Reviews and meta-analysis

Beyond internet gaming disorder: problematic internet use or internet addiction in a Research Domain Criteria (RDoC) perspective

Author

G. Grassi^1-3, M.V. Ameringen², I. Zilio³, and S. Pallanti^1,3

Affiliations

¹ Department of Neurofarba, University of Florence, Florence, Italy
² Professor, McMaster University, Dept. of Psychiatry and Behavioural Neurosciences, Director, MacAnxiety Research Centre, Hamilton, Ontario, Canada
³ Institute of Neuroscience, Florence Italy

Corresponding author

Giacomo Grassi
Institute of Neuroscience
via Lamarmora 24,
50121 Florence, Italy
E-mail: giacomograssimd@gmail.com

Abstract

The DSM-5 included internet gaming disorder in its appendix in order to stimulate research in the field of so called “behavioural addictions”. However, internet gaming represents only a small part of internet-related activities that could potentially be addictive. Here, we discuss the rationale for the definition of an internet-related disorder (differently named problematic internet use or internet addiction) focusing on current proposed diagnostic criteria, psychological models, and neurobiological evidence in a Research Domain Criteria (RDoC)-based perspective. Current literature seems to converge on some common features between a putative internet-related disorder and other behavioural and substance addictions. However, the specificity of the proposed diagnostic criteria is still debated. Also, the currently accepted diagnostic criteria seems to lack RDoC-based support. Finally, the lack of longitudinal studies focusing on comorbidities leave several unanswered questions. For instance,  should an internet-related disorder be considered a discrete disorder, a coping strategy or a specifier of other psychiatric disorders? Additional RDoC-based studies are needed to further  develop a reliable definition of a putative internet-related disorder and thereby promoting the development of specific treatments.

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Keywords

Internet addiction, behavioral addiction, RDoC

Introduction

Behaviours, such as gambling, internet use, work, sex and shopping have been suggested to have addictive properties and therefore have been proposed as putative behavioral addictions. The DSM-5 [1] also moved gambling disorder from impulse-control disorders to join the substance-related and addictive disorders chapter given the overlap with substance use disorders in terms of etiology, biology, comorbidity and treatment [2]. Other non-substance addictive behaviours, involving the internet, sex and work have also been considered for inclusion in the manual. However, the DSM-5 workgroup concluded that there was only evidence to support the inclusion of internet gaming, a specific type of internet use, in the DSM-5 appendix to stimulate new research [1]. While the clinical definition of the so-called “behavioural addictions” is still a debated issue, the Research Domain Criteria (RDoC) approach, a neural networks-based classification of phenomenology, could represent a promising resolution and a road to a “precision-medicine” definition of these putative disorders.
Over the last 16 years, the number of Internet users has increased by 1000% [3]. In Europe alone, the percentage of individuals using the Internet has increased from 46.3% in 2005 to 79.1% in 2016 [4]. The exponential growth of internet use has been mirrored by the growing body of research on its putative addictive uses. Despite several bodies of evidence highlighting the negative impacts of excessive internet use, the rationale and definition of a discrete disorder is still debated. Here, we discuss the rationale for the definition of an internet-related disorder (differently named problematic internet use or internet addiction) focusing on current proposed diagnostic criteria, psychological models, and neurobiological evidence in an RDoC-based perspective.

Why do we need a diagnosis of excessive internet use? Ethical vs health-related perspectives

Although internet use has now become a worldwide phenomenon and has permeated daily life. Several studies have shown that internet use can become uncontrolled and time-consuming, to the point it severely disrupts people’s lives, or in other words, it can become “excessive”. A common criticism when using the term “excessive” to describe a particular behaviour is its implicit ethical judgment. A central goal in achieving a clinically reliable picture of this phenomenon and in overcoming any moralistic definition involves focusing on the health-related meaning of this term and consequently its effects on disability, health and life expectancy. “Excessive” internet use has been associated with higher disability levels and higher rates of psychiatric comorbidities [5,6]. Several studies have shown an association with mood and anxiety disorders, attention-deficit hyperactivity disorder (ADHD), poor sleep quality, low self-esteem, impulsivity and suicide risk [6,7,8]. Excessive internet use has also been consistently associated with low levels of physical activity, increased rates of obesity [9,10] and other somatic complaints such as back pain, headache and migraine [7,11]. The association between excessive internet use and obesity highlights the relevance of investigating the impact of this putative disorder on life expectancy. However, there are no studies addressing this issue at present time. Thus, future studies should investigate this field as it has been for other recognized psychiatric conditions such as anxiety, mood and psychotic disorders.
Another relevant health-related concern on excessive internet use involves its worldwide prevalence. In fact, excessive internet use has became a great concern all around the world, particularly in Asian countries such as South Korea and China. Recent studies revealed that 8.8% of Chinese adolescents are affected by internet addiction.  Furthermore, in China, internet addiction has been considered an official psychiatric disorder since 2008 [12], and the South Korean Government opened the first ever Internet Addiction Prevention Counselling Centre in 2002 [13]. Excessive internet use and internet addiction are of great concern as prevalence rates also seem to be higher in adolescents and young people, comparable to the development of most of other substance and behavioural addictions [13]. Large scale epidemiological studies in European countries showed prevalence rates ranging from 2.6% to 5.4% among adolescents [14,15]. Thus, the definition of reliable diagnostic criteria has become a central objective for the recognition and treatment of this disorder.

Current models and proposed diagnostic criteria

Several terms have been used to describe internet-related disorders: excessive internet use, problematic internet use (PIU), internet addiction (IA), pathological internet use, compulsive internet use, and internet use disorder (IUD). It would appear that these terms seem to converge in describing a common set of phenomena  typically involving excessive or poorly controlled preoccupations, urges or behaviors regarding Internet use that lead to impairment or distress, However diagnostic criteria, psychological models, sub-classifications (according to the type of internet activity: social networking, gaming etc.) and even the name of this possible internet-related disorder are still largely debated [16].
A specific form of internet addiction, “internet gaming disorder (IGD)”, has been recently included in the DSM-5 in the section of conditions needing further investigation. The DSM-5 diagnostic criteria of IGD incorporates the classical facets of substance and behavioral addictions (as is the case for gambling disorder) including, excessive behaviour and preoccupation for the behaviour, tolerance, withdrawal and functional impairment. According to DSM-5, to fulfill an IGD diagnosis the individual must present at least 5 of the following symptoms:

a) Preoccupation with Internet games (individual thinks about previous gaming activity or anticipates playing the next game; Internet gaming becomes the predominant activity in daily life);
b) Withdrawal symptoms when the Internet is taken away (typically irritability, anxiety, sadness);
c) Tolerance (the need to spend increasing amounts of time on Internet games to achieve the same “high”);
d) Unsuccessful attempts to control or cut down the participation in Internet games;
e) Loss of interest in previously enjoyable activities with the exception of Internet gaming;
f) Continued excessive use despite knowledge of negative psychosocial problems;
g) Has deceived family members, therapists, or others regarding time spent on gaming;
h) Use of Internet games to escape or improve dysphoric mood; and
i) Jeopardized or lost relationships, jobs, educational opportunities because of Internet use.

The presence of 5 or more of these symptoms in the past 12 months in combination with persistent, maladaptive, and recurrent use of the Internet is required [1].
However, IGD describes just a small part of internet overuse. A broader concept of Internet addiction could potentially include several other internet activities such as social networking, messaging, sex, online shopping, etc. Recent studies have shown that there is not complete psychopathological overlap between IGD and other internet-related excessive behaviours [17]. For example a recent Hungarian study by Kiraly et al. [17] showed that IGD adolescents and problematic internet use adolescents differ on several clinical aspects such as sex, depressive symptoms and type of internet involvement. However, there is still debate within the internet addiction research field whether each subtype of internet activities (such as social networking, messaging, etc.) should be considered separately, or if it should be defined  more generally as internet overuse. Studies investigating the differences between different internet behaviours are limited and results are still inconclusive [18].
Concerning current psychological and diagnostic models, three popular models of IA have been developed in the last few years: the Griffiths components model [19]; Young’s Internet Addiction Test (IAT) [20,21,22]; and the more recent diagnostic criteria by Tao et al. [23,24].
In the “components model” Griffiths [18] suggested that internet addiction could be defined by the presence of six different components: salience, mood modification, tolerance, withdrawal, conflict and relapse. In this model conflict refers to interpersonal conflict or even intrapsychic conflict, that  impair social relationships, work and recreational activities.
In 1998, Young and colleagues [21] proposed a screening tool for Internet Addiction based on eight putative diagnostic criteria. The work by Young takes the established criteria for pathological gambling as a starting point and defines Internet addiction as a failure of personal impulse control that does not involve external substances [22]. This failure is described by the following set of criteria: (1) a preoccupation with the Internet, (2) the need to use the Internet for increasing amounts of time, (3) unsuccessful efforts to stop using the Internet, (4) mood change when attempting to stop or cut down Internet usage, (5) staying online longer than intended, (6) jeopardizing of significant relationships or opportunities due to excessive Internet usage, (7) lying about Internet use and, (8) using the Internet as an escape from problems or seeking to relieve bad mood states [20]. Young’s criteria note that only personal (non-work related) Internet use should be evaluated, and that addiction is thought to be present when a client reports experiencing five or more of the above eight criteria [24]. Young’s conceptualization has been popularized through the expanded 20-item IAT proposed in the 1998 self-help book Caught in the Net [21]. Widyanto and McMurran [20] have characterized the IAT psychometrically using factor analysis. Using a convenience sample (online recruitment, N – 86), they obtained six factors in their analysis for Young’s IAT: (1) salience (preference for staying on line, preoccupation when offline), (2) excessive use, (e.g. sleep deprivation in order to stay online), (3) neglect of work, (impaired performance or productivity at work), (4) anticipation (tendency to anticipate the “online” phase), (5) lack of control (difficulty cutting down the amount of time spent on the Internet), (6) neglect social life (difficulty in maintaining relationships except for those online) [20].
Finally, Tao et al. [23] proposed a complex set of diagnostic criteria for IA by considering the clinical characteristics of a large group of Chinese patients thought to have IA, as evaluated by psychiatrists [24]. Tao et al. [23] proposed the following set of criteria: (a) symptom criteria (both must be present): preoccupation and withdrawal symptoms; (b) one or more of these criteria: (1) tolerance, (2) persistent desire and/or unsuccessful efforts to control use, (3) continued use despite problems, (4) loss of other interests, (5) use of the Internet to escape or relieve dysphoric mood; (c) clinically significant impairment criterion: functional impairments (reduced social, academic, working ability), including loss of a significant relationship, job, educational or career opportunities. The criteria also include a course criterion (d): Duration of IA must have lasted for an excess of three months, with at least six hours of Internet usage (non-business/non-academic) per day.
All these models seem to converge on some aspects of internet overuse such as salience, loss of control, tolerance, functional impairment (see table 1). However the specificity of this set of criteria is still controversial and most of them are not RDoC-based (see below).

 Table I: Common criteria between Griffiths [19], Young [21] and Tao et al. [23].

Internet Addiction and the Research Domain Criteria (RDoC)

 The National Institute of Mental Health (NIMH) has recently launched the RDoC project to overcome the limitations of current classification systems and to develop a framework for research on mental disorders that include multiple dimensions [25]: behaviour, thought patterns, neurobiological measures, and genetics, with a strong focus on neurocircuitries. The RDoC aims to facilitate the incorporation of behavioral neuroscience in the study of psychopathology and to identify reliable and valid psychological and biological mechanisms and their disruptions, with an eventual goal of understanding how abnormalities in these mechanisms drive psychiatric symptoms [26].
RDoC’s strong focus on neural circuits is evident from the assumption that mental illnesses are conceptualized as brain disorders. Specifically, mental disorders are considered disorders of brain circuits. Moreover, the RDoC assumes that dysfunctions in neural circuits can/will be identified by tools of neuroscience [25].
In an RDoC perspective, behaviorally addicted patients, such as gamblers, exhibit deficits in the domain of “Positive valence systems”, particularly in “Approach motivation” and “Reward learning” constructs, as well as in the “Cognitive systems” (specifically the “Cognitive control” construct). Therefore, in this section we will review the current evidence on these domains and constructs in internet addicted patients.

Cognitive system domain

 Cognitive systems are responsible for various cognitive processes. In particular, cognitive control “modulates the operation of other cognitive and emotional systems, in the service of goal-directed behaviour, when prepotent modes of responding are not adequate to meet the demands of the current context. Additionally, control processes are engaged in the case of novel contexts, where appropriate responses need to be selected from among competing alternatives” [27].

Cognitive control: Response inhibition/suppression

The proposed diagnostic criterion “loss of control” (“unsuccessful attempts to control or cut down the participation in internet activities”), in a RDoC-based perspective, refers to dysfunction of the cognitive system domain and cognitive control construct. This construct includes several cognitive functions underpinned by the so-called inhibitory-control networks. These networks include several prefrontal and subcortical structures. Cortical areas are mainly represented by the dorsolateral prefrontal cortex, the ventromedial prefrontal cortex, the pre-supplementary motor area and the cingulate cortex; while, the subcortical areas are mainly represented by the ventral structures of the basal ganglia.  A central subconstruct of cognitive control is represented by response inhibition and suppression. Response suppression and inhibition can be investigated through simple behavioural tasks such as Go/ No-Go, stop signal tasks or interference tasks (e.g. the Stroop task).
Evidence of a deficit in response inhibition remains  inconclusive in internet addiction, which may be due to heterogeneous small sample sizes used in neurocognitive studies [28]. However, both neurophysiological and neuroimaging studies show impaired cognitive control in internet addicted patients. An event-related potential study of response-inhibition (using a Go/No-Go task) found higher amplitude and longer peak latency in IAD participants’ No-Go-P3 wave compared  to healthy controls, suggesting less efficient inhibitory processes in the IAD Group [29,30]. The same group investigated response inhibition in internet addicted males through an event-related functional magnetic resonance imaging  Stroop task [31]. In this study IAD patients showed a trend toward slower reaction times than healthy controls during the task and greater activation during the Stroop effect in the anterior and posterior cingulate cortices. These results suggest diminished efficiency of response inhibition in IAD subjects versus healthy controls [31]. Moreover, a greater BOLD signal in the anterior cingulate cortex was associated with slower incongruent reaction time and internet addiction symptom severity. Also, other studies showed that impaired response-inhibition during behavioral tasks and a broader spectrum of impulsive behaviours (as measured by self-rating scales such as the Barratt Impulsiveness Scale) are positively correlated with IAD symptom severity [32].
Other evidence of inhibitory control network dysfunction comes from a recent neuroimaging study on adolescents with internet addiction,  where internet addicted subjects showed impaired fronto-basal ganglia connectivity during response-inhibition respect to healthy controls [33].

Working memory

“Working Memory is the active maintenance and flexible updating of goal/task relevant information (items, goals, strategies, etc.) in a form that has limited capacity and resists interference. These representations: may involve flexible binding of representations; may be characterized by the absence of external support for the internally maintained representations; and are frequently temporary, though this may be due to ongoing interference. It involves active maintenance, flexible updating, limited capacity, and interference control.” [27].
A recent study examined working memory processes with two different materials (internet-related and internet-unrelated stimuli) among adolescents with internet addiction, ADHD and comorbid IA/ADHD [34]. IA subjects and comorbid IA/ADHD subjects showed impaired working memory performance on the 2-Back task iin the internet-unrelated condition respective to healthy controls [34].

Positive valence system domain

Positive valence systems are primarily responsible for responses to motivational situations such as reward seeking, consummatory behavior, and reward/habit Learning [27]. The construct of Approach Motivation involves “mechanisms/processes that regulate the direction and maintenance of approach behavior influenced by pre-existing tendencies, learning, memory, stimulus characteristics, and deprivation states” (ibidem).

Approach-motivation: Preference-based decision-making

Particularly relevant to internet addiction is the subconstruct Action Selection/Preference-Based Decision Making: “Processes involving an evaluation of costs/benefits and occurring in the context of multiple potential choices being available for decision-making” [27].
Risky decision-making is a core feature of addiction disorders. Addicted subjects show a high tolerance toward risk and a bias to select short-term over long-term rewards.
In a recent study Seok et al. [35] reported that compared to controls, internet addicted subjects showed more frequent risky decision-making, and greater activation in the dorsal anterior cingulate cortex and the left caudate nucleus, which are brain regions involved in conflict monitoring and reward, respectively [35].  These results have been replicated showing impaired decision-making performances of internet addicted subjects [36].

Reward learning

Reward learning seems to be another relevant dimension of internet addiction. This construct refers to “A process by which organisms acquire information about stimuli, actions, and contexts that predict positive outcomes, and by which behavior is modified when a novel reward occurs or outcomes are better than expected. Reward learning is a type of reinforcement learning, and similar processes may be involved in learning related to negative reinforcement.” [27].
In a study by Sun et al. [36] Internet addicted subjects’ performance on the Iowa Gambling Task was compared to that of healthy controls.  The Iowa Gambling Task (IGT [37]) has also been employed as a measure of decision-making, since it is considered to be the most widely used and ecologically valid measure of decision making in this clinical population. In the IGT, players are given four decks of cards and an endowment of fake money (e.g., $2000) and are instructed to select cards one at a time and try to lose the least and win the most amount of money. In this study IA patients performed worse in the IGT than healthy controls (as it has been widely replicated for gambling disorder and several substance addictions), and made progress more slowly in selecting strategy [37]. These results suggest impaired reward learning as it has been shown in other behavioural and substance addictions.

Table II: Common RDoC contruct and subcontruct between Internet addiction and gambling.

Open questions

Current proposed diagnostic criteria and psychological models for an internet-related disorder (internet addiction or problematic internet use) seem to converge on a cluster of symptoms that includes preoccupation with internet, tolerance, withdrawal, lack of control over the behavior and functional impairment. These criteria are central facets of substance and behavioural addictions. However, these criteria are not fully RDoC-based and therefore they lack specificity. For example, RDoC studies investigating response inhibition deficits in internet addiction (that refers to the “loss of control” diagnostic criterion) are inconclusive and often results are mixed. Moreover, there is at least some RDoC-based evidence of attentional and working memory problems in IA, but these attributes are not considered in the current proposed diagnostic criteria. As such, additional RDoC-based studies are needed in order to better define a full set of diagnostic criteria for internet addiction.
Another relevant unanswered question pertains to whether internet addiction is a single entity or a spectrum of disorders. The first postulates that the activity in question is simply using the internet, while the latter pays more attention to specific internet activities. There is still a lack of controlled studies investigating the specific features of different internet activities (social networking, messaging, gaming, etc.). There is also limited data regarding the differences between internet use on different devices (e.g. personal computer versus smartphone).
Moreover, there is a need for more focused studies on the medical impact of internet overuse and its potential impact on life expectancy.
Finally, several studies have consistently reported that so-called internet addicted patients have a higher rate of different clusters of psychiatric comorbidities ^[38,39]. Indeed, studies reported that IA is highly comorbid with other substance addictions (such alcohol and nicotine addiction), affective disorder, anxiety disorders (such as social anxiety) and ADHD ^[39]. Therefore, perhaps the most poignant  question is whether internet addiction is a discrete disorder, a coping mechanism for other psychiatric disorders or should be considered a simple specifier?  The lack of longitudinal studies does not allow us to effectively answer this question and its tremendous treatment implications. Thus, a central goal of future research would involve focusing on internet addiction comorbidities.

Conflict of Interest: The authors declare no conflict of interest.

Doi

https://doi.org/10.30435/ABA.01.2019.05

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