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Enregistrement W4392588385 · doi:10.1111/add.16471

Commentary on Manthey <i>et al</i> .: No more missed opportunities—We need to address the absence of robust and comprehensive evaluations about the real‐world impact of statutory restrictions on alcohol marketing

2024· letter· en· W4392588385 sur OpenAlexaboutno aff
Nathan Critchlow

Notice bibliographique

RevueAddiction · 2024
Typeletter
Langueen
DomaineMedicine
ThématiqueSubstance Abuse Treatment and Outcomes
Établissements canadiensnon disponible
Organismes subventionnairesUniversity of StirlingSociety for the Study of Addiction
Mots-clésStatutory lawQuality (philosophy)Public healthMarketingScientific evidenceBusinessSocial marketingPublic relationsMedicinePolitical scienceLawNursing

Résumé

récupéré en direct d'OpenAlex

The pattern of inertia and missed opportunities for undertaking high-quality evaluations of real-world statutory restrictions on alcohol marketing is untenable. Jurisdictions planning to implement statutory restrictions for alcohol marketing must start doing so alongside high-quality, comprehensive and well-resourced research programmes. In a 2014 Cochrane Review, Siegfried and colleagues [1] concluded there was an absence of robust evidence for or against statutory restrictions on alcohol advertising. Ten years on, Manthey and colleagues [2] find this situation largely unchanged. This is despite the earlier review recommending that future restrictions be implemented alongside robust research programmes to ensure evaluation of all relevant outcomes over time [1]. That two reviews, published a decade apart, reach similar assessments about the state of the evidence comes down to a central and recurrent issue in alcohol marketing literature—we are not capitalising on opportunities to generate robust naturalistic data about the impact of these statutory restrictions. This is not intended to devalue the findings of existing research into alcohol marketing restrictions, which has improved markedly in recent years. There is now evidence that Norway's advertising ban reduced recorded alcohol sales [3], that Ireland's Public Health (Alcohol) Act reduced past-month awareness of some advertising activities among adults [4] and that France's Évin law on advertising content reduces positive reactions among young adults [5]. There is also recent evidence about the process of designing and implementing marketing restrictions in multiple European countries [6] and growing evidence of how companies circumvent restrictions using alibi and surrogate marketing [7-9]. These provide key insight into the application and impact of marketing restrictions and highlight the importance of considering outcomes beyond consumption, the focus of the two prior reviews. The principal issue, however, is that the overall evidence base remains disparate, with no single jurisdiction providing a comprehensive evaluation of their restrictions. Instead, studies are limited in terms of the outcomes considered, populations sampled and restrictions evaluated. There is also heterogeneity in the methods used, which creates challenges in comparing the relative impact of different degrees of restrictions (e.g. full bans, partial restrictions and content controls). Going forward, alcohol marketing restrictions should be accompanied by comprehensive evaluation programmes, making best use of naturalistic experimental designs that are well established as an appropriate way of evaluating the health impacts of policies, programmes and interventions [10]. These programmes should be guided by theories of change and logic models, involving structured identification of the key outcomes anticipated from the restrictions, the indicators needed to examine them (including differences among subpopulations) and the data required to ensure robust evaluation. For example, in addition to consumption, evaluations should consider changes in both marketing exposure and the key antecedents to alcohol use that are influenced by marketing (e.g. brand salience, motives and norms). The latter are particularly important to consider given the role they may play in mediating the impact of restrictions on consumption over time [11]. To interpret changes in consumer outcomes, or lack thereof, evaluations should also gather data on compliance, circumvention and displacement of marketing to unrestricted activities. Evaluations must also consider wider societal impacts, including positive and negative economic effects. Where possible, evaluations should incorporate counterfactual data, therefore isolating any impact of the restrictions from extraneous, confounding and competing factors. This is not an exhaustive agenda, simply an illustration of the gaps in current understanding. Our limited understanding about the real-world impact of alcohol marketing restrictions is brought into sharper focus when the state of the evidence is juxtaposed against the breadth and methodological rigour exhibited elsewhere in literature. In tobacco control, for example, restrictions on advertising, sponsorship, point-of-sale display and packaging have been evaluated using a variety of robust methods, including multi-country natural experiments, longitudinal surveys and other pre/post designs [12-16]. Tobacco control literature has also ensured evaluation across a spectrum of outcomes (e.g. awareness, salience and susceptibility) and among adult and youth populations. There are also examples in the wider alcohol policy literature of implementation being accompanied by extensive multi-method evaluation programmes, such as minimum unit pricing in Scotland [17] and warning labels in Yukon, Canada [18]. The pattern of inertia and missed opportunities for robustly evaluating statutory restrictions on alcohol marketing is untenable. Evidence must move forward to ensure future reviews can reach clear conclusions about the directional impact of such measures, rather than continually finding an absence of robust evidence either for or against. Maintaining this status quo is unhelpful for evidence-based policymaking. Jurisdictions with existing statutory restrictions are largely unable to evidence impact in response to continued challenge from critics, which may lead to restrictions being weakened over time [6, 19], nor are they able to monitor the continued efficacy of their restrictions in an ever-changing marketing landscape. For jurisdictions considering statutory restrictions, current evidence provides policymakers with little direct insight from which to make judgements about what they consider a proportionate response to the competing public health and economic arguments made around alcohol marketing. Jurisdictions planning statutory restrictions for alcohol marketing must, therefore, not continue to ignore the key recommendation of the 2014 Cochrane Review [1]—implement restrictions alongside high-quality, comprehensive and well-resourced research programmes, which ensure evaluation of all relevant outcomes over time to build the evidence base. Nathan Critchlow: Conceptualisation (lead); writing—original draft (lead); writing—review and editing (lead). Thanks to Dr Richard Purves and Prof Crawford Moodie, both from the Institute for Social Marketing and Health, University of Stirling, for their advice on this commentary. Between 2017 and 2022, N.C. was on the board of directors at Alcohol Focus Scotland. Since 2020, N.C. has been part of Alcohol Focus Scotland's expert network on alcohol marketing. The University of Stirling has received funds for consultancy work undertaken by N.C. for the Public Health Alcohol Research Group, which was appointed by the Minister for Health in Ireland to advise on monitoring and evaluating the Public Health (Alcohol) Act 2018, which contains restrictions on alcohol marketing. The University of Stirling has also received funding from the Institute of Public Health in Ireland to support Nathan Critchlow's fellowship research into the marketing restrictions under the Public Health (Alcohol) Act.

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 distillée sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.

score de la tête « metaresearch » (Codex)0,000
score de la tête « metaresearch » (Gemma)0,000
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Sans objet · Signal consensuel: Sans objet
GenreSignal candidat: Commentaire · Signal consensuel: Commentaire
Score de désaccord entre enseignants0,155
Score d'incertitude au seuil0,904

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0000,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,000
Études des sciences et des technologies0,0000,000
Communication savante0,0000,000
Science ouverte0,0000,000
Intégrité de la recherche0,0000,001
Charge utile insuffisante (le modèle a refusé de juger)0,0000,000

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 Opus0,109
Tête enseignante GPT0,362
Écart entre enseignants0,253 · 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; un appel candidat d’une seule tête enseignante, pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeSans objet
Domainenon disponible
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

Citations0
Publié2024
Routes d'admission1
Résumé présentoui

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