Abstract
This study investigates the extent to which the GHQ-12 exhibits configural, metric and scalar invariance across six ethnic groups in Britain and Northern Ireland, using the UK Household Longitudinal Study (N = 35 410). A confirmatory factor analysis was carried out on a white British group in order to establish an adequate measurement model. Secondly, a multi-group confirmatory factor analysis was conducted in order to assess measurement invariance. A sensitivity analysis comparing summated and latent means across groups was carried out. Finally, revised estimates of scale reliability were derived using two different methods. A one-factor model including correlated error terms on the negatively phrased items showed superior fit in all ethnic groups. Tests for equal factor loadings and intercepts also showed adequate fit demonstrating metric and scalar invariance. Latent and summated scale estimates of mean group differences were similar for all groups. Scale reliability using McDonald's ω is lower than when using the more conventional Cronbach's α. Reliability across groups is reasonably consistent. We find that the GHQ-12 does not display obvious bias in regard to ethnic groups in the UK and that valid comparisons across these groups can be made for the purposes of population research. Caution is needed when using as a screening tool for individuals.
Highlights
The General Health Questionnaire (GHQ) was developed in 1972 as a screening tool to identify those who are at risk of identifying psychiatric disorders (Romppel et al, 2017, p. 1)
The GHQ-12 is one of the most widely used for both individual screening purposes and population research (Hankins, 2008)
We instead rely on several measures of approximate fit as suggested by Hu and Bentler (1999), namely comparative fit index (CFI), Tucker–Lewis index (TLI), root mean square error of approximation (RMSEA) and standardised root mean residual (SRMR)
Summary
The General Health Questionnaire (GHQ) was developed in 1972 as a screening tool to identify those who are at risk of identifying psychiatric disorders (Romppel et al, 2017, p. 1). When assessing the mental health profile of individuals and populations, it is assumed that the measurement properties of the survey items are consistent across different groups. Latent factor structures may vary across groups; individual item loadings may differ across groups; and the estimated mean values of scales and subscales may differ across social groups even though no real differences pertain. These issues of what are known in the literature as configural, metric and scalar invariance (Allum, Read, & Sturgis, 2018) are of practical importance for the following reason. Caution is needed when using as a screening tool for individuals
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