Applications of Artificial Intelligence in Back Pain Management: A Systematic Review of Mobile and Digital Health Interventions
Review Article | Journal of Clinical Orthopaedics | Vol 10 | Issue 2 | July-December 2025 | page: 34-36 | Vishal Kumar, Manuj Jain, Aditya Gupta, Arvind Vatkar, Akashdeep Singh, Sarvdeep Singh, Sachin Kale
DOI: https://doi.org/10.13107/jcorth.2025.v10.i02.770
Open Access License: CC BY-NC 4.0
Copyright Statement: Copyright © 2025; The Author(s).
Submitted Date: 13 Aug 2025, Review Date: 10 Sep 2025, Accepted Date: 10 Oct 2025 & Published Date: 10 Dec 2025
Author: Vishal Kumar [1], Manuj Jain [2], Aditya Gupta [1], Arvind Vatkar [3], Akashdeep Singh [1], Sarvdeep Singh [1], Sachin Kale [4]
[1] Department of Orthopaedics, Postgraduate Institute of Medical Education and Research, Chandigarh, India
[2] Department of Orthopaedics, 158 Base Hospital, Bagdogra, West Bengal, India
[3] Department of Orthoapedics, MGM Medical College, Navi Mumbai, Maharashtra, India
[4] Department of Orthopaedics, Dr D Y Patil School of Medicine, Navi Mumbai, Maharashtra, India.
Address of Correspondence
Dr. Vishal Kumar,
Department of Orthopaedics, Postgraduate Institute of Medical Education and Research, Chandigarh, India
E-mail: drkumarvishal@gmail.com
Abstract
The objective of this systematic review is to evaluate the effectiveness and impact of artificial intelligence (AI)-based applications in the management of back pain, particularly through mobile health solutions. The review examines current AI interventions for their potential to improve pain outcomes, enhance self-management, and increase patient adherence. We conducted a comprehensive literature search across multiple databases, including PubMed, Scopus, and IEEE Xplore, following a rigorous inclusion and exclusion process. Studies were selected based on their focus on AI-enabled mobile applications specifically designed to aid back pain patients, with data extracted on outcomes such as pain reduction, patient engagement, and quality of life improvements. The findings reveal promising results, with many AI applications achieving notable success in pain management and user satisfaction; however, certain limitations, such as user engagement rates and app accessibility, were identified. This review underscores the potential of AI-driven health interventions in personalizing care and improving back pain outcomes, while also highlighting areas for future research, particularly in advancing AI algorithms and expanding access to digital health tools.
Keywords: Artificial intelligence, back pain, mobile health applications, pain management, systematic review, digital health, patient adherence.
References
1. Lo WL, Lei D, Li L, Huang DF, Tong KF. The perceived benefits of an artificial intelligence-embedded mobile app implementing evidence-based guidelines for the self-management of chronic neck and back pain: Observational study. JMIR MHealth UHealth 2018;6:e198.
2. Amorim P, Paulo JR, Silva PA, Peixoto P, Castelo-Branco M, Martins H. Machine learning applied to low back pain rehabilitation-a systematic review. Int J Digit Health 2021;1:10.
3. Rughani G, Nilsen TI, Wood K, Mair FS, Hartvigsen J, Mork PJ, et al. The selfBACK artificial intelligence-based smartphone app can improve low back pain outcome even in patients with high levels of depression or stress. Eur J Pain 2023;27:568-79.
4. Marcuzzi A, Nordstoga AL, Bach K, Aasdahl L, Nilsen TI, Bardal EM, et al. Effect of an artificial intelligence-based self-management app on musculoskeletal health in patients with neck and/or low back pain referred to specialist care: A randomized clinical trial. JAMA Netw Open 2023;6:e2320400.
5. Zhang M, Zhu L, Lin SY, Herr K, Chi CL, Demir I, et al. Using artificial intelligence to improve pain assessment and pain management: A scoping review. J Am Med Inform Assoc 2023;30:570-87.
6. Nordstoga AL, Aasdahl L, Sandal LF, Dalager T, Kongsvold A, Mork PJ, et al. The role of pain duration and pain intensity on the effectiveness of app-delivered self-management for low back pain (selfBACK): Secondary analysis of a randomized controlled trial. JMIR MHealth UHealth 2023;11:e40422.
7. Hornung AL, Hornung CM, Mallow GM, Barajas JN, Rush A 3rd, Sayari AJ, et al. Artificial intelligence in spine care: Current applications and future utility. Eur Spine J 2022;31:2057-81.
8. Hasan F, Mudey A, Joshi A. Role of Internet of Things (IoT), artificial intelligence and machine learning in musculoskeletal pain: A scoping review. Cureus 2023;15:e37352.
9. Kawchuk GN, Guan R, Keen C, Hauer B, Kondrak G. Using artificial intelligence algorithms to identify existing knowledge within the back pain literature. Eur Spine J 2020;29:1917-24.
| How to Cite this Article: Kumar V, Jain M, Gupta A, Vatkar A, Singh A, Singh S, Kale S. Applications of Artificial Intelligence in Back Pain Management: A Systematic Review of Mobile and Digital Health Interventions. Journal of Clinical Orthopaedics. July-December 2025;10(2):34-36. |
(Article Text HTML) (Download PDF)



