An uneven playing field: A mixed methods, multiphase feasibility study of a programme to reduce gambling among at-risk men in a professional football club setting
Notice bibliographique
Résumé
BackgroundSports betting is a growth area for the gambling industry, with football fans a key target ofadvertising. Men are particularly at risk from gambling harm. Prior research has shown thatthe delivery of health behaviour-related interventions through professional football clubscan attract and support health behaviour change among men. The 8-week Football Fansand Betting (FFAB) programme was designed as an early health behaviour changeintervention for delivery in professional football clubs by club community coaches toreduce their sports betting and other forms of gambling among men aged 18-55 with aPGSI score of 15 and under. This paper reports the acceptability and feasibility of delivering thisprogramme in football clubs in England.MethodsThe FFAB feasibility study’s objectives were to determine whether FFAB has the potentialto reduce gambling behaviour by assessing: 1) recruitment to and retention in theprogramme, 2) the acceptability of FFAB to both club coaches and participants, and 3) togather preliminary evidence on potential impact. To meet aim 1, we initiated recruitmentat 6 clubs and recorded recruitment data throughout, and conducted focus groups onrecruitment materials with fans of Club C-F. For aim 2, we collected data on retentionthroughout our programme deliveries. For aim 3, we completed delivery of FFAB at asmany clubs as possible (n=3); observed the delivery of sessions; completed semi-structuredinterviews with coaches, participants, and non-completers.Results1) Recruitment to the programmeRecruiting the intended number of participants proved highly challenging. This was partly dueto the commercial landscape, where sponsorship by gambling companies lessened club interestin the programme. Even in clubs without direct gambling sponsors, FFAB ads struggled forvisibility against more prominent gambling sponsorships in stadiums. Moreover, stigmasurrounding gambling harm hindered participant recruitment and retention, compounded bybroader commercial challenges. Engaging the target group of the FFAB model was difficultbecause they perceived gambling as normal, making it challenging to connect with FFAB'sobjectives.2) Retention in the programmeRetention to the programme faced similar challenges as recruitment – the commercial landscapeand stigma being key challenges FFAB did not overcome. Retention at our first two programmedeliveries struggled. The final delivery used a more local-hub approach to recruitment andbolted FFAB’s classroom element on to an existing social football game and was successful inretaining its small cohort from session 0-9.3) The acceptability of FFAB to both club coaches and participantsCoaches and participants reported that FFAB was acceptable and that there is a need forearly intervention delivered in this setting. Participants who went through the programmeand the coaches who delivered it reported positive experiences of FFAB.4) Gather preliminary data on potential impactAlthough we were able to carry out our research the FFAB programme facedchallenges. This meant that it was not possible to progress to an RCT to assess impactas intended. However preliminary data from men who completed the programmesuggest that 1) there is a need for an intervention to help men address gambling harm inthe sports space, 2) these men are an underserved population, with sometimes complexneeds, and 3) they often do not recognise the signs of gambling harm and experiencestigma around their behaviour.ConclusionsWe found that FFAB was acceptable to the coaches who delivered it and the participantswho attended. However, our model for recruitment did not work. We also faced difficultieswith retention. More feasibility work to develop a different approach to a gamblingreduction with men between 18-55 with a PGSI score of less than 15 is required.
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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 | 0,013 | 0,009 |
| Méta-épidémiologie (sens strict) | 0,002 | 0,002 |
| Méta-épidémiologie (sens large) | 0,002 | 0,001 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,004 | 0,002 |
| Communication savante | 0,002 | 0,002 |
| Science ouverte | 0,002 | 0,002 |
| Intégrité de la recherche | 0,003 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,005 | 0,001 |
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 ».