Sono insuficiente na infância: impactos no desenvolvimento neurológico e comportamental
Bibliographic record
Abstract
Introduction: Insufficient sleep in childhood can negatively influence children's development. Objective: To investigate the impact of sleep deprivation on child development, analyzing the effects on cognition, behavior and mental health, with a focus on interventions that can promote healthy sleep habits. Methods: A systematic review was conducted using the PICO strategy, searching databases such as the Virtual Health Library (VHL), the National Library of Medicine (PubMed) and Embase. The inclusion criteria considered observational studies published between 2019 and 2024. The methodological quality of the studies was assessed using the Newcastle Ottawa Scale. Results: Five studies were included, revealing a consistent association between insufficient sleep and negative impacts on child development, including increased risk of obesity, learning difficulties and increased caregiver stress. The findings indicate that both sleep duration and quality play a crucial role in child development, with some studies highlighting the importance of sleep schedule and others emphasizing behavioral effects. Conclusion: Sleep deprivation in childhood is a determining factor for neurological and behavioral development. Despite the methodological limitations of the studies, such as the predominance of observational designs, the results reinforce the need for interventions to improve the quality of children's sleep.
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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 | 0.007 | 0.026 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".