Factors associated with lower-risk cannabis use in adults in their mid-thirties
Bibliographic record
Abstract
BACKGROUND: Harm reduction strategies encourage people who use cannabis to adopt lower-risk behaviors, such as refraining from daily or intensive use or limiting simultaneous use with other psychoactive substances. However, little is known about the characteristics of people who use cannabis but are at lower risk of cannabis use disorder (CUD). This study identified sociodemographic, lifestyle, and mental health factors associated with lower-risk cannabis use among adults in their mid-thirties. METHODS: Cross-sectional data from 731 adults in the Nicotine Dependence in Teens study were analyzed from the 2022-2023 data collection. Risk of CUD was assessed with the Cannabis Abuse Screening Test (CAST). Sociodemographic, mental health, lifestyle factors, and patterns of cannabis use were compared across participants who did not use cannabis, those with lower-risk cannabis use, and those at higher risk of CUD using cross-tabulations. Among participants who used cannabis, log-binomial regression models adjusted for age, sex, and education were fitted to identify factors associated with lower-risk cannabis use. RESULTS: Of 731 participants (mean [SD] age = 35.3 [0.6] years; 58% female), 44% reported past-year cannabis use, including 63% classified as lower risk and 37% at higher risk of CUD. Compared with other participants, those at higher risk of CUD were more often male and had lower levels of education. Several mental health indicators were less favorable among participants at higher risk of CUD, who also reported a higher prevalence of cigarette smoking. In multivariable models, being female and simultaneous cannabis and alcohol use were associated with a higher prevalence of lower-risk cannabis use, whereas higher frequency of cannabis use, simultaneous cannabis and tobacco use, cigarette smoking, and GAD-7 scores > 10 were associated with a lower prevalence. CONCLUSION: Participants with lower-risk cannabis use resemble participants who do not use cannabis more than participants at higher risk of CUD. While use frequency is key, other factors, such as cigarette smoking, distinguish higher CUD risk from lower-risk cannabis use. Findings underscore the importance of harm reduction strategies and evidence-based education for cannabis-related policies.
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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 | 0.005 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.004 |
| 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".