Predictors of missed school days among military connected families: A feasibility study.

Abstract

There is a paucity of research specific to military children's health, especially those with special needs. This may be partly attributed to the difficulty in accessing military connected families as a population. Yet, given the recognized importance of military connected families to the national security agenda, a need exists for studies to explore factors underlying child and family health. We sought to identify factors among a sample of military children with special health care needs (CSHCN) predictive of missed school days, a commonly used measure of health and one used by NPs to monitor chronic conditions management success. We used a secondary data analysis design and multivariable logistic regression with a subsample of military connected families from the National Survey of CSHCN identified by their reported insurance type. We identified 1,656 military CSHCN. According to the adjusted model, hours of care per week, family work hours change, and activity limitations for the child were positive predictors of ≥4 missed school days per year. Our models identified important predictors of missed school days among military children that may inform assessments, interventions, and referrals by nurse practitioners caring for them. We identified a robust sample of military CSHCN from the National Survey of CSHCN by using self-reported insurance, a novel and simple approach to conducting a focused study of this population. Although feasible, this sampling approach was not without limitations. We advocate for including military connected families within sampling frameworks of national surveys to ensure that studies with this critical and unique population continue.