Evidence for the development of skills for education, leadership and innovation through experiential‐based foundational pharmacy residency programs: a narrative review
Bibliographic record
Abstract
Abstract Aim The aim of this narrative literature review was to describe the existing evidence for a post‐graduate experiential learning program, such as a foundational pharmacy residency, to support the competency development for early‐career pharmacists in conducting education, leadership and supporting innovation. Methods We identified publications that addressed research in skills development within foundational pharmacy residency programs. Articles were identified using the databases Scopus and Embase. Results It was found that foundational residency programs have supported competency development in delivering education, leadership and management, and support of innovation and quality improvement. Residency programs have fostered these skills development through the use of courses, assessments and activities, but to varying degrees. Many of these skills are attained as a benefit of inclusion and mentorship in non‐clinical tasks. Conclusion Residency programs can serve as a strong platform for the development of non‐clinical skills in education, leadership and innovation. A mix of activities and course‐specific skills building courses have demonstrated levels of success in developing skills in education, leadership and innovation when implemented.
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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 | 0.009 | 0.047 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.010 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".