The evaluation of the General Health Questionnaire (GHQ-12) reliability generalization: A meta-analysis.

Abstract

BackgroundThe General Health Questionnaire (GHQ-12) is widely used for detecting psychiatric disorders, but its reliability across different populations remains to be determined.ObjectiveThis meta-analysis aims to evaluate the reliability of GHQ-12 across varied cultural and demographic settings.MethodThis meta-analysis evaluates the reliability of General Health Questionnaire [GHQ-12]' across diverse populations, employing a systematic search strategy and rigorous inclusion criteria. This meta-analysis evaluates the General Health Questionnaire (GHQ-12) using a pre-registered protocol (CRD42023488436) to ensure unbiased results. Data from 20 studies published between 2016-2023 were analysed using a random-effects model, with quality assessment guided by COSMIN Risk of Bias and QUADAS-2. This study enhances our understanding of GHQ-12's psychometric properties.ResultsFor the GHQ-12 subscales, Cronbach's alpha coefficients were 0.72 (90% CI [0.68, 0.75]) for anxiety and depression, 0.82 (90% CI [0.79, 0.86]) for social dysfunction, and 0.72 (90% CI [0.68, 0.76]) for loss of confidence. However, the analysis showed substantial heterogeneity (I2 = 90.04%), with significant variability in reliability estimates across different studies. The overall Cronbach's alpha was 0.84 (95% Cl [0.810, 0.873]) with SE = 0.016 (90% CI [0.68, 0.82], p ConclusionWhile reaffirming the GHQ-12's utility in mental health assessment, our findings urge a more cautious and context-aware application of the questionnaire. The substantial heterogeneity and variability in reliability scores indicate a need for further research. Future studies should explore the reasons behind this variability, focusing on cultural, socio-economic, and methodological factors that might influence the GHQ-12's reliability. This critical analysis underscores the need for a deeper understanding of the GHQ-12's applicability and the importance of tailoring mental health assessment tools to specific population characteristics.