Time‐Use Patterns and the Recreational Use of Prescription Medications Among Rural and Small Town Youth
Bibliographic record
Abstract
PURPOSE: To examine the relationship between rural and small town adolescents' time-use and an increased risk for recreational use of prescription drugs in rural settings. METHODS: Rural students in grades 9 and 10 (n = 2,393) were asked about past-year recreational use of prescription medications and their time-use in structured and unstructured activity contexts in the 2009/2010 Cycle of the Canadian Health Behaviour in School-aged Children survey. Time-use patterns of rural and small town youth from across Canada were examined using multilevel, multivariate Poisson regression analyses to determine whether they may impact the risk of this kind of substance use. FINDINGS: Peer time outside school hours and nonparticipation in extracurricular activities were significantly associated with rural youths' recreational use of prescription drugs. Peer drug use, unhappy home lives and frequent binge drinking explained most of these associations. CONCLUSIONS: Structured and unstructured activity contexts within rural settings play a role in the nonmedical use of prescription medications. Results support interventions aimed at increasing structured time-use opportunities in addition to focusing on peer contexts and multiple risk-taking behaviors among rural youth.
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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 | 0.000 | 0.001 |
| 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) | 0.002 | 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".