‘Low‐normal’ motor skills in infants at high risk for poor developmental outcomes: A prevalence and prognostic study
Bibliographic record
Abstract
AIM: To investigate the prevalence and prognostic value of 'low-normal' motor skills in infants at high-risk for poor developmental outcomes. METHOD: Infants born extremely low-birthweight and extremely preterm discharged from neonatal intensive care between 2015 and 2018 completed the Alberta Infant Motor Scale (AIMS), Neuro-Sensory Motor Developmental Assessment (NSMDA) at corrected age 4, 8, and 12 months, and Griffiths Mental Development Scale at corrected age 12 months. RESULTS: Participating infants (n = 191) with a mean gestational age (95% confidence interval [CI]) of 26.80 weeks (26.60, 27.1) and mean birthweight (95% CI) of 869 grams (843, 895) included 45 (23.80%) infants small for gestational age. AIMS rated 50.32%, 35.37%, and 14.86% of infants within the 'low-normal' motor skills range (1-2 SD below the mean for age) at 4, 8, and 12 months respectively. Of the infants within the AIMS 'low-normal' skills range, 55.70%, 88.46%, and 59.10% were classified as having impairment by NSMDA at 4, 8, and 12 months respectively. Griffiths assessment at 12 months identified only 7.33% of infants with 'low-normal' skills and 3.33% with motor disability. Minimal motor impairment rating on the NSMDA at 4 or 8 months significantly predicted general development at 12 months. INTERPRETATION: High-risk infants with 'low-normal' motor skills may warrant referral to early intervention as associated impairment represents increased risk for poorer general development outcomes. WHAT THIS PAPER ADDS: High prevalence of 'low-normal' motor skill exists in high-risk infants. Clinical motor assessment validly identifies infants with motor impairment. Minimal motor impairment in high-risk infants is prognostic of general development. High-risk infants with 'low-normal' motor skills may warrant early intervention. Griffiths Scales of Child Development, Third Edition assessment at 12-months age may under-identify motor difficulties.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".