SynthesisJMIR mHealth and uHealth2024
Evaluation of Patient-Facing Mobile Apps to Support Physiotherapy Care: Systematic Review.
Synthesis in JMIR mHealth and uHealth, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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
5 citing papers in PubMed.
- Coping experiences in child and adolescent rehabilitation through a novel device: A multi-method feasibility study.Journal of pediatric rehabilitation medicine · 2026Review
- Acceptance and use of digital health technologies among physiotherapists in Germany: a web-based cross-sectional survey.BMC health services research · 2026Article
- App-based exercise intervention versus supervised exercise therapy for patients with hip or knee osteoarthritis-the randomised noninferiority DigiOA trial.EULAR rheumatology open · 2025Article
- Behavior Change Support Systems for Self-Treating Procrastination: Systematic Search in App Stores and Analysis of Motivational Design Archetypes.Journal of medical Internet research · 2025Article
- Usage, Attitudes, Facilitators, and Barriers Toward Digital Health Technologies in Musculoskeletal Care: Survey Among Primary Care Physiotherapists in Norway.JMIR rehabilitation and assistive technologies · 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
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundMobile health interventions delivered through mobile apps are increasingly used in physiotherapy care. This may be because of the potential of apps to facilitate changes in behavior, which is central to the aims of care delivered by physiotherapists. A benefit of using apps is their ability to incorporate behavior change techniques (BCTs) that can optimize the effectiveness of physiotherapeutic interventions. Research continues to suggest that despite their importance, behavior change strategies are often missing in patient management. Evaluating mobile apps that physiotherapists can use to drive behavior change may inform clinical practice and potentially improve patient outcomes. Examining the quality of apps and exploring their key features that can support behavior change and physiotherapy care are important aspects of such an evaluation.
objectiveThe primary aim of this study was to describe the range of mobile apps in app stores that are intended for use by patients to support physiotherapy care. The secondary aims were to assess app quality, BCTs, and their behavior change potential.
methodsA systematic review of mobile apps in app stores was undertaken. The Apple App Store and Google Play were searched using a 2-step search strategy, using terms relevant to the physiotherapy discipline. Strict inclusion and exclusion criteria were applied: apps had to be intended for use by patients and be self-contained (or stand-alone) without the requirement to be used in conjunction with a partner wearable device or another plugin. Included apps were coded for BCTs using the Behavior Change Technique Taxonomy version 1. App quality was assessed using the Mobile App Rating Scale, and the App Behavior Change Scale was used to assess the app's potential to change behavior.
resultsIn total, 1240 apps were screened, and 35 were included. Of these 35 apps, 22 (63%) were available on both the Apple App Store and Google Play platforms. In total, 24 (69%) were general in their focus (eg, not condition-specific), with the remaining 11 (31%) being more specific (eg, knee rehabilitation and pelvic floor training). The mean app quality score (Mobile App Rating Scale) was 3.7 (SD 0.4) of 5 (range 2.8-4.5). The mean number of BCTs identified per app was 8.5 (SD 3.6). BCTs most frequently included in the apps were instruction on how to perform a behavior (n=32), action planning (n=30), and self-monitoring of behavior (n=28). The mean behavior change potential score (App Behavior Change Scale) was 8.5 (SD 3.1) of 21 (range 3-15).
conclusionsMobile apps available to support patient care received from a physiotherapist are of variable quality. Although they contain some BCTs, the potential for behavior change varied widely across apps. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): RR2-10.2196/29047.
Indexed as
Identifiers
What Socratic 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 Socratic graph.