학술논문

A comparison of univariate and meta-analytic structural equation modeling approaches to reliability generalization applied to the Maslach Burnout Inventory
Document Type
article
Source
Frontiers in Psychology, Vol 15 (2024)
Subject
MBI
MASEM
meta-analysis
reliability generalization
burnout
Psychology
BF1-990
Language
English
ISSN
1664-1078
Abstract
IntroductionReliability is a property of tests scores that varies from sample to sample. One way of generalizing reliability of a test is to perform a meta-analysis on some reliability estimator. In 2011, a reliability generalization meta-analysis on the Maslach Burnout Inventory (MBI) was conducted, concluding that average alpha values for the MBI dimensions ranged from 0.71 to 0.88. In the present study, we aimed to update the average reliability values of the MBI by conducting a literature search from 2010 until now and comparing to statistical procedures of meta-analysis: the Univariate approach, that were used in the previous study, and a novel meta-analytic approach based on structural equation modeling.MethodAn estimation of average reliability was done based on 69 independent primary reliability coefficients for the Univariate approach. The average reliability was based on 9 independent studies in the case of the Meta-analytic Structural Equation Modeling (MASEM) approach. Given that MASEM has the additional capability of testing the internal structure of a test, we also fitted several models.ResultsThe data was well-suited to the bifactor model, revealing the dominance of the general factor over the domain-specific ones. Acceptable overall alpha and omega coefficients were achieved for the two of the MBI dimensions, having depersonalization reliability estimates below recommendations.DiscussionIn general, the MBI can be viewed as a highly interconnected three-factor scale, being its appropriate for research purposes.