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Enregistrement W2610479076 · doi:10.4073/csr.2017.6

Effects of early, computerized brief interventions on risky alcohol use and risky cannabis use among young people

2017· article· en· W2610479076 sur OpenAlexaff
Geir Smedslund, Sabine Wollscheid, Lin Fang, Wendy Nilsen, Asbjørn Steiro, Lillebeth Larun

Notice bibliographique

RevueCampbell Systematic Reviews · 2017
Typearticle
Langueen
DomaineMedicine
ThématiqueCannabis and Cannabinoid Research
Établissements canadiensUniversity of Toronto
Organismes subventionnairesnon disponible
Mots-clésCannabisPsychological interventionIntervention (counseling)PsychiatryMedicineBrief interventionPoison controlInjury preventionPsychologyEnvironmental health

Résumé

récupéré en direct d'OpenAlex

This Campbell systematic review examines research on the effectiveness of early, computerized brief interventions on alcohol and cannabis use by young people who are high or risky consumers of either one or both of these substances. The review summarises findings from 60 studies from 10 countries. The participants were young people between the ages of 15 and 25, defined as risky consumers of alcohol or cannabis or both. The review included 33,316 participants. The interventions significantly reduce alcohol consumption in the short-term compared to no intervention, but the effect size is small, and there is no significant effect in the long-term. There are also shortcomings in the quality of the evidence. Interventions which provide an assessment of alcohol use with feedback may have a larger effect that those which do not, but again, the evidence is weak. The few studies on cannabis did not show significant effects in the reduction of cannabis consumption. There was no evidence of adverse effects. Plain language summary Computerized brief interventions seem to reduce risky alcohol use among young people; no evidence of effect on cannabis consumption Young people who abuse alcohol or cannabis are at risk of immediate and long-term health and legal consequences. There is some evidence of an impact on alcohol use. Findings are hampered by a lack of rigorous evidence, so further research is needed. What did the review study? Alcohol abuse and use of recreational drugs among young people are significant public health concerns. These should be addressed by effective interventions that provide assistance and counselling to drug and alcohol users. A computerized brief intervention is any preventive or therapeutic activity delivered through online or offline electronic devices, such as a mobile phone, and administered within an hour or less, even a few minutes, of the substance abuse. Such interventions aim to reduce alcohol abuse or drug abuse in general. This review assesses research on the effectiveness of early, computerized brief interventions on alcohol and cannabis use by young people who abuse either one or both of these substances. What studies are included? The included studies employed randomized controlled trials and reported on any computerized brief intervention used as a standalone treatment aimed at reducing alcohol and cannabis consumption. The secondary outcome measured was reported adverse outcomes. The studies were conducted in the United States, New Zealand, The Netherlands, Sweden, Australia, Germany, Switzerland and Brazil, with one study conducted in several countries (Sweden, Belgium, the Czech Republic and Germany). The participants were consumers of alcohol or cannabis or both, and aged 15 to 25 years. A total of 60 studies with a sample size of 33,316 participants were included in the review. What is the aim of this review? This Campbell systematic review examines research on the effectiveness of early, computerized brief interventions on alcohol and cannabis use by young people who are high or risky consumers of either one or both of these substances. The review summarises findings from 60 studies from 10 countries. The participants were young people between the ages of 15 and 25, defined as risky consumers of alcohol or cannabis or both. The review included 33,316 participants. What are the main findings of this review? The interventions significantly reduce alcohol consumption in the short-term compared to no intervention, but the effect size is small, and there is no significant effect in the long-term. There are also shortcomings in the quality of the evidence. Interventions which provide an assessment of alcohol use with feedback may have a larger effect that those which do not, but again, the evidence is weak. The few studies on cannabis did not show significant effects in the reduction of cannabis consumption. There was no evidence of adverse effects. What do the findings in this review mean? Generally, the alcohol interventions seem to work. However, all the studies included in the review had methodological shortcomings. Given the lack of rigorous evidence, this conclusion should be read with caution. Only a few studies focused on cannabis, thus hampering any firm conclusion as to the intervention effectiveness. While there is doubt as to the validity of the findings, computerized brief interventions should not be completely ruled out as they are easy to administer, low cost and have no adverse effects. There is a need to conduct more high quality research, especially with regard to studies focused on cannabis use. Executive Summary/Abstract BACKGROUND Young people's risky use of alcohol or recreational drugs, such as cannabis, remains a significant public health issue. Many countries have made substantial efforts to minimize the long-term consequences of alcohol and/or cannabis use at multiple levels, ranging from government policy initiatives to primary health care services. In this review, we focused on the effects of brief interventions, provided by electronic devices (computerized brief interventions). A brief intervention is defined as any preventive or therapeutic activity delivered by a health worker, psychologist, social worker, or volunteer worker, and given within a maximum of four structured therapy sessions each lasting between five and ten minutes with a maximum total time of one hour. Brief interventions may work by making the clients think differently about their alcohol/cannabis use, and by providing them with skills to change their behavior if they are motivated to change. A computerized brief intervention, in contrast, is not directly delivered by a human being, but may be delivered through online and offline electronic devices. Such interventions can reach large audiences at a low cost and can simultaneously simulate an ‘interpersonal therapeutic component’ by targeting recipients’ feedback. OBJECTIVES To assess the effectiveness of early, computerized brief interventions on alcohol and cannabis use by young people aged 15 to 25 years who are high or risky consumers of either one or both of these substances by synthesizing data from randomized controlled trials. SEARCH METHODS We searched 11 electronic databases including MEDLINE, PsycINFO, EMBASE, Cinahl and The Cochrane Library in April 2016 for published, unpublished and ongoing studies using adapted subject headings and a comprehensive list of free-text terms. Additionally, we searched the reference lists of the included studies. We also have set up an EBSCO host alert notification ( EPAlerts@EPNET.COM ) that continuously surveys the Cochrane Library (including CENTRAL), Medline and Embase. We receive updated searches via email. This search is up to date as of May 2016. SELECTION CRITERIA We included all randomized or quasi-randomized controlled trials of any computerized brief intervention used as a stand-alone treatment aimed at reducing alcohol and/or cannabis consumption. Eligible comparators included no intervention, waiting list control or an alternative brief intervention (computerized or non-computerized). Participants were young people between 15 and 25 years of age who were defined as risky consumers of alcohol or cannabis, or both. DATA COLLECTION AND ANALYSIS

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)0,004
score de la tête « metaresearch » (Gemma)0,026
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Revue systématique · Signal consensuel: Revue systématique
GenreSignal candidat: Synthèse · Signal consensuel: Synthèse
Score de désaccord entre enseignants0,009
Score d'incertitude au seuil0,029

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0040,026
Méta-épidémiologie (sens strict)0,0010,001
Méta-épidémiologie (sens large)0,0040,005
Bibliométrie0,0030,003
Études des sciences et des technologies0,0000,000
Communication savante0,0020,001
Science ouverte0,0010,001
Intégrité de la recherche0,0020,002
Charge utile insuffisante (le modèle a refusé de juger)0,0090,001

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 Opus0,070
Tête enseignante GPT0,352
Écart entre enseignants0,281 · 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'étudeRevue systématique
Domainenon disponible
GenreSynthèse

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

En bref

Citations22
Publié2017
Routes d'admission1
Résumé présentoui

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