Development of the Internet addiction scale based on the Internet Gaming Disorder criteria suggested in DSM-5
Introduction
In the last two decades, the Internet has become a necessary part of our daily lives. Its influence has even intensified in the last decade due to the ease of Internet access through mobile phones and other devices. Moreover, people easily access excitative online-based contents such as games, gambling, shopping and pornography, and their excessive use has become a big problem. Excessive Internet use in relation to the aforementioned contents adversely influences academic outcomes, occupational success or family relationships.
In particular, overuse of the Internet can hinder teenager achievement in terms of developmental tasks. It could affect them continually even after they have grown up (Ko, Yen, Chen, Chen and Yen, 2005). As such, it is very important to identify teenagers who have early-stage Internet addiction problems so they can receive treatment interventions.
A global consensus has been reached regarding this concern related to Internet overuse, but many studies are still being performed on how to best understand and define this phenomenon. Some researchers conducted studies to suggest and validate the diagnostic criteria based on the substance use disorder and impulse control disorder. Other researchers developed a scale with items that reflect addictive use of Internet, and suggested sub-factors that gather some items showing similar patterns using statistical methods such as exploratory factor analysis. The suggested sub-factors usually share similar concepts with some diagnostic criteria for substance use disorder or pathological gambling (Lai, Mak, Watanabe, Ang, Pang and Ho, 2013).
The term ‘Internet addiction’ was first used by Goldberg (1996). He suggested the diagnostic criteria for Internet Addiction Disorder (IAD) that focused on tolerance, withdrawal and giving up or reduction of important social and occupational activities, based on the diagnostic criteria for substance abuse disorder in the Diagnostic and Statistical Manual of Mental Disorder, fourth edition (DSM-IV).
Young (2000), who developed the Internet Addiction Test (IAT) which is now being used worldwide, suggested the following diagnostic criteria: compulsive tendency to use the Internet, tolerance, withdrawal, unintended excessive use of the Internet, continuous desire to use the Internet, decreased interest in other activities and ignorance of the negative effects of excessive Internet use. However, further studies and other validation studies that were translated into other languages had different results when their construct validity was reviewed using factor analysis (Chang and Man Law, 2008, Ferraro et al., 2007, Jelenchick et al., 2012, Khazaal et al., 2008, Korkeila et al., 2010; Guan, Isa, Hashim, Pillai & Harbajan Singh, 2012; Widyanto, Griffiths, & Brunsden, 2001).
Davis, Flett, and Besser (2002) have developed an online cognitive scale based on the cognitive-behavioral model and suggested diminished impulse control, loneliness/depression, social comfort and distraction as the four subscales. Caplan (2002) developed the Generalized Problematic Internet Use Scale (GPIUS) based on Davis' (2001) cognitive-behavioral model and suggested mood alteration, social benefits, negative outcomes, compulsive use, too much time online, withdrawal and social control as the seven subscales.
Charlton and Danforth (2007) found that previous Internet addiction scales cannot distinguish high engagement but do not show any disadvantageous outcome and addiction on Internet games, but rather, overestimation about the addiction group can occur. As such, they classified the tendency toward Internet game addiction into addiction as the core criteria, and engagement as the peripheral criteria. The core criteria are withdrawal, conflict, and relapse and reinstatement, while the peripheral criteria are salience, euphoria and tolerance.
The South Korean government has recognized early the risks of Internet addiction and taken various actions, including prevention. In 2002, an Internet addiction scale (the K-scale) was developed, and its simple version was released after continuous research. The K-scale has seven subscales: daily life disturbance, disturbance of reality testing, automatic addictive thoughts, virtual interpersonal relationships, deviant behavior and tolerance. The simple version has four subscales: daily life disturbance, withdrawal, tolerance and preference of the virtual world. In addition to these standardized scales, many researchers attempted to independently develop Internet addiction scales or modify international scales, and validate them to screen and evaluate Internet addiction in Korea (Jang and Lee, 2007, Kang and Oh, 2001, Kim et al., 2008, Kim et al., 2003, Moon et al., 2004).
Park, Kang, Oh, and Kim (2001) suggested obsessive use and preoccupation, tolerance and withdrawal as the symptoms of Internet addiction. Kim et al. (2003) suggested dependency and withdrawal symptoms, negative effects and tolerance. Kang and Oh (2001) suggested five subscales as the symptoms of Internet addiction: preoccupation, obsessive use, relapse, tolerance/dependency and daily life disturbance. Moon et al. (2004) suggested six subscales: obsessive immersion in the virtual world, tolerance and obsessive access, pursuit of a virtual identity, loss of self-control, academic failure and physical problems, and damaged relationships with others.
As reviewed earlier, various concepts related to Internet addiction have been suggested by many researchers who developed a self-reporting scale or suggested diagnostic criteria based on the previous substance dependence scale or impulse control disorder. Although some subscales were commonly mentioned, no standardized criteria for diagnosis were suggested. Recently, Internet Gaming Disorder was added to Section 3 of DSM-V, which is widely used for mental disorder diagnosis in many countries. Despite the many studies on Internet overuse, there are no consistent diagnostic criteria, and such lack of criteria has led to inconsistent reporting related to the prevalence, progress and treatment of Internet overuse. DSM-V proposes nine diagnostic criteria, but it points out the limitation of the criteria of Internet addiction and the need for further studies (Table 1). These suggested criteria are expected to play an important role in future studies related to Internet addiction (Petry & O'Brien, 2013). This study was conducted to develop scale based on the IGD criteria and to pave the way for the development of a self-diagnostic scale that can be used as a standard in the future.
Section snippets
Participants
A total of 1192 first- (age 13) and second-year (age 14) students from two middle schools in Kangwon-do participated in this study. One hundred ten incomplete and inappropriate data were excluded while 1082 data were used for the analysis. The demographic data of the participants are shown in Table 2.
Each participant submitted a written informed consent form after receiving a full explanation of the study's purpose and procedure, as approved by the Institutional Review Board of Seoul St. Mary's
Inter-item consistency
The results showed that the internal consistency reliability for all 41 items was good (Cronbach's α = 0.994). However, when the internal consistency reliability of each factor was analyzed, Factors A (Cronbach's α = .499), B (Cronbach's α = .658) and F (Cronbach's α = .390) showed less than 0.7. In detail, item 4 in Factor A showed a − 0.096 item-total correlation, and item 6 in Factor B, − 0.001, which means that there was no correlation. Items 21 and 22 in Factor F showed a 0.261 item-total
Discussion
This study was conducted to develop a screening tool for Internet addiction based on the diagnostic criteria. To achieve this purpose, we developed a scale with items based on the diagnostic criteria of Internet Gaming Disorder (IGD) as suggested in DSM-V, and performed CFA to see if the items reflect the relevant concepts. Also, the correlation among factors was investigated to see if each criterion in the diagnostic criteria in DSM-V shows appropriate correlations. The results showed that the
Role of funding sources
Funding for this study was provided by HI12C0113. The Korean Health Technology R&D Project, Ministry of Health & Welfare, Republic of Korea had no role in the study design, collection, analysis or interpretation of the data, writing the manuscript, or the decision to submit the paper for publication.
Contributors
Authors Dai-Jin Kim and Hyun Cho designed the study. Author Hyun Cho wrote the protocol, conducted literature searches, provided summaries of previous research studies, conducted the statistical analysis, wrote the first draft of the manuscript and all authors contributed to and have approved the final manuscript. Also all authors were involved in the development of the Internet addiction scale which was gathered and items were selected by them.
Conflict of interest
All authors declare that they have no conflicts of interest.
References (29)
Problematic Internet use and psychosocial well-being: Development of a theory-based cognitive-behavioral measurement instrument
Computers in Human Behavior
(2002)- et al.
Factor structure for Young's Internet Addiction Test: A confirmatory study
Computers in Human Behavior
(2008) - et al.
Distinguishing addiction and high engagement in the context of online game playing
Computers in Human Behavior
(2007) A cognitive-behavioral model of pathological Internet use
Computers in Human Behavior
(2001)- et al.
Assessing the psychometric properties of the Internet Addiction Test (IAT) in US college students
Psychiatry Research
(2012) - et al.
Attached to the web — Harmful use of the Internet and its correlates
European Psychiatry
(2010) Impulsiveness subtraits: Arousal and information processing
(1985)- et al.
Validation of a new scale for measuring problematic Internet use: Implications for pre-employment screening
CyberPsychology and Behavior
(2002) - et al.
Internet Addiction Disorder: An Italian study
CyberPsychology & Behavior
(2007) - et al.
Evaluating structural equation models with unobservable variables and measurement error
Journal of Marketing Research
(1981)