Gross motor trajectories of pre-term and full-term infants under different parental educational approaches
Bibliographic record
Abstract
This study aimed to explore motor trajectories of Brazilian pre-term and full-term infants from 3 to 12 months old whose parents participated in an educational program and had received guidance on gross motor development. Forty-eight Brazilian infants aged 3 months old were divided into Group 1 (full-term infants and their parents who received only verbal guidance, n = 14), Group 2 (full-term infants with parents who received an educative folder in addition to the same verbal guidance, n = 23), and Group 3 (preterm infants with parents who received the same verbal guidance and educative folder, n = 11). The folder had similar information to the verbal guidance; nonetheless, it helped to teach parents and allowed later consultation at home. We applied Alberta Infant Motor Scale, Affordances in Home Environment for Motor Development–Infant Scale, and a questionnaire about infants’ information at 3-, 6-, 9-, and 12-months old. In longitudinal comparison, all groups showed a significant difference for AIMS variables on total score and subscales; all subitems of AHEMD-IS; and time spent in prone, supine, sitting, and standing positions. In general, no differences were found between groups. Motor trajectory, home opportunities, and parental positioning practices were similar between full-term and preterm infants with different guidance approaches.
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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 | 0.001 | 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".