Relationship Between Prone Skills and Motor‐Based Problem‐Solving Abilities in Full‐Term and Preterm Infants During the First 6 Months of Life
Bibliographic record
Abstract
Motor experiences shape cognitive development in infancy, with the prone position being one such crucial motor experience in the first 6 months of life. Although the motor benefits of the prone position are well-documented, its influence on early cognitive abilities remains insufficiently explored. This study quantified the relationship between prone motor skills and motor-based problem-solving abilities in 48 full-term and preterm infants aged 3-6 months. Prone skills were assessed using the Alberta Infant Motor Scale's prone domain. The Assessment of Problem-Solving in Play was utilized to measure motor-based problem-solving by observing how motor actions were used to solve toys. Advanced prone motor skills were correlated with an increase in sophisticated exploration skills and a concurrent decline in lower order exploration skills in all infants, with correlations being stronger in preterm infants. Notably, a 1-point increase in prone skills was associated with a 1.3-point increase in total motor-based problem-solving abilities in all infants. Our findings provide preliminary evidence for the contribution of prone play to cognitive development in infants, prompting considerations for assessment and intervention strategies. Further research is needed to ascertain if the delayed acquisition of prone motor skills is indicative of poor early problem-solving abilities in preterm infants.
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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 | 0.005 |
| 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 | 0.000 |
| 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".