Department of Psychology, Ryerson University, 350 Victoria Street, 8th Floor, Jorgenson Hall, Toronto, Ontario M5B 2K3, Canada.
J Psychiatr Res. 2011 Sep;45(9):1243-9. doi: 10.1016/j.jpsychires.2011.03.011. Epub 2011 Apr 12.
Assessing for clinical levels of anxiety is crucial, as comorbid insomnias far outnumber primary insomnias (PI). Such assessment is complex since those with Anxiety Disorders (AD) and those with PI have overlapping symptoms. Because of this overlap, we need studies that examine the assessment of anxiety in clinical insomnia groups. Participants (N = 207) were classified as having insomnia: 1) without an anxiety disorder (I-ND), or 2) with an anxiety disorder (I-AD). Mean Beck Anxiety Inventory (BAI) item responses were compared using multivariate analysis of variance (MANOVA) and follow-up ANOVAs. As a validity check, a receiver operating characteristic (ROC) curve analysis was conducted to determine if the BAI suggested clinical cutoff was valid for identifying clinical levels of anxiety in this comorbid patient group. The I-ND had lower mean BAI scores than I-AD. There were significant group differences on 12 BAI items. The ROC curve analysis revealed the suggested BAI cutoff (≥16) had 55% sensitivity and 78% specificity. Although anxiety scores were highest in those with insomnia and an anxiety disorder, those with insomnia only had scores in the mild range for anxiety. Nine items did not distinguish between those insomnia sufferers with and without an anxiety disorder. Additionally, published cutoffs for the BAI were not optimal for identifying anxiety disorders in those with insomnia. Such limitations must be considered before using this measure in insomnia patient groups. In addition, the poor specificity and high number of overlapping symptoms between insomnia and anxiety highlight the diagnostic challenges facing clinicians.
评估临床焦虑水平至关重要,因为共病性失眠的数量远远超过原发性失眠(PI)。这种评估很复杂,因为焦虑障碍(AD)患者和 PI 患者有重叠的症状。由于这种重叠,我们需要研究在临床失眠患者群体中评估焦虑。将参与者(N=207)分为以下几类:1)无焦虑障碍(I-ND),或 2)有焦虑障碍(I-AD)。使用多元方差分析(MANOVA)和后续 ANOVA 比较贝克焦虑量表(BAI)的平均项目反应。作为有效性检查,进行了接收者操作特征(ROC)曲线分析,以确定 BAI 是否建议的临床截止值在该共病患者群体中有效识别临床焦虑水平。I-ND 的 BAI 平均得分低于 I-AD。在 12 个 BAI 项目中有显著的组间差异。ROC 曲线分析显示,建议的 BAI 截止值(≥16)具有 55%的敏感性和 78%的特异性。尽管失眠和焦虑障碍患者的焦虑评分最高,但仅失眠患者的焦虑评分处于轻度范围。有 9 个项目无法区分有和没有焦虑障碍的失眠患者。此外,BAI 的发表截止值对于识别失眠患者中的焦虑障碍并不理想。在将该测量方法用于失眠患者群体之前,必须考虑到这些局限性。此外,失眠和焦虑之间症状重叠的特异性差和数量高突出了临床医生面临的诊断挑战。