International Survey of Self-Reported Medicine Use Among Adolescents
Bibliographic record
Abstract
OBJECTIVE: To examine gender, age, and country variations in adolescents' self-reported medicine use. DESIGN: Cross-sectional school surveys of representative samples of 11- to 15-year-old girls and boys were used. The 1997/1998 Health Behaviour in School-aged Children study was referenced. A standardized questionnaire was completed during school hours. SETTING: Canada, US, Greenland, Israel, and 24 European countries. PARTICIPANTS: 123 227 participants equally distributed by gender and by 3 age groups (mean 11.7, 13.6, 15.6 y). MAIN OUTCOME MEASURES: Self-reported medicine use for headache, stomachache, difficulties in getting to sleep, and nervousness during the past month. RESULTS: The magnitude of the adolescents' medicine use for headache, stomachache, difficulties in getting to sleep, and nervousness varied substantially across countries. In each of the 28 countries, more girls than boys used medicine for pain. Use of medicine for headache increased by age; use of medicine for stomachache increased by age among girls, but decreased among boys; and use of medicine for difficulties in getting to sleep and nervousness decreased from the age of 11 to 15 years. There was an increase in the crude girl versus boy ratios for medicine use by age for all 4 symptoms. Multivariate logistic regression analyses, adjusting for age group and country, revealed the following odds ratios (95% CI) for girls' versus boys' medicine use: headache 1.56 (1.53 to 1.60), stomachache 2.16 (2.10 to 2.22), difficulties in getting to sleep 0.96 (0.91 to 1.00), and nervousness 1.04 (0.99 to 1.08). CONCLUSIONS: Substantial proportions of adolescents used medicine for common health problems. The prevalence of use differed between type of symptom for which the medicine was used, between countries, and between gender and age groups. We suggest that young people's medicine use should be addressed in public health policy.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| 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) | 0.002 | 0.001 |
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".