Effects of 28 days of cannabis abstinence on cognition in major depressive disorder: A pilot study
Bibliographic record
Abstract
BACKGROUND AND OBJECTIVES: Cannabis is a widely used substance that may impair select cognitive domains, including attention and memory. Problematic cannabis use is a common clinical problem among patients with major depressive disorder (MDD). Few studies have investigated the effects of cannabis abstinence on cognition in MDD. Thus, our study aimed to determine whether a 28-day period of cannabis abstinence is associated with improvements in cognition in patients with MDD and comorbid cannabis use disorder (CUD). METHODS: We evaluated the effects of 28 days of cannabis abstinence on cognition in MDD patients with comorbid CUD facilitated by contingency management, motivational interviewing, psychoeducation, and coping-skills training (N = 11). Primary outcomes included Baseline to Day 28 changes in verbal memory and learning, while secondary outcomes included Baseline to Day 28 changes in working memory, visuospatial working memory (VSWM), visual search speed, mental flexibility, response inhibition, attention, manual dexterity, and fine motor movement. RESULTS: Eight participants (72.7%) met the pre-specified criteria for cannabis abstinence and three participants significantly reduced their cannabis use (≥90%). Visual search speed, selective attention, and VSWM improved over the study period. These improvements were not associated with changes in cannabis metabolite levels from baseline to endpoint. DISCUSSION AND CONCLUSIONS: Our findings suggest that 28 days of cannabis abstinence may improve select cognitive domains in patients with MDD and comorbid CUD. SCIENTIFIC SIGNIFICANCE: This is the first study to longitudinally examine the effects of cannabis on cognition in MDD. CLINICAL TRIAL: Effects of Cannabis Abstinence on Symptoms and Cognition in Depression (NCT03624933; https://www. CLINICALTRIALS: gov).
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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) | 0.001 | 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".