Sex differences in perceived pain are affected by an anxious brain
Bibliographic record
Abstract
Decades of research confirm that women have greater pain sensitivity than men. Women also show greater overall anxiety sensitivity than men. Given these differences, we hypothesized that sex differences in anxiety would explain sex differences in experienced pain and physiological responses to pain (at both spinal and cortical levels). By measuring subjective pain, state/trait anxiety, nociceptive flexion reflexes, and somatosensory evoked potentials (SEPs), it was possible to test the effects of anxiety on the processing of painful drives at different levels of the neuraxis while also documenting the role played by anxiety on sex differences in experienced pain. Results confirm that women are indeed more sensitive to pain than men. Importantly, this difference was accompanied by a significant sex difference in cortical activity (SEP amplitude) but not spinal nociceptive activity, suggesting that much of the sex difference in experienced pain is attributable to variations in thalamocortical processing and to ensuing changes in the appraisal of and/or emotional response to noxious insult. In support of this claim, we found that sex differences in cortical activity and subjective pain disappeared when trait anxiety was controlled for. This means that stable predispositions to respond with heightened apprehension contribute to baseline pain sensitivity differences between the sexes. These results indicate that the modulatory effect of affect on pain-related brain processes may explain why men and women experience painful shocks so differently. In our study, the mediating role of anxiety on sex differences in pain was tested and confirmed using path analysis.
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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 | 0.000 |
| 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".