|Year : 2018 | Volume
| Issue : 1 | Page : 110-114
Study of internet addiction in children with attention-deficit hyperactivity disorder and normal control
Rupesh Enagandula1, Shipra Singh2, Gaurav W Adgaonkar3, Alka A Subramanyam4, Ravindra M Kamath4
1 Department of Psychiatry, Vardhman Mahavir Healthcare, Patiala, India
2 Department of Psychiatry, Dr. RML Hospital and PGIMER, New Delhi, India
3 Department of Psychiatry, Smt. K. N. Medical College and General Hospital, Pune, India
4 Department of Psychiatry, BYL Nair Hospital and TNMC, Mumbai, Maharashtra, India
|Date of Web Publication||15-Oct-2018|
Dr. Shipra Singh
Department of Psychiatry, Dr. R.M.L. Hospital & PGIMER, New Delhi
Source of Support: None, Conflict of Interest: None
| Abstract|| |
Background: In the current era, the use of electronic media in the form of Internet has increased exponentially, particularly among children, and has led to their excessive involvement in Internet. In this context, attention-deficit hyperactivity disorder (ADHD) children were found to have increased tendency for this addiction. Aims and Objectives: The aim is to study and compare Internet addiction between ADHD and normal children and the relation of demographic profile to Internet addiction. Materials and Methods: This was a cross-sectional study including 100 children (50 ADHD cases and 50 normal children without any psychiatric illness as controls) between the ages of 8 and 16 years. A semi-structured pro forma for demographic profile and Internet usage using Young's Internet Addiction Test (YIAT) was used. Statistical analysis was done using SPSS 20. Results: Internet addiction among ADHD children was 56% (54% having “probable Internet addiction” and 2% having “definite Internet addiction”). This was statistically significant (P < 0.05) in comparison with normal children where only 12% had Internet addiction (all 12% had “probable Internet addiction”). ADHD children were 9.3 times more prone to the development of Internet addiction as compared to normal (odds ratio – 9.3). Significant increase in average duration of Internet usage in ADHD children with increasing score of YIAT (P < 0.05) was seen. The incidence of Internet addiction was more in male ADHD children as compared to normal (P < 0.05). Conclusions: ADHD children are more prone to Internet addiction as compared to normal children and thus require preventive strategies.
Keywords: Adolescents, attention-deficit hyperactivity disorder, Internet addiction
|How to cite this article:|
Enagandula R, Singh S, Adgaonkar GW, Subramanyam AA, Kamath RM. Study of internet addiction in children with attention-deficit hyperactivity disorder and normal control. Ind Psychiatry J 2018;27:110-4
|How to cite this URL:|
Enagandula R, Singh S, Adgaonkar GW, Subramanyam AA, Kamath RM. Study of internet addiction in children with attention-deficit hyperactivity disorder and normal control. Ind Psychiatry J [serial online] 2018 [cited 2020 Feb 19];27:110-4. Available from: http://www.industrialpsychiatry.org/text.asp?2018/27/1/110/243317
Children and adolescents these days are getting easy access to Internet. The use of Internet has become a must part of our daily lives. Easy availability of Internet has problems of its own which psychiatrists throughout the world have started to notice recently. This has an addictive potential.
While maximum makes the use of the Internet in a controlled fashion, a progressive loss of the ability to control the frequency and duration of Internet activities emerges in some users. As a consequence, the excessive time devoted to Internet use and the behavioral narrowing can lead to serious psychosocial outcomes. This phenomenon is referred to as “Pathological Internet Use” (PIU) by Petersen  or “Internet addiction.”
Studies from different parts of the world suggest that overall prevalence of Internet addiction in adolescents ranges between 2% and 18%.,,,,
Cross-sectional studies on samples of patients with psychiatric disorders report high comorbidity of PIU, for example, affective disorder and attention-deficit hyperactivity disorder (ADHD). Internet addiction is associated with ADHD, depression, and hostility in males, while it is associated with ADHD and depression in females.
Teens with ADHD are at even greater risk for developing this compulsion. Adolescents who are addicted to the Internet are more likely than nonaddicted teens to engage in self-injurious behaviors such as hitting themselves, pulling their own hair, or pinching or burning themselves.
South Korea considers Internet addiction as one of its most serious public health issues. Using data from 2006, South Korean government estimates that approximately 2, 10, 000 South Korean children (2.1%; ages 6–19) are afflicted and require treatment. About 80% of those needing treatment may need psychotropic medications and perhaps 20%–24% require hospitalization. Results reveal that, based on studies conducted in China, Hong Kong, Taiwan, and Korea, there are about 12% of Asian youth who are addicted to the Internet. China is also greatly concerned about the disorder. As a result, in 2007, China began restricting computer game use; current laws now discourage more than 3 hours of daily game use.
Internet addiction appears to be a common disorder that merits inclusion in DSM-5., Due to the lack of methodological and sufficient research, currently, there are no specific guidelines for the management of PIU.
India has a huge number of Internet users, with an exponential increase of Internet usage and online activity by the younger generation as a principal modality of social interaction in the current era. A study conducted in Gujarat (India) showed that the prevalence of Internet usage among school-going adolescents is 98.9%; however, the prevalence of Internet addiction was 8.7%.
The data of Internet addiction and associated elements still are not robust. This study aims at examining Internet addiction in normal and ADHD children and its relation to sociodemographic variants in an Indian setting.
| Materials and Methods|| |
Study design and setting
It was a cross-sectional study carried out in the psychiatry and pediatric outpatient department (OPD) of a tertiary care teaching municipal hospital, after obtaining institutional ethics committee approval. In the psychiatry OPD, a child clinic runs, especially to address the psychiatric issues in children and adolescents.
A total of 100 children, aged 8–16 years, who had access to Internet usage, were included in the study. Fifty consecutive children from pediatric OPD who were ruled out for ADHD and other psychiatric comorbidities according to the DSM-5 criteria were included as controls. Fifty consecutive children from child psychiatry clinic, diagnosed with ADHD according to the DSM-5 criteria, were taken in the second group. Any child having any unstable or chronic disabling physical condition was excluded from the study. The diagnosis of ADHD was further objectively supported through Conners' Rating Scales for ADHD. Children with any other psychiatric morbidity or chronic/unstable medical illness were excluded from the study. A written informed consent from the parents of the child and assent from the child were taken before commencing the study. Interview was conducted by a single interviewer in a single setting.
- Semi-structured pro forma: To capture the demographic and pattern of Internet usage details
- Young's Internet Addiction Test (YIAT.): Developed by Dr. Kimberly Young, it is a validated and reliable measure of addictive use of the Internet. Cronbach's α is >0.9.,, YIAT is a twenty-item questionnaire that assesses Internet use in terms of the degree of preoccupation, inability to control use, extent of hiding or lying about online use, and continued online use despite negative consequences of behavior. Each item asks respondent the level of selected symptoms/psychological states which are scored as – does not apply (0), rarely (1), occasionally (2), frequently (3), often (4), and always (5). The total score measures the Internet usage as an average user (score 20–49), frequent problems (score 50–79), and significant problems (80–100). As defined in other studies, we defined the “Internet addiction” group as YIAT score ≥50 and the “Internet nonaddiction” group as YIAT score ≤49 and Internet addiction can be further subgrouped into 'probable internet addiction with frequent problem' group (when score is 50-79), and 'definite internet addiction with significant problems' (score 80-100).
- Conners' Parent Rating Scales-Revised Short (CPRS-R:S): To assess the severity of ADHD, the CPRS-R:S was completed for the patients. CPRS-R:S which has been used in this study has 27 questions and 5 subscales including opposition, cognitive problems, inattention, hyperactivity, and ADHD index. Internal coefficients have been reported in a range of 75%–90%, and test–retest reliability coefficients with the 8-week interval have been achieved in a range of 60%–90%.
Descriptive statistics, Pearson's Chi-square test, and one-way ANOVA were used to analyze the variables.
| Results|| |
Sociodemographic and Internet usage pattern
The demographic profile and Internet usage pattern of the participants were assessed. The sample had a male preponderance that is 74%, of which 43% had ADHD and rest (31%) were controls. More than half of them belonged to the age group of 11–13 years (52%), followed by 39% belonging to 14–16 years and rest in 8–10 years' category. Sixty-nine percent of them belonged to nuclear family. Home was the most common place of Internet usage (78%); school, cyber cafe, and friend's house were other places where children used Internet. Most of them (55%) used Internet alone without any supervision.
Comparison of Internet addiction between attention-deficit hyperactivity disorder and control group
Mean YIAT score of ADHD sample was 50 and of normal children 30; this difference was statistically significant (P = 0.001). The sample mean for ADHD children pointed more toward “probable Internet use” and that of normal children toward “average use.”
Studying the distribution of the participants based on the grading of YIAT score, a large number (56%) of ADHD children were found in Internet addiction range as compared to the number in normal group (12%); the difference was statistically significant (P< 0.001). ADHD children were found to be 9.3 times more prone (odd's ratio) to get addicted to the Internet as compared to normal children.
Distribution of sample based on Young's Internet Addiction Test
The mean duration of hours of Internet usage in the normal and ADHD group based on their categories of YIAT scores is depicted in [Table 1]. The scores in the ADHD group show that children having higher scores on YIAT have higher mean duration of Internet usage, and the difference among the various subgroups is statistically significant (P = 0.002). However, in the control group, the difference is not significant (P = 0.667). The average duration of time spent on Internet is higher in definite Internet addicts, i.e., 21 hours/week as compared to probable Internet addicts, where it was 12.53 hours/week.
|Table 1: Gender distribution and average duration of Internet usage with respect to Young's Internet Addiction Test scores in attention-deficit hyperactivity disorder and control groups|
Click here to view
Comparison based on gender shows that the number of male ADHD children (n = 25) in “frequent problem” category on YIAT scores is more as compared to normal children (n = 3), and this difference is statistically significant (P = 0.008), suggesting that male ADHD children probably have higher propensity toward Internet addiction. However, in case of female children, no considerable difference was observed [Table 1].
Considering the distribution as per the age [Table 2], there is statistically significant difference between the ADHD and the control group in the nonaddicted range of YIAT scoring, i.e., score <50 (P< 0.05). The number of children beyond the age group of 11 years (i.e., 11–16 years) using Internet was although high, but it was not problematic or addictive use. This could be attributed to the understanding of how to use Internet according to the needs after a certain age. Similarly, the distribution of ADHD sample in the age group of 11–16 years is higher (although not statistically significant difference) than the control group in the probable Internet addiction range (i.e., frequent problems). This result could be attributed to the lack of judgment and impulsivity seen in ADHD children.
|Table 2: Age-wise distribution of grading of Young's Internet Addiction Test score in the study groups|
Click here to view
Similarly, no statistically significant comparison was observed in family type, place of Internet use, and usage (alone/accompaniment/supervision) with grades of YIAT score.
| Discussion|| |
In line with previous studies,,,, we found that Internet addiction was higher in children who had ADHD (in the age group of 8–16 years), such that they are 9.3 times more prone to get addicted to Internet as compared to normal children. One such study including more than 2000 seventh graders having similar findings suggested certain plausible explanations for it: children with ADHD have lack of self-control and require instant gratification, which is provided by Internet through option to surf multiple participants simultaneously. Furthermore, Internet and social media temporarily provide an emotionally and socially safe platform to children to escape from their daily hassles and obligations, becoming a faulty coping mechanism for their stress and fears.
Previous literature also suggests that Internet addiction in ADHD children can also be attributed to behavioral and cognitive dysregulation. Behavioral dysregulation was observed in the form of deficits of attention, planning, working memories, self-monitoring, and judgment.,, Internet provides an ever-changing, multimodal means of instant gratification with minimal delay fits into the cognitive model of ADHD children hypothesized by Sonuga-Barke. In addition, excessive Internet usage is maintained over a long period through stimulatory effects on reward and sensitization as ADHD children are hypothesized to have low dopamine availability in the brain reward system, which is overcome to an extent by dopamine secreted at reward center following the instant gratification.
We found that male ADHD children had a greater propensity for Internet addiction, which is in accordance with previous studies. This suggests that ADHD or specifically male ADHD is a potential risk factor for Internet addiction.
Considering the duration of time spent on Internet, we found it higher in definite Internet addicts, which is in accordance with earlier studies.,, A recent study having the similar sample groups as ours showed similar findings. The prolonged hours of Internet use in ADHD children further reinforce the inattention, quick responsiveness, and instant rewards. Dalbudak and Evren found that severity of Internet addiction was related to the severity of the ADHD symptoms and suggested impulsivity as the mediator in this relationship.
Thus, taking into prior consideration of ADHD features increasing Internet addiction and later consideration of prolonged hours of Internet use consolidating inclination to impulsive, rapid, and hyperfocused reactivity, it could be inferred that ADHD features and Internet addiction may share a bidirectional relationship.
| Conclusions and Implication|| |
It is apparent that Internet addiction is higher in children with ADHD, especially boys, as compared to normal children. Thus, it seems imperative to watch out for Internet use and possible addiction in ADHD children. The converse is also true that if a parent complains of excessive Internet use, then it should alert a clinician to probe for comorbid ADHD. However, longitudinal studies with larger sample involving multiple sites including the possibility of constructive Internet use in ADHD children to understand complex tasks and social cues could be explored and would give more generalizable results. Furthermore, studies on limit setting, as far as time is concerned, may help understand their specific needs.
Financial support and sponsorship
Conflicts of interest
There are no conflicts of interest.
| References|| |
Petersen KU, Weymann N, Schelb Y, Thiel R, Thomasius R. Pathological internet use – Epidemiology, diagnostics, co-occurring disorders and treatment. Fortschr Neurol Psychiatr 2009;77:263-71.
Ge Y, Se J, Zhang J. Research on relationship among internet-addiction, personality traits and mental health of urban left-behind children. Glob J Health Sci 2014;7:60-9.
Bahrainian A, Khazaee A. Internet addiction among students: The relation of self esteem and depression. Bull Environ Pharmacol Life Sci 2014;3:1-6.
Kormas G, Critselis E, Janikian M, Kafetzis D, Tsitsika A. Risk factors and psychosocial characteristics of potential problematic and problematic internet use among adolescents: A cross-sectional study. BMC Public Health 2011;11:595.
Kamal NN, Mosallem FA. Determinants of problematic internet use among el-minia high school students, Egypt. Int J Prev Med 2013;4:1429-37.
Sharma A, Sahu R, Kasar PK, 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.
Ko CH, Yen JY, Chen CS, Yeh YC, Yen CF. Predictive values of psychiatric symptoms for internet addiction in adolescents: A 2-year prospective study. Arch Pediatr Adolesc Med 2009;163:937-43.
Whitlock JL, Powers JL, Eckenrode J. The virtual cutting edge: The internet and adolescent self-injury. Dev Psychol 2006;42:407-17.
Block JJ. Issues for DSM-V: Internet addiction. Am J Psychiatry 2008;165:306-7.
Hechanova MR, Czincz J. Internet Addiction in Asia: Reality or Myth. International Development Research Centre Digital Library; 2009. Available from: http://www.hdl.handle.net/10625/38567
. [Last accessed on 2017 Feb 4].
Weinstein A, Lejoyeux M. Internet addiction or excessive internet use. Am J Drug Alcohol Abuse 2010;36:277-83.
Prabhakaran MC, Patel VR, Ganjiwale DJ, Nimbalkar MS. Factors associated with internet addiction among school-going adolescents in Vadodara. J Family Med Prim Care 2016;5:765-9.
Whang LS, Lee S, Chang G. Internet over-users' psychological profiles: A behavior sampling analysis on internet addiction. Cyberpsychol Behav 2003;6:143-50.
Widyanto L, McMurran M. The psychometric properties of the internet addiction test. Cyberpsychol Behav 2004;7:443-50.
Yoo HJ, Cho SC, Ha J, Yune SK, Kim SJ, Hwang J, et al.
Attention deficit hyperactivity symptoms and internet addiction. Psychiatry Clin Neurosci 2004;58:487-94.
Young KS. Cognitive behavior therapy with internet addicts: Treatment outcomes and implications. Cyberpsychol Behav 2007;10:671-9.
Kumar G, Steer RA. Factorial validity of the Conners' parent rating scale-revised: Short form with psychiatric outpatients. J Pers Assess 2003;80:252-9.
Conners CK, Sitarenios G, Parker JD, Epstein JN. The revised conners' parent rating scale (CPRS-R): Factor structure, reliability, and criterion validity. J Abnorm Child Psychol 1998;26:257-68.
Yen JY, Ko CH, Yen CF, Wu HY, Yang MJ. The comorbid psychiatric symptoms of internet addiction: Attention deficit and hyperactivity disorder (ADHD), depression, social phobia, and hostility. J Adolesc Health 2007;41:93-8.
Ha JH, Yoo HJ, Cho IH, Chin B, Shin D, Kim JH, et al.
Psychiatric comorbidity assessed in Korean children and adolescents who screen positive for internet addiction. J Clin Psychiatry 2006;67:821-6.
Yang SC, Tung CJ. Comparison of Internet addicts and non-addicts in Taiwanese high school. Comput Human Behav 2007;23:79-96.
Schachar R, Logan GD. Impulsivity and inhibitory control in normal development and childhood psychopathology. Dev Psychol 1990;26:710.
Sergeant J. The cognitive-energetic model: An empirical approach to attention-deficit hyperactivity disorder. Neurosci Biobehav Rev 2000;24:7-12.
Cepeda NJ, Cepeda ML, Kramer AF. Task switching and attention deficit hyperactivity disorder. J Abnorm Child Psychol 2000;28:213-26.
Sonuga-Barke EJ. Psychological heterogeneity in AD/HD – A dual pathway model of behaviour and cognition. Behav Brain Res 2002;130:29-36.
Blum K, Chen AL, Braverman ER, Comings DE, Chen TJ, Arcuri V, et al.
Attention-deficit-hyperactivity disorder and reward deficiency syndrome. Neuropsychiatr Dis Treat 2008;4:893-918.
Chan PA, Rabinowitz T. A cross-sectional analysis of video games and attention deficit hyperactivity disorder symptoms in adolescents. Ann Gen Psychiatry 2006;5:16.
Morahan-Martin J, Schumacher P. Incidence and correlates of pathological internet use among college students. Comput Human 2000;16:13-29.
Weinstein A, Yaacov Y, Manning M, Danon P, Weizman A. Internet addiction and attention deficit hyperactivity disorder among schoolchildren. Isr Med Assoc J 2015;17:731-4.
Dalbudak E, Evren C. The relationship of internet addiction severity with attention deficit hyperactivity disorder symptoms in Turkish university students; impact of personality traits, depression and anxiety. Compr Psychiatry 2014;55:497-503.
[Table 1], [Table 2]