Intrinsic attention to pain is associated with a pronociceptive phenotype
Bibliographic record
Abstract
INTRODUCTION: Evidence suggests that attention to pain is a product of both incoming sensory signals and cognitive evaluation of a stimulus. Intrinsic attention to pain (IAP) is a measure that captures an individual's natural tendency to attend to a painful stimulus and may be important in understanding why pain disrupts cognitive functioning in some individuals more than others. OBJECTIVE: In this study, we explored the extent to which IAP was associated with the modulation of incoming sensory signals characteristic of a pronociceptive phenotype: temporal summation (TS) and conditioned pain modulation (CPM). METHOD: =23.57, S.D.=5.50) were assessed on IAP, TS and CPM. RESULTS: We found that IAP was positively correlated with TS and CPM. A regression model showed that TS and CPM explained 39% of the variance in IAP scores. Both mechanisms seem to contribute independently to the propensity to attend to pain. CONCLUSION: These findings highlight that modulatory mechanisms at the spinal/supraspinal level exert a strong influence on an individual's ability to disengage from pain.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.006 | 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".