Adaptation of the Pittsburgh Sleep Quality Index in Chinese adults with type 2 diabetes
journal contributionposted on 2018-06-19, 00:00 authored by Bingqian Zhu, Meng Xie, Chang G. Park, Mary C. Kapella
Background: Sleep disturbance is a major health issue in people with type 2 diabetes (T2DM). The Pittsburgh Sleep Quality Index (PSQI) has been the most widely used instrument to measure subjective sleep disturbance. Nevertheless, its factor structure in the context of T2DM has not been examined. The purpose of the study is to evaluate the factor structure of the PSQI in Chinese adults with T2DM and thereby to facilitate its use in clinical practice and research. Methods: The PSQI (Chinese version) was administered to 240 patients with T2DM. Confirmatory factor analysis was conducted to examine the one-factor, adapted one-factor by removing the component "use of sleep medication", and the three-factor structure of the PSQI. Goodness-of-fit indices were used to evaluate the fit of the model. Construct validity of the resultant model was further examined using contrasted groups. Cronbach's α of the resultant model was obtained to evaluate its internal consistency. Results: The three-factor model proposed by Cole et al. did not fit the sleep data. Confirmatory factor analysis supported the adapted one-factor model with the PSQI global score as an indicator of overall sleep quality, and the goodness-of-fit indices for the adapted model were better compared to the original one-factor model. As expected, women, older adults, and patients with poor glycemic control had higher adapted PSQI global score (P < 0.01). Cronbach's α of the adapted PSQI was 0.78. Conclusion: The adapted PSQI was similar to the original PSQI in that only the component "use of sleep medication" was removed from the original scale and the one-factor scoring worked better. In contrast, the three-factor model has limited usefulness in this population.
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CitationZhu, B., Xie, M., Park, C. G. and Kapella, M. C. Adaptation of the Pittsburgh Sleep Quality Index in Chinese adults with type 2 diabetes. Journal of the Chinese Medical Association. 2017. 10.1016/j.jcma.2017.06.021.