Per-capita consumption of analgesics: a nine-country survey over 20 years
Bibliographic record
Abstract
There are no reliable data at present on use of analgesics in various countries. We compared per-capita consumption in nine different countries during the period 1986-2005. The per-capita consumption was calculated on the basis of the sales figures of distributors to pharmacies and direct purchases by pharmaceutical companies in a sample of 1,000 pharmacies. The countries studied were: Australia, Austria, Belgium, Canada, France, Germany, Sweden, Switzerland, and the USA. In international comparison Austria, Switzerland, and Germany showed the lowest per-capita consumption of analgesics (approx. 40-50 Standard Units (SU) per capita per year), while in Sweden and France consumption was three times as high. The correlation analysis over the various countries and time points confirmed a significant correlation between use of single analgesics and overall use of analgesics. In Germany, where an allegedly particularly high and constantly rising analgesic use has been discussed controversially (Meiner, Pharm Ind 49:1247-1251, 1987), per-capita consumption of analgesics from 1980 to 2005 remained practically unchanged at approx. 50 SU per capita per year. The prevalence of conditions inducing analgesic use shows appropriate analgesics use on an overall population level.
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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 | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".