ArticlePDF Available

Impulsivity in Internet Addiction: A Comparison with Pathological Gambling


Abstract and Figures

Internet addiction has been considered to be associated with poor impulse control. The aim of this study is to compare the trait impulsivity of those suffering from Internet addiction with that of individuals suffering from pathological gambling. Twenty-seven patients diagnosed with Internet addiction (age: 24.78±4.37 years), 27 patients diagnosed with pathological gambling (age: 25.67±3.97 years), and 27 healthy controls (age: 25.33±2.79 years) were enrolled in this study. All patients were men seeking treatment. Trait impulsivity and the severity of the Internet addiction and pathological gambling were measured by the Barratt Impulsiveness Scale-11, the Young's Internet Addiction Test, and the South Oaks Gambling Screen, respectively. The Beck Depression Inventory and the Beck Anxiety Inventory were also administered to all subjects. Our results show that those suffering from Internet addiction showed increased levels of trait impulsivity which were comparable to those of patients diagnosed with pathological gambling. Additionally, the severity of Internet addiction was positively correlated with the level of trait impulsivity in patients with Internet addiction. These results state that Internet addiction can be conceptualized as an impulse control disorder and that trait impulsivity is a marker for vulnerability to Internet addiction.
No caption available
Content may be subject to copyright.
Impulsivity in Internet Addiction:
A Comparison with Pathological Gambling
Hae Woo Lee, M.D.,
Jung-Seok Choi, M.D., Ph.D.,
Young-Chul Shin, M.D., Ph.D.,
Jun-Young Lee, M.D., Ph.D.,
Hee Yeon Jung, M.D., Ph.D.,
and Jun Soo Kwon, M.D., Ph.D.
Internet addiction has been considered to be associated with poor impulse control. The aim of this study is to
compare the trait impulsivity of those suffering from Internet addiction with that of individuals suffering from
pathological gambling. Twenty-seven patients diagnosed with Internet addiction (age: 24.78 4.37 years), 27
patients diagnosed with pathological gambling (age: 25.67 3.97 years), and 27 healthy controls (age: 25.33 2.79
years) were enrolled in this study. All patients were men seeking treatment. Trait impulsivity and the severity of
the Internet addiction and pathological gambling were measured by the Barratt Impulsiveness Scale-11, the
Young’s Internet Addiction Test, and the South Oaks Gambling Screen, respectively. The Beck Depression
Inventory and the Beck Anxiety Inventory were also administered to all subjects. Our results show that those
suffering from Internet addiction showed increased levels of trait impulsivity which were comparable to those of
patients diagnosed with pathological gambling. Additionally, the severity of Internet addiction was positively
correlated with the level of trait impulsivity in patients with Internet addiction. These results state that Internet
addiction can be conceptualized as an impulse control disorder and that trait impulsivity is a marker for
vulnerability to Internet addiction.
Internet addiction, defined as an inability to control In-
ternet use, can lead to serious impairment in psychological
and social functioning.
The individuals with Internet ad-
diction show behavioral problems in Internet use or excessive
Internet usage, and they experience various psychiatric
symptoms such as depressive mood or anxiety.
addiction has been categorized as a behavioral addiction,
because it includes several features that are characteristic of
addictions, such as preoccupation, mood changes, tolerance,
withdrawal, and functional impairment.
and Beard and Wolf
have suggested that Internet
addiction is a disorder involving, or at least related to, poor
impulse control. Pathological gambling is also considered a
behavioral addiction and is classified as an impulse control
disorder in the Diagnostic and Statistical Manual of Mental
Disorders, Fourth Edition (DSM-IV).
Impulsivity has a range of definitions that include lack
of planning or forethought, reduced perseverance, and
seeking novel experiences.
Impulsivity is a trait that has
often been related to addictive behavior.
Barnes et al.,
Vitaro et al.,
Moeller et al.,
and De Wit
showed evi-
dence that impulsivity is related to addictions to substance
or behaviors (e.g., pathological gambling). Vitaro et al.
investigated whether the impulsivity of 12–14-year-olds
could predict problem gambling in late adolescence and
reported evidence in support of the DSM-IV classification
of pathological gambling as an impulse control disorder.
Goudriaan et al.
and Grant et al.
studied increased
impulsivity in pathological gambling using neurocogni-
tive tasks assessing impulsivity. Patients diagnosed with
pathological gambling had longer reaction times on stop-
signal trials in the stop-signal task, which is indicative
of greater difficulties with regard to inhibiting the stop
With regard to impulsivity in Internet addiction, Cao
et al.
examined the relationship between impulsivity and
Internet addiction among Chinese adolescents. The authors
showed that the Internet addiction group was more impul-
sive than the control group, as measured by both the Barratt
Impulsiveness Scale 11 (BIS-11) and the Go-Stop impulsivity
Department of Psychiatry, SMG-SNU Boramae Medical Center, Seoul, Republic of Korea.
Department of Psychiatry, Seoul National University College of Medicine, Seoul, Republic of Korea.
Department of Psychiatry, Kangbuk Samsung Hospital, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea.
Volume 15, Number 7, 2012
ªMary Ann Liebert, Inc.
DOI: 10.1089/cyber.2012.0063
paradigm, supporting the classification of Internet addiction
as an impulse control disorder.
Until now, there is no study about the impulsivity in In-
ternet addiction by directly comparing it with that in patho-
logical gambling. This study was performed to determine the
degree to which the subjects diagnosed with Internet addic-
tion, subjects diagnosed with pathological gambling, and
healthy controls demonstrated trait impulsivity as measured
by the BIS-11 and to examine the relationship between the
severity of Internet addiction and the degree of impulsivity.
Treatment-seeking male patients diagnosed with Internet
addiction or pathological gambling were enrolled in this
We hypothesized that the subjects diagnosed with Internet
addiction would show an increased impulsivity that was
comparable to that shown by individuals diagnosed with
pathological gambling.
Materials and Methods
Twenty-seven patients diagnosed with Internet addiction
(age: 24.78 4.37 years), 27 patients diagnosed with patho-
logical gambling (age: 25.67 3.97 years), and 27 healthy
controls (age: 25.33 2.79 years) were enrolled in this study.
All patients were treatment seeking, that is, they visited our
clinics due to their suffering from Internet use or gambling-
related problems; only male patients were enrolled, because
the prevalence rate of excessive Internet use differs between
men and women, and men are more likely to be problematic
users of the Internet.
We included homogeneous male
subjects to control variables, affecting the impulsivity, such as
gender and biological factors.
Patients were recruited from
the outpatient clinics of the SMG-SNU Boramae Medical
Center and the Kangbuk Samsung Hospital in Seoul, South
We assessed the participants using Young’s Internet Ad-
diction Test (IAT),
South Oaks Gambling Screen (SOGS),
Beck’s Depression Inventory (BDI),
and Beck’s Anxiety
Inventory (BAI).
Young after the DSM-IV criteria for pathological gambling,
standardized scale in South Korea. In addition, we can
assess the severity of Internet addiction using the total
score of Young’s IAT. SOGS is also the standardized scale in
South Korea. The subjects with pathological gambling are
classified by the scores of SOGS from level 1 to 3, not as a
dichotomy. Therefore, we can evaluate the relationships
between the impulsivity and severity of symptoms. The
reasons behind the choice of BDI and BAI is to evaluate the
anxiety and depressive symptoms in subjects with Internet
addiction and pathological gambling to control the effect on
Previous studies have defined excessive Internet users as
those with scores of at least 50 on the IAT.
However, we
included only subjects with scores of at least 70 on the IAT
who also spent more than 4 hours per day and 30 hours per
week using the Internet to collect the severe Internet addic-
tion group, not the high-risk group with excessive Internet
use. The mean score on the IAT obtained by patients in the
Internet addiction group was 75.67 4.60. The mean number
of hours of Internet use per day and per week in this group
were 6.75 2.86 and 47.61 15.83, respectively. In addition,
the Structured Clinical Interview for DSM-IV (SCID)
used to identify the past and current psychiatric illnesses. Of
the 27 patients diagnosed with Internet addiction, four ful-
filled the DSM-IV criteria for depressive disorder. The main
purpose of Internet use in all patients with Internet addiction
was online gaming, and no patients used the Internet for
online gambling. The diagnosis of pathological gambling was
based on the SCID.
The diagnosis of pathological gambling
was also defined for patients with an SOGS
score q5. Out
of the 27 patients diagnosed with pathological gambling, 15
were included in our previous report.
Healthy controls
were recruited from the local community and had no history
of any psychiatric disorder. Patients with pathological gam-
bling and healthy controls used the Internet for less than 2
hours per day. All patients were drug naı
¨ve. The BDI
the BAI
were administered to all subjects to measure de-
pressed and anxious symptoms, respectively. The institu-
tional review boards of the SMG-SNU Boramae Medical
Center and the Kangbuk Samsung Medical Center approved
the study protocol, and all subjects provided written in-
formed consent before participation.
IAT. We used the Korean version of Young’s IAT
assess the severity of Internet addiction. Items in this test are
rated on a five-point scale on which one indicates ‘‘very
rarely,’’ and five indicates ‘‘very frequently.’’ Total scores
were calculated according to Young’s method,
and the
possible scores for all 20 items ranged from 20 to 100.
SOGS. The SOGS consists of a 20-item questionnaire and
is used to screen pathological gambling. Scores of five or
more are considered indicative of pathological gambling.
We used the Korean version of the SOGS.
BIS-11. We used the BIS-11
to measure impulsivity.
The BIS-11 includes three subscales: cognitive impulsiveness,
motor impulsiveness, and nonplanning impulsiveness. We
used the Korean version of the BIS-11.
Statistical analysis
All statistical analyses were conducted with SPSS 17.0.
Demographic and clinical data were compared using analy-
ses-of-variance (ANOVAs) tests with Tukey’s post hoc anal-
ysis. The correlation between IAT scores and clinical variables
in subjects with Internet addiction was assessed using Pear-
son’s correlation analysis. Statistical significance was set at
the level of 0.05, which was two tailed.
Demographic and clinical characteristics
Table 1 presents the demographic and clinical character-
istics of the subjects. No significant differences in age or ed-
ucation were observed among the three groups. The three
groups differed significantly in terms of BDI, F(2, 78) =22.27,
p<0.01, and BAI, F(2, 78) =11.36, p<0.01, scores. Both the
Internet addiction and pathological gambling groups ob-
tained higher scores in the BDI and BAI than did the healthy
controls ( post hoc, p <0.01). The Internet addiction group was
374 LEE ET AL.
characterized by longer illnesses than was the pathological
gambling group ( p<0.01).
Comparison of impulsivity among the Internet
addiction, pathological gambling, and healthy
control groups
We found significant differences among the groups with
regard to total scores on the BIS-11, F(2, 78) =16.68, p<0.01,
and scores on all three subscales: cognitive impulsiveness,
F(2, 78) =6.68, p<0.01, motor impulsiveness, F(2, 78) =17.12,
p<0.01, and nonplanning impulsiveness, F(2, 78) =14.01,
p<0.01. The post hoc analyses revealed that both the Internet
addiction and pathological gambling groups obtained higher
total scores and higher scores on the three subscales than did
the healthy controls ( p<0.01). To control the effects of de-
pressive mood and anxiety, we reanalyzed the ANOVA
treating the BDI and BAI as covariates. Significant differences
were observed among three groups with regard to scores for
motor impulsiveness, F(2, 78) =4.75, p=0.01. The post hoc an-
alyses revealed that both the Internet addiction and patho-
logical gambling groups obtained higher scores for motor
impulsiveness than did the healthy control group ( p=0.01 and
p=0.02, respectively). Furthermore, we conducted a regression
analysis to evaluate how much more likely it is to develop
impulsivity in subjects with Internet addiction and pathologi-
cal gambling than in healthy controls. Each of the Internet
addiction and pathological gambling groups showed signifi-
cantly higher impulsivity compared with the healthy con-
trol group (b=16.89, confidence interval (C.I): 12.49*21.30,
p<0.01; b=15.68, C.I: 12.49*21.30, p<0.01, respectively).
Relationship between severity of Internet addiction
and impulsivity in the Internet addiction group
We conducted Pearson’s correlation analysis to examine
the relationship between the severity of Internet addiction
and the impulsivity in patients with Internet addiction. We
found that scores on the IAT were positively correlated with
total scores and scores on the three subscales. All correlations
demonstrated a statistical significance ( p<0.05). Figure 1
shows the relationship between the severity of Internet ad-
diction and total scores on the BIS-11 in patients with Internet
The present study compared the trait impulsivity, as
measured by the BIS-11, of individuals diagnosed with In-
ternet addiction with that of individuals diagnosed with
pathological gambling from the perspective of considering
Internet addiction to be an impulse control disorder. We
found that the Internet addiction group showed increased
levels of trait impulsivity that were comparable to those
Table 1. Demographic and Clinical Characteristics in Study Subjects
Internet addiction (N =27) Pathological gambling (N =27) Healthy controls (N =27)
Variables Mean SD Mean SD Mean SD F, t p
Age (years) 24.78 4.37 25.67 3.97 25.33 2.79 0.38 0.68
Education (years) 14.26 1.93 13.96 1.95 14.67 1.41 1.06 0.35
Duration of illness (years) 11.37 3.68 2.44 1.17 -12.02 <0.01
IAT 75.67 4.60
SOGS 17.67 2.77
BDI 15.59 6.52 15.89 10.90 3.48 4.58 22.27 <0.01
BAI 14.37 8.12 12.59 12.15 3.81 3.78 11.36 <0.01
Cognitive 19.67 3.14 19.07 4.82 16.30 2.49 6.68 <0.01
Motor 23.93 4.35 23.67 5.57 17.19 4.36 17.12 <0.01
Nonplanning 29.59 4.17 29.11 7.85 22.70 2.55 14.01 <0.01
Total 73.07 8.70 71.85 17.33 56.19 7.40 16.68 <0.01
SD, standard deviation; IAT, Internet addiction test; SOGS, South Oaks Gambling Screen; BDI, Beck Depression Inventory; BAI, Beck
Anxiety Inventory; BIS-11, Barratt Impulsiveness Scale 11.
FIG. 1. Correlation between the severity of Internet addic-
tion and the level of impulsivity (total scores on Barratt Im-
pulsiveness Scale-11) in the Internet addiction group (r=0.64,
p<0.01). Solid line is the best fit line (r=0.64, p<0.01), and
dashed line means a 95 percent confidence interval.
observed in patients with pathological gambling. In addition,
the severity of Internet addiction was positively correlated
with the level of trait impulsivity in patients diagnosed with
Internet addiction. To our knowledge, this is the first study
that measures trait impulsivity in treatment-seeking patients
with Internet addiction and compares these results with those
obtained from patients with pathological gambling and
healthy controls.
Impulsivity has been addressed as an endophenotype of
individuals at risk for developing addictions, including sub-
stance use disorders and pathological gambling.
In partic-
ular, trait impulsivity, which refers to an enduring
personality characteristic, has been reported to be a marker of
susceptibility to pathological gambling.
Trait impulsivity
has also been associated with Internet addiction.
Cao et al.
reported that impulsivity was positively correlated with In-
ternet addiction, supporting the hypothesis that impulsivity
is a risk factor for developing Internet addiction. Park et al.
reported that those who overused Internet games showed
greater impulsivity than did normal users, and noted a pos-
itive correlation between the severity of the overuse and im-
pulsivity. Those who overused Internet games had abnormal
glucose metabolism in the brain regions associated with im-
pulse control, suggesting that overuse of Internet games
shares psychological and neural mechanisms with other
types of impulse control disorders and addictions.
Based on
previous reports, Internet addiction has been considered an
impulse control disorder. Our current findings also indicated
that patients diagnosed with Internet addiction were char-
acterized by higher levels of trait impulsivity than were
healthy controls and by levels of trait impulsivity which were
comparable to those of patients diagnosed with pathological
gambling. This study may be interpreted as a confirmation of
the construal of Internet addiction as an impulse control
The Internet addiction and pathological gambling groups
in this study showed increased depressed and anxious
symptoms. Four patients with Internet addiction also had a
diagnosis of depressive disorder. Indeed, depression has been
reported to be associated with Internet addiction.
pressed individuals may rely on the Internet as a way of
coping with their depressive state. When we controlled for
the effects of depressed and anxious symptoms on Internet
addiction and impulsivity, the Internet addiction group
demonstrated increased impulsivity, especially motor im-
pulsiveness on the BIS-11. The significant correlation between
the severity of Internet addiction and impulsivity also re-
mained. These findings suggest that the higher trait impul-
sivity in the Internet addiction group may be independent of
mood state.
This study has several limitations. First, the sample size
was small, and only male subjects were included; thus, the
generalization of the results may be limited. Second, this
study is a case-control study design that has limitations in
showing the correlations between impulsivity and clinical
psychiatric symptoms. However, we included drug-naive
patients, and it is important to recruit a homogeneous sample
to control for confounding factors such as medication and
gender effects. Furthermore, we included treatment-seeking
patients, and diagnoses were made by psychiatrists to accu-
rately identify individuals with pathological Internet use or
gambling. Future studies should use larger samples as well as
longitudinal study design to investigate the neurobiological
markers associated with impulsivity among those diagnosed
with Internet addiction.
The present study found that treatment-seeking patients
diagnosed with Internet addiction showed increased trait
impulsivity as measured by the BIS-11 and that their levels of
trait impulsivity were comparable to those of patients diag-
nosed with pathological gambling. We also found a signifi-
cant positive correlation between the severity of Internet
addiction and the level of impulsivity. These results provide
evidence that Internet addiction can be conceptualized as an
impulse control disorder and that trait impulsivity is a mar-
ker for vulnerability to develop Internet addiction.
Author Disclosure Statement
The authors have no conflict of interest.
1. Young KS. Psychology of computer use: XL. Addictive use
of the Internet: a case that breaks the stereotype. Psycholo-
gical Reports 1996; 79:899–902.
2. Griffiths M. Psychology of computer use: XLIII. Some com-
ments on ‘addictive use of the Internet’ by Young. Psycho-
logical Reports 1997; 80:81–82.
3. Davis RA. A cognitive-behavioral model of pathological
Internet use. Computers in Human Behavior 2001; 17:187–
4. Morahan-Martin J, Schumacher P. Incidence and correlates
of pathological Internet use among college students. Com-
puters in Human Behavior 2000; 16:13–29.
5. Kalwar SK, Heikkinen K, Porra J. An evaluation of human
anxiety on the Internet. IADIS International Conference e-
Society 2010; 272–286.
6. Chou C, Hsiao MC. Internet addiction, usage, gratification,
and pleasure experience: the Taiwan college students’ case.
Computers & Education 2000; 35:65–80.
7. Hall AS, Parsons J. Internet addiction: college student case
study using best practices in cognitive behavior therapy.
Journal of Mental Health Counseling 2001; 23:312–327.
8. Beard KW, Wolf EM. Modification in the proposed diag-
nostic criteria for Internet addiction. Cyberpsychology and
Behavior 2001; 4:377–383.
9. Potenza MN. Should addictive disorders include non-
substance-related conditions? Addiction 2006; 101(suppl 1):
10. Verdejo-Garcia A, Lawrence AJ, Clark L. Impulsivity as a
vulnerability marker for substance-use disorders: review of
findings from high-risk research, problem gamblers and
genetic association studies. Neuroscience & Biobehavioral
Reviews 2008; 32:777–810.
11. Dawe S, Gullo MJ, Loxton NJ. Reward drive and rash im-
pulsiveness as dimensions of impulsivity: Implications for
substance misuse. Addictive Behaviors 2004; 29:1389–1405.
12. Barnes GM, Welte JW, Hoffman JH, Dintcheff BA. Shared
predictors of youthful gambling, substance use, and delin-
quency. Psychology of Addictive Behaviors 2005; 19:165–
13. Vitaro F, Arseneault L, Tremblay RE. Impulsivity predicts
problem gambling in low SES adolescent males. Addiction
1999; 94:565–575.
376 LEE ET AL.
14. Moeller FG, Dougherty DM, Barratt ES, et al. The impact of
impulsivity on cocaine use and retention in treatment.
Journal of Substance Abuse Treatment 2001; 21:193–198.
15. De Wit H. Impulsivity as a determinant and consequence of
drug use: a review of underlying processes. Addiction
Biology 2009; 14:22–31.
16. Goudriaan AE, Oosterlaan J, de Beurs E, van den Brink W.
Neurocognitive functions in pathological gambling: a com-
parison with alcohol dependence, Tourette syndrome and
normal controls. Addiction 2006; 101:534–547.
17. Grant JE, Chamberlain SR, Odlaug BL, et al. Memantine
shows promise in reducing gambling severity and cognitive
inflexibility in pathological gambling: a pilot study. Psy-
chopharmacology 2010; 212:603–612.
18. Cao F, Su L, Liu T, Gao X. The relationship between im-
pulsivity and Internet addiction in a sample of Chinese ad-
olescents. European Psychiatry 2007; 22:466–471.
19. Becker JB. Sexual differentiation of motivation: a novel
mechanism? Hormones and Behavior 2009; 55:646–654.
20. Beard KW. Internet addiction: a review of current assess-
ment techniques and potential assessment questions. Cy-
berPsychology & Behavior 2005; 8:7–14.
21. Mottram AJ, Fleming MJ. Extraversion, impulsivity, and
online group membership as predictors of problematic In-
ternet use. CyberPsychology & Behavior 2009; 12:319–321.
22. Lesieur HR, Blume SB. The South Oaks Gambling Screen
(SOGS): a new instrument for the identification of patho-
logical gamblers. American Journal of Psychiatry 1987;
23. Beck AT, Ward C, Mendelson M. Beck Depression Inventory
(BDI). Archives of General Psychiatry 1961; 4:561–571.
24. Beck AT, Epstein N, Brown G, Steer RA. An inventory
for measuring clinical anxiety: psychometric properties.
Journal of Consulting and Clinical Psychology 1988; 56:
25. Hardie E, Tee M. Excessive Internet use: the role of per-
sonality, loneliness, and social support networks in Internet
addiction. Australian Journal of Emerging Technologies and
Society 2007; 5:34–47.
26. First MB, Spitzer RL, Gibbon M, Williams JBW. (1996)
Structured clinical interview for DSM-IV axis I disorder. New
York: New York State Psychiatric Institute.
27. Choi WC, Kim KB, Oh DY, Lee TK. A preliminary study on
standardization of Korean form of South Oaks gambling
screening. Journal of Korean Academy of Addiction Psy-
chiatry 2001; 5:46–52.
28. Hwang JY, Shin YC, Lim SW, et al. Multidimensional com-
parison of personality characteristics of the big five model,
impulsiveness, and affect in pathological gambling and
obsessive-compulsive disorder. Journal of Gambling Studies
2011 [Epub ahead of print] DOI: 10.1007/s10899-011-9269-6.
29. Song MJ. (2000) Internet addictive users’ communicative satis-
faction in online and offline situation. Master’s thesis, Graduate
School of Korea University, Seoul,Korea.
30. Barratt ES. (1985) Impulsiveness subtraits: arousal and infor-
mation processing. In: Spence JT, Izard CE, eds. Motivation,
emotion and personality. North Holland: Elsevier Science, pp.
31. Lee HS. (1992) Impulsivity test. Seoul: Korean guidance.
32. Lai FD, Yip AK, Lee TM. Impulsivity and pathological
gambling among Chinese: is it a state or a trait problem?
BMC Research Notes 2011; 4:492.
33. Park HS, Kim SH, Bang SA, et al. Altered regional cerebral
glucose metabolism in Internet game overusers: a 18F-
fluorodeoxyglucose positron emission tomography study.
CNS Spectrum 2010; 15:159–166.
34. Yen JY, Ko CH, Yen CF, et al. The comorbid psychiatric
symptoms of Internet addiction: attention deficit and hy-
peractivity disorder (ADHD), depression, social phobia, and
hostility. Journal of Adolescent Health 2007; 41:93–96.
35. Lin MP, Ko HC, Wu JY. Prevalence and psychosocial risk
factors associated with Internet addiction in a nationally
representative sample of college students in Taiwan. Cy-
berpsychology, Behavior, and Social Networking 2011;
36. Ha JH, Kim SY, Bae SC, et al. Depression and Internet ad-
diction in adolescents. Psychopathology 2007; 40:424–430.
37. Yeh YC, Ko HC, Wu JY, et al. Gender differences in rela-
tionships of actual and virtual social support to Internet
addiction mediated through depressive symptoms among
college students in Taiwan. Cyberpsychology, Behavior, and
Social Networking 2008; 11:485–487.
38. Morrison CM, Gore H. The relationship between excessive
Internet use and depression: a questionnaire-based study of
1,319 young people and adults. Psychopathology 2010;
Address correspondence to:
Dr. Jung-Seok Choi
Department of Psychiatry
SMG-SNU Boramae Medical Center
20 Boramae-ro 5-gil
Seoul 156-707
Republic of Korea
This article has been cited by:
1. Su Mi Park, Yoon A. Park, Hae Woo Lee, Hee Yeon Jung, Jun-Young Lee, Jung-Seok Choi. 2012. The effects of behavioral
inhibition/approach system as predictors of Internet addiction in adolescents. Personality and Individual Differences .
... The decrease in inhibitory response may be a factor that contributes to the maintenance and worsening of addictive behaviors in relation to the Internet (Dieter et al., 2017). In this sense, Lee et al. (2012) concludes that IA can be considered an impulse control disorder, with reduced prefrontal processing in subjects with Internet addiction, which may be related to the lack of control in the use of this tool (Brand et al., 2014 ). ...
Full-text available
The increasing availability of the Internet, although with many positive effects for most, has triggered addictive effects for part of the population. They experience social isolation due to Internet overuse and, when deprived of it, they feel anxiety, fissure, and psychomotor agitation. This study investigated associations among Internet addiction, demographic and cognitive variables, such as impulsivity, aggression, and depressive and/or anxiety symptoms. In this study, 1,485 young adults (67.9% women) were assessed using four psychological instruments. It was found that 19.1% of the participants presented a moderate or severe internet addiction, with men having a higher prevalence (45.0%). The risk population also included individuals who use the Internet for gaming and residents of the Northeastern region of Brazil. Moreover, a higher index of motor or attentional impulsivity, or more depressive symptoms, seems to increase the prevalence of Internet Addiction, requiring greater attention in preventive strategies.
Full-text available
Tato zpráva je první souhrnnou zprávou o nadužívání digitálních technologií, tj. nadměrném trávení času na internetu, zejména na sociálních sítích a hraním digitálních her, které může vést ke vzniku a rozvoji závislostí, označovaných souhrnně v této zprávě jako digitální závislosti. Zpráva kromě výskytu tohoto fenoménu v populaci shrnuje dostupné informace o zdravotních a sociálních dopadech nadužívání digitálních technologií. Součástí je základní vymezení pojmů, popis národní strategie a politiky v této oblasti a podrobně jsou prezentována zjištění populačních i dalších výběrových studií, data ze zdravotnické statistiky týkající se léčby i data ze sítě adiktologických služeb pracujících se skupinou klientů s problémy v oblasti nadužívání digitálních technologií. Prezentovaná data shrnují situaci ke konci května 2022 – popisovány jsou tedy poslední dostupné výsledky (z běžných statistik jde obvykle o údaje za r. 2021) a tam, kde jsou dostupné časové řady studií, jsou prezentovány i trendy ve vývoji situace. This report is the first summary report on excessive use of digital technologies, i.e. excessive time spent on the Internet, especially on social media and digital (computer) games that can lead to the development of addiction, called in this report as digital addiction. The report summarizes the extent of this phenomenon in the adult and adolescent population, and available information on health and social consequences of the excessive use of digital technologies. It countains the description of the concept and definitions, description of the National Strategy and policy in this area, presents in detail the results of population and other sample surveys, treatment data from health statistics, as well as data from addictology services working with clients overusing digital technologies and at risk of digital addiction. Data presented summarize the situation as of the end of May 2022 - the latest available data from routine monitoring systems refer to 2021, and where available, time series, trends and developments are presented.
Background Problematic use of the internet (PUI) is a growing concern, particularly in the young population. Family factors influence internet use among children in negative ways. This study examined the existing literature on familial or parental factors related to PUI in children. Methods A scoping review was conducted in EBSCOhost, PubMed, ScienceDirect, JSTOR, Biomed Central, VHL Regional Portal, Cochrane Library, Emerald Insight, and Oxford Academic Journal databases. Studies reporting data on family factors associated with PUI in children, published in English in the 10 years to July 2020 were included. The following data were extracted from each paper by two independent reviewers: methodology and demographic, familial, psychiatric, and behavioral correlates of PUI in children. Results Sixty-nine studies fulfilled the eligibility criteria. Three themes emerged: parenting, parental mental health, and intrafamilial demographic correlates of PUI in children. Parenting styles, parental mediation, and parent–child attachment were the major parenting correlates. Conclusion Literature on significant familial and parental factors associated with PUI in children is scarce. More research is required to identify the interactions of familial and parental factors with PUI in children, to develop informed management strategies to address this issue.
Background. The study of the prevalence and structure of various types of online behavior, the characteristics of the content consumed by adolescents of different age, sex and ethnic groups is an important area of scientific research. The aim. To study the features of online behavior and the structure of content consumed in Abakan adolescents of various age and sex groups and ethnicity (Russians and Khakasses). Materials and methods. 1400 adolescents of the city of Abakan (Republic of Khakassia) aged 12–18 were examined: 962 (68.7 %) Russians, 438 (31.3 %) Khakasses, 678 (48.4 %) boys and 722 (51.6 %) girls, aged 12–14 years – 39.8 % and 15–18 years – 60.2 %. The type of online behavior was verified using the Chen scale (CIAS). Emotional and behavioral disorders were diagnosed using the SDQ questionnaire. The indicators were compared in groups formed by sex, age and ethnicity. The data were processed using the Statistica 12.0 program (StatSoft Inc., USA). Results. It has been established that the prevalence and structure of online behavior among adolescents in Abakan depends on gender, age and ethnicity. Pathological Internet use (PIU) is more common among Khakasses, more often in the older age group. Regardless of ethnicity, maladaptive online behavior (pathological and maladaptive Internet use) is recorded more often among girls. In the structure of consumed content, gaming addiction prevails, social network addiction is in second place, and the proportion of mixed and undifferentiated Internet addiction is less. Dependence on online games prevails in boys, while dependence on social networks and undifferentiated internet addiction prevail in girls. Conclusion. One of the reasons for the greater prevalence of maladaptive online behavior among Khakasses may be the association of maladaptive Internet use with the presence of emotional disorders and behavioral problems that reach the borderline level and are causally significant factors in the development of Internet addiction. Adolescents with maladaptive online behavior, who have not yet reached the level of formed Internet addiction, are the target group requiring medical and psychological assistance.
Problematic Internet use is broadly regarded as a level of Internet use resulting in consequential outcomes at the psychological, social, familial, and educational levels, often occurring due to struggles in adjusting oneself and their use of the Internet. There exists an intersectionality affecting the risk factors for problematic Internet use, which manifests across a neurobehavioral setting associated with a temporary structural imbalance wherein the adolescent is primarily guided by the reward pathway instead of prefrontal control. The resulting susceptibility to influence and risk-taking engages with adolescent psychosocial development as they interact with their environment and establish their sense of identity amongst their peers. Thus, adolescent psychosocial development can be influenced by Internet and social media activity in a manner that can often turn into a cycle with negative implications. The resulting form of dependency can be associated with problematic Internet use as a form of self-validation, but also render them vulnerable to negative outcomes through their manner of Internet use. Nuances in individual personality and tendencies such as aggression, can often reflect increased risks of engaging in problematic Internet use. Social functioning, relationships, and self-esteem are amongst the attributes that become affected, and can be related to the onset of conditions that can be comorbid with problematic Internet use, such as depression, anxiety, mood disorders and ADHD. Additionally, examining the interplay between problematic Internet use and demographics is crucial for better informing interventions. Current treatment methodology and interventions focus on therapy as a basis of alleviating symptomatology, and novel methods are also being studied. In this chapter, we discuss the relationship between problematic Internet use and the intersectionality of various components of adolescent development and environment.
Background: Smartphone use patterns may predict daily life efficacy and performance improvements in sports. Additionally, personal characteristics may be associated with smartphone overuse. Methods: We investigated the correlation between the temperament and character inventory (TCI) and academic performance using smartphone log data. We hypothesized that the elite and general groups, divided based on academic performance, differed according to the TCI and downloadable smartphone apps (applications). Additionally, we hypothesized a correlation between smartphone app usage patterns and TCI. A total of 151 students provided smartphone log data of the previous four weeks. They also completed the TCI and provided academic records of the previous year. Results: The first and second most frequently used apps by both groups of students were social networking and entertainment, respectively. Elite students scored higher on novelty seeking, reward dependence, persistence, self-directedness, and self-transcendence than general students. In all participants, the usage time of serious apps was correlated with the scores for novelty seeking (r = 0.32, P < 0.007), reward dependence (r = 0.32, P < 0.007), and self-transcendence (r = 0.35, P < 0.006). In the elite group, the usage time of serious apps was correlated with the scores for novelty seeking (r = 0.45, P < 0.001), reward dependence (r = 0.39, P = 0.022), and self-transcendence (r = 0.35, P = 0.031). In the general group, the usage time of serious apps was correlated only with self-transcendence (r = 0.32, P < 0.007). Conclusion: High usage time of serious apps can help sports majors to excel academically. Particularly among sports majors, serious apps are related to activity, the desire for rewards and recognition, and the tendency to transcend themselves.
Adolescence is a transitional phase of growth and development between childhood and adulthood. Establishing social relationships is one of the basic needs of adolescences as any other human beings at any age. Especially, romantic relationships. Romantic relations are, to an extent, is good enough for adolescents. It is good for their social skills and good future relationships. Now relations are basing more on virtual platforms i.e. internet. Overuse of internet can be lead to the condition “internet addiction”. Even though social media platforms are intensively unsung teens for initiating and sustaining romantic relationships internet addiction can lead one to the toxic relationship and nally unaccepted emotional physical, sexual, economical abuses to even suicide and homicide. The aim of the study is to analysis how Internet addiction leads to toxic romantic relationship in adolescence. It is concluded that jealousy and suspicion, narcissistic traits, aggression, mood swings, sexual harassment, social isolation, dishonesty, impulsivity is common in internet addicted teenagers. This can lead to toxic romantic relationships.
Although brand attachment has positive effects on favorable consumer behavior, recent studies have advocated that brand attachment may have dark sides which stimulate some harmful behaviors. Nevertheless, research on the dark side of brand attachment is scant. This study investigates the effect of brand attachment on two negative behaviors (compulsive buying and trash talking). The survey findings show that the three components of brand attachment - passion, prominence, and anxiety - are positively related to impulsive and obsessive–compulsive buying. In turn, consumers who exhibit obsessive–compulsive buying are more likely to practice trash talking. Furthermore, consumer age moderates the relationship between brand passion, brand anxiety and compulsive buying. The research adds to the body of knowledge of consumer-brand relationship, particularly on the dark side of brand attachment. The findings contribute to the creation and deployment of altruistic customer relationship programs and regulations.
Full-text available
Objective: Attention deficit hyperactivity disorder (ADHD) is a genetically predisposed neurodevelopmental disorder. Although it has been stated that the incidence of mental disorders in the families of children with ADHD has increased, data on behavioral addictions is insufficient. This study aimed to investigate the relationship between risky internet use and behavioral addictions accessed via the internet and impulsivity in parents of children with ADHD. Method: The parents of 65 children diagnosed with ADHD in Department of Child and Adolescent Psychiatry and the parents of 64 children who did not have any mental disorders were included. Wender Utah Rating Scale, Barratt Impulsivity Scale-11 (BIS), Young's Internet Addiction Test short form, Smartphone Addiction Scale short form, Internet Gaming Disorder Scale (IGDS) were administered to the participants. Results: Parents of children with ADHD and the control group were similar in terms of sociodemographic characteristics. The mean scores of the IGDS mood modification, conflict, relapse, withdrawal subgroups and total scores of the parents with a child with ADHD were higher than the control group (p=0.02, p=0.03, p=0.03, p=0.03, p=0.02, respectively). There was a positive correlation between IGDS and BIS in parents of children with ADHD (rb=0.33; p<0.001). Conclusion: This study determined that internet gaming habits were higher in parents of children with ADHD, and these habits were associated with impulsivity. Recognition and treatment of mental disorders such as impulsivity and behavioral addictions in the families of children with ADHD will also contribute to the treatment of children.
Full-text available
This study aimed to determine how the Behavioral Inhibition System (BIS) and the Behavioral Approach System (BAS) affect Internet addiction in adolescents. Two hundred and eleven high school students participated in this study and completed the Young’s Internet Addiction Test (IAT), BIS/BAS scales, and several self-administered questionnaires about depression, anxiety, and impulsivity. Hierarchical regressions showed that BIS and BAS × BIS emerged as significant predictors of IAT; however, only BAS-fun seeking subscale predicted IAT among BAS related subscales. In further analyses, the BAS-fun seeking subscale was mediated by impulsivity and anxiety, and BIS was mediated by anxiety and depression. The current findings imply that BIS and BAS interdependently influence vulnerability to Internet addiction through both shared (anxiety) and different (depression and impulsivity, respectively) pathways.
Full-text available
Abstract. Standardizing measuring instruments availability in the local environment and other communities permits accurate diagnosis for psychological disorders, and the carrying out of survey studies and cross cultural comparisons particularly in connection with one or more of the most widespread forms of psychological disorders, namely depression. This study aims at standardizing the Beck Depression Inventory (BDI), which is considered one of the most widespread measuring instruments in the world. The sample contained 1134 examinees taken from the students of Damascus University. The researcher used the Beck Depression Inventory (BDI), which was adapted to the Arabic language by Ahmad Abdul Khalek, contained in the manual guide in the form of instructions in 1996. The statistical analysis consisted of the test of reliability of the Beck Depressions Inventory through its re-test analysis, nonstructural validity, and internal consistency analysis. The results showed that the Beck Depression Inventory (BDI) had good validity and reliability and correlated with a number of variables, such as neuroticism, introversion, helplessness and social anxiety, together with some clinical symptoms and obsession, and it correlated negatively with extroversion. Items were subjected to factor analysis, which led to the deducing of 4 factors, the Eigen value of which was more than one. All items had been loaded which meant the presence of good qualities of the list. The study did not indicate the presence of any significant differences between age groups with the exception of two male age groups. Standard degrees were calculated in the form of t-scores. In general, the results indicate the relevance of the Beck Depression Inventory (BDI) for diagnostic and research purposes in Syria.
Internet Behavior Dependence (IBD), a form of Internet addiction, is a new disorder requiring informed response from addictions clinicians such as mental health counselors. Presents a working definition for IBD, overviews the prevalence rates and demographic profiles of dependent users, and reviews assessment criteria and treatment for IBD. (Contains 34 references.) (GCP)
This article introduces a cognitive-behavioral model of Pathological Internet Use (PIU). While previous studies on Internet addiction have described behavioral factors, such as withdrawal and tolerance, the present article focuses on the maladaptive cognitions associated with PIU. The cognitive-behavioral model of PIU distinguishes between specific PIU and generalized PIU. Specific PIU refers to the condition in which an individual pathologically uses the Internet for a particular purpose, such as online sex or online gambling, whereas generalized PIU describes a more global set of behaviors. The model implies a more important role of cognitions in PIU, and describes the means by which PIU is both developed and maintained. Furthermore, it provides a framework for the development of cognitive-behavioral interventions for PIU.