ArticleHealth science reports2023
Impact of an AI app-based exercise program for people with low back pain compared to standard care: A longitudinal cohort-study.
Article in Health science reports, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers, 2 of them syntheses that pooled it.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
12 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Moving towards the use of artificial intelligence in pain management.European journal of pain (London, England) · 2025Pooled it
- Impact of 25 Years of Mobile Health Tools for Pain Management in Patients With Chronic Musculoskeletal Pain: Systematic Review.Journal of medical Internet research · 2024Pooled it
- Effective real-time self-rehabilitation exercise monitoring and correctness system for low back pain management.Scientific reports · 2026Article
- Artificial intelligence in spine care: A scoping review of treatment applications.North American Spine Society journal · 2026Review
- Evaluating YouTube content on appendicitis: a comparative analysis of Arabic and English videos in terms of quality.Scientific reports · 2026Article
- The validity and reliability of a real-time AI-based neck exercise program among young adults in Thailand: evaluation of accuracy and execution time.Frontiers in artificial intelligence · 2026Article
- A Comparison Between Physical Methods Based on Mechanical Action and Pharmacotherapy in the Treatment of Discogenic Low Back Pain.Healthcare (Basel, Switzerland) · 2025Article
- 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.JMIR formative research · 2025Article
- Article
- Multidisciplinary Digital Therapeutics for Chronic Low Back Pain Versus In-Person Therapeutic Exercise with Education: A Randomized Controlled Pilot Study.Journal of clinical medicine · 2024Article
- The use of artificial intelligence in treating chronic back pain.The Korean journal of pain · 2023Article
- Impact of an AI app-based exercise program for people with low back pain compared to standard care: A longitudinal cohort-study.Health science reports · 2023Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: Low Back Pain (LBP) is a common health problem worldwide. In recent years, the use of mobile applications for the treatment of various diseases has increased, due to the Corona pandemic. Objective: The aim of this study is to investigate the extent to which artificial intelligence (AI)-assisted exercise recommendations can reduce pain and pain-related impairments in daily life for patients with LBP, compared to standard care. Methods: To answer the research question, an 8-week app-based exercise program was conducted in the intervention group. To measure the influence of the exercise program, pain development and pain-related impairment in daily life have been evaluated. A so-called rehabilitation sports group served as the control group. The main factors for statistical analysis were factor time and group comparison. For statistical calculations, a mixed analysis of variance for pain development was conducted. A separate check for confounders was made. For pain impairment in daily life nonparametric tests with the mean of change between the time points are conducted. Results: The intervention group showed a reduction in pain development of 1.4 points compared to an increase of 0.1 points in the control group on the numeric rating scale. There is a significant interaction of time and group for pain development. Regarding pain-related impairments in daily life, the intervention group has a reduction of the oswestry disability index scores by 3.8 points compared to an increase of 2.3 in the control group. The biggest differences become apparent 8 weeks after the start of treatment. The significant results have a medium to strong effect. Conclusion: The results shown here suggest that the use of digital AI-based exercise recommendations in patients with LBP leads to pain reduction and a reduction in pain-related impairments in daily living compared to traditional group exercise therapy.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.