How and why are non-prescription analgesics used in Scotland?
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND: UK Government policy increasingly encourages self-care of minor illnesses, including self-medication. Analgesics constitute a quarter of UK over-the-counter medicines sales, but concerns have been expressed about their potential for inappropriate use. OBJECTIVES: To estimate the prevalence of recent use of non-prescription analgesics in Scotland, to describe by whom they are used, and to estimate inappropriate use. METHOD: A cross-sectional postal survey consisting of a self-completed questionnaire that collected data on respondents' use of non-prescription and prescription medicines, as well as demographic and lifestyle data. The sample comprised 2708 subjects of 18 years and over, randomly selected from the Scottish electoral roll. RESULTS: The response rate was 55% (n=1501). Some 37% (555/1501) of respondents had used a non-prescription analgesic in the previous two weeks. Analgesics accounted for 59% (636/1081) of all non-prescription medicines used in that period. After controlling for all other variables, age, sex, level of education, self-reported health status, prescription exemption status, and use of prescription analgesics, remained significant predictors of non-prescription analgesic use. There was evidence of possible inappropriate use of non-prescription analgesics including use of multiple analgesics (n=67), use by individuals self-reporting conditions associated with cautious use of certain analgesics (n=51), and potential drug-drug interactions (n=15). A few respondents appeared to be using non-prescription analgesics to supplement medical treatment of chronic conditions (n=4). CONCLUSIONS: Our findings have demonstrated a high level of use of non-prescription analgesics amongst the general public, with significant potential for inappropriate use. As we move towards a culture of increased self-management of minor illness, this demonstrated need for improved pharmacovigilance of non-prescribed medicines must be addressed.
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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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it