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Record W4298091984 · doi:10.2196/42651

Group Telegaming Through Immersive Virtual Reality to Improve Mental Health Among Adolescents With Physical Disabilities: Pre- and Posttrial Protocol

2022· article· en· W4298091984 on OpenAlexvenueno aff
Byron Lai, Drew Davis, Raven Young, Erin Swanson‐Kimani, Cynthia Wozow, Kelli Chaviano, James H. Rimmer

Bibliographic record

VenueJMIR Research Protocols · 2022
Typearticle
Languageen
FieldMedicine
TopicTelemedicine and Telehealth Implementation
Canadian institutionsnot available
Fundersnot available
KeywordsLonelinessPsychologyLikert scaleMental healthClinical psychologyFeelingDevelopmental psychologyPsychiatrySocial psychology

Abstract

fetched live from OpenAlex

BACKGROUND: Adolescents with physical disabilities have higher rates of mental health conditions and issues than adolescents without disabilities, and this disparity was exacerbated by the onset of the COVID-19 pandemic. They also have limited access to on-site programs and nearby peers. OBJECTIVE: This pilot aims to investigate the potential effects of a low-dose multiplayer virtual reality telegaming program on depression, socialization, and loneliness among a cohort of children with physical disabilities. A secondary aim is to describe feasibility metrics, namely, recruitment and adherence rates and perceived program enjoyment and satisfaction. The tertiary aim is to describe behavioral mechanisms that affect participant adherence and social participation in the classes. METHODS: This study is a single-group pre- and posttest-designed trial. A single cohort of 12 children with physical disabilities will pilot a 1-month program that includes 2 supervised 1-hour sessions per week of group-based exergaming. Participants will complete questionnaires before and after the program. The primary aim measures will include the Children's Depression Inventory 2 Short Form, a measure of feelings of depression, and the UCLA Loneliness Scale, a measure of both loneliness and social isolation. Secondary aim measures will include three posttest Likert scale questionnaires: perceived program enjoyment, program satisfaction, and satisfaction with multiplayer experiences. At postintervention or dropout, participants will undergo semistructured interviews to identify behavioral mechanisms that underlie participation. Data will be reported descriptively and be supported by t tests as appropriate. RESULTS: Recruitment procedures started in July 2022. All data are expected to be collected by January 2023. Full trial results are expected to be published by March 2023. Secondary analyses of data will be subsequently published. CONCLUSIONS: This trial tests a peer-to-peer virtual reality telegaming program that includes a completely remote enrollment, assessment, and intervention protocol. This program is accessible and short in duration and frequency, allowing it to be integrated into other interventions. Knowledge obtained from this study will inform the development of a larger trial for improving the mental health and well-being of adolescents with physical disabilities. TRIAL REGISTRATION: ClinicalTrials.gov NCT05259462; https://clinicaltrials.gov/ct2/show/NCT05259462. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): PRR1-10.2196/42651.

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)0.011
metaresearch head score (Gemma)0.012
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: none
GenreCandidate signal: Protocol · Consensus signal: Protocol
Teacher disagreement score0.047
Threshold uncertainty score0.156

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0110.012
Meta-epidemiology (narrow)0.0030.002
Meta-epidemiology (broad)0.0050.002
Bibliometrics0.0020.001
Science and technology studies0.0030.002
Scholarly communication0.0010.002
Open science0.0030.002
Research integrity0.0030.005
Insufficient payload (model declined to judge)0.0470.006

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 head0.134
GPT teacher head0.547
Teacher spread0.413 · 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
GenreProtocol

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

Citations5
Published2022
Admission routes1
Has abstractyes

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