Changes in Dental Student Empathy During Training
Bibliographic record
Abstract
Because empathic patient interactions by dentists are associated with improved patient outcomes, self-reported declines in empathy during dental student training are a concern. This study examined differences in empathy in 178 dental students at the University of Toronto and the University of Western Ontario from years one through four using an anonymous self-report web-based survey in a cross-sectional design. To localize the effects of training on empathy, an instrument that separately evaluated emotive (Emo) and cognitive (Cog) types of empathy in both personal (Per) and professional (Pro) contexts was developed, using items modified from previously validated scales and resulting in an empathy scale with four thirteen-item subscales (Per-Emo, Per-Cog, Pro-Emo, Pro-Cog). The response rate was 36.5 percent, and all subscales showed good reliability and validity. A 2x2x4 mixed design ANOVA tested differences in mean scores among the four subscales across the four years of training. Following a significant three-way interaction, subanalyses demonstrated no significant effects in the Per-context, but a significant year by empathy-type interaction in the Pro-context. Post hoc analyses of Pro measures indicated year three emotive empathy scores were significantly lower than earlier years, whereas years three and four cognitive empathy scores were significantly higher. This isolated decrease in Pro-Emo empathy with an increase in Pro-Cog empathy is consistent with the development of "professional empathy," described elsewhere as detached concern.
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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 | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".