探索为期8周的人工智能编排运动计划对脊柱疼痛患者疼痛强度和幸福感的影响:回顾性队列分析。
Exploring the Effect of an 8-Week AI-Composed Exercise Program on Pain Intensity and Well-Being in Patients With Spinal Pain: Retrospective Cohort Analysis.
作者信息
Griefahn Annika, Avermann Florian, Zalpour Christoff, Marshall Robert Percy, Cordon Morillas Inés, Luedtke Kerstin
机构信息
Department of Physiotherapy, Institute of Health Sciences, University of Lübeck, Lübeck, Germany.
Faculty of Business Management and Social Sciences, Hochschule Osnabrück, Albrechtstraße 30, Osnabrück, Germany, 49 541969 ext 2998.
出版信息
JMIR Form Res. 2025 Feb 18;9:e57826. doi: 10.2196/57826.
BACKGROUND
Spinal pain, one of the most common musculoskeletal disorders (MSDs), significantly impacts the quality of life due to chronic pain and disability. Physical activity has shown promise in managing spinal pain, although optimizing adherence to exercise remains a challenge. The digital development of artificial intelligence (AI)-driven applications offers a possibility for guiding and supporting patients with MSDs in their daily lives.
OBJECTIVE
The trial aimed to investigate the effect of an 8-week AI-composed exercise program on pain intensity and well-being in patients with spinal pain. It also examined the relationship between exercise frequency, pain intensity, and well-being. In addition, app usage frequency was examined as a proxy for app engagement.
METHODS
Data from users who met the inclusion criteria were collected retrospectively from the medicalmotion app between January 1, 2020, and June 30, 2023. The intervention involved the use of the medicalmotion app, which provides 3-5 personalized exercises for each session based on individual user data. The primary outcomes assessed pain intensity and well-being using the numeric rating scale (NRS) and the Likert scale. Data were collected at baseline (t0), 4 weeks (t1), and 8 weeks (t2). The correlation between exercise frequency, pain intensity, and well-being was analyzed as a secondary outcome. In addition, average session length and frequency were measured to determine app engagement. Statistical analysis included ANOVA and Spearman correlation analysis.
RESULTS
The study included 379 participants with a mean age of 50.96 (SD 12.22) years. At t2, there was a significant reduction of 1.78 points on the NRS (P<.001). The score on the Likert scale for well-being improved by 3.11 points after 8 weeks. Pain intensity showed a negative correlation with the number of daily exercises performed at t1 and t2. Well-being had a small negative correlation with the average number of exercises performed per day. The average number of exercises performed per day was 3.58. The average session length was approximately 10 minutes, and the average interaction with the app was 49.2% (n=27.6 days) of the 56 available days.
CONCLUSIONS
Overall, the study demonstrates that an app-based intervention program can substantially reduce pain intensity and increase well-being in patients with spinal pain. This retrospective study showed that an app that digitizes multidisciplinary rehabilitation for the self-management of spinal pain significantly reduced user-reported pain intensity in a preselected population of app users.
背景
脊柱疼痛是最常见的肌肉骨骼疾病(MSD)之一,由于慢性疼痛和残疾,严重影响生活质量。体育活动在管理脊柱疼痛方面已显示出前景,尽管优化运动依从性仍然是一项挑战。人工智能(AI)驱动应用程序的数字化发展为在日常生活中指导和支持患有MSD的患者提供了一种可能性。
目的
该试验旨在调查为期8周的人工智能编排运动计划对脊柱疼痛患者疼痛强度和幸福感的影响。它还研究了运动频率、疼痛强度和幸福感之间的关系。此外,检查应用程序使用频率作为应用程序参与度的代理指标。
方法
回顾性收集了2020年1月1日至2023年6月30日期间符合纳入标准的用户在medicalmotion应用程序中的数据。干预措施包括使用medicalmotion应用程序,该应用程序根据用户个人数据为每个疗程提供3-5项个性化运动。主要结局使用数字评分量表(NRS)和李克特量表评估疼痛强度和幸福感。在基线(t0)、4周(t1)和8周(t2)收集数据。运动频率、疼痛强度和幸福感之间的相关性作为次要结局进行分析。此外,测量平均疗程长度和频率以确定应用程序参与度。统计分析包括方差分析和斯皮尔曼相关性分析。
结果
该研究纳入了379名参与者,平均年龄为50.96(标准差12.22)岁。在t2时,NRS评分显著降低了1.78分(P<0.001)。8周后,幸福感李克特量表评分提高了3.11分。疼痛强度在t1和t2时与每日进行的运动次数呈负相关。幸福感与每天平均进行的运动次数呈小的负相关。每天平均进行的运动次数为3.58次。平均疗程长度约为10分钟,与应用程序的平均互动天数为56天中的49.2%(n = 27.6天)。
结论
总体而言,该研究表明基于应用程序的干预计划可以显著降低脊柱疼痛患者的疼痛强度并提高幸福感。这项回顾性研究表明,一个将脊柱疼痛自我管理的多学科康复数字化的应用程序在预先选择的应用程序用户群体中显著降低了用户报告的疼痛强度。