2022 Pharmacy Practice Research Abstracts
Bibliographic record
Abstract
OBJECTIVES: To describe public attitudes toward the temporary COVID-19 policy of 30-day supply dispensing practice implemented in Nova Scotia pharmacies at the outset of the pandemic. METHODS:The dispensed days' supply (30-day limit) was introduced in Nova Scotia on March 18, 2020, and lifted for drugs with a stable supply on May 19, 2020.Nova Scotia adults were surveyed about their awareness of, and attitudes toward, the 30-day limit between May 28th and June 17th, 2020, via an online questionnaire.Respondents were recruited by Dynata, a third-party survey sampling firm.Quota sampling achieved representativeness by age, gender, and household income, and reasonable representation from rural, suburban, and urban locales.Descriptive statistics were calculated using SPSS v26.RESULTS: A sample size of 769 respondents was achieved, yielding a margin of error of 3.47% at a 95% confidence level.Respondents were aware (86%) of the 30-day limit policy change, learning about it through news outlets (57%), pharmacy staff (45%), pharmacy signage (24%), social media (23%), friends and family (22%), and/or the provincial regulator (9%).Most respondents (67%) agreed the 30-day limit was in the public interest, that it was the responsible thing to do (57%) and that its rationale was clear (65%).The policy caused problems for some respondents (33%) including making medications too expensive (35%) and increasing anxiety about the health risks of multiple pharmacy visits (46%).CONCLUSIONS: Results revealed that Nova Scotians were generally accepting of the temporary supply restrictions when they understood its rationale and information was clearly communicated.The importance of transparent, clear public communication using a variety of media was illustrated.Results also suggested that future supply restrictions should aim to limit the negative impact experienced by a small, but not insignificant, segment of the population.
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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 | 0.003 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.395 | 0.202 |
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".