Jennifer Schuffelen,Leonie F Maurer,Annika Gieselmann
{"title":"数字认知行为疗法对慢性疼痛患者失眠的影响:一项随机对照试验。","authors":"Jennifer Schuffelen,Leonie F Maurer,Annika Gieselmann","doi":"10.1159/000547436","DOIUrl":null,"url":null,"abstract":"INTRODUCTION\r\nManaging chronic pain is a significant healthcare challenge requiring a multimodal approach. The frequent presence of comorbid insomnia and its bidirectional relationship with pain complicates treatment. This study tested whether adding digital cognitive behavioral therapy for insomnia (dCBT-I) to standard chronic pain treatment improves symptoms compared to a waitlist control (WLC).\r\n\r\nMETHODS\r\nParticipants with chronic pain and insomnia were randomized (1:1) to dCBT-I or WLC. Assessments occurred at baseline, eight, and 24 weeks post-randomization. The primary outcome was insomnia severity (Insomnia Severity Index; ISI). Secondary outcomes included sleep- and pain-related symptoms, well-being, and dreams. Linear mixed models assessed between-group differences.\r\n\r\nRESULTS\r\nA total of 207 participants (182 women, mean age=51.96±12.97 years) were randomized to dCBT-I (n=103) or WLC (n=104). The dCBT-I group showed large improvements in insomnia severity versus WLC at both eight (-4.36, p<.001; d=-1.18) and 24 weeks (-4.88, p<.001; d=-1.32). Pain-related impairments and life control also improved, favoring dCBT-I (ds=0.22-0.35). Moderate-to-large effects were observed for secondary outcomes, including daytime sleepiness, fatigue, and dysfunctional sleep beliefs (ds=0.47-1.12).\r\n\r\nCONCLUSION\r\ndCBT-I effectively reduces insomnia severity in individuals with chronic pain and insomnia. Improvements in chronic pain symptoms highlight its potential as a scalable, evidence-based intervention for multimodal pain management.","PeriodicalId":20744,"journal":{"name":"Psychotherapy and Psychosomatics","volume":"3 1","pages":"1-35"},"PeriodicalIF":16.3000,"publicationDate":"2025-07-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"The Effects of Digital Cognitive Behavioral Therapy for Insomnia in Chronic Pain: A Randomized Controlled Trial.\",\"authors\":\"Jennifer Schuffelen,Leonie F Maurer,Annika Gieselmann\",\"doi\":\"10.1159/000547436\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"INTRODUCTION\\r\\nManaging chronic pain is a significant healthcare challenge requiring a multimodal approach. The frequent presence of comorbid insomnia and its bidirectional relationship with pain complicates treatment. This study tested whether adding digital cognitive behavioral therapy for insomnia (dCBT-I) to standard chronic pain treatment improves symptoms compared to a waitlist control (WLC).\\r\\n\\r\\nMETHODS\\r\\nParticipants with chronic pain and insomnia were randomized (1:1) to dCBT-I or WLC. Assessments occurred at baseline, eight, and 24 weeks post-randomization. The primary outcome was insomnia severity (Insomnia Severity Index; ISI). Secondary outcomes included sleep- and pain-related symptoms, well-being, and dreams. Linear mixed models assessed between-group differences.\\r\\n\\r\\nRESULTS\\r\\nA total of 207 participants (182 women, mean age=51.96±12.97 years) were randomized to dCBT-I (n=103) or WLC (n=104). The dCBT-I group showed large improvements in insomnia severity versus WLC at both eight (-4.36, p<.001; d=-1.18) and 24 weeks (-4.88, p<.001; d=-1.32). Pain-related impairments and life control also improved, favoring dCBT-I (ds=0.22-0.35). 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The Effects of Digital Cognitive Behavioral Therapy for Insomnia in Chronic Pain: A Randomized Controlled Trial.
INTRODUCTION
Managing chronic pain is a significant healthcare challenge requiring a multimodal approach. The frequent presence of comorbid insomnia and its bidirectional relationship with pain complicates treatment. This study tested whether adding digital cognitive behavioral therapy for insomnia (dCBT-I) to standard chronic pain treatment improves symptoms compared to a waitlist control (WLC).
METHODS
Participants with chronic pain and insomnia were randomized (1:1) to dCBT-I or WLC. Assessments occurred at baseline, eight, and 24 weeks post-randomization. The primary outcome was insomnia severity (Insomnia Severity Index; ISI). Secondary outcomes included sleep- and pain-related symptoms, well-being, and dreams. Linear mixed models assessed between-group differences.
RESULTS
A total of 207 participants (182 women, mean age=51.96±12.97 years) were randomized to dCBT-I (n=103) or WLC (n=104). The dCBT-I group showed large improvements in insomnia severity versus WLC at both eight (-4.36, p<.001; d=-1.18) and 24 weeks (-4.88, p<.001; d=-1.32). Pain-related impairments and life control also improved, favoring dCBT-I (ds=0.22-0.35). Moderate-to-large effects were observed for secondary outcomes, including daytime sleepiness, fatigue, and dysfunctional sleep beliefs (ds=0.47-1.12).
CONCLUSION
dCBT-I effectively reduces insomnia severity in individuals with chronic pain and insomnia. Improvements in chronic pain symptoms highlight its potential as a scalable, evidence-based intervention for multimodal pain management.
期刊介绍:
Psychotherapy and Psychosomatics is a reputable journal that has been published since 1953. Over the years, it has gained recognition for its independence, originality, and methodological rigor. The journal has been at the forefront of research in psychosomatic medicine, psychotherapy research, and psychopharmacology, and has contributed to the development of new lines of research in these areas. It is now ranked among the world's most cited journals in the field.
As the official journal of the International College of Psychosomatic Medicine and the World Federation for Psychotherapy, Psychotherapy and Psychosomatics serves as a platform for discussing current and controversial issues and showcasing innovations in assessment and treatment. It offers a unique forum for cutting-edge thinking at the intersection of medical and behavioral sciences, catering to both practicing clinicians and researchers.
The journal is indexed in various databases and platforms such as PubMed, MEDLINE, Web of Science, Science Citation Index, Social Sciences Citation Index, Science Citation Index Expanded, BIOSIS Previews, Google Scholar, Academic Search, and Health Research Premium Collection, among others.