ArticleArchives of rehabilitation research and clinical translation2022
Can Physical Therapy Deliver Clinically Meaningful Improvements in Pain and Function Through a Mobile App? An Observational Retrospective Study.
Article in Archives of rehabilitation research and clinical translation, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 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
3 citing papers in PubMed, 2 syntheses or guidelines pooled 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
- Efficacy of mHealth Interventions for Improving the Pain and Disability of Individuals With Chronic Low Back Pain: Systematic Review and Meta-Analysis.JMIR mHealth and uHealth · 2023Pooled it
- Digital Health as a Mechanism to Reduce Neonatal Intensive Care Unit Admissions: Retrospective Cohort Study.JMIR pediatrics and parenting · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Objective: To examine the effect of digital physical therapy (PT) delivered by mobile application (app) on reducing pain and improving function for people with a variety of musculoskeletal conditions. Design: An observational, longitudinal, retrospective study using survey data collected pre- and postdigital PT to estimate multilevel models with random intercepts for patient episodes. Setting: Privately insured employees participating in app-based PT as an employer health care benefit. Participants: The study sample included 814 participants (N=814) 18 years or older who completed their digital PT program with reported final clinical outcomes between February 2019 (program launch) through December 2020. Mean age of the sample at baseline was 40.9±11.89 years, 47.5% were female, 21% sought care for lower back pain, 16% for shoulders, 15% for knees, and 13% for neck. Interventions: Digital PT consisted of a synchronous video evaluation with a physical therapist followed by a course of PT delivered through a mobile app. Main Outcome Measures: Pain was measured by the visual analog scale from 0 "no pain" to 10 "worst pain imaginable" and physical function by the Patient-Specific Functional Scale on a scale from 0 "completely unable to perform" to 10 "able to perform normally." Results: After controlling for significant demographics, comorbid conditions, adverse symptoms, chronicity, and severity, the results from multilevel random intercept models showed decreased pain (-2.69 points; 95% CI, -2.86 to -2.53; Conclusions: Digital PT was associated with clinically meaningful improvements in pain and function among a diverse set of participants. These early data are an encouraging indicator of the clinical benefit of digital PT.
Indexed as
Identifiers
What OpenQuestion holds
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.