MétaCan
Menu
Retour à la cohorte
Enregistrement W4388616027 · doi:10.1111/add.16369

‘No evidence of harm’ implies no evidence of safety: Framing the lack of causal evidence in gambling advertising research

2023· letter· en· W4388616027 sur OpenAlexafffundabout
Philip Newall, Youssef Allami, Maira Andrade, Peter Ayton, Rosalind Baker, Daniel Bennett, Matthew Browne, Christopher Bunn, Reece Bush‐Evans, Sonia Chen, Sharon Collard, Steffi De Jans, Jeffrey L. Derevensky, Nicki A. Dowling, Simon Dymond, Andrée Froude, Elizabeth Goyder, Robert Heirene, Nerilee Hing, Liselot Hudders, Kate Hunt, Richard J. E. James, En Li, Elliot A. Ludvig, Virve Marionneau, Ellen McGrane, Stephanie Merkouris, Jim Orford, Alberto Parrado‐González, Robert Pryce, Matthew Rockloff, Ulla Romild, Raffaello Rossi, Alex Russell, Henrik Singmann, Trudy Smit Quosai, Sasha Stark, Aino Suomi, Thomas B. Swanton, Niri Talberg, Volker Thoma, Jamie Torrance, Catherine Tulloch, Ruth J. van Holst, Lukasz Walasek, Heather Wardle, Jane West, Jamie Wheaton, Leon Y. Xiao, Matthew M. Young, Maria Bellringer, Steve Sharman, Amanda Roberts

Notice bibliographique

RevueAddiction · 2023
Typeletter
Langueen
DomainePsychology
ThématiqueGambling Behavior and Treatments
Établissements canadiensCarleton UniversityCanadian Centre on Substance Use and AddictionGreoMcGill UniversityUniversity of Calgary
Organismes subventionnairesEconomic and Social Research CouncilMedical Research CouncilAlberta Gambling Research Institute, University of CalgaryResponsible Gambling FundGambling Research Exchange OntarioHealth Research Council of New ZealandGambleAwareQueensland GovernmentMovember FoundationMinistry of Health, New ZealandDeakin UniversityDepartment of Social Services, Australian GovernmentNational Health and Medical Research CouncilOntario Ministry of Health and Long-Term CareNational Institute for Health and Care ResearchInternational Center for Responsible GamingGovernment of South AustraliaAustralian GovernmentUniversity of BristolHealth and Care Research Wales
Mots-clésHarmFraming (construction)PsychologyAdvertisingSocial psychologyCriminologyBusinessEngineering

Résumé

récupéré en direct d'OpenAlex

Gambling advertising is a common feature in international jurisdictions that have liberalized gambling. In the Anglosphere, countries such as Australia, New Zealand and the United Kingdom have experienced extensive gambling advertising during the past decade. This advertising is particularly prominent in relation to professional sports and lottery products. More recently, some Canadian provinces and US states have also witnessed a similar rise in gambling advertising. Several European governments, including Belgium, Italy, Netherlands and Spain, have more recently restricted gambling advertising and sponsorship in professional sports, but the UK government did not announce any action on gambling advertising and sponsorship in its 2023 White Paper. In September 2023, the UK's Minister for Sport, Gambling and Civil Society addressed a governmental select committee, stating: ‘We have very much gone on the evidence, and there's little evidence that exposure to advertising alone causes people to enter into gambling harm’ [1]. This is consistent with the position of the main UK gambling industry trade body, which frequently states in the media that there is ‘no evidence’ linking gambling advertising to harm [2]. We are a group of stakeholders writing to say that this is a misleading framing of the underlying evidence base. It would be equally true to say that there is no evidence demonstrating gambling advertising's safety. This supposed lack of causal evidence (a point contested by some academics [3]) is simply an absence of evidence due to methodological difficulties inherent to gambling advertising research. Importantly, there is also no evidence of an absence of an effect. People are exposed to gambling advertising in their daily lives, and yet the majority of the research community lacks access to the gambling operator data which could be used to investigate longitudinal relationships [4]. Causality is often best tested for via well-controlled laboratory experiments, and yet no contrived experiment can recreate the experience of being exposed to—and potentially influenced by—gambling advertising during one's daily life. Despite these methodological challenges regarding causality, gambling researchers have assembled a wealth of evidence on other aspects of gambling advertising. Gambling advertising can be highly prevalent, especially around live sport [5, 6]; features certain distinct types of content which use a variety of psychological hooks [5, 6], and is often perceived poorly by its recipients [5, 6]. Research has also linked self-reported advertising exposure and gambling [7-9], especially among disordered gamblers, and linked the use of wagering inducements to gambling behaviour using data from an on-line gambling operator [10]. Evidence also suggests that the safer gambling messages found in many gambling adverts are unlikely to counteract any potential harms from advertising [11, 12]. In time, econometric analyses might be run to test for causal reductions in gambling harm from various governmental restrictions on gambling advertising. Policy decisions regarding gambling advertising should not necessitate evidence of a direct causal link to change the status quo, as those who argue that gambling advertising is safe have not been held to the same evidential standard.

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 enseignants

Ni 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.

score de la tête « metaresearch » (Codex)0,469
score de la tête « metaresearch » (Gemma)0,627
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesMétarecherche
Catégories consensuellesMétarecherche
DomaineSignal candidat: Méthodes · Signal consensuel: aucune
Devis d'étudeSignal candidat: Théorique ou conceptuel · Signal consensuel: Théorique ou conceptuel
GenreSignal candidat: Commentaire · Signal consensuel: Commentaire
Score de désaccord entre enseignants0,531
Score d'incertitude au seuil0,655

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,4690,627
Méta-épidémiologie (sens strict)0,0030,004
Méta-épidémiologie (sens large)0,0070,003
Bibliométrie0,0200,010
Études des sciences et des technologies0,0110,140
Communication savante0,0280,050
Science ouverte0,0120,022
Intégrité de la recherche0,0660,059
Charge utile insuffisante (le modèle a refusé de juger)0,0040,001

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.

Tête enseignante Opus0,487
Tête enseignante GPT0,526
Écart entre enseignants0,039 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_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 découle

Classification

machine, non validée

Prédiction automatique; l’étiquette directe de Gemma et le classifieur distillé Codex s’accordent sur ce qui est montré ici.

Devis d'étudeThéorique ou conceptuel
DomaineMéthodes
GenreCommentaire

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations28
Publié2023
Routes d'admission3
Résumé présentoui

Explorer davantage

Même revueAddictionMême sujetGambling Behavior and TreatmentsTravaux en français237 207