Perceptions, knowledge, and perceived barriers to practicing evidence‐based medicine among pharmacists in Japanese community hospitals: A cross‐sectional multicenter survey
Bibliographic record
Abstract
Abstract Introduction Evidence‐based medicine (EBM) skills are required for pharmacists. However, the current status of EBM skills and its education in Japanese pharmacists remains unknown. Objectives We investigated the perceptions, knowledge, and barriers for EBM in Japanese pharmacists. Methods We conducted a cross‐sectional survey of pharmacists employed by four community hospitals in Japan. A questionnaire including 55 questions to evaluate pharmacists' perceptions, knowledge, exposure, access, terminology, and barriers for EBM was developed based on our previous research. Results The questionnaire was provided to 70 pharmacists and the response rate was 90% ( n = 63). Regarding the 5As (Ask, Acquire, Appraise, Apply, Assess) skills, only 30.2% of pharmacists were confident in their skills for Ask, 17.5% for Acquire, 19.0% for Appraise, 34.9% for Apply, and 25.4% for Assess. Additionally, although less than 20% of pharmacists felt comfortable teaching EBM to pharmacy residents and were confident to explain to others any EBM‐related terms, more than 90% of the pharmacists recognized the importance of EBM education for patient care. Furthermore, they reported many barriers to EBM, such as skills, statistical knowledge, training, English, and opportunities to practice EBM. Conclusion Although most Japanese pharmacists in this study were not confident in their EBM skills and in teaching them, they acknowledged the importance of EBM. Our study suggests that providing EBM training, and the clinical roles and responsibilities could address the identified barriers, such as, lack of skills, knowledge, and opportunities to practice EBM, and pharmacists could better embrace EBM in their practice to optimize patient care.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".