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Record W2079071253 · doi:10.1007/s10194-008-0046-6

Per-capita consumption of analgesics: a nine-country survey over 20 years

2008· article· en· W2079071253 on OpenAlexaboutno aff
H. C. Diener, Reinhard Schneider, Bernhard Aicher

Bibliographic record

VenueThe Journal of Headache and Pain · 2008
Typearticle
Languageen
FieldMedicine
TopicMigraine and Headache Studies
Canadian institutionsnot available
Fundersnot available
KeywordsPer capitaMedicineConsumption (sociology)PopulationDemographyPharmacyAgricultural economicsEnvironmental healthEconomicsFamily medicine

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.224
Threshold uncertainty score0.239

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.048
GPT teacher head0.297
Teacher spread0.249 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations33
Published2008
Admission routes1
Has abstractyes

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