Video gaming and cannabis use: A scoping review
Bibliographic record
Abstract
Background and aim: Video gaming (VG) and cannabis use are two behaviors that are particularly prevalent among adolescents and young adults, as they can both be sedentary activities that are used to help decompress. As such, this raises questions about the possible relationship between VG and cannabis use. The aim of the present review is to document the relationship between VG and cannabis use. Methods: A scoping review identified 25 articles published between 2000 and February 2025, and presenting original findings on the relationship between VG and cannabis use. Results: Results demonstrate that existing literature is heterogeneous in its methods and measures. Nonetheless, evidence suggests that a relationship does exist, as the majority of studies did find a positive relationship between VG and cannabis use, although several studies also found no significant relationship, and a few even found a negative relationship. Discussion: Being a new and emerging subject, few studies exist exploring the relationship between VG and cannabis use. Thus, there is much that needs to be explored before drawing clear conclusions on what type of relationship exists between both behaviours. An inability to draw clear conclusions is, in part, due to a lack of consistency in the way both VG and cannabis use have been operationalized, and the use of convenience samples, which have created additional challenges that the field will need to address moving forward.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".