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Does Internet Addiction Affects Sleep Quality of Pre-University Students?
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The purpose of the study was to find out the relationship between internet usages and sleep quality among Pre-University (PU) students in the city of Mysuru. The sample consisted of 200 PU students pursuing various courses, aged between 15-17 years. Internet addiction was assessed using Young’s 20-item Internet Addiction Test (IAT-1998) and sleep quality was assessed using the Pittsburgh Sleep Quality Index (PSQI-1989). The Internet addiction scale measured addiction in 7 dimensions – salience, excessive use, neglect work, anticipation, lack of control, and neglect social life. PSQI measures sleep quality of the students. To find out the relationship between internet addictions and sleep quality, Pearson’s product moment method was employed. Stepwise multiple regressions were employed to find out the major predictors of sleep quality by dimensions of internet addiction. Analysis revealed that as the internet addiction increased, sleep quality of the female students decreased linearly and significantly in salience, excessive use, and neglect work and in total internet addiction scores. ‘Salience’ and ‘neglect social life’ domains of the Internet addiction test were found to be the major predictors of sleep quality.
Title: Does Internet Addiction Affects Sleep Quality of Pre-University Students?
Description:
The purpose of the study was to find out the relationship between internet usages and sleep quality among Pre-University (PU) students in the city of Mysuru.
The sample consisted of 200 PU students pursuing various courses, aged between 15-17 years.
Internet addiction was assessed using Young’s 20-item Internet Addiction Test (IAT-1998) and sleep quality was assessed using the Pittsburgh Sleep Quality Index (PSQI-1989).
The Internet addiction scale measured addiction in 7 dimensions – salience, excessive use, neglect work, anticipation, lack of control, and neglect social life.
PSQI measures sleep quality of the students.
To find out the relationship between internet addictions and sleep quality, Pearson’s product moment method was employed.
Stepwise multiple regressions were employed to find out the major predictors of sleep quality by dimensions of internet addiction.
Analysis revealed that as the internet addiction increased, sleep quality of the female students decreased linearly and significantly in salience, excessive use, and neglect work and in total internet addiction scores.
‘Salience’ and ‘neglect social life’ domains of the Internet addiction test were found to be the major predictors of sleep quality.
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Abstract
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