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.

Highlights

  • The Short Form Health Survey (SF-12v2) is an increasingly popular measure of health-related quality of life (HRQoL) in Singapore

  • Findings indicate that algorithm-derived Physical Component Summary (PCS) and Mental Component Summary (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 12-Item Short Form Health Survey Version 2 (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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Summary

Introduction

The Short Form Health Survey (SF-12v2) is an increasingly popular measure of health-related quality of life (HRQoL) in Singapore. Self-reported measures of health-related quality of life (HRQoL) are important for clinicians and researchers to monitor and assess health outcomes at the individual and population levels [3]. They allow public health policymakers and planners to determine physical and mental health status across different demographic groups, evaluate the effectiveness of healthcare, determine the burden of preventable diseases, injuries, and disabilities, and identify areas for resource allocation. The scoring method provided by its developers was based on principle component analysis (PCA) with orthogonal factor rotations and allows for the 12-items to produce two summary scores: Physical Component Summary (PCS) and Mental Component Summary (MCS). The crux of the issue is that a shorter and simpler battery of questions that provides the same information can reduce time and energy spent by both respondents and interviewers, and decrease the chances of missing data (due to the smaller number of questions needed to be answered) [39], and researchers may still opt to utilize the SF-12v2 instead of the SF-36

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