By John Cramer and Joseph Blumberg
Dartmouth researchers and colleagues have built the first smartphone app that automatically monitors and assesses college students’ mental health, academic performance, and behavioral trends. In other words, your smartphone knows your state of mind—even if you don’t—and how that affects you.
Scientists from the University of Texas at Austin and Northeastern University collaborated with Dartmouth’s researchers on the project.
The app, which compares students’ happiness, stress, depression, and loneliness with their academic performance, also may be used in the general population—for example, to monitor mental health, trigger intervention, and improve productivity in workplace employees.
“The StudentLife app is able to continuously make mental health assessment 24/7, opening the way for a new form of assessment,” says Professor of Computer Science Andrew Campbell, the study’s senior author. “This is a very important and exciting breakthrough.”
Assistant Professor of Computer Science Xia Zhou and Assistant Professor of Psychiatry Dror Ben-Zeev collaborated on the project. The researchers presented their findings in a paper to the ACM International Joint Conference on Pervasive and Ubiquitous Computing (UbiComp) on September 17. The paper has been nominated for the best paper award at UbiComp, the top conference on mobile computing.
The researchers built an Android app that monitored readings from smartphone sensors carried by 48 Dartmouth students during a 10-week term to assess their mental health (particularly regarding depression, loneliness, and stress), academic performance (looking at grades across all their classes, term GPA, and cumulative GPA) and behavioral trends (how stress, sleep, visits to the gym, etc., change in response to college workload—assignments, midterms, and finals as the term progresses).
They used computational method and machine-learning algorithms on the phone to assess sensor data and make higher-level inferences (i.e., sleep, sociability, activity, etc.). The app that ran on students phones automatically measured behaviors 24/7 such as sleep duration, the number and duration of conversations per day, physical activity (walking, sitting, running, standing), where they were located and how long they stayed there (i.e., dorm, class, party, gym), stress level, how good they felt about themselves, eating habits, and more.
The results show that passive and automatic sensor data from the Android phones significantly correlated with the students’ mental health and their academic performance over the term.
Some specific findings: Students who sleep more or have more conversations are less likely to be depressed; students who are more physically active are less likely to feel lonely; students who are around other students are less likely to be depressed. Also, surprisingly, there was no correlation between students’ academic performance and their class attendance; students who are more social (i.e., had more conversations) have a better GPA; students who have higher GPAs tend to be less physically active, have lower indoor mobility at night, and spend more time around others.
“Under similar conditions, why do some individuals excel while others fail?” Campbell asks. “What is the impact of stress, mood, workload, sociability, sleep, and mental health on academic performance? To shine a light on student life, we developed the first-of-a-kind smartphone app and sensing system to automatically infer human behavior.”
The Dartmouth researchers’ next step for the StudentLife app is to provide feedback and intervention to help students boost their academic performance while living a balanced life on campus. The app also could be used in other ways, such as real-time feedback on campus safety and stress levels, students at risk, and the quality of teaching at any given moment.
The StudentLife app was recently featured in an article published by New Scientist