Motor Development of Infants with Positional Plagiocephaly
Bibliographic record
Abstract
Concurrent with recommendations to place infants to sleep in supine, there has been a dramatic increase in the number of infants with positional plagiocephaly (PP). Recent evidence suggests that infants who have decreased exposure to prone position may have a higher incidence of PP and may be at risk for a delay in the acquisition of certain motor skills. The purpose of this study was to compare motor development between infants with PP and matched peers without PP. We also examined differences in infant positioning practices when asleep and awake between the two groups. Twenty-seven infants with PP, 3 to 8 months of age, were matched by age, gender, and race to infants without PP. Motor performance was evaluated using the Alberta Infant Motor Scale (AIMS) and the Peabody Developmental Motor Scales (PDMS). Parents completed a diary that recorded infant positioning over a 3-day period. Mean AIMS percentile score for infants with PP was 31.1 +/- 21.6 as compared with 42.7 +/- 20.2 in infants without PP (p = .06). Better performance on the AIMS was positively correlated with the amount of time in prone position when awake, for both groups of children (PP r = .52, no PP r = .44, p < .05). Therapists should be aware of a risk of a motor delay when evaluating infants with PP. It is also important for parents to be informed about the importance of supervised prone playtime to enhance the development of early motor skills.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.003 |
| 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 | 0.000 |
| 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".