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Record W7037292102

Diferencias en la automedicación en la población adulta española según el paÃs de origen

2010· article· es· W7037292102 on OpenAlexaboutno aff

Bibliographic record

VenueScientific Electronic library online (Sciences Carlos III Health Institute) · 2010
Typearticle
Languagees
FieldSocial Sciences
TopicPublic Health and Social Inequalities
Canadian institutionsnot available
Fundersnot available
KeywordsDisease preventionPopulationQuarter (Canadian coin)
DOInot available

Abstract

fetched live from OpenAlex

Objetivos: Este estudio tiene como finalidad explorar los factores determinantes del consumo de fármacos sin receta médica en la población adulta española, prestando especial atención a la existencia de patrones diferenciales de automedicación entre la población inmigrante y la autóctona. Métodos: Para explicar la automedicación se empleó un modelo de regresión logística, utilizando como variables de control diversos indicadores demográficos, socioeconómicos, de salud y de estilos de vida. Los datos proceden de la muestra de adultos de la Encuesta Nacional de Salud de 2006, que incluye 29.478 individuos mayores de 15 años. Resultados: Los resultados muestran que los individuos con un riesgo mayor de incurrir en la automedicación son los individuos jóvenes, con buena percepción de salud y ausencia de enfermedades crónicas, los consumidores habituales de alcohol, los viudos, los usuarios de un seguro privado no concertado a través de mutua, los residentes en las Comunidades de Madrid y Valencia, y los nacidos en un país de Europa central y del este. Conclusiones: La identificación del perfil de los consumidores de fármacos sin prescripción médica puede ayudar a las autoridades sanitarias a establecer medidas específicas para los individuos de alto riesgo a fin de cumplir con los objetivos de salud pública establecidos por la Unión Europea.

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)0.023
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Scholarly communication, Research integrity
Consensus categoriesScience and technology studies, Research integrity
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.942
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0230.003
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.006
Science and technology studies0.0080.010
Scholarly communication0.0030.007
Open science0.0050.001
Research integrity0.0020.005
Insufficient payload (model declined to judge)0.0010.000

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 head0.019
GPT teacher head0.367
Teacher spread0.348 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
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

Citations0
Published2010
Admission routes1
Has abstractyes

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