Clinical validation of the Paediatric Pain Profile
Bibliographic record
Abstract
The Paediatric Pain Profile (PPP) is a 20–item behaviour rating scale designed to assess pain in children with severe neurological disability. We assessed the validity and reliability of the scale in 140 children (76 females, mean age 9 years 11 months, SD 4 years 7 months; range 1 to 18 years), unable to communicate through speech or augmentative communication. Parents used the PPP to rate retrospectively their child's behaviour when‘at their best’and when in pain. To assess interrater reliability, two raters concurrently observed and individually rated each child's behaviour. To assess construct validity and responsiveness of the scale, behaviour of 41 children was rated before and for four hours after administration of an‘as required’analgesic. Behaviour of 30 children was rated before surgery and for five days after. Children had significantly higher scores when reported to have pain than‘at their best’and scores increased in line with global evaluations of pain. Internal consistency ranged from 0.75 to 0.89 (Cronbach's alpha) and interrater reliability from 0.74 to 0.89 (intraclass correlation). Sensitivity (1.00) and specificity (0.91) were optimized at a cut‐off of 14/60. PPP score was significantly greater before administration of the analgesic than after (paired‐sample t ‐tests, p < 0.001). Though there was no significant difference in mean pre‐ and postoperative scores, highest PPP score occurred in the first 24 hours after surgery in 14 (47%) children. Results suggest that the PPP is reliable and valid and has potential for use both clinically and in intervention research.
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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 | 0.018 | 0.044 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".