MacLean R Ross, Shor Rachel, Reilly Erin D, Reuman Lillian, Solar Chelsey, Halat Allison M, Higgins Diana M
VISN1 Mental Illness Research, Education, and Clinical Center, VA Connecticut Healthcare System, West Haven.
Department of Psychiatry, Yale University School of Medicine, New Haven, CT.
Clin J Pain. 2025 Jun 1;41(6):e1289. doi: 10.1097/AJP.0000000000001289.
Digital interventions promise to increase access to non-pharmacological chronic pain treatment and reduce burden for both individuals seeking care and pain providers/clinics. Unfortunately, despite early evidence of efficacy, engagement in self-management digital interventions for chronic conditions is typically low. A comprehensive analysis into how engagement in these programs is measured and reported is warranted. The current systematic review evaluated engagement in digital self-management interventions for chronic pain and identified gaps to improve reporting of engagement data.
We conducted a pre-registered systematic review using Boolean search terms to identify digital chronic pain self-management interventions that did not include clinician support. After removal of duplicates and screening, 150 full-text manuscripts were assessed, and 43 studies met inclusion criteria. Data was extracted and examined from included manuscripts.
Of the 43 included articles, five articles were based on 2 separate datasets, resulting in a final sample of 41 unique datasets representing 4205 participants that were mostly non-Hispanic White, female, and with at least some college education. Approximately 10% of studies did not report any data related to system use or self-reported engagement. Most engagement data consisted of mean system use variables, with a handful of studies describing self-reported use of skills and very few studies examining demographic variables associated with engagement.
To address identified gaps in the reviewed literature, we suggest guidelines for collecting and reporting engagement in digital chronic pain interventions. Consistent reporting of engagement data will improve evaluation, efficacy, and improvement of interventions designed to assist individuals who may otherwise not receive non-pharmacological pain treatment.
数字干预有望增加非药物慢性疼痛治疗的可及性,并减轻寻求治疗的个体以及疼痛治疗提供者/诊所的负担。不幸的是,尽管有早期疗效证据,但慢性病自我管理数字干预的参与度通常较低。有必要对这些项目的参与度测量和报告方式进行全面分析。本系统评价评估了慢性疼痛数字自我管理干预的参与度,并确定了改善参与度数据报告的差距。
我们使用布尔搜索词进行了一项预先注册的系统评价,以识别不包括临床医生支持的数字慢性疼痛自我管理干预措施。在去除重复项和筛选后,评估了150篇全文手稿,43项研究符合纳入标准。从纳入的手稿中提取并检查数据。
在纳入的43篇文章中,5篇文章基于2个独立的数据集,最终样本为41个独特的数据集,代表4205名参与者,这些参与者大多为非西班牙裔白人、女性,且至少接受过一些大学教育。约10%的研究未报告任何与系统使用或自我报告的参与度相关的数据。大多数参与度数据由平均系统使用变量组成,少数研究描述了自我报告的技能使用情况,很少有研究考察与参与度相关的人口统计学变量。
为解决已审查文献中发现的差距,我们提出了收集和报告数字慢性疼痛干预参与度的指南。一致地报告参与度数据将改善旨在帮助那些可能无法接受非药物疼痛治疗的个体的干预措施的评估、疗效和改进。