Predicting Next Call Duration: A Future Direction to Promote Mental Health in the Age of Lockdown

ABSTRACT

When high school students leave their homes for a college education, they often face enormous changes and challenges in life, such as meeting new people, more responsibilities in life, and being away from family and their comfort zones. These sudden changes often lead to an elevation of stress and anxiety, affecting a student's health and well-being. Situations can even get worse in the age of global pandemics, such as COVID-19, when regular life and social activities are significantly disrupted due to lockdown or stay-at-home orders. Therefore, predicting phone call patterns (a measure of social engagement) based on various factors and activities of a person can be helpful to foster social engagement and promote health and well-being during sudden lifestyle changes. In this work, we investigate a cohort of 370 on-campus college students over three consecutive semesters and breaks between them to find various geo-temporal factors and activities that affect students' phone call behaviors and develop models that can predict the next call duration with a correlation of up to 0.89 between the actual and predicted duration using individual-level generalized linear models. Findings from this work can further be extended to other populations, and thereby, our findings will enable the design and delivery of new smartphone-based health interventions (guided feedback) to help people to adapt and cope up with situations that affect their lifestyle and social activities.