Scale-Up and Scale-Out of a Gender-Sensitized Weight Management and Healthy Living Program Delivered to Overweight Men via Professional Sports Clubs: The Wider Implementation of Football Fans in Training (FFIT)
Bibliographic record
Abstract
Increasing prevalence of obesity poses challenges for public health. Men have been under-served by weight management programs, highlighting a need for gender-sensitized programs that can be embedded into routine practice or adapted for new settings/populations, to accelerate the process of implementing programs that are successful and cost-effective under research conditions. To address gaps in examples of how to bridge the research to practice gap, we describe the scale-up and scale-out of Football Fans in Training (FFIT), a weight management and healthy living program in relation to two implementation frameworks. The paper presents: the development, evaluation and scale-up of FFIT, mapped onto the PRACTIS guide; outcomes in scale-up deliveries; and the scale-out of FFIT through programs delivered in other contexts (other countries, professional sports, target groups, public health focus). FFIT has been scaled-up through a single-license franchise model in over 40 UK professional football clubs to 2019 (and 30 more from 2020) and scaled-out into football and other sporting contexts in Australia, Canada, New Zealand, England and other European countries. The successful scale-up and scale-out of FFIT demonstrates that, with attention to cultural constructions of masculinity, public health interventions can appeal to men and support them in sustainable lifestyle change.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".