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Record W4408464668 · doi:10.2196/65801

School-Based Virtual Reality Programming for Obtaining Moderate-Intensity Exercise Among Children With Disabilities: Pre-Post Feasibility Study

2025· article· en· W4408464668 on OpenAlexvenueno aff
Byron Lai, Ashley Wright, Bailey Hutchinson, Larsen Bright, Raven Young, Drew Davis, Sultan Ali Malik, James H. Rimmer

Bibliographic record

VenueJMIR Formative Research · 2025
Typearticle
Languageen
FieldMedicine
TopicSpinal Cord Injury Research
Canadian institutionsnot available
FundersNational Institute on Minority Health and Health Disparities
KeywordsPreprintVirtual realityPsychologyComputer scienceGerontologyMedicineHuman–computer interactionWorld Wide Web

Abstract

fetched live from OpenAlex

Background: Children have busy daily schedules, making school an ideal setting for promoting health-enhancing exercise behavior. However, children with mobility disabilities have limited exercise options to improve their cardiorespiratory fitness and cardiometabolic health. Objective: This study aims to test the feasibility of implementing a virtual reality (VR) exercise program for children with mobility disabilities in a high school setting. Methods: A pre- to posttrial single-group design with a 6-week exercise intervention was conducted at a high school. The study aimed to enroll up to 12 students with a disability. Participants were given the option of exercising at home or school. The exercise prescription was three 25-minute sessions per week at a moderate intensity, using a head-mounted VR display. School exercise sessions were supervised by research staff. Home exercise sessions were performed autonomously. Several implementation metrics of feasibility were recorded, including exercise attendance, volume, adverse events or problems, and benefits related to health-related fitness (walking endurance and hand-grip strength). The study also included a qualitative evaluation of critical implementation factors and potential benefits for participants that were not included in the study measures. Outcomes were descriptively analyzed, and 2-tailed t tests were used as appropriate. Results: In total, 10 students enrolled in the program and 9 completed the study (mean age 17, SD 0.6 y). In total, 5 (56%) participants exercised at school, and 4 (44%) exercised at home; 1 participant dropped out prior to exercise. The mean attendance for all 9 completers was 61.1% (11/18 sessions). The mean exercise minutes per week was 35.5 (SD 22) minutes. The mean move minutes per session was 17.7 (SD 11) minutes. The mean minutes per session was 18 (SD 1.4) minutes for school exercisers and 17 (SD 18) minutes for home exercisers, indicating variable responses from home exercisers. The mean rating of perceived exertion per exercise session was 4.3 (SD 2), indicating a moderate intensity that ranged from low to hard intensity. No adverse events or problems were identified. No improvements in walking endurance or hand-grip strength were observed. School exercisers achieved a higher attendance rate (83%) than home exercisers (27%; P<.001) and seemingly had a 2-fold increase in the volume of exercise achieved (school: mean 279, SD 55 min; 95% CI 212-347; home: mean 131, SD 170 min; 95% CI -140 to 401; P=.10). Qualitative themes relating to implementation factors and benefits to participant well-being were identified. Conclusions: This study identified factors to inform an optimal protocol for implementing a high school-based VR exercise program for children with disabilities. Study findings demonstrated that moderate exercise at school is feasible in VR, but simply providing children with VR exergaming technology at home, without coaching, will not successfully engage them in exercise.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.005
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Non-randomized trial · Consensus signal: Non-randomized trial
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.028

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.006
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.093
GPT teacher head0.469
Teacher spread0.375 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNon-randomized trial
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

Citations3
Published2025
Admission routes1
Has abstractyes

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