Peer support and online cognitive behavioural therapy for substance use concerns: protocol for a randomised controlled trial
Bibliographic record
Abstract
INTRODUCTION: Hazardous alcohol and drug use is associated with substantial morbidity, mortality and societal cost worldwide. Yet, only a minority of those struggling with substance use concerns receive specialised services. Numerous barriers to care exist, highlighting the need for scalable and engaging treatment alternatives. Online interventions have exhibited promise in the reduction of substance use, although studies to date highlight the key importance of patient engagement to optimise clinical outcomes. Peer support may provide a way to engage patients using online interventions. The goal of this study is to evaluate the efficacy and cost-effectiveness of Breaking Free Online (BFO), an online cognitive-behavioural intervention for substance use, delivered with and without peer support. METHODS AND ANALYSIS: A total of 225 outpatients receiving standard care will be randomised to receive clinical monitoring with group peer support, with BFO alone, or with BFO with individual peer support, in an 8-week trial with a 6-month follow-up. The primary outcome is substance use frequency; secondary outcomes include substance use problems, depression, anxiety, quality of life, treatment engagement and cost-effectiveness. Mixed effects models will be used to test hypotheses, and thematic analysis of qualitative data will be undertaken. ETHICS AND DISSEMINATION: The protocol has received approval by the Centre for Addiction and Mental Health Research Ethics Board. Results will help to optimise the effectiveness of structured online substance use interventions provided as an adjunct to standard care in hospital-based treatment programmes. Findings will be disseminated through presentations and publications to scholarly and knowledge user audiences. TRIAL REGISTRATION NUMBER: NCT05127733.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.060 | 0.052 |
| Meta-epidemiology (narrow) | 0.008 | 0.004 |
| Meta-epidemiology (broad) | 0.016 | 0.008 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.005 | 0.006 |
| Scholarly communication | 0.007 | 0.006 |
| Open science | 0.005 | 0.003 |
| Research integrity | 0.010 | 0.013 |
| Insufficient payload (model declined to judge) | 0.152 | 0.025 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".