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睡眠潜伏期觉醒量表(PSAS)和时间监测行为-10 量表(TMB-10)在睡眠良好者和失眠症患者中的应用。

Pre-Sleep Arousal Scale (PSAS) and the Time Monitoring Behavior-10 scale (TMB-10) in good sleepers and patients with insomnia.

机构信息

Department of Psychiatry and Psychotherapy, Medical Center - University of Freiburg, Faculty of Medicine, University of Freiburg, Germany.

Department of Psychiatry and Psychotherapy, Medical Center - University of Freiburg, Faculty of Medicine, University of Freiburg, Germany.

出版信息

Sleep Med. 2019 Apr;56:98-103. doi: 10.1016/j.sleep.2019.01.022. Epub 2019 Jan 30.

Abstract

OBJECTIVES

Pre-sleep arousal and time monitoring behavior are two putative factors involved in the development and maintenance of insomnia. We investigate two questionnaires measuring these factors in good sleepers and patients with insomnia.

PARTICIPANTS

A sample of 96 patients with non-organic insomnia according to ICD-10 and 208 good sleepers completed the Pre-Sleep Arousal Scale (PSAS), the Time Monitoring Behavior-10 scale (TMB-10), the Beck Depression Inventory (BDI)-II, the Pittsburgh Sleep Quality Index (PSQI), the Insomnia Severity Index (ISI) and the State-Trait Anxiety Inventory (STAI).

METHODS

In this study, 95% quantile cut-off scores were determined for good sleeper in the age and gender mathed subgroups of the insomnia group. Multiple logistic regression analysis was used to determine variables predicting above-threshold values in the two target questionnaires. Included predictors were age, gender as well as ISI, BDI-II, STAI-1 and -2 total scores.

RESULTS

Good sleepers showed 95% quantiles between 12.2 and 23.8 for PSAS and between 7.5 and 12.7 for TMB-10. Approximately 40% of patients with insomnia had scores above these cut-offs for PSAS and ca. 25% for TMB-10. Female gender and anxiety were variables associated with scores above cut-off on the PSAS. Insomnia severity and anxiety were associated with scores above cut-off on the TMB-10.

CONCLUSIONS

These findings underline the importance of PSAS and TMB-10 in the diagnostic investigation of insomnia and indicate that time monitoring is related to increased insomnia severity. Further research may investigate the impact of the corresponding two constructs on response rates to cognitive-behavioral treatment for insomnia.

摘要

目的

睡前觉醒和时间监控行为是与失眠的发生和维持有关的两个假定因素。我们调查了两种问卷,用于测量良好睡眠者和失眠患者的这些因素。

参与者

根据 ICD-10 标准,96 名非器质性失眠患者和 208 名良好睡眠者完成了睡眠前觉醒量表(PSAS)、时间监控行为-10 量表(TMB-10)、贝克抑郁量表第二版(BDI-II)、匹兹堡睡眠质量指数(PSQI)、失眠严重程度指数(ISI)和状态-特质焦虑量表(STAI)。

方法

在本研究中,确定了年龄和性别匹配的失眠组亚组中良好睡眠者的 95%分位数截断值。采用多元逻辑回归分析确定两个目标问卷中预测阈值以上值的变量。纳入的预测因子包括年龄、性别以及 ISI、BDI-II、STAI-1 和 -2 总分。

结果

良好睡眠者的 PSAS 得分 95%分位数在 12.2 至 23.8 之间,TMB-10 得分在 7.5 至 12.7 之间。大约 40%的失眠患者的 PSAS 得分高于这些截断值,约 25%的 TMB-10 得分高于这些截断值。女性性别和焦虑是 PSAS 得分高于截断值的相关变量。失眠严重程度和焦虑与 TMB-10 得分高于截断值有关。

结论

这些发现强调了 PSAS 和 TMB-10 在失眠诊断研究中的重要性,并表明时间监控与失眠严重程度增加有关。进一步的研究可能会调查这两个相应结构对认知行为治疗失眠反应率的影响。

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