2020
DOI: 10.3389/fpsyg.2020.00740
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Investigating the Multidimensionality of the Work-Related Flow Inventory (WOLF): A Bifactor Exploratory Structural Equation Modeling Framework

Abstract: 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 o… Show more

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Cited by 16 publications
(15 citation statements)
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References 48 publications
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“…The validation process could also be extended, notably by conducting a test-retest measure to verify the consistency of workers' perceptions of VOP over time (Cohen and Swerdlik, 2017) and a test of the social desirability of the scale (King and Bruner, 2000). Thirdly, it would be interesting to test the structure of the VOPi in other samples using bifactor exploratory structural equation modeling, a statistical approach increasingly used by the scientific community (Fadda et al, 2020;Gu et al, 2020) as it enables the variance explained by a global factor (e.g., VOP) to be examined simultaneously with the variance explained by specific factors (e.g., eight sub-dimensions), which is not possible with a hierarchical model (Morin et al, 2016). Adopting such a method based on data collection would support our innovative conceptualization and operationalization of VOP.…”
Section: Discussionmentioning
confidence: 99%
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“…The validation process could also be extended, notably by conducting a test-retest measure to verify the consistency of workers' perceptions of VOP over time (Cohen and Swerdlik, 2017) and a test of the social desirability of the scale (King and Bruner, 2000). Thirdly, it would be interesting to test the structure of the VOPi in other samples using bifactor exploratory structural equation modeling, a statistical approach increasingly used by the scientific community (Fadda et al, 2020;Gu et al, 2020) as it enables the variance explained by a global factor (e.g., VOP) to be examined simultaneously with the variance explained by specific factors (e.g., eight sub-dimensions), which is not possible with a hierarchical model (Morin et al, 2016). Adopting such a method based on data collection would support our innovative conceptualization and operationalization of VOP.…”
Section: Discussionmentioning
confidence: 99%
“…Finally, while the predictive validity of the VOPi on job satisfaction and organizational commitment was demonstrated, it would be interesting to test it on other indicators of wellbeing. Indeed, because VOP promote the psychological health of workers, their relations with flow at work (Gu et al, 2020), flourishing (Diener et al, 2010), or optimal psychological functioning (Jaotombo, 2019) could further confirm their virtuous nature.…”
Section: Discussionmentioning
confidence: 99%
“…This study applied the integrative psychometric framework developed by Morin et al (2016a) in order to investigate sources of construct-relevant multidimensionality of early numeracy and to test the superiority of the bifactor-ESEM of early numeracy. As stated by Gu et al (2020), by overcoming the shortcomings of both the CFA and the ESEM models, the bifactor-ESEM is theoretically the most comprehensive and flexible model, able to describe more accurately the complex psychological characteristics. In a first step, ICM-CFA and ESEM models with one, two or three sub-dimensions were compared.…”
Section: Discussionmentioning
confidence: 99%
“…Unlike CFA, this new modeling takes the relations of non-target constructs and items into account, and unlike ESEM, it allows the coexistence of both a latent general construct and specific subdomains. By overcoming the CFA and ESEM shortcomings, the bifactor-ESEM might be the most comprehensive and flexible model, able to describe the complex psychological characteristics with most accuracy (Gu et al, 2020 ).…”
Section: Introductionmentioning
confidence: 99%
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