Empathy hurts: Compassion for another increases both sensory and affective components of pain perception
Bibliographic record
Abstract
Recent studies demonstrate that some brain structures activated by pain are also engaged when an individual observes someone else in pain, and that these empathy-related responses are modulated as a function of the affective link between the empath and the individual in pain. In this study we test the hypothesis that empathy-evoked activation in the pain network leads to heightened pain perception. After inducing in half of our subjects a state of high empathy for an actor and in the other half a state of low empathy towards him, we measured the sensitivity to heat stimuli of various intensities in healthy participants while they watched the actor being exposed to similar stimuli. Participants in the "high-empathy" group rated painful (but not non-painful) stimuli applied to themselves as more intense and unpleasant than did those in the "low-empathy" group. Positive correlations between state empathy scores and pain ratings further suggest that this perceptual phenomenon depends on the magnitude of empathic response induced in the participants. The effects were observed when subjects watched the model receiving either neutral or painful stimuli, suggesting that it is empathy itself that alters pain perception, and not necessarily the observation of pain behaviors.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 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".