Postoperative Self‐Report of Pain in Children: Interscale Agreement, Response to Analgesic, and Preference for a Faces Scale and a Visual Analogue Scale
Bibliographic record
Abstract
OBJECTIVE: To augment available validation data for the Faces Pain Scale – Revised (FPS‐R) and to assess interscale agreement and preference in comparison with the Coloured Analogue Scale (CAS) in pediatric acute pain. METHOD: The present prospective, multicentre study included 131 inpatients five to 15 years of age (mean age 8.8 years; 56% male) seen in postoperative recovery. They provided CAS and FPS‐R pain scores before and after administration of analgesic medication. Nurses and physicians used the same tools as observational scales. Children and health care providers indicated which scale they preferred. RESULTS: FPS‐R scores for the intensity of postoperative pain correlated highly with the corresponding CAS scores in all age groups (0.66 ≤ r ≤ 0.88). There were no significant mean differences in any age group between the scales. Scores on the two scales differed by 2/10 or less in 81% to 91% of children, depending on age. Both scales demonstrated expected changes in postoperative pain following administration of an analgesic. Scores at the upper end point were given by approximately 20% of children five to six years of age on both scales, compared with 2% to 9% in the older age groups. Health care providers’ observational ratings were significantly lower than self‐ratings. The FPS‐R was preferred over the CAS by most children in all age groups and both sexes. Global satisfaction of the health care providers was similar for both tools. DISCUSSION: These results support the use of the FPS‐R for most children five years of age or older in the postoperative period. Further research is needed to identify young children, particularly those younger than seven years of age, who have difficulty with self‐report tools, and to establish methods for training them in the reliable use of these measures.
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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 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".