The Relationship between Empathy and Estimates of Observed Pain
Bibliographic record
Abstract
OBJECTIVE: Recent research suggests that higher scores on measures of empathy correlate with a stronger response to observed pain, as well as higher estimates of pain intensity. Little work to date has examined the impact of empathy on evaluations of different levels of expressed pain, or how empathy may alter the accuracy of interpreting these painful facial expressions. This study examines the role of empathy in rating the intensity of facial expressions of pain, and the accuracy of these ratings relative to self-reported pain. The potential mediating role of available pain cues or the moderating role of gender on this relationship are also examined. METHODS: Undergraduate participants (observers, N = 130) were shown video clips of facial expressions of individuals from a cold presser pain task (senders), and then asked to estimate that pain experience. This estimate was compared with the video sender's actual pain ratings. RESULTS: Higher empathy was associated with an overall increase in estimates of senders' pain, which was not mediated by video subject or participant gender or the duration of painful facial expressions. Further analyses revealed that high empathy was associated with greater accuracy in inferring pain on only one of three inferential accuracy indices. CONCLUSIONS: While observers with greater empathy may infer greater pain in senders, resulting in a smaller underestimation bias overall, they are not necessarily more accurate in estimating pain on any given stimuli. The importance of these potential differences in perceived pain for clinical assessment and interpersonal relationships are discussed.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.007 | 0.030 |
| 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 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".