A novel interprofessional shadowing initiative for senior medical students
Bibliographic record
Abstract
BACKGROUND: Interprofessional collaboration is vital to patient care. However, many medical students interact poorly with nurses during clinical clerkships, and less is known about their relationships with other healthcare professionals (HCPs). Two nurse shadowing interprofessional education (IPE) initiatives for first-year medical students have been studied. Similar programs for senior medical students have not been reported and none have included non-nurse HCPs. METHODS: Two-hundred seven third-year medical students were assigned to shadow a HCP from one of 20 professions for a two-hour period, one week prior to clerkship. The authors analyzed Likert-like rating scales and qualitative feedback from post-experience surveys. RESULTS: A large majority (92.3%) of the 207 respondents found the experience to be a valuable component of their medical education. Three quarters (74.9%) of students felt better equipped to communicate with HCPs. Qualitative feedback revealed students felt the program was practical, improved their understanding of HCPs and wanted additional similar opportunities to learn about HCPs. CONCLUSIONS: Analysis of this innovative IPE intervention suggests it may benefit senior medical students and other HCPs. Other medical schools may wish to pilot similar IPE activities in order to prepare a collaborative, practice-ready health workforce.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
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 | 0.005 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.027 | 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 teacher head, 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".