Articles Current Methods Used to Teach the Medication History Interview to Doctor of Pharmacy Students
Bibliographic record
Abstract
Current practices used to teach the medication history interview to Doctor of Pharmacy students were examined. An online survey was emailed to curriculum committee chairpersons at all 91 schools of pharmacy in the United States and Canada. Responses numbered 45 (48.9 percent). Respondents answered questions regarding how medication history interview skills are illustrated, practiced, and evaluated at their schools. Lack of consistency in interviewing skills taught at different schools was found. A mean of 8.62 ± 2.94 skills of 13 recommended skills was being taught. As schools introduce practice experiences earlier in the curriculum, an early introduction of the medication history interview may be beneficial. At 48.4 percent of the schools, the medication history interview was taught before the end of the first year. An interest was expressed by the respondents (97.8 percent) for a CD-ROM of a simulated medication history interview for use as a teaching tool.
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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 | 0.010 | 0.041 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.006 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.010 | 0.002 |
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".