Children and Youth Services Review 35 (2013) 1468–1475
Contents lists available at SciVerse ScienceDirect
Children and Youth Services Review
journal homepage: www.elsevier.com/locate/childyouth
The role of cognitive distortion in online game addiction among
Chinese adolescents
Li Huanhuan a,⁎, Wang Su b
a
b
Department of Psychology, Renmin University of China, Beijing 100872, PR China
Department of Psychology, Sun-Yat Sen University, Guangzhou 510275, PR China
a r t i c l e
i n f o
Article history:
Received 26 November 2012
Received in revised form 27 March 2013
Accepted 29 May 2013
Available online 7 June 2013
Keywords:
Online game addiction
Cognitive distortion
Cognitive–behavioral therapy
Adolescence
a b s t r a c t
The aim of the present study was to examine the role of cognitive distortions in the development of on-line game
addiction among Chinese adolescents. In Study 1, the sample comprised 495 adolescents aged 12 to 19 who
recruited from two middle schools in Guangzhou, China. They were administered questionnaires relating background variables, the Internet Addiction Scale (IAS), Cognitive Distortions Scale (CDS) and Online Game Cognitive Addiction Scale (OGCAS). In Study 2, Twenty eight adolescents with excessive on-line game play recruited
from a local mental hospital were randomly divided into to a CBT group (N = 14) and a clinical control group
(N = 14). Measures of severity of on-line game playing, anxiety, depression, and cognitive distortions were
assessed on baseline and after the 6 week intervention. Results of the present study showed that rumination
and short-term thinking were the most predictors of online game addiction, and all-or-nothing thinking predict
online game addiction at marginal significant levels. Males are at a greater risk of developing online game addiction than do females. CBT and basic counseling had different treatment effects on the all-or-nothing thinking
scores, online comfort scores and short-term thinking scores, SDS scores and SAS scores. Interestingly, CBT and
basic counseling had similar treatment effects on IAS scores and OGCAS scores. Applications of these findings
to etiological research and clinical treatment programs are discussed.
© 2013 Elsevier Ltd. All rights reserved.
1. Introduction
In China today, approximately 46.64 million adolescents between
the ages of 10 and 19 years spend a significant amount of time playing
in a persistent game world (China Internet Network Information
Center, 2011). Arguments continue over the benefits vs. deficits of
online gaming. Some researchers claim that participation in online
gaming can be beneficial to an adolescent's development due to its
entertainment, competition, and multi-player aspects (Chou & Tsai,
2007; Karakus, Inal, & Cagiltay, 2008; Lim & Lee, 2009; Utz, Jonas, &
Tonkens, 2012). Individuals who have higher academic competence,
general positive youth development, positive and clear identity
(Shek & Yu, 2012), and confrontative coping skills (Li, Wang, &
Wang, 2009) have been shown to be at a low risk for Internet addiction, whereas age and being male predict a higher probability for Internet addiction.
In the past two decades, a growing body of studies has suggested that
excessive online game playing is significantly associated with high levels
of depression, anxiety, loss of appetite, sleep disturbance, limited physical
activity, and aggressive behavior in adolescents (Freeman, 2008; Korkeila,
⁎ Corresponding author at: Department of Psychology, Renmin University of China,
Floor 10, Suite D, Huixian Building, 59 Zhongguangcun Street, Haidian District, Beijing
100872, PR China.
E-mail address: [email protected] (H. Li).
0190-7409/$ – see front matter © 2013 Elsevier Ltd. All rights reserved.
http://dx.doi.org/10.1016/j.childyouth.2013.05.021
Kaarlas, Jääskeläinen, Vahlberg, & Taiminen, 2010; Smyth, 2007; Stetina,
Kothgassner, Lehenbauer, & Kryspin-Exner, 2011). On-line game addiction is defined as the “excessive and compulsive use of computer or
video games that results in social and/or emotional problems; despite
these problems, the gamer is unable to control this excessive use”
(Lemmens, Valkenburg, & Peter, 2009, page 78). Although online game
addiction has not yet been recognized as a distinct psychological disorder
in the Diagnostic and Statistical Manual of Mental Disorders 4th Edition
(DSM-IV; American Psychiatric Association), this condition deserves careful attention due to a variety of negative outcomes.
There appears to a significant demand for the treatment of online
game addiction, particularly in China, where the estimated prevalence
of online game addiction among young adults has increased from 5.4%
in 2005 to 11.6% in 2008 (Li, Wang, & Wang, 2008; Yip and Kwok,
2005). Adolescents are particularly susceptible to online game addiction due to characteristics associated with this developmental period,
including the need for self-realization and difficulties in interpersonal
relationships (Lafrenière, Vallerand, Donahue, & Lavigne, 2009; Wan &
Chiou, 2006). On one hand, adolescents often find it easier to develop
intimate relationships with others in an imaginary game world than
they do in face-to-face communication. Thus, interactions in the game
world may represent one way of coping with real interpersonal problems. On the other hand, finely honed gaming skills may allow the adolescent to win respect from, and a reputation among, fellow players,
thereby fulfilling their need for self-realization.
H. Li, S. Wang / Children and Youth Services Review 35 (2013) 1468–1475
Cognitive distortions have been described as errors of logic in
interpreting situations, which include selective abstract-focusing,
overgeneralization, personalization, catastrophic thinking, and
all-or-nothing thinking (Beck, Rush, Shaw, & Emery, 1979). Given
the important role of cognitive distortion in the development of serious
medical conditions, such as major depression, anxiety, chronic pain, substance abuse, and pathological gambling, this area of interest has gained
increased attention among psychologists and psychiatrists (MacKillop,
Anderson, Castelda, Mattson, & Donovick, 2006; Moss-Morris & Petrie,
1997; Nasir, Zamani, Yusooff, & Khairudin, 2010). However, very few
studies have explored the role of cognitive distortion in the development of online game addiction, nor prevention programs been developed that focus on adjusting cognitive distortions in order to reduce
online game addiction among adolescents.
2. Background
2.1. Cognitive distortion and Internet addiction
Davis (2001) first proposed a cognitive–behavioral model in which
cognitive distortions play a central role in problematic Internet use.
Davis suggested a number of specific errors of logic in the interpretation
of Internet use, including rumination (constantly thinking about problems associated with the individual's Internet use, rather than other
events in one's life), self doubt, negative self-appraisal (having a negative view of oneself and using the Internet to achieve more positive responses from others in a non-threatening way), and all-or-nothing
thinking (assuming that oneself is worthless without the Internet, and
exacerbating the individual's Internet dependence, typified by phrases
such as “the Internet is the only place I am respected,” “Nobody loves
me offline,” and “the Internet is my only friend”). In this model, these
cognitive distortions are automatically enacted whenever Internet use
is available, thus leading to overuse of the Internet.
Although the relationship between cognitive distortion and Internet
addiction in Davis's model was at the time a hypothesis, researchers
have since gained evidences that individuals with problematic Internet
use have a tendency to make negative interpretations and dysfunctional
predictions of their Internet use (Decker & Gay, 2011; Kalkan, 2012).
However, a literature search revealed that the bulk of research designed
to assess the role of cognitive distortion in online game addictions has
taken place in the context of Western society. Importantly, it is not
known whether the cognitive distortions described in Davis's model
are representative among Chinese online game players.
Deficient self-regulation has been shown to play an important role
in the negative consequences associated with online gaming (Liu &
Peng, 2009) and in the difficulty to control playing time and to cease
bouts of game playing in Chinese game player (Rau, Peng, & Yang,
2006). These characteristics have been demonstrated to be core criteria
in the definition of online gaming addiction, thus cognitive distortions
specific to excessive online game-playing activities should be elucidated
in the context of Chinese adolescents. Towards this goal, we previously
developed an online gaming Cognitive Distortions Scale (CDC) to assess
all-or-nothing thinking, rumination, online comfort, and short-term
thinking and have demonstrated its useful psychometric properties in
a sample of Chinese adolescents (Wang & Li, 2009).
1469
method for substance dependence, have recently been applied to the
treatment of Internet addiction. CBT has consistently been reported to
be effective in the treatment of Internet addicts, as it allows them to acquire new coping skills and to monitor their thoughts, feelings, and behaviors that are associated with Internet use (Du, Jiang, & Vance, 2010;
Kalkan, 2012; Kim, Han, Lee, & Renshaw, 2012; Young, 2007).
In an eight-session CBT study of 114 adults with Internet addiction,
Young (2007) suggested that most participants could control their
symptoms through self-control and emotional regulation training. Du
et al. (2010) reported that group CBT for Internet addiction improves
pro-social behavior, problem solving, and time management skills,
and decreased problematic Internet use among adolescents aged from
12 to 17 years old. However, more heterogeneous populations, who
used Internet excessively for various purposes in addition to gaming,
were recruited for these two studies. Furthermore, the CBT in these
two studies focused mainly on coping and emotional management
skill training, rather than challenging cognitive distortions. Kim et al.
(2012) reported that a combination of group CBT and medication for
online game addiction in 14–18 year old students significantly decreased the severity of online game playing, mood, and anxiety symptoms, as well as improving life satisfaction and school adaptation
compared to medication alone. Although the CBT trials in Kim's study
did include disputing false beliefs and developing alternative beliefs,
measures of cognitive distortions at baseline and after the treatment period were lacking.
CBT has proven efficacious in the treatment of many psychological
disorders in Western society. Despite limited evidence for its therapeutic efficacy in China, the application of CBT has increased in clinical practice in this country over the past three decades (Chang, Tong, Shi, &
Zeng, 2005). A strong degree of compatibility between CBT and Chinese
values, such as integration, moral discipline, and human heartedness,
has been demonstrated in previous studies (Chen & Davenport, 2005;
Hodges & Oei, 2007), which suggest that the appropriate cultural
modification of CBT can lead to effective psychotherapy outcomes for
Chinese clients. Because therapists authority are highly respected in
Chinese society, where pragmatism has became a general life principle,
the following structural changes in the process of CBT when applied to
Chinese clients have been recommended: setting the direction of
session activity, the teaching of skills, an emphasis on homework,
and a focus on present and future experience. However, while the
role of cognitive distortions in online game addiction has received
increasing attention from mental health workers in China, little, if
any, data exists regarding the efficacy of specific treatments in this
new clinical population.
3. Study 1: the relationship between online game addiction and
cognitive distortion
Study 1 was conducted to further investigate the role of cognitive
distortion, measured by the CDC, in online game addiction among Chinese adolescents. The research questions addressed in the present
study are as follows: do online game addicts score higher on measures
of Internet addiction and on the CDC than do non-addicts? In addition,
is the presence of cognitive distortions significantly predictive of online
game addiction in Chinese adolescents?
2.2. Cognitive–behavior therapy for Internet addicts
3.1. Methods
Evidence to date suggests that individuals with Internet addiction
have typically received some form of treatment, mainly from medical service providers, which focuses on relieving their emotional and physical
symptoms, such as depression, anxiety, and sleep disturbances (Block,
2008). Due to the similar clinical features between individuals with
substance dependence and those with online game addiction, such as
craving, withdrawal, and tolerance (Ng & Wiemer-Hastings, 2005), techniques of cognitive–behavioral therapy (CBT), an established, effective
3.1.1. Participants
The International Review Board of Sun-Yat Sen University approved
the protocol for this study. Our original sample consisted of 540 Chinese
adolescents who were recruited from two middle schools in Guangzhou
and who voluntarily participated in this research with no compensation. Of these, 45 were excluded due to missing data or because they
had no Internet experience, resulting in the current sample of 495
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H. Li, S. Wang / Children and Youth Services Review 35 (2013) 1468–1475
students. The mean age for this sample was 15.52 (SD = 1.97) years of
age, with a range from 12 to 19 years of age.
Prior to the distribution of informed consent forms, the participants
were informed that the purpose of this research was to examine factors
associated with Internet use and that the participants' privacy and anonymity would be fully protected. Informed consent was then obtained
with both the signatures of the participants and their parents before
the actual administration of the questionnaires, which was conducted
in a group format. The questionnaires took approximately 30–35 min
to complete.
3.1.2. Measures
3.1.2.1. Demographic characteristics. The demographic section of the
questionnaire included questions on the participant's gender, age, and
years in middle school.
3.1.2.2. Internet experience. All participants were asked whether they
had used the Internet. Those who had replied in the positive were
asked about the duration of their use. Participants were also asked to
provide the average time they spend on online games weekly.
3.1.2.3. Measures of online game addiction. The Internet Addiction Scale
(IAS; Young, 1998) examines an individual's preoccupation with the Internet by measuring symptoms such as a need for increasingly more
time spent online to achieve the same amount of satisfaction, repeated
efforts to curtail Internet use, irritability, depression or mood lability
when Internet use is limited, staying online longer than anticipated,
and using the Internet as a means of mood regulation. The eight items
of the IAS are calibrated with scores of 0 (no) and 1 (yes). Participants
fulfilling five out of eight criteria are considered problematic Internet
users. A Chinese version (Zhu & Wu, 2004) was adopted for the present
study. An alpha coefficient of .70 was obtained for the current sample.
The Chinese version of the Online Game Cognitive Addiction Scale
(OGCAS; Li, Wang, & Wang, 2008) was used to examine cognitive styles,
compulsivity, withdrawal, and impaired social function related to online gaming. The 16 items of the Chinese version of the OGCAS are calibrated with scores ranging from 1 (strongly disagree) to 5 (strongly
agree), with higher scores reflecting a greater tendency toward online
game addiction. The internal consistency coefficient for the OGCAS
(Cronbach's α = 0.95) was excellent in the current sample.
The Chinese version of the Cognitive Distortions Scale (CDS) was
developed by our research group and was used to examine cognitive
distortions relevant to online game addiction(Wang & Li, 2009). The
CDS consists of 17 items and includes four subscales: all-or-nothing thinking, online comfort (assuming that the virtual world is more comfortable,
safe, and real than the real world), rumination, and short-term thinking
(avoiding problem-solving in which individuals confront emotional
stress, academic stress, and interpersonal conflicts, and merely indulging
in pleasure brought by current online game playing). All the questions of
CDC were specific to online gaming. The 17 items of the CDS are calibrated
using scores ranging from 1 (never) to 5 (always), with higher scores
reflecting a greater tendency toward cognitive distortions associated
with online game addiction. The CDS has previously demonstrated to
have a high internal consistency and good test–retest reliability over an
interval of two weeks in a sample of Chinese adolescents (Wang & Li,
2009). The internal consistency coefficients for the four subscales (Rumination: Cronbach's α = 0.74; all-or-nothing thinking: Cronbach's α =
0.87; online comfort: Cronbach's α = 0.83; short-term thinking:
Cronbach's α = 0.81) were excellent in the current sample.
3.1.3. Data analysis
The statistical analysis was performed using the Statistical Package for Social Sciences (SPSS, version 17.0 for Windows; Chicago,
IL). Descriptive analyses were performed on all variables. Bivariate
associations between online game addiction and each of the other
variables were evaluated using regression analyses. Variables with
p values b 0.05 were included in a simultaneous multivariate regression model, with online game addiction as the dependent variable, to
evaluate the significance of each predictor after controlling for all the
other predictors.
3.2. Results
3.2.1. Demographic characteristics
The education levels of the subjects were as follows: 17.2% in seventh grade, 15.6% in eighth grade, 18.2% in ninth grade, 17.6% in tenth
grade, 16.0% in eleventh grade, and 15.6% in twelfth grade. Among the
495 respondents, 235 (47.5%) were male and 260 (52.5%) were female.
3.2.2. Differences in CDC scores, IAS scores and OGCAS scores relative to
age, gender, and grade level
In Study 1, there were no significant differences in CDC scores,
IAS scores and OGCAS scores across all age groups and grade
level. The total CDC (t = 7.09, p b 0.01) and the four subscales
scores (rumination: t = 8.44, p b 0.01; all-or-nothing thinking:
t = 4.78, p b 0.01; online comfort: t = 3.08, p b 0.01; short-term
thinking: t = 5.96, p b 0.01) were significantly higher for males
than for females. In addition, the IAS (t = − 3.77, p b 0.001) and
OGCAS scores (t = − 10.02, p b 0.001) in males were significantly
higher than those in females.
3.2.3. Relationship between cognition distortions and online game
addiction
Using the data from all 495 participants, bivariate associations between online game addiction severity and demographic variables, rumination, all-or-nothing thinking, online comfort, and short-term
thinking were assessed using regression analyses. The results are summarized in Tables 1–4. All the predictive variables were significantly associated with IAS scores (M = 2.3, SD = 1.9, range: 0–8; see Table 1).
To determine the relative importance of each predictor after controlling
for the other predictors, variables significantly correlated with IAS
scores were included in a simultaneous multivariate regression model
with IAS scores as the dependent variable. The results indicated that rumination (M = 5.31, SD = 2.48, range: 3–15, β = 0.15, p b 0.05) and
short-term thinking (M = 7.24, SD = 3.34, range: 4–20, β = 0.27,
p b 0.001) were significant predictors of the severity of Internet addiction (see Table 2).
With the exception of age (M = 15.52, SD = 1.97, range: 12–19,
β = −0.01, not significant (ns)) and educational level (β = −0.01,
ns), all other predictive variables were significantly associated with
OGCAS scores (M = 27.27, SD = 11.23, range: 16–80). The two most
important predictors of OGCAS scores were rumination (β =0.62,
p b 0.001) and short-term thinking (β = 0.70, p b 0.001; Table 3). To
determine the relative importance of each predictor after controlling
the other predictors, variables significantly correlated with OGCAS
scores were included in a simultaneous multivariate regression model
Table 1
Summary of bivariate associations between IAS scores and each predictor.
Variable
B
SEB
β
Male
Age
Educational level
Rumination
All-or-nothing thinking
On-line comfort
Short-term thinking
1.30
0.16
0.21
0.28
0.14
0.29
0.25
0.24
0.07
0.08
0.04
0.02
0.05
0.03
0.31⁎⁎⁎
0.15⁎
0.17⁎⁎
0.36⁎⁎⁎
0.36⁎⁎⁎
0.37⁎⁎⁎
0.46⁎⁎⁎
Note:
⁎ p b 0.05.
⁎⁎ p b 0.01.
⁎⁎⁎ p b 0.001.
H. Li, S. Wang / Children and Youth Services Review 35 (2013) 1468–1475
Table 2
Summary of simultaneous multivariate regression analysis for variables predicting IAS
scores.
1471
Table 4
Summary of simultaneous multivariate regression analysis for variables predicting OGCAS
scores.
Variable
B
SEB
β
Variable
B
SEB
β
Male
Age
Educational level
Rumination
All-or-nothing thinking
On-line comfort
Short-term thinking
0.49
−0.09
0.39
0.11
0.02
0.05
0.15
0.25
0.16
0.19
0.05
0.04
0.07
0.04
0.12
−0.09
0.27
0.15⁎
0.04
0.07
0.27⁎⁎⁎
Male
Rumination
All-or-nothing thinking
On-line comfort
Short-term thinking
6.97
1.31
0.29
0.77
1.20
1.20
0.24
0.16
0.33
0.20
0.24⁎⁎⁎
0.25⁎⁎⁎
0.11a
0.14⁎
0.32⁎⁎⁎
Note:
⁎ p b 0.05.
⁎⁎⁎ p b 0.001.
with OGCAS scores as the dependent variable. These results indicated
that all the selected variables, with the exception of all-or-nothing
thinking (β = 0.11, p = 0.07) were significant predictors of OGCAS
scores, with the two most important predictors being rumination
(β =0.25, p b 0.05) and short-term thinking (β = 0.32, p b 0.001;
Table 4).
Having showed that rumination and short-term thinking were the
most significant predictors of online game addiction, and male are at
a greater risk of developing online game addiction than do female, the
next step was to examine the efficacy and application of CBT focused
on disputing these distorted beliefs for male online game addicts.
4. Study 2: the effectiveness of CBT in the treatment of online
game addiction
The protocols regarding intervention programs for Internet addiction in Chinese clients have not been well developed, and the effectiveness of existing psychological therapy remains unclear in this cultural
context (Shek, Tang, & Lo, 2009). The group CBT protocol used in
Study 2 was developed for the treatment of online game addiction in
adolescents at the Department of Psychology at the Renmin University
of China (Wang, 2009). Considering the contributory effects of cognitive
distortions such as rumination, all-or-nothing thinking, online comfort,
and short-term thinking to online game addiction, the aspects of CBT
employed in the current study were aimed towards disputing distorted
beliefs and replacing them with rational beliefs. We hypothesized that
group CBT can significantly improve the symptoms and severity of online game addiction compared to basic counseling, which include attending, observation, responding for reflecting thoughts and feelings,
and questioning. The purpose of basic counseling is to encourage online
game addicts to express their negative affect and to provide them affective support.
4.1. Method
4.1.1. Study design
The Review Board of the Sun-Yet Sen University in Guangzhou,
China, approved the protocol for Study 2. This study represents a
Table 3
Summary of bivariate associations between OGCAS scores and each predictor.
Variable
B
SEB
β
Male
Age
Educational level
Rumination
All-or-nothing thinking
On-line comfort
Short-term thinking
15.85
−0.04
−0.06
3.28
1.64
3.24
2.62
1.48
0.46
0.53
0.26
0.14
0.27
0.16
0.55⁎⁎⁎
−0.01
−0.01
0.62⁎⁎⁎
0.59⁎⁎⁎
0.60⁎⁎⁎
0.70⁎⁎⁎
Note:
⁎⁎⁎ p b 0.001.
Note:
a
P = 0.07.
⁎ p b 0.05.
⁎⁎⁎ p b 0.001.
longitudinal, randomized, controlled trial containing a CBT intervention
group and a control group that received basic counseling. A 2 by 2
mixed-effect factorial design was used to assess psychological outcome
measures.
4.1.2. Participants
The Center for Internet Addiction at Guangzhou Baiyun Hospital was
established in 2006. This center provides education and treatment to
people with online gaming addictions in the Guangdong Province of
China. In Study 2, 28 male participants, aged from 12 to 19 years, agreed
to participate in a randomized CBT trial. All participants were diagnosed
to be online game addicts by a senior psychiatrist based on the most recent revision of the Diagnostic and Statistical Manual of Mental Disorders 4th Edition criteria for substance abuse, (DSM-IV-TR; American
Psychiatric Association, 2000) and were not co-morbid for other psychiatric diseases, such as attention deficit hyperactivity disorder, major depression, anxiety, or schizophrenia.
The definition of online game addiction for this study was (1) excessive game play (more than 4 h per day/30 h per week; Ko et al., 2005);
(2) a score greater than 35 on the OGCAS (Li, Wang, & Wang, 2008; Li,
Wang, & Liu, 2008); (3) a score greater than 3 on the IAS-CR (Zhu &
Wu, 2004); and (4) maladaptive behaviors or distress due to a excessive
online game playing, including a difficulty in controlling playing duration, decreased academic performance or absence from school, interpersonal conflicts, borrowing money for purchasing items used in
online gaming, and feeling anxiety and distress upon withdrawal from
online game playing.
4.1.3. Measurement of emotional disorders
Zung's Self-Rating Depression Scale (SDS; 1965) is a self-report
scale that includes 20 items representing the most common clinical
symptoms of depression. Each item is rated on a 5-point Likert
scale that indicates the severity of a particular depression-related
symptom experienced during the past week, with scores ranging
from 1 (not at all) to 5 (extremely). The Chinese version of the SDS
is one of the most widely used measures of depression in this country, and its psychometric properties have been well documented (Liu
et al., 1994).
Zung's Self-Rating Anxiety Scale (SAS; 1971) is an easily administrated self-report scale that is used to examine mood alterations and
physical arousal related to anxiety. The 20 items of the SAS range
from scores of 1 (not at all) to 5 (extremely). The Chinese version of
the SAS has been demonstrated to be a valid tool for evaluating anxiety
levels in Chinese populations (Tao & Gao, 1994).
4.1.4. 6-week CBT procedure
Twenty-eight participants diagnosed with online game addiction
were randomly divided into the CBT and the control groups (14 per
group). Participants in the CBT group received a 12-session course of
CBT, with sessions twice a week. Each CBT session lasted 45 min and
was provided by a well-trained clinical psychologist. The control
group received a 45-min interview twice per week with a psychiatrist
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H. Li, S. Wang / Children and Youth Services Review 35 (2013) 1468–1475
in order to monitor their online game play activities and to provide
basic counseling. The severity of online game play, cognitive distortion,
depression, and anxiety symptoms scores were recorded for both
groups at baseline and at 6 weeks following the start of the study (the
CBT treatment period). These psychological measures were conducted
by a clinical nurse who was blind to group identity.
In the present study, the 12 CBT sessions (S) had the following
structure: S1–S2: Orientation — introducing the possible courses
and adverse consequences of online game addiction and setting
goals for treatment; S3: Rules — discussing the basic rules to be
followed in the therapy phrase; S4–S5: Introducing cognitive distortions closely related to online game addiction and disputing these irrational belief systems; S6–S7: Restructuring rational belief systems —
exposing motivation for excessive online game playing and irrational
belief systems pertinent to online game addiction, and replacing them
with rational belief systems; S8: Rating — establishing a plan to gradually cope with reinforcers of online game playing, including interpersonal conflicts, daily hassles, and learning-related stress, which may
be involved in a vicious cycle with cognitive distortions; S9–S10: Communication skills training; S11–S12: Review and relapse prevention —
discussing experiences and goals achieved in the therapy period and
how to monitor cognitive distortions and self-control while using the
Internet in the future.
4.1.5. Data analysis
The endpoint of intervention efficacy was considered to be
changes in psychological outcome variables measured between
pre- and post-treatment assessments, i.e. the significant interaction
effect of Pre–Post by Group. Baseline characteristics were compared
between groups using one-way ANOVA for quantitative variables
and Chi-squared test for qualitative variables, and these tests were
performed using SPSS version 17.0. The effects of the different interventions upon outcome measures were determined using two-way
mixed-effects repeated measures ANOVA (RMANOVA) with Group
as the between-subjects factor and Time (Time 1, pre-treatment;
Time 2, post-treatment) as the within-subject factor. Partial Eta
squared values (η2) were reported as measures of effect size. The
Group and Pre-Post main effect should be interpreted in light of significant two-way interactions.
4.2. Results
4.2.1. Demographic characteristics
A Chi-squared test and an independent-samples t-test were
conducted in order to examine the differences between the CBT and
control treatment groups. There were no significant differences between the groups at baseline in terms of age, education, the severity
of Internet use, the genre of online game play, presence of cognitive
distortions, anxiety, and depressive symptoms.
4.2.2. Changes in clinical measures during the 6-week treatment period
Table 5 summarizes the results of the repeated measures of the
analysis of variance (ANOVA). Both of group CBT and basic counseling
intervention showed a tendency towards lower post-treatment total
IAS scores, but the two treatment groups did not significantly differ
in the difference between the baseline and 6-week total IAS score
(p > 0.05). Both the CBT and basic counseling intervention groups
demonstrated significantly lower post-treatment OGCAS scores.
For the total CDC scores, all-or-nothing thinking scores, and online
comfort scores, the CBT intervention significantly lowered participants'
post-treatment outcome measures, while no Pre–Post difference was
found for the control group (Pre–Post by Group interaction effect, the
total CDC scores: F(1,26) = 10.60, p = 0.003, partial η2 = 0.30;
all-or-nothing thinking: F(1,26) = 7.14, p = 0.01, partial η2 = 0.22;
online comfort: F(1,26) = 6.99, p = 0.01, partial η2 = 0.22). For
short-term thinking scores, the CBT intervention marginally lowered
Table 5
Multivariate test of RMANOVA on significant psychological outcome measures.
Effects
F
df
p
Partial η2
Total IAS scores
Pre–Post
Group
Pre–Post × Group
2.74
0.79
0.47
1,26
1,26
1,26
0.11
0.38
0.90
0.10
0.03
0.01
Total OGCAS scores
Pre–Post
Group
Pre–Post × Group
11.89
1.41
1.99
1,26
1,26
1,26
0.002
0.25
0.17
0.32
0.05
0.07
Total CDC scores
Pre–Post
Group
Pre–Post × Group
0.95
0.23
10.60
1,26
1,26
1,26
0.34
0.64
0.003
0.04
0.01
0.30
Rumination
Pre–Post
Group
Pre–Post × Group
0.86
2.12
0.08
1,26
1,26
1,26
0.36
0.16
0.78
0.03
0.08
0.03
All-or-nothing thinking
Pre–Post
Group
Pre–Post × Group
0.51
0.31
7.14
1,26
1,26
1,26
0.48
0.58
0.01
0.02
0.01
0.22
On-line comfort
Pre–Post
Group
Pre–Post × Group
0.28
0.30
6.99
1,26
1,26
1,26
0.60
0.59
0.01
0.01
0.01
0.22
Short-term thinking
Pre–Post
Group
Pre–Post × Group
2.13
0.72
3.49
1,26
1,26
1,26
0.16
0.40
0.07
0.08
0.03
0.12
SDS scores
Pre–Post
Group
Pre–Post × Group
0.003
0.58
1.97
1,26
1,26
1,26
0.95
0.45
0.17
0.00
0.02
0.07
SAS scores
Pre–Post
Group
Pre–Post × Group
3.17
1.21
2.31
1,26
1,26
1,26
0.08
0.28
0.14
0.11
0.05
0.09
Note: RMANOVA: repeated measure analysis of variance. IAS: The Internet Addiction
Scale; OGCAS: The Chinese version of Online Game Cognitive Addiction Scale; CDC:
The Chinese version of Cognitive Distortions Scale; SAS: Zung's Self-rating Anxiety
scale; SDS: Zung's Self-rating depression scale. Partial η2: effect size estimate.
participants' post-treatment outcome measures, while no Pre–Post difference was found in the control group (Pre–Post by Group interaction
effect, F(1,26) = 3.49, p = 0.07, partial η2 = 0.12).
For the SDS scores, the mean change of Pre–Post measures was −4.6
in the CBT group and 4.22 in the control group. For the SAS scores, the
mean change of Pre–Post measures was −8.08 in CBT group, and 5.0
in control group. There was no significant difference on the Pre–Post
delta scores between the two intervention groups (p > 0.05). Changes
in psychological outcome variables measured pre- and post-treatment
and the significant interaction effect of Pre–Post by Group are shown
in Fig. 1.
In summary, CBT and basic counseling had different treatment effects
on the all-or-nothing thinking scores, online comfort scores and
short-term thinking scores, as were indicated by significant Time by
Group interaction effects. CBT and basic counseling had similar treatment
effects on the SDS scores and SAS scores, as were indicated by the mean
change of Pre–Post measures. Interestingly, CBT and basic counseling
had also similar treatment effects on IAS scores and OGCAS scores.
5. Discussion
Cognitive distortions, defined as irrational beliefs about, or inaccurate
perceptions of, oneself and/or of one's environment, may contribute to
H. Li, S. Wang / Children and Youth Services Review 35 (2013) 1468–1475
autonomy (Zhang, 2008), impulsive and aggressive behavior (Lemmens,
Valkenburg, & Peter, 2011; Nesbit & Conger, 2012), major depression
(Beck et al., 1979; Henriques & Leitenberg, 2002) and addictive disorders
(Kirisci, Tarter, Vanyukov, Reynolds, & Habeych, 2004; Toneatto, 2002).
The present study adds to the findings of previous Internet addiction
studies by examining the roles of cognitive distortions in the adolescent's
risk of online gaming addiction and provides empirical evidence for the
efficacy of CBT on this clinical population. We find that adolescents who
exhibit the cognitive distortion characteristics of rumination and shortterm thinking may be more susceptible to online game addiction. In addition, we find that adolescents who participate in CBT experience a significant decrease in the severity of their online game play addiction and CDC
scores following a 6-week treatment period compared to those of the
control group. Interestingly, the mean CDC scores, all-or-nothing thinking,
A
and online comfort in the CBT group decreased while these measures actually increased in the control group during the 6-week treatment period.
In both groups, the mean SAS and SDS scores in were improved following
the 6-week period.
In study 1, we found that IAS and OGCAS scores were significantly
higher for males than for females. These findings are consistent with
previous studies showing that males have a greater susceptibility to excessive Internet usage than do females (Charlton & Danforth, 2007;
Haddadain, Abedin, & Monirpoor, 2010; Soule, Shell, & Kleen, 2003). Interestingly, the CDC scores were also significantly higher in males compared to females in our study cohort. Considering that underlying
cognition distortions may contribute to online game addiction in adolescents, we speculated that the gender difference in online game addiction may at least partially result from differences in the presence of
B
Estimated Marginal
Means of Total IAS scores
45
4
40
3.5
CBT
Control
3
35
2.5
30
2
25
C
Estimated Marginal
Means of total IGCAS scores
50
4.5
1.5
1473
Pre-intervention
20
Post-intervention
D
Estimated Marginal
Means of total CDC scores
CBT
Control
Pre-intervention
Post-intervention
Estimated Marginal
Means of all-nothing thinking
36
13
34
12
32
11
30
10
CBT
Control
28
26
6
22
E
5
4
Pre-intervention
Post-intervention
Pre-intervention
F
Estimated Marginal
Means of all-nothing thinking
Post-intervention
Estimated Marginal
Means of on-line comfort
7
6.5
13
12
6
11
5.5
10
5
9
CBT
Control
8
7
CBT
Control
4.5
4
3.5
6
3
5
2.5
4
CBT
Control
8
7
24
20
9
Pre-intervention
Post-intervention
2
Pre-intervention
Post-intervention
Fig. 1. Change in psychological outcome variables measured at pre- and post-treatment and the significant interaction effect of Pre–Post by Group. A: IAS scores; B: OGCAS scores; C: the
total CDC scores; D: All-or-nothing thinking score; E: Rumination scores; F: On-line comfort scores; G: Short-term thinking scores; H: SDS scores; J: SAS scores.
1474
H. Li, S. Wang / Children and Youth Services Review 35 (2013) 1468–1475
G
H
Estimated Marginal
Means of short-term thinking
Estimated Marginal
Means of SDS scores
14
44
13
43
12
42
11
41
10
CBT
Control
9
40
39
8
38
7
37
6
36
5
35
4
I
Pre-intervention
CBT
Control
Pre-intervention
Post-intervention
Post-intervention
Estimated Marginal
Means of SAS scores
50
48
46
44
CBT
Control
42
40
38
36
Pre-intervention
Post-intervention
Fig. 1. (continued).
cognitive distortions, including rumination, all-or-nothing thinking, online comfort, and short-term thinking.
Our results indicated that adolescents, regardless of age and educational level, have equal possibilities of presenting with cognitive distortions associated with online gaming. Since adolescents, particularly
males, comprise a large percentage of online game players (Chou &
Tsai, 2007), they are at a greater risk of developing further online
game addiction in later adulthood than do older individuals. More importantly, the predictive value of rumination and short-term thinking
for the presence of online game addiction was highly significant in the
current sample. From these findings, it is reasonable to speculate that
adolescents who tend to use online games as a means of escape from
their real-life difficulties are more susceptible to online game addiction.
Another possible reason for this is the questions of CDC were specific to
online gaming playing, which may result in some certain conceptual
overlap between online addiction measured by the IAS and cognitive
distortions measured by CDC, such as getting enjoyment from the internet or online game playing and thinking a lot about internet use or online game playing. Future studies should add a unspecific cognitive
distortions measurement to further investigate the relationship between cognitive distortions and online game addiction.
The psychological outcome measurements in the current study
showed that the online game addiction symptoms as measured by IAS
and OGCAS, namely, distorted beliefs and negative emotions (i.e. depression and anxiety), were decreased following CBT intervention. In
addition, basic counseling was also helpful in reducing the addiction
symptoms and emotional disturbances, but did not resolve the presence
of cognitive distortions. Since the anxiety and depression that may result from Internet addiction can lead to compulsivity, withdrawal, and
craving symptoms, our findings indicate that the efficacy of group CBT
and basic counseling upon the severity of online game addiction
symptoms may be partially dependent upon alleviating emotional
symptoms. The changes we observed can be regarded as impressive in
view of the small sample size involved. Furthermore, although these
changes provide some support for the efficacy of group CBT on online
gaming addiction, it should be noted that not all cognitive distortion
characteristics, such as rumination, were significantly improved by
this therapy. The efficacy of group CBT has been elusive in dispelling
this species of cognitive distortion, in part because the practice of disputing rumination belief in the process of group CBT does not appear
sufficient. Another possible reason for this may be the low power of
the statistical tests in the current study due to the small sample size.
There are several limitations to the present study. First, the findings
of efficacy for CBT should only be considered as a preliminary analysis,
and as such must be interpreted with caution due to the small clinical
sample size and a lack of follow-up data. Second, the adolescents who
participated in the current CBT research were all male. Future studies
should verify the efficacy of CBT in female subjects. Third, the current
research represents a cross-sectional design and thus does not allow
conclusions to be drawn regarding a potentially causal relationship between cognitive distortions and online game addiction. Further research that includes concurrent individual interviews and longitudinal
designs is needed to more fully understand the influence of cognitive
distortions on online game addiction among adolescents.
Acknowledgments
This research was supported by a research grant from the National
Social Science Foundation of China (07CSH030) and the Basic Research
Funds in Renmin University of China from the Central Government of
China (12XNK039) to Dr. Huanhuan Li. Heartfelt thanks are given to
H. Li, S. Wang / Children and Youth Services Review 35 (2013) 1468–1475
all the participants in the study. We appreciate the assistance of Guangzhou Baiyun Hospital in conducting this research.
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