Don’t tell me, show me: Reactions from those with lived experience to the 2020 revised IASP definition of pain
Bibliographic record
Abstract
In 2020, the International Association for the Study of Pain (IASP) revised the definition of pain, providing an update to IASP's original definition in place since 1979. The origins of the field of pediatric pain, born in part in the 1980s from the advocacy of Jill Lawson, mother to Jeffrey Lawson who experienced gross inadequacies in pain care as a premature infant, emphasize the critical need to listen to and act with the voice of people living with pain and their families and caregivers. Furthermore, the field of pediatric pain emerged in the mid-1980s marking this revised definition of pain as the first opportunity within which the experience and science of pain in childhood has been considered. This invited commentary offers two lived experience reactions to the revised IASP definition of pain, from the perspective of one's own experience with pain during childhood and as parents and family members. Together, they highlight that the value of a revised definition must be judged on its ability to directly benefit children experiencing pain and their families. Their skeptical hope reflects their lived experience backed by empirical evidence demonstrating continued inequities and inadequacies in preventing and managing pediatric pain. We must mobilize together to ensure change in culture, knowledge, and behavior. With the combined efforts of researchers, healthcare professionals, and policymakers, in partnership with diverse people with lived experience, we can ensure that more effective action is taken to rapidly improve pain for children and their families.
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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 | 0.048 | 0.112 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.025 | 0.049 |
| Scholarly communication | 0.015 | 0.018 |
| Open science | 0.005 | 0.017 |
| Research integrity | 0.025 | 0.046 |
| Insufficient payload (model declined to judge) | 0.003 | 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".