The effects of a pedometer-based intervention on first-year university students: A randomized control trial
Bibliographic record
Abstract
OBJECTIVES: To assess the effects of a 12-week pedometer-based intervention on the physical activity behavior, health-related quality of life (HRQOL), and psychological well-being of first-year university students. PARTICIPANTS: First-year university students (N = 184) were recruited during September 2012 and randomly assigned to an intervention or a control group. METHODS: Intervention participants were provided with a pedometer, monthly tracking logs, and follow-up e-mails. Control participants received no intervention. Physical activity, HRQOL, and psychological well-being were measured at baseline and post intervention. Data were analyzed using multivariate/univariate analysis of variance (MANOVA/ANOVA). RESULTS: All participants experienced an increase in mild physical activity (p < .01) from baseline to follow-up. The intervention failed to produce significant differences between groups for physical activity (p = .28), HRQOL (p = .80), or psychological well-being (p = .72). Psychological well-being (p < .001), vigorous physical activity (p = .04), and mental health status (p < .001) decreased across the duration of the study. CONCLUSIONS: More intensive interventions may be required to elicit physical activity behavior change.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.009 | 0.001 |
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".