196. THE EFFECTS OF EXTENDED CANNABIS ABSTINENCE IN YOUNG ADULTS WITH CO-OCCURRING CANNABIS USE DISORDER AND MAJOR DEPRESSION
Bibliographic record
Abstract
Abstract Background Recreational cannabis use was legalized nation-wide in Canada in 2018, for people 19 years and older. There are considerable concerns about the effects of cannabis use on brain development and behavioral and mental health outcomes, including on the risk for, onset and course of psychiatric disorders, notable major depression. Aims & Objectives Our goal is to determine the effects of 28 days of biochemically-verified cannabis abstinence on clinical and cognitive outcomes in people with major depression. Method We are conducting a 4-year CIHR-funded controlled study of extended (28 day) cannabis abstinence on clinical and cognitive outcomes in N=100 participants with co-occurring cannabis use disorder and major depression, ages 18-55. A contingent reinforcement procedure (Lucatch et al., 2020) developed In our laboratory is used to facilitate cannabis abstinence. Cannabis abstinence was based on self-report, and biochemically-verified cannabis abstinenc Results To date, in the nascent sample (n=36; recruited primarily by social media and subway ads in downtown Toronto), the majority (29/36; ~80%) have been participants 19-35 years old, corresponding to late adolescent and emerging adulthood. Preliminary findings suggest that 28 days of produces clinically significant improvements (all p’s <0.03; Cohen’s d effect sizes >0.76) in depression, anxiety, anhedonia and selective aspects of neurocognition (e.g. working memory and sustained attention). Discussion & Conclusions Extended cannabis abstinence improves mood and cognitive outcome in young adults with major depression. These preliminary data have important biological, clinical and policy implications for understanding the links between cannabis addiction and depression in adolescents and emerging adults, and the development of treatments for this increasingly common co-morbidity.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".