|Year : 2015 | Volume
| Issue : 2 | Page : 72-78
Risk of internet addiction among undergraduate medical, nursing, and lab technology students of a health institution from Delhi, India
Anika Sulania, Sandeep Sachdeva, Nidhi Dwivedi
Department of Community Medicine, North DMC Medical College and Hindu Rao Hospital, New Delhi 110007, India
|Date of Web Publication||25-Jan-2016|
Department of Community Medicine, North DMC Medical College and Hindu Rao Hospital, New Delhi 110007
Source of Support: None, Conflict of Interest: None
Objective: To assess prevalence, usage pattern, and risk of internet addiction (IA) among undergraduate students of a health institution from Delhi. Materials and Methods: A cross-sectional descriptive study was carried out during March-April 2015 using 20-item Young's IA test, a Likert scale-based interview schedule with scores ranging from 0 to 100 points with a higher score indicating greater internet dependency. Background variables included sociodemographic details, general health practices, self-assessment of mental health status, inter-personal relation (family/friends), personality type, and global satisfaction in life. The scoring pattern was analyzed in the form of low risk (score ≤49 points) and high risk (score ≥50 points) for IA. The proportion, Chi-square test, adjusted, and un-adjusted odds ratio (OR) (95% confidence interval) were computed using regression analysis. Results: Out of 202, 40.6% were MBBS students, followed by 35.6% from nursing, and 23.8% from medical lab technology stream; 68.3% were females; the mean age was 20.3 ± 1.4 years; and 61.9% were residing in hostels. It was observed that 44 (21.8%) and 22 (10.9%) students had ever consumed alcohol and smoked, respectively, while only 42 (20.8%) were engaged in physical activity (≥30 min) during most (≥5) of the days of the week. Based on self-assessment, 33 (16.3%) were globally dissatisfied and 88 (43.6%) reported themselves to be introverts. The majority of students were using internet for educational purpose (98%), entertainment (95.0%), accessing social sites (92.5%), checking E-mails (76.2%), and pornographic websites (45%). With regard to IA, 171 (84.7%) were at low risk (score ≤49) and 31 (15.4%) were at high risk (score ≥50). Male students (P = 0.001), ever consumed alcohol (P = 0.003), ever smoker (P = 0.02), and regular physical activity (P = 0.04) were found to be significantly associated with a high risk of IA based on Chi-square test, but none were found significant at higher levels of analyses (adjusted OR). No significant association of IA was found with mental status, global satisfaction, inter-personal relationship, or personality type. Conclusion: A large majority (84.7%) of students in our study are found to be at low risk of internet addiction.
Keywords: Education, health practices, hours, leisure, media, mental health, personality, physical activity, satisfaction, screen viewing time, social, web, Young′s internet addiction test
|How to cite this article:|
Sulania A, Sachdeva S, Dwivedi N. Risk of internet addiction among undergraduate medical, nursing, and lab technology students of a health institution from Delhi, India. Digit Med 2015;1:72-8
|How to cite this URL:|
Sulania A, Sachdeva S, Dwivedi N. Risk of internet addiction among undergraduate medical, nursing, and lab technology students of a health institution from Delhi, India. Digit Med [serial online] 2015 [cited 2020 Oct 22];1:72-8. Available from: http://www.digitmedicine.com/text.asp?2015/1/2/72/174770
| Introduction|| |
Over the last two decades, use of internet and social media has increased tremendously, especially in younger age group across the globe. In India, there were approximately 7 million (2001) internet users, 40 million during 2006, that is expected to rise to 700 million by the year 2019.  Currently, there are approximately 51 million "active" internet users in India with 40 million urban and 11 million rural users. Internet reaches to almost 10% Indian households and 4.4% Indian households have multiple users, 97% are regular users and 79% are daily users.
India stood third on the ranking of internet users just behind China and America with the growth of 14% from the previous years and share 8.33% of world's internet users with penetration of 19.19%.  Mobile phones are fast emerging as an important point of internet access in rural India.  As of 2013, there were 130 million mobile internet users in India with a registered growth of 20% yearly. Dual users access internet on their mobiles habitually 2 out of 3 access daily and one in 3 use it for more than an hour daily. 
In the course of human development and evolution, internet has emerged as a double-edged sword, where on the one hand it acts as a beneficial concept in knowledge transfer/update, ease of system operation, higher efficiency, and effectiveness; whereas, on the other hand it may lead to point of habituation, addiction and adverse academic, mental, physical, and social effects. ,,,,,, The internet has become an inseparable means of learning in school and college curriculum with easy access, but how much use can overshadow compulsive or problematic behaviors is an area of evaluation. Symptoms often identified were preoccupation with internet, inability to control use, hiding or lying about the behavior, psychological withdrawal, and continued use despite consequences of behavior.  The term "internet addiction (IA)" was first proposed during 1995 for pathological compulsive internet use and the gravity of current situation has been recognized, discussed, and deliberated at all international forums with the inclusion of IA in the Diagnostic and Statistical Manual of Mental Health Disorders-V edition. 
There are diverse assessment tools such as Young's IA test (IAT), problematic internet use questionnaire, and compulsive internet use scale to determine the prevalence of this disorder. Global prevalence of IA disorder varies between 0.3% and 38% in different countries depending upon methods and study instruments.  There are limited studies carried out in India on this emerging public health issue, and the situation is the same in Delhi, where the accessibility to internet is quite high. A high penetration rate of the internet is being registered both in rural and urban areas leading to the definitive possibility of addiction. With this background, a study was undertaken with the objective to find out the usage pattern and IA among undergraduate students of a health institution from Delhi.
| Materials and Methods|| |
Setting and study participants
A cross-sectional descriptive study was carried out in the medical college of Delhi among MBBS, nursing, and medical lab technology (MLT) students during March-April 2015. The complete universe of students was undertaken with informed written consent. The purpose of the study was explained to the participants and they were given the option to withdraw at any stage of the interview. However, none declined to participate. The interview was conducted by researchers in a confidential, nonobligatory, and nonjudgmental manner followed by appropriate health education and counseling.
A predesigned and pretested semi-structured interview schedule was used for this study and consisted of two broad parts:
- The first part consisted of basic sociodemographic detail including study course, age, gender, residence, native state, religion, literacy, and occupation of parents. Some of the general health practices were also inquired, such as smoking habits, alcohol consumption, physical activity of at least 30 min/day with a high heart and breathing rate, and consumption of fruits and vegetable in the last 7 days. Self-assessment of mental state, global satisfaction, interpersonal relationship with friends/family, and type of personality (introvert/extrovert) were also elicited and recorded
- The second part consisted specific items to measure IA. For this purpose, Young's 20 point IAT based on Likert scale was used.  Most of the researchers across the globe have used this schedule to explore IA. The psychometric properties  of the IAT showed that it was a reliable and valid tool with very good internal consistency, with an alpha coefficient of 0.93 in another study. 
IAT consists of the following five-points namely: Not applicable, (0) rarely, (1) occasionally, (2) frequently, (3) often, (4) and always. (5) The test scores range from 0 to 100 and a higher score indicates greater internet dependency. On the basis of response, participants are classified into the following score categories as per Young's IAT: Normal range (0-30 points), mild IA (31-49 points), moderate (50-79 points), and severe (80-100 points).
On review of the literature, it was found out that some of the authors had reclassified scoring pattern into two broad categories of high risk (moderate plus severe score ≥50 points) and low risk (normal plus mild score ≤49 points) for IA. In this study, we have retained this scoring pattern for analyses.
Data management and statistical analysis
Data analyses were carried out using SPSS software version 12 (IBM, Chicago, IL, USA). Qualitative data were expressed as proportions, and Chi-square test was used to find an association between the variables. Adjusted and unadjusted odds ratio AOR and UA-OR (95% confidence interval [CI]) was calculated using logistic regression analysis.
| Results|| |
Out of a total of 250 students, 202 students participated in the survey giving a response rate of 81%. Out of 202, 40.5% were MBBS students followed by 35.5% from nursing and 24% from MLT stream; 68% students were females because in nursing only female candidates were admitted; the mean age was 20.3 ± 1.4 years; 87% were Hindu; and 61.9% were staying in hostels. Details are shown in [Table 1]. Out of 202 students, the majority, i.e., 171 (84.7%) were at low risk (score ≤49), while 31 (15.4%) were at high risk (score ≥50) for IA. Out of all, the demographic characteristics males (P = 0.001) were found to be at a high risk of IA than females, but AOR of 0.37 (95% CI = 0.81-1.71) did not yield any significant relationship.
|Table 1: Risk of internet addiction according to sociodemographic characteristics|
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It was observed that 44 (21.8%) and 22 (10.9%) students had ever consumed alcohol and smoked while 42 (20.8%) were engaged in physical activity (≥30 min) during most (≥5) of the days of the week. Ever alcohol consumer (P = 0.003) and smoker (P = 0.02) were found to be at a high risk of IA on Chi-square analysis. However, on further analysis, none was found to be significant alcohol (AOR 0.34, 95% CI = 0.13-0.91) and ever smoked (AOR 1.34, 95% CI = 0.35-5.17). Similarly, physical activity/exercise was found to be nonsignificant (AOR, 0.97; 95% CI = 0.63-1.50) while fruit and vegetable consumption was not related to IA [Table 2].
|Table 2: Risk of internet addiction according to general health practices|
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Based on self-assessment, 33 (16.3%) were globally dissatisfied; 8 (4.0%) students were in sad mental state; and 88 (43.6%) reported themselves to be introverts as shown in [Table 3]. It was found that IA had no significant association with the mental status of students, global satisfaction, inter-personal relationship, or personality type.
The majority of students were using the internet for educational purpose (98%), entertainment (95.0%) including watching videos/movies, or listening to music, etc., and accessing social sites (92.5%) such as the Facebook. A higher proportion of males (78.1%) were accessing pornographic websites in comparison with females (29.7%) as shown in [Table 4]. For the duration of internet use per day, approximately, 75% were found using internet for <3 h, while the rest (25%) were using it for at least 3 h, and some even going up to a maximum of 12 h (not shown in table). [Table 5] describes results of internet usage (qualitative parameter) based on 20-item Young's internet study instrument.
|Table 5: Online characteristics of study subjects (qualitative parameter)|
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| Discussion|| |
The present study was undertaken with the aim to find out the usage pattern, prevalence, and levels of IA among undergraduate students of three different educational streams in a health institution from Delhi. In our study, on an encouraging note majority, i.e., 171 (84.7%) had a low risk (score ≤49 points) while only 31 (15.4%) could be categorized into a high risk (score ≥50 points) for IA. [Table 6] depicts summary of selected similar studies undertaken in India using Young's IAT for comparison purpose. ,,,,,,,,
|Table 6: Selected studies conducted in India using Young's internet addiction (IA) test instrument|
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Recognizing the harmful effects of excessive screen-based media use (SBMU) including TV viewing, gaming, social networking, and web use guidelines were issued by the American Academy of Pediatrics in the year 2002 to limit the use and prevent related impairments.  Accordingly, parents of adolescents and children older than 8 years were advised to limit their wards exposure to SBMU to <2 h/day. The concept was adapted by the Australian and Canadian Paediatric Society also. However, in the present era, use of SMBU mainly to access the internet for entertainment and education has increased tremendously, so that the guidelines now appear unrealistic. Ongoing discussion regarding restraining the usage hours for SMBU has been realized, but cut-off limit up to which it is safe needs to be increased. These criteria were further modified by Tao et al. in 2010,  where on the basis of his research he concluded that the maximum limit of utilization of internet should be 6 h. However, the recent recommendation given by Prakash et al. in 2015 advised restricting the duration of daily nonessential use of internet to 4 h.  Currently, with limited research studies and lack of consensus with regard to the standard definition of IA and safe usage pattern per week, etc., there is an urgent need for attention of all stakeholders for the development of realistic guidelines.
Financial support and sponsorship
Conflicts of interest
There are no conflicts of interest.
| References|| |
Yen JY, Ko CH, Yen CF, Wu HY, Yang MJ. The co-morbid psychiatric symptoms of internet addiction: Attention deficit and hyperactivity disorder, depression, social phobia, and hostility. J Adolesc Health 2007;41:93-8.
Siomos KE, Dafouli ED, Braimiotis DA, Mouzas OD, Angelopoulos NV. Internet addiction among Greek adolescent students. Cyberpsychol Behav 2008;11:653-7.
Lam TL, Peng Z, Mai J, Jing J. Factors associated with Internet addiction among adolescents. Cyberpsychol Behav 2009;12:552-5.
Lee MS, Ko YH, Song HS, Kwon KH, Lee HS, Nam M, et al.
Characteristics of internet use in relation to game genre in Korean adolescents. Cyberpsychol Behav 2007;10:278-85.
Niemz K, Griffiths M, Banyard P. Prevalence of pathological internet use among university students and correlations with self-esteem, the General Health Questionnaire (GHQ), and disinhibition. Cyberpsychol Behav 2005;8:562-70.
Thomas NJ, Martin FH. Video-arcade game, computer game and internet activities of Australian student. Aust J Psychol 2010;62:59-66.
Zboralski K, Orzechowska A, Talarowska M, Darmosz A, Janiak A, Janiak M, et al.
The prevalence of computer and internet addiction among pupils. Postepy Hig Med Dosw (Online) 2009;63:8-12.
Young K. Internet addiction: The emergence of a new clinical disorder. Cyberpsychol Behav 1996;3:237-44.
Chakraborty K, Basu D, Vijaya Kumar KG. Internet addiction: Consensus, controversies, and the way ahead. East Asian Arch Psychiatry 2010;20:123-32.
Widyanto L, McMurran M. The psychometric properties of the internet addiction test. Cyberpsychol Behav 2004;7:443-50.
Goel D, Subramanyam A, Kamath R. A study on the prevalence of internet addiction and its association with psychopathology in Indian adolescents. Indian J Psychiatry 2013;55:140-3.
Andurkar S, Godale L. Internet use among intern doctors - A cross sectional study at government medical college, Aurangabad, Maharashtra, India. Int J Recent Trends Sci Technol 2013;7:80-1.
Kawa MH, Humera Shafi H. Evaluation of internet addiction, impulsivity and psychological distress among university students. Int J Clin Ther Diagn 2015;3:70-6.
Krishnamurthy S, Chetlapalli SK. Internet addiction: Prevalence and risk factors: A cross-sectional study among college students in Bengaluru, the Silicon Valley of India. Indian J Public Health 2015;59:115-21.
Sharma A, Sahu R, Kasar PK, Sharma R. Internet addiction among professional courses students. A study from central India. Int J Med Sci Public Health 2014;3:1069-73.
Zalavadiya DD, Joshi NB, Vala MC, Bhola CN, Sheth AM, Rangoonwala MM. Assessment of status of internet addiction and related factors among medical students of Rajkot city. Health Line 2014;5:20-4.
Grover S, Chakraborty K, Basu D. Pattern of Internet use among professionals in India: Critical look at a surprising survey result. Ind Psychiatry J 2010;19:94-100.
Gopala VV, Srijampana R, Endreddy RA, Prabhath K, Bhagawan R. Prevalence and patterns of internet addiction among medical students. Med J DY Patil Univ 2014;7:709-13.
Mishra S, Priyadarshini R, Jayakrishnan K. A correlative study to assess internet addiction and psychopathologies among students of SOA University Bhubaneswar. IOSR J Nurs Health Sci 2015;4:66-9.
Malviya A, Dixit S, Shukla H, Mishra A, Jain A, Tripathi A. A study to evaluate internet addiction disorder among students of a medical college and associated hospital of central India. Natl J Community Med 2014;5:93-5.
American Academy of Pediatrics. Children, adolescents, and the media. Pediatrics 2013;132:958-61.
Tao R, Huang X, Wang J, Zhang H, Zhang Y, Li M. Proposed diagnostic criteria for internet addiction. Addiction 2010;105:556-64.
Parkash V, Basu D, Grover S. Internet addiction: Do two diagnostic criteria measure the same thing? Indian J Soc Psychiatry 2015;31:47-54.
[Table 1], [Table 2], [Table 3], [Table 4], [Table 5], [Table 6]