The COVID-19 Pandemic and Early Child Cognitive Development: A Comparison of Development in Children Born During the Pandemic and Historical References

  1. Sean CL Deoni
  2. Jennifer Beauchemin
  3. Alexandra Volpe
  4. Viren D’Sa
  5. the RESONANCE Consortium

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Abstract

Objective

To characterize cognitive function in young children under 3 years of age over the past decade, and test whether children exhibit different cognitive development profiles through the COVID-19 pandemic.

Study Design

Neurocognitive data (Mullen Scales of Early Learning, MSEL) were drawn from 700 healthy and neurotypically developing children between 2011 to 2021 without reported positive tests or clinical diagnosis of SARS-CoV-2 infection. We compared MSEL composite measures (general cognition, verbal, and non-verbal development) to test if those measured during 2020 and 2021 differed significantly from historical 2011-2019 values. We also compared MSEL values in a sub-cohort comprising infants 0-16 months of age born during the pandemic vs. infants born prior. In all analyses, we also included measures of socioeconomic status, birth outcome history, and maternal stress.

Results

A significant decrease in mean population MSEL measures was observed in 2021 compared to historical references. Infants born during the pandemic exhibited significantly reduced verbal, non-verbal, and overall cognitive performance compared to children born pre-pandemic. Maternal stress was not found to be associated with observed declines but a higher socioeconomic status was found to be protective.

Conclusions

Results reveal a striking decline in cognitive performance since the onset of the COVID-19 pandemic with infants born since mid-2020 showing an average decrease of 27-37 points. Further work is merited to understand the underlying causative factors.

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  1. Version published to 10.1101/2021.08.10.21261846v2 on medRxiv
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    SciScore for 10.1101/2021.08.10.21261846: (What is this?)

    Please note, not all rigor criteria are appropriate for all manuscripts.

    Table 1: Rigor

    NIH rigor criteria are not applicable to paper type.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    Equation [1] was fit to the complete cohort dataset using the fitlme function in Matlab (MathWorks, Cambridge, MA v2019b).
    Matlab
    suggested: (MATLAB, RRID:SCR_001622)

    Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).

    Results from LimitationRecognizer: An explicit section about the limitations of the techniques employed in this study was not found. We encourage authors to address study limitations.

    Results from TrialIdentifier: No clinical trial numbers were referenced.

    Results from Barzooka: We did not find any issues relating to the usage of bar graphs.

    Results from JetFighter: We did not find any issues relating to colormaps.

    Results from rtransparent:
    • Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
    • Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
    • No protocol registration statement was detected.

    Results from scite Reference Check: We found no unreliable references.

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  3. Version published to 10.1101/2021.08.10.21261846v1 on medRxiv