Development of a parent‐report computer‐adaptive test to assess physical functioning in children with cerebral palsy I: lower‐extremity and mobility skills
Bibliographic record
Abstract
The objective of this project was to develop computer-adaptive tests (CATs) using parent reports of physical function in children and adolescents with cerebral palsy (CP). The specific aims of this study were to (1) examine the psychometric properties of an item bank of lower-extremity and mobility skills for children with CP; (2) evaluate a CAT using this item bank; (3) examine the concurrent validity of the CAT with the Pediatric Outcomes Data Collection Instrument (PODCI) and the Functional Assessment Questionnaire (FAQ); and (4) establish the discriminant validity of simulated CATs with Gross Motor Function Classification System (GMFCS) levels and CP type (diplegia, hemiplegia, or quadriplegia). Parents (n=190) of children and adolescents with spastic diplegic (48%), hemiplegic (22%), or quadriplegic (30%) CP consisting of 108 males and 82 females with a mean age of 10 years 7 months (SD 4y 1mo, range 2-21y) and in GMFCS levels I to V participated in item pool calibration and completed the PODCI and FAQ. Confirmatory factor analyses supported a unidimensional model for the 45 basic lower-extremity and mobility items. Simulated CATs of 5, 10, and 15 items demonstrated excellent accuracy (intraclass correlation coefficients [ICCs] >0.91) with the full item bank and had high correlations with PODCI transfers and mobility (ICC = 0.86) and FAQ scores (ICC = 0.77). All CATs discriminated among GMFCS levels and CP type. The lower-extremity and mobility skills item bank and simulated CATs demonstrated excellent performance over a wide span of ages and severity levels.
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 | 0.003 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| 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".