Interventions implemented through sporting organisations for promoting healthy behaviour or improving health outcomes
Bibliographic record
Abstract
BACKGROUND: Chronic diseases are the leading cause of mortality and morbidity worldwide. Much of this burden can be prevented by adopting healthy behaviours and reducing chronic disease risk factors. Settings-based approaches to address chronic disease risk factors are recommended globally. Sporting organisations are highly prevalent, and engage many people in many countries. As such, they represent an ideal setting for public health interventions to promote health. However, there is currently limited evidence of their impact on healthy behaviour and health outcomes as previous systematic reviews are either limited in their scope (e.g. restricted to professional sporting organisations), or are out of date. OBJECTIVES: Primary: to assess the benefits and harms of interventions implemented through sporting organisations to promote healthy behaviours (including physical activity, healthy diet) or reduce health risk behaviours (including alcohol consumption, tobacco use). Secondary: to assess the benefits and harms of these interventions to promote health outcomes (e.g. weight), other health-related behaviours (e.g. help-seeking behaviour) or health-related knowledge; to determine whether benefits and harms differ based on the characteristics of the interventions, including target population and intervention duration; to assess unintended adverse consequences of sporting organisation interventions; and to describe their cost or cost-effectiveness. SEARCH METHODS: We searched CENTRAL, MEDLINE, Embase, one other database and two clinical trial registries, from inception to May 2024, to identify eligible trials. We searched Google Scholar in May 2024. We did not impose language or publication status restrictions. We also searched reference lists of included trials for other potentially eligible trials. SELECTION CRITERIA: We included randomised controlled trials (RCTs), including cluster-RCTs, of any intervention conducted within or using a sporting organisation for access to a target group, that aimed to improve a health behaviour primary outcome or a secondary review outcome, and had a parallel control group (no intervention, alternative intervention). Eligible participants were any individual exposed to an intervention involving a sporting organisation, including players, members, coaches, and supporters. DATA COLLECTION AND ANALYSIS: We used standard methodological procedures expected by Cochrane. We conducted random-effects meta-analyses to synthesise results where we could pool data from at least two trials. Where we could not conduct meta-analysis, we followed Cochrane guidance for synthesis using other methods and reported results according to the Synthesis Without Meta-analysis (SWiM) guidance. MAIN RESULTS: = 78%; 7 trials, 2313 participants; very low-certainty evidence). Two trials that could not be synthesised reported equivocal findings on tobacco use (low-certainty evidence). The evidence is very uncertain about the effect of sporting club interventions on unintended adverse consequences. Five trials assessed this outcome, with two reporting that there were no adverse consequences, one reporting only non-serious adverse consequences, and two reporting that there were serious unintended adverse consequences in less than 1% of participants. AUTHORS' CONCLUSIONS: Overall, sporting organisation interventions probably increase MVPA by 7.4 minutes per day, may result in little to no difference in sedentary behaviour, and may increase fruit and vegetable consumption. The evidence is very uncertain about whether sporting organisation interventions decrease sugary drink and alcohol consumption. Findings for tobacco use and unintended adverse consequences were equivocal in the few trials reporting these; thus, the evidence was very uncertain. These findings should be interpreted in the context of the heterogeneity of the interventions, participants and sporting organisations for some outcomes.
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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 | 0.007 | 0.030 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.005 |
| Bibliometrics | 0.008 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.027 | 0.002 |
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".