Exploratory Structural Equation Modeling Framework Research Articles

Substance use and its association with mental health among Swiss medical students: A cross-sectional study.

Studies on mental health and substance use among medical students indicated worrying prevalence but have been mainly descriptive. To evaluate the prevalence of substance use in a sample of medical students and investigate whether mental health variables have an influence on substance use. The data were collected as part of the first wave of the ETMED-L, an ongoing longitudinal open cohort study surveying medical students at the University of Lausanne (Switzerland). N = 886 students were included and completed an online survey including measures of mental health (depression, suicidal ideation, anxiety, stress, and burnout) and use of and risk related with several substances (tobacco, alcohol, cannabis, cocaine, stimulants, sedatives, hallucinogens, opioids, nonmedical prescription drugs, and neuroenhancement drugs). We evaluated the prevalence of use of each substance and then tested the association between mental health and substance use in an Exploratory Structural Equation Modeling framework. Statistical indices indicated a four-factor solution for mental health and a three-factor solution for substance use. A factor comprising risk level for alcohol, tobacco, and cannabis use - which were the most prevalent substances - was significantly associated with a burnout factor and a factor related to financial situation and side job stress. There was a significant association between a factor comprising depression, anxiety, and suicidal ideation and a factor related to the use of sedatives, nonmedical prescription drugs and neuroenhancement drugs. Although their use was less prevalent, a factor comprising the risk level of stimulants and cocaine use was significantly but more mildly related to the burnout factor. A factor comprising stress related to studies and work/life balance as well as emotional exhaustion was not related to substance use factors. In this sample of medical students, the prevalence of substance use was substantial and poorer mental health status was related with higher substance use risk levels.

Using a bifactor exploratory structural equation modeling framework to examine the factor structure of the Depression Anxiety and Stress Scales-21.

This study proposed an improved representation of the DASS-21 factor structure developed by Lovibond and Lovibond in Behaviour Research and Therapy, 33, 335–342 (1995) using bifactor exploratory structural equation modeling (bifactor ESEM). This research was conducted by reference to 521 Turkish adults (45.3% females; Mage = 27.86, SD = 8.23). The bifactor ESEM findings indicated a strong general factor of negative affect underlying responses to all DASS-21 items but also that despite the presence of three specific factors (depression, anxiety, and stress), the depression subscale explained a high degree of variance and could be considered to constitute a specific factor. The results obtained from this study show that there is a common factor associated with DASS-21 scales, the total score of DASS-21 can be identified as a measure of general negative affect, and the bifactor ESEM structure of DASS-21 ensures measurement invariance across genders.

The Self-Compassion Scale: Validation and Psychometric Properties within the Exploratory Structural Equation Modeling Framework

The Self-Compassion Scale (SCS) is one of the several tools for measuring compassionate self-attitude. Despite its popularity, there is an ongoing controversy regarding its factor structure. Previous studies employing exploratory structural equation modeling (ESEM) found support for the single-bifactor (one general and six group factors) model over the competing two-bifactor (two general factors representing compassionate and uncompassionate self-responding and six group factors) model. Here, we replicated and extended previous ESEM studies through examining the validity and dimensionality of different bifactor models in a sample of UK adults. Model fit was examined across two estimators: maximum likelihood and weighted least square mean and variance adjusted. Finally, we investigated whether one or two observed scores of the SCS can better identify cases of depression, anxiety, and mental wellbeing. Both bifactor models showed good fit to the data irrespective of the estimators used, but only the single-bifactor model demonstrated satisfactory convergent and criterion validity and unidimensionality. The total observed SCS score detected depression, anxiety and high mental wellbeing with higher accuracy than any of the two scores. Overall, we propose to use the total score of the SCS in further research and practice.

Disentangling the associations of academic motivation with self-concept and academic achievement using the bifactor exploratory structural equation modeling framework

This study investigated the associations between academic motivation, self-concepts, and achievement in math and German using the bifactor exploratory structural equation modeling (bifactor-ESEM) framework. Data from two independent samples (N1 = 1402, N2 = 1154) of German elementary and secondary school students revealed that the bifactor-ESEM representation of academic motivation was the most optimal solution among all models (CFA, bifactor-CFA, ESEM, bifactor-ESEM). Measurement invariance was supported across domains and education levels for all models. Global self-determined motivation was strongly associated with both academic self-concept and academic achievement. The specific motivation factors also shared associations with these variables over and above those involving the global self-determined motivation factor. This study highlights the importance of distinguishing global and specific levels of academic motivation.

Exploratory Structural Equation Modeling Analysis of the Social Network Site Use Motives Scale.

Objective Social Network Site Use Motives Scale (SUMS) was developed under the assumption that it consists of six factors, but only four factors were extracted as a result of Exploratory Factor Analysis. The goal of the present study was to investigate whether SUMS consists of four or six factors using Confirmatory Factor Analysis (CFA) and Exploratory Structural Equation Modeling (ESEM) approach. Methods A Korean college student sample (n=600; mean age, 21 years; 58% female) filled out the SUMS and the Social Network Site Addiction Proneness Scale. CFA and ESEM were used to assess the factor structure of the SUMS. ResultsResults indicated that a four-factor solution to the SUMS had inadequate fit in the sample examined using both CFA and ESEM and a six-factor solution to the SUMS had insufficient fit using CFA, whereas fit was optimal using ESEM for the six-factor model. In addition, the scale showed adequate convergent validity and reliability. Conclusion These findings support the six-factor model of SNS use motives and suggest that ESEM is a more appropriate method than CFA for examining the factor structure of the SUMS. The results displayed the usefulness of the ESEM framework in the investigation of use motives.

Which hotel services really matter to Muslim travelers? Developing and validating a multidimensional-continuum scale

Tourism organizations around the globe, along with various professional and academic studies, have signaled the importance of halal tourism as an emerging lucrative market segment. Yet, there is no uniform and parsimonious scale to measure the range of hotel halal services that are most important to Muslim travelers when travelling to non-Muslim countries. Consequently, this study conceptualized a new multidimensional and continuum instrument for measuring the perceived importance of halal services provided by hotels to Muslim guests. A rigorous procedure consisting of a six-stage scale development, four studies, 1157 participants, and the novel application of an Exploratory Structural Equation Modeling framework (ESEM) culminated in a four-dimensional, twenty-five-item model. The results confirmed the continuum structure of halal services and supported reliability and validity. The new scale contributes to our understanding of the synergetic, complex, and multidimensional role of services in tourism.

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

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.

One step beyond emotional intelligence measurement in the career development of adult learners: A bifactor exploratory structural equation modeling framework

One step beyond emotional intelligence measurement in the career development of adult learners: A bifactor exploratory structural equation modeling framework

Validation of the French Psychological Capital Questionnaire (F-PCQ-24) and its measurement invariance using bifactor exploratory structural equation modeling framework

ABSTRACT The general purpose of this study was to validate the French Psychological Capital Questionnaire (F-PCQ-24) in a French Air Force sample (N = 3,665). One specific aim was to verify what the best measurement model is for PsyCap, notably by using Bifactor Exploratory Structural Equation Modeling (B-ESEM). Another specific aim was to examine the measurement invariance of the best fitting model for the F-PCQ-24 across gender, rank and tenure. Results supported the superiority of the B-ESEM model of PsyCap with the hope dimension divided into its two components (will-power and way-power). Moreover, multi-group confirmatory factor analyses indicated the measurement invariance of F-PCQ-24 for gender and tenure, while there was a small problem with measurement invariance for rank. Overall, these findings confirm that the F-PCQ-24 is a stable measure of PsyCap and support previous theoretical considerations that PsyCap is a core construct. Implications of these findings, limitations and directions for future research are discussed.

Refining acculturation measures for health research: Latina/o heterogeneity in the National Latino and Asian American Study.

ObjectivesThis study factor analyzes six scales relating to acculturation and related experiences among a nationally representative sample of United States‐residing Latina/os (n = 2,541) from the National Latino and Asian American Study (NLAAS), using measurement invariance (MI) testing to explore differences in latent constructs by Latina/o subgroup.MethodsFactor Analysis (FA) within an Exploratory Structural Equation Modeling framework was used to analyze the factor structure of six scales measuring acculturation and related experiences (i.e., acculturation [language use and preference], enculturation [ethnic identity], discrimination, neighborhood context, and family environment). We tested for MI by two important Latina/o subgroups: ethnic heritage and generational status.ResultsThe underlying latent factors resulting from FA strongly aligned with the NLAAS subscales. No scale achieved full MI, yet the degree to which MI held varied greatly by scale and by subgroup.ConclusionsFindings show that Latina/os are heterogeneous, but that this often depends on the construct and subgrouping of interest. Future research should use these scales in a latent framework, accounting for the lack of MI, to ensure that the underlying acculturative constructs of interest are validly measured when investigating their association with mental health outcomes in this population.

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.

Peer defending as a multidimensional behavior: Development and validation of the Defending Behaviors Scale

Defending represents any prosocial behavior taken to assist an individual being victimized. Like other forms of prosocial behavior, defending may be best conceptualized as a multidimensional set of behaviors, including both direct and indirect forms of defending. The objective of the current research was to design and validate the Defending Behaviors Scale (DBS), a multidimensional self-report scale of defending behaviors. Data were collected from 572 early adolescents in Grades 6 to 8. Participants completed the DBS as well as established measures of bullying, victimization, empathy, aggression, social self-efficacy, social support, and prosocial behavior. Data were analyzed using an exploratory structural equation modeling framework. A four-factor model provided the best fit to the data. Direct defending included aggressive and solution-focused behaviors, whereas indirect defending included comforting and reporting to authority. Girls were more likely to defend others by offering comfort and reporting to authority, whereas aggressive defending was more common among boys. Each subscale demonstrated good internal consistency (α's 0.80–0.92) and was uniquely associated with empathy, aggression, and other types of prosocial behavior. The DBS is a new, psychometrically-valid measure that will aid in the assessment of heterogenous defending behaviors.

A New Look on the Representation and Criterion Validity of Need Fulfillment: Application of the Bifactor Exploratory Structural Equation Modeling Framework

The present study re-investigated whether need satisfaction and frustration are better represented as two opposite ends of the same continuum or two distinct constructs through the application of the bifactor exploratory structural equation modeling (bifactor-ESEM) framework. Also, the criterion-related validity of the final representation was tested in relation to indicators of wellbeing. Using a sample of 774 participants (501 females, Mage = 27.86, SDage = 9.52), several alternative models were contrasted. The results supported the multidimensional bifactor-ESEM representation including one global factor of need fulfillment and the six specific factors being the combination of satisfaction and frustration with autonomy, competence, and relatedness. Most items tapped into meaningful specificity once the global factor was accounted for. Finally, the global factor was substantially and positively related to positive affect and negatively to negative affect. Competence satisfaction further predicted positive affect, while competence and relatedness frustration predicted negative affect.

Applying Exploratory Structural Equation Modeling to Examine the Student-Teacher Relationship Scale in a Representative Greek Sample

Teacher-child relationships in early childhood are a fundamental prerequisite for children's social, emotional, and academic development. The Student-Teacher Relationship Scale (STRS) is one of the most widely accepted and used instruments that evaluate the quality of teacher-child relationships. STRS is a 28-item questionnaire that assess three relational dimensions, Closeness, Conflict, and Dependency. The relevant literature has shown a pattern regarding the difficulty to support the STRS factor structure with CFA, while it is well-documented with EFA. Recently, a new statistical technique was proposed to combine the best of the CFA and EFA namely, the Exploratory Structural Equation Modeling (ESEM). The purpose of this study was (a) to examine the factor structure of the STRS in a Greek national sample. Toward this end, the ESEM framework was applied in order to overcome the limitations of EFA and CFA, (b) to confirm previous findings about the cultural influence in teacher-child relationship patterns, and (c) to examine the invariance of STRS across gender and age. Early educators from a representative Greek sample size of 535 child care and kindergarten centers completed the STRS for 4,158 children. CFA as well as ESEM procedures were implemented. Results showed that ESEM provided better fit to the data than CFA in both groups, supporting the argument that CFA is an overly restrictive approach in comparison to ESEM for the study of STRS. All primary loadings were statistically significant and were associated with their respective latent factors. Contrary to the existing literature conducted in USA and northern Europe, the association between Closeness and Dependency yielded a positive correlation. This finding is in line with previous studies conducted in Greece and confirm the existence of cultural differences in teacher-child relationships. In addition, findings supported the configural, metric, scalar, and variance/covariance equivalence of the STRS between males and females and between preschoolers (3–5 years) and early primary years (5–7 years). Latent factor means comparisons showed that females seem to have a warmer and more dependent relationship with their teachers and are less conflictual in comparison to males.

An Illustration of the Exploratory Structural Equation Modeling (ESEM) Framework on the Passion Scale.

While exploratory factor analysis (EFA) provides a more realistic presentation of the data with the allowance of item cross-loadings, confirmatory factor analysis (CFA) includes many methodological advances that the former does not. To create a synergy of the two, exploratory structural equation modeling (ESEM) was proposed as an alternative solution, incorporating the advantages of EFA and CFA. The present investigation is thus an illustrative demonstration of the applicability and flexibility of ESEM. To achieve this goal, we compared CFA and ESEM models, then thoroughly tested measurement invariance and differential item functioning through multiple-indicators-multiple-causes (MIMIC) models on the Passion Scale, the only measure of the Dualistic Model of Passion (DMP) which differentiates between harmonious and obsessive forms of passion. Moreover, a hybrid model was also created to overcome the drawbacks of the two methods. Analyses of the first large community sample (N = 7,466; 67.7% females; Mage = 26.01) revealed the superiority of the ESEM model relative to CFA in terms of improved goodness-of-fit and less correlated factors, while at the same time retaining the high definition of the factors. However, this fit was only achieved with the inclusion of three correlated uniquenesses, two of which appeared in previous studies and one of which was specific to the current investigation. These findings were replicated on a second, comprehensive sample (N = 504; 51.8% females; Mage = 39.59). After combining the two samples, complete measurement invariance (factor loadings, item intercepts, item uniquenesses, factor variances-covariances, and latent means) was achieved across gender and partial invariance across age groups and their combination. Only one item intercept was non-invariant across both multigroup and MIMIC approaches, an observation that was further corroborated by the hybrid model. While obsessive passion showed a slight decline in the hybrid model, harmonious passion did not. Overall, the ESEM framework is a viable alternative of CFA that could be used and even extended to address substantially important questions and researchers should systematically compare these two approaches to identify the most suitable one.

The Measurement Structure of School Engagement Among Youth in China: An Exploratory Structural Equation Modeling Study

In this research, we examined the construct of a school engagement scale using exploratory structural equation modeling (ESEM). This study involved a translated measurement model that was originally developed by Li and Lerner for U.S. youth, and data from a sample of eighth-, ninth-, and 11th-grade Chinese adolescents ( N = 364). First, the results indicated that instead of the three factors (cognitive, emotional, and behavioral engagement) that have been found in previous research on school engagement, four factors emerged for the current sample: school compliance, participation, emotional engagement, and cognitive engagement. Second, the factor structure was gender invariant in the ESEM framework. We further found that female students scored higher than males on school compliance and emotional engagement. Third, the convergent correlations among school engagement subscales and academic performance were in line with theoretical expectations. Finally, based on the differences between this study and previous studies in Western countries, the need for a more thorough investigation in the conceptualization and measurement of school engagement among youth in China was discussed.

New Wine in a New Bottle: Refining The Assessment of Authentic Leadership Using Exploratory Structural Equation Modeling (ESEM)

The aim of this study was to investigate the multidimensional nature of authentic leadership (AL) through the re-evaluation of the factor structure of the most commonly used scales in AL research, the Authentic Leadership Questionnaire (ALQ) and the Authentic Leadership Inventory (ALI). Results from Exploratory Structural Equation Modeling (ESEM) conducted among 538 workers of private (57,81%) and public (42,19%) organizations provide support for the multidimensional nature of AL but also reveal excessive content overlap across subscales and an inability to properly reflect the a priori factor structure of both instruments. Further analyses enabled the identification of key items from both instruments providing a cleaner depiction of the a priori dimensionality of AL, leading to the development of an integrated optimized measure, the Authentic Leadership Integrated Questionnaire (AL-IQ). The main contribution of this study is the proposition of an alternative and optimized measure of authentic leadership that sheds light on the distinct theoretical facets of this positive leadership style. Our data suggest that the AL-IQ is a promising tool for characterizing the strengths and weaknesses of leaders and managers’ AL practices. To our knowledge, this is the first study to use a combination of classical Confirmatory Factor Analyses (CFA) and newly developed ESEM framework to assess the construct validity (factor structure, reliability, and criterion-related validity) of the two main AL measures: the ALQ and the ALI.

An application of the exploratory structural equation modeling framework to the study of personality faking

This study compared the suitability of the restrictive framework of independent cluster model (ICM) and a more flexible framework of exploratory structural equation model (ESEM) to a personality instrument in a faking study. We proposed and answered five research questions using the model-testing procedures described by Morin, Arens, and Marsh (2016). More specifically, we compared the fit of ICM-CFA and ESEM, and ESEM and bi-factor ESEM, and we investigated the patterns of factor correlations and the presence of cross-loadings in these models. In our faking condition, we found the ESEM applications provided the better representation of the data, and the adverse effects of the strict assumptions of ICM-based models to be most apparent. Limitations and practical implications were discussed.

Differential Item Functioning of the Full and Brief Wisconsin Schizotypy Scales in Asian, White, Hispanic, and Multiethnic Samples and Between Sexes.

The Wisconsin Schizotypy Scales, including their brief versions, are among the most commonly used self-report measures of schizotypy. Although they have been used extensively in many ethnic groups, few studies have examined their differential item functioning (DIF) across groups. The current study included 1,056 Asian, 408 White, 476 Multiethnic, and 372 Hispanic undergraduates. Unidimensional models of the brief Magical Ideation Scale and Perceptual Aberration Scales fit the data well. For both scales, global tests of measurement invariance provided mixed evidence, but few of the items displayed DIF across ethnicities or between sexes within a multiple indicator multiple causes model. For the full versions of the scales and the brief Revised Social Anhedonia Scale, multiple indicator multiple causes models within an exploratory structural equation modeling framework found that few of the items had DIF. These findings suggest that some of the items may have different psychometric properties across groups, but most items do not.

Exploratory Structural Equation Modeling Analysis of the Self-Compassion Scale

The present research investigated the construct validity and psychometric properties of the Self-Compassion Scale (SCS) with a new and advanced statistical procedure, exploratory structural equation modeling (ESEM), in order to contribute to the ongoing discussion about its dimensionality by employing a bifactor-ESEM framework. A Hungarian online representative sample (N = 505, N female = 265, M age = 44.37) filled out the Hungarian version of the SCS. Confirmatory factor analysis (CFA) and ESEM methods were employed, and first-order and bifactor solutions were examined and compared. The bifactor ESEM model demonstrated the best fit to the data with the joint presence of the general self-compassion factor and the specific factors. Internal consistency was adequate in all cases. Reliability indices—omega and omega hierarchical—showed that not all specific factors had unique contributions over and above the general factor. High levels of gender invariance were also achieved with females having lower general self-compassion and self-judgment latent means, while having higher self-kindness scores. The findings shed new light on the underlying theory behind the SCS and proved the usefulness of the bifactor ESEM framework in the investigation of multidimensional constructs.