School Attendance Decisions for Children With Medical Complexity During COVID-19

Abstract

Objective: School attendance by children with medical complexity (CMC) may be influenced by parent perceptions of their child's risk for coronavirus disease 2019 (COVID-19). The authors of this study aimed to quantify in-person school attendance and identify attendance predictors.

Methods: From June to August 2021, surveys were collected from English- and Spanish-speaking parents of children aged 5 to 17 years with ≥1 complex chronic condition who received care at an academic tertiary children's hospital in the Midwestern United States and who attended school prepandemic. The outcome, in-person attendance, was defined dichotomously as any in-person attendance versus none. We evaluated parent-perceived school attendance benefits, barriers, motivation, and cues, COVID-19 severity and susceptibility using survey items derived from the health belief model (HBM). Latent HBM constructs were estimated with exploratory factor analysis. Associations between the outcome and the HBM were evaluated with multivariable logistic regression and structural equation models.

Results: Among 1330 families (response rate 45%), 19% of CMC were not attending in-person school. Few demographic and clinical variables predicted school attendance. In adjusted models, family-perceived barriers, motivation, and cues predicted in-person attendance, whereas benefits, susceptibility, and severity did not. The predicted probability (95% confidence interval) of attendance ranged from 80% (70% to 87%) for high perceived barriers to 99% (95% to 99%) for low perceived barriers. Younger age (P <.01) and previous COVID-19 infection (P = .02) also predicted school attendance.

Conclusions: Overall, 1 in 5 CMC did not attend school at the end of the 2020 to 2021 academic year. Family perceptions of schools' mitigation policies and encouragement of attendance may be promising avenues to address this disparity.

FIGURE 1

Structural equation model path analysis depicting relationships among health belief model variables and in-person school attendance. Shown is a path analysis from structural equation modeling. Numbers correspond to slope estimates of predictors, and statistically significant relationships are illustrated with red text. Squares represent observed variables, and ovals represent latent constructs. Cues, motivation, and perceived barriers were significantly associated with in-person school attendance in the final model. Susceptibility was reflected by the question “How well is your child’s school able to follow the recommendations to keep your child safe while in-person?”. Cues was reflected by the question “Has a teacher or staff member encouraged your child to attend school in-person?”. Motivation was reflected by the question “Based on the situation right now, how much do you want your child to attend school in-person at least some of the time?”.