| ORIGINAL RESEARCH ARTICLE |
|
| Year : 2019 | Volume
: 5
| Issue : 1 | Page : 12-18 |
|
|
Predicting depression among internet addicted students
Y Sanjay1, Ratna Kishy Kondaveeti2, Satish Athili3
1 Associate Professor, Dept. of Psychiatry, Katuri Medical College & Hospital, Guntur, Andhra Pradesh, India
2 Senior Resident, Dept. of Psychiatry, Katuri Medical College & Hospital, Guntur, Andhra Pradesh, India
3 Junior Resident, Dept. of Psychiatry, Katuri Medical College & Hospital, Guntur, Andhra Pradesh, India
Correspondence Address:
Ratna Kishy Kondaveeti
Senior Resident, Dept. of Psychiatry, Katuri Medical College & Hospital, Guntur, Andhra Pradesh
India
 Source of Support: None, Conflict of Interest: None
DOI: 10.18231/j.tjp.2019.004
|
|
|
Introduction: Internet has been easily accessible to students living in urban areas. With its unprecedented development and many benefits, it also leads to Internet addiction (IA) among people. Though IA is a disorder in itself, there can be other disorders associated with it as well. One such association of IA is with depression.
Objective: The aim of this paper is to show a potential relationship between internet addiction and depression among students belonging to the urban setting.
Materials and Methods: The research sample consisted of 228 students aged between 11-27 doing their schooling or graduation. To assess the study, a self-administered questionnaire consisting of three parts was given to them. The first part comprised of socio-demographic information and pattern of internet usage. Second part consisted assessment of internet addiction using Young’s 20 item Internet addiction test (IAT) and the third module comprised of Birleson’s depression self-rating scale (DSRS) questionnaire.
Results: The 228 study participants were classified based on their scores obtained on IAT and DSRS scales. They were divided into two class labels: Depression Yes and Depression No. 99 were classified to the “YES Depression class” and 129 were classified to the “No Depression class” and overall classification accuracy achieved was 85.5%.
Conclusion: Students get addicted to the internet due to its easy availability and accessibility. The current study showed that this addiction is associated with depression. It also showed that internet addiction and depression is more prevalent above the age of 19.
|
|
|
|
| [PDF]* |
|
 |
|
