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Enregistrement W3017251349 · doi:10.1111/add.15043

Commentary on Walsh <i>et al</i> . (2020): Tobacco and cannabis co‐use— considerations for treatment

2020· letter· en· W3017251349 sur OpenAlexafffundabout
Rachel A. Rabin

Notice bibliographique

RevueAddiction · 2020
Typeletter
Langueen
DomaineMedicine
ThématiqueCannabis and Cannabinoid Research
Établissements canadiensMcGill UniversityDouglas Mental Health University Institute
Organismes subventionnairesCanada First Research Excellence FundMcGill University
Mots-clésCannabisAbstinenceMedicinePsychiatryIntervention (counseling)Tobacco useSmoking cessationEnvironmental healthClinical psychologyPopulation

Résumé

récupéré en direct d'OpenAlex

Treatment success for tobacco and cannabis co-use remains poor. A better understanding of the triggers preceding relapse and when individuals are most vulnerable to them may guide clinicians towards adopting a single or multi-substance intervention approach. Treatment should consider high-risk groups who may be more resistant to abstinence maintenance. In the last decade there has been an upward trend in tobacco and cannabis co-use, which may reflect the changing legal landscape surrounding cannabis use [1], rendering this phenomenon a public health concern. Despite this, there is currently no gold standard for treating tobacco and cannabis co-use. Walsh et al. [2] performed a systematic review and meta-analysis investigating treatment efficacy for tobacco and/or cannabis use in intervention studies targeting co-users. Results demonstrate that current treatment strategies are far from satisfactory, only showing weak evidence for an effect on cannabis cessation and no clear effect on tobacco cessation. One limitation of the studies included in the meta-analysis is the under-representation of female participants, which is critical given the wealth of data supporting gender-specific effects associated with both tobacco and cannabis use. For example, several clinical reports have suggested that women are more vulnerable to tobacco [3] and cannabis [4] use compared to men, despite men being more sensitive to the rewarding effects of both drugs [5, 6]. In addition, women are less successful in their tobacco [7] and cannabis [8] quit attempts compared to men, which may reflect their greater severity of withdrawal symptoms [9, 10]. In light of these differences, considering gender-tailored pharmacological and behavioral interventions may lead to enhanced treatment success for both men and women co-users. Other specialized populations that warrant greater consideration for co-use treatment are individuals with serious mental illness, given that their rates of tobacco and cannabis use are two to three times higher than the general population [11, 12]. Among these patients, chronic use is associated with greater illness severity [13] and lower quit rate success [14]. Treating comorbid substance use presents additional challenges. First, tobacco and cannabis use may be more strongly associated in patients with severe mental illness [15] and secondly, addiction may be a direct consequence of the underlying neuropathophysiology of the psychiatric disorder [16], implying that unique treatment strategies may need to be considered for co-users with severe mental illness. Substance use disorders are chronic and relapsing in nature and thus prolonging abstinence is a primary focus of treatment. Determining critical windows for treating co-users (e.g. when vulnerability to relapse is at its highest) may help to inform clinicians whether single substance use interventions or multi-substance use interventions are more efficacious. One of the strongest predictors of relapse is the exposure to environmental stimuli that have become associated with the drug(s) of abuse. Paradoxically, cue-induced craving may not decrease linearly with abstinence over time, but may progressively increase or ‘incubate’ with longer periods of cessation in daily tobacco smokers [17]. While cue-induced craving for cannabis has been documented in problematic cannabis users [18], its trajectory during abstinence has not yet been established in human studies; however, pre-clinical studies suggest that an incubation effect may indeed exist [19]. Thus, tailoring interventions to coincide with periods of peak cue-induced craving, which may not necessarily occur when one first quits, or at the same time for tobacco and cannabis, may help to improve treatment efficacy for co-use. In summary, the high prevalence and negative consequences associated with tobacco and cannabis co-use underscore the need to identify empirically informed treatments. A better understanding of craving trajectories during abstinence and their association with relapse may help advocate for sequential or simultaneous treatment for co-use. Women and people with mental illness need to be studied alongside the general population as they represent subgroups of individuals who may be more resistant to cessation treatment and may require alternate intervention strategies. None. This work was undertaken thanks to funding from the Canada First Research Excellence Fund, awarded to the Healthy Brains for Healthy Lives initiative at McGill University.

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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 candidatesMéta-épidémiologie (sens strict)
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 enseignants0,017
Score d'incertitude au seuil1,000

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0000,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0010,000
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 Opus0,032
Tête enseignante GPT0,312
Écart entre enseignants0,280 · 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.

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

Citations3
Publié2020
Routes d'admission3
Résumé présentoui

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