Interventions implemented through sporting organisations for promoting healthy behaviour or improving health outcomes
Notice bibliographique
Résumé
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systematic reviews are either limited in their scope (e.g. restricted to professional sporting organisations), or are out of date.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.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,007 | 0,030 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,004 | 0,005 |
| Bibliométrie | 0,008 | 0,009 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,003 | 0,002 |
| Science ouverte | 0,001 | 0,002 |
| Intégrité de la recherche | 0,003 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,027 | 0,002 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».