Sleep & breathing = Schlaf & Atmung · 2024
Psychometric and structural properties of the traditional Chinese version of the sleep condition indicator for patients undergoing hemodialysis.
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Chang Yu-Han, Lee Hsun-Hua, Liao Yi-Shu, Guu Ta-Wei, Guo Shu-Liu, Hasan Faizul, Jan Ya-Wen, Lee Hsin-Chien, Chiu Hsiao-Yean
Аннотация
PURPOSE: Insomnia is a prevalent sleep disorder among patients undergoing hemodialysis for chronic kidney disease. This study aimed to translate the sleep condition indicator (SCI), an insomnia screening tool based on the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (DSM-5), into a traditional Chinese version (SCI-TC) and evaluate the reliability and validity of this version for patients undergoing hemodialysis.
METHODS: This cross-sectional study conducted from November 2022 to June 2023 involved 200 patients on hemodialysis (mean age, 65.56 years; 61.5% men). Participants completed a series of questionnaires, with insomnia diagnosed according to DSM-5 criteria as the gold standard. A receiver operating characteristic (ROC) curve analysis was conducted to examine the sensitivity and specificity of the SCI-TC.
RESULTS: According to the DSM-5 criteria, 38% of the participants had insomnia. Cronbach's alpha for the SCI-TC was 0.92. The SCI-TC exhibited a good fit as a two-factor model, and its scores were significantly associated with those of the traditional Chinese versions of the Insomnia Severity Index, Patient Health Questionnaire-9, Generalized Anxiety Disorder-7, EuroQol 5-Dimensions scale, and EuroQol Visual Analogue Scale (r = - 0.94, - 0.53, - 0.38, 0.27, and 0.30, respectively; all p < 0.05). The ROC curve analysis revealed an optimal cutoff of 16 points, with the sensitivity, specificity, and area under curve of 88.2%, 84.7%, and 0.91(95% confidence interval, 0.87-0.95), respectively.
CONCLUSION: The SCI-TC demonstrates robust reliability and validity in detecting insomnia among patients undergoing hemodialysis. These findings suggest that health-care providers should considering using the SCI as an easy-to-use tool for the timely detection of insomnia in this population.
METHODS: This cross-sectional study conducted from November 2022 to June 2023 involved 200 patients on hemodialysis (mean age, 65.56 years; 61.5% men). Participants completed a series of questionnaires, with insomnia diagnosed according to DSM-5 criteria as the gold standard. A receiver operating characteristic (ROC) curve analysis was conducted to examine the sensitivity and specificity of the SCI-TC.
RESULTS: According to the DSM-5 criteria, 38% of the participants had insomnia. Cronbach's alpha for the SCI-TC was 0.92. The SCI-TC exhibited a good fit as a two-factor model, and its scores were significantly associated with those of the traditional Chinese versions of the Insomnia Severity Index, Patient Health Questionnaire-9, Generalized Anxiety Disorder-7, EuroQol 5-Dimensions scale, and EuroQol Visual Analogue Scale (r = - 0.94, - 0.53, - 0.38, 0.27, and 0.30, respectively; all p < 0.05). The ROC curve analysis revealed an optimal cutoff of 16 points, with the sensitivity, specificity, and area under curve of 88.2%, 84.7%, and 0.91(95% confidence interval, 0.87-0.95), respectively.
CONCLUSION: The SCI-TC demonstrates robust reliability and validity in detecting insomnia among patients undergoing hemodialysis. These findings suggest that health-care providers should considering using the SCI as an easy-to-use tool for the timely detection of insomnia in this population.