COVID-19 Pandemic and the Developmental Health of Kindergarteners
Bibliographic record
Abstract
Importance: Recent studies have associated the COVID-19 pandemic with negative developmental outcomes in children. However, research focused on young children remains limited, with few studies including multiple years of pre- and postpandemic onset data. Objective: To examine the impact of the COVID-19 pandemic on US kindergarteners' developmental health. Design, Setting, and Participants: This repeated cross-sectional panel study examined developmental health trends, as measured by the Early Development Instrument (EDI), among a convenience sample US kindergarteners from 2010 to 2023. EDI data were obtained from 390 school districts across 19 states. Data were analyzed from June December 2024. Exposure: Kindergarteners' developmental health was compared between prepandemic (2018 to 2020) and postpandemic (2021 to 2023) onset cohorts. Main Outcomes and Measures: Outcomes were EDI scores across time in 5 domains: (1) physical health and well-being, (2) social competence, (3) emotional maturity, (4) language and cognitive development, and (5) communication and general knowledge. The mean (95% CI) EDI scores were assessed. Results: In this sample of of 475 740 US kindergarten students, 242 869 were male (51.1%), there were 53 841 African American or Black students (11.4%), 263 037 Hispanic or Latino/a students (55.5%), and 95 258 White students (20.1%), and the mean (SD) age was 6 (0.4) years (range, 4.0-8.0 years). Compared with the immediate prepandemic onset period, the rate of change in EDI scores was significantly lower following the pandemic onset in language and cognitive development (mean change, -0.45; 95% CI, -0.48 to -0.43), social competence (mean change, -0.03; 95% CI, -0.06 to -0.01), and communication and general knowledge (mean change, -0.18; 95% CI, -0.22 to -0.15). EDI scores were significantly higher in emotional maturity (mean change, 0.05; 95% CI, 0.03 to 0.07), and no significant changes were observed in the physical health and well-being domain (mean change, 0; 95% CI, -0.01 to 0.02). Conclusions and Relevance: The COVID-19 pandemic was associated with varying developmental health outcomes in kindergarteners. Negative developmental trends existed immediately before the pandemic, with most persisting or slowing postpandemic onset. These results highlight troubling trends in kindergarteners' development, both before and during the pandemic, and more information is needed to understand why developmental outcomes are worsening over time.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".