Risk for Developmental Delay Among Infants Born During the COVID-19 Pandemic
Bibliographic record
Abstract
OBJECTIVE: Attempts by governments around the world to mitigate the spread of COVID-19 have substantially altered the early rearing environment, raising concerns about potential negative consequences for babies born during this time. The objective of this study was to determine whether infants born during the COVID-19 pandemic were at greater risk of screening positive for developmental delay compared with infants born before the pandemic. METHODS: Participants were from 2 longitudinal cohorts. The prepandemic cohort, Impact of Maternal and Paternal Postpartum Depression, recruited postpartum individuals in the period between 2015 and 2018. Infant development milestone data (Ages and Stages Questionnaire [ASQ-3]) were collected at 1-year postpartum (n = 2903), between 2016 and 2019. The pandemic cohort, Pregnancy during the Pandemic, recruited pregnant individuals between April 2020 and April 2021. Infant development milestone data (ASQ-3) were collected at 1-year postpartum (n = 3742), between May 2021 and December 2022. Sociodemographic information, pregnancy outcomes, and depression symptom data were also collected. RESULTS: In covariate-adjusted analyses, pandemic-born infants had lower mean scores and higher odds of screening positive for delay on the Communication, Gross Motor, and Personal-Social domains of the ASQ-3 compared with prepandemic infants. Sex differences showed that males and females screened "at risk" in different domains. CONCLUSION: Most pandemic-born infants display typical development, and differences between prepandemic and pandemic-born infants were small. Nevertheless, an increased risk for delayed development among pandemic-born infants suggests the need for ongoing monitoring to determine what, if any, resources and interventions are needed to support healthy child development.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".