Emotion Dysregulation Is Associated With Increased Problem Cannabis Use Among Emerging Adults During COVID-19
Bibliographic record
Abstract
Objective: Emerging adulthood (18–25 years) is associated with peak prevalence of cannabis use. Although population-based longitudinal studies have found little change in cannabis use among emerging adults during COVID-19, research examining changes among vulnerable subgroups is lacking. The present study examined the association between emotion dysregulation at 23 years and change in cannabis use frequency and problem cannabis use among a large sample of emerging adults, from before to during the COVID-19 pandemic. Method: Longitudinal data were analyzed from 1,226 emerging adults (59% female; n = 738 reported cannabis use) who completed online surveys before the pandemic (2019; age 21) and 1 year into COVID-19 (2021; age 23) as part of the Québec Longitudinal Study of Child Development. Results: There was no significant overall within-person change in cannabis use outcomes during COVID-19 among the emerging adult sample. However, emotional clarity (a dimension of emotion dysregulation) at 23 years significantly moderated change in problem cannabis use during COVID-19. Namely, low emotional clarity at 23 years was associated with increased problem cannabis use (B = 0.79, 95% CI [0.23, 1.34]), whereas high emotional clarity at 23 years was associated with decreased problem cannabis use (B = -0.68, 95% CI [-1.27, -0.09]) during COVID-19, among men only. Conclusions: Findings highlight the need to consider changes in cannabis use during COVID-19 among emerging adults with elevated emotion dysregulation (and particularly, low emotional clarity among men) and reiterate the need for supports and targeted interventions to reduce cannabis use and decrease associated harms as society emerges from COVID-19.
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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 | 0.000 |
| 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) | 0.000 | 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".