Effects of Extended Cannabis Abstinence in Major Depressive Disorder
Bibliographic record
Abstract
ABSTRACT Background: Individuals with major depressive disorder (MDD) have higher rates of problematic cannabis use than the general population. Recent meta-analyses have found a link between cannabis use and increased risk for depression, suicidal behavior, and suicidal ideation. Few studies to date have examined the effects of cannabis use in individuals diagnosed with MDD. Objectives: We examined the effects of cannabis abstinence on clinical symptoms of depression in adults with comorbid cannabis use disorder (CUD) and MDD. Method: Participants with comorbid CUD and MDD (n = 11) underwent 28 days of cannabis abstinence. Mood symptoms were assessed weekly using the Hamilton Depression Rating Scale, the Beck Anxiety Inventory, the Snaith Hamilton Pleasure scale. Abstinence was biochemically verified using weekly urine assays for 11-nor-9-carboxy-Δ9-tetrahydrocannnabinol (THC-COOH), a metabolite of THC, and participants were rewarded with a contingent bonus if abstinence was confirmed. Results: 72.7% of study completers achieved abstinence. In all participants, including those who relapsed, urinary THC-COOH was significantly reduced throughout the study (P = 0.002). Participants exhibited significant improvements in depressive symptoms (43.7% reduction from baseline; P = 0.008), especially anhedonia (88.7% reduction from baseline; P < 0.001). Scientific significance: Findings from this study suggest that extended abstinence from cannabis is associated with improvement of depressive symptoms, particularly anhedonia, in individuals with MDD and CUD. Our results indicate that addressing problematic cannabis use in the treatment of individuals with MDD can improve clinical outcomes. Contexte: Les personnes atteintes de trouble dépressif majeur (MDD) ont des taux plus élevés de consommation problématique de cannabis que la population générale. Des méta-analyses récentes ont trouvé un lien entre la consommation de cannabis et un risque accru de dépression, de comportement suicidaire et d’idées suicidaires. À ce jour, peu d’études ont examiné les effets de la consommation de cannabis chez les personnes diagnostiquées avec un MDD. Objectifs: Nous avons examiné les effets de l’abstinence de cannabis sur les symptômes cliniques chez les adultes atteints de trouble de morbidité qui souffrent d’un désordre de consommation de cannabis (CUD) et de MDD. Méthode: Les participants atteints de troubles de morbidité CUD et MDD (n = 11) ont subi 28 jours d’abstinence de cannabis. Les symptômes de l’humeur ont été évalués chaque semaine à l’aide de la Hamilton Depression Rating Scale, du Beck Anxiety Inventory, de la Snaith Hamilton Pleasure scale. L’abstinence a été vérifiée biochimiquement en utilisant des analyses d’urine hebdomadaires pour le 11-nor-9-carboxy-Δ9-tétrahydrocannnabinol (THC-COOH), un métabolite du THC, et les participants ont été récompensés par un bonus contingent si l’abstinence était confirmée. Résultats: 72,7% des finissants de l’étude ont atteint l’abstinence. Chez tous les participants, y compris ceux qui ont rechuté, le THC-COOH urinaire a été significativement réduit tout au long de l’étude (P = 0,002). Les participants ont montré des améliorations significatives des symptômes dépressifs (réduction de 43,7% par rapport à la ligne de base; P = 0,008), en particulier de l’anhédonie (réduction de 88,7% par rapport à la ligne de base; P < 0,001). Importance scientifique: Les résultats de cette étude suggèrent que l’abstinence prolongée de cannabis est associée à une amélioration des symptômes dépressifs, en particulier de l’anhédonie, chez les personnes atteintes de MDD et de CUD. Nos résultats indiquent que la lutte contre la consommation problématique de cannabis dans le traitement des personnes atteintes de MDD peut améliorer les résultats cliniques.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.000 |
| 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".