Testing the Effectiveness of Exercise Videogame Bikes Among Families in the Home-Setting: A Pilot Study
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".