Team_202

Inspiration

Students in 2020 faced unprecedented challenges and their mental health suffered. We wanted to understand relationships and causes with anxiety in the university-aged population.

What it does

We analyzed data sources from the Census Bureau about anxiety, from the CDC about COVID cases, and from Google about search trends to find relationships between COVID cases and searches and reported anxiety.

How we built it

We used R and the packages plm, gtrendsR, maps, and ggplot2 to build models and create visualizations. These models and visualizations are in our final report.

Challenges we ran into

We needed to find comprehensive, national data about anxiety in university students. Unfortunately, such datasets are generally unavailable. However we were able to find Census-lead surveys of households which included questions about anxiety with responses broken down by age range. It was also a challenge to refine the model we used to be both flexible and powerful, but simple enough to draw interpretable conclusions.

Accomplishments that we're proud of

We are proud of the potential impact of this analysis to the understanding of student anxiety during this pandemic.

What we learned

We learned that students' anxiety is significantly affected by the ongoing pandemic around them. This can be seen with direct COVID case data but is more difficult to see with indirect measures such as Google trends for COVID-related searches.

Built With

• r