Identifying and Mapping Canadian Dietetic Students’ Interaction(s) with Simulation-Based Education: A Scoping Review
Bibliographic record
Abstract
This scoping review mapped literature available on Canadian dietetics, nutrition, and foods students’ and graduates’ interaction(s) with simulation-based education (SBE) during undergraduate and/or practicum. One certified Librarian led the preliminary search (Summer, 2021), while three Joanna Briggs Institute-trained reviewers conducted the comprehensive search via MEDLINE (OVID), CINAHL (EBSCO), Academic Search Premier (EBSCO), Embase (Elsevier), Scopus (Elsevier), and Google (February 2022). A data extraction tool designed specifically for the study objectives and research inclusion criteria was used. We recorded 354 results and included 7. Seven types of SBE were recorded: (i) comprehensive care plan (n = 2); (ii) nutritional diagnosis/assessment (n = 2); (iii) body composition assessment (n = 1); (iv) introducing patient to dysphagia care (n = 1); (v) nutrition counselling session (n = 1); (vi) nutrition-focused physical examination (n = 1); and (vii) professional communications via social media (n = 1). Results indicate that Canadian dietitian-led SBE includes the use of simulated patients, nutritional diagnosis/assessment, and the creation of comprehensive care plans, among others. Students have been assessed for performance of trained tasks through exams, self-awareness surveys, and interviews, and SBE activities have been evaluated for effectiveness through questionnaires and interviews with users/students. Canadian literature is limited, and more can be learned by exploring the global context within and outside the profession.
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 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 | 0.029 | 0.121 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.004 | 0.004 |
| Bibliometrics | 0.062 | 0.092 |
| Science and technology studies | 0.005 | 0.002 |
| Scholarly communication | 0.007 | 0.003 |
| Open science | 0.004 | 0.004 |
| 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".