Pain evaluation and prosocial behaviour are affected by age and sex
Bibliographic record
Abstract
BACKGROUND: Pain assessment and pain care are influenced by the characteristics of both the patient and the caregiver. Some studies suggest that the pain of older persons and of females may be underestimated to a greater extent than the pain of younger and male individuals. AIMS: This study investigated the effect of age and sex on prosocial behavior and pain evaluation. METHODS: 40 young (18-30 y/o; 20 women) and 40 older adults (55-82 y/o; 20 women) acted as healthcare professionals rating the pain and offering help to patients of both age groups. Trait empathy and social desirability were measured with questionnaires. RESULTS: Linear mixed models showed that older and male patients were offered more help and were perceived as being in more intense pain than younger and female patients. CONCLUSION: The characteristics of the patients seem to have a greater impact on prosocial behavior and pain assessment compared to those of the observers, which bears significant implications for the treatment of pain in clinical contexts.
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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 | 0.008 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".