ArticleHealth and quality of life outcomes2021
Confirmatory factor analysis and measurement invariance of the English, Mandarin, and Malay versions of the SF-12v2 within a representative sample of the multi-ethnic Singapore population.
Article in Health and quality of life outcomes, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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7 citing papers in PubMed.
- A comparative analysis of structural equation modeling and traditional regression analysis in investigating factors affecting health-related quality of life in general Thai population.Health and quality of life outcomes · 2025Article
- Factor structure and trends in SF-12v2 health-related quality of life scores among pre-and post-pandemic samples in Thailand: confirmatory factor analysis and Rasch analysis.Health and quality of life outcomes · 2025Article
- Transdiagnostic relevance of subjective cognitive complaints: a validation and population-based study using two Canadian scales (SSTICS and MoCA) in the UAE.Frontiers in behavioral neuroscience · 2025Article
- Association between sleep quality and quality of life in Singapore.Quality of life research : an international journal of quality of life aspects of treatment, care and rehabilitation · 2024Article
- A study of Filipina migrant workers' subjective health in Hong Kong and an assessment of eight scoring methods for the 12-Item Short Form Health Survey (SF-12).Frontiers in sociology · 2024Article
- Food insecurity and health outcome nexus: empirical evidence from the informal sector enterprises in Bangladesh.BMC public health · 2023Article
- Prevalence and patterns of physical activity, sedentary behaviour, and their association with health-related quality of life within a multi-ethnic Asian population.BMC public health · 2021Article
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9 authors.
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Abstract
backgroundThe Short Form Health Survey (SF-12v2) is an increasingly popular measure of health-related quality of life (HRQoL) in Singapore. In order to examine whether the SF-12v2 was appropriate for use in the population, the factor structure and validity of the English, Mandarin, and Malay versions were assessed in a representative sample of the general population of Singapore.
methods6126 respondents were recruited for the Singapore Mental Health Study 2016 (SMHS 2016), a cross-sectional and population-based survey. Confirmatory factor analyses (CFA) were conducted to examine the fit of a two-factor model for the SF-12v2 within a representative sample and amongst the different language (English, Mandarin, Malay) subgroups. Multiple-group CFAs (MGCFA) were conducted to test measurement invariance across the different languages, ethnicities, and chronic illnesses subgroups. CFA-generated latent factor scores (FSCORE command in MPlus) were also compared with the composite scores derived from the developer's scoring method via correlations. Sociodemographic correlates of the latent physical and mental health scores were explored.
resultsCFA results within the full sample supported a two-factor model (RMSEA = 0.044; CFI = 0.991; TLI = 0.988; SRMR = 0.044) in which physical functioning, role physical, bodily pain and general health items loaded onto a latent physical health factor, while role emotional, mental health, social functioning, and vitality items loaded onto a latent mental health factor. Physical and mental health factors were allowed to correlate, unlike the developer's orthogonal scoring method. All standardized loadings were high and statistically significant. Both factors had high internal consistency. CFA within subsamples of English, Mandarin, and Malay languages indicated similar findings. MGCFA results indicate that measurement invariance held across the different languages, ethnicities, and those with and without chronic illnesses.
conclusionThe present study identified a two-factor (physical and mental health) structure within the general population and amongst the three different languages and demonstrated the measurement invariance of SF-12v2 across different subgroups. Findings indicate that algorithm-derived PCS and MCS should be interpreted with caution as they may result in inaccurate conclusions regarding the relationships between HRQoL and its correlates. Future studies using the SF-12v2 within the general population of Singapore should consider utilizing the factor structure put forth in the present study to obtain more appropriate estimates of HRQoL.
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