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A Case Study of Videogame-Related Violence Among Adolescents

Videogames may negatively affect children and adolescents by promoting aggressive behaviors. These findings were presented during the American Psychiatric Association annual meeting held virtually from May 1 to 3, 2021.

Medical charts from 3 children who presented at the emergency department at the Buffalo General Medical Center due to aggressive behavior involving a videogame were reviewed.

A boy aged 11 years who was White and had previously been diagnosed with attention deficit hyperactive disorder and oppositional defiant disorder was brought to the hospital after a confrontation with his brother. The 2 boys had an episode of physical aggression over a videogame in which the boy chased his brother with a knife. The patient had a history of physical abuse from his stepfather and was being bullied at school.

Another 11-year-old White boy with attention deficit hyperactive disorder and oppositional defiant disorder was escorted to the hospital by the police for an emergency mental health evaluation. Unprovoked, the boy had become physically aggressive with his mother in reaction to losing in Super Smash Bros . The mother indicated he had a history of violent outburst after minimal provocation in the context of videogame use.

A boy who was 14 years of age and Black, who had not been diagnosed with any psychiatric condition was mandated by police to have a mental health evaluation after he displayed physical aggression in reaction to his mother confiscating his videogame console. The boy’s mother had caught him stealing her credit card in order to purchase online videogames. He had a history of violence at school and poor sleep hygiene due to nightly videogaming. The boy had been physically abused by his father.

The children listed above had at least one of the risk factors associated with aggression: inadequate parenting, childhood abuse, poor school performance, ADHD, substance abuse . It presents a real-life model in which children and adolescents with pre-existing risk factors could be affected by videogame use.

This case study was limited by the few cases and the retrospective review of medical records.

These data suggested some children may be negatively affected by playing videogames. Studies are needed to assess how playing certain videogames may promote aggressive behavior among children such that appropriate videogame use guidelines can be formulated. A clinical study with a larger sample size will help in understanding the risk factors, gender differences, ethnicity, and age groups that may be associated with video-game related aggression

Nijhara K, Antonius D, Brooks V. A clinical perspective on video game-related violence: A case series of adolescents who presented to the psychiatric ER after playing videogames. Presented at: APA annual meeting May 1-3, 2021. Abstract/Poster 4216.

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• Open access
• Published: 09 February 2022

Learning in digital play: a dual case study of video gamers’ independent play

• Weimin Toh   ORCID: orcid.org/0000-0002-6468-227X 1 &
• Fei Victor Lim   ORCID: orcid.org/0000-0003-3046-1011 2  

Research and Practice in Technology Enhanced Learning volume  17 , Article number:  6 ( 2022 ) Cite this article

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This paper explores the implications of youths’ out-of-school gaming practices for teaching and learning in formal and informal learning contexts. We report on a study where we examined the video game play of two youths using a case study approach. User experience approaches, e.g. the think-aloud protocol and interviews, were grounded in the theoretical framework of social semiotics to analyse the gameplay videos and to discuss the implications for the youths’ learning. The paper contends that youths are demonstrating critical thinking, empathy, and multimodal literacy through their gameplay. We offer suggestions for how adults can use video games for youths’ learning.

Introduction

People learn as they play (Oliver & Carr, 2009 ). Digital play involves the use of technology, including computers and laptops, tablets, smartphones, electronic toys, and console games for playing and learning activities (Marsh et al., 2016 ). The boundaries between online and offline spaces have become blurred in digital play as communication and play move across physical and virtual domains and integrate material and immaterial practices (Garcia, 2020 ; Giddings, 2014 ; Marsh et al., 2016 ). Digital play is rooted in children’s everyday experiences and can promote cognitive and imaginative development (Edwards, 2011 ). Engagement with video games is a type of digital play that can bring about learning (Toh & Lim, 2021 ; Squire, 2011 ) as they incorporate sound learning principles, such as “just in time learning” that can be used for teaching various subjects in schools (Gee, 2003 ).

Digital play motivates learning because it engages with the students’ “lifeworld” (New London Group, 1996 ). Digital play can be integrated into schools to intrinsically motivate students for their self-directed (Karakas & Manisaligil, 2012 ) and peer-to-peer learning (Butler, 2017 ). For example, Beavis et al. ( 2015 ) reported that teachers were able to improve students’ learning and engagement by connecting teaching to students’ lifeworlds and redesigning their English and literacy curriculum to leverage the joy of gameplay to build students’ literacy proficiency over time. Digital play can also be an effective way for students to demonstrate new literacies needed for the future workforce (Apperley & Walsh, 2012 ). Playing video games is a common pastime of many people, especially amongst males (Jansz, 2005 ). Video game play has also been described as a literacy practice (Steinkuehler, 2010 ; Steinkuehler & King, 2009 ). When video games are used in the school curriculum, it can motivate students (Deng et al., 2016 ) and draw on their funds of knowledge (Risko & Walker‐Dalhouse, 2007 ) for the learning activities. Digital play has been integrated into formal educational contexts for STEM learning (e.g. Ibáñez & Delgado-Kloos, 2018 ) and to motivate L2 vocabulary learning (e.g. Butler, 2017 ), argumentation and persuasion writing (e.g. Dickey, 2011 ), as well as social skills (e.g. Craig et al., 2015 ), creativity (e.g. Ott & Pozzi, 2012 ), critical thinking (e.g. Barab et al., 2012 ), ethical thinking (e.g. Schrier, 2015 ), and mathematical thinking and problem-solving skills (e.g. Kiili et al., 2015 ).

Video games incorporate a whole set of fundamentally sound learning principles that can be used for teaching and learning activities in schools (Gee, 2003 ). Gee ( 2005 ) also explicated the principles of learning that are built into successful games. These include empowering players as active agents who can co-design the learning experience as well as learning through well-ordered problems in which learners are scaffolded to learn how to proceed when they face harder problems later in the game. Squire ( 2002 ) also argued that examining how gameplay can be used to support learning in formal learning environments can be productive. Games like SimCity and Civilisation can mediate our understandings of other phenomena, and they can be used to support learning in formal and informal learning contexts. Pedagogical activities can be integrated into the game design or teachers can adapt the game to engage students in meaningful practices and critical thinking by using scaffolding questions for students to think about how games can be used as a tool for answering historical questions.

Shaffer et al. ( 2005 ) posited that video games are powerful contexts for learning because they make it possible to create virtual worlds and acting in such worlds help to develop the situated understandings, effective social practices, powerful identities, shared values, and ways of thinking of important communities of practice. For instance, Railroad Tycoon can help players to learn economic and geographic issues faced by railroad engineers in the 1800s by allowing them to engage in design activities when playing the game. However, the authors also highlighted that it was challenging to integrate game-based learning into institutional education because games encourage exploration, personalised meaning-making, individual expression, and playful experimentation with social boundaries, factors which conflict with institutional modes of teaching and learning that emphasise conformity, one size fits all curriculum, and standardised testing and assessment practices.

A game-based curriculum informed by the theoretical framework of digital play has been designed and integrated into classrooms to teach persuasion writing to seventh grade students (Barab et al., 2012 ). The results indicated statistically significant differences in learning and engagement between the control and experimental groups where the students in the game-based curriculum demonstrated significant improvements in their learning gains. The authors explained that the technological affordances of well-designed videogame play supported the students’ engagement and learning by allowing them to play out new possible selves, such as scientists, historians, or investigative reporters in the virtual world to enact disciplinary expertise.

Studies have also shown that commercial video games, such as The Walking Dead can be integrated into classrooms for teaching domain-specific content, such as ethical theories when teachers are able to orchestrate the learning activities with appropriate teaching approaches to support student learning and engagement (de Sousa et al., 2018 ). Playing commercial video games has been found to improve the desirable skills and competencies sometimes referred to as “graduate attributes” in higher education students. Using a laboratory-based randomised controlled trial, Barr ( 2017 ) reported that students in the gameplaying group obtained highly significant positive changes in their adaptability, resourcefulness, and communication skill.

The studies on digital play described here have been conducted in formal pedagogical contexts. However, there is a knowledge gap in terms of our understanding of youths’ gameplaying activities and the types of learning that are demonstrated in their gameplaying process in the informal space. As such, the goal of this study is to identify the types of learning, such as critical thinking, empathy, and multimodal literacy, that can be demonstrated from the players’ gameplaying activities. In our previous study (Toh & Kirschner, 2020 ), we have investigated how Participant 1 adopted an inquiry-based learning approach to progress the same game segment examined in this paper. The inquiry-based learning approach has been integrated into a self-directed learning framework in video games for that study. In an upcoming paper (Toh & Kirschner, 2022 ), we examine how Participant 2 exhibited resilience in his learning of the stealth option to progress the same game segment analysed in this paper. Resilience has been integrated into a social-emotional learning model in that paper. In this study, we adopt a case study approach through a multimodal discourse analysis of the gameplay videos to surface the types of learning that can be identified in two youths’ gameplay recordings. Our paper aims to answer the following research question: What is the learning that can be demonstrated through video gameplay?

The theoretical orientation of social semiotics informs our lenses on youths’ gaming practices (Kress, 2010 ; Kress & van Leeuwen, 2001 ). The participants’ gameplay interactions are described using social semiotic theory, which models meanings according to the sociocultural contexts where the interactions took place. Bezemer and Kress ( 2016 , p. 4) argue it is important to respond “theoretically to the social”, recognise the ways for making meaning, and describe the “semiotic work done”. From this argument, the tenets of multimodal social semiotics have been adopted in the analysis and interpretation of the data to understand youths’ gaming practices.

The first tenet recognises that youths communicate with multimodal ensembles, drawing from language, visual, and the verbal modes to constitute interactivity. The second tenet recognises signs of learning (Kress & Selander, 2012 ). Making meaning is guided by interest, and learning occurs as the learners’ entire set of resources is augmented and transformed when they integrate new ways of conceiving the world. The third tenet focuses on how semiotic modes and digital technologies facilitate different pedagogic relations in human–computer interaction and offer learning opportunities. From the participants’ gameplay interaction, we discuss the learning demonstrated by the participants in their gameplay, the affordances of the video games that supported their expression of these literacies, and pedagogical implications of digital play and learning.

Research design overview

This paper adopts a qualitative case study approach method (Creswell, 2013 ) through a multimodal discourse analysis of the gameplay videos produced by two youths. The qualitative case study approach involves the exploration of case(s) over time through detailed, in-depth data collection involving multiple sources of data. The rationale for a qualitative case study approach is that it allows for a holistic understanding of a phenomenon within real-life contexts from the perspective of those involved (Merriam, 1988 ; Stake, 1995 , 2005 ; Yin, 2009 ) and allows the researcher to grasp the intricacies of a phenomenon (Stake, 2005 ).

The think-aloud protocol (Hu & Gao, 2017 ; Li et al., 2012 ) was adapted for use in the study by asking participants to verbalise their gameplay experience. Participants were asked to explain how and why (Gillern, 2016 ) they made a specific choice or perform an action during and after gameplay. They were also instructed to record their natural reactions and comments in the game recordings. When they verbalised their experience as they played the game, the method used was concurrent think-aloud protocol (Kelley et al., 2015 ) that involved the participants thinking-aloud while simultaneously performing an activity in usability studies. When the participants discussed their experience after gameplay, retrospective think-aloud (Ji & Rau, 2019 ) was used to reflect on their game experience. The think-aloud protocol is an effective method to elicit the participants’ demonstration of their learning because of the prompt response of the participants when a problem is experienced (Ericsson & Simon, 1993 ), which shows how they overcome the problem to progress the game. As the participants were able to refer to their gameplay recordings during the interviews, stimulated recall (Dempsey, 2010 ) was also used to review their gameplay recordings.

The framework of multimodal discourse analysis (O’Halloran & Lim, 2014 ; Kress, 2012 ; O’Halloran, 2004 ) was adopted to analyse the video recordings of the participants. The multimodal discourse analysis approach integrates the tenets from social semiotics, discourse analysis, think-aloud protocol, and the interviews to examine the player experience in their video recordings. The multimodal combination of language, visual, verbal, and action semiotic modes in the gameplay recordings are combined to form the ludonarrative frame for video games, which conceptualises the gameplay, the narrative, and the player as a whole (Toh, 2018 ). A semiotic mode can be understood as a distinct way for meaning-making (Jewitt, 2009 ) and the multimodal discourse analysis approach to examining the gameplay recordings is relevant because video games are highly multimodal artefacts. A central tenet of multimodal discourse analysis is that a text is embedded within the sociocultural context (Guo, 2017 ) in which it is produced and the text’s meaning is never fixed but contingent on different external factors, such as the cultural background and prior gaming experience of the participants (Toh, 2018 ).

Data collection

Multiple sources of data were used to interpret the lived experience of the participants through the method of data triangulation and method triangulation. Data triangulation (Denzin, 2009 ) has been used to gather data from different players, and method triangulation (Bauwens, 2010 ) has been used for data gathering and analysis. The different methods of data collection include the interviews of the participants, the observation of the participants’ gameplay in the laboratory, and the gameplay recordings. Member checking has been adopted during the qualitative interviews to validate the interpretations of the participants’ gameplay recordings (Iivari, 2018 ).

Prior to the start of the study, the participants filled up a written survey to provide demographic information and gaming habits. During the first gameplay session, the participants played their selected game from the start for one to three hours in a computer laboratory. Their gameplay was streamed and recorded using Fraps (computer) and a PS3 recorder on a nearby computer whereby the researcher was using to observe their gameplay. At the end of the first gameplay session, the first author conducted a one-to-two-hour interview with the participants. The interview questions asked during the first gameplay session were more general and open-ended. Some of the questions that the interviewer asked the participants included whether they liked the scripted game sequences, whether they were clearly able to see a divide between narrative and gameplay in the game, and whether the information provided by the characters helped them to make decisions to progress the game.

The first author then instructed the participants to record their subsequent gameplay sessions at home. The participants incorporated their natural reactions with their think-aloud verbalisations in their gameplay recordings. A total of 15 and 14.8 h of think-aloud video recordings were collected and analysed for Participants 1 and 2, respectively. After they have completed the game, the first author arranged a final interview to review their gameplay recordings together with them and discuss their gaming experiences. A total of 7 and 6.7 h of interview recordings were collected for Participants 1 and 2, respectively. More specific interview questions were asked during the final session with the participants. For instance, the researcher asked Participant 1 to explain whether specific objects in the game world such as the spark plug and the pillow helped him to progress the game and how he figured out the sequential order to progress the game. For Participant 2, an example of a specific question the researcher asked him was whether playing as Joel after Ellie caused him to feel worried for Ellie’s safety and motivated him to progress the game to find out the story.

Participants

The data were obtained from the first author’s study on the player experience. The research aim for the study was to propose an original theoretical framework, the ludonarrative model for studying video games, and this model was grounded on the empirical data of a group of players in Singapore. For the study, participants were recruited through convenience and snowball sampling via advertisements posted on the university’s website. Consent was obtained from the participants to share their video recordings, which included their voices, for research purposes. This study was approved by the university’s Institutional Review Board.

The data from two of the participants were selected for analysis. The two participants were selected because they were experienced players (Soylu & Bruning, 2016 ). Participant 1 is a 22-year-old male undergraduate student with 11–15 years of gaming experience. He mentioned that he played a variety of games such as shooters, puzzle games, action games, and so on a few times a week. The game he chose for the study was The Walking Dead Season 1, Episodes 1–5. Participant 2 was a 24-year-old male undergraduate student with 11–15 years of gaming experience. He mentioned that he played a variety of games such as role-playing games, strategy games, shooters, and so on a few times a week. He chose The Last of Us .

Description and rationale of game choices

The Walking Dead (PC game) is set in a fictional world in which a zombie apocalypse has occurred. The player controls Lee Everett to explore the story world and is accompanied by several survivors, including Clementine, a young girl. The Last of Us (PS3 game) is set in a post-apocalyptic world in which a mutated strain of the Cordyceps fungus has infected humans and transformed them into zombie-like creatures. The player controls Joel to explore the story world and is accompanied by Ellie, a young girl.

Data analysis

The thematic analysis (Braun & Clarke, 2006 ) has been used to code the types of learning of Participants 1 and 2. Theoretical thematic analysis involves the use of theoretical frames in a deductive way to search across the data set in the form of the think-aloud verbalisations and players’ reflections in the gameplay recordings and the interviews to discover repeated patterns of meaning. The coding categories were developed a priori from relevant literature (e.g. Toh & Lim, 2021 ) and included the three main types of learning, namely, critical thinking, empathy, and multimodal literacy. During the thematic analysis, the researchers familiarised themselves with the data by watching the gameplay recordings and listening to the interviews multiple times. During each review of the data, the researchers generated initial codes and then collated these codes into themes. The themes were then reviewed and defined to arrive at the final analytic scheme (Braun & Clarke, 2006 ). The two authors of the paper coded the data, and they have received prior training to conduct the analysis. The data were independently coded by the two authors, and disagreements were discussed to reach a consensus.

Case 1 Footnote 1 involved Participant 1, who played The Walking Dead Season 1, Episode 1. The selected gameplay segment was set at the Travelier Motel. In a previous scene, Glenn, the non-player character (NPC), had gone searching for supplies and gas at the motel for Lee’s group. He noticed a woman, Irene, in a boarded-up room on the upper level of the motel. When Glenn tried to talk to her, she asked him to leave. Walkers emerged from the forest, and Glenn was forced to hide in an icebox until Lee and Carley arrived to rescue him. The trio then decided to rescue Irene together.

The analysis of this gameplay segment indicated that Participant 1 adopted a problem-solving and inquiry-based approach (Toh & Kirschner, 2020 ; cf. Squire & Jan, 2007 ) to reach Irene. Participant 1 performed the following actions sequentially and iteratively: understand (orientate), plan (conceptualise), act (apply), and reflect (evaluate). First, Participant 1 understood how to proceed by listening to the characters. For example, Lee hinted that stealth was important to proceed by saying that “Noise attracts these things”. At 3:16, Participant 1 demonstrated his understanding of using stealth to reach the objective by repeating that “noise attracts these things”.

At 4:12, the game hinted to Participant 1 that peeking too long will result in a “game over” if the zombies detected him. The linguistic text warned Participant 1: “Peek too long, and you will be seen”. Simultaneously, Participant 1 saw the visual display turning red and heard the heartbeat sound as he peeked over the wall to observe the setting. In his first attempt, Participant 1 peeked too long, so a “game over” occurred. Participant 1 laughed loudly at 4:22 as Lee died comically (Newman, 2016 ). Participant 1’s unsuccessful first attempt demonstrated how he experimented with the game rules to understand and plan his actions to progress the game. After his first failure, he understood that one specific condition that could result in a “game over” for him was his exposure to the zombies beyond a specific time limit.

Participant 1 continued to understand and plan the correct sequential order to reach the objective. As he crossed the road to go towards the recreational vehicle (5:05), the game hinted to him that he needed a weapon to kill the zombies by having Lee verbalise that he was not sure whether he could take out the zombies even if he had a weapon. This was followed by the camera’s zooming in on the zombies who were obstructing Lee. The game also hinted to Participant 1 by having Lee verbalise, while being shown the car and the zombie, that he could use the car to kill the zombies (6:10). However, before Participant 1 can use the car, he must remove the zombie who was lurking near the front of it.

Participant 1 then noticed an awl inside a locked vehicle, which he assumed can be used to kill the zombie lurking near the car (6:25). Participant 1 chose to hit the glass but was unsuccessful (6:33). Glenn hinted to Participant 1 that his action had attracted the zombie’s attention. At 6:50, Participant 1 reflected that the awl was the weapon that he needed and he must find some way to get it quietly. He planned his next action by commenting that he had to kill the zombie with the awl before using the car to kill something else (7:05).

When Participant 1 returned to the brick wall, he found a pillow on the other side of the wall. He planned to use the pillow to smother the zombie and kill him quietly with some other implement. Carley reaffirmed Participant 1’s plan by hinting, “Good luck smothering them to death”. Returning to the front of the vehicle, he killed the zombie quietly by smothering him with the pillow and asking Carley to shoot him with her gun. Participant 1 then reflected that the action will not work in real life because the gun did not have a silencer.

After removing the zombie, Participant 1 opened the car’s door, retrieved a spark plug, unlocked the gear shift, and opted to push the vehicle towards the wall to immobilise a zombie there (10:34). Returning to the car with the awl inside it, Participant 1 used the porcelain on the spark plug to break the car window to retrieve the awl (11:42). Finally, Participant 1 reflected that he can use the awl to kill the other three zombies (12:12). He then killed these zombies with the awl (13:25, 14:00) and retrieved the axe from the wall (14:27). Finally, Participant 1 reflected that he felt safer with the axe (14:32). He easily killed the last two zombies to reach the trapped survivor (15:22).

Case 1 demonstrates how Participant 1 adopted a problem-solving and inquiry-based approach to reach the game goal. Participant 1’s ability to perform his actions in the correct sequential order in an iterative manner enabled him to remove the zombies obstructing him from reaching the woman trapped on the upper level of the house across the street. Our analysis of his think-aloud shows how he safely removed the zombies through critical thinking and reflection before he succeeded in reaching the trapped woman to save her.

Case 2 Footnote 2 involved Participant 2, who played The Last of Us . The segment that we analysed occurred in the winter chapter when Ellie escaped from David, the antagonist, after his failure to recruit her into his group. Joel was searching for Ellie when she escaped from David. This gameplay segment involved Participant 2’s alternating control of Joel and Ellie. This alternating control allowed Participant 2 to demonstrate empathy for both characters, the understanding of their thoughts, feelings, and actions through embodied play and perspective shifting (Toh & Lim, 2021 ; Elliott et al., 2011 ).

Ellie killed James (David’s partner) with the chopper on the table when he was distracted while talking with David. She escaped and grabbed a knife from a nearby table for protection as David attempted to shoot her but missed. The cutscene ended as Ellie escaped into the snow, and Participant 2 was given control of Ellie in the snow outside (19:10). He controlled her to take shelter in a nearby building. Ellie’s verbal utterance and subtitles informed Participant 2 that Ellie needed to find a gun to protect herself (19:28). Inside the building, Participant 2 overheard David ordering his people to find Ellie (20:20). He controlled Ellie to sneak into another building and planned to wait for David’s people to come inside for him to kill them individually (21:17). When the first man came in, Participant 2 stealthily stabbed him and obtained a revolver (21:45). He repeated his action on the other man who entered the building (22:09).

As the game progressed, the video showed that he faced difficulties when Ellie had to fight two or more men simultaneously. This led to Ellie’s being surrounded and killed. In a later gameplay segment, he planned to distract and kill David’s men inside another building (34:20). He succeeded (34:48), but Ellie was killed by a nearby enemy who detected Ellie and shot her (35:05). This heightened Participant 2’s feeling of vulnerability when he played as Ellie. He said that he had to retry the game segment (35:07). When he replayed this segment, he was killed again as he controlled Ellie to fight the two men directly instead of stealthily (36:30). He reflected that he had to sneak into that room (36:40). During the third (37:30), fourth (38:24), and fifth attempts (39:47), he failed again when Ellie was surrounded and killed. He reflected: “The idea was there—the execution (39:50)”. Finally, on the sixth try, he cleared this segment by separating David’s men and stealthily killing them one at a time (40:30).

Participant 2 entered the open area in a restaurant and triggered the fight with David (45:58). During the fight, Participant 2 used Ellie’s stealth ability to track David’s location and planned his attacks. Participant 2’s ability to use Ellie’s ability to track David’s movements by sound was key to performing a stealth attack on him.

After Participant 2 stabbed David thrice, the game changed perspective and allowed him to control Joel to search for Ellie (56:25). When Participant 2 entered a nearby building, he heard David’s men searching for Ellie (57:05). It was easier for Participant 2 to play as Joel because he could choose to engage in close combat and kill enemies with a single blow of the axe (57:29, 57:48) or use stealth attacks. With Ellie, he could only use stealth attacks. As Participant 2 cleared several gameplay segments, he entered the slaughterhouse and found Ellie’s backpack (1:09:04). From Joel’s verbalisation, “What is this? Why is Ellie’s stuff here?”, Participant 2 understood that Joel was worried about Ellie (1:09:19). He picked up a meat ledger note that indicated the amount of meat that David’s men, who were cannibals, had collected for supplies (1:09:30). This note, along with the human corpses in the meat locker (1:09:50) and Joel’s utterance “I gotta find her”, (1:09:55) further underscored Participant 2’s understanding of Joel’s concern for Ellie’s safety. Participant 2 had just played as Ellie and understood the danger Ellie faced as she fought against David and his men.

Case 2 shows how Participant 2’s ability to control 2 characters allowed him to demonstrate empathy by understanding their thoughts, feelings, and actions through embodied play and perspective shifting. Our analysis of his think-loud and observation of his actions during the gameplay shows how Participant 2’s empathetic concern for Ellie motivates him to find her when he played as Joel.

Critical thinking

In the field of education, Bloom’s ( 1956 ) taxonomy is the most widely cited source when it comes to teaching and assessing higher-order thinking skills. Bloom’s ( 1956 ) taxonomy consists of the lower-order thinking skills, such as remember (recall, recognise), understand, and apply as well as the higher-order thinking skills, such as analyse, evaluate, and synthesis, which are frequently said to represent critical thinking (Kennedy et al., 1991 ). The analysis of Participant 1’s gameplay recording showed his ability to select information from the game world, reflect on it (e.g. failure to progress the game), and integrate it into a coherent whole in a mental model to gain a deeper understanding of the story, rules, and mechanics (Toh, 2018 , Buckingham, 2015 ). When he played the game, we observed that he was applying his critical thinking: the selection, evaluation, and integration/synthesis of information provided by digital texts (Salmerón et al., 2018 ) by adopting the inquiry-based learning approach (Toh & Kirschner, 2020 ) to reach the objective.

Participant 1 demonstrated an iterated approach of using a mixture of lower and higher-order critical thinking skills to progress the game. At the start of this gameplay segment, Participant 1 demonstrated lower-order critical thinking skills, such as recognising through his counting of the number of zombies that must be overcome to reach the objective. He demonstrated understanding by explaining what he had to do for this gameplay segment through his think-aloud “Ya, so basically, we are here rescuing Glenn from [the zombies]”. He also demonstrated recall by commenting on what happened previously in the game “He [Glenn] came to top up petrol from the motel but he got into a bit of trouble and now we have to rescue this survivor upstairs over here, yes.”, which is followed by understanding as he explained what he had to do to achieve the gameplay objective “So, we have to kill all the zombies to rescue her. So, let’s find some way to kill them quietly”.

At 4:10, Participant 1 experienced how the losing condition of the game could happen by peeking over the wall at the zombie eating the dead person on the ground. However, he spent too long peeking and Lee ended up being eaten by the zombie. On his second attempt, he demonstrated his understanding (a lower-order critical thinking skill) of the losing condition of the game by commenting that “Oh, it looks like a timed thing” and controlled his character not to long too long over the wall. At 5:36, Participant 1 demonstrated the use of evaluate, a higher-order critical thinking skill as he reflected on how Lee can see over the wall but not when he was running.

At 7:05, from Participant 1’s verbalisation that he had to kill a zombie in front of the vehicle with an awl (“the screwdriver”) before using the car to kill another zombie, he demonstrated planning and analysis, which is a higher-order critical thinking skill. At 8:54, Participant 1 demonstrated the use of the lower-order critical thinking skills when he applied his plan and chose the action in the dialogue option to kill the zombie quietly by covering him with the pillow and asking Carley to shoot him with her gun. Finally, Participant 1 demonstrated a higher-order critical thinking skill, such as evaluation from his verbalisation that the action would not have worked in real life because the gun did not have a silencer.

Likewise, a learning observed from the participants’ gameplay is empathy, that is the ability to understand and share the feelings of others (CASEL, 2015 ). This was observed in Participant 2’s gameplay. For example, when the game allowed Participant 2 alternate control of Ellie and Joel, he used embodied action to gain a better understanding of both characters’ playstyle through situated and just-in-time learning (Gee, 2005 ). Another example observed in the gameplay recordings was when Participant 2 discovered Ellie’s backpack, the meat ledger, and the hanging corpses, and he showed his concern for Ellie’s safety. For instance, in 1:09:19, Participant 2 verbalised that Joel felt worried for Ellie when he found her backpack in the slaughterhouse. He appreciated that Joel’s actions had been driven by his fear for Ellie’s safety. Participant 2 demonstrated his empathy in an interview:

So later on, when you shift to Joel to control him to save Ellie, did you feel an even more urgent need to save her? Because you discovered Ellie’s backpack.

Because you played what Ellie’s going through right? So, you know that she needs help. So, in that sense, you can empathise more with what Joel is feeling, as in Joel doesn’t know what is happening to Ellie, but you know the emergency. So …

When you discover all her objects, huh?

And then the slaughterhouse.

Um-hmm. So, he knows that she’s not in a good place.

In the above interview, Participant 2 explained how his ability to control two different player characters one after the other during the gameplay allowed him to understand both characters’ thoughts, feelings, and actions. Because Participant 2 was given control of Ellie early in the Winter chapter of The Last of Us , he was able to feel Joel’s sense of fear for Ellie’s safety when the game later offered him control of Joel to look for her. As Participant 2 had been able to play as Ellie, he could understand her precarious situation in the game world when she met the antagonist, David with his group of cannibals while searching for supplies to take care of Joel. David appeared to Ellie as a compassionate man who looked out for her needs and he even fought together with Ellie against waves of Infected enemies during their initial encounter.

However, as the chapter progressed, Ellie discovered that David and his group were cannibals. David captured Ellie and offered her a place in his group. When she rejected his offer, David and his man attempted to slaughter Ellie for food, but she managed to escape. The game then switched control to allow Participant 2 to play as Joel after playing as Ellie. He could then feel a greater connection to both player characters because he possessed more information than either of the player characters possessed on their own in the game world. The perspective shift (Toh & Lim, 2021 ) in the game therefore allowed Participant 2 to demonstrate empathy when playing the game.

Multimodal literacy

We also observed that the participants demonstrated multimodal literacy in their engagement with the multimodal orchestration in the game, such as the verbal mode of the NPCs, the linguistic mode of the game hints, the visual representations of the characters, and the characters’ actions and gestures to gain an overall idea of how to progress the game. Multimodal literacy (Jewitt & Kress, 2003 ; van Leeuwen, 2017 ) involves both critical and creative engagement with multimodal representations that reflect a semiotic awareness (Lim, 2021a ; Lim, 2021b ). Multimodal literacy also involves an understanding of the affordances of the different meaning-making resources and how they work together to produce a coherent and cohesive multimodal text (Mills, 2016 ). The player’s multimodal literacy refers to their sensitivity to the design features in the video games, including knowing how to work across different semiotic modes, such as language, visuals, audio, music, and action to perform critical and creative actions in the game.

Participant 1’s multimodal literacy can be observed at the beginning of the gameplay segment. He demonstrated verbal awareness by listening to the characters’ verbal interactions in the cutscene before commenting through his think-aloud to show his understanding that he must rescue the survivor in the house across the street, to achieve the winning condition of this gameplay segment. We see how he showed a visual awareness of the objective, by pointing at the house across the street with the mouse pointer to indicate his understanding that he must reach the objective, the house to progress the game. He showed us his linguistic awareness by following the game hints provided through the linguistic prompts, such as “peek over the wall”, “push car”, “look at truck”, “open door”, “examine window”, amongst others to perform the micro actions of the gameplay so that he can reach the gameplay objective. He also demonstrated an action awareness, which refers to his understanding of the dynamic interplay between game and player (Toh, 2018 ; Apperley & Beavis, 2013 ; Beavis, 2014 ) by selecting the specific actions in the correct sequential manner to interact with the zombies and overcome them to reach the woman in the house across the street. He combined his verbal awareness, visual awareness, linguistic awareness, and action awareness in the gameplay to reach the objective and progress the story.

Participant 1 also demonstrated his multimodal literacy in quickly making sense of the orchestration of multimodal meanings through the semiotic resources. He combined the visual mode of the entire screen turning red, the auditory mode of a pulsating heartbeat, the linguistic mode of a text that warned him not to peek for too long, and the verbal mode of the player character’s announcing that the zombie had discovered him to come to his understanding of the losing condition of this gameplay segment. Participant 1 verbalised his reading of the situation through his think-aloud that “it looks like a timed thing” to reflect his understanding that his peeking over the wall beyond a certain time limit resulted in the losing condition whereby his character was killed when the zombies discovered where he was hiding.

The findings of this study affirm the findings from previous studies that playing video games can allow players to demonstrate critical thinking (e.g. Gumulak & Webber, 2011 ) and empathy (e.g. Hilliard et al., 2018 ). Additionally, our study adds to the field of knowledge by showing that players can demonstrate multimodal literacy (Lim, 2021b ) during gameplay by learning how to combine information from semiotic modes, such as the language, verbal, visual, and aural modes to come to an overall understanding of the game. Their demonstration of their multimodal literacy is evidenced in their think-aloud verbalisations where they articulated how they understood, planned, acted, and reflected on how to progress the game by selecting and integrating information from multiple semiotic modes, such as language and visuals during the gameplay process. From an educational standpoint, we have noted that there is a difference between demonstrating these skills within a game context and having the players transfer skills such as critical thinking in digital play to academic subjects or real-world situations. We recognise that the demonstration of these skills in video gameplay does not mean that players are able to transfer the critical thinking to academic subjects or empathy to real-world situations. With this in mind, we have explored ways in which educators can design for digital play in the classrooms, such as introducing a pedagogic metalanguage for digital play (Toh & Lim, 2021 ; Lim & Toh, 2022 ) which teachers can use to guide players in transferring their critical thinking and empathy through reflection questions during classroom activities.

The affordances of video games that can facilitate the expression of these multiliteracies include immediate feedback from semiotic resources in the game world (Nadolny et al., 2020 ) and a safe space (LaFleur et al., 2017 ) that allows the player to retry again after failing the gameplay segment. Additionally, scaffolded learning in the form of virtual learning companions (Calvert, 2017 ) and multilinear pathways (Roswell & Wohlwend, 2016 ) in the gameplay can allow players to try out different approaches of solving a problem to demonstrate their critical thinking. Finally, the player’s ability to take control of two player characters during gameplay to understand their thoughts, emotions, and actions (Toh & Lim, 2021 ) can support their demonstration of empathy.

In contrast to empirical studies that suggest learning occurs in stages (e.g. Luft & Buitrago, 2005 ), our findings showed that learning is a nonlinear and iterated process where sometimes the learner may experience progress in their learning, but at other times, they may experience failure if they uncritically applied one approach that worked in a previous context on a different context. For instance, Participant 2 failed when he tried to play Ellie using Joel’s direct approach of attacking enemies in the open instead of adopting stealth when fighting multiple enemies.

Digital play is arguably attractive to people from all ages but is especially appealing to children and youths because of design features, such as immediate feedback, social affordances, and the presence of multisensory stimuli when using mobile devices and games to interact with others (Marlatt, 2018 ; Oliver & Carr, 2009 ). Notwithstanding the value of digital games, concerns have also been raised about the risks, such as exposure to sexual (Tompkins & Lynch, 2018 ) and violent content (Elson & Ferguson, 2014 ) as well as potential addiction (Grüsser et al., 2007 ) and health issues (Saunders & Vallance, 2017 ) related to the prolonged screen time with mobile devices. While these concerns are understandable, it is also acknowledged that studies have found no evidence of negative effects that playing violent video games has on youths (e.g. Ferguson & Olson, 2014 ). In addition, to mitigate the concerns on the possible ills of digital play, strategies of integrating digital play and learning into pedagogical context, such as the use of metacognitive scaffolding for inquiry-based learning activities (Ibáñez & Delgado-Kloos, 2018 ) and reflection questions to allow teachers to guide students’ digital play (Toh & Lim, 2021 ) have been proposed.

With the increasing ubiquity of mobile devices and gaming activities amongst youths and children, we argue that adults should not disregard youths’ use of video games. Instead, they can design learning experiences with video games using a series of learning activities and scaffolding questions structured by theoretical frameworks, such as Cope and Kalantzis’ ( 2015 ) learning by design framework or the metalanguage that we have developed for digital play (Toh & Lim, 2021 ; Lim & Toh, 2022 ). The framework allows adults to design learning using guided inquiry techniques, such as reflection and conversational prompts after gameplay for youths’ learning.

Given the resistance typical schools may have towards the use of video games for learning (Bourgonjon et al., 2013 ; Gee, 2005 ), we recognise that the degree of integration of video games into formal learning contexts will depend on the receptiveness and attitude of the educators, parents, and students (Mifsud et al., 2013 ). Nonetheless, video games can be used well in the classrooms for teaching and learning STEM subjects (e.g. Ormsby et al., 2011 ) or content subjects involving ethical thinking (e.g. Schrier, 2015 ), decision-making (Toh, 2021 ), and narrative concepts (Ostenson, 2013 ) in many schools.

In this study, we have explored the digital play of two players using a qualitative case study approach to examine the display of critical thinking, empathy, and multimodal literacy in their gameplay. These are important life skills that overlap with the skills required in school and the workplace. Through this study, we hope to advance the call for educators to harness video games in teaching, given how it can bring about different types of learning in the youths.

We also acknowledge that the limitations of the study include the male gender bias of the subjects recruited for the study due to the snowball and convenience sampling method used. Additionally, the qualitative research methods used, such as interviews, think-aloud protocol, and observations in the laboratory can be complemented with more objective measures in future studies, such as galvanic skin conductance, eye tracking, and brain scans to triangulate the findings. Future studies can also use a broader range of games to elicit the different types of learning that are demonstrated by gameplayers.

Availability of data and materials

The video recordings of the data analysed in the study have been provided in the endnotes of the manuscript for case study 1: https://tinyurl.com/Case00001 and case study 2: https://tinyurl.com/Case000002 .

The analysis of the scene started at 1:10 and ended at 16:40. https://tinyurl.com/Case00001 .

The analysis of the scene started at 17:54 and ended at 1:10:45. https://tinyurl.com/Case000002 .

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This work was supported by the National Youth Council’s National Youth Fund (NYF) grant and the National Institute of Education, Nanyang Technological University, Singapore’s Planning Grant PG 03/20 VLF “Multimodality and Pedagogy (MaP): A Systematic Review” (2020–2021).

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Idea: FVL and WT; Literature review: WT; Methodology: WT; Data analysis: WT; Case studies: WT; Findings and conclusions: FVL and WT; Writing (original draft): WT and FVL; Final revisions: FVL and WT; Project design and funding agency: FVL. Both authors read and approved the final manuscript.

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Weimin Toh is Research Fellow at the National Institute of Education, Nanyang Technological University, Singapore. His research interests are social semiotics, multimodal discourse analysis/multimodality, game studies, and game-based learning.

Fei Victor Lim is Assistant Professor at the National Institute of Education, Nanyang Technological University, Singapore. He researches and teaches multiliteracies, multimodal discourse analyses, and digital learning. He is editor of Multimodality and Society and author of the book Designing Learning with Embodied Teaching: Perspectives from Multimodality published in the Routledge Studies in Multimodality.

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Toh, W., Lim, F.V. Learning in digital play: a dual case study of video gamers’ independent play. RPTEL 17 , 6 (2022). https://doi.org/10.1186/s41039-022-00182-2

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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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Video Gaming Addiction: A Case Study of China and South Korea

Posted by Ryan, Amanda | Dec 13, 2021 | American Politics(B) , Asia(B) , China(B) , U.S.(B) | 0 |

To wrap up summer vacation, the two leading countries combating internet and gaming addiction—China and South Korea—took a step in diverging directions. This raises the issue of which country serves as a better model for the U.S. government and American gaming companies. With both countries entering the year enforcing similar policies of reducing the amount of play time available to minors, it came as a surprise when China’s increase in limitations was met alongside South Korea’s plan to abolish the harsh restraints. Ultimately, South Korea recognized the flaws in their previous law and is modifying their game plan to include less restrictions and encourage more self-regulation. After reviewing scholarship and research studies which analyzed the previous laws enacted by China and South Korea, the latter’s new, more flexible approach appears to be most promising for the U.S. to take into consideration.

Douglas Gentile, developmental psychologist and the Director of Research for the National Institute on Media and the Family, estimated that over 8.5 percent of children and teenagers—roughly 3 million Americans—exhibit multiple signs of gaming addiction [1]. Currently in the Western world, video game-related regulations are limited to rating systems which evaluate content and maturity-levels rather than the overuse of gaming [2]. As video game addiction becomes increasingly prevalent, understanding, and ultimately comparing, the different prevention approaches is vital in protecting the health and development of younger generations.

What is Gaming Addiction?

Video gaming has beneficial and adverse effects on the cultural attitudes, psychological development, and lifestyle choices of young gamers [3]. For instance, a 2009 study in the Annual Review of Cybertherapy and Telemedicine found gaming can alleviate stress and depression; Dr. Daphen Maurer of the Visual Development Lab discovered gaming can improve eyesight and increase dopamine levels; and cognitive neuroscientists at the University of Rochester found video games can enhance decision-making skills [4]. Especially during the recent pandemic, where isolation and a lack of social interaction was prominent, the ability to engage with others via gaming provided much needed “social connection, escapism and relief for millions of kids and teens” [5].

Although the evolution of technology and the internet has brought numerous benefits, many negative ramifications have been uncovered as well. One of the most significant impacts of problematic internet-use gaining momentum is the onslaught of video gaming addiction. As a subset of internet addiction, video gaming addiction is often when gaming is taken to the extreme—ultimately impairing an individual’s ability to function either socially, academically, or financially [6]. In 2014, a study by Zhejiang Normal University discovered that gaming addiction can lead to “lower volumes of gray and white brain matter,” which can cause impairment in decision-making, regulating emotions, and impulse control [7]. Likewise, the comorbidity rate of the gaming disorder with depression, anxiety, and ADHD is significantly high, as many young gamers use gaming as a coping mechanism [8].

While the classification of video gaming addiction as a mental illness is somewhat controversial, organizations have recently spoken up about the issue. In 2013, the American Psychiatric Association (APA) included an Internet Gaming Disorder in the DSM-5 , and, in 2018, the World Health Organization (WHO) stated Gaming Disorder (GD) will be listed in the 11 th addition of the International Classification of Diseases [9]. With nearly three billion people playing video games worldwide, 3-4 percent of them—more than 60 million gamers—are likely to be suffering from gaming disorder [10].

In China, problematic video gaming has been recognized as a public health crisis [11]. In 2007, around 14 percent of Chinese adolescent internet users—about 10 million teenagers—met the diagnostic criteria for internet addiction [12]. According to the China Internet Network Information Center, this number increased 16 percent by 2018, with over 30 percent of minors suffering from gaming disorder [13]. With the issue growing in severity, China placed video gaming addiction on par with substance-abuse and drug addictions, labeling the activity as “spiritual opium” [14].

Similarly, South Korea considers internet addiction as one of the country’s most critical health issues [15]. By 2015, internet usage in South Korean households rose to 85.1 percent across all ages [16]. Comparable to the duration of a part-time job, the average South Korean teen spends over 23 hours per week playing video games [17]. In Seoul, the capital of South Korea, a common leisure activity for youths is to stop by a ‘PC bang’—an internet gaming room or cafe, typically open 24 hours, where players have access to comfortable seating and fast computers for a dollar an hour [18].

Following trend lines for the addiction in South Korea, in 2012, an estimated 2.55 million people were addicted to their smartphones and the internet [19]. For adolescents in particular, around 12.5 percent of teenagers were at risk for internet addiction disorder in 2014 [20]. And in 2019, the latest government-issued survey revealed over 20 percent of South Korea’s population—nearly 10 million citizens—were now at risk for the addiction [21]. Due to the isolating nature of the COVID-19 pandemic, many countries have reported an uptake in the amount of time minors spent gaming, suggesting a probable increase in problematic gaming for South Korean adolescents [22].

Initial Prevention Response Plans

International response and prevention plans vary, with some countries authorizing harsher, more hands-on restrictions than others. But how effective are these various responses in curbing behavioral addictions? China and South Korea provide case studies of possible responses and their likely consequences.

From 2000 until 2015, China banned the production and sale of popular gaming consoles—including Xbox and PlayStation—in an attempt to reduce the likelihood of children developing addictions [23]. However, many players worked around this obstacle by illegally purchasing consoles, or simply turning towards PC and mobile games instead. Shortly after the ban was lifted, their government placed restrictions and censors on the “harmful attributes” in video games, including the addictive qualities of in-game rewards and achievements, as well as the portrayal of violence [24]. Specifically, China introduced an Online Game Addiction Prevention System (Fatigue System) in 2007, which targeted the addictive qualities of games [25]. In this system, as the time a person spent gaming increased, the number of rewards they could obtain decreased and pop-up warnings of unhealthy playtime appeared in an effort to limit the gamer’s desire to keep playing. However, as mentioned in sections below, this system proved largely ineffective and was ultimately discarded [26].

As for treatment measures, China established centers aimed at rehabilitation to address problematic gaming, such as at the General Hospital of Beijing Military Region’s Internet Addiction Treatment Center [27]. Likewise, to further reduce the negative impact of the internet on minors, China passed the Minors Internet Protection Ordinance in 2016, which limited nighttime gaming, provided education to guide players, and required gaming companies to adhere to anti-addiction parameters [28]. Yet, with more minors continuing down a path towards addiction, a revision for the law was required [29]. In 2019, China went a step further and created tighter time restraints on how long minors were allowed to play video games—limiting players to 1.5 hours on weekdays, 3 hours on weekends and holidays, and only during daytime hours [30].

With over 720 million gamers by 2021, gaming culture prospered in China, leading the country towards becoming the largest market in the video gaming industry [31]. By having such a substantial portion of the population active in gaming, and with many of the previous restrictions easily circumvented, the need for an effective method in China to stop addiction became even more crucial.

South Korea:

In response to the rise in internet-related addictions, South Korea established the Internet Addiction Prevention & Resolution Comprehensive Plan in 2010 [32]. Led by the National Safety Administration-affiliated agency of the MSIP, the primary goal was to establish intervention systems for problematic game and internet use before addiction manifested [33]. Although, while posing many benefits for minors at risk, these approaches were also criticized for the lack of “inter-agencies collaboration and clinical conceptualization” [34].

To assist those already effected, many treatment centers were founded to support the recovery of youths suffering from gaming addiction [35]. One of these programs is the Jump Up Internet Rescue School, where internet or online gaming addicted children are sent to a camp designed for rehabilitation—guiding minors in their journey through adapting healthier hobbies and learning new coping mechanisms [36].

In 2011, South Korea passed the Youth Protection Act, also known as the Shutdown Law or “Cinderella Law,” restricting the hours minors could play video games [37]. Under this law, those under the age of 16 were unable to access online games between midnight and 6am in an effort to promote healthy sleeping habits, increase productivity and attentiveness in the classroom, and prevent the likelihood of addictions to develop [38].

2021 Modifications in Gaming Prevention

Although both countries enforced strict video gaming strictions in the past, their policies deviated in 2021: China pushing for even stricter regimens on gaming, while South Korea is tearing down their shutdown law in favor of more flexible moderating and a stronger emphasis on health services. For China, authorities claim that rolling out firmer measures to limit minors’ gaming exposure come from a desire to safeguard their physical and mental health—as well as to satisfy a concern from parents that the old policy was insufficient [39]. On the other hand, South Korea is moving in the opposite direction in hopes of “respecting the rights of the youth and encourage[ing] healthy home education,” and to break away from the shutdown law’s ineffectiveness [40].

Released by the National Press and Publication Association (NPPA), China tightened the 2019 restrictions of online gaming for minors to one hour per day—8 PM to 9 PM—on Friday, weekends, and public holidays [41]. In addition to strict time restrictions, identification systems were installed to ensure the rules are followed, essentially forcing minors to enter identification—such as real names, government-issued ID documents, or identification numbers—before playing [42]. However, since many gamers under 18 attempt to bypass this limitation by acquiring fake ID numbers or using VPNs, the policy also requires gamers to register their ID number for fact-checking in the national citizen database [43]. Following suit, gaming companies have launched new methods to increase the likelihood of player cooperation. Tencent, one of China’s major gaming companies, recently introduced “facial recognition technology and an algorithm that identifies underage players” [44].

Issues with China’s 2021 Modification

China is asserting a strong association of high playing time with addiction—where more hours spent gaming equals addiction. However, China’s emphasis on time as the determining factor leading to addiction is misguided [45]. In 2018, a study published in the Journal of Behavioral Addictions by Kiraly et al., analyzed the effectiveness of policy responses on problematic video game use. The study argued that the strict policy and regulation approaches limiting playtime “were not sufficiently effective” and henceforth called for more “integrative approaches” for improvement [46]. Additionally, another data set found that gaming time is “weakly associated with negative psychological factors” often found in problematic use [47].

According to WHO, the diagnostic criteria for the “gaming disorder” does not include a specific amount of playtime [48]. Rather, that gaming must cause distress, impairment in the gamer’s life and ability to function, and typically last for at least one year [49]. Like with many behaviors, there is a substantial difference between those who are simply enthusiastic about the activity and want to dedicate time towards it with those who are addicted to it. Ultimately, all behaviors exist on a continuum, and the point where an individual falls isn’t fully decided according to the amount of time allotted to the behavior.

Instead, the threshold differentiating regular gaming (unproblematic behavior) from a gaming disorder (problematic behavior) resides with the effect the activity has on the gamer—as well as the gamer’s response to those outcomes [50]. In other words, the amount of time a person spends breaking blocks in Minecraft , farming crops in Stardew Valley , or leading revolutions in Homefront doesn’t guarantee the development of an addictive behavioral disorder. Alternatively, if a person is so absorbed in their gaming that they repeatedly forget to pick up their kids from daycare, sneak in round after round of solitaire in the office instead of finishing a report, or demonstrate their gaming is negatively impacting their life on another significant level—and continue to game regardless—then that behavior can enter the realm of addiction. By itself, the amount of time spent gaming isn’t a reliable predictor of problematic use; therefore, for China to implement harsher time restraints as the primary driver of their response plan to video gaming addiction demonstrates their shortcomings in addressing the heart of this issue.

Another failure with China’s law is that it only effects the gameplay of minors. However, recent data has proven that the median age of gamers is 24, and a growing demographic in gaming addiction is people in their 20s and 30s [51]. According to a specialist in gaming addiction, adults often turn to video gaming for the same reason teens do: to escape the harshness of reality—unemployment, isolation, and relationship issues [52]. Hence, to properly address all vulnerable groups susceptible to gaming addiction, an approach geared towards more than just minors is needed.

Similar Issues with South Korea’s 2011 Law

Regarding South Korea’s shutdown law, Jiyun Choi et al. in the Journal of Adolescent Health analyzed data collected from the Korea Youth Risk Behavior Web-based survey from 2011 to 2015, concluding the “shutdown policy had practically insignificant effects in reducing Internet use for target adolescents” [53]. Among middle school students, the effects of the initiative were null on internet abuse, and only increased sleep duration by a mere 2 minutes [54]. In fact, the shutdown law’s strategy was indicated to have an overall damaging effect—both on the average player’s experience and leaving “the players wanting more,”—consequently raising the potential for addiction [55].

Mainly, as explained with China’s new law, the shortcomings may be linked to the fact that the policies outlined “only address or influence specific aspects of the problem” and fail to recognize the individual differences between gamers [56]. For instance, the forementioned 2018 study by Kiraly et al. revealed that the policies by China and South Korea tended to focus on only one of the following: (i) reducing time spent gaming, (ii) changing the addictive potential, (iii) trying to help gamers by looking at psychological and motivation factors behind their desire to game [57]. Tackling video gaming addiction through only one of the forementioned approaches isn’t sufficient to properly address the issue, rather the most efficient mode of attack requires a cohesive regulation approach that targets multiple aspects. Additionally, according to the study, another method to solve this issue is through a targeted prevention approach: where warnings can be customized to target problem behaviors without encroaching on the “non-problematic gamers’ enjoyment of a largely healthy pastime activity” [58].

South Korea’s 2021 Plan

Ten years after the controversial shutdown law, South Korea is removing government-controlled time restraints in gaming to stay up to date on digital trends, respect young people’s rights, and allow households to enforce limitations themselves [59]. By the end of the year, following the modification of the Youth Protection Act, South Korea will be relying on the “choice permit system,” where parents and underage gamers can request a permit to designate their own playing hours [60]. The Korea Association of Game Industry is in favor of the decision, expecting the new plan to release the hold the previous law held over their gaming industry and children’s rights, as well as reducing the likelihood for addiction to significantly manifest [61].

Notably, one of China’s concerns and motivators behind their aforementioned time restrictions revolve around the misdirection of priorities. It is true that children repeatedly opting to game over completing their algebra homework, or game late into the night instead of getting a full eight hours of sleep, can hinder their ability to learn and satisfy academic responsibilities—as studies in China have shown that problematic video gaming interferes with “sleep, mood, and social learning in children and adolescents” [62].

However, forcibly removing gamers from the gaming environment ‘cold turkey’ can cause considerable distress and negate the benefits that games have demonstrated [63]. It’s important to acknowledge that gaming can generate positive impacts as well. In a study exploring the benefits of gaming, published by the National Center for Biotechnology Information, it was discovered that children who regularly play video games in healthy doses develop an improvement in cognitive abilities—such as deductive reasoning, processing speeds, mathematical intelligence, and skills pertaining analogy—over those who do not game [64].

The notion of time constraints isn’t completely invalid, but should be executed on a moderate level according to each case—and in combination with education and treatment programs—to keep individuals focused on their priorities while demonstrating safe ways to game. To achieve this goal, South Korea’s abolishment of the restriction is paired with a shift in attention: one that focuses on “strengthening the monitoring of harmful game content,” supporting “media and game-use education,” and increasing the implementation of prevention and recovery methods—such as counseling and rehabilitation camps [65]. Moreover, with an aim to raise awareness of problematic gaming habits, outreach programs pertaining the nature of gaming culture, media literacy, and the risks for addiction are included in this renewed focus on education [66].

Hwang Hee, Minister of Culture, Sports and Tourism in South Korea, expressed that gaming is an important avenue for youths to release stress and connect with others; therefore, the new measures strive to encourage these benefits by “establish[ing] a healthy culture of gaming and leisure for teenagers in a flexible manner” [67]. This revised system is more permissive than China’s reinforced gaming restrictions, subsequently leaving “China as the only nation to restrict gaming hours by law” [68].

Technology will only continue to evolve and integrate into our daily routines. There’s no going back to an age where smart phones and online platforms aren’t essential to everything we do, whether that be flaunting vacation pictures on social media, calculating a tip at the end of a meal, buying the latest Barbie on Amazon for Christmas, or paying taxes at the touch of a button. We have the world at our fingertips; however, as with every device or tool at our disposal, there is a potential for abuse.

And with the gaming industry booming, there’s no denying video gaming addiction is becoming an increasingly significant threat—especially amidst the youngest generation. By identifying the best ways to approach the issue, backed by relevant strategies that don’t take away from the benefits and experience of gaming, the ramifications can be better contained and predicted in the United States. Particularly in the wake of the recent pandemic, where gaming, streaming, and other forms of content consumption on the internet have risen exponentially to fill the void of stimulus in people’s lives.

With South Korea’s newfound direction in their efforts against video gaming addiction, and WHO adding the problematic behavior on the list of addictions, the international awareness regarding the consequences of overusing technology can receive the attention it deserves. Additionally, by analyzing these two contrasting policies, the United States can determine which aspects are most effective and gear similar techniques towards their own prevention plans. While political and cultural differences may limit the capacity for the U.S. government to fully implement all of the policies previously mentioned, gaming companies have more control on a self-regulatory basis. This could include providing built-in parental controls, warning messages for high levels of playtime, and rating systems to evaluate the addictive potential of games.

Above all, there’s a collective responsibility for parents, educators, clinicians, game developers, and the U.S. government to recognize the issue for what it is and work towards protecting all vulnerable demographics. For policymakers and community members to pay attention, take this addiction seriously, identify addict-risk teens, introduce the necessary information, and provide effective treatment programs for those in recovery.

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[11] Ibid .

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[20] Lee, Claire. (April 22, 2015). More Teenagers at Risk of Internet Addiction. The Korean Herald. Retrieved from: http://www.koreaherald.com/view.php?ud=20150422001211

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[25] Davies, B., and Blake, E. (March 4, 2016). Evaluating Existing Strategies to Limit Video Game Playing Time. IEEE Xplore. Retrieved from https://ieeexplore.ieee.org/document/7426249

[27] Stone, R. (June 26, 2009). China Reins in Wilder Impulses in Treatment of ‘Internet Addiction.’ Science. Retrieved from https://www.science.org/doi/10.1126/science.324_1630

[31] Hanson, L. (March 8, 2018). The Biggest Market By Far: Video Gaming in China. USC: US-China Annenberg Institute. Retrieved from https://china.usc.edu/calendar/biggest-market-far-video-gaming-china

[35] Choi, J., et al. (February 2018). Effect of the Online Game Shutdown Policy on Internet Use, Internet Addiction, and Sleeping Hours in Korean Adolescents. ResearchGate. Retrieved from https://www.researchgate.net/publication/323098593_Effect_of_the_Online_Game_Shutdown_Policy_on_Internet_Use_Internet_Addiction_and_Sleeping_Hours_in_Korean_Adolescents

[36] Koo, C., et al. (June 23, 2011). Internet-Addicted Kids and South Korean Government Efforts: Boot-Camp Case. Liebert Publishers. Retrieved from https://www.liebertpub.com/doi/10.1089/cyber.2009.0331

[41] Letzing, J. (September 6, 2021). What’s behind China’s video game restrictions? World Economic Forum. Retrieved from https://www.weforum.org/agenda/2021/09/what-s-behind-china-s-video-game-restrictions/

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[60] Batchelor, J. (August 27, 2021). South Korea plans to abolish gaming curfew. Games Industry. Retrieved from https://www.gamesindustry.biz/articles/2021-08-27-south-korea-plans-to-abolish-gaming-curfew

[64] Hisam, A., et al. Does playing video games effect cognitive abilities in Pakistani Children? NCBI: Pakistan Journal of Medical Sciences. Retrieved from https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6290198/

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The Case for Violent Video Games

A new book says kids know they’re a fantasy — even a healthy one..

Americans have long been drawn to the idea that violent movies or video games can provoke actual delinquency or serious crime. In 1963, the Stanford psychologist Albert Bandura performed an experiment in which one group of preschoolers watched films and cartoons of adults beating “Bobo,” a clown doll. When kids who witnessed Bobo’s travails were later left alone with the toy, they were more likely than other children to abuse Bobo themselves. Bandura concluded that “social scripts” presented on screen guide children’s behavior in real life.

Such anxieties intensified after the Columbine High School massacre in 1999. It turned out that Eric Harris and Dylan Klebold, the students who killed 13 and wounded 24, had been devotees of “Doom,” the groundbreaking first-person shooter game first released in 1993. Since Columbine, video games have only become more graphic. In “Grand Theft Auto,” players can beat and kill prostitutes; some players have written custom code for the game that allows them to rape other users. The best-selling game of 2014, “Call of Duty: Advanced Warfare,” encourages players to stage “ stealth attacks ” in which they stab characters or snap their necks.

It has long been doubtful that gaming causes crime on a mass scale. After all, gaming surged in popularity just as the violent crime rate sharply declined over the past two decades. But what if violent gaming is actually good for children — even troubled kids?

That is the contention of a new book The Game Believes in You: How Digital Play Can Make Our Kids Smarter . The author is Greg Toppo, a veteran reporter on education and a former teacher. Here Toppo talks about why even violent games can be part of healthy play.

I’m a 30-year-old woman, and few of my female friends regularly played video games as kids. I get the sense this has changed a lot. What percentage of kids today are gamers?

Some 81 percent of teens use game consoles — 90 percent of boys and 70 percent of girls. That includes really dedicated players all the way down to “Candy Crush” players. A lot of the growth in gaming across all devices has been since 2010. Mobile has really sent it through the roof.

And what percentage of these gamers are playing violent games?

The best data shows about half of kids, and 70 percent of boys, have played some of the most violent games, like “Grand Theft Auto” and “Halo.”

You cite a federal report, written by the Secret Service and Department of Education, that investigated the habits of 41 school shooters. Only five, including the Columbine shooters, were deeply interested in violent games. Yet the perception that gaming is at least partly to blame for school violence remains widespread.

What happened is that after Columbine, it became harder to get funding to study the cognitive benefits of gaming. All of a sudden, this was not something that had to be studied, it had to be controlled. It was really breathtaking. We’re just emerging from this in the past five years. But before Columbine, you could see a ton of research on things like how gaming can improve attention spans, reading comprehension, and visual acuity — really good bedrock research.

Michael Ward is an economist who has studied the growth of the gaming industry and its relationship to crime. What has he found?

There are two interesting studies. The first looked at violent crime rates around the time period when video game stores opened. He found that crime rates went down where new video game stores opened and they didn’t, by comparison, where sporting goods stores opened. The follow up compared the release of big triple-A violent games to the release of other, less violent games. It found a similar contrast. When violent games were released, crime rates went down.

If you look at Ward’s findings and the language he uses, he says, Listen, we know that the kids who would be out committing the crimes are at home playing the games . It’s almost a wink and a nod. The demographics of the gamers are the demographics of young people who commit crimes.

I get that young men disproportionately commit crimes, and also disproportionately play games. But does poverty play a role? Can poor adolescents of color who are the most likely to get arrested afford to game?

There’s not a lot of research on the economics of video game playing. But we know that “time on device” is higher for African-American and Latino kids. And there’s not much of a digital divide in terms of having gaming consoles at home or at least having access to them.

You acknowledge a body of research that competes with your own positive take on gaming. The psychologist Douglas Gentile, for example, found that players of violent games got into more arguments with teachers and more physical fights with peers.

I spent a lot of time thinking about this, because I didn’t want to ignore those absolutely serious aggression studies. I think it’s real.

Yet you argue that violent games can actually be “an affordable and efficient diagnostic tool” for parents and therapists working with troubled kids.

I talked to a psychologist from Connecticut, Eric Schleifer, who specializes in adolescent boys. He wants to know right off the bat about their media habits. Do you watch scary movies? Do you play violent games? If you have a kid who’s always pushing to play the most violent game or watch the bloodiest movie, that could be a sign that there’s some fear in his life over bigger issues.

So do you believe it could actually be good for this fearful boy to play violent games?

Absolutely, for a number of reasons. Violent entertainment helps kids process the big fears they have. That predates video games by a century or more. What’s Superman but this weird manifestation of this fear we have that the world is going to end?

You write about how the most primal and timeless children’s games, like tag, embody imitations of violence and death. But that type of imaginary play, or Superman for that matter, are radically different from the graphic violence depicted in some of today’s games.

The graphic quality is what really stops people cold. I have a couple of thoughts. Number one, it’s important to understand that kids these days are growing up steeped in imagery. Movies have been graphic for generations. It’s important to not single out video games.

News Inside

In the case of a video game, there’s almost a necessity to be explicit, to show where the bullet hit. They can’t be misty about where the wounds are. I will say, as a parent, I do think twice about that, and I do have a little squeamishness about it. I played a lot of these games, and they can be pretty intense. For parents, their taste and their standards need to come first. I would never deny a parent’s right to take the disk and throw it in the trash. That said, there’s more going on than we think.

What do you mean? Why is it necessary for players to see gunshot wounds?

It’s an indicator of progress within the world of the game. Your task is to get through this level, and these characters are in your way, so you’ve got to kill them and get past them. The more specific the feedback, the better.

You write that this process helps a kid learn from mistakes and overcome challenges.

Yes. It’s a hard thing to get our minds around, but what looks like killing isn’t. It’s different. A first-person shooter game, the games we’re really concerned with, are essentially hunting games. The player signs this weird contract that says, O.K. hunt me. I consent to be hunted . That’s really what’s happening.

They want to be challenged. They want to be part of something really big and scary and hard. A lot of these games now, you’re playing with and against your friends. So it’s team hunting. It’s the digital equivalent of being on a rugby or football team. It’s paintball without the welts.

I was fascinated by the ADHD treatment game you describe in the book, in which sensors attached to the player’s head allow him to move objects on the screen by focusing his mind. The goal is to throw massive trucks in order to crush other objects. In a way, that game is violent, too. It seems to tap into the adolescent drive for destruction.

Absolutely. The developer of that game, Lat Ware, is so funny and so genuine. His first version was single-player. You’re throwing things at computer characters. But what he found was that people wanted to crush their friends.

Even if violent games don’t cause real violence, they might have other harmful effects. Anita Sarkeesian is one of many critics concerned about the retrograde depictions of women in these games, as victims or sex objects.

I agree 85 percent with Anita. She makes a good point that if you’re going to spend so much time with these games, can we please have more generous representations of women? I do struggle with whether boys who play these games and have no other context are coming away with stupid ideas about girls. But I want to give enough credit to players that they understand this stuff on a deeper level than we think they do. Games are a fantasy and have always been a fantasy. They’re not the real world.

You have two daughters.

My kids don’t play much in the way of games! They are both much more into music and dance and the arts. They indulge me. But I don’t force them to game.

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Games user research: A case study approach

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New Study: Video Games and Teens’ Behavior

Previous studies show that violent video games increase adolescent aggressiveness, but new Dartmouth research finds for the first time that teenagers who play mature-rated, risk-glorifying video games are more likely subsequently to engage in a wide range of behaviors beyond aggression, including alcohol use, smoking cigarettes, delinquency, and risky sex.

More generally, such games—especially character-based games with anti-social protagonists—appear to affect how adolescents think of themselves, with potential real-world consequences.

The study appears August 4 in the American Psychological Association’s Journal of Personality and Social Psychology . The findings follow a 2012 Dartmouth study that shows such video games may lead teens to drive recklessly and experience increases in automobile accidents, police stops, and a willingness to drink and drive.

“Up to now, studies of video games have focused primarily on their effects on aggression and violent behaviors,” says the Geisel School of Medicine’s James Sargent , study co-author and the Scott M. and Lisa G. Stuart Professor in Pediatric Oncology and co-director of the Cancer Control Research Program at the Norris Cotton Cancer Center. “This study is important because it is the first to suggest that possible effects of violent video games go well beyond violence to apply to substance use, risky driving, and risk-taking sexual behavior.”

"With respect to playing deviant video game characters, we feel it best to follow the admonition of Kurt Vonnegut in Mother Night : 'We are what we pretend to be, so we must be careful about what we pretend to be,'" says Professor Jay Hull , the study’s lead author and chair of the Department of Psychological and Brain Sciences .

In the new study, researchers conducted a nationwide study involving more than 5,000 randomly sampled U.S. teenagers who answered a series of questions over four years in telephone interviews.

The researchers looked at a number of factors, including the playing of three violent risk-glorifying video games (Grand Theft Auto, Manhunt, and Spiderman) and other mature-rated video games. They found that such games are associated with subsequent changes in a wide range of high-risk behavior and suggest this is due, in part, to changes in the users' personality, attitudes, and values, specifically making them more rebellious and thrill seeking. The effect was similar for males and females and strongest among the heaviest game players and those playing games with anti social protagonists.

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Celebrating Excellence: The 2024 Faculty Awards

N.H. Researchers Using Machine Learning to Study Bats

Improving Generalization in Game Agents with Data Augmentation in Imitation Learning

This presentation was delivered at the IEEE World Congress on Computational Intelligence , which was held on 5 July 2024 in Yokohama, Japan.

Authors: Derek Yadgaroff, Alessandro Sestini, Konrad Tollmar, Ayça Özçelikkale, and Linus Gisslén. Presented by Alessandro Sestini.

How do we efficiently train in-game AI agents to handle new situations that they haven’t been trained on?

Imitation learning is an effective approach for training game-playing agents and, consequently, for efficient game production. However, generalization – the ability to perform well in related but unseen scenarios – is an essential requirement that remains an unsolved challenge for game AI. Generalization is difficult for imitation learning agents because it requires the algorithm to take meaningful actions outside of the training distribution. 

In this paper, we propose a solution to this challenge. Inspired by the success of data augmentation in supervised learning, we augment the training data so the distribution of states and actions in the dataset better represents the real state-action distribution. 

This study evaluates methods for combining and applying data augmentations to improve the generalization of imitation learning agents. It also provides a performance benchmark of these augmentations across several 3D environments. These results demonstrate that data augmentation is a promising framework for improving generalization in imitation learning agents.

Download the research paper (PDF 1.6 MB).

Download the slide deck (PDF 10 MB).

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Body camera video shows Sonya Massey's final moments before she was fatally shot by a deputy

Authorities released body camera footage Monday of Sonya Massey 's final moments before she was fatally shot by law enforcement at her home in Springfield, Illinois.

Massey, 36, was killed July 6 after she called the Sangamon County Sheriff's Office because she was afraid there might be a prowler outside, according to an attorney for her family and Illinois State Police.

Former Sangamon County Deputy Sean Grayson is accused of shooting Massey in the face after he and another deputy were dispatched to her home shortly before 1 a.m.

Grayson has been indicted on charges of first-degree murder , aggravated battery with a firearm and official misconduct, said Sangamon County State’s Attorney John Milhiser.

Grayson pleaded not guilty last week, according to his lawyer, Dan Fultz, who declined to comment after the body camera footage was released.

In the footage, Grayson and a second deputy can be seen knocking on Massey's door a few times until Massey opens it.

"Please don't hurt me," Massey is heard saying to Grayson. The second deputy was not identified by authorities.

"Why would I hurt you? You called us," Grayson responds.

The deputies tell Massey they checked the area around her house and didn't see anybody, and then ask if she needs help with anything else. Grayson also asks Massey if she's doing OK mentally, to which she answers, "Yes."

"I love ya'll, thank ya'll," Massey says as she's closing her door. The deputies ask her if a black SUV in her driveway with a smashed window is hers, to which she says no and that someone brought it there.

The deputies then go into Massey's house, where they ask her for her name so they "can get out of your hair."

Massey then moves to her stove, where she picks up a pot from a burner. The situation escalates when she moves the pot from the stove.

"Where you goin'?" she asks the deputies.

"Away from your hot, steaming water," Grayson responds.

"I rebuke you in the name of Jesus," she says.

Massey does not approach the deputies with the pot and stays in her kitchen.

"You better f------ not I swear to God I'll f------- shoot you in your f------- face," Grayson says before pulling out his gun.

"OK, I'm sorry!" Massey says as she ducks.

The second deputy also pulls out his gun.

"Drop the f------- pot!" Grayson screams.

Three gunshots are heard as Grayson continues to yell at Massey to drop the pot. Massey cannot be seen from behind the kitchen counter, but video from Grayson's body camera shows that Massey had let go of the pot when she ducked.

The deputies called for emergency personnel.

The second deputy says he's going to get his kit.

"Nah, headshot dude, she's done," Grayson says to him. "You can go get it but that's a headshot."

"Yeah I'm not taking f------- boiling hot water to the f------- head," Grayson continues. "Hey look, it f------- came right to our feet too."

He then goes to get his medical kit, saying, "I mean, there's not much we can do."

"We can at least try and hold the, stop the blood," the second deputy says. He then goes into the kitchen, finds a towel and holds it to Massey. Massey is blurred out in the footage, but a large pool of blood can still be seen near her head, and she can be heard gasping.

When Grayson makes his way back into the home, he asks another deputy who has since entered, "Is there anything we can do for her?" The deputy responds, "No."

"All right, I'm not even going to waste my med stuff then," Grayson says.

The deputy asks Grayson, "Where's the gun?"

"No, she had boiling water and came at me with boiling water," Grayson says.

When Grayson leaves the house, a member of law enforcement standing outside asks him if he's OK.

"Yeah I'm good. This f------- b---- is crazy," he responds and walks to his vehicle shortly afterward.

The second deputy stays with Massey, holding the towel to her head until medical help arrives. Grayson is not seen trying to aid Massey.

Massey was taken to a hospital, where she was declared dead, according to state police.

A use-of-force review conducted by state police found that while Grayson did not attempt to de-escalate the encounter, he was justified in pointing his service weapon at Massey to get her to comply. But it found the shooting was not justified because Grayson advanced toward Massey and put himself in a position where he could have been injured. 

Milhiser, the Sangamon County state's attorney, said in an earlier statement that a review of the state police investigation, including body camera footage, “does not support a finding that Deputy Sean Grayson was justified in his use of deadly force.”

Sangamon County Sheriff Jack Campbell said in a statement last week that Grayson had been fired because it was clear he “did not act as trained or in accordance with our standards.”

In a statement posted Monday to Facebook, Campbell said Massey is dead because of an "unjustifiable and reckless decision" made by Grayson.

"Grayson had other options available that he should have used," Campbell said. "His actions were inexcusable and do not reflect the values or training of our office. He will now face judgment by the criminal justice system and will never again work in law enforcement."

The sheriff went on to say that Massey "needlessly lost her life" and that her family deserves answers.

President Joe Biden also weighed in on the killing on Monday, saying Massey should still be alive and lauding prosecutors for their "swift actions."

Biden said he is "heartbroken" for Massey's children and her family.

"When we call for help, all of us as Americans — regardless of who we are or where we live — should be able to do so without fearing for our lives," the president said. "Sonya’s death at the hands of a responding officer reminds us that all too often Black Americans face fears for their safety in ways many of the rest of us do not."

In a news conference Monday, Ben Crump, the attorney representing Massey's family, contemplated whether race played a role in the deadly shooting.

"That is the lingering question in our community because many of us looked at that video and said, 'If it was a white woman, he would not have done this,'" Crump said.

In a subsequent statement, the lawyer praised a decision to hold the former deputy without bond, describing the move as "another crucial step in the pursuit of justice for Sonya Massey’s family."

Grayson’s next court date is scheduled for Aug. 26.

"We want equal justice for Sonya Massey," Crump said at the news conference. "We said it before: whatever Grayson would be convicted of and sentenced to had it been a white woman is the same thing we want for this Black queen named Sonya Massey."

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The contagious impact of playing violent video games on aggression: Longitudinal evidence

Tobias greitemeyer.

1 Department of Psychology, University of Innsbruck, Innsbruck Austria

Meta‐analyses have shown that violent video game play increases aggression in the player. The present research suggests that violent video game play also affects individuals with whom the player is connected. A longitudinal study ( N  = 980) asked participants to report on their amount of violent video game play and level of aggression as well as how they perceive their friends and examined the association between the participant's aggression and their friends’ amount of violent video game play. As hypothesized, friends’ amount of violent video game play at Time 1 was associated with the participant's aggression at Time 2 even when controlling for the impact of the participant's aggression at Time 1. Mediation analyses showed that friends’ aggression at Time 1 accounted for the impact of friends’ amount of violent video game play at Time 1 on the participant's aggression at Time 2. These findings suggest that increased aggression in video game players has an impact on the player's social network.

1. INTRODUCTION

Given its widespread use, the public and psychologists alike are concerned about the impact of violent video game play. In fact, a great number of studies have addressed the effects of exposure to violent video games (where the main goal is to harm other game characters) on aggression and aggression‐related variables. Meta‐analyses have shown that playing violent video games is associated with increased aggression in the player (Anderson et al., 2010 ; Greitemeyer & Mügge, 2014 ). The present longitudinal study examines the idea that violent video game play also affects the player's social network, suggesting that concern about the harmful effects of playing violent video games on a societal level is even more warranted.

1.1. Theoretical perspective

When explaining the effects of playing violent video games, researchers often refer to the General Aggression Model (GAM) proposed by Anderson & Bushman ( 2002 ). According to this theoretical model, person and situation variables (sometimes interactively) may affect a person's internal state, consisting of cognition, affect, and arousal. This internal state then affects how events are perceived and interpreted. Based on this decision process, the person behaves more or less aggressively in a social encounter. For example, playing violent video games is assumed to increase aggressive cognition and affect, which in turn results in behavioral aggression. An extension of this model further assumes that increased aggression due to previous violent video game play may instigate an aggression escalation cycle in that the victim also behaves aggressively (cf. Anderson & Bushman, 2018 , Figure 5). The present research tested key predictions derived from the GAM and its extension, that (a) violent video game play is associated with increased aggression in the player and that (b) individuals who are connected to the player will also become more aggressive.

1.2. Effects of violent video game play on aggression

The relationship between violent video game play and aggression has been examined in studies employing cross‐sectional, longitudinal, and experimental designs. Cross‐sectional correlational studies typically show a positive relationship between the amount of violent video game play and aggression in real‐world contexts (e.g., Gentile, Lynch, Linder, & Walsh, 2004 ; Krahé & Möller, 2004 ). Several longitudinal studies have been conducted, showing that habitual violent video game play predicts later aggression even after controlling for initial aggressiveness (e.g., Anderson, Buckley, & Carnagey, 2008 ). That violent video game play has a causal impact on aggression and related information processing has been demonstrated by experimental work (e.g., Anderson & Carnagey, 2009 ; Gabbiadini & Riva, 2018 ). Finally, meta‐analyses corroborated that violent video game play significantly increases aggressive thoughts, hostile affect, and aggressive behavior (Anderson et al., 2010 ; Greitemeyer & Mügge, 2014 ). Some studies failed to find significant effects (e.g., McCarthy, Coley, Wagner, Zengel, & Basham, 2016 ). However, given that the typical effect of violent video games on aggression is not large, it is to be expected that not all studies reveal significant effects.

1.3. The contagious effects of aggression

Abundant evidence has been collected that aggression and violence can be contagious (Dishion, & Tipsord, 2011 ; Huesmann, 2012 ; Jung, Busching, & Krahé, 2019 ). Indeed, the best predictor of (retaliatory) aggression is arguably previous violent victimization (Anderson et al., 2008 ; Goldstein, Davis, & Herman, 1975 ). However, even the observation of violence can lead to increased violence in the future (Widom, 1989 ). Overall, it is a well‐known finding that aggression begets further aggression. Given that violent video game play increases aggression, it thus may well be that this increased aggression then has an impact on people with whom the player is connected.

Correlational research provides initial evidence for the idea that the level of people's aggression is indeed associated with how often their friends play violent video games (Greitemeyer, 2018 ). In particular, participants who did not play violent video games were more aggressive the more their friends played violent video games. However, due to the cross‐sectional design, no conclusions about the direction of the effect are possible. It may be that violent video game players influence their friends (social influence), but it is also conceivable that similar people attract each other (homophily) or that there is some shared environmental factor that influences the behavior of both the players and their friends (confounding). That is, it is unclear whether indeed aggression due to playing violent video games spreads or whether the effect is reversed, such that aggressive people are prone to befriend others who are attracted to violent video game play. Moreover, it is possible that some third variable affected both, participants’ reported aggression and their friends’ amount of violent video game play. There is also the possibility that people are unsure about the extent to which their friends play violent video games. In this case, they may perceive their friends as behaving aggressively and then (wrongly) infer that the friends play violent video games. To disentangle these possibilities and to show that the effect of violent video game play (i.e., increased aggression in the player) indeed has an impact on the player's social network, relationships among variables have to be assessed over time while covarying prior aggression (Bond & Bushman, 2017 ; Christakis & Fowler, 2013 ).

Verheijen, Burk, Stoltz, van den Berg, and Cillessen ( 2018 ) tested the idea that players of violent video games have a long‐term impact on their social network. These authors found that participants’ exposure to violent video games increased their friend's aggressive behavior 1 year later. However, given that the authors did not examine whether the violent video game player's increased aggression accounts for the impact on their friend's aggressive behavior, it is unknown whether violent video game play indeed instigates an aggression cycle. For example, players of violent video games may influence their friends so that these friends will also play violent video games. Any increases in aggression could then be an effect of the friends playing violent video games on their own.

1.4. The present research

The present study examines the longitudinal association between the participant's aggression and their friends’ amount of violent video game play, employing an egocentric networking approach (Stark & Krosnick, 2017 ). In egocentric networking analyses, participants provide self‐reports but also report on how they perceive their friends. In the following, and in line with Greitemeyer ( 2018 ), the friends were treated as the players and the participant was treated as their friends’ social network. Please note that ties between the participant's friends (i.e., whether friends also know each other) were not assessed (Greitemeyer, 2018 ; Mötteli & Dohle, 2019 ), because this information was not needed for testing the hypothesis that participants become more aggressive if their friends play violent video games. It was expected that friends’ amount of violent video game play at Time 1 would predict the participant's aggression at Time 2 even when controlling for the impact of the participant's aggression and amount of violent video game play at Time 1. It was further examined whether friends’ aggression at Time 1 would account for the impact of friends’ amount of violent video game play at Time 1 on the participant's aggression at Time 2. Such findings would provide suggestive evidence that violent video game play may instigate an aggression cycle. The study received ethical approval from the Internal Review Board for Ethical Questions by the Scientific Ethical Committee of the University of Innsbruck. The data and materials are openly accessible at https://osf.io/jp8ew/ .

2.1. Participants

Participants were citizens of the U.S. who took part on Amazon Mechanical Turk. Because it was unknown how many of the participants will complete both questionnaires, no power analyses were conducted a priori but a large number of participants was run. At Time 1, there were 2,502 participants (1,376 females, 1,126 males; mean age = 35.7 years, SD =  11.8). Of these, 980 participants (522 females, 458 males; mean age = 38.9 years, SD =  12.5) completed the questionnaire at Time 2. Time 1 and Time 2 were 6 months apart. There were no data exclusions, and all participants were run before any analyses were performed. The questionnaire included some further questions (e.g., participant's perceived deprivation) that are not relevant for the present purpose and are reported elsewhere (Greitemeyer & Sagioglou, 2018 ). 1 Given that the questionnaire was relatively short, no attention checks were employed.

2.2. Procedure and measures

Procedure and measures were very similar to Greitemeyer ( 2018 ), with the main difference that individuals participated at two time points (instead of one). After providing demographics, self‐reported aggressive behavior was assessed. As in previous research (e.g., Krahé & Möller, 2010 ), participants indicated for 10 items how often they had shown the respective behavior in the past 6 months. Sample items are: “I have pushed another person” and “I have spread gossip about people I don't like” (5 items each address physical aggression and relational aggression, respectively). All items were rated on a scale from 1 ( never ) to 5 ( very often ), and scores were averaged. Participants were then asked about their amount of violent video game play, employing one item: “How often do you play violent video games (where the goal is to harm other game characters)?” (1 =  never to 7 =  very often ).

Afterwards, participants learned that they will be asked questions about people they feel closest to. These may be friends, coworkers, neighbors, relatives. They should answer questions for three contacts with whom they talked about important matters in the last few months. For each friend, they reported the level of aggression (αs between = 0.90 and 0.91) and the amount of violent video game play, employing the same questions as for themselves. Responses to the three friends were then averaged. Finally, participants were thanked and asked what they thought this experiment was trying to study, but none noted the hypothesis that their friend's amount of violent video game play would affect their own level of aggression. At Time 2, the same questions were employed. Reliabilities for how participants perceived the level of aggression for each friend were between 0.89 and 0.90.

Descriptive statistics, intercorrelations, and internal consistencies of all measures are shown in Table ​ Table1 1 .

Means, standard deviations, and bivariate correlations

Note : For Time 1, N  = 2,502; for Time 2, N  = 980. All correlation coefficients: p  < .001. Where applicable, α reliabilities are presented along the diagonal.

3.1. Time 1 ( N  = 2,502)

The relationship between the amount of violent video game play and reported aggression was significant, both for the participant and the friends. That is, violent video game play was associated with increased aggression in the player and participants perceived their friends who play more violent video games to be more aggressive than their less‐playing friends. Participant's and friends’ amount of violent video game play as well as their level of reported aggression, respectively, were also positively associated, indicating that participants perceived their friends to be similar to them. Most importantly, participant's aggression was significantly associated with friends’ amount of violent video game play. 2

It was then examined whether friends’ amount of violent video game play is still associated with the participant's aggression when controlling for the participant's amount of violent video game play. Participant sex (coded 1 = male, 2 = female) and age were included as covariates. In fact, a bootstrapping analysis showed that the impact of friends’ amount of violent video game play remained significant (point estimate = 0.08, SE  = 0.02, t  = 4.72, p  < .001, 95% confidence interval [CI] = [0.05, 0.11]). Participant's amount of violent video game play (point estimate = 0.03, SE  = 0.01, t  = 2.18, p  = .029, 95% CI = [0.00, 0.05]) and the interaction were also significant (point estimate = −0.01, SE  = 0.00, t  = 2.41, p  = .016, 95% CI = [−0.02, −0.00]). At low levels of the participant's amount of violent video game play (− 1 SD, equals that the participant does not play violent video games in the present data set), friends’ amount of violent video game play was associated with the participant's aggression (point estimate = 0.07, SE  = 0.01, t  = 5.06, p  < .001, 95% CI = [0.04, 0.10]). At high levels of the participant's amount of violent video game play ( + 1 SD), friends’ amount of violent video game play was also associated with the participant's aggression (point estimate = 0.03, SE  = 0.01, t  = 3.14, p  = .002, 95% CI = [0.01, 0.06]), but the effect was less pronounced. Participants were thus most strongly affected by whether their social network plays violent video games when they do not play violent video games themselves (Figure ​ (Figure1). 1 ). Participant sex was not significantly associated with the participant's aggression (point estimate = −0.04, SE  = 0.02, t  = 1.95, p  = .052, 95% CI = [−0.09, 0.00]), whereas age was (point estimate = −0.01, SE  = 0.00, t  = 7.84, p  < .001, 95% CI = [−0.009, −0.005]).

Simple slopes of the interactive effect of friends’ amount of violent video game play and the participant's amount of violent video game play on the participant's aggression, controlling for participant sex and age (Time 1, N  = 2,502)

3.2. Time 1 and Time 2 ( N  = 980)

To examine the impact of friends’ amount of violent video game play on the participant's aggression over time, a cross‐lagged regression analysis was performed on the data. Participant's amount of violent video game play, friends’ amount of violent video game play, participant's aggression at Time 1, as well as participant sex and age were used as predictors for participant's aggression at Time 2. The overall regression was significant, F (5,974) = 68.92, R 2  = 0.26, p  < .001. Most importantly, friends’ amount of violent video game play at Time 1 significantly predicted participant's aggression at Time 2, t  = 2.60, β  = .09, 95% CI = (0.02, 0.16), p  = .009. Participant's aggression showed high stability, t  = 16.77, β  = .48, 95% CI = (0.42, 0.53), p  < .001, whereas the participant's amount of violent video game play at Time 1 did not significantly predict the participant's aggression at Time 2, t  = 1.77, β  = −.07, 95% CI = (− 0.14, 0.01), p  = .077 (Figure ​ (Figure2 2 ). 3 , 4 Participant sex also received a significant regression weight, t  = 2.08, β  = −.06, 95% CI = (−0.12, −0.00), p  = .038, whereas age did not, t  = 1.93, β  = −.06, 95% CI = (−0.12, 0.00), p  = .054. The reverse effect that the participant's aggression at Time 1 predicts their friends’ amount of violent video game play at Time 2 when controlling for the participant's amount of violent video game play and friends’ amount of violent video game play at Time 1, as well as participant sex and age, was not significant, t  = 0.67, β  = .02, 95% CI = (−0.03, 0.06), p  = .504.

Participant's aggression at Time 2 simultaneously predicted by friends’ amount of violent video game play, participant's aggression, and participant's amount of violent video game play at Time 1. Participant sex and age were controlled for, but were not included in the figure (see the main text for the impact of participant sex and age). * p  < .01, ** p  < .001 ( N  = 980)

Finally, it was examined whether the impact of friends’ amount of violent video game play at Time 1 on the participant's aggression at Time 2 would be mediated by friends’ level of aggression at Time 1 (while controlling for the participant's aggression and amount of violent video game play at Time 1 as well as participant sex and age). A bootstrapping analysis (with 5.000 iterations) showed that the impact of friends’ level of aggression at Time 1 on the participant's aggression at Time 2 was significant (point estimate = 0.16, SE  = 0.04, t  = 4.28, p  < .001, 95% CI = [0.09, 0.23]). Participant's aggression at Time 1 was also a significant predictor (point estimate = 0.34, SE  = 0.03, t  = 10.19, p  < .001, 95% CI = [0.27, 0.40]). Friends’ amount of violent video game play at Time 1 (point estimate = 0.03, SE  = 0.01, t  = 1.82, p  = .069, 95% CI = [−0.00, 0.05]) and participant's amount of violent video game play at Time 1 (point estimate = −0.01, SE  = 0.01, t  = 1.65, p  = .099, 95% CI = [−0.03, 0.00]) were not significant predictors. Participant sex significantly predicted the participant's aggression at Time 2 (point estimate = −0.06, SE  = 0.03, t  = 2.31, p  = .021, 95% CI = [−0.11, −0.01]), whereas age did not (point estimate = −0.00, SE  = 0.00, t  = 1.90, p  = .058, 95% CI = [−0.00, 0.00]). The indirect effect was significantly different from zero (point estimate = 0.01, 95% CI = [.00, 0.02]), suggesting that participants are more aggressive if their friends play violent video games for the reason that these friends are more aggressive. Figure ​ Figure3 3 displays a simplified version of this mediation effect, based on regression coefficients and without controlling for the participant's aggression at Time 1, the participant's amount of violent video game play at Time 1, participant sex, and age.

Mediation of the impact of friends’ violent video game exposure (VVE) at Time 1 on the participant's aggression at Time 2 by friends’ aggression at Time 1. All paths are significant. β * = the coefficient from friends’ VVE at Time 1 to the participant's aggression at Time 2 when controlling for friends’ aggression at Time 1 ( N  = 980)

4. DISCUSSION

Violent video games have an impact on the player's aggression (Anderson et al., 2010 ; Greitemeyer & Mügge, 2014 ), but—as the present study shows—they also increase aggression in the player's social network. In particular, participants who do not play violent video games reported to be more aggressive the more their friends play violent video games. Mediation analyses showed that the increased aggression in the friends accounted for the relationship between friends’ amount of violent video game play and the participant's aggression. Because changes in aggression over time were assessed, the present study provides evidence for the hypothesized effect that violent video game play is associated with increased aggression in the player, which then instigates aggression in their social network. Importantly, the impact of the participant's amount of violent video game play was controlled for, indicating that the relationship between friends’ amount of violent video game play and the participant's aggression is not due to the friends being similar to the participants. Moreover, the reverse effect that aggressive people will become attracted to others who play violent video games was not reliable. The present research thus documents the directional effects that violent video games is associated with increased aggression in the player and that this increased aggression then has an impact on people with whom the player is connected.

Overall, the present study provides comprehensive support for key hypotheses derived from the GAM and its extension (Anderson & Bushman, 2018 ). It shows that violent video game play is associated with increased aggression in the player and it documents that others who are connected to players might be also affected even when controlling for their own amount of violent video game play. To the best of my knowledge, this study is the first that shows that because violent video game players are more aggressive their friends will become aggressive, too. Previous research either employed a cross‐sectional design and thus could not address the direction of the effect (Greitemeyer, 2018 ) or did not examine whether the effect of violent video game play (i.e., increased aggression) indeed spreads (Verheijen et al., 2018 ). As proposed by the GAM and its extension (Anderson & Bushman, 2018 ), increased aggression in violent video game players appears to instigate an aggression escalation cycle (cf. Anderson et al., 2008 ).

It is noteworthy, however, that the longitudinal effect of the participant's amount of violent video game play at Time 1 on the participant's aggression at Time 2 was not reliable. Hence, although there were significant correlations between participants’ aggression and their violent video game use at both time points, the present study does not show that repeatedly playing violent video games leads to long‐term changes in aggression. However, a recent meta‐analysis of the long‐term effects of playing violent video games confirmed that violent video game play does increase physical aggression over time (Prescott, Sargent, & Hull, 2018 ), although the effect size was relatively small ( β  = 0.11) and thus single studies that produce nonsignificant results are to be expected. Importantly, in the present study, a single‐item measure of violent video game play was employed. In contrast, previous research on the relationship between violent video game play and the player's aggression has often employed multi‐item measurement scales that are typically more reliable and precise (for an overview, Busching et al., 2015 ). Hence, it may well be that due to the limitations of the single‐item measure of the participant's amount of violent video game play the relationship between participants’ violent game play and their aggressive behavior was artificially reduced.

Even though the longitudinal design allows ruling out a host of alternative explanations for the impact of violent video games on the player's social network, causality can only inferred by using an experimental design. Future research may thus randomly assign participants to play a violent or nonviolent video game (players) and assesses their aggression against new participants (partners). It can be expected that the partners suffer more aggression when the player had played a violent, compared to a nonviolent, video game. Afterwards, it could be tested whether the partner of a violent video game player is more aggressive than a partner of a nonviolent video game player. Given that the partner is not exposed to any video games, firm causal conclusions could be drawn that violent video game play affects aggression in people who are connected to violent video game players. It could be also tested whether the partner of a violent video game player would not only be more likely to retaliate against the player, but also against a third party. In fact, previous research into displaced aggression has shown that people may react aggressively against a target that is innocent of any wrongdoing after they have been provoked by another person (Marcus‐Newhall, Pedersen, Carlson, & Miller, 2000 ). It may thus well be that the effect of playing violent video games spreads in social networks and that even people who are only indirectly linked to violent video game players are affected.

An important limitation of the present egocentric network data is the reliance on the participant's perception of their social network, leaving the possibility that participants did not accurately perceive their friends. It is noteworthy that participants perceived their friends to be highly similar to them. In this regard, it is important to keep in mind that participants always provided self‐ratings first, followed by perceptions of their friends. It is thus conceivable that participants used their self‐ratings as anchors for the perceptions of their friends. Such a tendency, however, would reduce the unique effect of friends’ amount of violent video game play on the participant's aggression when controlling for the participant's amount of violent video game play. The finding that participants in particular who do not play violent video games reported to be more aggressive if their friends play violent video games also suggests that the impact of violent video games on the player's social network is not due to participants providing both self‐reports and how they perceive their friends. Finally, rather than by their friends’ objective qualities, people's behavior should be more likely to be affected by their subjective perceptions of their friends.

As noted in the introduction, participants may not be aware of the extent to which their friends play violent video games and hence used the perception of how aggressive their friends are as an anchor for estimating their friends’ amount of violent video game play. Importantly, however, the participant's aggression at Time 2 was significantly predicted by friends’ amount of violent video game play at Time 1 even when controlling for friends’ level of aggression at Time 1 (see Figure ​ Figure3). 3 ). Moreover, whereas aggression might be used for estimating violent video game exposure of the friends, participants should be well aware of the extent to which they play violent video games so that anchoring effects for participant's self‐reports are unlikely. However, given that it cannot be completely ruled out that the correlation between violent game play of friends at Time 1 and aggressive behavior of participants at Time 2 reflects a pseudocorrelation that is determined by the correlation between aggressive behavior of friends at Time 1 and aggressive behavior of the participant at Time 2, future research that employs sociocentric network analyses where information about the friends is provided by the friends themselves would be informative.

Another limitation is the employment of self‐report measures to assess aggressive behavior. Self‐report measures are quite transparent, so participants may have rated themselves more favorably than is actually warranted. In fact, mean scores of reported aggressive behavior were quite low. This reduced variance, however, typically diminishes associations with other constructs. In any case, observing how actual aggressive behavior is influenced by the social network's violent video game play would be an important endeavor for future work. It also has to be acknowledged that some participants may have reported on different friends at Time 1 and Time 2. Future research would be welcome that ensures that participants consider the same friends at different time points.

Future research may also shed some further light on the psychological processes. In the present study, the violent video game players’ higher levels of aggression accounted for the relationship between their amount of violent video game play and the participants’ reported aggression. It would be interesting to examine why the players’ aggression influences the aggression level of their social network. One possibility is that witnessing increased aggression by others (who play violent video games) leads to greater acceptance of norms condoning aggression, which are known to be an antecedent of aggressive behavior (Huesmann & Guerra, 1997 ). After all, if others behave aggressively, why should one refrain from engaging in the same behavior.

Another limitation of the present work is that it was not assessed how participants and their friends play violent video games. A recent survey (Lenhart, Smith, Anderson, Duggan, & Perrin, 2015 ) showed that many video game users play video games together with their friends, either cooperatively or competitively. This is insofar noteworthy as there might be some overlap between participants’ and their friends’ violent video game play. Moreover, cooperative video games have been shown to increase prosocial tendencies (Greitemeyer, 2013 ; Greitemeyer & Cox, 2013 ; but see Verheijen, Stoltz, van den Berg, & Cillessen, 2019 ) and decrease aggression (Velez, Greitemeyer, Whitaker, Ewoldsen, & Bushman, 2016 ). In contrast, competitive video game play increases aggressive affect and behavior (e.g., Adachi & Willoughby, 2016 ). Hence, future research should examine more closely whether participants play violent video games on their own, competitively, or cooperatively. The latter may show some positive effects of video game play, both on the player and the player's friends, whereas opposing effects should be found for competitive video games.

To obtain high statistical power and thus to increase the probability to detect significant effects, data were collected via an online survey. The current sample was drawn from the MTurk population (for a review of the trend to rely on MTurk samples in social and personality psychology, see Anderson et al., 2019 ). Samples drawn from MTurk are not demographically representative of the U.S. population as a whole. For example, MTurk samples are disproportionally young and female and they are better educated but tend to be unemployed (for a review, Keith, Tay, & Harms, 2017 ). On the other hand, MTurk samples are more representative of the U.S. population than are college student samples (Paolacci & Chandler, 2014 ) and the pool of participants is geographically diverse. Moreover, MTurk participants appear to be more attentive to survey instructions than are undergraduate students (Hauser & Schwarz, 2016 ). Nevertheless, future research on the impact of violent video game play on the player's social network that employs other samples would improve the generalizability of the present findings.

In conclusion, violent video game play is not only associated with increased aggression in the player but also in the player's social network. In fact, increased aggression due to violent video game play appears to instigate further aggression in the player's social network. This study thus provides suggestive evidence that not only players of violent video games are more aggressive, but also individuals become more aggressive who do not play violent video games themselves but are connected to others who do play.

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1 Participant's perceived deprivation was positively related to both violent video game exposure, r (2,502) = 0.08, p  < .001, and reported aggression, r (2,502) = 0.14, p  < .001. However, the relationship between violent video game exposure and reported aggression, r (2,502) = 0.15, p  < .001, was relatively unaffected when controlling for perceived deprivation, r (2,499) = 0.14, p  < .001.

2 Given that the measures of violent video game exposure and aggressive behavior violated the normal distribution, Spearman's ρ coefficients were also calculated. However, the pattern of finding was very similar (e.g., the crucial relationship between the participant's aggression and friends’ amount of violent video game play was 0.18 [Pearson] and 0.17 [Spearman]). All these analyses can be obtained from the author upon request.

3 When dropping friends’ amount of violent video game play from the analysis, the participant's amount of violent video game play at Time 1 still did not predict participant's aggression at Time 2, t  = 0.44, β  = −.01, 95% CI = (− 0.02, 0.01), p  = .657 (when controlling for participant's aggression at Time 1, participant sex, and age).

4 Given that violent video games primarily model physical aggression, violent video games should have a stronger effect on the player's physical aggression than on other types of aggression. In fact, the impact of the participant's amount of violent video game play at Time 1 on the participant's physical aggression at Time 2, t  = 1.49, β  = .04, 95% CI = (− 0.00, 0.02), p  = .136 (when controlling for the participant's physical aggression at Time 1), was more pronounced than the impact on the participant's relational aggression at Time 2, t  = 0.52, β  = .02, 95% CI = (− 0.01, 0.02), p  = .603 (when controlling for the participant's relational aggression at Time 1), but both effects were not significant.

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These mobile games are for the birds

via The New York Times

March 20, 2024

• #behavioral science
• #technology
• Rebecca Kleinberger Former Postdoctoral Associate
• Sonic enrichment at the zoo
• Media Lab Research Theme: Cultivating Creativity

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By Emily Anthes

Parrots have much in common with toddlers. The brainy birds can learn to recognize colors and shapes, manipulate objects, build large vocabularies and make their needs known at improbably high volumes. They are also playful, intelligent and curious; without ample cognitive enrichment, they quickly become bored.

So owners of pet parrots sometimes turn to a strategy familiar to parents: reaching for the closest available screen. And some owners have found that they can keep their birds occupied with mobile games, drawing apps and music-making programs designed for young children. “Kids apps are quite popular,” said Rébecca Kleinberger, a scientist at Northeastern University who studies how animals interact with technology.

Rébecca Kleinberger, From DJ Macaw to Video-Flocking: Leveraging audio technology for animal’s social and cognitive enrichment

Alum Rébecca Kleinberger discusses her work at the intersection of new technology, animal-computer interaction, and the sonic environment.

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Media Lab alum Rébecca Kleinberger, who’s now a professor at Northeastern University, talks about her work on sonic enrichment in zoos.

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Kleinberger, Rébecca, et al. "Interspecies Interactions Mediated by Technology: An Avian Case Study at the Zoo." ACM CHI 2020 Conference (April 2020).

Meet the Labbers: Rébecca Kleinberger

"I like to think of the voice and all the sound from our bodies as some kind of rhythm of life and music of life."

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Surveillance video shows ambush murder of Jacksonville rapper Julio Foolio in Tampa; 3 arrested, 2 at large

Charles jones was gunned down outside a hotel in june.

Jenese Harris , Anchor/Meteorologist

Travis Gibson , Digital reporter/editor

TAMPA, Fla. – Three people have been arrested and accused in the shooting death of Charles Jones , a Jacksonville rapper known as “Julio Foolio.”

Jones, 26, was shot and killed in June in an ambush attack while celebrating his birthday in Tampa.

Tampa Police Chief Lee Bercaw, Hillsborough County State Attorney Suzy Lopez and Jacksonville Sheriff T.K. Waters announced the arrests Monday afternoon and said there are also warrants out for two other people believed to have been triggermen.

All five suspects, who are from Jacksonville, are accused of premeditated first-degree murder among other charges.

Isaiah Chance, 21, Alicia Andrews, 21, and Sean Gathright were arrested over the weekend in Jacksonville.

Police said Chance and Andrews tracked and followed Jones and his entourage to two locations. At each location, the two got out of their vehicle and Chance used a cell phone, police said. After the cell phone communication, a second suspect vehicle arrived at each location. Both vehicles then followed Jones and his entourage to a hotel located on McKinley Drive, where the murder happened.

Police said that Gathright, 18, along with two other outstanding suspects, Rashad Murphy and Davion Murphy, fired shots at Jones that night.

All of the people involved in the shooting are affiliated with Jacksonville gangs ATK and 1200 which are rival gangs to 6 Block, the gang Jones had connections to, according to police. The feud between 6 Block and its rival gangs ATK and 1200 has spanned over a decade with dozens of murders by and against both sides, officials said.

“Detectives believe that the ATK and the 1200 worked together to target Jones as part of an ongoing feud in Jacksonville,” Bercaw said.

Chance is a documented ATK gang member, and Rashad Murphy and Davion Murphy are documented 1200 gang members, according to police.

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During the news conference, Tampa police showed surveillance from the night of the shooting where the suspects can be seen stalking Jones. At one point, the shooters got out of a car parked across the street from the hotel where Jones was staying.

They can be seen on video wearing all black while sneaking around the parking lot before firing multiple shots at the car Jones was riding in.

Police said the three shooters were armed with a handgun and two rifles.

“Today, three dangerous criminals are off our Florida streets and in police custody where they belong,” Waters said. “These individuals have chosen lives of urban terrorism and with arrests we show Tampa, Jacksonville and the rest of Florida, we hold violent criminals accountable.”

Investigators said they used surveillance videos, license plate readers and phone logs to identify the two vehicles involved and tie them to the suspects.

Three other people were injured in the shooting outside the hotel but survived.

(Warning: The surveillance video, released by police, shows the shooting and is graphic. Viewer discretion is advised.)

“These criminals decided to bring their fight to Hillsborough County. Let me be clear, the feud ends here,” said Hillsborough County State Attorney Suzy Lopez. “My office will vigorously prosecute each of these defendants to ensure they are held accountable for the calculated murder of Charles Jones.”

The investigation is ongoing.

Waters was asked about Keyanta Bullard, a high-profile rapper who goes by “Yungeen Ace” and is affiliated with ATK, one of the gangs allegedly involved.

Waters wouldn’t speak regarding the Tampa investigation but did say JSO does not have an active investigation into Bullard. He did say the group doesn’t move in Jacksonville without JSO knowing about it.

Anyone with information that could assist in this ongoing investigation is asked to call the Tampa Police Department at 813-231-6130, or contact Crimestoppers of Tampa Bay at 800-873-TIPS.

To watch the sheriff’s office full conference, click here .

Copyright 2024 by WJXT News4JAX - All rights reserved.

About the Authors

Jenese harris.

Veteran journalist and Emmy Award winning anchor

Travis Gibson

Digital reporter who has lived in Jacksonville for over 25 years and focuses on important local issues like education and the environment.

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