Differences in responses to English and Korean versions of the Caregiver Priorities & Child Health Index of Life with Disabilities (CPCHILD)
Bibliographic record
Abstract
BACKGROUND: The purpose of this study was to identify differences in caregiver responses to Korean-language and English-language versions of the Caregiver Priorities & Child Health Index of Life with Disabilities (CPCHILD) questionnaire. METHODS: Patient data were acquired from the Cerebral Palsy Hip Outcomes Project database, which was established to run a large international multicenter prospective cohort study of the outcomes of hip interventions in cerebral palsy. Thirty-three children whose caregivers had completed the Korean version of CPCHILD were matched by propensity scoring with 33 children whose parents completed the English version. Matching was performed on the basis of 12 covariates: age, gender, gross motor function classification system level, migration percentage of right and hip, seizure status, feeding method, tracheostomy status, pelvic obliquity, spinal deformity, parental report of hip pain and contracture interfering with care. RESULTS: There were no significant differences in CPCHILD scores for section 4 (Communication and Social Interaction), and section 5 (Health) between two groups. Korean-language CPCHILD scores were significantly lower than English-language CPCHILD scores for section 1 (Personal Care/Activities of Daily Living), section 2 (Positioning, Transferring and Mobility), section 3 (Comfort and Emotions) and section 6 (Overall Quality of Life) as well as in terms of total score. CONCLUSIONS: Cultural influences, and the community or social environment may impact the caregivers' perception of the health-related quality of life of their children. Therefore, physicians should consider these differences when interpreting the study outcomes across different countries.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".