Initial development and validation of the Caregiver Priorities and Child Health Index of Life with Disabilities (CPCHILD)
Bibliographic record
Abstract
This paper reports the development and validation of a disease‐specific measure of health status and well‐being of children with severe cerebral palsy (CP). The Caregiver Priorities and Child Health Index of Life with Disabilities (CPCHILD) was constructed from recommendations from caregivers, healthcare providers, and review of other measures. Items spanning six domains are rated on an ordinal scale. Standardized scores (0–100) are reported for each domain and in total. Primary caregivers (n=77) of 45 males and 32 females between 5 and 18 years of age (mean age 13y 5mo [SD 3y 4mo]) with CP, categorized by the Gross Motor Function Classification System (GMFCS) level, completed the CPCHILD. Caregivers of children with severe CP (GMFCS Levels IV and V) also completed a second administration of the CPCHILD 2 weeks after the first. The mean CPCHILD score for children with severe CP was 56.2 (SD 15.7; range 24–93). The mean CPCHILD scores for children in GMFCS Levels I to V were 22.0, 38.2, 23.0, 44.5, and 59.3 respectively (p < 0.001). Reliability was tested in 41/52 caregivers who reported no change in health status between the two administrations of the CPCHILD. The intraclass correlation coefficient was 0.94 (95% confidence interval 0.90–0.97). The CPCHILD seems to be a reliable and valid measure of caregivers’perspectives on the health status, functional limitations, and well‐being of these children.
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 | 0.016 | 0.022 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| 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".