ReviewJMIR rehabilitation and assistive technologies2021
Digital Therapeutic Care and Decision Support Interventions for People With Low Back Pain: Systematic Review.
Review in JMIR rehabilitation and assistive technologies, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers, 2 of them syntheses that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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
24 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- The Effectiveness of Digital Apps Providing Personalized Exercise Videos: Systematic Review With Meta-Analysis.Journal of medical Internet research · 2023Pooled it
- Digital self-care in the management of spine musculoskeletal disorders: A systematic review and meta-analysis.Revista latino-americana de enfermagem · 2023Pooled it
- Digitally supported physical activity counselling for people with chronic back pain: a randomised controlled parallel feasibility study.BMC primary care · 2025Trial
- "Back Rx, a personalized mobile phone application for discogenic chronic low back pain: a prospective pilot study".BMC musculoskeletal disorders · 2022Trial
- One size does not fit all: Participants' experiences of the selfBACK app to support self-management of low back pain-a qualitative interview study.Chiropractic & manual therapies · 2022Trial
- Design and implementation of PharMe: a mobile application to return pharmacogenomic test results to patients.JAMIA open · 2026Article
- The Influence of Mobile Health Interventions on Aftercare and Medication Use for Patients With Chronic Pain: A Systematic Review.Mayo Clinic proceedings. Digital health · 2026Review
- Implementation of an Australian helpline for low back pain: protocol of a type 2 hybrid effectiveness-implementation trial.BMJ open · 2025Article
- Empowering Self-Management of Chronic Low Back Pain Among Spanish and Cantonese Speakers in the United States.Cureus · 2025Article
- Healthcare effects and evidence robustness of reimbursable digital health applications in Germany: a systematic review.NPJ digital medicine · 2025Article
- Combined Use of Digital and Analog Physical Therapy in Patients With Musculoskeletal Disorders and Indicators of Chronicity: German Claims Data Analysis.JMIR mHealth and uHealth · 2025Article
- Attitudes of People With Chronic Musculoskeletal Disorders Towards Telerehabilitation: A Cross-Sectional Survey.Cureus · 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
- Effect of Telemedicine-Supported Structured Exercise Program in Patients with Chronic Low Back Pain: Study Protocol for a Randomized Controlled Trial.Journal of pain research · 2025Article
- Article
- Economic Evaluation of Digital Therapeutic Care Apps for Unsupervised Treatment of Low Back Pain: Monte Carlo Simulation.JMIR mHealth and uHealth · 2023Article
- Exploring mHealth applications for self-management of chronic low back pain: A survey of features and benefits.Heliyon · 2023Review
- A Short Digital Food Frequency Questionnaire (DIGIKOST-FFQ) Assessing Dietary Intake and Other Lifestyle Factors Among Norwegians: Qualitative Evaluation With Focus Group Interviews and Usability Testing.JMIR formative research · 2022Article
- Digitally Delivered Exercise and Education Treatment Program for Low Back Pain: Longitudinal Observational Cohort Study.JMIR rehabilitation and assistive technologies · 2022Article
- Digital Therapeutic Care Apps With Decision-Support Interventions for People With Low Back Pain in Germany: Cost-Effectiveness Analysis.JMIR mHealth and uHealth · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundLow back pain (LBP) is the leading cause of worldwide years lost because of disability, with a tremendous economic burden for health care systems. Digital therapeutic care (DTC) programs provide a scalable, universally accessible, and low-cost approach to the multidisciplinary treatment of LBP. Moreover, novel decision support interventions such as personalized feedback messages, push notifications, and data-driven activity recommendations amplify DTC by guiding the user through the program while aiming to increase overall engagement and sustainable behavior change.
objectiveThis systematic review aims to synthesize recent scientific literature on the impact of DTC apps for people with LBP and outline the implementation of add-on decision support interventions, including their effect on user retention and attrition rates.
methodsWe searched bibliographic databases, including MEDLINE, Cochrane Library, Web of Science, and the Physiotherapy Evidence Database, from March 1, 2016, to October 15, 2020, in accordance with the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines and conducted this review based on related previously published systematic reviews. Besides randomized controlled trials (RCTs), we also included study designs with the evidence level of at least a retrospective comparative study. This enables the consideration of real-world user-generated data and provides information regarding the adoption and effectiveness of DTC apps in a real-life setting. For the appraisal of the risk of bias, we used the Risk of Bias 2 Tool and the Risk of Bias in Non-Randomized Studies of Interventions Tool for the RCTs and nonrandomized trials, respectively. The included studies were narratively synthesized regarding primary and secondary outcome measures, DTC components, applied decision support interventions, user retention, and attrition rates.
resultsWe retrieved 1388 citations, of which 12 studies are included in this review. Of the 12 studies, 6 (50%) were RCTs and 6 (50%) were nonrandomized trials. In all included studies, lower pain levels and increased functionality compared with baseline values were observed in the DTC intervention group. A between-group comparison revealed significant improvements in pain and functionality levels in 67% (4/6) of the RCTs. The study population was mostly homogeneous, with predominantly female, young to middle-aged participants of normal to moderate weight. The methodological quality assessment revealed moderate to high risks of biases, especially in the nonrandomized trials.
conclusionsThis systematic review demonstrates the benefits of DTC for people with LBP. There is also evidence that decision support interventions benefit overall engagement with the app and increase participants' ability to self-manage their recovery process. Finally, including retrospective evaluation studies of real-world user-generated data in future systematic reviews of digital health intervention trials can reveal new insights into the benefits, challenges, and real-life adoption of DTC programs.
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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.