Cannabis Consumption Among Adults Aged 55–65 in Canada, 2018–2021
Bibliographic record
Abstract
Cannabis consumption among aging adults in Canada is increasing. The aims of the study were to examine cannabis consumption patterns before and after non-medical cannabis legalization and assess whether these patterns differ between men and women. Data were analyzed from Canadian respondents in a repeat cross-sectional survey conducted in 2018–2021. Analyses were conducted among adults aged 55–65 ( n = 18,177) who had consumed cannabis in the past 12-month ( n = 4119). Past 12-month cannabis consumption significantly increased among 55–65-year-olds from 2018 (19.3%) to the first-year post-legalization in 2019 (24.5%; p < .001), but remained stable thereafter (24.3%, and 25.6% in 2020 and 2021). More men reported past 12-month consumption than women (28.4% vs. 21.4%; p < .001). A substantial number of cannabis consumers consumed to manage a physical or mental health condition. Targeted messaging might be beneficial for this age group, including possible interactions with other medications. This research may be helpful for informing age-adapted cannabis education.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".