Special Health Need among Canadian Kindergarten Children: A Pre-Post COVID-19 Onset Analysis Using the Early Development Instrument
Bibliographic record
Abstract
Background: The COVID-19 pandemic led to disruptions in healthcare, childcare, and early education programs, which may have affected children with special health needs (SHN) more severely than their typically developing peers. While medical diagnoses take time, kindergarten teachers’ observations can initiate early support for children at school. However, it remains unclear whether the proportion of children identified with SHN, based on teacher-reports, increased after the onset of COVID-19 pandemic. This thesis aimed to determine the proportion of Canadian kindergarten children identified with SHN before and after the onset of COVID-19 pandemic using the Early Development Instrument (EDI), and to examine the changes in mental health concerns among SHN children during this period. Methods: Kindergarten teachers used the EDI to report SHN and mental health concerns for their students. EDI records were linked with sociodemographic data from the 2016 Canadian Census and 2015 Taxfiler data across 1,639 neighbourhoods to determine associations between SHN prevalence and neighbourhood-level socioeconomic status (SES). Results: Among 485,543 kindergarteners, the study found that: (1) proportion of children with SHN increased after the onset of the pandemic (2) prevalence of SHN was inversely associated with neighbourhood-level SES, with a stronger association after the onset of pandemic, (3) the strength of this association varied across jurisdictions, and (4) while mental health concerns among SHN children increased, the adjusted odds of having mental health concerns were lower following the onset of the pandemic. Conclusion: The findings indicate an overall rise in SHN prevalence, including a rise in mental health concerns among SHN children, following the onset of COVID-19 pandemic. A greater proportion of children with SHN resided in lower-SES neighbourhoods, with this association becoming more pronounced after the onset of the pandemic, suggesting widening inequities. The study points to the urgency for additional classroom support and early identification strategies for children who are showing signs of difficulty in kindergarten.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.004 | 0.008 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| 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".