Attractiveness, diagnostic ambiguity, and disability cues impact perceptions of women with pain.
Bibliographic record
Abstract
PURPOSE/OBJECTIVE: This experimental study investigated how physical attractiveness, disability cue, and diagnostic ambiguity stereotypes impact perceptions of a patient's pain/disability and personality. RESEARCH METHOD/DESIGN: After viewing photographs of women pictured with or without a cane, accompanied by descriptions of the women's diagnosis (fibromyalgia or rheumatoid arthritis), 147 university students rated the women's pain/disability and personality. RESULTS: Analyses revealed that more attractive women received lower ratings on pain/disability and higher ratings (more positive) on personality. Moreover, those pictured with a disability cue got higher ratings on both pain/disability and personality, and those with medical evidence of pathology (less ambiguity) got higher ratings on pain/disability and lower ratings on personality. Examination of the 3 stereotypes in a single study enabled an evaluation of their interactions. An Attractiveness × Disability Cue × Diagnostic Ambiguity interaction for ratings of pain/disability revealed that the presence of both medical evidence and a disability cue were needed to override the strong "beautiful is healthy" stereotype. Significant 2-way interactions for ratings of personality indicated that the impact of the disability stereotype tends to be overshadowed by the attractiveness stereotype. CONCLUSION/IMPLICATIONS: The results indicate that these stereotypes have a large effect on perceptions of women with chronic pain and that attractiveness, a contextual variable unrelated to the pain experience, exerts an even stronger effect when there is less objective information available. This could have clinical ramifications for assessment and treatment of patients with chronic pain, which often occurs in the absence of "objective" medical evidence or any external cues of disability.
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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 | 0.002 | 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 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".