|Year : 2020 | Volume
| Issue : 2 | Page : 133-137
The prevalence of internet addiction among school-going adolescents: A comparative assessment as per two screening criteria
Deeksha Grover, Jaison Joseph
Department of Psychiatric Nursing, College of Nursing, Pt. B.D. Sharma University of Health Sciences, Rohtak, Haryana, India
|Date of Submission||21-Aug-2020|
|Date of Decision||04-Oct-2020|
|Date of Acceptance||25-Oct-2020|
|Date of Web Publication||23-Feb-2021|
College of Nursing, Pt. B.D. Sharma University of Health Sciences, Rohtak - 124 001, Haryana
Source of Support: None, Conflict of Interest: None
Background: The Internet is an integral part of modern life, and for the vast majority of Internet users, its benefits far outweigh the adverse consequences secondary to excessive use. There is a wide variation of the prevalence of Internet addiction worldwide and scanty evidence on its magnitude among school-going adolescents. Aim: In this study, we evaluated the self-reported Internet addiction measures in the high school children (14–16 years) attending selected schools of Rohtak. Materials and Methods: This cross-sectional study compared the Internet addiction as per the Young Diagnostic Questionnaire (YDQ) and Internet Addiction Test (IAT) from a consecutive sample of 400 students. We explored the relationship of IA as per these criteria and sociodemographic and Internet use profiles in this population. Results: The prevalence of severe Internet addiction ranged from 4.2% to 4.8% depending on the IAT (cutoff score of 80) and YDQ (cutoff score of >5) measurements, respectively. There was a good concordance between the two criteria for determining the level of Internet addiction (r = 0.848, k = 0.805, P < 0.001). Conclusion: The findings of the present study suggest that there is a good level of concordance between IAT and YDQ. When time is a limitation, YDQ (8 items) can be considered for screening Internet addiction in this setting.
Keywords: Internet addiction, prevalence, school-going adolescents, screening
|How to cite this article:|
Grover D, Joseph J. The prevalence of internet addiction among school-going adolescents: A comparative assessment as per two screening criteria. J Mental Health Hum Behav 2020;25:133-7
|How to cite this URL:|
Grover D, Joseph J. The prevalence of internet addiction among school-going adolescents: A comparative assessment as per two screening criteria. J Mental Health Hum Behav [serial online] 2020 [cited 2021 Sep 16];25:133-7. Available from: https://www.jmhhb.org/text.asp?2020/25/2/133/309961
| Introduction|| |
Internet is being integrated as part of lifestyle because the usage of the Internet has been growing explosively worldwide. It has dramatically changed the current communication scenario, and there has been a considerable increase in the number of Internet users worldwide in the last decade. With the advancement in media and technologies, the Internet has emerged as an effective tool in eliminating human geographical barriers. However, excessive use of the Internet has resulted in negative consequences, especially among regular users labeling it as addiction. Although the Internet contributes to the answering of many questions, the term “Internet addiction” remains a point of controversy regardless of the plethora of emerging researches over the last decades. Serious methodological issues in the available literature pose a pejorative notion on the conceptualization of “Internet addiction” as a new phenomenon. Many early studies relied on voluntary Internet surveys without measurable denominators and convenience samples of Internet users., The Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (DSM-V) identified excessive Internet gaming as a specific addictive behavior and proposed Internet gaming disorder in Section III as a condition warranting more clinical research and experience. Most of the epidemiological researches on Internet addiction used different diagnostic instruments to encounter this enigmatic problem, but none have emerged as the gold standard. The most commonly used ones are the Internet Addiction Test (IAT), the Young Diagnostic Questionnaire (YDQ), the Chen's Internet Addiction Scale, and the Internet Addiction Scale. One review identified that the prevalence of severe Internet addiction from Southeast Asia ranged from 0% to 47.4%. This wide variation in the estimated prevalence of Internet addiction is due to various factors such as the usage of different screening instruments, issues related to sampling technique, study setting, and study population adopted by the earlier studies. Despite the increasing number of researches in the existing literature, very few studies evaluated the magnitude of this topic with more than one screening criteria in the same set of individuals in the Indian context., The Internet Addiction Test (IAT), (30 items) and the Young Diagnostic Questionnaire (YDQ), (8 items) are two related but slightly different standard tools for the assessment of problematic Internet use developed by Young. However, a comparison of the prevalence of Internet addiction using these screening instruments is missing in the literature. Moreover, studies on Internet addiction among Indian school-going adolescents are limited., In this study, we compared the self-reported Internet addiction as per YDQ and IAT among school-going high school children (14–16 years) attending selected schools of Rohtak, Haryana.
| Materials and Methods|| |
This was a cross-sectional study conducted in six higher secondary schools funded and supported by the private management located in the urban area of Rohtak district. The period of data collection was between February 22, 2019, and March 20, 2019, and we compared the Internet addiction as per two screening criteria. After obtaining ethical approval and permission from the concerned authorities, all the students are informed that the study aims to assess the patterns of their Internet use rather than Internet addiction. The study settings were conveniently selected, and the participant information sheet with the details of the study, informed consent forms, and the screening questionnaire forms was distributed to all parents of the study participants. The concerned teachers were informed to get the filled forms from the parents of the respondents. All the eligible individuals who were able to read and write the English language were contacted for inclusion in the study. The students were encouraged to fill the form by themselves, and any difficulty in filling the form or understanding any question was clarified by the principal investigator. Besides, the students were specifically asked about the patterns of current Internet use to record the frequency of daily Internet use in hours, the mode, and the purpose of Internet use.
In total, 450 students were invited to participate in the study, of whom 400 completed the full questionnaires.
Sample size calculation
There is a wide variation of prevalence for Internet addiction among adolescents across the world. However, previous surveys conducted in Indian setting using similar research scales reported 8.7%–11.8% Internet addiction in school-going adolescents., Considering the rough estimate as 12% at 95% of the confidence interval and absolute precision of 5% in estimated prevalence with design effect 2, the minimum sample size required was calculated to be 325 using OpenEpi version 2.3, developed by Centers for Disease Control and Prevention, Atlanta, Georgia, USA (Source: https://www.openepi.com/SampleSize/SSPropor.htm). Assuming a nonresponse rate of 20%, 65 was added to the calculated sample size. Thus, the minimum total sample size was estimated as 390.
Internet addiction was assessed using YDQ and IAT. IAT consists of 20 items with total score ranges from 0 to 100. A score of 20–49, 50–79, and 80–100 was considered mild, moderate, and severe dependence on the Internet, respectively. The YDQ is based on patterns of Internet use over the past 6 months. This screening instrument consists of eight “yes” or “no” questions based on the DSM-IV criteria for pathological gambling. The present study adopted the widely used three subcategories of Internet addiction severity, in which respondents who answered yes to ≥5 of the criteria were categorized as “problematic users” and those answering yes to 3–4 criteria were categorized as “maladaptive users.”
| Results|| |
The mean age of study participants was 15.06 years (standard deviation = 0.85). More than half of the participants were boys (59.8%) and used the Internet for noneducational activities (54.8%). The most common mode of Internet use was mobile (76.2%), and the usage of Internet use was <5 h/day (76.2%). A major proportion of the parents of the children were educated up to secondary school level (70%–80%). The prevalence of severe Internet addiction ranged from 4.2% to 4.8% depending on the IAT (cutoff score of 80) and YDQ (cutoff score of >5) measurements, respectively [Table 1]. The comparison based on the measurements of two diagnostic questionnaires on the severity of the Internet addiction revealed a statistically significant association of Internet addiction in the following with selected characteristics: male gender, the noneducational purpose of Internet use, daily Internet usage of fewer than 5 h/day, and using the mobile phone as the mode of Internet use [P < 0.01; [Table 2]. The results of the present study showed a significant relationship between the IAT and YDQ addiction severity criteria as the kappa value, Chi-square value, and the Pearson correlation coefficient was statistically significant. The concordance between the two diagnostic criteria was established with Cohen's kappa analysis. There was a moderate and good concordance between the two criteria for determining the moderate and severe level of Internet addiction, respectively [k = 0.604 and k = 0.805, P < 0.01; [Table 3].
|Table 2: Comparison of the severity of Internet addiction as per the selected characteristics of the participants|
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|Table 3: Relationship between Young Diagnostic Questionnaire and Internet Addiction Test|
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| Discussion|| |
We conducted a cross-sectional study in school-going adolescent population of Haryana, North India. The present study identified approximately 4% of severe Internet addiction which is lower when compared to other earlier Indian studies. Previous studies from India reported 8.7%–11.8% of severe Internet addiction as per IAT among adolescents with an age range from 13 to 18 years.,
Despite the use of similar instruments, worldwide research on Internet addiction reports a wide variation in the prevalence of Internet addiction in school-going adolescents. The index study observed the prevalence of severe Internet addiction of 4.2% depending on the IAT scale cutoff score of 80 or above. Studies that investigated Internet addiction among school-going adolescents using similar cutoff scores reported the prevalence from 2.6% to 3.7%., Wang et al. surveyed 12,446 Chinese adolescents in the age range of 10–23 years and found 12.2% of Internet addiction (IAT cutoff score >50). We found that 4.8% of the students had severe Internet addiction as per the YDQ scale cutoff score of 5 and above. Studies that used a similar cutoff score observed the prevalence of Internet addiction from 5.5% (85/1552 Chinese adolescents) to 6.6% (7936/100,050 Japanese adolescents)., Another two studies among Chinese adolescents reported the prevalence ranging from 2.4% (64/2620) to 6.6% (1523/24,013) as per the YDQ scale., However, in Taiwan, it was shown that 13.8% of the high school adolescents (n =1708) were Internet addicts as per the YDQ scale. The studies that used other than IAT and YDQ also reported a wide variation of prevalence of Internet addiction among school-going adolescents across the world. In Turkey, 15.1% (175/1156) of the adolescents have been reported as Internet addicts, and in China, 8.8%–10.8% of the adolescents were found to be Internet addicts., In Korea, it was shown that 3.1%–4.3% of the adolescents were Internet addicts., Hence, our major findings of the prevalence of Internet addiction of approximately 4% among Indian school-going adolescents corroborate the earlier findings.
The study sample was recruited by a convenient sampling method and included those who can able to read and write the English language. The results of the study relied on self-reported standard screening tools, and no pilot study was undertaken for estimating a cutoff score as per the study population. The assessment of various patterns of Internet addiction particular to adolescents such as Internet gaming disorder and smartphone addiction was not explored. Furthermore, screening linked referral for the confirmation of the diagnosis was not possible due to logistic reasons.
Despite the limitation, the study gives insights about the magnitude of Internet addiction among school-going adolescents using two standardized screening tools. The findings of the study observed a good concordance of the two screening instruments and further highlight the clinical utility of these tools as per the study context. Adolescents are vulnerable to Internet addiction considering age and advancement in the technologies. Our study observed a lower prevalence of severe Internet addiction among school-going adolescents in this setting. Future studies should focus on the emerging trends such as smartphone addiction (“nomophobia”) in this population for a better understanding of the magnitude and patterns of problem.
| Conclusion|| |
The present study identified approximately 4% of severe Internet addiction among school-going adolescents. The findings of the present study suggest that there is a good level of concordance between IAT and YDQ. When time is a limitation, YDQ (8 items) can be considered for screening Internet addiction in this setting.
The authors are truly grateful to all the study participants and concerned authorities who provided the permission to conduct the study.
Financial support and sponsorship
Conflicts of interest
There are no conflicts of interest.
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