|Year : 2017 | Volume
| Issue : 4 | Page : 305-311
Study of internet addiction: Prevalence, pattern, and psychopathology among health professional undergraduates
Sachin R Gedam1, Santanu Ghosh2, Lipsy Modi1, Arvind Goyal1, Himanshu Mansharamani1
1 Department of Psychiatry, Jawaharlal Nehru Medical College, Wardha, Maharashtra, India
2 Department of Psychiatry, Tripura Medical College, Agartala, India
|Date of Web Publication||17-Nov-2017|
Sachin R Gedam
Department of Psychiatry, Jawaharlal Nehru Medical College, Sawangi (Meghe), Wardha, Maharashtra
Source of Support: None, Conflict of Interest: None
Background: Internet has become an essential part of our daily life, especially among adolescents and youth. It is mainly used for education, entertainment, social networking, and information sharing. Its excessive use among health care providers is becoming a major concern. Aims: The aim of our study was to estimate the prevalence, understand the pattern, and to determine the association between psychopathology and internet addiction among health profession undergraduates. Materials and Methods: A cross-sectional study was conducted among 846 students of various faculties from Deemed University. Students were assessed with semi-structured data, Internet Addiction Test and Mental Health Inventory, after giving them brief instructions. Students were classified into normal students and addicted students for comparison. Results: The total prevalence of internet addiction was 19.85%, with moderate and severe addiction being 19.5% and 0.4%, respectively. Internet addiction was associated with gender, computer ownership, preferred time of internet use, login status, and mode of internet access (P < 0.05). It was also associated with anxiety, depression, loss of emotional/behavioral control, emotional ties, life satisfaction, psychological distress, and lower psychological well-being (P < 0.05). Conclusion: Significant association was found between psychopathology and internet addiction. Male gender, login status, emotional ties, and psychological distress were found to be important predictors of internet addiction among students. Hence, these parameters should be taken into consideration while promoting awareness of problematic internet use and educating students regarding healthy internet use.
Keywords: Health education undergraduates, health professional undergraduates, internet addiction, internet use pattern, psychopathology
|How to cite this article:|
Gedam SR, Ghosh S, Modi L, Goyal A, Mansharamani H. Study of internet addiction: Prevalence, pattern, and psychopathology among health professional undergraduates. Indian J Soc Psychiatry 2017;33:305-11
|How to cite this URL:|
Gedam SR, Ghosh S, Modi L, Goyal A, Mansharamani H. Study of internet addiction: Prevalence, pattern, and psychopathology among health professional undergraduates. Indian J Soc Psychiatry [serial online] 2017 [cited 2021 Jan 19];33:305-11. Available from: https://www.indjsp.org/text.asp?2017/33/4/305/218605
| Introduction|| |
Internet has become an essential part of our daily life. It is being used extensively throughout the world, especially among adolescents and youth. Its problematic use is associated with various psychological symptoms.,, Internet is used for education, entertainment, social networking, and information sharing. In the field of medicine and healthcare, it helps in practice of evidence-based medicine, research and learning, access to medical and online databases, managing patients in remote areas, and academic and recreational purposes.,
Internet-related behavior is often described as internet addiction, internet addiction disorder, internet pathological use, or internet dependency.,,,,, The prevalence of internet addiction varies from 1.5% to 25% in different populations.,,, Surveys have shown a prevalence of 0.3-0.7% in the general population. A recent study reported a prevalence of 0.7% among Indian adolescents. Young individuals (i.e., between 18 and 24 years old) were more vulnerable to become internet addicts than old individuals.
Since the mid-1990s, internet addiction has been proposed as a new type of addiction and mental health problem, similar to alcoholism and compulsive gambling. Young has described internet addiction as an impulse-control disorder that does not involve an intoxicant. Internet addiction disorder is characterized by preoccupation with internet, need to spend long periods online, repeated attempts to reduce internet use, suffering withdrawal symptoms when reducing internet use, time management problems, environmental distress, deception regarding time spent online, and mood modification through internet use.
Research suggests that problematic internet use (PIU) is associated with decline in the size of social circle, depression, loneliness, lower self-esteem and life satisfaction, sensation seeking, poor mental health, and low family function.,,,,, PIU is also associated with anxiety and stress. It has been found that paranoid ideation, hostility, anxiety, depression, interpersonal sensitivity, and obsessive compulsive average scores are higher in people with high internet addiction scores than those without internet addiction., Studies also showed a negative impact of internet addiction on psychological well-being of students.
Considering the enormous use of internet among adolescents, it is important to analyze the pattern of internet use among health undergraduates. Besides using internet for information, education, and training for diagnosis, as well as patient management among healthcare students, they are a vulnerable group on account of the time they spend on the internet. The aim of the present survey was to estimate the prevalence of internet addiction, understand the pattern of internet use, and to determine the association between psychopathology and internet addiction among health education undergraduates.
| Materials and Methods|| |
A cross-sectional survey was conducted among undergraduate students of Datta Meghe Institute of Medical Sciences (DMIMS) in the city of Wardha, Maharashtra during August-September 2015. Study participants were from medical, dental, and nursing colleges. The survey covered about 860 students aged 17-24 years. Of the total 860 participants, 14 could not be included in the study as they were not using internet. Thus, a total of 846 students were finally included in the study. This study was approved by the Ethics Committee of DMIMS, Deemed University. A written informed consent was obtained from all the students who participated before collecting the data. A semi-structured proforma was distributed in classes, and necessary instructions were given.
The tools used in the study were as follows:
- A semi-structured proforma that included details of age, gender, educational qualification, computer ownership, place of access (home, cybercafé, or others), type of internet connection, login status, location of internet access, time of internet use, and reasons for internet use. Data were collected from those using internet for at least 6 months.
- The Internet Addiction Test (IAT): It is the validated and reliable measure of addictive use of the Internet. Developed by Dr. Kimberly Young, the IAT is a 20-item 5-point Likert scale that measures the severity of self-reported compulsive use of the internet. Cronbach's alpha computed for this questionnaire was 0.889 by Frangos. The marking for this questionnaire ranges from 20–100; the higher the marks are, the greater the dependence on the internet is. It is evaluated as:
<50: normal internet users
50-79: moderate addicts
80-100: severe addicts
Data were analyzed based on two groups of normal students (score < 50) and addict students (score > 50) adopted from a study by Ghamari et al.
- Mental health inventory is a method for evaluating mental health issues such as anxiety, depression, behavioral control, positive effect, and general distress. It helps in measuring overall emotional functioning. The mental health inventory is a self-report questionnaire including 38 items; a 6-point Likert-style response is used. The test has a reported 0.93 Cronbach alpha rating. The mental health inventory may be aggregated into six subscales – anxiety, depression, loss of behavioral/emotional control, general positive affect, emotional ties and life satisfaction. There are two global scales-psychological distress and psychological well-being. The subscales are scored in two steps: (1) item scoring and (2) the subscales themselves. All subscales are scored such that higher scores indicate more of the construct named by the subscale label. Thus, higher scores on three subscales indicate positive states of mental health (general positive affect, emotional ties, life satisfaction); higher scores on the other three subscales indicate negative states of mental health (anxiety, depression, loss of behavioral/emotional control). The psychological distress and psychological well-being global scales represent complementary summary scales with psychological distress indicating negative states of mental health and psychological well-being indicating positive states. Together, they use all 38 items to derive the scores (24 items for distress, 14 items for well-being) with no item overlap.
In this study, the data has been evaluated using the Statistical Package for the Social Sciences (SPSS Inc. 233 South Wacker Drive, 11th Floor Chicago, IL 60606-6412 version 17.0) and EPI INFO 5.0 version. The analysis was performed by chi-square test and binary logistic regression model. P-value was set at 0.05.
| Results|| |
In the present study, the total prevalence of internet addiction was 19.85%, with moderate and severe internet addiction being 19.5% and 0.4%, respectively. The mean age of the participants was 19.68 (± 1.34) years, and out of 846 internet users, 183 (21.6%) were males and 663 (78.4%) were females. Most of the students used their laptops [Table 1].
|Table 1: Age, gender, and pattern of internet use of the study participants|
Click here to view
Most of the students were using internet for 1-5 years, intermittently and during night time. Most common mode of internet access was mobile internet; purpose of use was educational and social networking [Table 1].
Most of the students had low scores on anxiety, depression, loss of emotional/behavioral control, and psychological distress subscales, whereas they had high scores on general positive affect, emotional ties, life satisfaction, and psychological well-being subscales [Table 2].
|Table 2: Symptoms on mental health inventory among the study participants|
Click here to view
The student's gender, computer ownership, preferred time of internet use, login status, and mode of internet access had significant association with internet addiction (P < 0.05), however, no significant association was found among duration of internet use, location of internet access, and purpose of internet use with the internet addiction (P > 0.05), as shown in [Table 3].
|Table 3: Association of pattern of internet use with internet addiction in the study participants|
Click here to view
The psychiatric symptoms such as anxiety, depression, loss of emotional/behavioral control, emotional ties, life satisfaction, psychological distress, and lower psychological well-being had significant association with internet addiction (P < 0.05), except general positive affect, which had no significant correlation with internet addiction (P > 0.05), as shown in [Table 4].
|Table 4: Association of psychopathology with internet addiction in the study participants|
Click here to view
Logistic regression analysis with forward method showed that male gender, login status, emotional ties, and psychological distress were the most important predictors of internet addiction among students [Table 5].
|Table 5: Multiple logistic regression analysis model with forward method when IAT score was taken as a dependent variable|
Click here to view
| Discussion|| |
The overall prevalence of internet addiction (representing moderate and severe addiction) was 19.85%, which is in accordance with most studies that have assessed internet addiction using Young's IAT. A study on university students in India reported a prevalence of 18.88%. Internet addiction is more common in males than in females, which corroborates with the finding of previous studies.,
The results of our study reported that internet addiction rate is correlated with computer ownership (students having personal desktop), internet use preferably during morning hours, permanent logged-in status, and internet access through Wi-Fi and mobile internet. These findings are not similar to previous studies stating that gadgets (e.g., desktop, laptop, mobile phone) and mode of internet access are not significant influential factors for internet addiction. Whereas findings such as using the internet for news, updates, checking mails, entertainment, social networking, and playing games, as well as location of internet access are not influential factors for addiction are consistent with our findings. The study also reported permanent logged-in status to be the most influential factor for internet addiction, which is similar to our finding.
These differences can be attributed to different study populations, the influence of confounding factors such as stress and psychiatric comorbidity, and a difference in methodological evaluation of studies.
This study also reported that internet addiction was associated with psychiatric symptoms such as anxiety, depression, loss of emotional/behavioral control, emotional ties, and psychological distress. Many studies have suggested that internet addiction is associated with loneliness, depression, anxiety, stress, and low self-esteem and life satisfaction.,, It has also been reported that addicted students are more likely to have low psychological well-being, which is comparable to our result. These findings are in accordance with the previous studies stating that there is a strong association between psychiatric symptoms and internet addiction.
The variables that contributed strongly were identified by logistic regression analysis with forward method. Male gender, login status, emotional ties, and psychological distress were found to be the main predictors of internet addiction. Thus, there was an increased risk of internet addiction among males, those using internet continuously, having higher emotional ties, and psychological distress.
| Conclusion|| |
The total prevalence of internet addiction among health education undergraduates is almost similar to other university students. Internet addiction among students varied according to the pattern of internet use. Internet addicted individuals showed anxiety, depression, loss of emotional/behavioral pattern, and psychological distress. Students use internet to cope with their stress by avoiding cognitive tasks. Hence, measures should be taken to find at-risk students, to promote awareness of PIU, and to educate students to use internet meaningfully and appropriately. Authorities should monitor internet use by the students.
The students were selected from only one university, and hence the results cannot be generalized. The responses may have been biased due to discussion as students were evaluated in groups in the classroom.
Financial support and sponsorship
Conflicts of interest
There are no conflicts of interest.
| References|| |
Murali V, George S. Lost online: An overview of internet addiction. Adv Psychiatric Treat 2007;13:24-30.
Shapira NA, Lessig MC, Goldsmith TD, Szabo ST, Lazoritz M, Gold MS, et al.
Problematic internet use: Proposed classification and diagnostic criteria. Depress Anxiety 2003;17:207-16.
Young KS. Internet addiction: The emergence of a new clinical disorder. Cyberpsychol Behav 1998;1:237-44.
Kuss DJ, Griffiths MD. Online social networking and addiction—A review of the psychological literature. Int J Environ Res Public Health 2011;8:3528-52.
Swaminath G. Internet addiction disorder: Fact or Fad? Nosing into Nosology. Indian J Psychiatry 2008;50:158-60.
] [Full text]
Dargahi H, Razavi SM. Internet addiction and its related factors: A study of an Iranian population. Payesh 2007;6:265-52.
Chou C, Hsiao MC. Internet addiction, usage, gratifications, and pleasure experience—The Taiwan college students' case. Comput Educ 2000;35:65-80.
Young KS. (1996a, August). Internet addiction: The emergence of a new clinical disorder. Poster presented at the 104th American Psychological Association Annual Convention, Toronto, Canada..
Davis RA. A cognitive–behavioral model of pathological Internet use. Comput. Human Behav 2001;77:187-95.
Morahan-Martin JM, Schumacker P. Incidence and correlates of pathological Internet use. Comput. Human Behav 2000;16:13-29.
Scherer K. College life online: Healthy and unhealthy Internet use. J Coll Stud Dev 1997;38:655-65.
Deng YX, Hu M, Hu GQ, Wang LS, Sun ZQ. An investigation on the prevalence of internet addiction disorder in middle school students of Hunan province. Zhonghua Liu Xing Bing Xue Za Zhi 2007;28:445-8.
Johansson A, Götestam KG. Internet addiction: Characteristics of a questionnaire and prevalence in Norwegian youth (12-18 years). Scand J Psychol 2004;45:223-8.
June KJ, Sohn SY, So AY, Yi GM, Park SH. A study of factors that influence Internet addiction, smoking, and drinking in high school students. Taehan Kanho Hakhoe Chi 2007;37:872-82.
Tsai HF, Cheng SH, Yeh TL, Shih CC, Chen KC, Yang YC, et al.
The risk factors of Internet addiction–a survey of university freshmen. Psychiatry Res 2009;167:294-9.
Sadock BJ, Sadock VA. Kaplon and Sadock Comprehensive Textbook of Psychiatry. 9th ed. Philadelphia: Lippincott Williams and Wilkins; 2009. p. 1063-4.
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.
] [Full text]
Soule L, Shell W, Kleen B. Exploring Internet addiction: Demographic characteristics and stereotypes of heavy internet users. J Comput Info Syst 2002;44:64-73.
OReilly M. Internet addiction: A new disorder enters the medical lexicon. CMAJ 1996;154:1882-3.
Kimberly S. Young. Internet Addiction: The Emergence of a New Clinical Disorder. Cyber Psychology & Behavior. 1998;1:237-44.
Young K. Internet addiction: Evaluation and treatment. Stud Br Med J 1999;7:351-2.
Kraut R, Patterson M, Landmark V, Kiesler S, Mukophadhyay T, Scherlis W. Internet paradox: A social technology that reduces social involvement and psychological well being?. Am Psychol 1998;53:1017-31.
Ko CH, Yen JY, Chen CC, Chen SH, Yen CF. Gender differences and related factors affecting online gaming addiction among Taiwanese adolescents. J Nerv Ment Dis 2005;193:273-7.
Lin SS, Tsai CC. Sensation seeking and internet dependence of Taiwanese high school adolescents. Comput Human Behav 2002;18:411-26.
Yang CK. Sociopsychiatric characteristics of adolescents who use computers to excess. Acta Psychiatr Scand 2001;104:217-22.
Young KS, Rogers RC. The relationship between depression and Internet addiction. Cyberpsychol Behavior 1998;1:25-8.
Armstrong L, Phillips JG, Saling LL. Potential determinants of heavier Internet usage. Int J Human Comput Stud 2000;53:537-50.
Panicker J, Sachdev R. Relations among loneliness, depression, anxiety, stress and problematic internet use. Int J Res App Natural Soc Sci 2014;2:1-10.
Xiuqin H, Huimin Z, Mengchen L, Jinan W, Ying Z, Ran T. Mental health, personality, and parental rearing styles of adolescents with Internet addiction disorder. Cyberpsychol Behav Soc Netw 2010;13:401-6.
Alavi SS, Alaghemandan H, Maracy MR, Jannatifard F, Eslami M, Ferdosi M. Impact of addiction to internet on a number of psychiatric symptoms in students of Isfahan universities, Iran, 2010. Int J Prev Med 2012;3:122-7.
Çardak M. Psychological well-being and internet addiction among university students. Turk Online J Educ Tech 2013;12.
Ghamari F, Mohammadbeigi A, Mohammadsalehi N, Hashiani AA. Internet addiction and modeling its risk factors in medical students, Iran. Indian J Psychol Med 2011;33:158-62.
] [Full text]
Mental Health National Outcomes and Casemix Collection: Overview of clinician-rated and consumer self-report measures, Version 1.50. Department of Health and Ageing, Canberra 2003.
Chathoth VM, Kodavanji B, Arunkumar N, Pai SR. Internet behaviour pattern in undergraduate medical students in Mangalore. Int J Innovative Res Sci Engg Tech 2013;2.
Anderson KJ. Internet use among college students: An exploratory study. J Am Coll Health 2001;50:21-6.
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 Pub Health 2015;59.
Alavi SS, Maracy MR, Jannatifard F, Eslami M. The effect of psychiatric symptoms on the internet addiction disorder in Isfahan's University students. J Res Med Sci 2011;16:793-800.
[Table 1], [Table 2], [Table 3], [Table 4], [Table 5]
|This article has been cited by|
||Prevalence and associated factors of internet addiction among undergraduate university students in Ethiopia: a community university-based cross-sectional study
| ||Yosef Zenebe,Kunuya Kunno,Meseret Mekonnen,Ajebush Bewuket,Mengesha Birkie,Mogesie Necho,Muhammed Seid,Million Tsegaw,Baye Akele |
| ||BMC Psychology. 2021; 9(1) |
|[Pubmed] | [DOI]|
||Prevalence and associated factors of Internet addiction among undergraduate students at Al-Beheira Governorate, Egypt
| ||Basem Salama |
| ||International Journal of Public Health. 2020; |
|[Pubmed] | [DOI]|
||Effectiveness of a Nurse-Led Intervention for Adolescents With Problematic Internet Use
| ||Preeti Mathew,Raman Krishnan,Adhin Bhaskar |
| ||Journal of Psychosocial Nursing and Mental Health Services. 2020; |
|[Pubmed] | [DOI]|