Bibliographic record
Abstract
Objective To assess perceptions related to facets of community pharmacy usage within the Portuguese general population. Methods 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. Main Results 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. Conclusions 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.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".