Factor Structure and Incremental Utility of the Multidimensional Cognitive Attentional Syndrome Scale (MCASS): A Bifactor Analysis

The Multidimensional Cognitive Attentional Syndrome Scale (MCASS) was developed to assess the seven maladaptive forms of self-regulation that make up the cognitive attentional syndrome (CAS). Both theory and empirical evidence highlight important distinctions among the seven forms of self-regulation underlying the CAS. The primary purpose of the present study was to determine whether the MCASS item scores are sufficiently multidimensional to warrant the use of subscale scores. A secondary aim was to examine the incremental utility of the MCASS domain-specific factors. A battery of self-report measures was administered to adults recruited through a crowd-sourcing website (N?=?359). Bifactor analysis was used to examine the multidimensionality of MCASS item scores. This analytic approach allowed for the quantification of variance captured by each domain-specific item score independent of the general factor. Results from the bifactor analysis suggest that the MCASS is a multidimensional measure, consisting of a strong general factor and domain-specific factors that are sufficiently distinct. Additionally, the majority of domain-specific factors provided incremental utility in predicting two criterion variables (i.e., general distress, happiness emotion goals) after accounting for the general factor. Taken together, results support continued use of the MCASS total scale and subscale scores and suggest that researchers may want to consider using a bifactor model when examining structural models that include the MCASS.

     

A bifactor model of subjective well-being: A re-examination of the structure of subjective well-being

The present research has aimed to extend the previous research on the structure of subjective well-being (SWB) by applying the bifactor model. The Satisfaction with Life Scale (SWLS) and the Positive and Negative Affect Schedule (PANAS) were administered to two large samples of Serbian young adults (N₁ = 1669, N₂ = 1522). The bifactor model of SWB with one general and three specific factors (life satisfaction, positive affect, and negative affect) provided the best fit to the data and outperformed the original three-factor model and the higher-factor model in both samples. The results supported the multidimensional nature of SWB, with a strong general factor underlying the SWLS and PANAS. Bifactor modeling has shown that SWLS and PANAS reflect both common and specific variance in SWB, with about half of the reliable variance in life satisfaction, positive affect, and negative affect being independent of the general factor. The present findings imply that researchers should be careful when interpreting SWLS and PANAS scores and that general SWB factor should be taken into account. Implications for scale scoring and interpretation, and theoretical conceptualization of SWB are discussed.     

Bifactor models and rotations: exploring the extent to which multidimensional data yield univocal scale scores

The application of psychological measures often results in item response data that arguably are consistent with both unidimensional (a single common factor) and multidimensional latent structures (typically caused by parcels of items that tap similar content domains). As such, structural ambiguity leads to seemingly endless "confirmatory" factor analytic studies in which the research question is whether scale scores can be interpreted as reflecting variation on a single trait. An alternative to the more commonly observed unidimensional, correlated traits, or second-order representations of a measure's latent structure is a bifactor model. Bifactor structures, however, are not well understood in the personality assessment community and thus rarely are applied. To address this, herein we (a) describe issues that arise in conceptualizing and modeling multidimensionality, (b) describe exploratory (including Schmid-Leiman [Schmid & Leiman, 1957] and target bifactor rotations) and confirmatory bifactor modeling, (c) differentiate between bifactor and second-order models, and (d) suggest contexts where bifactor analysis is particularly valuable (e.g., for evaluating the plausibility of subscales, determining the extent to which scores reflect a single variable even when the data are multidimensional, and evaluating the feasibility of applying a unidimensional item response theory (IRT) measurement model). We emphasize that the determination of dimensionality is a related but distinct question from either determining the extent to which scores reflect a single individual difference variable or determining the effect of multidimensionality on IRT item parameter estimates. Indeed, we suggest that in many contexts, multidimensional data can yield interpretable scale scores and be appropriately fitted to unidimensional IRT models.     

Is the Bifactor Model a Better Model or Is It Just Better at Modeling Implausible Responses? Application of Iteratively Reweighted Least Squares to the Rosenberg Self-Esteem Scale

Although the structure of the Rosenberg Self-Esteem Scale (RSES) has been exhaustively evaluated, questions regarding dimensionality and direction of wording effects continue to be debated. To shed new light on these issues, we ask (a) for what percentage of individuals is a unidimensional model adequate, (b) what additional percentage of individuals can be modeled with multidimensional specifications, and (c) what percentage of individuals respond so inconsistently that they cannot be well modeled? To estimate these percentages, we applied iteratively reweighted least squares (IRLS) to examine the structure of the RSES in a large, publicly available data set. A distance measure, d_s, reflecting a distance between a response pattern and an estimated model, was used for case weighting. We found that a bifactor model provided the best overall model fit, with one general factor and two wording-related group factors. However, on the basis of d_r?values, a distance measure based on individual residuals, we concluded that approximately 86% of cases were adequately modeled through a unidimensional structure, and only an additional 3% required a bifactor model. Roughly 11% of cases were judged as “unmodelable” due to their significant residuals in all models considered. Finally, analysis of d_s revealed that some, but not all, of the superior fit of the bifactor model is owed to that model's ability to better accommodate implausible and possibly invalid response patterns, and not necessarily because it better accounts for the effects of direction of wording.     

Modeling general and specific variance in multifaceted constructs: a comparison of the bifactor model to other approaches

This article recommends an alternative method for testing multifaceted constructs. Researchers often have to choose between two problematic approaches for analyzing multifaceted constructs: the total score approach and the individual score approach. Both approaches can result in conceptual ambiguity. The proposed bifactor model assesses simultaneously the general construct shared by the facets and the specific facets, over and above the general construct. We illustrate the bifactor model by examining the construct of Extraversion as measured by the Revised NEO Personality Inventory (NEO‐PI‐R; Costa & McCrae, 1992), with two college samples (N = 383 and 378). The analysis reveals that the facets of the NEO‐PI‐R Extraversion correlate with criteria in opposite directions after partialling out the general construct. The direction of gender differences also varies by facets. Bifactor models combine the advantages but avoid the drawbacks of the 2 existing methods and can lead to greater conceptual clarity.     

The Counseling Center Assessment of Psychological Symptoms Distress Index: A pragmatic exploration of general factors to enhance a multidimensional scale

Objective: The authors attempted to develop and validate a general distress index for a multidimensional psychological symptom/outcome measure used in over 300 college counseling centers with more than 100,000 cases annually: the Counseling Center Assessment of Psychological Symptoms (CCAPS). Method: Four models were compared for fit indices (n = 19,247): the existing first-order factor model (without a general factor), a second-order factor model, a bifactor model, and a single factor or “total score” model. In separate clinical and non-clinical samples, concurrent and divergent validity were examined using several well-established measures of psychological symptoms, as well as two-week test–retest and treatment utilization data. Results: Second-order and bifactor models which captured a single “distress” factor both exhibited good fit to the data relative to the baseline and “total score” model. Validity data indicated that factors adequately measured meaningful clinical onstructs. Conclusion: Both the bifactor and second-order models indicated the presence of a “distress index” comprised items across many of the CCAPS subscales. This distress scale has strong applicability for benchmarking the overall severity and complexity of patients at different centers, and can be used to help identify colleges and universities with areas of clinical strength, which can be studied to improve the field. Clinically, the distress index offers a parsimonious and efficient method for clinicians to monitor patients’ progress through treatment.     

Validity of evaluative factors from Big Five and HEXACO questionnaires

Bifactor models were applied to the NEO-FFI-3, HEXACO PI-R, and BFI-2 questionnaires. Factor scores of factors representing the domains of the questionnaires, evaluation, and acquiescence were estimated. Simple and multiple validities of the factor scores were compared with summated scale validities. The evaluation factor was a significant predictor of GPA in all questionnaires. There was little evidence of a relation of GPA to the acquiescence factor. The validities of the domain factor scores, controlling for the evaluation and acquiescence factors, were uniformly more negative than those of corresponding summated scales. Results suggest that the evaluative contamination of Big Five and HEXACO summated scores can be isolated and used effectively with bifactor modeling techniques.     

Attitudes Toward Religion Scale: development and initial psychometric evaluation among Chinese college students

The Attitudes Toward Religion Scale (ATRS) was developed to access the level of interest in and position toward the five state-approved religions in China. Data were analysed across two samples of Chinese college students. With Sample 1 (N = 278), exploratory factor analyses were used to select the 10 ATRS items corresponding to two factors: Interest and Position. With Sample 2, confirmatory factor analyses (N = 270) cross-validated the two-factor oblique model as well as a bifactor model. Cronbach alphas of ATRS subscale scores in the two samples ranged from .75 to .85. ATRS-Interest and Position were both positively associated with number of close relationships with religious people. In addition, negative attitudes toward religion was associated with being religiously proselytised by strangers. Moreover, female students reported more favourable attitudes toward religion compared to their male counterparts. The overall results support ATRS as a psychometrically strong and promising measure.     

Irritability and Emotional Impulsivity as Core Feature of ADHD and ODD in Children

The categorical approach of diagnosing mental disorders entails the problem of frequently occurring comorbidities, suggesting a more parsimonious structure of psychopathology. In this study, we therefore aim to assess how affective dysregulation (AD) is associated with attention-deficit/hyperactivity disorder (ADHD) and oppositional defiant disorder (ODD) in children. To assess AD in children aged 8–12 years (n?=?391), we employed the parent version of a newly constructed parent rating scale. Following item reduction, we conducted exploratory and confirmatory factor analyses to establish a factorial structure of AD. One core dimension was identified, comprising irritability and emotional impulsivity, and two smaller dimensions, comprising positive emotionality and exuberance. Subsequently, we examined five different latent factor models – a unidimensional model, a first-order correlated factor model, a second-order correlated factor model, a traditional bifactor model, and a bifactor S-1 model, in which the first-order factor AD-Irritability/Emotional Impulsivity (II) was modeled as the general reference factor. A bifactor S-1 model with the a priori defined general reference domain AD-II provided the best fit to our data and was straightforward to interpret. This model showed excellent model fit and no anomalous factor loadings. This still held true, when comparing it to bifactor S-1 models with ADHD/ODD-related reference factors. Differential correlations with emotion regulation skills and the established Parent Proxy Anger Scale validate the interpretation of the different dimensions. Our results suggest that irritability/emotional impulsivity might be a common core feature of ADHD and ODD.

     

Examining the Factor Structure of the Self-Compassion Scale in Four Distinct Populations: Is the Use of a Total Scale Score Justified?

This study examined the factor structure of the Self-Compassion Scale (SCS) using a bifactor model, a higher order model, a 6-factor correlated model, a 2-factor correlated model, and a 1-factor model in 4 distinct populations: college undergraduates (N = 222), community adults (N = 1,394), individuals practicing Buddhist meditation (N = 215), and a clinical sample of individuals with a history of recurrent depression (N = 390). The 6-factor correlated model demonstrated the best fit across samples, whereas the 1- and 2-factor models had poor fit. The higher order model also showed relatively poor fit across samples, suggesting it is not representative of the relationship between subscale factors and a general self-compassion factor. The bifactor model, however, had acceptable fit in the student, community, and meditator samples. Although fit was suboptimal in the clinical sample, results suggested an overall self-compassion factor could still be interpreted with some confidence. Moreover, estimates suggested a general self-compassion factor accounted for at least 90% of the reliable variance in SCS scores across samples, and item factor loadings and intercepts were equivalent across samples. Results suggest that a total SCS score can be used as an overall mesure of self-compassion.     

Exploratory structural equation modeling,bifactor models,and standard confirmatory factor analysis models: Application to the BASC-2 Behavioral and Emotional Screening System Teacher Form

Several psychological assessment instruments are based on the assumption of a general construct that is composed of multiple interrelated domains. Standard confirmatory factor analysis is often not well suited for examining the factor structure of such scales. This study used data from 1885 elementary school students (mean age = 8.77 years, SD = 1.47 years) to examine the factor structure of the Behavioral Assessment System for Children, Second Edition (BASC-2) Behavioral and Emotional Screening System (BESS) Teacher Form that was designed to assess general risk for emotional/behavioral difficulty among children. The modeling sequence included the relatively new exploratory structural equation modeling (ESEM) approach and bifactor models in addition to more standard techniques. Findings revealed that the factor structure of the BASC-2 BESS Teacher Form is multidimensional. Both ESEM and bifactor models showed good fit to the data. Bifactor models were preferred on conceptual grounds. Findings illuminate the hypothesis-generating power of ESEM and suggest that it might not be optimal for instruments designed to assess a predominant general factor underlying the data.     

Testing a Bifactor Model of Relational and Physical Aggression in Early Childhood

Different approaches have been used to classify children as relationally aggressive, physically aggressive, or both relationally and physically aggressive (co-occurring aggression). The goal of the current study (N = 164, 50.9% boys, M _age = 47.75 months, SD = 7.37) was to test a bifactor model of aggression, which allows for aggression to be assessed dimensionally, and postulates a co-occurring aggression factor as well as unique relational and physical aggression factors, during early childhood. Aggression was measured using reliable observer and teacher reports of physical and relational aggression subscales. The two-factor model was an adequate fit to the data but the bifactor model was a significant improvement in model fit compared to the two-factor model. Alternative statistics for evaluating bifactor models were used in the current study. The measurement invariance (e.g., configural invariance, metric invariance, and scalar invariance) of the bifactor model was tested across gender and results from the bifactor model using teacher report showed that the model was invariant across gender. Lastly, the criterion validity of the model was examined by evaluating the relations between the bifactor model and observations of physical and relational aggression and results generally supported the validity of the bifactor model. Overall, results suggest that a bifactor model of aggression may be a useful method for studying aggression in early childhood.     

Further Evidence of the Reliability and Validity of the Multidimensional Anxiety

The psychometric properties of the Multidimensional Anxiety Scale for Children (MASC) were examined in adolescent psychiatric inpatient samples. In Study 1 (n = 287), confirmatory factor analyses provided satisfactory fit for the four-factor (comparative fit index; CFI = 0.856) and higher-order (CFI = 0.854) solutions. Using parcels as items, the fit of the four-factor model was improved substantially (CFI = 0.935). Next, in the bifactor analyses, support was attained for a model that included a general factor and four domain specific subfactors. In Study 2 (n = 195 inpatient youths), the MASC showed good scale reliability and concurrent validity. Results of the receiver operating characteristic curve and binary logistic regression analyses provided adequate evidence for discriminative validity. In Study 3 (n = 40), test–retest reliability of scores on the MASC-10 scale over a 3-week period was adequate (r _tt = 0.83, p < 0.001) for children ages 8 to 11 years.     

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

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).     

Validation of the Measure of Delinquent Social Identity Among Youth Offenders in the UK

ABSTRACT

The current study aimed to develop and validate the Measure of Delinquent Social Identity (MDSI). Dimensionality and construct validity of the MDSI was investigated in a sample of youth offenders (N = 536). Four alternative models of the MDSI were estimated using Mplus. The model identified as being the best fit for the data was a bifactor model with three dimensions (cognitive centrality, in-group affect, in-group ties) while controlling for the general factor. The three subscales differentially correlated with criminal friend index, self-esteem, parental attachment, and peer rejection. Limitations and advantages, including practical implications, of the current research are discussed.     

Longitudinal Associations Between the Five-Factor Model of Personality and The Bi-Factor Model of Psychopathology: Continuity,Pathoplasty and Complication Effects in Adolescents

The study of the bifactor structure of psychopathology, which includes a general factor of psychopathology (or p factor) in addition to the internalizing and externalizing factors, has gained attention. However, its associations with the Five-Factor Model (FFM) of personality has been addressed in few studies, and none has examined different plausible etiological models (i.e., continuity, pathoplasty, complication) to explain its relationship, which is the aim of the present research. Additionally, the longitudinal association of the General Factor of Personality (GFP) and the p factor will be also explored. Personality and psychopathological symptoms of high school students were assessed at three time points (once a year) (n?=?655; M?=?13.79, SD?=?1.24; 49.8% girls). Confirmatory Factor Analysis (and measurement invariance across waves) were tested for the traits, the GFP and the bifactor model of psychopathology. While the bifactor model and the one-factor solution for each personality trait displayed good fit to the data and remained invariant over time, the structure of the GFP was adequate and invariant in two of the three waves. The resulting factors were included in cross-lagged panel models and showed that the FFM traits and the psychopathology factors influenced each other reciprocally. Most associations fell in line with the continuity model, but minor pathoplastic and complication effects were also reported. Similar associations were found between the GFP and the p factor. These results suggest that interventions in riskier personality profiles might prevent the development of general and more specific psychopathology spectra.

     

Comparing hierarchical models of personality pathology

Two dimensional, hierarchical classification models of personality pathology have emerged as alternatives to traditional categorical systems: multi-tiered models with increasing numbers of factors and models that distinguish between a general factor of severity and specific factors reflecting style. Using a large sample (N = 840) with a range of psychopathology, we conducted exploratory factor analyses of individual personality disorder criteria to evaluate the validity of these conceptual structures. We estimated an oblique, “unfolding” hierarchy and a bifactor model, then examined correlations between these and multi-method functioning measures to enrich interpretation. Four-factor solutions for each model, reflecting rotations of each other, fit well and equivalently. The resulting structures are consistent with previous empirical work and provide support for each theoretical model.     

Comparing score tests and other local dependence diagnostics for the graded response model

Score tests for identifying locally dependent item pairs have been proposed for binary item response models. In this article, both the bifactor and the threshold shift score tests are generalized to the graded response model. For the bifactor test, the generalization is straightforward; it adds one secondary dimension associated only with one pair of items. For the threshold shift test, however, multiple generalizations are possible: in particular, conditional, uniform, and linear shift tests are discussed in this article. Simulation studies show that all of the score tests have accurate Type I error rates given large enough samples, although their small‐sample behaviour is not as good as that of Pearson's Χ² and M₂ as proposed in other studies for the purpose of local dependence (LD) detection. All score tests have the highest power to detect the LD which is consistent with their parametric form, and in this case they are uniformly more powerful than Χ² and M₂; even wrongly specified score tests are more powerful than Χ² and M₂ in most conditions. An example using empirical data is provided for illustration.     

Scores composites CHC pour la WAIS-IV : normes francophones

Results from contemporary research have demonstrated the importance of fluid reasoning, working memory and processing speed in cognitive functioning. The developers of the WAIS-IV have introduced new subtests to strengthen the assessment of these cognitive dimensions. The interpretation of the WAIS-IV is currently based on four factorial indexes (VCI, PRI, WMI, and PSI), as well as on the FSIQ. The developers of the WAIS-IV indicated that one of the objectives of the revision was to update the theoretical foundations of this intelligence scale. However, the overall structure of the WAIS-IV is not aligned with the consensual Cattell-Horn-Carroll (CHC) theory of cognitive abilities. For instance, the technical manual of the WAIS-IV does not provide an index of fluid reasoning, although the authors emphasized the importance of this dimension in cognitive functioning. In this paper, we provide the French normative tables for five CHC composite scores of the WAIS-IV, namely, fluid reasoning (Gf), comprehension-knowledge (Gc), visual processing (Gv), short-term memory (Gsm), and processing speed (Gs). These norms were created using a statistical approximation procedure. Like the CHC norms that we have proposed for the WISC-IV, theses tables allow clinicians to switch towards the dominant interpretative framework and to use the CHC composite scores as complementary measures to the four standard index scores, in order to conduct normative and ipsative analyses.     

Assessing the Unidimensionality of Trait Reactance Using a Multifaceted Model Assessment Approach

This study employed a multifaceted model assessment approach to investigate the dimensionality and nomological network of a popular measure of trait reactance, the Hong Psychological Reactance Scale (HPRS; Hong &; Page, 1989 Hong, S.-M., &; Page, S. (1989). A psychological reactance scale: Development, factor structure and reliability. Psychological Reports, 64, 1323–1326.[Crossref], [Web of Science ®] , [Google Scholar]). To address confusion regarding the scoring and modeling of the HPRS as well as its limited external validity evidence, we tested competing factor models, diagnosed model–data misfit, examined relationships between competing factor models and key personality traits, and cross-validated the results. Confirmatory factor analytic results supported modeling the HPRS via a bifactor model and, when this model was applied, trait reactance was negatively related to agreeableness, conscientiousness, and conformity, and positively related to entitlement, as expected. However, we also demonstrated the consequences of championing a 1-factor model by highlighting differences in relationships with external variables. Specifically, although modeling the HPRS scores with the bifactor model resulted in greater model–data fit than the 1-factor model, relationships with external variables based on the 2 models differed negligibly. Moreover, bifactor statistical indexes indicted that scores were essentially unidimensional, providing some support that HPRS scores can be treated as unidimensional in structure. Implications for using and scoring the HPRS are discussed.