Bibliographic record
Abstract
pharmacists ’ knowledge and beliefs regarding the use of bioidentical hormones (BHs) for the management of menopause related symptoms. Methods: Using Dillman’s tailored design methodology, an invitation to complete the web-based questionnaire was emailed to pharmacists in NS as part of the Dalhousie College of Pharmacy Continuing Pharmacy Education Department’s (CPE) weekly email update. Data was analyzed using descriptive statistics. Results: Of approximately 1300 e-mails sent, 113 pharmacists completed the questionnaire (response rate 8.7%). The majority of respondents (94%) knew that BHs were not free from adverse drug reactions. More than 50 % were aware that conjugated equine estrogens and medroxyprogesterone acetate were not examples of BHs. For seven of eleven knowledge questions, 33-45 % indicated that they did not know the answer. When asked about their beliefs regarding BHs, many believed that BHs were similar in efficacy (49%) or more effective (21%) than conventional hormone therapy (CHT) for vasomotor symptoms. Most respondents also believed that both BHs and CHT had similar safety profiles. Additionally, responding pharmacists indicated that more education would be helpful, especially in the area of safety and efficacy of BHTs compared to CHT. Conclusion: NS pharmacists knew BHs were not free of adverse effects, however knowledge was lacking in other areas. This may reflect the level of coverage of this topic in pharmacy school curriculums and in the pharmacy literature. Results indicate a need for additional education of NS pharmacists with respect to BHs, which could be accomplished through modification of undergraduate pharmacy programs and supplementary CPE.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.758 | 0.567 |
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".