Empathy Levels in Canadian Paramedic Students: A Longitudinal Study
Bibliographic record
Abstract
Background Empathy in healthcare delivery is an essential component to providing high-quality patient care. Empathy in paramedics and paramedic students has been subject to limited study to date. This study aimed to determine the empathy levels demonstrated by first year paramedic students over the course of their first year of study. Methods This study employed a longitudinal design of a convenience sample of first year paramedic students in a community college program in Ontario, Canada. The Medical Condition Regard Scale (MCRS) was used to measure empathy levels across four medical conditions: intellectual disability, suicide attempt, substance abuse and mental health emergency. Surveys were conducted three times approximately 2-3 months apart; before first semester field placements (Nov/17), after first semester field placements (Jan/18) and near the end of second semester field placements (Mar/18). Results A total of 20 students completed all three surveys. Females, respondents aged 22-24, and participants with previous post-secondary education demonstrated higher mean empathy scores than their counterparts. Substance abuse was associated with the lowest mean empathy score for every demographic. Mean scores for intellectual disability, attempted suicide and mental health emergency decreased from the first survey to the last. Mean scores for substance abuse increased from 43.3 (SD±8.2) to 46.45 (SD±7.04). Conclusion Results from this study suggest that in general, empathy levels among paramedic students decline over the course of their education. Male paramedic students are less empathetic than their female counterparts, and those with previous post-secondary education displayed higher mean empathy scores. The findings in this research support previous findings, and suggest that paramedic education programs may benefit from the inclusion of additional empathy training and education.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.006 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".