ArticleJMIR mHealth and uHealth2018
An mHealth App for Self-Management of Chronic Lower Back Pain (Limbr): Pilot Study.
Article in JMIR mHealth and uHealth, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT03040310 (Personalized Back Rx Exercise Program With Coaching, Social Support, and Sensor-assisted Assessments as a Treatment for Discogenic Low Back Pain), which is not on this map. Cited by 27 papers, 3 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.
Personalized Back Rx Exercise Program With Coaching, Social Support, and Sensor-assisted Assessments as a Treatment for Discogenic Low Back Pain: A Prospective Pilot Study
Who cites it
27 citing papers in PubMed, 3 syntheses or guidelines pooled it.
- User Engagement With mHealth Interventions to Promote Treatment Adherence and Self-Management in People With Chronic Health Conditions: Systematic Review.Journal of medical Internet research · 2024Pooled 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
- Rates of Attrition and Dropout in App-Based Interventions for Chronic Disease: Systematic Review and Meta-Analysis.Journal of medical Internet research · 2020Pooled it
- "Back Rx, a personalized mobile phone application for discogenic chronic low back pain: a prospective pilot study".BMC musculoskeletal disorders · 2022Trial
- A Hospital-Community-Family-Based Telehealth Program for Patients With Chronic Heart Failure: Single-Arm, Prospective Feasibility Study.JMIR mHealth and uHealth · 2019Trial
- Impact of Different Onboarding Strategies on Low Adoption and Engagement With a Self-Monitoring and Management App for Chronic Musculoskeletal Pain: Prospective Study.JMIR mHealth and uHealth · 2026Article
- Mobile App-Supported Self-Management for Chronic Low Back Pain: Realist Evaluation.JMIR mHealth and uHealth · 2026Article
- Professional-Facing Digital Health Technology for the Care of Patients With Chronic Pain: Scoping Review.Journal of medical Internet research · 2025Article
- Development and Use of Mobile Messaging for Individuals With Musculoskeletal Pain Conditions: Scoping Review.JMIR mHealth and uHealth · 2024Article
- Mobile apps to self-manage chronic low back pain: A realist synthesis exploring what works, for whom and in what circumstances.PEC innovation · 2023Article
- A Continuous Aerobic Resistance Exercise Protocol for Concussion Rehabilitation Delivered Remotely via a Mobile App: Feasibility Study.JMIR formative research · 2023Article
- Feasibility and user acceptability of BreezingSmart health (Amsterdam, Netherlands) · 2023Article
- Article
- What Works Best to Engage Participants in Mobile App Interventions and e-Health: A Scoping Review.Telemedicine journal and e-health : the official journal of the American Telemedicine Association · 2022Article
- Challenges in Participant Engagement and Retention Using Mobile Health Apps: Literature Review.Journal of medical Internet research · 2022Review
- A mobile health + health coaching application for the management of chronic non-cancer pain in older adults: Results from a pilot randomized controlled study.Frontiers in pain research (Lausanne, Switzerland) · 2022Article
- Smartphone applications are used for self-management, telerehabilitation, evaluation and data collection in low back pain healthcare: a scoping review.F1000Research · 2022Article
- Digital Therapeutic Care and Decision Support Interventions for People With Low Back Pain: Systematic Review.JMIR rehabilitation and assistive technologies · 2021Review
- Measuring Success of Patients' Continuous Use of Mobile Health Services for Self-management of Chronic Conditions: Model Development and Validation.Journal of medical Internet research · 2021Article
- Pain and Function in Chronic Musculoskeletal Pain-Treating the Whole Person.Journal of multidisciplinary healthcare · 2021Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
11 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundAlthough mobile health (mHealth) interventions can help improve outcomes among patients with chronic lower back pain (CLBP), many available mHealth apps offer content that is not evidence based. Limbr was designed to enhance self-management of CLBP by packaging self-directed rehabilitation tutorial videos, visual self-report tools, remote health coach support, and activity tracking into a suite of mobile phone apps, including Your Activities of Daily Living, an image-based tool for quantifying pain-related disability.
objectiveThe aim is to (1) describe patient engagement with the Limbr program, (2) describe patient-perceived utility of the Limbr program, and (3) assess the validity of the Your Activities of Daily Living module for quantifying functional status among patients with CLBP.
methodsThis was a single-arm trial utilizing a convenience sample of 93 adult patients with discogenic back pain who visited a single physiatrist from January 2016 to February 2017. Eligible patients were enrolled in 3-month physical therapy program and received the Limbr mobile phone app suite for iOS or Android. The program included three daily visual self-reports to assess pain, activity level, and medication/coping mechanisms; rehabilitation video tutorials; passive activity-level measurement; and chat-based health coaching. Patient characteristics, patient engagement, and perceived utility were analyzed descriptively. Associations between participant characteristics and program interaction were analyzed using multiple linear regression. Associations between Your Activities of Daily Living and Oswestry Disability Index (ODI) assessments were examined using Pearson correlation and hierarchical linear modeling.
resultsA total of 93 participants were enrolled; of these, 35 (38%) completed the program (age: mean 46, SD 16 years; female: 22/35, 63%). More than half of completers finished assessments at least every 3 days and 70% (19/27) used the rehabilitation component at least once a week. Among respondents to a Web-based feedback survey, 76% (16/21) found the daily notifications helped them remember to complete their exercises, 81% (17/21) found the system easy to use, and 62% (13/21) rated their overall experience good or excellent. Baseline Your Activities of Daily Living score was a significant predictor of baseline ODI score, with ODI increasing by 0.30 units for every 1-unit increase in Your Activities of Daily Living (P<.001). Similarly, hierarchical linear modeling analysis indicated that Your Activities of Daily Living daily assessment scores were significant predictors of ODI scores over the course of the study (P=.01).
conclusionsEngagement among participants who completed the Limbr program was high, and program utility was rated positively by most respondents. Your Activities of Daily Living was significantly associated with ODI scores, supporting the validity of this novel tool. Future studies should assess the effect of Limbr on clinical outcomes, evaluate its use among a wider patient sample, and explore strategies for reducing attrition.
trial registrationClinicalTrials.gov NCT03040310; https://clinicaltrials.gov/ct2/show/NCT03040310 (Archived by WebCite at http://www.webcitation.org/722mEvAiv).
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