What is pain: Are cognitive and social features core components?
Bibliographic record
Abstract
Pain is a universal experience, but it has been challenging to adequately define. The revised definition of pain recently published by the International Association for the Study of Pain addressed important shortcomings of the previous version; however, it remains narrow in its focus on sensory and emotional features of pain, failing to capture the substantial roles of cognitive and social core components of the experience and their importance to advances in pain management. This paper reviews evidence and theoretical models for the significant role social and cognitive factors play in pain experience and we argue that without explicit recognition of these core components in the definition, significant nuances are lost at a cost to understanding and clinical management of pain. A focus on sensory and emotional features perpetuates biomedical interventions and research, whereas recognition of cognitive and social features supports a multidimensional model of pain, advances in interdisciplinary care, and the benefits of cognitive behavioral therapy and self-management interventions. We also explore the six Key Notes that accompany the new definition of pain, discuss their application to the understanding of pain in childhood, and, in doing so, further explore social and cognitive implications. Considerations are also described for assessment and treatment of pain in pediatric populations.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".