Brief Symptom Inventory Factor Structure in Antisocial Adolescents: Implications for Juvenile Justice

2011 ◽  
Vol 22 (2) ◽  
pp. 166-173 ◽  
Author(s):  
Ahmed Whitt ◽  
Matthew O. Howard
Keyword(s):  
Juvenile Justice ◽  
Factor Structure ◽  
Latent Variable ◽  
Structural Equation ◽  
Factor Model ◽  
Psychiatric Patients ◽  
Brief Symptom Inventory ◽  
Equation Modeling ◽  
Symptom Inventory ◽  
Antisocial Youth

Objectives: The Brief Symptom Inventory (BSI) is widely used in juvenile justice settings; however, little is known regarding its factor structure in antisocial youth. The authors evaluated the BSI factor structure in a state residential treatment population. Methods: 707 adolescents completed the BSI. Exploratory and confirmatory factor analyses were used to assess factor structure. Intergroup variability was examined using multiple-group structural equation modeling. Results: Findings supported a 6-factor, 25-item model explaining 49.5%of sample variance. The derived structure differed from prior findings with adult psychiatric patients by including a suicidal ideation latent variable and excluding several developmentally inappropriate factors. Conclusion: There may be problems associated with indiscriminant application of the original BSI factor model to juvenile justice populations.

scholarly journals Is China Moving toward Healthy Aging? A Tracking Study Based on 5 Phases of CLHLS Data

2020 ◽  
Vol 17 (12) ◽  
pp. 4343
Author(s):  
Yinan Yang ◽  
Yingying Meng
Keyword(s):  
Older People ◽  
Physical Health ◽  
Latent Variable ◽  
Structural Equation ◽  
Healthy Aging ◽  
Factor Model ◽  
Equation Modeling ◽  
Elderly Individuals ◽  
Comparison Results ◽  
Elderly Populations

Health is the key to the aging problem, and “healthy aging” depicts the overall changing trends in the health of all elderly individuals in a society. Based on the Chinese Longitudinal Healthy Longevity Survey (CLHLS) data from the years 2002, 2005, 2008, 2011 and 2014, this article investigates whether there is a trend of “healthy aging” in China. A second-order factor model including four dimensions of physical health, functional status, mental health and social health was constructed to measure a latent variable, “Health_elders”. The further multigroup comparison results by structural equation modeling showed that, with the exception of 2008, the Health_elders in 2002, 2005, 2011 and 2014 displayed an upward trend, and the mean differences in Health_elders across five periods were significant. These findings indicate that on the whole, compared with older people in the past, older people in more recent periods are healthier, which supports the trend of “healthy aging” in China. In terms of cohorts, the average health levels of male, town-residing elderly populations are higher, while the healthy aging trends among female, rural and urban elderly populations are stronger. Moreover, the physical health levels of the 60–74 years-old cohort are decreasing, and the participation of elderly individuals in social activities is low, which are the weaknesses in the healthy aging process in China.

A New Dimension of Organizational Justice: Procedural Voice

2009 ◽  
Vol 105 (2) ◽  
pp. 411-426 ◽  
Author(s):  
Denise Jepsen ◽  
John Rodwell
Keyword(s):  
Structural Equation Modeling ◽  
Organizational Justice ◽  
Latent Variable ◽  
Structural Equation ◽  
Factor Model ◽  
Model Fit ◽  
Equation Modeling ◽  
Wide Range

Dimensionality of the Colquitt justice measures was investigated across a wide range of service occupations. Structural equation modeling of data from 410 survey respondents found support for the 4-factor model of justice (procedural, distributive, interpersonal, and informational), although significant improvement of model fit was obtained by including a new latent variable, “procedural voice,” which taps employees' desire to express their views and feelings and influence results. The model was confirmed in a second sample ( N = 505) in the same organization six months later.

Modeling the Structure of the Triarchic Psychopathy Measure: Conceptual, Empirical, and Analytic Considerations

2019 ◽  
Vol 33 (4) ◽  
pp. 470-496 ◽  
Author(s):  
Antonella Somma ◽  
Serena Borroni ◽  
Laura E. Drislane ◽  
Christopher J. Patrick ◽  
Andrea Fossati
Keyword(s):  
Factor Structure ◽  
Structural Equation ◽  
Factor Model ◽  
Community Dwelling ◽  
Least Square ◽  
Equation Modeling ◽  
General Factor ◽  
Specific Content ◽  
Using Data ◽  
Three Factor

This study sought to characterize the factor structure of the Triarchic Psychopathy Measure (TriPM) using data from a sample of 1,082 community-dwelling Italian adults. Exploratory structural equation modeling (ESEM) was used to compare the fit of a bifactor model for each TriPM scale, in which specific-content factors were specified along with a general factor, with the fit of a single, general-factor model. Robust weighted least square (WLSMV) ESEM supported a bifactor latent structure of the TriPM items for all individual scales. When we jointly factor analyzed the 58 TriPM items, a WLSMV ESEM three-factor structure showed adequate fit; the three ESEM factors were akin to TriPM Boldness, Meanness, and Disinhibition theoretical dimensions, respectively, and could be effectively replicated across gender subgroups. Our findings support the three-factor structure of TriPM items, at least in Italian community-dwelling adults, and provide further evidence for the construct validity of the TriPM.

scholarly journals The Latent-Variable Structure of the Addenbrooke’s Cognitive Examination-Revised

2019 ◽  
Vol 35 (2) ◽  
pp. 205-212 ◽  
Author(s):  
Madeleine L Connolly ◽  
Stephen C Bowden ◽  
Leonie C Simpson ◽  
Malcolm Horne ◽  
Sarah McGregor
Keyword(s):  
Latent Variable ◽  
Structural Equation ◽  
Factor Model ◽  
Five Factor Model ◽  
Variable Structure ◽  
Equation Modeling ◽  
Long Term Memory ◽  
Chc Theory ◽  
Three Factor ◽  
Addenbrooke’S Cognitive Examination

Abstract Objectives To establish a theoretically justified factor structure for the Addenbrooke’s Cognitive Examination-Revised (ACE-R). Methods Our sample comprised 288 patients with Parkinson’s disease (179 men and 109 women). The mean age of participants was 66.66 (SD = 8.93). Confirmatory factor analysis (CFA) was used to evaluate the test developers’ five-factor model of the ACE-R, and alternative models as guided by the Cattell–Horn–Carroll (CHC) theory. Exploratory structural equation modeling (ESEM) was also employed to examine alternative factor structures to ensure that a good candidate model was not overlooked. Results A three-factor CHC-guided CFA and a similar three-factor ESEM model both showed acceptable overall fit, and interpretable factor structures. The three-factor CFA model showed two factors of pure CHC constructs: acquired knowledge (Gc), and visuospatial ability (Gv), and one combined factor, namely, long-term memory retrieval, fluency, and working memory (Glr-Gsm). The three-factor ESEM model showed three factors essentially in line with the CFA results. Conclusion The three-factor CHC-guided CFA model was selected as the best model to guide clinical interpretation of cognitive variables underlying ACE-R scores.

scholarly journals How to Compare Psychometric Factor and Network Models

2020 ◽  
Vol 8 (4) ◽  
pp. 35
Author(s):  
Kees-Jan Kan ◽  
Hannelies de Jonge ◽  
Han L. J. van der Maas ◽  
Stephen Z. Levine ◽  
Sacha Epskamp
Keyword(s):  
Latent Variable ◽  
Structural Equation ◽  
Factor Model ◽  
Empirical Finding ◽  
Network Models ◽  
Latent Variable Models ◽  
R Package ◽  
Equation Modeling ◽  
Adult Intelligence Scale ◽  
Intelligence Scale

In memory of Dr. Dennis John McFarland, who passed away recently, our objective is to continue his efforts to compare psychometric networks and latent variable models statistically. We do so by providing a commentary on his latest work, which he encouraged us to write, shortly before his death. We first discuss the statistical procedure McFarland used, which involved structural equation modeling (SEM) in standard SEM software. Next, we evaluate the penta-factor model of intelligence. We conclude that (1) standard SEM software is not suitable for the comparison of psychometric networks with latent variable models, and (2) the penta-factor model of intelligence is only of limited value, as it is nonidentified. We conclude with a reanalysis of the Wechlser Adult Intelligence Scale data McFarland discussed and illustrate how network and latent variable models can be compared using the recently developed R package Psychonetrics. Of substantive theoretical interest, the results support a network interpretation of general intelligence. A novel empirical finding is that networks of intelligence replicate over standardization samples.

Exploring the optimal factor structure of the Five Facet Mindfulness Questionnaire: Associations between mindfulness facets and dimensions of psychopathology

2021 ◽  
Author(s):  
Joseph M. Diehl ◽  
Craig Anthony Rodriguez-Seijas ◽  
Justine S. Thompson ◽  
Kristy Dalrymple ◽  
Iwona Chelminski ◽  
...  
Keyword(s):  
Substance Use ◽  
Substance Use Disorders ◽  
Factor Structure ◽  
Structural Equation ◽  
Factor Model ◽  
Equation Modeling ◽  
Clinical Samples ◽  
Underlying Structure ◽  
Five Facet Mindfulness Questionnaire ◽  
Mindfulness Facets

Recent studies of the Five Facet Mindfulness Questionnaire (FFMQ) and its condensed version (FFMQ-SF) fail to replicate the initially proposed 5-factor structure in clinical samples. Failure to adequately understand the dimensionality of common mindfulness measures within clinical samples, therefore, represents an important gap in the current literature. The increasing popularity of mindfulness-based interventions warrants further investigation of differential associations between facets of mindfulness and different forms of psychopathology. We examined (1) the underlying structure of the FFMQ and FFMQ-SF and (2) associations between FFMQ and FFMQ-SF facets and dimensions of psychopathology (i.e. internalizing and substance use disorders) in two large clinical samples (N = 2,779). Results from bass-ackwards analyses suggested similarly defensible 5- and 6-factor models solutions in terms of fit. The 5-factor model was optimal when factoring in parsimony. Exploratory structural equation modeling revealed that all FFMQ facets with the exception of observe were negatively associated with the internalizing factor. Associations with substance use disorders were more complex. In both samples, 5-factor FFMQ and FFMQ-SF models were determined to best represent these data. While deficits in all FFMQ facets with the exception of observe correspond with lower internalizing psychopathology, a more nuanced association was observed with substance use disorders.

A Psychometric Study of the Quality Perception Questionnaire

2012 ◽  
Vol 71 (2) ◽  
pp. 101-106 ◽  
Author(s):  
Raffaele Cioffi† ◽  
Anna Coluccia ◽  
Fabio Ferretti ◽  
Francesca Lorini ◽  
Aristide Saggino ◽  
...  
Keyword(s):  
Structural Equation ◽  
Factor Model ◽  
Equation Modeling ◽  
Fit Indices ◽  
Quality Perception ◽  
Italian Survey ◽  
Confirmatory Factor ◽  
Instrument Measuring ◽  
Hospital Structures

The present paper reexamines the psychometric properties of the Quality Perception Questionnaire (QPQ), an Italian survey instrument measuring patients’ perceptions of the quality of a recent hospital admission experience, in a sample of 4400 patients (Mage = 56.42 years; SD = 19.71 years, 48.8% females). The 14-item survey measures four factors: satisfaction with medical doctors, nursing staff, auxiliary staff, and hospital structures. First, we tested two models using a confirmatory factor analysis (structural equation modeling): a four orthogonal factor and a four oblique factor model. The SEM fit indices and the χ² difference suggested the acceptance of the second model. We then did a simulation using a bootstrap with 1000 replications. Results confirmed the four oblique factor solution. Third, we tested whether there were significant differences with respect to age or sex. The multivariate general linear model showed no significant differences in the factors with respect to sex or age.

Validating the Factor Structure of the Stigma of Suicide Scale–Short Form Spanish Version Among Healthcare Students

Crisis ◽  
2020 ◽  
pp. 1-5
Author(s):  
Ruthmarie Hernández-Torres ◽  
Paola Carminelli-Corretjer ◽  
Nelmit Tollinchi-Natali ◽  
Ernesto Rosario-Hernández ◽  
Yovanska Duarté-Vélez ◽  
...  
Keyword(s):  
Factor Structure ◽  
Structural Equation ◽  
Short Form ◽  
Small Sample Size ◽  
Small Sample ◽  
Spanish Version ◽  
Equation Modeling ◽  
Cross Sectional ◽  
Healthcare Students ◽  
Spanish Speaking

Abstract. Background: Suicide is a leading cause of death among Spanish-speaking individuals. Suicide stigma can be a risk factor for suicide. A widely used measure is the Stigma of Suicide Scale-Short Form (SOSS-SF; Batterham, Calear, & Christensen, 2013 ). Although the SOSS-SF has established psychometric properties and factor structure in other languages and cultural contexts, no evidence is available from Spanish-speaking populations. Aim: This study aims to validate a Spanish translation of the SOSS-SF among a sample of Spanish-speaking healthcare students ( N = 277). Method: We implemented a cross-sectional design with quantitative techniques. Results: Following a structural equation modeling approach, a confirmatory factor analysis (CFA) supported the three-factor model proposed by Batterham and colleagues (2013) . Limitations: The study was limited by the small sample size and recruitment by availability. Conclusion: Findings suggest that the Spanish version of the SOSS-SF is a valid and reliable tool with which to examine suicide stigma among Spanish-speaking populations.

Working Memory, Mental Prospection, Time Orientation, and Cognitive Insight

2013 ◽  
Vol 34 (3) ◽  
pp. 159-169 ◽  
Author(s):  
Sevtap Cinan ◽  
Aslı Doğan
Keyword(s):  
Working Memory ◽  
Structural Equation ◽  
Factor Model ◽  
Time Orientation ◽  
Equation Modeling ◽  
Cognitive Insight ◽  
Confirmatory Factor ◽  
Negative Effect ◽  
Positive Effect ◽  
Three Factor

This research is new in its attempt to take future time orientation, morningness orientation, and prospective memory as measures of mental prospection, and to examine a three-factor model that assumes working memory, mental prospection, and cognitive insight are independent but related higher-order cognitive constructs by using confirmatory factor analysis (CFA). The three-factor model produced a good fit to the data. An alternative one-factor model was tested and rejected. The results suggest that working memory and cognitive insight are distinguishable, related constructs, and that both are distinct from, but negatively associated with, mental prospection. In addition, structural equation modeling (SEM) showed that working memory had a strong positive effect on cognitive insight and a moderate negative effect on mental prospection.

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