Examining the influence of rurality on frequency of cannabis use and severity of consequences as moderated by age and gender
Bibliographic record
Abstract
AIM: A number of important health disparities associated with place of residence have been reported in the literature. The Remoteness Index (RI) was developed to account for community size, population density, and proximity to larger population centres. This exploratory analysis uses the RI to examine community level associations related to cannabis use. DESIGN: This secondary analysis uses data collected as part of a randomized controlled trial of a brief cannabis intervention. Participants' place of residence was matched to a corresponding value on the RI. Univariate regressions of RI and cannabis related outcomes were modeled with age and gender as moderating variables. Three outcomes were analyzed separately: 1) total number of days of cannabis use in the past 30 days; 2) risk of experiencing cannabis related problems; and 3) number of self-reported consequences related to cannabis. FINDINGS: Participants living in more remote areas were significantly more likely to drive within an hour of using cannabis, but also reported fewer consequences and less risky cannabis use. Although the overall regression models tested in the moderation analyses were significant, there were no interaction effects between RI and age or gender. CONCLUSION: While this analysis did not find significant conditional effects of age or gender on the relationship between cannabis use and place of residence, further research is needed to investigate other factors which may contribute to health disparities related to substance use between individuals living in different geographic regions.
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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 | 0.000 | 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 | 0.001 |
| 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".