Validation of the Insomnia Severity Index in Primary Care
Validation of the Insomnia Severity Index in Primary Care
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DOI：
10.3122/jabfm.2013.06.130064
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发表时间：
2013-11-01
影响因子：
2.9
通讯作者：
Morin, Charles M.
中科院分区：
文献类型：
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作者：
Gagnon, Christine;Belanger, Lynda;Morin, Charles M.
背景资料：虽然失眠是一种普遍的投诉，对生活质量，健康和卫生保健利用的显着后果，它往往仍然未被诊断和治疗的初级保健设置。需要简单、可靠和有效的工具来帮助在一般实践中筛查失眠症。本研究探讨了心理测量指数的失眠严重程度指数（ISI），以确定个人在初级保健settings.Methods的临床意义上的失眠：410例患者从6个普通医疗诊所招募的样本完成了ISI之前，他们的任命与初级保健医生。一个子样本的101人也完成了半结构化的临床电话采访，以确定是否存在失眠症。计算信度和效度指标，以及每个项目的区分能力。ISI总分和诊断之间的收敛来自采访进行了调查。接收器操作员特征分析被用来确定最佳ISI截止值，正确识别个人与失眠disorder.Results：ISI内部一致性是优秀的（Cronbach α = 0.92），每个单独的项目显示出足够的辨别能力（r = 0.65-0.84）。受试者工作特征曲线下面积为0.87，表明临界值14是检测临床失眠的最佳值（敏感性82.4%，特异性82.1%，一致性82.2%）。ISI削减分数和诊断面试之间的协议是温和的（Kappa = 0.62）。结论：这些研究结果表明，ISI是一个有效的筛选工具，用于检测失眠患者咨询在初级保健设置。
Background: Although insomnia is a prevalent complaint with significant consequences on quality of life, health, and health care utilization, it often remains undiagnosed and untreated in primary care settings. Brief, reliable, and valid instruments are needed to facilitate screening for insomnia in general practice. This study examined psychometric indices of the Insomnia Severity Index (ISI) to identify individuals with clinically significant insomnia in primary care settings.Methods: A sample of 410 patients recruited from 6 general medical clinics completed the ISI before their appointment with a primary care physician. A subsample of 101 individuals also completed a semistructured clinical interview by telephone to determine the presence or absence of an insomnia disorder. Reliability and validity indices were computed, as was the discriminative capacity of each individual item. Convergence between ISI total score and the diagnosis derived from the interview was investigated. Receiver operator characteristic analyses were used to determine the optimal ISI cutoff score that correctly identified individuals with an insomnia disorder.Results: ISI internal consistency was excellent (Cronbach alpha = 0.92), and each individual item showed adequate discriminative capacity (r = 0.65-0.84). The area under the receiver operator characteristic curve was 0.87 and suggested that a cutoff score of 14 was optimal (82.4% sensitivity, 82.1% specificity, and 82.2% agreement) for detecting clinical insomnia. Agreement between the ISI cut score and the diagnostic interview was moderate (kappa = 0.62).Conclusions: These findings suggest that the ISI is a valid screening instrument for detecting insomnia among patients consulting in primary care settings.