Using Theory and Practice to Develop Lottery Ticket Warning Messages as a Means of Promoting More Responsible Gambling
Notice bibliographique
Résumé
Background Playing the lottery is considered a public health concern in many countries due to financial losses associated with it, but also due to other harmful health and social problems. Focus of the article Informed by both theory and practice, this article focuses on developing lottery ticket warning messages targeting players harmed by excessive spending to promote sustainable behavior change. Research Question What should be communicated in lottery ticket warning messages targeting people at risk to facilitate behavior change and maintain it? Approach We bridge the gap between theory and practice and illustrate how theoretical models and current communications can shape messages. Specifically, we identify and examine lottery ticket warning messages and analyze their relative congruence to prevailing theories to assess the potential effectiveness of the messages and to recommend warning labels for lottery tickets. In addition, we incorporate knowledge used by cognitive psychologists in counselling to create warnings more likely to motivate and sustain behavior change. Importance to the Social Marketing Field Merging academic theory with existent communications ensures better knowledge translation and potentially better outcomes. Introducing verified techniques from Cognitive Behavior Therapy into social marketing initiatives could be a step forward into triggering behavior change. Methods A literature review was conducted to identify and select theoretical models appropriate to guide communications for lottery tickets harmful consumption. Searches were conducted to identify initiatives aiming at persuading and helping at-risk individuals to change their behavior in a healthy manner. Social marketing campaign messages were then compared with theoretical paradigms to identify ways in which campaign messages could be improved. Results Results show campaign messages were relatively consistent with some aspects of the theoretical models. Warning messages provide information that is relevant to the target audience and describe the severity and vulnerability of irresponsible consumption. They also attempt to decrease perceived costs and increase perceived self-efficacy in a variety of ways. Some also attempt to modify cognitive distortions the audience has in respect to chances of winning. However, initiatives should also increase consumers’ perceptions of the response-efficacy by emphasizing their agency, and further enhance individuals’ perception of self-efficacy by incorporating strategies from the Cognitive Model. Recommendations for Research and Practice Academics and practitioners can build on each other’s knowledge on an ongoing basis. By making it default to always consider both theory and practice, initiatives are likely to become more effective. Managers responsible for developing warning messages and implementing social marketing campaigns can experiment with the various theoretical approaches to determine which are comparatively more effective for their situations. Limitations Future research is needed to test the comparative effectiveness of these theories as a basis of creating persuasive warning messages.
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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 | 0,046 | 0,058 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,007 | 0,003 |
| Études des sciences et des technologies | 0,003 | 0,011 |
| Communication savante | 0,008 | 0,008 |
| Science ouverte | 0,004 | 0,006 |
| Intégrité de la recherche | 0,003 | 0,004 |
| 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 ».