Digital phenotyping of student mental health during COVID-19: an observational study of 100 college students

Autor: Hannah Wisniewski, Ryan Hays, Elena Rodriguez-Villa, Sarah Lagan, Ryan D'Mello, Aditya Vaidyam, Natali Rauseo-Ricupero, John Torous, Joel Lavoie, Erica Camacho, Jennifer Melcher
Rok vydání: 2021
Předmět:
Zdroj: Journal of American college health : J of ACH.
ISSN: 1940-3208
Popis: Objective: This study assessed the feasibility of capturing smartphone based digital phenotyping data in college students during the COVID-19 pandemic with the goal of understanding how digital biomarkers of behavior correlate with mental health. Participants: Participants were 100 students enrolled in 4-year universities. Methods: Each participant attended a virtual visit to complete a series of gold-standard mental health assessments, and then used a mobile app for 28 days to complete mood assessments and allow for passive collection of GPS, accelerometer, phone call, and screen time data. Students completed another virtual visit at the end of the study to collect a second round of mental health assessments. Results: In-app daily mood assessments were strongly correlated with their corresponding gold standard clinical assessment. Sleep variance among students was correlated to depression scores (ρ = .28) and stress scores (ρ = .27). Conclusions: Digital Phenotyping among college students is feasible on both an individual and a sample level. Studies with larger sample sizes are necessary to understand population trends, but there are practical applications of the data today.
Databáze: OpenAIRE