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Violent Media Use and Violent Outcomes

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Print Publication Date: Oct 2020 Subject: Psychology, Clinical Psychology Online Publication Date: Oct 2020 DOI: 10.1093/oxfordhb/9780190218058.013.18

Violent Media Use and Violent Outcomes Christopher L. Groves, Sara Prot, and Craig A. Anderson The Oxford Handbook of Digital Technologies and Mental Health Edited by Marc N. Potenza, Kyle A. Faust, and David Faust

 

Abstract and Keywords

Electronic media is an omnipresent form of entertainment in contemporary society. A large body of empirical evidence provides support for the notion that violent media use (e.g., television, films, video games) increases the likelihood of low-level everyday forms of physical, verbal, and relational aggression. Less work has been conducted on the ef­ fects of violent media on more extreme forms of aggression that can be considered vio­ lent. This chapter provides a review of the theoretical frameworks for understanding the potential effects of violent media use on violent outcomes. It follows this discussion with a selective review of the relevant literature regarding the effects of violent media use on vi­ olent outcomes, with a focus on the effects of violent video games. Conclusions are drawn regarding the state of the literature, current debate, and future directions needed for re­ search.

Keywords: violent media, video games, television, aggression, risk factors, violent behavior, criminal behavior

(p. 202) There is no doubt that the past few decades have brought about dramatic changes in the ways in which individuals entertain themselves. The public now has unprecedented access to media with the introduction of tablets, smartphones, and smart televisions. This shift in entertainment is marked most clearly by the rise in video game play, which contin­ ues to grow. In 2013, consumers spent nearly US$21 billion on video games and video game equipment (Entertainment Software Association, 2014). Nearly 90% of American children and teenagers report playing video games (Gentile, 2009) and do so for an aver­ age of 2 hours a day (Rideout, Foehr, & Roberts, 2010). This level of popularity has fos­ tered concern among policymakers, parents, and researchers alike regarding one of the most prevalent themes of video game play: its violent content.

Research regarding violent media effects has a rich history. Analyses of violent television and film effects have consistently found modest but significant effects on a wide range of aggression-related outcomes (for reviews, see Anderson et al., 2003; Strasburger & Wil­ son, 2014). Recently, the field has experienced renewed interest in these effects, fostered by the increasing popularity of video games. Scholarly interest in video game effects has

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produced hundreds of studies that are perhaps best summarized in meta-analyses on the subject. In the largest meta-analysis on the subject to date, Anderson et al. (2010) con­ cluded that violent video game play serves as a causal risk factor for aggressive behavior. While disagreements over specific details in the field exists, meta-analyses conducted by both proponents for and against violent media effects demonstrate a consistent relation­ ship between violent media use and aggressive behavior even when employing overly conservative statistical controls (Boxer, Groves, & Docherty, 2015).

Much of the research on violent video game use has focused on subcriminal levels of ag­ gression, such as the administration of hot sauce to someone participant who is known to dislike spicy foods (Barlett, Branch, Rodeheffer, & Harris, 2009), administering unpleas­ ant noise blasts to a competitor (Anderson et al., 2004), and rating another person as less deserving of financial support (Cicchirillo & Chory-Assad, 2005). We will label these ex­ amples of aggression low-level aggression. Such laboratory measures of aggression are frequently used in experimental studies designed to test the causal role of media vio­ lence. The use of these techniques has produced a thorough and methodologically sound literature that can speak to the causal nature of these relationships and to the underlying psychological processes. However, the administration of hot sauce and aversive noise blasts are far cries from the real-world extreme forms of violence that the general public and news media sometimes implicate as resulting from media violence.

This difference between the types of aggression that can ethically be used in laboratory experiments versus extreme real-world violence does not exonerate violent media use as a potential source of criminal-level aggressive outcomes. It does, however, indicate that before making strong claims about violent media effects on violent behavior, one must look beyond laboratory experiments of media violence effects on aggressive behavior. Specifically, we must consider basic theoretical processes that link media violence to ag­ gressive and violent behavior, both directly and through media violence effects on known risk factors for violence. We also must look to nonexperimental studies of media violence effects, as these are studies that can ethically examine more extreme forms of aggression as outcome variables. Next, we briefly discuss the theoretical processes responsible for violent media effects and conclude this section by describing a useful theoretical frame­ work for understanding how criminal-level or violent outcomes may transpire. Finally, we summarize the literature specific to such outcomes and provide directions for future re­ search.

Theory and Definitions Aggression is a behavior enacted with the intent to cause harm to a person who does not want to be harmed (Bushman & Anderson, 2001; Bushman & Huesmann, 2010). It is an observable behavior, not an emotion, a thought, or a fantasy that occurs inside the per­ son. This definition excludes accidental hurtful actions (e.g., unintentionally tripping someone) as well as intentional actions that are not done with the intent to cause harm (e.g., a dentist administering a painful medical procedure). Aggression can take several

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forms, including physical aggression (e.g., punching someone), verbal aggression (e.g., cursing at someone), and relational aggression (e.g., harming someone’s relationships by spreading a rumor behind his or her back).

Violence refers to more extreme forms of physical aggression that pose a significant risk of injury to the victim (such as assault and murder; Huesmann & Taylor, 2006). All violent behaviors are aggressive behaviors, but many aggressive behaviors are not violent (e.g., a kindergartner poking an annoyed classmate). Violent and aggressive behaviors can be viewed as a part of a continuum of severity, ranging from mild aggressive acts (e.g., pok­ ing) to severe aggressive acts which constitute violence (e.g., shooting; Anderson et al., 2003; Anderson & Huesmann, 2003). In support of the idea that aggression and violence exist on a continuum, research demonstrates strong associations between mildly aggres­ sive behavior earlier in life and risk of violent behavior later (Huesmann, Lagerspetz, & Eron, 1984). In addition, aggressive cognitions and affect are significant predictors of ag­ gression and violence (Anderson & Bushman, 2002; Bushman & Huesmann, 2010). There­ fore, research studies measuring mild forms of aggressive behavior, thoughts, or emo­ tions can provide valuable insight into understanding violent behavior. Of importance for the current discussion, violence is defined by the World Health Organization as “the in­ tentional use of physical force or power, threatened or actual, against another person or against a group or community that results in or has a high likelihood of resulting in injury, death, physiological harm, maldevelopment, or deprivation” (Zwi, Krug, Mercy, & Dahlberg, 2002). This definition is important to consider as it does not require that out­ comes of violent acts include injury or harm, merely that the act itself is highly capable of producing injury. This is perhaps one of the clearest differences between violent acts and criminal violence. By definition, criminal violence possesses a lower frequency compared to violent acts as violent actions do not always lead to injury and are (perhaps conse­ quently) reported to authorities less frequently. For this reason, research benefits from the use of violent behavior as an outcome rather than criminal behavior because such ac­ tions are more common, possess more variability to explain, and can be researched with somewhat smaller samples.

The General Aggression Model The General Aggression Model (GAM; Anderson & Bushman, 2002; DeWall, Anderson, & Bushman, 2011) provides a comprehensive framework for understanding aggression and violence. GAM (p. 204) describes the personal and situational factors and their resultant processes that influence an individual’s aggressive behavior in the current situation as well as forces that influence the long-term development of aggressive tendencies. The GAM has guided a wealth of research in the media violence domain (Anderson et al., 2010; Anderson & Dill, 2000; Möller & Krahe, 2009) but also has been applied to numer­ ous other aggression domains. Although GAM includes various biological processes (e.g., genetic, hormone), our present focus is on the social-cognitive aspects. It provides a basis

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Figure 18.1 The General Aggression Model: overall view.

From Anderson & Carnagey (2004).

for understanding how violent media influence aggression and violence both in short- and long-term contexts.

An overview of the key processes proposed by GAM is shown in Figure 18.1. The likeli­ hood that a person will act aggressively in a current social encounter is influenced both by person factors (e.g., trait aggression, hostility, and psychoticism) and situation factors (e.g., provocation, heat, violent media). Media violence increases the likelihood of aggres­ sive behavior in a current social encounter through its influence on a person’s present in­ ternal state (their current thoughts, affect, and arousal level). For example, watching a vi­ olent television show primes aggressive cognition, increases hostile affect, and leads to physiological arousal. These changes in internal state variables affect appraisal and deci­ sion making. They guide a person’s perception, interpretation of events, decision making, and behavior. For example, a person whose aggressive thoughts and affect have been primed by watching a violent television show is more likely to decide to act aggressively in response to provocation.

Once a behavioral response has been chosen, it influences the ongoing social encounter, creating a feedback loop. Over time, repeated aggressive encounters (such as bullying, rejection, or habitual violent video game use) strengthen a person’s habitual patterns of responding and can lead to the development of an aggressive personality. Repeated expo­ sure to violence (in real life or in the media) involves recurring rehearsal of aggressive knowledge structures. Over time, habitual violent media consumers can become more ag­ gressive in outlook by developing hostile perceptual biases, attitudes, beliefs, and behav­ iors (Bartholow, Sestir, & Davis, 2005; Gentile, Li, Khoo, Prot, & Anderson, 2014).

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Risk Factor Approach Research shows that violent actions are rarely the result of a single cause (Huesmann & Taylor, 2006). Instead, aggression and violence are caused and moderated by a large number of interacting factors, such as genetic predispositions (Hudziak et al., 2003), par­ enting practices (Eron, Huesmann, & Zelli, 1991), personality (Schmeck & Poustka, 2001), accessibility of guns (O’Donnell, 1995), cultural norms (Nisbett & Cohen, 1996), even climate change (Anderson & DeLisi, 2011). No reputable researcher would claim that media violence is “the cause” of violent behavior: it is one of many contributing fac­ tors (Huesmann & Taylor, 2006).

A useful approach for understanding how multiple causes contribute to violent behavior is the risk and resilience approach (Anderson, Gentile, & Buckley, 2007; Gentile & Bush­ man, 2012; Gentile & Sesma, 2003; Masten, 2001). This approach focuses on life experi­ ences that put people at risk for future maladaptation (risk factors) and factors that pro­ tect from this risk exposure (protective factors). Effects of different risk and protective factors accumulate; the cumulative risk model posits that the likelihood of problematic functioning is increased by every risk factor present and is decreased by each protective factor present (Masten, 2001; Wright, Masten, & Narayan, 2013). Cumulative risk is ex­ pected to have a bigger role in disrupting functioning than any single risk factor (Belsky & Fearon, 2002; Gentile & Sesma, 2003). For example, Gentile and Bushman (2012) ex­ plored effects of six risk and protective factors for aggression (media violence use, physi­ cal victimization, sex, hostile attribution bias, parental monitoring, and prior (p. 205) ag­ gression). Each risk factor increased the likelihood of aggression over a 6-month period, while each protective factor decreased it. Furthermore, the overall number of risk factors present was a better predictor of aggression than any single variable, showing evidence of cumulative risk.

Taking multiple risk factors into account is especially important when attempting to pre­ dict extreme and rare behaviors, such as violent behavior. After hearing about media vio­ lence effects, non-scientists sometimes give comments such as “I play violent video games, but I’ve never shot anyone” (Anderson et al., 2007). In fact, “shooting someone” is a severe form of physical aggression which most people will never engage in. Media vio­ lence, by itself, is unlikely to bring about extremely violent behavior (as is any single risk factor). However, it may increase the likelihood of more common or subtle forms of ag­ gression (e.g., verbally aggressive responses like swearing at someone). It can also in­ crease the risk of violent behavior for those individuals who have multiple risk factors (Anderson et al., 2007). In populations that have multiple risk factors and few protective factors, media violence effects on violent and criminal behaviors can be clearly observed (DeLisi, Vaughn, Gentile, Anderson, & Shook, 2013).

These processes can be illustrated using the metaphorical “aggression thermometer” (shown in Figure 18.2). People at the lowest end of the thermometer al­ ways act respectfully and nonaggressively. People at the highest end frequently engage in extremely aggressive and violent acts. Each risk factor may heat up the thermometer and

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Figure 18.2 The aggression thermometer.

From Gentile & Bushman (2012).

increase a person’s aggression level by several notches but is not powerful enough to change someone’s behavior from being routinely respectful to others to being violent. If, however, the person already has other risk factors (e.g., poverty, being bullied, living in a violent neighborhood, etc.), regular media violence use may contribute enough additional risk to push them to the top of the aggression thermometer, resulting in physical aggres­ sion and violence.

Selective Review of Empirical Evidence A central tenet of the risk-factor approach to understanding violent outcomes is that high- level aggression (such as assaults and murders) requires multiple risk factors to be present if it is to occur. The details of such interactions require more research in order to be fully understood. For example, future research could focus on the relative contribution of specific risk factors or determine whether specific risk factors must be present in or­ der for certain outcomes to occur, and work to better understand the potentially curvilin­ ear relationship between risk factor possession and such outcomes (Gentile & Bushman, 2012).

A resultant prediction from this approach is that the effect of any single risk factor should provide a progressively smaller impact on increasingly severe forms of aggression. As noted previously, the relationship between violent video game use and low-level aggres­ sive outcomes is small but robust (Anderson et al., 2010). The predicted effect of violent video game use alone on high-level aggressive outcomes is therefore likely to be much smaller and, as measured by many research designs, statistically undetectable.

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A good example of this is the oft-repeated claim that there are no studies demonstrating that media violence causes an increase in homicides. Statements such as these are rarely accompanied with the appropriate caveat that there are numerous risk factors at multiple levels (such as prenatal malnutrition, physical and psychological abuse, exposure to vio­ lence, provocation, access to guns, culture of honor) that conjunctively influence violent crimes. Furthermore, it is both practically and ethically impossible to conduct experimen­ tal studies of media violence effects on homicide rates. For this reason, we focus on stud­ ies using methods suited to (p. 206) answering research questions about media violence effects on violent behavior that actually are answerable. For the most part, that means fo­ cusing on correlational and longitudinal studies that include some type of violent behav­ ior as an outcome variable. Furthermore, we avoid studies that employed inappropriate statistical controls for investigations of this sort. For example, variables that are consid­ ered outcomes of violent media use (e.g., trait aggression; Anderson & Bushman, 2002) should not serve as statistical controls in such research as their inclusion effectively con­ trols for a study’s own dependent variable (Prot & Anderson, 2013).

Correlational Research

Among the most common methods for studying the effect of violent video game use on vi­ olent outcomes is the correlational design. This approach allows researchers to examine relationships between variables that are typically unmeasurable in a laboratory and de­ rive the large sample that is likely needed to observe the effects of violent video game use on violent outcomes.

In one large study by Denniston, Swahn, Hertz, and Romero (2011) of a nationally repre­ sentative sample of students in grades 9–12 (n = 14,041), media use (television, video game, and computer) was dichotomized by clustering individuals who reported spending more than versus less than 3 hours per day consuming either television or video games/ computer games/general computer use. Similarly, violent outcome variables were also di­ chotomous and included whether students had carried a weapon, a gun, or a weapon on school property within the 30 days prior to the survey. They also recorded whether stu­ dents had been in a physical fight or been in a physical fight on school property within the last 12 months. They found that frequent television and video game/computer use was associated with all of these outcomes. Furthermore, the relationships including outcomes such as physical fighting and carrying a weapon on school property remained significant even when controlling for race, gender, and grade. Of important note is that media use did not include the more specific measure of violent content and therefore the effects of violent content may be underestimated when considering these findings.

In another large-scale study by Boxer, Huesmann, Bushman, O’Brien, and Moceri (2008), 820 youth (390 of which were juvenile delinquents), as well as their parents and teachers, completed measures of violent media use (reported by youth) and a number of aggression and violence-related outcomes including frequency of punching or beating another indi­ vidual, throwing rocks or bottles at others, fights/bullying (reported by teachers and guardians), and several other related outcomes. Several additional risk factors for aggres­

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sion were also measured including general (low-level) aggressiveness, psychopathology, callous-unemotional traits, exposure to neighborhood violence, academic skills, and expo­ sure to low-level aggression. A composite of the violence-related measures was signifi­ cantly related to violent media use even after controlling for sex, age, and these other risk factors. Violent media use was also related to delinquency status, though this is a bi­ variate relationship in which gender and age were not controlled.

In a recent study by Ybarra, Huesmann, Korchmaros, and Reisner (2014), longitudinal da­ ta were collected from 9-to 18-year-olds (n = 1,489). This sample was analyzed as a cross- sectional set due to the rarity of youth reporting carrying a weapon in the past month across all three time points. They asked youth to report whether they had carried a weapon to school in the past month (such as a gun, knife, or club). They found that indi­ viduals who reported playing at least some games with violent content were five times more likely to report having carried a weapon to school compared to those who reported playing games with little to no violent content.

In an additional correlational study, DeLisi et al. (2013) collected data from 227 juvenile offenders. Predictors included measures of violent video game play, prosocial video game play, sex, age, race, and antisocial personality. The primary dependent variable was self- reported serious violence as measured by gang fighting, hitting a teacher/parent/peers, and attacking another person. Despite the use of statistical controls that are considered overly conservative (antisocial personality), violent video game use was significantly asso­ ciated with more violent acts.

Experimental Research

As noted previously, experimental research regarding the effects of violent media use on violence-related outcomes is rare due to the ethical considerations of eliciting seriously aggressive behavior in the laboratory. Experimental studies provide the strongest method for testing causality and ruling out potential confounding variables due to the use of ran­ dom assignment. One experimental study by Konijn, Bijvank, and Bushman (2007) was able to examine violent behavior (as defined by the World Health Organization) using a modified version (p. 207) of Taylor’s Competitive Reaction Time Task. This task involves asking participants to compete in reaction time trials against another, ostensible partici­ pant. Prior to each trial, participants select a noise volume and duration to administer to their opponent if the trial is won. Crucial to the violent outcome hypothesis, participants were told that high noise volume levels could cause permanent hearing damage to their opponent, which therefore meets the definition of violent behavior. As expected, they ob­ served a significant main effect of violent content on the selection of noise volume levels capable of producing damage. Furthermore, this tendency was exacerbated among those who expressed desires to be like the main character of the violent games.

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Longitudinal Research

Longitudinal studies are among the strongest in providing evidence for the effect of vio­ lent media use on violent behavior. They allow examination of violent behavioral change over time by measuring all key variables at two or more points in time. They also allow the testing of causal mechanisms by controlling for violent behavior at the onset of the study, thereby ruling out attraction effects that may occur if violent individuals gravitate toward violent media use. Importantly, effect sizes obtained when controlling for initial levels of violent behavior should not be considered measures of the “true” effect size as such a procedure effectively only captures the influence of violent media use on change in violent behavior between the two time periods measured and therefore ignores any prior influence of media violence that occurred before the study began.

In a short-term, longitudinal study by Gentile, Coyne, and Walsh (2011), children in the third, fourth, and fifth grades (total n = 430), their parents, and teachers completed sur­ veys at two time points within the school year (average lag between measurements was 5 months). Violent media use was measured by asking participants to report what their three favorite video games, television shows, and movies were; how violent each was; and how often they used each. The researchers then took the product of the frequency of use and the violent content for each show/video game/movie and summed these products to­ gether to produce a total violent content use measure. Of particular interest for the cur­ rent review, the measure was significantly related to a composite measure of child physi­ cal fighting as reported by the child, their teachers, and other forms of physical aggres­ sion reported by peers. Several studies have produced similar findings in which violent media use is related to physical fights among youth (Anderson et al., 2007; DuRant, Champion, & Wolfson, 2006; Gentile & Bushman, 2012). Considering this particular out­ come as violent behavior, however, may be debatable given that physical fighting among youth is arguably less likely to lead to serious outcomes such as physical injury requiring medical attention. However, longitudinal work by Huesmann, Eron, Lefkowitz, & Walder (1984) indicates that aggression levels early in life (age 8) are related to serious aggres­ sive behaviors later in life (age 30) including spousal abuse and antisocial and criminal behavior.

In other work by Huesmann et al. (Huesmann, Moise-Titus, Podolski, & Eron, 2003), indi­ viduals were followed for 15 years between the ages of 6–8 and 21–23. Data collection be­ gan in 1977–1978 and completed in 1992–1995. It is worth noting that only violent televi­ sion use was measured in the current sample. When considering this limitation, it is im­ portant to note that the psychological processes involved in both violent television and vi­ olent video game effects are thought of as highly similar (Anderson et al., 2003), and therefore results from work on violent television use should be considered relevant to questions regarding the influence of violent video game play on violent outcomes. The au­ thors found that high violent television use as a child was significantly related to adult­ hood pushing, grabbing, or shoving one’s spouse for males; throwing items at one’s spouse for females; shoving others for males and females; punching, beating, or choking

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another adult for females; and state-reported convictions for non-traffic violations among males.

In a study by Johnson, Cohen, Smailes, Kasen, and Brook (2002), children (n = 707) were followed over a 17-year interval. They found that television viewing among individuals (mean age 14) was associated with assault or physical fights resulting in injury, robbery, threats to injure someone, or using a weapon to commit a crime and other aggressive acts years later (mean ages 16 or 22). Furthermore, these associations continued when examined at the time these individuals were an average of 30 years old. Most critically, these associations persisted even when controlling for a variety of factors including previ­ ous aggressive behavior, childhood neglect, family income, neighborhood violence, parental education, and psychiatric disorders.

(p. 208) Contrasting Findings

Despite the seemingly strong findings of these studies, other investigations have found less support. One study by Gunter and Daly (2012) used a propensity score matching technique in which individuals who reported playing mature-rated (M-rated) games were individually matched with others who did not play such games but held similar scores on a large battery of control variables. They found that without using the matched sample, M-rated (mature) game players were significantly more likely to engage in all violent out­ comes including hitting another person, participating in a group fight, carrying a weapon, or carrying a gun and produced a higher overall violent score. When examining the matched sample, however, these relationships were reduced to nonsignificance for all measures except for participating in a group fight and carrying a weapon. Female matched participants scores were not reduced to nonsignificance but still showed fewer and weaker overall effects.

One issue worth noting in this study is that the use of playing M-rated games as an indi­ cator is not the best method for measuring violent video game use because such ratings take into account the presence of profanity and nudity in games—not solely the violent content. Previous research indicates that this difference in measuring violent video game exposure can lead to meaningful decrements in observed effect sizes (Busching et al., 2013). More importantly, however, the use of propensity score matching dramatically re­ duces the sample size used and thus the power to detect true but small effects. Given that the theoretical effect size of violent video game use on violent outcomes should be quite small, the statistical power required to detect such effects demands very large sample sizes. In fact, examination of the group differences between M-rated game players and nonviolent game players in the matched samples indicates that M-rated players scored higher on every metric of violent outcomes except for gun-carrying among males, sug­ gesting a larger sample is needed.

A cross-sectional study by Ybarra et al. (2008), of youth aged 10–15 years (n = 1,588) in­ cluded measures of violent video game, violent music, violent television use, and expo­ sure to depictions of real violence online using the Youth Internet Safety Survey. They

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measured seriously violent behaviors such as stabbing or shooting someone, aggravated assault, robbery, and sexual assault. Their primary dependent variable was whether indi­ viduals had engaged in one or more of these behaviors in the previous year. They found that violent television, video game play, and even music use were each associated with in­ creased likelihoods of engaging in at least one seriously violent act within the past year. Individuals consuming such violent media were between 2.6 and 7.2 times more likely to engage in violent acts depending on the type of violent media used. These relationships, however, dropped to nonsignificance for all forms of media except for the depiction of re­ al-life violence on Internet websites when a large battery of covariates including race, so­ cioeconomic status, substance use, violence in the home and community, a number of in­ dices of poor parental care, academic performance, and delinquent peers were added to the statistical model. Those who viewed instances of real violence on online websites, however, remained five times more likely to engage in seriously violent behavior within the past year compared to those who did not view such websites. The authors note that the explanations for the disparity between these effect sizes are unknown and require fur­ ther research.

In another contrasting study, Robertson, McAnally, and Hancox (2013) assessed a group of individuals (n = 1,037) from birth to 26 years of age beginning in 1972–1973. Impor­ tantly, they assessed television viewing throughout a large portion of the participants’ childhood (ages 5–15 years) and also measured several covariates during this time. They found that television viewing throughout childhood was related to the likelihood of being diagnosed with antisocial personality disorder, aggressive personality traits, and the like­ lihood of criminal conviction. These effects occurred even when statistically controlling for sex, IQ, socioeconomic status, previous antisocial behavior, and indices of parental control. The contrasting finding, however, was that the likelihood of violent convictions was not a significant outcome after including each of these statistical controls. Of course, the study suffers from failing to measure violent content of television viewing. Also, it may have been necessary to include more participants in the study as well, given that vio­ lent convictions are relatively rare.

Conclusion The effects of violent media have been heavily researched over the past several decades. There is now a wealth of evidence supporting the conclusion that violent video game use serves as a causal risk factor for aggressive affect, thoughts, and behavior (Anderson et al., 2010, Greitemeyer & Mügge, 2014). (p. 209) The evidence for violent television and film effects is similarly overwhelmingly strong.

As our review indicates, aggressive acts differ across a wide range of severity. The bulk of research, especially experimental research, has focused on milder forms of aggression. There is much less work regarding the influence of violent media use on the more ex­ treme forms of aggression covered in this chapter.

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A central theme arising from our review is that the studies conducted on this topic do not arrive to precisely the same conclusions. Studies that tend not to detect any effects of vio­ lent media use also tend to measure the most extreme forms of aggressive behavior (e.g., group fighting, stabbings, shootings). Sample sizes appear to be a potential factor con­ tributing to null effects in at least some of these cases. Some studies have failed to assess exposure to violent screen media, assessing total time spent rather than time on violent media.

Studies that demonstrate no relationship between violent media exposure and violent be­ havior also tend to include large numbers of statistical control variables, some of which are actually potential outcomes of high media violence exposure. Other control measures often tap into factors related to violent outcomes such as poor parenting, violence seen in the community, delinquent peer presence, and poor academic performance. Such factors are crucially important to parse out of the relationship between violent media use and vi­ olent outcomes. The results of these studies suggest that any bivariate relationship may be at least partially fueled by these and similar third variables. However, it is important to note that such techniques often are not pre-tested by ensuring that both violent media use and violent behavior are significantly related to each covariate. The inclusion of fac­ tors that do not meet this statistical criteria may serve to artificially deflate the relation­ ship between violent media use and violent outcomes. In cases such as this, the variance associated between the covariate, the predictor, and the outcome, is statistically re­ moved, even when there is no “true” relationship to be controlled. In other words, the variance in the dependent variable (violent behavior) is inappropriately attributed to the covariate, and, consequently, violent media use has less variance to “explain” the out­ come (Prot & Anderson, 2013). Future research needs to do a better job of testing and re­ porting details of the statistical control variable.

Investigations that do report significant effects on violent behavior tend to assess more common forms of violent behavior, use more specific measures of exposure to violent me­ dia, and tend to be large-scale longitudinal studies that examine behavior over very long periods of time. This may suggest that the effects of violent media use on severe violent behavior require sustained, long-term exposure in order for such extreme forms of ag­ gression to emerge. If this is the case, the “snapshot” method used in correlational stud­ ies may not be sufficient to detect effects of violent media use on truly violent behavior.

The subject matter discussed here has been the focus of intense debate with extreme points having been made on either side of the argument, especially within lay circles. In commenting on a murder in 2004, the lawyer Jack Thompson, stated that “We have dozens of killings in the US by children who had played these types of [violent] games…. These types of games are basically murder simulators. There are people being killed here almost on a daily basis” (CNN International, 2004). In contrast, the president of the Elec­ tronics Software Association, Doug Lowenstein, was cited in a 2000 interview as stating that “There is absolutely no evidence, none, that playing a violent video game leads to ag­ gressive behavior” (Cable News Network, 2000; as cited in Anderson & Bushman, 2001).

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Due to the work of numerous scholars on the subject cited here, we can safely assert that the truth lies somewhere in between these extreme points of view.

A lot is already known about both the short- and long-term processes by which television, film, and video game violence exposure increases aggressive and violent behavior. The basic bio-social-cognitive models have been well-tested and validated. Nonetheless, a great deal more work is required on this topic before we fully understand all of the conse­ quences of violent game play. For example, much more work is needed in examining such effects over long periods of time. Such work needs to include much larger samples; more precise measures of key predictor, outcome, and control variables; and a host of addition­ al variables that have only recently begun to receive research attention. The latter cate­ gory includes variables related to media violent effects on stereotypes of various out­ groups, on attention deficits and impulse control problems, and on moral reasoning, be­ liefs, and attitudes. Longitudinal studies are often limited to a span of a few years, but this review suggests that effects on extreme forms of behavior may be best studied under much longer time periods consisting of a decade or more of observation. More work is al­ so needed in determining (p. 210) the relationship between violent game play and the severity of outcomes. Findings supporting risk factor approaches to understanding ag­ gression frequently consider the impact of an increasing number of risk factors on the likelihood of engaging in a single violent outcome (e.g., Gentile & Bushman, 2012). Much less work has been conducted on the relationship between risk factor possession and out­ comes based on severity within an individual study (e.g., the number of risk factors re­ quired for highly violent outcomes to occur compared to relatively less extreme forms of violence). Without doubt, this area of study is likely to receive heavy focus by the scientif­ ic community in the next several decades.

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Christopher L. Groves

Christopher L. Groves, PhD, MS, Department of Psychology, University of Wisconsin, Oshkosh

Sara Prot

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Sara Prot, PhD, School of Psychological, Social and Behavioural Sciences, Coventry University

Craig A. Anderson

Craig A. Anderson, PhD, MS Department of Psychology, Iowa State University