JMIR Publications

ABSTRACT

Background:

Exercise prescription, a tailored plan of physical activity, is widely used by physicians and therapists in rehabilitation to treat and prevent various diseases. With the rise of mHealth, exercise prescription applications have emerged as tools for remotely prescribing exercise. Despite their potential benefits, concerns remain regarding the comprehensiveness and professionalism of these apps. This study evaluates the clinical usability of popular free exercise prescription apps, focusing on their functional design, behavior change techniques (BCTs), and overall user appeal.

Objective:

To assess whether popular and free exercise prescription applications are adequately comprehensive for clinical use, focusing on functional design, behavior change techniques, and user satisfaction.

Methods:

A systematic search on Google Play and the Apple App Store used terms like "exercise prescription AND doctor/therapist/rehabilitation." Inclusion criteria required apps to be free, available in English or Chinese, have over 10,000 downloads, and allow professional exercise prescriptions. Six apps met these criteria. Evaluations used the Consensus on Exercise Reporting Template (CERT) for completeness, the Behavior Change Technique Taxonomy version 1 (BCTTv1) for behavior change techniques, and the Mobile App Rating Scale (MARS) for quality and user appeal. Additionally, apps were assessed for adherence to the American College of Sports Medicine's FITT (Frequency, Intensity, Time, and Type) principle and the FITT-VP (Frequency, Intensity, Time, Type, Volume, and Progression) principle. Descriptive data were gathered as of July 28, 2024, and statistical analyses were conducted using Microsoft Excel.

Results:

The initial search identified 1020 applications, narrowed down to six after applying the inclusion criteria. These apps had download ranges from 10,000 to over one million. Using CERT, all apps adhered to the FITT principle but failed to meet the FITT-VP principle due to the lack of exercise progression guidance. The BCT analysis revealed an average of 16.2 BCTs per app, ranging from 14 to 19. Common BCTs included goal setting, action planning, and self-monitoring. However, critical BCTs like biofeedback and graded tasks were absent. The MARS evaluation showed an overall average quality score of 3.66 out of 5, with functionality scoring highest (mean 4.36) and engagement lowest (mean 2.5). Only two apps had undergone scientific evaluation, indicating a gap in empirical validation.

Conclusions:

The initial search identified 1020 applications, narrowed down to six after applying the inclusion criteria. These apps had download ranges from 10,000 to over one million. Using CERT, all apps adhered to the FITT principle but failed to meet the FITT-VP principle due to the lack of exercise progression guidance. The BCT analysis revealed an average of 16.2 BCTs per app, ranging from 14 to 19. Common BCTs included goal setting, action planning, and self-monitoring. However, critical BCTs like biofeedback and graded tasks were absent. The MARS evaluation showed an overall average quality score of 3.66 out of 5, with functionality scoring highest (mean 4.36) and engagement lowest (mean 2.5). Only two apps had undergone scientific evaluation, indicating a gap in empirical validation.