Reliability and Acceptability to Caregivers of Telehealth Administration of the Pediatric Evaluation of Disability Inventory – Computer Adaptive Test (PEDI-CAT) for Brazilian Youth with Down Syndrome
Bibliographic record
Abstract
Purpose: To estimate test-retest reliability of the two versions of the PEDI-CAT administered via telehealth to caregivers of Brazilian young people with DS, to compare scores on the two versions, and to determine caregiver acceptance of telehealth administration of the assessment. Method: A methodological study approved by the research ethics committee. Data collection was performed online, with a mean duration of 45.0 minutes for the content-balanced version of the PEDI-CAT and 17.5 minutes for the speedy version. Results: In total, 28 caregivers of individuals with DS up to age 21 years participated (mean = 5.9 years; SD = 4.9 years). Intra-class correlation coefficients for the four domains of the PEDI-CAT content-balanced version and four domains of the PEDI-CAT speedy version ranged from 0.77 to 0.97. There was a statistical difference between the versions in the scores of the social-cognitive domain (p < 0.05). A mean of 105 items (SD = 21) was administered in the content-balanced version and a mean of 51 items (SD = 8) in the speedy version. All the caregivers found the method of administration of the PEDI-CAT acceptable. Conclusions: This study demonstrated that either version of the Brazilian version of the PEDI-CAT can be used by telehealth in clinical practice to assess children, adolescents, and young adults with DS.
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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 | 0.005 | 0.022 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".