Twenty-first-Century Skills: Teaching Empathy to Health Professions Students
Bibliographic record
Abstract
A key component of therapeutic relationships is the ability of medical professionals to empathize with patients, as research indicates a link between a healthcare worker's ability to empathize with patients and improved patient outcomes. Empathy - the ability to perceive the meaning and feelings of another and to communicate those feelings to others - may be an innate concept, but it is shaped through behaviours and experiences. It is imperative, then, that post-secondary students entering the medical field be taught to develop empathy in order to facilitate positive patient outcomes. Embedding empathy-based education in the curriculum of medical, nursing, and allied health programs early in the course of study can help students understand the patient's perspective and facilitate positive therapeutic relationships early in students' professional careers. The shift from traditional teaching and learning styles to online learning has created deficiencies such as gaps in communication, empathy, and the development of emotional intelligence. To address these gaps, new and innovative ways to teach empathy, such as simulation, can be employed.
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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 | 0.006 | 0.022 |
| Meta-epidemiology (narrow) | 0.004 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.004 | 0.004 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.004 | 0.002 |
| Research integrity | 0.020 | 0.024 |
| Insufficient payload (model declined to judge) | 0.005 | 0.005 |
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".