Using mock interviews to prepare pharmacy students for professional placement: Results from a pilot study
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Introduction: Mock interviews were introduced into a second-year pharmacy course with an embedded pharmacy placement. The aim was to prepare pharmacy students for interviews with possible preceptors when seeking community pharmacy placements. This study aimed to assess students’ perspectives on the impact of this activity. Methods: Second year pharmacy students (n = 35) were provided with general interview guidance and participated in mock placement interviews conducted by community pharmacists. After participating in the mock interview, students were invited to complete two online questionnaires. The first questionnaire was completed following the mock interview and the second questionnaire was completed after students had secured professional placements. Both surveys contained multiple domains including student approach to placement, perceived impact of the mock interview on confidence and preparation, application of the feedback on their real-life interview, understanding employer priorities, linkage with the curriculum and overall student satisfaction. Results: Following the mock interview, most participants (89.5%, n = 17) indicated that they felt better prepared to approach a placement preceptor and for the interview process. All participants who completed the first questionnaire (100%, n = 19) agreed that the feedback following the mock interview was helpful. After securing a placement, more than half (56.5%, n = 13) indicated that they used the skillsets developed during the mock interview when approaching a placement preceptor. Conclusion: The inclusion of mock interviews in the pharmacy curricula was found beneficial and conducive to enhanced skills and confidence in students’ career development.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 it