scholarly journals Predicting depression outcomes throughout inpatient treatment using the general and specific personality disorder factors

2020 ◽  
pp. 1-9
Author(s):  
Matthew P. Constantinou ◽  
B. Christopher Frueh ◽  
J. Christopher Fowler ◽  
Jon G. Allen ◽  
Alok Madan ◽  
...  
Keyword(s):  
Personality Disorder ◽  
Personality Disorders ◽  
Inpatient Treatment ◽  
Structural Equation ◽  
Growth Curves ◽  
Equation Model ◽  
General Factor ◽  
Depression Severity ◽  
Latent Growth Curves ◽  
Specific Factors

Abstract Background Clinical intuition suggests that personality disorders hinder the treatment of depression, but research findings are mixed. One reason for this might be the way in which current assessment measures conflate general aspects of personality disorders, such as overall severity, with specific aspects, such as stylistic tendencies. The goal of this study was to clarify the unique contributions of the general and specific aspects of personality disorders to depression outcomes. Methods Patients admitted to the Menninger Clinic, Houston, between 2012 and 2015 (N = 2352) were followed over a 6–8-week course of multimodal inpatient treatment. Personality disorder symptoms were assessed with the Structured Clinical Interview for Diagnostic and Statistical Manual of Mental Disorders, 4th edition Axis II Personality Screening Questionnaire at admission, and depression severity was assessed using the Patient Health Questionnaire-9 every fortnight. General and specific personality disorder factors estimated with a confirmatory bifactor model were used to predict latent growth curves of depression scores in a structural equation model. Results The general factor predicted higher initial depression scores but not different rates of change. By contrast, the specific borderline factor predicted slower rates of decline in depression scores, while the specific antisocial factor predicted a U shaped pattern of change. Conclusions Personality disorder symptoms are best represented by a general factor that reflects overall personality disorder severity, and specific factors that reflect unique personality styles. The general factor predicts overall depression severity while specific factors predict poorer prognosis which may be masked in prior studies that do not separate the two.

Economic hardship, positive affect, and marital processes over middle years

2018 ◽  
Vol 36 (10) ◽  
pp. 3239-3258
Author(s):  
Kandauda (K.A.S.) Wickrama ◽  
Catherine Walker O’Neal
Keyword(s):  
Positive Affect ◽  
Marital Quality ◽  
Structural Equation ◽  
Growth Curves ◽  
Married Couples ◽  
Economic Hardship ◽  
Equation Model ◽  
Psychological Resources ◽  
Effective Prevention ◽  
Latent Growth Curves

Family economic hardship (FEH) can negatively impact the quality of marital relationships, and research has shown that increased distress of husbands and wives at least partially mediates this association. Research has shown that FEH not only increases feelings of distress but also depletes individuals’ positive feelings. The mediating role of positive affect (PA), however, has received less attention. The current study used data from the Iowa Midlife Transitions Project with a sample of 370 married couples providing data from 1991 to 2001. Latent growth curves were estimated for families’ economic hardship and spouses’ PA. Increasing FEH over time generally resulted in the depletion of individuals’ PA after controlling for each spouse’s negative personality characteristics. These growth curves were included in a structural equation model ultimately assessing spouses’ marital quality (MQ). PA trajectories were related to hostile couple context, which was associated with reduced MQ. Findings emphasize the long-term consequences of FEH across middle adulthood on subsequent marital processes through both intra-individual (i.e., PA) and inter-individual (i.e., marital hostility) processes, suggesting that effective prevention and intervention efforts must account for influences at multiple levels and over extended periods of time on MQ. Furthermore, these findings support efforts aiming to strengthen positive psychological resources, rather than reducing psychological distress, as a means to improve MQ.

scholarly journals How does the grade obtained at school for English and Mathematics affect the probability of graduation at a university?

Pythagoras ◽  
2017 ◽  
Vol 38 (1) ◽  
Author(s):  
Michael Murray
Keyword(s):  
Structural Equation ◽  
Equation Model ◽  
Mathematical Literacy ◽  
Percentage Point Increase ◽  
Point Increase ◽  
Kwazulu Natal ◽  
Specific Factors ◽  
And Mathematics ◽  
The University ◽  
Better Than

Over half of all students enrolling at a particular university in KwaZulu-Natal fail to complete a degree. This article is wanting to determine to what extent the marks they obtain for English and Mathematics at school impact on their probability of graduation at this university. In addressing this problem, other student specific factors associated with their gender, race and the type of school they have attended need also to be properly accounted for. To provide answers for this study, the performance of 24 392 students enrolling at the university over the period 2004 to 2012 was followed until they graduated or dropped out from their studies. A structural equation model was fitted because it allows one to separate a direct effect from that of an indirect effect. Gender, race and school background were found to be very significant with males, Black Africans and students coming from a less privileged school background having a smaller probability associated with eventually graduating from this university. Males tend to perform better than females in Mathematics, with females performing better males in English. More importantly, however, a single percentage point increase in one’s mark for English increases the probability associated with graduating from this university far more than would be the case if their Mathematics mark were to increase by a single percentage point. In the light of these mediated results, perhaps this university should be directing their efforts more towards improving the English (rather than mathematical) literacy of students entering the university.

Higher-Order and Bifactor Models of the Drinking Motives Questionnaire

Assessment ◽  
2016 ◽  
Vol 24 (2) ◽  
pp. 222-231 ◽  
Author(s):  
Andrew Lac ◽  
Candice D. Donaldson
Keyword(s):  
Structural Equation ◽  
Negative Reinforcement ◽  
Factor Model ◽  
Equation Model ◽  
Higher Order ◽  
Bifactor Model ◽  
Drinking Motives ◽  
General Factor ◽  
Fit Indices ◽  
Confirmatory Factor Analyses

The Drinking Motives Questionnaire, previously postulated and documented to exhibit a measurement structure of four correlated factors (social, enhancement, conformity, and coping), is a widely administered assessment of reasons for consuming alcohol. In the current study ( N = 552), confirmatory factor analyses tested the plausibility of several theoretically relevant factor structures. Fit indices corroborated the original four-factor model, and also supported a higher-order factor model involving a superordinate motives factor that explicated four subordinate factors. A bifactor model that permitted items to double load on valence type (positive or negative reinforcement) and source type (external or internal) generated mixed results, suggesting that this 2 × 2 motivation paradigm was not entirely tenable. Optimal fit was obtained for a bifactor model depicting a general factor and four specific factors of motives. Latent factors derived from this structure exhibited criterion validity in predicting frequency and quantity of alcohol usage in a structural equation model. Findings are interpreted in the context of theoretical implications of the instrument, alternative factor structures of drinking motives, and assessment applications.

scholarly journals Exploring the Correlation Between the Attitude Toward Education and the Subjective Social Status

2020 ◽  
Vol 8 (2) ◽  
pp. 39-53
Author(s):  
Nicoleta Onofrei
Keyword(s):  
Social Status ◽  
School Environment ◽  
Structural Equation ◽  
Subjective Social Status ◽  
Equation Model ◽  
Educational Process ◽  
General Factor ◽  
Latent Factors ◽  
Education Benefits ◽  
Validated Questionnaire

AbstractIn this article we investigate the correlation between the attitude toward education and the subjective social status of the students. We used a previously validated questionnaire to measure the attitude toward education and the MacArthur Scale of subjective social status capturing first, personal familial placement within society and secondly, personal placement in the school environment. This questionnaire was distributed online and was completed by 185 respondents from different schools and universities. The data was analyzed in R, performing factor analysis and a structural equation model. 4 latent factors were identified, that influence the formation of the attitude toward education, namely a general factor, usefulness of education, benefits of education and dislike of education. Only the second part of the scale influence 2 latent factors-general factor and usefulness of education. These results suggest that students positioning themselves higher in school or university have a better attitude toward education and are more prone to appreciate educational process and outcomes.

Domain-Specificity of Need for Cognition Among High School Students

2019 ◽  
Vol 35 (5) ◽  
pp. 607-616 ◽  
Author(s):  
Ulrich Keller ◽  
Anja Strobel ◽  
Romain Martin ◽  
Franzis Preckel
Keyword(s):  
High School Students ◽  
Structural Equation ◽  
Factor Model ◽  
Need For Cognition ◽  
Self Concept ◽  
Equation Modeling ◽  
Specific Factor ◽  
General Factor ◽  
Domain Specific ◽  
Specific Factors

Abstract. Need for Cognition (NFC) is increasingly investigated in educational research. In contrast to other noncognitive constructs in this area, such as academic self-concept and interest, NFC has consistently been conceptualized as domain-general. We employed structural equation modeling to address the question of whether NFC can be meaningfully and gainfully conceptualized as domain-specific. To this end, we developed a domain-specific 20-item NFC scale with parallel items for Science, Mathematics, German, and French. Additionally, domain-general NFC was assessed with five domain-general items. Using a cross-sectional sample of more than 4,500 Luxembourgish 9th graders, we found that a nested-factor model incorporating both a general factor and domain-specific factors better accounted for the data than a single-factor or a correlated-factor model. However, the influence of the general factor was markedly stronger than in corresponding models for academic self-concept and interest. When controlling for the domain-specific factors, only Mathematics achievement was significantly predicted by the domain-general factor, while all achievement measures (Mathematics, French, and German) were predicted by the corresponding domain-specific factor. The nested domain-specific NFC factors were clearly empirically distinguishable from first-order domain-specific interest factors.

scholarly journals Construct Validity of Scores From the Connor–Davidson Resilience Scale in a Sample of Postsecondary Students With Disabilities

Assessment ◽  
2016 ◽  
Vol 25 (2) ◽  
pp. 193-205 ◽  
Author(s):  
Harsha N. Perera ◽  
Rahul Ganguly
Keyword(s):  
Students With Disabilities ◽  
Structural Equation ◽  
Well Being ◽  
Equation Modeling ◽  
Postsecondary Students ◽  
General Factor ◽  
Validation Data ◽  
Resilience Scale ◽  
Specific Factors ◽  
Career Optimism

Although theory posits a multidimensional structure of resilience, studies have supported a unidimensional solution for data obtained from the commonly used Connor–Davidson Resilience Scale (CD-RISC). This study investigated the latent structure of CD-RISC responses in a sample of postsecondary students with disabilities. Furthermore, the validity of CD-RISC scores was examined with respect to career optimism and well-being. The analyses were conducted using confirmatory factor analysis and exploratory structural equation modeling (ESEM). Results supported a bifactor-ESEM representation of the CD-RISC data that accounts for construct-relevant multidimensionality in scores due to the presence of general and specific factors and the fallibility of indicators as pure reflections of the constructs they measure. Although three specific factors showed meaningful residual specificity over and above the general factor, two specific factors were weakly defined with little meaningful residual specificity. However, these factors may retain some utility in the bifactor-ESEM model insofar as they control for limited levels of residual covariance in items. Evidence was also obtained for relations of the general and substantively interpretable specific factors with career optimism and well-being. The results of the study provide validation data for the CD-RISC and clarify recent research converging on seemingly disparate unidimensional and multidimensional solutions.

scholarly journals Investigating the Dimensionality of Early Numeracy Using the Bifactor Exploratory Structural Equation Modeling Framework

2021 ◽  
Vol 12 ◽  
Author(s):  
Christophe Dierendonck ◽  
Anne-Françoise de Chambrier ◽  
Annick Fagnant ◽  
Christophe Luxembourger ◽  
Mélanie Tinnes-Vigne ◽  
...  
Keyword(s):  
Structural Equation Modeling ◽  
Structural Equation ◽  
Equation Modeling ◽  
General Factor ◽  
Early Numeracy ◽  
Exploratory Structural Equation Modeling ◽  
Numerical Ability ◽  
Specific Factors ◽  
Early Number ◽  
The One

The few studies that have analyzed the factorial structure of early number skills have mainly used confirmatory factor analysis (CFA) and have yielded inconsistent results, since early numeracy is considered to be unidimensional, multidimensional or even underpinned by a general factor. Recently, the bifactor exploratory structural equation modeling (bifactor-ESEM)—which has been proposed as a way to overcome the shortcomings of both the CFA and the exploratory structural equation modeling (ESEM)—proved to be valuable to account for the multidimensionality and the hierarchical nature of several psychological constructs. The present study is the first to investigate the dimensionality of early number skills measurement through the application of the bifactor-ESEM framework. Using data from 644 prekindergarten and kindergarten children (4 to 6 years old), several competing models were contrasted: the one-factor CFA model; the independent cluster model (ICM-CFA); the exploratory structural equation modeling (ESEM); and their bifactor counterpart (bifactor-CFA and bifactor-ESEM, respectively). Results indicated acceptable fit indexes for the one-factor CFA and the ICM-CFA models and excellent fit for the others. Among these, the bifactor-ESEM with one general factor and three specific factors (Counting, Relations, Arithmetic) not only showed the best model fit, but also the best coherent factor loadings structure and full measurement invariance across gender. The bifactor-ESEM appears relevant to help disentangle and account for general and specific factors of early numerical ability. While early numerical ability appears to be mainly underpinned by a general factor whose exact nature still has to be determined, this study highlights that specific latent dimensions with substantive value also exist. Identifying these specific facets is important in order to increase quality of early numerical ability measurement, predictive validity, and for practical implications.

Relational Uncertainty Within Relational Turbulence Theory: The Bifactor Exploratory Structural Equation Model

2021 ◽  
Author(s):  
Alan K Goodboy ◽  
San Bolkan ◽  
, Kellie Brisini ◽  
Denise Haunani Solomon
Keyword(s):  
Structural Equation Model ◽  
Structural Equation ◽  
Factor Model ◽  
Equation Model ◽  
Turbulence Theory ◽  
General Factor ◽  
Relational Uncertainty ◽  
Measurement Models ◽  
Relational Turbulence ◽  
Confirmatory Factor

Abstract Relational uncertainty consists of self, partner, and relationship uncertainty, which are core parameters in relational turbulence theory (RTT). Advances in latent variable modeling allow researchers to examine the multidimensional construct as a bifactor model, including a general factor of relational uncertainty and residualized factors of self, partner, and relationship uncertainty. This advance is theoretically consequential because RTT maintains the importance of distinctions among the facets of relational uncertainty, even while empirical evidence demonstrates considerable overlap among them. In two data sets (college sample, N = 513; married sample, N = 354), competing measurement models specified Relational Uncertainty Scale items as a unidimensional confirmatory factor model, 3-factor independent clusters confirmatory factor model, 3-factor exploratory structural equation model (ESEM), bifactor confirmatory factor model, and bifactor-ESEM. The bifactor-ESEM provided the best fit in both samples, and bifactor statistics clarified how variance from the scale is partitioned to yield essential unidimensionality for the general factor of relational uncertainty, controlling for its residualized factors. Tests of a latent predictive model using a bifactor specification of relational uncertainty were consistent with RTT. Implications for testing communication theory using bifactor-ESEM are discussed in light of these findings.

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