Bifactor Exploratory Structural Equation Modeling Research Articles

Looking Beyond the Value of Individual Facets of Mindfulness: a Person-Centered Examination of Mindfulness

This study aimed to (1) examine profiles of mindfulness in a large cohort from the general population by disentangling the level and shape effects of mindfulness, (2) identify the demographic predictors (i.e., age, gender, and educational level) of mindfulness profile membership, and (3) examine associations of mindfulness profiles with psychological outcomes (including both positive and negative indicators) and coping strategies (including positive reappraisal and rumination). This cross-sectional observational study included a large representative group of 1727 people from the general Dutch population. To separate the level and shape effects of mindfulness, the bifactor exploratory structural equation modeling (B-ESEM) and latent profile analyses (LPA) were performed. The factor scores of the B-ESEM were used as indicators of LPA. Using a combination of B-ESEM and LPA, we identified three profiles that differed on global levels and configurations of mindfulness: profile 1 “average mindfulness” (78.4%), profile 2 “low to average mindfulness” (16.2%), and profile 3 “high non-judgmentally aware” (5.4%). These profiles differed significantly on age, gender, and educational level, with people in profile 3 being older, male, and lower educated. Compared with the other two profiles, people in profile 3 reported the best psychological outcomes and coping strategies. Findings provide evidence for the importance of looking at profiles of mindfulness in future observational and intervention studies. Research is needed to test the feasibility and effectiveness of more personalized mindfulness interventions, tailored to specific profiles of mindfulness.

Students' multidimensional profiles of math engagement: Predictors and outcomes from a self-system motivational perspective.

Math engagement research has been largely limited to examining the unique and additive relations of engagement dimensions with outcomes. However, an emerging perspective is that students may simultaneously invest varying degrees of their distinct energetic resources (e.g., cognitive vs. emotional) in their interactions with the math learning environment. Adopting a person-centred perspective, we examined unique latent subpopulations of adolescents' multidimensional math engagement. Importantly, we did so while accounting for generality and specificity in engagement data, including general engagement and specific cognitive, emotional, and social engagement dimensions. Additionally, we examined students' math self-efficacy, outcome expectations, and gender as predictors, and math achievement indices as outcomes, of profile membership. The sample comprised 400 Australian school students taking mandatory math classes. Data on students' multidimensional engagement, math self-efficacy, math outcome expectations, and demographic characteristics were collected at the beginning of the academic semester. Standardized test scores and class grades were retrieved at the end of the semester. Latent profile analyses, based on preliminary bifactor exploratory structural equation models intended to tease apart generality from specificity in engagement data, revealed 'Minimally Engaged', 'Emotionally Disengaged', and 'Moderately-to-Highly Engaged' profiles. Additionally, math self-efficacy, outcome expectations, and gender were found to predict the likelihood of profile membership. Finally, class grades, but not standardized test scores, were found to significantly differ across the profiles, accounting for prior achievement, gender, and grade level. The findings replicate previous work that has shown profiles of student engagement and extend this work by (1) accounting for known generality and specificity in engagement data and (2) obtaining evidence for relations of profile membership with gender, self-beliefs, and achievement.

Refining the assessment of need supportive and need thwarting interpersonal behaviors using the bifactor exploratory structural equation modeling framework

The present research assessed the psychometric multidimensionality and criterion-related validity the Interpersonal Behaviours Questionnaire using the bifactor-exploratory structural equation modeling framework. Study 1 relied on a sample of 772 participants, and supported the superiority of a bifactor-ESEM representation compared to alternative representations. Ratings of need supportive and thwarting behaviors simultaneously reflected a global overarching need nurturing behaviors construct (rather than two separate need supportive and need thwarting behaviors), which co-existed with six specific dimensions (autonomy, competence, and relatedness need supportive and thwarting behaviors). These results were replicated in a second independent sample of 742 participants and across gender. Our findings supported the criterion-related validity of interpersonal behaviors in relation to positive affect, negative affect, and need fulfillment across samples and genders. We finally discuss the theoretical and practical implications of relying on the bifactor-ESEM framework when investigating need supportive and thwarting interpersonal behaviors.

Is Self-Compassion Universal? Support for the Measurement Invariance of the Self-Compassion Scale Across Populations.

The Self-Compassion Scale (SCS) is a widely used measure to assess the trait of self-compassion, and, so far, it has been implicitly assumed that it functions the same way across different groups. This assumption needs to be explicitly tested to ascertain that no measurement biases exist. To address this issue, the present study sought to systematically examine the generalizability of the bifactor exploratory structural equation modeling operationalization of the SCS via tests of measurement invariance across a wide range of populations, varying according to features such as student or community status, gender, age, and language. Secondary data were used for this purpose and included a total of 18 samples and 12 different languages (N = 10,997). Multigroup analyses revealed evidence for the configural, weak, strong, strict, and latent variance-covariance of the bifactor exploratory structural equation modeling operationalization of the SCS across different groups. These findings suggest that the SCS provides an assessment of self-compassion that is psychometrically equivalent across groups. However, findings comparing latent mean invariance found that levels of self-compassion differed across groups.

Revisiting the dimensionality of subjective task value: Towards clarification of competing perspectives

Expectancy-value researchers have described the components of subjective task value in multiple ways, leading to multiple competing structural representations of subjective task value data. The purpose of this study was to examine these competing multidimensional factor structures by comparing correlated factor, hierarchical, and bifactor representations of both confirmatory factor analysis and exploratory structural equation modeling (ESEM) models across three theoretical conceptualizations of subjective task value. Results indicate that, in an undergraduate life science learning context (n = 334), the best representation for subjective task value data was a bifactor ESEM model that allowed for the disentangling of general and specific variance of general subjective task value, specific value beliefs, and specific costs. Full measurement invariance of the retained structure across continuing generation and first-generation students was found, and no differential item functioning was found across gender. General subjective task value and specific opportunity cost significantly and positively predicted achievement and specific utility value significantly and negatively predicted achievement, providing support for the criterion-related validity of the general and specific factors for predicting achievement outcomes.

Investigating the Multidimensionality of the Work-Related Flow Inventory (WOLF): A Bifactor Exploratory Structural Equation Modeling Framework.

This study investigated the factor structure of the Work-Related Flow Inventory (WOLF) through the application of the bifactor exploratory structural equation modeling (B-ESEM) framework. Using a sample of 577 Chinese teachers, we contrasted a series of competing models, including CFA, ESEM, bifactor CFA, and B-ESEM models. The results suggested that the B-ESEM structure with three S-factors (absorption, work enjoyment, and intrinsic work motivation) and one G-factor (global flow) was the best representation of the WOLF ratings. The results also supported the composite reliability and the strict invariance of this measurement structure between male and female groups. Relative to males, female teachers showed a higher level of global work-related flow experience. Finally, the nomological validity of WOLF ratings was supported by the statistical relationships of the WOLF factors with job satisfaction and autonomy.

Trait Emotional Intelligence Questionnaire-Short Form: Brazilian Validation and Measurement Invariance between the United Kingdom and Latin-American Datasets

The present study aimed to evaluate the psychometric properties of the Brazilian adaptation of the Trait Emotional Intelligence Questionnaire-Short Form (TEIQue-SF). In a sample of 512 participants, we tested model fit by bifactor Exploratory Structural Equation Modeling (ESEM), followed by measurement invariance testing against UK and Chilean datasets of the measure. The Big Five Mini-Markers, Satisfaction with Life Scale and Subjective Happiness Scale were also administered as external validation measures. We obtained the following results: (a) final adequate bifactor ESEM model fit; (b) a significantly higher global trait EI mean for men (d = .27); (c) high internal consistency for global trait EI (α = .88), in spite of lower Cronbach’s α values at the factor level (.60−.85); (d) high correlation (r = .89) in the test-retest; (e) significant correlation between global trait EI and most of the Big Five dimensions (r = −.66−.46), life satisfaction (.59) and happiness (.68); (f) evidence of incremental validity of trait EI for life satisfaction and happiness over and above the Big Five; (g) equivalent measurement across the Brazilian, UK and Chilean versions of the TEIQue-SF. We conclude that the Brazilian TEIQue-SF is psychometrically sound and can be recommended for research and practical use.

Burnout-Depression Overlap: Exploratory Structural Equation Modeling Bifactor Analysis and Network Analysis.

Burnout has been viewed as a work-induced condition combining exhaustion, cynicism, and professional inefficacy. Using correlational analyses, an exploratory structural equation modeling bifactor analysis, structural regression analyses, and a network analysis, we examined the claim that burnout should not be mistaken for a depressive syndrome. The study involved 1,258 educational staff members. Burnout was assessed with the Maslach Burnout Inventory-General Survey and depression with the Patient Health Questionnaire-9 and the Hospital Anxiety and Depression Scale. Illegitimate work tasks and work-nonwork interferences were additionally measured. We notably found that (a) on average, exhaustion, cynicism, and professional inefficacy correlated less strongly with each other than with depression; (b) exhaustion-burnout's core-was more strongly associated with depression than with either cynicism or professional inefficacy; (c) the Patient Health Questionnaire-9 did not correlate more strongly with the Hospital Anxiety and Depression Scale than with exhaustion; (d) exhaustion and depression loaded primarily on a general distress/dysphoria factor in the exploratory structural equation modeling bifactor analysis; (e) on average, burnout and depression were related to job stressors in a similar manner; (f) work-nonwork interferences were strongly linked to distress/dysphoria. Overall, burnout showed no syndromal unity and lacked discriminant validity. Clinicians should systematically assess depressive symptoms in individuals presenting with a complaint of "burnout."

Development and Validation of the Self-Compassion Scale for Youth

We present a series of studies on the development and validation of the Self-Compassion Scale—Youth version (SCS-Y), which is intended for use with early adolescents in middle school. Study 1 (N = 279, Mage = 12.17) describes the selection of 17 items out of a pool of 36 potential items, with three items each representing the subscales of self-kindness, mindfulness, common humanity, self-judgment, isolation, and two items representing over-identification. Using state-of-the-art psychometric analyses ideal for examining multidimensional constructs like self-compassion—bifactor exploratory structural equation modeling (bifactor-ESEM)—findings supported the use of a general self-compassion score and six subscale scores. Study 2 cross-validated the factor structure of the SCS-Y with a second sample of youths (N = 402, Mage = 12.43). Study 3 found support for the test-retest reliability of the SCS-Y (N = 102, Mage = 12.52). Study 4 (N = 212, Mage = 12.18) established construct validity for the SCS-Y by demonstrating that SCS-Y scores were significantly associated with mindfulness, happiness, life-satisfaction, depression, resilience, and achievement goal orientation in expected directions. Overall, findings suggest that the SCS-Y is a reliable and valid measure of self-compassion for use with youths.

Value Beliefs About Math

Abstract. This study proposed an improved representation of the factor structure of the Gaspard et al. (2015) value beliefs about math scale relying on bifactor exploratory structural equation modeling (B-ESEM). Using a convenience sample of 537 Italian students (327 males; Mage = 18.2), our results supported the superiority of a B-ESEM solution including nine specific factors (intrinsic, importance of achievement, personal importance, utility for school/job, utility for life, social utility, effort required, opportunity cost, and emotional cost) and one global value factor. The results further revealed that the specific factors (with the exception of personal importance) retained meaning over and above participants’ global levels of value. Finally, our results confirmed that global value beliefs predicted career aspirations, whereas expectancies of success remained the strongest predictor of math achievement.

Confirmatory Factor Analysis and Exploratory Structural Equation Modeling of the Structure of Attention-Deficit/Hyperactivity Disorder Symptoms in Adults.

This study examined the structure of attention-deficit/hyperactivity disorder (ADHD) symptoms in an adult community sample using first-order confirmatory factor analysis, exploratory structural equation modeling (ESEM), and bifactor confirmatory factor analysis and ESEM models, with two group factors (inattention [IA] and hyperactivity/impulsivity [HY/IM]) and two different three group factors (IA, hyperactivity [HY], and impulsivity [IM]; and IA, motoric HY/IM, and verbal HY/IM). A total of 738 adults (males = 374 and females = 364) between 17 and 72 years of age completed the Adult ADHD Self-Report Scale. The results provided most support for the ESEM model with group factors for IA, motoric HY/IM, and verbal HY/IM. The factors in this model were reasonably well defined, had good internal consistency omega reliabilities, and had support for their external validities, thereby making it a suitable model for ratings of the ADHD symptoms presented in the Adult ADHD Self-Report Scale. The theoretical and clinical implications of the findings are discussed.

Examining Factors for the Academic Motivation Based on the Confirmatory, the Exploratory and the Bifactor Exploratory Structural Equation Models

One of the aims of the current study is to specify the model providing the best fit to the data among the exploratory, the bifactor exploratory and the confirmatory structural equation models. The study compares the three models based on the model data fit statistics and item parameter estimations (factor loadings, cross-loadings, factor correlations) provided by the models. The second aim of the study is to examine correlations among the factor scores, the academic achievement and the goal orientations to provide criterion validity for the person parameter estimations of the best-fitting model. The Academic Motivation Scale was conducted on 1,858 junior and senior students. The three measurement models were compared based on the model data fit and parameter estimations. All estimations were done on the Mplus 6.0 statistical program using the Maximum Likelihood method. It was found that the bifactor exploratory structural equation model provided only trivial improvement on the model data fit relative to the exploratory structural equation model. However, the results of the study revealed that including a general factor in the model achieved a decrease in item cross-loadings. In addition, items could lie along the relative autonomy continuum in a consistent way with the Self-Determination Theory according to their general factor loadings estimated by the bifactor model. The model data fit statistics, parameter estimations and correlation coefficients indicated that the bifactor exploratory structural equation better fit to data than the other two models both theoretically and statistically.

Do burnout and depressive symptoms form a single syndrome? Confirmatory factor analysis and exploratory structural equation modeling bifactor analysis

ObjectiveThe issue of burnout-depression overlap remains contentious. In this study, the question of whether burnout symptoms form a syndrome that is distinct from depression was reexamined. MethodsThe study involved 332 employed individuals (65% female; mean age: 34). Burnout symptoms were assessed with the Shirom-Melamed Burnout Measure (SMBM). The SMBM operationalizes burnout based on three interconnected components, namely, physical fatigue, cognitive weariness, and emotional exhaustion. Depressive symptoms were assessed with the PHQ-9, a scale that covers the main manifestations of major depression. Confirmatory factor analysis (CFA) and exploratory structural equation modeling (ESEM) bifactor analysis were conducted. ResultsOn average, the factors underlying burnout's components correlated more strongly with the Depressive Symptom factor than with each other. Remarkably, such results were obtained even when fatigue-related items were excluded from the depression scale. Second-order CFA revealed that the factors underlying burnout's components and the Depressive Symptom factor were reflective of the same higher-order factor. ESEM bifactor analysis indicated that the general factor accounted for about 2/3 of the common variance extracted. ConclusionConsistent with a growing corpus of research, this study suggests that the burnout-depression distinction is untenable. Because the burnout-depression distinction tends to convey the idea that burnout is not as serious a problem as depression, many people struggling with depression might underestimate the gravity of their condition and not seek help when self-identifying as “burned out.” Maintaining a line of demarcation between burnout and depression may thus be problematic from both a scientific and a health management standpoint.

Using Exploratory Structural Equation Modeling (ESEM) to Examine the Internal Structure of Posttraumatic Stress Disorder Symptoms.

Several studies have reported the factor structure of posttraumatic stress disorder (PTSD) using confirmatory factor analysis (CFA). The results show models with different number of factors, high correlations between factors, and symptoms that belong to different factors in different models without affecting the fit index. These elements could suppose the existence of considerable item cross-loading, the overlap of different factors or even the presence of a general factor that explains the items common source of variance. The aim is to provide new evidence regarding the factor structure of PTSD using CFA and exploratory structural equation modeling (ESEM). In a sample of 1,372 undergraduate students, we tested six different models using CFA and two models using ESEM and ESEM bifactor analysis. Trauma event and past-month PTSD symptoms were assessed with Life Events Checklist for DSM-5 (LEC-5) and PTSD Checklist for DSM-5 (PCL-5). All six tested CFA models showed good fit indexes (RMSEA = .051-.056, CFI = .969-.977, TLI = .965-.970), with high correlations between factors (M = .77, SD = .09 to M = .80, SD = .09). The ESEM models showed good fit indexes (RMSEA = .027-.036, CFI = .991-.996, TLI = .985-.992). These models confirmed the presence of cross-loadings on several items as well as loads on a general factor that explained 76.3% of the common variance. The results showed that most of the items do not meet the assumption of dimensional exclusivity, showing the need to expand the analysis strategies to study the symptomatic organization of PTSD.

The Development and Validation of the Compassion Scale.

This article presents a measure of compassion for others called the Compassion Scale (CS), which is based on Neff's theoretical model of self-compassion. Compassion was operationalized as experiencing kindness, a sense of common humanity, mindfulness, and lessened indifference toward the suffering of others. Study 1 (n = 465) describes the development of potential scale items and the final 16 CS items chosen based on results from analyses using bifactor exploratory structural equation modeling. Study 2 (n = 510) cross-validates the CS in a second student sample. Study 3 (n = 80) establishes test-retest reliability. Study 4 (n = 1,394) replicates results with a community sample, while Study 5 (n = 172) replicates results with a sample of meditators. Study 6 (n = 913) examines the finalized version of the CS in a community sample. Evidence regarding reliability, discriminant, convergent, construct, and known-groups validity for the CS is provided.

Study of the Mental Health Continuum Short Form (MHC-SF) amongst French Workers: a Combined Variable- and Person-Centered Approach

Keyes’s theory-driven model of mental health uses a diagnosis which leads to three levels of positive feelings and positive functioning: languishing, moderately mentally healthy and flourishing (Keyes 2002). Although these three-level categories may be justified for a unidimensional factor structure, or a factorial structure using summated scales, the recent works supporting a multidimensional structure of the Mental Health Continuum Short Form (MHC-SF) suggest the adoption of shape-based rather than level-based categories of mental health (Morin et al. 2017). This research aims at testing the empirical validity of Keyes’s taxonomy and its relationship to psychosocial functioning. We first adopted a variable approach by selecting the optimal factor structure for the MHC-SF: the bifactor exploratory structural equation modeling (Bi-ESEM). Following with a person-centered approach, we used a latent profile analysis on the factor scores of the Bi-ESEM. Psychosocial risks indicators were used as outcomes for testing the criterion validity of the models on a sample of 1065 French workers. Results show that the mental health subgroups are more intricate than the three-levels categories originally theorized by Keyes (2002, 2005). While the general Bi-ESEM factor warrants three levels akin to those of Keyes, accounting for the specific factors reveals two profiles of languishing: the hedonic languishers characterized by a low level of emotional wellbeing, and the eudaimonic languishers characterized by a low level of psychological wellbeing. Both variable and person-centered approach confirm Keyes’s initial statements (Keyes 2007) that those who are languishing exhibit the highest levels of psychosocial risks while those flourishing display the lowest. A rule-based diagnosis derived from a decision tree method is suggested as an alternative to a level-based taxonomy.

An exploratory structural equation modeling bi-factor analytic approach to uncovering what burnout, depression, and anxiety scales measure.

In this study, we addressed the ongoing debate about what burnout and depression scales measure by conducting an exploratory structural equation modeling (ESEM) bifactor analysis. A sample of 734 U.S. teachers completed a survey that included the Center for Epidemiologic Studies Depression scale (CES-D-10), the depression module of the Patient Health Questionnaire (PHQ-9), the Generalized Anxiety Disorder scale (GAD-7), and the Maslach Burnout Inventory (MBI), which contains emotional exhaustion (EE), depersonalization (DP), and (diminished) personal accomplishment (PA) subscales. Job adversity and workplace support were additionally measured for the purpose of a nomological network analysis. EE, burnout's core, was more highly correlated with the depression and anxiety scales than it was with DP and PA, even with controls for item content overlap. The CES-D-10, PHQ-9, GAD-7, and EE subscale of the MBI were similarly related to job adversity and workplace support. ESEM bifactor analysis revealed that the CES-D-10, PHQ-9, GAD-7, and EE items loaded highly on a general factor, which we labeled nonspecific psychological distress (NSPD). We conclude that depression, anxiety, and EE scales reflect NSPD. DP items largely reflect two factors, NSPD and depersonalization, about equally. PA items were found to be less related to NSPD. With respect to the debate surrounding burnout-depression overlap, our findings do not support the view that the burnout construct represents a syndrome that consists of EE, DP, and diminished PA and excludes (or does not primarily include) depressive symptoms. (PsycINFO Database Record (c) 2019 APA, all rights reserved).

Psychometric Properties of the Body Checking Questionnaire (BCQ) and of the Body Checking Cognitions Scale (BCCS): A Bifactor-Exploratory Structural Equation Modeling Approach.

This research sought to assess the psychometric properties of the French versions of the Body Checking Questionnaire and the Body Checking Cognitions Scale among community samples. A total sample of 922 adolescents and adults was involved in a series of two studies. The results from the first study supported factor validity and reliability of responses obtained on these two measures, and showed that both measures were best represented by a bifactor-exploratory structural equation modeling representation of the data. The results from the second study replicated these conclusions, while also supporting the measurement invariance of the bifactor-exploratory structural equation modeling solution and the equivalence of the correlations among the two measures (i.e., convergent validity) across samples. This second study also supported the criterion-related validity of ratings on both measures with measures of global self-esteem, physical appearance, social physique anxiety, fear of negative appearance evaluation, and disturbed eating attitudes and behaviors. Finally, the results of this last study also supported the measurement invariance and lack of differential item functioning of both measures in relation to sex, age, diagnosis of eating disorders, and body mass index.

The Forest and the Trees: Investigating the Globality and Specificity of Employees’ Basic Need Satisfaction at Work

This research assessed the underlying psychometric multidimensionality and nomological validity of 523 employees’ responses to the Work-related Basic Need Satisfaction (W–BNS) scale using bifactor-exploratory structural equation modeling (bifactor-ESEM). Our results first showed the superiority of a bifactor-ESEM representation when compared to alternative representations of the data. Thus, employees’ ratings of psychological need satisfaction simultaneously reflected a global need satisfaction construct, which coexisted with specific autonomy, competence, and relatedness needs satisfaction. Importantly, our findings also supported the nomological validity of employees’ ratings of psychological need satisfaction in relation to measures of positive affect, negative affect, job satisfaction, perceived organizational support, organizational citizenship behaviors, work engagement, and burnout. In addition, our results also supported the presence of indirect (mediated) effects between perceived organizational support and some of the outcome variables as mediated by employees’ levels of need satisfaction.

Assessing therapist development: Reliability and validity of the Supervisee Levels Questionnaire (SLQ-R).

Therapist development is a crucial target for clinical training in order to ensure high-quality psychotherapy. A major challenge in examining therapeutic development is the assessment of developmental processes. The Supervisee Levels Questionnaire (SLQ-R) was analyzed in this study to examine its validity, reliability, and underlying dimensional structure. Seven hundred and sixty therapists participated in an online survey concerning their current psychotherapy training. The factor structure as well as the validity of the SLQ-R were investigated using exploratory and confirmatory factor analysis. In line with the results of the exploratory factor analyses, a Bifactor ESEM (exploratory structural equation modeling) model with two factors and one global factor provided the best fit to the data. The two factors were labeled professional self-confidence and professional insecurity. Empirical support for reliability and validity of the new factor structure of the SLQ-R was found. The instrument is useful for assessing the therapist's developmental level.