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Record W2106500172 · doi:10.1123/jpah.10.2.211

Testing the Effectiveness of Exercise Videogame Bikes Among Families in the Home-Setting: A Pilot Study

2013· article· en· W2106500172 on OpenAlexafffund
Rachel Mark, Ryan E. Rhodes

Bibliographic record

VenueJournal of Physical Activity and Health · 2013
Typearticle
Languageen
FieldPsychology
TopicChildren's Physical and Motor Development
Canadian institutionsUniversity of Victoria
FundersSocial Sciences and Humanities Research Council of CanadaCanadian Institutes of Health ResearchUniversity of VictoriaCanadian Diabetes Association
KeywordsPhysical therapyMedicinePilot trialPhysical medicine and rehabilitationPsychologyGerontologyRandomized controlled trial

Abstract

fetched live from OpenAlex

BACKGROUND: Interactive stationary bikes provide positive affective experiences and physiological benefits; however, research is limited. METHODS: This study compared usage of GameBikes to traditional stationary bikes among families in the home following a 6-week randomized, controlled trial design. Parents completed questionnaires featuring constructs of the theory of planned behavior (TPB). Usage was tracked by all family members and belief elicitation with GameBike families followed the trial. RESULTS: Usage across the trial was significantly different for children in favor of the GameBike group (t36 = 2.61, P = .01, d = .85). No differences were identified for parents. Significant time effects for parents' (F5,48 = 5.07, P < .01; η2 = .35) and children's (F5,32 = 8.24, P < .01; η2 = .56) usage were found with declines across 6 weeks. Affective attitude was the only significant TPB variable between groups at both time one (t57 = 2.53, P = .01; d = .65) and follow-up (t52 = 2.70, P = .01; d = .74) in favor of the GameBike group. Elicited beliefs were primarily affective-and control-based. CONCLUSIONS: The results provide support for use of interactive video games to augment current PA initiatives. Larger-scale trials with longer durations are warranted.

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)0.002
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.329
Threshold uncertainty score0.461

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.044
GPT teacher head0.329
Teacher spread0.285 · 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 designObservational
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

Citations25
Published2013
Admission routes2
Has abstractyes

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