Impact of Hockey Fans in Training Program on Steps and Self-rated Health in Overweight Men
Bibliographic record
Abstract
Football Fans in Training (FFIT) is an effective, gender-sensitized, weight loss and healthy living program for overweight/obese men, delivered via professional football clubs. Hockey Fans in Training (Hockey FIT) is a new program adapted from FFIT for Canadian hockey. PURPOSE: To examine the impact of Hockey FIT on steps, self-esteem, mood, and self-rated health, 12 weeks after baseline (post program). METHODS: 80 male fans [35-65 years; body mass index (BMI) ≥ 28 kg/m2] of 2 Ontario Junior A hockey clubs were randomized to either intervention (Hockey FIT) or comparator (wait-list control), within a pilot, pragmatic randomized controlled trial (RCT). Hockey FIT involved 12 weekly, 90-minute group sessions delivered by trained coaches using club facilities. Each session combined classroom material, including evidence-based behaviour change techniques (e.g., self-monitoring, goal setting) and healthy eating advice (e.g., reducing portion size), with physical activity sessions. Prescriptive exercise (e.g., individualized target heart rates and pedometer-based incremental step targets) was incorporated throughout. We examined between-group differences in mean steps/day (7-day pedometer monitoring), self-esteem (Rosenberg scale), positive and negative affect (I-PANAS-SF scale), and self-rated health (EQ-5D-3L VAS score) using linear mixed effects regression models that accounted for club and age. RESULTS: Groups were similar at baseline [median (interquartile range): age: 48.0 (17.0) years; BMI: 35.1 (6.3) kg/m2]. 75% of men in the intervention group attended ≥ 6 sessions. At 12 weeks, the intervention group increased their daily steps to a greater extent than the comparator [difference between groups in mean change: 3127 (95% confidence interval: 1882 to 4372) steps/day, p <0.001]. The intervention group also improved their self-rated health (scale 0 to 100; 100 = best) to a greater extent than the comparator [difference between groups in mean change: 7.0 (2.1 to 11.9) points, p = 0.005]. There were no differences between groups in self-esteem or positive/negative affect post program. CONCLUSION: Hockey FIT has the potential to help overweight/obese men increase their physical activity levels and improve their self-rated health. Long-term follow-up and a full-scale pragmatic RCT is 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 | 0.001 | 0.001 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".