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通过数字认知行为疗法预防失眠患者的疼痛干扰

Prevention of Pain Interference in Insomnia Patients via Digital Cognitive-Behavioral Therapy for Insomnia.

作者信息

Jennings Matthew B, Kalmbach David A, Reffi Anthony N, Miller Christopher B, Roehrs Timothy, Drake Christopher L, Cheng Philip

机构信息

Sleep Disorders and Research Center, Henry Ford Health, Detroit, MI, USA.

Big Health Inc., San Francisco, USA.

出版信息

Behav Sleep Med. 2025 May 5:1-13. doi: 10.1080/15402002.2025.2500519.

DOI:10.1080/15402002.2025.2500519
PMID:40324067
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC12266104/
Abstract

OBJECTIVES

Insomnia disorder is co-morbid with and predictive of developing pain conditions and a key factor in pain interference (PI) - the extent to which pain impedes daily living. Emerging literature suggests treating insomnia with cognitive-behavioral therapy for insomnia reduces co-occurring PI. This secondary data analysis tested the extent to which digital CBT-I (dCBT-I) vs. sleep education reduces and prevents significant PI by treating insomnia.

METHODS

Insomnia disorder participants were randomized into dCBT-I ( = 697) and sleep education ( = 623) and reported pre- and post-treatment insomnia and PI. Logistic regressions evaluated intervention effects: 1) reduction of insomnia severity changes in PI and 2) prevention of treatment condition on PI.

RESULTS

The reduction model showed that dCBT-I participants with moderate-to-severe pre-treatment PI experienced 17% odds increase in reduced PI for each one-point reduction in insomnia severity compared to control, OR = 1.17, 95% CI [1.01, 1.35]. In the prevention model, dCBT-I participants with little-to-no pre-treatment PI exhibited a 32% odds reduction of post-treatment progression to moderate-to-severe PI compared to control, OR = 0.68, 95% CI [0.51, 0.90].

CONCLUSION

dCBT-I demonstrated significant and clinically meaningful reduction and prevention effects against PI in a large sample. dCBT-I may help providers address sleep issues to restore pain-related impairments to daytime function, quality of life, and overall sleep.

摘要

目的

失眠症与疼痛状况并存且可预测疼痛状况的发展,是疼痛干扰(PI)的关键因素,即疼痛对日常生活的妨碍程度。新出现的文献表明,采用失眠认知行为疗法治疗失眠可减少同时出现的PI。这项二次数据分析检验了数字认知行为疗法治疗失眠(dCBT-I)与睡眠教育相比,在减轻和预防显著PI方面的效果。

方法

将失眠症参与者随机分为dCBT-I组(n = 697)和睡眠教育组(n = 623),并报告治疗前后的失眠情况和PI。逻辑回归评估干预效果:1)PI中失眠严重程度变化的减轻情况;2)治疗条件对PI的预防情况。

结果

减轻模型显示,与对照组相比,治疗前PI为中度至重度的dCBT-I参与者,失眠严重程度每降低1分,PI减轻的几率增加17%,OR = 1.17,95% CI [1.01, 1.35]。在预防模型中,与对照组相比,治疗前PI轻微或无PI的dCBT-I参与者治疗后进展为中度至重度PI的几率降低了32%,OR = 0.68,95% CI [0.51, 0.90]。

结论

在大样本中,dCBT-I对PI显示出显著且具有临床意义的减轻和预防效果。dCBT-I可能有助于医疗服务提供者解决睡眠问题,恢复与疼痛相关的日间功能、生活质量和整体睡眠方面的损害。

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