Evaluation of a Cannabis Harm Reduction Intervention for People With First-Episode Psychosis: Protocol for a Pilot Multicentric Randomized Trial
Notice bibliographique
Résumé
BACKGROUND: Cannabis use is highly prevalent in young people with first-episode psychosis (FEP). Most report cannabis use and are often diagnosed with a cannabis use disorder upon admission to specialized services for psychosis. Cannabis use in this population is associated with worse clinical and psychosocial outcomes, rendering it an important clinical target. Despite this, few cannabis-specific interventions have been developed for FEP and empirically evaluated through randomized controlled trials. Most evaluated interventions have targeted cannabis abstinence, with limited efficacy, but none have centered on harm reduction outcomes for people with FEP who use cannabis. Early intervention services (EIS), the standard of care for FEP, have not successfully addressed problematic cannabis use in people with FEP either. Clinical trials are needed to explore the potential of harm reduction strategies, although these should be preceded by robust pilot studies to establish optimal design and approaches. OBJECTIVE: Recognizing the need for harm reduction strategies for individuals with FEP who use cannabis and based on research on patients' preferences supporting harm reduction interventions, we developed a mobile app-based cannabis harm reduction intervention for this population. This intervention is called Cannabis Harm-reducing Application to Manage Practices Safely (CHAMPS). Here, we describe the protocol for a multicenter, 2-arm, parallel group, randomized pilot trial evaluating the acceptability of CHAMPS for people with FEP who use cannabis and the feasibility of conducting a full-scale trial in this population using CHAMPS. The impact on key clinical outcomes will also be explored. METHODS: This pilot trial aims to recruit 100 young people with FEP using cannabis from 6 Canadian EIS clinics. Participants will be randomized in a 1:1 ratio to CHAMPS+EIS or EIS-only. CHAMPS acceptability will be assessed using completion rates for the intervention arm. Trial feasibility will be assessed using a retention rate for randomized participants. Secondary outcomes will explore tendencies of change in the use of protective behavioral strategies and in motivation to change strategies. Exploratory outcomes include cannabis use-related problems, other substance use, the severity of dependence, psychotic symptoms, and health care service use. RESULTS: Recruitment began in December 2021. Data collection and analysis are expected to be completed in early 2024. Study results describing CHAMPS acceptability and trial feasibility will then be submitted for publication in a peer-reviewed journal. CONCLUSIONS: CHAMPS uniquely combines evidence-based approaches, patient perspectives, and mobile health technology to support harm reduction in people with FEP who use cannabis. Attaining adequate acceptability and feasibility through this trial may justify further exploration of harm reduction tools, particularly within the context of conducting a larger-scale randomized controlled trial. This pilot trial has the potential to advance knowledge for researchers and clinicians regarding a feasible and user-acceptable research design in the cannabis and early psychosis fields. TRIAL REGISTRATION: ClinicalTrials.gov NCT04968275, https://clinicaltrials.gov/ct2/show/NCT04968275. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/53094.
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 enseignantsNi 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.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,046 | 0,047 |
| Méta-épidémiologie (sens strict) | 0,006 | 0,003 |
| Méta-épidémiologie (sens large) | 0,009 | 0,006 |
| Bibliométrie | 0,002 | 0,003 |
| Études des sciences et des technologies | 0,004 | 0,004 |
| Communication savante | 0,004 | 0,005 |
| Science ouverte | 0,004 | 0,003 |
| Intégrité de la recherche | 0,007 | 0,010 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,086 | 0,017 |
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.
score_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 découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».