High‐frequency use of over‐the‐counter analgesics among adolescents: reflections of an emerging difficult life, a cross‐sectional study
Bibliographic record
Abstract
AIMS: To examine characteristics of 15- to 16-year-old adolescents who used over-the-counter analgesics daily to weekly (high-frequency users) as compared to those who used less or no analgesics (low-frequency users). Further to analyse the differences in pain experience, lifestyle, self-esteem, school attendance and educational ambition. METHODS: An anonymous cross-sectional questionnaire-based study. The questionnaire covered the use of over-the-counter analgesics, pain experience, sociodemographics, lifestyle factors, self-esteem, school absence and future educational plans. The study took place in the 10th grade in six junior high schools in a medium-sized town in Norway. The local sales data for analgesics and antipyretics were close to the national average. We invited 626 adolescents to participate. Of the 367 adolescents (59%) who responded, 51% were girls. Associations between the frequency of use of over-the-counter analgesic and the mentioned variables were analysed using multiple logistic regression. RESULTS: In total, 26% (42 boys and 48 girls) used over-the-counter analgesics daily to weekly. These high-frequency users experienced more widespread pain, slept less, had more paid spare-time work, drank more caffeinated drinks, participated more often in binge drinking, had lower self-esteem, less ambitious educational plans and more frequent school absence than did the low-frequency users. These associations remained significant when controlling for gender, cultural background and self-evaluated economic status. CONCLUSION: Adolescent, who are high-frequency users of over-the-counter analgesics, suffer more pain and have identifiable characteristics indicative of complex problems. Their ability to handle stress appears to be discordant with the kind of situations to which they are exposed. The wear and tear associated with allostatic mechanisms counteracting stress may heighten their pain experience.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".