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Record W4206023617 · doi:10.1177/87551225211051593

Media Generation and Pharmacy Regulatory Authority Awareness

2022· article· en· W4206023617 on OpenAlexaffabout
Todd A. Boyle, Bobbi Morrison, Thomas Mahaffey

Bibliographic record

VenueJournal of Pharmacy Technology · 2022
Typearticle
Languageen
FieldPharmacology, Toxicology and Pharmaceutics
TopicPharmaceutical industry and healthcare
Canadian institutionsSt. Francis Xavier University
Fundersnot available
KeywordsPublic trustPublic relationsTest (biology)Nova scotiaNewspaperPharmacyBusinessCorporate governanceCredibilityThe InternetPolitical scienceAdvertisingSociology

Abstract

fetched live from OpenAlex

Background: Professional regulatory authorities play a critical role in protecting public interest. Yet, there is a growing view that trust in regulatory authorities may be on the decline. Objective: Awareness has been identified as important for maintaining trust. However, research that examines public awareness and trust in pharmacy regulatory authorities (PRAs) is lacking. This research explores public awareness and trust of PRAs and presents recommendations to enhance PRA communication strategies. Methods: An online survey was conducted with the Nova Scotia (Canada) public in 2020. Adopting classifications from the Communications literature, 3 media generations were explored: newspaper, television, and the Internet. The χ 2 test of independence and Kruskal-Wallis H test were adopted to explore differences between the generations. Results: Six hundred sixty-two usable surveys were obtained. Over 80% of those surveyed were aware of the existence of the PRA. Those who had heard of the PRA were most aware of its operational responsibilities and less aware of its governance. The Internet Generation was more aware that the PRA includes members of the public in its decision making than expected and showed increased trust toward the PRA versus the other media generations. Conclusion: The findings should help inform PRA communication plans and set baselines to assess whether such plans enhance awareness. Future studies should explore additional aspects of PRA awareness and trust, perform comparisons across pharmacy jurisdictions, and develop and test models of the relationship between PRA awareness and various dimensions of institutional trust.

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 categoriesMeta-epidemiology (narrow), Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.784
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.006
Insufficient payload (model declined to judge)0.0040.000

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 head0.448
GPT teacher head0.553
Teacher spread0.105 · 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.

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

Citations1
Published2022
Admission routes2
Has abstractyes

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