Early childhood development monitoring during the first thousand days: Investigating the relationship between the developmental surveillance instrument and standardized scales
Bibliographic record
Abstract
OBJECTIVE: This study aims to investigate the relationship between the Developmental Surveillance Instrument -Instrumento de Vigilância do Desenvolvimento (IVD), found in the Child's Booklet Caderneta da Crianca (CC), and standardized scales: Alberta Infant Motor Scale (AIMS) and Denver Developmental Screening Test (Denver-II). METHODS: Employing an exploratory observational approach, we adopted a prospective longitudinal design with a quantitative approach. The convenience sample included 83 Brazilian children born between May and August 2019 in a public hospital. Of the total, 45 (54.22 %) were male, and 38 (45.78 %) were female. Developmental screening utilized the IVD, AIMS and Denver-II tests. Comparative analysis between groups employed Mann-Whitney or Kruskal-Wallis tests for numerical variables and chi-square/Fisher tests for categorical variables, with a significance level of 5 % (p < 0.05). RESULTS: A significant correlation was observed between the IVD and the AIMS and Denver-II tests (p < 0.001) at months 1, 4, and 8. CONCLUSION: The presence of a robust correlation between the IVD and the AIMS and Denver-II tests at months 1, 4, and 8 implies that the IVD in the Child's Booklet serves as a reliable and effective indicator for screening infant development during this critical period. Detecting issues early through these methods is crucial to ensure the well-being of children, allowing for appropriate interventions as needed.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 | 0.021 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| 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".