Impact of the COVID-19 era on preventative primary care for children 0–5 years old: a scoping review
Bibliographic record
Abstract
BACKGROUND: Restrictions to routine preventative primary care well child visits (WCV) during COVID-19 may have affected a variety of outcomes for young children including growth, development, and the identification and management of developmental delays. To better understand the effect of the pandemic on these outcomes, we conducted a scoping review of studies published between March 2020 and April 2024. The objectives of this scoping review were to determine the impact of the COVID-19 era on WCV attendance and developmental outcomes in children 0-5 years old. RESULTS: 23 articles met inclusion criteria. Most studies were conducted in the U.S. The overall COVID-19 era WCV rate was lower compared to pre-COVID visit rates. Higher rates of missed WCVs and reduced access were reported for racialized children and those from families with lower socioeconomic status. Studies measuring developmental outcomes found associations between children born during the pandemic and increased rates of expressive language delays, decreased personal-social skills, increased delays in achieving verbal, motor, and overall cognitive performance milestones, increased externalizing behaviours, and decreased prosocial behaviour. No study examined the impact of WCV attendance rates on developmental outcomes. CONCLUSIONS: During the COVID-19 pandemic, infants, toddlers, and young children attended fewer preventative primary care visits and pandemic-born children were more likely to show signs of developmental delay. This review highlights the need for further research to better understand the longitudinal impact of reduced access to preventative primary care and child health outcomes, including the early detection of, and referral for, developmental delays.
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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 | 0.010 | 0.060 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.006 |
| Bibliometrics | 0.012 | 0.014 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| 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".