Mother-child bonding, environment, and motor development of babies at risk accompanied by a follow-up
Bibliographic record
Abstract
Abstract Objectives: to identify factors resulting from the correlation between mother-child bonding, environment, and infant motor development (MD). Methods: a cross-sectional study was conducted with 130 mothers/guardians and their infants at risk from 3 to 12 months of age, accompanied in an outpatient clinic follow-up at a public maternity. The data were collected using a form with socioeconomic data, mother/child routine at the hospital and home environments, and three other instruments validated in Brazil: Protocolo de Avaliação do Vínculo Mãe-Filho (Mother-Child Bonding Evaluation Protocol), Affordances in the Home Environment for Motor Development – Infant Scale, and Escala Motora Infantil de Alberta (Alberta Infant Motor Scale). Pearson's chi-square test, Fisher's exact test, and a significance level of 5% was used for the correlation. Results: the data showed a predominance of preterm babies (74.5%), low-income families (86.2%), and domestic opportunities below the adequate (93.8%) for good motor development. Regarding the mother-child bonding, 60% of the mothers showed a strong bonding with their children. A total of 62.3% of the children had typical motor development. Concerning the interaction between variables, statistical significance (p˂0.05) was observed in the correlation between bonding and typical motor development. Conclusion: despite the presence of risk factors, motor development was normal in most of the babies in this study, suggesting that the mother-child bonding favored motor development even with environmental and biological adversities.
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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 | 0.001 | 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) | 0.002 | 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".