41 The prevalence of Canadian kindergarten children with special health needs: A pre-post COVID-19 analysis using the Early Development Instrument
Bibliographic record
Abstract
Abstract Background Early childhood plays a significant role in child development, health, and well-being. The COVID-19 pandemic disrupted many aspects of everyday life for children in Canada. With healthcare visits being deferred and early education programs closing temporarily, the pandemic may have affected vulnerable populations, such as children with special health needs (SHN) more severely than children developing typically. SHN encompasses a range of disorders affecting behaviour, communication, physical and/or intellectual development. Kindergarten teachers’ observations and concerns of their students' abilities and behaviours play an important role in SHN identification. While formal medical diagnoses may take time, the teacher observations within a classroom can initiate early support for children at school. However, it remains unclear whether the teacher-reported prevalence of SHN in kindergarten children increased after the onset of COVID-19 pandemic. Objectives We aimed to determine the SHN prevalence of Canadian kindergarten children before (2017-2020) and after the onset of COVID-19 pandemic (2021-2023) in relation to neighbourhood-level socioeconomic status (SES). Design/Methods From 2017 to 2023, kindergarten teachers in seven provinces (British Columbia, Manitoba, Ontario, Quebec, Nova Scotia, Prince Edward Island, and Newfoundland & Labrador) and one territory (Northwest Territories) reported SHN for their students using the Early Development Instrument (EDI). EDI records were linked with neighbourhood sociodemographic data from the 2016 Canadian Census and 2015 Taxfiler for 2,058 neighbourhoods. We examined the relationship using linear regressions. Results Among 485,543 children valid for analysis, the prevalence of teacher-reported SHN in kindergarten children increased from 22.2% to 25.2% following the onset of COVID-19 pandemic (Cramer’s V = 0.035, p<0.001). This increase varied across jurisdictions, with the rise of provincial and territorial prevalence of SHN post-COVID-19 onset ranging from 0.8% to 22.2% (mean = 14.73%, SD = 0.113). The linear regression revealed that the prevalence of SHN varied by neighbourhood, with lower SES neighbourhoods having a greater percentage of children with SHNs. For one standard deviation decrease in neighbourhood-level SES, there was a 0.19 increase in the percentage of children with SHN pre-COVID-19 (R2 = 0.035, p<0.001), and a 0.24 increase post-COVID-19 onset (R2 = 0.068, p<0.001). Separate regressions for jurisdictions indicated that the association between neighbourhood SES and SHN was strongest in Newfoundland & Labrador and weakest in Quebec, both pre- and post-COVID-19 onset. Conclusion Our results demonstrate a higher prevalence in children with teacher-reported SHN after the COVID-19 pandemic with a greater proportion of children with SHN residing in lower SES-neighbourhoods. The neighbourhood-level SES association was stronger post-COVID-19, possibly indicating widening inequities in service access. Our findings points to the urgency for additional support in the classroom for children who are showing signs of difficulty in kindergarten. This study was funded by the Canadian Institute for Health Research (CIHR).
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".