Comparative predictive validity of the Harris Infant Neuromotor Test and the Alberta Infant Motor Scale
Bibliographic record
Abstract
AIM: We compared abilities of the Alberta Infant Motor Scale (AIMS) and the Harris Infant Neuromotor Test (HINT), during the infant's first year, in predicting scores on the Bayley Scales of Infant Development (BSID) at age 2 and 3 years. METHOD: This prospective study involved 144 infants (71 females, 73 males), assessed with the HINT and AIMS at 4 to 6.5 and 10 to 12.5 months and with the BSID at 2 and 3 years. Inclusion criteria for typical infants (n=58) were the following: 38 to 42 weeks' gestation, birthweight at least 2500g, and no congenital anomaly, postnatal health concern, nor major prenatal or perinatal maternal risk factor. For at-risk infants (n=86), inclusion criteria were any of the following: less than 38 weeks' gestation, birthweight less than 2500g, maternal age older than 35 years or younger than 19 years at infant birth, maternal psychiatric/mental health concerns, prenatal drug/alcohol exposure, multiple births, or use of reproductive technology. RESULTS: For the overall sample, the early (4-6.5mo) HINT had higher predictive correlations than the AIMS for 2-year BSID-II motor outcomes (r=-0.36 vs 0.26), and 3-year BSID-III gross motor outcomes (r=-0.45 vs 0.31), as did the 10- to 12.5-month HINT (r=-0.55 vs 0.47). Correlations were identical for 10- to 12.5-month HINT and AIMS scores and 3-year BSID-III gross motor (r=-0.58 and 0.58) and fine motor (r=-0.35 and 0.35) subscales. When the sample was divided into typical and at-risk groups, predictive correlations were consistently stronger for the at-risk infants. Categorical predictive analyses were reasonably similar across both tests. INTERPRETATION: Results suggest that the HINT has comparable predictive validity to the AIMS and should be considered for use in clinical and research settings.
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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 | 0.003 | 0.020 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 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".