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The intervention tool uses machine learning and artificial intelligence (AI) algorithms to detect a decline in undergraduate students' mental health and academic performance.
Students continue to feel the impact of the COVID-19 pandemic, which has created additional barriers to their academic success and mental well-being. A team of researchers in the College of Health and Human Services is working to address these concerns with an early intervention tool specifically designed for students from underserved and underrepresented backgrounds.
The team has created a predictive mobile app that integrates machine learning and artificial intelligence algorithms to detect when students are encountering academic and mental health challenges. The app connects students who are exhibiting risk factors to appropriate resources, such as Mason’s Counseling and Psychological Services and students’ academic advisors.
Data suggests that minority and low-income students have a greater risk for developing a mental illness and a higher need for COVID-19 related interventions.
The research team leveraged data from the ongoing Health Starts Here research project to refine the machine learning analytics. The Health Starts Here cohort study collected information on 155 diverse undergraduate students’ mental health challenges caused by the pandemic. The team will compare that data with a new cohort of 582 Mason undergraduate students using the app throughout the fall 2021 and spring 2022 semesters.
"Offering earlier assistance through the app will increase retention rates of vulnerable populations, improve mental well-being, and provide new insight into the daily lived experiences of these groups," says Erika Kennedy, a Master of Public Health student and the user interface design editor for the app.
Lawrence Cheskin, chair of the Department of Nutrition and Food Studies, and Hong Xue, associate professor in the Department of Health Administration and Policy, serve as co-principal investigators for the research project. The research team also includes Mason alumna and former postdoctoral researcher Xiaolu Cheng and PhD candidate Shuo-yu Lin.
“Users are asked some pre-screen questions about their age, employment, how many credits they are taking, and so on,” says Cheng, who developed the app. “Upon completing the pre-screen, users access a survey about mental health within the app once per week.”
The app is programmed to detect inconsistencies in participants' survey responses, allowing for intervention if the app recognizes a student exhibits behavioral, emotional, and academic risk factors that will need addressing. All information that the app collects will be securely stored on Amazon Web Services (AWS).
“We chose to use the secure AWS environment to process, maintain, and store protected health information,” Cheng said.
The group of researchers examines the data to determine if the app is effective on undergraduate student success and mental well-being throughout the COVID-19 pandemic. The team is also analyzing demographic differences, such as race, in student success when accessing the digital health solution.
"Now that the app has been developed, the next step is focusing on [sharing] the tool so that other universities and students nationwide can access and benefit from it," says Kennedy.