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Record W2122112128 · doi:10.1080/13548500903281088

Predicting the effect of interactive video bikes on exercise adherence: An efficacy trial

2009· article· en· W2122112128 on OpenAlex
Ryan E. Rhodes, Darren E. R. Warburton, Shannon S. D. Bredin

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenuePsychology Health & Medicine · 2009
Typearticle
Languageen
FieldPsychology
TopicBehavioral Health and Interventions
Canadian institutionsUniversity of British ColumbiaUniversity of Victoria
FundersCanadian Institutes of Health ResearchDiabetes CanadaMichael Smith Health Research BCCanadian Diabetes Association
KeywordsAttendanceTheory of planned behaviorMediationPsychologySession (web analytics)PopularityVideo gamePhysical activityPhysical therapyClinical psychologyMedicineSocial psychologyMultimediaControl (management)

Abstract

fetched live from OpenAlex

Exercise games that employ video game technology are increasing in the marketplace but have received scant research attention despite their popularity. The purpose of this study was to evaluate the effect of videobike gaming on the constructs of the theory of planned behavior (TPB) and adherence in comparison to a cycling condition where participants listen to self-selected music. Participants were 29 inactive young men assigned randomly to experimental (n = 16) or comparison (n = 13) conditions. The recommended training regime consisted of moderate intensity activity (60-75% heart rate reserve), 3 days/week for 30 min/day for 6 weeks. At the end of the first session, participants were asked to complete TPB measures and these were subsequently measured 6 weeks later. Attendance was used as the measure of adherence. Results showed that affective attitude and adherence across the 6 weeks significantly favored the videobike condition over the comparison condition. Regression analyses suggested partial mediation of the effect of the videobike condition on adherence via affective attitude. This is the first study to provide evidence that interactive videobikes may improve adherence over traditional cycling because the activity produces higher affective attitudes. The results are promising for expanding to community-based evaluation.

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.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.850
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
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.087
GPT teacher head0.528
Teacher spread0.441 · 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