Evaluation of the diagnostic criteria of Internet gaming disorder in the DSM-5 among young adults in Taiwan
Introduction
Internet gaming is one Internet activity. Excessive and prolonged Internet gaming results in negative consequences, such as impaired real-life relationships or academic performance (Kuss et al., 2013). Loss control of Internet gaming presents a cluster of cognitive and behavioral symptoms analogous to the symptoms of substance use disorder. As it is of significant public health importance, the DSM-5 proposed the diagnostic criteria of Internet gaming disorder (IGD) to define addiction to Internet gaming. It is classified under the conditions for further study of Section III and it is suggested that more evidence is necessary before it is included as a standard disorder in the DSM system (American Psychiatric Association, 2013).
The similarities in neuro-bio-psychosocial characteristics between IGD and substance use disorder (Kuss et al., 2013) are essential to determine the disorder classification of IGD. Impulsivity, a central factor involved in the etiology of addictive behaviors, has been reported to be associated with and predict IGD (Gentile et al., 2011, Metcalf and Pammer, 2013). Impaired response inhibition, error processing, cognitive flexibility, and decision-making have been reported in IGD and might contribute to loss of control and continued online gaming despite negative consequences (Littel et al., 2012, Pawlikowski and Brand, 2011, Zhou et al., 2012, Ko et al., 2014). IGD also shows a cue-induced brain craving response and implicit reaction in cognitive tasks similar to substance craving (Ko et al., 2013a, Ko et al., 2013b, Yen et al., 2011). Further, IGD shares similarities in comorbidities, such as social anxiety disorder, attention deficit and hyperactivity disorder and depression (Gentile et al., 2011, Ko et al., 2008, Kuss and Griffiths, 2011), and psychological factors, such as novelty seeking or low self-esteem (Ko et al., 2006, Ko et al., 2007, Kuss et al., 2013). These results indicate that IGD may share similarities in presentation or mechanism with substance use disorder. However, some essential factors, such as motivation or gaming characteristics, are specific to IGD (Kuss and Griffiths, 2011). Use of Internet gaming for immersion, achievement, escapism and socializing motives has been suggested to be associated with IGD (Billieux et al., 2011, Zanetta Dauriat et al., 2011). Thus, it is essential to develop a validated definition and evaluation tool to identify subjects with IGD for further detailed research of its nature and mechanisms.
However, most previously proposed diagnostic criteria were for a broad spectrum of addictive behaviors related to the Internet, but not specific for IGD. Loss of control of Internet use with impairment of psychosocial functions has been described as Compulsive Internet use (Sadock and Sadock, 2007), problematic Internet use (Shapira et al., 2000), Internet addiction (Ko et al., 2009b), and Internet use disorder in the proposed DSM-5 (American Psychiatric Association, 2012). Anderson used seven true-false questions that closely paralleled the DSM-IV criteria of substance dependence to define Internet dependence (Anderson, 2001). Young modified the DSM-IV criteria of pathological gambling to define pathological Internet use (Young, 1998). Shapira and colleagues proposed diagnostic criteria for problematic Internet use according to the concepts of impulse control disorder in the DSM-IV-TR (Shapira et al., 2000). However, these diagnostic criteria were established based on the researchers' reviews of the literature, and empirical evidence to support their contents and cut-off point is lacking. Tao and colleagues used “loss of interest in previous hobbies and entertainment as a result of Internet gaming” and “time consumption of at least 6 h per day on the Internet” as criteria for Internet addiction (Tao et al., 2010).
However, Internet use includes a variety of activities, such as gaming, cybersex, downloading, social networking, and gambling. The high heterogeneity makes it difficult to define these behaviors by distinct criteria. As there are factors, such as motivation factors or structure characteristics of individual Internet activities (Billieux, 2012), associated with addiction to specific Internet activities, it has been suggested that Internet addiction should be replaced by addictions to specific Internet activities (Starcevic, 2013). On the other hand, the general characteristics of the Internet, such as anonymity, high availability, or information and efficiency, might also be associated with Internet addiction (Chiang and Su, 2012). Further, it is also impractical to define addiction to every Internet activity as a distinct disorder. How to define the highly heterogenous spectrum of addictive behavior related to Internet activities deserves further research.
Ko and colleagues proposed the Diagnostic Criteria of Internet Addiction (DC-IA) for adolescents (Ko et al., 2005) and for college students (Ko et al., 2009b) based on empirical data collected by systemic diagnostic interview. A total of 13 candidate criteria according to the DSM-IV-TR criteria for impulse control disorder and substance use disorder and clinical experience were selected for testing of their diagnostic accuracy for Internet addiction among adolescents in a randomly selected sample from junior and senior high schools (Ko et al., 2005). Internet addiction was defined based on the clinical diagnosis of a psychiatrist in a semi-structure interviewing. The results demonstrated that nine criteria, including preoccupation, uncontrolled impulse, usage more than intended, tolerance, withdrawal, impairment of control, excessive time and effort spent on the Internet, and continued excessive use despite psychosocial problems, have a 79.3–85.9% diagnostic accuracy. Further analysis revealed that 6 or more criteria was the best cut-off point. It also raised the necessity of taking functional impairment and exclusion criteria into consideration to make a diagnosis based on the DC-IA. This results in diagnostic accuracy of 95.4%. Then, the DC-IA was validated again among college students, with diagnostic accuracy of 95.9% (Ko et al., 2009b). The DC-IA has been used in several studies of adolescents (Ko et al., 2009c) and young adults (Ko et al., 2013a). Further, the same criteria have been used to evaluate online gaming behavior to identify cases of Internet gaming disorder (Yen et al., 2011, Ko et al., 2013a, Ko et al., 2013b) to evaluate their neuropsychological characteristics. The revised diagnostic criteria of the DC-IA specific for online gaming behavior can be used as a reference to examine the validity of new criteria proposed for diagnosing Internet gaming disorder.
The criteria of IGD proposed in the DSM-5 include 9 items: preoccupation, withdrawal, tolerance, unsuccessful attempts to control, loss of interests, continued excessive use despite psychosocial problems, deceiving, escape, and functional impairment (American Psychiatric Association, 2013). The deceiving, escape, and preoccupation criteria are similar to the criteria of gambling disorder (American Psychiatric Association, 2013). The criterion of loss of interest was adopted from the criteria proposed by Tao et al. (2010). The other criteria are similar to those of substance use disorder in the DSM-IV. Five or more of the nine criteria should be fulfilled to diagnose IGD in the DSM-5. However, the DSM-5 suggests that optimal criteria and the threshold for the diagnosis of IGD should be determined empirically by further study (American Psychiatric Association, 2013). Thus, it is necessary to determine the diagnostic validity of individual criteria and determine the best cut-off point of the criteria for IGD based on empirical studies.
It is noteworthy that craving and irritability are not included in the diagnostic criteria of IGD in the DSM-5. The DSM-5 includes craving as one of the diagnostic criteria of substance use disorder (American Psychiatric Association, 2013). Research has found that craving forms a uni-dimensional latent trait for alcohol, cannabis, cocaine and heroin use (Hasin et al., 2012). Craving symptoms have also been reported in individuals with IGD (Ko et al., 2013a). The gaming cue-induced craving response drives the brain to activate the reward system (Ko et al., 2009a). A head-to-head comparison study of individuals with comorbid IGD and tobacco dependence also found that the gaming cue and tobacco cue induce similar brain activation over the hippocampus. This suggests that craving may play a similar psychopathological role in IGD and as in tobacco dependence (Ko et al., 2013b). However, no empirical study has examined the role of craving in diagnosing IGD. Further study is needed to examine this issue and provide information for the DSM system to consider whether to include craving as one of the diagnostic criteria of IGD, as in substance use disorder.
Individuals with IGD become irritable and angry if they are prevented from using a computer or returning to the game (American Psychiatric Association, 2013). Many online games, particularly massive multiplayer online role-playing games, provide a permanent virtual world that could satisfy a wide range of basic needs (Billieux et al., 2013). Game-related events will keep going if a player disconnects or is disturbed by events in the “real world”. This disconnection might result in loss of gains in the permanent gaming world and make a player irritable owing to disturbance from the “real world”. As the symptoms usually arise immediately when Internet use is interrupted, it should not be classified as a withdrawal symptom. As irritability is so prevalent in individuals with IGD, its diagnostic value for IGD should be examined to determine whether it is a candidate criterion for IGD.
The aims of this study were to: 1) evaluate the diagnostic validity of individual criteria of IGD in the DSM-5 and the criteria of craving and irritability by using the DC-IA as a reference; and 2) evaluate the best cut-off points of criteria of IGD in the DSM-5.
Section snippets
Participants
The participants were composed of three subgroups, including those who had current IGD (the IGD group), those who have had IGD but were in a remitted state (the remission group), and those who had never had IGD (the control group). All participants in the three groups were recruited by advertisement from September 2011 to June 2012. The recruitment criteria of the participants in the IGD group included: 1) young adults with an age ranging from 20 to 30 years and an educational level greater
Results
Table 1 presents the results of comparisons of gender, age, educational level, varieties of and time spent on Internet gaming, and severities of Internet gaming on the CIAS and Internet gaming urge on the QGU-B among participants of the IGD, remission, and control groups. There were no significant differences in gender, age, and educational level among the three groups. The IGD group spent the most time on Internet gaming on weekdays and weekends, followed by the remission and control groups.
Diagnostic validity of individual criteria of IGD in the DSM-5
This was the first study to test the diagnostic performance of IGD criteria in the DSM-5. The participants of the IGD group spent more time on Internet gaming on weekdays and weekends than those of the remission and control groups. Internet gaming may occupy daily time of individuals with IGD and prevent them from doing other things. This may result in impaired daily life function. In these evaluations, 64.8% of the participants with IGD based on the DSM-5 criteria had severe problems with
Contributors
Ju-Yu Yen designed the study and wrote the protocol. Cheng-Fang Yen and Sue-Huei Chen managed the literature searches and analyses. Peng-Wei Wang and Cheng-Sheng Chen undertook the statistical analysis, and Chih-Hung Ko wrote the first draft of the manuscript. All authors contributed to and have approved the final manuscript.
Role of the funding source
This study was supported by grants from the National Science Council in Taiwan (NSC 102-2314-B-037-005), Kaohsiung Municipal Hsiao-Kang Hospital (KMHK-101-009), and Kaohsiung Medical University Hospital (KMUH-99-9R50). The funding sources have no role in the design, processing, data analysis, and publication process of the study.
Conflict of interest
All authors declare that they have no conflicts of interest.
Acknowledgments
This study was supported by grants from the National Science Council in Taiwan (NSC 102-2314-B-037-005), Kaohsiung Municipal Hsiao-Kang Hospital (KMHK-101-009), and Kaohsiung Medical University Hospital (KMUH-99-9R50).
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