Influence of supine sleep positioning on early motor milestone acquisition
Bibliographic record
Abstract
This study aimed to determine whether supine sleep-positioned infants have delayed motor skills at age 4 and 6 months, and if delays are associated with decreased exposure to prone position. One 4 and one 6-month-old sample of healthy infants born at term were recruited. Motor assessments included the Peabody Developmental Motor Scale (PDMS) and Alberta Infant Motor Scale (AIMS). Parents completed an infant behavior diary for 3 consecutive days. Seventy-one 4-month-old infants were assessed (38 males; mean age 4.4 mo, standard deviation [SD] 0.2). Mean motor scores were close to normative standards (AIMS 47.7, SD 19.6; PDMS gross motor quotient [GMQ] 96.3, SD 6.5; PDMS fine motor quotient [FMQ] 99.2, SD 4.8). No infant scored below cut-off values used to identify motor delay. Milestones less likely to be achieved included extended arm support in prone, hands to feet in supine, and sitting with arm support. Exposure to 'tummy time' while awake was correlated with AIMS scores (r = 0.38, p < 0.01). F i fty 6-month-old infants were assessed (21 males; mean age 6.4 mo, SD 0.4). Mean scores were shifted down for all scales, and as much as 1 SD for PDMS (AIMS 44.5, SD 21.6; PDMS GMQ 85.7, SD 7.6; PDMS FMQ 88.9, SD 9.0). Only 22% of 6-month-olds could sit without arm support versus 50% expected in a normative sample. Remarkably, 22% of our sample exhibited gross motor delays (quotient <78). Tummy time (awake) was significantly associated with the AIMS (r = 0.64) and PDMS GMQ (r = 0.55) and FMQ (r = 0.33) quotients, even after adjusting for confounders. Typically developing infants who were sleep-positioned in supine had delayed motor development by age 6 months, and this was significantly associated with limited exposure to awake prone positioning. This has important implications for interpreting motor assessments of infants at risk and for preventing inappropriate referrals.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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".