Comparative Effectiveness of AI-Assisted Telerehabilitation, Telerehabilitation, In-Person Care, and Usual Care for Chronic Nonspecific Low Back Pain: Bayesian Network Meta-Analysis.

backgroundGuided exercise is central to rehabilitation for chronic nonspecific low back pain. Telerehabilitation enables remote delivery of guided exercise, but its effectiveness vs other rehabilitation modalities remains uncertain.

objectiveThis review systematically assessed the comparative efficacy of telerehabilitation, in-person rehabilitation (IPR), and usual care (UC) for improving pain, disability, kinesiophobia, and health-related quality of life in patients with chronic nonspecific low back pain. Telerehabilitation combined with artificial intelligence (TLRH-AI) was evaluated as an exploratory intervention because available evidence was limited.

methodsFollowing PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) 2020 guidelines, we searched randomized controlled trials in PubMed, Cochrane Library, Web of Science, and Embase from inception to April 30, 2026. A Bayesian network meta-analysis was conducted using R (version 4.4.1). Interventions were ranked using surface under the cumulative ranking curve (SUCRA) values. Evidence certainty was assessed using the GRADE (Grading of Recommendations Assessment, Development, and Evaluation) framework. Findings were interpreted considering heterogeneity, risk of bias, inconsistency, and estimated prediction intervals.

resultsAmong 2491 records, 20 randomized controlled trials involving 1854 participants were included. For pain intensity, IPR showed the greatest benefit at 4 weeks (low-certainty evidence), telerehabilitation at 8 weeks (moderate-certainty evidence), and telerehabilitation ranked highest at 12 weeks (SUCRA 87.2%; moderate-certainty evidence). For the Oswestry Disability Index-based disability, IPR ranked highest at 4 weeks (SUCRA 98.2%; low-certainty evidence) and 12 weeks (SUCRA 86.7%; low-certainty evidence), whereas telerehabilitation ranked highest at 8 weeks (SUCRA 90.4%; high-certainty evidence). For the Roland-Morris Disability Questionnaire-based disability, IPR was among the more effective interventions (SUCRA 67.3%; low-certainty evidence). For kinesiophobia, IPR ranked highest (SUCRA 99%; low-certainty evidence). For health-related quality of life, telerehabilitation significantly improved the physical component summary score (mean difference 6.05, 95% credible interval [CrI] 2.89-9.22; moderate-certainty evidence), whereas IPR showed a nonsignificant trend toward an improved mental component summary score (mean difference 2.79, 95% CrI -1.61 to 7.17; low-certainty evidence). Evidence for TLRH-AI remained limited and descriptive, suggesting possible short-term benefits with low to very low certainty. No significant small-study effects or global inconsistency were detected, although potentially important local inconsistency was observed in the 4-week Oswestry Disability Index comparison between UC and IPR.

conclusionsThis review uniquely compared telerehabilitation, IPR, UC, and exploratory TLRH-AI within a Bayesian network meta-analysis. Unlike previous reviews focused mainly on telerehabilitation vs conventional care, it provides a comparative hierarchy across delivery models, follow-up windows, and outcomes while incorporating evidence certainty and heterogeneity. The findings support individualized rehabilitation selection. In practice, telerehabilitation may offer a scalable option for longer-term pain relief and physical function improvement, whereas IPR may remain important for supervised functional recovery and psychological support. TLRH-AI remains exploratory and should not guide clinical decision-making until adequately powered trials are available.

trial registrationPROSPERO CRD420251146712; https://www.crd.york.ac.uk/PROSPERO/view/CRD420251146712.