Cognitive-Behavioral Approaches to Outpatient Treatment of Internet

Cognitive-Behavioral Approaches to Outpatient Treatment of Internet
Addiction in Children and Adolescents
Daniel L. King,1 Paul H. Delfabbro,1 Mark D. Griffiths,2 and Michael Gradisar3
1
The University of Adelaide
Nottingham Trent University
3
Flinders University
2
Excessive and potentially addictive use of the Internet among children and adolescents has emerged
as a major concern in recent times. Internet addiction is often conceptualized as an impulse control
disorder, with features similar to pathological gambling. However, there remains considerable debate
about the core components, etiological processes, course, and maintaining factors of the disorder. This
article presents a case study of a 16-year-old male with generalized pathological Internet use. Critical
issues relevant to case conceptualization, assessment, and choice of therapy are examined. Although
the evidence base is limited in this emerging area of clinical psychology, we provide a summary of
C 2012 Wiley Periodicals,
empirically supported cognitive-behavioral techniques for Internet addiction. Inc. J. Clin. Psychol: In Session 68:1185–1195, 2012.
Keywords: Internet addiction; cognitive-behavioral therapy; treatment; adolescence
Introduction
Over the last decade, the number and quality of research studies on Internet addiction have
steadily increased, in parallel to the burgeoning popularity of the Internet itself. The proposed
but as yet unrecognized disorder now has a presence within a range of peer-reviewed journals
covering specialist areas including (but not limited to) clinical, social, cognitive, developmental,
health, and organizational branches of psychology. Internet addiction disorder is often conceptualized as an impulse control disorder (Sim, Gentile, Bricolo, Serpollini, & Gulamoydeen,
2012), with features of its clinical presentation similar to pathological gambling. Internet addiction is thought to comprise several subtypes, including cyber-sexual preoccupations, online
video gaming, gambling, shopping, browsing, emailing, and social networking (Block, 2008).
However, there remains considerable debate about the core components, etiological processes,
course, and maintaining factors of the disorder (Griffiths, 2008; Turner, 2008; Wood, 2008).
Given this variability in the definition and methods of assessment of Internet addiction, it is not
surprising that estimated prevalence rates of the disorder vary significantly, ranging from 0.3%
to over 10% (King, Delfabbro, & Griffiths, 2012).
Currently, there are no plans to include Internet addiction (or a similar diagnosis) within the
spectrum of addictive disorders in the upcoming Diagnostic and Statistical Manual of Mental
Disorders Fifth Edition (DSM-5), but it may be noted within an appendix as being worthy
of further empirical investigation. Interestingly, despite the prominence and ubiquity of the
Internet in modern society, there have been only two proposed revisions to the current DSM
specifically related to the Internet and/or online behavior. These revisions refer to the following
disorders: (a) illness anxiety disorder (repeatedly seeking reassurance online about bodily signs
of illness) and (b) hypersexual disorder (viewing and downloading of pornographic images and
videos). Arguably, these revisions may be considered more easily accommodated by the existing
nomenclature given their attachment to a pre-existing disorder and/or established body of
knowledge.
Please address correspondence to: Daniel L. King, School of Psychology, Level 4, Hughes Building, The
University of Adelaide, Adelaide, SA 5005, Australia. E-mail: [email protected]
C 2012 Wiley Periodicals, Inc.
JOURNAL OF CLINICAL PSYCHOLOGY: IN SESSION, Vol. 68(11), 1185–1195 (2012)
Published online in Wiley Online Library (wileyonlinelibrary.com/journal/jclp). DOI: 10.1002/jclp.21918
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Proponents of an Internet addiction diagnosis appear to be road-blocked by the lack of a
knowledge base demonstrating consistent findings. In particular, the lack of a common framework for Internet addiction has prevented a unified research effort, such that many published
studies differ conceptually and methodologically. Side-by-side comparison of findings thus becomes difficult, if not impossible. Additionally, Blaszczynski (2006) has highlighted a specific
need for evidence of impaired control and neuroadaptation processes associated with Internet
addiction, rather than obtaining further evidence of the adverse consequences of prolonged
Internet use. In sum, the Internet addiction field appears to be caught in a classic Catch-22 situation: Further empirical research is needed to establish its legitimacy, but lacking a standardized
approach to assessment much research is often flawed in principle.
In the last 15 years, there have been several proposals for standard diagnostic criteria for
Internet addiction. For the most part, these definitions and/or conceptualizations of the disorder
have been modelled (in part or entirely) on the DSM-IV criteria for pathological gambling, the
DSM-IV criteria for substance dependence, the International Classification of Diseases 10th
Revision (ICD-10) criteria for substance dependence, or a combination of these criteria. A
recent review by Sim et al. (2012) has attempted to develop a common framework and criteria
for Internet addiction. The authors reviewed over 40 published studies and concluded that the
most valid and reliable way of conceptualising Internet addiction was using adapted DSMIV criteria for pathological gambling. Sim et al. claimed that these criteria were also suitable
for classifying pathological “computer use” and “video gaming,” by substitution of the term
“gambling.”
Although scholarly agreement on this method of assessment would advance the field, it has
been argued that there remains a need to distinguish between addictions on the Internet, and
addictions to the Internet. For example, Griffiths (2008) argues most “Internet addicts” are
not addicted to the Internet itself, but use it as a medium to fuel other addictions. In short, a
gambling addict who uses the Internet to gamble is a gambling addict not an Internet addict
(Blaszczynski, 2006). The Internet is just the place where they conduct their chosen (addictive)
behavior. Clinicians should therefore be mindful of whether problematic behavior related to the
Internet is in fact a client’s primary psychological problem, and not an unhelpful coping strategy
or safety behavior arising from other psychopathology (e.g., social anxiety). While Internet
use may still be relevant to case conceptualization and treatment in such cases, nonprimary
problems related to the Internet may not be appropriately catered to by treatment techniques
and approaches for addiction.
Our intention thus far has been to orient the reader to the conceptual confusion facing both
experts and relative newcomers in the emerging field of Internet addiction. This background
information is useful to bear in mind when considering choice of assessment and therapy
resources for clients with addictive tendencies on the Internet. The aim of this article is to
present a case study of a young male Internet addict, as conceptualized by an accepted cognitivebehavioral therapy (CBT) model of Internet addiction (Davis, 2001). This case example is
intended as a vehicle for discussion of assessment and treatment options for Internet addiction.
As such, this paper will highlight what is (and what is not) currently known in this emerging
clinical area, and will make a series of recommendations for clinicians.
Case Illustration
Presenting Problem and Client Description
John is a 16-year-old male who lives at home with his two parents in Adelaide, South Australia.
John spends up to 10 hours per day on the computer in his bedroom, browsing a variety of news
and entertainment websites, chatting on online forums, playing online video games (including
massively multiplayer online role playing games), and downloading movies, television shows,
and music for personal use. John has been familiar with computer technology since he was a
small child. However, he became more intensely engaged when he was gifted his own personal
computer on his 13th birthday. John recalls vividly the excitement of owning his first computer
and spending that day and most of the night learning its capabilities and going online.
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John’s parents noticed the frequency of John’s computer activities steadily increased within
a subsequent period of a few weeks. Initially, John’s preoccupation with the computer was
dismissed as a temporary “phase.” However, it became apparent that John was using all available
time at home on the computer. John’s parents attempted to reduce his computer time, using verbal
commands/threats or removing the power cable. John’s parents became engaged in a cycle of
removing and then restoring computer access to placate John’s frustrated complaints about
being bored or being treated “unfairly.” Permitting John to use the computer on his terms was
eventually seen as a way of avoiding confrontation and maintaining family harmony. In the past
year, John’s parents have given up completely on restricting access and allowed the computer to
be kept permanently in John’s bedroom.
John regularly stays up late (i.e., 2 a.m.) engaging in online activities and has difficulty in
waking for school. He often skips family gatherings to use his computer. Similarly, he has
stopped attending after-school training for a local basketball team, leading to being dropped
from the team. John’s mealtimes are irregular, and he often eats at his computer. He routinely
sleeps in late on weekends. He consumes several caffeine drinks each day to stay up late using
the computer and to help feel more alert in the morning. To avoid leaving his room to go to
the bathroom, John urinates in plastic bottles stored under his desk. When not on his computer
at home, John uses his mobile phone to maintain access to the Internet. He is often agitated in
situations where access to the Internet is not available, but uses this time to think about and plan
the next activity on his computer. Although John demonstrates a great deal of knowledge about
the Internet and online activities, he has difficulty in describing procedurally how he spends his
time online. He explains that, when online, he is often engaged in multiple tasks at once and will
lose track of time. John admits that sometimes he forgets or cannot be bothered to do things
due to spending time on the computer.
John’s school attendance is irregular and he often skips afternoon classes. His school grades
have declined significantly in the past year, and teachers have noted a lack of attention and
concentration in class. John is considered intelligent but does not apply his natural ability to
schoolwork. He neglects his homework, household chores, and personal hygiene. When he was
15 years old, he dated a girl at his school for a period of less than one month. The relationship
ended when John repeatedly failed to show for gatherings organized by the girlfriend. John
was playing video games at the time. John is not “popular” at his school, but does have one
friend. Their interaction outside of school is usually spent online in chat programs or playing a
competitive video game. John shows little interest in noncomputer-related activities and has not
expressed any ambitions (e.g., career or travel) for adult life.
Case Formulation
As with any psychological disorder, the client’s history forms the most important basis for
diagnosing Internet addiction. John reports a habit of engaging in a variety of nonessential
online activities for between 35 to 70 hours per week in the past 12 months. Although research
evidence suggests frequency of computer use is not a perfect indicator of problems, adolescent
media use for nonhomework purposes in excess of 2 hours/day is likely to indicate adverse social
and emotional consequences. Assessing how the Internet is used (i.e., the functional relationship
between user and computer) generally offers a much better insight into risk of clinical problems
(Young & de Abreu, 2011). For example, adolescents with addictive tendencies on the Internet
tend to spend abnormally long periods of time engaged in solitary online activities (e.g., browsing
or downloading), engaged in communication with strangers, and/or browsing sites with no clear
purpose in mind.
John’s first encounter with a computer at 13 years of age is noteworthy as an early critical
event. John recalls first owning a computer as being personally significant (other life activities
were instantly seen as less important) as well as emotionally gratifying (“exciting”). Theories
of addiction typically describe an addict’s first encounter with their addictive object or activity
of choice as an “aha!” moment, a moment of profound self-discovery. An addict may reflect,
“Where has this been all my life?” Many adult pathological gamblers began their gambling
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Journal of Clinical Psychology: In Session, November 2012
Figure 1. Davis’ (2001) cognitive-behavioral model of PIU.
career at an early age, and usually can recall experiencing a sizeable win that triggered automatic
thoughts of self-efficacy (e.g., “I am successful” or “I am a winner”) as well as strong emotions.
Similarly, many pathological online video gamers can recall the very first video game they
played and having positive emotions associated with the rewards and/or challenge involved.
Kouimtsidis, Reynolds, Drummond, Davis, and Tarrier (2007) explain that positive outcome
expectancy beliefs–those beliefs that good things will happen when engaged in the addictive
behavior (e.g., “I will feel better if I go online”)–are often formed in the early stages of addiction.
Positive expectancy beliefs make it difficult to resist the addictive activity in high-risk situations
(i.e., in the presence of Internet cues, social pressure to go online, or when feeling depressed or
anxious).
Some models of Internet addiction prioritize adverse consequences of prolonged Internet use.
Because of this, some forms of excessive Internet use, although harmful, may be misclassified as
an addiction. Davis’ (2001) model is useful in conceptualizing a client’s Internet use because it
may determine whether such use is the client’s primary problem. The model places an emphasis
on maladaptive cognitions underpinning pathological Internet use (PIU; i.e., Internet addiction),
thus making it useful for CBT approaches to treatment. The model distinguishes two types of
PIU. The first type is specific PIU, which refers to overuse of specific Internet functions, such
as email, pornography, shopping, or gambling. Such addictive tendencies are assumed to occur
in the absence of the Internet. The second type is generalized PIU, which refers to a general,
multidimensional overuse of the Internet and includes wasting time online.
John’s case indicates generalized PIU due to (a) his use of several different functions of the
Internet, (b) his social isolation, and (c) procrastination and time-wasting tendencies (i.e., lack
of a direct purpose of going online). It is likely that John’s problems may not have developed
(or would not be as severe) in the absence of the Internet. Further applying the model (see
Figure 1), John’s PIU is maintained by two core processes: distorted thoughts/thought processes
and reinforcement. Problematic cognitions may refer to the self, others, or the world. Like
depression, thoughts about the self that maintain PIU are generally characterized by negative
self-evaluation, self-doubt, and low self-efficacy. For example, these thoughts may include “I am
only good on the Internet,” “I am a worthless nobody when offline, but online I am important,”
and “I am a failure in the real world.”
Similarly, problematic Internet use is often maintained by negative evaluations and all-ornothing statements about the world, such as “The Internet is the only good place available to me”
and “People in the real world always treat you badly.” Distorted thoughts are triggered whenever
CBT Approaches
1189
the Internet or an associated stimulus is present. An early step in developing a conceptualization
would be to identify automatic thoughts and processes when going online and those situations
that precipitate Internet use.
John’s online use is also maintained by the many rewarding aspects of the Internet. Reward
features are less important in understanding the nature of PIU but can be useful in identifying
“high-risk” aspects of the Internet (e.g., online games) that a client has particular difficulty in
regulating use. The Internet offers many different types of reinforcers (e.g., new information,
positive social feedback, points/rewards in a video game). Such rewards may be particularly
salient for young people, such as John, who generally lack financial means and independence and
for whom the Internet may represent a new world of freedom and possibility. As an individual
spends more time online, less time is spent in real life activities. With fewer opportunities for
reinforcement from nononline activities, the Internet becomes increasingly attractive and relied
upon for gratification of needs. Over time, the user may disengage from activities in the real
world completely or to the extent that normal involvement is no longer an available option. The
24/7 nature of the Internet then fills the void of extra time and unmet needs resulting from social
exclusion and/or nonparticipation in normal activities.
Using current assessment techniques (Beard, 2005; Griffiths, 2008; Shaw & Black, 2008) it is
possible to assess the extent and severity of John’s presenting problem. Brief screening questions
adapted from DSM-IV criteria for pathological gambling may be appropriate for this purpose.
Using this approach revealed John meets at least 7 of the 10 criteria for Internet addiction, which
were as follows (a) increasing preoccupation with the Internet, (b) spending more and more time
on the Internet, (c) unsuccessful attempts to limit Internet use, (d) withdrawal symptoms when
Internet use is reduced, (e) using the Internet as an escape, (f) neglect of household chores
to spend more time on the Internet, and (g) poor school performance as a consequence of
Internet use. Meeting five or more criteria in the past 12-month period indicates addiction.
Additionally, John’s symptoms are not related to a manic episode or symptoms of Axis I
disorders. Thus, according to this assessment method, John may be considered a generalized
pathological Internet user.
Course of Treatment
Little is known about the effective course of CBT treatment for Internet addiction. Table 1
presents a summary of the published evidence base on treatment. Clinical interventions for
Internet-related problems vary considerably, with a mixture of studies employing pharmacological treatment, cognitive-behavioral therapies, or self-devised interventions (Griffiths & Meredith, 2009; King, Delfabbro, Griffiths, & Gradisar, 2011; Shaw & Black, 2008). Specifically, there
have been three studies that have employed CBT on its own or in conjunction with other treatment approaches (Du, Jiang, & Vance, 2010; Orzack, Voluse, Wolf, & Hennen, 2006; Young,
2007). Although this evidence base is not strong, there are promising early signs that CBT for
a relatively short period (i.e., 8 to 12 sessions) may be successful in reducing both frequency of
Internet use and symptoms of Internet addiction. Unfortunately, CBT treatments specifically
developed for Internet addiction have not yet been manualized, and thus specifics of treatment
protocol are not widely available.
Du et al. (2010) have conducted the only randomized, controlled trial for the treatment of
Internet addiction in adolescents. Their study involved a multimodal school-based intervention
involving eight sessions of group-based CBT. Group size comprised 6–10 participants. Therapy
involved addicted adolescents learning principles of effective communication with their parents;
learning how to manage online relationships; techniques for controlling impulses; and techniques
for recognizing and stopping problematic behavior. Parent training was also delivered in tandem,
and this involved teaching parents to recognize their child’s emotions, increase problem solving
and communication between family members, and develop techniques for managing adolescents
with problem technology use. Psychoeducation was also delivered to teachers in the school.
Posttreatment, adolescents significantly reduced their Internet use and anxiety and improved
their time management skills. Treatment gains were maintained at 6-month follow-up.
Beard’s Diagnostic
Questionnaire
Korean-Internet Addiction
Scale
Young Internet Addiction
Scale; DSM-IV criteria for
substance dependence
Korean-Internet Addiction
Scale
Du et al.
(2010)
Han et al.
(2009)
Han et al.
(2010)
Orzack Time Intensity Scale
Young Internet Addiction
Scale
Young Diagnostic
Questionnaire
Internet Addiction Test
Orzack et al.
(2006)
Shek et al.
(2009)
Su et al. (2011)
Young (2007)
Kim (2008)
Assessment
Study
1. CBT (12 sessions)
1. Multi-modal
counselling (15 to 19
months)
1. Self-help (3 types)
2. Control
1. Group counselling
(5 weeks)
2. Control
1. CBT; Readiness to
change; motivational
interviewing (16 weeks)
1. Methylphenidate
(8 weeks)
1. Bupropion (6 weeks)
2. Control
1. CBT (8 sessions)
2. Control
Treatment
Selected Characteristics of Treatment Studies for Internet Addiction
Table 1
11–18
59
114
–
–
26–59
35
65
–
17–29
19
25
8–12
12–17
Age (years)
62
56
N
CBT reduced most clients’ thoughts and
behaviors related to compulsive Internet use.
Gains observed at 6-month follow-up.
CBT reduced Internet overuse and associated
symptoms, and improved time management
skills. Treatment gains were observed at
6-month follow-up.
Methylphenidate significantly reduced severity of
addiction symptoms and overall Internet usage.
Bupropion reduced cravings for online video game
play, total game play time, and cue-induced
brain activity.
10 counselling sessions reduced addiction
symptoms and increased self-esteem, as
compared with the control group.
Group treatment increased quality of life and
depressive symptoms, but did not reduce
Internet misuse. Patients with co-morbid
anxiety/mood disorder responded best to
treatment, whereas ADHD clients showed no
improvement.
Counselling produced a decrease in IA symptoms.
Participants reported high satisfaction with the
program.
All treatment groups showed significant decreases
in online activity (hours) and YDQ scores after
1-month. The “expert system” treatments were
the most effective.
Outcome
Cohen’s d =
0.72–0.82 (YDQ
score); Cohen’s d
= 0.75–0.98
(online activity)
Not reported
Not reported
Not reported
Not reported
Not reported
Cohen’s d = 1.08
(post) and 1.35
(6-month
follow-up)
Not reported
Treatment effect size
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Journal of Clinical Psychology: In Session, November 2012
CBT Approaches
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Two studies employing CBT for adult Internet addicts suggest further techniques. In Young’s
(2007) study, CBT involved clients monitoring their thoughts and identifying those that trigger
addictive feelings and actions, as well as learning new coping skills and relapse prevention strategies. The initial stage of therapy was behavioral, focusing on specific behaviors and situations in
which Internet addiction causes the most difficulty in the client’s life. In later stages of therapy,
greater focus was placed on cognitive assumptions and distortions and their effect on behavior.
In Orzack et al.’s (2006) study, a similar approach was employed. Participants were guided to
identify and then modify maladaptive cognitions, develop a repertoire of coping strategies to
deal with unpleasant emotional states, and engage in homework assignments. Motivational interviewing techniques were also used to help patients gain insights into the costs and benefits of
their Internet use and develop problem-solving strategies to reach a goal of controlled Internet
use. Interestingly, in Orzack et al.’s study, CBT was not effective in reducing Internet addiction
symptoms but it did increase perceived quality of life and reduced depressive symptomology.
Quality of design and reporting in Internet addiction treatment studies is not optimal. A review
by King et al. (2011) evaluated clinical treatment studies for Internet-related problems using the
Consolidating Standards of Reporting Trials (CONSORT) statement. The CONSORT statement
is a recognized “gold standard” for assessing the reporting quality of clinical trials. King et al.
reported that the majority of studies had several key limitations, including (a) inconsistencies
in definition and diagnosis of problems, (b) a lack of randomization and blinding techniques,
(c) a lack of adequate controls or other comparison groups, and (d) insufficient information
concerning recruitment dates, sample characteristics, and treatment effect sizes. Despite these
limitations, the field is moving in the right direction in developing a greater evidence base. The
wide scope of Internet-related addictions (e.g., cyber-sexual addiction, compulsive browsing,
and online gaming), as well as the variance in at-risk populations (as a function of, among
other variables, age, educational background, and presence of comorbid disorders), necessitates
further studies to tease out and target separately different types of users and problems.
In coming years, the evidence base on CBT treatment for Internet addiction is expected to
grow in response to client need. Internationally, a large number of individuals with Internetrelated problems have received some form of treatment from a mental health or medical service
provider. In particular, there is significant demand for treatment for Internet-related problems in
China, Taiwan, and South Korea, where the estimated prevalence of Internet addiction problems
among adolescents is reportedly higher than in Western industrial countries. The South Korean
government has reportedly established a network of over 150 counseling centers for treatment
of Internet addiction and have introduced treatment programs at almost 100 hospitals (Kim,
2008).
In addition, numerous boot camp style programs for Internet-addicted adolescents have
emerged in both China and Korea (Koo et al., 2011). In Western countries, clinics specializing
in the psychological treatment of computer-based addictions have also emerged: the Center for
Online and Internet Addiction located in Bradford, Pennsylvania, United States; the Computer
Addiction Study Center, at McLean Hospital, Belmont, Massachusetts, United States; the
Broadway Lodge residential rehabilitation unit located in Somerset, England; and the Smith &
Jones 12-step (Minnesota Model) clinic located in Amsterdam, Holland.
Additionally, there are some online providers of treatment services for Internet addiction
(e.g., netaddiction.com; netaddictionrecovery.com; onlineaddiction.com.au; techaddiction.ca),
some of which are modelled on 12-step self-help treatment philosophies and offer books and
resources for parents and teachers dealing with Internet-addicted adolescents.
Outcome and Prognosis
Available literature suggests that adolescent Internet addiction may be treated effectively using
CBT approaches. Relatively short-term treatment (i.e., 3 to 6 months) may be adequate. John’s
example highlighted above is quite severe, given his older age, intense pattern of Internet use, and
DSM-IV symptom profile, but this is typical of many patients in clinical trials. Research evidence
suggests that Internet addiction is not likely to remit spontaneously in adolescent populations;
rather, an adolescent pathological adolescent user is highly likely to remain pathological 2 years
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Journal of Clinical Psychology: In Session, November 2012
later without an intervention. Internet addiction symptoms are also known to increase severity
of Axis I symptomology, as well as interfere with effective treatment of these disorders.
Evidence suggests comorbid attention deficit and hyperactivity disorders (ADHD) are likely
to reduce effectiveness of CBT (Orzack et al., 2006); however, pharmacological treatment (i.e.,
methylphenidate) may be effective in reducing both ADHD and addiction symptoms in this
client subgroup (Han et al., 2009). Engaging parents and teachers in the treatment process
demonstrates good preliminary support. Prognosis of Internet addiction is currently not well
understood given the lack of longitudinal studies and follow-up data in clinical trials.
Clinical Practices and Summary
The following clinical techniques with empirically supported utility may be drawn from treatment
studies for adolescent Internet addiction:
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An activity-monitoring schedule may be useful for a clinician and client to gain a shared
understanding of what types of online activities occur (i.e., in a typical week), at baseline
and over the course of therapy. It may also be useful for the client to document thoughts
and emotional states before, during, and after online activities to understand the functional
purpose of Internet use. Cognitions, emotions, and behavioral activity that occur in response
and in tandem to the online behavior should also be recorded. For example, John should keep
a log of those times when he fights with his parents about his computer use or urinates in a
bottle at his computer. This information may be helpful for John to understand the negative
effect of his excessive computer use, and motivate positive change.
Treatment goals should be realistic given the pervasiveness of the Internet in school and home
life. For example, abstinence from the Internet may not be possible, given its role in homework
assignments, social life, and so on. Controlled or regulated Internet use is often the target
goal in clinical studies (Shek, Tang, & Lo, 2009). John’s initial goal in therapy, therefore, may
be to not use the Internet when doing his homework.
Young (2007) suggests that behavior therapy (i.e., conditioning) may be 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-based strategies to reduce prolonged Internet use may be useful in the beginning
stages. For example, using an alarm clock to set a maximum limit of 45 minutes of Internet
use, and then having to do something else for 15 minutes. Similarly, having the client wait for
5 minutes at the computer with the screen turned off before initiating use.
Behavioral experiments to test problematic cognitions associated with Internet use (e.g., “I
have no control over my Internet use”) or reduced online behavior (e.g., “I am worthless
without the Internet in the life”) may help to build a client’s self-confidence. An example experiment may involve testing a belief about “uncontrollability” by having the client repeatedly
open and close a favorite website without interacting with the website.
Psychoeducation is an effective adjunct to CBT, particularly for an adolescent’s parental
authorities. Many parents have limited knowledge of the Internet, its functions, and issues of
cyber safety. Parents should also be informed that simply removing the computer from a heavy
adolescent user’s life can be a significant shock and may be counterproductive to developing
a trusting and supportive parent-child relationship (Dini, 2008). John’s parents’ attempts to
reduce John’s Internet use by removing and restoring Internet access in the bedroom were
not effective and created significant relationship discord. It would be helpful if they provided
John with support and encouragement for his efforts in reaching his therapeutic goals.
Working collaboratively with adolescent clients and their parents has been shown to improve
parent-child communication and consolidate CBT practice. In most cases, an adolescent’s
habitual Internet use is likely to have resulted in a breakdown in family communication and
cause significant stress and conflict. Family relationships may be repaired by collaboratively
reaching a shared understanding about what Internet addiction is and what it is not, having
common goals for therapy, and setting time for bonding as a family.
CBT Approaches
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Rowan (2001) presents the following Internet addiction prevention guidelines for parents with
young children: (a) limit technology use to 1–2 hours per day, (b) exercise for 3–4 hours per
day, (c) listen, hugs, bedtime stories, (d) removing TVs from bedrooms, no “tech dinners”
Sundays and holidays, and (e) no technology at school recess. These may also be adapted as
goals for therapeutic purposes. For example, it may be helpful for John to schedule meals
(particularly dinner) in the dining room or somewhere in the house where he cannot use the
Internet. John’s parents could use this “tech-free” time an opportunity for bonding.
Sleep patterns are often disrupted as a result of prolonged Internet use. Clients may benefit
from interventions aimed at establishing normal sleep/wake activity, particularly shifting
electronic media use to during daylight hours (without necessarily restricting Internet hours)
rather than directly before bed. Epidemiological studies of adolescent sleep suggest computer
use prior to sleep is associated with extended time taken to fall asleep, poorer quality of sleep,
and decreased daytime alertness and concentration. Improved sleep as a first step may aid in
motivating engagement in other life areas.
Motivational interviewing (MI) as an adjunct to CBT shows strong empirical support in field
of addiction. MI may be used to (a) elicit self-motivational statements, (b) handle (i.e., “roll
with”) client resistance to altering Internet use using reflection and summarizing techniques,
(c) examine helpful and unhelpful aspects of Internet use, and (d) explore costs and benefits
of changing Internet use in context of client’s values. Reminder cards (or “flashcards”) that
summarize treatment goal(s) and/or list a self-motivational statement may be useful for a
client to carry at all times.
A client’s preoccupation with the Internet may be an obstacle to identifying alternative ways
of spending time. The creation of a personal inventory of activities no longer engaged in
since using the Internet may be useful. For adolescents without a history of other interests or
hobbies, identifying new activities that cater to client strengths or competencies (e.g., teambased physical activity, arts/craft, volunteer work) could be explored. For John, this may
involve joining a local basketball team.
Distraction may be a useful tool for adolescent clients to help refocus attention from internal
(emotional states, automatic thoughts) or external Internet-related stimuli. Cognitive distraction involves helping clients to focus their attention away from the Internet cues by focussing
on other thoughts (Kouimtsidis et al., 2007). The goal is to improve regulation and control
of attention. Examples may include focussing on relaxing or pleasant images or a memory of
a positive event. The client should practice this skill so that he or she is easily able to switch
attention to such thoughts in a high-risk situation.
Although not always possible, a group setting may be helpful in normalizing adolescents’
feelings of shame, guilt, worthlessness, and isolation related to their Internet addiction symptoms. Group settings are often employed in treating addiction because they foster a supportive,
nurturing, and non-judgmental environment needed for recovery.
Young (2007) suggested that those who suffer from negative core beliefs may most attracted
to the anonymity of the Internet to overcome perceived inadequacies. At a later stage of
therapy, cognitive restructuring may be used to address underlying negative core beliefs. As a
precursor to working with core beliefs, addressing cognitive distortions and rationalizations
such as “Just a few more minutes won’t hurt” may help in managing primary symptoms.
Although research evidence is limited (Su, Fang, Miller, & Wang, 2011), some studies have
attempted to treat Internet addiction in an online setting. Although this may be compared
somewhat unfairly to treating alcoholism in a pub, this approach presents some advantages.
Principally, it allows clinicians to reach a subgroup of problem users who otherwise would
not present in treatment. Clients with generalized anxiety and/or agoraphobic tendencies
in addition to Internet addiction may have significant difficulty in even leaving the home to
present at a treatment center.
In summary, Internet addiction is an emerging disorder of growing relevance to adolescent
clinical populations. Internet-related problems may be due in part to the increasing uptake and
use of online-enabled devices among young people in home and school contexts. Although the
literature in this area is still quite new, and there is no consensus as to assessment and therapy
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protocol, a small evidence base suggests that CBT has good preliminary support in treating
addicted adolescents. Progress in established fields of adolescent addiction (e.g., pathological
gambling) may be translated successfully to Internet addiction. Randomized, controlled trials
using manualized CBT treatment protocols are needed to advance the field, in terms of both
improving overall research quality and making more specific recommendations to clinicians.
Selected References and Recommended Readings
Beard, K. W. (2005). Internet addiction: A review of current assessment techniques and potential assessment
questions. CyberPsychology & Behavior, 8, 7–14.
Blaszczynski, A. (2006). Internet use: In search of an addiction. International Journal of Mental Health and
Addiction, 4, 7–9.
Block, J. J. (2008). Issues for DSM-V: Internet addiction [Editorial]. American Journal of Psychiatry, 165,
306–307.
Davis, R. A. (2001). A cognitive-behavioral model of pathological Internet use. Computers in Human
Behavior, 17, 187–195.
Dini, K. (2008). Video game play and addiction: A guide for parents. Bloomington, IN: iUniverse Books.
Du, Y., Jiang, W., & Vance, A. (2010). Longer term effect of randomized, controlled group cognitive
behavioral therapy for Internet addiction in adolescent students in Shanghai. Australian and New
Zealand Journal of Psychiatry, 44, 129–134.
Griffiths, M. D. (2008). Internet and video-game addiction. In C. Essau (ed.), Adolescent Addiction:
Epidemiology, Assessment and Treatment (pp. 231–267). San Diego, CA: Elsevier.
Griffiths, M. D., & Meredith, A. (2009). Videogame addiction and treatment. Journal of Contemporary
Psychotherapy, 39, 47–53.
Han, D. H., Hwang, J. W., & Renshaw, P. F. (2010). Bupropion sustained release treatment decreases
craving for video games and cue-induced brain activity in patients with Internet video game addiction.
Environmental and Clinical Psychopharmocology, 18, 297–304.
Han, D. H., Lee, Y. S., Na, C., Ahn, J. Y., Chung, U. S., Daniels, M. A., Haws, C. A., & Renshaw, P. F. (2009).
The effect of methylphenidate on Internet video game play in children with attention-deficit/hyperactivity
disorder. Comprehensive Psychiatry, 50, 251–256.
Kim, J. (2008). The effect of an R/T group counselling program on the Internet addiction level and selfesteem of Internet addiction university students. International Journal of Reality Therapy, 17, 4–12.
King, D. L., Delfabbro, P. H., & Griffiths, M. D. (2012). Clinical interventions for technology-based
problems: Excessive Internet and video game use. Journal of Cognitive Psychotherapy: An International
Quarterly, 26, 43–56.
King, D. L., Delfabbro, P. H., Griffiths, M. D., & Gradisar, M. (2011). Assessing clinical trials of Internet
addiction treatment: A systematic review and CONSORT evaluation. Clinical Psychology Review, 31,
1110–1116.
Kouimtsidis, C., Reynolds, M., Drummond, C., Davis, P., & Tarrier, N. (2007). Cognitive-behavioural
therapy in the treatment of addiction. Chichester, UK: John Wiley & Sons.
Orzack, M. H., Voluse, A. C., Wolf, W., & Hennen, D. (2006). An ongoing study of group treatment for men
involved in problematic Internet-enabled sexual behavior. CyberPsychology & Behavior, 9, 348–360.
Rowan, C. (2010). Unplug-don’t drug: A critical look at the influence of technology on child behavior with
an alternative way of responding other than evaluation and drugging. Ethical Human Psychology and
Psychiatry, 12, 60–68.
Shapira, N. A., Lessig, M. C., Goldsmith, T. D., Szabo, S. T., Lazoritz, M., Gold, M. S., & Stein, D. J. (2003).
Problematic internet use: Proposed classification and diagnostic criteria. Depression and Anxiety, 17,
207–216.
Shaw, M., & Black, D. (2008). Internet addiction: Definition, assessment, epidemiology and clinical management. CNS Drugs, 22, 353–365.
Shek, D. T. L., Tang, V. M. Y., & Lo, C. Y. (2009). Evaluation of an Internet addiction treatment program
for Chinese adolescents in Hong Kong. Adolescence, 44, 359–373.
Sim, T., Gentile, D. A., Bricolo, F., Serpollini, G., & Gulamoydeen, F. (2012). A conceptual review of
research on the pathological use of computers, video games, and the Internet. International Journal of
Mental Health and Addiction. DOI:10.1007/s11469-011-9369-7
CBT Approaches
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Su, W., Fang, X., Miller, J. K., & Wang, Y. (2011). Internet-based intervention for the treatment of online
addiction for college students in China: A pilot study of the Healthy Online Self-Helping Center.
CyberPsychology, Behavior, & Social Networking. doi:10.1089/cyber.2010.0167
Tao, R., Huang, X., Wang, J., Zhang, H., Zhang, Y., & Li, M. (2010). Proposed diagnostic criteria for
Internet addiction. Addiction, 105, 556–564.
Young, K. (2007). Cognitive behavior therapy with Internet addicts: Treatment outcomes and implications.
CyberPsychology & Behavior, 10, 671–679.
Young, K. (2009). Understanding online gaming addiction and treatment issues for adolescents. The American Journal of Family Therapy, 37, 355–372.
Young, K. S., & de Abreu, C. N. (2011). Internet addiction: A handbook and guide to evaluation and
treatment. Hoboken, NJ: John Wiley & Sons.
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