To examine the psychometric properties of the Sleep Condition Indicator (SCI) using different psychometric approaches [including classical test theory, Rasch models, and receiver operating characteristics (ROC) curve] among patients with advanced cancer. Through convenience sampling, patients with cancer at stage III or IV (n = 859; 511 males; mean ± SD age = 67.4 ± 7.5 years) were recruited from several oncology units of university hospitals in Iran. All the participants completed the SCI, Insomnia Severity Index (ISI), Pittsburgh Sleep Quality Index (PSQI), Epworth Sleepiness Scale (ESS), Hospital Anxiety and Depression Scale (HADS), General Health Questionnaire (GHQ), and Edmonton Symptom Assessment Scale (ESAS). In addition, 491 participants wore an actigraph device to capture objective sleep. Classical test theory [factor loadings from confirmatory factor analysis = 0.76–0.89; test–retest reliability = 0.80–0.93] and Rasch analysis [infit mean square (MnSq) = 0.63–1.31; outfit MnSq = 0.61–1.23] both support the construct validity of the SCI. The SCI had significant associations with ISI, PSQI, ESS, HADS, GHQ, and ESAS. In addition, the SCI has satisfactory area under ROC curve (0.92) when comparing a gold standard of insomnia diagnosis. Significant differences in the actigraphy measure were found between insomniacs and non-insomniacs based on the SCI score defined by ROC. With the promising psychometric properties shown in the SCI, healthcare providers can use this simple assessment tool to target the patients with advanced cancer who are at risk of insomnia and subsequently provide personalized care efficiently.

中文翻译：

---

用于评估失眠的临床筛查工具的高级心理测试：晚期癌症患者的睡眠状况指标

使用不同的心理测量方法 [包括经典测试理论、Rasch 模型和接收器操作特征 (ROC) 曲线] 在晚期癌症患者中检查睡眠状况指标 (SCI) 的心理测量特性。通过便利抽样，从伊朗大学医院的几个肿瘤科招募了 III 期或 IV 期癌症患者（n = 859；511 名男性；平均 ± SD 年龄 = 67.4 ± 7.5 岁）。所有参与者都完成了 SCI、失眠严重程度指数 (ISI)、匹兹堡睡眠质量指数 (PSQI)、Epworth 嗜睡量表 (ESS)、医院焦虑和抑郁量表 (HADS)、一般健康问卷 (GHQ) 和埃德蒙顿症状评估量表(ESAS)。此外，491 名参与者佩戴了活动记录仪来捕捉客观睡眠。经典检验理论[来自验证性因子分析的因子载荷 = 0.76–0.89；重测信度 = 0.80–0.93] 和 Rasch 分析 [infit 均方 (MnSq) = 0.63–1.31; 装备 MnSq = 0.61–1.23] 都支持 SCI 的结构有效性。SCI 与 ISI、PSQI、ESS、HADS、GHQ 和 ESAS 有显着关联。此外，当比较失眠诊断的金标准时，SCI 具有令人满意的 ROC 曲线下面积 (0.92)。根据 ROC 定义的 SCI 评分，失眠者和非失眠者的活动记录测量存在显着差异。凭借 SCI 中显示的有希望的心理测量特性，医疗保健提供者可以使用这种简单的评估工具来针对有失眠风险的晚期癌症患者，并随后有效地提供个性化护理。