INTARAKAMHANG, Ungsinun and MACASKILL, Ann (2018). Multi-group causal model of health literacy and behaviors on family well-being among Thai adults at risk of non-communicable diseases (NCDs). Journal of research in health sciences, 18 (4). [Article]
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22683:515742
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Macaskill Multi-group Causal Model of Health Literacy.pdf - Accepted Version
Available under License Creative Commons Attribution.
Macaskill Multi-group Causal Model of Health Literacy.pdf - Accepted Version
Available under License Creative Commons Attribution.
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Abstract
Background: We aimed to develop a causal model of family well-being by mediating health literacy (HL) and to compare models between spouses in men and women and in urban and rural communities.
Study design: A cross-sectional study.
Methods: The samples included 2000 spouses at risk of non-communicable diseases (NCDs) by stratified random sampling in 2018. Data were collected by Likert questionnaires with reliability of 0.79-0.93, using to analyze via confirmatory factor analysis (CFA), and multi-group structural equation modeling (SEM).
Results: A causal model in overall group was consistent with an empirical data. Causal factors had direct effects on health behavior including social norm, positive attitudes, psychology capital, and HL (β=0.11, 0.14, 0.30, and 0.41, P<0.05 respectively). Health behavior and positive attitudes toward health had direct effects on family well-being (β=0.36 and 0.42, P<0.05, respectively). All factors could predict health behavior and family well-being of variance 70% and 50%. Invariance analysis of models showed no difference between spouses in men and women. In addition, mean comparison of latent variables showed that the positive attitudes toward health in women were lower than men. Moreover, HL and positive attitudes toward health of spouses in urban were lower in rural communities.
Conclusion: Thai adult families in urban showed higher risk with NCDs. Therefore, health providers improved the first priority of HL and positive attitude which were the main causal factors
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