Life & Style

Health: These surveys evaluated the participants on depression, loneliness, and stress.

September 24, 2014 11:52 AM
Mstress: ental health and behavioral surveys

With the recent announcement and anticipated rollout of the Apple Watch, a lot of attention has been paid to what new technology can do for our physical well-being. New research at Dartmouth College shows how our devices might be used to monitor mental health, as well, newrepublic.com reports.

A team at Dartmouth has developed an app called StudentLife to help predict students’ mental health and academic performance based on objective sensor data from smartphones. The study is the first of its kind to use automatic sensing in this way.

Sudy involving 48 Dartmouth students, automatic smartphone sensors collected 24/7 data about participants’ location, conversations, mobility and sleep patterns, without any user interaction.

Over the course of a ten-week study involving 48 Dartmouth students, automatic smartphone sensors collected 24/7 data about participants’ location, conversations, mobility and sleep patterns, without any user interaction. It monitored things like the length of conversations and how much the subjects moved around inside at night. On top of this, the app would prompt the students several times per day with a short series of questions about their mood and stress levels.

As a third data set, the research team administered mental health and behavioral surveys at the start and end of the term, using well-known measurements of well-being. These surveys evaluated the participants on depression, loneliness, and stress. The researchers also gathered the students’ academic records from the administration, as well as their GPAs.

The study’s lead author, computer science professor Andrew Campbell, explained that after years of teaching on a slower-moving semester schedule at Columbia, Dartmouth’s quarter system seemed like a quick and exhausting “marathon” to his students. He often watched his students burn out over the course of the term, and wanted to examine how objective factors like sleep and social interaction influenced their mental health, and in turn, their academic performance.

At the end of the study, the researchers compared the self-reported data with the automatic sensing data and found some strong correlations. They determined that, based solely on the automatic data, the app could effectively predict certain mental health issues and academic performance levels in the students. For example, monitoring consistently low levels of physical activity and conversation often correlated with depression, and low levels of physical activity often predicted loneliness. To their surprise, the team found no correlation between academic performance and class attendance, and students who engaged in more conversations tended to earn better grades. Also, lonely students didn’t necessarily spend less time talking to others.

 

 

 

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