Internet Addiction

A Handbook and Guide to Evaluation and Treatment

Kimberly S. Young, Cristiano Nabuco de Abreu, Kimberly S. Young, Cristiano Nabuco de Abreu

• Publisher: Wiley
• Year: 2010
• ISBN:
  9780470892268
• Edition: 1
• Topic: Psychology
• Subtopic: Addiction in Psychology
• Index: Psychology

Internet Addiction: A Handbook and Guide to Evaluation and Treatment

"This book provides cutting-edge coverage by expanding the field to include specific problems such as online gaming, cybersex addiction, and gambling addiction. Its extensive attention to dealing with adolescents is essential, given the rapid rise in media and technology use by both Net Generation young adults and iGeneration teenagers. I am thrilled to have this invaluable, comprehensive, well-written resource for my own work and recommend it to people who need to understand this unique form of addiction."
— Dr. Larry Rosen, Past Chair and Professor of Psychology at California State University, Dominguez Hills, author of Rewired: Understanding the iGeneration and the Way They Learn and Me, MySpace, and I: Parenting the Net Generation

"Our clients come to us when online pornography, video gaming, social networking, gambling, and surfing create untenable disruptions in their lives. If we do not understand what we are seeing and how to address it, we will not be able to provide the help they need. This book provides the practical information clinicians can use to assess and treat this growing problem."
— Hilarie Cash, PhD, coauthor of Video Games and Your Kids: How Parents Stay in Control, and cofounder of reSTART: Internet Addiction Recovery Program

" Internet Addiction: A Handbook and Guide to Evaluation and Treatment provides an integrated and current overview of the different types of Internet addiction-gaming addiction, gambling addiction, and cybersex addiction. The authors deserve ample praise in providing such a comprehensive and informative guide for Internet addiction."
— Ran Tao, MD, Professor and Director, and Xiuqin Huang, MD, Associate Professor, Treatment Center for Internet Addiction, General Hospital of Beijing Military Region, China

The first empirically informed reference for defining, assessing, diagnosing, and treating problematic Internet use Comprehensive and timely, Internet Addiction explores:

• Validated assessment tools to differentiate normal from compulsive patterns of computer and online usage
  
  

• The most addictive or problematic online activities
  
  

• Epidemiology and subtypes of Internet addiction such as online pornography, Internet gambling, and online gaming
  
  

• Current theories on the risk factors associated with the development of an addictive disorder related to Internet usage
  
  

• Evidence-based treatment strategies for helping clients of various ages, taking into account main presenting problems and individual situations and circumstances
  
  

International in scope and empirically based, the cultural and global impact of this subject is discussed, introducing practitioners to the latest clinical implications, assessment methods, and treatment approaches in working with clients suffering from this emerging addictive disorder.

Part I

Understanding Internet Behavior and Addiction

Chapter 1

Prevalence Estimates and Etiologic Models of Internet Addiction

KIMBERLY S. YOUNG, XIAO DONG YUE, and LI YING

INTERNET ADDICTION was first researched in 1996, and findings were presented at the American Psychological Association. The study reviewed over 600 cases of heavy Internet users who exhibited clinical signs of addiction as measured through an adapted version of the DSM-IV criteria for pathological gambling (Young, 1996). Since then, subsequent studies over the past decade have examined various aspects of the disorder. Early studies attempted to define Internet addiction and examined behavior patterns that differentiated compulsive from normal Internet usage. More recent studies examined the prevalence of Internet addiction and investigated the etiologic factors or causes associated with the disorder. Much of this examined the impact of computer-mediated communication on the way people will adapt to interactive features of the Internet, and initial studies from the United States spread into the United Kingdom and countries such as Russia, China, and Taiwan. As the problem has become more widespread, little is still understood as to the reasons why people become addicted to the Internet. This chapter presents the data associated with prevalence of Internet addiction, as available in various countries, to gather a sense of the scope of the problem. The chapter also provides the theoretical frameworks to understand the etiologic models or causal factors associated with the development of Internet addiction. From the academic perspective, this chapter helps identify future areas of research as new studies in the field continue to emerge. From the mental health perspective, the chapter will assist clinicians in developing more empirically sound methods to assess and potentially treat Internet-addicted clients.

PREVALENCE ACROSS CULTURES

Early research has investigated the prevalence of addictive use of the Internet. In one of the first studies, Greenfield (1999) partnered with ABCNews.com to survey Internet users. From 17,000 responses, the study estimated that 6% of Internet users fit the profile of Internet addiction. While this study relied on self-reported data, it did include a cross-sectional population and was considered one of the largest psychological surveys conducted solely on the Internet. Another well-known U.S. study, conducted by a team of researchers at Stanford University Medical Center, found that one in eight Americans suffered from one or more signs of Internet addiction (Aboujaoude, Koran, Gamel, Large, & Serpe, 2006).

Studies among college populations showed slightly higher prevalence rates than found in the general population of Internet users. Using various versions of the DSM-based criteria, at the University of Texas, Scherer (1997) found 13% of 531 campus students surveyed exhibited signs of Internet dependency. Morahan-Martin and Schumacher (1999) found that 14% of students at Bryant College in Rhode Island met the criteria, and Yang (2001) estimated that 10% of students met the criteria at the University of Taiwan. Conclusions suggested that college students had easier access to the Internet and it was more encouraged, contributing to the higher prevalence of addictive use on campuses.

Among adolescents, a study in Finland investigated the prevalence of Internet addiction among 12- to 18-year-olds. Findings suggested that 4.7% among girls met the definition of Internet addiction as assessed by Young's Internet Addiction Diagnostic Questionnaire (1998), and of boys 4.6% met the definition. Studies related to the prevalence of specific types of Internet abuse also emerged by the late 1990s. Studies on online sexual activities were the most prevalent, and estimates based on survey data showed that 9% of users fit signs of addiction related to sexually explicit material on the Internet (Cooper, 2002).

In 2001, Bai, Lin, and Chen reported the results of a survey to determine the prevalence of Internet addiction disorder among visitors to a virtual mental health clinic where 100 volunteer mental health professionals provide, at no charge, online answers to visitors' questions about mental problems. During the study period all visitors to the virtual clinic completed Young's eight-item Internet Addiction Diagnostic Questionnaire. Among the 251 clients, 38 clients or 15% met criteria for Internet addiction disorder. Clients who met the criteria did not differ significantly from those who did not in age, gender, education, marital status, occupation, or impending diagnosis. However, the rate of comorbid substance use disorder was significantly higher among clients who met the criteria for Internet addiction disorder than among those who did not.

In 2003, Whang, Lee, and Chang investigated the prevalence of Internet overuse in Korea. They used a modified version of Young's Internet Addiction Scale, and 13,588 users (7,878 males, 5,710 females), out of 20 million from a major portal site in Korea, participated in this study. Among the sample, 3.5% had been diagnosed as Internet addicts (IAs), while 18.4% of them were classified as possible Internet addicts (PAs).

A study, I-Cube 2006, conducted by the Internet & Mobile Association of India, covering 65,000 individuals by household survey in 26 cities in India, says that about 38% of Internet users in that country have shown signs of heavy usage (about 8.2 hours per week). Young males, especially college students, form the major chunk of Internet user base. Indians go online for a number of activities, including e-mail and instant messaging (98%), job search (51%), banking (32%), bill payment (18%), stock trading (15%), and matrimonial search (15%).

There are limited numbers of studies estimating how common the issue of Internet addiction is in India. Kanwal Nalwa, PhD, and Archana Preet Anand, PhD, of the department of psychology, Punjabi University in India, conducted a study for preliminary investigation of the extent of Internet addiction in schoolchildren 16 to 18 years old in India (Nalwa & Anand, 2003). They identified two groups, dependents and nondependents. Dependents were found to delay other work to spend time online, lose sleep due to late-night logons, and feel life would be boring without the Internet. Not surprisingly, dependents spent more time online and scored higher on loneliness measures than the nondependents.

The understanding that Internet use can be a disorder is still in its initial stages in India. Since 2007, certain educational institutions, such as the Indian Institutes of Technology (IITs), a group of leading engineering universities, have been restricting campus Internet use during night hours because of reports of some suicides being linked to the presumed antisocial behavior that excessive Internet use promotes (Swaminath, 2008).

According to the most recent Statistical Report on Internet Addictions in China (Cui, Zhao, Wu, & Xu, 2006) by the China Youth Association for Internet Development, adolescent Internet addicts in China make up about 9.72% to 11.06% of the total number worldwide of adolescent Internet users. Specifically, of 162 million Internet users in China, those users who are younger than 24 years old occupy approximately 63% of the total number of Internet users, which amounts to about 100 million. Of these 100 million young users, about 9.72% to 11.06% are serious addicts, amounting to about 10 million young people.

Prevalence statistics vary widely across cultures and societies. In part, researchers are utilizing various instruments to define Internet addiction, making it harder to have consistency across studies. Further, these studies are confounded by various methodologies, some using online survey data posted to the World Wide Web using cross sections of populations, and some only targeting a specific campus or university. Generally, we can say that it seems that the prevalence of Internet addiction is the lowest among adolescents, with ranges of 4.6 to 4.7%. That number goes up among the general population of Internet users, with ranges of 6 to 15% of the general population fitting the signs of addiction; and it goes up to 13 to 18.4% among college students, who appear to be the most at risk. These numbers estimate the scope of the problem and suggest that a significant proportion of online users may suffer one or more signs of Internet addiction.

ETIOLOGIC FACTORS

Addictions are defined as the habitual compulsion to engage in a certain activity or utilize a substance, notwithstanding the devastating consequences on the individual's physical, social, spiritual, mental, and financial well-being. Instead of addressing life's obstacles, tackling daily stress, and/or confronting past or present trauma, the addict responds maladaptively by resorting to a pseudo coping mechanism. Typically, addiction manifests both psychological and physical characteristics. Physical dependence occurs when an individual's body develops a dependence on a certain substance and experiences withdrawal symptoms upon discontinuing the consumption, such as drugs or alcohol. While initially an addictive substance induces pleasure to the user, his or her continued consumption is driven more by a need to eliminate the anxiety brought about by its absence, thus leading the individual to compulsive behavior. Psychological dependency becomes evident when the addict experiences withdrawal symptoms such as depression, cravings, insomnia, and irritability. Both behavioral addiction and substance addiction usually give rise to psychological dependence. The following outlines various models proposed to explain Internet addiction related to the psychological dependency. As a behavioral addiction, the focus on psychological issues that increase consumption of the Internet is helpful to aid in clinical understanding of why people overuse.

Cognitive-Behavioral Model

Caplan (2002) viewed technological addictions as a subset of behavioral addictions; Internet addiction featured the core components of addiction (i.e., salience, mood modification, tolerance, withdrawal, conflict, and relapse). From this perspective, Internet addicts displayed a salience for the activity, often experiencing cravings and feeling preoccupied with the Internet when offline. He also suggested that using the Internet as a way to escape troubling feelings, developing a tolerance for the Internet to achieve satisfaction, experiencing withdrawal when reducing Internet use, suffering from increased conflicts with others because of the activity, and relapsing back to the Internet were also signs of addiction. This model has been applied to behaviors such as sex, running, food consumption, and gambling (Peele, 1985; Vaillant, 1995) and is useful to examine pathological or addictive Internet use.

Davis (2001) introduced a cognitive-behavioral theory of pathological Internet use (PIU) that attempts to model the etiology, development, and outcomes associated with PIU. Davis characterizes PIU as more than a behavioral addiction; instead he conceptualizes PIU as a distinct pattern of Internet-related cognitions and behaviors that result in negative life outcomes. Davis proposes that there are two distinct forms of PIU: specific and generalized. Specific PIU involves overuse or abuse of content-specific functions of the Internet (e.g., gambling, stock trading, viewing pornography). Moreover, Davis argues that such stimuli-specific behavioral disorders would likely be manifested in some alternative way if the individual were unable to access the Internet. Generalized PIU is conceptualized as a multidimensional overuse of the Internet itself that results in negative personal and professional consequences. Symptoms of generalized PIU include maladaptive cognitions and behaviors related to Internet use that are not linked to any specific content. Rather, generalized PIU occurs when an individual develops problems due to the unique communication context of the Internet. In other words, the person is drawn to the experience of being online in and of itself, and demonstrates a preference for virtual, rather than face-to-face, interpersonal communication.

Within this context, researchers have suggested that moderated and controlled use of the Internet is most appropriate to treat Internet addiction (Greenfield, 2001; Orzack, 1999). Specifically, cognitive behavioral therapy (CBT) has been suggested as the preferred mode of therapy treatment for compulsive Internet use (Young, 2007). CBT is a familiar treatment based on the premise that thoughts determine feelings. In one study of 114 patients, CBT was used to teach patients to monitor their thoughts and identify those that trigger addictive feelings and actions while they learn new coping skills and ways to prevent a relapse. CBT required three months of treatment or approximately 12 weekly one-hour sessions. The early stage of therapy is behavioral, focusing on specific behaviors and situations where the impulse-control disorder causes the greatest difficulty. As therapy progresses, there is more of a focus on the cognitive assumptions and distortions that have developed and the effects of the compulsive behavior.

Specifically, research suggests that the focus of recovery should examine both computer behavior and noncomputer behavior (Hall & Parsons, 2001). Computer behavior deals with actual online usage with a primary goal of abstinence from problematic applications while retaining controlled use of the computer for legitimate purposes. For example, a lawyer addicted to Internet pornography would need to learn to abstain from adult web sites, while still being able to access the Internet to conduct legal research and to e-mail clients. Noncomputer behavior focuses on helping clients develop positive lifestyle changes for life without the Internet. Life activities that do not involve the computer, such as offline hobbies, social gatherings, and family activities, are encouraged. Similarly to food addiction, where recovery can be objectively measured through caloric intake and weight loss, online addicts can objectively measure success through maintaining abstinence from problematic online applications and increasing meaningful offline activities. Once a baseline has been established, behavioral therapy is used to relearn how to use the Internet to achieve specific outcomes, such as moderated online usage and more specifically abstinence from problematic online applications and controlled use for legitimate purposes. Behavior management for both computer usage and adaptive noncomputer behavior focuses on current online behavior.

From a cognitive perspective, addictive thinkers will for no logical reason feel apprehensive when anticipating disaster (Hall & Parsons, 2001). While addicts are not the only people who worry and anticipate negative happenings, they tend to do this more often than other people. Young (1998) first suggested that this type of catastrophic thinking might contribute to compulsive Internet use in providing a psychological escape mechanism to avoid real or perceived problems. Subsequent studies hypothesized that other maladaptive cog...