The efficacy of an opportunistic cognitive behavioral intervention package (OCB) on substance use and comorbid suicide risk: A multisite randomized controlled trial.
Bibliographic record
Abstract
OBJECTIVE: People with substance use disorders who present with suicidal behavior are at high risk of subsequent suicide. There are few effective treatments specifically tailored for this population that diminish this risk. We aimed to assess the impact of an opportunistic cognitive behavioral intervention package (OCB) among adult outpatients with a substance use and comorbid suicide risk. METHOD: A randomized controlled trial was conducted across 2 sites in which 185 patients presenting with suicide risk and concurrent substance use received either OCB (8 sessions plus group therapy) or treatment as usual (TAU) over a 6-month period. Primary outcomes were suicidal behavior (suicide attempts, suicidal intent and presence of suicide ideation) and level of drug and alcohol consumption. Secondary outcomes were changes in psychological measures of suicide ideation, depression, anxiety, and self-efficacy. RESULTS: There were no completed suicides, and only 2 participants reported suicide attempts at follow-up. Suicide ideation, alcohol consumption, and cannabis use fell over time but no significant Treatment × Time differences were found. There were also no differences between OCB and TAU over time on psychological measures of depression, anxiety, or self-efficacy. Suicide ideation at 6-month follow-up was predicted by cannabis use and higher scores on the Brief Psychiatric Rating Scale at baseline. CONCLUSIONS: The opportunistic cognitive behavioral intervention package did not appear to be beneficial in reducing suicide ideation, drug and alcohol consumption, or depression relative to treatment as usual.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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 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".