A Scoping Review on the Medical and Recreational Use of Cannabis During the COVID-19 Pandemic
Bibliographic record
Abstract
Background/Introduction: The shelter-in-place orders and social distancing regulations on account of the COVID-19 pandemic have impacted lifestyles, including the use of cannabis. The purpose of this scoping review is to summarize both the gray and academic literature on the use of cannabis during the pandemic. Materials and Methods: A total of 11 databases, including 2 medical databases, 7 social science databases, and 2 gray literature databases were searched resulting in 316 titles and abstracts of which 76 met inclusion criteria. Results: Nine themes emerged: (a) prevalence and trends of cannabis use during COVID[1]19; (b) demographics; (c) profile of mode of consumption; (d) context of using cannabis (i.e., solitary use vs. in groups); (e) factors contributing to use; (f) factors inhibiting use; (g) adverse clinical and psychiatric outcomes of cannabis use during the pandemic; (h) similarities between EVALI (E-Cigarette or Vaping Product Use-Associated Lung Injury) and COVID-19 symptoms; (i) implications for policy and practice. Studies published until February 2, 2021 were included in this review. Discussion: Findings have highlighted that feelings of boredom, depression, and anxiety during the pandemic have contributed to an increase in the use of cannabis. Furthermore, accessibility to cannabis was noted to affect use during the pandemic. Adverse psychiatric and clinical outcomes were associated with the increased use of cannabis. Conclusion: Practitioners and policymakers are called to employ harm reduction strategies to respond to increasing cannabis use. There is a need for population-based studies and further examination of factors contributing to the increased use of cannabis during the pandemic and associated negative consequences.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.012 | 0.019 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.005 |
| Insufficient payload (model declined to judge) | 0.005 | 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; both teacher heads agree on what is shown here.
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".