instruments are self-report questionnaires used with care providers working in nursing homes. The aim of this study was to assess the factor structure, reliability, and measurement invariance (MI) between care provider groups responding to these instruments. In a stratified random sample of 38 nursing homes in one German region (Metropolregion Rhein-Neckar), we collected questionnaires from 273 care aides, 196 regulated nurses, 152 allied health providers, 6 quality improvement specialists, 129 clinical leaders, and 65 nursing students. The factor structure was assessed using confirmatory factor models. The first model included all 10 ACT concepts. We also decided a priori to run two separate models for the scale-based and the count-based ACT concepts as suggested by the instrument developers. The fourth model included the five CRU Scale items. Reliability scores were calculated based on the parameters of the best-fitting factor models. Multiple-group confirmatory factor models were used to assess MI between provider groups. Rather than the hypothesized ten-factor structure of the ACT, confirmatory factor models suggested 13 factors. The one-factor solution of the CRU Scale was confirmed. The reliability was acceptable (>0.7 in the entire sample and in all provider groups) for 10 of 13 ACT concepts, and high (0.90–0.96) for the CRU Scale. We could demonstrate partial strong MI for both ACT models and partial strict MI for the CRU Scale. Our results suggest that the scores of the German ACT and the CRU Scale for nursing homes are acceptably reliable and valid. However, as the ACT lacked strict MI, observed variables (or scale scores based on them) cannot be compared between provider groups. Rather, group comparisons should be based on latent variable models, which consider the different residual variances of each group. PMID:27656156

A Model of Factors Determining Students' Ability to Interpret External Representations in Biochemistry

ERIC Educational Resources Information Center

Schonborn, Konrad J.; Anderson, Trevor R.

2009-01-01

The aim of this research was to develop a model of factors affecting students' ability to interpret external representations (ERs) in biochemistry. The study was qualitative in design and was guided by the modelling framework of Justi and Gilbert. Application of the process outlined by the framework, and consultation with relevant literature, led…

A Multiple Risk Factors Model of the Development of Aggression among Early Adolescents from Urban Disadvantaged Neighborhoods

ERIC Educational Resources Information Center

Kim, Sangwon; Orpinas, Pamela; Kamphaus, Randy; Kelder, Steven H.

2011-01-01

This study empirically derived a multiple risk factors model of the development of aggression among middle school students in urban, low-income neighborhoods, using Hierarchical Linear Modeling (HLM). Results indicated that aggression increased from sixth to eighth grade. Additionally, the influences of four risk domains (individual, family,…

Emerging Australian Education Markets: A Discrete Choice Model of Taiwanese and Indonesian Student Intended Study Destination.

ERIC Educational Resources Information Center

Kemp, Steven; Madden, Gary; Simpson, Michael

1998-01-01

Isolates factors influencing choice of Australia as a preferred destination for international students in emerging regional markets. Uses data obtained from a survey of students in Indonesia and Taiwan to estimate a U.S./Australia and rest-of-world/Australia discrete destination-choice model. This model identifies key factors determining country…

Assessing Psychological Symptoms and Well-Being: Application of a Dual-Factor Mental Health Model to Understand College Student Performance

ERIC Educational Resources Information Center

Antaramian, Susan

2015-01-01

A dual-factor mental health model includes measures of positive psychological well-being in addition to traditional indicators of psychopathology to comprehensively determine mental health status. The current study examined the utility of this model in understanding the psychological adjustment and educational functioning of college students. A…

Comparison of Cox's Regression Model and Parametric Models in Evaluating the Prognostic Factors for Survival after Liver Transplantation in Shiraz during 2000-2012.

PubMed

Adelian, R; Jamali, J; Zare, N; Ayatollahi, S M T; Pooladfar, G R; Roustaei, N

2015-01-01

Identification of the prognostic factors for survival in patients with liver transplantation is challengeable. Various methods of survival analysis have provided different, sometimes contradictory, results from the same data. To compare Cox's regression model with parametric models for determining the independent factors for predicting adults' and pediatrics' survival after liver transplantation. This study was conducted on 183 pediatric patients and 346 adults underwent liver transplantation in Namazi Hospital, Shiraz, southern Iran. The study population included all patients undergoing liver transplantation from 2000 to 2012. The prognostic factors sex, age, Child class, initial diagnosis of the liver disease, PELD/MELD score, and pre-operative laboratory markers were selected for survival analysis. Among 529 patients, 346 (64.5%) were adult and 183 (34.6%) were pediatric cases. Overall, the lognormal distribution was the best-fitting model for adult and pediatric patients. Age in adults (HR=1.16, p<0.05) and weight (HR=2.68, p<0.01) and Child class B (HR=2.12, p<0.05) in pediatric patients were the most important factors for prediction of survival after liver transplantation. Adult patients younger than the mean age and pediatric patients weighing above the mean and Child class A (compared to those with classes B or C) had better survival. Parametric regression model is a good alternative for the Cox's regression model.

A Comparison of the Validity of the Five-Factor Model (FFM) Personality Disorder Prototypes Using FFM Self-Report and Interview Measures

ERIC Educational Resources Information Center

Miller, Joshua D.; Bagby, R. Michael; Pilkonis, Paul A.

2005-01-01

Recent studies have demonstrated that personality disorders (PDs) can be assessed via a prototype-matching technique, which enables researchers and clinicians to match an individual's five-factor model (FFM) personality profile to an expert-generated prototype. The current study examined the relations between these prototype scores, using…

Modeling the influence of local environmental factors on malaria transmission in Benin and its implications for cohort study.

PubMed

Cottrell, Gilles; Kouwaye, Bienvenue; Pierrat, Charlotte; le Port, Agnès; Bouraïma, Aziz; Fonton, Noël; Hounkonnou, Mahouton Norbert; Massougbodji, Achille; Corbel, Vincent; Garcia, André

2012-01-01

Malaria remains endemic in tropical areas, especially in Africa. For the evaluation of new tools and to further our understanding of host-parasite interactions, knowing the environmental risk of transmission--even at a very local scale--is essential. The aim of this study was to assess how malaria transmission is influenced and can be predicted by local climatic and environmental factors.As the entomological part of a cohort study of 650 newborn babies in nine villages in the Tori Bossito district of Southern Benin between June 2007 and February 2010, human landing catches were performed to assess the density of malaria vectors and transmission intensity. Climatic factors as well as household characteristics were recorded throughout the study. Statistical correlations between Anopheles density and environmental and climatic factors were tested using a three-level Poisson mixed regression model. The results showed both temporal variations in vector density (related to season and rainfall), and spatial variations at the level of both village and house. These spatial variations could be largely explained by factors associated with the house's immediate surroundings, namely soil type, vegetation index and the proximity of a watercourse. Based on these results, a predictive regression model was developed using a leave-one-out method, to predict the spatiotemporal variability of malaria transmission in the nine villages.This study points up the importance of local environmental factors in malaria transmission and describes a model to predict the transmission risk of individual children, based on environmental and behavioral characteristics.

Perceived experiences of atheist discrimination: Instrument development and evaluation.

PubMed

Brewster, Melanie E; Hammer, Joseph; Sawyer, Jacob S; Eklund, Austin; Palamar, Joseph

2016-10-01

The present 2 studies describe the development and initial psychometric evaluation of a new instrument, the Measure of Atheist Discrimination Experiences (MADE), which may be used to examine the minority stress experiences of atheist people. Items were created from prior literature, revised by a panel of expert researchers, and assessed psychometrically. In Study 1 (N = 1,341 atheist-identified people), an exploratory factor analysis with 665 participants suggested the presence of 5 related dimensions of perceived discrimination. However, bifactor modeling via confirmatory factor analysis and model-based reliability estimates with data from the remaining 676 participants affirmed the presence of a strong "general" factor of discrimination and mixed to poor support for substantive subdimensions. In Study 2 (N = 1,057 atheist-identified people), another confirmatory factor analysis and model-based reliability estimates strongly supported the bifactor model from Study 1 (i.e., 1 strong "general" discrimination factor) and poor support for subdimensions. Across both studies, the MADE general factor score demonstrated evidence of good reliability (i.e., Cronbach's alphas of .94 and .95; omega hierarchical coefficients of .90 and .92), convergent validity (i.e., with stigma consciousness, β = .56; with awareness of public devaluation, β = .37), and preliminary evidence for concurrent validity (i.e., with loneliness β = .18; with psychological distress β = .27). Reliability and validity evidence for the MADE subscale scores was not sufficient to warrant future use of the subscales. Limitations and implications for future research and clinical work with atheist individuals are discussed. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

Modeling the Influence of Local Environmental Factors on Malaria Transmission in Benin and Its Implications for Cohort Study

PubMed Central

Pierrat, Charlotte; le Port, Agnès; Bouraïma, Aziz; Fonton, Noël; Hounkonnou, Mahouton Norbert; Massougbodji, Achille; Corbel, Vincent; Garcia, André

2012-01-01

Malaria remains endemic in tropical areas, especially in Africa. For the evaluation of new tools and to further our understanding of host-parasite interactions, knowing the environmental risk of transmission—even at a very local scale—is essential. The aim of this study was to assess how malaria transmission is influenced and can be predicted by local climatic and environmental factors. As the entomological part of a cohort study of 650 newborn babies in nine villages in the Tori Bossito district of Southern Benin between June 2007 and February 2010, human landing catches were performed to assess the density of malaria vectors and transmission intensity. Climatic factors as well as household characteristics were recorded throughout the study. Statistical correlations between Anopheles density and environmental and climatic factors were tested using a three-level Poisson mixed regression model. The results showed both temporal variations in vector density (related to season and rainfall), and spatial variations at the level of both village and house. These spatial variations could be largely explained by factors associated with the house's immediate surroundings, namely soil type, vegetation index and the proximity of a watercourse. Based on these results, a predictive regression model was developed using a leave-one-out method, to predict the spatiotemporal variability of malaria transmission in the nine villages. This study points up the importance of local environmental factors in malaria transmission and describes a model to predict the transmission risk of individual children, based on environmental and behavioral characteristics. PMID:22238582

The technology acceptance model: predicting nurses' intention to use telemedicine technology (eICU).

PubMed

Kowitlawakul, Yanika

2011-07-01

The purposes of this study were to determine factors and predictors that influence nurses' intention to use the eICU technology, to examine the applicability of the Technology Acceptance Model in explaining nurses' intention to use the eICU technology in healthcare settings, and to provide psychometric evidence of the measurement scales used in the study. The study involved 117 participants from two healthcare systems. The Telemedicine Technology Acceptance Model was developed based on the original Technology Acceptance Model that was initially developed by Fred Davis in 1986. The eICU Acceptance Survey was used as an instrument for the study. Content validity was examined, and the reliability of the instrument was tested. The results show that perceived usefulness is the most influential factor that influences nurses' intention to use the eICU technology. The principal factors that influence perceived usefulness are perceived ease of use, support from physicians, and years working in the hospital. The model fit was reasonably adequate and able to explain 58% of the variance (R = 0.58) in intention to use the eICU technology with the nursing sample.

Validation of the Parenting Stress Index--Short Form with Minority Caregivers

ERIC Educational Resources Information Center

Lee, Sang Jung; Gopalan, Geetha; Harrington, Donna

2016-01-01

Objectives: There has been little examination of the structural validity of the Parenting Stress Index--Short Form (PSI-SF) for minority populations in clinical contexts in the Unites States. This study aimed to test prespecified factor structures (one-factor, two-factor, and three-factor models) of the PSI-SF. Methods: This study used…

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

PubMed

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

2016-08-01

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

A Comparison of Rule-based Analysis with Regression Methods in Understanding the Risk Factors for Study Withdrawal in a Pediatric Study.

PubMed

Haghighi, Mona; Johnson, Suzanne Bennett; Qian, Xiaoning; Lynch, Kristian F; Vehik, Kendra; Huang, Shuai

2016-08-26

Regression models are extensively used in many epidemiological studies to understand the linkage between specific outcomes of interest and their risk factors. However, regression models in general examine the average effects of the risk factors and ignore subgroups with different risk profiles. As a result, interventions are often geared towards the average member of the population, without consideration of the special health needs of different subgroups within the population. This paper demonstrates the value of using rule-based analysis methods that can identify subgroups with heterogeneous risk profiles in a population without imposing assumptions on the subgroups or method. The rules define the risk pattern of subsets of individuals by not only considering the interactions between the risk factors but also their ranges. We compared the rule-based analysis results with the results from a logistic regression model in The Environmental Determinants of Diabetes in the Young (TEDDY) study. Both methods detected a similar suite of risk factors, but the rule-based analysis was superior at detecting multiple interactions between the risk factors that characterize the subgroups. A further investigation of the particular characteristics of each subgroup may detect the special health needs of the subgroup and lead to tailored interventions.

Subconstructs of the Edinburgh Postnatal Depression Scale in a multi-ethnic inner-city population in the U.S.

PubMed

Chiu, Yueh-Hsiu Mathilda; Sheffield, Perry E; Hsu, Hsiao-Hsien Leon; Goldstein, Jonathan; Curtin, Paul C; Wright, Rosalind J

2017-12-01

The ten-item Edinburgh Postnatal Depression Scale (EPDS) is one of the most widely used self-report measures of postpartum depression. Although originally described as a one-dimensional measure, the recognition that depressive symptoms may be differentially experienced across cultural and racial/ethnic groups has led to studies examining structural equivalence of the EPDS in different populations. Variation of the factor structure remains understudied across racial/ethnic groups of US women. We examined the factor structure of the EPDS assessed 6 months postpartum in 515 women (29% black, 53% Hispanic, 18% white) enrolled in an urban Boston longitudinal birth cohort. Exploratory factor analysis (EFA) identified that a three-factor model, including depression, anxiety, and anhedonia subscales, was the most optimal fit in our sample as a whole and across race/ethnicity. Confirmatory factor analysis (CFA) was used to examine the fit of both the two- and three-factor models reported in prior research. CFA confirmed the best fit for a three-factor model, with minimal differences across race/ethnicity. "Things get on top of me" loaded on the anxiety factor among Hispanics, but loaded on the depression factor in whites and African Americans. These findings suggest that EPDS factor structure may need to be adjusted for diverse samples and warrants further study.

Effort-reward imbalance at work and the co-occurrence of lifestyle risk factors: cross-sectional survey in a sample of 36,127 public sector employees

PubMed Central

Kouvonen, Anne; Kivimäki, Mika; Virtanen, Marianna; Heponiemi, Tarja; Elovainio, Marko; Pentti, Jaana; Linna, Anne; Vahtera, Jussi

2006-01-01

Background In occupational life, a mismatch between high expenditure of effort and receiving few rewards may promote the co-occurrence of lifestyle risk factors, however, there is insufficient evidence to support or refute this hypothesis. The aim of this study is to examine the extent to which the dimensions of the Effort-Reward Imbalance (ERI) model – effort, rewards and ERI – are associated with the co-occurrence of lifestyle risk factors. Methods Based on data from the Finnish Public Sector Study, cross-sectional analyses were performed for 28,894 women and 7233 men. ERI was conceptualized as a ratio of effort and rewards. To control for individual differences in response styles, such as a personal disposition to answer negatively to questionnaires, occupational and organizational -level ecological ERI scores were constructed in addition to individual-level ERI scores. Risk factors included current smoking, heavy drinking, body mass index ≥25 kg/m2, and physical inactivity. Multinomial logistic regression models were used to estimate the likelihood of having one risk factor, two risk factors, and three or four risk factors. The associations between ERI and single risk factors were explored using binary logistic regression models. Results After adjustment for age, socioeconomic position, marital status, and type of job contract, women and men with high ecological ERI were 40% more likely to have simultaneously ≥3 lifestyle risk factors (vs. 0 risk factors) compared with their counterparts with low ERI. When examined separately, both low ecological effort and low ecological rewards were also associated with an elevated prevalence of risk factor co-occurrence. The results obtained with the individual-level scores were in the same direction. The associations of ecological ERI with single risk factors were generally less marked than the associations with the co-occurrence of risk factors. Conclusion This study suggests that a high ratio of occupational efforts relative to rewards may be associated with an elevated risk of having multiple lifestyle risk factors. However, an unexpected association between low effort and a higher likelihood of risk factor co-occurrence as well as the absence of data on overcommitment (and thereby a lack of full test of the ERI model) warrant caution in regard to the extent to which the entire ERI model is supported by our evidence. PMID:16464262

Effort-reward imbalance at work and the co-occurrence of lifestyle risk factors: cross-sectional survey in a sample of 36,127 public sector employees.

PubMed

Kouvonen, Anne; Kivimäki, Mika; Virtanen, Marianna; Heponiemi, Tarja; Elovainio, Marko; Pentti, Jaana; Linna, Anne; Vahtera, Jussi

2006-02-07

In occupational life, a mismatch between high expenditure of effort and receiving few rewards may promote the co-occurrence of lifestyle risk factors, however, there is insufficient evidence to support or refute this hypothesis. The aim of this study is to examine the extent to which the dimensions of the Effort-Reward Imbalance (ERI) model--effort, rewards and ERI--are associated with the co-occurrence of lifestyle risk factors. Based on data from the Finnish Public Sector Study, cross-sectional analyses were performed for 28,894 women and 7233 men. ERI was conceptualized as a ratio of effort and rewards. To control for individual differences in response styles, such as a personal disposition to answer negatively to questionnaires, occupational and organizational-level ecological ERI scores were constructed in addition to individual-level ERI scores. Risk factors included current smoking, heavy drinking, body mass index > or =25 kg/m2, and physical inactivity. Multinomial logistic regression models were used to estimate the likelihood of having one risk factor, two risk factors, and three or four risk factors. The associations between ERI and single risk factors were explored using binary logistic regression models. After adjustment for age, socioeconomic position, marital status, and type of job contract, women and men with high ecological ERI were 40% more likely to have simultaneously > or =3 lifestyle risk factors (vs. 0 risk factors) compared with their counterparts with low ERI. When examined separately, both low ecological effort and low ecological rewards were also associated with an elevated prevalence of risk factor co-occurrence. The results obtained with the individual-level scores were in the same direction. The associations of ecological ERI with single risk factors were generally less marked than the associations with the co-occurrence of risk factors. This study suggests that a high ratio of occupational efforts relative to rewards may be associated with an elevated risk of having multiple lifestyle risk factors. However, an unexpected association between low effort and a higher likelihood of risk factor co-occurrence as well as the absence of data on overcommitment (and thereby a lack of full test of the ERI model) warrant caution in regard to the extent to which the entire ERI model is supported by our evidence.

Pragmatics fragmented: the factor structure of the Dutch children's communication checklist (CCC).

PubMed

Geurts, Hilde M; Hartman, Catharina; Verté, Sylvie; Oosterlaan, Jaap; Roeyers, Herbert; Sergeant, Joseph A

2009-01-01

A number of disorders are associated with pragmatic difficulties. Instruments that can make subdivisions within the larger construct of pragmatics could be important tools for disentangling profiles of pragmatic difficulty in different disorders. The deficits underlying the observed pragmatic difficulties may be different for different disorders. To study the construct validity of a pragmatic language questionnaire. The construct of pragmatics is studied by applying exploratory factor analysis (EFA) and confirmatory factor analysis to the parent version of the Dutch Children's Communication Checklist (CCC; Bishop 1998 ). Parent ratings of 1589 typically developing children and 481 children with a clinical diagnosis were collected. Four different factor models derived from the original CCC scales and five different factor models based on EFA were compared with each other. The models were cross-validated. The EFA-derived models were substantively different from the originally proposed CCC factor structure. EFA models gave a slightly better fit than the models based on the original CCC scales, though neither provided a good fit to the parent data. Coherence seemed to be part of language form and not of pragmatics, which is in line with the adaptation of the CCC, the CCC-2 (Bishop 2003 ). Most pragmatic items clustered together in one factor and these pragmatic items also clustered with items related to social relationships and specific interests. The nine scales of the original CCC do not reflect the underlying factor structure. Therefore, scale composition may be improved on and scores on subscale level need to be interpreted cautiously. Therefore, in interpreting the CCC profiles, the overall measure might be more informative than the postulated subscales as more information is needed to determine which constructs the suggested subscales are actually measuring.

Factors associated with adoption of health information technology: a conceptual model based on a systematic review.

PubMed

Kruse, Clemens Scott; DeShazo, Jonathan; Kim, Forest; Fulton, Lawrence

2014-05-23

The Health Information Technology for Economic and Clinical Health Act (HITECH) allocated $19.2 billion to incentivize adoption of the electronic health record (EHR). Since 2009, Meaningful Use Criteria have dominated information technology (IT) strategy. Health care organizations have struggled to meet expectations and avoid penalties to reimbursements from the Center for Medicare and Medicaid Services (CMS). Organizational theories attempt to explain factors that influence organizational change, and many theories address changes in organizational strategy. However, due to the complexities of the health care industry, existing organizational theories fall short of demonstrating association with significant health care IT implementations. There is no organizational theory for health care that identifies, groups, and analyzes both internal and external factors of influence for large health care IT implementations like adoption of the EHR. The purpose of this systematic review is to identify a full-spectrum of both internal organizational and external environmental factors associated with the adoption of health information technology (HIT), specifically the EHR. The result is a conceptual model that is commensurate with the complexity of with the health care sector. We performed a systematic literature search in PubMed (restricted to English), EBSCO Host, and Google Scholar for both empirical studies and theory-based writing from 1993-2013 that demonstrated association between influential factors and three modes of HIT: EHR, electronic medical record (EMR), and computerized provider order entry (CPOE). We also looked at published books on organizational theories. We made notes and noted trends on adoption factors. These factors were grouped as adoption factors associated with various versions of EHR adoption. The resulting conceptual model summarizes the diversity of independent variables (IVs) and dependent variables (DVs) used in articles, editorials, books, as well as quantitative and qualitative studies (n=83). As of 2009, only 16.30% (815/4999) of nonfederal, acute-care hospitals had adopted a fully interoperable EHR. From the 83 articles reviewed in this study, 16/83 (19%) identified internal organizational factors and 9/83 (11%) identified external environmental factors associated with adoption of the EHR, EMR, or CPOE. The conceptual model for EHR adoption associates each variable with the work that identified it. Commonalities exist in the literature for internal organizational and external environmental factors associated with the adoption of the EHR and/or CPOE. The conceptual model for EHR adoption associates internal and external factors, specific to the health care industry, associated with adoption of the EHR. It becomes apparent that these factors have some level of association, but the association is not consistently calculated individually or in combination. To better understand effective adoption strategies, empirical studies should be performed from this conceptual model to quantify the positive or negative effect of each factor.

Factor structure and clinical correlates of the 61-item Wender Utah Rating Scale (WURS).

PubMed

Calamia, Matthew; Hill, Benjamin D; Musso, Mandi W; Pella, Russell D; Gouvier, Wm Drew

2018-02-09

The objective of this study was to assess the factor structure and clinical correlates of a 61-item version of the Wender Utah Rating Scale (WURS), a self-report retrospective measure of childhood problems, experiences, and behavior used in ADHD assessment. Given the currently mostly widely used form of the WURS was derived via a criterion-keyed approach, the study aimed to use latent variable modeling of the 61-item WURS to potentially identify more and more homogeneous set of items reflecting current conceptualizations of ADHD symptoms. Exploratory structural equation modeling was used to generate factor scores which were then correlated with neuropsychological measures of intelligence and executive attention as well as a broad measure of personality and emotional functioning. Support for a modified five-factor model was found: ADHD, disruptive mood and behavior, negative affectivity, social confidence, and academic problems. The ADHD factor differed somewhat from the traditional 25-item WURS short form largely through weaker associations with several measures of personality and psychopathology. This study identified a factor more aligned with DSM-5 conceptualization of ADHD as well as measures of other types of childhood characteristics and symptoms which may prove useful for both research and clinical practice.

The effects of deterioration and technological levels on pollutant emission factors for gasoline light-duty trucks.

PubMed

Zhang, Qingyu; Fan, Juwang; Yang, Weidong; Chen, Bixin; Zhang, Lijuan; Liu, Jiaoyu; Wang, Jingling; Zhou, Chunyao; Chen, Xuan

2017-07-01

Vehicle deterioration and technological change influence emission factors (EFs). In this study, the impacts of vehicle deterioration and emission standards on EFs of regulated pollutants (carbon monoxide [CO], hydrocarbon [HC], and nitrogen oxides [NO x ]) for gasoline light-duty trucks (LDTs) were investigated according to the inspection and maintenance (I/M) data using a chassis dynamometer method. Pollutant EFs for LDTs markedly varied with accumulated mileages and emission standards, and the trends of EFs are associated with accumulated mileages. In addition, the study also found that in most cases, the median EFs of CO, HC, and NO x are higher than those of basic EFs in the International Vehicle Emissions (IVE) model; therefore, the present study provides correction factors for the IVE model relative to the corresponding emission standards and mileages. Currently, vehicle emissions are great contributors to air pollution in cities, especially in developing countries. Emission factors play a key role in creating emission inventory and estimating emissions. Deterioration represented by vehicle age and accumulated mileage and changes of emission standards markedly influence emission factors. In addition, the results provide collection factors for implication in the IVE model in the region levels.

Environmental Predictors of US County Mortality Patterns on a National Basis.

PubMed

Chan, Melissa P L; Weinhold, Robert S; Thomas, Reuben; Gohlke, Julia M; Portier, Christopher J

2015-01-01

A growing body of evidence has found that mortality rates are positively correlated with social inequalities, air pollution, elevated ambient temperature, availability of medical care and other factors. This study develops a model to predict the mortality rates for different diseases by county across the US. The model is applied to predict changes in mortality caused by changing environmental factors. A total of 3,110 counties in the US, excluding Alaska and Hawaii, were studied. A subset of 519 counties from the 3,110 counties was chosen by using systematic random sampling and these samples were used to validate the model. Step-wise and linear regression analyses were used to estimate the ability of environmental pollutants, socio-economic factors and other factors to explain variations in county-specific mortality rates for cardiovascular diseases, cancers, chronic obstructive pulmonary disease (COPD), all causes combined and lifespan across five population density groups. The estimated models fit adequately for all mortality outcomes for all population density groups and, adequately predicted risks for the 519 validation counties. This study suggests that, at local county levels, average ozone (0.07 ppm) is the most important environmental predictor of mortality. The analysis also illustrates the complex inter-relationships of multiple factors that influence mortality and lifespan, and suggests the need for a better understanding of the pathways through which these factors, mortality, and lifespan are related at the community level.

Environmental Predictors of US County Mortality Patterns on a National Basis

PubMed Central

Thomas, Reuben; Gohlke, Julia M.; Portier, Christopher J.

2015-01-01

A growing body of evidence has found that mortality rates are positively correlated with social inequalities, air pollution, elevated ambient temperature, availability of medical care and other factors. This study develops a model to predict the mortality rates for different diseases by county across the US. The model is applied to predict changes in mortality caused by changing environmental factors. A total of 3,110 counties in the US, excluding Alaska and Hawaii, were studied. A subset of 519 counties from the 3,110 counties was chosen by using systematic random sampling and these samples were used to validate the model. Step-wise and linear regression analyses were used to estimate the ability of environmental pollutants, socio-economic factors and other factors to explain variations in county-specific mortality rates for cardiovascular diseases, cancers, chronic obstructive pulmonary disease (COPD), all causes combined and lifespan across five population density groups. The estimated models fit adequately for all mortality outcomes for all population density groups and, adequately predicted risks for the 519 validation counties. This study suggests that, at local county levels, average ozone (0.07 ppm) is the most important environmental predictor of mortality. The analysis also illustrates the complex inter-relationships of multiple factors that influence mortality and lifespan, and suggests the need for a better understanding of the pathways through which these factors, mortality, and lifespan are related at the community level. PMID:26629706

External factors in hospital information system (HIS) adoption model: a case on Malaysia.

PubMed

Lee, Heng Wei; Ramayah, Thurasamy; Zakaria, Nasriah

2012-08-01

Studies related to healthcare ICT integration in Malaysia are relatively little, thus this paper provide a literature review of the integration of information and communication technologies (ICT) in the healthcare sector in Malaysia through the hospital information system (HIS). Our study emphasized on secondary data to investigate the factors related to ICT integration in healthcare through HIS. Therefore this paper aimed to gather an in depth understanding of issues related to HIS adoption, and contributing in fostering HIS adoption in Malaysia and other countries. This paper provides a direction for future research to study the correlation of factors affecting HIS adoption. Finally a research model is proposed using current adoption theories and external factors from human, technology, and organization perspectives.

Examining the factor structure of the Multiple Sclerosis Impact Scale.

PubMed

Fitzgerald, Shawn M; Li, Jian; Rumrill, Phillip D; Merchant, William; Bishop, Malachy

2014-01-01

The purpose of this study was to investigate the factor structure of the Multiple Sclerosis Impact Scale (MSIS-29) to assess its suitability for modeling the impact of MS on a nation-wide sample of individuals from the United States. Investigators completed a Confirmatory Factor Analysis (CFA) to examine the two-factor structure proposed by Hobart et al. [17]. Although the original MSIS-29 factor structure did not fit the data exactly, the hypothesized two-factor model was partially supported in the current data. Implications for future instrument development and rehabilitation practice are discussed.

The relative importance of physicochemical factors to stream biological condition in urbanizing basins: Evidence from multimodel inference

USGS Publications Warehouse

Carlisle, Daren M.; Bryant, Wade L.

2011-01-01

Many physicochemical factors potentially impair stream ecosystems in urbanizing basins, but few studies have evaluated their relative importance simultaneously, especially in different environmental settings. We used data collected in 25 to 30 streams along a gradient of urbanization in each of 6 metropolitan areas (MAs) to evaluate the relative importance of 11 physicochemical factors on the condition of algal, macroinvertebrate, and fish assemblages. For each assemblage, biological condition was quantified using 2 separate metrics, nonmetric multidimensional scaling ordination site scores and the ratio of observed/expected taxa, both derived in previous studies. Separate linear regression models with 1 or 2 factors as predictors were developed for each MA and assemblage metric. Model parsimony was evaluated based on Akaike’s Information Criterion for small sample size (AICc) and Akaike weights, and variable importance was estimated by summing the Akaike weights across models containing each stressor variable. Few of the factors were strongly correlated (Pearson |r| > 0.7) within MAs. Physicochemical factors explained 17 to 81% of variance in biological condition. Most (92 of 118) of the most plausible models contained 2 predictors, and generally more variance could be explained by the additive effects of 2 factors than by any single factor alone. None of the factors evaluated was universally important for all MAs or biological assemblages. The relative importance of factors varied for different measures of biological condition, biological assemblages, and MA. Our results suggest that the suite of physicochemical factors affecting urban stream ecosystems varies across broad geographic areas, along gradients of urban intensity, and among basins within single MAs.

The making of the modern airport executive: Causal connections among key attributes in career development, compromise, and satisfaction in airport management

NASA Astrophysics Data System (ADS)

Byers, David Alan

The purpose of this study was to identify specific career development attributes of contemporary senior-level airport executives and to evaluate the relationship of these attributes to the level of satisfaction airport executives have in their career choice. Attribute sets that were examined included early aviation interests, health factors, psychological factors, demographic factors, formal education, and other aviation-related experiences. A hypothesized causal model that expressed direct and indirect effects among these attributes relative to airport executives' career satisfaction was tested using sample data collected from 708 airport executives from general aviation and commercial service airport throughout the United States. Applying a multiple regression analysis strategy to the model, the overall results revealed that 16% of the variability in airport executives' career satisfaction scores was due to the collective influence of the six research attribute sets, this was significant. The results of the path analysis also indicated that four attribute sets (early aviation interests, health factors, formal education, and other aviation-related experiences) had respective direct significant effects on participants' career satisfaction. Early aviation interests, health factors, and demographic factors had additional indirect effects on career satisfaction; all were mediated by formal education attitude. These results were inconsistent with the hypothesized path model and a revised model was developed to reflect the sample data. The findings suggest that airport executives, as a group, are satisfied with their career choice. Early aviation interests appear to play an important role for influencing the career field selection phase of career development. The study also suggests health factors, formal education, and other aviation-related experiences such as flight training or military experience influence the compromise phase of career development. Each of these four factors had significant effects on career satisfaction. In addition to its applicability to airport executives, the study provides a generalized path model for investigating factors influencing the career development, compromise, and satisfaction process in other vocations.

The role of neuroticism, perfectionism and depression in chronic fatigue syndrome. A structural equation modeling approach.

PubMed

Valero, Sergi; Sáez-Francàs, Naia; Calvo, Natalia; Alegre, José; Casas, Miquel

2013-10-01

Previous studies have reported consistent associations between Neuroticism, maladaptive perfectionism and depression with severity of fatigue in Chronic Fatigue Syndrome (CFS). Depression has been considered a mediator factor between maladaptive perfectionism and fatigue severity, but no studies have explored the role of neuroticism in a comparable theoretical framework. This study aims to examine for the first time, the role of neuroticism, maladaptive perfectionism and depression on the severity of CFS, analyzing several explanation models. A sample of 229 CFS patients were studied comparing four structural equation models, testing the role of mediation effect of depression severity in the association of Neuroticism and/or Maladaptive perfectionism on fatigue severity. The model considering depression severity as mediator factor between Neuroticism and fatigue severity is the only one of the explored models where all the structural modeling indexes have fitted satisfactorily (Chi square=27.01, p=0.079; RMSE=0.047, CFI=0.994; SRMR=0.033). Neuroticism is associated with CFS by the mediation effect of depression severity. This personality variable constitutes a more consistent factor than maladaptive perfectionism in the conceptualization of CFS severity. Copyright © 2013 Elsevier Inc. All rights reserved.

Integrating social capital theory, social cognitive theory, and the technology acceptance model to explore a behavioral model of telehealth systems.

PubMed

Tsai, Chung-Hung

2014-05-07

Telehealth has become an increasingly applied solution to delivering health care to rural and underserved areas by remote health care professionals. This study integrated social capital theory, social cognitive theory, and the technology acceptance model (TAM) to develop a comprehensive behavioral model for analyzing the relationships among social capital factors (social capital theory), technological factors (TAM), and system self-efficacy (social cognitive theory) in telehealth. The proposed framework was validated with 365 respondents from Nantou County, located in Central Taiwan. Structural equation modeling (SEM) was used to assess the causal relationships that were hypothesized in the proposed model. The finding indicates that elderly residents generally reported positive perceptions toward the telehealth system. Generally, the findings show that social capital factors (social trust, institutional trust, and social participation) significantly positively affect the technological factors (perceived ease of use and perceived usefulness respectively), which influenced usage intention. This study also confirmed that system self-efficacy was the salient antecedent of perceived ease of use. In addition, regarding the samples, the proposed model fitted considerably well. The proposed integrative psychosocial-technological model may serve as a theoretical basis for future research and can also offer empirical foresight to practitioners and researchers in the health departments of governments, hospitals, and rural communities.

Integrating Social Capital Theory, Social Cognitive Theory, and the Technology Acceptance Model to Explore a Behavioral Model of Telehealth Systems

PubMed Central

Tsai, Chung-Hung

2014-01-01

Telehealth has become an increasingly applied solution to delivering health care to rural and underserved areas by remote health care professionals. This study integrated social capital theory, social cognitive theory, and the technology acceptance model (TAM) to develop a comprehensive behavioral model for analyzing the relationships among social capital factors (social capital theory), technological factors (TAM), and system self-efficacy (social cognitive theory) in telehealth. The proposed framework was validated with 365 respondents from Nantou County, located in Central Taiwan. Structural equation modeling (SEM) was used to assess the causal relationships that were hypothesized in the proposed model. The finding indicates that elderly residents generally reported positive perceptions toward the telehealth system. Generally, the findings show that social capital factors (social trust, institutional trust, and social participation) significantly positively affect the technological factors (perceived ease of use and perceived usefulness respectively), which influenced usage intention. This study also confirmed that system self-efficacy was the salient antecedent of perceived ease of use. In addition, regarding the samples, the proposed model fitted considerably well. The proposed integrative psychosocial-technological model may serve as a theoretical basis for future research and can also offer empirical foresight to practitioners and researchers in the health departments of governments, hospitals, and rural communities. PMID:24810577

Social and Psychological Factors Associated With Adolescent Physical Activity

PubMed Central

Garcia, Jeanette M.; Sirard, John R.; Larsen, Ross; Bruening, Meg; Wall, Melanie; Neumark-Sztainer, Dianne

2017-01-01

Objective The purpose of this study was to examine, using structural equation modeling, the associations between nominated friend physical activity (PA), friend social support with individual psychological factors, and adolescent PA. Methods Data were obtained from EAT 2010 (Eating and Activity Among Teens), a large cross-sectional study conducted in 20 middle and high schools. The sample consisted of 1951 adolescents (mean age: 14.25 ± 1.96, 54% female, 68% ethnic minorities). PA, parent and friend socia l support (perceived social support for PA from parents and friends), and psychological measures (PA enjoyment, PA self-efficacy, and PA barriers) were assessed by self-report questionnaires. The SEM analysis consisted of 1 observed variable: friend PA, and 2 latent constructs: psychological factors, perceived social support. Results The model was a good fit, indicating that there were significant direct effects of both friend PA (P < .01) and psychological factors (P < .0001) on adolescent PA. In addition, psychological factors mediated the association between friend PA and adolescent PA. Conclusion The results of this model suggest that psychological factors and friend PA are associated with adolescent PA, and that psychological factors may play an important role. Future studies should further examine the association of both friend PA and psychological variables with adolescent PA. PMID:27172613

Social and Psychological Factors Associated With Adolescent Physical Activity.

PubMed

Garcia, Jeanette M; Sirard, John R; Larsen, Ross; Bruening, Meg; Wall, Melanie; Neumark-Sztainer, Dianne

2016-09-01

The purpose of this study was to examine, using structural equation modeling, the associations between nominated friend physical activity (PA), friend social support with individual PA-related psychological factors, and adolescent PA. Data were obtained from EAT 2010 (Eating and Activity Among Teens), a large cross-sectional study conducted in 20 middle and high schools. The sample consisted of 1951 adolescents (mean age: 14.25 ± 1.96, 54% female, 68% ethnic minorities). PA, parent and friend social support (perceived social support for PA from parents and friends), and psychological measures (PA enjoyment, PA self-efficacy, and PA barriers) were assessed by self-report questionnaires. The SEM analysis consisted of 1 observed variable: friend PA, and 2 latent constructs: psychological factors, perceived social support. The model was a good fit, indicating that there were significant direct effects of both friend PA (P < .01) and psychological factors (P < .0001) on adolescent PA. In addition, psychological factors mediated the association between friend PA and adolescent PA. The results of this model suggest that psychological factors and friend PA are associated with adolescent PA, and that psychological factors may play an important role. Future studies should further examine the association of both friend PA and psychological variables with adolescent PA.

Stressful Life Events and Child Anxiety: Examining Parent and Child Mediators.

PubMed

Platt, Rheanna; Williams, Sarah R; Ginsburg, Golda S

2016-02-01

While a number of factors have been linked with excessive anxiety (e.g., parenting, child temperament), the impact of stressful life events remains under-studied. Moreover, much of this literature has examined bivariate associations rather than testing more complex theoretical models. The current study extends the literature on life events and child anxiety by testing a theory-driven meditational model. Specifically, one child factor (child cognitions/locus of control), two parent factors (parent psychopathology and parenting stress), and two parent-child relationship factors (parent-child dysfunctional interaction and parenting style) were examined as mediators in the relationship between stressful life events and severity of child anxiety. One hundred and thirty anxious parents and their nonanxious, high-risk children (ages ranged from 7 to 13 years) participated in this study. Results indicated that levels of parenting stress, parental anxious rearing, and dysfunctional parent-child interaction mediated the association between stressful life events and severity of anxiety symptoms. Child cognition and parent psychopathology factors failed to emerge as mediators. Findings provide support for more complex theoretical models linking life events and child anxiety and suggest potential targets of intervention.

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

PubMed Central

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

2011-01-01

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

Sustainability of cross-functional teams for marketing strategy development and implementation.

PubMed

Kono, Ken; Antonucci, Don

2006-01-01

This article presents a case study on a cross-functional team used for marketing strategy development and execution at a health insurance company. The study found a set of success factors that contributed to the initial success of the team, but the factors were not enough to maintain the team's high level of productivity over time. The study later identified a set of 8 factors that helped sustain the team's high-productivity level. The 2 sets (ie, success and its subsequent sustainability factors) are analyzed against a normative model of team effectiveness. All the factors are explained by the normative model except for 1 sustainability factor, "challenge motivator." In fact, the study found the "challenge motivator" to be the most critical factor to keep up the team's productivity over time. Apart from a performance crisis, the authors developed 3 "challenge motivators"--first, more granular market information that could unearth hidden performance issues; second, constant value creation to shareholders as the firm being publicly traded; and third, the firm's strategic mandate to meet and exceed customer expectations that puts ultimate performance pressure on the marketing strategy team.

Parenting Practices and Adolescent Sexual Behavior: A Longitudinal Study

ERIC Educational Resources Information Center

Bersamin, Melina; Todd, Michael; Fisher, Deborah A.; Hill, Douglas L.; Grube, Joel W.; Walker, Samantha

2008-01-01

The effects of parental attitudes, practices, and television mediation on adolescent sexual behaviors were investigated in a study of adolescent sexuality and media (N = 887). Confirmatory factor analyses supported an eight-factor parenting model with television mediation factors as constructs distinct from general parenting practices. Logistic…

Five-Factor Screener in the 2005 National Health Interview Survey Cancer Control Supplement: Validation Results

Cancer.gov

Risk Factor Assessment Branch staff have assessed indirectly the validity of parts of the Five-Factor Screener in two studies: NCI's Observing Protein and Energy (OPEN) Study and the Eating at America's Table Study (EATS). In both studies, multiple 24-hour recalls in conjunction with a measurement error model were used to assess validity.

Maternal factors contributing to under-five mortality at birth order 1 to 5 in India: a comprehensive multivariate study.

PubMed

Singh, Rajvir; Tripathi, Vrijesh

2013-01-01

The objective of the study is to assess maternal factors contributing to under-five mortality at birth order 1 to 5 in India. Data for this study was derived from the children's record of the 2007 India National Family Health Survey, which is a nationally representative cross-sectional household survey. Data is segregated according to birth order 1 to 5 to assess mother's occupation, Mother's education, child's gender, Mother's age, place of residence, wealth index, mother's anaemia level, prenatal care, assistance at delivery , antenatal care, place of delivery and other maternal factors contributing to under-five mortality. Out of total 51555 births, analysis is restricted to 16567 children of first birth order, 14409 of second birth order, 8318 of third birth order, 5021 of fourth birth order and 3034 of fifth birth order covering 92% of the total births taken place 0-59 months prior to survey. Mother's average age in years for birth orders 1 to 5 are 23.7, 25.8, 27.4, 29 and 31 years, respectively. Most mothers whose children died are Hindu, with no formal education, severely anaemic and working in the agricultural sector. In multivariate logistic models, maternal education, wealth index and breastfeeding are protective factors across all birth orders. In birth order model 1 and 2, mother's occupation is a significant risk factor. In birth order models 2 to 5, previous birth interval of lesser than 24 months is a risk factor. Child's gender is a risk factor in birth order 1 and 5. Information regarding complications in pregnancy and prenatal care act as protective factors in birth order 1, place of delivery and immunization in birth order 2, and child size at birth in birth order 4. Prediction models demonstrate high discrimination that indicates that our models fit the data. The study has policy implications such as enhancing the Information, Education and Communication network for mothers, especially at higher birth orders, in order to reduce under-five mortality. The study emphasises the need of developing interventions to address the issues of anaemia, mothers working in the agricultural sector and improving relevant literacy among mothers.

Venous Thrombosis Risk after Cast Immobilization of the Lower Extremity: Derivation and Validation of a Clinical Prediction Score, L-TRiP(cast), in Three Population-Based Case–Control Studies

PubMed Central

Nemeth, Banne; van Adrichem, Raymond A.; van Hylckama Vlieg, Astrid; Bucciarelli, Paolo; Martinelli, Ida; Baglin, Trevor; Rosendaal, Frits R.; le Cessie, Saskia; Cannegieter, Suzanne C.

2015-01-01

Background Guidelines and clinical practice vary considerably with respect to thrombosis prophylaxis during plaster cast immobilization of the lower extremity. Identifying patients at high risk for the development of venous thromboembolism (VTE) would provide a basis for considering individual thromboprophylaxis use and planning treatment studies. The aims of this study were (1) to investigate the predictive value of genetic and environmental risk factors, levels of coagulation factors, and other biomarkers for the occurrence of VTE after cast immobilization of the lower extremity and (2) to develop a clinical prediction tool for the prediction of VTE in plaster cast patients. Methods and Findings We used data from a large population-based case–control study (MEGA study, 4,446 cases with VTE, 6,118 controls without) designed to identify risk factors for a first VTE. Cases were recruited from six anticoagulation clinics in the Netherlands between 1999 and 2004; controls were their partners or individuals identified via random digit dialing. Identification of predictor variables to be included in the model was based on reported associations in the literature or on a relative risk (odds ratio) > 1.2 and p ≤ 0.25 in the univariate analysis of all participants. Using multivariate logistic regression, a full prediction model was created. In addition to the full model (all variables), a restricted model (minimum number of predictors with a maximum predictive value) and a clinical model (environmental risk factors only, no blood draw or assays required) were created. To determine the discriminatory power in patients with cast immobilization (n = 230), the area under the curve (AUC) was calculated by means of a receiver operating characteristic. Validation was performed in two other case–control studies of the etiology of VTE: (1) the THE-VTE study, a two-center, population-based case–control study (conducted in Leiden, the Netherlands, and Cambridge, United Kingdom) with 784 cases and 523 controls included between March 2003 and December 2008 and (2) the Milan study, a population-based case–control study with 2,117 cases and 2,088 controls selected between December 1993 and December 2010 at the Thrombosis Center, Fondazione IRCCS Ca’ Granda–Ospedale Maggiore Policlinico, Milan, Italy. The full model consisted of 32 predictors, including three genetic factors and six biomarkers. For this model, an AUC of 0.85 (95% CI 0.77–0.92) was found in individuals with plaster cast immobilization of the lower extremity. The AUC for the restricted model (containing 11 predictors, including two genetic factors and one biomarker) was 0.84 (95% CI 0.77–0.92). The clinical model (consisting of 14 environmental predictors) resulted in an AUC of 0.77 (95% CI 0.66–0.87). The clinical model was converted into a risk score, the L-TRiP(cast) score (Leiden–Thrombosis Risk Prediction for patients with cast immobilization score), which showed an AUC of 0.76 (95% CI 0.66–0.86). Validation in the THE-VTE study data resulted in an AUC of 0.77 (95% CI 0.58–0.96) for the L-TRiP(cast) score. Validation in the Milan study resulted in an AUC of 0.93 (95% CI 0.86–1.00) for the full model, an AUC of 0.92 (95% CI 0.76–0.87) for the restricted model, and an AUC of 0.96 (95% CI 0.92–0.99) for the clinical model. The L-TRiP(cast) score resulted in an AUC of 0.95 (95% CI 0.91–0.99). Major limitations of this study were that information on thromboprophylaxis was not available for patients who had plaster cast immobilization of the lower extremity and that blood was drawn 3 mo after the thrombotic event. Conclusions These results show that information on environmental risk factors, coagulation factors, and genetic determinants in patients with plaster casts leads to high accuracy in the prediction of VTE risk. In daily practice, the clinical model may be the preferred model as its factors are most easy to determine, while the model still has good predictive performance. These results may provide guidance for thromboprophylaxis and form the basis for a management study. PMID:26554832

Comparing Factor, Class, and Mixture Models of Cannabis Initiation and DSM Cannabis Use Disorder Criteria, Including Craving, in the Brisbane Longitudinal Twin Study

PubMed Central

Kubarych, Thomas S.; Kendler, Kenneth S.; Aggen, Steven H.; Estabrook, Ryne; Edwards, Alexis C.; Clark, Shaunna L.; Martin, Nicholas G.; Hickie, Ian B.; Neale, Michael C.; Gillespie, Nathan A.

2014-01-01

Accumulating evidence suggests that the Diagnostic and Statistical Manual of Mental Disorders (DSM) diagnostic criteria for cannabis abuse and dependence are best represented by a single underlying factor. However, it remains possible that models with additional factors, or latent class models or hybrid models, may better explain the data. Using structured interviews, 626 adult male and female twins provided complete data on symptoms of cannabis abuse and dependence, plus a craving criterion. We compared latent factor analysis, latent class analysis, and factor mixture modeling using normal theory marginal maximum likelihood for ordinal data. Our aim was to derive a parsimonious, best-fitting cannabis use disorder (CUD) phenotype based on DSM-IV criteria and determine whether DSM-5 craving loads onto a general factor. When compared with latent class and mixture models, factor models provided a better fit to the data. When conditioned on initiation and cannabis use, the association between criteria for abuse, dependence, withdrawal, and craving were best explained by two correlated latent factors for males and females: a general risk factor to CUD and a factor capturing the symptoms of social and occupational impairment as a consequence of frequent use. Secondary analyses revealed a modest increase in the prevalence of DSM-5 CUD compared with DSM-IV cannabis abuse or dependence. It is concluded that, in addition to a general factor with loadings on cannabis use and symptoms of abuse, dependence, withdrawal, and craving, a second clinically relevant factor defined by features of social and occupational impairment was also found for frequent cannabis use. PMID:24588857

On the factor structure of the Rosenberg (1965) General Self-Esteem Scale.

PubMed

Alessandri, Guido; Vecchione, Michele; Eisenberg, Nancy; Łaguna, Mariola

2015-06-01

Since its introduction, the Rosenberg General Self-Esteem Scale (RGSE, Rosenberg, 1965) has been 1 of the most widely used measures of global self-esteem. We conducted 4 studies to investigate (a) the goodness-of-fit of a bifactor model positing a general self-esteem (GSE) factor and 2 specific factors grouping positive (MFP) and negative items (MFN) and (b) different kinds of validity of the GSE, MFN, and MFP factors of the RSGE. In the first study (n = 11,028), the fit of the bifactor model was compared with those of 9 alternative models proposed in literature for the RGSE. In Study 2 (n = 357), the external validities of GSE, MFP, and MFN were evaluated using objective grade point average data and multimethod measures of prosociality, aggression, and depression. In Study 3 (n = 565), the across-rater robustness of the bifactor model was evaluated. In Study 4, measurement invariance of the RGSE was further supported across samples in 3 European countries, Serbia (n = 1,010), Poland (n = 699), and Italy (n = 707), and in the United States (n = 1,192). All in all, psychometric findings corroborate the value and the robustness of the bifactor structure and its substantive interpretation. (c) 2015 APA, all rights reserved).

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

PubMed

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

2015-12-15

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

Regression-Based Norms for a Bi-factor Model for Scoring the Brief Test of Adult Cognition by Telephone (BTACT).

PubMed

Gurnani, Ashita S; John, Samantha E; Gavett, Brandon E

2015-05-01

The current study developed regression-based normative adjustments for a bi-factor model of the The Brief Test of Adult Cognition by Telephone (BTACT). Archival data from the Midlife Development in the United States-II Cognitive Project were used to develop eight separate linear regression models that predicted bi-factor BTACT scores, accounting for age, education, gender, and occupation-alone and in various combinations. All regression models provided statistically significant fit to the data. A three-predictor regression model fit best and accounted for 32.8% of the variance in the global bi-factor BTACT score. The fit of the regression models was not improved by gender. Eight different regression models are presented to allow the user flexibility in applying demographic corrections to the bi-factor BTACT scores. Occupation corrections, while not widely used, may provide useful demographic adjustments for adult populations or for those individuals who have attained an occupational status not commensurate with expected educational attainment. © The Author 2015. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

The accuracy of climate models' simulated season lengths and the effectiveness of grid scale correction factors

DOE PAGES

Winterhalter, Wade E.

2011-09-01

Global climate change is expected to impact biological populations through a variety of mechanisms including increases in the length of their growing season. Climate models are useful tools for predicting how season length might change in the future. However, the accuracy of these models tends to be rather low at regional geographic scales. Here, I determined the ability of several atmosphere and ocean general circulating models (AOGCMs) to accurately simulate historical season lengths for a temperate ectotherm across the continental United States. I also evaluated the effectiveness of regional-scale correction factors to improve the accuracy of these models. I foundmore » that both the accuracy of simulated season lengths and the effectiveness of the correction factors to improve the model's accuracy varied geographically and across models. These results suggest that regional specific correction factors do not always adequately remove potential discrepancies between simulated and historically observed environmental parameters. As such, an explicit evaluation of the correction factors' effectiveness should be included in future studies of global climate change's impact on biological populations.« less

A flow resistance model for assessing the impact of vegetation on flood routing mechanics

NASA Astrophysics Data System (ADS)

Katul, Gabriel G.; Poggi, Davide; Ridolfi, Luca

2011-08-01

The specification of a flow resistance factor to account for vegetative effects in the Saint-Venant equation (SVE) remains uncertain and is a subject of active research in flood routing mechanics. Here, an analytical model for the flow resistance factor is proposed for submerged vegetation, where the water depth is commensurate with the canopy height and the roughness Reynolds number is sufficiently large so as to ignore viscous effects. The analytical model predicts that the resistance factor varies with three canonical length scales: the adjustment length scale that depends on the foliage drag and leaf area density, the canopy height, and the water level. These length scales can reasonably be inferred from a range of remote sensing products making the proposed flow resistance model eminently suitable for operational flood routing. Despite the numerous simplifications, agreement between measured and modeled resistance factors and bulk velocities is reasonable across a range of experimental and field studies. The proposed model asymptotically recovers the flow resistance formulation when the water depth greatly exceeds the canopy height. This analytical treatment provides a unifying framework that links the resistance factor to a number of concepts and length scales already in use to describe canopy turbulence. The implications of the coupling between the resistance factor and the water depth on solutions to the SVE are explored via a case study, which shows a reasonable match between empirical design standard and theoretical predictions.

Sufficient Forecasting Using Factor Models

PubMed Central

Fan, Jianqing; Xue, Lingzhou; Yao, Jiawei

2017-01-01

We consider forecasting a single time series when there is a large number of predictors and a possible nonlinear effect. The dimensionality was first reduced via a high-dimensional (approximate) factor model implemented by the principal component analysis. Using the extracted factors, we develop a novel forecasting method called the sufficient forecasting, which provides a set of sufficient predictive indices, inferred from high-dimensional predictors, to deliver additional predictive power. The projected principal component analysis will be employed to enhance the accuracy of inferred factors when a semi-parametric (approximate) factor model is assumed. Our method is also applicable to cross-sectional sufficient regression using extracted factors. The connection between the sufficient forecasting and the deep learning architecture is explicitly stated. The sufficient forecasting correctly estimates projection indices of the underlying factors even in the presence of a nonparametric forecasting function. The proposed method extends the sufficient dimension reduction to high-dimensional regimes by condensing the cross-sectional information through factor models. We derive asymptotic properties for the estimate of the central subspace spanned by these projection directions as well as the estimates of the sufficient predictive indices. We further show that the natural method of running multiple regression of target on estimated factors yields a linear estimate that actually falls into this central subspace. Our method and theory allow the number of predictors to be larger than the number of observations. We finally demonstrate that the sufficient forecasting improves upon the linear forecasting in both simulation studies and an empirical study of forecasting macroeconomic variables. PMID:29731537

A Multilevel Modelling Approach to Investigating Factors Impacting Science Achievement for Secondary School Students: PISA Hong Kong Sample

ERIC Educational Resources Information Center

Sun, Letao; Bradley, Kelly D.; Akers, Kathryn

2012-01-01

This study utilized data from the 2006 Programme for International Student Assessment Hong Kong sample to investigate the factors that impact the science achievement of 15-year-old students. A multilevel model was used to examine the factors from both student and school perspectives. At the student level, the results indicated that male students,…

Exploring the Different Trajectories of Analytical Thinking Ability Factors: An Application of the Second-Order Growth Curve Factor Model

ERIC Educational Resources Information Center

Saengprom, Narumon; Erawan, Waraporn; Damrongpanit, Suntonrapot; Sakulku, Jaruwan

2015-01-01

The purposes of this study were 1) Compare analytical thinking ability by testing the same sets of students 5 times 2) Develop and verify whether analytical thinking ability of students corresponds to second-order growth curve factors model. Samples were 1,093 eighth-grade students. The results revealed that 1) Analytical thinking ability scores…

Examining the Factor Structure and Discriminant Validity of the 12-Item General Health Questionnaire (GHQ-12) Among Spanish Postpartum Women

ERIC Educational Resources Information Center

Aguado, Jaume; Campbell, Alistair; Ascaso, Carlos; Navarro, Purificacion; Garcia-Esteve, Lluisa; Luciano, Juan V.

2012-01-01

In this study, the authors tested alternative factor models of the 12-item General Health Questionnaire (GHQ-12) in a sample of Spanish postpartum women, using confirmatory factor analysis. The authors report the results of modeling three different methods for scoring the GHQ-12 using estimation methods recommended for categorical and binary data.…

[Psychometric properties of the French version of the Effort-Reward Imbalance model].

PubMed

Niedhammer, I; Siegrist, J; Landre, M F; Goldberg, M; Leclerc, A

2000-10-01

Two main models are currently used to evaluate psychosocial factors at work: the Job Strain model developed by Karasek and the Effort-Reward Imbalance model. A French version of the first model has been validated for the dimensions of psychological demands and decision latitude. As regards the second one evaluating three dimensions (extrinsic effort, reward, and intrinsic effort), there are several versions in different languages, but until recently there was no validated French version. The objective of this study was to explore the psychometric properties of the French version of the Effort-Reward Imbalance model in terms of internal consistency, factorial validity, and discriminant validity. The present study was based on the GAZEL cohort and included the 10 174 subjects who were working at the French national electric and gas company (EDF-GDF) and answered the questionnaire in 1998. A French version of Effort-Reward Imbalance was included in this questionnaire. This version was obtained by a standard forward/backward translation procedure. Internal consistency was satisfactory for the three scales of extrinsic effort, reward, and intrinsic effort: Cronbach's Alpha coefficients higher than 0.7 were observed. A one-factor solution was retained for the factor analysis of the scale of extrinsic effort. A three-factor solution was retained for the factor analysis of reward, and these dimensions were interpreted as the factor analysis of intrinsic effort did not support the expected four-dimension structure. The analysis of discriminant validity displayed significant associations between measures of Effort-Reward Imbalance and the variables of sex, age, education level, and occupational grade. This study is the first one supporting satisfactory psychometric properties of the French version of the Effort-Reward Imbalance model. However, the factorial validity of intrinsic effort could be questioned. Furthermore, as most previous studies were based on male samples working in specific occupations, the present one is also one of the first to show strong associations between measures of this model and social class variables in a population of men and women employed in various occupations.

Dimensionality of DSM-5 posttraumatic stress disorder and its association with suicide attempts: results from the National Epidemiologic Survey on Alcohol and Related Conditions-III.

PubMed

Chen, Chiung M; Yoon, Young-Hee; Harford, Thomas C; Grant, Bridget F

2017-06-01

Emerging confirmatory factor analytic (CFA) studies suggest that posttraumatic stress disorder (PTSD) as defined by the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (DSM-5) is best characterized by seven factors, including re-experiencing, avoidance, negative affect, anhedonia, externalizing behaviors, and anxious and dysphoric arousal. The seven factors, however, have been found to be highly correlated, suggesting that one general factor may exist to explain the overall correlations among symptoms. Using data from the National Epidemiologic Survey on Alcohol and Related Conditions-III, a large, national survey of 36,309 U.S. adults ages 18 and older, this study proposed and tested an exploratory bifactor hybrid model for DSM-5 PTSD symptoms. The model posited one general and seven specific latent factors, whose associations with suicide attempts and mediating psychiatric disorders were used to validate the PTSD dimensionality. The exploratory bifactor hybrid model fitted the data extremely well, outperforming the 7-factor CFA hybrid model and other competing CFA models. The general factor was found to be the single dominant latent trait that explained most of the common variance (~76%) and showed significant, positive associations with suicide attempts and mediating psychiatric disorders, offering support to the concurrent validity of the PTSD construct. The identification of the primary latent trait of PTSD confirms PTSD as an independent psychiatric disorder and helps define PTSD severity in clinical practice and for etiologic research. The accurate specification of PTSD factor structure has implications for treatment efforts and the prevention of suicidal behaviors.

Dependence and physical exercise: Spanish validation of the Exercise Dependence Scale-Revised (EDS-R).

PubMed

Sicilia, Alvaro; González-Cutre, David

2011-05-01

The purpose of this study was to validate the Spanish version of the Exercise Dependence Scale-Revised (EDS-R). To achieve this goal, a sample of 531 sport center users was used and the psychometric properties of the EDS-R were examined through different analyses. The results supported both the first-order seven-factor model and the higher-order model (seven first-order factors and one second-order factor). The structure of both models was invariant across age. Correlations among the subscales indicated a related factor model, supporting construct validity of the scale. Alpha values over .70 (except for Reduction in Other Activities) and suitable levels of temporal stability were obtained. Users practicing more than three days per week had higher scores in all subscales than the group practicing with a frequency of three days or fewer. The findings of this study provided reliability and validity for the EDS-R in a Spanish context.

Studying the Impacts of Environmental Factors and Agricultural Management on Methane Emissions from Rice Paddies Using a Land Surface Model

NASA Astrophysics Data System (ADS)

Lin, T. S.; Gahlot, S.; Shu, S.; Jain, A. K.; Kheshgi, H. S.

2017-12-01

Continued growth in population is projected to drive increased future demand for rice and the methane emissions associated with its production. However, observational studies of methane emissions from rice have reported seemingly conflicting results and do not all support this projection. In this study we couple an ecophysiological process-based rice paddy module and a methane emission module with a land surface model, Integrated Science Assessment Model (ISAM), to study the impacts of various environmental factors and agricultural management practices on rice production and methane emissions from rice fields. This coupled modeling framework accounts for dynamic rice growth processes with adaptation of photosynthesis, rice-specific phenology, biomass accumulation, leaf area development and structures responses to water, temperature, light and nutrient stresses. The coupled model is calibrated and validated with observations from various rice cultivation fields. We find that the differing results of observational studies can be caused by the interactions of environmental factors, including climate, atmospheric CO2 concentration, and N deposition, and agricultural management practices, such as irrigation and N fertilizer applications, with rice production at spatial and temporal scales.

Event-based rainfall-runoff modelling of the Kelantan River Basin

NASA Astrophysics Data System (ADS)

Basarudin, Z.; Adnan, N. A.; Latif, A. R. A.; Tahir, W.; Syafiqah, N.

2014-02-01

Flood is one of the most common natural disasters in Malaysia. According to hydrologists there are many causes that contribute to flood events. The two most dominant factors are the meteorology factor (i.e climate change) and change in land use. These two factors contributed to floods in recent decade especially in the monsoonal catchment such as Malaysia. This paper intends to quantify the influence of rainfall during extreme rainfall events on the hydrological model in the Kelantan River catchment. Therefore, two dynamic inputs were used in the study: rainfall and river discharge. The extreme flood events in 2008 and 2004 were compared based on rainfall data for both years. The events were modeled via a semi-distributed HEC-HMS hydrological model. Land use change was not incorporated in the study because the study only tries to quantify rainfall changes during these two events to simulate the discharge and runoff value. Therefore, the land use data representing the year 2004 were used as inputs in the 2008 runoff model. The study managed to demonstrate that rainfall change has a significant impact to determine the peak discharge and runoff depth for the study area.

Risk factors for invasive fungal disease in critically ill adult patients: a systematic review.

PubMed

Muskett, Hannah; Shahin, Jason; Eyres, Gavin; Harvey, Sheila; Rowan, Kathy; Harrison, David

2011-01-01

Over 5,000 cases of invasive Candida species infections occur in the United Kingdom each year, and around 40% of these cases occur in critical care units. Invasive fungal disease (IFD) in critically ill patients is associated with increased morbidity and mortality at a cost to both the individual and the National Health Service. In this paper, we report the results of a systematic review performed to identify and summarise the important risk factors derived from published multivariable analyses, risk prediction models and clinical decision rules for IFD in critically ill adult patients to inform the primary data collection for the Fungal Infection Risk Evaluation Study. An internet search was performed to identify articles which investigated risk factors, risk prediction models or clinical decisions rules for IFD in critically ill adult patients. Eligible articles were identified in a staged process and were assessed by two investigators independently. The methodological quality of the reporting of the eligible articles was assessed using a set of questions addressing both general and statistical methodologies. Thirteen articles met the inclusion criteria, of which eight articles examined risk factors, four developed a risk prediction model or clinical decision rule and one evaluated a clinical decision rule. Studies varied in terms of objectives, risk factors, definitions and outcomes. The following risk factors were found in multiple studies to be significantly associated with IFD: surgery, total parenteral nutrition, fungal colonisation, renal replacement therapy, infection and/or sepsis, mechanical ventilation, diabetes, and Acute Physiology and Chronic Health Evaluation II (APACHE II) or APACHE III score. Several other risk factors were also found to be statistically significant in single studies only. Risk factor selection process and modelling strategy also varied across studies, and sample sizes were inadequate for obtaining reliable estimates. This review shows a number of risk factors to be significantly associated with the development of IFD in critically ill adults. Methodological limitations were identified in the design and conduct of studies in this area, and caution should be used in their interpretation.

Risk factors for invasive fungal disease in critically ill adult patients: a systematic review

PubMed Central

2011-01-01

Introduction Over 5,000 cases of invasive Candida species infections occur in the United Kingdom each year, and around 40% of these cases occur in critical care units. Invasive fungal disease (IFD) in critically ill patients is associated with increased morbidity and mortality at a cost to both the individual and the National Health Service. In this paper, we report the results of a systematic review performed to identify and summarise the important risk factors derived from published multivariable analyses, risk prediction models and clinical decision rules for IFD in critically ill adult patients to inform the primary data collection for the Fungal Infection Risk Evaluation Study. Methods An internet search was performed to identify articles which investigated risk factors, risk prediction models or clinical decisions rules for IFD in critically ill adult patients. Eligible articles were identified in a staged process and were assessed by two investigators independently. The methodological quality of the reporting of the eligible articles was assessed using a set of questions addressing both general and statistical methodologies. Results Thirteen articles met the inclusion criteria, of which eight articles examined risk factors, four developed a risk prediction model or clinical decision rule and one evaluated a clinical decision rule. Studies varied in terms of objectives, risk factors, definitions and outcomes. The following risk factors were found in multiple studies to be significantly associated with IFD: surgery, total parenteral nutrition, fungal colonisation, renal replacement therapy, infection and/or sepsis, mechanical ventilation, diabetes, and Acute Physiology and Chronic Health Evaluation II (APACHE II) or APACHE III score. Several other risk factors were also found to be statistically significant in single studies only. Risk factor selection process and modelling strategy also varied across studies, and sample sizes were inadequate for obtaining reliable estimates. Conclusions This review shows a number of risk factors to be significantly associated with the development of IFD in critically ill adults. Methodological limitations were identified in the design and conduct of studies in this area, and caution should be used in their interpretation. PMID:22126425

A resilience-based model for performance evaluation of information systems: the case of a gas company

NASA Astrophysics Data System (ADS)

Azadeh, A.; Salehi, V.; Salehi, R.

2017-10-01

Information systems (IS) are strongly influenced by changes in new technology and should react swiftly in response to external conditions. Resilience engineering is a new method that can enable these systems to absorb changes. In this study, a new framework is presented for performance evaluation of IS that includes DeLone and McLean's factors of success in addition to resilience. Hence, this study is an attempt to evaluate the impact of resilience on IS by the proposed model in Iranian Gas Engineering and Development Company via the data obtained from questionnaires and Fuzzy Data Envelopment Analysis (FDEA) approach. First, FDEA model with α-cut = 0.05 was identified as the most suitable model to this application by performing all Banker, Charnes and Cooper and Charnes, Cooper and Rhodes models of and FDEA and selecting the appropriate model based on maximum mean efficiency. Then, the factors were ranked based on the results of sensitivity analysis, which showed resilience had a significantly higher impact on the proposed model relative to other factors. The results of this study were then verified by conducting the related ANOVA test. This is the first study that examines the impact of resilience on IS by statistical and mathematical approaches.

The prevalence and structure of obsessive-compulsive personality disorder in Hispanic psychiatric outpatients

PubMed Central

Ansell, Emily B.; Pinto, Anthony; Crosby, Ross D.; Becker, Daniel F.; Añez, Luis M.; Paris, Manuel; Grilo, Carlos M.

2010-01-01

This study sought to confirm a multi-factor model of Obsessive-compulsive personality disorder (OCPD) in a Hispanic outpatient sample and to explore associations of the OCPD factors with aggression, depression, and suicidal thoughts. One hundred and thirty monolingual, Spanish-speaking participants were recruited from a community mental health center and were assessed by bilingual doctoral level clinicians. OCPD was highly prevalent (26%) in this sample. Multi-factor models of OCPD were tested and the two factors - perfectionism and interpersonal rigidity - provided the best model fit. Interpersonal rigidity was associated with aggression and anger while perfectionism was associated with depression and suicidal thoughts. PMID:20227063

Cross-Cultural Validation of the Preventive Health Model for Colorectal Cancer Screening: An Australian Study

ERIC Educational Resources Information Center

Flight, Ingrid H.; Wilson, Carlene J.; McGillivray, Jane; Myers, Ronald E.

2010-01-01

We investigated whether the five-factor structure of the Preventive Health Model for colorectal cancer screening, developed in the United States, has validity in Australia. We also tested extending the model with the addition of the factor Self-Efficacy to Screen using Fecal Occult Blood Test (SESFOBT). Randomly selected men and women aged between…

Comparison of the sensitivity of landscape-fire-succession models to variation in terrain, fuel pattern, climate and weather

Treesearch

Geoffrey J. Cary; Robert E. Keane; Robert H. Gardner; Sandra Lavorel; Michael D. Flannigan; Ian D. Davies; Chao Li; James M. Lenihan; T. Scott Rupp; Florent Mouillot

2006-01-01

The purpose of this study was to compare the sensitivity of modelled area burned to environmental factors across a range of independently-developed landscape-fire-succession models. The sensitivity of area burned to variation in four factors, namely terrain (flat, undulating and mountainous), fuel pattern (finely and coarsely clumped), climate (observed, warmer &...

Body Dissatisfaction and Eating Disturbances in Early Adolescence: A Structural Modeling Investigation Examining Negative Affect and Peer Factors

ERIC Educational Resources Information Center

Hutchinson, Delyse M.; Rapee, Ronald M.; Taylor, Alan

2010-01-01

This study tested five proposed models of the relationship of negative affect and peer factors in early adolescent body dissatisfaction, dieting, and bulimic behaviors. A large community sample of girls in early adolescence was assessed via questionnaire (X[overbar] age = 12.3 years). Structural equation modeling (SEM) indicated that negative…

The Longitudinal Stability and Dynamics of Group Membership in the Dual-Factor Model of Mental Health: Psychosocial Predictors of Mental Health

ERIC Educational Resources Information Center

Kelly, Ryan M.; Hills, Kimberly J.; Huebner, E. Scott; McQuillin, Samuel D.

2012-01-01

This study examined the longitudinal stability and dynamics of group membership within the Greenspoon and Sakflofske's dual-factor model of mental health. This expanded model incorporates information about subjective well-being (SWB), in addition to psychopathological symptoms, to better identify the mental health status and current functioning of…

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

PubMed

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

2017-06-01

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

Mining nutrigenetics patterns related to obesity: use of parallel multifactor dimensionality reduction.

PubMed

Karayianni, Katerina N; Grimaldi, Keith A; Nikita, Konstantina S; Valavanis, Ioannis K

2015-01-01

This paper aims to enlighten the complex etiology beneath obesity by analysing data from a large nutrigenetics study, in which nutritional and genetic factors associated with obesity were recorded for around two thousand individuals. In our previous work, these data have been analysed using artificial neural network methods, which identified optimised subsets of factors to predict one's obesity status. These methods did not reveal though how the selected factors interact with each other in the obtained predictive models. For that reason, parallel Multifactor Dimensionality Reduction (pMDR) was used here to further analyse the pre-selected subsets of nutrigenetic factors. Within pMDR, predictive models using up to eight factors were constructed, further reducing the input dimensionality, while rules describing the interactive effects of the selected factors were derived. In this way, it was possible to identify specific genetic variations and their interactive effects with particular nutritional factors, which are now under further study.

Post-Partum Depression, Personality, and Cognitive-Emotional Factors: A Longitudinal Study on Spanish Pregnant Women.

PubMed

Peñacoba-Puente, Cecilia; Marín-Morales, Dolores; Carmona-Monge, Francisco Javier; Velasco Furlong, Lilian

2016-01-01

In this study, our purpose was to examine whether personality and cognitive factors could be related to post-partum depression (PPD), mediated by anxiety, in Spanish women. Women were evaluated for personality and cognitive factors after the first trimester, for anxiety in the third trimester, and for PPD 4 months after childbirth. A structural equation model revealed that personality and cognitive factors were associated with anxiety and PPD as predictors. Neuroticism and extroversion proved to be the most relevant factors. Conscientiousness was associated with pregnancy anxiety. Pregnancy anxiety appeared as an independent predictor of PPD. The model presented here includes personality and cognitive and emotional factors as predictors of PPD. Comprehensive care for pregnant women should contemplate assessment and intervention on all these aspects. Special focus should be on cognitive factors and emotional regulation strategies, so as to minimize the risk of later development of emotional disorders during puerperal phases.

Psychological Factors in the Development of Football-Talent from the Perspective of an Integrative Sport-Talent Model

ERIC Educational Resources Information Center

Orosz, Robert; Mezo, Ferenc

2015-01-01

This study presents a new, integrative model of sports talent. Following the theoretical part of the study a football-talent research is presented, in which a theoretical framework is provided by this new theory of sports talent. This research examines the role of psychological factors in football talent development. The sample was N = 425…

Regression Levels of Selected Affective Factors on Science Achievement: A Structural Equation Model with TIMSS 2011 Data

ERIC Educational Resources Information Center

Akilli, Mustafa

2015-01-01

The aim of this study is to demonstrate the science success regression levels of chosen emotional features of 8th grade students using Structural Equation Model. The study was conducted by the analysis of students' questionnaires and science success in TIMSS 2011 data using SEM. Initially, the factors that are thought to have an effect on science…

Systematic Review of Smoking Initiation among Asian Adolescents, 20052015: Utilizing the Frameworks of Triadic Influence and Planned Behavior.

PubMed

Talip, Tajidah; Murang, Zaidah; Kifli, Nurolaini; Naing, Lin

2016-01-01

A recent WHO data report on mortality attributable to tobacco use including cigarette smoking indicated a very high burden of deaths in Asia and that people often initiate smoking as early as young adolescents. The objectives of this study were to systematically review peerreviewed articles on cigarette smoking initiation among Asian adolescents and to develop a conceptual model of factors influencing smoking initiation by integrating all relevant factors based on existing data. Following a PRISMA guideline, a systematic review of articles published between 2005 and June 2015 was conducted using 5 databases on cigarette smoking initiation among adolescents (aged 1019 years) living in Asia. We summarized the main findings of each study according to our research questions and data that emerged during the data extraction process. Analysis and categorization were based on the TTI and TPB models and classification of factors extracted from the study, were as follows: personal factors, social factors, broader environmental factors, mediators, and intention to initiate smoking and smoking behavior. Of 1,227 identified studies, only 20 were included in this review. Our findings found that the mean age of cigarette smoking initiation ranged from 10 to 14 years and those who are more likely to initiate smoking are male, older adolescents, adolescents with low parental SES, individuals with low parental monitoring, low parental education level and having no discussion on smoking at home, those living in public housing and those exhibiting healthrisk behavior. Our study also revealed that the risk of smoking initiation increased when they are exposed to smokers, influenced by peers, exposed to tobacco advertisements, receive pocket money, have lack of knowledge about smoking, have poor school performance, have a family conflict and have psychological problems. The conceptual model developed demonstrated complex networks of factors influencing initiation. This systematic review presents various factors influencing smoking initiation of the Asian adolescents and provides a conceptual framework to further analyze factors. Future studies should have a standard measure of smoking initiation, should analyze interactions and the intensity of relationships between different factors or variables in the conceptual model. This will in turn consolidate the understanding of the different factors affecting smoking initiation and will help to improve interventions in this area.

Constructing the Japanese version of the Maslach Burnout Inventory-Student Survey: Confirmatory factor analysis.

PubMed

Tsubakita, Takashi; Shimazaki, Kazuyo

2016-01-01

To examine the factorial validity of the Maslach Burnout Inventory-Student Survey, using a sample of 2061 Japanese university students majoring in the medical and natural sciences (67.9% male, 31.8% female; Mage  = 19.6 years, standard deviation = 1.5). The back-translated scale used unreversed items to assess inefficacy. The inventory's descriptive properties and Cronbach's alphas were calculated using SPSS software. The present authors compared fit indices of the null, one factor, and default three factor models via confirmatory factor analysis with maximum-likelihood estimation using AMOS software, version 21.0. Intercorrelations between exhaustion, cynicism, and inefficacy were relatively higher than in prior studies. Cronbach's alphas were 0.76, 0.85, and 0.78, respectively. Although fit indices of the hypothesized three factor model did not meet the respective criteria, the model demonstrated better fit than did the null and one factor models. The present authors added four paths between error variables within items, but the modified model did not show satisfactory fit. Subsequent analysis revealed that a bi-factor model fit the data better than did the hypothesized or modified three factor models. The Japanese version of the Maslach Burnout Inventory-Student Survey needs minor changes to improve the fit of its three factor model, but the scale as a whole can be used to adequately assess overall academic burnout in Japanese university students. Although the scale was back-translated, two items measuring exhaustion whose expressions overlapped should be modified, and all items measuring inefficacy should be reversed in order to statistically clarify the factorial difference between the scale's three factors. © 2015 The Authors. Japan Journal of Nursing Science © 2015 Japan Academy of Nursing Science.

Factor Structure of the Quality of Life Scale for Mental Disorders in Patients With Schizophrenia.

PubMed

Chiu, En-Chi; Lee, Shu-Chun

2018-06-01

The Quality of Life for Mental Disorders (QOLMD) scale was designed to measure health-related quality of life (HRQOL) in patients with mental illness, especially schizophrenia. The QOLMD contains 45 items, which are divided into eight domains. However, the factor structure of the QOLMD has not been evaluated, which restricts the interpretations of the results of this scale. The purpose of this study was to evaluate the factor structures (i.e., unidimensionality, eight-factor structure, and second-order model) of the QOLMD in patients with schizophrenia. Two hundred thirty-eight outpatients with schizophrenia participated. We first conducted confirmatory factor analysis to evaluate the unidimensionality of each domain. After the unidimensionality of the eight individual domains was supported, we examined the eight-factor structure and second-order model. The results of unidimensionality showed sufficient model fit in all of the domains with the exception of the autonomy domain. A good model fit was confirmed for the autonomy domain after deleting two of the original items. The eight-factor structure for the 43-item QOLMD showed an acceptable model fit, although the second-order model showed poor model fit. Our results supported the unidimensionality and eight-factor structure of the 43-item QOLMD. The sum score for each of the domains may be used to reflect its domain-specific function. We recommend using the 43-item QOLMD to capture the multiple domains of HRQOL. However, the second-order model showed an unsatisfactory model fit. Furthermore, caution is advised when interpreting overall HRQOL using the total score for the eight domains.

Drug development costs when financial risk is measured using the Fama-French three-factor model.

PubMed

Vernon, John A; Golec, Joseph H; Dimasi, Joseph A

2010-08-01

In a widely cited article, DiMasi, Hansen, and Grabowski (2003) estimate the average pre-tax cost of bringing a new molecular entity to market. Their base case estimate, excluding post-marketing studies, was $802 million (in $US 2000). Strikingly, almost half of this cost (or $399 million) is the cost of capital (COC) used to fund clinical development expenses to the point of FDA marketing approval. The authors used an 11% real COC computed using the capital asset pricing model (CAPM). But the CAPM is a single factor risk model, and multi-factor risk models are the current state of the art in finance. Using the Fama-French three factor model we find that the cost of drug development to be higher than the earlier estimate. Copyright (c) 2009 John Wiley & Sons, Ltd.

Associations between sociocultural home environmental factors and vegetable consumption among Norwegian 3-5-year olds: BRA-study.

PubMed

Kristiansen, Anne Lene; Bjelland, Mona; Himberg-Sundet, Anne; Lien, Nanna; Frost Andersen, Lene

2017-10-01

The home environment is the first environment to shape childhood dietary habits and food preferences, hence greater understanding of home environmental factors associated with vegetable consumption among young children is needed. The objective has been to examine questionnaire items developed to measure the sociocultural home environment of children focusing on vegetables and to assess the psychometric properties of the resulting factors. Further, to explore associations between the environmental factors and vegetable consumption among Norwegian 3-5 year olds. Parents (n 633) were invited to participate and filled in a questionnaire assessing the child's vegetable intake and factors potentially influencing this, along with a 24-h recall of their child's fruit and vegetable intake. Children's fruit and vegetable intakes at two meals in one day in the kindergarten were observed by researchers. Principal components analysis was used to examine items assessing the sociocultural home environment. Encouragement items resulted in factors labelled "reactive encouragement", "child involvement" and "reward". Modelling items resulted in the factors labelled "active role model" and "practical role model". Items assessing negative parental attitudes resulted in the factor labelled "negative parental attitudes" and items assessing family pressure/demand resulted in the factor labelled "family demand". The psychometric properties of the factors were for most satisfactory. Linear regression of the associations between vegetable intake and the factors showed, as expected, generally positive associations with "child involvement", "practical role model" and "family demand", and negative associations with "negative parental attitudes" and "reward". Unexpectedly, "reactive encouragement" was negatively associated with vegetable consumption. In conclusion, associations between sociocultural home environmental factors and children's vegetable consumption showed both expected and unexpected associations some of which differed by maternal education - pointing to a need for further comparable studies. Copyright © 2017 Elsevier Ltd. All rights reserved.

Analysis of the Environmental Management System based on ISO 14001 on the American continent.

PubMed

Neves, Fábio de Oliveira; Salgado, Eduardo G; Beijo, Luiz A

2017-09-01

The American continent is in broad economic and industrial development. Consequently, a more detailed discussion of the impacts generated by such development is needed. Moreover, there is an increase in the number of ISO 14001 certificates issued to this continent. Given the above, no studies were found that bridge the gap to identify the influence of different factors on ISO 14001 in the Americas. Thus, this article has as its main aim to check which economic, environmental and cultural factors have influence on ISO 14001 Certification in the American Continent. The data were collected in the ISO Survey, World Bank, United Nations Development Programme and International Energy Agency. Among the countries of that continent, thirteen were analyzed and only two did not show the economic factors as the influence factor in the multiple regression models fitted with Brazil and the United State. In these models, all presented environmental factors as influencing factors. Only in Brazil the index HDI presented as cultural factor in multiple regression model fitted. The economic factors: Gross Domestic Product and exports of goods and services and environmental: Carbon Dioxide (CO 2 ) and fossil fuel consumption were the most influential in ISO 14001 certification. Venezuela, Uruguay, Colombia and the United States were countries that had factors dependent on each other, featuring the environmental marketing. Briefly, this study brings up several implications: to the academy, with the proposal of new concepts and guidance on the factors that assist in ISO 14001 certification in the American Continent. Additionally, taking into account the industry, the factors serve as efficiency parameters for the implementation of ISO 14001 standard, and for the Government to improve through factors that do not fit in multiple regression models. Copyright © 2017 Elsevier Ltd. All rights reserved.

The relationship between the effect of pravastatin and risk factors for coronary heart disease in Japanese patients with hypercholesterolemia.

PubMed

Ishikawa, Toshitsugu; Mizuno, Kyoichi; Nakaya, Noriaki; Ohashi, Yasuo; Tajima, Naoko; Kushiro, Toshio; Teramoto, Tamio; Uchiyama, Shinichiro; Nakamura, Haruo

2008-10-01

Several epidemiologic studies in Japan have shown the risk factors for coronary heart disease (CHD) in the general population. The present analysis determined the risk factors for CHD in the MEGA Study, a large primary prevention trial with pravastatin in Japanese with hypercholesterolemia. The relationship between each baseline characteristic and the risk of CHD for the 5-year study period were evaluated using the Cox proportional hazard model. The multivariable predictors of CHD were sex, age, high-density lipoprotein-cholesterol (HDL-C), diabetes mellitus (DM), hypertension (HT), and history of smoking. Serum total and low-density lipoprotein-cholesterol were not independent risk factors for CHD in the current analysis. In addition, the effect of pravastatin was evaluated by subgroups in each risk factor using the interaction in a Cox model. Diet plus pravastatin treatment reduced CHD risk by 14-43% compared with diet alone, regardless of the presence or absence of risk factors. The risk factors for CHD were sex, age, DM, HT, smoking, and low HDL-C in the MEGA Study. The pravastatin treatment was effective for reducing the risk of CHD, regardless of the presence of risk factors.

Joint effects of climate variability and socioecological factors on dengue transmission: epidemiological evidence.

PubMed

Akter, Rokeya; Hu, Wenbiao; Naish, Suchithra; Banu, Shahera; Tong, Shilu

2017-06-01

To assess the epidemiological evidence on the joint effects of climate variability and socioecological factors on dengue transmission. Following PRISMA guidelines, a detailed literature search was conducted in PubMed, Web of Science and Scopus. Peer-reviewed, freely available and full-text articles, considering both climate and socioecological factors in relation to dengue, published in English from January 1993 to October 2015 were included in this review. Twenty studies have met the inclusion criteria and assessed the impact of both climatic and socioecological factors on dengue dynamics. Among those, four studies have further investigated the relative importance of climate variability and socioecological factors on dengue transmission. A few studies also developed predictive models including both climatic and socioecological factors. Due to insufficient data, methodological issues and contextual variability of the studies, it is hard to draw conclusion on the joint effects of climate variability and socioecological factors on dengue transmission. Future research should take into account socioecological factors in combination with climate variables for a better understanding of the complex nature of dengue transmission as well as for improving the predictive capability of dengue forecasting models, to develop effective and reliable early warning systems. © 2017 John Wiley & Sons Ltd.

Attachment change processes in the early years of marriage.

PubMed

Davila, J; Karney, B R; Bradbury, T N

1999-05-01

The authors examined 4 models of attachment change: a contextual model, a social-cognitive model, an individual-difference model, and a diathesis-stress model. Models were examined in a sample of newlyweds over the first 2 years of marriage, using growth curve analyses. Reciprocal processes, whereby attachment representations and interpersonal life circumstances affect one another over time, also were studied. On average, newlyweds became more secure over time. However, there was significant within-subject variability on attachment change that was predicted by intra- and interpersonal factors. Attachment representations changed in response to contextual, social-cognitive, and individual-difference factors. Reciprocal processes between attachment representations and marital variables emerged, suggesting that these factors influence one another in an ongoing way.

Spatial Patterns and Impacts of Environmental and Climatic Factors on Canine Sinonasal Aspergillosis in Northern California

PubMed Central

Magro, Monise; Sykes, Jane; Vishkautsan, Polina; Martínez-López, Beatriz

2017-01-01

Sinonasal aspergillosis (SNA) causes chronic nasal discharge in dogs and has a worldwide distribution, although most reports of SNA in North America originate from the western USA. SNA is mainly caused by Aspergillus fumigatus, a ubiquitous saprophytic filamentous fungus. Infection is thought to follow inhalation of spores. SNA is a disease of the nasal cavity and/or sinuses with variable degrees of local invasion and destruction. While some host factors appear to predispose to SNA (such as belonging to a dolichocephalic breed), environmental risk factors have been scarcely studied. Because A. fumigatus is also the main cause of invasive aspergillosis in humans, unraveling the distribution and the environmental and climatic risk factors for this agent in dogs would be of great benefit for public health studies, advancing understanding of both distribution and risk factors in humans. In this study, we reviewed electronic medical records of 250 dogs diagnosed with SNA between 1990 and 2014 at the University of California Davis Veterinary Medical Teaching Hospital (VMTH). A 145-mile radius catchment area around the VMTH was selected. Data were aggregated by zip code and incorporated into a multivariate logistic regression model. The logistic regression model was compared to an autologistic regression model to evaluate the effect of spatial autocorrelation. Traffic density, active composting sites, and environmental and climatic factors related with wind and temperature were significantly associated with increase in disease occurrence in dogs. Results provide valuable information about the risk factors and spatial distribution of SNA in dogs in Northern California. Our ultimate goal is to utilize the results to investigate risk-based interventions, promote awareness, and serve as a model for further studies of aspergillosis in humans. PMID:28717638

Spatial Patterns and Impacts of Environmental and Climatic Factors on Canine Sinonasal Aspergillosis in Northern California.

PubMed

Magro, Monise; Sykes, Jane; Vishkautsan, Polina; Martínez-López, Beatriz

2017-01-01

Sinonasal aspergillosis (SNA) causes chronic nasal discharge in dogs and has a worldwide distribution, although most reports of SNA in North America originate from the western USA. SNA is mainly caused by Aspergillus fumigatus , a ubiquitous saprophytic filamentous fungus. Infection is thought to follow inhalation of spores. SNA is a disease of the nasal cavity and/or sinuses with variable degrees of local invasion and destruction. While some host factors appear to predispose to SNA (such as belonging to a dolichocephalic breed), environmental risk factors have been scarcely studied. Because A. fumigatus is also the main cause of invasive aspergillosis in humans, unraveling the distribution and the environmental and climatic risk factors for this agent in dogs would be of great benefit for public health studies, advancing understanding of both distribution and risk factors in humans. In this study, we reviewed electronic medical records of 250 dogs diagnosed with SNA between 1990 and 2014 at the University of California Davis Veterinary Medical Teaching Hospital (VMTH). A 145-mile radius catchment area around the VMTH was selected. Data were aggregated by zip code and incorporated into a multivariate logistic regression model. The logistic regression model was compared to an autologistic regression model to evaluate the effect of spatial autocorrelation. Traffic density, active composting sites, and environmental and climatic factors related with wind and temperature were significantly associated with increase in disease occurrence in dogs. Results provide valuable information about the risk factors and spatial distribution of SNA in dogs in Northern California. Our ultimate goal is to utilize the results to investigate risk-based interventions, promote awareness, and serve as a model for further studies of aspergillosis in humans.

Psychosocial work environment factors and weight change: a prospective study among Danish health care workers.

PubMed

Gram Quist, Helle; Christensen, Ulla; Christensen, Karl Bang; Aust, Birgit; Borg, Vilhelm; Bjorner, Jakob B

2013-01-17

Lifestyle variables may serve as important intermediate factors between psychosocial work environment and health outcomes. Previous studies, focussing on work stress models have shown mixed and weak results in relation to weight change. This study aims to investigate psychosocial factors outside the classical work stress models as potential predictors of change in body mass index (BMI) in a population of health care workers. A cohort study, with three years follow-up, was conducted among Danish health care workers (3982 women and 152 men). Logistic regression analyses examined change in BMI (more than +/- 2 kg/m(2)) as predicted by baseline psychosocial work factors (work pace, workload, quality of leadership, influence at work, meaning of work, predictability, commitment, role clarity, and role conflicts) and five covariates (age, cohabitation, physical work demands, type of work position and seniority). Among women, high role conflicts predicted weight gain, while high role clarity predicted both weight gain and weight loss. Living alone also predicted weight gain among women, while older age decreased the odds of weight gain. High leadership quality predicted weight loss among men. Associations were generally weak, with the exception of quality of leadership, age, and cohabitation. This study of a single occupational group suggested a few new risk factors for weight change outside the traditional work stress models.

Factorial validity of an abbreviated neighborhood environment walkability scale for seniors in the Nurses' Health Study.

PubMed

Starnes, Heather A; McDonough, Meghan H; Tamura, Kosuke; James, Peter; Laden, Francine; Troped, Philip J

2014-10-10

Using validated measures of individuals' perceptions of their neighborhood built environment is important for accurately estimating effects on physical activity. However, no studies to date have examined the factorial validity of a measure of perceived neighborhood environment among older adults in the United States. The purpose of this measurement study was to test the factorial validity of a version of the Abbreviated Neighborhood Environment Walkability Scale (NEWS-A) modified for seniors in the Nurses' Health Study (NHS). A random sample of 2,920 female nurses (mean age = 73 ± 7 years) in the NHS cohort from California, Massachusetts, and Pennsylvania completed a 36-item modified NEWS-A for seniors. Confirmatory factor analyses were conducted to test measurement models for both the modified NEWS-A for seniors and the original NEWS-A. Internal consistency within factors was examined using Cronbach's alpha. The hypothesized 7-factor measurement model was a poor fit for the modified NEWS-A for seniors. Overall, the best-fitting measurement model was the original 6-factor solution to the NEWS-A. Factors were correlated and internally consistent. This study provided support for the construct validity of the original NEWS-A for assessing perceptions of neighborhood environments in older women in the United States.

Comparison of Linear and Non-linear Regression Analysis to Determine Pulmonary Pressure in Hyperthyroidism.

PubMed

Scarneciu, Camelia C; Sangeorzan, Livia; Rus, Horatiu; Scarneciu, Vlad D; Varciu, Mihai S; Andreescu, Oana; Scarneciu, Ioan

2017-01-01

This study aimed at assessing the incidence of pulmonary hypertension (PH) at newly diagnosed hyperthyroid patients and at finding a simple model showing the complex functional relation between pulmonary hypertension in hyperthyroidism and the factors causing it. The 53 hyperthyroid patients (H-group) were evaluated mainly by using an echocardiographical method and compared with 35 euthyroid (E-group) and 25 healthy people (C-group). In order to identify the factors causing pulmonary hypertension the statistical method of comparing the values of arithmetical means is used. The functional relation between the two random variables (PAPs and each of the factors determining it within our research study) can be expressed by linear or non-linear function. By applying the linear regression method described by a first-degree equation the line of regression (linear model) has been determined; by applying the non-linear regression method described by a second degree equation, a parabola-type curve of regression (non-linear or polynomial model) has been determined. We made the comparison and the validation of these two models by calculating the determination coefficient (criterion 1), the comparison of residuals (criterion 2), application of AIC criterion (criterion 3) and use of F-test (criterion 4). From the H-group, 47% have pulmonary hypertension completely reversible when obtaining euthyroidism. The factors causing pulmonary hypertension were identified: previously known- level of free thyroxin, pulmonary vascular resistance, cardiac output; new factors identified in this study- pretreatment period, age, systolic blood pressure. According to the four criteria and to the clinical judgment, we consider that the polynomial model (graphically parabola- type) is better than the linear one. The better model showing the functional relation between the pulmonary hypertension in hyperthyroidism and the factors identified in this study is given by a polynomial equation of second degree where the parabola is its graphical representation.

Effects of source shape on the numerical aperture factor with a geometrical-optics model.

PubMed

Wan, Der-Shen; Schmit, Joanna; Novak, Erik

2004-04-01

We study the effects of an extended light source on the calibration of an interference microscope, also referred to as an optical profiler. Theoretical and experimental numerical aperture (NA) factors for circular and linear light sources along with collimated laser illumination demonstrate that the shape of the light source or effective aperture cone is critical for a correct NA factor calculation. In practice, more-accurate results for the NA factor are obtained when a linear approximation to the filament light source shape is used in a geometric model. We show that previously measured and derived NA factors show some discrepancies because a circular rather than linear approximation to the filament source was used in the modeling.

Prediction of beef carcass and meat traits from rearing factors in young bulls and cull cows.

PubMed

Soulat, J; Picard, B; Léger, S; Monteils, V

2016-04-01

The aim of this study was to predict the beef carcass and LM (thoracis part) characteristics and the sensory properties of the LM from rearing factors applied during the fattening period. Individual data from 995 animals (688 young bulls and 307 cull cows) in 15 experiments were used to establish prediction models. The data concerned rearing factors (13 variables), carcass characteristics (5 variables), LM characteristics (2 variables), and LM sensory properties (3 variables). In this study, 8 prediction models were established: dressing percentage and the proportions of fat tissue and muscle in the carcass to characterize the beef carcass; cross-sectional area of fibers (mean fiber area) and isocitrate dehydrogenase activity to characterize the LM; and, finally, overall tenderness, juiciness, and flavor intensity scores to characterize the LM sensory properties. A random effect was considered in each model: the breed for the prediction models for the carcass and LM characteristics and the trained taste panel for the prediction of the meat sensory properties. To evaluate the quality of prediction models, 3 criteria were measured: robustness, accuracy, and precision. The model was robust when the root mean square errors of prediction of calibration and validation sub-data sets were near to one another. Except for the mean fiber area model, the obtained predicted models were robust. The prediction models were considered to have a high accuracy when the mean prediction error (MPE) was ≤0.10 and to have a high precision when the was the closest to 1. The prediction of the characteristics of the carcass from the rearing factors had a high precision ( > 0.70) and a high prediction accuracy (MPE < 0.10), except for the fat percentage model ( = 0.67, MPE = 0.16). However, the predictions of the LM characteristics and LM sensory properties from the rearing factors were not sufficiently precise ( < 0.50) and accurate (MPE > 0.10). Only the flavor intensity of the beef score could be satisfactorily predicted from the rearing factors with high precision ( = 0.72) and accuracy (MPE = 0.10). All the prediction models displayed different effects of the rearing factors according to animal categories (young bulls or cull cows). In consequence, these prediction models display the necessary adaption of rearing factors during the fattening period according to animal categories to optimize the carcass traits according to animal categories.

Multi-level Bayesian safety analysis with unprocessed Automatic Vehicle Identification data for an urban expressway.

PubMed

Shi, Qi; Abdel-Aty, Mohamed; Yu, Rongjie

2016-03-01

In traffic safety studies, crash frequency modeling of total crashes is the cornerstone before proceeding to more detailed safety evaluation. The relationship between crash occurrence and factors such as traffic flow and roadway geometric characteristics has been extensively explored for a better understanding of crash mechanisms. In this study, a multi-level Bayesian framework has been developed in an effort to identify the crash contributing factors on an urban expressway in the Central Florida area. Two types of traffic data from the Automatic Vehicle Identification system, which are the processed data capped at speed limit and the unprocessed data retaining the original speed were incorporated in the analysis along with road geometric information. The model framework was proposed to account for the hierarchical data structure and the heterogeneity among the traffic and roadway geometric data. Multi-level and random parameters models were constructed and compared with the Negative Binomial model under the Bayesian inference framework. Results showed that the unprocessed traffic data was superior. Both multi-level models and random parameters models outperformed the Negative Binomial model and the models with random parameters achieved the best model fitting. The contributing factors identified imply that on the urban expressway lower speed and higher speed variation could significantly increase the crash likelihood. Other geometric factors were significant including auxiliary lanes and horizontal curvature. Copyright © 2015 Elsevier Ltd. All rights reserved.

Analysis of structural relationship among the occupational dysfunction on the psychological problem in healthcare workers: a study using structural equation modeling

PubMed Central

Kyougoku, Makoto

2015-01-01

Purpose. The purpose of this study is to demonstrate the hypothetical model based on structural relationship with the occupational dysfunction on psychological problems (stress response, burnout syndrome, and depression) in healthcare workers. Method. Three cross sectional studies were conducted to assess the following relations: (1) occupational dysfunction on stress response (n = 468), (2) occupational dysfunction on burnout syndrome (n = 1,142), and (3) occupational dysfunction on depression (n = 687). Personal characteristics were collected through a questionnaire (such as age, gender, and job category, opportunities for refreshment, time spent on leisure activities, and work relationships) as well as the Classification and Assessment of Occupational Dysfunction (CAOD). Furthermore, study 1 included the Stress Response Scale-18 (SRS-18), study 2 used the Japanese Burnout Scale (JBS), and study 3 employed the Center for Epidemiological Studies Depression Scale (CES-D). The Kolmogorov–Smirnov test, confirmatory factor analysis (CFA), exploratory factor analysis (EFA), and path analysis of structural equation modeling (SEM) analysis were used in all of the studies. EFA and CFA were used to measure structural validity of four assessments; CAOD, SRS-18, JBS, and CES-D. For examination of a potential covariate, we assessed the correlation of the total and factor score of CAOD and personal factors in all studies. Moreover, direct and indirect effects of occupational dysfunction on stress response (Study 1), burnout syndrome (Study 2), and depression (Study 3) were also analyzed. Results. In study 1, CAOD had 16 items and 4 factors. In Study 2 and 3, CAOD had 16 items and 5 factors. SRS-18 had 18 items and 3 factors, JBS had 17 items and 3 factors, and CES-D had 20 items and 4 factors. All studies found that there were significant correlations between the CAOD total score and the personal factor that included opportunities for refreshment, time spent on leisure activities, and work relationships (p < 0.01). The hypothesis model results suggest that the classification of occupational dysfunction had good fit on the stress response (RMSEA = 0.061, CFI = 0.947, and TLI = 0.943), burnout syndrome (RMSEA = 0.076, CFI = 0.919, and TLI = 0.913), and depression (RMSEA = 0.060, CFI = 0.922, TLI = 0.917). Moreover, the detected covariates include opportunities for refreshment, time spent on leisure activities, and work relationships on occupational dysfunction. Conclusion. Our findings indicate that psychological problems are associated with occupational dysfunction in healthcare workers. Reduction of occupational dysfunction might be a strategy of better preventive occupational therapies for healthcare workers with psychological problems. However, longitudinal studies will be needed to determine a causal relationship. PMID:26618078

Analysis of structural relationship among the occupational dysfunction on the psychological problem in healthcare workers: a study using structural equation modeling.

PubMed

Teraoka, Mutsumi; Kyougoku, Makoto

2015-01-01

Purpose. The purpose of this study is to demonstrate the hypothetical model based on structural relationship with the occupational dysfunction on psychological problems (stress response, burnout syndrome, and depression) in healthcare workers. Method. Three cross sectional studies were conducted to assess the following relations: (1) occupational dysfunction on stress response (n = 468), (2) occupational dysfunction on burnout syndrome (n = 1,142), and (3) occupational dysfunction on depression (n = 687). Personal characteristics were collected through a questionnaire (such as age, gender, and job category, opportunities for refreshment, time spent on leisure activities, and work relationships) as well as the Classification and Assessment of Occupational Dysfunction (CAOD). Furthermore, study 1 included the Stress Response Scale-18 (SRS-18), study 2 used the Japanese Burnout Scale (JBS), and study 3 employed the Center for Epidemiological Studies Depression Scale (CES-D). The Kolmogorov-Smirnov test, confirmatory factor analysis (CFA), exploratory factor analysis (EFA), and path analysis of structural equation modeling (SEM) analysis were used in all of the studies. EFA and CFA were used to measure structural validity of four assessments; CAOD, SRS-18, JBS, and CES-D. For examination of a potential covariate, we assessed the correlation of the total and factor score of CAOD and personal factors in all studies. Moreover, direct and indirect effects of occupational dysfunction on stress response (Study 1), burnout syndrome (Study 2), and depression (Study 3) were also analyzed. Results. In study 1, CAOD had 16 items and 4 factors. In Study 2 and 3, CAOD had 16 items and 5 factors. SRS-18 had 18 items and 3 factors, JBS had 17 items and 3 factors, and CES-D had 20 items and 4 factors. All studies found that there were significant correlations between the CAOD total score and the personal factor that included opportunities for refreshment, time spent on leisure activities, and work relationships (p < 0.01). The hypothesis model results suggest that the classification of occupational dysfunction had good fit on the stress response (RMSEA = 0.061, CFI = 0.947, and TLI = 0.943), burnout syndrome (RMSEA = 0.076, CFI = 0.919, and TLI = 0.913), and depression (RMSEA = 0.060, CFI = 0.922, TLI = 0.917). Moreover, the detected covariates include opportunities for refreshment, time spent on leisure activities, and work relationships on occupational dysfunction. Conclusion. Our findings indicate that psychological problems are associated with occupational dysfunction in healthcare workers. Reduction of occupational dysfunction might be a strategy of better preventive occupational therapies for healthcare workers with psychological problems. However, longitudinal studies will be needed to determine a causal relationship.

Psychometric properties of the Belgian coach version of the coach-athlete relationship questionnaire (CART-Q).

PubMed

Balduck, A-L; Jowett, S

2010-10-01

The study examined the psychometric properties of the Belgian coach version of the Coach-Athlete Relationship Questionnaire (CART-Q). The questionnaire includes three dimensions (Closeness, Commitment, and Complementarity) in a model that intends to measure the quality of the coach-athlete relationship. Belgian coaches (n=144) of athletes who performed at various competition levels in such sports as football, basketball, and volleyball responded to the CART-Q and to the Leadership Scale for Sport (LSS). A confirmatory factor analysis proved to be slightly more satisfactory for a three-order factor model, compared with a hierarchical first-order factor model. The three factors showed acceptable internal consistency scores. Moreover, functional associations between the three factors and coach leadership behaviors were found offering support to the instrument's concurrent validity. The findings support previous validation studies and verify the psychometric properties of the CART-Q applied to Belgian coaches of team sports. © 2009 John Wiley & Sons A/S.

Does the model of additive effect in placebo research still hold true? A narrative review

PubMed Central

Berger, Bettina; Weger, Ulrich; Heusser, Peter

2017-01-01

Personalised and contextualised care has been turned into a major demand by people involved in healthcare suggesting to move toward person-centred medicine. The assessment of person-centred medicine can be most effectively achieved if treatments are investigated using ‘with versus without’ person-centredness or integrative study designs. However, this assumes that the components of an integrative or person-centred intervention have an additive relationship to produce the total effect. Beecher’s model of additivity assumes an additive relation between placebo and drug effects and is thus presenting an arithmetic summation. So far, no review has been carried out assessing the validity of the additive model, which is to be questioned and more closely investigated in this review. Initial searches for primary studies were undertaken in July 2016 using Pubmed and Google Scholar. In order to find matching publications of similar magnitude for the comparison part of this review, corresponding matches for all included reviews were sought. A total of 22 reviews and 3 clinical and experimental studies fulfilled the inclusion criteria. The results pointed to the following factors actively questioning the additive model: interactions of various effects, trial design, conditioning, context effects and factors, neurobiological factors, mechanism of action, statistical factors, intervention-specific factors (alcohol, caffeine), side-effects and type of intervention. All but one of the closely assessed publications was questioning the additive model. A closer examination of study design is necessary. An attempt in a more systematic approach geared towards solutions could be a suggestion for future research in this field. PMID:28321318

Does the model of additive effect in placebo research still hold true? A narrative review.

PubMed

Boehm, Katja; Berger, Bettina; Weger, Ulrich; Heusser, Peter

2017-03-01

Personalised and contextualised care has been turned into a major demand by people involved in healthcare suggesting to move toward person-centred medicine. The assessment of person-centred medicine can be most effectively achieved if treatments are investigated using 'with versus without' person-centredness or integrative study designs. However, this assumes that the components of an integrative or person-centred intervention have an additive relationship to produce the total effect. Beecher's model of additivity assumes an additive relation between placebo and drug effects and is thus presenting an arithmetic summation. So far, no review has been carried out assessing the validity of the additive model, which is to be questioned and more closely investigated in this review. Initial searches for primary studies were undertaken in July 2016 using Pubmed and Google Scholar. In order to find matching publications of similar magnitude for the comparison part of this review, corresponding matches for all included reviews were sought. A total of 22 reviews and 3 clinical and experimental studies fulfilled the inclusion criteria. The results pointed to the following factors actively questioning the additive model: interactions of various effects, trial design, conditioning, context effects and factors, neurobiological factors, mechanism of action, statistical factors, intervention-specific factors (alcohol, caffeine), side-effects and type of intervention. All but one of the closely assessed publications was questioning the additive model. A closer examination of study design is necessary. An attempt in a more systematic approach geared towards solutions could be a suggestion for future research in this field.

The risk factors of laryngeal pathology in Korean adults using a decision tree model.

PubMed

Byeon, Haewon

2015-01-01

The purpose of this study was to identify risk factors affecting laryngeal pathology in the Korean population and to evaluate the derived prediction model. Cross-sectional study. Data were drawn from the 2008 Korea National Health and Nutritional Examination Survey. The subjects were 3135 persons (1508 male and 2114 female) aged 19 years and older living in the community. The independent variables were age, sex, occupation, smoking, alcohol drinking, and self-reported voice problems. A decision tree analysis was done to identify risk factors for predicting a model of laryngeal pathology. The significant risk factors of laryngeal pathology were age, gender, occupation, smoking, and self-reported voice problem in decision tree model. Four significant paths were identified in the decision tree model for the prediction of laryngeal pathology. Those identified as high risk groups for laryngeal pathology included those who self-reported a voice problem, those who were males in their 50s who did not recognize a voice problem, those who were not economically active males in their 40s, and male workers aged 19 and over and under 50 or 60 and over who currently smoked. The results of this study suggest that individual risk factors, such as age, sex, occupation, health behavior, and self-reported voice problem, affect the onset of laryngeal pathology in a complex manner. Based on the results of this study, early management of the high-risk groups is needed for the prevention of laryngeal pathology. Copyright © 2015 The Voice Foundation. Published by Elsevier Inc. All rights reserved.

Validation of a multifactorial risk factor model used for predicting future caries risk with Nevada adolescents.

PubMed

Ditmyer, Marcia M; Dounis, Georgia; Howard, Katherine M; Mobley, Connie; Cappelli, David

2011-05-20

The objective of this study was to measure the validity and reliability of a multifactorial Risk Factor Model developed for use in predicting future caries risk in Nevada adolescents in a public health setting. This study examined retrospective data from an oral health surveillance initiative that screened over 51,000 students 13-18 years of age, attending public/private schools in Nevada across six academic years (2002/2003-2007/2008). The Risk Factor Model included ten demographic variables: exposure to fluoridation in the municipal water supply, environmental smoke exposure, race, age, locale (metropolitan vs. rural), tobacco use, Body Mass Index, insurance status, sex, and sealant application. Multiple regression was used in a previous study to establish which significantly contributed to caries risk. Follow-up logistic regression ascertained the weight of contribution and odds ratios of the ten variables. Researchers in this study computed sensitivity, specificity, positive predictive value (PVP), negative predictive value (PVN), and prevalence across all six years of screening to assess the validity of the Risk Factor Model. Subjects' overall mean caries prevalence across all six years was 66%. Average sensitivity across all six years was 79%; average specificity was 81%; average PVP was 89% and average PVN was 67%. Overall, the Risk Factor Model provided a relatively constant, valid measure of caries that could be used in conjunction with a comprehensive risk assessment in population-based screenings by school nurses/nurse practitioners, health educators, and physicians to guide them in assessing potential future caries risk for use in prevention and referral practices.

Weight management behaviors in a sample of Iranian adolescent girls.

PubMed

Garousi, S; Garrusi, B; Baneshi, Mohammad Reza; Sharifi, Z

2016-09-01

Attempts to obtain the ideal body shape portrayed in advertising can result in behaviors that lead to an unhealthy reduction in weight. This study was designed to identify contributing factors that may be effective in changing the behavior of a sample of Iranian adolescents. Three hundred fifty adolescent girls from high schools in Kerman, Iran participated in a cross-sectional study based on a self-administered questionnaire. Multifactorial logistic regression modeling was used to identify the factors influencing each of the contributing factors for body management methods, and a decision tree model was constructed to identify individuals who were more or less likely to change their body shape. Approximately one-third of the adolescent girls had attempted dieting, and 37 % of them had exercised to lose weight. The logistic regression model showed that pressure from their mother and the media; father's education level; and body mass index (BMI) were important factors in dieting. BMI and perceived pressure from the media were risk factors for attempting exercise. BMI and perceived pressure from relatives, particularly mothers, and the media were important factors in attempts by adolescent girls to lose weight.

Longitudinal factorial invariance of the PedsQL 4.0 Generic Core Scales child self-report Version: one year prospective evidence from the California State Children's Health Insurance Program (SCHIP).

PubMed

Varni, James W; Limbers, Christine A; Newman, Daniel A; Seid, Michael

2008-11-01

The measurement of health-related quality of life (HRQOL) in pediatric medicine and health services research has grown significantly over the past decade. The paradigm shift toward patient-reported outcomes (PROs) has provided the opportunity to emphasize the value and critical need for pediatric patient self-report. In order for changes in HRQOL/PRO outcomes to be meaningful over time, it is essential to demonstrate longitudinal factorial invariance. This study examined the longitudinal factor structure of the PedsQL 4.0 Generic Core Scales over a one-year period for child self-report ages 5-17 in 2,887 children from a statewide evaluation of the California State Children's Health Insurance Program (SCHIP) utilizing a structural equation modeling framework. Specifying four- and five-factor measurement models, longitudinal structural equation modeling was used to compare factor structures over a one-year interval on the PedsQL 4.0 Generic Core Scales. While the four-factor conceptually-derived measurement model for the PedsQL 4.0 Generic Core Scales produced an acceptable fit, the five-factor empirically-derived measurement model from the initial field test of the PedsQL 4.0 Generic Core Scales produced a marginally superior fit in comparison to the four-factor model. For the five-factor measurement model, the best fitting model, strict factorial invariance of the PedsQL 4.0 Generic Core Scales across the two measurement occasions was supported by the stability of the comparative fit index between the unconstrained and constrained models, and several additional indices of practical fit including the root mean squared error of approximation, the non-normed fit index, and the parsimony normed fit index. The findings support an equivalent factor structure on the PedsQL 4.0 Generic Core Scales over time. Based on these data, it can be concluded that over a one-year period children in our study interpreted items on the PedsQL 4.0 Generic Core Scales in a similar manner.

Predictive Factors of Regular Physical Activity among Middle-Aged Women in the West of Iran, Hamadan: Application of PRECEDE Model.

PubMed

Emdadi, Shohreh; Hazavehie, Seyed Mohammad Mehdi; Soltanian, Alireza; Bashirian, Saeed; Heidari Moghadam, Rashid

2015-01-01

Regular physical activity is important for midlife women. Models and theories help better understanding this behavior among middle-aged women and better planning for change behavior in target group. This study aimed to investigate predictive factors of regular physical activity among middle-aged women based on PRECEDE model as a theoretical framework. This descriptive-analytical study was performed on 866 middle-aged women of Hamadan City western Iran, recruited with a proportional stratified sampling method in 2015. The participants completed a self-administered questionnaire including questions on demographic characteristics and PRECEDE model constructs and IPAQ questionnaire. Data were then analyzed by SPSS-16 and AMOS-16 using the Pearson correlation test and the pathway analysis method. Overall, 57% of middle-aged women were inactive (light level) or not sufficiently active. With SEM (Structural Equation Modeling) analysis, knowledge b=0.84, P<0.001, attitude b=0.799, P<0.001, self-efficacy b=0.633, P<0.001 as predisposing factor and social support as reinforcing factor b=0.2, P<0.001 were the most important predictors for physical activity among middle-aged women in Hamadan. The framework of the PRECEDE model is useful in understanding regular physical activity among middle-aged women. Furthermore, results showed the importance of predisposing and reinforcing factors when planning educational interventions.

Impact of covariate models on the assessment of the air pollution-mortality association in a single- and multipollutant context.

PubMed

Sacks, Jason D; Ito, Kazuhiko; Wilson, William E; Neas, Lucas M

2012-10-01

With the advent of multicity studies, uniform statistical approaches have been developed to examine air pollution-mortality associations across cities. To assess the sensitivity of the air pollution-mortality association to different model specifications in a single and multipollutant context, the authors applied various regression models developed in previous multicity time-series studies of air pollution and mortality to data from Philadelphia, Pennsylvania (May 1992-September 1995). Single-pollutant analyses used daily cardiovascular mortality, fine particulate matter (particles with an aerodynamic diameter ≤2.5 µm; PM(2.5)), speciated PM(2.5), and gaseous pollutant data, while multipollutant analyses used source factors identified through principal component analysis. In single-pollutant analyses, risk estimates were relatively consistent across models for most PM(2.5) components and gaseous pollutants. However, risk estimates were inconsistent for ozone in all-year and warm-season analyses. Principal component analysis yielded factors with species associated with traffic, crustal material, residual oil, and coal. Risk estimates for these factors exhibited less sensitivity to alternative regression models compared with single-pollutant models. Factors associated with traffic and crustal material showed consistently positive associations in the warm season, while the coal combustion factor showed consistently positive associations in the cold season. Overall, mortality risk estimates examined using a source-oriented approach yielded more stable and precise risk estimates, compared with single-pollutant analyses.

Uncovering the influence of social skills and psychosociological factors on pain sensitivity using structural equation modeling.

PubMed

Tanaka, Yoichi; Nishi, Yuki; Nishi, Yuki; Osumi, Michihiro; Morioka, Shu

2017-01-01

Pain is a subjective emotional experience that is influenced by psychosociological factors such as social skills, which are defined as problem-solving abilities in social interactions. This study aimed to reveal the relationships among pain, social skills, and other psychosociological factors by using structural equation modeling. A total of 101 healthy volunteers (41 men and 60 women; mean age: 36.6±12.7 years) participated in this study. To evoke participants' sense of inner pain, we showed them images of painful scenes on a PC screen and asked them to evaluate the pain intensity by using the visual analog scale (VAS). We examined the correlation between social skills and VAS, constructed a hypothetical model based on results from previous studies and the current correlational analysis results, and verified the model's fit using structural equation modeling. We found significant positive correlations between VAS and total social skills values, as well as between VAS and the "start of relationships" subscales. Structural equation modeling revealed that the values for "start of relationships" had a direct effect on VAS values (path coefficient =0.32, p <0.01). In addition, the "start of relationships" had both a direct and an indirect effect on psychological factors via social support. The results indicated that extroverted people are more sensitive to inner pain and tend to get more social support and maintain a better psychological condition.

Generation of Organ-conditioned Media and Applications for Studying Organ-specific Influences on Breast Cancer Metastatic Behavior.

PubMed

Piaseczny, Matthew M; Pio, Graciella M; Chu, Jenny E; Xia, Ying; Nguyen, Kim; Goodale, David; Allan, Alison

2016-06-13

Breast cancer preferentially metastasizes to the lymph node, bone, lung, brain and liver in breast cancer patients. Previous research efforts have focused on identifying factors inherent to breast cancer cells that are responsible for this observed metastatic pattern (termed organ tropism), however much less is known about factors present within specific organs that contribute to this process. This is in part because of a lack of in vitro model systems that accurately recapitulate the organ microenvironment. To address this, an ex vivo model system has been established that allows for the study of soluble factors present within different organ microenvironments. This model consists of generating conditioned media from organs (lymph node, bone, lung, and brain) isolated from normal athymic nude mice. The model system has been validated by demonstrating that different breast cancer cell lines display cell-line specific and organ-specific malignant behavior in response to organ-conditioned media that corresponds to their in vivo metastatic potential. This model system can be used to identify and evaluate specific organ-derived soluble factors that may play a role in the metastatic behavior of breast and other types of cancer cells, including influences on growth, migration, stem-like behavior, and gene expression, as well as the identification of potential new therapeutic targets for cancer. This is the first ex vivo model system that can be used to study organ-specific metastatic behavior in detail and evaluate the role of specific organ-derived soluble factors in driving the process of cancer metastasis.

Racial Discrimination, Cultural Resilience, and Stress.

PubMed

Spence, Nicholas D; Wells, Samantha; Graham, Kathryn; George, Julie

2016-05-01

Racial discrimination is a social determinant of health for First Nations people. Cultural resilience has been regarded as a potentially positive resource for social outcomes. Using a compensatory model of resilience, this study sought to determine if cultural resilience (compensatory factor) neutralized or offset the detrimental effect of racial discrimination (social risk factor) on stress (outcome). Data were collected from October 2012 to February 2013 (N = 340) from adult members of the Kettle and Stony Point First Nation community in Ontario, Canada. The outcome was perceived stress; risk factor, racial discrimination; and compensatory factor, cultural resilience. Control variables included individual (education, sociability) and family (marital status, socioeconomic status) resilience resources and demographics (age and gender). The model was tested using sequential regression. The risk factor, racial discrimination, increased stress across steps of the sequential model, while cultural resilience had an opposite modest effect on stress levels. In the final model with all variables, age and gender were significant, with the former having a negative effect on stress and women reporting higher levels of stress than males. Education, marital status, and socioeconomic status (household income) were not significant in the model. The model had R(2) = 0.21 and adjusted R(2) = 0.18 and semipartial correlation (squared) of 0.04 and 0.01 for racial discrimination and cultural resilience, respectively. In this study, cultural resilience compensated for the detrimental effect of racial discrimination on stress in a modest manner. These findings may support the development of programs and services fostering First Nations culture, pending further study. © The Author(s) 2016.

Racial Discrimination, Cultural Resilience, and Stress

PubMed Central

Wells, Samantha; Graham, Kathryn; George, Julie

2016-01-01

Objective: Racial discrimination is a social determinant of health for First Nations people. Cultural resilience has been regarded as a potentially positive resource for social outcomes. Using a compensatory model of resilience, this study sought to determine if cultural resilience (compensatory factor) neutralized or offset the detrimental effect of racial discrimination (social risk factor) on stress (outcome). Methods: Data were collected from October 2012 to February 2013 (N = 340) from adult members of the Kettle and Stony Point First Nation community in Ontario, Canada. The outcome was perceived stress; risk factor, racial discrimination; and compensatory factor, cultural resilience. Control variables included individual (education, sociability) and family (marital status, socioeconomic status) resilience resources and demographics (age and gender). The model was tested using sequential regression. Results: The risk factor, racial discrimination, increased stress across steps of the sequential model, while cultural resilience had an opposite modest effect on stress levels. In the final model with all variables, age and gender were significant, with the former having a negative effect on stress and women reporting higher levels of stress than males. Education, marital status, and socioeconomic status (household income) were not significant in the model. The model had R2 = 0.21 and adjusted R2 = 0.18 and semipartial correlation (squared) of 0.04 and 0.01 for racial discrimination and cultural resilience, respectively. Conclusions: In this study, cultural resilience compensated for the detrimental effect of racial discrimination on stress in a modest manner. These findings may support the development of programs and services fostering First Nations culture, pending further study. PMID:27254805

Does Sluggish Cognitive Tempo Fit within a Bi-factor Model of Attention-Deficit/Hyperactivity Disorder?

PubMed Central

Garner, Annie A.; Peugh, James; Becker, Stephen P.; Kingery, Kathleen M.; Tamm, Leanne; Vaughn, Aaron J.; Ciesielski, Heather; Simon, John O.; Loren, Richard E. A.; Epstein, Jeffery N.

2014-01-01

Objective Studies demonstrate sluggish cognitive tempo (SCT) symptoms to be distinct from inattentive and hyperactive-impulsive dimensions of Attention-Deficit/Hyperactivity Disorder (ADHD). No study has examined SCT within a bi-factor model of ADHD whereby SCT may form a specific factor distinct from inattention and hyperactivity/impulsivity while still fitting within a general ADHD factor, which was the purpose of the current study. Method 168 children were recruited from an ADHD clinic. Most (92%) met diagnostic criteria for ADHD. Parents and teachers completed measures of ADHD and SCT. Results Although SCT symptoms were strongly associated with inattention they loaded onto a factor independent of ADHD ‘g’. Results were consistent across parent and teacher ratings. Conclusions SCT is structurally distinct from inattention as well as from the general ADHD latent symptom structure. Findings support a growing body of research suggesting SCT to be distinct and separate from ADHD. PMID:25005039

PTSD's factor structure and measurement invariance across subgroups with differing count of trauma types.

PubMed

Contractor, Ateka A; Caldas, Stephanie V; Dolan, Megan; Lagdon, Susan; Armour, Chérie

2018-06-01

To investigate the effect of the count of traumatizing event (TE) types on post-trauma mental health, several studies have compared posttraumatic stress disorder (PTSD) severity between individuals experiencing one versus multiple TE types. However, the validity of these studies depends on the establishment of measurement invariance of the construct(s) of interest. The current study examined the stability of the most optimal PTSD Model symptom cluster constructs (assessed by the PTSD Checklist for DSM-5 [PCL-5]) across subgroups experiencing one versus multiple TE types. The sample included university students (n = 556) endorsing at least one TE (Stressful Life Events Screening Questionnaire). Using data from the entire sample, results suggest that the PCL-5-assessed Hybrid Model provided a significantly better fit compared to other models. Results also indicated invariance of factor loadings (metric), and intercepts (scalar) for the PCL-5-assessed Hybrid Model factors across subgroups endorsing one (n = 191) versus multiple TE types (n = 365). Our findings thus support the stability, applicability, and meaningful comparison of the PCL-assessed Hybrid Model factor structure (including subscale severity scores) across subgroups experiencing one versus multiple TE types. Copyright © 2018 Elsevier B.V. All rights reserved.

[Study on factors influencing survival in patients with advanced gastric carcinoma after resection by Cox's proportional hazard model].

PubMed

Wang, S; Sun, Z; Wang, S

1996-11-01

A prospective follow-up study of 539 advanced gastric carcinoma patients after resection was undertaken between 1 January 1980 and 31 December 1989, with a follow-up rate of 95.36%. A multivariate analysis of possible factors influencing survival of these patients was performed, and their predicting models of survival rates was established by Cox proportional hazard model. The results showed that the major significant prognostic factors influencing survival of these patients were rate and station of lymph node metastases, type of operation, hepatic metastases, size of tumor, age and location of tumor. The most important factor was the rate of lymph node metastases. According to their regression coefficients, the predicting value (PV) of each patient was calculated, then all patients were divided into five risk groups according to PV, their predicting models of survival rates after resection were established in groups. The goodness-fit of estimated predicting models of survival rates were checked by fitting curve and residual plot, and the estimated models tallied with the actual situation. The results suggest that the patients with advanced gastric cancer after resection without lymph node metastases and hepatic metastases had a better prognosis, and their survival probability may be predicted according to the predicting model of survival rates.

Psychopathy, intelligence and conviction history.

PubMed

Heinzen, Hanna; Köhler, Denis; Godt, Nils; Geiger, Friedemann; Huchzermeier, Christian

2011-01-01

The current study examined the relationship between psychopathy, intelligence and two variables describing the conviction history (length of conviction and number of prior convictions). It was hypothesized that psychopathy factors (interpersonal and antisocial factors assuming a 2-factor model or interpersonal, affective, lifestyle and antisocial factors assuming a 4-factor model) would be related in different ways to IQ scores, length of conviction and number of prior convictions. Psychopathy and IQ were assessed using the PCL:SV and the CFT 20-R respectively. Results indicated no association between interpersonal psychopathy features (Factor 1, two-factor model), IQ and the number of prior convictions but a positive association between Factor 1 and the length of conviction. Antisocial features (Factor 2, two-factor model) were negatively related to IQ and the length of conviction and positively related to the number of prior convictions. Results were further differentiated for the four-factor model of psychopathy. The relationship between IQ and psychopathy features was further assessed by statistically isolating the effects of the two factors of psychopathy. It was found that individuals scoring high on interpersonal features of psychopathy are more intelligent than those scoring high on antisocial features, but less intelligent than those scoring low on both psychopathy features. The results underpin the importance of allocating psychopathic individuals to subgroups on the basis of personality characteristics and criminological features. These subgroups may identify different types of offenders and may be highly valuable for defining treatment needs and risk of future violence. Copyright © 2011 Elsevier Ltd. All rights reserved.

Confirmatory factor analysis and measurement invariance of the Child Feeding Questionnaire in low-income Hispanic and African-American mothers with preschool-age children.

PubMed

Kong, Angela; Vijayasiri, Ganga; Fitzgibbon, Marian L; Schiffer, Linda A; Campbell, Richard T

2015-07-01

Validation work of the Child Feeding Questionnaire (CFQ) in low-income minority samples suggests a need for further conceptual refinement of this instrument. Using confirmatory factor analysis, this study evaluated 5- and 6-factor models on a large sample of African-American and Hispanic mothers with preschool-age children (n = 962). The 5-factor model included: 'perceived responsibility', 'concern about child's weight', 'restriction', 'pressure to eat', and 'monitoring' and the 6-factor model also tested 'food as a reward'. Multi-group analysis assessed measurement invariance by race/ethnicity. In the 5-factor model, two low-loading items from 'restriction' and one low-variance item from 'perceived responsibility' were dropped to achieve fit. Only removal of the low-variance item was needed to achieve fit in the 6-factor model. Invariance analyses demonstrated differences in factor loadings. This finding suggests African-American and Hispanic mothers may vary in their interpretation of some CFQ items and use of cognitive interviews could enhance item interpretation. Our results also demonstrated that 'food as a reward' is a plausible construct among a low-income minority sample and adds to the evidence that this factor resonates conceptually with parents of preschoolers; however, further testing is needed to determine the validity of this factor with older age groups. Copyright © 2015 Elsevier Ltd. All rights reserved.

Formation factor in Bentheimer and Fontainebleau sandstones: Theory compared with pore-scale numerical simulations

NASA Astrophysics Data System (ADS)

Ghanbarian, Behzad; Berg, Carl F.

2017-09-01

Accurate quantification of formation resistivity factor F (also called formation factor) provides useful insight into connectivity and pore space topology in fully saturated porous media. In particular the formation factor has been extensively used to estimate permeability in reservoir rocks. One of the widely applied models to estimate F is Archie's law (F = ϕ- m in which ϕ is total porosity and m is cementation exponent) that is known to be valid in rocks with negligible clay content, such as clean sandstones. In this study we compare formation factors determined by percolation and effective-medium theories as well as Archie's law with numerical simulations of electrical resistivity on digital rock models. These digital models represent Bentheimer and Fontainebleau sandstones and are derived either by reconstruction or directly from micro-tomographic images. Results show that the universal quadratic power law from percolation theory accurately estimates the calculated formation factor values in network models over the entire range of porosity. However, it crosses over to the linear scaling from the effective-medium approximation at the porosity of 0.75 in grid models. We also show that the effect of critical porosity, disregarded in Archie's law, is nontrivial, and the Archie model inaccurately estimates the formation factor in low-porosity homogeneous sandstones.

Socio-Ecological Risk Factors for Prime-Age Adult Death in Two Coastal Areas of Vietnam

PubMed Central

Kim, Deok Ryun; Ali, Mohammad; Thiem, Vu Dinh; Wierzba, Thomas F.

2014-01-01

Background Hierarchical spatial models enable the geographic and ecological analysis of health data thereby providing useful information for designing effective health interventions. In this study, we used a Bayesian hierarchical spatial model to evaluate mortality data in Vietnam. The model enabled identification of socio-ecological risk factors and generation of risk maps to better understand the causes and geographic implications of prime-age (15 to less than 45 years) adult death. Methods and Findings The study was conducted in two sites: Nha Trang and Hue in Vietnam. The study areas were split into 500×500 meter cells to define neighborhoods. We first extracted socio-demographic data from population databases of the two sites, and then aggregated the data by neighborhood. We used spatial hierarchical model that borrows strength from neighbors for evaluating risk factors and for creating spatially smoothed risk map after adjusting for neighborhood level covariates. The Markov chain Monte Carlo procedure was used to estimate the parameters. Male mortality was more than twice the female mortality. The rates also varied by age and sex. The most frequent cause of mortality was traffic accidents and drowning for men and traffic accidents and suicide for women. Lower education of household heads in the neighborhood was an important risk factor for increased mortality. The mortality was highly variable in space and the socio-ecological risk factors are sensitive to study site and sex. Conclusion Our study suggests that lower education of the household head is an important predictor for prime age adult mortality. Variability in socio-ecological risk factors and in risk areas by sex make it challenging to design appropriate intervention strategies aimed at decreasing prime-age adult deaths in Vietnam. PMID:24587031

Socio-ecological risk factors for prime-age adult death in two coastal areas of Vietnam.

PubMed

Kim, Deok Ryun; Ali, Mohammad; Thiem, Vu Dinh; Wierzba, Thomas F

2014-01-01

Hierarchical spatial models enable the geographic and ecological analysis of health data thereby providing useful information for designing effective health interventions. In this study, we used a Bayesian hierarchical spatial model to evaluate mortality data in Vietnam. The model enabled identification of socio-ecological risk factors and generation of risk maps to better understand the causes and geographic implications of prime-age (15 to less than 45 years) adult death. The study was conducted in two sites: Nha Trang and Hue in Vietnam. The study areas were split into 500×500 meter cells to define neighborhoods. We first extracted socio-demographic data from population databases of the two sites, and then aggregated the data by neighborhood. We used spatial hierarchical model that borrows strength from neighbors for evaluating risk factors and for creating spatially smoothed risk map after adjusting for neighborhood level covariates. The Markov chain Monte Carlo procedure was used to estimate the parameters. Male mortality was more than twice the female mortality. The rates also varied by age and sex. The most frequent cause of mortality was traffic accidents and drowning for men and traffic accidents and suicide for women. Lower education of household heads in the neighborhood was an important risk factor for increased mortality. The mortality was highly variable in space and the socio-ecological risk factors are sensitive to study site and sex. Our study suggests that lower education of the household head is an important predictor for prime age adult mortality. Variability in socio-ecological risk factors and in risk areas by sex make it challenging to design appropriate intervention strategies aimed at decreasing prime-age adult deaths in Vietnam.

Right-Sizing Statistical Models for Longitudinal Data

PubMed Central

Wood, Phillip K.; Steinley, Douglas; Jackson, Kristina M.

2015-01-01

Arguments are proposed that researchers using longitudinal data should consider more and less complex statistical model alternatives to their initially chosen techniques in an effort to “right-size” the model to the data at hand. Such model comparisons may alert researchers who use poorly fitting overly parsimonious models to more complex better fitting alternatives, and, alternatively, may identify more parsimonious alternatives to overly complex (and perhaps empirically under-identified and/or less powerful) statistical models. A general framework is proposed for considering (often nested) relationships between a variety of psychometric and growth curve models. A three-step approach is proposed in which models are evaluated based on the number and patterning of variance components prior to selection of better-fitting growth models that explain both mean and variation/covariation patterns. The orthogonal, free-curve slope-intercept (FCSI) growth model is considered as a general model which includes, as special cases, many models including the Factor Mean model (FM, McArdle & Epstein, 1987), McDonald's (1967) linearly constrained factor model, Hierarchical Linear Models (HLM), Repeated Measures MANOVA, and the Linear Slope Intercept (LinearSI) Growth Model. The FCSI model, in turn, is nested within the Tuckerized factor model. The approach is illustrated by comparing alternative models in a longitudinal study of children's vocabulary and by comparison of several candidate parametric growth and chronometric models in a Monte Carlo study. PMID:26237507

Right-sizing statistical models for longitudinal data.

PubMed

Wood, Phillip K; Steinley, Douglas; Jackson, Kristina M

2015-12-01

Arguments are proposed that researchers using longitudinal data should consider more and less complex statistical model alternatives to their initially chosen techniques in an effort to "right-size" the model to the data at hand. Such model comparisons may alert researchers who use poorly fitting, overly parsimonious models to more complex, better-fitting alternatives and, alternatively, may identify more parsimonious alternatives to overly complex (and perhaps empirically underidentified and/or less powerful) statistical models. A general framework is proposed for considering (often nested) relationships between a variety of psychometric and growth curve models. A 3-step approach is proposed in which models are evaluated based on the number and patterning of variance components prior to selection of better-fitting growth models that explain both mean and variation-covariation patterns. The orthogonal free curve slope intercept (FCSI) growth model is considered a general model that includes, as special cases, many models, including the factor mean (FM) model (McArdle & Epstein, 1987), McDonald's (1967) linearly constrained factor model, hierarchical linear models (HLMs), repeated-measures multivariate analysis of variance (MANOVA), and the linear slope intercept (linearSI) growth model. The FCSI model, in turn, is nested within the Tuckerized factor model. The approach is illustrated by comparing alternative models in a longitudinal study of children's vocabulary and by comparing several candidate parametric growth and chronometric models in a Monte Carlo study. (c) 2015 APA, all rights reserved).

Development and application of a complex numerical model and software for the computation of dose conversion factors for radon progenies.

PubMed

Farkas, Árpád; Balásházy, Imre

2015-04-01

A more exact determination of dose conversion factors associated with radon progeny inhalation was possible due to the advancements in epidemiological health risk estimates in the last years. The enhancement of computational power and the development of numerical techniques allow computing dose conversion factors with increasing reliability. The objective of this study was to develop an integrated model and software based on a self-developed airway deposition code, an own bronchial dosimetry model and the computational methods accepted by International Commission on Radiological Protection (ICRP) to calculate dose conversion coefficients for different exposure conditions. The model was tested by its application for exposure and breathing conditions characteristic of mines and homes. The dose conversion factors were 8 and 16 mSv WLM(-1) for homes and mines when applying a stochastic deposition model combined with the ICRP dosimetry model (named PM-A model), and 9 and 17 mSv WLM(-1) when applying the same deposition model combined with authors' bronchial dosimetry model and the ICRP bronchiolar and alveolar-interstitial dosimetry model (called PM-B model). User friendly software for the computation of dose conversion factors has also been developed. The software allows one to compute conversion factors for a large range of exposure and breathing parameters and to perform sensitivity analyses. © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

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

PubMed Central

2014-01-01

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

Inference of sigma factor controlled networks by using numerical modeling applied to microarray time series data of the germinating prokaryote.

PubMed

Strakova, Eva; Zikova, Alice; Vohradsky, Jiri

2014-01-01

A computational model of gene expression was applied to a novel test set of microarray time series measurements to reveal regulatory interactions between transcriptional regulators represented by 45 sigma factors and the genes expressed during germination of a prokaryote Streptomyces coelicolor. Using microarrays, the first 5.5 h of the process was recorded in 13 time points, which provided a database of gene expression time series on genome-wide scale. The computational modeling of the kinetic relations between the sigma factors, individual genes and genes clustered according to the similarity of their expression kinetics identified kinetically plausible sigma factor-controlled networks. Using genome sequence annotations, functional groups of genes that were predominantly controlled by specific sigma factors were identified. Using external binding data complementing the modeling approach, specific genes involved in the control of the studied process were identified and their function suggested.

The structure of DSM-IV-TR personality disorder diagnoses in NESARC: a reanalysis.

PubMed

Trull, Timothy J; Vergés, Alvaro; Wood, Phillip K; Sher, Kenneth J

2013-12-01

Cox, Clara, Worobec, and Grant (2012) recently presented results from a series of analyses aimed at identifying the factor structure underlying the DSM-IV-TR (APA, 2000) personality diagnoses assessed in the large NESARC study. Cox et al. (2012) concluded that the best fitting model was one that modeled three lower-order factors (the three clusters of PDs as outlined by DSM-IV-TR), which in turn loaded on a single PD higher-order factor. Our reanalyses of the NESARC Wave 1 and Wave 2 data for personality disorder diagnoses revealed that the best fitting model was that of a general PD factor that spans each of the ten DSM-IV PD diagnoses, and our reanalyses do not support the three-cluster hierarchical structure outlined by Cox et al. (2012) and DSM-IV-TR. Finally, we note the importance of modeling the Wave 2 assessment method factor in analyses of NESARC PD data.

Reliability and Validity of the Sexual Pressure Scale for Women-Revised

PubMed Central

Jones, Rachel; Gulick, Elsie

2008-01-01

Sexual pressure among young urban women represents adherence to gender stereotypical expectations to engage in sex. Revision of the original 5-factor Sexual Pressure Scale was undertaken in two studies to improve reliabilities in two of the five factors. In Study 1 the reliability of the Sexual Pressure Scale for Women-Revised (SPSW-R) was tested, and principal components analysis was performed in a sample of 325 young, urban women. A parsimonious 18-item, 4-factor model explained 61% of the variance. In Study 2 the theory underlying sexual pressure was supported by confirmatory factor analysis using structural equation modeling in a sample of 181 women. Reliabilities of the SPSW-R total and subscales were very satisfactory, suggesting it may be used in intervention research. PMID:18666222

Comparison of Cox’s Regression Model and Parametric Models in Evaluating the Prognostic Factors for Survival after Liver Transplantation in Shiraz during 2000–2012

PubMed Central

Adelian, R.; Jamali, J.; Zare, N.; Ayatollahi, S. M. T.; Pooladfar, G. R.; Roustaei, N.

2015-01-01

Background: Identification of the prognostic factors for survival in patients with liver transplantation is challengeable. Various methods of survival analysis have provided different, sometimes contradictory, results from the same data. Objective: To compare Cox’s regression model with parametric models for determining the independent factors for predicting adults’ and pediatrics’ survival after liver transplantation. Method: This study was conducted on 183 pediatric patients and 346 adults underwent liver transplantation in Namazi Hospital, Shiraz, southern Iran. The study population included all patients undergoing liver transplantation from 2000 to 2012. The prognostic factors sex, age, Child class, initial diagnosis of the liver disease, PELD/MELD score, and pre-operative laboratory markers were selected for survival analysis. Result: Among 529 patients, 346 (64.5%) were adult and 183 (34.6%) were pediatric cases. Overall, the lognormal distribution was the best-fitting model for adult and pediatric patients. Age in adults (HR=1.16, p<0.05) and weight (HR=2.68, p<0.01) and Child class B (HR=2.12, p<0.05) in pediatric patients were the most important factors for prediction of survival after liver transplantation. Adult patients younger than the mean age and pediatric patients weighing above the mean and Child class A (compared to those with classes B or C) had better survival. Conclusion: Parametric regression model is a good alternative for the Cox’s regression model. PMID:26306158

Method Effects on an Adaptation of the Rosenberg Self-Esteem Scale in Greek and the Role of Personality Traits.

PubMed

Michaelides, Michalis P; Koutsogiorgi, Chrystalla; Panayiotou, Georgia

2016-01-01

Rosenberg's Self-Esteem Scale is a balanced, 10-item scale designed to be unidimensional; however, research has repeatedly shown that its factorial structure is contaminated by method effects due to item wording. Beyond the substantive self-esteem factor, 2 additional factors linked to the positive and negative wording of items have been theoretically specified and empirically supported. Initial evidence has revealed systematic relations of the 2 method factors with variables expressing approach and avoidance motivation. This study assessed the fit of competing confirmatory factor analytic models for the Rosenberg Self-Esteem Scale using data from 2 samples of adult participants in Cyprus. Models that accounted for both positive and negative wording effects via 2 latent method factors had better fit compared to alternative models. Measures of experiential avoidance, social anxiety, and private self-consciousness were associated with the method factors in structural equation models. The findings highlight the need to specify models with wording effects for a more accurate representation of the scale's structure and support the hypothesis of method factors as response styles, which are associated with individual characteristics related to avoidance motivation, behavioral inhibition, and anxiety.

Characterizing the Intersection of Co-Occurring Risk Factors for Illicit Drug Abuse and Dependence in a U.S. Nationally Representative Sample

PubMed Central

Kurti, Allison N.; Keith, Diana R.; Noble, Alyssa; Priest, Jeff S.; Sprague, Brian; Higgins, Stephen T.

2016-01-01

Few studies have attempted to characterize how co-occurring risk factors for substance use disorders intersect. A recent study examined this question regarding cigarette smoking and demonstrated that co-occurring risk factors generally act independently. The present study examines whether that same pattern of independent intersection of risk factors extends to illicit drug abuse/dependence using a U.S. nationally representative sample (National Survey on Drug Use and Health, 2011–2013). Logistic regression and classification and regression tree (CART) modeling were used to examine risk of past-year drug abuse/dependence associated with a well-established set of risk factors for substance use (age, gender, race/ethnicity, education, poverty, smoking status, alcohol abuse/dependence, mental illness). Each of these risk factors was associated with significant increases in the odds of drug abuse/dependence in univariate logistic regressions. Each remained significant in a multivariate model examining all eight risk factors simultaneously. CART modeling of these 8 risk factors identified subpopulation risk profiles wherein drug abuse/dependence prevalence varied from < 1% to > 80% corresponding to differing combinations of risk factors present. Alcohol abuse/dependence and cigarette smoking had the strongest associations with drug abuse/dependence risk. These results demonstrate that co-occurring risk factors for illicit drug/abuse dependence generally intersect in the same independent manner as risk factors for cigarette smoking, underscoring further fundamental commonalities across these different types of substance use disorders. These results also underscore the fundamental importance of differences in the presence of co-occurring risk factors when considering the often strikingly different prevalence rates of illicit drug abuse/dependence in U.S. population subgroups. PMID:27687534

Quantifying links between stroke and risk factors: a study on individual health risk appraisal of stroke in a community of Chongqing.

PubMed

Wu, Yazhou; Zhang, Ling; Yuan, Xiaoyan; Wu, Yamin; Yi, Dong

2011-04-01

The objective of this study is to investigate the risk factors of stroke in a community in Chongqing by setting quantitative criteria for determining the risk factors of stroke. Thus, high-risk individuals can be identified and laid a foundation for predicting individual risk of stroke. 1,034 cases with 1:2 matched controls (2,068) were chosen from five communities in Chongqing including Shapingba, Xiaolongkan, Tianxingqiao, Yubei Road and Ciqikou. Participants were interviewed with a uniform questionnaire. The risk factors of stroke and the odds ratios of risk factors were analyzed with a logistic regression model, and risk exposure factors of different levels were converted into risk scores using statistical models. For men, ten risk factors including hypertension (5.728), family history of stroke (4.599), and coronary heart disease (5.404), among others, were entered into the main effect model. For women, 11 risk factors included hypertension (5.270), family history of stroke (4.866), hyperlipidemia (4.346), among others. The related risk scores were added to obtain a combined risk score to predict the individual's risk of stoke in the future. An individual health risk appraisal model of stroke, which was applicable to individuals of different gender, age, health behavior, disease and family history, was established. In conclusion, personal diseases including hypertension, diabetes mellitus, etc., were very important to the prevalence of stoke. The prevalence of stroke can be effectively reduced by changing unhealthy lifestyles and curing the positive individual disease. The study lays a foundation for health education to persuade people to change their unhealthy lifestyles or behaviors, and could be used in community health services.

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

PubMed

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

2008-01-01

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

Income inequality and cardiovascular disease risk factors in a highly unequal country: a fixed-effects analysis from South Africa.

PubMed

Adjaye-Gbewonyo, Kafui; Kawachi, Ichiro; Subramanian, S V; Avendano, Mauricio

2018-03-06

Chronic stress associated with high income inequality has been hypothesized to increase CVD risk and other adverse health outcomes. However, most evidence comes from high-income countries, and there is limited evidence on the link between income inequality and biomarkers of chronic stress and risk for CVD. This study examines how changes in income inequality over recent years relate to changes in CVD risk factors in South Africa, home to some of the highest levels of income inequality globally. We linked longitudinal data from 9356 individuals interviewed in the 2008 and 2012 National Income Dynamics Study to district-level Gini coefficients estimated from census and survey data. We investigated whether subnational district income inequality was associated with several modifiable risk factors for cardiovascular disease (CVD) in South Africa, including body mass index (BMI), waist circumference, blood pressure, physical inactivity, smoking, and high alcohol consumption. We ran individual fixed-effects models to examine the association between changes in income inequality and changes in CVD risk factors over time. Linear models were used for continuous metabolic outcomes while conditional Poisson models were used to estimate risk ratios for dichotomous behavioral outcomes. Both income inequality and prevalence of most CVD risk factors increased over the period of study. In longitudinal fixed-effects models, changes in district Gini coefficients were not significantly associated with changes in CVD risk factors. Our findings do not support the hypothesis that subnational district income inequality is associated with CVD risk factors within the high-inequality setting of South Africa.

The Social Physique Anxiety Scale: an example of the potential consequence of negatively worded items in factorial validity studies.

PubMed

Motl, R W; Conroy, D E; Horan, P M

2000-01-01

Social physique anxiety (SPA) based on Hart, Leary, and Rejeski's (1989) Social Physique Anxiety Scale (SPAS) was originally conceptualized to be a unidimensional construct. Empirical evidence on the factorial validity of the SPAS has been contradictory, yielding both one- and two-factor models. The two-factor model, which consists of separate factors associated with positively and negatively worded items, has stimulated an ongoing debate about the dimensionality and content of the SPAS. The present study employed confirmatory factor analysis (CFA) to examine whether the two-factor solution to the 12-item SPAS was substantively meaningful or a methodological artifact. Results of the CFAs, which were performed on responses from four different samples (Eklund, Kelley, and Wilson, 1997; Eklund, Mack, and Hart, 1996), supported the existence of a single substantive SPA factor underlying responses to the 12-item SPAS. There were, in addition, method effects associated with the negatively worded items that could be modeled to achieve good fit. Therefore, it was concluded that a single substantive factor and a non-substantive method effect primarily related to the negatively worded items best represented the 12-item SPAS.

Deriving Scaling Factors Using a Global Hydrological Model to Restore GRACE Total Water Storage Changes for China's Yangtze River Basin

NASA Technical Reports Server (NTRS)

Long, Di; Yang, Yuting; Yoshihide, Wada; Hong, Yang; Liang, Wei; Chen, Yaning; Yong, Bin; Hou, Aizhong; Wei, Jiangfeng; Chen, Lu

2015-01-01

This study used a global hydrological model (GHM), PCR-GLOBWB, which simulates surface water storage changes, natural and human induced groundwater storage changes, and the interactions between surface water and subsurface water, to generate scaling factors by mimicking low-pass filtering of GRACE signals. Signal losses in GRACE data were subsequently restored by the scaling factors from PCR-GLOBWB. Results indicate greater spatial heterogeneity in scaling factor from PCR-GLOBWB and CLM4.0 than that from GLDAS-1 Noah due to comprehensive simulation of surface and subsurface water storage changes for PCR-GLOBWB and CLM4.0. Filtered GRACE total water storage (TWS) changes applied with PCR-GLOBWB scaling factors show closer agreement with water budget estimates of TWS changes than those with scaling factors from other land surface models (LSMs) in China's Yangtze River basin. Results of this study develop a further understanding of the behavior of scaling factors from different LSMs or GHMs over hydrologically complex basins, and could be valuable in providing more accurate TWS changes for hydrological applications (e.g., monitoring drought and groundwater storage depletion) over regions where human-induced interactions between surface water and subsurface water are intensive.

Assessing doses to terrestrial wildlife at a radioactive waste disposal site: inter-comparison of modelling approaches.

PubMed

Johansen, M P; Barnett, C L; Beresford, N A; Brown, J E; Černe, M; Howard, B J; Kamboj, S; Keum, D-K; Smodiš, B; Twining, J R; Vandenhove, H; Vives i Batlle, J; Wood, M D; Yu, C

2012-06-15

Radiological doses to terrestrial wildlife were examined in this model inter-comparison study that emphasised factors causing variability in dose estimation. The study participants used varying modelling approaches and information sources to estimate dose rates and tissue concentrations for a range of biota types exposed to soil contamination at a shallow radionuclide waste burial site in Australia. Results indicated that the dominant factor causing variation in dose rate estimates (up to three orders of magnitude on mean total dose rates) was the soil-to-organism transfer of radionuclides that included variation in transfer parameter values as well as transfer calculation methods. Additional variation was associated with other modelling factors including: how participants conceptualised and modelled the exposure configurations (two orders of magnitude); which progeny to include with the parent radionuclide (typically less than one order of magnitude); and dose calculation parameters, including radiation weighting factors and dose conversion coefficients (typically less than one order of magnitude). Probabilistic approaches to model parameterisation were used to encompass and describe variable model parameters and outcomes. The study confirms the need for continued evaluation of the underlying mechanisms governing soil-to-organism transfer of radionuclides to improve estimation of dose rates to terrestrial wildlife. The exposure pathways and configurations available in most current codes are limited when considering instances where organisms access subsurface contamination through rooting, burrowing, or using different localised waste areas as part of their habitual routines. Crown Copyright © 2012. Published by Elsevier B.V. All rights reserved.

Identifying Risk Factors for Drug Use in an Iranian Treatment Sample: A Prediction Approach Using Decision Trees.

PubMed

Amirabadizadeh, Alireza; Nezami, Hossein; Vaughn, Michael G; Nakhaee, Samaneh; Mehrpour, Omid

2018-05-12

Substance abuse exacts considerable social and health care burdens throughout the world. The aim of this study was to create a prediction model to better identify risk factors for drug use. A prospective cross-sectional study was conducted in South Khorasan Province, Iran. Of the total of 678 eligible subjects, 70% (n: 474) were randomly selected to provide a training set for constructing decision tree and multiple logistic regression (MLR) models. The remaining 30% (n: 204) were employed in a holdout sample to test the performance of the decision tree and MLR models. Predictive performance of different models was analyzed by the receiver operating characteristic (ROC) curve using the testing set. Independent variables were selected from demographic characteristics and history of drug use. For the decision tree model, the sensitivity and specificity for identifying people at risk for drug abuse were 66% and 75%, respectively, while the MLR model was somewhat less effective at 60% and 73%. Key independent variables in the analyses included first substance experience, age at first drug use, age, place of residence, history of cigarette use, and occupational and marital status. While study findings are exploratory and lack generalizability they do suggest that the decision tree model holds promise as an effective classification approach for identifying risk factors for drug use. Convergent with prior research in Western contexts is that age of drug use initiation was a critical factor predicting a substance use disorder.

Modeling the structure of the attitudes and belief scale 2 using CFA and bifactor approaches: Toward the development of an abbreviated version.

PubMed

Hyland, Philip; Shevlin, Mark; Adamson, Gary; Boduszek, Daniel

2014-01-01

The Attitudes and Belief Scale-2 (ABS-2: DiGiuseppe, Leaf, Exner, & Robin, 1988. The development of a measure of rational/irrational thinking. Paper presented at the World Congress of Behavior Therapy, Edinburg, Scotland.) is a 72-item self-report measure of evaluative rational and irrational beliefs widely used in Rational Emotive Behavior Therapy research contexts. However, little psychometric evidence exists regarding the measure's underlying factor structure. Furthermore, given the length of the ABS-2 there is a need for an abbreviated version that can be administered when there are time demands on the researcher, such as in clinical settings. This study sought to examine a series of theoretical models hypothesized to represent the latent structure of the ABS-2 within an alternative models framework using traditional confirmatory factor analysis as well as utilizing a bifactor modeling approach. Furthermore, this study also sought to develop a psychometrically sound abbreviated version of the ABS-2. Three hundred and thirteen (N = 313) active emergency service personnel completed the ABS-2. Results indicated that for each model, the application of bifactor modeling procedures improved model fit statistics, and a novel eight-factor intercorrelated solution was identified as the best fitting model of the ABS-2. However, the observed fit indices failed to satisfy commonly accepted standards. A 24-item abbreviated version was thus constructed and an intercorrelated eight-factor solution yielded satisfactory model fit statistics. Current results support the use of a bifactor modeling approach to determining the factor structure of the ABS-2. Furthermore, results provide empirical support for the psychometric properties of the newly developed abbreviated version.

Why item parcels are (almost) never appropriate: two wrongs do not make a right--camouflaging misspecification with item parcels in CFA models.

PubMed

Marsh, Herbert W; Lüdtke, Oliver; Nagengast, Benjamin; Morin, Alexandre J S; Von Davier, Matthias

2013-09-01

The present investigation has a dual focus: to evaluate problematic practice in the use of item parcels and to suggest exploratory structural equation models (ESEMs) as a viable alternative to the traditional independent clusters confirmatory factor analysis (ICM-CFA) model (with no cross-loadings, subsidiary factors, or correlated uniquenesses). Typically, it is ill-advised to (a) use item parcels when ICM-CFA models do not fit the data, and (b) retain ICM-CFA models when items cross-load on multiple factors. However, the combined use of (a) and (b) is widespread and often provides such misleadingly good fit indexes that applied researchers might believe that misspecification problems are resolved--that 2 wrongs really do make a right. Taking a pragmatist perspective, in 4 studies we demonstrate with responses to the Rosenberg Self-Esteem Inventory (Rosenberg, 1965), Big Five personality factors, and simulated data that even small cross-loadings seriously distort relations among ICM-CFA constructs or even decisions on the number of factors; although obvious in item-level analyses, this is camouflaged by the use of parcels. ESEMs provide a viable alternative to ICM-CFAs and a test for the appropriateness of parcels. The use of parcels with an ICM-CFA model is most justifiable when the fit of both ICM-CFA and ESEM models is acceptable and equally good, and when substantively important interpretations are similar. However, if the ESEM model fits the data better than the ICM-CFA model, then the use of parcels with an ICM-CFA model typically is ill-advised--particularly in studies that are also interested in scale development, latent means, and measurement invariance.

The role of self-perceived usefulness and competence in the self-esteem of elderly adults: confirmatory factor analyses of the Bachman revision of Rosenberg's Self-Esteem Scale.

PubMed

Ranzijn, R; Keeves, J; Luszcz, M; Feather, N T

1998-03-01

This article reports on a confirmatory analytic study of the Bachman Revision (1970) of Rosenberg's Self-Esteem Scale (1965) that was used in the Australian Longitudinal Study of Ageing (ALSA). Participants comprised 1,087 elderly people aged between 70 and 103 years (mean 77 years). Five competing factor models were tested with LISREL8. The best-fitting model was a nested one, with a General Self-Esteem second-order factor and two first-order factors, Positive Self-regard and Usefulness/Competence. This model was validated with data from a later wave of ALSA. Usefulness and competence have received little attention in the gerontological literature to date. Preliminary results indicate that usefulness/competence may be an important predictor of well-being. Further work is required on the relationships among usefulness, competence, self-esteem, and well-being in elderly people.

Construct validation of SF-36 Malay version among type 2 diabetes mellitus patients

NASA Astrophysics Data System (ADS)

Yap, Bee Wah; Jannoo, Zeinab; Razali, Nornadiah Mohd; Ghani, Nor Azura Md.; Lazim, Mohamad Alias

2015-02-01

The Short Form 36 (SF-36) is one of the most widely used generic health status measure. This study used the SF-36 Health Survey instrument to investigate the functional health and well-being of Malay Type 2 Diabetes Mellitus patients in Malaysia. The survey was carried out in three local hospitals in Selangor. The method of questionnaire administration was both self-administered and interviewer administered. A total of 354 questionnaires was returned, but only 295 questionnaires with no missing data were analyzed. Confirmatory Factor Analysis (CFA) was used to confirm the first-order and third-order CFA models. The higher order analyses included a third-order CFA models with two second-order factors (physical and mental component) and three second-order factors (physical, general well-being and mental health) and both showed satisfactory model fit indices. This study confirmed the multidimensional factor structure of the SF-36.

New factors controlling the balance between osteoblastogenesis and adipogenesis.

PubMed

Abdallah, Basem M; Kassem, Moustapha

2012-02-01

The majority of conditions associated with bone loss, including aging, are accompanied by increased marrow adiposity possibly due to shifting of the balance between osteoblast and adipocyte differentiation in bone marrow stromal (skeletal) stem cells (MSC). In order to study the relationship between osteoblastogenesis and adipogenesis in bone marrow, we have characterized cellular models of multipotent MSC as well as pre-osteoblastic and pre-adipocytic cell populations. Using these models, we identified two secreted factors in the bone marrow microenviroment: secreted frizzled-related protein 1 (sFRP-1) and delta-like1 (preadipocyte factor 1) (Dlk1/Pref-1). Both exert regulatory effects on osteoblastogenesis and adipogenesis. Our studies suggest a model for lineage fate determination of MSC that is regulated through secreted factors in the bone marrow microenvironment that mediate a cross-talk between lineage committed cell populations in addition to controlling differentiation choices of multipotent MSC. Copyright © 2011 Elsevier Inc. All rights reserved.

Factors associated with exclusive breastfeeding in the first six months of life in Brazil: a systematic review

PubMed Central

Boccolini, Cristiano Siqueira; de Carvalho, Márcia Lazaro; de Oliveira, Maria Inês Couto

2015-01-01

ABSTRACT OBJECTIVE To identify factors associated with exclusive breastfeeding in the first six months of life in Brazil. METHODS Systematic review of epidemiological studies conducted in Brazil with exclusive breastfeeding as outcome. Medline and LILACS databases were used. After the selection of articles, a hierarchical theoretical model was proposed according to the proximity of the variable to the outcome. RESULTS Of the 67 articles identified, we selected 20 cross-sectional studies and seven cohort studies, conducted between 1998 and 2010, comprising 77,866 children. We identified 36 factors associated with exclusive breastfeeding, being more often associated the distal factors: place of residence, maternal age and education, and the proximal factors: maternal labor, age of the child, use of a pacifier, and financing of primary health care. CONCLUSIONS The theoretical model developed may contribute to future research, and factors associated with exclusive breastfeeding may subsidize public policies on health and nutrition. PMID:26759970

An impact analysis of forecasting methods and forecasting parameters on bullwhip effect

NASA Astrophysics Data System (ADS)

Silitonga, R. Y. H.; Jelly, N.

2018-04-01

Bullwhip effect is an increase of variance of demand fluctuation from downstream to upstream of supply chain. Forecasting methods and forecasting parameters were recognized as some factors that affect bullwhip phenomena. To study these factors, we can develop simulations. There are several ways to simulate bullwhip effect in previous studies, such as mathematical equation modelling, information control modelling, computer program, and many more. In this study a spreadsheet program named Bullwhip Explorer was used to simulate bullwhip effect. Several scenarios were developed to show the change in bullwhip effect ratio because of the difference in forecasting methods and forecasting parameters. Forecasting methods used were mean demand, moving average, exponential smoothing, demand signalling, and minimum expected mean squared error. Forecasting parameters were moving average period, smoothing parameter, signalling factor, and safety stock factor. It showed that decreasing moving average period, increasing smoothing parameter, increasing signalling factor can create bigger bullwhip effect ratio. Meanwhile, safety stock factor had no impact to bullwhip effect.

The Construct Validity of Attitudes toward Career Counseling Scale for Korean College Students

ERIC Educational Resources Information Center

Nam, Suk Kyung; In Park, Hyung

2015-01-01

This study aimed to examine the construct validity of the Attitudes Toward Career Counseling Scale (ATCCS) in Korea. In Study 1, confirmatory factor analysis (CFA) was used for testing the factor structure of the scale. The results supported a two-factor (value and stigma) model, which was theoretically driven from the original study. Results of…

Depression Anxiety Stress Scales (DASS-21): Factor Structure in Traumatic Brain Injury Rehabilitation.

PubMed

Randall, Diane; Thomas, Matt; Whiting, Diane; McGrath, Andrew

To confirm the construct validity of the Depression Anxiety Stress Scales-21 (DASS-21) by investigating the fit of published factor structures in a sample of adults with moderate to severe traumatic brain injury (posttraumatic amnesia > 24 hours). Archival data from 504 patient records at the Brain Injury Rehabilitation Unit at Liverpool Hospital, Australia. Participants were aged between 16 and 71 years and were engaged in a specialist rehabilitation program. The DASS-21. Two of the 6 models had adequate fit using structural equation modeling. The data best fit Henry and Crawford's quadripartite model, which comprised a Depression, Anxiety and Stress factor, as well as a General Distress factor. The data also adequately fit Lovibond and Lovibond's original 3-factor model, and the internal consistencies of each factor were very good (α = 0.82-0.90). This study confirms the structure and construct validity of the DASS-21 and provides support for its use as a screening tool in traumatic brain injury rehabilitation.

The structure of post-traumatic stress symptoms in survivors of war: confirmatory factor analyses of the Impact of Event Scale--revised.

PubMed

Morina, Nexhmedin; Böhme, Hendryk F; Ajdukovic, Dean; Bogic, Marija; Franciskovic, Tanja; Galeazzi, Gian M; Kucukalic, Abdulah; Lecic-Tosevski, Dusica; Popovski, Mihajlo; Schützwohl, Matthias; Stangier, Ulrich; Priebe, Stefan

2010-08-01

The study aimed at establishing the factor structure of the Impact of Event Scale-Revised (IES-R) in survivors of war. A total sample of 4167 participants with potentially traumatic experiences during the war in Ex-Yugoslavia was split into three samples: two independent samples of people who stayed in the area of conflict and one sample of refugees to Western European countries. Alternative models with three, four, and five factors of post-traumatic symptoms were tested in one sample. The other samples were used for cross-validation. Results indicated that the model of best fit had five factors, i.e., intrusion, avoidance, hyperarousal, numbing, and sleep disturbance. Model superiority was cross-validated in the two other samples. These findings suggest a five-factor model of post-traumatic stress symptoms in war survivors with numbing and sleep disturbance as separate factors in addition to intrusion, avoidance and hyperarousal. (c) 2010 Elsevier Ltd. All rights reserved.

Soccer Players Cultural Capital and Its Impact on Migration

PubMed Central

Leskošek, Bojan; Vodičar, Janez; Topič, Mojca Doupona

2016-01-01

Abstract The purpose of this study was to identify factors that constituted the cultural capital among soccer players. We assumed that in the increasingly globalized world of professional soccer, a player’s success would often depend on migrating and adjusting to life in other countries. Willingness to migrate and successful adjustment are tied to player’s previous attitudes and/or behaviours (habitus), significant support from others, including family members, and previous experiences and success in sports and education. Our hypothesised model of the cultural capital was based on the Pierre Bourdieu’s theoretical framework. It consisted of 26 variables related to three sets of factors: soccer experiences, a family context and support, and educational achievements of the players and their parents. The model was tested using a sample of 79 current soccer coaches who also had been players at the elite level. A factor analysis was used to empirically verify the content of the hypothetical model of the soccer players’ cultural capital. Nine latent factors were extracted and together, they accounted for 55.01% of the total model variance. Individual factors obtained showed a sufficient level of substantial connection. The Cronbach’s alpha value of 0.77 confirmed the internal consistency of the operationalised variables in the hypothetical model. In addition, the impact of these aforementioned life dimensions on the migration of soccer players was studied. The results of the binary logistic regression analysis showed that the first factor of the hypothetical model (F1) had 2.2 times and the second factor (F8) had 3.9 times higher odds for migration abroad. Sociocultural findings using this new assessment approach could help create better “success conditions” in the talent development of young players. PMID:28031770

Biomechanical, psychosocial and individual risk factors predicting low back functional impairment among furniture distribution employees

PubMed Central

Ferguson, Sue A.; Allread, W. Gary; Burr, Deborah L.; Heaney, Catherine; Marras, William S.

2013-01-01

Background Biomechanical, psychosocial and individual risk factors for low back disorder have been studied extensively however few researchers have examined all three risk factors. The objective of this was to develop a low back disorder risk model in furniture distribution workers using biomechanical, psychosocial and individual risk factors. Methods This was a prospective study with a six month follow-up time. There were 454 subjects at 9 furniture distribution facilities enrolled in the study. Biomechanical exposure was evaluated using the American Conference of Governmental Industrial Hygienists (2001) lifting threshold limit values for low back injury risk. Psychosocial and individual risk factors were evaluated via questionnaires. Low back health functional status was measured using the lumbar motion monitor. Low back disorder cases were defined as a loss of low back functional performance of −0.14 or more. Findings There were 92 cases of meaningful loss in low back functional performance and 185 non cases. A multivariate logistic regression model included baseline functional performance probability, facility, perceived workload, intermediated reach distance number of exertions above threshold limit values, job tenure manual material handling, and age combined to provide a model sensitivity of 68.5% and specificity of 71.9%. Interpretation: The results of this study indicate which biomechanical, individual and psychosocial risk factors are important as well as how much of each risk factor is too much resulting in increased risk of low back disorder among furniture distribution workers. PMID:21955915

The Joint Effects of Lifestyle Factors and Comorbidities on the Risk of Colorectal Cancer: A Large Chinese Retrospective Case-Control Study

PubMed Central

Hu, Hai; Zhou, Yangyang; Ren, Shujuan; Wu, Jiajin; Zhu, Meiying; Chen, Donghui; Yang, Haiyan; Wang, Liwei

2015-01-01

Background Colorectal cancer (CRC) is a major cause of cancer morbidity and mortality. In previous epidemiologic studies, the respective correlation between lifestyle factors and comorbidity and CRC has been extensively studied. However, little is known about their joint effects on CRC. Methods We conducted a retrospective case-control study of 1,144 diagnosed CRC patients and 60,549 community controls. A structured questionnaire was administered to the participants about their socio-demographic factors, anthropometric measures, comorbidity history and lifestyle factors. Logistic regression model was used to calculate the odds ratio (ORs) and 95% confidence intervals (95%CIs) for each factor. According to the results from logistic regression model, we further developed healthy lifestyle index (HLI) and comorbidity history index (CHI) to investigate their independent and joint effects on CRC risk. Results Four lifestyle factors (including physical activities, sleep, red meat and vegetable consumption) and four types of comorbidity (including diabetes, hyperlipidemia, history of inflammatory bowel disease and polyps) were found to be independently associated with the risk of CRC in multivariant logistic regression model. Intriguingly, their combined pattern- HLI and CHI demonstrated significant correlation with CRC risk independently (ORHLI: 3.91, 95%CI: 3.13–4.88; ORCHI: 2.49, 95%CI: 2.11–2.93) and jointly (OR: 10.33, 95%CI: 6.59–16.18). Conclusions There are synergistic effects of lifestyle factors and comorbidity on the risk of colorectal cancer in the Chinese population. PMID:26710070