An integrated substance use treatment model for young adults with first‐episode psychosis: A naturalistic pilot evaluation
Bibliographic record
Abstract
AIM: Approximately 50% of individuals with first-episode psychosis meet criteria for a substance use disorder and these concurrent disorders are associated with worse long-term outcomes. Psychosocial interventions, including motivational interviewing as well as cognitive and behavioural therapies, have shown some evidence for effective treatment in substance use disorders; however, there is a paucity of existing studies that have successfully examined these interventions in first-episode psychosis. METHODS: Participants (n = 64) received the concurrent disorders intervention, which included individual support alongside participation in at least one of two groups: a 4-week Motivational Engagement group utilizing motivational interviewing (n = 59) and an 8-week Relapse Prevention Training group emphasizing skill acquisition, which some participants entered directly (n = 5) and some participants entered following completion of the Motivational Engagement group (n = 16). RESULTS: Participants who completed the Motivational Engagement group (n = 59) demonstrated significantly increased motivation to change substance use (d = -.0.58; t = -3.02, p < .01) and significantly decreased substance use frequency (d = 0.65; t = 3.26, p < .01). For participants who completed the Relapse Prevention Training group (n = 21), substance use frequency significantly decreased (d = 0.92; t = 3.46, p < .01) and self-efficacy in one's ability to maintain substance use changes significantly increased (d = -0.85; t = -3.59, p < .01). CONCLUSIONS: This pilot evaluation suggests that motivational interviewing and relapse prevention skills training are acceptable and feasible interventions in the treatment of substance use disorders in young adults with first-episode psychosis.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".