Université Laval and Centre de recherche Université Laval-Robert Giffard, Québec, Canada.
Sleep. 2011 May 1;34(5):601-8. doi: 10.1093/sleep/34.5.601.
Although insomnia is a prevalent complaint with significant morbidity, it often remains unrecognized and untreated. Brief and valid instruments are needed both for screening and outcome assessment. This study examined psychometric indices of the Insomnia Severity Index (ISI) to detect cases of insomnia in a population-based sample and to evaluate treatment response in a clinical sample.
Participants were 959 individuals selected from the community for an epidemiological study of insomnia (Community sample) and 183 individuals evaluated for insomnia treatment and 62 controls without insomnia (Clinical sample). They completed the ISI and several measures of sleep quality, fatigue, psychological symptoms, and quality of life; those in the Clinical sample also completed sleep diaries, polysomnography, and interviews to validate their insomnia/good sleep status and assess treatment response. In addition to standard psychometric indices of reliability and validity, item response theory analyses were computed to examine ISI item response patterns. Receiver operating curves were used to derive optimal cutoff scores for case identification and to quantify the minimally important changes in relation to global improvement ratings obtained by an independent assessor.
ISI internal consistency was excellent for both samples (Cronbach α of 0.90 and 0.91). Item response analyses revealed adequate discriminatory capacity for 5 of the 7 items. Convergent validity was supported by significant correlations between total ISI score and measures of fatigue, quality of life, anxiety, and depression. A cutoff score of 10 was optimal (86.1% sensitivity and 87.7% specificity) for detecting insomnia cases in the community sample. In the clinical sample, a change score of -8.4 points (95% CI: -7.1, -9.4) was associated with moderate improvement as rated by an independent assessor after treatment.
These findings provide further evidence that the ISI is a reliable and valid instrument to detect cases of insomnia in the population and is sensitive to treatment response in clinical patients.
尽管失眠是一种普遍存在的疾病，发病率很高，但它往往未被识别和治疗。我们需要既简单又有效的工具来进行筛查和结果评估。本研究旨在检验失眠严重程度指数（ISI）的心理计量学指标，以检测人群样本中的失眠病例，并评估临床样本中的治疗反应。
本研究从社区中选择了 959 名个体参加失眠的流行病学研究（社区样本），并选择了 183 名个体评估失眠治疗，选择了 62 名无失眠的对照个体（临床样本）。参与者完成了 ISI 以及几项睡眠质量、疲劳、心理症状和生活质量的测量；临床样本的参与者还完成了睡眠日记、多导睡眠图和访谈，以验证他们的失眠/良好睡眠状态，并评估治疗反应。除了可靠性和有效性的标准心理计量学指标外，还进行了项目反应理论分析，以检验 ISI 项目反应模式。接收者操作曲线用于得出最佳的病例识别截断分数，并量化与独立评估者获得的整体改善评分相关的最小重要变化。
ISI 在两个样本中的内部一致性都非常好（Cronbach α 为 0.90 和 0.91）。项目反应分析显示，7 个项目中的 5 个具有足够的区分能力。ISI 总分与疲劳、生活质量、焦虑和抑郁的测量结果之间存在显著相关性，这支持了其聚合效度。在社区样本中，10 分是最佳的截断分数（86.1%的敏感性和 87.7%的特异性），用于检测失眠病例。在临床样本中，与治疗后独立评估者评定的中度改善相关的变化分数为-8.4 分（95%CI：-7.1，-9.4）。
这些发现进一步证明，ISI 是一种可靠有效的工具，可用于在人群中检测失眠病例，并且对临床患者的治疗反应敏感。
