Meng Runtang, Yang Nongnong, Luo Yi, O'Driscoll Ciarán, Ma Haiyan, Gregory Alice M, Dzierzewski Joseph M
School of Public Health, Hangzhou Normal University, Hangzhou 311121, Zhejiang, China; Engineering Research Center of Mobile Health Management System, Ministry of Education, Hangzhou 311121, Zhejiang, China.
School of Public Health, Hangzhou Normal University, Hangzhou 311121, Zhejiang, China.
Gen Hosp Psychiatry. 2025 Jan-Feb;92:75-83. doi: 10.1016/j.genhosppsych.2024.12.001. Epub 2024 Dec 3.
The RU_SATED scale is increasingly used across the globe to measure sleep health. However, there is a lack of consensus around its psychometric and diagnostic performance. We conducted an empirical investigation into the psychometrics of the Chinese version of the RU_SATED (RU_SATED-C) scale, with a focus on structural validity and diagnostic performance.
1171 adults were enrolled from three communities in Hangzhou, China in July 2022. The dataset was spilt in half, and we ran a bootstrapped exploratory graph analysis (bootEGA) in one half and a confirmatory factor analysis (CFA) in the other half to assess structural validity. Correlations with insomnia, wellness, anxiety, and depression symptoms were examined in order to assess concurrent validity; and Cronbach's α and McDonald's ω were calculated to assess internal consistency. Additionally, a Receiver Operating Characteristic (ROC) analysis established and externally validated the optimal score for identifying insomnia symptoms.
A one-dimensional structure, as identified by bootEGA, was corroborated in the CFA [comparative fit index = 0.934, root mean square error of approximation = 0.088, standardized root mean square residual = 0.051]. A moderate correlation was shown with insomnia symptoms, while weak correlations were observed with wellness, anxiety, and depression symptoms. The RU_SATED-C scale displayed sub-optimal internal consistency where coefficients dropped if any item was removed. A recommended cutoff score of ≤13 was derived for probable insomnia with a satisfactory diagnostic performance.
The RU_SATED-C scale displayed a one-dimensional model, along with adequate concurrent validity, internal consistency, and diagnostic performance. Further work necessitates multi-scenario testing and additional validation using objective sleep assessments.
全球范围内越来越多地使用RU_SATED量表来衡量睡眠健康状况。然而，对于其心理测量学和诊断性能，尚未达成共识。我们对中文版RU_SATED（RU_SATED-C）量表的心理测量学进行了实证研究，重点关注结构效度和诊断性能。
2022年7月，从中国杭州的三个社区招募了1171名成年人。将数据集分成两半，我们在其中一半中进行了自抽样探索性图形分析（bootEGA），在另一半中进行了验证性因素分析（CFA），以评估结构效度。研究了与失眠、健康、焦虑和抑郁症状的相关性，以评估同时效度；计算了Cronbach's α和McDonald's ω以评估内部一致性。此外，通过受试者工作特征（ROC）分析确定并外部验证了识别失眠症状的最佳分数。
bootEGA确定的一维结构在CFA中得到证实[比较拟合指数=0.934，近似均方根误差=0.088，标准化均方根残差=0.051]。与失眠症状呈中度相关，而与健康、焦虑和抑郁症状呈弱相关。RU_SATED-C量表显示出次优的内部一致性，如果删除任何项目，系数会下降。得出可能失眠的推荐临界值分数≤13，诊断性能令人满意。
RU_SATED-C量表显示出一维模型，同时具有足够的同时效度、内部一致性和诊断性能。进一步的工作需要进行多场景测试，并使用客观睡眠评估进行额外验证。
