MétaCan
Menu
Back to cohort
Record W2924602208 · doi:10.2196/11689

A Mobile App to Promote Adapted Exercise and Social Networking for People With Physical Disabilities: Usability Study

2019· article· en· W2924602208 on OpenAlexvenueno aff
Byron Lai, Jereme Wilroy, Hui‐Ju Young, Jennifer Howell, James H. Rimmer, Tapan Mehta, Mohanraj Thirumalai

Bibliographic record

VenueJMIR Formative Research · 2019
Typearticle
Languageen
FieldHealth Professions
TopicMobile Health and mHealth Applications
Canadian institutionsnot available
FundersEunice Kennedy Shriver National Institute of Child Health and Human Development
KeywordsUsabilityThematic analysisApplied psychologyPsychologyMultimediaQualitative researchComputer scienceHuman–computer interaction

Abstract

fetched live from OpenAlex

BACKGROUND: People with physical disabilities (PWD) experience several unique challenges that prevent them from participating in onsite exercise programs. Although mobile apps can provide a ubiquitous channel for delivering convenient exercise services within the community, no exercise apps have been designed for people with disabilities who experience certain functional limitations. OBJECTIVE: The aim of this study was to examine the usability of a mobile exercise app in PWD. METHODS: A sequential explanatory mixed-method design was used to holistically test usability in 4 core areas: effectiveness (ie, ease of use), efficiency (ie, operation speed), perceived satisfaction, and usefulness. Participants completed 7 face-to-face usability tasks and 1 structured interview. Equipment included a computer tablet that came preinstalled with the exercise app. The app included exercise videos that focused on several components of fitness: aerobic capacity, muscular strength, functional strength or balance, and range of motion. The app contained 3 different versions of the exercise program: (1) a program for people with the ability to use the upper and lower limbs, (2) a seated program for people with the ability to use only upper limbs, and (3) a program designed for people with hemiparesis. The app also included educational resources in the form of infographics aimed at addressing key social cognitive theory constructs included social support, outcome expectancies, self-efficacy, and barriers or facilitators to exercising. Participant characteristics and quantitative usability data were descriptively reported. Qualitative data were analyzed using thematic analysis. RESULTS: A total of 12 PWD tested the usability of the exercise app and completed 96% (69/72) of the usability tasks on the first attempt. Operation speed varied among users, which prompted the development team to make minor revisions to the app. Qualitative results demonstrated 3 overarching themes: facilitates exercise adoption, positive experiences of videos, and easy to learn. Participants noted that the app circumvented several barriers to exercise associated with leaving the home (eg, inclement weather conditions, exacerbations of health conditions or disability symptoms, difficulties with transportation, and social support). CONCLUSIONS: The mobile exercise app provided a simple platform that was effective, useful, and appreciated by PWD. Participants also perceived the app as easy to use and felt it was a valuable tool for assisting PWD to obtain regular exercise. Study findings also offered insight into the participants' preferences for mobile exercise apps that can aid future research and development projects. Future exercise trials are needed to determine the true impact of mobile app technology on lifestyle physical activity in people with disabilities. TRIAL REGISTRATION: Clinicaltrials.gov NCT03024320; https://clinicaltrials.gov/ct2/show/NCT03024320 (Archived by WebCite at http://www.webcitation.org/75hNLgRFH).

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.299
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0020.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.085
GPT teacher head0.504
Teacher spread0.419 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designQualitative
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations26
Published2019
Admission routes1
Has abstractyes

Explore more

Same venueJMIR Formative ResearchSame topicMobile Health and mHealth ApplicationsFrench-language works237,207