Effects of Extended Cannabis Abstinence on Depression and Anhedonia in Individuals with Comorbid Major Depressive Disorder and Cannabis Use Disorder
Bibliographic record
Abstract
Comorbid Major Depressive Disorder (MDD) and Cannabis Use Disorder (CUD) is associated with more severe symptomatology, poorer treatment outcomes, and reduced life satisfaction compared to MDD alone. Anhedonia, a loss of interest in or pleasure from previously rewarding activities, is a core feature of MDD and additionally contributes to reward processing and CUD. We examined the effects of 28-days of cannabis abstinence on symptoms of depression in individuals with comorbid CUD and MDD. Participants (N=25) underwent 28-days of cannabis abstinence, randomized to a contingent reinforcement ($300) and non-contingent reinforcement group. Biochemically verified abstinence and clinical symptoms, including subjective and objective measures of anhedonia, were assessed weekly. Cannabis abstainers (56%) exhibited clinically significant improvements in depressive symptoms, and subjective measures of anhedonia, but not objective. Motivational deficits and anhedonia associated with CUD and MDD improve with cannabis abstinence, highlighting the importance of targeting cannabis use in the treatment of MDD.
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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 | 0.000 | 0.001 |
| 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) | 0.001 | 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".