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The Playing Brain. The Impact of Video Games on Cognition and Behavior in Pediatric Age at the Time of Lockdown: A Systematic Review

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A growing number of children and adolescents play video games (VGs) for long amounts of time. The current outbreak of the Coronavirus pandemic has significantly reduced outdoor activities and direct interpersonal relationships. Therefore, a higher use of VGs can become the response to stress and fear of illness. VGs and their practical, academic, vocational and educational implications have become an issue of increasing interest for scholars, parents, teachers, pediatricians and youth public policy makers. The current systematic review aims to identify, in recent literature, the most relevant problems of the complex issue of playing VGs in children and adolescents in order to provide suggestions for the correct management of VG practice. The method used searches through standardized search operators using keywords related to video games and the link with cognition, cognitive control and behaviors adopted during the pandemic. Ninety-nine studies were reviewed and included, whereas twelve studies were excluded because they were educationally irrelevant. Any debate on the effectiveness of VGs cannot refer to a dichotomous approach, according to which VGs are rigidly ‘good’ or ‘bad’. VGs should be approached in terms of complexity and differentiated by multiple dimensions interacting with each other.

1. Introduction

In the last decades, a very large body of literature has shown an increasing interest in video games (VGs) and their impact on the brain, cognition and behavior, especially in children and adolescents [ 1 ]. Indeed, a widely growing number of children and adolescents play VGs for a long time, often developing real addictive behaviors [ 2 , 3 ]. In addition, the current outbreak of the COVID-19 pandemic and the following lockdown have significantly reduced outdoor activities and direct interpersonal relationships [ 4 , 5 ]. However, literature data are still inconsistent. For example, according to some meta-analytic reviews [ 6 , 7 , 8 ], exposure to violent VGs is a causal risk factor for increased aggressive behavior, cognition and affection in children and adolescents. Conversely, many cross-sectional and intervention studies have shown that the intensive use of some types of VGs leads to significant improvements in many cognitive domains and behaviours [ 1 , 9 , 10 , 11 ]. Video games are even considered as ‘virtual teachers’ and effective and ‘exemplary teachers’ [ 12 , 13 ].

The current systematic review focuses on some crucial outstanding issues within the debate on the effects of VGs on cognition and behavior in order to provide suggestions for parents, pediatricians, health providers and educators dealing with pediatric ages, especially in the complex pandemic period. Namely, it analyzes the most debated and educationally relevant problems on the relationship between video games, cognition and behavior: 1. video games’ effects on cognitive function; 2. video games’ effects on attention and addictive behaviors; 3. video games and prosocial or aggressive behavior. Therefore, the current analysis may be accounted as an original contribution to the practical dimension in the educational and rehabilitation field for parents and educators.

Early common predominant opinions mainly focused on VGs according to dichotomous thinking, as enjoyable entertainment or harmful tools [ 14 ]. The recent literature instead provided evidence on the impact of VGs on the brain and its functional modifications while playing [ 15 , 16 , 17 , 18 , 19 ], showing that video games involve different cortical and subcortical structures, with cognitive and emotional competence, such as frontal and prefrontal regions, the posterior and superior parietal lobe, the anterior and posterior cingulate cortices, limbic areas, the amygdala, the entorhinal cortex and basal nuclei [ 1 , 20 , 21 , 22 ].

Mondéjar and colleagues [ 15 ], in a group of twelve healthy preadolescents between 8 and 12 years old, evaluated the frontal lobe activity and the different types of cognitive processing during five platform-based action videogame mechanics: 1. accurate action, related to processes such as concentration, attention, impulse control and information comprehension; 2. timely action, related to working memory, selective attention, decision-making, problem solving and perception; 3. mimic sequence, related to working memory, focalized attention and inhibition control; 4. pattern learning, as selective attention, planning, inhibition control and spatial orientation; 5. logical puzzles related to attention, working memory, the capacity for abstraction, information processing, problem solving, or resistance to interference. They found prominent bioelectrical prefrontal activity during the performance related to executive functions (timely action, pattern learning, logical puzzles) and more global brain activity and a higher presence of alpha waves, or a greater activation of the temporal lobe, in the accurate action and mimic sequence. Similarly, they correlated higher magnitudes on frequency bands with five game mechanics in ten healthy children, who played with a VG platform for an average of about 20 min [ 16 ]. Theta waves, related to memory and emotions, were more significant in the five mechanics, while beta waves, related to concentration, were more prominent in only two. Moreover, activation was more significant in the intermediate and occipital areas for all the mechanics, while recurrent magnitude patterns were identified in three mechanics.

Similarly, Lee et al. [ 17 ], found a thinner cortex and a smaller gray matter volume in critical areas for evaluating reward values, error processing and adjusting behavior, namely, the anterior cingulate cortex, the orbitofrontal cortex and the frontoparietal areas, in young male adults with internet gaming disorders, compared to age-matched healthy male controls. A neuroimaging study examined in individuals affected by gaming disorders the differences during the playing of a violence-related vs. a non-violence-related version of the same VG [ 18 ]. While functional connectivity of the reward-related network and the behavioral inhibition system was altered, the orbitofrontal cortex and anterior cingulate cerebral area were overstimulated, similarly to smart drug addiction [ 17 , 23 ].

Recently, Kwak et al. [ 19 ] longitudinally compared 14 adolescents with internet gaming disorder to 12 professional internet gaming students who practiced for about ten hours a day, within a defined support system that included practice, physical exercise, lectures on team strategy, rest and mealtimes. After one year, both groups showed increased brain activity within the attention system of the parietal lobe. However, professional gamers improved problematic behaviors, impulsivity, aggression, depression and anxiety, while adolescents with internet gaming disorder showed no behavioral improvement and a dysfunctional brain activity within the impulse control network in the left orbitofrontal cortex.

The current systematic review was structured according to the guidelines and recommendations contained in the PRISMA statement [ 24 ].

Eligibility Criteria

Both experimental and correlational studies and meta-analyses between the years of 2000 and 2020 that investigated outcomes of VG exposure were included. They were considered children and adolescents. Studies employing different methodologies were included: studies in which naive participants were trained to use a VG versus a control group and studies comparing experienced versus non-gamers, or inexperienced players. Primary outcome measures were any type of structural and functional data obtained using neuroimaging techniques and behavioral testing.

Information Sources

One hundred and twenty-two studies were identified through electronic database searching in Ovid MEDLINE, Embase, PsycINFO, PubMed, Scopus (Elsevier) and Web of Sciences. The final database search was run on January 2021 using the following keywords: video games; video games and cognition; video games and epidemic; cognitive control; behavior control; brain and video games; spatial cognition; prosocial behavior; violence in video games; aggressive behavior; addictions in adolescents; children and video games.

Study Selection

Inclusion criteria: written in English; published since 2000; deals in depth with cognitive skills, attention, executive functions, or cognitive control; follows a high methodological rigor.

Exclusion criteria: does not refer to key topics directly; the full text could not be obtained; lack of transparency due to missing methodology information. Ninety-nine studies were reviewed and included, whereas twelve studies were excluded because they were irrelevant to the topic or because the full text was not obtained. General communication materials, such as pamphlets, posters and infographics, were excluded as they do not provide evidence about their effectiveness.

Figure 1 shows the selection of studies flowchart.

Selection of studies flowchart.

3.1. Effect of Video Games on Cognitive Functions

Any modern VG requires an extensive repertoire of attentional, perceptual and executive abilities, such as a deep perceptual analysis of complex unfamiliar environments, detecting relevant or irrelevant stimuli, interference control, speed of information processing, planning and decision making, cognitive flexibility and working memory.

Literature data in the last years have proven that VGs may improve a variety of cognitive domains [ 1 , 25 ] as, for example, even just 10 hours of VG could improve spatial attention and mental rotation [ 26 , 27 ]. A large variety of design studies reported in habitual players better performance in multiple cognitive domains, including selective attention [ 3 , 21 , 26 , 28 ], speed of processing [ 21 , 28 ], executive functions [ 29 , 30 ] and working memory [ 31 ]. Similarly, a large body of intervention studies have shown improvements in the same cognitive domains in non-players following training in action VGs [ 27 , 32 , 33 , 34 , 35 , 36 , 37 ]. Recently, Benoit et al. [ 38 ] examined in 14 professional VG players and 16 casual VG players various cognitive abilities, such as processing speed, attention, memory, executive functions, manual dexterity and tracking multiple objects in three dimensions [ 39 ]. Professional players showed a very large advantage in visual–spatial short-term memory and visual attention, and less in selective and sustained attention and auditory working memory. Moreover, they showed better speed thresholds in tracking multiple objects in three dimensions overall, though the rate of improvement did not differ in the two groups. In two previous meta-analyses, Bediou et al. [ 40 ] focused on the long-term effects of action VGs on various cognitive domains using both cross-sectional and intervention studies. Overall, the results documented a positive impact of action video gaming on cognition. In cross-sectional studies, a main effect of about half a standard deviation was found. The habitual action game players showed better performance than non-players. Likewise, intervention studies showed about a third of a standard deviation advantage in cognition domains in action VG trainees. Perception, spatial cognition and top-down attention were the three cognitive domains with the most robust impact [ 40 ].

Homer et al. [ 41 ] examined the effectiveness of a custom-designed VG (‘alien game’) in a group of 82 healthy adolescents (age range 14–18 years; average = 15.5 years) trained to play for 20 min per week for 6 consecutive weeks. Such a digital game was devised to target, in a fun way, the specific executive ability of shifting, as the ability to shift between tasks or mental sets, hypothesizing that after playing the ‘alien game’ over a period of several weeks, adolescents would show significant improvements in the targeted ability. Pre- and post-test measures of another executive ability, inhibition, as the ability to control a prepotent response, were also recorded in order to examine the extent to which training would transfer from one executive ability to another. Significant advantages both in shifting and in inhibition abilities were found, providing evidence that VGs can be effective tools for training executive abilities [ 42 , 43 ].

Similarly, Oei and Patterson [ 44 ] examined the effect of action and non-action VGs on executive functions. Fifty-two non-VG gamers played one of four different games for 20 h. Pre- and post-training tests of executive function were administered. The group that trained on the physics-based puzzle game, demanding high level planning, problem solving, reframing, strategizing and new strategies from level to level, improved in several aspects of executive function. In a previous study, the same authors [ 45 ] instructed 75 non-gamers, (average age 21.07 ± 2.12) to play for 20 h, one hour a day/five days a week over four weeks. They compared effects of action and non-action games to examine whether non-action games also improve cognition. Four tests pre- and post-training were administered. The results showed that cognitive improvements were not limited to training with action games and that different games improved different aspects of cognition. Action VGs have even been used to treat dyslexic children [ 46 , 47 ]. Only 12 h of action VGs, for nine sessions of 80 min per day, significantly improved reading and attentional skills [ 48 ].

Moreover, several meta-analytic studies provide evidence that action VG training may become an efficient way to improve the cognitive performance of healthy adults. Wang et al. [ 49 ], in a meta-analysis, found that healthy adults achieve moderate benefits from action VG training in overall cognitive ability and moderate to small benefits in specific cognitive domains. In contrast, young adults gain more benefits than older adults in both overall cognition and specific cognitive domains.

In summation, the studies on VG effects, by different methodologies, document both in adults and in children significant positive outcomes in different cognitive domains. Such performance improvements may be paralleled by functional brain remodelling [ 14 ].

3.2. Video Games Effect on Attention and Addictive Behaviors

Attentional problems are accounted as a crucial area of focus on outcomes of intensive game-play practices in children and adolescents. However, literature on the topic appears inconsistent. While some research has found mixed results [ 50 ] or a positive effect [ 51 , 52 , 53 ], or no relationship between VG practice and attention, other studies have linked VG playing with greater attention problems, such as impulsiveness, self-control, executive functioning, and cognitive control [ 53 , 54 , 55 ].

Gentile et al. [ 56 ], examining longitudinally, over 3 years, a large sample of child and adolescent VG players aged 8–17 (mean = 11.2 ± 2.1), suggested a bidirectional causality: children who spend more time playing VGs have more attention problems; in turn, subjects who have more attention problems spend more time playing VGs. Therefore, children and adolescents with attention problems are more attracted to VGs (excitement hypothesis), and, in turn, they find it less engaging to focus on activities requiring more control and sustained attention, such as educational activities, homework or household chores (displacement hypothesis). According to such hypotheses, and to the operant conditioning model [ 57 , 58 ], VGs, providing strong motivational cues, become more rewarding for impulsive children and teenagers [ 51 ] who, in such contexts, experience a sense of value and feelings of mastery that they do not experience in their daily relationships [ 59 ].

Actually, any modern VG is a highly engaging activity with a variety of attractive cues, such as, for example, violence, rapid movement, fast pacing and flashing lights [ 60 , 61 ]. According to the attractive hypothesis [ 56 ], it may provide a strong motivation and support for attention and even become addictive, especially in subjects with problems maintaining attention in usual, monotonous and poorly engaging tasks. Therefore, paradoxically, a greater VG exposure may improve visual attention skills involved in such engaging play [ 26 ], but it may impair the ability to selectively focus on a target for lasting time, without external exciting cues.

Probably, in line with the bidirectional causality framework [ 56 ], such rewarding conditions could become the psychological context for the structuring of addictive behaviors, such as a sense of euphoria while playing, feeling depressed away from the game, an uncontrollable and persistent craving to play, neglect of family and friends, problems with school or jobs, alteration of sleeping routines, irregular meals and poor hygiene [ 14 ]. The most psychologically fragile subjects may be most attracted to an engaging and rewarding activity, ensuring an effective compensation to their fragility [ 14 ]. However, the topic of video game addiction continues to present today many outstanding issues. There is a large consensus that ‘pathological use’ is more debilitating than ‘excessive use’ of VGs alone [ 62 , 63 , 64 ]. Addictive behavior appears associated with an actual lowering in academic, social, occupational, developmental and behavioral dimensions, while excessive use may simply be an excessive amount of time gaming. According to Griffiths’ suggestions, ‘healthy excessive enthusiasms add to life, whereas addiction takes away from it’ [ 65 ]. However, it is sometimes difficult to identify the clear line between unproblematic overuse of gaming and the pathological and compulsive overuse that compromises one’s lifestyle and psychosocial adjustment [ 66 , 67 , 68 ]. Therefore, there may be a risk of stigmatizing an enjoyable practice, which, for a minority of excessive users, may be associated with addiction-related behaviors [ 69 , 70 ]. Przybylski and colleagues, in four survey studies with large international cohorts (N = 18,932), found that the percentage of the general population who could qualify for internet gaming disorders was extremely small (less than one percent) [ 71 ].

In such a discussion of the pathological nature of VGs, another outstanding question is whether pathological play is a major problem, or if it is the phenomenological manifestation of another pathological condition. Several studies have suggested that video game play can become harmful enough to be categorized as a psychiatric disorder, or it could be a symptom of an underlying psychopathological condition, such as depression or anxiety. Moreover, the functional impairments observed in individuals with game addictions are also thought to be similar to the impairments observed in other addictions. Neuroimaging studies have shown that the brain reward pathways which are activated during video game playing are also activated during cue-induced cravings of drug, alcohol or other type of substances abuse [ 72 , 73 , 74 ].

Some longitudinal studies [ 14 , 75 , 76 ] proved that pathological addictive behaviors, such as depression, are likely to be outcomes of pathological gaming rather than predictors of it [ 77 , 78 ]. Lam and Peng [ 79 ], in a prospective study with a randomly generated cohort of 881 healthy adolescents aged between 13 and 16 years, found that the pathological use of the internet results in later depression. Similarly, Liau et al. [ 80 ], in a 2-year longitudinal study involving 3034 children and adolescents aged 8 to 14 years, found that pathological video gaming has potentially serious mental health consequences, in particular of depression.

In summary, attention problems and addictive behaviors in the context of VGs should be addressed in a circular and bidirectional way in which each variable can influence the others.

3.3. Video Games Effect and Prosocial and Aggressive Behaviors

The positive impact of video games also concerns the social and relational dimension, as occurs in the VG training of prosocial or educational skills. Several studies have reported that playing prosocial VGs, even for a short time, increases prosocial cognition [ 81 ], positive affect [ 82 ] and helping behaviors [ 13 , 81 , 82 , 83 , 84 , 85 ], whereas it decreases antisocial thoughts and the hostile expectation bias, such as the tendency to perceive any provocative actions of other people as hostile even when they are accidental [ 13 , 86 ]. Such findings have been found in correlational, longitudinal and experimental investigations [ 82 , 85 , 87 ].

In four different experiments [ 13 ], playing VGs with prosocial content was positively related to increased prosocial behavior, even though participants played the VGs for a relatively short time, suggesting that VGs with prosocial content could be used to improve social interactions, increase prosocial behavior, reduce aggression and encourage tolerance.

Following experimental, correlational, longitudinal and meta-analytic studies provided further evidence that playing a prosocial VG results in greater interpersonal empathy, cooperation and sharing and subsequently in prosocial behavior [ 87 , 88 , 89 , 90 ].

Such literature’s data are consistent with the General Learning Model [ 91 , 92 ], according to which the positive or negative content of the game impacts on the player’s cognition, emotions and physiological arousal, which, in turn, leads to positive or negative learning and behavioral responses [ 12 , 93 , 94 , 95 ]. Therefore, repeated prosocial behavioral scripts can be translated into long-term effects in cognitive, emotional and affective constructs related to prosocial actions, cognition, feelings, and physiological arousal, such as perceptual and expectation schemata, beliefs, scripts, attitudes and stereotypes, empathy and personality structure [ 83 , 91 ].

In the same conceptual framework, educational video games have been found to positively affect behaviors in a wide range of domains [ 12 ], school subjects [ 96 ] and health conditions [ 97 , 98 ]. In randomized clinical trials, for example, diabetic or asthmatic children and adolescents improved their self-care and reduced their emergency clinical utilization after playing health education and disease management VGs. After six months of playing, diabetic patients decreased their emergency visits by 77 percent [ 99 ]. Therefore, well-designed games can provide powerful interactive experiences that can foster young children’s learning, skill building, self-care and healthy development [ 100 ].

Violence in VGs is a matter of intense debate, both in public opinion and in the scientific context [ 101 , 102 ]. A vast majority of common opinions, parents and educators consider the violence of VGs as the most negatively impacting feature to emotional and relational development of youth and children. Actually, studies agree on the negative impact of violent video games on aggressive behavior. Several meta-analyses have examined violent VGs [ 6 , 7 , 8 , 103 ] and, although they vary greatly in terms of how many studies they include, they seem to agree with each other. The most comprehensive [ 8 ] showed that violent VGs, gradually and unconsciously, as a result of repeated exposure to justified and fun violence, would increase aggressive thoughts, affect and behavior, physiological persistent alertnes, and would desensitize players to violence and to the pain and suffering of others, supporting a perceptual and cognitive bias to attribute hostile intentions to others.

Similarly, experimental, correlational and longitudinal studies supported the causal relationship between violent VGs and aggression, in the short- and long-term, both in a laboratory and in a real-life context. A greater amount of violent VGs, or even a brief exposure, were significantly associated with more positive attitudes toward violence [ 104 ], higher trait hostility [ 105 ] and with increased aggressive behaviors [ 106 ], physical fights [ 107 ] and aggressive thoughts [ 108 ] and affect [ 109 ]. In a two-year longitudinal study, children and adolescents who played a lot of violent VGs showed over time more aggressive behaviors, including fights and delinquency [ 110 ]. Saleem, Anderson and Gentile [ 82 ] examined the effects of short-term exposure to prosocial, neutral and violent VGs in a sample of 191 children of 9–14 years old. Results indicated that while playing prosocial games increased helpful and decreased hurtful behaviour, the violent games had the opposite effect.

In summation, the overall literature data support the opinion that violent video games, over time, affect the brain and activate a greater availability to aggressive behavior patterns, although some researchers have pointed out that the negative effects of violent VGs are small and may be a publication bias [ 14 , 111 ].

4. Discussion

The focus of the current overview was to identify, from a functional point of view, the most significant issues in the debate on the impact of VGs on cognition and behavior in children and adolescents, in order to provide suggestions for a proper management of VG practice.

Overall, the reviewed literature agrees in considering the practice of VGs as much more than just entertainment or a leisure activity. Moreover, research agrees that any debate on the effectiveness of VGs cannot refer to a unitary construct [ 14 ], nor to a rigidly dichotomous approach, according to which VGs are ‘good’ or ‘bad’ [ 1 , 12 , 112 , 113 ].

The term ‘video game’ should be viewed as an ‘umbrella term’ that covers different meanings, far from a single unitary construct [ 14 , 114 ]. Furthermore, VGs and their effects should be approached in terms of complexity and differentiated by multiple dimensions interacting with each other and with a set of other variables, such as, for example, the player’s age and personality traits, the amount of time spent playing, the presence of an adult, the game alone or together with others and so on [ 115 ].

Gentile and colleagues [ 116 , 117 , 118 , 119 ] have identified five main features of VGs that can affect players: 1. amount of play; 2. content; 3. context; 4. structure; and 5. mechanics. Each of these aspects can produce or increase different thoughts, feelings and behaviors.

However, the content effects, individually focused, are frequently overemphasized. According to the General Learning Model, children would learn the contents of the specific games and apply them to their lives. Nevertheless, a violent game using a team-based game modality may have different impacts than a violent game using a ‘free for all’ game modality. Although both are equally violent games, the former could suggest teamwork and collaborative behaviors, while playing in an ‘everyone for oneself’ mode could foster less empathy and more aggressive thoughts and behaviors [ 8 , 88 ].

Likewise, the outside social context can have different effects and it may even mitigate or reinforce the effects of the content. Playing violent games together with others could increase aggression outcomes if players reinforce each other in aggressive behavior. Instead, it could have a prosocial effect if the motivations to play together are to help each other [ 120 ].

According to the dominant literature, the psychological appeal of video games may be related to an operant conditioning that reinforces multiple psychological instances, including the need for belonging and social interaction [ 57 , 58 ]. On such drives and reinforcements, the playing time can expand, and it may become endless in addicted subjects. However, the amount of play, regardless of the content, can become harmful when it displaces beneficial activities, affects academic performance or social dimensions [ 52 , 121 ], or supports health problems, such as, for instance, obesity [ 122 , 123 , 124 ], repetitive strain disorder and video game addiction [ 76 , 83 ]. However, a greater amount of time inevitably implies increased repetition of other game dimensions. Therefore, it is likely that some associations between time spent and negative outcomes result from other dimensions, and not from amount of time per se. Moreover, children who perform poorly at school are likely to spend more time playing games, according to the displacement hypothesis, but over time, the excessive amount of play may further damage academic performance in a vicious circle [ 116 ].

VGs can also have a different psychological appeal in relation to their structural organization and the way they are displayed. Many structural features can affect playing behavior, regardless of the individual’s psychological, physiological, or socioeconomic status [ 125 ], such as, for instance, the degree of realism of the graphics, sound and back-ground, the game duration, the advancement rate, the game dynamics such as exploring new areas, elements of surprise, fulfilling a request, the control options of the sound, graphics, the character development over time and character customization options, the winning and losing features as the potential to lose or accumulate points, finding bonuses, having to start a level again, the ability to save regularly, the multi-player option building alliances and beating other players [ 125 ].

The more or less realistic mechanics can also configure the game differently and affect fine or gross motor skills, hand-eye coordination or even balance skills, depending on the type of controller, such as a mouse and keyboard, a game control pad, a balance board, or a joystick.

Therefore, VGs may differ widely in multiple dimensions and, as a result, in their effects on cognitive skills and behavior [ 3 , 33 ]. Moreover, the different dimensions may interact with each other and with the psychological, emotional and personality characteristics of the individual player and context. Even the same game can have both positive and negative effects in different contexts and for different subjects.

The current analysis of the literature, therefore, supports the need for further experimental and longitudinal research on the role of multiple characteristics of video games and their interactions. A wide-ranging approach dynamically focused on the multiple dimensions will allow a deeper theoretical understanding of the different aspects of video games.

Nevertheless, according to common opinion, the violence would always have a negative impact on behavior, especially in pediatric subjects. However, a strictly causal relationship between violent VGs and aggressive behavior appears rather reductive [ 126 , 127 ]. Aggressive behavior is a complex one and arises from the interaction of a lot of factors. Therefore, violent VGs, with no other risk factors, should not be considered ‘per se’ the linear cause and single source of aggressive or violent behavior. Antisocial outcomes can be influenced by personality variables, such as trait aggression, or by a number of the ‘third variables’ such as gender, parental education, exposure to family violence and delinquency history [ 83 ]. According to social learning theories [ 128 ], aggressive behavior would arise from repeated exposure to violence patterns [ 129 ]. Therefore, children who have other risk factors for violent or aggressive behavior, such as violent family patterns, excessive amount of time spent playing, playing alone, and so on are more likely to have negative consequences from playing violent video games.

An alternative theoretical framework [ 126 , 127 ] assumes that violent behavior would result from the interaction of genetically predisposed personality traits and stressful situations. In such a model, violent VGs would act as ‘stylistic catalysts’ [ 127 ], providing an individual predisposed to violence with the various models of violent behavior. Therefore, an aggressive child temperament would derive from a biological pathway, while the violent VG, as a ‘stylistic catalyst’, may suggest the specific violent behavior to enact.

Conversely, playing prosocial VGs, even for a short time, increases prosocial cognition, affect and behaviors in children and adolescents [ 13 , 81 , 82 , 83 , 84 , 85 , 89 ]. Several intervention or training studies showed that a prosocial VG should activate experiences, knowledge, feelings and patterns of behavior relating to prosocial actions, cognition, feelings and physiological arousal. In turn, in line with the General Learning Model, [ 91 , 130 ], recurrent prosocial behavioral scripts produce new learning, new behavioral patterns and emotional and affective cognitive constructs [ 83 ].

Moreover, several studies emphasize the educational and academic potential of VGs that may become effective and ‘exemplary teachers’ [ 12 , 82 ] providing fun and motivating contexts for deep learning in a wide range of content [ 12 ], such as school learning [ 96 ], rehabilitation activities [ 46 , 47 ], new health care and protection behavior development and the enhancement of specific skills [ 97 , 99 , 100 ]. Similarly, the literature data document that the intensive use of VGs results in generalized improvements in cognitive functions or specific cognitive domains, and in behavioral changes [ 1 ]. Actually, VGs involve a wide range of cognitive functions, and attentional, perceptual, executive, planning and problem solving skills. They can, therefore, be expected to improve different perceptual and cognitive domains. However, on a methodological level, the impact on behavior and cognition cannot be simplistically viewed as the linear result of a causal relationship between VG and performance. For instance, subjects with better perceptual abilities are likely to choose to play and, as a result, their increase in performance may reflect their baseline level rather than the effects of the game.

Studies focused on the attentional functions in VG playing reported inconsistent data. Playing action games may improve attention skills implied in a specific game. However, according to the attractive hypothesis [ 56 ] and operant conditioning theory, children and adolescents with attentional problems may be attracted by the motivating and engaging VG activities. On the other hand, children and adolescents with a wider VG exposure show greater attention problems [ 53 ]. The relationship between VGs and attention, then, seem to be approached in terms of bidirectional causality [ 56 ].

Similarly, since VGs and their cues appear more pleasant and desirable, a large amount of attractive VG exposure can lead to addiction and impair ability to focus on effortful goal oriented behavior [ 131 ]. However, the literature does not yet appear to agree on the objective diagnostic criteria for classifying behavioral game addiction [ 132 ].

In the fifth edition appendix of the Diagnostic and Statistical Manual of Mental Disorders [ 133 ], the diagnostic criteria for Internet Gaming Disorder included both specific internet games and offline games. However, this has led to some confusion as to whether excessive video games must necessarily occur online [ 134 , 135 ]. According to some authors, since ‘Internet addiction’ includes heterogeneous behaviors and etiological mechanisms, the term ‘video game disorder’ or simply ‘gaming disorder’ would be more suitable [ 136 , 137 ], while the term ‘Internet addiction’ appears inappropriate. Individuals rarely become addicted to the medium of the internet itself [ 137 , 138 ]. Moreover, it has also been supported theoretically [ 135 ] and empirically proven [ 139 ] that problematic internet use and problematic online gaming are not the same.

The debate on the relationship between pure game addiction behaviors and game addiction in comorbidity with other psychiatric disorders appears still on. Some researchers have argued that game addiction, as a standalone clinical entity, does not exist [ 140 ], but it is simply a symptom of psychiatric illnesses such as major depressive disorder or Attention Deficit Hyperactivity Disorder. Equally poorly defined is the question of genetic predisposition and vulnerability to game addiction.

Likewise, the relationship between clinical symptoms and changes in brain activity and the dynamics by which video games triggers such widespread brain plasticity needs to be more clearly defined.

5. Conclusions

The current analysis of the literature provides strong evidence on the power of video games as highly motivating and engaging tools in the broader context of cognitive, emotional and relational development of children and adolescents. However, the effectiveness of such tools does not arise exclusively from their content, but it results from a set of variables interacting each other.

Video games, beyond their content, can favor pathological aggression, withdrawal, escape from reality and reduction of interests. Virtual reality becomes more attractive than the real one and can become the ‘non-place’ to escape from the complexity of everyday life. Recently, to contain the spread of the COVID-19 pandemic, health authorities have forced populations to stay home and children and adolescents may experience an exacerbation of exposure to video games.

Parents, educators and teachers should ensure an educational presence, monitoring times and modalities of VG practice in a broader context in which children and adolescents live with a wider repertoire of interests, without losing social and relational engagement. Moreover, pediatric health care visits may be a great opportunity to support parents helping children to deal with media and video games.

On these assumptions, as practical suggestions to prevent or mitigate addictive behaviors, parents and educators should enforce the golden rule as the educational presence of the adult.

Moreover, in line with the literature, the core values to prevent a negative impact of video games should be focused on a few rules to be proposed with assertiveness and authority: 1. set a clear time limit to play, 2. prefer games that can also be played with family, 3. alternate video games with other games and activities, 4. avoid highly addictive games, 5. keep a social life in the real world.

Author Contributions

Conceptualization, D.S., L.D.F. and G.L.; methodology, D.S., E.G.; formal analysis, D.S., E.G. and L.D.F.; data curation, E.G. and L.D.F.; writing—original draft preparation, D.S., E.G. and L.D.F.; writing—review and editing, D.S.; supervision, D.S. and G.L.; funding acquisition, D.S. and G.L. All authors have read and agreed to the published version of the manuscript.

This research received no external funding.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Data availability statement, conflicts of interest.

The authors declare no conflict of interest.

Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.

SYSTEMATIC REVIEW article

Video games for well-being: a systematic review on the application of computer games for cognitive and emotional training in the adult population.

• Riccardo Massa Department of Human Sciences for Education, University of Milan Bicocca, Milan, Italy

Background: Although several excellent reviews and meta-analyses have investigated the effect of video game trainings as tools to enhance well-being, most of them specifically focused on the effects of digital games on brain plasticity or cognitive decline in children and seniors. On the contrary, only one meta-analysis results to be focused on the adult population, and it is restricted to examining the effects of training with a particular genre of games (action video games) on cognitive skills of healthy adults.

Objectives: This systematic review was aimed to identify research evidences about the impact on cognitive [i.e., processing and reaction times (RTs), memory, task-switching/multitasking, and mental spatial rotation] and emotional skills of video games training in the healthy adult population.

Methods: A multi-component analysis of variables related to the study, the video games, and the outcomes of the training was made on the basis of important previous works. Databases used in the search were PsycINFO, Web of Science (Web of Knowledge), PubMed, and Scopus. The search string was: [(“Video Games” OR “Computer Games” OR “Interactive Gaming”)] AND [(“Cognition”) OR (“Cognitive”) OR (“Emotion”) OR (“Emotion Regulation”)] AND [“Training”].

Results: Thirty-five studies met the inclusion criteria and were further classified into the different analysis' variables. The majority of the retrieved studies used commercial video games, and action games in particular, which resulted to be the most commonly used, closely followed by puzzle games. Effect sizes for training with video games on cognitive skills in general ranged from 0.06 to 3.43: from 0.141 to 3.43 for processing and RTs, 0.06 to 1.82 for memory, 0.54 to 1.91 for task switching/multitasking, and 0.3 to 3.2 for mental spatial rotation; regarding video games for the training of emotional skills, effect sizes ranged from 0.201 to 3.01.

Conclusion: Overall, findings give evidences of benefits of video games training on cognitive and emotional skills in relation to the healthy adult population, especially on young adults. Efficacy has been demonstrated not only for non-commercial video games or commercial brain-training programs, but for commercial video games as well.

Introduction

Over the last 40 years, video games have increasingly had a transformational impact on how people play and enjoy themselves, as well as on many more aspects of their lives ( Yeh et al., 2001 ; Zyda, 2005 ; Boyle et al., 2012 ). Contrary to popular belief, which sees male children or teenagers as main targets of the gaming industry, the average player is instead 30 years old, and the entire gaming population is roughly equally divided into male and female players, therefore representing a daily activity for a consistent percentage of the adult population ( Entertainment Software Assotiation, 2015 ). Thanks to the wide availability on the market, the affordable cost and the massive popularity, video games already represent crucial tools as a source of entertainment, and are soon expected to become critical also in another fields, including the mental health panorama ( Granic et al., 2014 ; Jones et al., 2014 ).

While much of the early research on computer games focused on the negative impacts of playing digital games, particularly on the impact of playing violent entertainment games on aggression (e.g., Ferguson, 2007 ), and addiction (e.g., Gentile, 2009 ), gradually, scientific studies have also recognized the potential positive impact of video games on people's health (e.g., Anderson et al., 2010 ; Jones et al., 2014 ).

In recent decades, the field of computer gaming has increasingly developed toward serious purposes, and both commercial and non-commercial video games (i.e., developed ad hoc by researchers for the training of specific individuals' skills) have been tested by several studies. As early as in 1987, it was for the first time observed that famous commercial video games (i.e., Donkey Kong e Pac-Man ) can have a positive effect on cognitive skills, improving the RTs of older adults ( Clark et al., 1987 ). A few years later, in 1989, Space Fortress , the first non-commercial computer game designed by cognitive psychologists as a training and research tool ( Donchin, 1989 ) was considered so successful that it was added to the training program of the Israeli Air Force. From that moment on, numerous video games have been developed with the specific purpose of changing patterns of behavior, and are often defined in literature as “serious games” ( Zyda, 2005 ) as they use gaming features as the primary medium for serious purposes ( Fleming et al., 2016 ).

Since these pioneering studies, numerous researches have investigated the potentiality of various video games, both commercial and non-commercial, mainly in relation with cognitive skills of seniors. For instance, it has been observed that the use of complex strategy video games can enhance cognitive flexibility, particularly in older adults ( Stern et al., 2011 ). Furthermore, playing a commercial computer cognitive training program results in significant improvement in visuospatial working memory, visuospatial learning, and focused attention in healthy older adults ( Peretz et al., 2011 ).

Besides being useful tools for the training of cognitive processes, various studies have demonstrated that video games offer a variety of positive emotion-triggering situations (e.g., Ryan et al., 2006 ; Russoniello et al., 2009 ; McGonigal, 2011 ), that may be of benefit during training of emotional skills, including self-regulation habits ( Gabbiadini and Greitemeyer, 2017 ). For instance, puzzle video games such as Tetris , characterized by low cognitive loads and generally short time demands, are capable of positive effects on the players' mood, generating positive emotions and relaxation ( Russoniello et al., 2009 ). Furthermore, by continuously providing new challenges, either it is switching from one level to another (e.g., Portal 2 ) or between different avatars (e.g., World of Warcraft ), video games demand players to “unlearn” their previous strategies and flexibly adapt to new systems without experiencing frustration and anxiety ( Granic et al., 2014 ).

Although several excellent reviews and meta-analyses have investigated the effect of video games training as tools for enhancing individuals well-being, in particular regarding cognitive and emotive enhancement (e.g., Boyle et al., 2016 ; Lumsden et al., 2016 ), most of them specifically focused on the effects of digital games on brain plasticity or cognitive decline in children and seniors (e.g., Lu et al., 2012 ; Lampit et al., 2014 ). Consonant findings regarding the positive relationship between video game training and benefits on various cognitive skills have been demonstrated by both behavioral studies (e.g., Baniqued et al., 2014 ) and meta-analytic studies ( Toril et al., 2014 ) regarding both the aforementioned populations. On the contrary, only one meta-analysis focused on the adult population and it is restricted to examining the effects of training with a particular genre of games (action video games) on cognitive skills on healthy adults ( Wang et al., 2016 ).

Despite this scarcity of focus on the adult population, the latter represents an extremely interesting and unique group, with very peculiar characteristics from a neurological and psychological point of view if compared to children and elders. As stated by Finch, the adult age, including both young adults (18–35 years old) and middle age adults (35–55 years old), plays an important role in the life-span development, and therefore very well deserves to be studied thoroughly ( Finch, 2009 ). On the one hand, the effects of the so-called inverted U curve of neuroplasticity and cognitive performance starts to be evident during the adult age, especially the middle-age ( Cao et al., 2014 ; Zhao et al., 2015 ). On the other, it is well known that the level of psychological stress perceived by adults is rather high, and it can result in important mental and health disorders ( Kudielkaa et al., 2004 ).

Moreover, as the literature states, baseline individual differences regarding age can determine variations in training effectiveness ( Jaeggi et al., 2011 ; Valkanova et al., 2014 ), and if it is safe to say that video games can have beneficial effects when included in a training (e.g., Baniqued et al., 2014 ; Toril et al., 2014 ), such effects might indeed vary based on age-specific aspects which therefore cannot be overlooked ( Wang, 2017 ).

Consequently, in the current review, we will describe experimental studies that have been conducted between 2012 and 2017, with the aim to identify research evidences about the impact on cognitive and emotional skills of video games training in the adult population. Specifically, a multi-component analysis of variables related to the study, video games, and outcomes of training was made on the basis on important previous works ( Connolly et al., 2012 ; Kueider et al., 2012 ; Boyle et al., 2016 ), which provide a useful framework for organizing the research along key variables.

We followed the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) guidelines ( Moher et al., 2009 ).

Search Strategy

With the objective of providing an overview of the experimental studies that have been conducted to test the benefits of different categories of video games used as training tools of cognitive or emotional domains for the adult population, a computer-based search for relevant publications was performed in several databases. Databases used in the search were PsycINFO, Web of Science (Web of Knowledge), PubMed, and Scopus. The search string was: [(“Video Games” OR “Computer Games” OR “Interactive Gaming”)] AND [(“Cognition”) OR (“Cognitive”) OR (“Emotion”) OR (“Emotion Regulation”)] AND [”Training"].

Selection of Articles for Inclusion in the Review

To avoid the risk of bias, PRISMA recommendations for systematic literature analysis have been strictly followed ( Moher et al., 2009 ). Two authors (Federica Pallavicini, Ambra Ferrari) independently selected paper abstracts and titles, analyzed the full papers that met the inclusion criteria, and resolved any disagreements through consensus. Selected papers have to: (a) include empirical evidences on the impact and outcomes of video game based training; (b) have been published during the last 5 years (namely from January 2012 to August 2017), in analogy with several other relevant previous works (i.e., Connolly et al., 2012 ; Boyle et al., 2016 ); (c) include participants within an age range of 18–59 years old; (d) only include samples of healthy participants, i.e., not suffering from any neurological disorder (e.g., traumatic brain injury), or psychiatric disorders according to DSM-5 Axis I ( American Psychiatric Association, 2013 ); (e) be published on peer-reviewed journals.

Coding of Selected Studies, Video Games, and Training Outcomes

The papers selected on the basis of the inclusion criteria were coded from the data extraction pro-forma that was developed by Connolly ( Connolly et al., 2012 ), and subsequently modified by Boyle et al. (2016) , adapting it to the specificity of this review and its area of interest. In particular, in this systematic review papers were coded with respect to:

• Video Game Variables: The game category ( whether the game was commercial or non-commercial); the game genre (action games; driving-racing games; puzzle games; strategy games; simulation games; exergames; horror games; commercial brain training programs; arcade games; adventure games); the platform for the game (console, PC/laptop, or mobile gaming). First of all, the category of the game has been included to explore the effectiveness of several commercial titles, used “as-is” (without modifications), which in previous studies resulted to be effective for the cognitive training (e.g., Green and Bavelier, 2006 ; Dye et al., 2009 ). Furthermore, the categorization was included in order to analyze the efficacy of ad hoc developed games, about which an ongoing debate about their effectiveness still persists (e.g., Owen et al., 2010 ). Secondly, the classification of video game genres was considered because of the fact that, under many points of view, not all video games are equal and their effects strongly depend on specific characteristics of the game itself ( Achtman et al., 2008 ; van Muijden et al., 2012 ). In addition, it has been reported that combinations between the neurological stage of the participants and the precise features of each video game produce unique results in a matter of benefits on mental skills ( Ball et al., 2002 ; van Muijden et al., 2012 ). There is no standard accepted taxonomy of genre, although one of the most adopted is the Herz's system ( Herz, 1997 ), while others studies seem to simply divide action games from any other kind, often defined as casual games as a whole (e.g., Baniqued et al., 2013 , 2014 ). Here, we propose the above categorization, which resembles the present commercial classification as much as possible, defining ten different genres of commercial video games. Thirdly, new technologies such as mobile devices and online games have recently expanded the ways in which games have traditionally been played, their medium of delivery and the different platforms available. Platforms of delivery represent important information about video game training, primarily because they are the way in which the training itself can be accessed ( Aker et al., 2016 ).

• Variables Related to the Study: The sample included in the study (sample size, mean age, or age range); the research design used (categorized as a Randomized Controlled Trial or Quasi Experimental); the measures used for the assessment of outcomes (self-report questionnaires, cognitive tests, fMRI, physiological data, etc.); the duration of training (duration, intensity, and the total amount of sessions); the effects size of each training outcome , reporting partial-eta squared (η 2 ), with values closer to 1.0 indicating a stronger effect size, and Cohen's d; the calculation of range and mean value of effect sizes for each training outcome has been expressed as Cohen's d , applying the conversion formula when reported by the study in terms of partial-eta squared (η 2 ) ( Cohen, 1998 ); where not reported in the study, standardized Cohen's d effect sizes were derived following a computation formula: the one described in Dunlap et al. (1996) in order to calculate d from dependent t -tests; the computation formula by Thalheimer and Cook (2002) for ANOVAs with two distinct groups ( df = 1); the calculation formula by Rosenthal and DiMatteo (2001) from χ 2 (with one degree of freedom); otherwise, in cases where effect sizes could not be calculated because not reported in the study or because the necessary data to derive them through formulas were not present, p -value was reported instead ( e.g., Oei and Patterson, 2013 ; Wang et al., 2014 ; Chandra et al., 2016 ). The sample, study design, and measures of training outcomes have been included as relevant variables in analogy to what has been done in previous reviews ( Boyle et al., 2012 ; Connolly et al., 2012 ), to facilitate the access to easily classified and comparable studies among the literature. An indication of mean age or age range has been provided in order to identify studies conducted on young vs. middle-aged adults. Training-related factors have also been considered, including the duration, intensity, and total amount of training sessions, as well as the effect sizes of the training outcomes, since they represent useful information about the characteristics and feasibility of the training itself ( Hempel et al., 2004 ).

• Video Game-Based Training Outcome Variables: The selected papers have been divided into two macro-categories : cognition and emotion. Regarding cognition, authors identified five domain-specific subcategories , following the classification proposed by Kueider et al. (2012) , partially adapted to the specificity of the results that emerged from the review, specifically: (1) multiple domain , namely trainings focused on more than one cognitive skill, such as trainings including reasoning, episodic memory, and perceptual speed as target skills at the same time; (2) processing speed and reaction times (RTs), i.e., respectively, the ability to quickly process information ( Shanahan et al., 2006 ), and the amount of time needed to process and respond to a stimulus and is critical for handling information ( Garrett, 2009 ) ; (3) memory , defined as the ability to retain, store, and recall information ( Baddeley and Hitch, 1974 ), including many different types of memory, such as episodic, short-term, visual and spatial working memory; (4) task-switching/multitasking , defined as a whole as attributes of control processes while switching from one task to another ( Dove et al., 2000 ); (5) mental spatial rotation , that is the ability to mentally rotate an object ( Shepard and Metzler, 1971 ). Such categorization has been chosen among many others proposed by literature (e.g., Sala and Gobet, 2016 ; Stanmore et al., 2017 ; Bediou et al., 2018 ), because of its particular adaptability to the search results at hand, and because of its effectiveness in defining precise sub-categories of cognitive skills.

Papers Identified by Search Terms

A large number of papers (1,423) published in the time period between January 2012 and August 2017 was identified. As discussed in section Papers Selected Using our Inclusion Criteria, this set of papers was further screened, obtaining a set of 35 relevant papers (see Figure 1 ).

Figure 1 . The flow chart of the systematic review.

Papers Selected Using Our Inclusion Criteria

Applying the four inclusion criteria to these papers, 35 papers were identified (see Table 1 ). The largest number of papers was found in Scopus, followed by PsycINFO, Pubmed, and Web of Science (Web of Knowledge).

Table 1 . Information about the video games variables of the selected studies.

Analysis of Game Variables

Video games category.

Considering the entirety of the studies, 42 commercial video games and 7 non-commercial video games have been tested as training tools for cognitive or emotional skills. As for video games used for cognitive enhancement specifically, a total of 38 commercial video games and 6 non-commercial video games have been adopted; concerning emotional enhancement, instead, 4 commercial games and 1 non-commercial game have been used as training tools in the studies included in this review.

Video Games Genres

Among the studies included in this systematic review, the genre of commercial games was very varied, with action games (15) being the most used, followed by puzzle games (8), brain training games (5), exergames, and driving-racing games (3 for each category), simulation, driving racing games and exergames (3 games each), adventure games (2 games for each genre), and, finally, strategy games, arcade games, and horror games (1 game for each genre). Regarding training of cognitive skills specifically, among commercial games, the genre was very varied, with action games (14) and puzzle games (7) being the most used, followed by brain training games (5), simulation and driving-racing games (3 games), exergames and adventure games (2 games each), and, finally, strategy games and arcade games (1 game for each genre). As for emotional training, only 1 study adopted a non-commercial video games, while a variety of commercial video games were used (1 horror game, 1 action game, 1 puzzle game, and 1 exergame).

Platform/Delivery

Considering the retrieved studies, games delivered via PC or laptop were the most popular in all categories (20 studies), followed by mobile (8 studies) and console (7 studies). Regarding cognitive training, 18 video games delivered via PC were used, 6 via console, 6 via mobile. As for emotional training, 2 video games were delivered via PC, 2 via console, and 1 via mobile.

Analysis of Variables Related to the Study

The mean number of participants included in the emerged studies was 54.4 (cognition: M = 56.1; emotion: M = 42.8), ranging between 5 ( Chandra et al., 2016 ) and 209 ( Baniqued et al., 2013 ). The samples' mean age, instead, was 24.2 (cognition: M = 23.8; emotion: M = 27.7).

Study Design

In general, 28 studies included in the review have use a randomized control trial (RCT), while 7 studies have used a quasi-experimental design. The RCT was the design of choice of 24 studies related to cognitive training (e.g., Hutchinson et al., 2016 ; Looi et al., 2016 ). A quasi-experimental design was instead adopted in six studies directed at the evaluation of cognitive trainings based on video games ( Mathewson et al., 2012 ; Montani et al., 2014 ). As for emotional training, four studies followed a RCT design (e.g., Bouchard et al., 2012 ), while 1 a quasi-experimental design ( Naugle et al., 2014 ).

Duration of the Training

The length of the trainings proposed by studies included in this systematic review resulted to be rather heterogeneous, both in the number of sessions and in the number of weeks. In particular, the mean number of sessions was 10.1, ranging from 1 to 60 sessions, while the mean number of hours played was 13.5, ranging between 10 min and 50 h. As for cognitive training, a minimum of one session (e.g., Colzato et al., 2013 ; Cherney et al., 2014 ), and a maximum of 60 sessions ( Kühn et al., 2014 ). The number of hours spent playing the different video games differed from study to study as well: from several minutes ( Stroud and Whitbourne, 2015 ) to up to 50 h ( Green et al., 2012 ; Chandra et al., 2016 ). As for emotional training, the minimum number of sessions was 1 as well, while the maximum was 10 ( Bailey and West, 2013 ); the minimum time spent playing was of 25 min ( Dennis and O'Toole, 2014 ; Dennis-Tiwary et al., 2016 ), and the maximum was 10 h ( Bailey and West, 2013 ).

Measures Used for the Assessment of Outcomes

The measures of the training outcome adopted in the studies included in this systematic review predictably have largely been constituted by cognitive tests, for a total of 33 studies, 30 related to cognitive training (e.g., Baniqued et al., 2014 ), and 3 to emotional training (e.g., Bailey and West, 2013 ). Nonetheless, numerous studies (19) have included self-administered psychological questionnaires: 14 aimed at cognitive training (e.g., Chandra et al., 2016 ), and 5 to emotional training (e.g., Dennis and O'Toole, 2014 ), while physiological measures were used in a total of 2 studies, both emotional trainings (e.g., Bouchard et al., 2012 ). fMRI-based assessments were instead used to measure the outcomes of cognitive trainings in two studies (e.g., Nikolaidis et al., 2014 ) and EEG assessments were used in a total of three studies (1) related to cognitive training (i.e., Mathewson et al., 2012 ), and (2) to emotional training (e.g., Bailey and West, 2013 ).

Analysis of Video Game Training Outcomes

Thirty studies used cognitive domain-specific training programs including memory, task-switching/multitasking and mental spatial rotation. Across all cognitive trainings, the effect sizes' (Cohen's d) range was 0.141–3.43 for processing and RTs ( M = 1.18), 0.06–1.82 for memory ( M = 0.667), 0.54–1.91 for task-switching/multitasking ( M = 1.11), and 0.3–3.2 for mental spatial rotation ( M = 1.5).

• Multiple domains (13 studies): Because of the wide literature consensus about the little to non-transferability of cognitive training effects to untrained skills ( Rebok et al., 2007 ), a rather high number of retrieved studies aimed at the enhancement of multiple cognitive domains with a single training, with the objective of deepening our knowledge about generalizability across domains. Training with action video games has been reported to enhance processing speed and RTs ( Oei and Patterson, 2013 , 2015 ; Schubert et al., 2015 ; Chandra et al., 2016 ), but no effect on spatial ( Oei and Patterson, 2015 ) nor visual ( Schubert et al., 2015 ; Chandra et al., 2016 ) working memory has been reported. Concerning other categories of commercial video games, training with puzzle games was shown to improve task switching skills and inhibitory control, but not visual and spatial working memory, episodic memory or perceptual speed ( Baniqued et al., 2014 ). Spatial working memory, as well as RTs, improved after training with a simulation game ( Rolle et al., 2017 ). Better RTs have also been reported after training with FPS games (i.e., first person shooter games, in which the player shoots at targets while witnessing the scene as through the eyes of the character they are controlling), which also seemed to have positive effects on processing speed, but not on mental spatial rotation skills ( Choi and Lane, 2013 ). Moreover, it was reported that video game training with an adventure game can augment gray matter in brain areas crucial for spatial navigation and visual working memory, along with evidence for behavioral changes of navigation strategy ( Kühn et al., 2014 ). As far as brain training games are concerned, studies confirmed that this genre of video games can improve task-switching, short-term memory, RTs and processing speed more heavily compared to a puzzle game ( Nouchi et al., 2013 ). Nonetheless, two different studies did not highlight any advantage of puzzle games over other video game genres in enhancing cognitive skills such as mental spatial rotation ( Shute et al., 2015 ), nor for cognitive performance on other domains (e.g., task-switching, visual, and spatial working memory) ( Kable et al., 2017 ). Lastly, a non-commercial game, Space Fortress , was proven to be effective as a training for visual working memory ( Lee et al., 2012 ), and alpha and delta EEG oscillations during game play of this particular video game were shown to predict learning and improvements in such cognitive skill, while no similar effects were found on task-switching/multitasking skills ( Mathewson et al., 2012 ).

• Processing speed and reaction times (8 studies): Studies reported that action games ( Green et al., 2012 ; Wang et al., 2014 ), FPS games ( Colzato et al., 2013 ; Hutchinson et al., 2016 ), adventure ( Li et al., 2016 ), and puzzle games ( Stroud and Whitbourne, 2015 ) can be considered effective training tools for processing speed and RTs. Moreover, in a study comparing the effectiveness of various genres of commercial video games, action and driving-racing games were proven to decrease RTs and processing speed more effectively than a puzzle game ( Wu and Spence, 2013 ). Only one study did not report any benefit of commercial video games over these particular skills ( van Ravenzwaaij et al., 2014 ).

• Memory (4 studies): Effective trainings of visual working memory have been carried out with an action game ( Blacker et al., 2014 ) as well as with an adventure game ( Clemenson and Stark, 2015 ). Concerning non-commercial video games, a mathematics video game training was shown to be effective on short-term and visual working memory ( Looi et al., 2016 ). Furthermore, individual differences in the post-minus-pre changes in activation of regions implicated in visual working memory during gameplay of an ad hoc developed game ( Space Fortress ) have been reported to predict performance changes in an untrained working memory task ( Nikolaidis et al., 2014 ).

• Task-switching/multitasking (3 studies): The cost of dual tasking, as well as the cost of task switching, decreased after training with a custom-made video game ( Montani et al., 2014 ). Moreover, a training based on an ad hoc developed game lead to significantly better performance on cognitive shifting tests after playing for 2 h over four sessions (i.e., reaching a high level in the game) ( Parong et al., 2017 ). The same results, in fact, were not obtained if participants were asked to play for only 1 h over two sessions ( Parong et al., 2017 ). Furthermore, playing commercial puzzle games improved task-switching ability ( Oei and Patterson, 2014 ).

• Mental spatial rotation (2 studies): Enhancement of mental spatial rotation abilities was reported after training with commercial exergames and driving-racing games, with a greater advance for women ( Cherney et al., 2014 ). In contrast, no improvement was observed after training with other commercial games (one exergame and several action games), probably because of the limited number of participants ( Dominiak and Wiemeyer, 2016 ).

Five studies tested video games as tools for training emotional skills (Table 2 ). Across all these training programs, the effect sizes' range (Cohen's d ) was 0.201–3.01 ( M = 0.897). First of all, playing a commercial action game resulted in brain changes related to the emotion processing of facial expressions, with a reduction in the allocation of attention to happy faces, suggesting that caution should be exercised when using action video games to modify visual processing ( Bailey and West, 2013 ). Moreover, playing exergames at a self-selected intensity has been reported to positively influence emotional responses (enjoyment, changes in positive and negative affects) ( Naugle et al., 2014 ). Interestingly, commercial video games have also been tested as a tool to provide interactive Stress Management Training (SMT) programs, mainly used for decreasing levels of perceived stress and negative effects. In particular, training with a commercial horror video game combined with arousal reduction strategies (e.g., exposure to stressful scenarios, traditional biofeedback techniques) has shown efficacy in increasing resilience to stress in soldiers, as observed through analyses of salivary cortisol level conducted along the training ( Bouchard et al., 2012 ). Regarding non-commercial video games, training with an ad hoc non-commercial video game has been shown to help trait-anxious adult people handle emotional and physiological responses to stressors ( Dennis and O'Toole, 2014 ), as well as improve behavioral performance in an anxiety-related stress task among female participants ( Dennis-Tiwary et al., 2016 ).

Table 2 . Information about the selected studies on video games for emotional training.

In the present systematic review, we examine experimental studies that have been conducted with the aim to identify research evidences about the impact on cognitive and emotional skills of video games training in the healthy adult population. The large number of papers (1,423) identified using our search terms confirmed that there has been a surge of interest in the use of games for the aforementioned specific population, following the tendency already registered about elders (e.g., Lampit et al., 2014 ), and young people (e.g., Gomes et al., 2015 ). After the application of the inclusion criteria, 35 papers were finally included and described on the basis of important previous works, which provide a useful framework for organizing the research along key variables ( Connolly et al., 2012 ; Kueider et al., 2012 ; Boyle et al., 2016 ).

With respect to video game variables , starting from the games' category , efficacy was demonstrated not only for non-commercial video games or commercial brain-training programs, but for commercial off-the-shelf video games as well. Interesting cases regard Tetris, which resulted to be more effective than a commercial brain training program (i.e., Brain Age ) in improving cognitive skills such as short-term memory and processing speed ( Nouchi et al., 2013 ), and Portal 2 , that has proven to be effective in improving skills such as problem solving even more effectively than a brain training program specifically developed for this purpose (i.e., Lumosity) ( Shute et al., 2015 ). The fact that not only ad hoc non-commercial games, but also commercial video games can be useful for training cognitive and emotional capacities, if confirmed, appears to be very interesting, as it opens the possibility to use commercial titles for the training of cognitive and emotional abilities in the adult population. This could mean increasing adherence to training, keeping the trainee engaged with an effective feedback system ( Cowley et al., 2008 ), and enhancing the accessibility of training programs in terms of costs and ease of access to treatment, since it would be sufficient to simply have a console or another gaming device.

As for the distribution of game genre , considering only commercial games, in the emotional training sector no genre prevalence is recorded, while in cognitive training action games are the most commonly used, followed by puzzle games, and by brain training games. Such result should not be considered surprising, as previous literature indicates action games as the class of video games which has been scientifically assessed for the longest time (e.g., Adachi and Willoughby, 2011 ), similarly to puzzle games (e.g., Carvalho et al., 2012 ), and brain training games (e.g., Owen et al., 2010 ).

Results showed that the delivery platform of choice for more than half of the included studies was the PC, distantly followed by games delivered via consoles or via mobile. This distribution is valid for both commercial and non-commercial games, which seems to be a rather interesting fact and various reasons behind this consistency of distribution can be hypothesized. Future studies should better investigate especially mobile training, which, because of its potential ubiquity, its low costs, and its potentially real-time use, could offer unique advantages over traditional tools such as PCs.

Regarding the variables related to the studies , namely the sample characteristics , the results of this systematic review showed that the majority of studies have been conducted on young adults (18–35 years) rather than middle-aged adults (35–55 years). A possible explanation of this tendency could be linked to the fact that many studies have enlisted college students as participants, for a matter of simplicity of recruitment. However, it is important to note that the differentiation between young and middle-aged adults can be particularly relevant. As it is reported by scientific literature, in fact, the effects of the so-called inverted U curve of neuroplasticity and cognitive performance and of the perceived stress starts to be evident during the middle-age ( Cao et al., 2014 ; Zhao et al., 2015 ). Moreover, strong differences in terms of knowledge and use of video games characterize these two age ranges. For these reasons, future studies should better investigate differences and analogies between young and middle-aged adults, for instance to identify in which life-span moment a game-based cognitive or emotional treatment would potentially be more effective.

Secondly, regarding the experimental design adopted in the studies, results show that in the majority of cases studies were conducted using a RCT design. This seems to be linked to the need for evidences of well-controlled studies, differently from previous studies in which less strong methods (e.g., survey, correlational design) were used. It will be important for future studies to continue using this type of experimental design, which is considered as the most reliable empirical design in order to prove a treatment's effectiveness, minimizing the impact of confounding variables ( Levin, 2007 ).

The measures of outcome of the training adopted in the studies included in this systematic review predictably have largely been constituted by cognitive tests (e.g., Blacker et al., 2014 ). Nonetheless, numerous studies have included self-administered psychological questionnaires (e.g., Nouchi et al., 2013 ), physiological measures (e.g., Naugle et al., 2014 ), EEG-based assessment measures (e.g., Dennis-Tiwary et al., 2016 ), and fMRI-based assessments measures (e.g., Kable et al., 2017 ), which seem to be more reliable in assessing change over time, therefore an openness to such ways of assessment is desirable in a perspective of empirical evidence.

The length of the training programs proposed by studies included in this systematic review resulted to be rather heterogeneous, both in the number of sessions and in the number of weeks: from a minimum of one session (e.g., Colzato et al., 2013 ; Cherney et al., 2014 ) to a maximum of 60 sessions ( Kühn et al., 2014 ), and with gameplay time ranging from 10 min to 50 h ( Green et al., 2012 ; Chandra et al., 2016 ). Since the duration and intensity of training has been reported to be a relevant variable, as it has a rather important impact on the accessibility and feasibility of the training itself ( Hempel et al., 2004 ), future studies should address in detail such aspects of the training, for instance comparing the effectiveness of shorter trainings to longer ones in order to identify the minimum number of sessions to obtain an effective program.

Finally, regarding the training outcome , based on this review, video games appear to hold promise for improving both cognitive and emotional skills in the healthy adult population. Empirical evidences were identified for all the training outcomes (i.e., cognition: multiple domain, processing speed and RTs, memory, task-switching/multitasking, mental spatial rotation; emotion).

Effect sizes (Cohen's d ) for cognitive training, in general, ranged from 0.06 to 3.43: in particular from 0.141 to 3.43 for processing and RTs, 0.06 to 1.82 for memory, 0.54 to 1.91 for task-switching/multitasking, and 0.3 to 3.2 for mental spatial rotation (Table S1 ). Effect sizes reported in this systematic review are comparable to those reported for video game interventions aimed at enhancing cognitive skills of senior populations ( Kueider et al., 2012 ; Lampit et al., 2014 ). For instance, a systematic review of a computerized cognitive training with older adults reported a range standardized pre-post training gain from 0.09 to 1.70 after the video game intervention, which appears to be similar to the values emerged from the traditional (0.06–6.32) or computerized (0.19–7.14) trainings ( Kueider et al., 2012 ).

Based on the studies reviewed, the largest impact of video game trainings for cognitive skills was found on processing speed and RTs, as these cognitive domains presented the larger effect sizes. In particular, it has been observed that training with action games ( Green et al., 2012 ; Wang et al., 2014 ), FPS games ( Colzato et al., 2013 ; Hutchinson et al., 2016 ), adventure ( Li et al., 2016 ), and puzzle games ( Stroud and Whitbourne, 2015 ) can enhance these skills in healthy adults. In only one case no benefits have been reported over these particular skills after training with commercial video games ( van Ravenzwaaij et al., 2014 ). The possibility to train processing speed and RTs with video games, especially with action video games, represents one of the largest interests of video game and cognitive training literature in spite of mixed results about its effectiveness (e.g., Dye et al., 2009 ; Wang et al., 2016 ), therefore further investigation is surely needed. For instance, action video game novices assigned to action video game training show faster visual information processing according to one study ( Castel et al., 2005 ), while no improvement has been reported for seniors involved in a brief training ( Seçer and Satyen, 2014 ).

Results were generally positive across studies on training of memory as well. In particular, improvements in visual and spatial working memory have been observed after training with an action game (e.g., Blacker et al., 2014 ), an adventure game ( Clemenson and Stark, 2015 ), and a non-commercial game ( Looi et al., 2016 ). Concerning other forms of memory, a positive effect of an adventure game-based training on mnemonic discrimination was reported in one study ( Clemenson and Stark, 2015 ), while improvements in short term memory skills have been noticed after a brain training program ( Nouchi et al., 2013 ). On the contrary, no positive effects on episodic memory nor on visual and spatial working memory have been reported after training with puzzle games ( Baniqued et al., 2014 ). What emerged from the studies included in this review appears to be in line with previous evidences concerning the possibility to effectively use video games to enhance the memory skills of young and older populations, in particular regarding visual and spatial working memory (e.g., Wilms et al., 2013 ; Toril et al., 2014 ). It is nonetheless important to highlight the fact that, in this systematic review and in previous literature, the efficacy (or the ineffectiveness) of each training seems to differ on the basis of the specific game genre, as well as of the sample characteristics (e.g., Baniqued et al., 2013 ; Oei and Patterson, 2015 ; Chandra et al., 2016 ). Future studies are therefore necessary in order to better investigate the role of video games in such sense.

Regarding mental spatial rotation, even though the effect sizes are averagely high, only two studies have been included in this review, therefore results should be considered in the context of such numerical limitation. From what emerged from this systematic review, an enhancement of mental spatial rotation abilities was reported after training with commercial exergames and driving-racing games, with a greater advance for women ( Cherney et al., 2014 ), while no improvement was observed after training with other commercial games (one exergame and several action games) ( Dominiak and Wiemeyer, 2016 ). Since early findings in this research field have reported evidences supporting an enhanced performance in spatial relations after video game training in elders (e.g., Maillot et al., 2012 ) and children ( Subrahmanyam and Greenfield, 1994 ), future studies should deeply verify the possible usefulness of video games as training of such cognitive skill in adults specifically.

As for task-switching/multitasking, in spite of high effect sizes suggesting the effectiveness of video game trainings in such sense, it is once again important to underline the limited number of considered studies (three). According to the included studies, the cost of dual tasking and the cost of task-switching decreased after training with a commercial puzzle game ( Oei and Patterson, 2014 ), as well as with a custom-made video game ( Montani et al., 2014 ; Parong et al., 2017 ). The use of video games for such purpose, because of their own nature of requiring complex planning and strategizing, appears to be rather significant, as it could potentially allow training or rehabilitation of these cognitive skills (e.g., Boot et al., 2008 ). Literature, nonetheless, still presents mixed results, not always positive (e.g., Green et al., 2012 ), and for this reason future studies providing an in-depth analysis are still necessary.

Finally, regarding video games for the training of emotional skills, effect sizes ranged from 0.201 to 3.01. Despite the generally high values, it is currently impossible to compare them with results emerged from other systematic reviews or meta-analyses concerning the same topic, as the few works around the subject do not provide any information about effect sizes (e.g., Villani et al., 2018 ). The studies included in this review provide evidences suggesting that non-commercial video games ( Dennis and O'Toole, 2014 ; Dennis-Tiwary et al., 2016 ) and commercial video games (exergames and horror games) can be effective in inducing positive emotions and in reducing individual levels of stress in healthy adults ( Bouchard et al., 2012 ; Naugle et al., 2014 ). From this review, it appears that the number of studies conducted about this kind of training is smaller than the amount of studies related to cognitive training. This fact is rather curious, because the video games' intrinsic characteristics of being motivating, engaging, and easily accessible ( Granic et al., 2014 ), make computer games potentially useful tools in order to better the individuals' emotion regulation. Future studies will be fundamental in order to explore the potentiality of video games as emotional training tools, and to identify the most effective game genres for this purpose, examining potentially interesting genres that have not been investigated yet (e.g., affective gaming, virtual reality-based gaming).

Limitations

As with all literature reviews, the current review does not claim to be comprehensive, but summarizes the current research on video games for the cognitive and the emotional training in the adult population based on specific key words used in the search string, the database included and the time period of the review. Moreover, in this review we based our choice of categories on a specific model ( Connolly et al., 2012 ; Kueider et al., 2012 ; Boyle et al., 2016 ), however the level of specificity and distinctiveness of different categories is an ongoing discussion in the scientific world, both in relation with the outcomes of cognitive and emotive trainings, and with analyzing video games. Finally, the follow-up effect of video games training was not specifically addressed in this review, since a very limited number of studies provided follow-up tests.

Future Directions

The present systematic review provides several directions for future studies in this research field. First of all, further studies are needed to better examine the video games effects on cognitive and emotional skills, especially in middle age adults, population which has been investigated in a limited number of studies. Secondly, one of the biggest unresolved issues appears to be the generalizability of improvements: up to now, only short-term effects and specific improvements have been recorded in most studies (e.g., Hardy et al., 2015 ; Tárrega et al., 2015 ). In addition, video game characteristics (e.g., genre, platform) in relation with trained skills should be further investigated in the future, in order to create specific and effective training programs.

To summarize, the present systematic review gives evidences of benefits of video game trainings on cognitive and emotional skills in relation to the healthy adult population, especially on young adults. Efficacy has been demonstrated not only for non-commercial video games or commercial brain-training programs, but for commercial video games as well. As for the distribution of game genre, action games are the most commonly used, followed by puzzle games. Finally, in this review, empirical evidences were identified for all the training outcomes, showing the potential effectiveness of video games for the training of both cognitive (i.e., multiple domain, processing speed and RTs, memory, task-switching/multitasking, mental spatial rotation), and emotional skills.

Author Contributions

FP, AF, and FM conceived the idea of this systematic review. FP and AF examined and write the description of the studies included. FM supervised the scientific asset. FP and AF write the first draft of the paper. All the authors read and approve the final version of 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.

Supplementary Material

The Supplementary Material for this article can be found online at: https://www.frontiersin.org/articles/10.3389/fpsyg.2018.02127/full#supplementary-material

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Keywords: video games, computer games, cognitive training, emotional training, well-being

Citation: Pallavicini F, Ferrari A and Mantovani F (2018) Video Games for Well-Being: A Systematic Review on the Application of Computer Games for Cognitive and Emotional Training in the Adult Population. Front. Psychol. 9:2127. doi: 10.3389/fpsyg.2018.02127

Received: 13 June 2018; Accepted: 15 October 2018; Published: 07 November 2018.

Reviewed by:

Copyright © 2018 Pallavicini, Ferrari and Mantovani. 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: Federica Pallavicini, [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.

January 1, 2013

12 min read

How Video Games Change the Brain

Playing violent video games can sharpen our focus, reasoning and decision-making skills. But do we really need the weapons?

By Lydia Denworth

I am in an overgrown lot leaning against an eight-foot-tall shipping container. I look both ways, weighing my options. A man with an assault rifle is looking for me, just as I am looking for him. Hoping for a better vantage point, I run toward the abandoned car to my right. A metallic bang rings out as my opponent's shot hits the wall I have just left. I dodge around the next container, then circle behind it. Raising my M16, I peer through the scope as I run. There he is! I hit the track pad of my laptop hard and fast, but my aim is wobbly. I miss. He spins, fires, and I'm dead.

So ended my introduction to first-person-shooter video games. Clearly, I was not very good. With practice, I would probably get better. What is less obvious is that a decade of research has shown that if I spent a few more hours playing Call of Duty, I could improve more than my aim and the life expectancy of my avatar. Aspects of my vision, attention, spatial reasoning and decision making would all change for the better.

These striking findings have contributed to a shift in the national conversation about video games. Not long ago a few lone voices contested the conventional wisdom that they were at best frivolous and at worst a dangerous waste of time and brainpower. Yet more than 90 percent of children play them, and adults do, too. In fact, the average gamer's age is 33 years. Along with continuing popularity has come a surge in acknowledging the positive side of gaming. Game designer Jane McGonigal's best-selling 2011 book Reality Is Broken even argued that games can change the world. In a 2011 speech to students, President Barack Obama recognized the potential and called for investment in educational technology, though with a caveat: “I want you guys to be stuck on a video game that's teaching you something other than just blowing something up.”

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Teaching is the critical word. The most consequential conclusion of the research is that video games have a power few other activities can claim. With practice, a violinist can play a Mozart string concerto beautifully, but that will not make her better at much else. Gamers, though, do not just learn to be good at shooting. In neurological terms, action games seem to “retune connectivity across and within different brain areas,” according to neuroscientist Daphne Bavelier of the University of Rochester and the University of Geneva. That means that gamers “learn to learn.” The ability to apply learning to broader tasks is called transfer, and it is the holy grail of education.

So far the games shown to have the most potent neurological effects are the ones parents hate the most: violent first-person shooters. Scientists are trying to figure out how and why these games affect players so as to create products that emphasize benefits but have fewer drawbacks. “I'm really interested in how the brain learns and how we can promote brain plasticity for learning,” Bavelier says. “The issue is trying to understand how technology can be leveraged for the better.”

Bavelier stumbled on the subject of video games by accident. Until a decade ago, her laboratory focused on the effects of congenital deafness on vision. In the fall of 2000 she assigned an undergraduate, C. Shawn Green, to program his own version of a standard test of visual attention in which individuals first identify a central white square and then indicate on a touch screen the location of a shape that briefly flashes some distance away. The task, known as the “useful field of view,” measures spatial attention—that is, the ability to keep track of multiple locations and shift attention across space. You employ this skill while driving, for example, to transfer your focus from the road to a sudden movement on the right. When Green tested it on himself, he did about twice as well as the norm. He faulted his programming but brought in some friends to test it further. They scored as high as Green did.

So Bavelier took the test. She fell within the normal range, meaning she did rather poorly. “We looked at each other and said, ‘What's common between you and your friends?’ ” Bavelier remembers. The answer: they all regularly played action-packed, first-person-shooter video games.

Bavelier reassigned Green to a new study that compared various aspects of visual attention in eight action gamers and eight nongamers. In one task, subjects reported how many squares flashed on a screen at one time. The more items a person can register immediately, without counting them one by one, the greater his or her attentional capacity. Gamers averaged 4.9 items versus 3.3 for nongamers. In a test of attention to locations in space, gamers were roughly twice as accurate as nongamers at indicating where targets appeared. Gamers also significantly outperformed nongamers when they had to identify, and thus pay attention to, whether certain letters appeared in a string of letters flashed in rapid succession.

The action-game players were not more attentive from the start, the researchers determined. Instead it appears that experience with these games is what improves attention. Bavelier and Green had nine nongamers play Medal of Honor, a first-person shooter set on the battlefield, for an hour a day for 10 days while eight nongamers played Tetris. Before and after training, both groups took three tests of visual attention. Those who played Medal of Honor improved on all three tasks; those who played Tetris showed no improvements. Bavelier did not yet know what accounted for the benefits, but she guessed that the simultaneous demands of action games might be a critical ingredient. Tetris, after all, requires attending to only one falling tile at a time.

With such striking results in hand, Bavelier decided to approach action video games more methodically. First, she backtracked to examine the games' effect on vision. “We were trying to understand whether very early sensory processes, which typically are not very plastic, might be changed for the better,” she says. To study visual acuity—a person's ability to see detail—she and Green asked 10 gamers and 10 nongamers to say whether a T was right side up or upside down as other T shapes crowded in. They measured how close together the letters could be before interfering with performance. This skill—actually the ability to see detail in cluttered visual environments—is critical for reading. Gamers could tolerate more crowding and still pick out the T, suggesting their detail detection was better. In addition, nongamers who trained on an action game, this time Unreal Tournament 2004, improved on this same test of visual acuity. In other findings, Bavelier and her team demonstrated that gamers also have better contrast sensitivity, or the capacity to distinguish different degrees of gray, which is useful for driving a car in fog (and a necessary skill for radiologists).

Playing video games might even ameliorate certain visual disorders. In amblyopia, or “lazy eye,” blurred or otherwise poor vision in one eye disrupts neuronal circuits in the visual cortex during development, leaving one eye underdeveloped. In children, doctors patch the dominant eye to strengthen the weaker eye. Yet the treatment does not work in adults. In 2011 research optometrists Roger Li and Dennis Levi and their colleagues at the University of California, Berkeley, published a pilot study in which 10 adults with amblyopia played Medal of Honor for 40 hours with one eye patched. Three other patients played a nonaction video game, and seven had their eyes patched before play began. Tested before and after training, patients who played one-eyed saw their acuity improve more than 30 percent, a fivefold greater recovery than would be expected from patching in children. In addition, the adults' spatial attention skills got a 40 percent boost, and their depth perception was enhanced by 50 percent. Li and Levi are now conducting a randomized trial with another 20 patients. They expect results within two years.

Big Thinkers

If games improve eyesight and visual attention, researchers considered what other brain processes they might be able to tweak. Cognitive psychologist Ian Spence of the University of Toronto wondered why males tend to perform better than females on tasks such as field of view, which measures spatial attention, and mental rotation, which tests a higher-level capacity called spatial reasoning that enables us to visualize how objects behave in three-dimensional space. Both types of spatial skills correlate with success in science and math. Spence and his colleague Jing Feng, a psychologist, theorized that video games could partially account for the gender gap because more males play them and because Green and Bavelier's work suggested that playing these games had benefits for spatial attention.

First, they established a disparity in spatial attention along gender lines in a group of 48 university students. They then divided six male and 14 female students, none of them gamers, into matched pairs of the same sex. One member of each pair of students trained for 10 hours on Medal of Honor: Pacific Assault, and the other played Ballance, a three-dimensional puzzle game involving steering a ball through an obstacle-laden maze. After training, action-game players improved by 10 to 15 percent on both the field-of-view task and a mental rotation challenge, whereas the puzzle-game players saw no change. In both instances, the females improved the most, virtually erasing the gender disparity in field of view and significantly reducing it in mental rotation. The results indicate that the theory was right: a difference in gaming experience between males and females could account for some of the gender inequality in spatial skills. Also, notably, playing these games can sharpen both types of spatial acuity and therefore, perhaps, even scientific aptitude.

Indeed, in a study published last year cognitive psychologist Christopher A. Sanchez, now at Oregon State University, connected game-induced improvements in spatial reasoning with the ability to learn certain types of scientific material. Participants played just 25 minutes of either Halo, an interstellar first-person shooter, or Word Whomp, a timed spelling game. Next, they read a brief nonscientific text as a diversionary task followed by an explanation of plate tectonics. Finally, they wrote an essay on the causes of the eruption of Mount St. Helens. Those who played Halo scored better on the essay than those who played Word Whomp as measured by their knowledge of five facts about plate tectonics. Spatial reasoning also improved after playing Halo (but not after the word game), as determined by two standard tests of this skill taken before and after the session. “In first-person-shooter games, you are rotating constantly and locating yourself in space,” says Sanchez, who believes this skill is linked to grasping some types of concepts. “When you're trying to learn [plate tectonics], you're extrapolating a spatial mental representation, a three-dimensional model that is running and changing all the time inside your head.”

Action gamers are also better at making decisions when a rapid response is important, according to a 2010 study by Green and Bavelier, probably because they are faster at assessing new visual information. They asked 12 nongamers and 11 gamers to look at a display of moving dots and indicate the net direction of motion—whether more dots were moving to the right or left. Both groups were equally accurate, but gamers were substantially faster at deciding. A second experiment in which participants were asked to distinguish pure tones from white noise showed that gamers were also faster at making decisions about auditory input. This type of decision making can be critical behind the wheel. For example, it enables a driver to recognize more rapidly whether the flash of movement to the right of the vehicle is relevant: Is it a child about to run in front of the car or an inconsequential flashing light?

Video games also train hand-eye coordination, although the primary improvement in this domain appears to be cognitive. In a 2010 study neuroscientist Lauren E. Sergio of York University in Toronto and her colleagues scanned the brains of gamers and nongamers (13 of each) using functional MRI while they performed increasingly difficult hand-eye tasks while looking at a screen. The easiest tasks were those in which a person could watch a target, such as pressing a tab on the screen, followed by those that required a user to look away from their hands, akin to using a mouse to operate a computer. In the most difficult tests, participants could not look at their hands and had to move a joystick in the opposite direction of the stimulus—if it moved right, they moved left—meaning they had to inhibit the natural tendency to follow what the eye sees. The harder the task, the more it recruited a part of the brain behind the forehead called the prefrontal cortex, which is involved in planning complex actions and, when necessary, can act as an inhibitor of gut responses, forcing us to stop and reconsider.

“Everybody used the same basic network of brain parts, and the performance was the same, but the network was reweighted,” Sergio says. “The gamers were using much less of the basic motor control parts, and other areas were more active, mainly in the front part of the brain.” The difference was greatest on the most difficult skills, such as those that involved acting in a manner discordant with that of a cue. We need to employ such cognitive control, for example, to steer a sailboat, which turns left when the tiller is moved right, and vice versa. These results, Sergio believes, suggest that gamers use their prefrontal cortex to perform visuomotor skills more than nongamers do. This pattern, which is also seen in concert musicians, is considered a sign of expertise and may lead to better performance during extremely complex motor feats, such as piano playing or surgery.

A striking application of this skill surfaced in a 2007 study of 33 laparoscopic surgeons, who operate while looking through a camera rather than directly at the patient. Developmental psychologist Douglas A. Gentile of Iowa State University tested the doctors on a set of standardized suturing skills. “The number-one predictor of surgical skill was how good they were at video games,” he says. “The number-two predictor was how much they had played video games in the past. Only after that did we get to things like how many years of training they had or how many surgeries they had performed.” Other researchers have found similar results with airplane and drone pilots.

Just a Game?

Despite such positive findings, heavy use of video games can also have serious drawbacks. Game addiction has not yet been officially recognized as a disorder, but studies by Gentile and others found between 5 and 11 percent of children worldwide say such games are disrupting their lives, suggesting they could be considered addicted. In the U.S., where Gentile worked with Harris Polls, the figure was 8.5 percent. In contrast, 4 to 6 percent of casino gamblers are considered addicted. Thus, even if playing violent video games can be beneficial, as Gentile recognizes it can be, people need to be alert to the dangers of too high a dose.

Gentile has also been taking a closer look at the content of these violent games, the blowing things up that the president decried. Researchers agree that such games lead to a short-lived increase in aggression. “Even though you know it's just a game, your body dumps stress hormones into your bloodstream that get you prepared to fight,” Gentile says. “Once you stop playing, it wears off after half an hour.”

Of more concern are studies across thousands of gamers indicating that regular exposure to violent video games (meaning several hours a week) accounts for 1 to 4 percent of the many possible triggers for aggression. (Other predictors range from provocation to poverty and child abuse.) Most consider this percentage to represent a small effect. Gentile also emphasizes that protective factors such as involved parents and good social skills can minimize the problem. Put another way, players for whom games can spawn violence usually have other troubles. If you are looking at violent crime, Gentile agrees video games have almost nothing to do with it. Still, he adds, gaming could have an impact on milder forms of aggressiveness. “If what you care about is the everyday aggression you see in seventh grade—people ostracizing one another, saying unkind things, bullying,” Gentile explains. “I say there's a huge effect. Games change the way kids see the world.”

Making Peace

Ideally, then, researchers would be able to tease out the beneficial ingredients of these games to create nonviolent versions that train brains just as effectively. So far these factors seem to include operating from a first-person point of view, managing multiple streams of information and goals, and making rapid decisions. Bavelier imagines a game in which you are on a planet where animals are suffering from a deadly disease. You are the veterinarian who must find them and inject them with lifesaving medicine. To add to the challenge, the disease is deadly to humans, so you cannot let them touch you. “It's all the same dynamics of an action game,” Bavelier says, “but suddenly you're doing good.”

What makes games fun and absorbing are rich graphics and sufficiently complex storylines. All of it stimulates the brain's reward system—releasing a jolt of dopamine, a neurotransmitter associated with pleasure that both encourages continued play and sparks learning. “The very mechanics that seem to make commercially successful games superfun are also the ones that are seeming to have the positive effects in terms of brain plasticity,” says Alan Gershenfeld, president of E-Line Media, a company he co-founded to create games for learning, health and social impact.

Success in building a new suite of brain-changing games, however, will require not only good science but also partnerships between neuroscientists and expert game designers. Bavelier has joined forces with Gershenfeld, and the two are raising funds to develop what they say will be the first game “designed from the ground up” to take advantage of the new research: a nonviolent action game targeted at developing number sense in eight- to 14-year-olds.

Meanwhile some existing nonviolent video games may lead to other benefits. In a 2009 study Gentile found that prosocial games, those that require cooperation, make children more helpful and sociable. “I don't believe action games are going to be the solution to everything—quite the contrary,” Bavelier says. Given that games are here to stay, getting the best out of them could be an epic win for everyone.

Lydia Denworth is an award-winning science journalist and contributing editor for Scientific American . She is author of Friendship (W. W. Norton, 2020).

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Research Article

The same video game in 2D, 3D or virtual reality – How does technology impact game evaluation and brand placements?

Roles Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Project administration, Validation, Visualization, Writing – original draft

* E-mail: [email protected]

Affiliation Department of Marketing & International Management, Alpen-Adria-Universität Klagenfurt, Klagenfurt, Austria

Roles Conceptualization, Supervision, Writing – review & editing

• Johanna Roettl, 
• Ralf Terlutter

• Published: July 20, 2018
• https://doi.org/10.1371/journal.pone.0200724
• Reader Comments

Video game technology is changing from 2D to 3D and virtual reality (VR) graphics. In this research, we analyze how an identical video game that is either played in a 2D, stereoscopic 3D or Head-Mounted-Display (HMD) VR version is experienced by the players, and how brands that are placed in the video game are affected. The game related variables, which are analyzed, are presence, attitude towards the video game and arousal while playing the video game. Brand placement related variables are attitude towards the placed brands and memory (recall and recognition) for the placed brands. 237 players took part in the main study and played a jump’n’run game consisting of three levels. Results indicate that presence was higher in the HMD VR than in the stereoscopic 3D than in the 2D video game, but neither arousal nor attitude towards the video game differed. Memory for the placed brands was lower in the HMD VR than in the stereoscopic 3D than in the 2D video game, whereas attitudes towards the brands were not affected. A post hoc study (n = 53) shows that cognitive load was highest in the VR game, and lowest in the 3D game. Subjects reported higher levels of dizziness and motion-sickness in the VR game than in the 3D and in the 2D game. Limitations are addressed and implications for researchers, marketers and video game developers are outlined.

Citation: Roettl J, Terlutter R (2018) The same video game in 2D, 3D or virtual reality – How does technology impact game evaluation and brand placements? PLoS ONE 13(7): e0200724. https://doi.org/10.1371/journal.pone.0200724

Editor: Stefano Triberti, Universita Cattolica del Sacro Cuore, ITALY

Received: September 4, 2017; Accepted: July 2, 2018; Published: July 20, 2018

Copyright: © 2018 Roettl, Terlutter. This is an open access article distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Data Availability: All relevant data are within the paper and its Supporting Information files.

Funding: This research was supported by grants from the "Verein zur Förderung der Wirtschaftswissenschaften an der Alpen-Adria-Universität Klagenfurt" (Association for the Promotion of Economics at the Alpen-Adria University Klagenfurt). The funding organization had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Competing interests: The authors have declared that no competing interests exist.

Introduction

The video game industry is one of the fastest-growing industries. The global value for the video games market is expected to grow from almost USD 71 billion in 2015 to about USD 90 billion in 2020 [ 1 – 3 ]. At least one person in more than 60% of US American households plays video games on a regular basis, doing so for at least 3 hours per week, and 65% of US American households own at least one device which is capable of playing video games [ 4 ]. Similar usage data can be found in Europe or Asia. For instance, 40% of all Eastern Europeans play video games; in Germany, about one in two plays video games occasionally [ 2 , 5 , 6 ]. In Southeast Asia, every fifth person plays video games, and in China, almost every third person is a video game player [ 5 , 7 ]. In the US, the most popular game genres in 2016 were shooter games (27.5%), followed by action (22.5%), role-playing (12.9%) and sport games (11.7%) [ 8 ].

Video games create a virtual reality in which the individual plays the game. Virtual reality is understood as an environment that is created by a computer or other media and in which the user has a feeling of being present in the environment [ 9 ]. Over the last few years, there has been a technological change in the video game sector. Instead of a conventional two-dimensional (2D) virtual environment, many video games can be played in a stereoscopic three-dimensional (3D) or even in a Head-Mounted-Display (HMD VR) based virtual reality environment. A 3D environment is deemed to be more realistic and vivid than a 2D environment [ 10 – 14 ]. HMD VR aims at depicting an environment that is even closer to the real world than a 3D environment. Wearing specific VR goggles, a person’s physical presence is simulated in a virtual 3D environment, and at the same time, the goggles shield the individual from the real physical surroundings during the VR experience [ 15 ]. HMD VR in particular is currently expected to bring about major changes for the video game sector (e.g. [ 16 ]). 63% of frequent gamers in the USA are familiar with the HMD VR technology [ 17 ]. The total worldwide market size for HMD VR and AR (augmented reality) is expected to grow from 6.1 USD billion in 2016 to more than 215 USD billion in 2021 [ 18 ]. The worldwide sales revenue for HMD VR video gaming only is expected to increase from 5.2 USD billion in 2016 to 22.9 billion US dollars in 2020 [ 19 ]. In 2016, North America and Europe were the two biggest markets for HMD VR video gaming with sales revenues of 1.5 billion USD and 1.9 billion USD, respectively. The most popular HMD VR video game genres are adventure, action and simulation games. In 2016, more than 50% of HMD VR video game players were interested in these genres [ 20 ].

One phenomenon that exists in many video games are brand placements and they are also addressed in the current research. Brand placements in video games are a form of advertising in which branded goods or services are featured in the video game (e.g. [ 21 – 23 ]). They are “a combination of advertising and publicity designed to influence the audience by unobtrusively inserting branded products in entertainment programs such that the viewer is unlikely to be aware of the persuasive intent” ([ 24 ]; p. 89). For game developers, embedding brands is a method to make the game more reality-like and it is also an important income source that contributes to meeting the production costs [ 25 ]. For companies, placements in video games are a method of promoting products or brands by embedding them in the game play. The placing companies typically value the chance of relatively intensive and repeated contacts of the player with the brands, especially if the brands are integrated in the main video game plot (e.g. if the player has to use the brands as part of the game play). They also appreciate that brands or products are promoted in a more unobtrusive way than in traditional advertising (e.g. [ 26 ]). The most relevant variables for marketers are memory for the placed brands as well as attitudes towards the placed brands [ 27 ].

The present study investigates how the game play experience is affected, depending on whether players play an identical video game in 2D, stereoscopic 3D (in the following just “3D”) or Head-Mounted-Display VR (“VR”). In addition, the study analyzes how brand placements in the video games are affected and whether they gain or suffer from advanced technology. By shedding light on the evaluation of 2D, 3D and VR video games and the brands placed therein, the study yields important insights for researchers, video game producers as well as marketers who want to promote their brands via placements in video games.

Theoretical background

2d, stereoscopic 3d and hmd virtual reality video games.

In comparison to the conventional 2D technology, which does not give depth to the objects, 3D and VR technology offer additional experiences for the user. The technologies allow for the perception of spatial depth on the screen. In the 3D technology, this is realized by using stereoscopic displays, which creates spatial depth off the screen with 3D pop-up visualizations, so that some objects within the game appear closer to the player and seem touchable, the usage of 3D-capable screens or the usage of dedicated 3D-capable glasses. 3D technology can be more realistic, immersive and allows e.g. improved eye-hand coordination, as compared to the 2D technology experience that lacks depth perception. One of the first 3D home video game devices was Tomytronic 3D in which 3D was simulated using two LCD panels, developed by a Japanese toy maker in 1982. Other early home devices were developed by e.g. Nintendo in 1995 [ 28 , 29 ].

In comparison to the 3D technology, HMD VR tries to deliver an even stronger feeling of being in the world or in the moment [ 30 ]. VR is a computer-simulated reality, where the player immerses himself/herself in a fictive 3D world by using a special head-mounted display (HMD), which is a headset that shows visual effects directly in front of the player’s eyes (e.g. Google Cardboard, Oculus Rift, Samsung Gear VR). In VR, the player can interact with and in the environment and is sheltered from the outside world as compared to Augmented Reality (AR) (e.g. Google Glass), where the visuals can be projected on glasses, too, but the player is not sheltered from the outside world) [ 9 , 31 – 33 ]. In VR the user can move through and experience the game world while thinking that he/she is truly somewhere else. Hence, a VR video game might offer the possibility to be more realistic than a game displaying a 2D or 3D condition [ 34 – 36 ]. Arguably, the first VR headset with goggles was developed in the Mid-Eighties by VPL research and Jaron Lanier. Nowadays, many different VR types and headsets exist. One of the least expensive open source models, developed for Android smartphones, is Google Cardboard. Google Cardboard can be made by the user him- or herself or is sold at prices between 5 USD and 20 USD [ 30 , 37 ]. A more sophisticated device is the Oculus Rift that is currently sold at about 399 USD. Other well-known technologies include the Microsoft HoloLens, a holographic computer, where the user can engage with the digital content and interact with holograms in the world around him or her [ 38 ], the PlayStation VR [ 39 ], HTC’s Vive, another content streaming headset [ 40 ] or the Samsung Gear VR [ 30 ].

However, the quality of 3D technologies [ 13 , 41 , 42 ] as well as VR technologies [ 35 , 36 ] have been debated critically and researchers have demonstrated a range of negative effects, too, e.g. discomfort, eye fatigue, dizziness, headache, disorientation or motion-sickness when using these technologies. Furthermore, VR users might become socially isolated when using head-mounted displays, as a consequence of locking their eyes and ears into a fictional video game generated world for longer periods of time [ 36 , 43 , 44 ].

Presence in the 2D, stereoscopic 3D and HMD VR video game

The concept of presence in virtual environments has received a lot of attention during the last decades, especially with the rise of interactive technologies in the 90s, and has been debated from different perspectives (e.g. [ 31 , 45 , 46 ]). Presence in a virtual environment can be described as the sense of being in a virtually mediated location instead of being in the real location (the place the person is actually located in) [ 47 ]. The sense of presence plays an important role in linking perceptions, intentions and actions of an individual in the environment (e.g. [ 48 – 52 ]). High levels of presence in a virtual environment allow the subject to put his / her intentions into action, to monitor the actions and adjust activities if needed. The subject can adapt the own action to the environment [ 52 ].

The level of presence seems to be of special interest for the comparison of different technological environments and in the game context. The question is how deeply participants are immersed or “inside” the game [ 53 , 54 ]. Kim and Biocca [ 55 ] speak of “departure”, which describes the feeling of not being in the physical environment anymore and “arrival”, which describes the feeling of being within in the mediated environment. Especially in the VR environment, and to a lesser extent in the 3D environment, game players are likely more immersed in the mediated environment (“arrival”) and perceive less of the physical environment (“departure”). If elements of the 3D or VR game play are seemingly touchable as they appear to be around the player, the player probably pays more attention to the 3D effects of the mediated environment, hence the level of immersion and presence should be increased. In the VR video game, wearing the goggles, the player is even sealed off from all visual stimuli around him/her in the physical environment. Hence, there will be an even higher level of “departure” than in 3D. The player will be more immersed and absorbed in the mediated environment, as the stimuli from the mediated environment are practically the only stimuli he/she receives while playing the game, leading to a higher level of “arrival”.

We therefore expect that presence should be higher in the VR than in the 3D than in the 2D video game.

“H1: Presence will be highest in the VR video game, lower in 3D and lowest in the 2D video game.”

Arousal while playing the video game

Arousal can be defined as stimulation, alertness or activation and is a process, which initiates behavior [ 56 ]. According to Bolls et al. [ 57 ] arousal “indicates the level of activation associated with the emotional response and ranges from very excited or energized at one extreme to very calm or sleepy at the other” ([ 56 ]; p. 629). Measuring arousal in different media formats, such as 3D or VR, has become a common practice in research settings (e.g. [ 58 – 61 ]). Video game players will experience arousal, depending on, for instance, how exiting or involving the playing experience is. Levels of arousal that are too low might lead to boredom and reduced attention directed towards the game. In contrast, if the gamer experiences too much arousal, attention can also be diverted. Hence, the level of arousal elicited by a video game is an important variable [ 62 ]. According to previously conducted research, games which are played with 3D or VR can cause a higher arousal than games played with a simpler technology, such as 2D (e.g. [ 58 , 63 – 65 ]). Thus, we expect a higher arousal in the VR condition than in the 3D than in the 2D condition.

“H2: Arousal will be highest in the VR video game, lower in the 3D and lowest in the 2D video game.”

Attitude towards the video game

Attitude towards the game in this research is defined as the overall evaluation of the game played. Attitudes are a composite of feelings and beliefs as well as behavioral intentions toward an object [ 66 ]. The components are highly interdependent and influence each other. When playing a computer game, individuals will like the game more or less and evaluate it more or less positively or negatively. Attitude towards the game is an important variable for game producers as it determines to a large extent how the player will react to the object, e.g. how much time the player is willing to devote to the game, whether or not he/she replays the game or recommends it to somebody else. Attitudes toward the game are also important because they impact the brands that are embedded in the computer games [ 67 , 68 ].

As outlined above, 3D and VR offer additional technological features (e.g. higher immersion) that may allow for a better attitude towards the game. On the other hand, negative aspects are also related to the technological enhancements (e.g. higher visual fatigue, dizziness), which are likely to impair attitudes towards the game. Since the literature is contradictory with regard to whether the positive or negative aspects related to the technology enhancement dominate, and since no research has examined the attitude towards the game when playing the game either in a 2D or in a 3D or in a VR condition, hence no empirical evidence is available so far, we investigate the impact of the technology on attitude towards the game and formulate the following research question:

“RQ1: Do attitudes toward the game differ in the 2D, stereoscopic 3D and HMD VR condition?”

Attitude towards the brands placed in the video game

As outlined above, brand placements play an important role in video games. Though previous research has analyzed several factors that influence the recipients’ attitude towards brands placed in computer games, such as game involvement [ 69 ], enjoyment and attitude toward the game [ 70 ], or brand prominence [ 71 ], surprisingly little research has addressed how different delivery modes such as 2D, 3D, or VR might impact the brands placed in video games. Drawing from related research fields, mainly from advertising and product presentation on websites, there is some indication that brands might benefit from 3D as compared to 2D presentation. Li et al. [ 72 ] found that ‘flat’ 3D advertisements on websites generate more positive brand attitudes than 2D advertisements. Flat 3D means that the product representation is 2D, but that users can rotate products, animate their functions and features or can zoom in or out for inspection. These findings are also consistent with the study conducted by Choi and Tylor [ 73 ], which shows that flat 3D brand representations (by moving, zooming and rotating the object) on websites leads partly to a higher brand attitude than 2D brand representations (static pictures). However, this was only the case for a geometric product (watch) but not for the tested material product (jacket) [ 73 ]. Debbabi et al. [ 74 ] report similar findings, since the brand attitude was more positive for flat 3D Internet-based advertisements than for 2D ones. According to Lee et al. [ 75 ], consumers’ brand attitudes were more responsive and were held with greater confidence for flat 3D visualized products on an interactive website than for 2D products on a website that was static. Kerrebroeck et al. [ 76 ] demonstrate that attitude toward the ad, attitude toward the brand and purchase intentions were higher in the case of VR versus 2D. In their experiment participants watched a video either in a 2D condition on a mobile phone or in a VR condition on a HMD based Google Cardboard-type device.

To the best of the authors’ knowledge, no study has addressed this question in the context of 2D, stereoscopic 3D and HMD VR video games. Hence, several studies have shown that an enhanced technology might influence the attitude towards the brand positively. We therefore derive the following hypothesis:

“H3: Attitude toward the placed brands will be more positive in the VR video game compared to the 3D, and it will be least positive in the 2D video game.”

Memory for the placed brands

Recall and recognition are the most common measures to examine the memory of brand placements (e.g. [ 25 , 27 , 77 – 79 ]). Recall is the ability of a person to retrieve a brand name correctly from memory without any mention of other brand names or the product class. Recognition is the ability to remember that there exists past exposure to the brand and it is usually measured by using aided memory based techniques, e.g. where brands are listed and the person can choose the brand/s which he/she has recognized [ 80 , 81 ]. One model that may explain effects of technology enhancement on the memory for brand placements in computer games is the limited capacity model of motivated mediated message processing [ 82 ]. The model assumes that an individual’s attentional capacity and his/her ability to process information cognitively is limited. The cognitive capacity, which is used to perform a primary task, cannot simultaneously be used to accomplish a secondary task. When playing video games, the game play is the primary task because the player primarily focuses his/her attention on those aspects which are relevant for a successful game play. While the player focuses his/her attention on the primary task, fewer cognitive resources are available for secondary tasks, such as processing embedded advertisements [ 82 – 85 ]. The more attentional capacity is needed to play the video game, the less capacity will be left for processing the information about the placed brands [ 83 , 84 ].

It can be assumed that a 3D and a VR condition require more cognitive resources than a 2D condition. The depth perception in the 3D and the VR environment and the higher complexity of the VR world in general are additional items of information that occupy more cognitive resources. There is also empirical evidence that supports this assumption. Mun et al. [ 86 ] demonstrated in cognitive tests that the brain activity of recipients who were exposed to a stereoscopic 3D environment was higher than that of subjects who were exposed to a 2D environment. Furthermore, those who were exposed to the 3D environment needed longer execution times for tasks and paid more attention to the 3D effects than to other areas because of their visual fatigue (exhaustion of the eyes). Yim et al. [ 87 ] explored how stereoscopic 3D technology in comparison to a 2D display influences the viewers’ memory of brand names embedded in a soccer game. Results showed that the viewers remembered less brand names in the 3D condition compared to the 2D condition [ 87 ]. Other studies also found that subjects have a longer reaction time in 3D conditions than in 2D conditions, since their cognitive load is increased (e.g. [ 88 – 90 ]). Furthermore, in a 3D as well as in a VR environment, the backgrounds are often blurred and the 3D or VR environment can stress the viewers’ eyes, which can also lead to cognitive fatigue and a reduction of attention. Comparing 2D, 3D and 4D movies (3D plus scent), Terlutter et al. [ 91 ] found that memory for brand placements suffered in the 3D and 4D condition as compared to the 2D condition, except for one extremely prominent placement that was better memorized in the 3D condition, and they attribute the typically lower memory in 3D and 4D to the greater amount of cognitive resources needed for processing the central movie plot, leaving less resources for processing the brand placements.

Thus, the player has to process more information in a VR and a 3D video game in comparison to a 2D video game and hence more cognitive resources are needed for the game play (the primary task), leaving less cognitive resources for secondary tasks, such as memorizing the brand placements in the video game. This leads us to the following hypothesis:

“H4: Recall and recognition of the brands included in the video game will be lowest in the VR condition, higher in the 3D condition and highest in the 2D condition.”

Control variables

Skepticism towards advertising, general attitude towards video games, prior video game playing experience and video game literacy serve as control variables.

In Austria, it is not necessary to go through an Institutional Review Board or an Ethical Committee when performing a study with human participants who are of legal age. The research design and the questionnaire are in line with the Austrian and the EU privacy regulations. The research as well as the questionnaire have been approved by several professors and employees of the University. Subjects have been notified and have been properly instructed about their voluntary participation in an experiment and that their data will be handled strictly confidential by using appropriate tools, instruments, and protocols to secure their privacy. Consenting participants have been informed about the survey verbally and in written form in advance and after filling out the questionnaire. The data was handled in a strictly confidential fashion and anonymously.

Main study design

In order to address the above proposed hypotheses and research question, a “jump’n’run” video game was designed and developed in a 2D, 3D and VR condition by a professional game designer. The 2D condition was developed with traditional pictures and without depth of the objects. The 3D condition refers to stereoscopic three-dimensional technology, where the objects pop-up with true depth and float off the screen [ 14 ]. The VR condition was based on the HMD technology. The game was designed with the software tool Unity 3D. We chose a jump’n’run action game for several reasons: Action video games place a focus on the player’s reflexes as well as on his / her reaction time, the eye-hand coordination is important and players try to accomplish a goal [ 92 ]. “Jump’n’run” video games are one of the most common game genres and spatial depth perception is likely to be of relevance for game play. The game consisted of three levels of increasing difficulty. Playing time was between 7 and 10 minutes. In the 2D and 3D condition, the game was played on a large 46-inch, stereoscopic 3D-capable television. Participants who played the game in the 3D condition received special 3D glasses, which allowed the players to experience depth perception. Players of the VR condition wore an Oculus Rift headset. The whole game was accompanied by the same music in all three conditions. Participants played the game by using an Xbox 360 controller for Windows.

In total eight different brands were integrated in the game, each brand appeared in each level (hence each brand appeared three times during game play). The brands belonged to the following product categories: airline, chocolate, bank, energy drink, coffee, fitness club, nachos, and smartphone. All brands were fictitious to avoid confounding effects of previous brand knowledge. The size and presentation type of all brands were kept constant across all three different levels and across all three game conditions. The brands remained on screen until they were collected by the player. One goal that players pursued was to collect as many brands as possible in order to get to the next level. All participants reached the last level. At the end of the game, participants could record their name in a high score list. After playing the game, each participant filled out an electronic questionnaire (see S1 Appendix ).

Data was analyzed with SPSS (see S1 Data ). Analyses of variance and t-tests were carried out. In order to determine the practical and theoretical relevance of an effect as well as the power of the analyses, effect sizes were estimated for each analysis [ 93 ]. Partial eta-squared (η 2 p ) was used for the effect size measurement for the analysis of variance (ANOVA). It measures the strength of the effect on a continuous field, where η 2 p = 0.01 indicates a small effect, η 2 p = 0.06 indicates a medium effect and η 2 p = 0.14 indicates a strong effect [ 94 – 96 ]. Hedges’ g (g Hedges ) was used to evaluate the effect of group differences of t-tests. Hedges’ g accounts for different group sizes and also allows for smaller group sizes [ 97 – 100 ]. Values of g Hedges = 0.2 indicate a small effect, g Hedges = 0.5 a medium effect, and g Hedges = 0.8 a large effect. Phi (ϕ) was used to measure effect size for the chi-squared test, whereas ϕ = 0.1 indicates a small effect, ϕ = 0.3 indicates a medium effect and ϕ = 0.5 indicates a large effect [ 100 , 101 ].

Before conducting the main study, a first pre-test was carried out to develop and to test the video game in all three conditions (n = 10 students). The aim of the pre-test was to ensure that the game was neither too difficult nor too easy to play, that the brand positions were appropriate and not annoying, and that the questionnaire was comprehensible and not too long. None of the participants had any prior video game experiences in 3D or VR. Three subjects played the 2D video game, four people played the 3D video game and three subjects played the VR video game. Minor adaptions were made in the video game and in the questionnaire based on students’ feedback. All ten students were of the opinion that the programed game was of high quality and fun to play, regardless of the technology they had played. None of the students mentioned any concerns regarding playing the game or filling in the questionnaire.

Participants

237 students from a midsize university in Europe participated in the main study, held in computer labs on the campus. Participants were randomly assigned to one of the three game conditions (2D, 3D, VR). Three participants were excluded from the analysis because of an extremely short answer time and/or inconsistent answer patterns (e.g. flatliners, contradictions), resulting in 234 usable respondents (2D: 79 subjects; 3D: 78; VR: 77). We used a student sample, because most video game players are aged 18–49 and students are in the main target group for a jump’n’run video game like the one at hand [ 102 , 103 ]. Students received extra credit in a course in exchange for their participation; in addition, chocolate bars were given as small incentives as well as the option to win a voucher for a local shopping center. Respondents were between the ages of 18–46, with a mean age of 24.52 years (SD = 4.13). Age distribution did not differ between the three conditions (2D, 3D, VR) (F(2,230) = 2.165; ns, η 2 p = .018). Females (n = 134) were slightly overrepresented in the study in comparison to males (n = 100), but gender distribution did not differ between the three conditions (χ 2 = 1.826 (df = 2) , ns, ϕ = .088). 48.3% of the participants played video games at least once per month with an average playing time of 22.29h per month (SD = 33.04). Men (M = 31.26h per month, SD = 40.19) played video games almost three times as often as women (M = 11.34h per month, SD = 15.62) (t = -4.272 (117,205) , p<0.01, g Hedges = .63), but average monthly playing time did not differ between the three conditions (F(2,157) = .041; ns, η 2 p = .001).

Measurement of variables

Measurement of the variables was based on existing literature (see S2 Appendix ). All interval scaled items had a “no answer” category as an alternative. Demographic data had to be provided (e.g. gender, age, field of study) at the end of the questionnaire. Data were analyzed using SPSS version 22 (IBM Corp, Armonk, NY, USA) (see S1 Data and S2 Data ).

Attitude towards the game (α = .864) was measured with six bipolar adjectives, using 7-point semantic differential scales, with the negative adjectives coded 1 and the positive adjectives coded 7. The adjectives were: unappealing-appealing, unpleasant-pleasant, dull-dynamic, unattractive-attractive, not enjoyable-enjoyable, and depressing-refreshing [ 104 ]. The mean value of the items was calculated and used for further analyses.

Attitude towards the brand (α nachos = .916; α chocolate_bar = .932; α smartphone = .930; α energy_drink = .951): In order to avoid an overly long questionnaire, attitude toward the brand was measured for only four out of the eight brands that were placed in the game. Subjects were asked to evaluate the brands based on the following six items, using a 7-point scale: this is a bad / good product, I feel negative / positive toward the product, the product is awful / nice, the product is unpleasant / pleasant, the product is unattractive / attractive, I disapprove / approve of the product. The questions were adapted from Shamdasani et al. [ 105 ]. The mean value of the items was calculated and used for further analyses.

Arousal (α = .846) was measured immediately after playing the video game. Subjects were asked to indicate their perceived level of arousal based on three bipolar adjectives and on a 7-point semantic differential scale, hence, a self-reported arousal measurement was used. The items read excited-calm, stimulated-relaxed and alerted-soothed [ 56 ]. The mean value of the items was calculated and used for further analyses.

Presence was assessed by asking about the level of agreement to the following statement: “I was totally absorbed in what I was doing” [ 106 ]. The answer scale ranged from 1 (low agreement) to 7 (full agreement). Hence, the current research applied a single item measurement of presence. A single item measurement was chosen for practical reasons to avoid an overlong questionnaire. In addition, the level of absorption in what somebody is doing in an environment is an important indicator for the individuals’ presence in that environment. If individuals’ presence in an environment is high, they are able to adapt their actions to the environment [ 52 ] and individuals do not necessarily perceive the state of being in the virtual environment [ 53 ].

Brand recall was measured by asking the participants to write down the remembered brands, which they had seen while playing the game.

To measure brand recognition each of the eight brands that had appeared in the game was presented along with two mock brands from the same product category which had not appeared in the game. Participants had the possibility to choose “others”, if they felt they could not remember any of the three brands. The eight brands with their respective mock brands were presented one after the other, and participants could only tick one option. This option was either the correct brand (true memory) or not (i.e. false or no memory). If the participants just guessed, there would be a 25% probability of choosing the brand that appeared in the game for each brand category, which would be same for all conditions. We deliberately chose to measure recognition for each brand one after the other, instead of presenting a list with all appearing brands and the mock brands at once. Our measurement avoids the problem that is related to presenting a long list of all appearing brands and mock brands at once, namely that memory is easily overestimated if participants just start ticking many alternatives (and by doing so have the chance to hit the correct brands, too, even though they do not recognize them). However, our measurement does not allow for a recognition sensitivity test as suggested by e.g. Grier [ 107 ]. Brand logos were presented in random order for each participant to avoid order and context effects. 1 was coded if a subject named or ticked the correct brand, otherwise 0 was coded.

For both, recall and recognition, the named or ticked brands were added up to an 8-point sum scale for each participant.

Control variables.

Skepticism towards advertising (α = .899) was examined according to Obermiller & Spangenberg [ 108 ] by using the following nine items: we can depend on getting the truth in most advertising; advertising's aim is to inform the consumer; I believe advertising is informative; advertising is generally truthful; advertising is a reliable source of information about the quality and performance of products; advertising is truth well told; in general, advertising presents a true picture of the product being advertised; I feel I've been accurately informed after viewing most advertisements; most advertising provides consumers with essential information. The answer scale ranged from 1 (low agreement) to 7 (full agreement). Hence, low values of the items indicate high levels of skepticism. The mean value of the items was calculated and used for further analyses.

General attitude towards video games was measured by asking the subjects “In general, what kind of feelings do you have toward video games?”, where 1 was “very negative” and 7 was “very positive” (adapted from Porter & Donthu) [ 109 ].

Prior video game experience was investigated by asking the following question: “How much experience with games of this type (jump’n’run games), such as you have just played, do you have?” The answer scale ranged from 1 (no experience at all) to 7 (a lot of experience).

Video game literacy was measured with the following question: “How good are your skills in relation to video games?”, where the answer scale ranged from 1 (no skills at all) to 7 (very good skills).

Results of the main study

Before the hypotheses and research question were addressed, ANOVAs were conducted with the three groups (2D, 3D, VR) as independent variable and the control variables skepticism towards advertising, general attitude towards video games, prior video game playing experience and video game literacy as dependent variables. Analyses revealed that the three groups did not differ significantly in all four control variables (skepticism towards advertising: F(2,231) = .127, ns, η 2 p = .001; general attitude towards video games: F(2,230) = .741, ns, η 2 p = .006; prior video game playing experience: F(2,231) = .186, ns, η 2 p = .002; and video games literacy: F(2,231) = .338, ns, η 2 p = .003. Additionally, gender differences were checked. As could be expected, significant gender differences with regard to prior video games experiences with jump’n’run games could be revealed, with males being more experienced than females (t = -5.835 (230.079) , p<0.01, g Hedges = .748).

Presence in the 2D, 3D and VR video game

H1 postulates a higher level of presence in the VR condition than in the 3D condition than in the 2D condition. An ANOVA with the three different technologies as independent variable and presence as dependent variable revealed that the three groups differed significantly in their presence (F(2,228) = 5.104, p<0.01, η 2 p = .043). Results show that the mean was lowest in the 2D condition (M = 5.28; SD = 1.71), followed by the mean of the 3D condition (M = 5.63; SD = 1.38). The mean was highest in the VR condition (M = 6.03, SD = 1.21). Contrast tests show that significant differences were found between the 2D and VR condition (t = 3.13 (139.19) , p < .01, g Hedges = .499). The differences between the 2D and 3D condition (t = -1.40 (147.24) , ns, g Hedges = .225) as well as between the 3D and VR condition (t = -1.87 (147.95) , .063, g Hedges = .300) were as expected, but were not significant. Hypothesis H1 was partly supported by the data.

Regarding the second hypothesis that arousal will be higher in the VR video game than in the 3D than in the 2D video game, an ANOVA with technology (2D, 3D, VR) as independent variable and arousal as dependent variable revealed no significant differences between the three different technological conditions (F(2,228) = .984, ns, η 2 p = .009). Players in all three technology groups were moderately aroused (2D: M = 4.18, SD = 1.57; 3D: M = 4.25, SD = 1.60; VR: M = 3.90; SD = 1.63). H2 is rejected by the data.

In order to answer the research question whether attitudes toward the game differ in the 2D, 3D and VR condition, an ANOVA with technology (2D, 3D, VR) as independent variable and attitude towards the game as dependent variable was carried out. The analysis showed no significant differences between the three technologies (F(2,226) = .365, ns, η 2 p = .003). The mean values in all three technology groups were relatively high, indicating that the players liked the video game, regardless of the technology they had played (2D: M = 5.08, SD = 1.09; 3D: M = 5.24, SD = 1.16; VR: M = 5.16; SD = 1.08).

To address the third hypothesis that attitude toward the placed brands will be higher in the VR video game than in the 3D than in the 2D video game, four consecutive ANOVAs, one for each brand in the four product categories, were performed (independent variable = technology, dependent variable = attitude towards the brand). Results of the ANOVAs revealed that the attitude towards the placed brands did not differ among the three technology groups, for any of the four brands (nachos: F(2,224) = .437, ns, η 2 p = .004; chocolate bar: F(2,226) = 1.340, ns, η 2 p = .012; smartphone: F(2,225) = 1.186, ns, η 2 p = .010; energy drink: F(2,227) = .748, ns, η 2 p = .007).

Hypothesis H4 expected that recall and recognition of the brands included in the video game will be lower in the VR condition than in the 3D condition than in the 2D condition.

An ANOVA with technology as independent variable and recall as dependent variable revealed significant differences among the three groups (F(2,231) = 8.514, p < .01, η 2 p = .069). As expected, subjects in the VR condition had the lowest recall of brands (M = .61, SD = .96), subjects in the 3D condition had a higher recall (M = 1.06, SD = 1.33) and subjects in the 2D condition had the highest recall (M = 1.52, SD = 1.72). Contrast tests indicate that the differences between 2D and VR (t = -4.09 (123.24) , p < .01, g Hedges = .651) as well as between 3D and VR (t = 2.43 (140.18) , p = .016, g Hedges = .388) were significant. The difference between 2D and 3D (t = 1.86 (146.86) , p = .065, g Hedges = .299) was significant only on the 10% level. Gender did not affect brand recall (t = -1.923 (185,788) , ns, g Hedges = .262).

The above mean values indicate that, overall, brand recall appeared to be low. In the 2D condition 32 participants could not recall any brand. In the 3D condition 39 students did not recall any brand, whereas in the VR condition 50 participants memorized none of the brands.

Recognition.

An ANOVA revealed that the three technology groups differed significantly in their brand recognition (F(2,231) = 14.571, p < .01, η 2 p = .112). Similar to the results for brand recall, in the VR condition, subjects recognized fewest brands (M = 3.42, SD = 1.51), subjects in the 3D condition recognized more brands (M = 4.23, SD = 1.77) and subjects in the 2D condition recognized the highest number of brands (M = 4.91, SD = 1.90). Contrast tests showed that all pairwise differences were significant (2D and 3D: t = 2.33 (154.47) , p = .021, g Hedges = .371; 2D and VR: t = -5.46 (148.07) , p < .01, g Hedges = .869; 3D and VR: t = -3.09 (149.91) , p < .01, g Hedges = .493). Gender did not affect brand recognition (t = -.272 (232) , ns, g Hedges = .038). The values of brand recognition were much higher than the values for brand recall, which could be expected. Over all three conditions, only four participants did not recognize any brand.

Summarizing, the data lends support to our expectation that memory for placed brands will be lower in the VR than in the 3D than in the 2D condition (see S3 Appendix ). H4 on brand recall and brand recognition receives substantial support.

Post hoc study on cognitive load and physical reactions while playing the video game

A post hoc study was carried out in order to gain more insights into the cognitive load and some physical reactions (dizziness and motion-sickness) while playing the video game. In addition, the aim was to confirm the memory results of the main study.

Fifty-three students participated in the post hoc study. The same video game as in the main study was used and played in either 2D, stereoscopic 3D or HMD VR. 19 students played the 2D video game, 19 students played the video game in 3D and 15 students played the video game in the VR condition. 37 participants were female, 16 were male.

Cognitive load

Cognitive load was measured to test our assumption made in the theoretical part that participants playing the video game in the 3D and VR condition need more cognitive capacity for playing the game, as compared to participants in the 2D condition. Cognitive load refers to the total amount of mental effort that is used in the working memory when performing a learning task, it is “the manner in which cognitive resources are focused and used during learning” ([ 110 ]; p. 294). To measure cognitive load, participants in all conditions were asked to memorize the same 8-digit number prior to playing the video game [ 111 ]. After playing the video game, participants were asked to recall as many digits as possible of the number they had been given. A lower number of digits that can be memorized and recalled result from higher cognitive load while playing the game.

The results showed that the mean of correctly recalled digits was indeed lowest in the VR condition (M = 3.47; S = 1.06). However, other than expected, the mean of the 2D condition (M = 4.00, SD = 1.56) was lower than the mean in the 3D condition (M = 4.42, SD = 1.56). Hence, cognitive load while playing the video game appeared to be highest in the VR condition and lowest in the 3D condition. While an ANOVA with the three conditions as independent variable did not reveal significant differences between the three groups (F (2,50) = 2.50, ns, η 2 p = .091), post hoc t-tests between two groups revealed that the mean of the number of correctly recalled digits in in the 3D and VR condition differed significantly (t = -2.236 (5) , p = .03, g Hedges = .696). There were no differences between male and female participants (t = .233 (51) , ns, g Hedges = .074).

Brand memory (recall and recognition)

Recall and recognition of brands were measured in the same way as in the main study. The results of the post hoc study confirmed the findings of the main study. With regard to recall, the three technologies differed significantly (Recall: F(2,50) = 5.237, p < .01, η 2 p = .181). Recall was lowest in the VR condition (M = .40, SD = .91), followed by the mean in the 3D condition (M = .63, SD = 1.07), and highest in the 2D condition (M = 1.58, SD = 1.30). Significant differences between 2D and 3D (t = 2.609 (50) , p = .012, g Hedges = -.798) and 2D and VR (t = -3.049 (50) , p < .01, g Hedges = 1.03) were revealed. The results for brand recognition were similar (F(2,50) = 5.479, p < .01, η 2 p = .180). Recognition was lowest in the VR condition (M = 3.00, SD = 1.73), followed by the 3D condition (M = 4.52, SD = 1.71), and highest in the 2D condition (M = 4.79, SD = 1.55). Post hoc t-tests revealed significant differences between 3D and VR (t = 2.661 (50) , p < .01, g Hedges = .884) and 2D and VR (t = -3.230 (50) , p < .01, g Hedges = 1.097). Values for brand recognition were again much higher than values for brand recall.

Dizziness and motion-sickness while playing

Perceived dizziness and motion sickness while playing the game were also measured. Dizziness was measured with the question “Did you feel dizzy when playing the video game”, motion-sickness with the question “Did you become motion sick while playing the video game?”. The questions were adopted from Jones et al. [ 112 ] and Merhi et al. [ 113 ]. The answer scale ranged from 1 (not at all) to 7 (very much).

Subjects reported significantly different levels of dizziness that they had experienced during game play (F(2,50) = 10.265, p < .01, η 2 p = .291). Dizziness was significantly higher while playing the VR game (M = 2.60, SD = 1.55) than while playing the 3D game (M = 1.47, SD = .84; t = 2.536 (20.416) , p = .019, g Hedges = .939) and the 2D game (M = 1.11, SD = .32; t = -3.677 (14.918) , p < .01). No significant differences were found between playing the 2D and 3D game (t = 1.788 (22.960) , ns, g Hedges = .566).

Results for motion-sickness were similar (F(2,50) = 12.359, p < .01, η 2 p = .331). Subjects reported significantly higher levels of motion-sickness in the VR game (M = 2.40, SD = 1.64) than in the 3D game (M = 1.05, SD = .229; t = 3.160 (14.434) , p < .01, g Hedges = 1.229) and the 2D game (M = 1.05, SD = .229; t = -3.160 (14.434) , p < .01, g Hedges = 1.229). Again, no significant differences were found between 2D and 3D (t = .000 (36.000) , ns, g Hedges = 0).

This study sheds more light on our understanding of 2D versus 3D versus VR video games by analyzing whether and how the delivery mode of an identical video game in either 2D, 3D, or virtual reality (VR) impacts players’ game evaluation as well as the brands that are placed in the game.

Presence was highest in the VR video game and lowest in the 2D video game, presence in the 3D game was in between. The VR video game, and to a lesser extent the 3D video game, obviously lead to a higher feeling of being in the mediated gaming environment (high levels of “arrival”, as outlined in the beginning) and to a lower perception of the real physical environment (high levels of “departure” [ 55 ] as compared to the 2D video game). The latter is probably mostly due to the goggles that individuals wear during game play and that shield them from all visual stimuli of the physical environment. The fact that the difference in presence between the 2D and 3D was not significant, but the difference between 2D and VR was, is an indicator that individuals perceive 2D as quite different to VR, whereas the step from 2D to 3D is perceived as less substantial. Obviously, the VR environment offers more potential for immersion and the feeling of “being there” than the 3D environment. The finding that immersion and absorption between the 2D and 3D condition change to a lesser extent corroborates findings of Williams [ 22 ].

The level of arousal that players reported to have experienced while playing the game did not differ between the three technologies. This is an interesting finding. Even though presence and the feeling of “being in the game” is higher in the VR and 3D video games, the players’ level of arousal seems to be comparable, regardless of technology. A recent finding from the movie sector that has analyzed movie viewers’ reactions to a movie that was either aired in 2D or in 3D points into a similar direction. The study found that, even though viewers in the 3D condition rated their experience as more realistic than viewers in the 2D condition, no significant differences were found with regard to movie viewers’ emotional arousal [ 12 ].

With reference to the attitude towards the game, no group differences between the 2D, 3D and VR technology occurred. As was outlined in the theoretical portion of this paper, both, the 3D and the VR technology offer additional features that might contribute to a higher liking of the game. Yet, on the other side, the new technologies often come along with negative experiences during usage such as dizziness, headaches, or motion sickness (e.g. [ 36 , 43 , 44 ]). The post hoc study showed that the VR players also sensed dizziness and motion-sickness while playing the game. It appears that the possible disadvantages of the enhanced technology counterbalance the possible advantages with regard to attitude towards the game, at least in our video game.

As regards how brand placements which are commonly found in video games, are affected by the video game technology, our findings indicate that attitudes towards the brands placed in the video games are not influenced by the technology, but that memory of the brands is. In both, the main study as well as the post hoc study, subjects playing the 2D video game were more likely to recall and recognize brand placements compared to subjects who played the 3D or VR video game. In both studies, the memory was highest in the 2D group and was diminished by the additional technology in the 3D group and further reduced in the VR group.

Thus, the results from both studies clearly indicate that in terms of memory, brand placements suffer by an increase of the video game technology. We expect that performing the primary task of playing the game likely needs more cognitive resources (i.e. higher cognitive load) in the VR and the 3D video game as compared to the 2D video game, hence, these cognitive resources are no longer available for performing secondary tasks, such as processing and memorizing the brand placements in the game. Our post hoc study on cognitive load while playing the video game lends at least some support to our interpretation. The study showed that cognitive load was highest in the VR playing condition. However, cognitive load was lower in the 3D than in 2D condition, which was contrary to expectations (though differences were not significant). Obviously, additional research is needed. Our interpretation of the results points in the same direction as earlier research in the field of neuroscience, which indicates that the VR technology requires more cognitive capacity than the 3D and that 3D requires more than 2D technology (e.g. [ 41 , 86 , 88 – 90 ]). The findings that memory for the brand placements is lower in the VR than in the 3D condition indicate that the VR technology probably needs even more cognitive capacity for the primary task than the 3D technology. In the VR video game, the player has to deal additionally with a 3D-world in which the player can move through and experience the world individually. While immersed in a fictional world and believing him- or herself to be somewhere else, the player is likely even more focused on the game itself and has less cognitive capacity left to memorize the integrated brands.

Another explanation for the lower memory in the VR and 3D video playing condition might be the higher levels of dizziness and motion-sickness that players experienced during game play, as compared to players in the 2D video game. These negative physiological reactions might have distracted individuals from the brands in the game, leading to lower memory for brands in these conditions.

The fact that brand recall was relatively low in all three gaming conditions deserves some elaboration. While recognition only requires a simple familiarity decision about whether the stimulus has been encountered before, recall needs active reconstructing of information, i.e. remembering a fact, event or object that is not currently physically present and requires high mental efforts. Hence, it is not surprising that the brand recall values were much lower than the brand recognition values, over all three gaming conditions. The low brand recall indicates that players were distracted from the brand during the time of encoding, which is likely to have impaired subsequent retrieval success of the brand name. As was outlined in the theoretical part above, the players’ primary task was the successful playing of the game, rather than the encoding of the brand names they were confronted with during game play. Obviously, the primary task of the game play bound many cognitive resources that were consequently no longer available for memorizing the brand names. It is not uncommon, however, that brand recall is found to be low in advertising and placement studies, especially if the brands are not placed prominently enough. In a recent study of recall of brands that were placed in Hollywood movies, recall of brand names was also low (e.g., of 26 brands that appeared in one of the movies, movie watchers could only recall between 1 or 2 brands on average). In another movie, recall was even lower [ 91 ]. It is very likely that higher levels of brand prominence in a game are needed (e.g. the players in a car racing game drive a specific car brand, the players interact with a brand intensively, etc.) to increase brand recall.

Implications

The findings of our study are relevant for game developers, marketers and researchers. This study contributes to research and theory in various ways, since it empirically examines the evaluation of video games and the brand placements within the games, by directly comparing players’ reactions to a 2D, stereoscopic 3D and Head-Mounted Display VR video game. Our results indicate that 3D and VR lead to higher presence, i.e. to a pronounced feeling of “being in the game”, but game evaluation did not differ between the 2D, 3D, and VR version. This is an important finding, because it shows that an enhancement in technology to 3D or VR does not necessarily lead to a better game evaluation. The additional depth perception in the 3D environments and the increased presence lead to a higher cognitive load and also come along with negative aspects such as dizziness and eye fatigue that probably impair video game evaluation. Subjects who played the VR game in particular reported higher levels of dizziness and motion-sickness while playing the game. Hence, the fact that video game evaluation was not worse in the 2D condition as compared to the 3D and VR condition indicates that game developers can still be quite successful by continuing to offer “traditional” 2D video games. Game developers of 3D or VR video games need to be aware that the 3D and VR experiences can come along with negative feelings that could possibly harm game evaluation, so they need to develop video games in which the advantages of 3D or VR use clearly outweigh these associated disadvantages.

The research also offers implications for brand placements in 2D, 3D, or VR video games, which are important for both, marketers who want to promote their brands, as well as for game developers who often seek placements to contribute to meeting the production costs and as a means to enhance the perceived reality of the games. According to the results of both our studies, memory for the brands placed is negatively affected by enhancement in technology, i.e., in the VR and in the 3D video game, players remembered a lower number of the brands, as compared to the 2D video game, while attitudes towards the brands were unaffected by the technology. The finding that memory is lower with enhancement in technology while at the same time attitude towards the brands does not benefit is an important finding as it indicates that marketers may stick to 2D video games when they seek to promote their brand via placements in video games. In the VR and in the 3D condition it seems very likely that the player needs more resources for the game play, resources that are then no longer available for the processing of the brands placed in the movie.

Limitations and Directions for future research

There are some limitations within this study. First, we were able to demonstrate that attitudes towards the game did not differ between the three video game technologies and we assumed that possible advantages related to the new technology (such as higher immersion in the mediated world) are counterbalanced by possible disadvantages of the technologies (such as motion sickness). We measured dizziness and motion-sickness in a post hoc study, but not in the main study. Future studies might want to put a stronger focus on advantages and disadvantages that players associate with the new technologies. We used an easy to play “jump’n’run” game, which is a very common action game genre among players. Further research could examine the influence of 3D and VR video games in different video game genres (e.g. sports games such as football games or car racing games, ego shooter games or arcade) or different sectors (e.g. health area) with different product categories and try to find out the generalizability of the findings to other game types and kinds of games (e.g. video games on social media platforms or mobile devices).

Another field of research that certainly needs additional attention is the level of cognitive load needed to experience the different technologies. We have tried to analyze the cognitive load based on theoretical reasoning and by drawing upon extant studies and we measured cognitive load in a post hoc test. However, cognitive load was not measured in the main study. Future research may focus on cognitive load while subjects are playing a 2D, 3D and VR video game. Future research may also want to apply different measures of cognitive load, e.g. by self-reports of the players’ invested mental effort, by a different dual-task methodology (e.g. [ 62 , 114 , 115 ]), or by electroencephalography. We also did not measure the players’ visual attention, e.g. by using a reliable eye-tracking device. Moreover, of current interest, a longitudinal study would be interesting to ascertain whether the negative impact of the VR technology on brand memory is due to the newness of and lack of experience with the technology. Furthermore, future studies can analyze the moderating role of prior video game playing experience on the relationships of the variables.

It would also be interesting to investigate familiar brands in the placements instead of unfamiliar brands. According to previous research, players usually memorize brands more easily to which they have been exposed previously [ 116 , 117 ]. In our measurement, each brand that had appeared in the game was presented with three other options at the same time, two mock brands from the same product category and the option “others”, and recognition for the eight brands was measured one after the other. Even though this measurement helps to avoid overestimation of memory because participants cannot simply tick many alternatives in a long list of appearing brands and mock brands (if all brands were presented at the same time), a recognition sensitivity test (e.g. [ 107 ]) cannot be applied to our data and future studies may take this into consideration when designing the measurement.

Another limitation of this study is that, although we asked about prior game experience, subjects played the video game only once and did not repeat playing it. While playing the same video game several times, repeated exposure to the same brand placements might influence the brand memory differently in the different technologies [ 118 ]. Thus, in future studies, an experiment with repeated game playing could also be conducted.

One aspect that needs additional research is the role of presence while playing the video games. In our research, presence was conceptualized as the level of absorption that subjects perceived while playing the game. However, presence can be understood and conceptualized in different and more elaborated ways, too (e.g. [ 52 ]). As stated by Triberti and Riva [ 52 ], presence is defined as a cognitive process with the purpose “to locate the Self in a physical space or situation, based on the perceived possibility to act in it” [ 52 ]. This sense of presence allows the individual to adapt his / her own actions to the external environment [ 52 ]. According to Zahorik and Jenison [ 119 ], presence is “tantamount to successfully supported action in the environment ” ([ 119 ]; p. 87), where the environment can be virtual or real and can be near to or far from the person. The term “successfully supported action” means that the environment reacts to the person’s actions in a way that is “commensurate with the response that would be made by the real-world environment in which our perceptual systems have evolved” ([ 119 ]; p. 87), leading to high levels of presence [ 119 ]. Lombard and Ditton [ 53 ] define presence as perceptual illusion of non-mediation. The term “perceptual” refers to real time responses or feelings towards an object or entity in a person’s environment and involves real time responses from the individual’s affective and cognitive processing systems or the individual’s sensory system. “Illusion of non-mediation” basically indicates that a person fails to perceive the existence of a medium and the user reacts as if the medium were not in his / her environment.

According to Coelho et al. [ 120 ] presence can be differentiated between a psychological experience (inner presence) and a technological experience (media presence). Media presence, also referred to as a rationalist point of view, “describes the sense of presence as a function of the experience of a given medium” ([ 120 ]; p. 27 and [ 121 ]). This means that presence is a “perceptual illusion of non-mediation produced by means of the disappearance of the medium from the conscious attention of the subject” ([ 120 ]; p. 28). Inner presence, also referred to as an ecological perspective, is a view which describes presence as a “neuropsychological phenomenon, evolved from the interplay of our biological and cultural inheritance, whose goal is the control of the human activity” ([ 120 ]; p. 28). According to Gorini et al. [ 122 ] immersion and narrative are important factors to create an effective experience with virtual reality. Narratives can create a meaning for the experiences of the participants, influence the way participants will assess them, change the person’s emotional condition, contribute to generate emotional responses and hence reinforce the person’s sense of inner presence, while immersion can increase illusion and mainly contributes to increased media presence [ 122 ]. Future studies should aim at analyzing in detail how narration and immersion are affected by the three technologies and apply a more elaborate conceptualization of presence. Measurement of presence could also be carried out in different ways. In order to measure presence, it might for instance be fruitful if external observers monitored the extent to which people fail to respond to real time occurrences while being immersed in the virtual environment (e.g. [ 121 , 123 ]).

More research could also be carried out on the circumstances under which the different technologies may influence attitude towards the game or towards the brands placed in the games. In the study on games by Kerrebroeck et al. [ 76 ], playing the HMD VR game led to higher vividness than playing the 2D version. Furthermore, Kerrebroeck et al. showed that there is a positive influence of vividness and presence as a mediator influencing the attitude toward the ad and the attitude toward the brand. The impact of vividness on attitude toward the advertisement and in further consequence on the attitude toward the ad and the mediating role of presence on the attitude toward the brands between the three technologies should be examined in a follow-up study [ 76 ].

This study used a student sample. Even though they clearly represent a possible target group of the video game used in our study, it would be interesting to see how other target groups (e.g. adolescents) react to the three technologies. Additionally, further research might want to focus on the influence of player variables (e.g. gender, prior game experience) in more detail. Another interesting aspect would be to analyze how different levels of prominence of the brand placements affect brand memory and attitudes in the different technologies. Given that players devote more cognitive resources to the game play in a VR video game, it could well be that a brand that is highly integrated in the game play (much more than in the game used in this study) could benefit from the enhanced technology. Additional research is clearly needed.

Future studies could also focus on how the player perceives the product type and design and the positioning and size of the brands in the game within the three conditions. Different product types and designs may influence the player in different ways (e.g. perception of the brand or brand attitude). Also, the size of the brand (e.g. small, bigger) and the positioning of the brands (e.g. in the corner, in the middle, at the top or bottom of the screen) could impact the player’s perception of the brands. Furthermore, it would be interesting to examine the different impact between the three technologies depending on product type variables, such as product type-game congruity or the involvement.

Future research should also be devoted to ergonomic or perceptual aspects of the games. In our video game, in all three conditions players steered the avatar, hence players experienced the action by guiding and observing the avatar, as opposed to a first-person perspective in which the gamer sees the action with the eyes of the avatar. Future studies may analyze the impact of the gamer perspective (especially a first-person game) when playing games in different technologies.

Another interesting field of research might be the analysis of video games that include additional sensory stimulation, e.g. scent, vibration or airflow. According to previous research, for instance, olfactory senses can have a strong influence on the selection, processing and consolidation of information and on memory (e.g. [ 124 , 125 ]). Finally, whereas experiences with 2D and 3D are widespread, the VR technology is less distributed and individuals do not have much experience with it. This might have influenced the results, since subjects in the VR condition might have experienced distraction due to the novelty of the technology.

Supporting information

S1 appendix. experimental design..

https://doi.org/10.1371/journal.pone.0200724.s001

S2 Appendix. Questions and justification of items.

https://doi.org/10.1371/journal.pone.0200724.s002

S3 Appendix. Supplementary figures and tables.

https://doi.org/10.1371/journal.pone.0200724.s003

S1 Data. Data set of the main study.

https://doi.org/10.1371/journal.pone.0200724.s004

S2 Data. Data set of the post hoc study.

https://doi.org/10.1371/journal.pone.0200724.s005

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Competitive Video Game Exposure Increases Aggression Through Impulsivity in Chinese Adolescents: Evidence From a Multi-Method Study

• Empirical Research
• Published: 15 April 2024

Cite this article

• Shuai Chen   ORCID: orcid.org/0000-0002-4467-1274 1 ,
• Mingchen Wei 1 ,
• Xu Wang 1 ,
• Jinqian Liao 1 ,
• Jiayi Li 1 &
• Yanling Liu 1  

It is widely known controversies about the results of violent video game increase aggression. However, the role of competitive video games, has received less research attention, and the underlying mechanisms of their influence are unknown. This study aimed to expand the existing literature by systematically exploring the effects of competitive video game exposure on adolescent aggression and the mediating role of impulsivity. In so doing, three types of studies (collectively N  = 2919, mean age varied from 13.75 to 15.44 years, with a balanced gender) combining cross-sectional, experimental, and longitudinal approaches, were conducted. The findings consistently show that competitive video game exposure increased adolescents’ aggression and impulsivity. Also, impulsivity mediated the correlation and long-term effect of competitive video game exposure on aggression. However, the experimental study did not confirm the short-term mediating effect of impulsivity, which may be related to the type of aggression measured in the study. The results indicate that competitive video game exposure is an important antecedent factor for adolescent aggression, and impulsivity is the key underlying mechanism.

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Introduction

The impact of video games (especially violent ones) on aggression, which is defined as any behavior that intends to harm another individual (Anderson & Bushman, 2002 ), is a central issue for psychologists and the public (Anderson et al., 2010 ; Greitemeyer & Mugge, 2014 ; Prescott et al., 2018 ). Researchers have proposed that competition, which is as prevalent in video games as violence, also contributes to increased aggression (Dowsett & Jackson, 2019 ), and its effect size may even greater than violence (Adachi & Willoughby, 2011 ; Hawk & Ridge, 2021 ). Thus, the effects of competitive video game (video games in which players compete with an opponent which usually controlled by a distant human) exposure (CVGE) on aggression has become a new direction for the field (Adachi & Willoughby, 2016 ). However, the number of competitive video game exposure studies is much fewer and they often have important limitations which have not yet been addressed. Among these, some studies have indicated that competitive video game exposure increase aggression (Adachi & Willoughby, 2011 , 2016 ), while others have not (Lobel et al., 2017 ). Further, most of these studies only used single research methods which lack systematic multi-methods study, especially very few have been longitudinal. Finally, little is known about the mechanisms by which competitive video game exposure influences aggression. This research through three studies with diverse designs, comprehensively examine the effects of competitive video game exposure on Chinese adolescents’ aggression and the potential mediating role of impulsivity.

Competitive Video Game Exposure and Aggression

The metatheories of aggression such as the General Aggression Model (GAM) (Allen et al., 2018 ; Anderson & Bushman, 2002 , 2018 ) predict that competitive video game exposure should increase aggression as a situational factor. Based on GAM, studies have explored the effects of competitive video game exposure on aggression in terms of competitive context, competitive outcome, and level of competitiveness. In the context of multiplayer gaming, researchers have found that competitive contexts increase aggressive behavior in players in both violent and nonviolent games (Eden & Eshet-Alkalai, 2014 ; Sun & Liu, 2019 ). However, there are mixed findings regarding the effects of competitive contexts on aggressive cognition and affect. Some studies have found that competitive contexts increase players’ aggressive cognition (Schmierbach, 2010 ) and affect (Shafer, 2012 ; Williams & Clippinger, 2002 ). Other empirical studies have shown competitive contexts do not increase aggressive affect, and may even decrease it (Eastin, 2007 ; Mihan et al., 2015 ; Waddell & Peng, 2014 ). Playing competitive video games inevitably results in victory or defeat, studies have consistently found that being defeated increases a player’s frustration and negative affect, which in turn may increase aggressive behavior (Breuer et al., 2015 ; Shafer, 2012 ). Meanwhile, the effect of competitive failure on aggressive affect may be moderated by the competitiveness of the game (Dowsett & Jackson, 2019 ) and the game identification of the players (Griffiths et al., 2016 ).

As investigations in the area have increased, researchers have begun to focus on the competitiveness of video games. Early experimental studies found that even when controlling for the level of competitiveness, violent video games that reward violent actions still significantly increased aggression (Anderson & Carnagey, 2009 ; Carnagey & Anderson, 2005 ). However, these studies focused on the potential role of competitiveness without directly testing it. Subsequently, two experimental studies found that only competitiveness, not violence and difficulty, was the main video game characteristic that increased aggression (Adachi & Willoughby, 2011 ; Hawk & Ridge, 2021 ). A cross-sectional study of 1170 adolescents also found that exposure to highly competitive types of games was significantly positively associated with physical aggression (Dickmeis & Roe, 2019 ). However, another experimental study found that neither competitiveness nor violence had a significant effect on aggressive behavior in college students (Dowsett & Jackson, 2019 ).

The longitudinal studies have helped shed light on the long-term causal relationship between competitive video game exposure and aggression, although the current number of longitudinal studies is extremely small, and results are mixed. Two studies found a longitudinal association between competitive video games and aggression among adolescents and young adults (Adachi & Willoughby, 2013 , 2016 ). Conversely, another longitudinal study found that competitive gaming exposure reduced behaviors related to conduct disorders among children aged between 8 and 11 over a one-year period; they also viewed competitive gaming exposure as a pathway to benefit children’s social development (Lobel et al., 2019 ). In sum, although most studies have shown that competitive video game exposure increases aggression, there are still inconsistent findings, and they are all based on a single type of study that lacks comprehensive evidence from multi-method research.

Mediation of Impulsivity

To date, researchers have little examined the mechanisms of the effects of competitive video game exposure on aggression. The GAM (Allen et al., 2018 ; Anderson & Bushman, 2002 , 2018 ) suggests that the psychological processes that underlie this link between exposure to violent media and aggression can be divided into short- and long-term processes. The “competition hypothesis” (Carnagey & Anderson, 2005 ) holds that competitive video game exposure may increases aggression by similar mechanisms as violent media. Specifically, short-term competitive video game exposure could activates internal states (cognition, affects, and arousal) that influence appraisal decision processes (including immediate appraisal and reappraisal), which in turn result in impulsive or thoughtful action (aggressive or nonaggressive behavior). Repeated competitive video game exposure will affects the aggression knowledge structures, brain structure, and function, which in turn leads to increase in aggressive personality. Recently, the extended GAM proposed that executive function-impulsivity deficits and peer group shifts are the new paths for media increased aggression (Anderson & Bushman, 2018 ).

Studies have examined the mechanisms of competitive video game exposure on aggression from the affective (Adachi & Willoughby, 2016 ; Breuer et al., 2015 ; Sun et al., 2023 ) and cognitive path (Sun et al., 2023 ), however, the traditional pathway is still insufficient to fully explain this effect (Anderson & Bushman, 2018 ). Based on the emerging “executive function-impulsivity deficit” path, which has not received much attention, the present study proposes that the impulsivity may play another key mechanism in the effects of competitive video game exposure on aggression. Specifically, the immediate impulsive action which is defined as an action that is poorly conceived, taken without much forethought, and expressed prematurely (Guzulaitis & Palmer, 2023 ), could serves as important process for appraisal and decisions which mediate the short-term competitive video game exposure effect. The impulsive personality which defined as a predisposition toward rapid, unplanned reactions to internal or external stimuli without regard to the negative consequences either to the impulsive individual or to others (Moeller et al., 2001 ), could serves as an aggressive knowledge structure and mediate the long-term competitive video game exposure effect.

Three areas of research also provide evidence for the mediating role of impulsivity. First, previous studies support the relationship between competitive video game exposure and impulsivity. Some cross-sectional studies found that online gaming addiction was positively associated with individual impulsivity (Fumero et al., 2020 ; Kim et al., 2021 ; Yu et al., 2021 ), and competition is strongly associated with gaming addiction (Harris et al., 2022 ). Meanwhile, the experimental studies have found that highly competitive racing games increase players’ impulsive risk-taking behavior (Deng et al., 2015 , 2017 ; Fischer et al., 2009 ), which can be used as the indirect evidence. Second, the meta-analytic results (Bresin, 2019 ; Moore et al., 2022 ) have suggested that highly impulsive individuals typically exhibit more aggression. Third, impulsivity can mediate the relationship between violent media (including violent video games) and aggressive behavior (Swing & Anderson, 2014 ; Zhao et al., 2021 ). Thus, based on the theories and empirical evidence, it appears that competitive video game exposure may lead players to develop impulsive response patterns and show more aggression. However, no study has explored this association. The present study fills this gap in the literature.

Current Study

The effect of competitive video game exposure on aggression is an emerging scientific question, however, the current literature remains limited by inconsistent results and unclear underlying mechanisms. The present study examined the effects of competitive video game exposure on aggression, and the mediating role of impulsivity. This study encompasses two primary research hypotheses. The competitive video game exposure increases adolescent aggression (Hypothesis 1). Impulsivity mediate the effects of competitive video game exposure on adolescent aggression (Hypothesis 2). The current study tests these hypotheses by a series of three studies combining correlational, experimental, and longitudinal methods. The current study builds on a Preliminary Study that had found a positive correlation between competitive video game exposure and aggression, as well as a mediating role for impulsivity (see the Electronic Supplementary Materials). Study 1 used an experimental approach to explore the short-term effects of competitive video game exposure on adolescent aggression and the mediating role of immediate impulsive action. Study 2 was a one-year, three-wave follow-up study examining the long-term effects of competitive video game exposure on the development of adolescent aggression and the mediating role of impulsive personality. These three sequential and mutually supportive research designs provide a comprehensive and rigorous test addressing the research questions.

Participants

Referring to Hou et al. ( 2021 ), and on the basis of a power analysis of G*Power 3.1.9.7 (Faul et al., 2009 ), this study estimated that a sample size of 44 would be needed to provide 95% statistical power to achieve a medium effect size ( f  = 0.25) using within-factors repeated measures ANOVA (group = 2, measurements = 3, correlation among repeated measure = 0.5) and an α of 0.05. Assuming a sample attrition rate of about 10% and reference to a previous study (Yin et al., 2022 ), 62 adolescent participants were recruited from a high school in Sichuan province in China; 29 participants (11 boys, 18 girls) were in the competitive condition, and 30 participants (11 boys, 19 girls) were in the single-player condition (three participants were excluded due to invalid data) ranging in age from 15 to 18 ( M  = 15.44, SD  = 0.62). All participants and their guardians agreed to participate in the experiment and received gifts.

Video game and manipulation

The video game, TypeRacer: School Edition, a simple typing game used to increase one’s typing speed through a simulated multi-player car game, was used in the study. In TypeRacer, players accurately type a given text passage and a racing avatar representing the player’s advances on a track until it reaches the finish line. When a player makes a mistake, the car stops and the text turns red. At any time, players can see their typing speed by a displayed number of WPM (words per minute). The game allows players to play not only alone but also in typing matches with others, which provides clear conditions for playing alone or in competition. This study set the typed content to meaningless strings of 60 letters (e.g., “t f d v n k p f s v m q …”), thus controlling difficulty and content effects (e.g., violence and prosocial).

In the single-player condition, participants completed five rounds of the typing game after practicing for one round, after which their typing speed and correctness were recorded. In the competitive condition, two participants advanced their cars by typing; the first to reach the finish line wins. At this point, they can see each other’s progress and speed through the same interface. Participants were told that those who won more times in five rounds of the game would receive a better gift. They then began playing after one round of practice. Previous study has used this video game and manipulation to test the effects of CVGE (Sepehr & Head, 2018 ).

• Impulsivity

The Social Information Sampling Task was used to measure impulsivity (Brennan & Baskin-Sommers, 2019 ) to measure immediate impulsive action post gameplay. Participants were shown information about a person who engaged in a range of behaviors and instructed to judge whether the person was nasty (hostile judgment) or nice (benign judgment) based on the behaviors. Behavioral stimuli used the following construction: verb + object. The verb either had a positive value (consistent with a “nice” behavior, e.g., “praised others”) or a negative value (consistent with a “nasty” behavior, e.g., “scolded others”). This study initially selected 30 positive verbs and 30 negative verbs from the Chinese Affective Word System (Yao et al., 2017 ); then recruited 57 secondary school students (27 middle school students, 29 boy, M age  = 14.89, SD  = 1.45) to rate vocabulary attributes on a nine-point scale. Finally, 20 positively and 20 negatively valued verbs were used that differed significantly in valence ( p  < 0.001) but did not differ significantly in readability, arousal, and extremeness of valence (|score − mean|). See Table S1 for detailed results.

Programming and Presenting Stimuli with E-prime 2.0, after a 1 s fixation cross displayed in the center of the screen, 25 gray boxes (i.e., showed no behavioral description) were presented. When participants clicked a box, the behavioral description inside the box was revealed and remained visible for the duration of the trial. Participants decided for themselves how many boxes to open until they could make a final decision (clicking one of two panels labeled “nasty” and “nice” at the bottom of the screen). Each trial lasted 50 s. If participants did not respond within 50 s, the trial ended and the next trial was conducted. If the participants responded within 50 s, they waited to proceed to the next trial. The task contained two practice trials and ten experimental trials. In the experimental trial, 25 boxes contained a ratio of 15:10 (five trials) or 10:15 (five trials) in terms of positive versus negative behaviors. The average number of boxes not opened was used as an indicator of impulsivity.

The Tangram Task was used to measure aggression post gameplay (Saleem et al., 2015 ). Participants were told that the researcher would be using a tangram to assess other students in the future. Participants were invited to choose 11 out of 30 puzzles (10 easy, 10 medium, and 10 difficult) for a student who did not exist. Participants were told that if the “student” completed at least 10 of the 11 puzzles within 10 min, the “student” would win a gift; otherwise, the student would be considered to have failed the test. Thus, participants could hurt/help the student by assigning difficult/easy puzzles. Hurting scores (the number of difficult puzzles minus 1) and difference scores (the number of difficult puzzles minus the number of easy puzzles) were used as indicators of aggression (Saleem et al., 2015 ).

Subjective gaming experience

Two items (Adachi & Willoughby, 2011 ) (“to what extent did you feel like you were competing with your opponents,” and “to what extent did this video game involve competition,” 1 =  very low to 7 =  very high , Cronbach’s α  = 0.83) were used to assess the level of competition in the game, and the mean score was used to test the effectiveness of competitive manipulation. Similarly, participants also rated the game on a seven-point scale of enjoyability, frustration, difficulty, excitement, action, and violence (e.g., “to what extent did this video game involve violence”) (Anderson & Dill, 2000 ).

Demographics

A series of basic questionnaires was used to assess gender, age, and typing skill (1 =  very bad to 7 =  very good ).

Competitive and violent video game experience

Participants listed their three favorite games, and rated how frequently they played each game (1 =  sometimes to 5 =  very often ), and rated how competitive and violent each game was (1 =  not at all to 5 =  very much ) (Dowsett, 2017 ; Teng et al., 2019 ). Competitive (Cronbach’s α  = 0.83) and violent (Cronbach’s α  = 0.90) video game experience scores were computed by multiplying the frequency ratings by competition and violence ratings, and averaged the three game scores.

Personality trait

The Brief Aggression Questionnaire (Webster et al., 2014 ) was used to measure trait aggression, which contains 12 items (e.g., “If somebody hits me, I hit back”) based on a five-point scale (1 =  strongly disagree to 5 =  strongly agree ), Cronbach’s α  = 0.81. The Brief Barratt Impulsiveness Scale (Morean et al., 2014 ) was used to measure trait impulsivity, which contains eight items (e.g., “I say things without thinking”) based on a four-point scale (1 =  never , 4 =  always ), Cronbach’s α  = 0.86. The Competitive Personality Scale (Xie et al., 2006 ) was used to measure trait competitiveness, which included ten items (i.e., “It bothers me if others behave better than me”) using a five-point scale (1 =  strongly disagree to 5 =  strongly agree ), Cronbach’s α  = 0.77.

Participants were told that they would participate in three unrelated psychological tests involving personality, reaction time, and judgment. First, participants completed an informed consent form and basic questionnaire which including information on demographics, video game experience, and personality trait. Participants were then randomly allocated into competitive or single-player conditions separately by gender and play the video game. At the end of gameplay, participants sequentially completed the Social Information Sampling Task, Tangram Task, and the subjective gaming experience questionnaire. Then, participants were probed for suspicion with two open-ended questions, and no participants indicated any suspicion about the real nature of the study. Finally, the participants were informed of the true purpose of the experiment, thanked, and dismissed.

Manipulation checks

The competitive condition ( M  = 3.98, SD  = 1.20) produced significantly higher competition scores than the single-player condition ( M  = 3.24, SD  = 1.51), t (57) = 2.09, p  = 0.041, d  = 0.54, and, all other video game characteristics were the same. There were also no significant differences in personality traits, gaming experience, and typing levels between the two groups of participants (see Table S2 ). These results indicate the game manipulation was valid and that the game and participants’ characteristics would not interfere with the results of the study.

Effects of CVGE on aggression and impulsivity

As Table 1 shows, an ANOVA revealed a significant difference in aggression and impulsivity across video game conditions. The competitive condition had a significantly higher hurting score ( F (1, 57) = 4.56, p  = 0.037, η p 2  = 0.07), difference score ( F (1, 57) = 5.32, p  = 0.025, η p 2  = 0.09), and impulsivity score ( F (1, 57) = 4.95, p  = 0.030, η p 2  = 0.08) than the single-player condition. These results indicate that short CVGE significantly increased the participant’s aggression and impulsivity with moderate effect sizes.

The mediating role of impulsivity

A structural equation model was developed using Mplus 8.3 to test the mediating role of immediate impulsive action in the short-term effect of competitive video game exposure (0 = single-player condition, 1 = competitive condition) on aggression. The maximum likelihood approach was used, and the bootstrapping method with 1000 samples at 95% confidence intervals was used to examine indirect effects. The model fitted as a saturated model and the results shown in Fig. 1 . CVGE positively predicted impulsivity ( β  = 0.28, p  = 0.024), and aggression ( β hurting score  = 0.29, p  = 0.024; β difference score  = 0.30, p  = 0.0029), but impulsivity did not predict aggression ( β hurting score  = −0.05, p  = 0.691; β difference score  = −0.02, p  = 0.853). The indirect effect of CVGE on aggression via impulsivity ( β hurting score  = −0.01, SE = 0.04, 95% CI [−0.079, 0.055]; β difference score  = −0.01, SE = 0.04, 95% CI [−0.069, 0.070]) was not significant.

Short-term mediation model of CVGE and aggression. * p  < 0.05, *** p < 0.001

The results of Study 1 partially support the research hypotheses. Study 1 revealed that playing competitive video games in the laboratory increased adolescents’ aggression and impulsivity, consistent with previous research on the short-term effects of CVGE on aggression (Adachi & Willoughby, 2011 ; Sun & Liu, 2019 ) and risk-taking inclination (Deng et al., 2015 ; Fischer et al., 2009 ). However, contrary to expectations, this study did not find a significant mediating effect of impulsivity, and this result will be explained in the general discussion. Given the inability of the experimental design to provide information on longitudinal relationships, Study 2 was conducted to provide evidence of long-term causation.

Participants were 1296 secondary school students at four schools in Sichuan province who were surveyed three times (6-month intervals) from October 2021 to December 2022. In the first assessment (T1), the participants ( M age  = 13.73, SD  = 1.49) were in the seventh grade (673, 51.93%) and tenth grade (623, 48.07%), 637 (49.15%) boys, and 659 girls. At T2, 1187 (91.59%) participants remained, and at T3, 1059 (81.71%) participants remained.

The results of Little’s Missing Completely at Random (MCAR) test (Little, 1988 ) for all research variables at three times indicated the missing data was completely random ( χ 2 (115) = 133.13, p  = 0.119). Meanwhile, this study created an indicator variable (1 = missing, 0 = complete) to test whether the missing data were conditional on any of the research variables in this study. The results of t test were significant for T1 impulsivity ( t (1294) = 3.12, p  = 0.002), T1 ( t (1294) = 3.43, p  = 0.001), and T2 ( t (1294) = 2.970, p  = 0.003) aggression, suggesting that impulsivity and aggression were missing at random (MAR), and CVGE was MCAR. Given that both MCAR and MAR occur in the main variables, the final sample included all 1296 participants, and full information maximum likelihood was used to address the missing data.

• Competitive video game exposure

To measure CVGE, participants listed their three favorite games, and rated how frequently they played each game (1 =  sometimes to 5 =  very often ), and rated how competitive each game was (1 =  not at all to 5 =  very much ). This self-report measure has been shown to be both reliable and valid (Fikkers et al., 2017 ), and successfully used in many previous studies (Dowsett, 2017 ; Teng et al., 2019 ). Game competition scores were computed by multiplying the competition ratings by the frequency ratings. The competition scores for the three video games were used as measured variables for a latent variable titled “competitive video game exposure.” For those participants who reported they did not play video games, their scores were recorded as “0” (Prot et al., 2014 ). The reliability of the measure of CVGE in this study was good across the three times (Cronbach’s α  = 0.89, 0.90, and 0.91, respectively).

Impulsivity was measured using the Chinese Version (Luo et al., 2020 ) of the Brief Barratt Impulsiveness Scale (Morean et al., 2014 ), which contains eight items (e.g., “I say things without thinking”) based on a four-point scale (1 =  never , 4 =  always ) measuring two dimensions of impulsivity: poor self-regulation and impulsive behavior. In this study, the measure of impulsivity was internally consistent across the three times (Cronbach’s α  = 0.81, 0.81, and 0.82, respectively).

Aggression was assessed with the Brief Aggression Questionnaire (Webster et al., 2014 ), which contains 12 items (e.g., “If somebody hits me, I hit back”) based on a five-point scale (1 =  strongly disagree to 5 =  strongly agree ) to measure four dimensions of trait aggressiveness: physical aggression, verbal aggression, anger, and hostility. In this study, the measure of aggression was internally consistent across the three times (Cronbach’s α  = 0.76, 0.77, and 0.78, respectively).

Data analysis

SPSS25.0 was used to compute missing data analyses, descriptive statistics, Pearson correlations, and repeated measures of ANOVA. Mplus 8.3 was adopted for longitudinal measurement invariance and the cross-lagged panel models, and the maximum likelihood approach was used. The cross-lagged panel Model 1 (M1) was established to examine the long-term effect of CVGE on aggression, and the cross-lagged panel Model 2 (M2) was established to examine the longitudinal mediating role of impulsive personality. According to the previous research (Orth et al., 2021 ), if the constraints do not significantly reduce the model fit, structural coefficients (autoregressive effects and cross-lagged effects) should be constrained to be equivalent across time. Therefore, this study has tested unconstrained and constrained models for Model 1 and Model 2, respectively.

The following indices were used to evaluate model adequacy: chi-square/degrees of freedom ratio ( χ 2 / df ), the Comparative Fit Index (CFI), the Tucker–Lewis Index (TLI), the Root Mean Square Error of Approximation (RMSEA), and the Standardized Root Mean Square Residual (SRMR). When χ 2 / df  ≤ 5, CFI, and TLI were ≥ 0.90, RMSEA and SRMR ≤ 0.08, the model was considered indicative of a good fit (Kline, 2015 ). The ΔCFI was ≤ 0.01 and the ΔRMSEA was ≤ 0.015 indicating the fit between the models was equivalent (Chen, 2008 ; Cheung & Rensvold, 2002 ). The bootstrapping method with 5000 samples computed at the 95% confidence interval (CI) was used to examine indirect effects. The mediating effect was significant if the 95% CI did not include zero.

Preliminary analyses

Table 2 shows the means, standard deviations, and correlations for study variables at all three times, indicating that they were positively correlated. Repeated measures ANOVA results showed that T2 CVGE was significantly lower than T3 ( p  = 0.013), T2 impulsivity was significantly higher than T1 and T3 ( p  < 0.001), and T1 aggression was significantly higher than in T2 and T3 ( p  < 0.001). The measures of the three variables and the total measurement model all established scalar invariance (see Table S3 ), indicating invariance across time for the research variables.

Main analyses

After controlling for age and gender, the cross-lagged panel model of CVGE and aggression (M1) were examined. The results revealed that the unconstrained and constrained models fit the data well, and the relative fit indicated that the two models did not differ significantly (Table 3 ), suggesting that the patterns of associations among the variables were consistent across the three times. Thus, further interpretations were based on the constrained model (Fig. 2 ). Previous CVGE predicted higher aggression over time ( β  = 0.05, p  = 0.002), when controlling for previous aggression. Previous aggression also predicted higher CVGE over time ( β  = 0.06, p  = 0.001).

Constrained cross-lagged panel model for CVGE and aggression. Path coefficients were standardized. Dashed lines are nonsignificant. Indicator variables, within-time correlations, and residuals are not shown. ** p  < 0.01, *** p  < 0.001

Based on previous research (Adachi & Willoughby, 2016 ), the cross-lagged panel models (M2) were constructed to examine longitudinal mediation of impulsivity between CVGE and aggression after controlling for age and gender. Similarly, the unconstrained and constrained models fit the data well, and the relative fit indicated that the two models did not differ significantly (see Table 3 ). Based on the constrained model (Fig. 3 ), T1 CVGE predicted T2 impulsivity ( β  = 0.03, p  = 0.044), and T2 impulsivity predicted T3 aggression ( β  = 0.12, p  < 0.001). The indirect effect of T1 CVGE on T3 aggression through T2 impulsivity was significant ( β  = 0.004, SE = 0.002, 95% CI = [0.001, 0.007]). These results suggest that impulsivity played a mediating role in the longitudinal effects of CVGE on aggression.

Constrained cross-lagged panel mediation model for CVGE and aggression. Path coefficients were standardized. Dashed lines are nonsignificant. Indicator variables, within-time correlations, and residuals are not shown. * p  < 0.05, ** p  < 0.01, *** p  < 0.001

Additional analyses

Some additional analyses were conducted to explore whether there were other longitudinal and mediating relationships between the study variables (see Table S4 and Figs. S1 – S5 ). The results showed a significant indirect effect for T2 aggression in the effect of T1 CVGE on T3 impulsivity ( β  = 0.006, SE = 0.002, 95% CI = [0.003, 0.010]). This result suggests that CVGE may have a pernicious cyclical effect on impulsivity and aggression, which consistent with the bidirectional relationship between impulsivity and aggression which found in previous longitudinal study (MacDonell & Willoughby, 2020 ). Otherwise, no significant longitudinal mediating effects were found in other models.

The results from Study 2 fully support the research hypotheses. First, Study 2 reveals the long-term effect of CVGE on adolescents’ aggression. Second, the results demonstrate that impulsivity plays a longitudinal mediating role between CVGE and adolescent aggression. In sum, these results show that CVGE has a long-term effect on adolescent aggression and the mechanistic role of impulsivity.

General Discussion

Whether and how exposure to competitive video game increases aggression is an important issue for researchers. However, very little is known about this. Based on the GAM, the current study used a series of three studies that examined the short- and long-term effects of competitive video game exposure on adolescent aggression and the role of impulsivity as a mediator. Collectively, the findings from the three studies provide converging support, showing that highly competitive video game exposure should increases adolescent aggression. The findings presented also constitute some of the first evidence to consider impulsivity as a key psychological mechanism underlying the competitive video game exposure effects.

The Effects of Competitive Video Game Exposure on Adolescent Aggression

Consistent with previous correlational (Dickmeis & Roe, 2019 ), experimental (Sun et al., 2023 ), and longitudinal findings (Adachi & Willoughby, 2013 , 2016 ), the results of current study show that competitive video game exposure has a correlational relationship, and short- and long-term effects on adolescent aggression. From a competitive perspective, Social Interdependence Theory (Johnson, 2003 ) states that when people share a common goal, they jointly influence each other, resulting in two types of interdependence: cooperation and competition. In competitive interdependence, individuals use a variety of methods to thwart each other to achieve their goals. When competing in video games, players acquire resources and ultimately win by engaging in direct and intense confrontation with each other. As a result, they are then likely to harm others for personal gain, thus, exhibiting higher levels of aggression (Gao et al., 2021 ). Meanwhile, competitive interdependence eventually manifests itself in obstructive interaction patterns, which can lead to negative interpersonal relationships (Verheijen et al., 2019 ), which in turn produce aggressive behavior.

From the perspective of aggression, first, players’ goal behaviors are impeded and threatened by opponents, even leading to failure. Thus, competition in games can elicit a range of negative emotions (e.g., hostility, frustration) (Breuer et al., 2015 ; Dowsett & Jackson, 2019 ; Shafer, 2012 ) typically frustration, which in turn predisposes them to the display of highly aggressive behaviors (Frustration Aggression Hypothesis) (Berkowitz, 1989 ). Second, competition is an important source of immersion and enjoyment for players (Chen et al., 2022 ; Sepehr & Head, 2018 ). Players typically have higher levels of arousal during competitive play (Adachi & Willoughby, 2011 ), which predisposes them to be in a state of readiness for aggression (Excitation Transfer Theory) (Zillmann, 1988 ). Finally, since individuals often conceptualize competition as aggression early in life, it is likely that when they re-encounter competitive environments, they will generate aggressive behavior by creating, activating, or diffusing aggressive cognitions or memory networks (Anderson & Morrow, 1995 ). Short-term competitive video game exposure can significantly increase players’ aggressive cognition (Schmierbach, 2010 ), and repeated competitive video game exposure may instill the notion that aggression is an appropriate way to deal with frustration and arousal (Adachi & Willoughby, 2013 ), which in turn can lead to high levels of aggression (cognition path of GAM) (Allen et al., 2018 ; Anderson & Bushman, 2002 , 2018 ).

The Mediating Role of Impulsivity

As expected, this study found that the underlying mechanism for this association is impulsivity. Results from Preliminary Study and Study 2 indicate a correlational and longitudinal mediating role for impulsivity between competitive video game exposure and adolescent aggression. In other words, playing competitive video games can lead to a decrease in executive functioning and self-control, and a lack of control over impulsive responses, which in turn increases aggression. These results are consistent with the GAM (Anderson & Bushman, 2018 ), and other empirical findings which found impulsivity mediated the effects of violent media on aggression (Swing & Anderson, 2014 ; Zhao et al., 2021 ).

On the one hand, adolescents who play highly competitive video games have higher impulsivity. According to Social Learning Theory (Bandura, 2001 ), players learn behavioral experience from competitive video games, which in turn affects their reality. In competitive video games, players must react quickly to gain more resources and win; meanwhile, given the virtual nature of the game, players do not need to think about the negative consequences of their rapid reactive behavior. Thus, prolonged exposure to such situations may cause individuals to learn to respond to real-life stimuli with an irrational pattern of quick, unplanned, and unthinking consequences, which defines impulsivity. On the other hand, impulsive adolescents often exhibit higher aggression. Theoretical formulations of Social Information Processing (Crick & Dodge, 1994 ; Fontaine & Dodge, 2006 ) have emphasized impulsive cognitive and reactive patterns as important risk factors for aggression. In specific social situations, impulsive individuals are prone to make inappropriate attributions (e.g., hostile attributions) without adequate information gathering and assessment, thereby activating their aggression schema, and they are also less likely to consider the negative consequences of aggression, which increases the likelihood of aggressive behavior (Barlett & Anderson, 2011 ). In sum, adolescents may learn an impulsive tendency to react quickly and recklessly in the heat of competition, which in turn leads to an increase in aggression manifested by a state of irritability in real life.

The results of Study 1 also suggested that short-term exposure to competitive video games increased impulsivity, which is consistent with previous experimental studies (Deng et al., 2015 , 2017 ; Fischer et al., 2009 ). Such impulsivity can be explained by ego depletion. The strength model of self-control (Baumeister et al., 2007 ) states that self-control is a limited resource, and that acts of self-control cause short-term impairments in subsequent self-control. The proximal process of GAM (Anderson & Bushman, 2002 , 2018 ) also indicates that the activation of internal states affects subsequent appraisal and decision processes. Players have higher immersion and more psychological resources to invest in competitive play (Adachi & Willoughby, 2011 ; Chen et al., 2022 ; Sepehr & Head, 2018 ), ultimately leading to impulsive action due to relative resource depletion during immediate appraisal.

However, contrary to expectations, Study 1 did not find a mediating role for impulsivity in the short-term effect of competitive video game exposure on aggression because the path coefficient from impulsivity to aggression was not significant. This may be related to the type of aggression measured in Study 1. Based on motives, aggression is categorized as either reactive or proactive, which differ in their causes and functions (Dodge & Coie, 1987 ; Wrangham, 2018 ). Impulsivity affects individuals’ aggression more in terms of reactive than proactive (Vaughan et al., 2023 ) because impulsive individuals typically exhibit deficits for cue encoding and hostile attribution bias, which in turn is manifested in reactive aggression. In contrast, the cognitive processing problem in proactive aggression is primarily a higher positive outcome expectancy for aggressive behavior, rather than impulsivity and attention deficits (Arsenio et al., 2009 ; Dodge et al., 1997 ). The tangram task used in Study 1 in which participants were asked to solve “puzzles” (for others) measures proactive aggression by nature and therefore has less to do with impulsivity. The empirical results support this interpretation, which reveals that impulsivity only mediated the effects of violent media and video games on reactive aggression, not proactive aggression among American college students (Swing & Anderson, 2014 ) and Chinese children (Zhao et al., 2021 ). Whether the mediating role of impulsivity can be accentuated when aggression is measured using a reactive aggression orientation paradigm should be examined in future studies. In addition, differences in impulsivity measurement may have contributed to the inconsistent results. A review and meta-analysis (Sharma et al., 2014 ) noted that the impulsivity constructs of laboratory task and self-reported measures were not entirely consistent and that the correlation between the scores of two measures is very low. Future study should consider potential differences across impulsivity measures and dimensions.

Theoretical and Practical Implications

This study has important theoretical and practical implications. It is the first study to use a combination of methods to explore the effects and underlying mechanisms of competitive video game exposure on adolescent aggression providing evidence of greater ecological validity and support for causality. Based on mutually supportive research, this study provides consistent evidence that competitive video game exposure increases aggression, responding to the potential controversy surrounding the findings. The study innovatively introduces notions of impulsivity to reveal the key psychological mechanisms by which competitive video game exposure influences aggression, which not only fills a research gap but also extends and emphasizes the new perspectives on theories of aggression such as the GAM (Anderson & Bushman, 2018 ).

Practically, the current study provides guidance to educators and governments urging them to reduce adolescents’ aggression. First, educators need to emphasize and monitor adolescents’ exposure to games with highly competitive elements to avoid adverse effects. The government should regulate the classification of competitive video games in the same way that grades levels of violence to restrict minors. Second, educators should recognize the role of impulsivity to take measures to reduce aggression in adolescents. For example, educators can teach adolescents to engage in mindfulness training to alleviate impulsive drives and increase impulsive control (Vekety et al., 2021 ).

Limitations and Future Research

Despite the strengths of this study, there are several limitations. First, this study failed to achieve consistent results regarding the mediating role of impulsivity. Future research should examine the effects of competitive video game exposure on different types of aggression and impulsivity to validate the interpretations. Second, the findings are limited to the Chinese adolescent population; thus, future research should be extended to other ages (e.g., children and adults) and regional groups (e.g., Western countries). For example, Chinese adolescents growing up in highly competitive school environments may be more sensitive to competition in video games, resulting in greater competitive video game exposure effects. Third, the use of self-reporting methods in Preliminary Study and Study 2 may have been influenced by social praiseworthiness; thus, multidimensional data such as daily behavioral indicators (game behavior and time recorded by software) and reports from others (teachers, parents, and peers) should be considered. Fourth, the game material for Study 1 was limited to one game, and although the chosen game was able to circumvent the interference of extraneous factors well, the use of additional, more generalized games is necessary to validate the results. Finally, the current study focused on only one mediator (impulsivity). Future research should consider the relative magnitude and order of the effects of multiple mediating paths (e.g., affects, cognitions, impulsive, etc.) to fully explain the processes influencing competitive video game exposure on aggression. For example, some studies have shown that cognitive paths play a greater mediating role than affective ones (Anderson et al., 2017 ; Gentile et al., 2014 ). Future research should also examine which individual (e.g., competitive personality) and game variables (e.g., cooperation, video game scenario) moderate the effects of competitive video game exposure on aggression.

Previous studies have examined the relationship between competitive video game exposure and aggression, but the findings have been mixed. Furthermore, the mechanisms underlying the relationship have been largely unexplored. The current study aimed to extend prior scholarship by conducting a series of three studies with diverse designs and systematically examining the short- and long-term effects of competitive video game exposure on adolescent aggression and the mediating role of impulsivity. The findings first provide triangulated evidence indicating that competitive video game exposure increases aggression. And, the results showed that impulsivity is a mechanism of this link, deepening theoretical insights. Specifically, adolescents may learn to behave in a fast, reckless manner during competitive gaming, which makes them prone to react aggressively in the real world. These findings underscore the need for governments and the public to consider the influence of competitive factors that are prevalent in video games on adolescents’ personality and behavioral development.

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Acknowledgements

We want to thank the students who participated, thank every teacher for their hard work on collecting data. We also sincerely thank the editor and autonomous reviewers for their valuable comments.

This work was supported by the Humanities and Social Science Fund of Ministry of Education of China [grant number 23XJA190002].

The datasets generated and/or analyzed during the current study are not publicly available but are available from the corresponding author on reasonable request.

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S.C. conceived of the study, conducted data collection and statistical analyses, wrote and revised the draft of the manuscript; M.C.W. participated in the data collection and analysis, and helped write and revise the draft of the manuscript; X.W. assisted in the data collection and writing; J.Q.L. assisted in the data collection and analyses; J.Y.L. assisted in the data collection and analyses; Y.L.L. supervised this study, organized the data collection, and revised the manuscript. All authors read and approved the final manuscript.

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Chen, S., Wei, M., Wang, X. et al. Competitive Video Game Exposure Increases Aggression Through Impulsivity in Chinese Adolescents: Evidence From a Multi-Method Study. J. Youth Adolescence (2024). https://doi.org/10.1007/s10964-024-01973-0

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New U-M study explores video game addiction rates

By J.T. Godfrey Stephen M. Ross School of Business

Using data from a top video game streaming service, researchers at the Stephen M. Ross School of Business are challenging preconceived notions of high addiction rates in the video game-playing community.

Puneet Manchanda, Isadore and Leon Winkelman Professor of Retail Marketing and professor of marketing, and Ph.D. student Bruno Castelo Branco are building off Manchanda’s previous research on addiction to explore video-game addiction using data on actual gaming behavior in the real world.

• Is Video Gaming Addictive?: An Empirical Analysis (submitted for publication)

Previous research on the addiction rate of video games has focused on individual representations of addiction through surveys and questionnaires. Rather than looking at just time played as a key indicator for addiction, Manchanda and Branco explored the rates of consumption — whether playing video games makes a person play even more.

In their exploration of data from the computer game streaming platform Steam, Manchanda and Branco were able to look at consumption and addictive behavior objectively.

“To consider a person addicted, our definition is that playing video games makes you want to play video games even more,” Branco said. “Our methodological approach allows us to test each individual’s behavior separately and come up with a share of people with addiction within the gamer population.”

Using this definition, they found that, depending on the type of video game, 14.6%-18.3% of their sample of 13,400 video gamers on Steam show signs of addictive consumption. Manchanda and Branco noted this may be a surprising statistic depending on an individual’s relationship to the video game industry.

“If I share this with some parents, they think, ‘It’s way too low, right?’ But if I share this with gamers, they think, ‘Oh, it’s ridiculously high. Your definition of addiction must be wrong,’” Manchanda said. “I found a similar situation when I started researching gambling. First, (advocates) have to agree with the number. The problem, then, is the valence around the number. Is it a positive or a negative? And that depends on your worldview, experience, who you are, and whether you are a video game player.”

One particularly impactful finding was the negligible differences in the rates of addiction among types of video games. There are many critics of the new style of ‘battle royale’ games, such as Fortnite, Apex Legends, and Valorant. Casual observers believe that the games are intentionally designed to increase addiction with bright animation and increased free access.

Manchanda and Branco said that despite claims that some video games are purposefully designed to be addictive, they found that game characteristics are not strong predictors of addiction status.

“We look at the nuances of all the different types of games and try to correlate them with the addiction parameter, and we find that there isn’t a lot of correlation,” said Manchanda. “Based on our discussions with game designers, they all design games to be engaging. So perhaps one explanation is that all these games on Steam are meant to make you come back. So there’s no differential advantage one game has over the other.”

A better predictor of addiction is an individual’s predisposition to addictive consumption. In other words, video games are not inherently addictive because of certain design elements or genres. Rather, an individual’s specific needs are being met by video games in an addictive manner.

“While playing video games related to survival, RPG, single-player, and shooter are more correlated with addiction, game type explains very little of the addictive behavior,” shared Branco. “This suggests that addiction is mostly determined by person-specific traits.”

Additionally, the study found that the addictive subgroup of the gaming population had some unique features that separated them from the total population of gamers. For example, people classified as being addicted to video games, on average, own more games, have more friends on the platform, play longer sessions, and are more likely to purchase new games.

The questions of addictive consumption of video games, which Manchanda and Branco elucidate in their research, are ongoing. In their future research, Manchanda and Branco hope to explore avenues such as video games’ impact on rational versus irrational behavior, the ethics of video game marketing and advertising, the particular design traits of specific video games, and more.

• Stephen M. Ross School of Business
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Frontiers for Young Minds

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How Scientists Use Webcams to Track Human Gaze

Eye tracking is a technology that can record people’s eye movements and tell scientists what people look at on screens or out in the world. Scientists use eye tracking to understand what people notice or remember; marketing researchers who create ads use eye tracking to see what type of ads or products capture people’s attention; and video game designers use eye tracking to see what parts of a game are confusing to players, so designers can fix the game. Eye-tracking equipment can be expensive and time consuming for researchers to use, so is there another way to record eye movements without buying an eye tracker? There is! Computer scientists can use a computer-based method called machine learning to turn an everyday webcam into an eye tracker. They can even do this with mobile phones! In this article, you will learn about how eye trackers work and the advantages of disadvantages of using webcams to track eyes.

Eyes are Windows to the Mind

Have you ever had a conversation with a friend and noticed your friend’s eyes were no longer looking at you but were suddenly looking behind you? What did you do? You probably turned around to see what your friend was looking at. This illustrates that eye movements tell us where people are paying attention. Scientists measure eye movements to understand what people remember and pay attention to, how people read, and even to screen for certain disorders. An eye tracker is a camera that takes pictures of a person’s eyes [ 1 ]. Eye trackers study information from these pictures (like the shape of the pupils) to pinpoint where a person is looking. These cameras take hundreds or even thousands of pictures each second! The large number of eye pictures allows eye trackers to be very exact in pinpointing where and when a person looks at something.

If an eye tracker was recording your eye movements while you watched a video, a scientist could use your eye movements to understand what you were paying attention to on the screen and for how long. For example, an eye tracker could detect your fixations : when your eyes seem like they have stopped moving to look at something. Longer fixations (like when you stare at something) might mean that you are really focused on a character in the video, while shorter and frequent fixations may mean you are either distracted by some other characters or objects, or that you are having trouble understanding what is happening on the screen. The tracker may also detect that your eyes follow the movement of the characters without you even noticing ( Figure 1 ). The large, sweeping movements that your eyes make between fixations are called saccades (for more information about eye movements, see this Frontiers for Young Minds article ).

• Figure 1 - A tablet shows a video with eye scan paths on it.
• A scan path refers to the path that the eyes take when a person is looking at something. The large circles represent fixations, where the person’s eyes seem to stop, and the lines show the saccades that the person’s eyes took between fixations. What parts of this video did the person look at?

Teaching Computers to Predict Gaze Location

In the lab, scientists use special eye-tracking equipment that is extremely good at figuring out where a person’s eyes are looking on a screen, which is called gaze location ( Figure 2 ). Even though eye trackers are excellent tools, they have some challenges. First, eye-tracking equipment can be very expensive, so not every scientist who wants to research eye movements can purchase the equipment for their laboratory. Also, eye trackers can only measure eye movements in-person and with one person at a time. This means research that requires lots of people can take a long time to conduct. It can be challenging to find people to participate in research when participants have to go to a laboratory to do so.

• Figure 2 - (A) A participant works on a computer with an eye-tracking system.
• The eye-tracking system uses a lot of technical equipment and requires the participant to keep her head still on a chin rest. All of this equipment makes the system very accurate in figuring out where the participant is looking on the computer screen. (B) A person works on a laptop with a built-in webcam. The webcam does not require as much equipment and the participants can sit comfortably and is free to move her head.

These challenges in using eye-tracking equipment can be overcome by using webcams to track eyes. Webcams are in most common personal devices (like phones or laptops), making it easy for scientists to reach a diverse group of people, without participants needing to come to a lab. Webcams are also much less expensive than eye-tracking equipment. Scientists could use webcams to collect eye-movement data remotely, which could save time and money [ 2 ]. Webcams were not designed to track eyes, so how do scientists get eye-movement data from them? There are several ways to use webcams as eye trackers, but one popular way is with machine learning [ 3 ].

Machine learning is a way for computers to use data (like pictures or numbers) and a set of mathematical calculations to learn from experience and find patterns in the world. Using machine learning, computers can learn from lots of pictures of people’s faces. When you are playing with your friends, have you ever noticed where they were looking, like at a cool toy or a yummy snack? You use clues to figure out where your friend looking, like their eye movements, how their head is turned, or how close they are to something. Computers can do something similar. They look at thousands of pictures of people’s faces and try to find patterns in those pictures, just like your brain finds patterns in your friends’ actions. Computers use these patterns to guess where someone might be looking when they look at a face, for instance. Scientists have improved machine learning to make more accurate predictions of where a person is looking by using other helpful information like eye and face landmarks that point out edges on a face ( Figure 3 ); depth information, like how far away a person is from the webcam; and even information from the scene on the screen [ 4 ].

• Figure 3 - Webcam images with facial landmarks.
• The dots (landmarks) on this woman’s face are on important edges and corners of the face, such her jaw, mouth, eyebrows, and importantly, her eyes. Machine learning can use landmarks to make better gaze-location predictions from webcam images like these.

Challenges with Webcam Eye Tracking

Though webcam eye tracking can help scientists make conclusions about peoples’ gaze locations for little cost, it is far from perfect. Webcam eye tracking does not have great precision or accuracy in saying where the eyes are really looking. Compared to a laboratory eye tracker, webcam eye tracking is not very good at separating types of eye movements from each other. This is because the pictures taken on a webcam are of lower quality than those on a laboratory tracker. Also, the frame rates (how quickly cameras can take pictures) are very different. A webcam can take around 30 pictures per second. While that may seem like a lot, laboratory eye trackers can take hundreds or even thousands of images per second! Taking fewer pictures per second means that the webcam cannot capture certain types of eye movements that happen very quickly.

Scientists can use webcams to track the general pattern of eye movements, but the measurements are not exact for finer eye movements. When someone wants to track eye movements to large characters and scenes in a video or an ad, low precision might not be a big deal. However, when scientists are doing experiments, they need better precision for tracking small or fast eye movements, like those eye movements that happen during reading or searching for small objects in a scene. For instance, say that you are focused on a person talking in a video, then you move your gaze to see an animal moving in the background just behind the person, and then you shift your eyes back to the person talking. Those small shifts in gaze may not be detected in webcam eye tracking. Also, think about where and how you normally watch videos, browse the internet, or use a camera. Are you in the dark, and maybe sometimes moving around? Because webcams have lower image quality compared to laboratory eye trackers, it is ideal for people to be in rooms with good lighting and to be sitting still while tracking. It is not always possible to make sure people are doing these things while researchers collect webcam images remotely.

Looking Ahead: The Future of Eye Tracking

Webcam eye tracking can be a cost-effective and time-saving approach for researchers who want to study eye movements. However, there are limitations in using webcams for eye tracking, as they are not as accurate as laboratory eye trackers at predicting where someone is looking. Scientists are working to improve webcam eye-tracking methods, such as by using machine learning, so they can more accurately predict eye movements using images from webcams. This work is important because it helps make eye-tracking technology easy to use for everyone, allowing scientists to learn more about how we see and interact with the world around us, even from the comfort of our own homes.

Eye Tracker : ↑ Technology that can record people’s eye movements and tell scientists what participants are looking at and for how long.

Fixation : ↑ The time between large eye movements when the eyes seem like they have stopped to look at something.

Saccade : ↑ A large, sweeping movement that your eyes make between fixations.

Machine Learning : ↑ A way of analyzing data that allows computers to learn from experience.

Landmarks : ↑ Marks that help a computer understand where edges of important parts of a face are in a picture, like eye corners or the chin.

Precision : ↑ Accuracy, or the degree to which the tracking system is correct in saying where someone is looking.

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

Written informed consent was obtained from the individual(s) for the publication of any identifiable images or data included in this article.

[1] ↑ Robbins, A., and Hout, M. C. 2015. Look into my eyes. Sci. Am. Mind 26:54–61. doi: 10.1038/scientificamericanmind0115-54

[2] ↑ Papoutsaki, A., Laskey, J., and Huang, J. 2017. “Searchgazer: Webcam eye tracking for remote studies of web search”, in Proceedings of the 2017 Conference on Conference Human Information Interaction and Retrieval (New York, NY: ACM), 17–26.

[3] ↑ Valliappan, N., Dai, N., Steinberg, E., He, J., Rogers, K., Ramachandran, V., et al. 2020. Accelerating eye movement research via accurate and affordable smartphone eye tracking. Nat. Commun. 11:4553. doi: 10.1038/s41467-020-18360-5

[4] ↑ Park, S., Aksan, E., Zhang, X., and Hilliges, O. 2020. “Towards end-to-end video-based eye-tracking”, in Computer Vision–ECCV 2020: 16th European Conference, Glasgow, UK, August 23–28, 2020, Proceedings, Part XII 16 (Berlin: Springer International Publishing), 747–63.

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Video Games Are a Playwright’s Muse, Not Her Hobby

In Bekah Brunstetter’s new play “The Game,” women withhold sex from their partners who are obsessed with a Fortnite-like game. Her previous work includes “The Oregon Trail.”

By Eric Grode

The writer Bekah Brunstetter is decidedly not a video game aficionado. Her personality type — “psychotically obsessed with productivity,” as she put it — has sealed off all gaming rabbit holes for the past 25 years.

And yet Brunstetter, perhaps best known for her television work on “This Is Us” and the book for the current Broadway adaptation of “The Notebook,” has now written not one but two plays about the ways that video games can hinder or facilitate human connection.

“The Game,” which is currently having its world premiere , is about a fictionalized version of Fortnite Battle Royale , a third-person shooter where each round ends with only one survivor. It comes seven years after Brunstetter’s “The Oregon Trail,” inspired by the game that condemned countless 1990s middle schoolers to an array of awful deaths (cholera, dysentery, snake bites, etc.) as they tried to replicate the grueling 19th-century passage west from Independence, Mo.

In “The Oregon Trail,” Brunstetter paralleled the modern-day struggles of a young woman with the higher-stakes perils of her video game counterpart. With “The Game,” she is taking the outsider perspective, focusing on a support group of wives who decide to withhold sex to get their partners off Fortnite — or The Game, as it is called here. (The play is a very loose adaptation of “Lysistrata,” the ancient Greek comedy in which the sex strike is designed to end the Peloponnesian War.)

Brunstetter, 41, spoke over a video call about “The Game” the day after its final dress rehearsal at Playmakers Repertory Company in Chapel Hill, N.C. She discussed the two plays, her learning curve and the TV show that might lure her back into the world of gaming.

Here are edited excerpts from the conversation.

Your characters show a familiarity with The Oregon Trail that they comically lack with The Game. Is that a fair estimation of your own expertise? Did you research Fortnite for “The Game”?

I know what I know about video games from my husband, mostly through hearing the one-sided version of conversations he has on his headset as he plays. I took a deep dive into the gaming terms after I finished my first draft. He read them and would be like: “That would never happen. This is completely inaccurate.” Sometimes, when I’m writing, I like to make fun of my own ignorance.

It sounds like you learned about the perils of the Oregon Trail the hard way back in middle school.

I always died because I have zero skill or patience for games. I went to this private Lutheran school where we went right from chapel to the computer lab and killed a bunch of people. It’s crazy that this thing we called a game had so much danger that we took so lightly. How much do humans need to feel scared and feel danger for our own comfort?

For the women in “The Game,” an open-world update of The Game is a source of dismay. Did the preordained nature of The Oregon Trail dictate a different approach to your storytelling than the sandbox of Fortnite?

The technology back in 1995 and the way we related to it were so different. “The Oregon Trail” was much more about finite choices. The main character in my play is in her early to mid-20s, which is where I think a lot of people start to feel: “Oh, no. I made the wrong mistake. My life is over.”

As for “The Game,” it’s an open world, which I think speaks to right now. How is the real world going to keep these men here when this other world is becoming so much richer and giving them so much control?

Not just men, though. One woman in the support group is there because of her female partner.

That was something my husband pointed out to me years ago: Somewhere around 45 percent of gamers are women . I knew I had to include that. Especially in terms of the shoot-’em-up games, it’s easy to assume that this is a male space. But of course women also have rage and frustration, and they need an outlet for that as well.

Whereas war in “Lysistrata” is definitely a male space.

“Lysistrata” ended up being more of a springboard. It had a lot of what I would call boner comedy — big, bawdy, crowd-pleasing comedy — and I wanted to find the similarities there. So I created the same women and started with the same story, but then just played it out in a contemporary setting. Also, unlike in “Lysistrata,” the sex strike doesn’t work.

Near the end, you also make a point of showing some of the more positive, world-building aspects of The Game.

The first idea I had for the play came from this in-between space in our lives where my husband and I were trying to have children and it wasn’t working out. And he showed me what he had been building in Fallout . And it really struck me that he wasn’t just in there shooting things. He was making something. Then, during the pandemic, he set me up with this really calming farm game where you make crops grow. But I wasn’t very good at it.

So you have done a bit of gaming in the last 25 years!

Well, and I did get into Words With Friends for a while. My thing is more looking at shoes that I don’t need or, like: “My kid needs a raincoat! I’m going to look at kids’ raincoats for the next half-hour!” But the game thing — it just feels like it has no point to me. And as I say that, I recognize that the thing I need to do more than anything is to do things with no point.

Do you have any particular titles in mind?

Actually, yes. My husband and I watched “The Last of Us,” and I just loved that father-daughter — well, father-surrogate daughter — relationship. I am really curious to see if I ever find-slash-make the time to play that one .

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• Published: 13 March 2018

Does playing violent video games cause aggression? A longitudinal intervention study

• Simone Kühn 1 , 2 ,
• Dimitrij Tycho Kugler 2 ,
• Katharina Schmalen 1 ,
• Markus Weichenberger 1 ,
• Charlotte Witt 1 &
• Jürgen Gallinat 2  

Molecular Psychiatry volume  24 ,  pages 1220–1234 ( 2019 ) Cite this article

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It is a widespread concern that violent video games promote aggression, reduce pro-social behaviour, increase impulsivity and interfere with cognition as well as mood in its players. Previous experimental studies have focussed on short-term effects of violent video gameplay on aggression, yet there are reasons to believe that these effects are mostly the result of priming. In contrast, the present study is the first to investigate the effects of long-term violent video gameplay using a large battery of tests spanning questionnaires, behavioural measures of aggression, sexist attitudes, empathy and interpersonal competencies, impulsivity-related constructs (such as sensation seeking, boredom proneness, risk taking, delay discounting), mental health (depressivity, anxiety) as well as executive control functions, before and after 2 months of gameplay. Our participants played the violent video game Grand Theft Auto V, the non-violent video game The Sims 3 or no game at all for 2 months on a daily basis. No significant changes were observed, neither when comparing the group playing a violent video game to a group playing a non-violent game, nor to a passive control group. Also, no effects were observed between baseline and posttest directly after the intervention, nor between baseline and a follow-up assessment 2 months after the intervention period had ended. The present results thus provide strong evidence against the frequently debated negative effects of playing violent video games in adults and will therefore help to communicate a more realistic scientific perspective on the effects of violent video gaming.

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The concern that violent video games may promote aggression or reduce empathy in its players is pervasive and given the popularity of these games their psychological impact is an urgent issue for society at large. Contrary to the custom, this topic has also been passionately debated in the scientific literature. One research camp has strongly argued that violent video games increase aggression in its players [ 1 , 2 ], whereas the other camp [ 3 , 4 ] repeatedly concluded that the effects are minimal at best, if not absent. Importantly, it appears that these fundamental inconsistencies cannot be attributed to differences in research methodology since even meta-analyses, with the goal to integrate the results of all prior studies on the topic of aggression caused by video games led to disparate conclusions [ 2 , 3 ]. These meta-analyses had a strong focus on children, and one of them [ 2 ] reported a marginal age effect suggesting that children might be even more susceptible to violent video game effects.

To unravel this topic of research, we designed a randomised controlled trial on adults to draw causal conclusions on the influence of video games on aggression. At present, almost all experimental studies targeting the effects of violent video games on aggression and/or empathy focussed on the effects of short-term video gameplay. In these studies the duration for which participants were instructed to play the games ranged from 4 min to maximally 2 h (mean = 22 min, median = 15 min, when considering all experimental studies reviewed in two of the recent major meta-analyses in the field [ 3 , 5 ]) and most frequently the effects of video gaming have been tested directly after gameplay.

It has been suggested that the effects of studies focussing on consequences of short-term video gameplay (mostly conducted on college student populations) are mainly the result of priming effects, meaning that exposure to violent content increases the accessibility of aggressive thoughts and affect when participants are in the immediate situation [ 6 ]. However, above and beyond this the General Aggression Model (GAM, [ 7 ]) assumes that repeatedly primed thoughts and feelings influence the perception of ongoing events and therewith elicits aggressive behaviour as a long-term effect. We think that priming effects are interesting and worthwhile exploring, but in contrast to the notion of the GAM our reading of the literature is that priming effects are short-lived (suggested to only last for <5 min and may potentially reverse after that time [ 8 ]). Priming effects should therefore only play a role in very close temporal proximity to gameplay. Moreover, there are a multitude of studies on college students that have failed to replicate priming effects [ 9 , 10 , 11 ] and associated predictions of the so-called GAM such as a desensitisation against violent content [ 12 , 13 , 14 ] in adolescents and college students or a decrease of empathy [ 15 ] and pro-social behaviour [ 16 , 17 ] as a result of playing violent video games.

However, in our view the question that society is actually interested in is not: “Are people more aggressive after having played violent video games for a few minutes? And are these people more aggressive minutes after gameplay ended?”, but rather “What are the effects of frequent, habitual violent video game playing? And for how long do these effects persist (not in the range of minutes but rather weeks and months)?” For this reason studies are needed in which participants are trained over longer periods of time, tested after a longer delay after acute playing and tested with broader batteries assessing aggression but also other relevant domains such as empathy as well as mood and cognition. Moreover, long-term follow-up assessments are needed to demonstrate long-term effects of frequent violent video gameplay. To fill this gap, we set out to expose adult participants to two different types of video games for a period of 2 months and investigate changes in measures of various constructs of interest at least one day after the last gaming session and test them once more 2 months after the end of the gameplay intervention. In contrast to the GAM, we hypothesised no increases of aggression or decreases in pro-social behaviour even after long-term exposure to a violent video game due to our reasoning that priming effects of violent video games are short-lived and should therefore not influence measures of aggression if they are not measured directly after acute gaming. In the present study, we assessed potential changes in the following domains: behavioural as well as questionnaire measures of aggression, empathy and interpersonal competencies, impulsivity-related constructs (such as sensation seeking, boredom proneness, risk taking, delay discounting), and depressivity and anxiety as well as executive control functions. As the effects on aggression and pro-social behaviour were the core targets of the present study, we implemented multiple tests for these domains. This broad range of domains with its wide coverage and the longitudinal nature of the study design enabled us to draw more general conclusions regarding the causal effects of violent video games.

Materials and methods

Participants.

Ninety healthy participants (mean age = 28 years, SD = 7.3, range: 18–45, 48 females) were recruited by means of flyers and internet advertisements. The sample consisted of college students as well as of participants from the general community. The advertisement mentioned that we were recruiting for a longitudinal study on video gaming, but did not mention that we would offer an intervention or that we were expecting training effects. Participants were randomly assigned to the three groups ruling out self-selection effects. The sample size was based on estimates from a previous study with a similar design [ 18 ]. After complete description of the study, the participants’ informed written consent was obtained. The local ethics committee of the Charité University Clinic, Germany, approved of the study. We included participants that reported little, preferably no video game usage in the past 6 months (none of the participants ever played the game Grand Theft Auto V (GTA) or Sims 3 in any of its versions before). We excluded participants with psychological or neurological problems. The participants received financial compensation for the testing sessions (200 Euros) and performance-dependent additional payment for two behavioural tasks detailed below, but received no money for the training itself.

Training procedure

The violent video game group (5 participants dropped out between pre- and posttest, resulting in a group of n  = 25, mean age = 26.6 years, SD = 6.0, 14 females) played the game Grand Theft Auto V on a Playstation 3 console over a period of 8 weeks. The active control group played the non-violent video game Sims 3 on the same console (6 participants dropped out, resulting in a group of n  = 24, mean age = 25.8 years, SD = 6.8, 12 females). The passive control group (2 participants dropped out, resulting in a group of n  = 28, mean age = 30.9 years, SD = 8.4, 12 females) was not given a gaming console and had no task but underwent the same testing procedure as the two other groups. The passive control group was not aware of the fact that they were part of a control group to prevent self-training attempts. The experimenters testing the participants were blind to group membership, but we were unable to prevent participants from talking about the game during testing, which in some cases lead to an unblinding of experimental condition. Both training groups were instructed to play the game for at least 30 min a day. Participants were only reimbursed for the sessions in which they came to the lab. Our previous research suggests that the perceived fun in gaming was positively associated with training outcome [ 18 ] and we speculated that enforcing training sessions through payment would impair motivation and thus diminish the potential effect of the intervention. Participants underwent a testing session before (baseline) and after the training period of 2 months (posttest 1) as well as a follow-up testing sessions 2 months after the training period (posttest 2).

Grand Theft Auto V (GTA)

GTA is an action-adventure video game situated in a fictional highly violent game world in which players are rewarded for their use of violence as a means to advance in the game. The single-player story follows three criminals and their efforts to commit heists while under pressure from a government agency. The gameplay focuses on an open world (sandbox game) where the player can choose between different behaviours. The game also allows the player to engage in various side activities, such as action-adventure, driving, third-person shooting, occasional role-playing, stealth and racing elements. The open world design lets players freely roam around the fictional world so that gamers could in principle decide not to commit violent acts.

The Sims 3 (Sims)

Sims is a life simulation game and also classified as a sandbox game because it lacks clearly defined goals. The player creates virtual individuals called “Sims”, and customises their appearance, their personalities and places them in a home, directs their moods, satisfies their desires and accompanies them in their daily activities and by becoming part of a social network. It offers opportunities, which the player may choose to pursue or to refuse, similar as GTA but is generally considered as a pro-social and clearly non-violent game.

Assessment battery

To assess aggression and associated constructs we used the following questionnaires: Buss–Perry Aggression Questionnaire [ 19 ], State Hostility Scale [ 20 ], Updated Illinois Rape Myth Acceptance Scale [ 21 , 22 ], Moral Disengagement Scale [ 23 , 24 ], the Rosenzweig Picture Frustration Test [ 25 , 26 ] and a so-called World View Measure [ 27 ]. All of these measures have previously been used in research investigating the effects of violent video gameplay, however, the first two most prominently. Additionally, behavioural measures of aggression were used: a Word Completion Task, a Lexical Decision Task [ 28 ] and the Delay frustration task [ 29 ] (an inter-correlation matrix is depicted in Supplementary Figure 1 1). From these behavioural measures, the first two were previously used in research on the effects of violent video gameplay. To assess variables that have been related to the construct of impulsivity, we used the Brief Sensation Seeking Scale [ 30 ] and the Boredom Propensity Scale [ 31 ] as well as tasks assessing risk taking and delay discounting behaviourally, namely the Balloon Analogue Risk Task [ 32 ] and a Delay-Discounting Task [ 33 ]. To quantify pro-social behaviour, we employed: Interpersonal Reactivity Index [ 34 ] (frequently used in research on the effects of violent video gameplay), Balanced Emotional Empathy Scale [ 35 ], Reading the Mind in the Eyes test [ 36 ], Interpersonal Competence Questionnaire [ 37 ] and Richardson Conflict Response Questionnaire [ 38 ]. To assess depressivity and anxiety, which has previously been associated with intense video game playing [ 39 ], we used Beck Depression Inventory [ 40 ] and State Trait Anxiety Inventory [ 41 ]. To characterise executive control function, we used a Stop Signal Task [ 42 ], a Multi-Source Interference Task [ 43 ] and a Task Switching Task [ 44 ] which have all been previously used to assess effects of video gameplay. More details on all instruments used can be found in the Supplementary Material.

Data analysis

On the basis of the research question whether violent video game playing enhances aggression and reduces empathy, the focus of the present analysis was on time by group interactions. We conducted these interaction analyses separately, comparing the violent video game group against the active control group (GTA vs. Sims) and separately against the passive control group (GTA vs. Controls) that did not receive any intervention and separately for the potential changes during the intervention period (baseline vs. posttest 1) and to test for potential long-term changes (baseline vs. posttest 2). We employed classical frequentist statistics running a repeated-measures ANOVA controlling for the covariates sex and age.

Since we collected 52 separate outcome variables and conduced four different tests with each (GTA vs. Sims, GTA vs. Controls, crossed with baseline vs. posttest 1, baseline vs. posttest 2), we had to conduct 52 × 4 = 208 frequentist statistical tests. Setting the alpha value to 0.05 means that by pure chance about 10.4 analyses should become significant. To account for this multiple testing problem and the associated alpha inflation, we conducted a Bonferroni correction. According to Bonferroni, the critical value for the entire set of n tests is set to an alpha value of 0.05 by taking alpha/ n  = 0.00024.

Since the Bonferroni correction has sometimes been criticised as overly conservative, we conducted false discovery rate (FDR) correction [ 45 ]. FDR correction also determines adjusted p -values for each test, however, it controls only for the number of false discoveries in those tests that result in a discovery (namely a significant result).

Moreover, we tested for group differences at the baseline assessment using independent t -tests, since those may hamper the interpretation of significant interactions between group and time that we were primarily interested in.

Since the frequentist framework does not enable to evaluate whether the observed null effect of the hypothesised interaction is indicative of the absence of a relation between violent video gaming and our dependent variables, the amount of evidence in favour of the null hypothesis has been tested using a Bayesian framework. Within the Bayesian framework both the evidence in favour of the null and the alternative hypothesis are directly computed based on the observed data, giving rise to the possibility of comparing the two. We conducted Bayesian repeated-measures ANOVAs comparing the model in favour of the null and the model in favour of the alternative hypothesis resulting in a Bayes factor (BF) using Bayesian Information criteria [ 46 ]. The BF 01 suggests how much more likely the data is to occur under the null hypothesis. All analyses were performed using the JASP software package ( https://jasp-stats.org ).

Sex distribution in the present study did not differ across the groups ( χ 2 p -value > 0.414). However, due to the fact that differences between males and females have been observed in terms of aggression and empathy [ 47 ], we present analyses controlling for sex. Since our random assignment to the three groups did result in significant age differences between groups, with the passive control group being significantly older than the GTA ( t (51) = −2.10, p  = 0.041) and the Sims group ( t (50) = −2.38, p  = 0.021), we also controlled for age.

The participants in the violent video game group played on average 35 h and the non-violent video game group 32 h spread out across the 8 weeks interval (with no significant group difference p  = 0.48).

To test whether participants assigned to the violent GTA game show emotional, cognitive and behavioural changes, we present the results of repeated-measure ANOVA time x group interaction analyses separately for GTA vs. Sims and GTA vs. Controls (Tables  1 – 3 ). Moreover, we split the analyses according to the time domain into effects from baseline assessment to posttest 1 (Table  2 ) and effects from baseline assessment to posttest 2 (Table  3 ) to capture more long-lasting or evolving effects. In addition to the statistical test values, we report partial omega squared ( ω 2 ) as an effect size measure. Next to the classical frequentist statistics, we report the results of a Bayesian statistical approach, namely BF 01 , the likelihood with which the data is to occur under the null hypothesis that there is no significant time × group interaction. In Table  2 , we report the presence of significant group differences at baseline in the right most column.

Since we conducted 208 separate frequentist tests we expected 10.4 significant effects simply by chance when setting the alpha value to 0.05. In fact we found only eight significant time × group interactions (these are marked with an asterisk in Tables  2 and 3 ).

When applying a conservative Bonferroni correction, none of those tests survive the corrected threshold of p  < 0.00024. Neither does any test survive the more lenient FDR correction. The arithmetic mean of the frequentist test statistics likewise shows that on average no significant effect was found (bottom rows in Tables  2 and 3 ).

In line with the findings from a frequentist approach, the harmonic mean of the Bayesian factor BF 01 is consistently above one but not very far from one. This likewise suggests that there is very likely no interaction between group × time and therewith no detrimental effects of the violent video game GTA in the domains tested. The evidence in favour of the null hypothesis based on the Bayes factor is not massive, but clearly above 1. Some of the harmonic means are above 1.6 and constitute substantial evidence [ 48 ]. However, the harmonic mean has been criticised as unstable. Owing to the fact that the sum is dominated by occasional small terms in the likelihood, one may underestimate the actual evidence in favour of the null hypothesis [ 49 ].

To test the sensitivity of the present study to detect relevant effects we computed the effect size that we would have been able to detect. The information we used consisted of alpha error probability = 0.05, power = 0.95, our sample size, number of groups and of measurement occasions and correlation between the repeated measures at posttest 1 and posttest 2 (average r  = 0.68). According to G*Power [ 50 ], we could detect small effect sizes of f  = 0.16 (equals η 2  = 0.025 and r  = 0.16) in each separate test. When accounting for the conservative Bonferroni-corrected p -value of 0.00024, still a medium effect size of f  = 0.23 (equals η 2  = 0.05 and r  = 0.22) would have been detectable. A meta-analysis by Anderson [ 2 ] reported an average effects size of r  = 0.18 for experimental studies testing for aggressive behaviour and another by Greitmeyer [ 5 ] reported average effect sizes of r  = 0.19, 0.25 and 0.17 for effects of violent games on aggressive behaviour, cognition and affect, all of which should have been detectable at least before multiple test correction.

Within the scope of the present study we tested the potential effects of playing the violent video game GTA V for 2 months against an active control group that played the non-violent, rather pro-social life simulation game The Sims 3 and a passive control group. Participants were tested before and after the long-term intervention and at a follow-up appointment 2 months later. Although we used a comprehensive test battery consisting of questionnaires and computerised behavioural tests assessing aggression, impulsivity-related constructs, mood, anxiety, empathy, interpersonal competencies and executive control functions, we did not find relevant negative effects in response to violent video game playing. In fact, only three tests of the 208 statistical tests performed showed a significant interaction pattern that would be in line with this hypothesis. Since at least ten significant effects would be expected purely by chance, we conclude that there were no detrimental effects of violent video gameplay.

This finding stands in contrast to some experimental studies, in which short-term effects of violent video game exposure have been investigated and where increases in aggressive thoughts and affect as well as decreases in helping behaviour have been observed [ 1 ]. However, these effects of violent video gaming on aggressiveness—if present at all (see above)—seem to be rather short-lived, potentially lasting <15 min [ 8 , 51 ]. In addition, these short-term effects of video gaming are far from consistent as multiple studies fail to demonstrate or replicate them [ 16 , 17 ]. This may in part be due to problems, that are very prominent in this field of research, namely that the outcome measures of aggression and pro-social behaviour, are poorly standardised, do not easily generalise to real-life behaviour and may have lead to selective reporting of the results [ 3 ]. We tried to address these concerns by including a large set of outcome measures that were mostly inspired by previous studies demonstrating effects of short-term violent video gameplay on aggressive behaviour and thoughts, that we report exhaustively.

Since effects observed only for a few minutes after short sessions of video gaming are not representative of what society at large is actually interested in, namely how habitual violent video gameplay affects behaviour on a more long-term basis, studies employing longer training intervals are highly relevant. Two previous studies have employed longer training intervals. In an online study, participants with a broad age range (14–68 years) have been trained in a violent video game for 4 weeks [ 52 ]. In comparison to a passive control group no changes were observed, neither in aggression-related beliefs, nor in aggressive social interactions assessed by means of two questions. In a more recent study, participants played a previous version of GTA for 12 h spread across 3 weeks [ 53 ]. Participants were compared to a passive control group using the Buss–Perry aggression questionnaire, a questionnaire assessing impulsive or reactive aggression, attitude towards violence, and empathy. The authors only report a limited increase in pro-violent attitude. Unfortunately, this study only assessed posttest measures, which precludes the assessment of actual changes caused by the game intervention.

The present study goes beyond these studies by showing that 2 months of violent video gameplay does neither lead to any significant negative effects in a broad assessment battery administered directly after the intervention nor at a follow-up assessment 2 months after the intervention. The fact that we assessed multiple domains, not finding an effect in any of them, makes the present study the most comprehensive in the field. Our battery included self-report instruments on aggression (Buss–Perry aggression questionnaire, State Hostility scale, Illinois Rape Myth Acceptance scale, Moral Disengagement scale, World View Measure and Rosenzweig Picture Frustration test) as well as computer-based tests measuring aggressive behaviour such as the delay frustration task and measuring the availability of aggressive words using the word completion test and a lexical decision task. Moreover, we assessed impulse-related concepts such as sensation seeking, boredom proneness and associated behavioural measures such as the computerised Balloon analogue risk task, and delay discounting. Four scales assessing empathy and interpersonal competence scales, including the reading the mind in the eyes test revealed no effects of violent video gameplay. Neither did we find any effects on depressivity (Becks depression inventory) nor anxiety measured as a state as well as a trait. This is an important point, since several studies reported higher rates of depressivity and anxiety in populations of habitual video gamers [ 54 , 55 ]. Last but not least, our results revealed also no substantial changes in executive control tasks performance, neither in the Stop signal task, the Multi-source interference task or a Task switching task. Previous studies have shown higher performance of habitual action video gamers in executive tasks such as task switching [ 56 , 57 , 58 ] and another study suggests that training with action video games improves task performance that relates to executive functions [ 59 ], however, these associations were not confirmed by a meta-analysis in the field [ 60 ]. The absence of changes in the stop signal task fits well with previous studies that likewise revealed no difference between in habitual action video gamers and controls in terms of action inhibition [ 61 , 62 ]. Although GTA does not qualify as a classical first-person shooter as most of the previously tested action video games, it is classified as an action-adventure game and shares multiple features with those action video games previously related to increases in executive function, including the need for hand–eye coordination and fast reaction times.

Taken together, the findings of the present study show that an extensive game intervention over the course of 2 months did not reveal any specific changes in aggression, empathy, interpersonal competencies, impulsivity-related constructs, depressivity, anxiety or executive control functions; neither in comparison to an active control group that played a non-violent video game nor to a passive control group. We observed no effects when comparing a baseline and a post-training assessment, nor when focussing on more long-term effects between baseline and a follow-up interval 2 months after the participants stopped training. To our knowledge, the present study employed the most comprehensive test battery spanning a multitude of domains in which changes due to violent video games may have been expected. Therefore the present results provide strong evidence against the frequently debated negative effects of playing violent video games. This debate has mostly been informed by studies showing short-term effects of violent video games when tests were administered immediately after a short playtime of a few minutes; effects that may in large be caused by short-lived priming effects that vanish after minutes. The presented results will therefore help to communicate a more realistic scientific perspective of the real-life effects of violent video gaming. However, future research is needed to demonstrate the absence of effects of violent video gameplay in children.

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SK has been funded by a Heisenberg grant from the German Science Foundation (DFG KU 3322/1-1, SFB 936/C7), the European Union (ERC-2016-StG-Self-Control-677804) and a Fellowship from the Jacobs Foundation (JRF 2016–2018).

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Kühn, S., Kugler, D., Schmalen, K. et al. Does playing violent video games cause aggression? A longitudinal intervention study. Mol Psychiatry 24 , 1220–1234 (2019). https://doi.org/10.1038/s41380-018-0031-7

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Prime Video’s ‘Fallout’ Is an Ultra-Violent and Twistedly Fun Video Game Adaptation: TV Review

By Aramide Tinubu

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The big and small screens are stuffed full of post-apocalyptic adventures, yet despite that cluttered landscape, few shows and films stick out to offer something unique for viewers. However, in “ Fallout ” for Prime Video , a thrilling adaptation of the beloved video game series, creators Geneva Robertson-Dworet and Graham Wagner present an off-kilter and fascinating look at humanity in the 23rd century.

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Video game adaptations have produced a mixed bag. While films, including the recent “Super Mario Bros. Movie” and “Dungeons and Dragons,” saw box office success, others like “Rampage” have not fared so well. On television, there are the successes of HBO’s “The Last of Us” and Netflix’s “The Witcher,” and then there is the less buzzy “Halo” on Paramount+. Here, Wagner and Robertson-Dworet wisely chose to avoid a straight adaptation. Instead, they constructed an original story within the game universe. Moreover, unexpected stylistic choices, including archaic technology, a soundtrack full of hits from Ella Fitzgerald and Bing Crosby and odd mid-20th century dialogue, contrast against disturbingly vicious deaths, making “Fallout” a sensory-fueled feast.

The scope of the series is massive. When the narrative stalls in the sixth episode, recounting Cooper’s life in the months and weeks before the bomb drop, the visuals led by production designer Howard Cummings and art and set direction led by Ann Bartek and Regina Graves keep the audience engaged. Robertson-Dworet and Wagner give their audience intricate looks into various aspects of this universe. From different vaults run by various overseers to the endless deserted sands of California and into the lawless city of Filly, the artisans worked tirelessly to ensure no detail was left unattended.

The first half of “Fallout” is undoubtedly the strongest, as Lucy tries to grapple with the lies she’s been told about the world while barely keeping herself alive. Still, even as the storylines linger too long in less exciting places, viewers are eager to see how the varied mysteries and secrets of the surface and the dwellers will reveal themselves. Bizarre but intensely fun, “Fallout” is like nothing you’ve ever seen; for that reason alone, you won’t be able to turn away.

The eight episodes of “Fallout” premiere on April 11 on Prime Video.

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Star Wars Outlaws' ESRB Description Reveals That Sabacc Will Appear for the Very First Time in a Game

Sabacc has long been popular been scoundrels, but it's been strangely absent from star wars' video games..

Star Wars Outlaws is not out for a few more months, but as the release date slowly approaches, the game's ESRB rating summary revealed that a popular and nearly-forgotten card game is set to return as a playable mini-game.

Spotted by GamesRadar , the ESRB summary description for Star Wars Outlaws reveals that "players can wager in-game currency on Sabacc, a blackjack-like card game with detailed rules." The card game, which first debuted in the L. Neil Smith novel Lando Calrissian and the Mindharp of Sharu, has rules and concepts similar to those of blackjack and poker.

The rules of Sabacc were first published in 1989 with the release of the Crisis on Cloud City supplement for the Star Wars: The Roleplaying Game, which Games International described in an issue published in 1990 as "a sort of Blackjack variant."

Despite its known existence over the last several decades, its appearance in Star Wars media has been slim. Sabacc is never directly shown but rather mentioned in Star Wars media, such as in the Star Wars: Squadrons short story , The Light You Bring, or when it appeared in a scene in Solo: A Star Wars Story . And Disney began selling an official Sabacc deck at its Star Wars: Galaxy's Edge attraction in 2019. Yet, no Star Wars game has ever made Sabacc playable in any capacity, thus making its inclusion in Star Wars Outlaws all the more noteworthy.

This news is positive for Ubisoft's upcoming open-world game, as the publisher is under scrutiny for locking a mission behind the Star Wars Outlaws season pass. While Ubisoft clarified that the mission is "optional," the publisher has yet to elaborate on its scope, leaving players confused about whether or not purchasing the season pass to access it is worth it.

Star Wars Outlaws is out on August 27 for PC, PS5, and Xbox Series X/S. Pre-orders are now available at the starting price of $69.99 for the Standard Edition, while the Gold and Ultimate Edition costs $109.99 and $129.99, respectively . The latter two not only include the controversial season pass, but players will also get access to the base game three days early.

Taylor is a Reporter at IGN. You can follow her on Twitter @TayNixster.

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