Pharmacy Students Leading Pharmacy Practice Change
Bibliographic record
Abstract
Objective:To develop an interview tool for students to help assess a potential employer's willingness to allow new employees to practice patient-centred care and thereby allow the student to make better-informed employment decisions. Methods:We developed an interview tool by asking leading pharmacists what requests they would make to facilitate a high level of patient-centred care if they were applying for a new job. Responses to this question were compiled until saturation was apparent. The requests were ranked by frequency and the level of importance described by the interviewed pharmacists and used to develop a list of supports found to be critical in delivering a high level of patient-centred care. The interview tool was then designed to move the student from open-ended questions about patient-centred care to specifically asking the interviewer to address supports for patient-centred care. The interview tool also provided students with important definitions, suggested phrasing for questions, and room for individualized questions. An accompanying interview guide for students was developed based upon previous work by CAPSI. The guide included background information about the current state of pharmacy practice, interviewing resources, an extensive list of interview questions and the interview tool with instructions for its use. The materials were printed and posted on the websites of CAPSI (www.capsi.ca/compris.php) and COMPRIS (www.epicore.ualberta.ca/compris/PharmacyGuide.html). Hard copies were distributed through CAPSI representatives at each Canadian school of pharmacy in September 2007 and at CAPSI's 2008 Professional Development Week. Our next steps include:•Translation into French•Distribution of hard copies to first-year students in September 2008•Display booth at Professional Development Week 2009•Updating the tool and guide based on comments received from students Conclusion:Students will help to make pharmacy practice more patient-centred by asking critical questions, negotiating for patient care supports, and ultimately influencing the manner in which they are recruited. Evaluation of the program is ongoing. Feedback from students has been exceptional: “Overall, I believe the employers were caught off guard by the tool's questions and the shift of focus to them, their fit for me. I had confidence in the tool and in the market strength for pharmacists.” “It changed the interview; instead of me having to impress them, it was they who were trying to impress me. I totally felt like I was in the driver's seat and came out of that interview knowing I'd nailed it.” “By using the questions outlined in the tool, I negotiated with a pharmacy manager until he redefined a position that was focused on dispensing to one with a clinical focus.”
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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 | 0.007 | 0.018 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.002 |
| Scholarly communication | 0.008 | 0.003 |
| Open science | 0.002 | 0.010 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.034 | 0.008 |
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".