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Enregistrement W1658877854 · doi:10.1111/add.12548

The importance of tobacco research focusing on marginalized groups

2014· editorial· en· W1658877854 sur OpenAlexaboutno aff
Megan Passey, Billie Bonevski

Notice bibliographique

RevueAddiction · 2014
Typeeditorial
Langueen
DomaineMedicine
ThématiqueSmoking Behavior and Cessation
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésTobacco usePolitical scienceEnvironmental healthPsychologyMedicine

Résumé

récupéré en direct d'OpenAlex

Research on tobacco use in marginalized groups with high smoking prevalence should receive greater priority for publication in high-impact journals, not just because of the tobacco-related harm these populations experience, but also because of the greater understanding such research can provide on what drives tobacco use and undermines quitting in the human population generally. Tobacco use in many high-income countries is increasingly dominated by marginalized groups that experience the greatest social and economic disadvantage. These include Indigenous people, homeless people, those with substance abuse or mental illness and those of low socio-economic status 1. Smoking adds to the disadvantage experienced by these groups, further exacerbating health, social and financial inequities 2. The increasing disparities in smoking rates suggest that current tobacco control approaches, and the science on which they are based, do not adequately meet the needs of these populations. Despite the heightened smoking-related burden, research with marginalized groups continues to represent a small proportion of published tobacco research 3. Intervention studies providing an evidence base for effective tobacco dependence treatments for these smokers are scarce 3, 4. There is also a sense that high-impact journals have a tendency to consider manuscripts addressing some marginalized groups (e.g. Indigenous populations) as occupying a specialist niche of low priority. Here we outline some of the main benefits of tobacco research with marginalized groups and argue for greater priority for research in this area and for it to be considered as a priority for publication in high-impact journals. The excessive smoking prevalence among disadvantaged groups is striking. General adult population smoking rates in the United Kingdom, United States, Canada, New Zealand and Australia range from 16 to 21% 4. However, across countries, smoking prevalence ranges from 68 to 89% among homeless populations, from 30 to 62% among people with mental illness and from 56 to 93% among people with substance use disorders 4. The reasons for these disparities are complex and poorly understood. Smokers from disadvantaged groups report higher rates of uptake with earlier initiation, heavier nicotine dependence and lower rates of cessation 2. UK research shows that lower socio-economic smokers make as many quit attempts and are as motivated to quit as the more advantaged, but are less successful at achieving cessation 5. Others report that financially stressed smokers have greater interest in quitting, but make fewer quit attempts 6. Understanding the factors which undermine motivation to try to quit, or success when cessation is attempted, and how these vary by socio-economic status, will yield valuable information for targeting cessation treatments. Similarly, little is known about the drivers of smoking among marginalized groups, which may vary depending on the socio-cultural context and values of the group 7. For example, the socio-cultural drivers of smoking for people from a marginalized ethnic group may well be different from those for people with severe mental illness or homeless people. This suggests that a ‘one size fits all’ approach may be inappropriate, and that multiple frameworks are needed. Research among one marginalized group may also inform development of further research in other settings, building the evidence regarding the diversity of drivers of smoking in different socio-cultural groups. This enables greater understanding of the commonalities and differences across the human population, contributing to a more comprehensive science of addictive behaviour. Applying interventions known to reduce overall smoking behaviour will not necessarily reduce inequalities, as some interventions impact negatively upon the most disadvantaged 8. Ceci & Papiemo argue that in order to address health disparities, interventions that are tailored for each marginalized group are needed 9. However, most primary research and systematic reviews do not assess the differential effectiveness of tobacco cessation interventions across socio-cultural groups 10. A recent systematic review of peer-support programmes for smoking cessation in disadvantaged groups suggests that these may have greater value for disadvantaged than advantaged groups, particularly those with less access to informal support 11. A meta-analysis of smoking cessation behavioural interventions in six marginalized groups found 32 controlled trials (n = 1 homeless, n = 2 Indigenous populations, n = 1 prisoners, n = 6 at-risk youth, n = 12 low-income groups, n = 10 mental illness). The included studies showed promising effectiveness of behavioural interventions for some groups; however, few studies were available within each group. Poor access and reach also probably contribute to reduced impact of smoking cessation services. Greater research effort into ways to increase the reach of existing cessation treatments and improve access for marginalized groups will yield useful information. For example, traditional health-care settings may not be the best access point, and more innovative settings, such as social welfare agencies 12, drug and alcohol services 13 or homeless shelters 14 may prove more fruitful. The primary purpose of tobacco control research is to underpin the development of policies and programmes that reduce population smoking rates and address inequalities. A number of recent literature reviews have challenged the effectiveness of tobacco control policies at achieving equity 8, 15. The only strategy identified by these reviews as reducing inequities was taxation. Many other commonly implemented tobacco control strategies such as smoke-free environments, media campaigns, health warnings and community-wide cessation support either showed mixed effects, had limited evidence or exacerbated inequities. Similarly, a review of European smoking cessation support found that non-targeted cessation services generally have a negative equity impact, but that services targeted specifically to disadvantaged groups in the United Kingdom were reducing inequities 16. Graham has also identified the importance of examining the unintended, inequitable consequences of smoking cessation policies, such as increasing the stigmatization of smokers themselves 17. These reviews highlight the need for research which evaluates the equity impact of population-level tobacco control measures, including unintended consequences, as well as research that improves understanding of the varied drivers of smoking among marginalized groups to inform targeting of strategies more effectively. While there are clear benefits to conducting tobacco research with marginalized groups, there are also many challenges. Most groups with the highest smoking rates are ‘hard-to-reach’ and consequently present methodological challenges in sampling, recruitment, retention, literacy and compliance 18. These and other challenges make research with most marginalized groups both difficult and resource-intensive. Methodological research to validate innovations is needed to support rigorous research in this area. The full range of research designs will be necessary in developing understanding of how and why theoretically developed interventions have less impact than expected, and identifying more appropriate approaches 19. Research focusing on interventions with marginalized groups will help to elucidate the processes and mechanisms of change, facilitating theoretical development, while studies using a comparative design should assess the differential impact of interventions by group. B.B. was supported by Cancer Institute NSW Career Development Fellowship (10/CDF/2-40).

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)0,002
score de la tête « metaresearch » (Gemma)0,001
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: Éditorial · Signal consensuel: Éditorial
Score de désaccord entre enseignants0,100
Score d'incertitude au seuil0,486

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0020,001
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 recherche0,0010,001
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 Opus0,046
Tête enseignante GPT0,370
Écart entre enseignants0,324 · 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
GenreÉditorial

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

En bref

Citations42
Publié2014
Routes d'admission1
Résumé présentoui

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