Peer Support Facilitated Online Cognitive Behavioural Therapy for Substance Use Disorder: Lessons Learned from a Peer Support Perspective
Notice bibliographique
Résumé
Despite the high prevalence of substance use-related harms, the majority of individuals affected do not seek formal treatment. Digital interventions, such as Breaking Free Online (BFO) based in CBT, are being used to bridge this gap through improved accessibility and responding to an increasingly online world. However, many individuals who interact with digital mental health receive little or no human support. Peer support— defined by support grounded in shared lived experience and the values of hope, empathy and self-determination—may offer a valuable way to enhance engagement with digital tools. This presentation outlines the implementation of peer-facilitated BFO within a randomized controlled trial. 197 Participants were randomized to 1 of 3 arms; group peer support, BFO or individual peer support, each arm also included clinical monitoring. The study design, assessment schedule and peer support worker training was collaboratively developed with the input of an advisory committee that included lived experts and service users as well as scientists and clinicians. 66 participants—primarily diagnosed with Alcohol and Cannabis Use Disorders—were randomized to BFO with peer support. I personally provided peer support to 31 of the 66 participants. While individual preferences varied, key themes emerged. Participants consistently reported that peer support improved their ability to engage with BFO by helping them set personalized goals, challenge unhelpful thinking, stay accountable, and apply the digital content to their own lives. The biggest piece of feedback I received was “I would not have engaged with BFO as much if there wasn’t a peer support worker” Challenges that were identified, included technical barriers, missed appointments, and the need to better define and capture meaningful outcomes. Many participants described personal growth and positive changes that were not reflected in standard digital metrics. Importantly, peer supporters themselves reported benefits from the process, including professional and personal development and the opportunity to provide meaningful, person-centered care. In summary, integrating peer support with digital interventions like BFO offers a promising, scalable approach to substance use treatment. It brings structure to a complex discipline, while maintaining the flexibility and responsiveness that peer support requires. Thank you.
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Prédiction distillée sur la base complète
Imitation des enseignantsNi 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.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,002 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,001 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 0,000 |
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.
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 tête enseignante, pas un consensus.
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