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Impaired inhibition and working memory in response to internetrelated words among adolescents with internet addiction: A comparison with attention-deficit/hyperactivity disorder Jia Nie a,b, Wei Zhang a,b,n, Jia Chen a,b,1, Wendi Li a,b a b
School of Psychology, Central China Normal University, Hubei, China Key Laboratory of Adolescent Cyberpsychology and Behavior (CCNU), Ministry of Education, Wuhan, China
art ic l e i nf o
a b s t r a c t
Article history: Received 12 August 2015 Received in revised form 12 November 2015 Accepted 4 January 2016
Impairments in response inhibition and working memory functions have been found to be closely associated with internet addiction (IA) symptoms and attention-deficit/hyperactivity disorder (ADHD) symptoms. In this study, we examined response inhibition and working memory processes with two different materials (internet-related and internet-unrelated stimuli) among adolescents with IA, ADHD and co-morbid IA/ADHD. Twenty-four individuals with IA, 28 individuals with ADHD, 17 individuals with IA/ADHD, and 26 matched normal controls (NC) individuals were recruited. All participants were measured with a Stop-Signal Task and 2-Back Task under the same experimental conditions. In comparison to the NC group, subjects with IA, ADHD and IA/ADHD demonstrated impaired inhibition and working memory. In addition, in comparison to internet-unrelated conditions, IA and co-morbid subjects performed worse on the internet-related condition in the Stop trials during the stop-signal task, and they showed better working memory on the internet-related condition in the 2-Back Task. The findings of our study suggest individuals with IA and IA/ADHD may be impaired in inhibition and working memory functions that might be linked to poor inhibition specifically related to internet-related stimuli, which will advance our understanding of IA and contribute to prevention and intervention strategies. & 2016 Published by Elsevier Ireland Ltd.
Keywords: Internet addiction Attention-deficit/hyperactivity disorder Response inhibition Working memory
1. Introduction With the increased use of the internet in the 21st century, problems related to internet use have emerged. Internet addiction (IA) can be broadly conceptualized as an inability to control one's use of the internet, which comprises the problematic use of internet/video gaming, mobile hand-held devices and other forms of addictive internet usage (Yung et al., 2015). The negative consequences of IA include emotional, social and mental dysfunction in a wide range of areas of daily activities (Davis, 2001; Spada, 2014; Young, 1998). In China, many people are readily exposed to the internet from a very young age, and IA has already become a serious mental health and behavior problem among adolescents, gradually attracting the attention of numerous researchers and the public (Cao and Su, 2007; Tang et al., 2014). IA is not only considered one type of behavioral addiction n Corresponding author at: School of Psychology, Central China Normal University, 152 Luoyu Street, Wuhan 430079, Hubei, China. E-mail address: [email protected] (W. Zhang). 1 Permanent address: Usability and Design Lab, Beijing, China.
(Holden, 2001), it is also considered by some to be an impulse control disorder or at least to have the characteristics of impulse control disorders (Beard and Wolf, 2001; Shaw and Black, 2008). Although a clinical diagnosis of IA not currently found in the DSMV, it is thought to be similar to internet gaming disorder (IGD), which belongs to the class of disorders that includes substance use and addictive disorders in DSM-V (Gunuc, 2015). While the diagnosis remains controversial, diminished control has been regarded as a core defining concept of substance dependence or addiction, and accordingly, IA should present the “loss of control” characteristics similar to these types of disorders. Indeed, one study showed that individuals with IA indeed could not successfully control their internet activities in their daily life, or they had withdrawal symptoms (e.g., irritability, anxiety or sadness) when they were asked to stop playing with the computer or stop their internet usage (Tzang et al., 2015). These symptoms are also the diagnostic criteria commonly found on many questionnaires used to assess IA (Lortie and Guitton, 2013). Successfully inhibiting prepotent responses (response inhibition) is a major contributor to an individual's ability to avoid inappropriate behaviors. Although neuropsychological investigations
http://dx.doi.org/10.1016/j.psychres.2016.01.004 0165-1781/& 2016 Published by Elsevier Ireland Ltd.
Please cite this article as: Nie, J., et al., Impaired inhibition and working memory in response to internet-related words among adolescents with internet addiction: A.... Psychiatry Research (2016), http://dx.doi.org/10.1016/j.psychres.2016.01.004i
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have reported that impaired response inhibition (inhibitory control) are seen in IA (Cao et al., 2007; Choi et al., 2013, 2014; Dong et al., 2012, 2010; Zhou et al., 2013, 2010), it is unclear why some individuals cannot control their internet use. An emerging view is that internet addicted individuals have difficulty in suppressing responses only to explicitly addiction-related or internet-related stimuli (Brand et al., 2014; Sun et al., 2009). Previous findings about IGD have also suggested that IGD subjects show impaired inhibition function in response to internet gaming-related cues on the Go/NoGo task or other similar cognitive tasks (Liu et al., 2014; Yao et al., 2015; Zhou et al., 2012). Consequently, the experimental materials (e.g. digits or letters) that are commonly used in the laboratory may not reflect the specific types of impairments of internet addicted individuals in inhibiting their prepotent responses when they are using the internet. It is necessary to use an internet-related inhibition task for assessing response inhibition of IA. Working memory is an executive function that allows the maintenance of the information required to execute high-order plans, which is important for adolescents' reasoning, learning and language comprehension. Many studies have shown that individuals with IA present impairments in working memory similar to behavioral and substance addictions, such as alcohol dependence (Zhou et al., 2014) and pathological gambling (Zhou et al., 2015). A review summarizing some recent neuropsychological researches suggested that internet-related cues interfere with control processes mediated by the prefrontal brain areas, and internet-related stimuli interfere with some prefrontal functions such as working memory and other executive functions (Brand et al., 2014). For instance, concentrating on the excessive use of internet pornography, which is a form of IA, one study reported that healthy individuals showed lower working memory performance for pornographic stimuli than for positive, negative, and neutral pictures (Laier et al., 2013). It has further been suggested that working memory performance may be differentially affected when individuals with IA are confronted with internet-related cues. IA and its psychiatric comorbid conditions have received increasing research attention in recent years, with a particular focus on attention-deficit/hyperactivity disorder (Bozkurt et al., 2013; Chou et al., 2015; Dalbudak et al., 2015; Ko et al., 2012; Weinstein, 2010). ADHD-related symptoms (e.g. inattention and hyperactivity/impulsivity) are highly relevant to IA (Chen et al., 2015), and a recent meta-analysis of the literature reported that IA was significantly associated with ADHD (Ho et al., 2014). One possible explanation for the coexistence of IA and ADHD is that adolescents with ADHD have abnormal brain activities associated with impaired inhibition (Rubia et al., 2005), which may cause people with ADHD to have difficulty in controlling internet use and to become vulnerable to internet addiction (Yen et al., 2014). Based on observed experimental data and clinical manifestations among patients with ADHD, previous researches have already shown that adolescents with ADHD demonstrate neuropsychological deficits across a wide range of impairments in executive functions including response inhibition and working memory (Barkley, 1997; Epstein et al., 2011; McAuley et al., 2014; van Rooij et al., 2015). ADHD may also be shown to be associated with impaired response inhibition and working memory in response to internet-related stimuli. Although executive dysfunctions in response inhibition and working memory are heavily studied with ADHD, few studies have examined the relationships of ADHD with response inhibition and working memory in adolescents using internet-related cognitive tasks. The aims of the present study were to investigate response inhibition and working memory processes using two neuropsychological tasks (Stop-Signal Task and 2-Back Task) with two different materials (internet-related and internet-unrelated
stimuli) among adolescents with IA, ADHD and co-morbid IA/ ADHD. Neuropsychological tasks have contributed significantly to our understanding of the effect of IA and ADHD on cognitive functions, and may be useful for identifying potential neurobiological mechanisms and adequate treatments in these diagnostic groups. Based on the results of previous studies, we hypothesized that, relative to normal controls, participants with IA would show a lower ability to suppress internet-related response (Liu et al., 2014; Yao et al., 2015; Zhou et al., 2012), and show weakened working memory for internet-related materials relative to internet-unrelated materials (Laier et al., 2013; Zhou et al., 2015; Zhou et al., 2014). In addition, it was hypothesized that ADHD and comorbid ADHD/IA would also unsuccessfully suppress internet-related responses, and show weakened working memory for internet-related materials relative to internet-unrelated materials.
2. Method 2.1. Participants Twelve classes were selected from three grades (i.e., senior one, senior two and senior three) in a vocational high school in Guangzhou City (the capital of Guangdong Province in southern China, a city with a population of over 100 million). This study was approved by the high school and the participants’ parents. A total of 828 students (all right-handed) participated. To assess internet addiction, students were screened with the Chen Internet Addiction Scale (CIAS), which is a widely used criterion for internet addiction in Mainland China and Taiwan. The internal reliability of the scale and its sub-scales in the original study ranged from 0.79 to 0.93 (Chen et al., 2003). The CIAS contains 26 items on a four-point Likert scale, with total scores ranging from 26 to 104. A higher total score indicates increased severity of addiction to internet-related activity. Accordingly, those with total scores of 57 or less in the current study were classified as the normal control (NC) group, and those with CIAS scores of 64 or more were classified as the internet addiction group (Ko et al., 2005). The participants whose total score was between 57 and 64 were excluded. Participants with ADHD were diagnosed according to The Diagnostic and Statistical Manual of Mental Disorders, 4th edition (DSM-IV). The DSM-IV criteria for ADHD contain 18 symptoms, with ADHD diagnosed based on evaluations of two separate but correlated symptom dimensions: inattention and hyperactivity/ impulsivity (American Psychiatric Association, 2000). One meets the criteria for ADHD by having six or more inattention or hyperactivity/impulsivity symptoms. The criteria were translated into Chinese by the researchers, and a self-report questionnaire was developed based on these criteria. In accordance with the DSM-IV, participants fulfilled the criteria for ADHD when their scores wereZ6. These participants were classified as individuals with ADHD, and the remainder (scores o6) were classified as normal controls. According to the diagnostic criteria of the CIAS and the DSM-IV, 24 students who were diagnosed with internet addiction were included in the IA-only group, 28 students who were diagnosed with ADHD were included in the ADHD-only group and 17 students who met the inclusion criteria for both IA and ADHD were included in the co-morbid group. The NC group was composed of 26 students without IA or ADHD. Of the participants, 63 (66.32%) were boys and 32 (33.68%) were girls. The mean age of the participants was 16.34 years (SD ¼0.81), ranging from 15 to 18. The four groups were matched on gender, age and educational levels (see Table 1). In addition, two child psychiatrists and two
Please cite this article as: Nie, J., et al., Impaired inhibition and working memory in response to internet-related words among adolescents with internet addiction: A.... Psychiatry Research (2016), http://dx.doi.org/10.1016/j.psychres.2016.01.004i
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Table 1 Demographic characteristics, ADHD symptoms and CIAS scores.
Sex ratio (M/F) Mean age (SD) Mean education (SD) ADHD symptoms on the DSM-IV Inattention (SD) Hyperactivity/Impulsivity (SD) CIAS(SD)
IA
ADHD
Co-morbid
NC
Test statistic
24 (16/8) 16.29 (0.91) 10.00 (0.72)
28 (18/10) 16.29 (0.71) 10.11 (0.69)
17 (12/5) 16.41 (0.94) 10.29 (0.92)
26 (17/9) 16.38 (0.75) 10.19 (0.75)
χ2 ¼0.202 F¼ 0.19 F¼ 0.57
3.08 (1.69) 1.92 (1.86) 69.75 (8.24)
5.93 (1.18) 3.82 (2.23) 52.32 (8.94)
6.65 (1.57) 4.59 (2.62) 73.76 (11.43)
1.35 (1.16) 0.73 (1.04) 40.38 (8.68)
F¼ 72.795nnn F¼ 18.22nnn F¼ 66.087nnn
IA¼ Internet Addiction; ADHD ¼ Attention-deficit/hyperactivity disorder; Co-morbid ¼ both ADHD and IA; NC¼ Normal Control; M ¼ male; F ¼female; SD ¼ standard deviation; DSM-IV ¼the Diagnostic and Statistical Manual of Mental Disorders, 4th edition; CIAS¼ Chen Internet Addiction Scale. nnn
p o 0.001.
2.2. Measures
variable stop-signal delay (SSD): 100, 250 or 400 ms after the onset of the target word. Go trials occurred 60% of the time, and the remaining 40% were Stop trials. Participants first completed a practice block of 10 trials. The practice block provided feedback, whereas the experimental block did not. The mean Go trial reaction times (GORT), the error rate on Go trials and the proportion of successful stops on Stop trials were used as dependent variables in this task. Participants received standardized task instructions before the computerized task, and they completed a total of 128 trials.
2.2.1. Materials Chinese words were selected as experimental materials to be presented to participants visually in the Stop-Signal Task and the 2-Back Task. These words were divided into two sets: the noun set (36 words) and the verb set (30 words). Given that the majority of Chinese words are disyllabic, all selected words were disyllabic. Each word fit into one of two subtypes: internet-related (e.g., Micro-blog) or internet-unrelated (e.g., Lightning). The Internetrelated words included several categories such as online shopping, web browsing, social networking, internet/video gaming, downloading and normal internet usage (e.g., Login). Each internetunrelated word matched a corresponding Internet-related word on the Chinese character pattern and structure. All selected words were matched by 15 psychological professionals in accordance with the Modern Chinese Dictionary. To evaluate word categorization, an additional 15 raters answered the question, “How much do you agree that each of the following Chinese words is associated with Internet usage/activity?” The raters responded on a 5-point scale, ranging from strongly disagree (1) to strongly agree (5), and there was a high degree of consistency between raters (Kendall W¼ 0.954). An independent-samples t-test compared ratings between internet-related and internet-unrelated words. As expected, internet-related words were rated as significantly more internet-related than internet-unrelated words (t¼105.948, p o0.001).
2.2.3. Working memory measure: 2-Back Task The working memory measure in this study employed a 2-Back design. Participants were asked to monitor the identity of a series of Chinese words (the same as those used in the SST) presented in a random sequence. Participants were instructed to press the “F” button if the currently presented word was identical to the one that was presented two trials before and to press the “J” button if the current word was different from the word presented two trials before. Following 10 practice trials, participants were presented with two blocks (internet-related block and internet-unrelated block) of 60 trials each, for a total of 120 trials. The practice block provided feedback, whereas the two experimental blocks did not. For each block, the first two words were not analyzed due to an insufficient number of previous words to validly complete the task. Target stimuli (same stimulus as two trials before) were presented randomly throughout the remaining trials. The mean reaction times (RT) and the accuracy on experiment blocks were taken as dependent variables in this task. Each trial began with the presentation of a red fixation point for 500 ms, followed by the randomly generated words for that trial. Each word was displayed for 750 ms, with an interstimulus interval of 4000 ms. In order to prevent the order of experimental conditions from affecting responses, half of the participants completed an internet-related task, and the other half completed an internetunrelated task initially.
2.2.2. Response inhibition measure: Stop-Signal Task (SST) The SST is a classic approach to measuring response inhibition (Verbruggen and Logan, 2008). For the SST in the current study, participants were shown a series of Chinese words on a computer screen. Each trial began with the presentation of a red fixation point for 300 ms, followed by a blank screen for 300 ms. One of the 66 experimental words was then randomly presented for 2 s. Trials were either Go trials or Stop trials. In the Go trials, participants were instructed to press the “F” button on a standard keyboard when they saw a noun and the “J” button when they saw a verb. In the Stop trials, participants were told to continue with the same procedure as the Go trials; however, if they heard an auditory signal (a beep), they should withhold their response and not press the button. The stop signal (the beep) was presented after a
2.3. Procedure
psychological professionals conducted interviews with the participants in the three disorder groups and their parents. The interviews were conducted to confirm that none of the participants had been clinically diagnosed with neurological diseases (e.g., head injury), intellectual disabilities psychosis, or history of drug abuse. Interviews also confirmed that adolescents who were diagnosed with ADHD for the purposes of the current study had never received medication for it.
Participants were tested individually. They completed two selfreport questionnaires in class after the researchers explained the procedure and requirements. Questionnaires were collected immediately after completion. After finishing the CIAS questionnaire, the DSM-IV questionnaire about ADHD and a demographic questionnaire made by the researchers, they performed the SST followed by the 2-Back Task. The experiment was programmed with E-Prime (Version 2.0) software. Participants who completed both tasks were positioned approximately 100 cm away from a computer screen (DELL 14-inch, LCD monitor) with horizontal and vertical visual angles of less than 5°. There was a twenty-minute break between these two tasks to avoid fatigue. It took no more
Please cite this article as: Nie, J., et al., Impaired inhibition and working memory in response to internet-related words among adolescents with internet addiction: A.... Psychiatry Research (2016), http://dx.doi.org/10.1016/j.psychres.2016.01.004i
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than one hour to complete the entire testing session. All participants received a small monetary reward after the experiment. 2.4. Statistical analysis Statistical analyses were performed using SPSS 17.0 statistical software package (SPSS Inc., Chicago, IL, USA). First, possible group differences in demographic variables were analyzed using a chisquare analysis and a one-way ANOVA. Second, separate repeatedmeasures ANOVAs were used to explore between-group differences in performance on the SST and the 2-Back Task. Finally, Pearson's correlations were used to investigate the relationships between ADHD symptoms and CIAS scores with the scores from the two neuropsychological tests (the SST and 2-Back Task). Statistical significances were defined at the 0.05 level, two-tailed.
3. Results 3.1. Demographic characteristic The participants' demographic characteristics, ADHD symptoms and CIAS scores are shown in Table 1. In addition, internet addiction symptoms on the CIAS were significantly correlated with inattention symptoms (r ¼ 0.371, po 0.001) and hyperactivity/impulsivity symptoms (r ¼0.319, p o0.001) on the DSM-IV. 3.2. Performance of the four groups on the SST Data were excluded for 15 participants because they performed the SST in an invalid manner (i.e., Go trials had less than 50% accuracy or a mean GORT of less than 200 ms, indicating that they may have been guessing on the Go trials due to their impulsivity). The remaining data (IA, 19; ADHD, 23; co-morbid group, 14; NC, 24; gender, χ2 ¼0.99, p ¼0.804; age, F¼0.343, p ¼0.794) consisted of the mean GORT, the error rate on Go trials and the proportion of successful stops on Stop trials. A repeated-measures ANOVA was used to analyze these three variables, with group (IA, ADHD, comorbid IA/ADHD and NC) as the between-subjects factor and word-type (internet-related and internet-unrelated) as the withinsubjects factor. Go trial performance on the SST among IA, ADHD, co-morbid IA/ADHD and NC groups are shown in Table 2. For mean GORT, results showed a significant main effect of word-type (F(1, 76) ¼11.12, p o0.01) and a marginally significant interaction between word-type and group (F(3, 76) ¼2.51, p¼ 0.065); however, the main effect of group was not significant (F(3, 76) ¼ 1.35, p 40.05). The mean GORT of the IA group for the internet-unrelated words was significantly higher than for the internet-related words (F(1, 76) ¼ 7.17, p o0.01), and the mean GORT of the comorbid group for the internet-unrelated words was significantly higher than for the internet-related words (F(1, 76) ¼ 6.41, po 0.05). The results of error rate on Go trials showed that the main effect of
word-type was significant (F(1, 76) ¼ 8.68, p o0.01); however, the main effect of group and the interaction between word-type and group were not significant (F(3, 76) ¼0.53, p 40.05; F(3, 76) ¼1.87, p4 0.05). Previous research has reported that an approximately 250 ms stop-signal delay (SSD) was sensitive enough to distinguish between ADHD and normal-control groups (Pliszka et al., 2000; Rubia et al., 1998; Wang et al., 2005). In the present study, 250 ms (SSD) was analyzed as a variable indicator to describe the proportion of successful stops on Stop trials. For proportion of successful stops (250 ms), results showed significant main effects of word-type (F(1, 76) ¼ 9.37, p o0.01) and group (F(3, 76) ¼ 3.78, po 0.05), and the interaction between word-type and group was also significant (F(3, 76) ¼ 4.24, po 0.01). Fig. 1 shows a simple effect analysis of the proportion of successful stops on the SST. For the IA group, the proportion of successful stops for the internet-unrelated words was significantly higher than for the internet-related words (F(1, 76) ¼11.75, p o0.01), and for the co-morbid group the proportion of successful stops for the internet-unrelated words was also significantly higher than for the internet-related words (F(1, 76) ¼6.36, p o0.05). 3.3. Performance of the four groups on the 2-Back Task Data were excluded for 29 participants because they performed the 2-Back Task in an invalid manner (i.e., experiment blocks with less than 50% accuracy or mean RT less than 150 ms, indicating that they responded too early because of their impulsivity). The remaining data (IA, 19; ADHD, 19; co-morbid group, 10; NC, 18; gender, χ2 ¼ 0.897, p ¼0.826; age, F¼0.305, p ¼0.822) consisted of the mean RT and the accuracy on the 2-Back Task. A repeatedmeasures ANOVA was used to analyze these two variables, with group (IA, ADHD, co-morbid and NC) as the between-subjects factor and word-type (internet-related and internet-unrelated) as the within-subjects factor. The 2-Back Task performance for the IA, ADHD, co-morbid and NC groups are shown in Fig. 2. For mean RT, results showed significant main effects of word-type (F(1, 62) ¼4.01, p ¼0.05) and group (F(3, 62) ¼2.96, p o0.05). The interaction between word-type and group was marginally significant (F(3, 62) ¼2.20, p ¼0.09). The mean RT of the IA and co-morbid groups for the internet-unrelated words was significantly higher than for the internet-related words (IA, F(1, 62) ¼ 4.21, po 0.05; co-morbid, F(1, 62) ¼4.43, p o0.05). For task accuracy, results showed a significant main effect of wordtype (F(1, 62) ¼4.39, p o0.05) and a marginally significant main effect of group (F(3, 62) ¼2.74, p ¼0.051); however, the interaction between word-type and group was not significant (F(3, 62) ¼1.66, p4 0.05). 3.4. Relationships between ADHD symptoms and internet addiction symptoms with two neuropsychological tests Correlational analyses were used to examine ADHD scores
Table 2 Go trials performance on SST among IA, ADHD, Co-morbid IA/ADHD and NC groups. Internet-related words
IA ADHD Co-morbid NC
Internet-unrelated words
Mean GORT (ms)
Error rate (%)
Mean GORT (ms)
Error rate (%)
725.92(81.97) 751.14(115.99) 734.08(67.15) 718.20(158.21)
26.89(10.67) 30.00(9.88) 26.84(12.89) 27.62(12.65)
804.75(144.88) 793.17(158.97) 820.91(162.58) 706.20(170.80)
31.70(9.50) 32.77(6.53) 29.81(12.18) 28.00(13.21)
IA¼ Internet Addiction; ADHD ¼Attention-deficit/hyperactivity disorder; Co-morbid ¼both ADHD and IA; NC¼Normal Control; SST¼ Stop-Signal Task; Mean GORT ¼Mean reaction time on Go trials.
Please cite this article as: Nie, J., et al., Impaired inhibition and working memory in response to internet-related words among adolescents with internet addiction: A.... Psychiatry Research (2016), http://dx.doi.org/10.1016/j.psychres.2016.01.004i
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CIAS scores and the 2-Back Task.
4. Discussion
Fig. 1. A simple effect analysis of the proportion of successful stops on stop-signal task; *, p o0.05; **, p o0.01; IA ¼Internet Addiction; ADHD ¼ Attention-deficit/hyperactivity disorder; Co-morbid ¼both ADHD and IA; NC¼ Normal Control.
The current study aimed to assess response inhibition and working memory processes among adolescents with IA, ADHD and co-morbid IA and ADHD, using two neuropsychological tasks (SST and 2-Back Task) with two different materials (internet-related and internet-unrelated stimuli). Partly consistent with our hypothesis, we found that, in comparison to the NC group, subjects with IA, ADHD and IA/ADHD performed worse on the SST and 2-Back Task. However, the IA and co-morbid subjects showed an unexpected pattern in which they had lower inhibition in response to internet-related words (compared to internet-unrelated words) in the Stop trials (SST), but showed better working memory performance for the internet-related words in the 2-Back Task. By contrast, the ADHD group no significant differences between internet-related and internet-unrelated words were observed. Clarifying whether impaired inhibition and working memory functions among individuals with IA and co-morbid ADHD are related to internet usage will advance understanding of IA and contribute to prevention and intervention in the mechanisms of co-morbid IA/ADHD. Findings of our study and their clinical implication are discussed below. 4.1. Impairments in response inhibition and working memory in IA
Fig. 2. (a), Mean RT (Reaction Time) for internet-related and internet-unrelated words; (b), accuracy for internet-related and internet-unrelated words; *, p o0.05; IA¼ Internet Addiction; ADHD ¼ Attention-deficit/hyperactivity disorder; Co-morbid ¼both ADHD and IA; NC¼Normal Control.
(with two dimensions: inattention and hyperactivity/impulsivity) and CIAS scores in relation to scores on the two neuropsychological tests (SST and 2-Back Task). The results indicated that, in the SST, the proportion of successful stops on the internet-related condition was significantly negatively correlated with three variables: ADHD inattention symptoms (r(80) ¼ 0.352, p ¼0.001), ADHD hyperactivity/impulsivity symptoms (r(80) ¼ 0.296, p ¼0.008) and CIAS scores (r(80) ¼ 0.343, p ¼0.002). The proportion of successful stops on the internet-unrelated condition was significantly negatively correlated only with ADHD inattention symptoms (r(80) ¼ 0.306, p ¼0.006) and ADHD hyperactivity/impulsivity symptoms (r(80) ¼ 0.223, p ¼0.047). There were no other significant correlations between ADHD and CIAS scores and variables of the SST. In the 2-Back Task, mean RT in the internetrelated condition was significantly positively correlated with ADHD inattention symptoms (r(66) ¼0.402, p ¼0.001) and ADHD hyperactivity/impulsivity symptoms (r(66) ¼ 0.389, p ¼0.001); mean RT in the internet-unrelated condition was significantly positively correlated with CIAS scores (r(66) ¼0.262, p ¼ 0.034). No other significant correlations were observed between ADHD and
Our results showed that IA subjects performed better for the internet-related words (relative to internet-unrelated words) in the Go trials (SST), and they more frequently failed to inhibit their response to internet-related words (relative to internet-unrelated words) in the Stop trial (SST). One possible explanation for the Go trials performance is that internet-related stimuli may be a more distinctive target for individuals with IA, who are frequent internet users. Distinctiveness draws attention and guides searches more efficiently (Treisman and Gelade, 1980). In Go trial processes, subjects were asked to judge only whether a randomly generated word on the screen was a verb or a noun or to respond quickly to internet-related words, the latter of which may be a prepotent response for IA subjects. Although IA may have shown a prepotent response to the Go trials, it would be difficult to suppress the prepotent response in the Stop trial. This finding is consistent with previous studies, which found that individuals with IGD showed lower inhibition in their prepotent response to gaming-related stimuli (Liu et al., 2014; Yao et al., 2015; Zhou et al., 2012). It is also consistent with hypotheses positing that cognitive control processes in particular may be disrupted by the presence of addiction-related stimuli (Brand et al., 2014; Sun et al., 2009; Volkow and Baler, 2014). The prepotent responses to internet-related stimuli can be thought of as ‘hot’ tasks that are theorized to engage ‘hot’ executive functions (e.g., self-control) that are activated in the presence of stronger affective salience; these override ‘cold’ executive functions (e.g., response inhibition) mediated by brain areas such as the dorsolateral prefrontal cortex which may reflect addiction-related reduced inhibitory control, resulting in alterations in inhibitory control processes (Brand et al., 2014; Li et al., 2015; Prencipe et al., 2011; Volkow and Baler, 2014; Yao et al., 2015). During the 2-Back Task, partially contrary to our hypothesis about IA, subjects with IA showed better working memory performance for internet-related words than for internet-unrelated words. Inconsistent with the assumptions in a recent review (Brand et al., 2014), the result suggests that working memory function may be improved rather than being disrupted among internet addicted individuals. One possible explanation for this
Please cite this article as: Nie, J., et al., Impaired inhibition and working memory in response to internet-related words among adolescents with internet addiction: A.... Psychiatry Research (2016), http://dx.doi.org/10.1016/j.psychres.2016.01.004i
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unexpected result is that different stimulus materials were used in previous studies and our research. Previous studies presented various pictures in their experimental conditions, such as gamingrelated pictures (Lorenz et al., 2013), pornographic-related pictures (Laier et al., 2013), or other addiction-related pictures (Turel et al., 2014). Compared with words, pictures contain richer content that is usually more associated with emotion and attention, and thus they might be stronger in terms of inducing arousal reactions or interfering with working memory performance. For instance, an electroencephalographic study concerning specific cue-reactivity showed significant between-group differences in event-related potentials evoked by computer game-related pictures by comparing excessive computer game players with casual players (Thalemann et al., 2007). In other words, early studies used pictures to possibly focus on the visual working memory. Visual stimuli have also been the focus of more recent work. For example, a Chinese study on visual working memory found that individuals with IA may differ from normal controls in the attention capture led by working memory (Zhang et al., 2015). However, in contrast to previous work, our study used words, which might correspond to the verbal working memory. Therefore, memorizing internetrelated words in the present study may improve the verbal working memory of internet addicted individuals, and further study needs to investigate the different components of working memory with IA. 4.2. Impairments in response inhibition and working memory in ADHD and IA/ADHD Consistent with a study by Chen et al. (2015), our findings indicated that two dimensions of ADHD symptoms (inattention and hyperactivity/impulsivity) were positively correlated with CIAS scores, and ADHD subjects (relative to NC) showed impaired response inhibition and lower working memory performance during the SST and the 2-Back Task. However, the poor performance of ADHD subjects for internet-related stimuli did not differ from internet-unrelated stimuli on either of the two cognitive tasks. With regard to the coexistence of IA and ADHD, a review of the literature by Ko et al. (2012) suggested that internet behavior is characterized by rapid response, immediate reward, and multiple windows with different activities, which may reduce the feeling of tediousness or provide immediate stimulation and reward for individuals with the core ADHD symptoms of “being easily bored” and “having an aversion for delayed reward”. Despite individuals with ADHD being possibly familiar with internet-related stimuli in their daily lives, the two cognitive tasks in our study (e.g., judging or memorizing words) were perhaps easy but uninteresting to them. That is, individuals with ADHD might not have reacted differentially to internet-related stimuli in the present study. However, correlational analysis indicated a positive association between mean RT in the 2-Back Task and the two ADHD symptom dimensions (i.e. inattention and hyperactivity/impulsivity). This suggests that the executive functions in ADHD might still be affected by internet-related cues, hence further researches need to design more interesting tasks that may engage the ‘hot’ executive functioning of ADHD individuals. Although the co-morbid group performed more poorly than the NC group during the SST and 2-Back Tasks in the current study, the co-morbid group performed better in response to internetrelated stimuli than internet-unrelated stimuli, similar to the IA group in this study. This result indicated that internet-related stimuli in the present study may be a significant visual stimulus to draw attention for the co-morbid subjects, and that internet-related activities might improve the performance of the co-morbid group in cognitive tasks. Previous studies have shown that impairment observed in patients with ADHD may be explained by
associated psychiatric disorders and not only by ADHD itself (Biederman, 2004; Grevet et al., 2006; Kessler et al., 2006), and our findings provide empirical evidence to support the assumption that specific co-morbid disorders may influence neuropsychological functions in adults with ADHD (Silva et al., 2013). With regard to the association between ADHD and IA, our findings support the assumption that people with ADHD should be an important target group of preventive scheduling for IA (Ko et al., 2012). The results also suggest that prevention and intervention strategies for providing internet-related stimuli are needed for the treatment of ADHD and co-morbid IA. 4.3. Strengths, limitations and conclusions The present study should be interpreted in the context of some limitations. The cross-sectional research design limited the possibility to determine the causal relationships between response inhibition and working memory in IA (and ADHD). The generalizability of our findings is also limited because we studied a small sample recruited from a vocational high school. Further studies with larger and representative samples are needed to replicate our findings. A further limitation of the present study is that we did not consider types of IA, meaning that some selected words may not have served as addiction-related stimuli for all participants. Thus, further comparative studies on different types of IA are needed and different neuropsychological mechanisms in some specific subtypes of IA might be found. Despite the above noted limitations, this study provides important initial evidence of impaired response inhibition and working memory functions in the presence of internet-related stimuli among adolescents with IA, ADHD and co-morbid IA/ ADHD. Our findings support the hypothesis that addiction-related cues could further reduce control in addicted individuals (Brand et al., 2014; Sun et al., 2009; Volkow and Baler, 2014), and suggest that internet-related stimuli might be important in strengthening inhibition and working memory when treating adolescents with IA and co-morbid ADHD.
Conflict of interest The authors have no conflict of interest to report.
Acknowledgments This study was supported by The National Natural Science Foundation of China Youth Science Fund Project (31300865) and the Fundamental Research Funds for the Chinese Central Universities (CCNU14A007) for Central China Normal University.
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Psychiatry Research journal homepage: www.elsevier.com/locate/psychres
Impaired inhibition and working memory in response to internetrelated words among adolescents with internet addiction: A comparison with attention-deficit/hyperactivity disorder Jia Nie a,b, Wei Zhang a,b,n, Jia Chen a,b,1, Wendi Li a,b a b
School of Psychology, Central China Normal University, Hubei, China Key Laboratory of Adolescent Cyberpsychology and Behavior (CCNU), Ministry of Education, Wuhan, China
art ic l e i nf o
a b s t r a c t
Article history: Received 12 August 2015 Received in revised form 12 November 2015 Accepted 4 January 2016
Impairments in response inhibition and working memory functions have been found to be closely associated with internet addiction (IA) symptoms and attention-deficit/hyperactivity disorder (ADHD) symptoms. In this study, we examined response inhibition and working memory processes with two different materials (internet-related and internet-unrelated stimuli) among adolescents with IA, ADHD and co-morbid IA/ADHD. Twenty-four individuals with IA, 28 individuals with ADHD, 17 individuals with IA/ADHD, and 26 matched normal controls (NC) individuals were recruited. All participants were measured with a Stop-Signal Task and 2-Back Task under the same experimental conditions. In comparison to the NC group, subjects with IA, ADHD and IA/ADHD demonstrated impaired inhibition and working memory. In addition, in comparison to internet-unrelated conditions, IA and co-morbid subjects performed worse on the internet-related condition in the Stop trials during the stop-signal task, and they showed better working memory on the internet-related condition in the 2-Back Task. The findings of our study suggest individuals with IA and IA/ADHD may be impaired in inhibition and working memory functions that might be linked to poor inhibition specifically related to internet-related stimuli, which will advance our understanding of IA and contribute to prevention and intervention strategies. & 2016 Published by Elsevier Ireland Ltd.
Keywords: Internet addiction Attention-deficit/hyperactivity disorder Response inhibition Working memory
1. Introduction With the increased use of the internet in the 21st century, problems related to internet use have emerged. Internet addiction (IA) can be broadly conceptualized as an inability to control one's use of the internet, which comprises the problematic use of internet/video gaming, mobile hand-held devices and other forms of addictive internet usage (Yung et al., 2015). The negative consequences of IA include emotional, social and mental dysfunction in a wide range of areas of daily activities (Davis, 2001; Spada, 2014; Young, 1998). In China, many people are readily exposed to the internet from a very young age, and IA has already become a serious mental health and behavior problem among adolescents, gradually attracting the attention of numerous researchers and the public (Cao and Su, 2007; Tang et al., 2014). IA is not only considered one type of behavioral addiction n Corresponding author at: School of Psychology, Central China Normal University, 152 Luoyu Street, Wuhan 430079, Hubei, China. E-mail address: [email protected] (W. Zhang). 1 Permanent address: Usability and Design Lab, Beijing, China.
(Holden, 2001), it is also considered by some to be an impulse control disorder or at least to have the characteristics of impulse control disorders (Beard and Wolf, 2001; Shaw and Black, 2008). Although a clinical diagnosis of IA not currently found in the DSMV, it is thought to be similar to internet gaming disorder (IGD), which belongs to the class of disorders that includes substance use and addictive disorders in DSM-V (Gunuc, 2015). While the diagnosis remains controversial, diminished control has been regarded as a core defining concept of substance dependence or addiction, and accordingly, IA should present the “loss of control” characteristics similar to these types of disorders. Indeed, one study showed that individuals with IA indeed could not successfully control their internet activities in their daily life, or they had withdrawal symptoms (e.g., irritability, anxiety or sadness) when they were asked to stop playing with the computer or stop their internet usage (Tzang et al., 2015). These symptoms are also the diagnostic criteria commonly found on many questionnaires used to assess IA (Lortie and Guitton, 2013). Successfully inhibiting prepotent responses (response inhibition) is a major contributor to an individual's ability to avoid inappropriate behaviors. Although neuropsychological investigations
http://dx.doi.org/10.1016/j.psychres.2016.01.004 0165-1781/& 2016 Published by Elsevier Ireland Ltd.
Please cite this article as: Nie, J., et al., Impaired inhibition and working memory in response to internet-related words among adolescents with internet addiction: A.... Psychiatry Research (2016), http://dx.doi.org/10.1016/j.psychres.2016.01.004i
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have reported that impaired response inhibition (inhibitory control) are seen in IA (Cao et al., 2007; Choi et al., 2013, 2014; Dong et al., 2012, 2010; Zhou et al., 2013, 2010), it is unclear why some individuals cannot control their internet use. An emerging view is that internet addicted individuals have difficulty in suppressing responses only to explicitly addiction-related or internet-related stimuli (Brand et al., 2014; Sun et al., 2009). Previous findings about IGD have also suggested that IGD subjects show impaired inhibition function in response to internet gaming-related cues on the Go/NoGo task or other similar cognitive tasks (Liu et al., 2014; Yao et al., 2015; Zhou et al., 2012). Consequently, the experimental materials (e.g. digits or letters) that are commonly used in the laboratory may not reflect the specific types of impairments of internet addicted individuals in inhibiting their prepotent responses when they are using the internet. It is necessary to use an internet-related inhibition task for assessing response inhibition of IA. Working memory is an executive function that allows the maintenance of the information required to execute high-order plans, which is important for adolescents' reasoning, learning and language comprehension. Many studies have shown that individuals with IA present impairments in working memory similar to behavioral and substance addictions, such as alcohol dependence (Zhou et al., 2014) and pathological gambling (Zhou et al., 2015). A review summarizing some recent neuropsychological researches suggested that internet-related cues interfere with control processes mediated by the prefrontal brain areas, and internet-related stimuli interfere with some prefrontal functions such as working memory and other executive functions (Brand et al., 2014). For instance, concentrating on the excessive use of internet pornography, which is a form of IA, one study reported that healthy individuals showed lower working memory performance for pornographic stimuli than for positive, negative, and neutral pictures (Laier et al., 2013). It has further been suggested that working memory performance may be differentially affected when individuals with IA are confronted with internet-related cues. IA and its psychiatric comorbid conditions have received increasing research attention in recent years, with a particular focus on attention-deficit/hyperactivity disorder (Bozkurt et al., 2013; Chou et al., 2015; Dalbudak et al., 2015; Ko et al., 2012; Weinstein, 2010). ADHD-related symptoms (e.g. inattention and hyperactivity/impulsivity) are highly relevant to IA (Chen et al., 2015), and a recent meta-analysis of the literature reported that IA was significantly associated with ADHD (Ho et al., 2014). One possible explanation for the coexistence of IA and ADHD is that adolescents with ADHD have abnormal brain activities associated with impaired inhibition (Rubia et al., 2005), which may cause people with ADHD to have difficulty in controlling internet use and to become vulnerable to internet addiction (Yen et al., 2014). Based on observed experimental data and clinical manifestations among patients with ADHD, previous researches have already shown that adolescents with ADHD demonstrate neuropsychological deficits across a wide range of impairments in executive functions including response inhibition and working memory (Barkley, 1997; Epstein et al., 2011; McAuley et al., 2014; van Rooij et al., 2015). ADHD may also be shown to be associated with impaired response inhibition and working memory in response to internet-related stimuli. Although executive dysfunctions in response inhibition and working memory are heavily studied with ADHD, few studies have examined the relationships of ADHD with response inhibition and working memory in adolescents using internet-related cognitive tasks. The aims of the present study were to investigate response inhibition and working memory processes using two neuropsychological tasks (Stop-Signal Task and 2-Back Task) with two different materials (internet-related and internet-unrelated
stimuli) among adolescents with IA, ADHD and co-morbid IA/ ADHD. Neuropsychological tasks have contributed significantly to our understanding of the effect of IA and ADHD on cognitive functions, and may be useful for identifying potential neurobiological mechanisms and adequate treatments in these diagnostic groups. Based on the results of previous studies, we hypothesized that, relative to normal controls, participants with IA would show a lower ability to suppress internet-related response (Liu et al., 2014; Yao et al., 2015; Zhou et al., 2012), and show weakened working memory for internet-related materials relative to internet-unrelated materials (Laier et al., 2013; Zhou et al., 2015; Zhou et al., 2014). In addition, it was hypothesized that ADHD and comorbid ADHD/IA would also unsuccessfully suppress internet-related responses, and show weakened working memory for internet-related materials relative to internet-unrelated materials.
2. Method 2.1. Participants Twelve classes were selected from three grades (i.e., senior one, senior two and senior three) in a vocational high school in Guangzhou City (the capital of Guangdong Province in southern China, a city with a population of over 100 million). This study was approved by the high school and the participants’ parents. A total of 828 students (all right-handed) participated. To assess internet addiction, students were screened with the Chen Internet Addiction Scale (CIAS), which is a widely used criterion for internet addiction in Mainland China and Taiwan. The internal reliability of the scale and its sub-scales in the original study ranged from 0.79 to 0.93 (Chen et al., 2003). The CIAS contains 26 items on a four-point Likert scale, with total scores ranging from 26 to 104. A higher total score indicates increased severity of addiction to internet-related activity. Accordingly, those with total scores of 57 or less in the current study were classified as the normal control (NC) group, and those with CIAS scores of 64 or more were classified as the internet addiction group (Ko et al., 2005). The participants whose total score was between 57 and 64 were excluded. Participants with ADHD were diagnosed according to The Diagnostic and Statistical Manual of Mental Disorders, 4th edition (DSM-IV). The DSM-IV criteria for ADHD contain 18 symptoms, with ADHD diagnosed based on evaluations of two separate but correlated symptom dimensions: inattention and hyperactivity/ impulsivity (American Psychiatric Association, 2000). One meets the criteria for ADHD by having six or more inattention or hyperactivity/impulsivity symptoms. The criteria were translated into Chinese by the researchers, and a self-report questionnaire was developed based on these criteria. In accordance with the DSM-IV, participants fulfilled the criteria for ADHD when their scores wereZ6. These participants were classified as individuals with ADHD, and the remainder (scores o6) were classified as normal controls. According to the diagnostic criteria of the CIAS and the DSM-IV, 24 students who were diagnosed with internet addiction were included in the IA-only group, 28 students who were diagnosed with ADHD were included in the ADHD-only group and 17 students who met the inclusion criteria for both IA and ADHD were included in the co-morbid group. The NC group was composed of 26 students without IA or ADHD. Of the participants, 63 (66.32%) were boys and 32 (33.68%) were girls. The mean age of the participants was 16.34 years (SD ¼0.81), ranging from 15 to 18. The four groups were matched on gender, age and educational levels (see Table 1). In addition, two child psychiatrists and two
Please cite this article as: Nie, J., et al., Impaired inhibition and working memory in response to internet-related words among adolescents with internet addiction: A.... Psychiatry Research (2016), http://dx.doi.org/10.1016/j.psychres.2016.01.004i
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Table 1 Demographic characteristics, ADHD symptoms and CIAS scores.
Sex ratio (M/F) Mean age (SD) Mean education (SD) ADHD symptoms on the DSM-IV Inattention (SD) Hyperactivity/Impulsivity (SD) CIAS(SD)
IA
ADHD
Co-morbid
NC
Test statistic
24 (16/8) 16.29 (0.91) 10.00 (0.72)
28 (18/10) 16.29 (0.71) 10.11 (0.69)
17 (12/5) 16.41 (0.94) 10.29 (0.92)
26 (17/9) 16.38 (0.75) 10.19 (0.75)
χ2 ¼0.202 F¼ 0.19 F¼ 0.57
3.08 (1.69) 1.92 (1.86) 69.75 (8.24)
5.93 (1.18) 3.82 (2.23) 52.32 (8.94)
6.65 (1.57) 4.59 (2.62) 73.76 (11.43)
1.35 (1.16) 0.73 (1.04) 40.38 (8.68)
F¼ 72.795nnn F¼ 18.22nnn F¼ 66.087nnn
IA¼ Internet Addiction; ADHD ¼ Attention-deficit/hyperactivity disorder; Co-morbid ¼ both ADHD and IA; NC¼ Normal Control; M ¼ male; F ¼female; SD ¼ standard deviation; DSM-IV ¼the Diagnostic and Statistical Manual of Mental Disorders, 4th edition; CIAS¼ Chen Internet Addiction Scale. nnn
p o 0.001.
2.2. Measures
variable stop-signal delay (SSD): 100, 250 or 400 ms after the onset of the target word. Go trials occurred 60% of the time, and the remaining 40% were Stop trials. Participants first completed a practice block of 10 trials. The practice block provided feedback, whereas the experimental block did not. The mean Go trial reaction times (GORT), the error rate on Go trials and the proportion of successful stops on Stop trials were used as dependent variables in this task. Participants received standardized task instructions before the computerized task, and they completed a total of 128 trials.
2.2.1. Materials Chinese words were selected as experimental materials to be presented to participants visually in the Stop-Signal Task and the 2-Back Task. These words were divided into two sets: the noun set (36 words) and the verb set (30 words). Given that the majority of Chinese words are disyllabic, all selected words were disyllabic. Each word fit into one of two subtypes: internet-related (e.g., Micro-blog) or internet-unrelated (e.g., Lightning). The Internetrelated words included several categories such as online shopping, web browsing, social networking, internet/video gaming, downloading and normal internet usage (e.g., Login). Each internetunrelated word matched a corresponding Internet-related word on the Chinese character pattern and structure. All selected words were matched by 15 psychological professionals in accordance with the Modern Chinese Dictionary. To evaluate word categorization, an additional 15 raters answered the question, “How much do you agree that each of the following Chinese words is associated with Internet usage/activity?” The raters responded on a 5-point scale, ranging from strongly disagree (1) to strongly agree (5), and there was a high degree of consistency between raters (Kendall W¼ 0.954). An independent-samples t-test compared ratings between internet-related and internet-unrelated words. As expected, internet-related words were rated as significantly more internet-related than internet-unrelated words (t¼105.948, p o0.001).
2.2.3. Working memory measure: 2-Back Task The working memory measure in this study employed a 2-Back design. Participants were asked to monitor the identity of a series of Chinese words (the same as those used in the SST) presented in a random sequence. Participants were instructed to press the “F” button if the currently presented word was identical to the one that was presented two trials before and to press the “J” button if the current word was different from the word presented two trials before. Following 10 practice trials, participants were presented with two blocks (internet-related block and internet-unrelated block) of 60 trials each, for a total of 120 trials. The practice block provided feedback, whereas the two experimental blocks did not. For each block, the first two words were not analyzed due to an insufficient number of previous words to validly complete the task. Target stimuli (same stimulus as two trials before) were presented randomly throughout the remaining trials. The mean reaction times (RT) and the accuracy on experiment blocks were taken as dependent variables in this task. Each trial began with the presentation of a red fixation point for 500 ms, followed by the randomly generated words for that trial. Each word was displayed for 750 ms, with an interstimulus interval of 4000 ms. In order to prevent the order of experimental conditions from affecting responses, half of the participants completed an internet-related task, and the other half completed an internetunrelated task initially.
2.2.2. Response inhibition measure: Stop-Signal Task (SST) The SST is a classic approach to measuring response inhibition (Verbruggen and Logan, 2008). For the SST in the current study, participants were shown a series of Chinese words on a computer screen. Each trial began with the presentation of a red fixation point for 300 ms, followed by a blank screen for 300 ms. One of the 66 experimental words was then randomly presented for 2 s. Trials were either Go trials or Stop trials. In the Go trials, participants were instructed to press the “F” button on a standard keyboard when they saw a noun and the “J” button when they saw a verb. In the Stop trials, participants were told to continue with the same procedure as the Go trials; however, if they heard an auditory signal (a beep), they should withhold their response and not press the button. The stop signal (the beep) was presented after a
2.3. Procedure
psychological professionals conducted interviews with the participants in the three disorder groups and their parents. The interviews were conducted to confirm that none of the participants had been clinically diagnosed with neurological diseases (e.g., head injury), intellectual disabilities psychosis, or history of drug abuse. Interviews also confirmed that adolescents who were diagnosed with ADHD for the purposes of the current study had never received medication for it.
Participants were tested individually. They completed two selfreport questionnaires in class after the researchers explained the procedure and requirements. Questionnaires were collected immediately after completion. After finishing the CIAS questionnaire, the DSM-IV questionnaire about ADHD and a demographic questionnaire made by the researchers, they performed the SST followed by the 2-Back Task. The experiment was programmed with E-Prime (Version 2.0) software. Participants who completed both tasks were positioned approximately 100 cm away from a computer screen (DELL 14-inch, LCD monitor) with horizontal and vertical visual angles of less than 5°. There was a twenty-minute break between these two tasks to avoid fatigue. It took no more
Please cite this article as: Nie, J., et al., Impaired inhibition and working memory in response to internet-related words among adolescents with internet addiction: A.... Psychiatry Research (2016), http://dx.doi.org/10.1016/j.psychres.2016.01.004i
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than one hour to complete the entire testing session. All participants received a small monetary reward after the experiment. 2.4. Statistical analysis Statistical analyses were performed using SPSS 17.0 statistical software package (SPSS Inc., Chicago, IL, USA). First, possible group differences in demographic variables were analyzed using a chisquare analysis and a one-way ANOVA. Second, separate repeatedmeasures ANOVAs were used to explore between-group differences in performance on the SST and the 2-Back Task. Finally, Pearson's correlations were used to investigate the relationships between ADHD symptoms and CIAS scores with the scores from the two neuropsychological tests (the SST and 2-Back Task). Statistical significances were defined at the 0.05 level, two-tailed.
3. Results 3.1. Demographic characteristic The participants' demographic characteristics, ADHD symptoms and CIAS scores are shown in Table 1. In addition, internet addiction symptoms on the CIAS were significantly correlated with inattention symptoms (r ¼ 0.371, po 0.001) and hyperactivity/impulsivity symptoms (r ¼0.319, p o0.001) on the DSM-IV. 3.2. Performance of the four groups on the SST Data were excluded for 15 participants because they performed the SST in an invalid manner (i.e., Go trials had less than 50% accuracy or a mean GORT of less than 200 ms, indicating that they may have been guessing on the Go trials due to their impulsivity). The remaining data (IA, 19; ADHD, 23; co-morbid group, 14; NC, 24; gender, χ2 ¼0.99, p ¼0.804; age, F¼0.343, p ¼0.794) consisted of the mean GORT, the error rate on Go trials and the proportion of successful stops on Stop trials. A repeated-measures ANOVA was used to analyze these three variables, with group (IA, ADHD, comorbid IA/ADHD and NC) as the between-subjects factor and word-type (internet-related and internet-unrelated) as the withinsubjects factor. Go trial performance on the SST among IA, ADHD, co-morbid IA/ADHD and NC groups are shown in Table 2. For mean GORT, results showed a significant main effect of word-type (F(1, 76) ¼11.12, p o0.01) and a marginally significant interaction between word-type and group (F(3, 76) ¼2.51, p¼ 0.065); however, the main effect of group was not significant (F(3, 76) ¼ 1.35, p 40.05). The mean GORT of the IA group for the internet-unrelated words was significantly higher than for the internet-related words (F(1, 76) ¼ 7.17, p o0.01), and the mean GORT of the comorbid group for the internet-unrelated words was significantly higher than for the internet-related words (F(1, 76) ¼ 6.41, po 0.05). The results of error rate on Go trials showed that the main effect of
word-type was significant (F(1, 76) ¼ 8.68, p o0.01); however, the main effect of group and the interaction between word-type and group were not significant (F(3, 76) ¼0.53, p 40.05; F(3, 76) ¼1.87, p4 0.05). Previous research has reported that an approximately 250 ms stop-signal delay (SSD) was sensitive enough to distinguish between ADHD and normal-control groups (Pliszka et al., 2000; Rubia et al., 1998; Wang et al., 2005). In the present study, 250 ms (SSD) was analyzed as a variable indicator to describe the proportion of successful stops on Stop trials. For proportion of successful stops (250 ms), results showed significant main effects of word-type (F(1, 76) ¼ 9.37, p o0.01) and group (F(3, 76) ¼ 3.78, po 0.05), and the interaction between word-type and group was also significant (F(3, 76) ¼ 4.24, po 0.01). Fig. 1 shows a simple effect analysis of the proportion of successful stops on the SST. For the IA group, the proportion of successful stops for the internet-unrelated words was significantly higher than for the internet-related words (F(1, 76) ¼11.75, p o0.01), and for the co-morbid group the proportion of successful stops for the internet-unrelated words was also significantly higher than for the internet-related words (F(1, 76) ¼6.36, p o0.05). 3.3. Performance of the four groups on the 2-Back Task Data were excluded for 29 participants because they performed the 2-Back Task in an invalid manner (i.e., experiment blocks with less than 50% accuracy or mean RT less than 150 ms, indicating that they responded too early because of their impulsivity). The remaining data (IA, 19; ADHD, 19; co-morbid group, 10; NC, 18; gender, χ2 ¼ 0.897, p ¼0.826; age, F¼0.305, p ¼0.822) consisted of the mean RT and the accuracy on the 2-Back Task. A repeatedmeasures ANOVA was used to analyze these two variables, with group (IA, ADHD, co-morbid and NC) as the between-subjects factor and word-type (internet-related and internet-unrelated) as the within-subjects factor. The 2-Back Task performance for the IA, ADHD, co-morbid and NC groups are shown in Fig. 2. For mean RT, results showed significant main effects of word-type (F(1, 62) ¼4.01, p ¼0.05) and group (F(3, 62) ¼2.96, p o0.05). The interaction between word-type and group was marginally significant (F(3, 62) ¼2.20, p ¼0.09). The mean RT of the IA and co-morbid groups for the internet-unrelated words was significantly higher than for the internet-related words (IA, F(1, 62) ¼ 4.21, po 0.05; co-morbid, F(1, 62) ¼4.43, p o0.05). For task accuracy, results showed a significant main effect of wordtype (F(1, 62) ¼4.39, p o0.05) and a marginally significant main effect of group (F(3, 62) ¼2.74, p ¼0.051); however, the interaction between word-type and group was not significant (F(3, 62) ¼1.66, p4 0.05). 3.4. Relationships between ADHD symptoms and internet addiction symptoms with two neuropsychological tests Correlational analyses were used to examine ADHD scores
Table 2 Go trials performance on SST among IA, ADHD, Co-morbid IA/ADHD and NC groups. Internet-related words
IA ADHD Co-morbid NC
Internet-unrelated words
Mean GORT (ms)
Error rate (%)
Mean GORT (ms)
Error rate (%)
725.92(81.97) 751.14(115.99) 734.08(67.15) 718.20(158.21)
26.89(10.67) 30.00(9.88) 26.84(12.89) 27.62(12.65)
804.75(144.88) 793.17(158.97) 820.91(162.58) 706.20(170.80)
31.70(9.50) 32.77(6.53) 29.81(12.18) 28.00(13.21)
IA¼ Internet Addiction; ADHD ¼Attention-deficit/hyperactivity disorder; Co-morbid ¼both ADHD and IA; NC¼Normal Control; SST¼ Stop-Signal Task; Mean GORT ¼Mean reaction time on Go trials.
Please cite this article as: Nie, J., et al., Impaired inhibition and working memory in response to internet-related words among adolescents with internet addiction: A.... Psychiatry Research (2016), http://dx.doi.org/10.1016/j.psychres.2016.01.004i
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CIAS scores and the 2-Back Task.
4. Discussion
Fig. 1. A simple effect analysis of the proportion of successful stops on stop-signal task; *, p o0.05; **, p o0.01; IA ¼Internet Addiction; ADHD ¼ Attention-deficit/hyperactivity disorder; Co-morbid ¼both ADHD and IA; NC¼ Normal Control.
The current study aimed to assess response inhibition and working memory processes among adolescents with IA, ADHD and co-morbid IA and ADHD, using two neuropsychological tasks (SST and 2-Back Task) with two different materials (internet-related and internet-unrelated stimuli). Partly consistent with our hypothesis, we found that, in comparison to the NC group, subjects with IA, ADHD and IA/ADHD performed worse on the SST and 2-Back Task. However, the IA and co-morbid subjects showed an unexpected pattern in which they had lower inhibition in response to internet-related words (compared to internet-unrelated words) in the Stop trials (SST), but showed better working memory performance for the internet-related words in the 2-Back Task. By contrast, the ADHD group no significant differences between internet-related and internet-unrelated words were observed. Clarifying whether impaired inhibition and working memory functions among individuals with IA and co-morbid ADHD are related to internet usage will advance understanding of IA and contribute to prevention and intervention in the mechanisms of co-morbid IA/ADHD. Findings of our study and their clinical implication are discussed below. 4.1. Impairments in response inhibition and working memory in IA
Fig. 2. (a), Mean RT (Reaction Time) for internet-related and internet-unrelated words; (b), accuracy for internet-related and internet-unrelated words; *, p o0.05; IA¼ Internet Addiction; ADHD ¼ Attention-deficit/hyperactivity disorder; Co-morbid ¼both ADHD and IA; NC¼Normal Control.
(with two dimensions: inattention and hyperactivity/impulsivity) and CIAS scores in relation to scores on the two neuropsychological tests (SST and 2-Back Task). The results indicated that, in the SST, the proportion of successful stops on the internet-related condition was significantly negatively correlated with three variables: ADHD inattention symptoms (r(80) ¼ 0.352, p ¼0.001), ADHD hyperactivity/impulsivity symptoms (r(80) ¼ 0.296, p ¼0.008) and CIAS scores (r(80) ¼ 0.343, p ¼0.002). The proportion of successful stops on the internet-unrelated condition was significantly negatively correlated only with ADHD inattention symptoms (r(80) ¼ 0.306, p ¼0.006) and ADHD hyperactivity/impulsivity symptoms (r(80) ¼ 0.223, p ¼0.047). There were no other significant correlations between ADHD and CIAS scores and variables of the SST. In the 2-Back Task, mean RT in the internetrelated condition was significantly positively correlated with ADHD inattention symptoms (r(66) ¼0.402, p ¼0.001) and ADHD hyperactivity/impulsivity symptoms (r(66) ¼ 0.389, p ¼0.001); mean RT in the internet-unrelated condition was significantly positively correlated with CIAS scores (r(66) ¼0.262, p ¼ 0.034). No other significant correlations were observed between ADHD and
Our results showed that IA subjects performed better for the internet-related words (relative to internet-unrelated words) in the Go trials (SST), and they more frequently failed to inhibit their response to internet-related words (relative to internet-unrelated words) in the Stop trial (SST). One possible explanation for the Go trials performance is that internet-related stimuli may be a more distinctive target for individuals with IA, who are frequent internet users. Distinctiveness draws attention and guides searches more efficiently (Treisman and Gelade, 1980). In Go trial processes, subjects were asked to judge only whether a randomly generated word on the screen was a verb or a noun or to respond quickly to internet-related words, the latter of which may be a prepotent response for IA subjects. Although IA may have shown a prepotent response to the Go trials, it would be difficult to suppress the prepotent response in the Stop trial. This finding is consistent with previous studies, which found that individuals with IGD showed lower inhibition in their prepotent response to gaming-related stimuli (Liu et al., 2014; Yao et al., 2015; Zhou et al., 2012). It is also consistent with hypotheses positing that cognitive control processes in particular may be disrupted by the presence of addiction-related stimuli (Brand et al., 2014; Sun et al., 2009; Volkow and Baler, 2014). The prepotent responses to internet-related stimuli can be thought of as ‘hot’ tasks that are theorized to engage ‘hot’ executive functions (e.g., self-control) that are activated in the presence of stronger affective salience; these override ‘cold’ executive functions (e.g., response inhibition) mediated by brain areas such as the dorsolateral prefrontal cortex which may reflect addiction-related reduced inhibitory control, resulting in alterations in inhibitory control processes (Brand et al., 2014; Li et al., 2015; Prencipe et al., 2011; Volkow and Baler, 2014; Yao et al., 2015). During the 2-Back Task, partially contrary to our hypothesis about IA, subjects with IA showed better working memory performance for internet-related words than for internet-unrelated words. Inconsistent with the assumptions in a recent review (Brand et al., 2014), the result suggests that working memory function may be improved rather than being disrupted among internet addicted individuals. One possible explanation for this
Please cite this article as: Nie, J., et al., Impaired inhibition and working memory in response to internet-related words among adolescents with internet addiction: A.... Psychiatry Research (2016), http://dx.doi.org/10.1016/j.psychres.2016.01.004i
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unexpected result is that different stimulus materials were used in previous studies and our research. Previous studies presented various pictures in their experimental conditions, such as gamingrelated pictures (Lorenz et al., 2013), pornographic-related pictures (Laier et al., 2013), or other addiction-related pictures (Turel et al., 2014). Compared with words, pictures contain richer content that is usually more associated with emotion and attention, and thus they might be stronger in terms of inducing arousal reactions or interfering with working memory performance. For instance, an electroencephalographic study concerning specific cue-reactivity showed significant between-group differences in event-related potentials evoked by computer game-related pictures by comparing excessive computer game players with casual players (Thalemann et al., 2007). In other words, early studies used pictures to possibly focus on the visual working memory. Visual stimuli have also been the focus of more recent work. For example, a Chinese study on visual working memory found that individuals with IA may differ from normal controls in the attention capture led by working memory (Zhang et al., 2015). However, in contrast to previous work, our study used words, which might correspond to the verbal working memory. Therefore, memorizing internetrelated words in the present study may improve the verbal working memory of internet addicted individuals, and further study needs to investigate the different components of working memory with IA. 4.2. Impairments in response inhibition and working memory in ADHD and IA/ADHD Consistent with a study by Chen et al. (2015), our findings indicated that two dimensions of ADHD symptoms (inattention and hyperactivity/impulsivity) were positively correlated with CIAS scores, and ADHD subjects (relative to NC) showed impaired response inhibition and lower working memory performance during the SST and the 2-Back Task. However, the poor performance of ADHD subjects for internet-related stimuli did not differ from internet-unrelated stimuli on either of the two cognitive tasks. With regard to the coexistence of IA and ADHD, a review of the literature by Ko et al. (2012) suggested that internet behavior is characterized by rapid response, immediate reward, and multiple windows with different activities, which may reduce the feeling of tediousness or provide immediate stimulation and reward for individuals with the core ADHD symptoms of “being easily bored” and “having an aversion for delayed reward”. Despite individuals with ADHD being possibly familiar with internet-related stimuli in their daily lives, the two cognitive tasks in our study (e.g., judging or memorizing words) were perhaps easy but uninteresting to them. That is, individuals with ADHD might not have reacted differentially to internet-related stimuli in the present study. However, correlational analysis indicated a positive association between mean RT in the 2-Back Task and the two ADHD symptom dimensions (i.e. inattention and hyperactivity/impulsivity). This suggests that the executive functions in ADHD might still be affected by internet-related cues, hence further researches need to design more interesting tasks that may engage the ‘hot’ executive functioning of ADHD individuals. Although the co-morbid group performed more poorly than the NC group during the SST and 2-Back Tasks in the current study, the co-morbid group performed better in response to internetrelated stimuli than internet-unrelated stimuli, similar to the IA group in this study. This result indicated that internet-related stimuli in the present study may be a significant visual stimulus to draw attention for the co-morbid subjects, and that internet-related activities might improve the performance of the co-morbid group in cognitive tasks. Previous studies have shown that impairment observed in patients with ADHD may be explained by
associated psychiatric disorders and not only by ADHD itself (Biederman, 2004; Grevet et al., 2006; Kessler et al., 2006), and our findings provide empirical evidence to support the assumption that specific co-morbid disorders may influence neuropsychological functions in adults with ADHD (Silva et al., 2013). With regard to the association between ADHD and IA, our findings support the assumption that people with ADHD should be an important target group of preventive scheduling for IA (Ko et al., 2012). The results also suggest that prevention and intervention strategies for providing internet-related stimuli are needed for the treatment of ADHD and co-morbid IA. 4.3. Strengths, limitations and conclusions The present study should be interpreted in the context of some limitations. The cross-sectional research design limited the possibility to determine the causal relationships between response inhibition and working memory in IA (and ADHD). The generalizability of our findings is also limited because we studied a small sample recruited from a vocational high school. Further studies with larger and representative samples are needed to replicate our findings. A further limitation of the present study is that we did not consider types of IA, meaning that some selected words may not have served as addiction-related stimuli for all participants. Thus, further comparative studies on different types of IA are needed and different neuropsychological mechanisms in some specific subtypes of IA might be found. Despite the above noted limitations, this study provides important initial evidence of impaired response inhibition and working memory functions in the presence of internet-related stimuli among adolescents with IA, ADHD and co-morbid IA/ ADHD. Our findings support the hypothesis that addiction-related cues could further reduce control in addicted individuals (Brand et al., 2014; Sun et al., 2009; Volkow and Baler, 2014), and suggest that internet-related stimuli might be important in strengthening inhibition and working memory when treating adolescents with IA and co-morbid ADHD.
Conflict of interest The authors have no conflict of interest to report.
Acknowledgments This study was supported by The National Natural Science Foundation of China Youth Science Fund Project (31300865) and the Fundamental Research Funds for the Chinese Central Universities (CCNU14A007) for Central China Normal University.
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Please cite this article as: Nie, J., et al., Impaired inhibition and working memory in response to internet-related words among adolescents with internet addiction: A.... Psychiatry Research (2016), http://dx.doi.org/10.1016/j.psychres.2016.01.004i