Yan Cheng

George Washington University

1 active project

SDOH & COVID

The impact of COVID-19 is particularly severe on older adults. The older adults (>= 65yr old) account for more than 80% of the mortality. Other reported negative outcomes include anxiety, depression, poor sleep quality and physical inactivity. We propose to…

Scientific Questions Being Studied

The impact of COVID-19 is particularly severe on older adults. The older adults (>= 65yr old) account for more than 80% of the mortality. Other reported negative outcomes include anxiety, depression, poor sleep quality and physical inactivity. We propose to utilize this unique, rich set of data to study the relationship between social determinants of health (SDOH) and COVID impact on older adults’ behavior and mental health. Our overall hypothesis is that a comprehensive set of SDOH is associated the COVID impact. Our specific aims are: Aim 1. Identify SDOH factors that are significantly associated with COVID impact on older adults’ behavior, adjusting for age and comorbidities; Aim 2. Identify SDOH factors that are significantly associated with COVID impact on older adults’ mental health, adjusting for age and comorbidities.

Project Purpose(s)

  • Social / Behavioral

Scientific Approaches

We will use a logistic regression model as the primary approach, to describe and examine whether patients with certain SDOH will have a lower rate of COVID-related behavior (including hand washing and social distancing) and higher prevalence rates of mental health concerns. Multivariable models will adjust for potential confounding factors. In addition, given the multiple factors to be examined (i.e., SDOH, age, and comorbidities), the final models will consider controlling multiplicity to avoid inflated Type I error using Hochberg or false discovery rate method. Besides, we will complement the statistical analysis with explainable deep learning modeling. We will train deep transformer model (type of DNN designed for sequence data) to identify the level of association between SDOH and COVID experience. The DNN approach will allow us to assess the impact and significance of each variable in the model using a DNN as well as the interactions between factors.

Anticipated Findings

This study will help understand how SDOH factors affects COVID-related behavior and mental health issues. The findings will help identify risk factors and provide the study basis for the potential preventive strategies for the negative behavior or mental health among the old population.

Demographic Categories of Interest

  • Age

Research Team

Owner:

  • Yijun Shao - Research Fellow, George Washington University
  • Yan Cheng - Other, George Washington University

Collaborators:

  • Qing Zeng - Late Career Tenured Researcher, George Washington University
  • Youxuan Ling - Graduate Trainee, Boston University
  • Phillip Ma - Project Personnel, George Washington University
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