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Dysfunctional inhibitory control and impulsivity in Internet addiction
Psychiatry Research 215 (2014) 424–428
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Psychiatry Research journal homepage: www.elsevier.com/locate/psychres
Dysfunctional inhibitory control and impulsivity in Internet addiction Jung-Seok Choi a,b,1, Su Mi Park a,c,1, Myoung-Sun Roh d, Jun-Young Lee a,b, Chan-Bin Park a, Jae Yeon Hwang a,b, Ah Reum Gwak a, Hee Yeon Jung a,b,c,e,n a
Department of Psychiatry, SMG-SNU Boramae Medical Center, Seoul, Republic of Korea Department of Psychiatry and Behavioral Science, Seoul National University College of Medicine, Seoul, Republic of Korea c Department of Advanced Education for Clinician-Scientists, Seoul National University College of Medicine, Seoul, Republic of Korea d Department of Medicine, Seoul National University College of Medicine, Seoul, Republic of Korea e Institute of Human Behavioral Medicine, Seoul National University College of Medicine, Seoul, Republic of Korea b
art ic l e i nf o
a b s t r a c t
Article history: Received 23 April 2013 Accepted 2 December 2013 Available online 11 December 2013
The purpose of this study was to explore a psychological profile of Internet addiction (IA) considering impulsivity as a key personality trait and as a key component of neuropsychological functioning. Twenty three subjects with IA (Young's Internet Addiction Test scores¼ 70 or more) and 24 sex-, age-, and intelligence-matched healthy controls were enrolled. Participants filled out a questionnaire about trait impulsivity, the Trait Characteristic Inventory, depression, and anxiety. Next, we administered traditional neuropsychological tests including the Stroop et al. and computerized neuropsychological tests using the Cambridge Neuropsychological Test Automated Battery. The IA group exhibited more trait impulsivity than the healthy control group. They also scored higher for novelty seeking and harm avoidance. The IA group performed more poorly than the healthy control group in a computerized stop signal test, a test for inhibitory function and impulsivity; no group differences appeared for other neuropsychological tests. The IA group also scored higher for depression and anxiety, and lower for self-directedness and cooperativeness. In conclusion, individuals with IA exhibited impulsivity as a core personality trait and in their neuropsychological functioning. & 2013 Elsevier Ireland Ltd. All rights reserved.
Keywords: Internet addiction Impulsive personality trait Impulsivity Neuropsychological test Stop signal test
1. Introduction Internet addiction (IA) is defined as the inability to control Internet use; it increases vulnerability to impairments in psychological and social functioning, including depression/anxiety, and difficulties with school, work, and interpersonal relationships (Young, 1996; Young, 1998b; Young and Rogers, 1998). IA can be considered a behavioral addiction like those involving pathological gambling, sexual activity, or spending (Holden, 2001). These disorders share clinical features such as repetitive behavior despite negative results, lack of control over urges, cravings prior to engagement in the behavior, etc. (Grant et al., 2006). IA is not only a behavioral addiction; it is also an impulse control disorder (Sadock et al., 2007). One study found that participants in their IA group were more impulsive than their control group, as measured by both self-reports and the Go–Stop impulsivity paradigm (Cao et al., 2007). A recent study suggested that trait impulsivity is a marker of vulnerability to IA as well as to
n Correspondence to: Department of Psychiatry, SMG-SNU Boramae Medical Center, 20 Boramae-ro 5-gil, Dongjak-gu, Seoul 156-707, Republic of Korea. Tel.: þ 82 2 870 2461; fax: þ82 2 831 2826. E-mail address: [email protected] (H.Y. Jung). 1 Jung-Seok Choi and Su Mi Park contributed equally to this work.
0165-1781/$ - see front matter & 2013 Elsevier Ireland Ltd. All rights reserved. http://dx.doi.org/10.1016/j.psychres.2013.12.001
pathological gambling (Lee et al., 2012). Impulsivity is a key personality trait that can predict an individual’s loss of control and addictive behaviors (Blaszczynski et al., 1997). Individuals with addictions to drugs, or gambling score highly on self-reported questionnaires regarding trait impulsivity, including the Barratt Impulsiveness Scale (BIS) (Barratt, 1965, 1975), the NEO Personality Inventory (NEOPI) (Costa and McCrae, 1985), and the Temperament and Character Inventory (TCI) (Cloninger, 1994). Our previous research demonstrated that impulsivity plays an important role in addictive behavior and that fun-seeking (Gray, 1991) predicts IA (Park et al., 2013). Impulsivity is often related to the response-inhibition or inhibition-control of executive functioning due to a frontal lobe malfunction; many patients suffering from addiction exhibit impaired executive functioning and impulse control (Crews and Boettiger, 2009). Most studies on behavioral addictions have focused on pathological gambling and have reported that pathological gamblers exhibit impaired executive functioning represented by diminished performance during inhibition, timeestimation, cognitive-flexibility, planning, and decision-making tasks (Brand et al., 2007). Researchers have also widely reported that neuropsychological functions, including those related to attention, memory, and executive control, are frequently impaired as a consequence of substance abuse (Baldacchino et al., 2012).
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With respect to IA, Stroop task results indicate that heavy Internet users exhibit impaired the executive control functioning with regard to interference-control (Wright et al., 2003); this finding was confirmed by electro-physiological brain potential and functional brain imaging (Dong et al., 2011, 2012).However, one study reported that subjects with IA were not likely to exhibit executive dysfunction on a decision-making task (Ko et al., 2010). This discrepancy suggests that a battery of neuropsychological test make help clarify IA and global executive functioning related to impulsivity. This study aimed to develop a psychological profile of individuals with IA considering impulsivity as a key personality trait and as a key component of neuropsychological functioning as assessed by traditional and computerized tests. We tested the following hypotheses: (1) individuals with IA would exhibit more impulsivity than normal controls on both self-administered questionnaires and neuropsychological tests; (1-1) individuals with IA would score higher for personality traits related to impulsivity, such as novelty seeking; and (1-2) individuals with IA would exhibit less efficient executive functioning than normal controls. We also investigated factors related to psychological well-being, such as depression, anxiety, and personality characteristics, and analyzed correlations among the variables. 2. Methods 2.1. Participants A total of 23 participants with IA (M ¼12, F¼ 11) and 24 age-, sex-, and IQmatched healthy controls (M¼ 13, F ¼11) were enrolled in this study. They were recruited using an online advertising and referral system operated by the Health Service Center of a university located in Seoul, Korea. The mean age of participants was 22.76 years (S.D. ¼ 2.91), and the mean number of years of education was 14.82 (S.D.¼ 1.67). Based on Young's criteria (Young, 1998a), participants who scored 70 or more on the Internet Addiction Test (IAT) and spent four or more hours per day using the Internet were placed into the IA group, and those who scored less than 40 on the IAT and spent less than 2 h per day using the Internet were placed in the normal control (NC) group (Hardie and Tee, 2007; Young, 1996). Additionally, the Structured Clinical Interview for DSM-IV (SCID) was used to identify past and current psychiatric illnesses. Normal controls had no history of any psychiatric disorder (First et al., 1996). All subjects were drug-naïve. 2.2. Assessment instruments 2.2.1. Self-reported questionnaires 2.2.1.1. Young's Internet Addiction Test (IAT). Items were rated on a five-point scale where 1 indicates ‘very rarely’ and 5 indicates ‘very frequently’ (Cronbach's alpha coefficient ¼0.84). Total scores were calculated according to Young's method (Young, 1998a), with possible scores for all 20 items ranging from 20 to 100. Those who scored 20–39 were classified as ‘average online users’, those who scored 40– 69 were classified as ‘experiencing frequent problems’, and those who scored 70– 100 were classified as suffering from ‘significant problems’ because of Internet use. We used a version of the IAT that has been validated for Korea (Kim et al., 2003).
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harm-avoidance (HA), which reflects behavioral inhibition and corresponds to the tendency to engage in an inhibitory response to aversive stimuli, leading to avoidance of punishment and non-reward; (3) reward dependence (RD), which reflects the maintenance of behavior and is defined as the tendency to positively respond to signals of reward to maintain or resist behavioral extinction; and (4) persistence (PE), which was originally included in the RD dimension and was later treated as a separate dimension. PE is not presently linked to a specific neurotransmitter, and we did not include it as a variable in this study. The three character dimensions in the instrument are (1) self-directedness (SDT), which refers to the ability of an individual to control, regulate, and adapt his/her behavior to fit the situation based on his/her own goals and values; (2) cooperativeness (CO), which was developed to account for individual differences in the identification with and acceptance of other people; (3) self-transcendence (ST), which is a characteristic associated with spirituality, and generally refers to identification with everything conceived as an essential and consequential part of a unified whole (Cloninger et al., 1993; Cloninger, 1994). 2.2.1.4. Beck Depression Inventory (BDI) and Beck Anxiety Inventory (BAI). The Korean version of the BDI (Beck and Steer, 1987; Lee and Song, 1991) is a 21-item selfreported questionnaire in which each item consists of four statements reflecting different levels of the severity of a particular symptom experienced during the past week. Scores for all 21 items are summed to yield a single depression score. The internal consistency of the BDI is 0.89. The Korean version of the BAI (Beck and Steer, 1993; Yook and Kim, 1997) consists of 21 symptoms rated on a four-point scale and measures the severity of certain symptoms experienced during the past week. Scores for the 21 items are summed to yield a single anxiety score. The internal consistency of the BAI is 0.88. 2.2.2. The short form of Korean-Wechsler Adult Intelligence Scale (K-WAIS SF) The K-WAIS SF (Thompson, 1987; Yeom et al., 1992; Wechsler, 1997) was used to assess verbal and nonverbal intellectual functioning. The short form includes four subtests: vocabulary, arithmetic, block design, and picture arrangement. 2.2.3. Traditional neuropsychological test battery The traditional neuropsychological test battery includes the following: the Letter–Number Sequencing subtest from K-WAIS (Yeom et al., 1992) and the Korean Color-Word Stroop Test (K-CWST) (Stroop, 1935; Kang and Na, 2003), which assess sustained and selective attention, cognitive inhibition, and working memory; the Trails Making Test (TMT) (Reitan, 1992; Seo et al., 2006), which assesses motor planning and cognitive shifting; and the Verbal Fluency (VF) test (Kim, 2001), which assesses cognitive fluency. 2.2.4. Cambridge Neuropsychological Test Automated Battery (CANTAB) The CANTAB (Robbins et al., 1994) tests were among the most important in this study. This series of computerized tasks was run on an Acorn BBC Master 128 microcomputer with a high resolution Microvitec (Bradford, U.K.) 12-in. VDU and a Microvitec Touchtec 501 touch-sensitive screen. Participants sat at a comfortable height approximately 0.5 m from the monitor. They were instructed to respond to stimuli by touching the screen or response pad. The CANTAB tests used in this study included: the Intra-Extra Dimensional Set Shift (IED) test, a test of rule acquisition and reversal used to assess visual discrimination, attentional set-formation maintenance, and the ability to shift and flexibly allocate attention; the Stockings of Cambridge (SOC) test, used to assess spatial planning; the Spatial Span (SSP) test, a visuo-spatial analog of the Digit Span test used to assess working memory capacity; and the Stop-Signal Test (SST), a classic stop-signal response-inhibition test used to assess the ability to inhibit a prepotent response (see 〈http://www.camcog.com for details〉). 2.3. Procedure
2.2.1.2. Barratt Impulsiveness Scale-11 (BIS-11). A translated version of the Korean Barratt Impulsiveness Scale-11 (BIS-11) (Barratt, 1975; Lee, 1992) was used to assess impulsivity (Cronbach's alpha coefficient ¼0.83). This instrument includes three subscales: cognitive impulsiveness (e.g., “I get easily bored when solving thought problems”), motor impulsiveness (e.g., “I do things without thinking”), and nonplanning impulsiveness (e.g., “I am more interested in the present than in the future”). 2.2.1.3. Temperament and Character Inventory (TCI). The Korean version of the TCI (Cloninger, 1994; Sung et al., 2002) contains 226 items designed to measure dimensions of personality traits using a forced binary-choice questionnaire. It includes four temperament and three character dimensions. Temperament manifests early in life and involves pre-conceptual or unconscious learning. Character refers to conceptual or insight-based learning of self-concepts, matures in adulthood, and is not linked to particular biological processes. The four temperament dimensions in the instrument are: (1) novelty-seeking (NS), which reflects behavioral activation and is defined as the tendency to respond actively to novel stimuli, leading to pursuing rewards and escaping punishment; (2)
This study was approved by the Institutional Review Board of SMG-SNU Boramae Medical Center. All participants completed consent forms after receiving information about the study; they then completed the questionnaires. The K-WAIS III SF and traditional neuropsychological tests were then administered. Finally, participants completed the CANTAB battery. The entire procedure took approximately 90 min.
3. Results 3.1. Demographic and clinical characteristics of IA and NC groups All statistical analysis in this study was conducted by SPSS 18.0 version and two-tailed tests. Table 1 presents descriptive statistics regarding the demographic and clinical characteristics of the IA and NC groups.
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ANOVAs and a Chi-square test were conducted. The two groups did not differ with respect to age, sex, years of education, or IQ scores. Unsurprisingly, the IA group scored higher on the IAT and spent more weekday and weekend time on the Internet than did the NC group. The IA group was also characterized by higher levels of depression and anxiety. 3.2. Personality profiles of IA and NC groups Fig. 1 presents the personality differences between the IA and NC groups. A MANOVA, conducted to analyze group differences in BIS-11 scores, revealed that the IA group scored higher than the NC group on the BIS-11 as a whole (IA mean¼ 75.35, S.D.¼ 10.82; NC mean¼55.65, S.D.¼7.82) and on all BIS-11 subscales, including non-planning (IA Table 1 Demographics and clinical characteristics in the IA and NC group Variable
IA (n¼ 23)
NC (n¼ 24)
Mean
Mean
S.D.
Age (years) 23.22 3.44 22.42 Education (years) 14.68 1.91 15.00 Internet start age (years) 12.91 2.98 12.46 TIME for weekday (h/d) 5.96 2.18 1.31 TIME for weekend (h/d) 8.43 2.82 1.73 IAT 77.09 5.17 17.08 BDI 15.91 6.82 4.86 BAI 14.96 8.46 5.79 K-WAIS SF IQ 122.74 10.52 122.58 % Sex Female Male
%
F
d.f. p
0.85 0.40 0.38 100.11nn 121.16nn 836.18nn 41.61nn 10.78nn 0.00
46 46 46 46 46 46 45 46 46
S.D. 2.47 1.47 2.02 0.62 0.94 8.57 4.07 1.26 9.51
χ2 0.02
47.83 52.17
0.362 0.529 0.542 0.000 0.000 0.000 0.000 0.002 0.958
p o 0.01
3.3. Comparison between the neuropsychological profiles of IA and NC groups The ANOVAs were conducted and no significant differences appeared between the IA and NC groups in traditional neuropsychological test scores (i.e., digit span, Stroop, TMT, and verbal fluency; see Table 2). With regard to the neuropsychological tests included in the CANTAB, the IA group performed less well than the NC group on the SST (Table 2). The IA group marginally made more direction errors on go trials and had a lower proportion of successful stops than the NC group, even though they marginally reacted to faster on go trials than the NC group. No differences were observed between the two groups in the other tasks, including the IED, SOC, and SSP.
0.891
45.83 54.17
IA¼ Internet Addiction, NC¼ Normal Control, BIS-11¼Barratt Impulsiveness Scale11, TIME¼ time for Internet use, IAT ¼Internet Addiction Test, BDI ¼Beck Depression Inventory, BAI¼ Beck Anxiety Inventory, and K-WAIS SF IQ¼ Intelligence Quotient from a Short Form Version of Korean-Wechsler Adult Intelligence Scale. nn
mean¼ 30.18, S.D.¼4.5; NC mean¼23.96, S.D.¼5.09), motor (IA mean¼ 25.31, S.D.¼ 4.51; NC mean¼23.96, S.D.¼ 5.09), and cognitive (IA mean¼16.59, S.D.¼3.47; NC mean¼13.73, S.D.¼ 3.91) (F(1, 45)¼ 54.82, p¼0.000, F(1, 45)¼18.81, p¼0.000, F(1, 45)¼51.76, p¼ 0.000, and F(1, 45)¼6.66, p¼0.015; multivariate variable of BIS-11 subscales in MANOVA F(3,41)¼20.67, p¼0.000). The ANOVA results revealed that the IA group also scored higher on NS (IA mean ¼57.36, S.D. ¼11.01; NC mean ¼49.80, S.D.¼ 9.7) and HA (IA mean ¼54.32, S.D.¼ 10.50; NC mean ¼45.75, S.D.¼ 12.03) than the NC group with respect to TCI-trait (F(1, 46) ¼ 5.54, p ¼0.024 and F(1, 46)¼ 6.07, p ¼0.018). Additionally, the IA group scored lower on the TCI characteristics of SDT (IA mean ¼40.32, S.D. ¼9.73; NC mean ¼55.05, S.D. ¼12.15) and CO (IA mean ¼ 45.00, S.D. ¼11.47; NC mean ¼54.40, S.D. ¼9.85) (F(1, 46)¼ 18.96, p ¼0.000 and F(1,46) ¼8.04, p ¼0.007).
3.4. Pearson's correlational analyses Scores on the IAT were positively correlated with the BIS-11 total (r ¼ 0.78, p ¼0.000) and sub-scale scores (r ¼0.60, p ¼0.000; r ¼0.78, p ¼0.000; and r ¼0.36, p¼ 0.013 for non-planning, motion, and cognitive, respectively), indicating that IA was strongly
Fig. 1. Personality of the IA and NC group. np o 0.05, nnp o 0.01; IA¼ Internet Addiction, NC¼Normal Control, BIS-11 ¼Barratt Impulsiveness Scale-11, TCI ¼Temperament and Character Inventory, NS¼ Novelty-seeking, HA¼ Harm-avoidance, RD ¼ Reward-dependence, SDT¼ Self-directedness, CO¼ Cooperativeness, & ST¼Self-transient
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Table 2 Neuropsychological performance in the IA and NC group. Variable
Digit span K-CWST Interference (s) TMT TMT A TMT B VF IED Total errors SOC ITT (s) SSP Span length Total errors SST DE on go trials POSS on stop trials RT on go trials (s)
IA (n¼ 23)
NC (n¼ 24)
Mean
Mean
S.D.
F
d.f.
p
S.D.
13.87
2.80
12.58
2.52
0.92
46
0.104
37.61
14.13
33.08
17.60
0.93
46
0.338
21.48 49.26 53.57
8.05 34.62 10.88
18.67 51.21 53.67
4.66 24.46 13.85
2.17 0.05 0.00
46 46
0.148 0.824 0.978
10.56
3.87
10.67
4.56
0.01
46
0.921
5.59
0.76
5.63
0.86
0.25
46
0.623
8.52 7.35
0.79 6.81
8.25 6.38
1.15 5.38
0.05 0.05
46 46
0.353 0.589
1.16 0.50 430.54
1.41 0.80 95.09
0.42 0.57 527.01
0.92 0.13 193.56
4.73 5.06n 4.97
46 46 46
0.050 0.038 0.051
IA¼ Internet Addiction, NC¼ Normal Control, K-CWST ¼ Korean-Color Word Stroop Test, TMT ¼ Trail Making Test, VF ¼Verbal Fluency, IED¼ Intra-Extra Dimensional Set Shift, SOC¼ Stockings of Cambridge, ITT ¼Initial Thinking Time at 5 moves, SSP ¼Spatial Span, SST¼ Stop Signal Test, DE ¼Direction Errors, POSS ¼ Proportion of Successful Stop, RT ¼Reaction time. n
po 0.05. p o 0.01.
nn
correlated with impulsiveness as a personality trait. We found significant correlations between the IAT and TCI NS (r ¼0.35, p ¼0.018) and HA (r ¼0.38, p ¼ 0.012); the IAT was also strongly correlated with the BDI (r ¼ 0.72, p ¼0.000) and BAI (r ¼0.47, p ¼0.001) assessments of psychological well-being. BIS-11 total scores were positively correlated with TCI NS (r ¼0.32, p¼ 0.018) and HA (r ¼0.35, p¼ 0.012) scores and negatively correlated with TCI SDT (r ¼ 0.67, p¼ 0.000) scores. Not surprisingly, the SST variables on the CANTAB were correlated with impulsivity as measured by the BIS-11 (e.g., r ¼ 0.38, p ¼0.010 for the correlation between proportion of successful stops in the SST and BIS-11 total).
4. Discussion The goal of this study was to investigate a psychological profile of IA by exploring relationships among IA, impulsivity, personality, and neuropsychological functioning. The IA group scored higher than the NC group for impulsivity on the BIS-11 (total and all subscales). The IA group also scored higher than the NC group on the TCI NS and TCI HA. We also found significant correlations between IA and BIS-11, TCI NC, and TCI HA scores; and BIS-11 total scores were correlated with TCI NS and TCI HA scores. Many studies have reported that novelty-seeking behavior is highly correlated with impulsivity; these data may help explain addictive behavior (Black et al., 2012). Novelty-seeking and impulsive individuals may share some a number of features, e.g., low basal dopamine activity, potentially requiring individuals to require excitement to raise their level of arousal (Cloninger et al., 1993). This type of person may engage in excessive Internet activity as a means of satisfying his or her needs. However, our findings revealed that a high degree of harm-avoidance was correlated with both trait impulsivity and severity of IA, even though novelty-seeking and harm-avoidance were negatively correlated. One interpretation of harm-avoidance behavior is
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that it serves a protective function, shielding individuals from impulsive and addictive behaviors. This interpretation is based on observed outcomes of harm-avoidance, e.g., acting to inhibit certain behaviors, as well as the link between serotonergic activity and the increased likelihood of an inhibitory response to perceived aversive stimuli and the avoidance of punishment and non-reward (Cloninger et al., 1993). This paradoxical result may be explained by the results of our previous study (Park et al., 2013): the tendency to enact avoidance behavior (which we called a ‘behavioral inhibition system’) is mediated by anxiety as a predictor of IA. A person with elevated levels of anxiety and novelty-seeking behavior is vulnerable to social anxiety and may use the Internet as a means of avoiding uncomfortable feelings such as stress, anxiety, and loneliness, while potentially still having a way to satisfy his or her needs: living in the Internet rather than facing the perceived risks in the real world (Amiel and Sargent, 2004). Another important finding in this study was that the IA group performed poorer than the NC group on the SST of the CANTAB (assessing response-inhibition and impulsivity). The IA group significantly had more difficulty inhibiting responses during ‘stop’ trials and marginally made more direction errors than the NC group during ‘go’ trials. As expected, these two variables were correlated with the total BIS-11 (p¼0.010 and p¼0.047, respectively), with the BIS-11 non-plan (p¼0.025) and cognitive (p¼0.037) for the former and the BIS-11 motor for the latter (p¼0.022), respectively. Furthermore, the IA group tended to pressed buttons more rapidly than the NC group, a result that was also correlated with impulsivity (p¼0.004). The IA and NC groups did not differ in performance during any of the other neuropsychological tests. Inconsistencies appear in research about addiction-related functioning, particularly regarding frontal lobe and executive functioning (Joranby et al., 2005). One possible explanation for our findings is that our participants had a mean IQ of more than 120 points; individuals with superior intellectual ability may use other cognitive skills to compensate for weaknesses in executive functions. An alternative explanation is that excessive Internet users may, over time, develop cognitive skills that compensate for otherwise-problematic executive functioning. For example, many Internet games require users to provide definitive and instantaneous responses involving simple to complex strategies. A recent study found no differences between their participants with IA and the normal controls in full scale IQ; working memory, visual organization, or motor speed, with the exception of social functioning (Park et al., 2011). In our study, findings indicate that the IA group did not differ in terms of overall neuropsychological functioning, but they exhibited impaired inhibitory control in the SST and on self-reported scales measuring impulsivity. Therefore, while the symptom of impulsivity operating within the realm of impaired inhibitory control is likely a core neuro-cognitive factor in some IA individuals, it is becoming increasingly clear that symptoms of IA share at least one psychological/neuropsychological variable—impulsivity—with other addiction-related conditions (Lee et al., 2012). This study was limited in its ability to explore correlations among variables because the limited sample size was insufficient to determine the predictive validity using select variables and pathway findings. In future research, it may be helpful to investigate how impulsivity mediates, and may predict, the psychological and cognitive functioning of individuals who exhibit behaviors consistent with IA. This study was also limited by including participants with very high IQ scores, making the generalizability of the results distinctly limited. In an effort to control for confounding, we used a strict criterion (IAT4 70) to identify individuals who were ‘addictive’ Internet users. Additionally, we included well-matched participants with respect to age, sex, education, and IQ, to establish an appropriate control group.
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Hardie, E., Tee, M.Y., 2007. Excessive internet use: the role of personality, loneliness and social support networks in internet addiction. Australian Journal of Emerging Technologies and Society 5, 34–47. Holden, C., 2001. Addiction: ‘behavioral’ addictions: do they exist? Science 294, 980–982. Joranby, L., Pineda, K.F., Gold, M., 2005. Addiction to food and brain reward systems. Sexual Addiction & Compulsivity 12, 2–3. Kang, Y., Na, D.L., 2003. Seoul Neuropsychological Screening Battery (SNSB), 1st ed., Human Brain Research & Consulting Co., Incheon. Kim, H.K., 2001. Kims Frontal—Executive Function Neuropsychological Test. Publishing Neuropsychology, Daegu. Kim, E.J., Lee, S.Y., Oh, S.G., 2003. The validation of korean adolescent internet addiction scale. Korean Journal of Clinical Psychology 22, 125–139. Ko, C.H., Hsiao, S., Liu, G.C., Yen, J.Y., Yang, M.J., Yen, C.F., 2010. The characteristics of decision making, potential to take risks, and personality of college students with Internet addiction. Psychiatry Research 175, 121–125. Lee, H.S., 1992. Impulsivity Test. Korean Guidance, Seoul. Lee, H.W., Choi, J.S., Shin, Y.C., Lee, J.Y., Jung, H.Y., Kwon, J.S., 2012. Impulsivity in internet addiction: a comparison with pathological gambling. Cyberpsychology, Behavior, and Social Networking 15, 373–377. Lee, Y.H., Song, J.Y., 1991. A study of the reliability and the validity of BDI, SDS, and MMPI-D scales. Korean Journal of Clinical Psychology 10, 98–113. Park, M.H., Park, E.J., Choi, J., Chai, S., Lee, J.H., Lee, C., Kim, D.J., 2011. Preliminary study of Internet addiction and cognitive function in adolescents based on IQ tests. Psychiatry Research 190, 275–281. Park, S.M., Park, Y.A., Lee, H.W., Jung, H.Y., Lee, J.Y., Choi, J.S., 2013. The effects of behavioral inhibition/approach system as predictors of Internet addiction in adolescents. Personality and Individual Differences 54, 7–11. Reitan, R.M., 1992. Trail Making Test: Manual for Administration and Scoring [Adults]. Reitan Neuropsychology Laboratory, Tucson, Ariz. Robbins, T.W., James, M., Owen, A.M., Sahakian, B.J., McInnes, L., Rabbitt, P., 1994. Cambridge Neuropsychological Test Automated Battery (CANTAB): a factor analytic study of a large sample of normal elderly volunteers. Dementia and Geriatric Cognitive Disorders 5, 266–281. Sadock, B.J., Kaplan, H.I., Sadock, V.A., 2007. Kaplan & Sadock's Synopsis of Psychiatry: Behavioral Sciences/Clinical Psychiatry. Wolter Kluwer/Lippincott Williams & Wilkins, Philadelphia. Seo, E.H., Lee, D.Y., Kim, K.W., Lee, J.H., Jhoo, J.H., Youn, J.C., Choo, I.H., Ha, J., Woo, J.I., 2006. A normative study of the Trail Making Test in Korean elders. International Journal of Geriatric Psychiatry 21, 844–852. Stroop, J.R., 1935. Studies of Interference in Serial Verbal Reactions. George Peabody College for Teachers, Nashville, Tenn. Sung, S.M., Kim, J.H., Yang, E., Abrams, K.Y., Lyoo, I.K., 2002. Reliability and validity of the Korean version of the temperament and character inventory. Comprehensive Psychiatry 43, 235–243. Thompson, A.P., 1987. Methodological issues in the clinical evaluation of two- and four-subtest short forms of the WAIS-R. Journal of Clinical Psychology 43, 142–144. Wechsler, D., 1997. WAIS-III: Wechsler Adult Intelligence Scale. Psychological Corporation, San Antonio, Tex. Wright, I., Waterman, M., Prescott, H., Murdoch-Eaton, D., 2003. A new Stroop-like measure of inhibitory function development: typical developmental trends. Journal of Child Psychology and Psychiatry 44, 561–575. Yeom, T., Park, Y., Oh, K., Kim, J., Lee, Y., 1992. K-WAIS Manual. Korean Guidance, Seoul. Yook, S.P., Kim, J.S., 1997. A clinical study on the Korean version of Beck Anxiety Inventory: comparative study of patient and non-patient. Korean Journal of Clinical Psychology 16, 185–197. Young, K.S., 1996. Psychology of computer use: XL. Addictive use of the Internet: a case that breaks the stereotype. Psychological Reports 79, 899–902. Young, K.S., 1998a. Caught in the Net: How to Recognize the Signs of Internet Addiction and a Winning Strategy for Recovery. J. Wiley, New York. Young, K.S., 1998b. Internet addiction: the emergence of a new clinical disorder. CyberPsychology and Behavior 1, 237–244. Young, K.S., Rogers, R.C., 1998. The relationship between depression and Internet addiction. CyberPsychology and Behavior 1, 25–28.
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Psychiatry Research journal homepage: www.elsevier.com/locate/psychres
Dysfunctional inhibitory control and impulsivity in Internet addiction Jung-Seok Choi a,b,1, Su Mi Park a,c,1, Myoung-Sun Roh d, Jun-Young Lee a,b, Chan-Bin Park a, Jae Yeon Hwang a,b, Ah Reum Gwak a, Hee Yeon Jung a,b,c,e,n a
Department of Psychiatry, SMG-SNU Boramae Medical Center, Seoul, Republic of Korea Department of Psychiatry and Behavioral Science, Seoul National University College of Medicine, Seoul, Republic of Korea c Department of Advanced Education for Clinician-Scientists, Seoul National University College of Medicine, Seoul, Republic of Korea d Department of Medicine, Seoul National University College of Medicine, Seoul, Republic of Korea e Institute of Human Behavioral Medicine, Seoul National University College of Medicine, Seoul, Republic of Korea b
art ic l e i nf o
a b s t r a c t
Article history: Received 23 April 2013 Accepted 2 December 2013 Available online 11 December 2013
The purpose of this study was to explore a psychological profile of Internet addiction (IA) considering impulsivity as a key personality trait and as a key component of neuropsychological functioning. Twenty three subjects with IA (Young's Internet Addiction Test scores¼ 70 or more) and 24 sex-, age-, and intelligence-matched healthy controls were enrolled. Participants filled out a questionnaire about trait impulsivity, the Trait Characteristic Inventory, depression, and anxiety. Next, we administered traditional neuropsychological tests including the Stroop et al. and computerized neuropsychological tests using the Cambridge Neuropsychological Test Automated Battery. The IA group exhibited more trait impulsivity than the healthy control group. They also scored higher for novelty seeking and harm avoidance. The IA group performed more poorly than the healthy control group in a computerized stop signal test, a test for inhibitory function and impulsivity; no group differences appeared for other neuropsychological tests. The IA group also scored higher for depression and anxiety, and lower for self-directedness and cooperativeness. In conclusion, individuals with IA exhibited impulsivity as a core personality trait and in their neuropsychological functioning. & 2013 Elsevier Ireland Ltd. All rights reserved.
Keywords: Internet addiction Impulsive personality trait Impulsivity Neuropsychological test Stop signal test
1. Introduction Internet addiction (IA) is defined as the inability to control Internet use; it increases vulnerability to impairments in psychological and social functioning, including depression/anxiety, and difficulties with school, work, and interpersonal relationships (Young, 1996; Young, 1998b; Young and Rogers, 1998). IA can be considered a behavioral addiction like those involving pathological gambling, sexual activity, or spending (Holden, 2001). These disorders share clinical features such as repetitive behavior despite negative results, lack of control over urges, cravings prior to engagement in the behavior, etc. (Grant et al., 2006). IA is not only a behavioral addiction; it is also an impulse control disorder (Sadock et al., 2007). One study found that participants in their IA group were more impulsive than their control group, as measured by both self-reports and the Go–Stop impulsivity paradigm (Cao et al., 2007). A recent study suggested that trait impulsivity is a marker of vulnerability to IA as well as to
n Correspondence to: Department of Psychiatry, SMG-SNU Boramae Medical Center, 20 Boramae-ro 5-gil, Dongjak-gu, Seoul 156-707, Republic of Korea. Tel.: þ 82 2 870 2461; fax: þ82 2 831 2826. E-mail address: [email protected] (H.Y. Jung). 1 Jung-Seok Choi and Su Mi Park contributed equally to this work.
0165-1781/$ - see front matter & 2013 Elsevier Ireland Ltd. All rights reserved. http://dx.doi.org/10.1016/j.psychres.2013.12.001
pathological gambling (Lee et al., 2012). Impulsivity is a key personality trait that can predict an individual’s loss of control and addictive behaviors (Blaszczynski et al., 1997). Individuals with addictions to drugs, or gambling score highly on self-reported questionnaires regarding trait impulsivity, including the Barratt Impulsiveness Scale (BIS) (Barratt, 1965, 1975), the NEO Personality Inventory (NEOPI) (Costa and McCrae, 1985), and the Temperament and Character Inventory (TCI) (Cloninger, 1994). Our previous research demonstrated that impulsivity plays an important role in addictive behavior and that fun-seeking (Gray, 1991) predicts IA (Park et al., 2013). Impulsivity is often related to the response-inhibition or inhibition-control of executive functioning due to a frontal lobe malfunction; many patients suffering from addiction exhibit impaired executive functioning and impulse control (Crews and Boettiger, 2009). Most studies on behavioral addictions have focused on pathological gambling and have reported that pathological gamblers exhibit impaired executive functioning represented by diminished performance during inhibition, timeestimation, cognitive-flexibility, planning, and decision-making tasks (Brand et al., 2007). Researchers have also widely reported that neuropsychological functions, including those related to attention, memory, and executive control, are frequently impaired as a consequence of substance abuse (Baldacchino et al., 2012).
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With respect to IA, Stroop task results indicate that heavy Internet users exhibit impaired the executive control functioning with regard to interference-control (Wright et al., 2003); this finding was confirmed by electro-physiological brain potential and functional brain imaging (Dong et al., 2011, 2012).However, one study reported that subjects with IA were not likely to exhibit executive dysfunction on a decision-making task (Ko et al., 2010). This discrepancy suggests that a battery of neuropsychological test make help clarify IA and global executive functioning related to impulsivity. This study aimed to develop a psychological profile of individuals with IA considering impulsivity as a key personality trait and as a key component of neuropsychological functioning as assessed by traditional and computerized tests. We tested the following hypotheses: (1) individuals with IA would exhibit more impulsivity than normal controls on both self-administered questionnaires and neuropsychological tests; (1-1) individuals with IA would score higher for personality traits related to impulsivity, such as novelty seeking; and (1-2) individuals with IA would exhibit less efficient executive functioning than normal controls. We also investigated factors related to psychological well-being, such as depression, anxiety, and personality characteristics, and analyzed correlations among the variables. 2. Methods 2.1. Participants A total of 23 participants with IA (M ¼12, F¼ 11) and 24 age-, sex-, and IQmatched healthy controls (M¼ 13, F ¼11) were enrolled in this study. They were recruited using an online advertising and referral system operated by the Health Service Center of a university located in Seoul, Korea. The mean age of participants was 22.76 years (S.D. ¼ 2.91), and the mean number of years of education was 14.82 (S.D.¼ 1.67). Based on Young's criteria (Young, 1998a), participants who scored 70 or more on the Internet Addiction Test (IAT) and spent four or more hours per day using the Internet were placed into the IA group, and those who scored less than 40 on the IAT and spent less than 2 h per day using the Internet were placed in the normal control (NC) group (Hardie and Tee, 2007; Young, 1996). Additionally, the Structured Clinical Interview for DSM-IV (SCID) was used to identify past and current psychiatric illnesses. Normal controls had no history of any psychiatric disorder (First et al., 1996). All subjects were drug-naïve. 2.2. Assessment instruments 2.2.1. Self-reported questionnaires 2.2.1.1. Young's Internet Addiction Test (IAT). Items were rated on a five-point scale where 1 indicates ‘very rarely’ and 5 indicates ‘very frequently’ (Cronbach's alpha coefficient ¼0.84). Total scores were calculated according to Young's method (Young, 1998a), with possible scores for all 20 items ranging from 20 to 100. Those who scored 20–39 were classified as ‘average online users’, those who scored 40– 69 were classified as ‘experiencing frequent problems’, and those who scored 70– 100 were classified as suffering from ‘significant problems’ because of Internet use. We used a version of the IAT that has been validated for Korea (Kim et al., 2003).
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harm-avoidance (HA), which reflects behavioral inhibition and corresponds to the tendency to engage in an inhibitory response to aversive stimuli, leading to avoidance of punishment and non-reward; (3) reward dependence (RD), which reflects the maintenance of behavior and is defined as the tendency to positively respond to signals of reward to maintain or resist behavioral extinction; and (4) persistence (PE), which was originally included in the RD dimension and was later treated as a separate dimension. PE is not presently linked to a specific neurotransmitter, and we did not include it as a variable in this study. The three character dimensions in the instrument are (1) self-directedness (SDT), which refers to the ability of an individual to control, regulate, and adapt his/her behavior to fit the situation based on his/her own goals and values; (2) cooperativeness (CO), which was developed to account for individual differences in the identification with and acceptance of other people; (3) self-transcendence (ST), which is a characteristic associated with spirituality, and generally refers to identification with everything conceived as an essential and consequential part of a unified whole (Cloninger et al., 1993; Cloninger, 1994). 2.2.1.4. Beck Depression Inventory (BDI) and Beck Anxiety Inventory (BAI). The Korean version of the BDI (Beck and Steer, 1987; Lee and Song, 1991) is a 21-item selfreported questionnaire in which each item consists of four statements reflecting different levels of the severity of a particular symptom experienced during the past week. Scores for all 21 items are summed to yield a single depression score. The internal consistency of the BDI is 0.89. The Korean version of the BAI (Beck and Steer, 1993; Yook and Kim, 1997) consists of 21 symptoms rated on a four-point scale and measures the severity of certain symptoms experienced during the past week. Scores for the 21 items are summed to yield a single anxiety score. The internal consistency of the BAI is 0.88. 2.2.2. The short form of Korean-Wechsler Adult Intelligence Scale (K-WAIS SF) The K-WAIS SF (Thompson, 1987; Yeom et al., 1992; Wechsler, 1997) was used to assess verbal and nonverbal intellectual functioning. The short form includes four subtests: vocabulary, arithmetic, block design, and picture arrangement. 2.2.3. Traditional neuropsychological test battery The traditional neuropsychological test battery includes the following: the Letter–Number Sequencing subtest from K-WAIS (Yeom et al., 1992) and the Korean Color-Word Stroop Test (K-CWST) (Stroop, 1935; Kang and Na, 2003), which assess sustained and selective attention, cognitive inhibition, and working memory; the Trails Making Test (TMT) (Reitan, 1992; Seo et al., 2006), which assesses motor planning and cognitive shifting; and the Verbal Fluency (VF) test (Kim, 2001), which assesses cognitive fluency. 2.2.4. Cambridge Neuropsychological Test Automated Battery (CANTAB) The CANTAB (Robbins et al., 1994) tests were among the most important in this study. This series of computerized tasks was run on an Acorn BBC Master 128 microcomputer with a high resolution Microvitec (Bradford, U.K.) 12-in. VDU and a Microvitec Touchtec 501 touch-sensitive screen. Participants sat at a comfortable height approximately 0.5 m from the monitor. They were instructed to respond to stimuli by touching the screen or response pad. The CANTAB tests used in this study included: the Intra-Extra Dimensional Set Shift (IED) test, a test of rule acquisition and reversal used to assess visual discrimination, attentional set-formation maintenance, and the ability to shift and flexibly allocate attention; the Stockings of Cambridge (SOC) test, used to assess spatial planning; the Spatial Span (SSP) test, a visuo-spatial analog of the Digit Span test used to assess working memory capacity; and the Stop-Signal Test (SST), a classic stop-signal response-inhibition test used to assess the ability to inhibit a prepotent response (see 〈http://www.camcog.com for details〉). 2.3. Procedure
2.2.1.2. Barratt Impulsiveness Scale-11 (BIS-11). A translated version of the Korean Barratt Impulsiveness Scale-11 (BIS-11) (Barratt, 1975; Lee, 1992) was used to assess impulsivity (Cronbach's alpha coefficient ¼0.83). This instrument includes three subscales: cognitive impulsiveness (e.g., “I get easily bored when solving thought problems”), motor impulsiveness (e.g., “I do things without thinking”), and nonplanning impulsiveness (e.g., “I am more interested in the present than in the future”). 2.2.1.3. Temperament and Character Inventory (TCI). The Korean version of the TCI (Cloninger, 1994; Sung et al., 2002) contains 226 items designed to measure dimensions of personality traits using a forced binary-choice questionnaire. It includes four temperament and three character dimensions. Temperament manifests early in life and involves pre-conceptual or unconscious learning. Character refers to conceptual or insight-based learning of self-concepts, matures in adulthood, and is not linked to particular biological processes. The four temperament dimensions in the instrument are: (1) novelty-seeking (NS), which reflects behavioral activation and is defined as the tendency to respond actively to novel stimuli, leading to pursuing rewards and escaping punishment; (2)
This study was approved by the Institutional Review Board of SMG-SNU Boramae Medical Center. All participants completed consent forms after receiving information about the study; they then completed the questionnaires. The K-WAIS III SF and traditional neuropsychological tests were then administered. Finally, participants completed the CANTAB battery. The entire procedure took approximately 90 min.
3. Results 3.1. Demographic and clinical characteristics of IA and NC groups All statistical analysis in this study was conducted by SPSS 18.0 version and two-tailed tests. Table 1 presents descriptive statistics regarding the demographic and clinical characteristics of the IA and NC groups.
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ANOVAs and a Chi-square test were conducted. The two groups did not differ with respect to age, sex, years of education, or IQ scores. Unsurprisingly, the IA group scored higher on the IAT and spent more weekday and weekend time on the Internet than did the NC group. The IA group was also characterized by higher levels of depression and anxiety. 3.2. Personality profiles of IA and NC groups Fig. 1 presents the personality differences between the IA and NC groups. A MANOVA, conducted to analyze group differences in BIS-11 scores, revealed that the IA group scored higher than the NC group on the BIS-11 as a whole (IA mean¼ 75.35, S.D.¼ 10.82; NC mean¼55.65, S.D.¼7.82) and on all BIS-11 subscales, including non-planning (IA Table 1 Demographics and clinical characteristics in the IA and NC group Variable
IA (n¼ 23)
NC (n¼ 24)
Mean
Mean
S.D.
Age (years) 23.22 3.44 22.42 Education (years) 14.68 1.91 15.00 Internet start age (years) 12.91 2.98 12.46 TIME for weekday (h/d) 5.96 2.18 1.31 TIME for weekend (h/d) 8.43 2.82 1.73 IAT 77.09 5.17 17.08 BDI 15.91 6.82 4.86 BAI 14.96 8.46 5.79 K-WAIS SF IQ 122.74 10.52 122.58 % Sex Female Male
%
F
d.f. p
0.85 0.40 0.38 100.11nn 121.16nn 836.18nn 41.61nn 10.78nn 0.00
46 46 46 46 46 46 45 46 46
S.D. 2.47 1.47 2.02 0.62 0.94 8.57 4.07 1.26 9.51
χ2 0.02
47.83 52.17
0.362 0.529 0.542 0.000 0.000 0.000 0.000 0.002 0.958
p o 0.01
3.3. Comparison between the neuropsychological profiles of IA and NC groups The ANOVAs were conducted and no significant differences appeared between the IA and NC groups in traditional neuropsychological test scores (i.e., digit span, Stroop, TMT, and verbal fluency; see Table 2). With regard to the neuropsychological tests included in the CANTAB, the IA group performed less well than the NC group on the SST (Table 2). The IA group marginally made more direction errors on go trials and had a lower proportion of successful stops than the NC group, even though they marginally reacted to faster on go trials than the NC group. No differences were observed between the two groups in the other tasks, including the IED, SOC, and SSP.
0.891
45.83 54.17
IA¼ Internet Addiction, NC¼ Normal Control, BIS-11¼Barratt Impulsiveness Scale11, TIME¼ time for Internet use, IAT ¼Internet Addiction Test, BDI ¼Beck Depression Inventory, BAI¼ Beck Anxiety Inventory, and K-WAIS SF IQ¼ Intelligence Quotient from a Short Form Version of Korean-Wechsler Adult Intelligence Scale. nn
mean¼ 30.18, S.D.¼4.5; NC mean¼23.96, S.D.¼5.09), motor (IA mean¼ 25.31, S.D.¼ 4.51; NC mean¼23.96, S.D.¼ 5.09), and cognitive (IA mean¼16.59, S.D.¼3.47; NC mean¼13.73, S.D.¼ 3.91) (F(1, 45)¼ 54.82, p¼0.000, F(1, 45)¼18.81, p¼0.000, F(1, 45)¼51.76, p¼ 0.000, and F(1, 45)¼6.66, p¼0.015; multivariate variable of BIS-11 subscales in MANOVA F(3,41)¼20.67, p¼0.000). The ANOVA results revealed that the IA group also scored higher on NS (IA mean ¼57.36, S.D. ¼11.01; NC mean ¼49.80, S.D.¼ 9.7) and HA (IA mean ¼54.32, S.D.¼ 10.50; NC mean ¼45.75, S.D.¼ 12.03) than the NC group with respect to TCI-trait (F(1, 46) ¼ 5.54, p ¼0.024 and F(1, 46)¼ 6.07, p ¼0.018). Additionally, the IA group scored lower on the TCI characteristics of SDT (IA mean ¼40.32, S.D. ¼9.73; NC mean ¼55.05, S.D. ¼12.15) and CO (IA mean ¼ 45.00, S.D. ¼11.47; NC mean ¼54.40, S.D. ¼9.85) (F(1, 46)¼ 18.96, p ¼0.000 and F(1,46) ¼8.04, p ¼0.007).
3.4. Pearson's correlational analyses Scores on the IAT were positively correlated with the BIS-11 total (r ¼ 0.78, p ¼0.000) and sub-scale scores (r ¼0.60, p ¼0.000; r ¼0.78, p ¼0.000; and r ¼0.36, p¼ 0.013 for non-planning, motion, and cognitive, respectively), indicating that IA was strongly
Fig. 1. Personality of the IA and NC group. np o 0.05, nnp o 0.01; IA¼ Internet Addiction, NC¼Normal Control, BIS-11 ¼Barratt Impulsiveness Scale-11, TCI ¼Temperament and Character Inventory, NS¼ Novelty-seeking, HA¼ Harm-avoidance, RD ¼ Reward-dependence, SDT¼ Self-directedness, CO¼ Cooperativeness, & ST¼Self-transient
J.-S. Choi et al. / Psychiatry Research 215 (2014) 424–428
Table 2 Neuropsychological performance in the IA and NC group. Variable
Digit span K-CWST Interference (s) TMT TMT A TMT B VF IED Total errors SOC ITT (s) SSP Span length Total errors SST DE on go trials POSS on stop trials RT on go trials (s)
IA (n¼ 23)
NC (n¼ 24)
Mean
Mean
S.D.
F
d.f.
p
S.D.
13.87
2.80
12.58
2.52
0.92
46
0.104
37.61
14.13
33.08
17.60
0.93
46
0.338
21.48 49.26 53.57
8.05 34.62 10.88
18.67 51.21 53.67
4.66 24.46 13.85
2.17 0.05 0.00
46 46
0.148 0.824 0.978
10.56
3.87
10.67
4.56
0.01
46
0.921
5.59
0.76
5.63
0.86
0.25
46
0.623
8.52 7.35
0.79 6.81
8.25 6.38
1.15 5.38
0.05 0.05
46 46
0.353 0.589
1.16 0.50 430.54
1.41 0.80 95.09
0.42 0.57 527.01
0.92 0.13 193.56
4.73 5.06n 4.97
46 46 46
0.050 0.038 0.051
IA¼ Internet Addiction, NC¼ Normal Control, K-CWST ¼ Korean-Color Word Stroop Test, TMT ¼ Trail Making Test, VF ¼Verbal Fluency, IED¼ Intra-Extra Dimensional Set Shift, SOC¼ Stockings of Cambridge, ITT ¼Initial Thinking Time at 5 moves, SSP ¼Spatial Span, SST¼ Stop Signal Test, DE ¼Direction Errors, POSS ¼ Proportion of Successful Stop, RT ¼Reaction time. n
po 0.05. p o 0.01.
nn
correlated with impulsiveness as a personality trait. We found significant correlations between the IAT and TCI NS (r ¼0.35, p ¼0.018) and HA (r ¼0.38, p ¼ 0.012); the IAT was also strongly correlated with the BDI (r ¼ 0.72, p ¼0.000) and BAI (r ¼0.47, p ¼0.001) assessments of psychological well-being. BIS-11 total scores were positively correlated with TCI NS (r ¼0.32, p¼ 0.018) and HA (r ¼0.35, p¼ 0.012) scores and negatively correlated with TCI SDT (r ¼ 0.67, p¼ 0.000) scores. Not surprisingly, the SST variables on the CANTAB were correlated with impulsivity as measured by the BIS-11 (e.g., r ¼ 0.38, p ¼0.010 for the correlation between proportion of successful stops in the SST and BIS-11 total).
4. Discussion The goal of this study was to investigate a psychological profile of IA by exploring relationships among IA, impulsivity, personality, and neuropsychological functioning. The IA group scored higher than the NC group for impulsivity on the BIS-11 (total and all subscales). The IA group also scored higher than the NC group on the TCI NS and TCI HA. We also found significant correlations between IA and BIS-11, TCI NC, and TCI HA scores; and BIS-11 total scores were correlated with TCI NS and TCI HA scores. Many studies have reported that novelty-seeking behavior is highly correlated with impulsivity; these data may help explain addictive behavior (Black et al., 2012). Novelty-seeking and impulsive individuals may share some a number of features, e.g., low basal dopamine activity, potentially requiring individuals to require excitement to raise their level of arousal (Cloninger et al., 1993). This type of person may engage in excessive Internet activity as a means of satisfying his or her needs. However, our findings revealed that a high degree of harm-avoidance was correlated with both trait impulsivity and severity of IA, even though novelty-seeking and harm-avoidance were negatively correlated. One interpretation of harm-avoidance behavior is
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that it serves a protective function, shielding individuals from impulsive and addictive behaviors. This interpretation is based on observed outcomes of harm-avoidance, e.g., acting to inhibit certain behaviors, as well as the link between serotonergic activity and the increased likelihood of an inhibitory response to perceived aversive stimuli and the avoidance of punishment and non-reward (Cloninger et al., 1993). This paradoxical result may be explained by the results of our previous study (Park et al., 2013): the tendency to enact avoidance behavior (which we called a ‘behavioral inhibition system’) is mediated by anxiety as a predictor of IA. A person with elevated levels of anxiety and novelty-seeking behavior is vulnerable to social anxiety and may use the Internet as a means of avoiding uncomfortable feelings such as stress, anxiety, and loneliness, while potentially still having a way to satisfy his or her needs: living in the Internet rather than facing the perceived risks in the real world (Amiel and Sargent, 2004). Another important finding in this study was that the IA group performed poorer than the NC group on the SST of the CANTAB (assessing response-inhibition and impulsivity). The IA group significantly had more difficulty inhibiting responses during ‘stop’ trials and marginally made more direction errors than the NC group during ‘go’ trials. As expected, these two variables were correlated with the total BIS-11 (p¼0.010 and p¼0.047, respectively), with the BIS-11 non-plan (p¼0.025) and cognitive (p¼0.037) for the former and the BIS-11 motor for the latter (p¼0.022), respectively. Furthermore, the IA group tended to pressed buttons more rapidly than the NC group, a result that was also correlated with impulsivity (p¼0.004). The IA and NC groups did not differ in performance during any of the other neuropsychological tests. Inconsistencies appear in research about addiction-related functioning, particularly regarding frontal lobe and executive functioning (Joranby et al., 2005). One possible explanation for our findings is that our participants had a mean IQ of more than 120 points; individuals with superior intellectual ability may use other cognitive skills to compensate for weaknesses in executive functions. An alternative explanation is that excessive Internet users may, over time, develop cognitive skills that compensate for otherwise-problematic executive functioning. For example, many Internet games require users to provide definitive and instantaneous responses involving simple to complex strategies. A recent study found no differences between their participants with IA and the normal controls in full scale IQ; working memory, visual organization, or motor speed, with the exception of social functioning (Park et al., 2011). In our study, findings indicate that the IA group did not differ in terms of overall neuropsychological functioning, but they exhibited impaired inhibitory control in the SST and on self-reported scales measuring impulsivity. Therefore, while the symptom of impulsivity operating within the realm of impaired inhibitory control is likely a core neuro-cognitive factor in some IA individuals, it is becoming increasingly clear that symptoms of IA share at least one psychological/neuropsychological variable—impulsivity—with other addiction-related conditions (Lee et al., 2012). This study was limited in its ability to explore correlations among variables because the limited sample size was insufficient to determine the predictive validity using select variables and pathway findings. In future research, it may be helpful to investigate how impulsivity mediates, and may predict, the psychological and cognitive functioning of individuals who exhibit behaviors consistent with IA. This study was also limited by including participants with very high IQ scores, making the generalizability of the results distinctly limited. In an effort to control for confounding, we used a strict criterion (IAT4 70) to identify individuals who were ‘addictive’ Internet users. Additionally, we included well-matched participants with respect to age, sex, education, and IQ, to establish an appropriate control group.
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