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• Published: 28 November 2022

Psychological treatments for excessive gaming: a systematic review and meta-analysis

• Jueun Kim 1 ,
• Sunmin Lee 1 ,
• Dojin Lee 1 ,
• Sungryul Shim 2 ,
• Daniel Balva 3 ,
• Kee-Hong Choi 4 ,
• Jeanyung Chey 5 ,
• Suk-Ho Shin 6 &
• Woo-Young Ahn 5  

Scientific Reports volume  12 , Article number:  20485 ( 2022 ) Cite this article

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Despite widespread public interest in problematic gaming interventions, questions regarding the empirical status of treatment efficacy persist. We conducted pairwise and network meta-analyses based on 17 psychological intervention studies on excessive gaming ( n  = 745 participants). The pairwise meta-analysis showed that psychological interventions reduce excessive gaming more than the inactive control (standardized mean difference [SMD] = 1.70, 95% confidence interval [CI] 1.27 to 2.12) and active control (SMD = 0.88, 95% CI 0.21 to 1.56). The network meta-analysis showed that a combined treatment of Cognitive Behavioral Therapy (CBT) and Mindfulness was the most effective intervention in reducing excessive gaming, followed by a combined CBT and Family intervention, Mindfulness, and then CBT as a standalone treatment. Due to the limited number of included studies and resulting identified methodological concerns, the current results should be interpreted as preliminary to help support future research focused on excessive gaming interventions. Recommendations for improving the methodological rigor are also discussed.

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Introduction.

Excessive gaming refers to an inability to control one’s gaming habits due to a significant immersion in games. Such an immersion may result in experienced difficulties in one’s daily life 1 , including health problems 2 , poor academic or job performance 3 , 4 , and poor social relationships 5 . Although there is debate regarding whether excessive gaming is a mental disorder, the 11th revision of the International Classification of Diseases (ICD-11) included Gaming Disorder as a disorder in 2019 6 . While there is no formal diagnosis for Gaming Disorder listed in the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (DSM-5), the DSM-5 included Internet Gaming Disorder (IGD) as a condition for further study 7 . In the time since the DSM-5’s publication, research on excessive gaming has widely continued. Although gaming disorder’s prevalence appears to be considerably heterogeneous by country, results from a systematic review of 53 studies conducted between 2009 and 2019 indicated a global prevalence of excessive gaming of 3.05% 8 . More specifically, a recent study found that Egypt had the highest IGD prevalence rate of 10.9%, followed by Saudi Arabia (8.8%), Indonesia (6.1%), and India (3.8%) among medical students 9 .

While the demand for treatment of excessive gaming has increased in several countries 10 , standard treatment guidelines for problematic gaming are still lacking. For example, a survey in Australia and New Zealand revealed that psychiatrics— particularly child psychiatrists, reported greater frequency of excessive gaming in their practice, yet 43% of the 289 surveyed psychiatrists reported that they were not well informed of treatment modalities for managing excessive gaming 11 . Similarly, 87% of mental health professionals working in addiction-related institutions in Switzerland reported a significant need for professional training in excessive gaming interventions 12 . However, established services for the treatment of gaming remain scarce and disjointed.

Literature has identified a variety of treatments for excessive gaming, but no meta-analysis has yet been conducted on effectiveness of the indicated interventions. The only meta-analysis to date has focused on CBT 13 , and while results demonstrated excellent efficacy in reducing excessive gaming. However, the study did not compare the intervention with other treatment options. Given that gaming behavior is commonly affected by cognitive and behavioral factors as well as social and familial factors 14 , 15 , 16 , it would also be important to examine the effectiveness of treatment approaches that reflect social and familial influences. While two systematic reviews examined diverse therapeutic approaches, they primarily reported methodological concerns of the current literature and did not assess the weight of evidence 17 , 18 . Given that studies in this area are rapidly evolving and studies employing rigorous methodological approaches have since emerged 19 , 20 , a meta-analytic study that analyzes and synthesizes the current stage of methodological limitations while also providing a comprehensive comparison of intervention options is warranted.

In conducting such a study, undertaking a traditional pairwise meta-analysis is vital to assess overall effectiveness of diverse interventions. Particularly, moderator and subgroup analyses in pairwise meta-analysis provide necessary information as to whether effect sizes vary as a function of study characteristics. Furthermore, to obtain a better understanding of the superiority and inferiority of all clinical trials in excessive gaming psychological interventions, it is useful to employ a network meta-analysis, which allows for a ranking and hierarchy of the included interventions. While a traditional pair-wise analysis synthesizes direct evidence of one intervention compared with one control condition, a network meta-analysis incorporates multiple comparisons in one analysis regardless of whether the original studies used them as control groups. It enters all treatment and control arms of each study, and makes estimates of the differences in interventions by using direct evidence (e.g., direct estimates where two interventions were compared) and indirect evidence (e.g., generated comparisons between interventions from evidence loops in a network 21 . Recent meta-analytic studies on treatments for other health concerns and disorders have used this analysis to optimize all available evidence and build treatment hierarchies 22 , 23 , 24 .

In this study, the authors used a traditional pairwise meta-analysis and network meta-analysis to clarify the overall and relative effectiveness of psychological treatments for excessive gaming. The authors also conducted a moderator analysis to examine potential differences in treatment efficacy between Randomized Controlled Trials (RCTs) and non-RCTs, age groups, regions, and research qualities. Finally, the authors examined follow-up treatment efficacy and treatment effectiveness on common comorbid symptoms and characteristics (e.g., depression, anxiety, and impulsivity).

The protocol for this review has been registered in the International Prospective Register of Systematic Review (PROSPERO 2021: CRD 42021231205) and is available for review via the following link: https://www.crd.york.ac.uk/PROSPERO/display_record.php?RecordID=231205 . Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) network meta-analysis checklist 25 is included in Supplementary Material 1 .

Identification and selection of studies

The authors searched seven databases, which included ProQuest, PubMed, Scopus, Web of Science, PsycINFO, Research Information Sharing Service (RISS), and DBpia. Given that a substantial number of studies have been published particularly in East Asia and exclusion of literature from the area in languages other than English has been discussed as a major limitation in previous reviews 17 , 18 , the authors gave special attention to gaming treatment studies in English and other languages from that geographical area. Additionally, the authors searched Google Scholar to ensure that no studies were accidentally excluded. The authors conducted extensive searches for studies published in peer-reviewed journals between the first available year (year 2002) and October 31, 2022, using the following search terms: “internet”, or “video”, or “online”, or “computer”, and “game”, or “games”, or “gaming”, and “addiction”, or “addictions”, or “disorder”, “disorders”, or “problem”, or “problems”, or “problematic”, or “disease”, or “diseases”, or “excessive”, or “pathological”, or “addicted”, and “treatment”, or “treatments”, or “intervention”, or “interventions”, or “efficacy”, or “effectiveness”, or “effective”, or “clinical”, or “therapy”, or “therapies”. Search strategies applied to each database is provided in Supplementary Material 2 .

The authors included studies that recruited individuals who were excessively engaging in gaming, according to cutoff scores for different game addiction scales. Since there is not yet an existing consensus on operational definitions for excessive gaming, the authors included studies that recruited individuals who met high-risk cutoff score according to the scales used in each respective study (e.g., Internet Addiction Test [modified in game environments] > 70). The authors also sought studies that provided pretest and posttest scores from the game addiction scales in both the intervention and control groups. Studies meeting the following criteria were excluded: (a) the study targeted excessive Internet use but did not exactly target excessive gaming; (b) the study provided a prevention program rather than an intervention program; (c) the study provided insufficient data to perform an analysis of the effect sizes and follow-up contact to the authors of such studies did not yield the information necessary for inclusion within this paper; and (d) the study conducted undefinable types of intervention with unclear psychological orientations (e.g., art therapy with an undefined psychological intervention, fitness programs, etc.).

Two authors (D.L. and S.L.) independently screened the titles and abstracts of articles identified by the electronic searches and excluded irrelevant studies. A content expert (J.K.) examined the intervention descriptions to determine intervention types that were eligible for this review. All treatments were primarily classified based on the treatment theory, protocol, and descriptions about the procedures presented in each paper. D.L. and S.L.—both of whom have been in clinical training for 2 years categorized treatment type, to which J.K., a licensed psychologist, cross-checked and confirmed the categorization. The authors resolved disagreements through discussion. The specific example of intervention type classification is provided in Supplementary Material 3 .

Risk of bias and data extraction

Three independent authors assessed the following risks of bias among the included studies. The authors used the Risk of Bias 2.0 (RoB 2) tool for RCT studies and the Risk Of Bias In Non-Randomized Studies of Intervention (ROBINS-I) tool for non-RCT studies. The RoB 2 evaluates biases of (a) randomization processes; (b) deviations from intended interventions; (c) missing outcome data; (d) measurement of the outcome; and (e) selection of the reported result, and it categorizes the risk of bias in each dimension into three levels (low risk, moderate risk, and high risk). The ROBINS-I evaluates biases of (a) confounding variables; (b) selection of participants; (c) classification of interventions; (d) deviations from intended interventions; (e) missing data; (f) measurement of outcomes; and (g) selection of the reported result, and it categorizes the risk of bias in each dimension into five levels (low risk, moderate risk, serious risk, critical risk, and no information). After two authors (D.L. and S.L.) assessed each study, another author (J.K.) cross-checked the assessment.

For each study, the authors collected descriptive data, which included the sample size as well as participants’ ages, and regions where the studies were conducted. The authors also collected clinical data, including whether the study design was a RCT, types of treatment and control, treatment duration, and the number of treatment sessions. Finally, the authors collected data on the follow-up periods and the measurement tools used in each study.

Data analysis

The authors employed separate pairwise meta-analyses in active control and inactive control studies using R-package “meta” 26 and employed a random-effects model due to expected heterogeneity among studies. A random-effects model assumes that included studies comprise random samples from the larger population and attempt to generalize findings 27 . The authors categorized inactive control groups including no treatment and wait-list control and categorized active control groups including pseudo training (e.g., a classic stimulus-control compatibility training) and other types of psychological interventions (e.g., Behavioral Therapy, CBT, etc.). The authors also used the bias-corrected standardized mean change score (Hedges’ g ) due to small sample sizes with the corresponding 95% confidence interval 28 . The authors’ primary effectiveness outcome was a mean score change on game addiction scales from pre-treatment to post-treatment. Hedges’ g effect sizes were interpreted as small ( g  = 0.15), medium ( g  = 0.40) and large ( g  = 0.75), as suggested by Cohen 29 . The authors used a conservative estimate of r  = 0.70 for the correlation between pre-and post-treatment measures 30 , and to test heterogeneity, the authors calculated Higgins’ I 2 , which is the percentage of variability in effect estimates due to heterogeneity among studies rather than chance. I 2  > 75% is considered substantial heterogeneity 31 .

The authors conducted moderator analyses as a function of RCT status (RCT versus non-RCT), age group (adolescents versus adults), region (Eastern versus Western), and research quality (high versus low). The authors divided high versus low quality studies using median values of research quality scores (RCT: low [0–2] versus high [3–5], non-RCT: low [0–4] versus high [5]). The authors calculated Cochran’s Q for heterogeneity: A significant Q value indicates a potentially important moderator variable. For the subgroup analyses of follow-up periods and other outcomes, the authors conducted separate pairwise analyses in 1- to 3-month follow-up studies and in 4- to 6-month follow-up studies and separate analyses in depression, anxiety, and impulsivity outcome studies.

The authors sought to further explore relative effectiveness of treatment types and performed a frequentist network meta-analysis using the R-package “netmeta” 4.0.4 version 26 . To examine whether transitivity and consistency assumptions for network meta-analysis were met, the authors assessed global and local inconsistency. To test network heterogeneity, the authors calculated Cochran’s Q to compare the effect of a single study with the pooled effect of the entire study. The authors drew the geometry plot of the network meta-analysis through the netgraph function in “netmeta”, and the thicker lines between the treatments indicated a greater number of studies.

The authors presented the treatment rankings based on estimates using the surface area under the cumulative ranking curve (SUCRA) 32 . The SUCRA ranged from 0 to 100%, with higher scores indicating greater probability of more optimal treatment. The authors also generated a league table to present relative effectiveness between all possible comparisons between treatments. When weighted mean difference for pairwise comparisons is bigger than 0, it favors the column-defining treatment. Finally, funnel plots and Egger’s test were used to examine publication bias.

Included studies and their characteristics

Figure  1 presents the flow diagram of the study selection process. The authors identified 1471 abstracts in electronic searches and identified an additional seven abstracts through secondary/manual searches (total n  = 1478). After excluding duplicates ( n  = 765) and studies that did not meet the inclusion criteria based on the study abstract ( n  = 550), the authors retrieved studies with potential to meet the inclusion criteria for full review ( n  = 163). Of these, 144 studies were excluded due to not meeting inclusion criteria based on full-text articles, leaving 19 remaining studies. Of the 19, two studies did meet this paper’s inclusion criteria but were excluded from this network meta-analysis 33 , 34 because the consistency assumption between direct and indirect estimates was not met at the time of this study's consideration based on previous studies 35 , 36 . Therefore, a total of 17 studies were included in this network meta-analysis, covering a total of 745 participants 36 .

Flow diagram of the study selection process.

Table 1 lists the characteristics of the 17 included studies. CBT ( n  = 4), Behavioral Treatment (BT) + Mindfulness ( n  = 4), and BT only ( n  = 4) were most frequently studied, followed by CBT + Family Intervention ( n  = 1), CBT + Mindfulness ( n  = 1), virtual reality BT ( n  = 1), Mindfulness ( n  = 1), and Motivational Interviewing (MI) + BT ( n  = 1). Seven studies were conducted in Korea and six were conducted in China, followed by Germany and Austria ( n  = 1), Spain ( n  = 1), the United States ( n  = 1), and the Philippines ( n  = 1). Twelve articles were written in English, and five articles were written in a language other than English. Nine studies conducted a follow-up assessment with periods ranging from one to three months, and two studies conducted a follow-up assessment with periods ranging four to six months. In one study 20 , the authors described their 6-month follow-up but did not present their outcome value, and thus only two studies were included in the four- to six-month follow-up analysis. Among the 17 included studies, eight had no treatment control group, five had an active control group (e.g., pseudo training, BT, and CBT), and four had a wait-list control group. Seven of the studies were RCT studies, and 10 were non-RCT studies.

Pairwise meta-analysis

The results of meta-analyses showed a large effect of all psychological treatments when compared to any type of comparison groups ( n  = 17, g  = 1.47, 95% CI [1.07, 1.86]). The treatment effects were separately provided according to active versus inactive comparison groups in Fig.  2 . The effects of psychological treatments were large when compared to the active control ( n  = 5, g  = 0.88, 95% CI [0.21, 1.56]) or inactive control ( n  = 12, g  = 1.70, 95% CI: [1.27, 2.12]). Substantial heterogeneity was evident in studies that were compared to both the active controls (I 2  = 72%, < 0.01) and inactive controls at p -value level of 0.05 (I 2  = 69%, p  < 0.001).

Pairwise Meta-analysis. Psychological treatment effects on excessive gaming by comparison group type (active and inactive controls). SMD standardized mean difference, SD standard deviation,  CI confidence interval, I 2  = Higgins' I 2 .

Moderator analysis

As shown in Table 2 , the moderator analysis suggested that effect sizes were larger in non-RCT studies ( n  = 10, g  = 1.60, 95% CI [1.36, 1.84]) than RCT studies ( n  = 7, g  = 1.26, 95% CI [0.30, 2.23]). However, the results of a Q-test for heterogeneity yielded insignificant results (Q = 0.44, df[Q] = 1, p  = 0.51), indicating that no statistically significant difference in treatment efficacy at p level of 0.05 between RCT and non-RCT studies.

The results of Q-test for heterogeneity did not yield any significant results, indicating no significant differences in treatment efficacy between adults and adolescents (Q = 2.39, df[Q] = 1, p  = 0.12), Western and Eastern regions (Q = 0.40, df[Q] = 1, p  = 0.53), or low and high research qualities among RCT studies (Q = 2.25, df[Q] = 1, p  = 0.13) and non-RCT studies (Q = 3.06, df[Q] = 1, p  = 0.08).

Subgroup analysis

The results demonstrated that the treatment effect was Hedges’ g  = 1.54 (95% CI [0.87, 2.21]) at 1-to-3-month follow-up and Hedges’ g  = 1.23 (95% CI [0.77, 1.68]) 4- to-6-month follow-up. The results also showed that the treatment for excessive gaming was also effective on depression and anxiety. Specifically, treatment on depression was Hedges’ g  = 0.52 (95% CI: [0.22, 0.81], p  < 0.001), and anxiety was Hedges’ g  = 0.60 (95% CI [0.11, 1.08], p  = 0.02), which are medium and significant effects. However, the effect on impulsivity was insignificant, Hedges’ g  = 0.26 (95% CI [− 0.14, 0.67], p  = 0.20).

Network meta-analysis

As shown in Fig.  3 , a network plot represents a connected network of eight intervention types (CBT, BT + Mindfulness, BT, Virtual Reality BT, CBT + Mindfulness, CBT + Family, MI + BT, and Mindfulness) and three control group types (wait-list control, no treatment, treatment as usual). The widest width of nodes was observed when comparing BT + Mindfulness and no treatment, indicating that those two modules were most frequently compared. No evidence of global inconsistency based on a random effects design-by-treatment interaction model was found (Q = 8.5, df[Q] = 7, p  = 0.29). Further, local tests of loop-specific inconsistency did not demonstrate inconsistency, indicating that the results from the direct and indirect estimates were largely in agreement ( p  = 0.12- 0.78).

Network plot for excessive gaming interventions. Width of lines and size of circles are proportional to the number of studies in each comparison. BT behavioral therapy, CBT cognitive behavioral therapy, Family family intervention, MI motivational interviewing, TAU treatment as usual.

As shown in Fig.  4 , according to SUCRA, a combined intervention of CBT and Mindfulness ranked as the most optimal treatment (SUCRA = 97.1%) and demonstrated the largest probability of effectiveness when compared to and averaged over all competing treatments. A combined treatment of CBT and Family intervention ranked second (SUCRA = 90.2%), and Mindfulness intervention ranked third (SUCRA = 82.1%). As shown in Table 3 , according to league table, CBT + Mindfulness intervention showed positive weighted mean difference values in the lower diagonal, indicating greater effectiveness over all other interventions. The CBT + Mindfulness intervention was more effective than CBT + Family or Mindfulness interventions, but their differences were not significant (weighted mean differences = 0.23–1.11, 95% CI [− 1.39 to 2.68]). The top three ranked interventions (e.g., CBT + Mindfulness, CBT + Family intervention, and Mindfulness in a row) were statistically significantly superior to CBT as a standalone treatment as well as the rest of treatments.

Surface under the cumulative ranking curve (SUCRA) rankogram of excessive gaming. BT behavioral therapy, CBT cognitive behavioral therapy, Family family intervention, MI motivational interviewing, TAU treatment as usual.

Risk of bias

Figure  5 displays an overview of the risk of bias across all included studies. Of note was that in the RCT studies, bias due to missing outcome data was least problematic, indicating a low dropout rate (six out of seven studies). In contrast, bias due to deviations from intended interventions was most problematic, indicating that, in some studies, participants and trial personnel were not blinded and/or there was no information provided as to whether treatments adhered to intervention protocols (six out of seven studies). In the non-RCT studies, bias in the selection of participants in the study was least problematic, indicating that researchers did not select participants based on participant characteristics after the start of intervention (10 out of 10 studies). In contrast, bias in the measurement of outcomes was most problematic, indicating that participants and outcome assessors were not blinded and/or studies used self-reported measures without clinical interviews (10 out of 10 studies).

Overview of risk of bias results across all included studies. Cl bias in classification of interventions, Co bias due to confounding, De bias due to deviations from intended interventions, Me bias in measurement of the outcome, Mi bias due to missing outcome data, R bias arising from the randomization process, RoB risk of bias, ROBINS-I risk of bias in non-randomized studies of intervention, Sp bias in selection of participants in the study, Sr bias in selection of the reported result.

Funnel plots and Egger’s test showed no evidence of publication in network meta-analyses. Funnel plots were reasonably symmetric and the result from Egger’s test for sample bias were not significant ( p  = 0.22; see Supplementary Material 4 ).

In this pairwise and network meta-analyses, the authors assessed data from 17 trials and analyzed the overall and relative effectiveness of eight types of psychological treatments for reducing excessive gaming. The pairwise meta-analysis results indicated large overall effectiveness of psychological treatments in reducing excessive gaming. Although the effectiveness was smaller when compared to the active controls than when compared to the inactive controls, both effect sizes were still large. However, this result needs to be interpreted with caution because there are only seven existing RCT studies and several existing low-quality studies. Network meta-analysis results indicated that a combined treatment of CBT and Mindfulness was the most effective, followed by a combined therapy of CBT and Family intervention, Mindfulness, and then CBT as a standalone treatment, however, this finding was based on a limited number of studies. Overall, the findings suggest that psychological treatments for excessive gaming is promising, but replications are warranted, with additional attention being placed on addressing methodological concerns.

The large effect of psychological treatments in reducing excessive gaming seems encouraging but the stability and robustness of the results need to be confirmed. These authors’ moderator analysis indicated that the effect size of non-RCT studies was not significantly different from that of RCT studies. The authors conducted a moderator analysis using the research quality score (high vs low) and found that research quality did not moderate the treatment effect. The authors also examined publication bias using both funnel plots and Egger’s test and found no evidence of publication bias in network meta-analysis. Because most of the studies included in the review were from Asian countries, the authors examined the generalizability of the finding by testing moderator analysis by regions and found no significant difference of treatment effect sizes between Eastern and Western countries. Finally, although limited studies exist, treatment benefits did not greatly diminish after 1–6 months of follow-ups, indicating possible lasting effects.

Network meta-analysis findings provide some preliminary support for the notion that a combined treatment of CBT and Mindfulness and a combined treatment of CBT and Family intervention are most effective in addressing individuals’ gaming behaviors. These combined therapies were significantly more effective than the CBT standalone approach. CBT has been studied and found to be highly effective in addiction treatment—particularly in reducing excessive gaming due to its attention to stimulus control and cognitive restructuring 13 . However, adding Mindfulness and family intervention may have been more effective than CBT alone, given that gaming is affected not only by individual characteristics, but also external stress or family factors.

Mindfulness generally focuses on helping individuals to cope with negative affective states through mindful reappraisal and aims to reduce stress through mindful relaxation training. The effectiveness of Mindfulness has been validated in other substance and behavioral addiction studies such as alcohol 37 , gambling 38 , and Internet 39 addiction treatments. Indulging in excessive gaming is often associated with the motivation to escape from a stressful reality 40 , and mindful exercises are likely to help gamers not depend on gaming as a coping strategy.

Because excessive gaming is often entangled with family environments or parenting-related concerns—particularly with adolescents, addressing appropriate parent–adolescent communication and parenting styles within excessive gaming interventions are likely to increase treatment efficacy 41 , 42 , 43 . Based on a qualitative study focused on interviews with excessive gamers 43 , and per reports from interviewed gamers, parental guidance to support regulatory control and encouragement to participate in other activities are important factors to reduce excessive gaming. However, at the same time, if parents excessively restrict their children’s behavior, children will feel increased stress and may further escape into the online world through gaming 44 as a means of coping with their stress. Our study indicates that appropriate communication among parents and adolescents in addition to parenting styles with respect to game control must be discussed in treatment. However, because only two studies examined the top two ranked combined interventions within this paper, such findings warrant replication.

Limitations and future directions

These authors identified methodological limitations and future directions in the reviewed studies, which include the following. The authors included non-RCTs to capture data on emerging treatments, but a lack of RCT studies contributes to this paper’s identified methodological concerns. Of 17 studies included, seven were RCT studies and 10 were non-RCT studies. The lack of RCT studies has been repeatedly mentioned in previous review studies 17 , 18 . In fact, one of the two identified reviews 17 made the criticism that even CBT (the most widely studied treatment for excessive gaming) was mostly conducted in non-RCT studies, which was commensurate with this paper’s data (only one out of four CBT studies included in this review is a RCT). Including non-RCTs may be likely to increase selection bias by employing easily accessible samples and assigning participants with more willingness (which is an indicator of better treatment outcome) to intervention groups. Selection bias may have increased the effect size of treatments than what is represented in reality and may limit the generalizability of this finding. Thus, more rigorous evaluation through RCTs is necessary in future studies.

While there are concerns surrounding assessment tools, given that all included studies used self-report measures without clinical interviews, this may lead to inaccurate results due to perceived stigma. Additionally, 11 self-reported measurement tools were employed in the included studies—and some of those tools may have poor sensitivity or specificity. A previous narrative review 45 and a recent meta-analytic review 46 suggested that the Game Addiction Scale-7, Assessment of Internet and Computer Addiction Scale-Gaming, Lemmens Internet Gaming Disorder Scale-9, Internet Gaming Disorder Scale 9- Short Form, and Internet Gaming Disorder Test-10 have good internal consistency and test–retest reliability. Thus, there is a need for studies to employ clinical interviews and self-report measures with good psychometric features.

Many studies in this included review did not describe whether participants and experimenters were blinded and there was no information about whether treatments adhered to intervention protocols. Although blinding of participants and personnel may be impossible in most psychotherapy studies, it is crucial to evaluate possible performance biases such as social desirability. Also, a fidelity check by content experts is needed to confirm whether treatments adhered to intervention protocols.

Finally, future studies need to examine treatment efficacy in treating both excessive gaming and its comorbid psychiatric symptoms. Internet/gaming addiction has been reported to have a high comorbidity with attention deficit hyperactivity disorder, depression, anxiety, and other substance abuse 47 , 48 . Our results showed that CBT, BT, and BT + Mindfulness may be effective in reducing depression or anxiety symptoms of excessive gamers. However, other psychological and/or pharmacological treatments such as CBT + Bupropion or Bupropion as a standalone treatment have been also reported as potentially effective treatments for excessive gamers with major depressive disorder 49 , 50 . Thus, it would be worthwile to examine efficacy of treatments on excessive gamers with dual diagnoses.

TO the best of the authors’ knowledge, this is the first pairwise meta-analytic and network meta-analytic study that examined the overall effectiveness of psychological treatments and compared the relative effectiveness of diverse treatment options for excessive gaming. Although the authors intentionally used network meta-analysis because of its usefulness in comparing relative effectiveness of currently existing literature, this finding should be interpreted with caution due to the small number of studies. However, as previously indicated, the global prevalence of excessive gaming highlights the need for greater attention to this topic. Studies focused on the effectiveness of diverse gaming interventions help meet the call for further inquiry and study on this topic placed by the DSM-5 7 , and allow greater advances to be made in treating individuals who may have difficulty controlling excessive gaming habits. As such, this study can provide preliminary support for beneficial treatment interventions for excessive gaming as well as recommendations for more rigorous studies to be directed at helping those who have excessive gaming habits.

Data availability

The datasets used and/or analyzed during the current study are available from the corresponding author upon reasonable request.

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This research was supported by the project investigating scientific evidence for registering gaming disorder on Korean Standard Classification of Disease and Cause of Death funded by the Ministry of Health and Welfare and Korea Creative Content Agency.

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Symptoms, Mechanisms, and Treatments of Video Game Addiction

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• 1 Department of Anatomy, Taibah University, Madinah, SAU.
• 2 Collage of Medicine, Taibah University, Madinah, SAU.
• PMID: 37009362
• PMCID: PMC10065366
• DOI: 10.7759/cureus.36957

Video game addiction is defined as the steady and repetitive use of the Internet to play games frequently with different gamers, potentially leading to negative consequences in many aspects of life. As recent technological development has given easy access to gaming on many devices, video game addiction has become a serious public health issue with increased prevalence. Many studies have shown that video game addiction leads to changes in the brain that are similar to those that occur in substance addiction and gambling. Evidence has also shown that there is an association between video game addiction and depression, as well as other psychological and social problems. In light of these issues, our review article aims to increase awareness of video game addiction in society. The main objectives of this review are as follows: to describe the mechanism of addiction, to consider whether video game addiction is a real addiction, and to highlight the signs and symptoms of addiction. In addition, we identify the consequences of video game addiction and possible treatments for addicts. The information was extracted from high-quality research papers and reliable websites like PubMed and ScienceDirect.

Keywords: addiction; internet gaming disorders; mechanism of addiction; treatment of addiction; video game addiction.

Copyright © 2023, Mohammad et al.

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• Published: 12 December 2020

Video gaming addiction and its association with memory, attention and learning skills in Lebanese children

• Youssef Farchakh 1 ,
• Chadia Haddad 2 , 3 ,
• Hala Sacre 4 ,
• Sahar Obeid 2 , 4 , 5   na1 ,
• Pascale Salameh 4 , 6 , 7   na1 &
• Souheil Hallit   ORCID: orcid.org/0000-0001-6918-5689 1 , 4   na1  

Child and Adolescent Psychiatry and Mental Health volume  14 , Article number:  46 ( 2020 ) Cite this article

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Examining whether any association exists between addiction to video games and cognitive abilities in children could inform ongoing prevention and management of any possible harm. The objective of this study was to investigate the associations between addiction to video games, and memory, attention and learning abilities among a sample of Lebanese school children.

This cross-sectional study, conducted between January and May 2019, enrolled 566 school children aged between 9 and 13 years. Three private schools were chosen conveniently for this study. Students were randomly chosen from the list given by the school administration. The students’ parents are those who responded to the questionnaire.

The results showed that higher addiction to video gaming salience was significantly associated with worse episodic memory, problem solving, basic reading skills, written expression skills and worse clinical attention. Higher addiction to video gaming tolerance were significantly associated with worse novel problem solving and worse attention. Higher addiction to video gaming withdrawal were significantly associated with worse attention, factual memory, attention, processing speed, visual spatial organization, sustained sequential processing, working memory, novel problem solving and worse written expression skills.

The results suggest a correlation between addiction to video games and worse memory, attention, as well as cognitive and academic abilities among school children. Those findings indicate the need for more extensive research, and serve to highlight vital next steps needed in future papers, such as identifying predicting factors that could aid in early detection of video gaming addiction in children.

Recent advances in new technologies have made video games the top leisure time occupation for children, who are particularly susceptible for addiction. Currently, video games have become the most famous type played worldwide among children. Nielsen reports that total weekly time spent playing games increased expeditiously from 5.1 to 6.3 h in 2011 and 2013 respectively [ 1 ]. In a study involving children aged between 9 and 12, from 12 different countries, it was found that 8.6 h per day were spent on playing video games [ 2 ]. Importantly, the emerging phenomenon of video game addiction represents a real and potential widespread problem that defies easy solutions and prevention methods, and requires further investigations, especially in the childhood population.

In fact, despite the benefits that video games have, such as socialization and entertainment, empirical and clinical studies have frequently demonstrated that the excessive use of video games may drive to adverse consequences in miscellaneous areas of psychological development and can result in an addiction among a small portion of gamers [ 3 ]. Impaired control over gaming and increasing priority over daily activities and other life interests could manifest as an evidence of gaming addiction [ 4 ]. In its fifth edition, the Diagnostic and Statistical Manual of Mental Disorders (DSM-5) identified video game addiction in the form of internet gaming disorder, as a condition in need of supplementary studies [ 5 ]. Additionally, the 11th revision of International Classification of Diseases (ICD-11) defined gaming disorder as a recurrent gaming behavior pattern that carries both offline and online gaming [ 6 ]. Science suggests that addictions arise from a mixture of a genetic predisposition and a repeated exposure to a particular substrate [ 7 ].

Along with that, there has been growing public concerns about potential adverse effects, including the possibility that video games might affect memory in children [ 8 ]: as an important process for comprehension, memory updating and working memory, among other cognitive skills, have usually been reported to be damaged across different behavioral disorder individuals and addictive populations [ 9 ]. Even though there are some studies that investigate the effect of video games on cognitive functions and academic performance in children [ 10 , 11 ], consequences on memory are still a prevalent subject of debate.

Although video gaming is a free time activity, it does cause problems for some children, affecting their attention competencies. Both a meta-analysis and a systematic review conducted by Ho et al. and Carli et al. respectively suggested an association between inattention and internet/gaming addiction [ 12 ]. Moreover, plenty of other studies supported this finding and proved a strong correlation between the severity of inattention in attention deficit hyperactivity disorder (ADHD) and internet/gaming addiction [ 13 ], even after regulating the effects of depression and anxiety symptoms, as well as personality traits [ 12 ].

Unsurprisingly, video gaming advancements have led to concerns from parents and educators that the exaggerated amount of time consumed by children on video games, may result in decreased learning and academic abilities [ 11 ]. Handful of studies have generated inconclusive results regarding a possible association between poor school grades and problematic gaming [ 11 , 14 ]. Furthermore, in cross-sectional studies, pathological video gaming has been connected to a range of negative consequences, such as lower school and academic performances, but the need for further research to explore this finding is mandatory [ 11 ]. Moreover, researchers have been attempting to shed light on addiction to video games and its association with children’s development and behaviors. Despite all the efforts made, the literature still lacks sufficient studies on the subject.

In Lebanon, adolescents showed a 43.6% of moderate to severe problematic internet use [ 15 ]. Children are affected by video gaming and its related addiction. According to a Lebanese research study published in 2018, gaming disorder was associated with being younger. Moreover, Lebanese children are witnessing devastating long-term adverse effects on their behavioral, physical and psychological health, due to the rapidly advancing technology, which makes it very essential to focus on this particular Lebanese age group [ 14 ]. From the research point of view, only three Lebanese studies were detected concerning video games addiction [ 14 , 16 , 17 ]. Two of them worked on the development and validation of specific scales for video games addiction and internet gaming disorder [ 15 , 16 ], while the third one explored the relationships between gaming disorders, sleep habits, and academic achievement in Lebanese adolescents [ 14 ]. The last study showed that the pooled prevalence of internet gaming disorder was 9.2% [ 14 ]. Examining whether any association exists between addiction to video games and cognitive abilities in children could inform ongoing prevention and management of any possible harm. The objective of this study was to investigate the associations between addiction to video games, and memory, attention and learning abilities among a sample of Lebanese schoolchildren.

Participants

This study was a cross-sectional, conducted between January and May 2019. Three private schools were chosen conveniently for this study. Students were randomly chosen from the list given by the school administration. All participants between the age of 9 and 13 years of age were eligible to participate. The students’ parents are those who answered the questionnaire. Prior to participation, parents were briefed on the study objectives and methodology, and were assured of the anonymity of their participation. Parents had the right to accept or refuse participation in the study, with no financial compensation provided in return.

Sample size calculation

The Epi info program [Centers for Disease Control and Prevention (CDC), Epi Info™] was employed for the calculation of the required sample size for our study, with a prevalence of internet gaming disorder of 9.2% among 524 Lebanese high school students from a study done by Hawi et al. [ 14 ], with an acceptable margin of error of 5% and design effect of 2. The youth population is estimated to be 585,000 according to the UNDP statistics in Lebanon; the result showed that the biggest required sample size is 256 participants.

The questionnaire was distributed to each student in the classroom to be taken home. Parents filled it within 25 min approximately. The completed questionnaires were collected back and sent for data entry. During the data collection process, the anonymity of the participants was guaranteed.

Questionnaire

The self-administered questionnaire used was in Arabic, the native language of Lebanon. The first part assessed the sociodemographic details of the participants (i.e. age, gender, grade, and father and mother education level). The second part of the questionnaire included the following scales:

Game Addiction Scale for Children (GASC)

The 21-item Gaming Addiction Scale (GASC) is an instrument based on DSM criteria to assess gaming addiction. The seven items in the GAS are rated using a five-point Likert scale ranging from 1 (never) to 5 (very often). A higher score on the GAS indicates more problematic use of online gaming. The scale measures 7 criteria of computer addiction: salience, tolerance, mood modification, withdrawal, relapse, conflict and problems [ 18 ]. In this study, the Cronbach alpha values for the GAS was 0.948.

Children’s Memory Questionnaire (CMQ)

The CMQ is a 36-item questionnaire designed to assess parents’ perceptions of their children’s memory. The CMQ requires parents to assess their child’s memory based on five possible options: 1 = never or almost never happens; 2 = happens less than once a week; 3 = happens once or twice in a week; 4 = happens about once a day; and 5 = happens more than once a day [ 19 ]. Three subscales derived from the total scale representing the episodic memory, visual memory and working memory and attention. The higher the scores, the greater the impairment in the cognition domain [ 19 ]. In this study, the Cronbach alpha values for the episodic memory subscale was 0.888, for the visual memory was 0.770 and for the working memory was 0.845.

Clinical attention problems scale

The scale measures the frequency of activity and attention by asking the parent and teacher to respond to a series of 12 statements and their applicability to their child in the morning and afternoon. Response options range from “not true” (0), “somewhat or sometimes true” (1), “very often” or often true (2). The higher the scores, the greater the attention problems exist [ 20 ]. In this study, the Cronbach alpha values for the clinical attention problem in the morning and in the afternoon were 0.844 and 0.839 respectively.

Learning, Executive and Attention Functioning (LEAF) Scale

The LEAF is a 55 item self-report questionnaire that assesses executive functions, related neurocognitive functions, and academic skills in children and adults. The LEAF evaluates a broad set of core cognitive abilities as well as related cognitive learning and academic abilities. Cognitive areas assessed by the LEAF include attention, processing speed (including visual-spatial organization skills), and sustained sequential processing to achieve goals (e.g., planning and executing goal-directed behavior), working memory, and novel problem-solving. Also, LEAF includes comprehension and concept formation, declarative/factual memory, and academic functioning. The LEAF contains Academic subscales assessing reading, writing, and math fluency and abilities. LEAF items are grouped by subscale, and all subscales have the same number of items.

The subscales of the LEAF are: (1) comprehension and conceptual learning (tracking and understanding information), (2) factual memory (memorization and retention of facts); (3) attention (sustained focus); (4) processing speed (speed of completing cognitive and behavioral tasks that involve a component of focus and concentration); (5) visual-spatial organization (organization and visual-constructive skills); (6) sustained sequential processing (planning and sustaining effort in order to follow and complete multistep directions and sequences); (7) working memory (remembering and processing multiple things at the same time); and (8) novel problem solving (initiating effort toward processing new or unfamiliar information). (9) Mathematics skills (math calculation difficulty); (10) basic reading skills (reading/phonics difficulty); and (11) written expression skills (limited/impoverished or slow/effortful written expression). Individual items are rated on a 0–3 scale, and a raw subscale score for each of the 11 content areas is created by summing the 5 constituent items, such that higher scores indicate more cognitive problems [ 21 ]. In this study, the Cronbach alpha values for the subscales was: comprehension and conceptual learning = 0.961; factual memory = 0.792; attention = 0.901; processing speed = 0.866; visual-spatial organization = 0.729; sustained sequential processing = 0.768; working memory = 0.816; novel problem solving = 0.811; mathematics skills = 0.871; basic reading skills = 0.923 and written expression skills = 0.905.

Translation procedure

The forward translation was done by one translator. An expert committee formed by healthcare professionals and a language professional verified the Arabic translated version. A backward translation was then performed by a second translator, unaware of the initial English version. The back-translated English questionnaire was subsequently compared to the original English one, by the expert committee. Discrepancies related to inadequate expressions and concepts, confusing in meaning and slightly off in meaning during the reconciliation of the back translated questionnaire with the original source were resolved by consensus.

Statistical analysis

SPSS software version 23 was used to conduct data analysis. Cronbach’s alpha values were recorded for reliability analysis for all the scales. A descriptive analysis was done using the counts and percentages for categorical variables and mean and standard deviation for continuous measures. A multivariate analysis of covariance (MANCOVA) was carried out to compare multiple measures (each scale was taken as a dependent variable) taking the GAS as the major independent variable, controlling for potential confounding variables: age, gender, family monthly income, and mother and father education level. A p-value less than 0.05 was considered significant.

Out of 700 distributed questionnaires, 566 (80.86%) questionnaires were completed and collected back. The sociodemographic characteristics of the participants are summarized in Table 1 . The mean age was 10.77 ± 1.38 years, with 55.2% male. Also, higher education level in parents was found in 58.9% among mother and 39.4% among father.

Description of the scales used

The description of all the scales used in terms of mean, standard deviation, median, minimum and maximum is summarized in Table 2 .

Bivariate analysis

The bivariate analysis of the sociodemographic variables associated with the memory and attention scores is summarized in Tables 3 and 4 .

Higher addiction to video gaming salience, tolerance, relapse, withdrawal, conflict and problems scores were significantly correlated with lower/worse episodic memory, working memory, visual memory, clinical attention in the morning and in the afternoon, comprehension and conceptual learning, factual memory, LEAF attention, processing speed, visual spatial organization, sustained sequential processing, LEAF working memory, novel problem solving, mathematics skills, basic reading and written expression skills scores, except for the mood modification that was not associated with the visual memory and mathematics skills scores (Table 5 ).

Multivariate analysis

The MANCOVA analysis was performed taking the scales as the dependent variables and the addiction to video gaming salience as the independent variable, adjusting for the covariates (age, gender, family monthly income, and mother and father education levels).

Higher addiction to video gaming salience was significantly associated with higher episodic memory score (worse episodic memory), higher novel problem solving score (worse problem solving), higher basic reading skills score (worse basic reading skills), higher written expression skills score (worse written expression skills) and higher clinical attention in the morning and afternoon scores (worse episodic memory and attention).

Higher addiction to video gaming tolerance were significantly associated with higher novel problem solving score (worse novel problem solving) and higher clinical attention in the morning and afternoon scores (worse attention).

Higher addiction to video gaming withdrawal were significantly associated with higher clinical attention in the afternoon score (worse attention), higher factual memory score (worse factual memory), higher attention score (worse attention), higher processing speed score (worse processing speed), higher visual spatial organization score (worse visual spatial organization), higher sustained sequential processing score (worse sustained sequential processing), higher working memory score (worse working memory), higher novel problem solving score (worse novel problem solving) and higher written expression skills score (worse written expression skills) (Table 6 ).

Thus far, this is the first study to be conducted on Lebanese school children to evaluate the association between addiction to video games, memory, attention and learning abilities. Taking into consideration that intensive video gaming has frequently been linked to the development of addictive-like behaviors among children, we found highly important to assess some cognitive factors that could be affected in this delicate population. The results showed that higher addiction to video gaming was significantly associated with higher memory score (worse memory), with higher attention score (worse attention), and higher LEAF scale and subscales scores (worse cognitive and academic abilities). We also found that having a father with university education level was significantly associated with lower attention score (better attention) and lower LEAF scale and subscales scores (better cognitive and academic abilities).

Higher addiction to video gaming was significantly associated with higher memory score (worse memory). When the different studies were reviewed, the results were found to be contradictory. Some of the studies argued that video games have negative effects on memory, while other ones did not support this finding [ 22 ]. Moreover, an observational study comparing patients with internet gaming disorder against healthy control groups revealed that the formers had lower working memory functioning [ 8 ]. This particular result regarding memory may relate to the fact that spending too much time playing the same type of games could be harming their abilities to retain and boost memories.

Moreover, higher addiction to video gaming was significantly associated with higher attention score (worse attention). Similar to our results, increasing behavioral studies proved that video games addicts showed attention deficits. De facto, Zhou et al. [ 23 ] demonstrated that when performing the attention-related task, more total error rates was observed in subjects with internet gaming addiction in comparison to controls. To boot, Song et al. [ 24 ] established a positive correlation between inattention and internet gaming addiction severity, while lack of attention was verified to be a high predictor of online gaming addiction by Ko et al. [ 25 ]. The finding we obtained could be interpreted by the instant rewards and constant stimulation of video games that raise the threshold for children to pay attention in less stimulating situations, where working harder is required to get rewards. Another theory could be that children suffering from attentional problems become captivated by video games as a coping strategy of their behavioral disorder.

Likewise, higher addiction to video gaming was significantly associated with higher LEAF scale and subscales scores (worse cognitive and academic abilities). Correspondingly, Gentile et al. [ 26 ] found that video games addiction among Singaporean adolescents predicted worse school grades and cognitive well-being. In contrast, another study conducted by Regina et al. [ 11 ] demonstrated no evidence that excessive video gaming negatively affects adolescents’ school performances. Our result may be understood in the light of the fact that more time spent on video games means less time spent on academic activities, as well as less hours of sleep overall, which generally make children with heavy video gaming attitudes, less alert and more susceptible to cognitive errors.

In addition to the previous findings, having a father with university education level was significantly associated with lower attention score (better attention) and lower LEAF scale and subscales scores (better cognitive and academic abilities). To our knowledge, no study in the literature discussed the education level of the parents, particularly the father, in this particular context. The cause for our result could be that highly educated fathers raise their children in a similar educative way, which enhances their cognitive and academic skills.

Clinical implications

The current study provides many valuable contributions to the literature. Despite growing numbers of published studies examining cognitive skills in children playing video games, there is a paucity of rigorous ones from which to draw firm conclusions. This study procures firm evidence that addiction to video games is linked to worse memory, attention, as well as cognitive and academic skills in school children. This analysis constitutes a vital first step towards a better understanding of video games addiction in children, supporting its evidence as a plausible entity with detrimental association. By this, the study encourages parents of children addicted to video games to set particular gaming rules (such as limiting gaming time and avoiding exploration of new games), advocates schools to introduce children to other fun activities to do, and highlights the importance of consulting a therapist in extreme cases.

Limitations

There are several limitations that should be noted. First of all, all scales were self-rated, which may only show high risk of addiction to video gaming rather than the diagnosis. Second, residual confounding bias is also possible, since there could be factors related to video gaming such as pre-existing attention problems, ADHD diagnosis that were not measured in this study. Moreover, parents might have over-or underestimated the answers to the questions, possibly predisposing us to information bias. A selection bias is also possible because of the enrollment of the students from three schools only and because of the convenient sample. The group of students chosen in this study were not representative of most of students in their age. Students’ parents filled up the video gaming addiction scale, which could lead to information bias since this scale is not applicable to them. To add on that, since this study is cross-sectional, the findings of this study cannot address the causal relationships among the primary constructs of interest. Finally, the scales used have not been validated in Lebanon. The use of a random sample is an important advantage to the study, thus, the results we obtained can be generalized to the whole population. The results cannot be generalized to the whole population since it only recruited students from private schools, as well as a high percentage of well-educated mothers. A prospective longitudinal study is needed to better follow up the cognitive function of children over time.

In conclusion, the results suggest a correlation between addiction to video games and worse memory, attention, as well as cognitive and academic abilities among school children. Those findings indicate the need for more extensive research, and serve to highlight vital next steps needed in future papers, such as identifying predicting factors that could aid in early detection of video gaming addiction in children.

Availability of data and materials

There is no public access to all data generated or analyzed during this study to preserve the privacy of the identities of the individuals. The dataset that supports the conclusions is available to the corresponding author upon request.

Abbreviations

Diagnostic and Statistical Manual of Mental Disorders

11th Revision of International Classification of Diseases

Attention deficit hyperactivity disorder

Game Addiction Scale for Children

Children’s Memory Questionnaire

Learning, Executive and Attention Functioning Scale

Multivariate analysis of covariance

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Acknowledgements

The authors would like to thank the mothers for accepting to be part of this study.

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Sahar Obeid, Pascale Salameh, and Souheil Hallit are last co-authors

Authors and Affiliations

Faculty of Medicine and Medical Sciences, Holy Spirit University of Kaslik (USEK), Jounieh, Lebanon

Youssef Farchakh & Souheil Hallit

Research and Psychology Departments, Psychiatric Hospital of the Cross, P.O. Box 60096, Jal Eddib, Lebanon

Chadia Haddad & Sahar Obeid

INSERM, Univ. Limoges, CH Esquirol, IRD, U1094 Tropical Neuroepidemiology, Institute of Epidemiology and Tropical Neurology, GEIST, Limoges, France

Chadia Haddad

INSPECT-LB: Institut National de Santé Publique, Epidémiologie Clinique Et Toxicologie-Liban, Beirut, Lebanon

Hala Sacre, Sahar Obeid, Pascale Salameh & Souheil Hallit

Faculty of Arts and Sciences, Holy Spirit University of Kaslik (USEK), Jounieh, Lebanon

Sahar Obeid

Faculty of Pharmacy, Lebanese University, Beirut, Lebanon

Pascale Salameh

Faculty of Medicine, University of Nicosia, Nicosia, Cyprus

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Contributions

The authors would like to thank Mr. Jihad Gerges, Mr. Joseph Chahine and the following persons of College Central des Moines Libanais Maronites—Jounieh: Father Superior Antoine Salame, General Director Father Dr. Wadih Al Skayem, Mrs. Hélène Chbeir—Director of the kindergarten, Mr. Joseph Rassi—Director of the primary cycle as well as the teachers of the primary cycle for their help in the data collection. The authors would like to thank Pr. William G. Kronenberger for giving us the permission to use the LEAF scale. Special thanks to the parents who participated in this study and for Ms. Marine Arisdakessian for her help in the data entry. All authors read and approved the final manuscript.

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Correspondence to Sahar Obeid or Souheil Hallit .

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Farchakh, Y., Haddad, C., Sacre, H. et al. Video gaming addiction and its association with memory, attention and learning skills in Lebanese children. Child Adolesc Psychiatry Ment Health 14 , 46 (2020). https://doi.org/10.1186/s13034-020-00353-3

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ORIGINAL RESEARCH article

Video game addiction and emotional states: possible confusion between pleasure and happiness.

• 1 Research Center for Work and Consumer Psychology, Université Libre de Bruxelles, Brussels, Belgium
• 2 Department of Psychiatry and Neurosciences, Maastricht University, Maastricht, Netherlands

Internet gaming disorder is characterized by a severely reduced control over gaming, resulting in an increasing gaming time and leading to negative consequences in many aspects of the individual life: personal, family, social, occupational and other relevant areas of functioning (World Health Organization). In the last years, the significant boom in using video games has been raising health issues that remain insufficiently understood. The extent of this phenomenon (the estimated prevalence is between 1.7 and 10% of the general population) has led the mentioned Organization to include gaming disorders in the list of mental health conditions (2018). Several studies show converging findings that highlight the common brain activities between substance use disorders and behavioral addictions (i.e., gaming disorders). Addiction specialists observed that addict subjects tend to confuse pleasure with happiness when linking emotional states to their addictive activities. As far as we know, beyond the mentioned observations, distinguishing the perception of these two emotional states in the frame of an addiction has not been yet the object of formal research. This study aims at examining the possible confusion between pleasure and happiness within the addiction sphere. Video game addiction has been chosen to explore the possible occurrence of this perceptional distortion. A mixed design lab-based study was carried out to compare between video games addicts and non-addicts (between-subjects), and video games-related activities and neutral activities (within-subject). Emotional reactions were gauged by self-reported scales and physiological data acquired through a range of biosensors: Relaxation and Hearth Rate. From a therapeutic standpoint, this research intends to explore alternatives to deal with this sort of disorders. More specifically, at the cognitive level, the idea is elaborating guidelines to develop patients’ insights into these emotional states and thus increasing their ability to handle them. Overall, several indices resulting from this study constitute a bundle of arguments that argue in favor of the confusion between pleasure and happiness made by addict users when associating their affective states to video gaming. Furthermore, this approach illustrates how reappraising emotions may contribute to reducing the perceptional distortion of these emotional states.

Introduction

In the last years, the significant boom in using video games (VG) has been raising health issues that remain insufficiently understood ( Khazaal et al., 2016 ). The World Health Organization [WHO] (2018) has recently included “gaming disorders” in the list of mental health conditions. According to WHO this affliction is a “persistent or recurrent behavior pattern of sufficient severity to result in significant impairment in personal, family, social, educational, occupational or other important areas of functioning.”

The fifth revision of the Diagnostic and Statistical Manual of Mental Disorders (DSM-5) considers the ‘Internet Gaming Disorder’ as a potential new diagnosis that requires further research ( Petry et al., 2015 ). The prevalence of problematic gaming is estimated to range from 1.7% to over 10% among general population ( Griffiths et al., 2012 ).

Compared to the core topics of research in neuroscience such as stress, depression, etc., the chronic use of VG is a rather recent field of investigation. Yet, a growing number of studies have been produced in this field in the last two decades ( Andreassen et al., 2016 ). Indeed, several research projects have been exploring VG addiction from a behavioral, emotional, brain circuits and genetic perspectives ( Griffiths et al., 2012 ; Dong et al., 2017 ).

There seems to be converging findings that highlight the common brain activities between VG disorders (belonging to the cluster of behavioral addictions) and substance use disorders (SUD). It has been shown that the dorsolateral prefrontal cortex, orbital frontal cortex, para-hippocampal gyrus and thalamus were activated in both disorders ( Han et al., 2011 ). The limbic structures appear to be the key circuits linked with reward and addiction ( Cooper et al., 2017 ). In subjects suffering from these disorders, cues associated with SUD and with behavioral addiction can trigger craving, which is connected with the dopamine reward system ( Ko et al., 2009 ; Han et al., 2011 ). In addition, it has been observed that the level of dopamine released in the ventral striatum when playing a competition like video game is comparable to that provoked by psycho-stimulant drugs ( Koepp et al., 1998 ; Yau et al., 2012 ). Few studies have been carried out on the genetic aspects of this topic. Some of them indicate that there would be genetic background similarities between these two disorders. For example, the homozygous short allelic variant of the 5HTTLPR gene (encoding the serotonin transporter) is more prevalent among the excessive Internet user, which is also linked with increased drug consumption ( Serretti et al., 2006 , as cited in Yau et al., 2012 ; Lee et al., 2008 , as cited in Yau et al., 2012 ).

As described later, studying the confusion between pleasure and happiness in the frame of addiction requires as clear a demarcation as possible between these two emotional states. Although a consensus among scientists on how to define and distinguish pleasure and happiness remains to be reached (see next section Pleasure and Happiness ), in this research we have adopted the following distinctive traits to describe and to work with these two emotional states: pleasure relates to a transient emotional state resulting from the satisfaction of a desire, a craving, and happiness refers to a lasting emotional state of contentment, euthymia ( Pollard, 2003 ; Lustig, 2017 ).

According to Lustig (2017) , addictions together with depression are two rampant afflictions in the last decades and constitute the harmful extremes of pleasure (associated with the dopaminergic system) and happiness (associated with the serotoninergic system) respectively ( Üstün et al., 2004 ; Lepine and Briley, 2011 ; Szalavitz, 2011 ; Whiteford et al., 2013 ; Gowing et al., 2015 ; Keyes et al., 2015 ). Based on his long practice on addiction issues, this author argues that confusing pleasure (in the sense of longing, craving, strongly driven by a short term reward) with happiness is linked with SUD and with behavioral addictions (i.e., gambling, eating disorders, excessive use of technology like for example social media and VG, etc.), which could lead to depression ( Lawrence et al., 2014 ). According to the author, confusing pleasure with happiness is related to the growth rate of this disorder insofar as it would encourage seeking immediate gratifications perceived as sources of happiness, which in turn triggers the reward system with the risk to sink into the vicious circle of addiction ( Pollard, 2003 ). Besides, the significant industrial development, through its commercial campaigns, probably tended to lead individuals to equate consumption with happiness ( Schmidt, 2016 ; Lustig, 2017 ). From a physiological standpoint, the author highlights that an over excited reward system engenders an excess of dopamine (DA) release from the ventral tegmental area, which in return decreases serotonin (5HT) level (associated with depression) ( Pollard, 2003 ; MacNicol, 2016 ).

Moreover, Lustig underlines that DA and 5HT amino acids (needed for the production of DA and 5HT) share the amino acid transporters, which poses a problem in case of DA amino acid over presence: that is to say, the more amino acids for DA, the less amino acids transporters are available for 5HT amino acids. In short, this DA-5HT unbalance illustrates one of the facets of the DA-5HT interaction in which the low 5HT level, associated with depression, prevents the serotoninergic system to exert its inhibitory role to imped the over drive of the dopaminergic system ( Esposito et al., 2008 ).

Chronic stress and anxiety may further aggravate this problem by increasing the cortisol level and thus creating a loop with dopamine activating the sympathetic nerve system and reinforcing the reward seeking behavior while down-regulating 5HT -1a receptor, which decreases the serotonin signaling and increases the depression likelihood ( Lustig, 2017 ). These findings are in line with studies that associate stress, anxiety and depression with Internet gaming disorders ( Wenzel et al., 2009 ; Griffiths et al., 2012 ).

Fundamentally, from a phylogenetic standpoint, it is likely that pleasure has contributed more than happiness ( Pollard, 2003 ; Lustig, 2017 ), which could explain the stronger drive of the short term gratifications over the quest for medium and long term euthymia. In sum, this suggests that identifying the possible confusion between the mentioned emotional states associated with the addictive activities may contribute to deepen the understanding of this sort of disorders and consequently to explore new therapeutic options.

The emotional states (and their consequences) associated with VG as felt and perceived by chronic users led to thorough interrogations of health professionals. Several studies intended to explore this issue by focusing on the individual characteristics of addict players. For instance, the general level of happiness appears to be a firm candidate to predict addiction to VG playing ( Hull et al., 2013 ). In effect, it has been shown that gaming disorders are positively correlated with depression and loneliness and negatively correlated with well-being ( Lemmens et al., 2011 ; Sarda et al., 2016 ). These two studies relied on a eudaimonic notion of well-being (i.e., life satisfaction, a life well lived). Thus, based on the mentioned definitions of pleasure and happiness, on the semantic net (see Annex ) and on the analysis made in the next section (Pleasure and Happiness), in this research well-being is assimilated to happiness due to the considerable common ground shared between these two concepts. In line with these findings, another study highlights the association between high frequency of online gaming with depression and social phobia ( Wei et al., 2012 ). Similar results were found in a study in which, compared with no addict Internet user, Internet addict subjects used to play online games reported significantly more depressive symptoms ( Geisel et al., 2015 ).

From a psychological symptoms standpoint, it has also been observed that when playing VG, addict gamers have a sense of well being or euphoria while playing VG, inability to stop the activity, craving more time at playing VG, feeling empty, depressed, irritable when not playing VG, with all the pernicious consequences these symptoms have on the private, social and professional life ( Griffiths, 2008 ). At glance, the coexistence of well being and craving might come across as paradoxical, although the mentioned work ( Lustig, 2017 ) on this issue provides some elements of answer to this finding.

Using a video game clip as a stimulation trial, it has been studied ( Kim et al., 2018 ) the craving state of chronic users when playing VG through measures resulting from addiction questionnaires and several bio signals such as eye blinking, eye saccadic movements, skin conductance and respiratory rate. The results of this work showed that during the stimulation trial video game there was a decrease of eye blinking rate, eye saccadic movement rate and mean amplitude of the skin conductance response whereas there was a significant increase of the mean respiratory rate.

Another study ( Lu et al., 2010 ; as cited in Kim et al., 2018 ) focused on a group of individuals with high risks of developing Internet gaming disorders (IGD) and their sympathetic nervous system responses. When using Internet in this experiment, increases were observed in blood volume, body temperature and respiratory rate. Heart rate (HR) has also been used as a reliable indicator of craving in subjects with SUD ( Kennedy et al., 2015 ).

Pleasure and Happiness

The psychophysiological and brain mechanisms of pleasure and happiness are quite complex and probably more research is required to better discerning these processes. Some studies have underlined that the hedonic system includes wanting and liking and each of these two emotional states may operate in a conscious and unconscious mode ( Berridge and Kringelbach, 2011 ). Studies indicate that unconscious wanting would function as a conditioned desire involving the nucleus accumbens, ventral tegmental area, hypothalamus and dopamine; on the other hand the unconscious liking would relate to a sensory hedonic dimension associated with the nucleus accumbens, ventral pallidum, periaqueductal gray, amygdala, opioids and cannabinoids ( Kringelbach and Berridge, 2009 ; Berridge and Kringelbach, 2013 ). The same studies show that conscious wanting would relate to cognitive incentives, subjective desires and dopamine whereas conscious liking would be linked with subjective pleasures, opioids and cannabinoids; both would involve the orbitofrontal cortex, anterior cingulate and insular.

It has been shown that the level of activation of some of the mentioned areas would be altered in subjects with Internet gaming disorders: sensing craving for gaming is associated with an increased activation of the left orbitofrontal cortex (correlated with desire for VG play) and with a decreased activation in the anterior cingulate cortex (probably linked with the reduced capacity to inhibit craving for gaming) ( Wang et al., 2017 ).

There might be a relation between the complexity of these brain circuits linked to these emotional states and the polysemy of these two terms, happiness and pleasure , which may contribute to the possible confusion between them. Indeed, the intense interrelation between them finds expression in subtle distinctive features and in some connotations with vague borders, to the extent that these words might be regarded as almost synonyms. The semantic analysis of these two terms produced in this research intends to show their core meanings, their nuances and the possible intersections between them ( Procter, 1985 ). Trying to unravel and to understand these two emotional states is not a recent endeavor. For instance, Greek thinkers approached the notion of happiness as a state constituted by two components: Hedonia (pleasure) and Eudaimonia (a life well lived) ( Kringelbach and Berridge, 2009 ).

Due to its nature, defining and studying happiness is a quite uneasy task. Although progress has been made on this rather recent area of study, there is still a lack of consensus when it comes to defining this concept. Some authors distinguish fluctuating happiness (self centered) from durable, authentic happiness (self-transcendent) ( Dambrun et al., 2012 ). Another study uses the value-arousal model on emotions to define it, according to which happiness results from a positive valence, high arousal and engaged and satisfied in life ( Cipresso et al., 2014 ). Lustig (2017) emphasizes the time perspective as one of the distinguishing traits between these two emotional states by opposing the short-term logic of pleasure to the longer-term characteristics of happiness .

These last two studies are quite illustrative of the differences with regard to defining happiness , in particular when it comes to including or not pleasure in it. Whilst there seems to be a consensus on “life satisfaction,” “connecting with others” and “contentment” as the main traits of happiness , it is less clear whether pleasure is part of it. Usually, in the literature there are two understandings to articulate these emotional states: either both ( happiness and pleasure) are seen as inseparable concepts or happiness is regarded as a state free from distress (‘liking’ without ‘wanting’) ( Kringelbach and Berridge, 2010 ; Berridge and Kringelbach, 2011 ; Loonen and Ivanova, 2016 ; Lustig, 2017 ). Whether or not pleasure is included in the definition of happiness , to the best of our knowledge there is no study that includes craving (intense desire, longing) as a trait of happiness .

Thus, based on the mentioned definitions and on the association between craving and arousal ( Kennedy et al., 2015 ), craving for playing VG may subscribe itself within the realm of pleasure , but stands outside of the happiness’ sphere.

Within the frame of this research, Pleasure refers to the hedonic reward processes driven by a desire to obtain a gratification that can lead to craving in certain circumstances ( Berridge and Kringelbach, 2011 ). Pleasure has been associated with the dopaminergic circuit which can, in certain circumstances, function in an addictive mode and can affect also habits, conditioning, motivation and executives functions such as decision making, inhibitory control, etc. ( Volkow et al., 2011 ).

Happiness is understood as contentment and euthymic state, in line with a happy emotional state defined by a positive valence and low arousal ( Jatupaiboon et al., 2013 ). Physiologically, this state implies a reposed mind; akin to the relaxation state measured through the brain electrical activity ( Teplan and Krakovskà, 2009 ). In the literature this mood is related to the serotoninergic circuit ( Lustig, 2017 ).

To the best of our knowledge, there is no existing questionnaire focusing on the association between VG and pleasure/happiness. Thus, our study required a preliminary phase to design such self-report tool whose aim is to explore the perceived emotional states (pleasure/happiness) associated with VG play.

As far as we know, distinguishing the perception of these two emotional states in the frame of an addiction has not been yet the object of formal research, hence the reduced literature on this specific issue, in particular the experimental one.

Consequently this research may be seen as a preliminary study, which aims at examining the possible confusion between pleasure and happiness within the addiction sphere. VG addiction has been chosen to explore the possible occurrence of this perceptional distortion. Emotional reactions of VG addicts and VG non-addicts were gauged via self-report scales and physiological data (Heart rate and Relaxation state) acquired by a range of biosensors.

Resulting from the mentioned background, it is hypothesized that addict VG users:

Are likely to confuse the notions of pleasure with that of happiness when associating their emotional states to VG play.

The results of this study are expected to show that addict VG users associate happiness with VG activities while feeling craving for playing accompanied by an increased HR and a low relaxation level. Given the shortage of previous researches on the specific issue related to the confusion between pleasure and happiness in VG addiction, the outcome of this study is approached in an exploratory manner.

From a therapy standpoint, this project intends to explore alternatives to deal with this kind of scenarios. More specifically, at the cognitive level, the idea is finding means to develop patients’ insights into these emotional states and thus increasing their ability to handle them.

Materials and Methods

Preliminary phase: design of the “pleasure and/or happiness and vg” questionnaire, participants.

In total 105 VG players participated in this survey, out of which 61 filled all the questionnaires required for the design of the “Pleasure and/or Happiness and VG” questionnaire. The mean age of these 61 participants was 24.28 and the standard deviation 5.48. There were 33 males (54.1%) and 28 females (45.9%). The mean of playtime during working days was 4.49 h and the standard deviation 6.82, and during holidays and weekends 4.68 h and the standard deviation 3.13.

An online survey was run via video game forum and Reddit site (network of communities with common interests). The purpose of this survey was to evaluate the internal coherence of our self-report tool (Pleasure and/or Happiness and VG) relative to two validated questionnaires (on Hedonic tone and Happiness). Thus the survey consisted in filling the three questionnaires. Participants completed anonymously and voluntarily the questionnaires through their online gamers groups.

Two validated and known questionnaires were used to construct the ‘ Pleasure and/or Happiness and VG’ questionnaire through which the emotional states associated with VG activities were evaluated: the Snaith-Hamilton Pleasure Scale (SHAPS) ( Snaith et al., 1995 ), an assessment tool of hedonic tone, and the Oxford Happiness Questionnaire (OHQ) ( Hills and Argyle, 2002 ). The French version of these two questionnaires was used ( Loas et al., 1997 ; Bruchon-Schweitzer and Boujut, 2014 ).

The abbreviated SHAPS is composed of 14 items to assess the hedonic tone and the absence of it. The answer scale for each item offers four possible options ranging from ‘Definitely agree’ to ‘Strongly disagree.’ The OHQ is extensively used to evaluate the individual level of happiness. For each of its 29 items, the answer scale has 6 options going from ‘Strongly disagree’ to ‘Strongly agree.’

Several items of the SHAPS and the OHQ are quite adapted to the VG paradigm and lend themselves to be contextualized. For example, the first item of the SHAPS questionnaire is formulated as: “I would enjoy my favorite television or radio program.” In this case “television or radio program” is replaced by “video game.” An example of OHQ concerns the item “I am very happy,” which became “I am very happy when playing VG.” So, these kinds of items constitute the questionnaire whose aim is identifying the emotional states that users associate with VG. Initially, eight items were adapted to VG from these two questionnaires: four items from SHAPS and four items from OHQ. The answer scale provides with six possible options ranging from ‘fully disagree’ to ‘fully agree.’

Statistical Analysis

In order to ensure the usefulness of the designed self-report tool, an Alpha Cronbach test was run on the results of this survey to measure the internal coherence between the ‘VG and Pleasure/Happiness’ and the two other questionnaires (SHAPS and OHQ). Moreover, it has been examined whether there is a correlation between VG play frequency and the two areas explored in this survey: the general happiness level (OHQ) and the emotional states associated with VG (‘Pleasure and/or Happiness and VG’).

The Experiment

The study was announced through the Université Libre de Bruxelles (ULB) scientific social media as well as via leaflets available in public cyber games centers in Brussels. Gamers interested to participate in this study had to answer an on-line survey ( N = 163), in which the following data was gathered: age, play frequency, name of VG played and a validated test to assess the gaming addiction level (Gaming Addiction Scale, Lemmens et al., 2009 ). The French version of this scale was used ( Gaetan et al., 2014 ). Being used to play to at least one of these five popular VG (Fornite, Overwatch, League of Legends, Counter-Strike or Rocket League) and an age ranging from 18 to 70 years old were the inclusion criteria. Competing against another team and playing in groups are the common characteristics of these VG. The exclusion criteria were having vision impairments and neurological problems.

Two groups of gamers were invited to participate in this study: addict users (AU) and non-addict users (NAU). None of the invitees met the exclusion criteria. The selection and recruitment were based on the score obtained in the test on gaming addiction, resulting in: AU ( N = 12) and NAU ( N = 17) (7 females and 22 males, ranging from 19 to 29 years old). They were all French speakers Belgian residents. The mean age was 23 and the standard deviation of 3. The difference between sexes in terms of VG addiction is not statistically significant (3/7 AU females and 9/22 AU males, U 45.5, p = 0.130).

This experiment took place within the frame in the usability laboratory of the Research Centre of Work and Consumer Psychology, Université Libre de Bruxelles (ULB).

Before the experiment all the procedures were explained to participants and their consent was asked on formal basis. They were informed that:

– This experiment aims at better understanding the video game phenomenon (without mentioning the issue relative to the emotional states and VG).

– They have to fill several questionnaires (in French).

– Some non-invasive artifacts are set to gather measurements on physiological signals while they watch video clips.

– The Ethical Committee of ULB approved this study in accordance with the Declaration of Helsinki.

The participants were welcome into the testing room of the laboratory by the examiner. They were seated and given an informed consent form. Once the form was read and signed, the study procedure was explained. Then, the Electroencephalogram (EEG) headset was placed onto the participant’s head and an impedance check was run.

Before the beginning of the experiment, each participant chose his/her favorite VG he/she uses to play among the five initially proposed. During the experiment, the examiner observed the participant through a one-way-glass, avoiding interference.

Finally, participants were thanked for their participation, compensated and given information on obtaining the results of the study. The whole experimental run took around 1 h.

Prior to starting the operational phases of the experiment, all devices are set to initiate the baseline recording of all the physiological signals.

Six phases compose this experiment ( Figure 1 ). In each phase of the experiment the emotional states associated with VG were examined either through self-report questionnaires or via physiological measures. The physiological measures were recorded during the visioning of two sorts of video clips: VG clips whose aim was to induce craving and neutral video clips (documentaries on nature) intending to reduce craving.

Figure 1. Synthetic view of the experimental phases.

The six experimental phases:

(1) “Pleasure and/or Happiness and VG” (six items): Participants were invited to fill the self-report questionnaire designed in the preliminary phase.

(2) Watching a neutral clip during 2 min while recording physiological signals related the mentioned two emotional states. This phase intends to decrease craving in participants.

(3) Craving score: Participants were asked to express their craving state to play their favorite VG via a one item self-report questionnaire.

(4) Watching a VG clip during 2 min while recording the same physiological signals as in phase two related to the mentioned emotional states. The objective of this phase is to increase craving in participants.

(5) Craving score: the same procedure and self-report tool as in phase 3 were applied.

(6) Submission of three self-report questionnaires:

(6.1) “Pleasure and/or Happiness and VG” (Three bipolar items).

(6.2) “Key words and VG”: participants were invited to associate a list of words to VG activities.

(6.3) “Pleasure and VG or Happiness and VG” (one bipolar item): participants were asked to associate one of the two emotional states to VG play.

The cycle from the 2nd phase to the 5th phase was repeated five times for each participant. In each of these five cycles, different episodes of video clips (the chosen VG and the neutral clip) were shown randomly so as to avoid the habituation phenomenon and minimize the influence that the order of the sequence of episodes could have on participants’ responses.

– Experimental groups: AU and NAU

The Gaming Addiction Scale (GAS) ( Lemmens et al., 2009 ; Gaetan et al., 2014 ) was used to constitute these groups. As a tool to measure game addiction, GAS possesses significant assets. Lemmens et al. (2009) showed the validity of this scale from a cross population point of view and its one-dimensional characteristic resulting from the factorial analysis. In addition, in the same study it has been shown the concurrent validity of GAS insofar as this scale is associated with play frequency as well as with psychological features related with game addiction, namely decreased level of social competence and of well being, and high level of aggression and of loneliness. Moreover, high scores in GAS are also linked with attentional deficiencies in response inhibition when perceiving game cues ( van Holst et al., 2012 ; in Khazaal et al., 2016 ), which converges with results produced by other researches associating impulsivity and cue reactivity with other addictive behaviors ( Billieux et al., 2011 ; Khazaal et al., 2012 ; Torres et al., 2013 ). Relative to other game addiction measurements, GAS has the most complete covering of the Internet gaming disorder criteria of the DSM-5 ( Petry et al., 2014 ). Although it was initially designed for adolescents, there are substantial evidences to state that GAS is applicable for young adults too ( Khazaal et al., 2016 ).

Each of the seven items of this scale starts with the question “How often in the last 6 months…?” to explore the impact of video gaming on different aspects of the subject’s life. The possible answers are: never, rarely, sometimes, often and very often. The first two answers score 0, the last three answers score 1. If the total sum of these scores is 4 or higher, the subject is considered an AU according to this scale.

– The experiment

In the first phase, participants were asked to fill the “ Pleasure and/or Happiness and VG” questionnaire composed by six items: three items that tie Pleasure (P) and VG, three items that tie Happiness (H) and VG (six-items in total).

The answer scale for each item was composed of six options ranging from ‘Fully disagree’ to ‘fully agree.’ Each of these six items is answered separately, thus the overall possible results of this questionnaire can be: (1) P and VG > H and VG or (2) H and VG < P and VG or, (3) P and VG = H and VG.

In the second phase (Neutral video clip), two physiological signals related to Pleasure and Happiness were recorded. Based on the correlates found between HR and craving, this physiological signal is used as an indicator of arousal ( Kennedy et al., 2015 ).

Despite the difficulty in defining and in measuring happiness , the brain electrical activity is recorded (Electroencephalogram, EEG) mainly to detect the relaxation state. This state appears close to the notion of happiness; in the literature it is accepted that the increase of alpha waves is correlated with mental and physical rest ( Teplan and Krakovskà, 2009 ).

In the third phase, participants were asked to express their craving state to play his/her favorite VG. The statement employed in this self-report tool was: “State your present craving for gaming.” Participants have to choose the answer that best fitted their self-assessment among six possible answers offered by the scale ranging from “I do not feel any craving for gaming” to “I feel a very strong craving for gaming.”

In the fourth phase (VG clip), the same physiological signals as in the second phase were measured.

In the fifth phase, the same procedure to assess craving for gaming as in the third phase was employed.

In the sixth phase, three other self-report questionnaires were submitted to participants and used to evaluate the association between the mentioned emotional states and VG:

– “Pleasure and/or Happiness and VG” (three bipolar items). The same six items of the “Pleasure and/or Happiness and VG” questionnaire used in phase 1 were presented in a bipolar structure: three items opposing “Pleasure and VG” vs. “Happiness and VG.” For example, if in the six items questionnaire the items “I would enjoy my favorite VG” (Pleasure/VG) and “I am happy when playing VG” (Happiness/VG) are presented separately, in this questionnaire they are part of the same item: “I would enjoy my favorite VG” vs. “I am happy when playing VG.” By doing so, participants are encouraged to choose which of their emotional states (Pleasure, Happiness) is associated with VG playing. That said, the scale has an uneven number of options (five) between the two extremes, the central option representing the equal association of Pleasure and Happiness with VG play. Thus, the overall possible results are identical as in phase 1.

– “Key words and VG”. Participants were asked to choose three words (out of ten) that they associate most with their VG activities. These 10 key words come from the semantic mapping elaborated in this research of the terms used in the formal statements defining pleasure and happiness in this study. For example, some words from the happiness sphere are contentment and well being , whereas desire and joy relate to pleasure . Besides, they are in line with both definitions Lustig’s (2017) . Only the ten words (French version) were shown to participants. Although the possible results are similar to those of six-item “Pleasure and/or Happiness and VG” questionnaire and three-bipolar item “Pleasure and/or Happiness and VG” questionnaire, this time the same association (emotional states and VG) is tackled via key words directly linked to the two studied emotional states ( Pleasure, Happiness ) but without mentioning them. This self-report format intends to gain accuracy in the identification of gamers’ emotional states associated with VG.

– “Pleasure and VG or Happiness and VG”. The written definitions of both pleasure and happiness , based on work Lustig’s (2017) , were shown to participants. Then they were asked to read carefully these definitions and to take them into account when answering one bi-polar item that opposes “Pleasure and VG” vs. “Happiness and VG.” Unlike in the three-bipolar items questionnaire, the answer scale between these this bipolar item has an even number of options (six). This time is an “either/or” choice they are faced with, therefore the possible results are: P and VG < H and VG or P and VG > H and VG. Basically this questionnaire intends to strengthen consistency in participants’ insights into this issue by inviting them to confront their perception of their emotional states associated with VG play with the mentioned formal definitions, comparable to an emotions reappraisal process ( Seay and Kraut, 2007 ).

In short, four self-report questionnaires (see Annex ) aim at exploring this dependent variable (association between these two emotional states and VG play) by looking at the consistency of participants’ answers to the different formats of questions. The questions’ formats are:

– Pleasure and/or happiness can be associated with VG (six independent items);

– Pleasure and/or happiness can be associated to VG (three bipolar items);

– Pleasure and/or happiness can be associated to VG through key words defining the two emotional states (without mentioning the words pleasure and happiness );

– Pleasure or happiness can be associated to VG (written explicit definitions of pleasure and happiness are given to participants).

This approach aims at exploring the coherence between the self-reported answers and the physiological signals, as a means to objectivize the perceived emotional states associated with VG play by the two mentioned groups of participants (addict gamers and non-addict gamers).

The previously mentioned theoretical framework indicates that the notion of craving relates to an arousal state that could lead to an addictive pattern and consequently stands out of the realm of happiness.

Expected Results

Based on the analysis made on this issue previously as well as on the hypothesis of this study, the expected results could be synthesized as shown in Table 1 .

Table 1. Summary of the expected results.

– Self-Report Questionnaires

For the self-report questionnaires, it is expected that, compared to NAU, the AU group:

– In “Pleasure and/or happiness associated with VG” (six independent items) associates more happiness than pleasure with VG play.

– Reports more craving for playing after watching VG clip.

– In “ Pleasure and/or happiness associated to VG” (three bipolar items) associates more happiness than pleasure with VG play.

– Associates VG play with key words more related to happiness category than to those of pleasure .

– In “ Pleasure or happiness associated to VG” associates VG play with pleasure (like NAU).

– Physiological Signals

It is expected to observe an interaction between the groups (AU, NAU) and the conditions (VG clip, Neutral clip). Namely, it is assumed that visioning the VG clips has an effect on AU increasing HR while decreasing Relaxation.

After verifying the normality of distributions (Kolmogorov–Smirnov), the means comparison between the two groups (NAU, AU) was calculated for self-report questionnaires measuring the association between VG and Pleasure/Happiness (Mann–Whitney U ) for the six-items “Pleasure and/or Happiness and VG,” the three-bipolar items “Pleasure and/or Happiness and VG” and the one-bipolar item “Pleasure and VG or Happiness and VG.” The Chi square was used for “Key words and VG.” In order to determine whether there are differences between independent groups over time and to identify possible interactions between the two independent variables on the dependent variables, a two-way mixed ANOVA (within and between subjects) was used for the craving scores and the physiological signals recorded ( Table 2 ).

Table 2. Synthetic view of independent and dependent variables.

The experiment was run on a desktop computer with an Intel Core i7 quad processor and 8 GB RAM, running Windows 10. Stimuli were displayed on a 22-inch monitor and resolution was set to 1680 × 1050. Participants used standard mouse and keyboard as input devices. EEG measurement includes detecting the fluctuation of voltage potential generated by large group of neurons in the brain. The EEG signal was obtained through the use of EPOC headset. This device allows to remotely getting data of brain activity using a wireless set of fourteen electrodes (AF3, AF4, F3, F4, F7, F8, FC5, FC6, T7, T8, P7, P8, O1, O2) sampled at 128 hertz.

The relaxation state was measured by one of the composite metrics of the Emotiv software. HR was measured by using Schimer 3 (Photoplethysmography). The I. Motions software version 7.1 (Imotions Inc. 2018) was used to recording the mentioned data and presenting stimuli to participants. The statistical analysis was conducted with IBM SPSS statistics v.25.

Design of the “Pleasure and/or Happiness and VG” Questionnaire

The Cronbach’s alpha (0.859) showed a high internal coherence between the SHAPS and three items (out of four) of the “Pleasure and VG” within the “Pleasure and/or Happiness and VG” questionnaire. The fourth item has been disregarded; its presence would have dropped the Cronbach’s alpha to 0.685. The internal coherence obtained between the OHQ and the “Happiness and VG” items within the “Pleasure and/or Happiness and VG” questionnaire was quite high for the four items concerned (alpha 0.901). However, the internal coherence between these four items was too weak due to one item (alpha 0.407). The exclusion of this item raised the alpha significantly (0.836). Consequently, only the consistent items have been kept (six out of the initial eight items: three on “Pleasure and VG,” and three on “Happiness and VG,” see Annex ).

Moreover, it has been examined whether there is an association between VG play frequency and the two areas explored in this survey: the general happiness level (OHQ) and the emotional states associated with VG via the “Pleasure and/or Happiness and VG” questionnaire. The constitution of the group of frequent gamers and that of non-frequent gamers was determined by calculated median (18 h per week). In line with several studies linking problematic gaming and well-being and life satisfaction, a moderate negative correlation ( R = −0.249; p = 0.056) was found between VG high play frequency and the OHQ scores ( Griffiths, 2008 ; Lemmens et al., 2011 ). In addition, there is a marginal significant difference [ T (58) = 1.923; p = 0.059] between frequent VG users and non-frequent VG users relative to the OHQ scores.

The “Pleasure and/or Happiness and VG” Six-Items Questionnaire

The Kolmogorov–Smirnov outcome indicates the need for using a non-parametric test to compare the two groups. The Mann–Whitney test shows that there was no significant difference observed between the AU and NAU relative to association between VG play and pleasure (item 1. U = 78, p = 0.30; item 3. U = 75, p = 0.24 and item 5 U = 86, p = 0.49) ( Table 3 ).

Table 3. Descriptive statistics of “Pleasure and/or Happiness associated with VG” (6-items): [Pleasure (P), Happiness (H) associated with VG].

In contrast, there is a significant statistical difference in the three items where AU associate VG play with happiness (item 2. U = 40, p = 0.005; item 4. U = 54, p = 0.034 and item 6. U = 34, p = 0.002) more than NAU.

Craving Scores

Results in craving ( Table 4 and Figure 2 ) show a statistically significant interaction F (1,25) = 4.78 ( p = 0.038). Indeed, relative to the neutral clip, the VG clip condition has significantly amplified the reported craving difference between the two groups (AU craving score > NAU craving scores).

Table 4. Descriptive statistics for self-report Craving.

Figure 2. Self-report craving (groups: AU, NAU; conditions: Neutral clips, VG clips).

Physiological Signals Measurements

The AU’s relaxation is significantly lower [ F (1,24) = 8.616; p = 0.007] than NAU’s in both conditions (Between-Subjects Effects). The relaxation level decreases in both groups during the VG clip. On the other hand, conditions do not influence the relaxation difference between the two groups [ F (1,24) = 0.001; p = 0.98] ( Table 5 and Figure 3 ). Furthermore, there is a significant statistical gender difference in both conditions (Neutral clip: Male 17.36, Female 7.57. U = 25, p = 0.008 – VG clip: Male 17.09, Female 8.43. U = 31, p = 0.019).

Table 5. Descriptive statistics: Relaxation index (EEG EPOC, Emotiv software).

Figure 3. Relaxation [groups: AU, NAU; Conditions: (1) Neutral clips, (2) VG clips].

Concerning the other physiological variable (HR) ( Table 6 and Figure 4 ), there is an effect of VG clips on both groups [ F (1,15) = 20.802; p < 0.001]. Nevertheless, there was no statistically significant interaction [ F (1,15) = 0.028; p = 0.86], nor an effect of addiction on VG clip condition [ F (1,15) = 0.083; p = 0.777]. It is important noting that due to corrupted data the number of valid subjects taken into account was 17 (8 AU and 9 NAU).

Table 6. Descriptive statistics: Heart Rate (HR).

Figure 4. Heart Rate [groups: AU, NAU; Conditions: Neutral clips (1), VG clips (2)].

The “Pleasure and/or Happiness and VG” Three-Bipolar Items Questionnaire

The descriptive statistics of this three-bipolar items questionnaire ( Table 7 ), indicate that the AU group linked VG activities more with happiness than the NAU group. The Mann–Whitney test shows a significant difference between these two associations ( U = 47; p = 0.013).

Table 7. Descriptive Statistics: Pleasure/VG vs. Happiness/VG (3 bipolar items).

Key Words and VG

Results state the absence of significant difference between AU and NAU in associating the key words from the Pleasure cluster with VG play, and words from the Happiness cluster with VG (Chi square, p = 0.942) ( Table 8 ). When taking words separately, the biggest gap between the two groups relates to the word well-being (belonging to the happiness cluster) associated to VG play (AU: 25%, NAU: 0%).

Table 8. Descriptive statistics: number of words per category (Pleasure, Happiness) associated to VG play chosen by NAU and AU.

“Pleasure and VG or Happiness and VG” (One Bipolar Item Questionnaire With Written Definitions)

The outcome of this questionnaire indicates that there is no significant difference between AU and NAU ( U = 102, p = 1). Both groups have clearly associated VG play with pleasure ( Table 9 ).

Table 9. Descriptive statistics: Happiness/VG or Pleasure/VG (1 bipolar item, with Definitions of Pleasure and Happiness shown to subjects).

The following scheme summarizes the outcomes of the self-report tools used to evaluate the association between the emotional states (Pleasure and Happiness) with VG play ( Table 10 ).

Table 10. Synthetic view of self-report results (Emotional states associated with VG play).

The following table indicates the mean, standard deviation and Skewness and Kurtosis values of the self-report craving, the HR and the relaxation level for both groups in the two conditions ( Table 11 ).

Table 11. Descriptive statistics for self-report Craving, Relaxation, Heart Rate.

Overall, the results of this study show that AU associate happiness to VG while reporting craving for VG play and having a low relaxation level. These outcomes observed in this experiment constitute a bundle of arguments that argue in favor of the hypothesis of this study ( Lustig, 2017 ). Indeed, in AU, the high self-report craving score and low Relaxation level during VG clips visioning do contrast with their association of VG more with happiness than with pleasure in the mentioned “Pleasure and/or Happiness and VG” questionnaires (six-items and three-bipolar-items) relative to NAU. Consistent with previous findings in this area, these four measurements highlight the coexistence of the perception of happiness linked with VG play combined with elements related to pleasure such as craving ( strong desire, wanting ) ( Pollard, 2003 ; Griffiths, 2008 ; Waterman et al., 2008 ). Since craving and low Relaxation are rather incompatible with the mentioned notion of happiness ( Pollard, 2003 ; Waterman et al., 2008 ; Lustig, 2017 ), these indices may raise the question as to how accurate are AU’s insights into their emotional states associated to VG play and may support the idea that AU’s perception of their emotional states is somewhat distorted. In the literature, VG addiction would be linked with impairment in the self-regulation process, this finding may be linked with the difficulties AU have to observe and evaluate their own behavior ( Seay and Kraut, 2007 ). Besides, the mentioned results suggest that VG clip effect on self-report craving would depend on the addiction level.

Considering that sensing happiness and craving are probably experienced as positive emotions by AU, and that usually negative and positive emotional events are reported to last longer and shorter respectively ( Gil and Droit-Volet, 2012 ; Tian et al., 2018 ), the arousal triggered by motivating stimuli, may modify the time perception and could mediate the effect of emotions on behavior ( Gil and Droit-Volet, 2012 ). In other words, the level of excitement produced by VG play could make AU underestimate the time spent at this activity, which may be perceived as an alleviating evasion free from stressors and possibly assimilated with the notion of happiness . This hypothetic mechanism would match one of the possible motives for online gaming ( Demetrovics et al., 2011 ). In this sort of precognitive process, several studies mentioned the involvement of the amygdala in interaction with the thalamus together with the dopaminergic system and a poor inhibitory control ( Gil and Droit-Volet, 2012 ; Petry et al., 2015 ).

It is noteworthy underlining that the bipolar structure of the three-items questionnaire increases the relevance of this outcome. In effect, although participants were incited to choose between the two emotional states opposing each other (VG and pleasure vs. VG and happiness), like in the six-items questionnaire, AU again did choose happiness as the main emotional state linked with VG play. This outcome would further state the difference between these two groups when it comes to associating the two emotional states to VG play. Besides, this would reveal to an important extent that the possibility whereby pleasure and happiness were regarded as synonyms could be overcome. In other words, this outcome shows that the similarity of meanings of these two concepts did not prevent these groups to make a clear choice. Finally, the similar scores obtained in the two questionnaires (six-items and three-bipolar items “Pleasure and/or Happiness and VG”), in spite of the different disposition of the same items in these two instances, strengthen the value of the designed scale (“Pleasure and/or Happiness and VG play”).

The absence of interaction between the two independent variables on HR may be explained by the fact that a higher arousal would take place in AU when playing VG rather than when watching at VG clips. Moreover, the reduced number of valid subjects when measuring this physiological parameter (due to technical recording problems) could have contributed to this outcome too. The fact that the independent variables did not produce the expected different HR effects on AU and NAU could also be linked with one of the limitations of this study: the difficulty in integrating in this research the interaction between HR and depression (as mentioned, VG addiction is positively correlated with depression) ( Griffiths et al., 2012 ) that may lead to HR index modifications ( Cipresso et al., 2014 ). In sum, this issue illustrates that the difficulty to circumscribe the notion of happiness is also reflected in the complexity to establish physiological correlates so as to objectify this emotional state ( Cipresso et al., 2014 ).

Associating the clusters of key words with VG did not produce the expected results. Since AU linked VG with both pleasure and happiness , may be these words played a clarification role and facilitated Au’s insights into their emotional states when playing VG. It could also suggest the inadequacy of this self-report tool. However, it is probably worthwhile mentioning an index related our hypothesis: when taking words separately, the word “well-being” associated with VG play was chosen by 25% of AU and by 0% of NAU.

The outcome of the binary question in the “Pleasure and VG or Happiness and VG” one-item questionnaire with the definitions of pleasure and happiness ( Pollard, 2003 ; Deci and Ryan, 2008 ; Waterman et al., 2008 ; Kashdan et al., 2008 ; Lustig, 2017 ) shows that AU ceased associating happiness to VG play and instead, like NAU, clearly linked pleasure to their cyber activity. Caution is required in the analysis of these results because the validity of this questionnaire remains to be demonstrated. Having instructed participants to answer the bipolar question by taking into account the written definitions of the two measured emotional states, did modify the result of AU group relative to both questionnaires (“Pleasure and/or Happiness and VG” six-items and three bipolar items). Within the framework of this careful approach, it could be hypothesized that explicit definitions of the two emotional states induced AU to adopting an introspection mode through a more pronounced involvement of cortical brain structures, akin to a therapeutic process in which the appropriate verbalization of pleasure and happiness facilitates the clarification of one own feeling as a prerequisite to elaborate more adaptive behavior in spite of the constraining psychological characteristics usually associated with VG addicts ( Kim et al., 2007 ; Kashdan et al., 2008 ; Wenzel et al., 2009 ).

This may be regarded as an example of emotions reappraisal which would increase accuracy of insights into one-self, reduce distorted perception of emotions and assess the adequacy of the behavioral response to a given stimulus ( Compare et al., 2014 ). In other words, it could be posited that the mentioned explicit definitions have somewhat constrained AU to use a cognitive approach to examine their emotional states related to VG play rather than merely relying on the sensory information as it tends to occur when sensing craving for video gaming ( Wang et al., 2017 ).

Moreover, the result of this one-item binary questionnaire would further support the hypothesis. In effect, the studied interrelation between hedonia and eudaimonia suggests that a highly rated hedonic activity (VG play in this case) is usually related with low rating in eudaimonia ( Waterman et al., 2008 ). This interpretation would fit with the resounding association between depression and gaming disorders ( Lemmens et al., 2011 ; Hull et al., 2013 ; Sarda et al., 2016 ; Bonnaire and Baptista, 2019 ) together with the confusion between pleasure and happiness occurring in addictive activities (AU associated VG with happiness in the first two self-report questionnaires and ended linking pleasure with VG in the last one-item questionnaire) ( Pollard, 2003 ; Lustig, 2017 ).

Overall, the more explicit the definition of pleasure and happiness and the narrower the choice offered by the self-report questionnaires, the less confusion of emotional states associated with VG occurred in AU group members whereas NAU invariably associated pleasure to VG as illustrated in Figure 5 .

Figure 5. Shift of AU perception of their emotional states associated with VG according to the self-report tools.

Based on these results, it could be postulated that the tendency of AU to perceive happiness when feeling craving and pleasure linked to VG play, might be moderated by a clarifying cognitive process on the meaning of these studied emotional sates, which would interfere with the behavioral habits linked to the urge of gaming ( Ko et al., 2009 ).

The findings resulting from “Pleasure and/or Happiness and VG” six-items questionnaire could be regarded as an illustration of the confusion that AU might have when linking the studied emotional states with VG play. Unlike NAU, the significantly higher association between VG play and happiness expressed by AU matches the perceived level of well being reported by individuals with Internet gaming disorders ( Griffiths, 2008 ). On the other hand, apart from well-being , the same author cites euphoria as the other main emotional state that addict gamers may report when playing VG. Whilst happiness and well-being rely on each other to define themselves, euphoria would convey the notion of intense excitement, which would rather stand in the pleasure sphere. Moreover, in medical terms, euphoria refers to a feeling of great elation, not necessarily founded (especially when resulting from substances consumption). Since AU also associated VG with pleasure although they did it to a lesser extent than with happiness, it could hypothesized that the feeling of intense excitement derives, at least partially, from satisfying the craving for VG play, which in turn could engender relieve experienced as a sense of well-being ( Loonen and Ivanova, 2016 ).

The impact of VG clips on AU craving and relaxation scores underlines relevant aspects of this study, which support the hypothesis of this research. First of all, it highlights the incongruent perception of AU’s emotional states whereby both craving and happiness coexist as emotional states associated with VG play. Thus, this finding constitutes a relevant component of the confusion that consists in placing a short-term pleasure (VG play) within the sphere of happiness. Besides, the low relaxation state of AU would correspond with their self-reported craving and, therefore, further highlights the contrast between the perceived happiness associated with VG play and the indicators measured during the VG clip visioning (high craving level and low relaxation state level). Finally, it is noteworthy mentioning that relaxation was the only measure in this study where gender differences were observed. The lower relaxation level in female gamers in both conditions might be related to the gender expectation about playing VG in society at large and in the gamers’ community in particular ( Shen et al., 2016 ). Indeed, since female gamers are a minority in these sorts of VG ( Shen et al., 2016 ) (in line with our sample: 7 females, 22 males), it could be posited that they feel under scrutiny in an activity regarded as male oriented.

Putative Reasons of Distorted Perceptions of Emotional States Associated With VG Addiction

The social dimension of popular VG has been identified as one of the factors that may explain the addiction pattern ( Hull et al., 2013 ). In this kind of competitive games, improving the required abilities and obtaining better results would be part of the key motives for VG play ( Demetrovics et al., 2011 ), that usually generates the appreciation and the acceptance of the other group players. Getting this sort of feedback from others can be motivating indeed, especially when taking into account the correlation between IGD and social isolation, low self-esteem, traumatic experiences, depression and low life satisfaction ( Petry et al., 2015 ; Schimmenti et al., 2017 ; Bonnaire and Baptista, 2019 ). In turn, these psychosocial characteristics are probably related also with the high impulsivity level in VG addicts ( Billieux et al., 2011 ), which has been found to be associated with difficulties in interpersonal relationships ( Ryu et al., 2018 ). Thus, it would seem that VG activities are, at least partially, sating the mentioned social and psychological deficiencies. This suggests that AU’s emotional states related to VG play may be quite contrasting, in which components of happiness (i.e., interacting with others, fellowship and belonging to a group) are intertwined with those of short-term pleasure (i.e., craving for getting quick results, praise from others, etc.) ( Loonen and Ivanova, 2016 ). Now, craving for undertaking these cyber activities to respond to the mentioned social isolation issues places this emotional state much closer to the ‘pleasure governed by desire’ than to ‘atmosphere of good fellowship’ (Happiness) ( Lawrence et al., 2014 ; Lustig, 2017 ).

The flow, defined as the emotional state embracing perception distortion and enjoyment produced by VG activities, is another element that can create confusion in gamers’ insights into their emotional states ( Chou and Ting, 2003 ; Hull et al., 2013 ). As described in the mentioned study, experiencing flow implies not only losing the notion of time but also merging oneself with the VG actions. In these conditions, the gamer’s senses and attention are in the here and now , with little or no awareness about sources of stress relative to past, present or future events. In this line, the motivation to experience immersion has been associated with problematic gaming ( Billieux et al., 2011 ). Considering the fact that loneliness and depression have been identified as predictors of VG addiction and of Internet Gaming Disorders ( Hull et al., 2013 ; Sarda et al., 2016 ), it is understandable why in gamers’ mind experiencing flow could equate this feeling with a relieving emotional state ( Loonen and Ivanova, 2016 ). This sense of alleviation could match the notion of happiness as free from distress ( Kringelbach and Berridge, 2010 ; Loonen and Ivanova, 2016 ) if it resulted from the quality of real life being lived. Instead, in AU, this relieving and enjoyable emotional state would be engendered by a virtual activity (VG), possibly used as a means to escape from stress and to forget tensions ( Demetrovics et al., 2011 ; Bonnaire and Baptista, 2019 ). In the literature, the escaping strategy is a way to find relieve from stressors through the engagement in a pleasant activity, which may end up representing a space of happiness ( Seay and Kraut, 2007 ).

In sum, the incongruence lies in the coexistence of regarding VG as a space of happiness while using VG to get quick pleasures and relief. Individuals suffering from this disorder tend to pursuit short-term pleasures rather than long-term gains ( Dong and Potenza, 2015 ). Being driven by short-term gratifications rather belongs to the reward-seeking realm ( Waterman et al., 2008 ; Lustig, 2017 ). Thus, this pleasant emotional state could be associated with the arousal linked to a reward seeking behavior through which quick and positive results are obtained, which in turn reinforce the mentioned behavior. Probably, this intense arousal situates itself within the sphere of pleasure as a dysfunction in the rewarding system ( Pollard, 2003 ; Berridge and Kringelbach, 2013 ; Lustig, 2017 ) and not in that of happiness in spite of the relieving benefits it provides.

Another possible reading on why the emotional states generated by these cyber activities are linked with happiness may be related to the way in interpreting the experienced sensations. This representation is probably shaped by the individual background, experiences, culture, etc. From a brain mechanism stand point, conscious liking does not limit it self to a sensory outcome, it is also translated into a subjective liking through the recruitment of cognitive processes ( Berridge and Kringelbach, 2013 ). Indeed, these authors state that conscious pleasure rating is sometimes detached from affective reactions as people can elaborate reasons to themselves for how they should feel. Therefore, associating VG with happiness may be the result of a rationalization process to reduce the cognitive dissonance. In other words, the unwished consequences of the VG addiction pattern (increased stress, problems at working, studying, socializing, etc.) ( Griffiths et al., 2012 ) probably produce an increasing amount of pressure (due to the difficulty to reduce gaming time, guilt, etc.) that can become overwhelming if it lasts too long. Consequently, if the affected individuals are unable to master the yearning for VG, perceiving VG activities as a source of well being may reduce the mentioned pressures insofar as the notion of happiness usually suggests a socially acceptable mood, a legitimate aim and a safe emotional state. In this perspective, equating happiness with satisfying craving and with short-term pleasure might contribute to feed the addictive pattern ( Lustig, 2017 ).

In a broader perspective, the rationalization process described in the previous paragraph may be also related with coping strategies to deal with adversity. For instance, it has been observed that problematic gamers may use VG play as a means to cope with stressors and to enhance mood ( Demetrovics et al., 2011 ). An association has been found between stressful life events and addiction to Internet activities ( Schimmenti et al., 2017 ), with the mediating role of psychological needs satisfaction and the moderating role of coping styles ( Dongping et al., 2016 ). Several theories and studies support this approach that strives for a more holistic understanding of this issue. The self-determination theory postulates that humans share three universal psychological needs ( Deci and Ryan, 2000 ; in Dongping et al., 2016 ): autonomy (i.e., feeling of being self-determining in one’s behavior), relatedness (i.e., the feeling of connectedness to others) and competence (i.e., the feeling of dealing with issues in a competent manner). Besides, individuals can adopt different strategies to cope with adversity ( Lazarus and Folkman, 1984 ; in Dongping et al., 2016 ). According to Zheng et al. (2012 ; in Dongping et al., 2016 ), the positive coping approach is the set of strategies aiming at problem solving, support seeking and cognitive restructuring to address the stressors. On the other hand, according to the same authors, the negative coping consists in strategies such as blaming, social withdrawing, denial and disengagement so as to avoid the stressful situations. Now, a parallel can be established between these two coping styles and the brain activities involved in the goal-directed learning and the habit learning.

The goal-directed learning would correspond to the positive coping style insofar as it focuses on the relationship between an action and the motivational value of the outcome, and is associated with the activation of the prefrontal cortex, the dorsomedial striatum and the dorsomedial thalamus ( Ballaine and Dickinson, 1998 ; in Schwabe et al., 2012 ). On the other hand, habit learning, would be linked with the avoidant coping style. This learning process encodes the relationship between a response and preceding stimuli without taking into account the outcome caused by the response and is related to the activation of the dorsolateral striatum ( Yin et al., 2004 ; Tricomi et al., 2009 ; in Schwabe et al., 2012 ). According to Schwabe et al. (2012) , stressful situations may modulate the processes involved in instrumental learning in a way that may produce the shift from goal-directed learning to habitual learning.

In line with these findings, it has been observed that, like cocaine cues, psychological stress induction can generate the same craving response in a cocaine abusers population ( Bradley et al., 1989 ; Wallace, 1989 ; in Sinha et al., 2000 ). The relevance of these observations lies in the fact that both SUD and behavioral addictions (including gaming disorders, Han et al., 2011 ) recruit to an important extent common brain regions and produce similar physiological patterns, as quoted in the introduction of this document.

Considering the association between unhappiness and VG disorders mentioned earlier, it could be posited that the gamers concerned could not overcome the causes of their unhappiness. Indeed, studies suggest that subjects with Internet gaming disorders embark in VG play more to deal with negative affect than to achieve a good performance in the game ( Schimmenti and Caretti, 2010 ; Billieux et al., 2013 ; both in Bonnaire and Baptista, 2019 ). In this scenario, based on the mentioned studies, a low level of happiness would imply that psychological needs are somewhat unmet and associated with the avoidant coping style together with the habit learning. Furthermore, this pattern is supported by compensatory Internet use theory, which postulates that adversity can operate as a stimulus to seek psychological comfort (i.e., satisfying the psychological needs via the cyberspace) ( Kardefelt-Winther, 2014 ; in Dongping et al., 2016 ).

In other words, the psychological comfort engendered by the VG activities in this population of gamers, combined with the characteristics of the avoidant coping style (denial, social withdrawal, avoiding stressful situation, etc.) and with the traits of the habitual learning (actions’ outcomes are disregarded, with little or no awareness of actions’ consequences), might explain, at least partially, the biased perception of the emotional states in AU ( happiness associated to VG) and of their causes of craving for VG. This assumption suggests that online gaming might not be the cause of VG addiction, but rather that VG excessive use could be a compensatory strategy to deal with pre-existing psychological characteristics and deleterious social context ( Kowert et al., 2015 ). For instance, some studies suggest that traumatic experiences, poor emotions regulation, elements of impulsivity and the motivation to experience immersion in a virtual world would increase the likelihood of IGD and Internet addiction ( Billieux et al., 2011 ; Schimmenti et al., 2017 ).

In sum, it would seem as if for AU the mentioned behavioral pattern is a manner to mitigate the difficulties to deal with stressors. This interpretation would be in line with the motives for play in problematic gaming ( Demetrovics et al., 2011 ). Through a massive survey these authors observed seven dimensions that would cover the entire spectrum of motives for VG play in all sort of on line games: escape (from reality), cope (with stressors, playing as a way to improve mood), fantasy (trying new identities/things in a virtual world), skills development (improving concentration, coordination, new skills) recreation (relaxing aspects of gaming), competing (sense of achievement), and social (knowing/being/playing with others). This study suggests that there would be positive and beneficial motives for playing (entertaining gaming) as well as harmful ones (problematic gaming). The correlations between these factors appear to shed light on the positive and negative aspects of gaming. Whilst the weakest correlation is between escape and recreation (also low correlation was found between escape and both, skills development and competition), the strongest correlations were observed between escape and cope and fantasy. These results would indicate that escape and coping are motives associated with problematic gaming, however, the authors argue that escapism would facilitate the coping efforts to deal with stressors and negative moods. Moreover, it is noteworthy underlining that escapism had the lowest mean score in this study among the seven dimensions, which would match with the prevalence level of problematic gaming mentioned previously ( Griffiths et al., 2012 ).

Probably, regarding AU, the accuracy in perceiving emotional states, the ability to deal with stressors and the quality of insights into oneself are dimensions that deserve much attention in the therapeutic processes.

Therapeutic Implications

A cognitive-behavioral approach may contribute to the recovery process by enabling problematic gamers to explore the motives that lead them to abuse of VG play ( Orzack et al., 2006 ; in Griffiths, 2008 ). Developing strategies to tackle stressors appears to be a therapeutic priority for treating this disorder. Consequently, this axis of work includes the understanding of the environmental demands that are perceived as exceeding the individual abilities to handle them. In this line, ensuring the accuracy of the individual’s insights into the emotional states linked to the sources of stress as well as to the game habit could increase the awareness of the underlying issues to be addressed. In particular, deciphering the conditioned desires (unconscious wanting) and the hedonic dimension (unconscious liking) ( Kringelbach and Berridge, 2009 ; Berridge and Kringelbach, 2013 ) linked to VG play may produce added value information for understanding and overcoming the problematic gaming pattern. Within this frame, it could be hypothesized that distinguishing between happiness and feeling alleviated could be beneficial to the therapeutic process, although it remains to be demonstrated.

Overall, this sort of therapeutic approach may contribute to reduce the alexithymia, usually associated with this kind of disorders ( Kandri et al., 2014 ).

In problematic internet/gaming several studies have explored and highlighted to role of alexithymia and its links with other therapeutic issues. For instance, it has been shown that alexithymic individuals are more associated with Internet addiction than non-alexthymic ones ( Baysan-Arslan et al., 2016 ). In this research, the authors consider that the difficulty in identifying and differentiating emotions that characterizes alexithymia may lead individuals with this affliction to regulate their emotional states via their addictive activities.

Another study showed that IGD would be related with alexithymia, anxiety and depression ( Bonnaire and Baptista, 2019 ).

Schimmenti et al. (2017) observed that traumatic experiences (mainly in males) and traits of alexithymia (mainly in females) were associated with Internet addiction symptoms, which may enable a tailored prevention and treatment approach. Besides, Internet addiction (including online role-playing) would be correlated with alexithymia, dissociation (protecting one-self in a more pleasant created reality as a means to deal with traumatic experiences) and insecure attachment ( Craparo, 2011 ).

However, the causal link in the association between alexithymia and Internet addiction would still need to be verified, as indicated by Mahapatra and Sharma (2018) . Moreover, discerning the nature of alexithymia remains an uneasy task: this emotional identification and differentiation disorder might be regarded as a stable personality trait that could increase risks of mental disorder development, and also may be seen as a defense mechanism to cope with psychological stressors ( Mikolajczak and Luminet, 2006 ; in Mahapatra and Sharma, 2018 ).

Apart from alexithymia and traumatic memories, high urgency (a dimension of impulsivity defined by the proneness to have strong reactions usually tied with negative affect) and being motivated to experience immersion in a virtual world would be psychological predictors of problematic multiplayer online games ( Billieux et al., 2011 ). These findings led the authors to posit that individuals with the two mentioned traits are more likely to use the immersion in the virtual world as a means to avoiding facing real life adverse issues. According to the authors, this behavior will lead to a deleterious outcome (culpability and embarrassment as a result of feeling unable to deal with problems), which in turn is experienced as a pernicious condition likely to activate behaviors related to high urgency and immersion.

Like the previously mentioned clinical issues, this vicious loop reinforcing escapism also appears to be a therapeutic target.

Considering the possible association between alexithymia and problematic gaming as a manner to regulate emotions ( Baysan-Arslan et al., 2016 ; Bonnaire and Baptista, 2019 ), the Emotion Regulation Therapy (ERT) might strengthen the therapeutic process. The aim being that the observed difficulties in Internet (including VG) addicts to identifying emotions and regulating affects ( Caretti et al., 2010 ; in Craparo, 2011 ) could be, at least partially, overcome through the ERT process. In effect, Compare et al. (2014) , show that ERT operates as a means to reappraise emotions that trigger actions leading to negative consequences. Reappraising emotions is associated with the involvement of the medial prefrontal cortex, which attenuates the amygdala activation and, thus, reduces the intensity of negative affect; these two areas being coordinated by the orbitofrontal cortex ( Compare et al., 2014 ). Since AU would be prone to associate happiness with VG play, ERT might facilitate the perceptional change enabling to link VG play with pleasure [ Caretti and Craparo, 2009 ; in Craparo (2011) consider Internet addiction (including VG) “as a syndromic condition characterized by a recurrent and reiterated search for pleasure derived from dependence behavior, associated with abuse, craving , clinically significant stress, and compulsive dependence actions despite the possible negative consequences”]. Within this approach, it may be postulated that enabling problematic gamers to familiarize with and to see the self-transcendent notion of happiness could favor the distinction between pleasure and happiness and would render them less vulnerable from impulses and from environmental circumstances ( Dambrun et al., 2012 ). The idea is to facilitate the shift from wanting more than liking (or even without liking) toward liking with little or without wanting ( Berridge and Kringelbach, 2011 ). Furthermore, regarding motives for playing, it could be posited that helping problematic gamers to identify and distinguish the emotions tied to escaping/coping from those related to recreational gaming ( Demetrovics et al., 2011 ), would be a necessary condition to orient effectively the ERT toward the escaping issues and targeted emotional states requiring therapeutic input. In this line, based on the previously mentioned studies in this section, it might be useful exploring the possible link that the excessive time spent in cyber activity could have with past traumatic experiences, insecure attachment, impulsivity, anxiety and depression.

In conclusion, this study suggests that the mentioned confusion of emotional states (pleasure and happiness) associated with addiction ( Lustig, 2017 ), could take place in subjects with VG addiction, and potentially in the entire spectrum of addictions. Moreover, from a cognitive therapeutic perspective, it shows the potential benefits of reappraising emotions as a means to contribute to the emotional distortion reduction.

Limitations

The small sample of this study demands cautiousness when making generalizations from its results. Besides, watching VG clips rather than actually playing VG might be less stimulating for chronic gamers and could have influenced the physiological values recorded during the clip visioning phases. That said, many gamers do attend to public competitions to watch other gamers playing VG. Although, to the best of our knowledge, there is no information available to affirm that there are VG addicts in these audiences.

We also faced the usual paradox when assessing craving via self-report tools. Indeed, participants were asked to judge their craving intensity for VG play whereas sensing craving often may imply a compromised self-awareness level and thus a self-assessment whose value needs to be interpreted carefully.

Although the GAS is a validated tool, which has shown its usefulness in screening addict gamers, having complemented this measurement with thorough diagnostic-driven interviews run by specialists when choosing participants to form the AU and the NAU groups would have strengthened the selection process.

The participants’ selection was centered on the gamer status (gaming addiction/non-addiction and names of games usually played) rather than on the cultural and/or educational background of the persons. Future researches could complete this approach by assessing the possible cultural and educational bias in perceiving the studied emotional states.

Moreover, including more physiological parameters related to pleasure and happiness could further complete the self-reported information and may enable reaching more robust results.

Prospective Research

Further research is required to better understand the relationship between the studied emotional states and this addiction. For instance, since VG addiction decreases with age ( Wittek et al., 2016 ) a longitudinal study could reveal the factors (psychophysiological, environmental, etc.) that operate that change. Moreover, VG addiction is only one area of the spectrum of addictions. Undertaking similar researches on other addictions and with larger samples could also contribute to deepening the comprehension of this issue. Finally, keep enhancing the scales that measure pleasure and happiness may provide with more accurate information about the range of nuances intrinsic to these two emotional states.

Data Availability Statement

All datasets generated for this study are included in the article/supplementary material.

Ethics Statement

The studies involving human participants were reviewed and approved by the Université Libre de Bruxelles Ethical Committee. The patients/participants provided their written informed consent to participate in this study.

Author Contributions

LG developed the proposal and the conception of the original project research, searched and articulated the theoretical background, participated in the study and protocol design, elaborated the results interpretation, assembled all the chapters of the study, and in charge of the manuscript writing. ND was involved in the scientific and publication management, participated – as the Research Center Manager – in the study and protocol design, and in charge of the configuration and writing of the physiological measures. JL, as a member of the Research Center, was involved in the study and protocol design, also involved in the configuration of physiological measures, managed the experimental phases in the laboratory, and elaborated the data analysis. CL, as a full Professor at the Faculty of Psychology and Director of the Research Center for Work and Consumer Psychology, assured the scientific and publication management, participated in the study and protocol design, in charge of making the critical reviews of the manuscript along the process, and involved in the manuscript writing.

Conflict of Interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Acknowledgments

We would like to express our gratitude to Maastricht University (Department of Psychiatry and Neuropsychology) as well as Université Libre de Bruxelles (Faculty of Psychological Sciences and of Education – Research Center for Work and Consumer Psychology). This work was performed as a partial fulfillment toward the International Master in Affective Neuroscience of Maastricht University and the University of Florence.

Abbreviations

AU, addict users; EEG, Electroencephalogram; ETR, Emotions Regulation Therapy; GAS, Gaming Addiction Scale; H, happiness; HR, heart rate; I.G.D., Internet Gaming Disorders; NAU, non-addict users; OHQ, Oxford Happiness Questionnaire; P, pleasure; SHAPS, Snaith-Hamilton Pleasure Scale; VG, video games.

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Self-Report Questionnaires

– Six items Questionnaire: Pleasure and/or Happiness associated with VG play (Items 7 and 8 were suppressed after the preliminary phase)

(1) I enjoy playing video games.

(2) I am happy when I play video games.

(3) I would find pleasure in my video game activities.

(4) I find video games amusing.

(5) I enjoy playing my favorite video game.

(6) I often experience joy and exaltation when playing video games.

(7) I would feel pleasure when I receive praise from other people on my capacity to play video games.

(8) I don’t have fun when playing video games with other people.

fully disagree disagree slightly disagree slightly agree agree fully agree

<———I——————I——————I————————I——————I—————I———>

– Questionnaire on Craving for playing VG

– After having watched this clip I feel craving for playing video games.

– Three bipolar items Questionnaire: Pleasure and/or Happiness associated with VG play

Bipolar items.

(1) I enjoy playing video games I am happy when I play video games

I——————I——————I——————I—————I

(2) I would find pleasure in I find video games amusing my video game activities

(3) I enjoy playing my favorite I often experience joy and exaltation video game when playing video games

– Ten key words [resulting from the semantic mapping of pleasure (P) and happiness (H)]: 3/10 words to be associated with VG play

– Joy

– Craving

– Well-being

– Impulsivity

– Fellowship

– Desire

– Fun

– Contentment

– Gratification

– Serenity

Pleasure cluster: joy, craving, impulsivity, desire, fun, gratification.

Happiness cluster: well-being, fellowship, contentment, serenity.

– One bipolar item Questionnaire: Pleasure or Happiness associated with VG play (with explicit definitions)

Happiness : emotional state of lasting contentment.

Pleasure : transient emotional state when satisfying a desire, a craving.

A bipolar item

Keywords : video games, addiction, confusion, pleasure and happiness, emotional states

Citation: Gros L, Debue N, Lete J and van de Leemput C (2020) Video Game Addiction and Emotional States: Possible Confusion Between Pleasure and Happiness? Front. Psychol. 10:2894. doi: 10.3389/fpsyg.2019.02894

Received: 03 July 2019; Accepted: 06 December 2019; Published: 27 January 2020.

Reviewed by:

Copyright © 2020 Gros, Debue, Lete and van de Leemput. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY) . The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

*Correspondence: Lucio Gros, [email protected]

Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.

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The Association Between Video Gaming and Psychological Functioning

Juliane m. von der heiden.

1 Department of Psychology, Johannes Gutenberg University Mainz, Mainz, Germany

Beate Braun

2 Department of Psychosomatic Medicine, University Medical Center, Mainz, Germany

Kai W. Müller

Boris egloff, associated data.

Video gaming is an extremely popular leisure-time activity with more than two billion users worldwide ( Newzoo, 2017 ). However, the media as well as professionals have underscored the potential dangers of excessive video gaming. With the present research, we aimed to shed light on the relation between video gaming and gamers’ psychological functioning. Questionnaires on personality and psychological health as well as video gaming habits were administered to 2,734 individuals (2,377 male, 357 female, M age = 23.06, SD age = 5.91). Results revealed a medium-sized negative correlation between problematic video gaming and psychological functioning with regard to psychological symptoms, affectivity, coping, and self-esteem. Moreover, gamers’ reasons for playing and their preferred game genres were differentially related to psychological functioning with the most notable findings for distraction-motivated players as well as action game players. Future studies are needed to examine whether these psychological health risks reflect the causes or consequences of video gaming.

Introduction

Video gaming is a very popular leisure activity among adults ( Pew Research Center, 2018 ). The amount of time spent playing video games has increased steadily, from 5.1 h/week in 2011 to 6.5 h/week in 2017 ( The Nielsen Company, 2017 ). Video gaming is known to have some benefits such as improving focus, multitasking, and working memory, but it may also come with costs when it is used heavily. By spending a predominant part of the day gaming, excessive video gamers are at risk of showing lower educational and career attainment, problems with peers, and lower social skills ( Mihara and Higuchi, 2017 ). On the one hand, video game use is widespread, and it may come with certain precursors as well as consequences. On the other hand, little is known about the relations between various video gaming habits and psychological functioning. This study aims to shed light on these important relations using a large sample.

A video game is defined as “a game which we play thanks to an audiovisual apparatus and which can be based on a story” ( Esposito, 2005 ). In the last few years, the amount of scientific research devoted to video game playing has increased (e.g., Ferguson, 2015 ; Calvert et al., 2017 ; Hamari and Keronen, 2017 ). Most scientific studies in this area of research have focused on the extent of video game play and its diverse correlates. While some researchers have emphasized the benefits of game playing and even suggested a therapeutic use of video games ( Primack et al., 2012 ; Granic et al., 2014 ; Colder Carras et al., 2018 ), others have been intrigued by its potential dangers ( Anderson et al., 2010 ; Müller and Wölfling, 2017 ).

Parents and professionals may be worried about their excessively playing children being “addicted.” However, problematic and potentially addictive video game use goes beyond the extent of playing (in hours per week; Skoric et al., 2009 ). It also includes such issues as craving, loss of control, and negative consequences of excessive gaming. While it is still a matter of debate whether problematic video game play should be considered a behavioral addiction , its status as a mental disorder has been clarified since the release of the DSM-5 in 2013. In the DSM-5, the American Psychiatric Association (2013) defined Internet Gaming Disorder with diagnostic criteria closely related to Gambling Disorder. Generally, this decision has been supported by many researchers (e.g., Petry et al., 2014 ) but has also caused controversies. Researchers have criticized the selection of diagnostic criteria and the vague definition of the Internet Gaming Disorder construct, which excludes offline games from being related to addictive use (e.g., Griffiths et al., 2016 ; Bean et al., 2017 ).

Several studies, literature reviews, and meta-analyses have focused on the correlates of problematic video gaming, usually assessed as a continuum with addiction marking the upper end of the scale (e.g., Ferguson et al., 2011 ; Kuss and Griffiths, 2012 ). The degree of addictive video game use has been found to be related to personality traits such as low self-esteem ( Ko et al., 2005 ) and low self-efficacy ( Jeong and Kim, 2011 ), anxiety, and aggression ( Mehroof and Griffiths, 2010 ), and even to clinical symptoms of depression and anxiety disorders ( Wang et al., 2018 ). Potential consequences of video game use have been identified as well, such as a lack of real-life friends ( Kowert et al., 2014a ), stress and maladaptive coping ( Milani et al., 2018 ), lower psychosocial well-being and loneliness ( Lemmens et al., 2011 ), psychosomatic problems ( Müller et al., 2015 ; Milani et al., 2018 ), and decreased academic achievement ( Chiu et al., 2004 ; Gentile, 2009 ). Effect sizes have varied widely across studies ( Ferguson et al., 2011 ). There seem to be sex and age differences with regard to video gaming behavior: potentially problematic video gaming was found to be more likely among males than females (e.g., Greenberg et al., 2010 ; Estévez et al., 2017 ), and among younger gamers ( Rehbein et al., 2016 ).

In addition to looking at problematic video game use and its relation to psychological functioning, it is relevant to also focus on why individuals play video games. Players use video games for very different reasons ( Ryan et al., 2006 ; Yee, 2006 ) such as to distract themselves from daily hassles or because they enjoy the social relationships they have developed in the virtual world. Potentially problematic video gaming has been found to be related to various reasons for playing such as coping and escape ( Hussain and Griffiths, 2009 ; Schneider et al., 2018 ), socialization ( Laconi et al., 2017 ), and personal satisfaction ( Ng and Wiemer-Hastings, 2005 ). Coping ( Laconi et al., 2017 ), social interaction, and competition were among the main reasons for gaming among males but not among females ( Lucas and Sherry, 2004 ). Mixed results emerged concerning age differences ( Greenberg et al., 2010 ), but especially younger gamers seemed to be motivated for video gaming by social interactions ( Hilgard et al., 2013 ). However, so far it remains unclear to what extent people’s various reasons for playing video games are differentially related to their psychological functioning.

Besides investigating the links between potentially problematic video game use and psychological functioning as well as between reasons for playing video games and psychological functioning, it is relevant to also look at which game genres individuals prefer. Correlates of preferences for certain game genres (e.g., simulation, strategy, action, role-playing) are cognitive enhancement ( Dobrowolski et al., 2015 ; Bediou et al., 2018 ), but also the amount of time spent playing ( Lemmens and Hendriks, 2016 ; Rehbein et al., 2016 ) and psychopathological symptoms ( Laconi et al., 2017 ). Males were shown to prefer action and strategy games, whereas females showed a preference for games of skill ( Scharkow et al., 2015 ; Rehbein et al., 2016 ). Younger gamers seemed to prefer action games, older players more so games of skill ( Scharkow et al., 2015 ). However, it is not yet understood to what extent preferences for certain video game genres are differentially related to psychological functioning.

Typically, research has focused merely on violent video games (e.g., Anderson and Bushman, 2001 ; Elson and Ferguson, 2014 ) or one specific game within one specific game genre (frequently World of Warcraft; Graham and Gosling, 2013 ; Visser et al., 2013 ; Herodotou et al., 2014 ), thereby neglecting the variety of possible gaming habits across various game genres.

In the present study, our objective was to examine the relation between video gaming and psychological functioning in a fine-grained manner. For this purpose, we examined psychological functioning by employing various variables such as psychological symptoms, coping strategies, and social support. Likewise, we assessed video gaming in a similarly detailed way, ranging from (a) problematic video game use, (b) the reasons for playing, to (c) the preferred game genres. This strategy prevented us from making potentially invalid generalizations about video gaming in general and allowed us to examine the spectrum of gaming habits and the respective relations between such habits and a diverse set of variables representing psychological functioning.

Playing video games excessively should be appealing to individuals with poor psychological functioning because games allow people to avoid their everyday problems and instead immerse themselves in another environment ( Taquet et al., 2017 ). Moreover, video games offer people a chance to connect with other people socially despite any more or less evident psychological problems they may have ( Kowert et al., 2014b ; Mazurek et al., 2015 ). On the other hand, potentially problematic video game use may also lead to psychological problems because it reduces the amount of time and the number of opportunities gamers have to practice real-life behavior ( Gentile, 2009 ). Thus, we expected to find a negative correlation between problematic video gaming and variables representing psychological functioning such that we expected more potentially problematic video game use to be related to dysfunctional coping strategies ( Wood and Griffith, 2007 ), negative affectivity ( Mathiak et al., 2011 ), and poor school performance ( Mihara and Higuchi, 2017 ). Moreover, we expected to find differential correlates of people’s reasons for playing video games and their psychological functioning: Playing for escape-oriented reasons such as distraction should go along with diverse indices of poor psychological functioning ( Király et al., 2015 ), whereas playing for gain-oriented reasons such as the storyline or the social connections in the game should be related to adequate psychological functioning ( Longman et al., 2009 ). Also, we expected to find people’s preferred game genres (e.g., strategy, action) to be differentially related to their psychological functioning ( Park et al., 2016 ). Finally, we aimed to shed light on the unique contribution of each measure of psychological functioning to the prediction of problematic video game use.

Materials and Methods

Participants 1.

A total of N = 2,891 individuals (2,421 male, 470 female) with a mean age of 23.17 years ( SD = 5.99, Range: 13–65) participated in our study. Of these participants, N = 2,734 (95%) confirmed their use of video games and were thus included in further analyses (2,377 male, 357 female, with a mean age of 23.06 years; SD = 5.91, Range: 13–65). The distribution of participants with regard to sex and age mirrors the findings of past research with males and younger individuals being more likely to play video games (e.g., Griffiths et al., 2004 ). Participants’ place of residence was Germany.

Procedure and Instruments 2

We posted links to our online questionnaire on various online forums as well as on popular online game sites. To achieve heterogeneity of the sample, no exclusion criteria other than having access to the Internet and understanding German were specified. As an incentive to participate in the study, four vouchers of 50€ were raffled.

Video Gaming

Potentially problematic video game use.

The AICA-S, the Scale for the Assessment of Internet and Computer game Addiction ( Wölfling et al., 2016 ), was used to assess participants’ gaming behavior with regard to potential problematic use. Based on the DSM criteria for Internet Gaming Disorder (tolerance, craving, loss of control, emotion regulation, withdrawal, and unsuccessful attempts to cut back), this standardized self-report scale consists of 15 items usually with a five-point scale ranging from 1 ( never ) to 5 ( very often ). The final score (Min = 0, Max = 27 points) is computed using weighted scoring (items with an item-total correlation > 0.55 in the norm sample are weighted double; Wölfling et al., 2011 ). The AICA-S score can be used to differentiate between regular (0–6.5 points) and problematic use of video games (7–13 points: abuse; 13.5–27 points: addiction). In our sample, N = 2,265 (83%) were identified as regular gamers, and N = 469 (17%) as problematic gamers. We used the AICA-S as a continuous variable for all further analyses ( M = 3.98, SD = 3.22, Range: 0–24). The instrument has been validated for different age groups in the general population and in clinical samples ( Müller et al., 2014a , 2019 , but note small sample size; Müller et al., 2014b ). Cronbach’s alpha was α = 0.70. As expected, the AICA-S score was correlated with male sex ( r = 0.17 ∗∗∗ ) and age ( r = –0.15 ∗∗∗ ). On average, participants played video games for M = 4.09 hours per weekday ( SD = 4.44, Range: 0–24), and M = 4.21 h per day at the weekend ( SD = 2.99, Range: 0–24).

Reasons for playing

Gamers indicated how often they played video games for certain reasons. They rated each of 10 reasons separately on Likert scales ranging from 1 ( never ) to 4 ( very often ). The most prevalent reasons were relaxation ( M = 2.96, SD = 0.91), amusement ( M = 2.94, SD = 0.85), and because of the storyline ( M = 2.67, SD = 1.10).

Game genres

Gamers were asked how often they usually played various video game subgenres such as first-person shooter, round-based strategy, massively multiplayer online role-playing games (MMORPGs), life simulations, and others. Ratings were made on Likert scales ranging from 1 ( never ) to 4 ( very often ). Using Apperley’s (2006) classification of game genres, we categorized the subgenres into the main genres action ( M = 2.54, SD = 0.84), strategy ( M = 2.13, SD = 0.80), role-playing ( M = 2.01, SD = 0.73), and simulation ( M = 1.58, SD = 0.44). A cluster for unclassified subgenres ( M = 1.54, SD = 0.39) was added to additionally account for such subgenres as jump’n’runs and games of skill. Descriptive statistics and intercorrelations for all measures (including sex and age) are presented in Supplementary Tables S1–S4 .

Psychological Functioning

Participants provided ratings of their psychological functioning on the following constructs:

General psychopathology

The SCL-K-9 ( Klaghofer and Brähler, 2001 ), a short version of the SCL-90-R ( Derogatis, 1975 ), was administered to assess participants’ subjective impairment regarding psychological symptoms (somatization, obsessive-compulsive, interpersonal sensitivity, depression, anxiety, hostility, phobic anxiety, paranoid ideation, and psychoticism). The SCL-K-9 score is strongly correlated with the original score of the SCL-90-R ( r = 0.93). The 9 items were answered on 5-point Likert-type scales ranging from 1 ( do not agree at all ) to 5 ( agree completely ). Cronbach’s alpha was satisfactory (α = 0.77).

We assessed 10 coping strategies with the Brief COPE ( Carver, 1997 ; German version by Knoll et al., 2005 ), which is the shorter version of the COPE ( Carver et al., 1989 ): self-distraction, denial, substance use, venting, self-blame, behavioral disengagement, acceptance, active coping, planning, and positive reframing. The two items per subscale were administered on 5-point Likert-type scales ranging from 1 ( never ) to 5 ( very often ). Intercorrelations of the two items per subscale ranged from r = 0.32, p < 0.001 for positive reframing to r = 0.78, p < 0.001 for substance use (with one exception: r = -0.05, p = 0.01 for self-distraction).

We measured general affect as a trait and affect during video gaming as a state using the German version ( Krohne et al., 1996 ) of the Positive and Negative Affect Schedule (PANAS; Watson et al., 1988 ). On a 5-point Likert-type scale ranging from 1 ( not at all ) to 5 ( completely ), participants rated the intensity of 20 adjectives. Cronbach’s alpha was α = 0.78 for general positive affect, α = 0.83 for general negative affect, α = 0.85 for positive affect while playing, and α = 0.83 for negative affect while playing.

The measure for the assessment of shyness in adults ( Asendorpf, 1997 ) consists of 5 items that were answered on a 5-point Likert-type scale ranging from 1 ( not at all ) to 5 ( completely ). Cronbach’s alpha was excellent (α = 0.86).

We administered the German version ( Elbing, 1991 ) of the NYU Loneliness Scale ( Rubenstein and Shaver, 1982 ). The 4 items were answered on 5- to 6-point Likert-type scales. Cronbach’s alpha was satisfactory (α = 0.79).

Preference for solitude

A 10-item measure of preference for solitude ( Nestler et al., 2011 ) was answered on a 6-point Likert-type scale ranging from 1 ( not at all ) to 6 ( completely ). Cronbach’s alpha was excellent (α = 0.86).

Life satisfaction

Participants answered a one-item life satisfaction measure on a 4-point Likert-type scale ranging from 1 ( not at all ) to 4 ( completely ).

Self-esteem

We administered the German version ( von Collani and Herzberg, 2003 ) of the Rosenberg Self-Esteem Scale (RSES; Rosenberg, 1979 ). The 10 items were answered on a 4-point Likert-type scale ranging from 1 ( not at all ) to 4 ( completely ). Cronbach’s alpha was excellent (α = 0.88).

Self-efficacy

We administered a 10-item generalized self-efficacy scale ( Schwarzer and Jerusalem, 1995 ), which was answered on a 4-point Likert-type scale ranging from 1 ( not at all ) to 4 ( completely ). Cronbach’s alpha was excellent (α = 0.86).

Social support and friends

We administered the perceived available social support subscale from the Berlin Social Support Scales (BSSS; Schwarzer and Schulz, 2003 ). The 8 items were answered on a 5-point Likert-type scale ranging from 1 ( not at all ) to 5 ( completely ). Cronbach’s alpha was excellent (α = 0.94). Participants indicated how many offline friends and offline acquaintances they had ( r = 0.44, p < 0.001) as well as how many online friends and online acquaintances they had ( r = 0.33, p < 0.001). Due to left-skewed distributions, we logarithmized the data before aggregation.

Participants reported their grade point average. German grades are assessed on a scale that ranges from 1 ( excellent ) to 6 ( insufficient ). Thus, higher scores indicate worse grades.

Participants further reported their sex and age. Both were used as control variables in further analyses.

In a first step, we computed zero-order correlations between the video gaming variables and the measures of psychological functioning. In a second step, we computed partial correlations in which we controlled for sex and age because past research has repeatedly shown that sex and age are correlated with both video gaming ( Homer et al., 2012 ; Mihara and Higuchi, 2017 ) and psychological functioning ( Kessler et al., 2007 ; Nolen-Hoeksema, 2012 ). Finally, we explored the unique contribution of each measure of psychological functioning to the prediction of potentially problematic video gaming. Therefore, we computed regressions with potentially problematic video gaming as the dependent variable and sex, age, and the measures of psychological functioning as predictors (entered simultaneously into the regression equation). By employing this procedure, we were able to determine the effect that each variable had over and above the other ones. For instance, we could identify whether general psychopathology was predictive of potentially problematic video game use when the influence of all other variables (e.g., shyness, loneliness, and others) was held constant.

Additionally, we included analyses regarding sex and age differences in the link between video gaming and psychological functioning. Since we collected a self-selected sample where different sexes and age groups were not represented equally, our findings are only preliminary, but may stimulate future research.

Potentially Problematic Video Game Use and Psychological Functioning

First, we examined whether potentially problematic video game use was related to various psychological functioning variables. As can be seen in Table 1 , the results for the zero-order correlations were similar to those for the partial correlations in which we controlled for sex and age. A medium-sized positive relation to the potentially problematic use of video games emerged for the presence of psychological symptoms including depression, anxiety, and hostility. Furthermore, several coping strategies were differentially associated with the potentially problematic use of video games: Self-blame and behavioral disengagement showed the strongest positive relations to potentially problematic video game use, followed by denial, acceptance, substance use, self-distraction, and venting. Planning, active coping, and, to a lesser extent, positive reframing were negatively associated with the potentially problematic use of video games. Moreover, the association with potentially problematic video game use was negative for general positive affect and positive and larger in size for general negative affect. However, potentially problematic video game use was clearly positively associated with the experience of both positive and negative affect while playing. Further, a preference for solitude, shyness, and loneliness were positively correlated with the potentially problematic use of video games. Lower self-esteem, lower life satisfaction, and, to a lesser extent, poorer perceived social support and lower self-efficacy went along with potentially problematic video game use. There was an association between fewer offline friends and acquaintances but more online connections with potentially problematic video gaming. Finally, poorer performance in school (i.e., higher grades) was related to the potentially problematic use of video games. These results suggest that potentially problematic video gaming goes along with poor psychological functioning and vice versa.

Associations between potentially problematic video gaming and psychological functioning.

Reasons for Playing Video Games and Psychological Functioning

Second, we investigated whether players’ reasons for playing video games were differentially related to the psychological functioning variables. Table 2 presents the partial correlations, controlling for sex and age. Using video games to distract oneself from stress was clearly connected to a high level of psychological symptoms. Distraction-motivated gamers preferred coping strategies such as self-blame, behavioral disengagement, self-distraction, denial, substance use, venting, and acceptance, but they neglected active coping and planning. They showed less general positive affect and more negative affect both in general and while playing as well as more positive affect while playing. These gamers further reported low self-esteem and low life satisfaction, loneliness, a preference for solitude, shyness, a lack of self-efficacy and social support, and poor achievement in school. A similar but somewhat less extreme picture was revealed for gamers who played video games in order to have something to talk about . However, these gamers reported more online connections. Gamers who played video games to improve their real-life abilities also reported more online connections. In addition, these gamers showed higher levels of general positive affect. The strongest association with online friends and acquaintances emerged, as expected, for gamers who played because of the social relations in the virtual world. Although all reasons for playing video games were related to positive affect while playing, the strongest associations emerged for gamers who played because of the social relations , to stimulate their imagination , and for curiosity . It is interesting that, for gamers who played video games because of the storyline and for relaxation , there was a relation only to positive but not to negative affect while playing. Reasons for playing were only weakly related to sex and age (see Supplementary Table S2 ). In sum, several reasons for playing video games were differentially associated with psychological functioning.

Associations between reasons for playing video games and psychological functioning.

Video Game Genre and Psychological Functioning

Third, we examined whether players’ preferences for different video game genres were differentially associated with the measures of psychological functioning. Table 3 shows the partial correlations in which we controlled for sex and age. There was a weak connection between general psychological symptoms and all of the video game genres we investigated except strategy. A preference for action games had the strongest association with affect while playing. Thus, action games seem to be both rewarding and a source of frustration. A preference for action games went along with poorer school performance. Gamers who preferred role-playing games scored higher on shyness and a preference for solitude and lower on self-esteem; they also reported fewer offline connections. By contrast, preferences for games of the unclassified category on average went along with a larger number of offline friends and more positive affect, both while playing and in general. Two game genres (i.e., role-playing and unclassified games) were related to the coping strategy of self-distraction. Because preferred game genre was related to participants’ sex (see Supplementary Table S3 ), we had a more detailed look at the correlations between preferred game genre and psychological functioning separately for both sexes: For males ( n = 2,377), the strongest correlation between general psychopathology and game genre emerged for action ( r = 0.08, p < 0.001), followed by role playing ( r = 0.07, p < 0.01), and unclassified ( r = 0.07, p < 0.01). For females ( n = 357), the strongest relation between general psychopathology and game genre emerged for simulation ( r = 0.17, p < 0.01). Differences were also found regarding the strength of the relation between number of friends online and the genre action: r = 0.06, p < 0.01 for males, and r = 0.27, p < 0.001 for females. Similarly, preferred game genre was related to participants’ age (see Supplementary Table S3 ). However, there were merely differences with regard to the relation of psychological functioning and game genre, when analyzed separately for different age groups (<19 years, n = 557; 19–30 years, n = 1916; >31 years, n = 261). In sum, our results speak to the idea that individuals with different levels of psychological functioning differ in their choices of game genres and vice versa.

Associations between preferred video game genre and psychological functioning.

Predicting Potentially Problematic Video Game Use by Psychological Functioning Variables

In a final step, we entered all of the investigated psychological functioning variables as well as sex and age as predictors of the potentially problematic use of video games. By employing this procedure, we were able to determine the unique contribution of each psychological functioning variable when the influence of all other variables was held constant. As Table 4 shows, the number of online friends and acquaintances as well as positive affect while playing were most predictive of potentially problematic video game use over and above all other variables. General psychopathology, a lack of offline connections, and poor school performance were weaker but still relevant predictors of potentially problematic video game use.

Prediction of potentially problematic video game use by psychological functioning variables.

With this study, we aimed to shed light on the association of diverse video gaming habits with gamers’ psychological functioning. Drawing on a large sample, our results revealed a medium-sized relation between potentially problematic video game use and poor psychological functioning with regard to general psychological symptoms, maladaptive coping strategies, negative affectivity, low self-esteem, and a preference for solitude as well as poor school performance. These findings are in line with those of prior work (e.g., Kuss and Griffiths, 2012 ; Milani et al., 2018 ). Also, reasons for playing video games were differentially related to psychological functioning with the most pronounced findings for escape-oriented in contrast to gain-oriented motives. Specifically, distraction-motivated gaming went along with higher symptom ratings, lower self-esteem, and more negative affectivity, whereas playing to establish social relationships in the virtual world was related to a larger number of online connections and more positive affect while playing. Furthermore, there were only weak relations between the preferred game genres and psychological functioning. The action games genre was associated with the strongest ratings of affect while playing. These results on reasons and genres may help to explain conflicting findings of former studies, because in our work we examined various reasons for playing, several game genres, and various aspects of psychological functioning simultaneously. Finally, positive affect while playing and a larger number of online friends were the strongest unique predictors of potentially problematic video game use, followed by psychological symptoms, a lack of offline connections, and poor school performance. These findings suggest that, on the one hand, independent of one’s psychological conditions, enjoying oneself during gaming (i.e., experiencing positive affect, connecting with online friends) may go along with potentially problematic use of video games. On the other hand, poor psychological functioning seems to be a unique risk factor for potentially problematic video gaming.

The presented results are generally in line with previous work that has identified a connection between video gaming and psychological health, academic problems, and social problems ( Ferguson et al., 2011 ; Müller et al., 2015 ). However, our study moved beyond prior research by providing in-depth analyses of both video gaming habits (including potentially problematic use, reasons for playing, and preferred game genre) and psychological functioning (including psychological symptoms, coping styles, affectivity, as well as variables that are related to individuals and their social environments). In addition, we identified unique predictors of potentially problematic video game use.

How can the findings on differential relations between video gaming and various indices of psychological functioning – ranging from beneficial results ( Latham et al., 2013 ) to unfavorable results ( Barlett et al., 2009 ; Möller and Krahé, 2009 ; Anderson et al., 2010 ) – be integrated? According to Kanfer and Phillips (1970) , problematic behavior (e.g., excessive video gaming) can be understood as a function of the situation (e.g., being rejected by a peer); the organism (e.g., low self-esteem); the person’s thoughts, physical reactions, and feelings (e.g., sadness, anger); and finally, the short- as well as long-term consequences of the behavior (termed SORKC model). In the short run, according to our results, playing video games may be a way to distract oneself from everyday hassles and may lead to positive affect while playing and a feeling of being connected to like-minded people, all of which are factors that have an immediate reinforcing value. In the long run, however, spending many hours per day in front of a computer screen may prevent a person from (a) developing and practicing functional coping strategies, (b) finding friends and support in the social environment, and (c) showing proper school achievement, factors that are potentially harmful to the person. Thus, differentiating between short- and long-term perspectives may help us understanding the differential correlates of intensive video gaming.

When is it appropriate to speak of video game addiction? More and more researchers have suggested a continuum between engagement ( Charlton and Danforth, 2007 ; Skoric et al., 2009 ) and pathological gaming/addiction, instead of a categorical perspective. In part, this recommendation has also been followed in the DSM-5 ( American Psychiatric Association, 2013 ) where Internet Gaming Disorder is classified with different degrees of severity, ranging from mild to moderate to severe, according to the functional impairment associated with it. The AICA-S also allows for a differential perspective on gaming behavior by providing ways to assess both the time spent playing video games and the main DSM criteria that indicate Internet Gaming Disorder. However, in our study we did not aim at making a diagnosis, but at having a closer look at potentially problematic gaming behavior and its correlates in a non-clinical sample.

In sum, it seems relevant to assess not only the extent of video game use but also the reasons behind this behavior (e.g., distraction) and the concrete rewards that come from playing (e.g., the experience of strong affect while playing action games) to fully understand the relation between video gaming and psychological functioning.

Limitations and Future Directions

With the present study, we aimed to uncover the association between video gaming and psychological functioning. Our approach was cross-sectional and warrants interpretative caution because correlations cannot determine the direction of causation. It remains unclear whether potentially problematic gaming is a factor that contributes to the development of psychological dysfunction or whether psychological dysfunction contributes to potentially problematic gaming. Also, a third factor (e.g., preexisting mental difficulties) may produce both psychological dysfunction and potentially problematic gaming. Thus, longitudinal studies that are designed to identify the causal pathway may provide a promising avenue for future research. Future studies may also answer the question whether the link between video gaming and psychological functioning is moderated by sex, age, the reasons for playing, or the preferred game genre. In addition, it is important not to forget that the present results are based on a self-selected sample in which potentially problematic video gamers were overrepresented (e.g., Festl et al., 2013 , for a representative sample). Thus, future research should replicate our findings in a representative sample. Further, we relied on self-reported data, which is a plausible method for assessing inner affairs such as people’s reasons for their behaviors, but it would be helpful to back up our findings with evidence derived from sources such as peers, caregivers, and health specialists. Our work reflects only a first approach to the topic, and future work may additionally collect in-game behavioral data from the players ( McCreery et al., 2012 ; Billieux et al., 2013 ) to objectively and more specifically investigate diverse patterns of use. Furthermore, one must not forget that the used taxonomy to classify video game genres is only one of various possible options and one should “think of each individual game as belonging to several genres at once” ( Apperley, 2006 , p. 19). Finally, some of the effects reported in our paper were rather modest in size. This is not surprising considering the complexity and multiple determinants of human behavior. In our analyses, we thoroughly controlled for the influence of sex and age and still found evidence that video gaming was differentially related to measures of psychological functioning.

The current study adds to the knowledge on gaming by uncovering the specific relations between video gaming and distinct measures of psychological functioning. Potentially problematic video gaming was found to be associated with positive affect and social relationships while playing but also with psychological symptoms, maladaptive coping strategies, negative affectivity, low self-esteem, a preference for solitude, and poor school performance. Including gamers’ reasons for playing video games and their preferred game genres helped deepen the understanding of the specific and differential associations between video gaming and psychological health. This knowledge might help developing adequate interventions that are applied prior to the occurrence of psychological impairments that may go along with potentially problematic video gaming.

Ethics Statement

In our online survey, participants were given information on voluntary participation, risks, confidentiality/anonymity, and right to withdraw. Whilst participants were not signing a separate consent form, consent was obtained by virtue of completion. We implemented agreed procedures to maintain the confidentiality of participant data.

Author Contributions

BB, BE, JH, and KM conceived and designed the study. BB, JH, and KM collected and prepared the data. JH analyzed the data. BE and JH wrote the manuscript.

Conflict of Interest Statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

1 The data were gathered as part of a larger project ( Stopfer et al., 2015 ; Braun et al., 2016 ). However, the analyses in the present article do not overlap with analyses from previous work.

2 Other measures were administered, but they were not relevant to the present research questions and are thus not mentioned in this paper. The data set and analysis script supporting the conclusions of this manuscript can be retrieved from https://osf.io/emrpw/?view_only=856491775efe4f99b407e258c2f2fa8d .

Supplementary Material

The Supplementary Material for this article can be found online at: https://www.frontiersin.org/articles/10.3389/fpsyg.2019.01731/full#supplementary-material

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