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Record W7010075867

Gauging Portuguese community pharmacy users’ perceptions

2007· article· en· W7010075867 on OpenAlexaboutno aff

Bibliographic record

VenueUCL Discovery (University College London) · 2007
Typearticle
Languageen
FieldEnvironmental Science
TopicAir Quality and Health Impacts
Canadian institutionsnot available
Fundersnot available
KeywordsPharmacyCommunity pharmacyPortuguesePerceptionQuarter (Canadian coin)PopulationHealth careOdds
DOInot available

Abstract

fetched live from OpenAlex

To assess perceptions related to facets of community pharmacy usage within the Portuguese general population. An ONSA (The Governmental Public Health Observatory) instrument was used, the ECOS (E m C asa O bservamos S aúde) sample. This consisted of a national representative sample of household units with atelephone. General demographics and pharmacy users’ perceptions related to five facets of community pharmacy usage were collected by telephone interviews. Almost one-third (31.9%) of the participants were probable chronic drug users, hence in regular contact with the community pharmacy. Thirty-four percent preferred not to talk with the person who dispenses their prescribed drugs. Most users (47.6%) expressed opinions of pharmacists as being health care rather than business oriented, although one quarter of the sample was not sure. A large majority (73.7%) would like pharmacists to participate in their treatment decisions, but 55.1% did not seem able to distinguish between pharmacists and non-pharmacist technical staff working at the pharmacy counter. Most significant predictors of users’ dichotomous perceptions related to the usage facets surveyed were age, education and occupation. Being older, less literate and economically inactive increased the odds of inappropriate users’ perceptions of the pharmacists. Results showed that erroneous concepts and behaviours exist within the Portuguese population in relation to the community pharmacists’ role. This is a matter for pharmacy professional and educational bodies to take into account when developing intervention strategies, in particular when communicating with the general public. © 2007, Cambridge University Press. All rights reserved.

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)0.002
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.007
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
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 head0.037
GPT teacher head0.284
Teacher spread0.248 · 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.

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

Citations0
Published2007
Admission routes1
Has abstractyes

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