**1. Introduction**

Contemporary use of the Internet has led to a number of benefits in the health field (e.g., digital health), but also negative impacts at an individual and psychological level (e.g., gaming addiction).

Excessive Internet use has been classed in the mid-nineties as Internet Addiction (IA) [1], Problematic Internet Use (PIU) [2], or as technological (behavioral) addiction [3]. This broad term, however, has evolved and at present encompasses many types of addiction problems related to generalized Internet addiction (GIA) and a set of specific addictive uses of the Internet [4]. These include online gambling, online gaming, social networking, and cybersex, which are the most prevalent ones that have evolved alongside gaming addiction [5]. These behavioral problems can be engaged in using any device as the Internet is ubiquitous. Accordingly, during the last decade, the Internet has facilitated the development of addiction problems through online technology in many ways, and is associated with health problems (e.g., distress, functional impairment, and comorbidity [6]).

During the last decade, international health bodies, which publish diagnostic manuals for mental health diseases, recognized two associated conditions as behavioral addictions, i.e., gambling and gaming disorders. First, the American Psychiatric Association (APA) proposed Internet Gaming Disorder (IGD) in its fifth Diagnostic and Statistical Manual of Mental Disorders (DSM-5) within its third appendix in April 2013 [7]. Subsequently, the World Health Organization (WHO) included Gaming Disorder (GD) in its first version of the eleventh International Classification of Diseases (ICD-11) in April 2018 [8]. This inclusion has produced the following consequences. Firstly, gambling and gaming disorders have been recognized in the mental health sciences and by health practitioners as behavioral or process addictions, leading to many debates [9,10]. Secondly, the mass media have alerted the general public regarding these emerging online addiction problems which usually affect young populations [11,12]. Thirdly, these addictions are now understood as international public health concern, and the preventive actions undertaken have had limited success and focused on English speaking countries (i.e., in American, European, and Australasian regions [13]), and Asian countries [14].

However, to the authors' knowledge, no literature review has been conducted focusing on the period when gaming addiction was officially recognized by global health organizations, within an intercultural continental region (i.e., Europe), to detect the main concerns, and to propose a set of policy options which are culturally and geographically based. For these reasons, the European Parliament's Scientific Foresight Unit (STOA) endeavored to perform a recent literature review to study the individual and psychological aspects of the harms associated with Internet use, including IA and related harms (e.g., gaming addiction) in the European Union (EU) [15].

To the authors' knowledge, only two reviews exist with similar characteristics, but both with an international scope rather than a regional focus performed in 2016 [6,16].

Kuss and Lopez-Fernandez [6] focused on clinical research on IA and reported characteristics of treatment seekers and online addiction treatments. First, treatment seeker characteristics from various continents included European clinical studies performed in Germany, The Netherlands, and Greece, and focused on both, GIA and gaming addiction problems (among other comorbidities). Second, psychopharmacotherapy was covered, which appeared to have positive effects in decreasing IA symptomatology and Internet gaming addiction problems through antidepressants and anxiolytics, and obsessive–compulsive disorders (OCD) and attention deficit hyperactivity disorder (ADHD) medications for comorbid problems. Third, psychological therapies usually with an individual approach (e.g., cognitive behavioral therapy (CBT)) were applied to outpatients, apart from a few group therapy approaches (e.g., multi-family group therapy (MFGT)). Fourth, combined treatments were researched, which included psychological treatment in combination with pharmacotherapy or electroacupuncture therapy.

Vondráckov ˇ á and Gabrhelík's review [16] focused on IA prevention. First, they stated some target groups may benefit from prevention (e.g., children and adolescents) when it is indicated (e.g., focusing on psychopathological factors). Second, the need to improve specific skills with the help of professionals and other significant individuals (i.e., counsellors, parents) was emphasized. Third, program characteristics were deemed relevant (e.g., information-provision versus interactive interventions). Fourth, environmental interventions were indicated as being needed in some regions (e.g., in countries in which IA is a public health concern where regulation should be promoted, similar to the approach taken by the Chinese government [17]).

Apart from these reviews, a world-wide meta-analysis on IA performed by Chen and Li in 2014 [18] indicated that the global estimated prevalence rate was approximately 6%, with the lowest numbers found in Northern and Western Europe (2.6%). IA prevalence was inversely associated with self-perception of quality of life regarding subjective (e.g., life satisfaction) and objective indicators (e.g., environmental conditions). Furthermore, many cross-cultural studies on IA have emerged since 2012, especially in intercultural regions, such as Europe [19,20]. These studies were school based with adolescent samples and found between 1%–4% estimated prevalence of GIA (which was higher in males). There has been a continuing increase in the number of these studies in the field [21], including mostly cross-national intercontinental studies (covering Asia, America, and Europe), which have researched GIA and estimated its prevalence with psychometric scales, obtaining higher rates in Asian countries and in young male users.

Considering the above, the objective of the present paper was to present a timely critical review of the literature on Internet use-related addiction and associated problems published in Europe between April 2013 (i.e., when IGD was included in the DSM-5 s III appendix) and April 2018 (i.e., when GD was first officially recognized in the ICD-11 beta test version). The aims were to critically analyze online harms by addressing: (i) the cross-cultural approach adopted within the EU, (ii) the users' characteristics based on community and clinical populations, (iii) Internet use-related addiction problems and the interventions to target the resultant harms in Europe, and (iv) its implications at a public health level with an eye towards prevention. Furthermore, we aim to provide the first set of policy options for harm minimization at the level of the individual in Europe.

#### **2. Materials and Methods**

A literature review was conducted using the databases PsycINFO and Web of Science between January and April 2018 at Nottingham Trent University (United Kingdom). The rationale to select these two scientific databases was to contain research in Psychology and related disciplines [15]. Initially, PubMed was also selected but the results almost duplicated all outcomes collected via the first two databases, and consequently this search was discarded. PsycINFO and Web of Science are also among the most relevant in the field of Internet addiction covering the majority of current scientific sources targeted in the present paper's aims. Moreover, they offered sufficient information to perform a timely, expeditious, and recent review, and are among the databases which are usually used in literature reviews published in this field from a disciplinary perspective (i.e., PsycINFO) and also using interdisciplinary approaches (i.e., Web of Science), which allowed us to study the individual and psychological aspects of the harms associated with IA.

The review comprised scientific papers published between April 2013 and April 2018 as this is the period between the official recognition of IGD and GD. The following search was undertaken using the following terms, clusters, and Boolean operators: ("Internet" OR "online" OR "game\*" OR "gaming" OR "video gam\*" OR "videogame\*" OR "video-game\*" OR "social network\*" OR "social media") AND ("Addict\*" OR "compuls\*" OR "problem\*" OR "disorder" OR "pathology\*" OR "excess\*") AND ("clinic\*" OR "treat\*" OR "therap\*" OR "harm\*" OR "risk factor" OR "prevent\*"). The search was performed by paper titles as this was the only option available across both search engines.

The inclusion criteria were for studies to: (i) contain empirical data (i.e., data collected using quantitative, qualitative, and mixed methods approaches), (ii) assess online addictions in the EU, (iii) be published between 2013–2018, (iv) include community and clinical samples, (v) provide a full-text article, and (vi) be published in the languages the authors manage (i.e., English, Spanish, French, German, Polish, Italian, and Portuguese).

The literature review was performed as indicated in Figure 1 [22]. Over 390 sources resulted from the initial search. Of these, a great number were filtered out based on the following criteria: (i) duplicates, (ii) meeting and conference abstracts and non-empirical studies (e.g., case studies, anecdotal studies, reviews, editorials, letters, and commentaries), (iii) studies that did not assess IA and related harms in the EU, (iv) studies that were not published between April 2013 and April 2018 (both months included), (v) did not include the population groups targeted (i.e., community and clinical samples), (vi) did not provide a full text article, (vii) were not published in a language the authors manage. Thus, after removing duplicates (*n* = 34), articles in other languages (*n* = 32), conference abstracts (*n* = 188), non-empirical studies (*n* = 81) and non-EU papers (*n* = 36), 19 relevant sources were included in the final analysis.

#### *Int. J. Environ. Res. Public Health* **2020**, *17*, 3797

**Figure 1.** PRISMA Flow diagram of study selection processes.

Two rounds of searches were used: a first round (in January and February 2018) using PsycINFO and subsequently Web of Science, followed by a second round (in April 2018) to ensure all papers were consistently collected and no new paper was published within the specified period and in accordance with the inclusion and exclusion criteria. From the initial pool of 390 papers, after deleting duplicate papers, the remaining 324 results were manually scanned (i.e., title, abstract, key words, and, the paper) to identify the relevant outcomes. Thus, the literature search provided non-exclusive categories of Internet use-related addiction problems as follows: eight Internet addiction papers (i.e., seven by Internet addiction itself, and one including Internet addiction and gaming addiction), 11 online gaming addiction papers (i.e., eight with gaming addiction by itself, and two about gambling and gaming addictions together, and one including Internet addiction and gaming addiction), and three online gambling addiction papers (i.e., own with gambling addiction by itself, and two including gambling and gaming addictions together).

#### **3. Results**

Data were initially organized into four main categories which emerged in the qualitative analysis of the 19 European empirical papers undertaken by the two co-authors by categories (see Table 1).


**Table 1.** Papers selected for the review (*N* = 19).

Therefore, both authors independently first qualitatively analyzed the papers divided by categories (i.e., O.L.-F. performed the examination of gaming and gambling addiction articles [24,28,30,31,33–36, 38–40]; and D.J.K. evaluated Internet addiction articles [23,25–27,29,32,37,41]). Therefore, both authors reviewed the contents of the identified articles according to the following categories of analysis: title and journal, authors and country, sample, design, aim(s), measures, results, implications for policy options and prevention, and conclusions for harm minimization [15]. From this categorical analysis the authors proceeded to discuss the main preliminary results, and extracted the information based on the aims with the final purpose of creating a set of preliminary policy options and preventive actions for IA and related harms in Europe. This process included several rounds until theoretical saturation of the contents from all 19 papers was achieved, according to the aims.

The present qualitative and narrative analysis resulted in the division of identified research papers into four categories: (i) the characteristics of problem users (including community and clinical samples); (ii) GIA; (iii) specific IA problems (i.e., gaming, and gambling addictions); and (iv) policy options for preventing Internet use-related harm in Europe. The first category about users' characteristics is subdivided by Internet use-relate addiction problems (i.e., GIA and specific problems), as the literature shows there are differences in Internet users based on typology of disordered behaviour. Therefore, the categories related to GIA and specific problems were analyzed in detail covering both non-clinical and clinical studies, which were researched from a policy implications perspective. Lastly, the fourth category was divided into respective policy options to reduce Internet harm from an individual person perspective.

Regarding geographical location, half of the studies included in this review (*n* = 10; 53%) were from the Southern European region (countries are ordered from higher to lower frequency): Spain (*n* = 7), Italy (*n* = 2), and Greece (*n* = 1); and 42% (*n* = 8) were from the Western European region: Germany (*n* = 4), France (*n* = 3), and The Netherlands (*n* = 1). Finally, only one study (5%) was conducted in the Northern region (i.e., Denmark).

### *3.1. The Characteristics of Targeted Problem Internet Users*

Almost all participants included in the studies were adolescents and young adults from high schools or universities, and the assessed studies dealt with GIA and gaming addiction. Only a few studies assessed online gambling addiction, with participants usually being middle-aged male adults.

#### 3.1.1. Generalized Internet Addiction Users

The main characteristics extracted were:


Sample sizes included studies which varied in number depending on the research methods applied. For instance, samples ranged from 16 Italian Internet-addicted patients investigated through an experiment with a control group to assess the biological causes of IA [32] to a survey with 1,019 German adults to test a new model for GIA [25]. Regarding life stage, participants were usually adolescents and students in high schools [23,27,29], although a few studies included adults [25]. Regarding participant gender, studies on GIA tended to cover both genders in a balanced way. However, when participants were university students, there tended to be more females than males in the sample [25,26,29], and there were significantly more males in clinical samples [27,37]). No study analyzed potential differences between female and male problem Internet users.

3.1.2. Specific Internet Addiction Problem Users: Gamers and Gamblers

The main characteristics extracted from Internet-addicted gamers and gamblers were:


Sample sizes included clinical case studies of one [38] and nine adolescent patients [24], and online surveys with gaming or gambling participants [30,31] used mixed methods studies combining interviews and surveys on Internet gambling [33,34]. Almost all studies about gaming addiction used adolescent samples [28,38–40], and the clinical studies were conducted with males who usually played Massively Multiplayer Online Role-Playing Games (MMORPGs [24,38,39]) and sometimes Multiplayer Online Battle Arena games (MOBA [39]) or First-Person Shooters (FPS [39]). Interestingly, these studies usually included family members (e.g., the mother, both parents, or a sibling [24,28,38,39]), type of family [41], or type of parenting style [28] to treat existing conflicts (e.g., loneliness and discussions with parents) and measured the impact of environmental factors and interventions [28,38–40].

However, studies on Internet gambling were conducted with patients within a pathological gambling unit [31,34] and explored factors related to IGD, and some participants were invited from an online gambling site (i.e., Winnimax [33]). These studies came from Spain [31,33–36,39], France [33,38], Germany [28,41], The Netherlands [40], and Denmark [30].

#### *3.2. Generalised Internet Addiction Problems*

Eight studies (42.1%) assessed GIA, and referred to non-specific Internet use (i.e., not reliant on the engagement with a particular online activity), and few considered prevention of IA [23]. The studies reviewed were from Germany [25,37], France [26], Greece [27], Italy [23,32], and Spain [29].

Findings suggested a wide range of problems could arise from overusing (e.g., difficulty cutting down, lack of sleep, fatigue, irritability, apathy, racing thoughts, declining grades or poor job performance, and neglecting other duties). Thus, the presence of addiction symptoms (e.g., tolerance), impairment in daily functioning, high comorbidity (i.e., anxiety, depression, and OCD), and risk factors (e.g., preoccupied and fearful attachment styles) were identified. Specifically, problem users tended to present psychological characteristics and co-occurring disorders (i.e., when two or more health problems occur at the same time, e.g., an addiction problem and a mental health disorder are present simultaneously). Usually, these other mental health disorders related to personality disorders, mood disorders, or anxiety disorders. For example, those who were affected by GIA also presented with poor coping strategies and low self-esteem [25], and attachment difficulties (e.g., preoccupied and fearful types [26]). Regarding co-occurring disorders, it seems at least half of the samples presented at least two problems [25,27]). The most prevalent associated problems were depression and anxiety disorder (e.g., the latter with the social subtype [25]). However, CBT emerged as effective in leading to significant changes in symptom experience.

The main characteristics of individuals with GIA in Europe were:


Prevalence rates were higher in clinical studies than in community studies. For instance, Müller et al. [37] estimated a prevalence of 71% of German treatment seekers with the clinical diagnosis of IA; while Andrisano and colleagues [23] found a prevalence rate of 4% of severe Internet-addicted Italian adolescent users among the community sample they studied, which was similar to the other community samples with young Spanish adults, where the prevalence was 10% according to Gonzalez and Orgaz [29]. The scale that most frequently used to measure IA [23,25,27] was the Internet Addiction Test (IAT [42]) and its short version (s-IAT [43]). However, other valid measures have also been used [27,29] (e.g., Online Cognitions Scale (OCS [44]); Index of Problematic Online Experiences (I-POE [45]), and the Assessment of Internet and Computer game Addiction—Scale (AICA-S [41])).

Brandt et al.'s [25] model on GIA explained 64% of GIA variance based on addiction symptoms, and included associated disorders and IA symptoms experience, suggesting users' cognitions (e.g., poor coping and cognitive expectations) increase the risk of IA. However, comorbidity can also mediate the relationship between symptomatology and factors which seem to act as a cause. Similarly, Danet and Miljkovitch [26] stated fearful and preoccupied attachments can be associated with IA, and Lai et al. [32] suggested a generalized impairment in emotional and cognitive processing abilities in those who suffer from IA, which can be linked to dissociative symptoms. Comorbidities in IA seem, therefore, to be diverse and present in half of Internet-addicted patients [25,27,37,41]. The identified comorbidities include depression, social anxiety, and associated symptoms experienced, such as low self-esteem, low self-efficacy, and high stress vulnerability. According to Müller et al. [27], the majority of treatment seekers present criteria sufficient to be diagnosed with IA, and half of them have comorbidities (i.e., depression, OCD, and dissociative symptoms) and stress. In general, comorbidities include Axis I diagnoses, such as:


*Int. J. Environ. Res. Public Health* **2020**, *17*, 3797

Furthermore, it seems anxiety disorders are associated with the onset of GIA, and mood disorders can be precursors of or follow IA [27].

School interventions which have shown excellent outcomes are the peer education program evaluated by Andrisano and colleagues [23] in Italy, which included brainstorming and video co-creation. In Spain, potential Internet-addicted students [29] also presented with the problem, and this was associated with environmental factors (e.g., family, friends, online interactions, etc.). Both school-based studies came from Southern Europe, suggesting there is a need of educational policies to prevent GIA and related harms in this European region.

Clinical interventions usually aimed to validate tools and cut-off points to estimate the prevalence of GIA [37,41] (e.g., AICA-S [41]).

#### *3.3. Specific Internet Addiction Problems: Gaming and Gambling*

Twelve papers (63.2%) reported results on online gaming and gambling addictions, nine of which focused only on gaming (44.4%). Thus, these two problems together were more prevalent in comparison with GIA in the assessed samples of European studies.

#### 3.3.1. Internet Gaming Addiction

The main characteristics of Internet gaming addiction in Europe were:


Studies that screened for gaming addiction in community samples were a minority in this section, and usually measured self-perceived problematic video gaming through different devices (e.g., computers and consoles) to assess both offline and online gaming through cross-sectional surveys in Denmark and Spain [30,35]. Regarding their commonalities, males and older adolescents were at a higher risk of gaming addiction problems, non-clinical measures were useful as preventive actions, and programs to reduce gaming were usually effective, and even more so if personality traits (such as impulsivity) were addressed in the interventions.

However, clinical studies were the most common in the samples that were included in the present review, coming from Spain [24,36,39], France [38], The Netherlands [40], and Germany [28]. Patients were brought to health centers by their families, usually by their mother or a sibling [24,38], and in general parent supervision was required [28]. The main factors associated with problematic MMORPG, MOBA and FPS behaviors were dissociation (i.e., a psychological mechanism of stepping out of oneself to be protected from external harm; e.g., bullying or the loss of a loved one), entertainment (e.g., enjoyment and escapism), and virtual friendship (e.g., social relationships in game without any need to personally know one's fellow gamers; the 'clan' or the 'guild') [24]. Therefore, there was a need to assess present motivations [38]: to change (e.g., if you continue gaming like this during a decade, what will happen to you?), and to work therapeutically (e.g., playing time was double the usual adult working time per week). Simultaneously, functional analyses were performed (e.g., to support the patient to treat themselves regarding the co-occurring disorders associated with gaming), treating the gaming behaviour (i.e., psychological gaming experience), while addressing alternative pastime opportunities, and improving other relationships.

In CBT interventions, the emotional component was as relevant as the cognitive component; e.g., using techniques related to empathy, self-esteem, self-control, assertiveness, communication skills, or insight [39]. One of the main aspects in the therapeutic intervention was relapse prevention [24,38,39]. Furthermore, one study [28,38–40] showed that nonspecific psychiatric disorders pose an increased risk for gaming addiction. This supports the argument that Internet gaming addiction might be

a discrete psychiatric entity usually combined with emotional and social problems [24,38]. It can be related to ADHD, Asperger's, Autism, and other disorders, such as anxiety and depression, social phobia, pervasive developmental disorders, among other comorbid conditions and problems (e.g., parent–child relationship problems, school relationship problems, obesity, cannabis use, and anhedonia). The prognosis is generally positive at three or six months of treatment [24,36,38] for those patients with an externalized profile (i.e., disruptive behaviour disorder, ADHD, and adaptive disorder) or an internalized profile (i.e., anxiety, mood and personality disorders, social relationship problems, previous mental disorders family histories, and individuals who use gaming to escape discomfort experienced in their daily lives [39]). Furthermore, clinicians have stated that increasing numbers of patients sought help through families in the recent years in European public hospitals and health centers [34,36].

Thus, gaming addiction in Europe during the last decade has required both, the development of new short non-clinical measures to screen for it in young adolescents (e.g., using the computer gaming index, console gaming index, or the Internet use index [30]), while clinical studies usually were case studies and used mixed methods dealing with interventions through tailored CBT, including for instance the 'Individualized Psychotherapeutic Program for the Addiction to the Information and Communication Technologies' (PIPATIC [39]), and new psychometric tools (e.g., Clinical Video game Addiction test second version(C-VAT 2.0 [40]), or Assessment of Internet and Computer Game Addiction (AICA-S [41])). Related to prevalence, according to Martin-Fernandez et al. [36], 69% of Spanish adolescent patients met the DSM-5 criteria for IGD, and 91% of young Dutch patients met the IGD criteria through the C-VAT 0.2 [40]. However, only 37% of gamblers also experienced video game addiction as co-occurring disorder.

Furthermore, the effectiveness of impulsivity techniques to prevent gaming addiction has been demonstrated [35]. The most studied gaming problem is related to using MMORPGs [24,38,39], which has been researched through qualitative and mixed methods approaches to create a theoretical model [24] or to test CBT interventions [38,39]. The MMORPG online gaming addiction phenomenon has been described by Beranuy et al. [24], including use motivations (e.g., entertainment, escapism or disassociation, and virtual friendship) and factors associated with it, its symptomatology, and consequences (e.g., game context, conflict, and loss of control, respectively). Taquet and Hautekeete [38] and Torres-Rodriguez et al. [39] also highlighted good knowledge of the world of video games by the therapist and a balance between emotional and cognitive components in the intervention are positive factors to ensure therapeutic alliance and successful treatment outcome.

The scales used to measure gaming addiction in this European review were diverse and validated in different languages. These instruments include the AICA-S [41], Assessment of Pathological Computer Gaming (CSV-S [46]), Problem Video Game Playing Scale (PVP [47]), and the Video game dependency test (TDV [35]). Consequently, only a few of the assessed studies measured IGD, as stated by the APA [36,39,40] (e.g., the C-VAT 2.0 [40], the Internet Gaming Disorder test with 20 items (IGD-20 [48])).

School interventions have also been studied [30,35], usually to develop non-clinical measures for problematic gaming and Internet use, screen time, and other problems. The study from Denmark [30] did not find any problems regarding GIA or specific Internet uses in their population of study. On the other hand, a similar Spanish study [35] used an intervention for adolescents to prevent video gaming addiction and to treat two intervention groups with a program to prevent addiction to technologies (i.e., "PrevTec 3.1"). In one group, impulsivity management techniques were added to intensify the positive outcomes of the preventive program, in addition to a waitlist control group. They found the preventive program significantly reduced perceived dependence on video games, and the group who received instructions on impulsivity techniques maintained the successful results in the follow-up better than those who did not receive these techniques in the program. Accordingly, personality traits, such as impulsivity, appear to play a role in prevention on a long-term basis.

Ten lessons have been extracted regarding the problem gamer profile in Europe:


These studies also highlighted that preventative programs are effective over time in reducing gaming. However, in clinical settings, time spent gaming, age and gender, type of games (e.g., MMORPGs), and type of comorbidities were associated with gaming addiction (e.g., individuals with externalizing profiles have the best prognosis after three months and both profiles have a good prognosis at six months of treatment [36]). Moreover, lack of external parental control should be considered as important risk factor. However, one study did not find any specific psychiatric disorder as a risk factor for this addiction problem [28]. Thus, gaming addiction appears to be a unique clinical entity that can be treated by CBT (e.g., with a treatment length of three to six months). Follow-up studies are required to verify its benefits across groups and cultures.

#### 3.3.2. Internet Gambling Addiction

The main characteristics of Internet gambling addiction in Europe were:


Three studies (15.8%) addressed mainly Internet Gambling Disorder in clinical samples, suggesting it is a different clinical entity in comparison to IGD, although both share some sociodemographic characteristics (e.g., both usually affect males) and psychological features (e.g., type of emotional distress, higher harm avoidance, and reward dependence traits).

The measures used to assess gambling addiction can be considered traditional (i.e., Stinchfield's Diagnostic Questionnaire for Pathological Gambling [49], and the Problem Gambling Severity Index (PGSI [50])).

In addition, when gambling was the main addiction and the patient played videogames, the comorbidity was more severe than for Internet gaming addiction itself [31,34,36], specifically if gaming addiction was identified together with gambling addiction (in which case paranoid ideation, distress, OCD, and interpersonal sensitivity were also present [31]). However, inversely, comorbidity did not appear in gamblers who were not gaming addicts, although the reviewed research indicated that gambling addiction appeared to be the more severe behavioral addiction. In other words, both disorders appear to be independent of each other, which is supported by evidence regarding their different clinical profiles [24]. Internet gambling had a higher mean age of disordered onset, disorder severity, somatization and depression symptoms, among other personality traits (i.e., novelty seeking and persistence) and associations with substance use (e.g., tobacco use). Furthermore, patients with both problems are younger, present more dysfunctional personality traits (e.g., lower self-directedness and higher persistence), and general psychopathology (e.g., depression, anxiety, and social phobia), higher body mass index (BMI) and food addiction (FA). In summary, although both addictive online behaviors share some emotional distress and personality traits, gambling disorder appeared to be more severe in the included studies.

Moreover, online interventions seem only to be effective when the gambler seeks treatment, and a commitment with a health professional is made, even if it is short-lived; inversely, if there is no help-seeking the efficacy of any intervention is counter-productive or may have an aversive effect [33]; therefore, 'more is not always better' in terms of prevention. Lastly, CBT should also be personalized to the type of gambling activity (e.g., online poker), which again requires knowledge from the therapist, as highlighted in the case of gaming [38].
