College Students’ Internet Usage Patterns Could Signify Depression
In a new study analyzing Internet usage among college students, researchers at Missouri University of Science and Technology have found that students who show signs of depression tend to use the Internet differently than those who show no symptoms of depression.
Using actual Internet usage data collected from the university’s network, 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.
The researchers’ findings provide new insights on the association between Internet use and depression compared with existing studies, says Sriram Chellappan, PhD, an assistant professor of computer science at Missouri S&T and the lead study researcher.
“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 says. Previous research on Internet usage has relied on surveys, which are “a far less accurate way” of assessing how people use the Internet, he says.
Chellappan and his fellow researchers collected a month’s worth of Internet data for 216 Missouri S&T undergraduate students. The data were collected anonymously and unobtrusively, and students involved in the study were assigned pseudonyms to keep their identities hidden from the researchers.
Before the researchers collected the usage data from the campus network, the students were tested to determine whether they showed signs of depression. The researchers then analyzed the usage data of the study participants. They found that students who showed signs of depression used the Internet much differently than the other study participants.
Chellappan and his colleagues found that depressed students tended to use file-sharing services, send e-mail, and chat online more than the other students. Depressed students also tended to use higher “packets per flow” applications, those high-bandwidth applications often associated with online videos and games, than their counterparts.
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 e-mail. Chellappan thinks that randomness may indicate trouble concentrating, a characteristic associated with depression.
The randomness stood out to Chellappan after his graduate student, Raghavendra Kotikalapudi, examined the “flow duration entropy” of students’ online usage. Flow duration entropy refers to the consistency of Internet use during certain periods of time. The lower the flow duration entropy, the more consistent the Internet use.
“Students showing signs of depression had high flow duration entropy, which means that the duration of Internet flows of these students is highly inconsistent,” Chellappan says.
At the beginning of the study, the 216 participating students were tested to determine whether they exhibited symptoms of depression. Based on the Center for Epidemiologic Studies-Depression scale, about 30% of the students in the study met the minimum criteria for depression. Nationally, previous studies show that between 10% and 40% of all American students suffer from depression.
To ensure that participants were not identified during the study, each participant was assigned a pseudonym. The campus information technology department then provided the on-campus Internet usage data for each participant from the month of February 2011.
The researchers’ analysis of the month’s worth of data led Chellappan and his colleagues to conclude that students who were identified as exhibiting symptoms of depression used the Internet differently than the other students in the study.
Chellappan’s research will be published in December in the Winter 2012 issue of IEEE Technology and Society Magazine and is also accessible from Chellappan’s website.
— Source: Missouri University of Science and Technology