Health care providers' judgments in chronic pain: the influence of gender and trustworthiness
Why this work is in the frame
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Bibliographic record
Abstract
Estimates of patients' pain, and judgments of their pain expression, are affected by characteristics of the observer and of the patient. In this study, we investigated the impact of high or low trustworthiness, a rapid and automatic decision made about another, and of gender and depression history on judgments made by pain clinicians and by medical students. Judges viewed a video of a patient in pain presented with a brief history and rated his or her pain, and the likelihood that it was being exaggerated, minimized, or hidden. Judges also recommended various medical and treatment options. Contrary to expectations, trustworthiness had no main effect on pain estimates or judgments, but interacted with gender producing pervasive bias. Women, particularly those rated of low trustworthiness, were estimated to have less pain and to be more likely to exaggerate it. Unexpectedly, judgments of exaggeration and pain estimates were independent. Consistent with those judgments, men were more likely to be recommended analgesics, and women to be recommended psychological treatment. Effects of depression history were inconsistent and hard to interpret. Contrary to expectations, clinicians' pain estimates were higher than medical students', and indicated less scepticism. Empathy was unrelated to these judgments. Trustworthiness merits further exploration in healthcare providers' judgments of pain authenticity and how it interacts with other characteristics of patients. Furthermore, systematic disadvantage to women showing pain is of serious concern in healthcare settings.
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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 | 0.003 | 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 | 0.000 |
| 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 it