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Record W4390284512 · doi:10.1123/jege.2023-0016

The Effect of Extended Reality Exercise on Physical Activity and Physical Performance in Children and Youth: A Scoping Review

2023· review· en· W4390284512 on OpenAlexaff
Simon Schaerz, Morgan Boyes, Amanda Mohamed

Bibliographic record

VenueJournal of Electronic Gaming and Esports · 2023
Typereview
Languageen
FieldHealth Professions
TopicSports and Physical Education Research
Canadian institutionsLethbridge College
Fundersnot available
KeywordsPhysical activityPsychologyTypically developingDevelopmental psychologyPreferenceMedicinePhysical medicine and rehabilitation

Abstract

fetched live from OpenAlex

Physical activity is vital for children’s and youth’s healthy growth and development. Despite the physical, psychological, and social benefits, many children and youth are not physically active enough. Extended reality exercise (XRE), which incorporates virtual, augmented, and mixed reality exercise-based gaming, has been touted as a possible tool for not only promoting physical activity but also developing physical performance. Accordingly, we conducted a five-stage scoping review to identify themes and gaps in the literature pertaining to the application of XRE in physical activity-related research. We identified a positive impact of XRE on physical activity and performance in children and youth, including those with and without impairments, with a predominant preference for nonimmersive virtual reality in the majority of studies. There is a paucity of studies that specifically investigate the effects of XRE on physical activity in impaired children and youth. Likewise, more research is needed to determine how XRE can be leveraged to develop physical performance in nonimpaired children and youth. There is also a need for more large-sample studies that incorporate fully immersive XRE.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.953
Threshold uncertainty score0.791

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.002
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 head0.073
GPT teacher head0.502
Teacher spread0.429 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designOther design
Domainnot available
GenreReview

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

Citations2
Published2023
Admission routes1
Has abstractyes

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