|Year : 2018 | Volume
| Issue : 3 | Page : 197-210
Problematic internet use among students in South-East Asia: Current state of evidence
Yatan Pal Singh Balhara1, Ananya Mahapatra2, Pawan Sharma3, Rachna Bhargava1
1 Associate Professor, Department of Psychiatry, National Drug Dependence Treatment Centre, All India Institute of Medical Sciences, New Delhi, India
2 Senior Resident Doctor, Department of Psychiatry, All India Institute of Medical Sciences, New Delhi, India
3 Junior Resident Doctor, Department of Psychiatry, All India Institute of Medical Sciences, New Delhi, India
|Date of Web Publication||12-Sep-2018|
Yatan Pal Singh Balhara
Department of Psychiatry, National Drug Dependence Treatment Centre, All India Institute of Medical Sciences, New Delhi
Source of Support: None, Conflict of Interest: None
| Abstract|| |
Problematic Internet use (PIU) among students has become a significant mental health concern. Our goals were to review the existing studies on problematic Internet from Southeast Asian Region and examine: the prevalence for PIU among students; explore for sociodemographic and clinical correlates; and assess the physical, mental, and psychosocial impact of PIU in this population. All studies conducted among population of the Southeast Asia, involving students (school students to postgraduate students) of any age which explored etiological factors and/or the prevalence or any other factor associated with PIU/Internet addiction were considered eligible for the present review. The electronic databases of PubMed and Google Scholar were systematically searched for the relevant published studies up to and including October 2016. Our search strategy yielded 549 articles, 295 of which were eligible for screening based on their publication in English language in a peer-reviewed journal. Of these, a total of 38 studies met the inclusion criteria and were included in the review. The prevalence of severe PIU/Internet addiction ranged from 0 to 47.4%, whereas the prevalence of Internet overuse/possible Internet addiction ranged from 7.4% to 46.4% among students from Southeast Asia. Physical impairments in the form of insomnia (26.8%), daytime sleepiness (20%), and eye strain (19%) were also reported among problem users. There is a need to conduct further research in this area to explore the protective and risk factors associated with it and also longitudinally assess the trajectories of the outcome.
Keywords: Behavioral addiction, Behavioral Addictions Clinic, Internet addiction, Internet gaming disorder, problematic Internet use
|How to cite this article:|
Balhara YP, Mahapatra A, Sharma P, Bhargava R. Problematic internet use among students in South-East Asia: Current state of evidence. Indian J Public Health 2018;62:197-210
|How to cite this URL:|
Balhara YP, Mahapatra A, Sharma P, Bhargava R. Problematic internet use among students in South-East Asia: Current state of evidence. Indian J Public Health [serial online] 2018 [cited 2019 May 22];62:197-210. Available from: http://www.ijph.in/text.asp?2018/62/3/197/241093
| Introduction|| |
The use of the Internet among students has increased in recent years. Internet use is nearly ubiquitous among students. The academic use of the Internet is primarily intended for learning and research purposes. The Internet has become an important part of student life.
However, excessive Internet use has also become a significant mental health concern among students. Several studies globally, and numerous anecdotal media reports, suggest possible links between overuse of the Internet by adolescents and young adults and negative health consequences such as depression, attention deficit hyperactivity disorder, excessive daytime sleepiness, problematic alcohol use, or injury. Excessive Internet use has also been associated with negative academic consequences such as missed classes, lower grades, and academic dismissal. Similar observations have been made in the Behavioral Addictions Clinic (BAC) started around a year back at All India Institute of Medical Sciences, New Delhi. Psychological and environmental factors in the lives of students may leave them disproportionately vulnerable to problematic Internet use (PIU). Developmental stressors coupled with increased access to Internet services may contribute to college student's vulnerability to PIU.
PIU is characterized by excessive or poorly controlled preoccupations, urges, or behaviors regarding computer use and Internet access that lead to impairment or distress. PIU has been described under various pseudonyms as computer addiction, Internet addiction (disorder), and pathological Internet use.,,
PIU has become a serious behavioral health problem in Southeast Asia. Despite the increasing relevance of this topic a systematic review of the existing literature on PIU among students in Southeast Asia examining prevalence as well as sociodemographic and clinical correlates is lacking. Our goals were to review the existing studies from this region and examine: (1) the prevalence for PIU among students; (2) explore for sociodemographic and clinical correlates; and (3) assess the physical, mental, and psychosocial impact of PIU in this population.
| Materials and Methods|| |
All studies (cross-sectional, case–control, and cohort) conducted among population of the Southeast Asia, involving students (school students to postgraduate students) of any age which explored etiological factors and/or the prevalence or any other factor associated with PIU/Internet addiction were considered eligible for the present review. Study selection was conducted in two phases: In the first phase, abstracts and titles were selected and in the second phase, full texts of the selected titles were obtained and read to determine the final sample set. The epidemiological questions investigated in this study were as follows: (1) What is the prevalence of PIU among students in Southeast Asia and (2) what are the sociodemographic as well as psychosocial factors associated with it. Studies investigating physical and mental health outcomes associated with PIU were also included.
The electronic databases of PubMed and Google Scholar were systematically searched for the relevant published studies in October 2016. All the studies published till and including October 2016 were eligible for inclusion. Only the articles published in English language were selected. The following search terms were used: “Internet addict*”, “Internet gaming addiction”, “gaming addiction”, “Internet Gaming Disorder”, “pathological Internet use”, “excessive internet use”, or “problematic Internet use” AND (India/Bangladesh/Nepal/Indonesia/Timor Leste/DPR Korea/Thailand/Myanmar/Maldives/Sri Lanka). Search was limited to include only studies conducted in student population (school students/undergraduate/postgraduate students of any discipline). The search was conducted independently by two authors (AM and PS).
Studies retrieved from the databases were selected after reading the abstracts and titles, following a calibration exercise with 10% of the studies read by two independent reviewers to determine interexaminer agreement (Kappa: 0.68–0.97). Disagreements were resolved by consensus. The following were the inclusion criteria for the initial selection process: reviews, epidemiological studies with subjects who fulfilled the criteria of being a student enrolled in school, undergraduate or postgraduate course in any discipline, studies addressing risk factors for PIU/Internet addiction, and studies reporting socioeconomic indicators. No cohort studies or randomized controlled trials were found by the search process. For this reason, cohort studies were not considered in this review. Reviews were also not included, although their reference lists were searched in turn for any studies not retrieved by the electronic search. Qualitative studies, commentaries, and expert opinions were not included.
The extraction of the data was based on the study design, population characteristics, and the type of socioeconomic indicators used. A high degree of heterogeneity was found among the methodologies and types of socioeconomic indicators used. Measures of PIU and socioeconomic variables had several categories and cut points. Therefore, it was not possible to group data for meta-analysis. Instead, narrative synthesis was conducted in this review.
| Results|| |
Our search strategy initially yielded 549 articles, 295 of which were initially eligible based on their publication in English language in a peer-reviewed journal. Of excluded studies, 186 were not conducted in the countries under the Southeast Asia and 58 were not focused on students, and 13 were in languages other than English [Figure 1].
A total of 38 studies met the inclusion criteria and were included in the review. These studies are presented in [Table 1]. The included studies mostly used community samples and focused on the sociodemographic characteristics of the population as well as the prevalence of PIU/Internet addiction among students. All the studies were cross-sectional in nature. No cohort studies could be obtained. There were also no intervention studies conducted for PIU in Southeast Asia.
Country of origin
Of the 38 studies included in the current review, the most were from India (27),,,,,,,,,,,,,,,,,,,,,,,,,,,, followed by Nepal (three),,, Bangladesh (two),, and Sri Lanka (two)., There was one study each from Bhutan, Indonesia, and Thailand.
Six out of the 38 studies were conducted among school students, 13 in graduate/postgraduate college students, and 19 in students of health sciences (medical, nursing, etc.). The sample size of the studies ranged from 30 to 3264.
Prevalence of problematic Internet use
Most of the studies (23 out of 38) used the Young's Internet Addiction Test (IAT) to quantify the level of Internet use. The IAT is a 20-item self-report scale that measures the extent of Internet addiction based on criteria for substance dependence and pathological gambling and includes loss of control, neglecting everyday life, relationships and alternative recreational activities, behavioral and cognitive salience, negative consequences, escapism/mood modification, and deception. However, the cutoff scores for defining the PIU varied across the studies. In majority of the studies, an IAT score <50 was taken as that of an average Internet user and a score of >80 reflected Internet addiction. A score of 50–79 reflected PIU. However, few studies have taken the IAT score <20 to be of normal users and quantified Internet addiction as mild, moderate, and severe based on IAT scores of 20–49, 50–79, and 80–100, respectively. The prevalence of Internet addiction across these studies varied from 0% to 47.4%. The prevalence of over users/problematic use ranged from 7.4% to 46.4%. Among other problematic behavior related to Internet use, online pornography use, fraudulent financial transactions, and cyberattacks were reported, among which online pornography use was most common. The prevalence of online pornography use ranged from 20.8% to 40%.
Another assessment measure used was the Online Cognition Scale, which is a 36-item questionnaire that measures cognitions related to PIU and includes subscales on loneliness/depression, diminished impulse control, social comfort, and distraction. In another study, the Chen's Internet Addiction Scale  was used, which is a 26-item self-report measure of core Internet addiction symptoms, including tolerance, compulsive use, withdrawal, and related problems (i.e., negative impact on social activities, interpersonal relationships, physical condition, and time management).
The age of students included in the sample varied from 11 years to 26 years. Majority of the studies found male students to have more PIU than female students. Students in urban areas were found to have more PIU compared to rural areas. More number of students using smartphones were reported to be addicted to the Internet than those using simple phones. An association has been found between time spent on using Internet per day and Internet addiction by few of the studies. Krishnamurthy and Chetlapalli  reported Internet addiction to be associated with male gender (adjusted odds ratio [AOR] 1.69, 95% confidence interval [CI], 1.081–2.65, P = 0.021), continuous availability online (AOR 1.724, 95% CI, 1.018–2.923, P = 0.042), using the Internet less for coursework/assignments (AOR 0.415, 95% CI, 0.263–0.655, P < 0.001), making new friendships online (AOR 1.721, 95% CI, 1.785–2.849, P = 0.034), and getting into relationships online (AOR 2.283, 95% CI, 1.424–3.663, P = 0.001). Chaudhari et al., exploring the factors associated with Internet addiction in medical students found male gender, staying in private accommodation, lesser age of first Internet use, using mobile for Internet access, higher expenditure on Internet, staying online for longer time, and using Internet for social networking, online videos, and watching website with sexual content to be significantly associated with Internet addiction.
A multicountry study by Balhara et al., including India found that Indians student scoring more than the cutoff score (>30) on the IAT were more likely to be males and had a significantly greater (P < 0.05) average duration of daily use of the Internet. Moreover, a significantly higher (P < 0.05) proportion of participants who scored above the cutoff score on the IAT social networking, chatting, gaming, shopping, and viewing pornography, as compared to those with lower scores.
Physical, mental, and psychosocial impact of problem Internet use
A study among college students from India found that students with Internet addiction had poor physical and mental health score on the Duke Health Profile. Late night Internet surfing leading to sleep deprivation was reported in up to 31.53% college students. Physical impairments in the form of insomnia (26.8%), daytime sleepiness (20%), and eye strain (19%) were also reported among problem users.
A study conducted in Thailand among university students found three health risk behaviors (sedentary lifestyle, illicit drug use, and gambling) and three health outcomes (being underweight, overweight, or obese and having screened positive for posttraumatic stress disorder) to be associated with heavy Internet use.
Another study conducted among postgraduate students in India demonstrated significant association between psychological distress (measured by Kessler's Distress Scale) and Internet addiction. A cross-sectional study exploring Internet addiction among university students found 44.7% male and 41.6% female students had depression when measured using the Beck Depression Inventory. A similar study conducted in medical students showed depression and anxiety scores to be positively correlated with severity of PIU. A study exploring the role of personality traits associated with Internet addiction found that Internet addiction was positively correlated with neuroticism, loneliness (r = 0.272, P < 0.01), and negative affect, while it was negatively correlated with extraversion and positive affect. The IAT scores were found to be significantly associated with negative affect score in another study. However, in contrast to previous findings, another study from India among students of health sciences reported no significant association of PIU with mental status, global satisfaction, interpersonal relationship, or personality type.
A number of studies have demonstrated association of decline in academic performance with the severity of PIU and related behaviors. A study from Nepal exploring the role of social networking through Internet among medical, dental, nursing, and allied health science undergraduate students found that almost two-third had a negative impact on their academic performance.
| Discussion|| |
The prevalence of severe PIU/Internet addiction ranged from 0% to 47.4%, whereas the prevalence of Internet overuse/possible Internet addiction ranged from 7.4% to 46.4% among students in Southeast Asia. PIU was associated with male gender, living in urban area, use of smartphone, lesser age at first Internet use, online relationships, social networking, and watching sexually explicit content on the Internet. It was also frequently associated with psychological distress, depression, anxiety symptoms, sleep deprivation, insomnia, daytime sleepiness, and eye strain. PIU frequently led to poor academic performance among students.
There are few major concerns with the current research exploring extent and consequences of PIU in student population in Southeast Asia. Heterogeneity in the assessment tools and cutoff parameters for PIU led to difficulty in comparing the results across the studies. There are no longitudinal studies to explore the association between PIU and subsequent development of psychopathology. Similarly, research studies have considered limited outcome variables from the perspective of psychological morbidity. The impact of PIU on emotional, behavioral, academic as well as cognitive functioning has not been systematically assessed till now. Overall, there is a lack of intervention studies to investigate the effectiveness of interventions among the students in Southeast Asia.
However, despite the current limitations, it was heartening to note that seven out of the ten Southeast Asia nations have started to focus on PIU in student population from a research perspective, which till recently was considered an obscure entity. Furthermore, clinical services are being set up for such persons in this region. A BAC has been set up at All India Institute of Medical Sciences (AIIMS), New Delhi, around a year back. In addition, resources on identification and management of behavioral addictions are being developed for the region. This includes recommendations on identification and management of behavioral addictions being developed by BAC, AIIMS in collaboration with the World Health Organization-Regional Office for Southeast Asia.
Although majority of the studies are preliminary in nature, they provide the initial information regarding the status of PIU in this specific population from this region. The current studies provide incontrovertible evidence regarding the adverse effect of PIU on physical as well as mental health of students. The evidence thus generated should garner focus on the health consequences of PIU and spur further research with more robust methodology in order to fill the current gaps in our understanding as well as to formulate intervention strategies.
There are certain limitations to the current review. We restricted our search to two databases. Only English language publications were included in this review. Finally, it must be remembered, this is an active area of interest among researchers and more evidence is likely to have emerged between submission of this manuscript and its publication.
| Conclusions|| |
PIU among the student population in Southeast Asian Region has been a focus of attention in the recent years, and it has the potential to become one of the significant public health issues in the near future. There is an imminent need to conduct further research in this area in order to explore the protective and risk factors associated with it and also longitudinally assess the trajectories of the outcome. Furthermore, there is a need to formulate culturally-informed intervention as well as preventive strategies for the same.
Financial support and sponsorship
Conflicts of interest
There are no conflicts of interest.
| References|| |
Moreno MA, Jelenchick L, Cox E, Young H, Christakis DA. Problematic internet use among US youth: A systematic review. Arch Pediatr Adolesc Med 2011;165:797-805.
Hawi N. Internet addiction among adolescents in Lebanon. Comput Hum Behav 2012;28:1044-53.
Weinstein A, Lejoyeux M. Internet addiction or excessive internet use. Am J Drug Alcohol Abuse 2010;36:277-83.
Bai YM, Lin CC, Chen JY. Internet addiction disorder among clients of a virtual clinic. Psychiatr Serv 2001;52:1397.
Beard KW, Wolf EM. Modification in the proposed diagnostic criteria for internet addiction. Cyberpsychol Behav 2001;4:377-83.
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.
Chakrabarty S, Latifee E. Consequences of internet usage among students of the first specialized public science and technology university of Bangladesh: A survey. Afr Dev Resour Res Inst (ADRRI) J 2014;4:149-72.
Uddin S, Mamun A, Iqbal M, Nasrullah M, Asaduzzaman M, Sarwar S, et al
. Internet addiction disorder and its pathogenicity to psychological distress and depression among university students: A cross-sectional pilot study in Bangladesh. Psychology 2016;7:1126-37.
Jap T, Tiatri S, Jaya ES, Suteja MS. The development of indonesian online game addiction questionnaire. PLoS One 2013;8:e61098.
Pramanik T, Sherpa MT, Shrestha R. Internet addiction in a group of medical students: A cross sectional study. Nepal Med Coll J 2012;14:46-8.
Marahatta S, Adhikari B, Aryal N, Regmi R. Internet addiction and associated factors among health sciences students in Nepal. J Community Med Health Educ 2015;5:6-10.
Jha RK, Shah DK, Basnet S, Paudel KR, Sah P, Sah AK, et al.
Facebook use and its effects on the life of health science students in a private medical college of Nepal. BMC Res Notes 2016;9:378.
Rodrigo C, Ranasinghe N, Wijayaratne D, Navinan R, Fernando D, Rajapakse S, et al.
Problematic internet behaviours among university students in Sri Lanka. Asian J Psychiatr 2012;5:275-6.
Sachitra K. Internet addiction, academic performance and university students. J Glob Res Educ Soc Sci 2015;3:179-86.
Peltzer K, Pengpid S, Apidechkul T. Heavy internet use and its associations with health risk and health-promoting behaviours among Thai university students. Int J Adolesc Med Health 2014;26:187-94.
Kawa M, Shafi H. Evaluation of internet addiction and psychological distress among university students. Int J Mod Soc Sci 2015;4:29-41.
Dhir A, Chen S, Nieminen M. Predicting adolescent internet addiction: The roles of demographics, technology accessibility, unwillingness to communicate and sought Internet gratifications. Comput Hum Behav 2015;51:24-33.
Mahanty B, Mishra G. Internet Addiction and Estimation Procedure, Among Computer and Medical Professional Students: A Cross Sectional Study Odisha, International Journal of Biomedical Materials Research 2016;4:1-5.
Jain T, Mohan Y, Surekha S, Svathi Mouna V, Swapna US, Swathy Y, et al
. Prevalence of internet overuse among undergraduate students of a private university in South India. Int J Recent Trends Sci Technol 2014;11:301-4.
Chathoth V, Kodavanji B, Arunkumar N, Pai S. Internet behaviour pattern in undergraduate medical students in Mangalore. Int J Innov Res Sci Eng Technol 2013;2:2133-6.
Sharma A, Sahu R, Kasar P, Sharma R. Internet addiction among professional courses students: A study from central India. Int J Med Sci Public Health 2014;3:1069-73.
Zou M, Yaduvanshi P, Malik A. Antecedents of internet addiction among college students in India. Int J Glob Educ 2015;4:1-10.
Singh N, Barmola K. Internet addiction, mental health and academic performance of school students/adolescent. Int J Indian Psychol 2015;2:98-108.
Kakkar N, Ahuja J, Dahiya P. Influence of internet addiction on the academic performance and mental health of college students. Sch Res J Interdiscip Stud 2015;3:1151-61.
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]
Chaudhari B, Menon P, Saldanha D, Tewari A, Bhattacharya L. Internet addiction and its determinants among medical students. Ind Psychiatry J 2015;24:158-62.
] [Full text]
Chathoth V, Bhagyalakshmi K, Nayanatara A, Anupama N, Kini R, Pai S. Impact of internet use on lifestyle in undergraduate medical students. Int J Biomed Res 2014;5:190-2.
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. [Full text]
Banjara S, Bhukya K. The role of internet and its addiction among medical students in a tertiary care teaching hospital. Glob J Res Anal 2015;1:316-7.
Kawa M, 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.
] [Full text]
Balhara YP, Gupta R, Atilola O, Knez R, Mohorović T, Gajdhar W, et al.
Problematic internet use and its correlates among students from three medical schools across three countries. Acad Psychiatry 2015;39:634-8.
Mitra A, Willyard J, Platt C, Parsons M. Exploring web usage and selection criteria among male and female students. J Comput Mediat Commun 2005;10:JCMC 1039.
Vyjayanthi S, Makharam S, Afraz M, Gajrekar S. Gender differences in the prevalence and features of internet addiction among Indian college students. Med Innov 2014;3:65-70.
Srijampana V, Endreddy A, Prabhath K, Rajana B. Prevalence and patterns of internet addiction among medical students. Med J Dr DY Patil Univ 2014;7:709-13.
Nalwa K, Anand AP. Internet addiction in students: A cause of concern. Cyberpsychol Behav 2003;6:653-6.
Setty S, Sudha K, Usha V. A cross sectional study of internet addiction in undergraduate medical students. J Dent Med Sci 2015;14:108-11.
Yadav P, Banwari G, Parmar C, Maniar R. Internet addiction and its correlates among high school students: A preliminary study from Ahmedabad, India. Asian J Psychiatr 2013;6:500-5.
Saini V, Baniya G, Verma K, Soni A, Kesharwani S. A study on relationship of facebook and game addictive behaviour with personality traits among medical students. Int J Res Med Sci 2017;4:3492-7.
Gedam SR, Shivji IA, Goyal A, Modi L, Ghosh S. Comparison of internet addiction, pattern and psychopathology between medical and dental students. Asian J Psychiatr 2016;22:105-10.
Meena PS, Mittal PK, Solanki RK. Problematic use of social networking sites among urban school going teenagers. Ind Psychiatry J 2012;21:94-7.
] [Full text]
Nath K, Naskar S, Victor R. A cross-sectional study on the prevalence, risk factors, and ill effects of internet addiction among medical students in Northeastern India. Prim Care Companion CNS Disord 2016;18:10.4088/PCC.15m01909.
Kodavanji B, Chathoth V, Kumar N, Anupama N, Pai S. Impact of internet use on lifestyle in undergraduate medical students. Cancer Res Oncol 2014;1:187-9.
Jafri H. A Study on facebook addiction and its relationship with emotional experience and coping strategies. Int J Indian Psychol 2015;2:7-14.
Young K. Caught in the Net: How to Recognize the Signs of Internet Addiction – And a Winning Strategy for Recovery. New Jersey, USA: John Wiley & Sons; 1998.
Davis RA, Flett GL, Besser A. Validation of a new scale for measuring problematic internet use: Implications for pre-employment screening. Cyberpsychol Behav 2002;5:331-45.
Chen S, Weng L, Su Y, Wu H, Yang P. Development of a Chinese internet addiction scale and its psychometric study. Chin J Psychol 2003;45:279.
Balhara YP, Singh S. Recommendations on Identification and Management of Behavioral Addictions in the World Health Organization Southeast Asia Region; 2018.