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).

OBJECTIVES

The SF-12 version 2 is a survey instrument for collecting data on subjective health. The US-based scoring method is the recommended standard for measuring subjective health with data collected with this instrument. The inadequacy of the US-based scoring method of the SF-12 version 2 instrument for non-US populations is widely documented. However, few studies systematically assessed relative performance of alternative scoring methods against the US-based method, our main objective in this paper. Through this investigation, we also intend to shed light on Filipina migrant workers' subjective health in Hong Kong, our case study.

METHODS

This study investigates the feasibility of eight such scoring methods-six latent-variable models, the raw score index, and the US-based method-for analyzing an SF-12 version 2 instrument via a range of bootstrapped samples of varying sizes and an empirical study of the original 2017 Hong Kong Domestic Workers survey data with a set of covariates associated with Filipina migrant domestic workers' subjective mental and physical health in Hong Kong.

FINDINGS

Our analyses favor the latent-variable factor model with the normal distribution and the identity link for analyzing the SF-12 version 2 type of data. Our empirical study of the survey data provides evidence for the beneficial effects of education, social support, and positive working conditions on migrant domestic workers' subjective physical health and especially subjective mental health, with these two types of health analyzed on the same measurement scale.

CONCLUSION

For studying non-US populations with the SF-12 version 2 instrument, we recommend using the latent confirmatory factor analysis model that assumes a normal distribution and an identity link function for analyzing the MCS and PCS dimensions simultaneously.