Psychometric properties of the non-communicating children's pain checklist-revised
Bibliographic record
Abstract
The non-communicating children's pain checklist (NCCPC) has displayed preliminary validity and reliability for measuring pain in children with severe cognitive impairments (Dev Med Child Neurol 42 (2000) 609). This study provides evidence of the psychometric properties of a revised NCCPC (NCCPC-R) with a larger cohort of children. Caregivers of 71 children with severe cognitive impairments (aged 3-18) conducted observations of their children using the NCCPC-R during a time of pain and a time without pain. Fifty-five caregivers completed a second set of observations. The score results on the NCCPC-R were: internally consistent, significantly related to pain intensity ratings provided by caregivers, consistent over time, sensitive to pain, and specific to pain. Analyses of children's individual scores indicated up to 95% of their scores were consistent. Receiver operating characteristic curves suggest a score of 7 or greater on the NCCPC-R as indicative of pain in children with cognitive impairments, with 84% sensitivity and up to 77% specificity. These results provide evidence of NCCPC-R having excellent psychometric properties.
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 | 0.010 | 0.042 |
| Meta-epidemiology (narrow) | 0.001 | 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 | 0.001 | 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".