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27.09.2016 | Ausgabe 4/2017

Quality of Life Research 4/2017

The importance of considering differential item functioning in investigating the impact of chronic conditions on health-related quality of life in a multi-ethnic Asian population

Zeitschrift:
Quality of Life Research > Ausgabe 4/2017
Autoren:
Edimansyah Abdin, Mythily Subramaniam, Louisa Picco, Shirlene Pang, Janhavi Ajit Vaingankar, Shazana Shahwan, Vathsala Sagayadevan, Yunjue Zhang, Siow Ann Chong

Abstract

Purpose

The present study aims to examine the impact of chronic conditions after adjusting for differential item functioning (DIF) on the various aspects of health-related quality of life (HRQoL) in a multi-ethnic Asian population in Singapore.

Method

Data on 3006 participants from a nation-wide cross-sectional survey of mental health literacy conducted in Singapore were used. Multiple Indicators Multiple Causes model was used to investigate the effects of chronic medical conditions on various HRQoL dimensions assessed with the 36-item Medical Outcomes Study Short Form Health Survey (SF-36) after adjusting for DIF.

Results

Twenty out of 36 items were detected with DIF for chronic conditions including high blood pressure, cardiovascular disorders, diabetes, cancer, neurological disorders and ulcer as well as for a few demographic factors such age, gender and marital status. Twenty significant associations between chronic conditions and SF-36 domains were observed. After controlling for all chronic conditions, socio-demographic and DIF items, a significant association emerged between cardiovascular disorders and physical functioning, while the association between diabetes and ulcer and general health became nonsignificant. All other associations remained statistically significant.

Conclusion

Our findings provide useful information and important implications of DIF on the impact of chronic conditions on HRQoL. We found the impact of DIF with respect to the impact of chronic conditions on HRQoL to be minimal after accounting for measurement bias in this multiracial Asian population.

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