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Pharmaceutical services and health promotion: how far have we gone and how are we faring? Scientific output in pharmaceutical studies

2014· article· en· W2062955718 on OpenAlexaboutno aff
Carina Akemi Nakamura, Luciano Soares, Mareni Rocha Farías, Silvana Nair Leite

Bibliographic record

VenueBrazilian Journal of Pharmaceutical Sciences · 2014
Typearticle
Languageen
FieldHealth Professions
TopicHealth, Nursing, Elderly Care
Canadian institutionsnot available
Fundersnot available
KeywordsPharmacyPharmacistPromotion (chess)Pharmaceutical careHealth promotionInclusion (mineral)MedicineCharterPopulationAlternative medicineHealth servicesHealth careFamily medicineMedical educationPublic relationsBusinessPublic healthNursingPolitical scienceEnvironmental healthSociologySocial science

Abstract

fetched live from OpenAlex

The objective of this study was to investigate the scientific output on health promotion within the pharmaceutical field and its relation with the development of pharmaceutical services within health systems. A comprehensive review of published scientific articles from the Medline and Lilacs databases was carried out. The review comprised articles published until December 2011, and used combinations of the terms 'health promotion' or 'health education' and 'pharmacy', 'pharmacist' or 'pharmaceutical'. The articles were selected according to inclusion and exclusion criteria. A total of 170 full texts and 87 indexed abstracts were analyzed, evidencing that most described actions of health promotion in community pharmacies and other services. Following the Ottawa Charter, most of the studies dealt with new guidance of the service and the supply of pharmaceutical information and services. It was concluded that there is a lack of theoretical background on health promotion in the pharmaceutical field to sustain the professional education and practice required by the health system and the population.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.077
metaresearch head score (Gemma)0.188
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Bibliometrics
Consensus categoriesnone
DomainCandidate signal: Evaluation · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.979
Threshold uncertainty score0.410

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0770.188
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0040.002
Bibliometrics0.0210.034
Science and technology studies0.0020.008
Scholarly communication0.0210.015
Open science0.0020.004
Research integrity0.0040.003
Insufficient payload (model declined to judge)0.0050.001

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 head0.293
GPT teacher head0.516
Teacher spread0.223 · 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 source (direct Gemma or distilled Codex), not a consensus.

Study designObservational
DomainEvaluation
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

Citations10
Published2014
Admission routes1
Has abstractyes

Explore more

Same venueBrazilian Journal of Pharmaceutical SciencesSame topicHealth, Nursing, Elderly CareFrench-language works237,207