Can a Sports Team-based Lifestyle Program (Hockey Fans In Training) Improve Weight In Overweight Men?
Bibliographic record
Abstract
The issue of gender is often neglected when planning and implementing chronic disease prevention and management strategies. Football Fans in Training (FFIT) — a gender-sensitized, weight loss and healthy living program for men delivered via professional football clubs — has been shown to be highly effective in helping overweight/obese men lose weight and improve their health risk. PURPOSE: To examine the potential for new male-friendly, physical activity and healthy living program — Hockey Fans in Training (Hockey FIT) — to help overweight/obese men decrease their weight, waist circumference (WC), and body mass index (BMI), after 12 weeks. METHODS: A pilot, pragmatic randomized controlled trial (RCT) whereby male fans (35-65 years; BMI ≥ 28 kg/m2) of 2 Junior A hockey clubs (Ontario, Canada) were randomized to either the intervention (Hockey FIT) or comparator (wait-list control). Hockey FIT involved 12 weekly, 90-minute group sessions delivered by trained coaches using club facilities. Each session combined classroom activities, including evidence-based behaviour change techniques (e.g., self-monitoring, goal setting) and healthy eating advice (e.g., reducing portions), with physical activity training. Lifestyle prescriptions, including incremental step count targets, were also prescribed each week. We examined between-group differences in mean weight loss, WC, and BMI using linear mixed effects regression models that accounted for club and age. RESULTS: Baseline characteristics were similar between groups [total N = 80, median (interquartile range) — i) age: 48.0 (17.0) years; ii) weight: 112.2 (23.2) kg; iii) WC: 119.3 (13.5) cm; iv) BMI: 35.1 (6.3) kg/m2]. Of the 40 men in the Hockey FIT group, 30 (75%) attended at least 6 sessions. At 12 weeks, the Hockey FIT group lost more weight than the control group [difference between groups in mean weight change (control is reference): -3.6 (95% confidence interval: -5.2 to -1.9) kg, p<0.001]. The Hockey FIT group also saw greater reductions in WC and BMI, when compared to the control group [difference between groups in mean i) WC: -2.8 (-5.0 to -0.6) cm, p=0.01; ii) BMI: -0.9 (-1.4 to -0.4) kg/m2, p<0.001]. CONCLUSION: Hockey FIT has the potential to help overweight/obese men lose weight and improve health risk. A definite RCT is warranted with long-term follow-up.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".