目的:失眠是慢性肾脏病血液透析患者普遍存在的睡眠障碍。本研究旨在翻译睡眠状况指标(SCI),基于精神疾病诊断和统计手册的失眠筛查工具,第五版(DSM-5),加入繁体中文版本(SCI-TC),并评估该版本对血液透析患者的信度和效度。
方法:这项从2022年11月至2023年6月进行的横断面研究涉及200名血液透析患者(平均年龄,65.56岁;61.5%男性)。参与者完成了一系列问卷,根据DSM-5标准诊断为失眠的金标准。进行受试者工作特征(ROC)曲线分析以检查SCI-TC的敏感性和特异性。
结果:根据DSM-5标准,38%的参与者有失眠。Cronbach对SCI-TC的α为0.92。SCI-TC作为双因素模型表现出良好的拟合,其得分与失眠严重程度指数的繁体中文版本的得分显着相关,患者健康问卷-9,广义焦虑症-7,EuroQol5维量表,和EuroQol视觉模拟评分(分别为r=-0.94、-0.53、-0.38、0.27和0.30;所有p<0.05)。ROC曲线分析显示16点的最佳截止点,有了灵敏度,特异性,曲线下面积为88.2%,84.7%,和0.91(95%置信区间,0.87-0.95),分别。
结论:SCI-TC在检测血液透析患者的失眠方面具有可靠的信度和效度。这些发现表明,医疗保健提供者应考虑使用SCI作为一种易于使用的工具,以及时发现该人群的失眠。
OBJECTIVE: 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.
CONCLUSIONS: 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.