Risk and/or protective factors for the neuropsychomotor development of babies from the perspective of the sustainable development goals
Bibliographic record
Abstract
This research approached 4- to 18-month-old children who attended daycare centers aiming to identify their neuropsychomotor development (NPMD) and home stimulation and verify the association of neonatal, socioeconomic, and environmental variables with NPMD, from the perspective of the sustainable development goals (SDGs). Cross-sectional study in 181 children, assessing their NPMD (Alberta Infant Motor Scale – AIMS and Denver II screening test) and contexts (Affordances in the Home Environment for Motor Development Infant Scale – AHEMD-IS). The data were analyzed with chi-square independence tests. The NPMD of 45.3% of the children were at risk/delayed; 31.5% had little home stimulation. There was an association with NPMD perceived as typical by parents (p=0.005), who were 7.5 times more likely to correctly identify NPMD. There was an association with maternal educational attainment (p=0.011); mothers with lower educational attainment were up to 3.8 times more likely to have at-risk babies. Better AHMED-IS Physical Space (p=0.006), Variety of Stimulation, and Total scores (p<0.001) were protective to NPMD. The results showed that SGD 3 and 4 are threatened by the lack of home stimulation and low maternal educational attainment; hence, the parental perception must be given importance. These findings may optimize NPMD protective measures proposed by SDGs, providing services and actions to improve early childhood development.
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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) | 0.002 | 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".