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Enregistrement W4401890628 · doi:10.1111/add.16656

Commentary on Conde <i>et al</i>.: Addressing evidence gaps on the impact of vaping among young people

2024· article· en· W4401890628 sur OpenAlexaboutno aff
Katherine East

Notice bibliographique

RevueAddiction · 2024
Typearticle
Langueen
DomaineMedicine
ThématiqueSmoking Behavior and Cessation
Établissements canadiensnon disponible
Organismes subventionnairesSociety for the Study of Addiction
Mots-clésDisadvantagedHarmAddictionAttritionMedicineSmoking cessationHarm reductionPsychologyGateway (web page)ConfoundingEnvironmental healthPublic healthPsychiatrySocial psychologyPolitical science

Résumé

récupéré en direct d'OpenAlex

Repetition of poor-quality studies assessing vaping as a ‘gateway’ into smoking among young people (aged < 30 years) may fuel vaping misconceptions and highly restrictive policies. Little is known about young peoples’ vaping for smoking prevention/cessation. Addressing this gap is critical, because the earlier someone stops smoking the better their health outcomes. In their recent article, Conde et al. [1] introduce the concept of interactive evidence and gap maps (EGMs) to assess vaping (e-cigarettes). In health research, repetition of poor-quality studies is, unfortunately, common, and Conde et al. demonstrate the utility of stepping back to identify gaps and what is needed to fill them. Conde et al. map the evidence exploring the relationship between vaping and subsequent smoking among young people (aged < 30 years). They found that the evidence to date clusters around vaping and subsequent initiation of smoking or current smoking (i.e. ‘gateway hypothesis’), with little attention given to the harm reduction potential of vaping among young people, particularly those from disadvantaged groups. They also found that most studies were from a few high-income countries. Of the 134 studies mapped, 106 assessed vaping as an exposure and current, or initiation of, smoking as an outcome. Reviews previously published in Addiction [2] and elsewhere [3, 4] have discussed the limitations of such ‘gateway’ studies, including inadequate adjustment for confounders, reliance upon self-report measures of infrequent use (e.g. ever use) without biochemical verification and high attrition. These limitations mean it is difficult to establish meaningful associations or causality. Evidence also suggests that the association between starting vaping and starting smoking works both ways [5] and that both behaviours share genetic aetiology [6], which is more consistent with a common liability rather than a causal association. Rather than more studies in this area, researchers could focus their attention elsewhere. Vaping poses only a fraction of the health harms of smoking, and there is now a substantial evidence base for vaping for tobacco harm reduction among adults [7]. Vaping nicotine can help adults to quit or reduce their smoking [8], and this effect is greater among adults with no initial plans to quit smoking [9]. Qualitative work also suggests some ‘accidental quitting’ or ‘sliding’ into tobacco abstinence among adults who try vaping [10]. Young adults have historically underutilized evidence-based cessation treatments for smoking [11], and quit rates are low among this age group [12]. However, at the population level, since disposable vapes have come onto the market in Great Britain smoking declines have been most pronounced among young adults, a group with the largest increases in vaping [13]. Vaping could therefore be a ‘gateway out’ of smoking although, as Conde et al. show, there are few studies specifically assessing vaping for smoking cessation, reduction or prevention among young adults. Addressing this gap is crucial, because the earlier someone stops smoking the better their health outcomes [14]. Conde et al. also highlight an evidence gap with respect to vaping among young people from more disadvantaged groups of society. Tobacco smoking is a leading cause of health inequalities, causing at least 50% of the difference in life expectancy between the least and most affluent in the United Kingdom, Canada and the United States [15]. In the United Kingdom, smoking is more common among people with lower levels of education and income [16] and those with mental ill-health [17]. Research assessing vaping for tobacco harm reduction among these specific groups of young people is therefore critical for intervening early and reducing life-long inequalities and ill-health. Conde et al. further highlight that the vast majority of research assessing associations between vaping and smoking among young adults is from the United States, the United Kingdom and Canada. Several countries (e.g. India, Singapore, Australia) have restricted nicotine-containing e-cigarettes to a greater extent than cigarettes or have banned vaping entirely, with youth vaping and ‘gateway’ concerns often underpinning such decisions. However, care must be taken not to generalize findings globally from a handful of western high-income countries, particularly given different product markets, cultures and historical approaches to tobacco control and harm reduction. Addressing research gaps with respect to vaping among young people is important because it might help to tackle pervasive misperceptions. Only 16% of adults who smoke in England accurately believe that vaping is less harmful than smoking, down from 41% in 2014 [18]. Despite their limitations [2], ‘gateway’ studies are often reported in the media as evidence that vaping can increase smoking among young people, potentially fuelling broader misconceptions that could deter people who smoke from switching to vaping [7]. As someone who published the first study in Great Britain assessing the association between trying vaping and trying smoking, subject to the limitations noted above and also finding that the association worked both ways [5], I have seen selective media reporting first-hand [19]. High-quality research among young people (particularly from disadvantaged groups) that assesses vaping for smoking prevention and cessation may update the narrative around vaping among this age group, with implications for equity across the life-span. K.E. is the recipient of Fellowship funding from the Society for the Study of Addiction (SSA). No other conflicts of interest to declare. No data described.

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)0,024
score de la tête « metaresearch » (Gemma)0,155
Version: metacan-v3-hybrid-931329e0061cStatut 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 enseignants0,062
Score d'incertitude au seuil0,125

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0240,155
Méta-épidémiologie (sens strict)0,0020,002
Méta-épidémiologie (sens large)0,0040,005
Bibliométrie0,0030,004
Études des sciences et des technologies0,0060,008
Communication savante0,0080,011
Science ouverte0,0130,005
Intégrité de la recherche0,0620,063
Charge utile insuffisante (le modèle a refusé de juger)0,0150,012

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 Opus0,058
Tête enseignante GPT0,364
Écart entre enseignants0,307 · 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 source (Gemma direct ou Codex distillé), 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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