Effects of COVID-19 on Mood of Healthcare Workers: A Machine Learning Analysis

Understanding the pandemic's impact on U.S. healthcare workers' mental health using statistical analysis and AI techniques.

Timeline

Deliverables

Context

Pennsylvania State University Applied Data Sciences Class

Team

Overview

Our team embarked on a mission to investigate the early mental health impacts of the pandemic. Recognizing the need for reliable data, we turned to the CDC website to access pertinent datasets. Our primary aim was to discern the mental health ramifications experienced by individuals in the United States following the onset of COVID-19 in March 2020.


Our objective was to quantitatively assess the extent of these mental health effects using advanced statistical analysis and artificial intelligence methods as the outbreak unfolded in the United States. Our research honed in on the relationship between substance abuse and mental health during the pandemic's first year. To narrow our focus and enable precise measurement, we examined shifts in substance abuse patterns a few months after the outbreak's arrival in the United States.


Our study utilized CDC data collected throughout the summer of 2020, obtained from sources including social media posts and survey responses gathered between January and June. The specific survey periods were in April (2nd-8th), May (5th-12th), and June (24th-30th), 2020. The major research question we are attempting to answer with this study is: What were the effects of the pandemic on an individual's mental health?

My Role:

Data Scientist

As a team, we worked together to choose a project topic, design a plan of execution, and tackle any challenges along the way. Some of my distinct contributions include:

Final Presentation

Final Presentation