The Impact of Regular Cannabis Use on Mood and Anxiety Levels in Young Adults Compared to Non-Users: A Literature Review
Bibliographic record
Abstract
Introduction: Cannabis, otherwise known as marijuana, is one of the most commonly used psychoactive substances among young adults, yet its impact on mental health, particularly mood and anxiety disorders, remains contested. While some studies suggest potential anxiolytic and mood-stabilizing effects, primarily related to cannabidiol (CBD), a growing body of longitudinal and clinical evidence links regular cannabis use to heightened risks of depression, anxiety, and emotional dysregulation. Despite its widespread use, there is conflicting evidence regarding the therapeutic effects of cannabis on mood and anxiety and its long-term effects. Methods: This literature review systematically examines the relationship between regular cannabis use (defined as using it at least once per week) and mood and anxiety levels in young adults aged 18–25, a demographic especially vulnerable to mood and anxiety disorders due to ongoing neurodevelopment and high prevalence of cannabis use.7 Studies were identified using PubMed, OVID Medline, and the Cochrane Library, with inclusion criteria focused on observational studies, randomized controlled trials, and meta-analyses published in English over the last decade. Data regarding mood and anxiety outcomes were extracted, including depressive, anxiety, and emotional dysregulation symptoms, and analyzed to determine a potential relationship between cannabis use and mood disorder symptoms. Results: The review finds consistent evidence that regular cannabis use is associated with increased symptoms of depression, anxiety, and, in some cases, suicidal ideation. These associations appear stronger in females and in individuals with lower emotional regulation capacity. Neurobiological mechanisms, such as dysregulation of Cannabinoid Receptor 1 (CB1) in the endocannabinoid system and psychosocial factors, including cannabis use as a maladaptive coping strategy, are discussed as underlying contributors. Discussion: While cannabis may provide short-term relief for some, its regular use is linked to increased depression, anxiety, and suicidality and poses a significant risk to emotional well-being during a critical period of psychological development. Conclusion: These findings emphasize the need for early screening, sex-specific risk assessments, and targeted public health messaging. Further longitudinal and mechanistic studies are needed to clarify causality and guide effective harm reduction strategies.
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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 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.004 |
| Bibliometrics | 0.011 | 0.011 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".