Screening for motor deficits using the Pediatric Evaluation of Disability Inventory (PEDI) in children with language impairment
Bibliographic record
Abstract
OBJECTIVE: To evaluate the association between the Pediatric Evaluation of Disability Inventory (PEDI) motor and self-care domains with the Peabody Developmental Motor Scales-second edition (PDMS-2) gross motor and fine motor sub-scales. METHODS: Forty children (35-62 months) with primary language impairment (PLI) were recruited. The PEDI was completed at admission and the PDMS-2 was administered within 1 month by an OT, who was unaware of the PEDI results. RESULTS: Correlation between PEDI mobility and PDMS-2 gross motor domains was r = 0.23 (p = 0.15) and between PEDI self-care and PDMS-2 fine motor domains was r = 0.12 (p = 0.47). Associations between PEDI and PDMS-2 scores for age, gender and severity of language impairment sub-groups were poor-to-moderate. CONCLUSION: Findings indicate the PEDI is not sufficiently accurate to screen for motor deficits in children with PLI. More sensitive measures of motor performance are needed to detect subtle motor deficits in children with PLI.
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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 | 0.001 | 0.006 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 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".