`Internet usage pattern can indicate depression`

Updated: May 17, 2012, 16:04 PM IST

Washington: People who use the Internet more randomly, switching between applications may be showing signs of depression, a new study led by an Indian-origin researcher has claimed.

Analysing Internet usage among college students, a team led by Sriram Chellappan at Missouri University of Science and Technology found that those who show signs of depression tend to browse differently than others.

The researchers identified nine fine-grained patterns of Internet usage that may indicate depression. For example, students showing signs of depression tend to use file-sharing services more than their counterparts, and also use the Internet in a more random manner, frequently switching among several applications. They also tend to send email and chat online more than the other students, LiveScience reported.

Depressed students also tended to use higher "packets per flow" applications, those high-bandwidth applications often associated with online videos and games, than their peers, the researchers said.

"The study is believed to be the first that uses actual Internet data, collected unobtrusively and anonymously, to associate Internet usage with signs of depression," Chellappan said in a statement.

For the study, which is to be published in a forthcoming issue of IEEE Technology and Society Magazine, the researchers anonymously collected a month`s worth of Internet data for 216 undergraduate students. The students were also tested for signs of depression, about 30 per cent of whom met the minimum criteria for depression.

The researchers then analysed their Internet usage data and found that those who showed signs of depression used the Internet much differently than the other study participants.

Students who showed signs of depression also tended to use the Internet in a more "random" manner -- frequently switching among applications, perhaps from chat rooms to games to email.

That randomness, Chellappan thinks, may indicate trouble concentrating, a characteristic associated with depression.

Chellappan and his team are now interested in using these findings to develop software that could be installed on home computers to help individuals determine whether their Internet usage patterns may indicate depression.

The software would unobtrusively monitor Internet usage and alert individuals if their usage patterns indicate symptoms of depression.

"The software would be a cost-effective and an in-home tool that could proactively prompt users to seek medical help if their Internet usage patterns indicate possible depression," Chellappan said.

"The software could also be installed on campus networks to notify counsellors of students whose Internet usage patterns are indicative of depressive behaviour," he added.