A longitudinal study of change in substance use from before to during the COVID-19 pandemic in young adults
Bibliographic record
Abstract
Introduction: We assessed change in substance use from before to during the COVID-19 pandemic in young adults and identified factors associated with initiation/increase in use. Methods: The sample comprised young adults from a longitudinal investigation of 1294 youth recruited at ages 12-13 (1999-2000) in 10 Montréal-area high schools. Pre-pandemic data on use of cannabis, alcohol, combustible cigarette, e-cigarette and binge drinking were collected at ages 20.4, 24.0 and 30.6. During COVID-19, data were collected from December 2020 to June 2021 (age 33.6). We studied the prevalence of any and weekly/daily use from age 20.4 to 33.6. Individual-level change in substance use during the pandemic was estimated as differences in the frequency of use from age 30.6 to 33.6 versus from age 24.0 to 30.6. Heterogeneity in the risk of initiated/increased substance use during COVID-19 across sociodemographic subgroups was assessed using modified Poisson regression. Results: The prevalence of cannabis use increased from 17.5% to 23.1% from before to during the pandemic; e-cigarette use increased from 3.8% to 5.4%. In individual change analyses, the proportion of participants whose substance use did not change ranged from 48.9% (alcohol) to 84.0% (e-cigarettes). The incidence of initiated/increased cannabis use (22.4%), and quit/decreased alcohol (35.2%) and binge drinking (53.5%) were higher during the pandemic than between ages 24.0 to 30.6. Low education and living alone were associated with higher risks of initiated/increased use of most substances. Discussion: Most participants reported stable patterns in substance use from before to during the COVID-19 pandemic. Funding: The NDIT study was supported by the Canadian Cancer Society (grant numbers 010271, 017435, 704031) and the Canadian Institutes of Health Research (grant number 451832).
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".