research paper on violence in the media

Tools and Resources
Customer Services
Corrections
Crime, Media, and Popular Culture
Criminal Behavior
Criminological Theory
Critical Criminology
Geography of Crime
International Crime
Juvenile Justice
Prevention/Public Policy
Race, Ethnicity, and Crime
Research Methods
Victimology/Criminal Victimization
White Collar Crime
Women, Crime, and Justice
Share This Facebook LinkedIn Twitter

Article contents

Violence, media effects, and criminology.

Nickie D. Phillips Nickie D. Phillips Department of Sociology and Criminal Justice, St. Francis College
https://doi.org/10.1093/acrefore/9780190264079.013.189
Published online: 27 July 2017

Debate surrounding the impact of media representations on violence and crime has raged for decades and shows no sign of abating. Over the years, the targets of concern have shifted from film to comic books to television to video games, but the central questions remain the same. What is the relationship between popular media and audience emotions, attitudes, and behaviors? While media effects research covers a vast range of topics—from the study of its persuasive effects in advertising to its positive impact on emotions and behaviors—of particular interest to criminologists is the relationship between violence in popular media and real-life aggression and violence. Does media violence cause aggression and/or violence?

The study of media effects is informed by a variety of theoretical perspectives and spans many disciplines including communications and media studies, psychology, medicine, sociology, and criminology. Decades of research have amassed on the topic, yet there is no clear agreement about the impact of media or about which methodologies are most appropriate. Instead, there continues to be disagreement about whether media portrayals of violence are a serious problem and, if so, how society should respond.

Conflicting interpretations of research findings inform and shape public debate around media effects. Although there seems to be a consensus among scholars that exposure to media violence impacts aggression, there is less agreement around its potential impact on violence and criminal behavior. While a few criminologists focus on the phenomenon of copycat crimes, most rarely engage with whether media directly causes violence. Instead, they explore broader considerations of the relationship between media, popular culture, and society.

media exposure
criminal behavior
popular culture
media violence
media and crime
copycat crimes

Media Exposure, Violence, and Aggression

On Friday July 22, 2016 , a gunman killed nine people at a mall in Munich, Germany. The 18-year-old shooter was subsequently characterized by the media as being under psychiatric care and harboring at least two obsessions. One, an obsession with mass shootings, including that of Anders Breivik who ultimately killed 77 people in Norway in 2011 , and the other an obsession with video games. A Los Angeles, California, news report stated that the gunman was “an avid player of first-person shooter video games, including ‘Counter-Strike,’” while another headline similarly declared, “Munich gunman, a fan of violent video games, rampage killers, had planned attack for a year”(CNN Wire, 2016 ; Reuters, 2016 ). This high-profile incident was hardly the first to link popular culture to violent crime. Notably, in the aftermath of the 1999 Columbine shooting massacre, for example, media sources implicated and later discredited music, video games, and a gothic aesthetic as causal factors of the crime (Cullen, 2009 ; Yamato, 2016 ). Other, more recent, incidents have echoed similar claims suggesting that popular culture has a nefarious influence on consumers.

Media violence and its impact on audiences are among the most researched and examined topics in communications studies (Hetsroni, 2007 ). Yet, debate over whether media violence causes aggression and violence persists, particularly in response to high-profile criminal incidents. Blaming video games, and other forms of media and popular culture, as contributing to violence is not a new phenomenon. However, interpreting media effects can be difficult because commenters often seem to indicate a grand consensus that understates more contradictory and nuanced interpretations of the data.

In fact, there is a consensus among many media researchers that media violence has an impact on aggression although its impact on violence is less clear. For example, in response to the shooting in Munich, Brad Bushman, professor of communication and psychology, avoided pinning the incident solely on video games, but in the process supported the assertion that video gameplay is linked to aggression. He stated,

While there isn’t complete consensus in any scientific field, a study we conducted showed more than 90% of pediatricians and about two-thirds of media researchers surveyed agreed that violent video games increase aggression in children. (Bushman, 2016 )

Others, too, have reached similar conclusions with regard to other media. In 2008 , psychologist John Murray summarized decades of research stating, “Fifty years of research on the effect of TV violence on children leads to the inescapable conclusion that viewing media violence is related to increases in aggressive attitudes, values, and behaviors” (Murray, 2008 , p. 1212). Scholars Glenn Sparks and Cheri Sparks similarly declared that,

Despite the fact that controversy still exists about the impact of media violence, the research results reveal a dominant and consistent pattern in favor of the notion that exposure to violent media images does increase the risk of aggressive behavior. (Sparks & Sparks, 2002 , p. 273)

In 2014 , psychologist Wayne Warburton more broadly concluded that the vast majority of studies have found “that exposure to violent media increases the likelihood of aggressive behavior in the short and longterm, increases hostile perceptions and attitudes, and desensitizes individuals to violent content” (Warburton, 2014 , p. 64).

Criminologists, too, are sensitive to the impact of media exposure. For example, Jacqueline Helfgott summarized the research:

There have been over 1000 studies on the effects of TV and film violence over the past 40 years. Research on the influence of TV violence on aggression has consistently shown that TV violence increases aggression and social anxiety, cultivates a “mean view” of the world, and negatively impacts real-world behavior. (Helfgott, 2015 , p. 50)

In his book, Media Coverage of Crime and Criminal Justice , criminologist Matthew Robinson stated, “Studies of the impact of media on violence are crystal clear in their findings and implications for society” (Robinson, 2011 , p. 135). He cited studies on childhood exposure to violent media leading to aggressive behavior as evidence. In his pioneering book Media, Crime, and Criminal Justice , criminologist Ray Surette concurred that media violence is linked to aggression, but offered a nuanced interpretation. He stated,

a small to modest but genuine causal role for media violence regarding viewer aggression has been established for most beyond a reasonable doubt . . . There is certainly a connection between violent media and social aggression, but its strength and configuration is simply not known at this time. (Surette, 2011 , p. 68)

The uncertainties about the strength of the relationship and the lack of evidence linking media violence to real-world violence is often lost in the news media accounts of high-profile violent crimes.

Media Exposure and Copycat Crimes

While many scholars do seem to agree that there is evidence that media violence—whether that of film, TV, or video games—increases aggression, they disagree about its impact on violent or criminal behavior (Ferguson, 2014 ; Gunter, 2008 ; Helfgott, 2015 ; Reiner, 2002 ; Savage, 2008 ). Nonetheless, it is violent incidents that most often prompt speculation that media causes violence. More specifically, violence that appears to mimic portrayals of violent media tends to ignite controversy. For example, the idea that films contribute to violent crime is not a new assertion. Films such as A Clockwork Orange , Menace II Society , Set it Off , and Child’s Play 3 , have been linked to crimes and at least eight murders have been linked to Oliver Stone’s 1994 film Natural Born Killers (Bracci, 2010 ; Brooks, 2002 ; PBS, n.d. ). Nonetheless, pinpointing a direct, causal relationship between media and violent crime remains elusive.

Criminologist Jacqueline Helfgott defined copycat crime as a “crime that is inspired by another crime” (Helfgott, 2015 , p. 51). The idea is that offenders model their behavior on media representations of violence whether real or fictional. One case, in particular, illustrated how popular culture, media, and criminal violence converge. On July 20, 2012 , James Holmes entered the midnight premiere of The Dark Knight Rises , the third film in the massively successful Batman trilogy, in a movie theater in Aurora, Colorado. He shot and killed 12 people and wounded 70 others. At the time, the New York Times described the incident,

Witnesses told the police that Mr. Holmes said something to the effect of “I am the Joker,” according to a federal law enforcement official, and that his hair had been dyed or he was wearing a wig. Then, as people began to rise from their seats in confusion or anxiety, he began to shoot. The gunman paused at least once, several witnesses said, perhaps to reload, and continued firing. (Frosch & Johnson, 2012 ).

The dyed hair, Holme’s alleged comment, and that the incident occurred at a popular screening led many to speculate that the shooter was influenced by the earlier film in the trilogy and reignited debate around the impact about media violence. The Daily Mail pointed out that Holmes may have been motivated by a 25-year-old Batman comic in which a gunman opens fire in a movie theater—thus further suggesting the iconic villain served as motivation for the attack (Graham & Gallagher, 2012 ). Perceptions of the “Joker connection” fed into the notion that popular media has a direct causal influence on violent behavior even as press reports later indicated that Holmes had not, in fact, made reference to the Joker (Meyer, 2015 ).

A week after the Aurora shooting, the New York Daily News published an article detailing a “possible copycat” crime. A suspect was arrested in his Maryland home after making threatening phone calls to his workplace. The article reported that the suspect stated, “I am a [sic] joker” and “I’m going to load my guns and blow everybody up.” In their search, police found “a lethal arsenal of 25 guns and thousands of rounds of ammunition” in the suspect’s home (McShane, 2012 ).

Though criminologists are generally skeptical that those who commit violent crimes are motivated solely by media violence, there does seem to be some evidence that media may be influential in shaping how some offenders commit crime. In his study of serious and violent juvenile offenders, criminologist Ray Surette found “about one out of three juveniles reports having considered a copycat crime and about one out of four reports actually having attempted one.” He concluded that “those juveniles who are self-reported copycats are significantly more likely to credit the media as both a general and personal influence.” Surette contended that though violent offenses garner the most media attention, copycat criminals are more likely to be career criminals and to commit property crimes rather than violent crimes (Surette, 2002 , pp. 56, 63; Surette 2011 ).

Discerning what crimes may be classified as copycat crimes is a challenge. Jacqueline Helfgott suggested they occur on a “continuum of influence.” On one end, she said, media plays a relatively minor role in being a “component of the modus operandi” of the offender, while on the other end, she said, “personality disordered media junkies” have difficulty distinguishing reality from violent fantasy. According to Helfgott, various factors such as individual characteristics, characteristics of media sources, relationship to media, demographic factors, and cultural factors are influential. Overall, scholars suggest that rather than pushing unsuspecting viewers to commit crimes, media more often influences how , rather than why, someone commits a crime (Helfgott, 2015 ; Marsh & Melville, 2014 ).

Given the public interest, there is relatively little research devoted to exactly what copycat crimes are and how they occur. Part of the problem of studying these types of crimes is the difficulty defining and measuring the concept. In an effort to clarify and empirically measure the phenomenon, Surette offered a scale that included seven indicators of copycat crimes. He used the following factors to identify copycat crimes: time order (media exposure must occur before the crime); time proximity (a five-year cut-off point of exposure); theme consistency (“a pattern of thought, feeling or behavior in the offender which closely parallels the media model”); scene specificity (mimicking a specific scene); repetitive viewing; self-editing (repeated viewing of single scene while “the balance of the film is ignored”); and offender statements and second-party statements indicating the influence of media. Findings demonstrated that cases are often prematurely, if not erroneously, labeled as “copycat.” Surette suggested that use of the scale offers a more precise way for researchers to objectively measure trends and frequency of copycat crimes (Surette, 2016 , p. 8).

Media Exposure and Violent Crimes

Overall, a causal link between media exposure and violent criminal behavior has yet to be validated, and most researchers steer clear of making such causal assumptions. Instead, many emphasize that media does not directly cause aggression and violence so much as operate as a risk factor among other variables (Bushman & Anderson, 2015 ; Warburton, 2014 ). In their review of media effects, Brad Bushman and psychologist Craig Anderson concluded,

In sum, extant research shows that media violence is a causal risk factor not only for mild forms of aggression but also for more serious forms of aggression, including violent criminal behavior. That does not mean that violent media exposure by itself will turn a normal child or adolescent who has few or no other risk factors into a violent criminal or a school shooter. Such extreme violence is rare, and tends to occur only when multiple risk factors converge in time, space, and within an individual. (Bushman & Anderson, 2015 , p. 1817)

Surette, however, argued that there is no clear linkage between media exposure and criminal behavior—violent or otherwise. In other words, a link between media violence and aggression does not necessarily mean that exposure to violent media causes violent (or nonviolent) criminal behavior. Though there are thousands of articles addressing media effects, many of these consist of reviews or commentary about prior research findings rather than original studies (Brown, 2007 ; Murray, 2008 ; Savage, 2008 ; Surette, 2011 ). Fewer, still, are studies that specifically measure media violence and criminal behavior (Gunter, 2008 ; Strasburger & Donnerstein, 2014 ). In their meta-analysis investigating the link between media violence and criminal aggression, scholars Joanne Savage and Christina Yancey did not find support for the assertion. Instead, they concluded,

The study of most consequence for violent crime policy actually found that exposure to media violence was significantly negatively related to violent crime rates at the aggregate level . . . It is plain to us that the relationship between exposure to violent media and serious violence has yet to be established. (Savage & Yancey, 2008 , p. 786)

Researchers continue to measure the impact of media violence among various forms of media and generally stop short of drawing a direct causal link in favor of more indirect effects. For example, one study examined the increase of gun violence in films over the years and concluded that violent scenes provide scripts for youth that justify gun violence that, in turn, may amplify aggression (Bushman, Jamieson, Weitz, & Romer, 2013 ). But others report contradictory findings. Patrick Markey and colleagues studied the relationship between rates of homicide and aggravated assault and gun violence in films from 1960–2012 and found that over the years, violent content in films increased while crime rates declined . After controlling for age shifts, poverty, education, incarceration rates, and economic inequality, the relationships remained statistically non-significant (Markey, French, & Markey, 2015 , p. 165). Psychologist Christopher Ferguson also failed to find a relationship between media violence in films and video games and violence (Ferguson, 2014 ).

Another study, by Gordon Dahl and Stefano DellaVigna, examined violent films from 1995–2004 and found decreases in violent crimes coincided with violent blockbuster movie attendance. Here, it was not the content that was alleged to impact crime rates, but instead what the authors called “voluntary incapacitation,” or the shifting of daily activities from that of potential criminal behavior to movie attendance. The authors concluded, “For each million people watching a strongly or mildly violent movie, respectively, violent crime decreases by 1.9% and 2.1%. Nonviolent movies have no statistically significant impact” (Dahl & DellaVigna, p. 39).

High-profile cases over the last several years have shifted public concern toward the perceived danger of video games, but research demonstrating a link between video games and criminal violence remains scant. The American Psychiatric Association declared that “research demonstrates a consistent relation between violent video game use and increases in aggressive behavior, aggressive cognitions and aggressive affect, and decreases in prosocial behavior, empathy and sensitivity to aggression . . .” but stopped short of claiming that video games impact criminal violence. According to Breuer and colleagues, “While all of the available meta-analyses . . . found a relationship between aggression and the use of (violent) video games, the size and interpretation of this connection differ largely between these studies . . .” (APA, 2015 ; Breuer et al., 2015 ; DeCamp, 2015 ). Further, psychologists Patrick Markey, Charlotte Markey, and Juliana French conducted four time-series analyses investigating the relationship between video game habits and assault and homicide rates. The studies measured rates of violent crime, the annual and monthly video game sales, Internet searches for video game walkthroughs, and rates of violent crime occurring after the release dates of popular games. The results showed that there was no relationship between video game habits and rates of aggravated assault and homicide. Instead, there was some indication of decreases in crime (Markey, Markey, & French, 2015 ).

Another longitudinal study failed to find video games as a predictor of aggression, instead finding support for the “selection hypothesis”—that physically aggressive individuals (aged 14–17) were more likely to choose media content that contained violence than those slightly older, aged 18–21. Additionally, the researchers concluded,

that violent media do not have a substantial impact on aggressive personality or behavior, at least in the phases of late adolescence and early adulthood that we focused on. (Breuer, Vogelgesang, Quandt, & Festl, 2015 , p. 324)

Overall, the lack of a consistent finding demonstrating that media exposure causes violent crime may not be particularly surprising given that studies linking media exposure, aggression, and violence suffer from a host of general criticisms. By way of explanation, social theorist David Gauntlett maintained that researchers frequently employ problematic definitions of aggression and violence, questionable methodologies, rely too much on fictional violence, neglect the social meaning of violence, and assume the third-person effect—that is, assume that other, vulnerable people are impacted by media, but “we” are not (Ferguson & Dyck, 2012 ; Gauntlett, 2001 ).

Others, such as scholars Martin Barker and Julian Petley, flatly reject the notion that violent media exposure is a causal factor for aggression and/or violence. In their book Ill Effects , the authors stated instead that it is simply “stupid” to query about “what are the effects of [media] violence” without taking context into account (p. 2). They counter what they describe as moral campaigners who advance the idea that media violence causes violence. Instead, Barker and Petley argue that audiences interpret media violence in a variety of ways based on their histories, experiences, and knowledge, and as such, it makes little sense to claim media “cause” violence (Barker & Petley, 2001 ).

Given the seemingly inconclusive and contradictory findings regarding media effects research, to say that the debate can, at times, be contentious is an understatement. One article published in European Psychologist queried “Does Doing Media Violence Research Make One Aggressive?” and lamented that the debate had devolved into an ideological one (Elson & Ferguson, 2013 ). Another academic journal published a special issue devoted to video games and youth and included a transcript of exchanges between two scholars to demonstrate that a “peaceful debate” was, in fact, possible (Ferguson & Konijn, 2015 ).

Nonetheless, in this debate, the stakes are high and the policy consequences profound. After examining over 900 published articles, publication patterns, prominent authors and coauthors, and disciplinary interest in the topic, scholar James Anderson argued that prominent media effects scholars, whom he deems the “causationists,” had developed a cottage industry dependent on funding by agencies focused primarily on the negative effects of media on children. Anderson argued that such a focus presents media as a threat to family values and ultimately operates as a zero-sum game. As a result, attention and resources are diverted toward media and away from other priorities that are essential to understanding aggression such as social disadvantage, substance abuse, and parental conflict (Anderson, 2008 , p. 1276).

Theoretical Perspectives on Media Effects

Understanding how media may impact attitudes and behavior has been the focus of media and communications studies for decades. Numerous theoretical perspectives offer insight into how and to what extent the media impacts the audience. As scholar Jenny Kitzinger documented in 2004 , there are generally two ways to approach the study of media effects. One is to foreground the power of media. That is, to suggest that the media holds powerful sway over viewers. Another perspective is to foreground the power and heterogeneity of the audience and to recognize that it is comprised of active agents (Kitzinger, 2004 ).

The notion of an all-powerful media can be traced to the influence of scholars affiliated with the Institute for Social Research, or Frankfurt School, in the 1930–1940s and proponents of the mass society theory. The institute was originally founded in Germany but later moved to the United States. Criminologist Yvonne Jewkes outlined how mass society theory assumed that members of the public were susceptible to media messages. This, theorists argued, was a result of rapidly changing social conditions and industrialization that produced isolated, impressionable individuals “cut adrift from kinship and organic ties and lacking moral cohesion” (Jewkes, 2015 , p. 13). In this historical context, in the era of World War II, the impact of Nazi propaganda was particularly resonant. Here, the media was believed to exhibit a unidirectional flow, operating as a powerful force influencing the masses. The most useful metaphor for this perspective described the media as a “hypodermic syringe” that could “‘inject’ values, ideas and information directly into the passive receiver producing direct and unmediated ‘effects’” (Jewkes, 2015 , pp. 16, 34). Though the hypodermic syringe model seems simplistic today, the idea that the media is all-powerful continues to inform contemporary public discourse around media and violence.

Concern of the power of media captured the attention of researchers interested in its purported negative impact on children. In one of the earliest series of studies in the United States during the late 1920s–1930s, researchers attempted to quantitatively measure media effects with the Payne Fund Studies. For example, they investigated how film, a relatively new medium, impacted children’s attitudes and behaviors, including antisocial and violent behavior. At the time, the Payne Fund Studies’ findings fueled the notion that children were indeed negatively influenced by films. This prompted the film industry to adopt a self-imposed code regulating content (Sparks & Sparks, 2002 ; Surette, 2011 ). Not everyone agreed with the approach. In fact, the methodologies employed in the studies received much criticism, and ultimately, the movement was branded as a moral crusade to regulate film content. Scholars Garth Jowett, Ian Jarvie, and Kathryn Fuller wrote about the significance of the studies,

We have seen this same policy battle fought and refought over radio, television, rock and roll, music videos and video games. Their researchers looked to see if intuitive concerns could be given concrete, measurable expression in research. While they had partial success, as have all subsequent efforts, they also ran into intractable problems . . . Since that day, no way has yet been found to resolve the dilemma of cause and effect: do crime movies create more crime, or do the criminally inclined enjoy and perhaps imitate crime movies? (Jowett, Jarvie, & Fuller, 1996 , p. 12)

As the debate continued, more sophisticated theoretical perspectives emerged. Efforts to empirically measure the impact of media on aggression and violence continued, albeit with equivocal results. In the 1950s and 1960s, psychological behaviorism, or understanding psychological motivations through observable behavior, became a prominent lens through which to view the causal impact of media violence. This type of research was exemplified by Albert Bandura’s Bobo Doll studies demonstrating that children exposed to aggressive behavior, either observed in real life or on film, behaved more aggressively than those in control groups who were not exposed to the behavior. The assumption derived was that children learn through exposure and imitate behavior (Bandura, Ross, & Ross, 1963 ). Though influential, the Bandura experiments were nevertheless heavily criticized. Some argued the laboratory conditions under which children were exposed to media were not generalizable to real-life conditions. Others challenged the assumption that children absorb media content in an unsophisticated manner without being able to distinguish between fantasy and reality. In fact, later studies did find children to be more discerning consumers of media than popularly believed (Gauntlett, 2001 ).

Hugely influential in our understandings of human behavior, the concept of social learning has been at the core of more contemporary understandings of media effects. For example, scholar Christopher Ferguson noted that the General Aggression Model (GAM), rooted in social learning and cognitive theory, has for decades been a dominant model for understanding how media impacts aggression and violence. GAM is described as the idea that “aggression is learned by the activation and repetition of cognitive scripts coupled with the desensitization of emotional responses due to repeated exposure.” However, Ferguson noted that its usefulness has been debated and advocated for a paradigm shift (Ferguson, 2013 , pp. 65, 27; Krahé, 2014 ).

Though the methodologies of the Payne Fund Studies and Bandura studies were heavily criticized, concern over media effects continued to be tied to larger moral debates including the fear of moral decline and concern over the welfare of children. Most notably, in the 1950s, psychiatrist Frederic Wertham warned of the dangers of comic books, a hugely popular medium at the time, and their impact on juveniles. Based on anecdotes and his clinical experience with children, Wertham argued that images of graphic violence and sexual debauchery in comic books were linked to juvenile delinquency. Though he was far from the only critic of comic book content, his criticisms reached the masses and gained further notoriety with the publication of his 1954 book, Seduction of the Innocent . Wertham described the comic book content thusly,

The stories have a lot of crime and gunplay and, in addition, alluring advertisements of guns, some of them full-page and in bright colors, with four guns of various sizes and descriptions on a page . . . Here is the repetition of violence and sexiness which no Freud, Krafft-Ebing or Havelock Ellis ever dreamed could be offered to children, and in such profusion . . . I have come to the conclusion that this chronic stimulation, temptation and seduction by comic books, both their content and their alluring advertisements of knives and guns, are contributing factors to many children’s maladjustment. (Wertham, 1954 , p. 39)

Wertham’s work was instrumental in shaping public opinion and policies about the dangers of comic books. Concern about the impact of comics reached its apex in 1954 with the United States Senate Judiciary Subcommittee on Juvenile Delinquency. Wertham testified before the committee, arguing that comics were a leading cause of juvenile delinquency. Ultimately, the protest of graphic content in comic books by various interest groups contributed to implementation of the publishers’ self-censorship code, the Comics Code Authority, which essentially designated select books that were deemed “safe” for children (Nyberg, 1998 ). The code remained in place for decades, though it was eventually relaxed and decades later phased out by the two most dominant publishers, DC and Marvel.

Wertham’s work, however influential in impacting the comic industry, was ultimately panned by academics. Although scholar Bart Beaty characterized Wertham’s position as more nuanced, if not progressive, than the mythology that followed him, Wertham was broadly dismissed as a moral reactionary (Beaty, 2005 ; Phillips & Strobl, 2013 ). The most damning criticism of Wertham’s work came decades later, from Carol Tilley’s examination of Wertham’s files. She concluded that in Seduction of the Innocent ,

Wertham manipulated, overstated, compromised, and fabricated evidence—especially that evidence he attributed to personal clinical research with young people—for rhetorical gain. (Tilley, 2012 , p. 386)

Tilley linked Wertham’s approach to that of the Frankfurt theorists who deemed popular culture a social threat and contended that Wertham was most interested in “cultural correction” rather than scientific inquiry (Tilley, 2012 , p. 404).

Over the decades, concern about the moral impact of media remained while theoretical and methodological approaches to media effects studies continued to evolve (Rich, Bickham, & Wartella, 2015 ). In what many consider a sophisticated development, theorists began to view the audience as more active and multifaceted than the mass society perspective allowed (Kitzinger, 2004 ). One perspective, based on a “uses and gratifications” model, assumes that rather than a passive audience being injected with values and information, a more active audience selects and “uses” media as a response to their needs and desires. Studies of uses and gratifications take into account how choice of media is influenced by one’s psychological and social circumstances. In this context, media provides a variety of functions for consumers who may engage with it for the purposes of gathering information, reducing boredom, seeking enjoyment, or facilitating communication (Katz, Blumler, & Gurevitch, 1973 ; Rubin, 2002 ). This approach differs from earlier views in that it privileges the perspective and agency of the audience.

Another approach, the cultivation theory, gained momentum among researchers in the 1970s and has been of particular interest to criminologists. It focuses on how television television viewing impacts viewers’ attitudes toward social reality. The theory was first introduced by communications scholar George Gerbner, who argued the importance of understanding messages that long-term viewers absorb. Rather than examine the effect of specific content within any given programming, cultivation theory,

looks at exposure to massive flows of messages over long periods of time. The cultivation process takes place in the interaction of the viewer with the message; neither the message nor the viewer are all-powerful. (Gerbner, Gross, Morgan, Singnorielli, & Shanahan, 2002 , p. 48)

In other words, he argued, television viewers are, over time, exposed to messages about the way the world works. As Gerbner and colleagues stated, “continued exposure to its messages is likely to reiterate, confirm, and nourish—that is, cultivate—its own values and perspectives” (p. 49).

One of the most well-known consequences of heavy media exposure is what Gerbner termed the “mean world” syndrome. He coined it based on studies that found that long-term exposure to media violence among heavy television viewers, “tends to cultivate the image of a relatively mean and dangerous world” (p. 52). Inherent in Gerbner’s view was that media representations are separate and distinct entities from “real life.” That is, it is the distorted representations of crime and violence that cultivate the notion that the world is a dangerous place. In this context, Gerbner found that heavy television viewers are more likely to be fearful of crime and to overestimate their chances of being a victim of violence (Gerbner, 1994 ).

Though there is evidence in support of cultivation theory, the strength of the relationship between media exposure and fear of crime is inconclusive. This is in part due to the recognition that audience members are not homogenous. Instead, researchers have found that there are many factors that impact the cultivating process. This includes, but is not limited to, “class, race, gender, place of residence, and actual experience of crime” (Reiner, 2002 ; Sparks, 1992 ). Or, as Ted Chiricos and colleagues remarked in their study of crime news and fear of crime, “The issue is not whether media accounts of crime increase fear, but which audiences, with which experiences and interests, construct which meanings from the messages received” (Chiricos, Eschholz, & Gertz, p. 354).

Other researchers found that exposure to media violence creates a desensitizing effect, that is, that as viewers consume more violent media, they become less empathetic as well as psychologically and emotionally numb when confronted with actual violence (Bartholow, Bushman, & Sestir, 2006 ; Carnagey, Anderson, & Bushman, 2007 ; Cline, Croft, & Courrier, 1973 ; Fanti, Vanman, Henrich, & Avraamides, 2009 ; Krahé et al., 2011 ). Other scholars such as Henry Giroux, however, point out that our contemporary culture is awash in violence and “everyone is infected.” From this perspective, the focus is not on certain individuals whose exposure to violent media leads to a desensitization of real-life violence, but rather on the notion that violence so permeates society that it has become normalized in ways that are divorced from ethical and moral implications. Giroux wrote,

While it would be wrong to suggest that the violence that saturates popular culture directly causes violence in the larger society, it is arguable that such violence serves not only to produce an insensitivity to real life violence but also functions to normalize violence as both a source of pleasure and as a practice for addressing social issues. When young people and others begin to believe that a world of extreme violence, vengeance, lawlessness, and revenge is the only world they inhabit, the culture and practice of real-life violence is more difficult to scrutinize, resist, and transform . . . (Giroux, 2015 )

For Giroux, the danger is that the normalization of violence has become a threat to democracy itself. In our culture of mass consumption shaped by neoliberal logics, depoliticized narratives of violence have become desired forms of entertainment and are presented in ways that express tolerance for some forms of violence while delegitimizing other forms of violence. In their book, Disposable Futures , Brad Evans and Henry Giroux argued that as the spectacle of violence perpetuates fear of inevitable catastrophe, it reinforces expansion of police powers, increased militarization and other forms of social control, and ultimately renders marginalized members of the populace disposable (Evans & Giroux, 2015 , p. 81).

Criminology and the “Media/Crime Nexus”

Most criminologists and sociologists who focus on media and crime are generally either dismissive of the notion that media violence directly causes violence or conclude that findings are more complex than traditional media effects models allow, preferring to focus attention on the impact of media violence on society rather than individual behavior (Carrabine, 2008 ; Ferrell, Hayward, & Young, 2015 ; Jewkes, 2015 ; Kitzinger, 2004 ; Marsh & Melville, 2014 ; Rafter, 2006 ; Sternheimer, 2003 ; Sternheimer 2013 ; Surette, 2011 ). Sociologist Karen Sternheimer forcefully declared “media culture is not the root cause of American social problems, not the Big Bad Wolf, as our ongoing public discussion would suggest” (Sternheimer, 2003 , p. 3). Sternheimer rejected the idea that media causes violence and argued that a false connection has been forged between media, popular culture, and violence. Like others critical of a singular focus on media, Sternheimer posited that overemphasis on the perceived dangers of media violence serves as a red herring that directs attention away from the actual causes of violence rooted in factors such as poverty, family violence, abuse, and economic inequalities (Sternheimer, 2003 , 2013 ). Similarly, in her Media and Crime text, Yvonne Jewkes stated that U.K. scholars tend to reject findings of a causal link because the studies are too reductionist; criminal behavior cannot be reduced to a single causal factor such as media consumption. Echoing Gauntlett’s critiques of media effects research, Jewkes stated that simplistic causal assumptions ignore “the wider context of a lifetime of meaning-making” (Jewkes, 2015 , p. 17).

Although they most often reject a “violent media cause violence” relationship, criminologists do not dismiss the notion of media as influential. To the contrary, over the decades much criminological interest has focused on the construction of social problems, the ideological implications of media, and media’s potential impact on crime policies and social control. Eamonn Carrabine noted that the focus of concern is not whether media directly causes violence but on “how the media promote damaging stereotypes of social groups, especially the young, to uphold the status quo” (Carrabine, 2008 , p. 34). Theoretically, these foci have been traced to the influence of cultural and Marxist studies. For example, criminologists frequently focus on how social anxieties and class inequalities impact our understandings of the relationship between media violence and attitudes, values, and behaviors. Influential works in the 1970s, such as Policing the Crisis: Mugging, the State, and Law and Order by Stuart Hall et al. and Stanley Cohen’s Folk Devils and Moral Panics , shifted criminological critique toward understanding media as a hegemonic force that reinforces state power and social control (Brown, 2011 ; Carrabine, 2008 ; Cohen, 2005 ; Garland, 2008 ; Hall et al., 2013 /1973, 2013/1973 ). Since that time, moral panic has become a common framework applied to public discourse around a variety of social issues including road rage, child abuse, popular music, sex panics, and drug abuse among others.

Into the 21st century , advances in technology, including increased use of social media, shifted the ways that criminologists approach the study of media effects. Scholar Sheila Brown traced how research in criminology evolved from a focus on “media and crime” to what she calls the “media/crime nexus” that recognizes that “media experience is real experience” (Brown, 2011 , p. 413). In other words, many criminologists began to reject as fallacy what social media theorist Nathan Jurgenson deemed “digital dualism,” or the notion that we have an “online” existence that is separate and distinct from our “off-line” existence. Instead, we exist simultaneously both online and offline, an

augmented reality that exists at the intersection of materiality and information, physicality and digitality, bodies and technology, atoms and bits, the off and the online. It is wrong to say “IRL” [in real life] to mean offline: Facebook is real life. (Jurgenson, 2012 )

The changing media landscape has been of particular interest to cultural criminologists. Michelle Brown recognized the omnipresence of media as significant in terms of methodological preferences and urged a move away from a focus on causality and predictability toward a more fluid approach that embraces the complex, contemporary media-saturated social reality characterized by uncertainty and instability (Brown, 2007 ).

Cultural criminologists have indeed rejected direct, causal relationships in favor of the recognition that social meanings of aggression and violence are constantly in transition, flowing through the media landscape, where “bits of information reverberate and bend back on themselves, creating a fluid porosity of meaning that defines late-modern life, and the nature of crime and media within it.” In other words, there is no linear relationship between crime and its representation. Instead, crime is viewed as inseparable from the culture in which our everyday lives are constantly re-created in loops and spirals that “amplify, distort, and define the experience of crime and criminality itself” (Ferrell, Hayward, & Young, 2015 , pp. 154–155). As an example of this shift in understanding media effects, criminologist Majid Yar proposed that we consider how the transition from being primarily consumers to primarily producers of content may serve as a motivating mechanism for criminal behavior. Here, Yar is suggesting that the proliferation of user-generated content via media technologies such as social media (i.e., the desire “to be seen” and to manage self-presentation) has a criminogenic component worthy of criminological inquiry (Yar, 2012 ). Shifting attention toward the media/crime nexus and away from traditional media effects analyses opens possibilities for a deeper understanding of the ways that media remains an integral part of our everyday lives and inseparable from our understandings of and engagement with crime and violence.

Over the years, from films to comic books to television to video games to social media, concerns over media effects have shifted along with changing technologies. While there seems to be some consensus that exposure to violent media impacts aggression, there is little evidence showing its impact on violent or criminal behavior. Nonetheless, high-profile violent crimes continue to reignite public interest in media effects, particularly with regard to copycat crimes.

At times, academic debate around media effects remains contentious and one’s academic discipline informs the study and interpretation of media effects. Criminologists and sociologists are generally reluctant to attribute violence and criminal behavior directly to exposure to violence media. They are, however, not dismissive of the impact of media on attitudes, social policies, and social control as evidenced by the myriad of studies on moral panics and other research that addresses the relationship between media, social anxieties, gender, race, and class inequalities. Scholars who study media effects are also sensitive to the historical context of the debates and ways that moral concerns shape public policies. The self-regulating codes of the film industry and the comic book industry have led scholars to be wary of hyperbole and policy overreach in response to claims of media effects. Future research will continue to explore ways that changing technologies, including increasing use of social media, will impact our understandings and perceptions of crime as well as criminal behavior.

Reactions to Media Violence: It’s in the Brain of the Beholder

* E-mail: [email protected]

Affiliations Department of Psychiatry, Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, New York, United States of America, Department of Neuroscience, Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, New York, United States of America

Affiliations Department of Psychiatry, Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, New York, United States of America, Laboratory of Neuroimaging, National Institute on Alcohol Abuse and Alcoholism, Bethesda, Maryland, United States of America

Affiliation Department of Psychiatry, Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, New York, United States of America

Affiliation Applied Mathematics and Statistics, SUNY, Stony Brook, New York, United States of America

Affiliation Laboratory of Neuroimaging, National Institute on Alcohol Abuse and Alcoholism, Bethesda, Maryland, United States of America

Affiliation Medical Department, Brookhaven National Laboratory, Upton, New York, United States of America

Nelly Alia-Klein,
Gene-Jack Wang,
Rebecca N. Preston-Campbell,
Scott J. Moeller,
Muhammad A. Parvaz,
Wei Zhu,
Millard C. Jayne,
Chris Wong,
Dardo Tomasi,

Published: September 10, 2014
https://doi.org/10.1371/journal.pone.0107260
Reader Comments

Media portraying violence is part of daily exposures. The extent to which violent media exposure impacts brain and behavior has been debated. Yet there is not enough experimental data to inform this debate. We hypothesize that reaction to violent media is critically dependent on personality/trait differences between viewers, where those with the propensity for physical assault will respond to the media differently than controls. The source of the variability, we further hypothesize, is reflected in autonomic response and brain functioning that differentiate those with aggression tendencies from others. To test this hypothesis we pre-selected a group of aggressive individuals and non-aggressive controls from the normal healthy population; we documented brain, blood-pressure, and behavioral responses during resting baseline and while the groups were watching media violence and emotional media that did not portray violence. Positron Emission Tomography was used with [ 18 F]fluoro-deoxyglucose (FDG) to image brain metabolic activity, a marker of brain function, during rest and during film viewing while blood-pressure and mood ratings were intermittently collected. Results pointed to robust resting baseline differences between groups. Aggressive individuals had lower relative glucose metabolism in the medial orbitofrontal cortex correlating with poor self-control and greater glucose metabolism in other regions of the default-mode network (DMN) where precuneus correlated with negative emotionality. These brain results were similar while watching the violent media, during which aggressive viewers reported being more Inspired and Determined and less Upset and Nervous , and also showed a progressive decline in systolic blood-pressure compared to controls. Furthermore, the blood-pressure and brain activation in orbitofrontal cortex and precuneus were differentially coupled between the groups. These results demonstrate that individual differences in trait aggression strongly couple with brain, behavioral, and autonomic reactivity to media violence which should factor into debates about the impact of media violence on the public.

Citation: Alia-Klein N, Wang G-J, Preston-Campbell RN, Moeller SJ, Parvaz MA, Zhu W, et al. (2014) Reactions to Media Violence: It’s in the Brain of the Beholder. PLoS ONE 9(9): e107260. https://doi.org/10.1371/journal.pone.0107260

Editor: Jonathan A. Coles, Glasgow University, United Kingdom

Received: May 5, 2014; Accepted: August 7, 2014; Published: September 10, 2014

This is an open-access article, free of all copyright, and may be freely reproduced, distributed, transmitted, modified, built upon, or otherwise used by anyone for any lawful purpose. The work is made available under the Creative Commons CC0 public domain dedication.

Data Availability: The authors confirm that, for approved reasons, some access restrictions apply to the data underlying the findings. All relevant brain and behavior data are provided in the supporting information files in excel format.

Funding: Funding was provided by (1) Brookhaven National Laboratory under contract DE-AC02-98CH10886, http://www.bnl.gov/world/ ; (2) National Institute of Mental Health: R01MH090134 (NAK), http://www.nimh.nih.gov/index.shtml ; and (3) National Institute of Mental Health NIDA and NIH K05DA020001 (JSF) and the National Institute of Alcohol Abuse and Alcoholism Intramural Program, http://www.drugabuse.gov/ and http://www.niaaa.nih.gov/ . The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

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

Introduction

While visual media is replete with images of violence, only a small minority in the population engages in real-life violent behavior. Critically, whether a person will act violently depends on individual trait variations which play a prominent role in how visual media is experienced and processed [1] . Therefore, understanding the neurobiological underpinnings of those with aggressive personality traits above the documented norms, is an important prerequisite to the ongoing debate about media impact on behavior [2] . Enduring trait aggression reflects self-report of retaliatory motivation, with high face validity, where individuals endorse questions regarding the degree of their readiness to hurt others. It is emerging in the literature that aggressive individuals differ from non-aggressive individuals in their baseline, trait-like, neurobiological architecture [3] , suggesting involvement of the brain’s default mode network (DMN) [4] , [5] . The DMN forms a distributed circuit of connected brain systems that shows high and coherent metabolic activity or blood flow during awake yet passive resting states which may represent internal and self-referential processing [4] – [7] . The DMN includes regions typically spanning the posterior cingulate cortex (PCC) and precuneus, lateral inferior parietal gyrus (IPG), medial temporal gyrus (MTG), and ventromedial prefrontal cortex, including the orbitofrontal cortex (OFC) [8] . We hypothesize that at resting baseline, individuals with high trait aggression will exhibit different brain metabolism patterns in the DMN including its ventromedial prefrontal regions, revealing fundamentally different internal preoccupations than those with normative trait aggression.

Stimuli with violent themes can prime, or perhaps facilitate existing trait tendencies [1] , [9] . The General Aggression Model (GAM) [10] outlines the processes by which exposure to violence can cause aggressive behavior through the interplay of enduring traits that drive internal states, coupled with congruent visual stimuli from the environment (e.g., violent media). Therefore, according to GAM, chronic exposure to violent images in the media reinforces existing aggressive traits, thereby preparing the individual towards future violence [11] , [12] . The OFC is specifically involved in elements of aggressive behaviors [13] – [15] through its role in prioritizing emotional cues according to intrinsic salience [16] . Likewise, gray matter deficits in the OFC have been observed in individuals with aggressive and violent behavior [17] . As such, we predict involvement of the OFC since it appears to be specifically involved in response to repeated media violence [18] , [19] . Individual differences in brain and behavior during visual media viewing can be further understood in the context of self-reported affective states and autonomic responses (or lack thereof) [20] , [21] . For example, self-reported distress and systolic blood pressure changes were observed in response to viewing violent media [1] , [21] . Cortical representations of emotion-dependent autonomic response (e.g., blood pressure) have been shown in the OFC, anterior cingulate, and insula in response to viewing violent media in healthy controls [22] .

To test our hypotheses regarding baseline and media viewing differences as a function of trait aggression, we recruited a group of healthy aggressive individuals with a history of assault behavior and a group of non-aggressive healthy controls. Measurements of glucose metabolism with [ 18 F]fluoro-deoxyglucose using positron emission tomography (PET) were obtained at three conditions: at resting baseline, during exposure to violent media, and during exposure to emotional, non-violent media. Blood pressure (BP) and behavioral ratings of state affect were collected intermittently during the movie presentations. We expected that aggressive individuals would have a distinct intrinsic brain activity pattern at resting baseline and during passive viewing of the violent media compared to emotional media.

Ethics Statement

This research protocol was approved by the ethical review board of Stony Brook University and conducted accordingly. All participants provided written informed consent prior to participation. Approval number BNL-381.

Participants

A total of 54 males who responded to advertisement for healthy controls and healthy individuals with history of physical fights, were evaluated for their physical assault tendencies and other inclusion/exclusion criteria. Individuals were initially screened by phone and then seen at Brookhaven National Laboratory by a physician for general exclusion criteria which included current or past psychiatric disorders (e.g., drug abuse or dependence), neurological disease, significant medical illness, current treatment with medication (including over the counter drugs) and head trauma with loss of consciousness >30 minutes. Normal physical examination and laboratory tests were required for entry and pre-scan urine tests ensured the absence of any psychoactive drugs. Individuals were classified as aggressive (Ag) or non-aggressive (Na) depending on their responses on the Physical Aggression subscale of the Buss-Perry Aggression Questionnaire (the physical aggression subscale correlates strongly with peer ratings of aggression demonstrating its concurrent validity) [23] . Of these 54 participants, only individuals who reported physical fights in the last year and scored at or higher than 75 th percentile on the Physical Aggression scale (Ag, n = 12) or those who reported they did not engage in physical fights and scored at 50 th percentile or below on the Physical Aggression scale (Na, n = 13) were chosen for the study (mean age 25.15) [23] . As planned, the participants differed on Physical Aggression (Ag, mean ± standard error 33.5±1.2; Na, 14.5±1.0, p<.0001). They also differed significantly on the other subscales of the Buss-Perry: Verbal Aggression (Ag, 18.8±1.0; Na, 11.6±1.2, p<.0001), Anger (Ag, 23.7±1.5; Na, 9.6±0.6, p<.0001), Hostility (Ag, 23.1±2.0; Na, 11.8±0.9, p<.0001) and the total score (Ag, 99.5±3.8; Na, 47.5±2.7, p<.0001). The two groups did not differ on age, handedness [24] , socio-economic status [25] , estimates of verbal and non-verbal intelligence [26] , [27] , and depression symptoms [28] . Participants were asked about their media habits including the number of hours they watched TV per day on weekdays and on weekends ( Table 1 ). The participants were monetarily compensated for their participation. It is important to note that the staff performing the media exposure, imaging, nursing, and questionnaire completion, were blind to the subject’s assignment as aggressive or non-aggressive.

PPT PowerPoint slide
PNG larger image
TIFF original image

https://doi.org/10.1371/journal.pone.0107260.t001

Personality and Behavioral Measures

In addition to the Buss-Perry Aggression Questionnaire, the Multidimensional Personality Questionnaire (MPQ) [29] , a three-factor structural model of personality was used. As listed in Table 1 , the MPQ models three higher order dimensions of personality: Negative Emotionality (NEM, or Neuroticism ) reflecting tendency toward emotional distress, alienation from others and aggressive behavior; Positive Emotionality (PEM, or extraversion) reflecting enduring positive affect through interpersonal engagement, and Constraint measuring tendencies toward self-control. Several lines of evidence have shown that high levels of NEM as Neuroticism are robustly associated with violence and aggression [30] . Similarly, individuals with elevated scores of NEM tend to experience/report more frequent negative emotions such as anger and anxiety, perceive their environment as hostile/unfair, and often exhibit poor coping mechanisms in a stressful situation [31] . The three NEM sub-scales include Stress Reaction which is linked to low frustration tolerance; Aggression which reflects the tendency to respond with retaliatory response style; and Alienation which is the most predictive primary scale of aggressive behavior. We also assessed attention and inhibitory control using a performance based measure, the Attention Network Task (ANT), that captures reaction-time performance on Alerting (response readiness), Orienting (scanning and selection), and Conflict (inhibitory control) in attention [32] .

Imaging Conditions and State Reactivity

There were three 40-minute imaging conditions: resting baseline, where participants were instructed to rest with eyes open, a video presentation of violent scenes, and a video presentation of emotional scenes not portraying violence. The two videos (violent and emotional) were edited from R-rated movies and documentary films. The violent media presentation contained 20 scenes of violent acts encompassing the depiction of intentional acts of violence from one individual to another (e.g. interpersonal, shootings, street fights). The emotional media presentation contained 19 emotionally intense and action filled but non-violent scenes (e.g. people interacting during a natural disaster, sudden failures during competitive sports). The length of each of the violent or emotional scenes was between 1–4 minutes; these scenes were separated by a black screen that appeared for 30 seconds which signaled the next scene. The level of valence and intensity of each of the violent and emotional scenes was evaluated internally in the laboratory (data not shown) for valence and intensity and sequenced to optimize with the dynamics of FDG uptake (most intense scenes during the first 10 minutes of FDG uptake period). During the movie presentations, state levels of emotional reactivity were assessed using the Positive and Negative Affective Schedule (PANAS) with adjectives of mood states (ranked from 1, slightly to 5, extremely) [33] . The PANAS was completed by the subjects 5 minutes before the media presentations, 10 minutes into the presentations, and at the end of the media presentations. Table 2 shows PANAS adjectives where differences were found between the groups at p<0.05 during the violent as compared to emotional media presentations. Systolic and diastolic BP was monitored with a compression cuff that operated automatically (Propaq Encore) on the participant’s non-dominant arm starting 5 minutes before the imaging and continued throughout the scanning sessions occurring at 5-minute intervals. For Figure 1 systolic BP data was first averaged within each group at each point in the time series during the violent and during the emotional media presentation. Then, the percentage changes in BP (delta) were calculated from the emotional to the violent media within each group [(violent-emotional)/emotional].

Ag (red) individuals show reduction in systolic blood pressure while watching the violent media versus Na (blue) individuals who show progressive increase in systolic blood pressure. Systolic blood pressure measures were averaged for each group at each time point and a percent change and a trend line were calculated (Y-axis). Error bars (joined and filled) reflect the standard deviation of the data that are presented.

https://doi.org/10.1371/journal.pone.0107260.g001

https://doi.org/10.1371/journal.pone.0107260.t002

PET Imaging

The 25 subjects were scanned 3 times with PET-FDG in counterbalanced order on separate days and under 3 conditions: resting baseline, violent scenes, non-violent emotional scenes. The scanning procedure is standardized and was described before [34] . The violent and neutral video presentations started 10 min prior to FDG injection and continued for a total of 40 min. PET imaging was conducted with a Siemens HR+ tomograph (resolution 4.5×4.5×4.5 mm 3 full-width half-maximum, 63 slices) in 3D dynamic acquisition mode. Static emission scan started 35 min after FDG injection and continued for the next 20 min. Arterialized blood was used to measure FDG in plasma. During the uptake period of FDG, subjects were resting with eyes open (no stimulation) or watching a movie (violent or emotional) in a quiet dimly lit room with a nurse by their side to ensure that they did not fall asleep. Metabolic rates were computed using an extension of Sokoloff’s model [35] . The emission data for all the scans were corrected for attenuation and reconstructed using filtered back projection.

Image and Data Analyses

Prior to the analysis, each participant’s PET image was mapped onto the Montreal Neurological Institute (MNI) template and smoothed via a Gaussian kernel with full width half maximum at 16 mm. Normalized metabolic images were analyzed using Statistical Parametric Mapping (SPM) [36] . The normalized images (relative images) were obtained by dividing the signal level of each voxel by the global mean, which was the average signal level of all voxels in the PET image. Analyses were performed in SPM8 with a flexible factor model design with one between-subject factor (Ag and Na groups) and one within-subject factor (baseline, violent, emotional conditions). Main effects of group were tested separately ( Figure 2 ) as well as group x condition interactions. The cluster threshold used was p<0.001, cluster extent >100; given the number of subjects, these parameters were chosen to ensure a minimum of t = 3.00 for each cluster reported. After the SPM results were obtained, cubic regions of interest (ROIs) with 125 voxels were centered at the peak coordinates of relevant activation clusters to compute average metabolic values within these ROIs. Pearson linear correlations were used to assess the association between average ROI measures and BP.

Left panel: Relative glucose metabolism (Y-axis) in Ag (red) and Na (blue) in response to the violent media. On the left of the dotted line are results from Ag>Na contrast and on the right of the dotted line are results from the Ag<Na contrast. Right panel: Glucose metabolism results in response to the emotional media Ag>Na. There were no significant results for Ag<Na. Standard error is presented in the corresponding error bars.

https://doi.org/10.1371/journal.pone.0107260.g002

The behavior and personality indices ( Table 1 ) were analyzed using independent-samples t-tests Bonferroni corrected for multiple comparisons [37] . The changes in BP (delta) were calculated from the emotional to the violent media within each group [(violent-emotional)/emotional] ( Figure 1 ). We tested whether the progressive change in systolic BP was significantly different between the groups with a general linear model (GLM), where time points and group were independent variables while the BP delta was the dependent variable. Two separate linear regression models were fitted within each group and used to test whether the delta in BP changed significantly over time and whether the slopes were significantly different between the groups. Analysis of PANAS responses to the violent and emotional media presentations was done by calculating differences in responses between violent and emotional presentations at 3 time points (pre, 10 min and end) using a GLM ( Table 2 ).

Traits, Inhibitory Control, and Resting Metabolism

As documented in Table 1 , the groups were not different on demographics and media exposure and no differences were found on MPQ personality traits of PEM which includes the subscales Well Being , Social Potency , Social Closeness and Achievement . Not surprisingly, the groups were substantially different on Negative Emotionality and inhibitory control. Individuals from the Ag group, reported more NEM, with high scores on the NEM subscales, Alienation , Aggression and Stress Reaction . The Ag group also demonstrated poor inhibitory control, reporting less self- Control on the MPQ and also showed increased latency to respond specifically in the Conflict condition of the ANT. This performance measure of inhibitory control correlated with self-reported aggression such that more latency as a result of conflict in attention was seen in those with more trait aggression as measured by two different self-report scales (Buss-Perry Physical Aggression scale r = .76, P<0.0001, and MPQ Aggression (r = .66, P<0.001).

The normalized brain metabolic measures were characterized by robust group effects at resting baseline, involving hyperactivity in the DMN and caudate, and dampened OFC metabolism in Ag as compared to Na ( Table 2 ). These resting metabolic measures in precuneus correlated positively across participants with NEM (R = .56, p<.01) and negatively with Control (R = −.46, 0<.05) whereas those in OFC showed the opposite pattern revealing a negative correlation with NEM (R = −.40, p<.05) and positive correlation with Control (R = .48, p<.05).

Glucose Metabolism and Mood Reactivity during Media Viewing

Listed in Table 2 are the main effects of group for each condition separately. These results show similar group differences at resting baseline than for the comparisons during violent media presentation, involving hyperactivity in the DMN and caudate, and dampened OFC metabolism in Ag than Na participants ( Figure 2, left panel ). While viewing the emotional media presentation, the only significant difference between groups was higher glucose metabolism in bilateral lingual gyrus in the Ag group ( Figure 2, right panel ). Group x condition interactions were not significant at our threshold or at a reduced threshold of p<0.005.

As documented in Table 3 , differences emerged between the groups in state reactivity 10 minutes into and at the end of the media presentations. During the violent media presentation as compared to the emotional media presentation, Ag participants when compared with the Na participants reported feeling less Upset ( Figure 3 ) and Nervous and more Inspired and Determined ( Table 3 ). In-line with the mood reactivity data, there were divergent responses between the groups in systolic BP across time. In the Na group, percent BP change progressively increased over time (t 16 = 3.26, p = 0.002) while in the Ag group, systolic BP progressively decreased (t 16 = −4.23, p = 0.0003) in response to the violent media as compared to emotional media ( Figure 1 ). A comparison of the trend lines between the groups shows that the trend lines were significantly opposite (F 1, 32 = 27.60, p<0.0001). Systolic and diastolic BP did not differ between the groups at resting baseline (p>0.05). Diastolic BP was not different between the groups in any of the conditions.

Self-report of being Upset immediately before, during, and at the end (EOV) of the violent media viewing. Standard error is presented in the corresponding error bars.

https://doi.org/10.1371/journal.pone.0107260.g003

https://doi.org/10.1371/journal.pone.0107260.t003

To examine the coupling of BP with glucose metabolism between the groups, we conducted ROI analyses to assess the correlation between regional metabolism during the violent media exposure and changes in systolic BP at time 37 (when most accentuated differences in BP were found between groups, as shown in Figure 1 ). In the Na, increases in BP were positively associated with increased metabolism in the right OFC (x = 22, y = 34, z = −26; r = 0.74; p<0.005) whereas the correlation was negative in (r = −0.56, p<0.005) ( Figure 4 ) in whom decreases in BP were also associated with metabolism in precuneus (R = −.81, p<.001). That is, in Na participants increases in BP were associated with higher metabolism in OFC whereas in Ag participants decreases in BP were associated with increased metabolism in the OFC and precuneus.

On the y-axis is response in the OFC response to violent media compared with emotional media; on the x-axis is systolic BP change between violent media compared with emotional media at time 37 into the media viewing.

https://doi.org/10.1371/journal.pone.0107260.g004

This study documented brain, behavior, and blood-pressure response as a function of trait aggression. Results showed that Ag had heightened traits of NEM and poor inhibitory control compared to Na. These constitutional differences between the groups were apparent in their brain function at resting baseline and during the violent media viewing, where Ag had higher relative metabolism in the retrosplenial DMN, and lower relative metabolism in OFC, gyrus rectus, and posterior cerebellum. While watching the violent compared to emotional media, the Ag viewers reported being more Inspired and Determined, less Upset and Nervous, and showed a progressive decline in systolic blood-pressure compared with controls in whom systolic BP increased. Furthermore, the BP findings were differentially coupled with glucose metabolism between the groups. While viewing violent media, increased blood-pressure in Na was associated with increased metabolism in OFC; in Ag, the observed reduced blood-pressure was associated with increased metabolism in this same region and also in the precuneus.

The Value of Pre-Selection Based on Abnormal Aggression Traits

In pre-selecting participants based on trait aggression this study revealed important baseline differences in brain and behavior compared with controls. Elevated trait aggression is found specifically in individuals with associated disorders, such as antisocial personality disorder and intermittent explosive disorder, as it has straightforward face validity [38] . In addition to elevated trait aggression, Ag also reported more Alienation and Stress Reaction and demonstrated poor inhibitory control, as measured by the ANT conflict [39] , which are part of externalizing behaviors in adults [40] . Studies show that inhibitory control (as documented here using the ANT) play an important role in violent media effects and aggression [41] . Similarly, high levels of NEM as Neuroticism have shown robust connections with violence and aggression [30] . These results on characterizing personality in trait aggression, lend support to the GAM theory, documenting the specificity of trait aggression in its effects on other personality traits [42] and their potential cognitive substrates. Those who endorse few or no aggression items, hence, the Na group, scored at the norms in NEM and PEM, demonstrating that it is normative to endorse very few aggression questions, providing an adequate control for Ag. Importantly, PEM and its subscales were comparable between the groups, perhaps validating a characterization of trait aggression specifically involving NEM while having normative PEM [42] . Supportive of the GAM theory on the role of traits in media viewing, these trait results are important in setting the context of brain metabolism comparisons between the groups.

Characterization of Trait Aggression through Resting Brain Metabolism

The most robust finding in this study is relative hyperactivity of the DMN during resting baseline with relative hypoactivity of the OFC and cerebellum in Ag compared to Na. The documented over-activity in components of the DMN may reflect a neural marker of enduring traits fostering inwardly directed attention to self-referential information stemming from years of social and cognitive learning [43] . Each of the DMN nodes and their network is associated with awareness and conscious information processing [44] , mental imagery, perspective taking, and autobiographical memory retrieval [45] – [47] needed to facilitate an enduring brain activity pattern of behavioral patterns (i.e., trait) [48] , [49] . Several studies mapped DMN regions with trait profiles; for example, Neuroticism (NEM in this study), was associated with lower volumetric measures and lower metabolism of the OFC [50] , [51] in line with our results of hypoactive OFC in Ag. Conducting direct correlations between resting metabolism and NEM as well as with trait Control , we found that the lower resting metabolism in the OFC the higher were NEM and lower Control scores. In contrast the higher resting metabolism in precuneus the higher was NEM and lower Control trait scores. Supporting this finding are recent findings of higher precuneus with reduced conscientiousness and openness [49] both associated with NEM and characteristic of those with high trait aggression.

Other over activated regions at baseline among Ag participants included the sensory motor area and caudate. One could speculate that this increased activity during rest would have a role in compromised responses during a cognitive task. A recent study proposed that striatal dopamine circuits, particularly the caudate, may provide a mechanism for the active suppression of the DMN under conditions that require increased processing of external stimuli (e.g., an attention demanding cognitive task) relative to internal, self-directed processing [52] . This might be related to a recent finding where heightened trait aggression is associated with reduced dopamine in striatum [53] and that striatal dopamine influences the DMN to affect shifting between internal states and cognitive demands [54] .

Brain Metabolism during Violent Media Viewing

The fusiform gyrus was uniquely activated during violent media viewing in Ag, perhaps suggesting increased attention to facial representation of socially relevant cues [55] . Aside from the fusiform activation, while viewing the violent media presentation, the Ag participants compared with the Na showed similar patterns of activation as they had during resting baseline. As such, it appears that DMN regions are active during passive viewing of visual stimuli (e.g., movie) [56] , [57] . We postulate that the violent media condition reflects congruence between the trait and the visual stimuli, such that the stimuli are syntonic (oscillating together) with internal processing, perhaps indicating personal experience with this material. Since resting baseline refers to mind wondering, it could be that participants in the Ag group have had aggressive thoughts that were instigating similar brain networks as during violent media viewing. A study in children during exposure to violent media documented engagement of the posterior cingulate and hippocampi, which was postulated to link memory and emotion to motor activation integrating existing aggression-related thoughts, thereby making them strongly accessible scripts over time [58] . The amygdala is a likely target for cortical arousal in violence viewing. Mathiak and Weber (2006) documented amygdala activation during active game-play in fMRI environment [59] . Their activation pattern showed signal decrease in the amygdala during players’ virtual violent behavior. Our study did not document amygdala responses possibly as a result of the passive nature of the viewing violent media or alternatively, amygdala was not documented because of the temporal resolution differences between PET and fMRI.

Hypoactivity of the Orbitofrontal Cortex

In our study, the Ag participants showed a pattern of reduced OFC activity relative to the Na in the both resting baseline and violent media conditions. The OFC plays a role in externalizing/impulsive behavior, and regulating emotional and social behavior [13] , [60] – [64] . Specific damage to the OFC is associated with impulsive and aggressive behavior [64] , and individuals with such damage show little control over their emotions as well as limited awareness of the moral implications of their actions, and poor decision making [65] . Impulsive aggressive personality disordered patients demonstrate impaired emotion regulation, and exhibit blunted prefrontal, including OFC, metabolism in response to a serotonergic challenge [66] . Deficits in the orbitofrontal lobes as represented by atrophy, lesion, or hypoactive metabolism have been observed across a number of psychiatric populations prone to aggression (e.g., antisocial personality disorder, psychopathy, borderline personality disorder, intermittent explosive disorder) [66] – [68] and suggest that OFC hypo-function may be a common mechanism underlying the pathophysiology of aggressive behavior in general (e.g., both impulsive and premeditated forms). Hypoactivity of the OFC in this study and its correlation with high NEM and low Control scores further support the reliable implication of OFC in the externalizing continuum.

This OFC hypoactivity is consistent with other studies where exposure to violent media is associated with decreased OFC activation. In a study that examined components of the fronto-parietal network in response to aggressive video cues, reduced levels of OFC activation were found [19] . It is possible that OFC hypoactivation reflects desensitization to violence and disrupts the process of moral evaluation of the violent visual stimuli [69] .

Familiarity with violent material could breed desensitization [69] – [71] . It could be that Ag have exhibited reduced inhibition and blunted evaluative categorization of violent stimuli as supported in other studies [71] such that they demonstrate a response (physiological/behavioral/cortical) that is suggestive of an overall desensitization to media violence [72] , [73] .

Under-reactive Emotional and Autonomic Response to Violent Media

There is further evidence in this study supporting the desensitization hypothesis. The Ag group reported being less Nervous and Upset and more Inspired and Determined during the media violence (compared with emotional media) while their systolic BP progressively decreased. In stark contrast, The Na mood and BP responses to the violent media may be associated with a threat evaluation producing sympathetic activation, resulting in BP increase in the Na group. In a study with healthy adolescents, participants viewing violent movie clips experienced increased BP compared to baseline; however, prior exposure to violence was associated with lowered BP [21] . Autonomic under-arousal to threat stimuli has been documented in individuals who exhibit low levels of fear [74] . Angered subjects permitted to commit aggression against the person who had annoyed them often display a drop in systolic blood pressure. They seem to have experienced a physiological relaxation, as if they had satisfied their aggressive urges [75] , [76] .

Indeed, the documented pattern of BP under-reactivity in Ag was associated with hypoactivations in the OFC ( Figure 3 ) and hyperactivation of the precuneus. Behaviorally-evoked changes in cardiovascular (e.g., blood pressure, heart rate) and cardiac-autonomic (e.g., heart rate variability) activity are correlated directly with neural activity within areas of the anterior cingulate cortex, OFC, medial prefrontal cortices, and the amygdala and often in interaction with activity in the insula, and relay regions of the thalamus and brainstem [22] , [77] , [78] . Based on neuroimaging and lesion evidence, a neurobiological model of cardiovascular reactivity shows that physiological and behavioral reactions are instantiated in the corticolimbic brains systems (e.g., medial/prefrontal corticies, insula, and amygdala) [79] . Afferent feedback, appraised by the OFC is integral in generation of somatic markers which trigger an emotional response, subsequently biasing overt behavior [80] . It is important to note here, that these results are relative to responses to emotional media viewing. It appears from our results that non-violent, yet emotionally salient action stimuli increase BP in the Ag individuals, whereas violent stimuli have the opposite effect of decreasing BP in these individuals. The specificity of hypo-response to violent content supports our assertion that the effects of violent media on individuals depend on theme-related traits, in this case aggression, and the brain of the beholder.

There are several limitations in this study that constrain our interpretation power and generalizability. First, there may have been too few participants in the study to ascertain group by condition interactions and to conduct correlations between trait and brain measures. Second, the inclusion of males only in this study was done to control for potentially differential emotional reaction patterns of activation as a function of sex. However, this approach prevents us from making any claims about female response to violent media. Future studies must include females. Third, the experimental design did not include an acute test of aggression following the media condition. Future studies could include such a test to document aggressive responses following violent media as a function of brain response during the violent media. Fourth, there are brain activity results during violent video games finding anterior cingulate involvement [59] , [81] . These results may not be comparable to this study since playing video games requires task-dependent active attention compared to passive attention maintained during movie viewing as we show in our results; therefore more studies are needed to distinguish responses to media sources requiring active attention such as video games from those requiring only passive attention as movie scenes [82] .

Acknowledgments

The authors gratefully acknowledge the contributions of all members of the Brookhaven PET team for advice and assistance in different aspects of this study.

Author Contributions

Conceived and designed the experiments: NAK NDV RZG JSF GJW. Performed the experiments: NAK MCJ CW DT. Analyzed the data: NAK MAP WZ CW. Contributed reagents/materials/analysis tools: WZ CW DT. Contributed to the writing of the manuscript: NAK SJM RPC RZG NDV MAP.

View Article
Google Scholar
25. Hollingshead AB (1975) Four-factor index of social status. Unpublished paper.
26. Wilkinson G (1993) The Wide-Range Achievement Test 3: Administration Manual. Wilminton, DE: Wide-Range Inc.
27. Wechsler D (1999) Wechsler abbreviated scale of intelligence: San Antonio, TX: Psychological Corporation.
28. Beck AT, Steer RA, Brown GK. (1996) Beck Depression Inventory Manual. 2nd ed. San Antonio, TX: The Psychological Corporation.
29. Tellegen A, Waller NG (1997) Exploring personality through test construction: development of the multidimensional personality questionnaire. In: Briggs SR, Cheek JM, editors. Personality measures: development and evaluation. Greenwich: JAI Press.
30. Blonigen DM, Krueger RF. (2007) Personaity & Violence: The unifying role of structural models of personality. In: Flannery DJ VA, Waldman ID (Eds.), editor. The Cambridge handbook of violent behavior. New York, NY: Cambridge University Press.
37. Stevens J (1992) Applied multivariate statistics for the social sciences. 2nd ed. Lawrence Erlbaum Associates: NewJersey.
41. Swing EL, Anderson CA (2014) The role of attention problems and impulsiveness in media violence effects on aggression. Aggress Behav.
49. Sampaio A, Soares JM, Coutinho J, Sousa N, Goncalves OF (2013) The Big Five default brain: functional evidence. Brain Struct Funct.
69. Funk JB (2005) Children’s exposure to violent video games and desensitization to violence. Child Adolesc Psychiatr Clin N Am 14: 387–404, vii–viii.
70. Huesmann LR, Kriwil L (2007) Why observing violence increases the risk of violent behavior in the observer; (Ed.) DF, editor. Cambridge, UK: Cambridge University Press.
74. Raine A (1996) Autonomic nervous system factors underlying disinhibited antisocial and violent behavior. Annals New York Academy of Sciences: 46–60.
79. Gianaros PJ, Sheu L (2009) A review of neuroimaging studies of stressor-evoked blood pressure reactivity: Emerging evidence for a brain-body pathway to coronary heart disease risk. NeuoImage 47.
80. Damasio A (1994) Descartes’ Error: Emotion, Reason, and the Human Brain. New York: HarperCollins.

An official website of the United States government

The .gov means it’s official. Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

The site is secure. The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Publications
Account settings
My Bibliography
Collections
Citation manager

Save citation to file

Email citation, add to collections.

Create a new collection
Add to an existing collection

Add to My Bibliography

Your saved search, create a file for external citation management software, your rss feed.

Search in PubMed
Search in NLM Catalog
Add to Search

The role of media violence in violent behavior

Affiliation.

1 Institute for Social Research, University of Michigan, Ann Arbor, Michigan 48106-1248, USA. [email protected]
PMID: 16533123
DOI: 10.1146/annurev.publhealth.26.021304.144640

Media violence poses a threat to public health inasmuch as it leads to an increase in real-world violence and aggression. Research shows that fictional television and film violence contribute to both a short-term and a long-term increase in aggression and violence in young viewers. Television news violence also contributes to increased violence, principally in the form of imitative suicides and acts of aggression. Video games are clearly capable of producing an increase in aggression and violence in the short term, although no long-term longitudinal studies capable of demonstrating long-term effects have been conducted. The relationship between media violence and real-world violence and aggression is moderated by the nature of the media content and characteristics of and social influences on the individual exposed to that content. Still, the average overall size of the effect is large enough to place it in the category of known threats to public health.

PubMed Disclaimer

Publication types

Search in MeSH

Related information

Linkout - more resources, full text sources.

Ingenta plc
Citation Manager

NCBI Literature Resources

MeSH PMC Bookshelf Disclaimer

The PubMed wordmark and PubMed logo are registered trademarks of the U.S. Department of Health and Human Services (HHS). Unauthorized use of these marks is strictly prohibited.

A-Z Publications

Annual Review of Public Health

Volume 27, 2006, review article, the role of media violence in violent behavior.

L. Rowell Huesmann 1 , and Laramie D. Taylor 1
View Affiliations Hide Affiliations Affiliations: 1 Institute for Social Research, University of Michigan, Ann Arbor, Michigan 48106-1248; email: [email protected] 2 Communication Department, University of California, Davis, California 95616; email: [email protected]
Vol. 27:393-415 (Volume publication date April 2006) https://doi.org/10.1146/annurev.publhealth.26.021304.144640
© Annual Reviews

Article metrics loading...

Full text loading...

Literature Cited

Abelson RP . 1985 . A variance explanation paradox: when a little is a lot. Psychol. Bull. 97 : 129– 33 [Google Scholar]
Alvarez MM , Huston AC , Wright JC . 1988 . Gender differences in visual attention to television form and content. J . Appl. Dev. Psychol. 9 :( 4 ) 459– 75 [Google Scholar]
Anderson CA . 1997 . Effects of violent movies and trait irritability on hostile feelings and aggressive thoughts. Aggress. Behav. 23 : 161– 78 [Google Scholar]
Anderson CA , Bushman BJ . 2001 . Effects of violent video games on aggressive behavior, aggressive cognition, aggressive affect, physiological arousal, and prosocial behavior: a meta-analytic review of the scientific literature. Psychol. Sci. 12 : 353– 59 [Google Scholar]
Anderson CA , Bushman BJ . 2002 . Human aggression. Annu. Rev. Psychol. 53 : 27– 51 [Google Scholar]
Anderson CA , Carnagey NL , Flanagan M , Benjamin AJ , Eubanks J , Valentine JC . 2004 . Violent video games: specific effects of violent content on aggressive thoughts and behavior. In Advances in Experimental Social Psychology ed. M Zanna New York: Academic [Google Scholar]
Anderson CA , Dill KE . 2000 . Video games and aggressive thoughts, feelings, and behavior in the laboratory and in life. J. Pers. Soc. Psychol. 78 : 772– 90 [Google Scholar]
Anderson CA , Huesmann LR . 2003 . Human aggression: a social-cognitive view. In Handbook of Social Psychology ed. MA Hogg, J Cooper pp. 296– 323 London: Sage [Google Scholar]
Atkin C . 1983 . Effects of realistic TV violence vs. fictional violence on aggression. Journal. Q. 60 : 615– 21 [Google Scholar]
Bandura A . 1977 . Social Learning Theory Englewood Cliffs, NJ: Prentice-Hall [Google Scholar]
Bandura A . 1986 . Social Foundations of Thought and Action: A Social Cognitive Theory Upper Saddle River, NJ: Prentice-Hall [Google Scholar]
Bandura A . 1994 . Social cognitive theory of mass communication. In Media Effects: Advances in Theory and Research ed. J Bryant, D Zillmann pp. 61– 90 Hillsdale, NJ: Erlbaum [Google Scholar]
Bandura A , Ross D , Ross SA . 1963 . A comparative test of the status envy, social power, and secondary reinforcement theories of identificatory learning. J. Abnorm. Soc. Psychol. 67 : 527– 34 [Google Scholar]
Bandura A , Ross D , Ross SA . 1963 . Imitation of film-mediated aggressive models. J. Abnorm. Soc. Psychol. 67 : 3– 11 [Google Scholar]
Bandura A , Ross D , Ross SA . 1963 . Vicarious reinforcement and imitative learning. J. Abnorm. Soc. Psychol. 67 : 601– 7 [Google Scholar]
Bartholow BD , Anderson CA . 2002 . Effects of violent video games on aggressive behavior: Potential sex differences. J. Exp. Soc. Psychol. 38 : 283– 90 [Google Scholar]
Berkowitz L . 1965 . Some aspects of observed aggression. J. Pers. Soc. Psychol. 2 : 359– 69 [Google Scholar]
Berkowitz L . 1993 . Aggression: Its Causes, Consequences, and Control New York: McGraw-Hill [Google Scholar]
Berkowitz L , Alioto JT . 1973 . The meaning of an observed event as a determinant of its aggressive consequences. J. Pers. Soc. Psychol. 28 : 206– 17 [Google Scholar]
Berkowitz L , Geen RG . 1967 . Stimulus qualities of the target of aggression: a further study. J. Pers. Soc. Psychol. 5 : 364– 68 [Google Scholar]
Berkowitz L , LePage A . 1967 . Weapons as aggression-eliciting stimuli. J. Pers. Soc. Psychol. 7 : 202– 7 [Google Scholar]
Berkowitz L , Macaulay J . 1971 . The contagion of criminal violence. Sociometry 34 : 238– 60 [Google Scholar]
Berkowitz L , Powers PC . 1979 . Effects of timing and justification of witnessed aggression on the observers' punitiveness. J. Res. Pers. 13 : 71– 80 [Google Scholar]
Bjorkqvist K . 1985 . Violent Films, Anxiety, and Aggression Helsinki: Finn. Soc. Sci. Lett. [Google Scholar]
Bryant J , Zillmann D . 1979 . Effect of intensification of annoyance through unrelated residual excitation on substantially delayed hostile behavior. J. Exp. Soc. Psychol. 15 :( 5 ) 470– 80 [Google Scholar]
Bushman BJ . 1995 . Moderating role of trait aggressiveness in the effects of violent media on aggression. J. Pers. Soc. Psychol. 69 : 950– 60 [Google Scholar]
Bushman BJ , Geen RG . 1990 . Role of cognitive-emotional mediators and individual differences in the effects of media violence on aggression. J. Pers. Soc. Psychol. 58 : 156– 63 [Google Scholar]
Bushman BJ , Huesmann LR . 2001 . Effects of televised violence on aggression. In Handbook of Children and the Media ed. D Singer, J Singer pp. 223– 54 Thousand Oaks, CA: Sage [Google Scholar]
Butterworth G . 1999 . Neonatal imitation: existence, mechanisms and motives. In Imitation in Infancy ed. J Nadel, G Butterworth pp. 63– 88 New York: Cambridge Univ. Press [Google Scholar]
Calvert SL , Tan S . 1994 . Impact of virtual reality on young adults' physiological arousal and aggressive thoughts: interaction versus observation. J. Appl. Dev. Psychol. 15 : 125– 39 [Google Scholar]
Cantor J . 1994 . Confronting children's fright responses to mass media. In Media, Children, and the Family: Social Scientific, Psychodynamic, and Clinical Perspectives ed. D Zillmann, J Bryant pp. 139– 50 Hillsdale, NJ: Erlbaum [Google Scholar]
Cantor J . 2002 . Fright reactions to mass media. In Media Effects: Advances in Theory and Research ed. J Bryant, D Zillmann pp. 287– 306 Mahwah, NJ: Erlbaum, 2nd ed.. [Google Scholar]
Cline VB , Croft RG , Courrier S . 1973 . Desensitization of children to television violence. J. Pers. Soc. Psychol. 27 :( 3 ) 360– 65 [Google Scholar]
Comstock G , Paik H . 1991 . Television and the American Child San Diego, CA: Academic [Google Scholar]
Dodge KA . 1980 . Social cognition and children's aggressive behavior. Child Dev. 51 :( 1 ) 162– 70 [Google Scholar]
Dodge KA . 1985 . Attributional bias in aggressive children. In Advances in Cognitive-Behavioral Research and Therapy ed. PC Kendall 4 73– 110 San Diego, CA: Academic [Google Scholar]
Dodge KA , Pettit GS , Bates JE , Valente E . 1995 . Social information-processing patterns partially mediate the effect of early physical abuse on later conduct problems. J. Abnorm. Psychol. 104 :( 4 ) 632– 43 [Google Scholar]
Dorr A , Kovaric P . 1980 . Some of the people some of the time—but which people? Televised violence and its effects. In Children and the Faces of Television ed. EL Palmer, A Dorr pp. 183– 99 New York: Academic [Google Scholar]
Eron LD , Huesmann LR , Lefkowitz MM , Walder LO . 1972 . Does television violence cause aggression. Am. Psychol. 27 : 253– 63 [Google Scholar]
Fenigstein A . 1979 . Does aggression cause a preference for viewing media violence. J. Pers. Soc. Psychol. 37 : 2307– 17 [Google Scholar]
Feshbach S . 1972 . Reality and fantasy in filmed violence. In Television and Social Behavior: A Technical Report to the Surgeon General's Scientific Advisory Committee on Television and Social Behavior: Vol. 3. Television and Adolescent Aggressiveness ed. GA Comstock, EA Rubinstein pp. 318–45. DHEW Publ. No. HSM 72–9058 Washington, DC: U.S. Gov. Print. Off. [Google Scholar]
Friedrich LK , Stein AH . 1973 . Aggressive and prosocial television programs and the natural behavior of preschool children. Monogr. Soc. Res. Child 38 :( 4 ) 1– 63 [Google Scholar]
Geen RG , O'Neal EC . 1969 . Activation of cue-elicited aggression by general arousal. J. Pers. Soc. Psychol. 11 :( 3 ) 289– 92 [Google Scholar]
Geen RG , Stonner R . 1973 . Context effects in observed violence. J. Pers. Soc. Psychol. 25 : 145– 50 [Google Scholar]
Gentile DA , Lynch PL , Linder JR , Walsh DA . 2004 . The effects of violent video game habits on adolescent hostility, aggressive behaviors, and school performance. J. Adolesc. 27 :( 1 ) 5– 22 [Google Scholar]
Gerbner G , Gross L , Morgan M , Signorielli N . 1994 . Growing up with television: the cultivation perspective. See Ref. 12 pp. 17– 41
Guerra NG , Huesmann LR , Hanish L . 1995 . The role of normative beliefs in children's social behavior. In Social Development ed. N Eisenberg pp. 140– 58 Thousand Oaks, CA: Sage [Google Scholar]
Guerra NG , Huesmann LR , Spindler AJ . 2003 . Community violence exposure, social cognition, and aggression among urban elementary-school children. Child Dev. 74 :( 5 ) 1561– 76 [Google Scholar]
Guerra NG , Huesmann LR , Tolan PH , VanAcker R , Eron L . 1995 . Stressful events and individual beliefs as correlates of economic disadvantage and aggression among urban children. J. Consult. Clin. Psychol. 63 :( 4 ) 518– 28 [Google Scholar]
Gunter B . 1983 . Do aggressive people prefer violent television. Bull. Br. Psychol. Soc. 36 : 166– 68 [Google Scholar]
Haninger K , Thompson KM . 2004 . Content and ratings of teen-rated video games. JAMA 291 :( 7 ) 856– 65 [Google Scholar]
Hansen CH , Hansen RD . 1990 . Rock music videos and antisocial behavior. Basic Appl . Soc. Psychol. 11 :( 4 ) 357– 69 [Google Scholar]
Hapkiewicz WG , Stone RD . 1974 . The effect of realistic versus imaginary aggressive models on children's interpersonal play. Child Study J. 4 :( 2 ) 47– 58 [Google Scholar]
Harrison K , Cantor J . 1999 . Tales from the screen: enduring fright reactions to scary media. Media Psychol. 1 :( 2 ) 97– 116 [Google Scholar]
Huesmann LR . 1988 . An information processing model for the development of aggression. Aggress. Behav. 14 : 13– 24 [Google Scholar]
Huesmann LR . 1998 . The role of social information processing and cognitive schema in the acquisition and maintenance of habitual aggressive behavior. In Human Aggression: Theories, Research, and Implications for Social Policy ed. RG Geen, E Donnerstein pp. 73– 109 New York: Academic [Google Scholar]
Huesmann LR , Eron LD . eds. 1986 . Television and the Aggressive Child: A Cross-National Comparison Hillsdale, NJ: Erlbaum [Google Scholar]
Huesmann LR , Eron LD , Dubow EF . 2003 . Childhood predictors of adult criminality: Are all risk factors reflected in childhood aggressiveness. Crim. Behav. Mental Health 12 : 185– 208 [Google Scholar]
Huesmann LR , Guerra NG . 1997 . Children's normative beliefs about aggression and aggressive behavior. J. Pers. Soc. Psychol. 72 :( 2 ) 408– 19 [Google Scholar]
Huesmann LR , Lagerspetz K , Eron LD . 1984 . Intervening variables in the TV violence-aggression relation: evidence from two countries. Dev. Psychol. 20 : 746– 75 [Google Scholar]
Huesmann LR , Miller LS . 1994 . Long-term effects of repeated exposure to media violence in childhood. In Aggressive Behavior: Current Perspectives ed. LR Huesmann pp. 153– 83 New York: Plenum [Google Scholar]
Huesmann LR , Moise JF , Podolski CL . 1997 . The effects of media violence on the development of antisocial behavior. In Handbook of Antisocial Behavior ed. DM Stoff, J Breiling, JD Maser pp. 181– 93 New York: Wiley [Google Scholar]
Huesmann LR , Moise-Titus J , Podolski CL , Eron LD . 2003 . Longitudinal relations between children's exposure to TV violence and their aggressive and violent behavior in young adulthood: 1977–1992. Dev. Psychol. 39 : 201– 21 [Google Scholar]
Huesmann LR , Taylor LD . 2003 . The case against the case against media violence. In Media Violence and Children ed. DA Gentile pp. 107– 30 Westport, CT: Praeger [Google Scholar]
Ihori N , Sakamoto A , Kobayashi K , Kimura F . 2003 . Does video game use grow children's aggressiveness? Results from a panel study. In Social Contributions and Responsibilities of Simulation and Gaming ed. K Arai pp. 221– 30 Tokyo: Jap. Assoc. Simul. Gaming [Google Scholar]
Irwin AR , Gross AM . 1995 . Cognitive tempo, violent video games, and aggressive behavior in young boys. J. Family Violence 10 : 337– 50 [Google Scholar]
Johnson JD , Adams MS , Ashburn L , Reed W . 1995 . Differential gender effects of exposure to rap music on African American adolescents' acceptance of teen dating violence. Sex Roles 33 : 597– 605 [Google Scholar]
Johnson JD , Jackson LA , Gatto L . 1995 . Violent attitudes and deferred academic aspirations: deleterious effects of exposure to rap music. Basic Appl. Soc. Psychol. 16 :( 1–2 ) 27– 41 [Google Scholar]
Johnson JG , Cohen P , Smailes EM , Kasen S , Brook JS . 2002 . Television viewing and aggressive behavior during adolescence and adulthood. Science 295 : 2468– 71 [Google Scholar]
Josephson WL . 1987 . Television violence and children's aggression: testing the priming, social script, and disinhibition predictions. J. Pers. Soc. Psychol. 53 : 882– 90 [Google Scholar]
Kirsh SJ . 1998 . Seeing the world through Mortal Kombat-colored glasses: violent video games and the development of a short-term hostile attribution bias. Childhood 5 : 177– 84 [Google Scholar]
Kirwil L , Huesmann LR . 2003 . The relation between aggressiveness and emotional reactions to observed violence Presented at Annu. Meet. Midwest. Psych. Assoc., Chicago [Google Scholar]
Lando HA , Donnerstein EI . 1978 . The effects of a model's success or failure on subsequent aggressive behavior. J. Res. Pers. 12 : 225– 34 [Google Scholar]
Leyens JP , Picus S . 1973 . Identification with the winner of a fight and name mediation: their differential effects upon subsequent aggressive behavior. Br. J. Soc. Clin. Psychol. 12 : 374– 77 [Google Scholar]
Lord CG , Ross L , Lepper MR . 1979 . Biased assimilation and attitude polarization: the effects of prior theories on subsequently considered evidence. J. Pers. Soc. Psychol. 37 :( 11 ) 2098– 109 [Google Scholar]
Malamuth NM , Check JVP . 1983 . Sexual arousal to rape depictions: individual differences. J. Abnorm. Psychol. 92 :( 1 ) 55– 67 [Google Scholar]
Malamuth NM , Check JVP . 1985 . The effects of aggressive pornography on beliefs in rape myths: individual differences. J. Res. Personal. 19 : 299– 320 [Google Scholar]
Meltzoff AN , Moore MK . 2000 . Imitation of facial and manual gestures by human neonates: resolving the debate about early imitation. In Infant Development: The Essential Readings ed. D Muir, A Slater pp. 167– 81 Malden, MA: Blackwell [Google Scholar]
Milavsky JR , Kessler R , Stipp H , Rubens WS . 1982 . Television and aggression: results of a panel study. In Television and Behavior: Ten Years of Scientific Progress and Implications for the Eighties: Vol. 2. Technical Reviews ed. D Pearl, L Bouthilet, J Lazar pp. 138– 57 DHHS Publ. No. ADM 82–1196 Washington, DC: U.S. Gov. Print. Off. [Google Scholar]
Moffitt TE , Caspi A , Harrington H , Milne BJ . 2002 . Males on the life-course-persistent and adolescence-limited antisocial pathways: follow-up at age 26 years. Dev. Psychopathol. 14 :( 1 ) 179– 207 [Google Scholar]
Moise-Titus J . 1999 . The role of negative emotions in the media violence-aggression relation Unpubl. PhD diss., Univ. Mich. [Google Scholar]
Nathanson AI . 1999 . Identifying and explaining the relationship between parental mediation and children's aggression. Commun. Res. 26 : 124– 43 [Google Scholar]
Neely JJ , Hechel RV , Leichtman HM . 1973 . The effect of race of model and response consequences to the model on imitation in children. J. Soc. Psychol. 89 : 225– 31 [Google Scholar]
O'Neal EC , Taylor SL . 1989 . Status of the provoker, opportunity to retaliate, and interest in video violence. Aggress. Behav. 15 : 171– 80 [Google Scholar]
Paik H , Comstock G . 1994 . The effects of television violence on antisocial behavior: a meta-analysis. Commun. Res. 21 : 516– 46 [Google Scholar]
Peterson DL , Pfost KS . 1989 . Influence of rock videos on attitudes of violence against women. Psychol. Rep. 64 : 319– 22 [Google Scholar]
Phillips DP . 1979 . Suicide, motor vehicle fatalities, and the mass media: evidence toward a theory of suggestion. Am. J. Sociol. 84 : 1150– 74 [Google Scholar]
Phillips DP . 1982 . The impact of fictional television stories on U.S. adult fatalities: new evidence on the effect of the mass media on violence. Am. J. Sociol. 87 : 1340– 59 [Google Scholar]
Phillips DP . 1983 . The impact of mass media violence on U.S. homicides. Am. Sociol. Rev. 48 : 560– 68 [Google Scholar]
Potts R , Huston AC , Wright JC . 1986 . The effects of television form and violent content on boys' attention and social behavior. J. Exp. Child Psychol. 41 : 1– 17 [Google Scholar]
Prinz J . 2005 . Emotional Perception New York: Oxford Univ. Press In press [Google Scholar]
Rizzolati G , Fadiga L , Gallese V , Fogassi L . 1996 . Premotor cortex and the recognition of motor actions. Cogn. Brain Res. 3 : 131– 41 [Google Scholar]
Roberts DF , Foehr UG , Rideout VJ . 2005 . Generation M: Media in the Lives of 8–18 Year-Olds Menlo Park, CA: Henry J. Kaiser Family Found. [Google Scholar]
Rosenthal R . 1986 . Media violence, antisocial behavior, and the social consequences of small effects. J. Soc. Issues 42 :( 3 ) 141– 54 [Google Scholar]
Simon A . 1979 . Violence in the mass media: a case of modeling. Percept. Mot. Skills 48 : 1081– 82 [Google Scholar]
Singer JL , Singer DG . 1986 . Family experiences and television viewing as predictors of children's imagination, restlessness, and aggression. J. Soc. Issues 42 :( 3 ) 107– 24 [Google Scholar]
Singer JL , Singer DG . 1986 . Television-viewing and family communication style as predictors of children's emotional behavior. J. Child. Contemp. Soc. 17 : 75– 91 [Google Scholar]
Slater MD , Henry KL , Swaim RC , Anderson LL . 2003 . Violent media content and aggressiveness in adolescents: a down ward spiral model. Commun. Res. 30 :( 6 ) 713– 36 [Google Scholar]
Stack S . 1989 . The effect of publicized mass murders and murder-suicides on lethal violence, 1968–1980: A research note. Soc. Psychiatry Psychiatr. Epidemol. 24 : 202– 8 [Google Scholar]
Stack S . 2000 . Media impacts on suicide: a quantitative review of 293 findings. Soc. Sci. Q. 81 :( 4 ) 957– 71 [Google Scholar]
Thompson KM , Haninger K . 2001 . Violence in E-rated video games. JAMA 286 :( 5 ) 591– 98 [Google Scholar]
Valentino NA , Traugott M , Hutchings V . 2002 . Group cues and ideological constraint: A replication of political advertising effects studies in the lab and in the field. Polit. Commun. 19 : 29– 48 [Google Scholar]
Walters RH , Parke RD . 1964 . Influence of response consequences to a social model on resistance to deviation. J. Exp. Child Psychol. 1 : 269– 80 [Google Scholar]
Wilson BJ , Kunkel D , Linz D , Potter J , Donnerstein E . et al. 1997 . Violence in television programming overall: University of California, Santa Barbara study. In National Television Violence Study ed. M Seawall 1 3– 184 Thousand Oaks, CA: Sage [Google Scholar]
Wyrwicka W . 1996 . Imitation in Human and Animal Behavior New Brunswick, NJ: Transaction [Google Scholar]
Zajonc RB , Murphy ST , Inglehart M . 1989 . Feeling and facial efference: implications of the vascular theory of emotion. Psychol. Rev. 96 : 395– 416 [Google Scholar]

Data & Media loading...

Article Type: Review Article

Most Read This Month

Most cited most cited rss feed, review of community-based research: assessing partnership approaches to improve public health, nature and health, measuring social class in us public health research: concepts, methodologies, and guidelines, the epidemiology of depression across cultures, acute respiratory effects of particulate air pollution, racism and health: evidence and needed research, the social determinants of health: coming of age, the role of behavioral science theory in development and implementation of public health interventions, mediation analysis: a practitioner's guide, the prescription opioid and heroin crisis: a public health approach to an epidemic of addiction.

Violence in the media: Psychologists study potential harmful effects

Early research on the effects of viewing violence on television—especially among children—found a desensitizing effect and the potential for aggression. Is the same true for those who play violent video games?

Video Games

Television and video violence

Virtually since the dawn of television, parents, teachers, legislators, and mental health professionals have wanted to understand the impact of television programs, particularly on children. Of special concern has been the portrayal of violence, particularly given psychologist Albert Bandura’s work in the 1970s on social learning and the tendency of children to imitate what they see.

As a result of 15 years of “consistently disturbing” findings about the violent content of children’s programs, the Surgeon General’s Scientific Advisory Committee on Television and Social Behavior was formed in 1969 to assess the impact of violence on the attitudes, values, and behavior of viewers. The resulting report and a follow-up report in 1982 by the National Institute of Mental Health identified these major effects of seeing violence on television:

Children may become less sensitive to the pain and suffering of others.
Children may be more fearful of the world around them.
Children may be more likely to behave in aggressive or harmful ways toward others.

Research by psychologists L. Rowell Huesmann, Leonard Eron, and others starting in the 1980s found that children who watched many hours of violence on television when they were in elementary school tended to show higher levels of aggressive behavior when they became teenagers. By observing these participants into adulthood, Huesmann and Eron found that the ones who’d watched a lot of TV violence when they were 8 years old were more likely to be arrested and prosecuted for criminal acts as adults.

Interestingly, being aggressive as a child did not predict watching more violent TV as a teenager, suggesting that TV watching could be a cause rather than a consequence of aggressive behavior. However, later research by psychologists Douglas Gentile and Brad Bushman, among others, suggested that exposure to media violence is just one of several factors that can contribute to aggressive behavior.

Other research has found that exposure to media violence can desensitize people to violence in the real world and that, for some people, watching violence in the media becomes enjoyable and does not result in the anxious arousal that would be expected from seeing such imagery.

Video game violence

The advent of video games raised new questions about the potential impact of media violence, since the video game player is an active participant rather than merely a viewer. 97% of adolescents age 12–17 play video games—on a computer, on consoles such as the Wii, Playstation, and Xbox, or on portable devices such as Gameboys, smartphones, and tablets. A Pew Research Center survey in 2008 found that half of all teens reported playing a video game “yesterday,” and those who played every day typically did so for an hour or more.

Many of the most popular video games, such as “Call of Duty” and “Grand Theft Auto,” are violent; however, as video game technology is relatively new, there are fewer empirical studies of video game violence than other forms of media violence. Still, several meta-analytic reviews have reported negative effects of exposure to violence in video games.

A 2010 review by psychologist Craig A. Anderson and others concluded that “the evidence strongly suggests that exposure to violent video games is a causal risk factor for increased aggressive behavior, aggressive cognition, and aggressive affect and for decreased empathy and prosocial behavior.” Anderson’s earlier research showed that playing violent video games can increase a person’s aggressive thoughts, feelings, and behavior both in laboratory settings and in daily life. “One major conclusion from this and other research on violent entertainment media is that content matters,” says Anderson.

Other researchers, including psychologist Christopher J. Ferguson, have challenged the position that video game violence harms children . While his own 2009 meta-analytic review reported results similar to Anderson’s, Ferguson contends that laboratory results have not translated into real world, meaningful effects. He also claims that much of the research into video game violence has failed to control for other variables such as mental health and family life, which may have impacted the results. His work has found that children who are already at risk may be more likely to choose to play violent video games. According to Ferguson, these other risk factors, as opposed to the games, cause aggressive and violent behavior.

APA launched an analysis in 2013 of peer-reviewed research on the impact of media violence and is reviewing its policy statements in the area.

Anderson, C.A., Ihori, Nobuko, Bushman, B.J., Rothstein, H.R., Shibuya, A., Swing, E.L., Sakamoto, A., & Saleem, M. (2010). Violent video game effects on aggression, empathy, and prosocial behavior in Eastern and Western countries: A Meta-analytic review. Psychological Bulletin , Vol. 126, No. 2.

Anderson, C. A., Carnagey, N. L. & Eubanks, J. (2003). Exposure to violent media: The effects of songs with violent lyrics on aggressive thoughts and feelings. Journal of Personality and Social Psycholog y, Vol. 84, No. 5.

Anderson, C. A., & Dill, K. E. (2000). Video games and aggressive thoughts, feelings, and behavior in the laboratory and in life. Journal of Personality and Social Psychology , Vol. 78, No. 4.

Ferguson, C.J. (2011). Video games and youth violence: A Prospective analysis in adolescents. Journal of Youth and Adolescence , Vol. 40, No. 4.

Gentile, D.A., & Bushman, B.J. (2012). Reassessing media violence effects using a risk and resilience approach to understanding aggression. Psychology of Popular Media Culture , Vol. 1, No. 3.

Huesmann, L. R., & Eron, L. D. (1986). Television and the aggressive child: A cross-national comparison. Hillsdale, NJ: Erlbaum.

Huesmann, L. R., Moise-Titus, J., Podolski, C. L., & Eron, L. D. (2003). Longitudinal relations between children’s exposure to TV violence and their aggressive and violent behavior in young adulthood: 1977–1992. Developmental Psychology , Vol. 39, No. 2, 201–221.

Huston, A. C., Donnerstein, E., Fairchild, H., Feshbach, N. D., Katz, P. A., Murray, J. P., Rubinstein, E. A., Wilcox, B. & Zuckerman, D. (1992). Big world, small screen: The role of television in American society. Lincoln, NE: University of Nebraska Press.

Krahe, B., Moller, I., Kirwil, L., Huesmann, L.R., Felber, J., & Berger, A. (2011). Desensitization to media violence: Links with habitual media violence exposure, aggressive cognitions, and aggressive behavior. Journal of Personality and Social Psychology , Vol. 100, No. 4.

Murray, J. P. (1973). Television and violence: Implications of the Surgeon General’s research program. American Psychologist , Vol. 28, 472–478.

National Institute of Mental Health (1982). Television and behavior: Ten years of scientific progress and implications for the eighties, Vol. 1. Rockville, MD: U.S. Department of Health and Human Services.

Desensitization to Media Violence: Links With Habitual Media Violence Exposure, Aggressive Cognitions, and Aggressive Behavior

Barbara krahé.

Department of Psychology, University of Potsdam, Potsdam, Germany

Ingrid Möller

L. rowell huesmann.

Institute for Social Research, University of Michigan

Lucyna Kirwil

Department of Social Psychology, Warsaw School of Social Sciences and Humanities, Warsaw, Poland

Juliane Felber

Anja berger.

This study examined the links between desensitization to violent media stimuli and habitual media violence exposure as a predictor and aggressive cognitions and behavior as outcome variables. Two weeks after completing measures of habitual media violence exposure, trait aggression, trait arousability, and normative beliefs about aggression, undergraduates ( N = 303) saw a violent film clip and a sad or a funny comparison clip. Skin conductance level (SCL) was measured continuously, and ratings of anxious and pleasant arousal were obtained after each clip. Following the clips, participants completed a lexical decision task to measure accessibility of aggressive cognitions and a competitive reaction time task to measure aggressive behavior. Habitual media violence exposure correlated negatively with SCL during violent clips and positively with pleasant arousal, response times for aggressive words, and trait aggression, but it was unrelated to anxious arousal and aggressive responding during the reaction time task. In path analyses controlling for trait aggression, normative beliefs, and trait arousability, habitual media violence exposure predicted faster accessibility of aggressive cognitions, partly mediated by higher pleasant arousal. Unprovoked aggression during the reaction time task was predicted by lower anxious arousal. Neither habitual media violence usage nor anxious or pleasant arousal predicted provoked aggression during the laboratory task, and SCL was unrelated to aggressive cognitions and behavior. No relations were found between habitual media violence viewing and arousal in response to the sad and funny film clips, and arousal in response to the sad and funny clips did not predict aggressive cognitions or aggressive behavior on the laboratory task. This suggests that the observed desensitization effects are specific to violent content.

The hypothesis that media violence increases aggressive behavior has been widely studied in experimental research looking at the short-term effects of exposure to violent media stimuli, as well as in cross-sectional and longitudinal studies relating habitual media violence exposure to individual differences in the readiness to show aggressive behavior. Although there is disagreement among some researchers as to whether or not the evidence currently available supports the view that media violence exposure is a risk factor for aggression ( Huesmann & Taylor, 2003 ), most meta-analyses and reviews have reported substantial effect sizes across different media, methodologies, and outcome variables, suggesting that exposure to violent media contents increases the likelihood of aggressive behavior in the short term as well as over time (e.g., Anderson et al., 2003 ; Bushman & Huesmann, 2006 ; Huesmann, 1982 ; Huesmann & Kirwil, 2007 ; Murray, 2008 ; Paik & Comstock, 1994 ). Other authors have questioned both the strength of the evidence and its implications (e.g., Ferguson, 2007 ; Savage & Yancey, 2008 ). Ferguson and Kilburn (2009 , 2010 ) concluded from their meta-analysis that there was no support for the claim that media violence increases aggressive behavior. However, they acknowledged that experimental studies using proxy measures of aggression did produce substantive effect sizes and were relatively unaffected by publication bias, and their conclusions have been vigorously disputed by others ( Anderson et al., 2010 ; Bushman, Rothstein, & Anderson, 2010 ; Huesmann, 2010 ).

Beyond studying the strength of the link between media violence usage and aggression, researchers have worked toward identifying the underlying processes that mediate between violent media stimuli as input variables and aggressive behavior as an outcome. Whereas priming, mimicry, and excitation transfer are thought to be important mechanisms for the short-term effects of media violence on aggression, observational learning and desensitization have been hypothesized as key mechanisms for long-term effects ( Bandura, 1973 ; Berkowitz, 1965 ; Huesmann, 1982 , 1988 ; Huesmann & Kirwil, 2007 ; Huesmann, Moise, Podolski, & Eron, 2003 ). Observational learning refers to the acquisition of cognitive structures that promote specific behaviors from observing others perform similar behaviors. Watching media characters behave in a violent fashion can instigate a process of observational learning in which a new cognitive and behavioral repertoire promoting violence is acquired. Desensitization , on the other hand, is a process involving changes in emotional responsiveness. In general terms, desensitization refers to the gradual reduction in responsiveness to an arousal-eliciting stimulus as a function of repeated exposure. In the context of media violence, desensitization more specifically describes a process “by which initial arousal responses to violent stimuli are reduced, thereby changing an individual’s ‘present internal state’” ( Carnagey, Anderson, & Bushman, 2007 , p. 491). In particular, desensitization to violent media stimuli is thought to reduce anxious arousal. Fear is a spontaneous and probably innate response of humans in reaction to violence. As with other emotional responses, repeated exposure to media violence can decrease negative affect, because violent stimuli lose their capacity to elicit strong emotions the more often the stimulus is presented ( Anderson & Dill, 2000 ).

Several studies have shown that in the long run, habitual exposure to media violence may reduce anxious arousal in response to depictions of violence. Research has found that the more time individuals spent watching violent media depictions, the less emotionally responsive they became to violent stimuli (e.g., Averill, Malstrom, Koriat, & Lazarus, 1972 ) and the less sympathy they showed for victims of violence in the real world (e.g., Mullin & Linz, 1995 ). Bartholow, Bushman, and Sestir (2006) used event-related brain potential data (ERPs) to compare responses by violent and nonviolent video game users to violent stimuli and relate them to subsequent aggressive responses in a laboratory task. Bartholow et al. found that the more violent games participants played habitually, the less brain activity they showed in response to violent pictures and the more aggressively they behaved in the subsequent task. In a series of studies with children age 5 to 12, Funk and colleagues demonstrated that habitual usage of violent video games was associated with reduced empathy with others in need of help ( Funk, Baldacci, Pasold, & Baumgardner, 2004 ; Funk, Buchman, Jenks, & Bechtoldt, 2003 ).

Evidence is less clear with regard to short-term desensitization effects in experimental settings. In one recent study, Carnagey et al. (2007) showed that participants’ physiological arousal to depictions of real-life violence was reduced after participants had played a violent video game compared to a control group that had played a nonviolent game. In contrast, Funk et al. (2003) found no evidence of short-term desensitization (indicated by reduced empathy with others in need of help) in the children in their study who played a violent video game as compared with those who played a nonviolent game. Ballard, Hamby, Panee, and Nivens (2006) found some evidence of physiological desensitization over a 3-week game playing period but failed to find differential desensitization as a function of playing a violent versus nonviolent game. Finally, Arriaga, Esteves, Carneiro, and Monteiro (2006) failed to find a decrease in physiological arousal from the beginning to the end of a 4-min playing period regardless of whether participants played a violent or a nonviolent game.

Past research has varied with regard to the critical measure of desensitization. Some studies have used self-reported affect (e.g., Fanti, Vanman, Henrich, & Avraamides, 2009 ), while others have used different indicators of physiological arousal, such as heart rate, blood pressure, skin conductance, or measured brain activity (e.g., Bartholow et al., 2006 ; Carnagey et al., 2007 ). Few studies have concurrently examined physiological and subjective indices of arousal (e.g., Ballard et al., 2006 ), and yet fewer have included subjective reports of both negative (anxiety, anger) and positive (enjoyment) emotional responses (for an exception, see Kirwil, 2008 ). This diversity in operationalizing arousal may be one of the reasons for the lack of consistency in research on short-term desensitization.

The vast majority of studies have looked at desensitization in terms of reduced negative arousal in response to media violence. Another pertinent effect of habitual or repeated exposure to media violence may be increased positive arousal or enjoyment. The role of positive arousal to violent media is less than clear. In line with Zillmann’s (1996) model of suspense enjoyment based on excitation transfer principles, a positive association was found between experienced negative affect and enjoyment of violent media in a meta-analysis by Hoffner and Levine (2005) . However, this pattern held only for self-reported negative affect and enjoyment and failed to emerge for the link between physiological arousal and enjoyment.

An alternative perspective on the relationship between anxious and pleasant arousal may be derived from the general aggression model extended by Carnagey et al. (2007) , to include desensitization. They argued that because repeated exposure to media violence reduces the anxiety reaction to violence, new presentations of violence “instigate different cognitive and affective reactions than would have occurred in the absence of desensitization” (p. 491). One such affective reaction may be a positive response to violence that would otherwise have been inhibited by anxious arousal. Huesmann and Kirwil (2007) have called this process sensitization . They argued that, for some individuals, watching violence is enjoyable, and, whereas it may provoke anger, it does not produce anxious arousal. On the contrary, the more such individuals watch violence, the more they like watching it. They are experiencing a “sensitization” of positive feelings. Because finding violence pleasant is incompatible with experiencing anxious arousal, increased pleasant arousal to depictions of violence in individuals with a high exposure to media violence would constitute indirect evidence of desensitization of “negative feelings” about violence. On the basis of this line of reasoning, we propose that anxious arousal by violent media stimuli is negatively related to pleasant arousal and that habitual exposure to media violence should both decrease negative emotional reactions and increase positive emotional reactions to violence, though the increase in positive emotions may occur for only a subset of individuals. For example, in a recent study of young adults in Poland, Kirwil (2008) found that proactively aggressive individuals tended to respond to violent media stimuli with a reduction in anxious arousal, whereas reactively aggressive individuals tended to respond with an increase in enjoyment.

A further key question refers to the content specificity of desensitization in response to violent media stimuli. Does desensitization to other arousing stimuli also predict increased aggression, or is the link dependent on violent content? Anderson and Bushman (2001) pointed out that although exciting nonviolent video games can increase arousal, “only violent games should directly prime aggressive thoughts and stimulate the long-term development of aggressive knowledge structures” (p. 356). Experimental studies comparing the effects of violent and nonviolent video games matched for difficulty, enjoyment, arousal quality, and level of frustration have provided empirical support for this line of reasoning (e.g., Anderson et al., 2004 ; Bartholow, Sestir, & Davis, 2005 ). Carnagey et al. (2007) found that although there were no differences in heart rate immediately after playing a violent versus a nonviolent game for 20 min, participants in the violent but not in the nonviolent game condition subsequently showed reduced arousal when witnessing a real-life incident of violence. This finding indicates that desensitization to real-life violence is contingent upon the violent content of the media stimulus. However, this explanation focuses on the cognitive effects of violent media input, and a different mechanism is required to explain how changes in emotional reactivity might affect aggression. Huesmann and colleagues ( Huesmann, 1997 , p. 81; Huesmann, 2007 ; Huesmann & Kirwil, 2007 ; Huesmann et al., 2003 ) proposed that a person’s emotional reaction to the anticipation of aggression and violence plays a role in inhibiting or promoting aggressive responding. When scripts for behaving aggressively are activated by some situation, they may be inhibited if the anxious arousal stimulated by that activation is greater than the pleasant arousal. Consequently, people whose negative emotional reactions to violence have been desensitized (or who by disposition have lower reactions) may experience more positive emotions when anticipating aggression and should be more likely to engage in aggression. According to this theoretical position, people who react less negatively to violent media scenes and experience more positive reactions to such scenes should be more aggression prone. The key mechanism is the person’s emotional reaction to violent scenes, not the person’s reaction to other kinds of arousing scenes. Relating emotional reactions to scenes of violence to aggression, Moise-Titus (1999) found that people who showed lower anxious reactions to violent scenes scored higher on trait aggression, had watched more media violence, and subsequently behaved more aggressively on a laboratory task. However, she examined only reactions to violent films and did not compare them with reactions to other types of arousing scenes.

Regarding the link between aggression and skin conductance level (SCL) as a quantitative measure of arousal, empirical evidence is mixed, varying for measures of electrodermal activity, age, and the psychological meaning assigned to the stimuli ( Fowles, 2000 ; Fowles, Kochanska, & Murray, 2000 ; Lorber, 2004 ; Patrick & Verona, 2007 ). There is some indication that adults low on resting SCL and in SCL responses to negative stimuli are more prone to showing hostility and aggression. Huesmann and Kirwil (2007) reviewed evidence that individuals displaying low physiological arousal at baseline level were more likely to show aggressive behavior over a subsequent period of observation. Longitudinal studies showed that boys who had lower heart rate and SCLs at age 15 were significantly more likely to commit violent offenses in the following years ( Scarpa & Raine, 2007 ). However, to complicate matters, studies have shown different links between SCL and proactive and reactive aggression, respectively. For example, Hubbard et al. (2002 , 2004 ) found low SCL to be associated with proactive aggression in children, whereas higher levels of SC were related to reactive aggression.

Each of these studies linked individual differences in arousal to relatively stable aggressive dispositions. More pertinent to the present study are studies linking physiological activation to laboratory-induced aggression. In reviewing this research, relying mostly on heart rate as a measure of arousal, Patrick and Verona (2007) concluded that these studies have produced mixed results and called for more research using multiple measures of activation, including SCL. The potential relation of SCL to aggressive cognitions is even less clear. Past research provides at best indirect evidence concerning this issue. Studies have demonstrated a link between low SCL and shorter response latencies in a word association task ( Jones, 1960 ) or a visual discrimination task ( Vossel, 1988 ), but neither study addressed responses to aggression-related stimuli. Against this limited body of research, the present study examined whether differences in baseline SCL and SCL responses during the violent clips would be associated with differences in aggressive cognitions.

Few studies are available that have addressed desensitization to arousing stimuli differing in affective quality. Fanti et al. (2009) showed participants a series of violent and funny film scenes and asked them to indicate how much they enjoyed them. For the violent scenes, there was a curvilinear pattern of liking. An initial decline in enjoyment of the violent scenes was followed by an increase during subsequent scenes, and enjoyment was greater at the end than at the beginning of the series. In contrast, a gradual decline in enjoyment was found for the funny scenes. This finding suggests that sensitization (defined here in terms of an increase in positive affect to depictions of violence that can be assumed to correlate with a decrease in negative affect [desensitization]) was specific to violent content. Unfortunately, Fanti et al. did not include a measure of habitual usage of media violence. Bartholow et al. (2006) compared ERPs to violent pictures with nonviolent but negatively arousing images (e.g., images of facial disfigurements). They found that greater preference and past use of violent games predicted decreased ERPs to the violent pictures but not to the unpleasant comparison pictures and that differences in responses to the nonviolent pictures, unlike differences in response to violent images, were unrelated to subsequent aggressive behavior. In combination, the two studies suggest (a) that repeated media exposure desensitizes emotional reactions to violence only if the exposure is to scenes of violence and (b) that it is only decreased emotional reactions to violence that are linked to increases in aggressive cognitions and behavior.

The Current Study

The current study was designed to add to the existing body of evidence on the role of desensitization in the media violence– aggression link in four ways: (a) by looking at altered emotional reactions to a violent film clip as an outcome variable of long-term, habitual media violence exposure; (b) by looking at desensitization to violence both in terms of a decrease in anxious arousal and of an increase in pleasant arousal; (c) by looking at altered emotional reactions to violent films as a situational predictor of aggressive cognitions and behavior; and (d) by comparing responses to violent media stimuli with responses to sad and funny stimuli to address the issue of the content specificity of the aggression-promoting effects of desensitization.

The study was designed to test our hypotheses about how anxious and pleasant emotional responses to arousing scenes of violence (in contrast to other arousing scenes) relate both to habitual media violence exposure and to proactive and reactive immediate aggression. As described above, existing evidence suggests that those who watch or play violent media should become desensitized to the negative emotions violence stimulates and should experience both less anxious arousal and more pleasant arousal when viewing or thinking about violence. In turn, as Huesmann and colleagues have argued ( Huesmann & Kirwil, 2007 ; Huesmann et al., 2003 ), the reduced anxious and increased pleasant arousal that accompanies thinking about violence should cause more aggressive thoughts to be stimulated by the violent scene and should allow more aggressive scripts—scripts that would normally be inhibited by the anxious arousal—to be used proactively in social problem solving. However, it is unlikely that the more reactive type of angry emotional aggression in response to provocation would be made any more likely by such changes in emotional arousal to scenes of violence. The present study included measures of both proactive and reactive aggression to test this line of reasoning.

This thinking leads us to four specific hypotheses:

The more media violence exposure individuals have had in the past, the less increase in physiological arousal they will show in response to a violent film clip, both compared to arousal at baseline and compared to other arousing media stimuli (sad and funny clips).
The more media violence exposure individuals have had in the past, the less anxious and, correspondingly, the more pleasant arousal will they report in response to a violent film clip. No significant correlations are expected between habitual media violence exposure and anxious and pleasant arousal in response to sad or funny clips, because the desensitization that prior exposure produced would be specific to violent content.
The lower the anxious arousal and the higher the pleasant arousal of individuals in response to a violent film clip, the more rapid will be the accessibility of aggressive cognitions, as evidenced in shorter response latencies in recognizing aggression-related words, and the greater will be the individuals’ immediate proactive unprovoked aggression. The effects will occur independently of the effects of habitual media violence exposure, trait aggression, and aggressive beliefs on the aggression measures and independent of the effects of trait arousability on the arousal measures. The arousal response to violent film clips is not assumed to be related to immediate reactive provoked aggression.
Finally, the relations between emotional arousal to film clips and subsequent aggressive cognitions and behavior are hypothesized to be dependent on the violent content of the arousing stimulus. That is, lower anxious arousal and greater pleasant arousal to the violent film clip but not to the sad or funny clips should be linked to increased accessibility of aggressive cognitions and higher levels of proactive aggressive behavior.

To examine these predictions, we conducted a study in which participants first completed an online questionnaire about their habitual media violence exposure. In addition, trait aggression, trait arousability, and normative beliefs about aggression were measured at this stage as alternative predictors of arousal, aggressive cognitions, and aggressive behavior to enable us to identify the unique contribution of media violence exposure. Two weeks later the participants came into the laboratory and were exposed to two different emotionally arousing films: a violent clip and a sad or a funny comparison clip. They answered a brief questionnaire after each clip assessing a variety of variables including their emotional arousal during the film clip. SCL was recorded constantly before and during the films as a measure of physiological arousal. Following the film clips, participants completed a lexical decision task as a measure of the cognitive accessibility of aggressive thoughts and a competitive reaction time task as a measure of aggressive behavior.

Participants

Students enrolled in a broad range of courses at the University of Potsdam, Germany, were invited by university intranet and flyers to participate in a two-part study on emotional responses to films, the first part of which was to be completed as an online survey. They were informed that following the first part they would be invited to the lab for an experimental session in which they would be shown different film clips. Students were asked to respond by e-mail to express their willingness to participate, and those who did so were sent the link to the online questionnaire, also via e-mail. Participants were offered 15 Euros or, alternatively, 3 hours of course credit for participation in both parts. A total of 625 undergraduate students, 413 men and 212 women, with a mean age of 23.7 years ( SD = 3.09) participated in this initial online survey.

At the end of the online questionnaire, participants received detailed information about the second part of the study and were asked to sign up for a lab session in which they would view some film clips, be recorded physiologically, play a game, and answer more questions. In compliance with the requirements of the Ethics Committee of the University of Potsdam, which formally approved the study, participants were then told about the violent nature of some of the film clips and possible viewer reactions to them as well as about the recording of physiological arousal. Once they had made an appointment for the lab session, participants received a confirmation e-mail instructing them to refrain from drinking coffee or other stimulating drinks for at least two hours prior to the scheduled appointment, as this would interfere with the SCL recording. A total of 341 of the 625 undergraduate students who had completed the online survey participated in the second part of the study; of these, 38 had to be excluded due to unusable SCL data. The final sample consisted of 303 participants (215 men and 88 women) for whom complete data were available from both data points. The mean age of this sample was 23.75 years ( SD = 2.76). On average, lab sessions took place 2 weeks after the return of the online questionnaire.

Measures: Online Questionnaire

Habitual media violence exposure.

Participants were provided with genre lists for movies and electronic games. For each item on the two lists, they were asked to indicate how frequently they used the respective genre on a 5-point scale ranging from 1 ( never ) to 5 ( very often ). Frequency ratings are commonly used in studies operationalizing media violence exposure through providing broad media categories or genre lists (e.g., Potts, Dedmon, & Halford, 1996 ; Slater, Henry, Swaim, & Anderson, 2003 ).

For movies, 10 genres were provided: (a) action, (b) drama, (c) horror/slasher, (d) comedies, (e) military and war, (f) crime thrillers, (g) romantic fiction, (h) martial arts, (i) science fiction, and (j) western. For electronic games, 15 genres were presented: (a) beat-em ups, (b) shoot-em ups, (c) first-person shooters, (d) third-person shooters, (e) tactical shooters, (f) survival horror games, (g) genre mix, (h) classic adventure, (i) action adventure, (j) role-playing games, (k) general simulations, (l) military simulations, (m) sports games, (n) construction strategy, and (o) military strategy. Each game category was illustrated by a specific example prominent at the time of the study.

A sample of 21 undergraduate students (5 women and 16 men, mean age = 23.8 years, SD = 3.12) who identified themselves as regular media users rated the genres in terms of violent content. They were asked to rate the level of violence typically characteristic of each genre, using a 5-point scale from 1 ( nonviolent ) to 5 ( very violent ). Interrater agreement as indicated by Kendall’s W was high ( W = .86, p < .001). On that basis, a mean violence score was computed across raters for each genre.

To arrive at a measure of media violence exposure, we selected those genres that had received violence ratings of higher than 2 on the 5-point scale from 1 ( nonviolent ) to 5 ( very violent ) from the sample of independent raters for the media violence exposure index. This was true for nine out of the 10 movie genres (all except romantic fiction; violence ratings ranged from 2.43 for drama to 4.81 for military and war films) and 12 of the 15 video game genres (all except general simulations, sports games, and construction strategy games; range from 2.05 for classic adventure to 4.95 for first-person shooters). Participants’ frequency ratings for each of the selected genres were multiplied by the average violence rating of that genre obtained from the independent raters. The resulting product scores per genre were then averaged across the 21 genres. 1

Trait arousability

This construct referred to a person’s susceptibility to strong emotional responsiveness in terms of the general tendency to experience strong emotions and the ease of getting into strong positive and negative emotional states. It was measured by a 21-item scale composed of 11 items from Mehrabian’s (1995) Trait Arousability Scale (example item: “I get happy or sad easily”) and 10 items from the Affect Intensity Scale by Geuens and de Pelsmacker (2002; example item: “My happy moods are so strong that I feel like I’m in heaven”). Responses were made on a 7-point scale ranging from 1 ( not at all true ) to 7 ( exactly true ). An overall arousability score was computed for each participant by averaging responses across the 21 items. The scale reliability data for the scales of the online questionnaire are presented in Table 1 .

Reliabilities, Descriptive Statistics, and Gender Differences for the Dispositional Measures in the Online Survey (Time 1 Sample, N 625)

Measure	Items	α	Range			Men	Women		Final sample ( = 303)
Media violence exposure	21	.85	2.05–24.75	7.53	1.86	8.06	6.49	119.60	6.75 (1.62)
Trait aggression	33	.89	1–5	2.08	0.43	2.09	2.00	6.24	2.06 (0.44)
Trait arousability	21	.84	1–7	4.57	0.76	4.32	5.04	152.02	4.57 (0.73)
Aggressive norms	11	.84	1–5	1.78	0.60	1.83	1.69	6.42	1.76 (0.57)

Note . Values for final sample are M (SD ).

Trait aggression

The dispositional tendency toward aggression was measured by a German version of the Aggression Questionnaire by Buss and Perry (1992 ; Krahé & Möller, 2010 ). The original Aggression Questionnaire comprises aggressive behavior (physical aggression, e.g., “I may hit someone if he or she provokes me”; verbal aggression, e.g., “I can’t help getting into arguments when people disagree with me”), anger (e.g., “I have trouble controlling my temper”), and hostility (e.g., “I know that ‘friends’ talk about me behind my back”) as facets of dispositional aggressiveness and has a total of 29 items. Four new items were added to measure relationally aggressive behavior (e.g., “I have sometimes spread rumors about someone who had treated me badly”), bringing the total number of items on this measure to 33. Responses were made on a 5-point scale ranging from 1 ( not at all true ) to 5 ( exactly true ). A total aggression score was computed for each participant by averaging responses across the 33 items.

Aggressive normative beliefs

Normative acceptance of aggression was measured with a vignette describing a provocation scenario based on Krahé and Möller (2004) . The scenario described a confrontation where the protagonist was criticized unfairly by a colleague in front of others and then finds himself/herself alone with that colleague later in the day. The protagonist was described as male or female to match the participants’ gender. A total of 11 aggressive responses by the protagonist toward the colleague were presented as potential actions in that situation (e.g., “to scream at him”, “to insult him”). Participants were asked to indicate, on a 5-point scale, ranging from 1 ( not at all ok ) to 5 ( very much ok ), how acceptable they would find the response in that situation. Ratings were averaged across the 11 items to create an overall index of normative acceptance of aggression. Huesmann and Guerra (1997) have previously found that norms of this type are predictive of aggressive behavior and related to observation of violence.

Order variation

To control for order effects, we created different versions of the questionnaire in which each dispositional measure appeared once in every possible position. The media violence exposure measure was always presented first because it was most closely related to the theme of the study (i.e., a study on emotional reactions to films), as advertised to the participants.

Measures: Laboratory Session

Violent film clips.

Two violent film clips were used in the laboratory part of the study. 2 The first was taken from the film Casino ( Scorsese, 1995 ) and lasted a total of 2:19 min. Within the clip, two critical violent scenes were selected, lasting 59 and 32 s, respectively. The second clip was taken from the film Reservoir Dogs ( Tarantino, 1992 ) with a total length of 4.41 min and two critical scenes of 60 s each. The clips were selected on the basis of a pilot study with 87 undergraduate students that showed them to elicit strong negative affect, in particular anxiety. They had also been used in a previous study by Moise-Titus (1999) and were found to elicit high levels of anxiety.

Based on the results of the pilot study, two clips were selected to elicit sad mood. One was taken from the film The Champ ( Zeffirelli, 1979 ) and lasted 4:19 min. The first critical sad scene lasted 106 s, and the second sad scene lasted 104 s. The second clip was selected from the film Stepmom ( Columbus, 1998 ) and lasted 4:12 min. The two critical scenes lasted 93 s and 92 s, respectively.

Funny clips

The two funny clips were also selected on the basis of the pilot study. Selection criteria were that they contained an action element (excluding purely verbal humor) and that there was no aggression (excluding slapstick scenes, e.g., cream cakes being thrown into a person’s face). The first clip was taken from Monty Python’s Life of Brian ( Jones, 1979 ) and had a total length of 4:07 min. The two critical scenes lasted 136 s and 79 s, respectively. The second funny clip was taken from another Monty Python sketch, Philosophers’ World Cup ( Cleese, 1972 ; http://www.metacafe.com/watch/yt-92vV3QGagck/monty_python_philosophers_world_cup/ ) and had a total length of 3:50 min and two critical scenes of 98 s and 78 s, respectively. Participants in the pilot study were asked if they had seen the clips in question; percentages ranged below 20% across the three types of film. On that basis, it was concluded that familiarity with the selected clips was low in the target sample.

Physiological arousal

SCL was recorded as a measure of physiological arousal. This measure has been widely used in research of desensitization and was described by Ravaja (2004) as an excellent operationalization of arousal in the context of media research. The present study used PAR-PORT, a portable device that records SCL data at a rate of 10 measures per second ( www.par-berlin.com ). This sampling rate is common in studies in which SCL is used as an outcome measure in media research (e.g., Lang, Zhou, Schwartz, Bolls, & Potter, 2000 ). Prior to the film presentation, an 80-s baseline measure was taken during a resting period. 3 SCL was then recorded continuously throughout the presentation of the film clips.

Self-reported affective responses and perceptions of film clips

Immediately after each film clip ended, participants were asked to rate how they had felt while watching the clip by indicating how pleasant they had found the clip and how much anxiety they had felt while watching it. These two critical items were embedded within three manipulation check items and four further filler items, and responses were made on a 7-point scale ranging from 0 ( not at all ) to 6 ( very much ). For the manipulation check items, participants were asked to rate how violent, sad, and funny they had found the film clip. Ratings were made on a 7-point scale ranging from 0 ( not at all ) to 6 ( very much ).

Accessibility of aggressive thoughts

To measure response latencies for aggressive words as an index of cognitive availability, we asked participants to work on a lexical decision task and measured their reaction time to complete it. They were presented with a total of 160 six-letter strings and had to indicate for each string whether or not it represented a meaningful German word. The stimulus material was drawn from a pilot study with linguistics students and consisted of 40 aggressive words (e.g., cannon, weapon, knives ), 40 nonaggressive words (e.g., flower, summer, meadow ), and 80 nonwords (e.g., rahmin, strese, faltar ) presented in random order. The nonaggressive words and the nonwords served as covariates to control for overall differences in response latencies regardless of content. The reaction times in the lexical decision task were converted into log scores and were then aggregated into mean scores for aggressive words, nonaggressive words, and nonwords, respectively.

Aggressive behavior

The noise blast paradigm, a standard competitive reaction time task often employed in media violence research, was used as a measure of aggressive behavior ( Anderson & Bushman, 1997 ; Ferguson, Rueda, Cruz, Ferguson, & Fritz, 2008 ). Participants were instructed that they would compete against another person in a series of 25 trials in how fast they could press a button in response to a visual signal and that the faster of the two would win the trial. They were told that the winner could send an aversive noise stimulus to the other person and that prior to each trial both participants would set the intensity of the noise level they were going to send to the other person in case they won. In fact, there was no other player involved, and the winning and losing trials were computer generated. Prior to the first round, participants received a sample noise blast and did a dummy run to familiarize themselves with the procedure. Noise levels ranged from 60 dB (Level 1) to 105 dB (Level 10, about the same volume as a smoke or fire alarm). A nonaggressive no-noise option (Level 0) was also provided. They were told that prior to each trial they would see the alleged opponent’s chosen noise level for the preceding trial and that the other person would see theirs.

The noise level set for the first trial (before participants learned about the noise level set by the alleged opponent) yielded a measure of proactive, unprovoked aggression ( Giancola & Parrott, 2008 ). The mean noise level set for the remaining 24 trials served as a measure of reactive, provoked aggression , because participants were aware of the noise levels their alleged opponent had set before selecting theirs. The noise level set for the first trial is considered the purer measure of individual differences in aggression, because it is not confounded by the pattern of provocations the participant receives on subsequent trials.

Upon arrival at the lab, participants were seated in front of a computer and connected to the PAR-PORT device for measuring SCL. After the 80-s baseline was recorded, they were shown the first film clip. Participants were randomly allocated to one of two orders (violent film first, comparison film second and vice versa), one of two comparison conditions (sad vs. funny), and one of the two film clips per condition, yielding a total of 16 different combinations. Following the film clip, they rated their pleasant and anxious arousal during the clip and also made ratings of how violent, sad, and funny they found the clip. These measures were completed in a paper-and-pencil format, and the SCL recoding was halted during this phase. Then the SCL recording was resumed and, after another 80-s baseline recording period, the second film clip was shown. The procedure was exactly the same for the second film clip, with the same measurements of self-reported arousal and evaluation of the film clip taken immediately afterward. After the second clip ratings were completed, the participants received a standardized set of verbal instructions on screen for the word completion task and for the noise blast task (see Bartholow et al., 2006 ). These two tasks were presented in counterbalanced order. The experimenter was present during the whole session but separated from the participant by a screen. At the end of the session, participants were shown an entertaining film about frolicking monkeys designed to dissipate any remaining negative arousal and were fully debriefed before receiving their monetary reward or course credit.

Dispositional Measures (Time 1)

The means and standard deviations for the dispositional measures from the online survey (i.e., media violence exposure, trait aggression, trait arousability, and normative beliefs) along with information about internal consistency are presented in Table 1 . All measures were found to have good reliability. It should be noted that conceptually, the media violence exposure measure is not required to have high internal consistency because the different genres and media can be used independently of one another, and the index therefore presents a cumulative measure of exposure. Nonetheless, the alpha of .85 reported in Table 1 is substantial, suggesting that preference for violent media contents shows a consistent pattern across genres.

One-way analyses of variance revealed significant gender differences on all of the variables in the study. As shown in Table 1 , men scored higher on media violence exposure, acceptance of aggressive norms, and aggressive behavior, and women scored higher on trait arousability. A comparison of participants who took part in both parts of the study with those who dropped out after Time 1 showed no significant differences between the two groups on any of the Time 1 measures, multivariate F (4, 567) = 1.23, p = .30, all univariate effects p > .10 (see Table 1 for means of the final sample). Therefore, there is no indication that the final sample of participants who took part in the full study was different from the initial, larger sample on any of the variables of interest.

Laboratory Measures of Aggression and Self-Reported Emotional Arousal (Time 2)

The means, reliabilities, and gender differences for the self-report arousal measures and aggression variables are shown in Table 2 . Again, the measures had high internal consistencies, and again there were significant gender differences. Men scored significantly higher on pleasant arousal while watching the clips, whereas women scored significantly higher on anxious arousal. Men also scored higher on unprovoked aggression in the competitive reaction time task.

Means and Gender Differences for Self-Reports of Arousal and Situational Aggression Measures During Laboratory Task (N = 303)

Measure	Items	α	Range			Men	Women
Pleasant arousal: All films	3		0–6	2.76	1.04	2.93	2.41	15.71
Anxious arousal: All films	3		0–6	1.13	1.19	0.98	1.58	14.75
Log response times aggressive words	40	.92	6.21–7.60	6.60	0.20	6.60	6.60	0.01
Unprovoked aggression	1		0–10	2.19	1.63	2.29	1.82	4.95
Provoked aggression	24	.96	0–10	3.63	2.02	3.62	3.50	0.19

Manipulation Checks for Film Clips

The manipulation checks for the three types of film clips are presented in Table 3 . As expected, the two violent film clips were perceived as highly violent, and violence ratings were significantly higher than those for the sad and funny comparison films. The two sad films produced significantly higher sadness ratings than the violent and funny films did, and the two funny films produced significantly higher funniness ratings than the violent and the sad films did. Thus, the clips were successful at representing the categories of violent, sad, and funny films. There were no significant differences within each film condition or between different orders of presentation. Therefore, the data were collapsed across these two variables for further analysis.

Manipulation Checks for Violent, Sad, and Funny Films in Laboratory Study

	Violent clips		Sad clips		Funny clips
Affective response
Was violent	5.30 (1.07)	5.00 (1.00)	0.54 (0.94)	0.02 (0.15)	1.06 (1.12)	0.02 (0.16)
Was sad	2.95 (1.84)	1.81 (1.72)	4.11 (1.46)	4.50 (1.30)	0.28 (0.97)	0.04 (0.20)
Was funny	0.27 (0.82)	0.94 (1.30)	0.22 (0.61)	0.50 (0.24)	4.82 (1.22)	4.74 (1.22)

Note . Values are M (SD ). Scale range was 0–6. Violence ratings were significantly higher in the two violent clips than in the sad and funny clips, sadness ratings were significantly higher in the two sad clips than in the violent and funny clips, and funniness ratings were significantly higher in the two funny clips than in the sad and violent clips. All ps < .000.

Bivariate Correlations Between Violence Exposure, Aggressive Norms, Arousal, and Aggression

The correlations between the dispositional trait measures from the online survey, the self-reported measures of arousal in response to the violent film clip, and the postfilm aggression measures are presented in Table 4 . Because men and women differed on several of the measures, the correlations are presented separately for men and for women. For both genders, habitual media violence exposure correlated positively with trait aggression, with pleasant arousal to the violent clip, and with more rapid recognition of aggressive words in the lexical decisions task. Trait aggression was linked to beliefs accepting aggression, and trait arousability showed a positive correlation with anxious arousal elicited by the violent clip. In addition, some gender-specific correlations were found. For women, media violence exposure correlated with beliefs accepting aggression and trait aggression correlated with pleasant arousal. For men, trait arousability was negatively correlated with pleasant arousal by the violent clip. Habitual media violence exposure was unrelated to both unprovoked and provoked aggression on the competitive reaction time task for both genders.

Correlations Between Media Violence Exposure, Trait Aggression, Trait Arousability, Aggressive Norms, Self-Reported Arousal From Violent Clip, and Situational Aggression (N = 303)

Variable	1	2	3	4	5	6	7	8	9
1. Media violence exposure	—	.18	.04	.06	.13	−.03	−.21	.09	.11
2. Trait aggression	.18	—	.21	49	.00	.05	−.15	.18	.12
3. Trait arousability	−.18	.09	—	.11	−.21	.15	.02	−.03	.11
4. Aggressive norms	.26	.38	.04	—	.01	.10	−.08	.18	.26
5. Pleasant arousal from violent clip	.30	.27	.06	.08	—	−.43	.17	.07	.03
6. Anxious arousal from violent clip	−.19	−.03	.30	−.06	−.39	—	.12	−.11	−.01
7. Log RT aggressive words	−.19	−.14	.11	−.18	−.11	−.08	—	−.03	−.08
8. Unprovoked aggression	−.03	.17	.09	.01	−.08	−.14	−.09	—	.59
9. Provoked aggression	−.07	.10	.05	−.11	.12	.03	−.09	.54	—

Note . Men ( N = 215) are above and women ( N = 88) are below the diagonal. RT = reaction time.

Aggregate Scores of Physiological Arousal

After they had been cleaned for outliers and adjusted for skewness through square root transformations, the continuous SCL measures during each clip were transformed into five aggregated scores: (a) mean across the first 15 s of the first critical scene (i.e., averaged across 150 data points; Time 1); (b) mean across the rest of the first critical scene (Time 2); (c) mean between the first and second critical scene (Time 3); (d) mean across the first 15 s of the second critical scene (Time 4); and (e) mean across the rest of the second critical scene (Time 5). The rationale for selecting the first 15 s into each critical scene (Time 1 and Time 4) was to have a time window of the same duration across scenes that otherwise varied in length. In addition, the 80-s baseline measure was created by averaging across the 800 data points prior to the start of the first clip. No gender differences were found on any of these indices: baseline, F (1, 302) = 0.07, p = .78; violent clips, multivariate F (6, 296) = 1.70, p = .13; sad clips, F (6, 151) = 1.32, p = .25; funny clips, F (6, 138) = 1.86, p = .09.

Relations of Self-Reports of Emotional Arousal to SCL Indices of Arousal

Table 5 shows the partial correlations between self-reports of emotional arousal during the film clips and SCL arousal during the film clips, controlling for baseline SCL. The results show positive correlations between ratings of anxious arousal in response to violent films and SCL for all five consecutive points in time. Conversely, negative correlations were found between reported pleasant arousal and SCL levels across the five indices. In contrast, for viewing the sad and funny clips, none of the correlations between SCL arousal and self-reported pleasant or anxious arousal were significant. These results confer particular validity on the self-report measures of anxious and pleasant arousal while watching violent clips as accurate measures of the strength of emotional responses to such clips. While as Table 7 indicates, the participants showed just as much average SCL arousal to funny films as to violent films, SCL arousal from funny films did not translate into subjective experiences of pleasant (or anxious) arousal.

Partial Correlations of SCLs During Violent, Sad, and Funny Film Clips (Controlled for Baseline SCL) With Self-Reported Anxious Arousal and Pleasant Arousal During the Film Clips

	Type of film
	Anxious arousal			Pleasant arousal
SCL period	Violent	Sad	Funny	Violent	Sad	Funny
T1	.18	.12	.01	−.12	−.05	.05
T2	.19	.01	−.04	−.19	−.06	.01
T3	.17	−.05	−.04	−.15	.11	−.06
T4	.18	−.06	−.07	−.19	.12	.03
T5	.16	−.06	−.06	−.18	.12	.02

Note. N = 303 for the violent film; N = 158 for the sad film; N = 145 for the funny film. SCL = skin conductance level; T1 = mean across the first 15 s of the first critical scene; T2 = mean across the rest of the first critical scene; T3 = mean between the first and second critical scenes; T4 = mean across the first 15 s of the second critical scene; T5 = mean across the rest of the second critical scene.

Comparison of Mean SCL Arousal for Violent Films With Mean Arousal for Sad and Funny Films

SCL period	Violent film ( = 303)	Sad film ( = 158)	Funny film ( = 145)
T1	2.86 (0.58)	2.77 (0.61)	2.76 (0.53)
T2	2.85 (0.57)	2.69 (0.69)	2.73 (0.53)
T3	2.79 (0.55)	2.65 (0.64)	2.72 (0.54)
T4	2.79 (0.56)	2.65 (0.64)	2.72 (0.55)
T5	2.74 (0.56)	2.65 (0.64)	2.72 (0.55)

MANOVA comparison with violent clip		(5, 152) = 2.66, < .05	(5, 139) = 1.99, n.s.

Note . Means (shown with standard deviations) for violent and sad films are different at p < .05 for every SCL period; means for violent and funny films are not significantly different for any SCL period. SCL = skin conductance level; T1 = mean across the first 15 s of the first critical scene; T2 = mean across the rest of the first critical scene; T3 = mean between the first and second critical scenes; T4 = mean across the first 15 s of the second critical scene; T5 = mean across the rest of the second critical scene; MANOVA = multivariate analysis of variance; n.s. = nonsignificant.

The analyses addressing our hypotheses are reported in three steps: First, to examine the proposed links between habitual media violence usage and situationally induced arousal and affect, we report the bivariate correlations between past media violence exposure and physiological arousal (Hypothesis 1) as well as self-reported affect (Hypothesis 2) in response to the three types of films. Second, situational arousal and affect elicited by the violent clip are linked to aggressive cognitions and aggressive behavior, placing them in the context of other relevant predictors. A series of multivariate path analyses that includes trait aggression, trait arousability, and aggressive norms is reported to assess the independent contribution of desensitization to the prediction of aggressive cognitions and proactive/unprovoked as well as reactive/provoked aggression (Hypothesis 3). Finally, we contrast responses to the violent clips with those to the sad and funny clips to address the issue of the content specificity of desensitization (Hypothesis 4).

Relation of Media Violence Exposure With Physiological Arousal to Film Clips (Hypothesis 1)

To control for individual differences in characteristic SCL, we computed partial correlations (controlling for baseline SCL) between habitual media violence exposure and the five SCL indices into which the continuous SCL data were divided. As there were no gender differences in SCL reactions to the films, genders were combined for this analysis. The results are displayed in Table 6 . As predicted, habitual media violence exposure showed significant negative correlations with each of the five indices for violent clips, indicating that the more participants were used to media violence, the less physiological response they showed in the course of watching the violent clip. This finding supports the desensitization hypothesis for violent media. Table 6 further reveals that habitual exposure to media violence was also associated with reduced physiological arousal to sad scenes, indicating that habituation at the physiological levels in those who use a lot of media violence occurs for sad as well as violent content. However, media violence exposure did not correlate with SCL for funny films.

Partial Correlations of Habitual Media Violence Exposure With SCLs During Violent, Sad, and Funny Film Clips (Controlling for Baseline SCL)

	Type of film
SCL period	Violent ( = 303)	Sad ( = 158)	Funny ( = 145)
T1	−.14	−.22	.11
T2	−.17	−.19	.04
T3	−.19	−.16	−.04
T4	−.21	−.17	.00
T5	−.23	−.21	.03

Note . N = 303 for the violent film; N = 158 for the sad film; N = 145 for the funny film. SCL = skin conductance level; T1 = mean across the first 15 s of the first critical scene; T2 = mean across the rest of the first critical scene; T3 = mean between the first and second critical scenes; T4 = mean across the first 15 s of the second critical scene; T5 = mean across the rest of the second critical scene.

Relations of Media Violence Exposure With Self-Reports of Arousal to Film Clips (Hypothesis 2)

Our desensitization hypothesis predicted that the more participants habitually used media violence, the more pleasant and the less anxious arousal they would experience when viewing the violent clip. As shown in Table 4 , a positive correlation was found for both genders between media violence exposure and pleasant arousal. The correlations with anxious arousal were in the predicted direction but were only marginally significant for women and failed to reach significance for men. When the data from both genders were combined, media violence exposure correlated with self-reports of pleasant arousal to the violent clips, r (302) = .26, p < .001, and with self-reports of anxious arousal to the violent clips, r (303) = −.17, p < .01. The correlations of habitual media violence exposure with anxious and pleasant arousal following the sad and funny clips were nonsignificant: sad films: anxious arousal, r (158) = −.08, p = .35; pleasant arousal, r (158) = −.04, p = .57; funny films: anxious arousal, r (145) = −.11, p = .19; pleasant arousal, r (145) = .09, p = .31. Although, due to the smaller sample sizes, the power of these significance tests with sad and funny films is less than the tests with violent films, none of the obtained correlations would have been significant even if the sample size had been doubled. Thus, Hypothesis 2 is confirmed by the data.

Relations of Self-Reports of Arousal to Violent Film Clip With Situational Aggression (Hypothesis 3)

None of the five SCL indices of emotional arousal to violent clips correlated significantly with reaction times for aggressive words in the subsequent lexical decision task or with the intensity of noise blasts in the competitive reaction time task. Consequently, to investigate relations between arousal to the violent films and state aggression outcomes, we examined subjective appraisals by participants of the quality of their arousal in terms of anxiety or enjoyment.

From our theoretical perspective, individual differences in anxious and pleasant arousal while viewing violent clips should be related to individual differences in immediate aggression after viewing violent clips over and above the impact of dispositional variables, such as trait aggression, trait arousability, and normative acceptance of aggression. The pattern of correlations in Table 4 suggests that one needs to examine the relations in a multivariate context to be able to identify the unique role of desensitization. First, pleasant and anxious arousal correlated with each other, for women, r (88) = −.39, p < .001; for men, r (215) = −.43, p < .001. Second, trait arousability correlated positively with anxious arousal for both genders and negatively with pleasant arousal and positively with trait aggression for men. Third, trait arousability correlated negatively with media violence exposure in women but not at all in men. This suggests that one needs to test the relations with a multivariate model taking account of gender. To review, we had hypothesized that habitual exposure to media violence would be linked to reduced anxious arousal and increased pleasant arousal in response to violent film clips. Furthermore, we predicted that increased pleasant arousal and reduced anxious arousal in response to a violent film clip would be associated with lower reaction times for recognizing aggressive words and a greater readiness to engage in unprovoked aggressive behavior. The relations were hypothesized to be independent of the correlations of aggressive cognitions and behavior with trait aggression, trait arousability, and aggressive normative beliefs.

These hypotheses were examined with the three path analyses shown in Figure 1 , one for reaction time for recognizing aggressive words as the outcome variable, one for unprovoked aggression in the competitive reaction time task as the outcome, and one for provoked aggression as the outcome. The distinction between unprovoked and provoked aggression is critical for the present analysis, because the unprovoked aggression measure is thought to provide a more conclusive test of the role of habitual media violence exposure unaffected by the alleged actions of another person. On the basis of this conceptual argument, separate analyses were conducted for unprovoked and provoked aggression as outcome variables. Because trait aggression, aggressive beliefs, and trait arousability were shown above to be correlated with the key elements in the models, they were also included. The analyses were carried out with the Mplus software ( Muthén & Muthén, 2007 ).

An external file that holds a picture, illustration, etc.
Object name is nihms708569f1.jpg

Path analyses predicting aggressive cognitions (top), unprovoked aggressive behavior (middle), and provoked aggressive behavior (bottom) as a function of arousal during the violent clips, self-reports of media violence viewing, and other dispositional variables.

First, the models were estimated as two-group models, with gender being the grouping variable to allow for gender differences. However, a comparison of the two-group models with the models without gender as a grouping variable on the basis of Bayesian information criterion scores showed no significant advantage in fit for the two-group models. Therefore, single-group models were estimated and are shown in Figure 1 . All three single-group models fitted the data well with nonsignificant chi-square values and cumulative fit indices above .99.

The path model for predicting aggressive cognition (reaction times for recognizing aggressive words) showed good fit, χ 2 / df = 1.07, p = .37, comparative fit index (CFI) = 0.99, root-mean-square error of approximation (RMSEA) = .02, standardized root-mean-square residual (SRMR) = .02. The more media violence participants used habitually, the shorter their reaction times in recognizing aggression-related words, independently of the remaining dispositional variables included in the model. Participants who watched more media violence scored significantly higher on pleasant arousal and nonsignificantly lower on anxious arousal. Greater pleasant arousal while viewing the violent clips was linked to shorter reaction times for recognizing aggressive words, but the path fell short of significance ( p < .10). The total effect of habitual media violence exposure on reaction times was −.20 ( p < .001), consisting of the direct link of −.17 ( p < .01) and a marginally significant indirect link via pleasant arousal of −.02 ( p = .07).

Anxious arousal predicted slightly longer reaction times, but the path was not significant. Anxious arousal was highly negatively correlated with pleasant arousal. These links were independent of the paths from trait arousability to higher anxious arousal and lower pleasant arousal. Overall, these results are consistent with the assumption that media violence exposure desensitized viewers so they responded with more pleasant arousal (highly correlated with less anxious arousal), which in turn increased the availability of aggressive cognitions. These processes operated in parallel with other independent pathways from trait aggression and media violence usage (e.g., observational learning) to increased accessibility of aggression cognitions.

The path model for unprovoked aggression in the laboratory task after exposure to the violent film clips also showed a good fit, χ 2 / df = .88, p = .49, CFI = 1.00, RMSEA = .00, SRMR = .02. Participants who viewed more media violence experienced significantly more pleasant arousal (.17, p < .001) while watching violent clips, which was highly negatively correlated (−.41, p < .001) with anxious arousal. Lower anxious arousal was significantly (−.14, p < .05) related to more unprovoked aggressive responding in the competitive reaction time tasks. Again, these links were independent of the significant paths from trait arousability on pleasant and anxious arousal in the film task and of trait aggression on unprovoked aggressive responding in the laboratory task. No significant indirect links via pleasant or anxious arousal were found for unprovoked aggression.

Finally, the path model for provoked aggression in the competitive reaction time revealed that lower anxious arousal and greater pleasant arousal to scenes of violence did not play a major role in reactive provoked aggression, χ 2 / df = 1.17, p = .32, CFI = 0.99, RMSEA = .03, SRMR = .02. Neither of the paths from the self-report arousal measures to the aggression measure were significant. The model also showed that normative beliefs approving of aggression were directly linked with provoked aggression. The direct link from trait aggression was not significant, but trait aggression was highly correlated with normative beliefs approving of aggression.

Examining the Content Specificity of Desensitization (Hypothesis 4)

Physiological arousal to the different kinds of film clips.

The means for the five SCL indices during the film clips are presented in Table 7 . The baseline SCL had a mean of 2.70 ( SD = 0.56). The five SCL scores for violent films were significantly higher than those for sad films, multivariate F (5, 152) = 2.66, p < .05, partial η 2 = .08 (all univariate effects significant at p < .05). The five SCL scores for the funny films were not significantly different from those for the violent films, multivariate F (5, 139) = 1.99, p = .09 (all univariate effects not significant). Thus, we conclude that the sad films stimulated less physiological arousal than the violent clips but the funny films stimulated about the same amount of physiological arousal as the violent clips.

Self-reports of arousal to the different kinds of film clips

According to our script theory of desensitization, media violence exposure should be associated with desensitization of anxious arousal to violent films and corresponding increases in pleasant arousal, but the desensitization should be specific to arousal during violent clips. To examine this prediction, we computed the mean arousal scores during the violent clips for high and low media violence viewers and compared those means with the mean arousal scores for high and low violence viewers during the sad and funny clips. To compare the means we conducted a mixed factorial multivariate analysis of variance with habitual media violence exposure (high vs. low; defined via median split) as between-subjects factor and film type as within-subjects factor, using the two arousal measures (anxious, pleasant) as dependent variables. Because only half of the sample watched the sad and funny comparison clips, respectively, separate analyses had to be conducted for comparing violent with sad and violent with funny films.

For the comparison of violent vs. sad films, the analysis yielded a significant multivariate effect of film type, F (2, 155) = 53.85, p < .001, partial η 2 = .41. Both univariate effects were significant, with violent films producing greater anxious arousal ( M = 1.75, SE = 0.14) than sad films ( M = 0.86, SE = 0.11), F (1, 156) = 38.69, p < .001, partial η 2 = .20. Violent films also produced less pleasant arousal ( M = 1.49, SE = 0.10) than did sad films ( M = 2.93, SE = 0.10), F (1, 156) = 95.46, p < .001, partial η 2 = .38. The multivariate main effect of habitual media violence exposure was also significant, F (2, 155) = 4.46, p < .05, partial η 2 = .05. Here, the univariate effect for anxious arousal was significant Participants with high media violence exposure reported lower anxious arousal ( M = 1.00, SE = 0.15) than did those low on habitual media violence exposure ( M = 1.61, SE = 0.14), F (1, 156) = 8.55, p < .001, partial η 2 = .05. The univariate effect for pleasant arousal was marginally significant ( M = 2.10, SE = 0.09, in the low media violence exposure group and M = 2.32, SE = 0.09, in the high media violence exposure group), F (1, 156) = 2.76, p < .10, partial η 2 = .02. However, the two main effects were qualified by a significant multivariate interaction effect, F (2, 155) = 4.68, p < .05, partial η 2 = .06. The means are shown in the top panel of Figure 2 . Follow-up t -tests indicated that the high and low media violence exposure groups differed significantly for the violent films but not for the sad films on anxious arousal, t (156) = 2.78, p < .01, and on pleasant arousal, t (156) = −3.23, p < .01. These findings indicate that, as we predicted, participants high in habitual exposure to media violence showed a more positive response to violent scenes than those low in media violence exposure, but the high and low media violence viewers showed no difference in their responses to sad films.

An external file that holds a picture, illustration, etc.
Object name is nihms708569f2.jpg

Bar graphs comparing mean anxious and pleasant arousal during violent versus sad clips (top panel) and violent versus funny clips (bottom panel). MVE = habitual media violence exposure.

The comparison of violent and funny films also yielded a significant multivariate effect of film type, F (2, 141) = 369.47, p < .001, partial η 2 = .84. Both univariate effects were significant, with violent films producing greater anxious arousal ( M = 1.80, SE = 0.14) than funny films ( M = 0.07, SE = 0.04), F (1, 142) = 151.93, p < .001, partial η 2 = .52, and violent films also producing less pleasant arousal ( M = 1.48, SE = 0.12) than funny films ( M = 5.22, SE = 0.08), F (1, 142) = 712.07, p < .001, partial η 2 = .83. A second significant multivariate main effect was found for habitual media violence exposure, F (2, 141) = 6.57, p < .01, partial η 2 = .09. Both univariate effects were significant. Participants with high media violence exposure reported lower anxious arousal ( M = 0.68, SE = 0.11) than did those low on habitual media violence exposure ( M = 1.19, SE = 0.11), F (1, 142) = 10.81, p < .01, partial η 2 = .07. They also showed higher pleasant arousal ( M = 3.55, SE = 0.09, in the high exposure group, M = 3.16, SE = 0.11, in the low exposure group), F (1, 142) = 7.55, p < .01, partial η 2 = .05. However, the two main effects were qualified by a significant multivariate interaction, F (2, 142) = 4.66, p < .01, partial η 2 = .06, and both univariate effects were significant, F (1, 142) = 6.71, p < .05, partial η 2 = .05, for anxious arousal; F (1, 142) = 5.05, p < .05, partial η 2 = .03, for pleasant arousal. The means are shown in the bottom panel of Figure 2 . Follow-up t -tests indicated that the high and low media violence exposure groups differed significantly for the violent films but not for the funny films on anxious arousal, t (142) = 2.99, p < .01, and on pleasant arousal, t (142) = −3.08, p < .01. Again, these findings indicate that, as predicted, participants high in habitual exposure to media violence showed a more positive response to violent scenes than those low in media violence exposure, but media violence exposure did not affect responses to funny films.

Self-reported arousal and situational aggression

The final set of analyses compared the pathways from anxious and pleasant arousal to aggressive cognitions and behavior for the three film types in a set of multiple regression analyses. We predicted that the paths from emotional arousal during viewing the clips to subsequent aggressive cognitions and behavior should be specific to violent clips. The first analysis regressed reaction times for aggressive words (controlled for nonaggressive and nonwords) on anxious arousal in response to violent and funny films. The analysis showed that anxious arousal to violent films significantly predicted reaction times for aggressive words (β = .21, p < .05; the higher the anxious arousal, the longer it took to recognize an aggressive word), but anxious arousal to funny films did not predict reaction times (β = .03). The second analysis examined pleasant arousal to violent and funny films. Pleasant arousal to violent films significantly predicted reaction times for aggressive words (β = −.23, p < .01; the higher the pleasant arousal, the less time it took to recognize aggressive words), but pleasant arousal to funny films did not predict reaction times (β = .11). Finally, for the sad films neither anxious arousal (β = .01) nor pleasant arousal (β = −.03) predicted reaction times for aggressive words. In combination, the findings indicate that individual differences in responsiveness to emotionally arousing material had a content-specific effect on the accessibility of aggressive cognitions and could not be demonstrated for other arousing stimuli.

A parallel set of regression analyses was conducted for unprovoked aggressive behavior as an outcome variable. Higher anxious arousal to violent clips predicted significantly lower levels of unprovoked immediate aggression (β = −.23, p < .01), but higher anxious arousal to funny clips (β = −.06) and sad clips (β = −.03) did not. Similarly, higher pleasant arousal to violent films predicted significantly higher levels of unprovoked immediate aggression (β = .17, p < .05), but again pleasant arousal to sad films did not (β = .06), though pleasant arousal to funny films did predict significantly lower aggressive behavior (β = −.19, p < .05). These findings support the hypothesis that the likelihood of aggressive behavior is increased by desensitization to violent scenes and generally not predicted by desensitization to other kinds of scenes.

A last set of regression analyses compared the three types of film as predictors of provoked aggression. Anxious arousal to violent, sad, or funny films failed to predict provoked aggression, and pleasant arousal to violent and sad clips was also unrelated to provoked aggression. The only significant finding was that pleasant arousal to funny films was negatively related to provoked aggression (β = −.19, p < .05), paralleling the finding for unprovoked aggression.

In summary, the majority of our predictions were confirmed by the data. Fully supporting Hypothesis 1, habitual media violence exposure showed consistent negative associations with SCL measured at five points in time during exposure to a violent film clip. Partial support was found for Hypothesis 2 predicting lower anxious arousal and higher pleasant arousal to the violent film in participants high on habitual media violence usage. The predicted direct links were found for pleasant arousal but not for anxious arousal. Hypothesis 3 predicted that participants showing higher pleasant arousal and lower anxious arousal to the violent film would respond faster to aggressive words in a lexical decision task and show more unprovoked aggression in the competitive reaction time task. This prediction was confirmed for the link between pleasant arousal and response latencies to aggressive words and for the link between anxious arousal and unprovoked aggression, lending partial support to the hypothesis. Finally, Hypothesis 4, predicting that the links between habitual media violence usage, responses to the film clips, and aggressive thoughts as well as behavior would be dependent on the violent content and not found for other emotionally charged media stimuli, was also mostly supported by the data.

The debate about the potential of media violence to increase aggression is far from being over, as reflected in a recent issue of Psychological Bulletin ( Anderson et al., 2010 ; Bushman et al., 2010 ; Ferguson & Kilburn, 2010 ; Huesmann, 2010 ) and in a 2008 special issue of the American Behavioral Scientist , in which Grimes, Anderson, and Bergen (2008) accused “causationists” of “the attempt of making ideology a science” (p. 213). The present research was not designed to settle this question, although we believe that the prior research strongly favors the conclusion of causation. Rather, the present research was designed to investigate the role that emotional desensitization to depictions of violence might play as a potential process variable in the link between media violence and aggression. The study explored desensitization both as an outcome of habitual media violence usage and as a situational antecedent of aggressive cognitions and behavior. Furthermore, it included both SCL and subjectively experienced affect as indicators of desensitization and considered both negatively and positively valenced affective responses. Finally, it compared violent clips with two other types of arousing media stimuli, namely, sad and funny films, to examine the content specificity of the effects.

In support of our hypotheses and in line with previous research, reviewed in the introduction, the findings provide some support for the desensitization hypotheses. Our findings suggest that the more individuals habitually used violent media contents, the less physiological reactivity they showed to a violent film clip presented to them in a laboratory setting. For women there was also a significant link between greater habitual media violence exposure and greater pleasant arousal in response to the violent film. For men, the correlation was in the same direction but was only marginally significant. For men there was a significant correlation between greater habitual media violence exposure and more rapid accessibility of aggressive cognitions after viewing the violent film clip. For women, the correlation was in the same direction but was only marginally significant.

Although significant correlations were found between SCL and the subjectively experienced ratings of anxious and pleasant arousal, when examined on their own, physiological responses reflecting the intensity of arousal turned out to be unrelated to subsequent aggressive cognitions and behavior. The failure to find any links of SCL with aggressive cognitions and behavior ties in with prior research that found little evidence of a link between physiological arousal and laboratory-induced aggression ( Patrick & Verona, 2007 ). Research on psychopathy points to a link between habitual electrodermal hyporeactivity and higher aggression ( Scarpa & Raine, 2007 ) as well as low anxiety combined with higher information processing deficits (for a review see Fowles, 2000 ). However, the short-term variations in SCL observed in the present study did not covary with differences in aggressive cognitions and behavior. Our data suggest that it is the qualitative aspect of arousal that is needed to understand the role of desensitization by negative affect and sensitization by positive affect in aggressive cognitions and behavior following exposure to violent media stimuli. When we examined self-reports of emotional reactions to the films, we found that anxious arousal to the violent clip was lower and pleasant arousal was higher among heavy users of media violence than among low media violence users, also indicating that habitual media violence usage is linked to desensitization of negative and sensitization of positive affect in response to violent media stimuli.

In moving beyond bivariate relationships to examine the role of media violence usage in the context of other dispositional predictors of aggressive cognitions and behavior, path analysis was used. This is a common approach in research designed to identify the specific contribution of media violence exposure to aggression-related outcome variables controlling for other relevant predictors (e.g., Ferguson et al., 2008 ). For response latencies in the lexical decision task, a significant direct path was found from habitual media violence exposure to recognition times for aggressive words. In addition, there was evidence of an indirect pathway through higher pleasant arousal which in turn showed a marginally significant negative link with recognition times. For unprovoked aggression as outcome variable, no direct or indirect links were found with habitual media violence exposure, but a significant negative link was found with anxious arousal. Of the dispositional measures, trait aggression was positively related to unprovoked aggression. Finally, in the path model for provoked aggression, the trait of acceptance of aggression as normative was the only significant predictor. Neither habitual media violence exposure nor the affective responses to the violent clips were significantly related to provoked aggression.

Although not all predicted links between habitual media violence exposure, situational arousal, and aggressive cognitions and behavior were confirmed, the present data provide significant support for the claim that habitual users of media violence become desensitized to violence as evidenced in higher self-reported pleasant arousal to scenes of violence in the media. There is also some indication that differences in pleasant arousal, associated with differences in habitual media violence exposure, affect the speed with which individuals access aggressive cognitions and the likelihood of engaging in unprovoked aggression in the noise blast task. Results were less conclusive with respect to the role of reduced anxious arousal. Lower anxious arousal in response to the violent clip predicted higher scores of unprovoked aggression, but the level of anxious arousal in our study was unrelated to habitual media violence exposure. There was no evidence in the present data that emotional responses to the violent film were related to provoked aggression or that SCL measures of physiological arousal were linked to the aggression-related outcome variables.

The associations observed between media violence exposure, emotional responses to the film clips, and aggression-related outcome variables were specific to violent media stimuli and were not apparent for other emotionally charged stimuli, such as sad or funny film clips. Lower anxious arousal and higher pleasant arousal to violent clips but not to sad or funny clips predicted faster recognition of aggressive words. Lower anxious arousal to violent but not to sad or funny clips predicted higher unprovoked aggression, as did higher pleasant arousal to violent but not to sad films. One exception was the finding that habitual media violence exposure was not only correlated with reduced physiological arousal to the violent film clips but also correlated with reduced arousal to the sad clips. The latter finding can be attributed to the conceptual overlap between the themes of violence and death in the violent and sad clips. Violent media stimuli are closely related to the theme of death, and the two sad film clips used in our study centered on the death of a beloved person, so the finding that reduced responsiveness at the physiological level was also found for the sad clips is compatible with the desensitization hypothesis. Another unexpected result was that higher pleasant arousal to funny films predicted reduced aggression. However, this result is consistent with the theory that when emotions incompatible with aggression are stimulated, aggression becomes less likely ( Tyson, 1998 ).

The links of pleasant and anxious arousal to the aggression outcomes occurred independently of the dispositional variables that were measured. Trait aggression showed independent direct paths on reaction times and unprovoked aggression; media violence exposure directly predicted the reaction time for recognizing aggressive words; trait arousability was a positive predictor of anxious arousal and a negative predictor of pleasant arousal; and normative beliefs approving of aggression directly predicted provoked (reactive) aggressive behavior. Also as expected, trait aggression was significantly correlated with media violence exposure and normative beliefs approving of aggression. The hypothesized paths from media violence exposure through arousal reactions to violent clips to the aggression outcomes occurred independently of these relations.

Physiological arousal to violent clips, as measured by SCL, was lower the more participants habitually used media violence. Within the experimental situation, SCL during the violent scenes was positively correlated with anxious arousal and negatively correlated with pleasant arousal. This finding fits with a study by Ravaja, Saari, Salminen, Laarni, and Kallinen (2006) , who analyzed patterns of SCL during video game play in relation to predefined positive and negative game events and found higher SCL responses to negative than to positive events. In understanding this pattern, dimensional models of emotion that differentiate between activation (physiological arousal) and valence (perceived pleasant or unpleasant quality; Ravaja, 2004 ) may be useful. In the dimensional model proposed by Larsen and Diener (1992) , for example, fear is regarded as an emotion that is high in activation and negative in valence, whereas happiness/satisfaction is considered to be of medium activation at the positive end of the valence dimension. Thus, fear/anxiety is seen as being associated with high activation, whereas happiness/satisfaction is seen as being associated with a lower level of activation. The negative correlation between subjective ratings of anxious arousal and pleasant arousal corroborates the theoretical conceptualization of the two emotional responses as opposite ends of the valence continuum. The dimensional model can also be used to explain the finding that the five SCL indices were higher during the violent clips than during the sad clips. Sadness and fear are both negatively valenced emotions but they differ in activation, with fear being at the high end and sadness being close to the midpoint of this dimension.

In our data, differences in physiological arousal during the violent film clips were unrelated to differences in the subsequent lexical decision and noise blast tasks, but differences in the qualitative indices of anxious and pleasant arousal mostly showed the expected relations with aggressive cognitions and behavior. The lack of relationships between SCL in response to violent films and subsequent aggressive cognitions and behavior is at odds with meta-analytic evidence by Anderson and Bushman (2001) . However, their analysis was restricted to interactive video games, whereas the present study involved passive reception of filmed violence. Studies comparing active playing of video games and merely observing the violent contents by watching the players showed that active playing produced higher levels of arousal than passive observation of identical content did ( Calvert & Tan, 1994 ). Furthermore, none of the seven studies included in Anderson and Bushman’s (2001) meta-analysis used SCL as a measure of arousal. Past research has been inconsistent with regard to the relationship between SCL and self-reported affect. Over a 3-week period, Ballard et al. (2006) found evidence of decreased reactivity to video game exposure (regardless of violent content) at the physiological level but not at the level of affective responses. Arriaga et al. (2006) compared both physiological arousal and affect over a much shorter game-playing period of 4 min, finding differences between violent and nonviolent game players in affective responses but not at the physiological level. Our study was more similar in design to the Arriaga study in that our film clips were of similar length to their game-playing periods, and we also found little evidence of desensitization at the physiological level but more evidence at the affective level. In any case, clarifying the relative contribution of physiological arousal and experienced affect is an important task for future research.

Several limitations must be noted about this study. The first is that whereas SCL was recorded continuously during exposure to the film clips, the qualitative measures of anxious and pleasant arousal were obtained immediately after the film clips had ended. Reliance on self-reports to yield these measures made continuous assessment impossible as it would have distracted from watching the films. Other methodological approaches, such as recording physical responses indicative of the quality of arousal, would be required to overcome this problem. The study by Ravaja et al. (2006) , who combined SCL with the electromyographic recording of facial muscle movements as a continuous measure of quality of arousal during video game playing, illustrates this possibility.

A second limitation was that transfer effects of reduced arousal during the violent clip to reduced arousal to depictions of real-life violence were not considered. Our focus was on the disinhibiting effect of reduced anxious reactivity on aggressive cognitions and behavior, but it would also be critically important to demonstrate that reduced negative affect as a result of exposure to media violence leads to reduced arousal by real-life violence and reduced empathy with victims. Carnagey et al. (2007) demonstrated that participants who had previously played a violent game showed less arousal in response to real-life violence than those who had played a nonviolent game. However, they presented the depictions of real-life violence immediately after the game-playing session, so nothing can be said on the basis of that study about the duration of desensitization, nor about any cumulative effects. Further research combining measures of habitual media violence exposure and situational desensitization are needed to clarify these issues.

Third, although the noise blast test is a tried and tested method of measuring aggression in the laboratory and there is evidence of a high convergence between laboratory and field studies of aggression ( Anderson, Lindsay, & Bushman, 1999 ), no inferences can be derived from the present laboratory data to aggression in natural contexts. In addition, unprovoked aggression was represented by a single-item measure due to the interactive design of the noise blast task, which makes all responses from the second trial onward contingent upon the initial response by the alleged opponent. Therefore, the findings should be substantiated by other measures of unprovoked aggressive behavior with known reliability. At the same time, this weakness should not obscure the fact that for the male participants at least, the measure of trait aggression, representing their “real-world aggression”, was correlated both with their habitual media violence exposure and with their aggressive behavior on the laboratory task.

Fourth, and perhaps most important theoretically, no short-term field or laboratory study can determine with certainty that the relation between an individual’s history of media violence exposure and current emotional reactions to violent clips is due to desensitization. A plausible alternative hypothesis will always be that dispositional factors promote both the different emotional reactions and the exposure to media violence. However, in the current study we controlled for the most plausible dispositional “third variables” that might be alternatives (trait aggression, trait arousability, and beliefs accepting aggression as normative) and found that habitual media violence exposure predicted desensitization independently of these dispositions.

Finally, the present study was limited in that only responses to passive media exposure were studied. A number of recent studies have looked at desensitization in response to violent video game usage that entails a much more active involvement of players. There is evidence from this research that immersion in the violent events of the game, for example by playing with a virtual reality device, is a critical variable with respect to arousal ( Arriaga et al., 2006 ), but it is as yet unclear how such increased arousal potential affects desensitization. Moreover, studies are needed that compare passive reception of and active involvement in violent events in the virtual reality of the media in terms of their desensitizing potential (see Ballard et al., 2006 ).

Despite these limitations, the present findings can provide some new insights into the dynamics of affective reactivity to media violence. Several, yet not all, of the findings support our theorizing that weakening fear and anxiety in response to media violence (and the concomitant increase in pleasant emotions) through repeated exposure promotes aggression-enhancing cognitions and, ultimately, the likelihood of initiating proactive aggressive behavior. Our results further suggest that the relations are contingent upon the violent content of the media stimuli, as evidenced by the comparison with sad and funny clips that are also emotionally arousing. The findings join a growing body of research directed at elucidating the processes by which exposure to violent media stimuli may impact aggression, moving on from the issue of whether or not media violence exposure is linked to aggression to a better understanding of the psychological mechanisms that may explain such a link.

Acknowledgments

The research reported in this paper was supported by German Research Foundation Grant Kr 972/8-1 to Barbara Krahé. The support of Annika Bergunde, Cathleen Kappes, Julia Kleinwa¨chter, Kaspar Schattke, and Jessica Wenzlaff is gratefully acknowledged.

1 Although different participants, if asked, might think of any one specific program as falling into multiple genres (e.g., action–adventure vs. military–war), this is unlikely to produce much difference in violence exposure scores when the participants are being asked about frequency of media genres. The self-reports of how often genres are used are more subjective self-perceptions that allow the same media game or movie to influence frequencies of multiple categories. For example, if asked about their viewing of war–military genres, participants who have watched The Matrix are likely to think of it as in that category. When asked about science fiction or action, the participants are likely to think of The Matrix as in those genres. Thus, self-reported viewing frequencies for all three categories are likely to be increased. However, because the overall violence viewing score for a participant is the average of the violence viewing scores for genres, the contribution to the participant’s overall violence viewing score will actually be lower than that for another participant who perceives The Matrix only as military–war, which has a higher violence rating. We consider this property of our rating system desirable, as perceiving a game or movie only in a more violent genre probably indicates more of a focus on the violence.

2 All film clips are available in both German and English and can be obtained from the first author.

3 The total length of the SCL measurement prior to the presentation of the film clips was 90 s. The first 10 s were discarded from the analyses to clean the data from fluctuations due to movements and orienting responses at the start of the recording, leaving a baseline period of 80 s.

Contributor Information

Barbara Krahé, Department of Psychology, University of Potsdam, Potsdam, Germany.

Ingrid Möller, Department of Psychology, University of Potsdam, Potsdam, Germany.

L. Rowell Huesmann, Institute for Social Research, University of Michigan.

Lucyna Kirwil, Department of Social Psychology, Warsaw School of Social Sciences and Humanities, Warsaw, Poland.

Juliane Felber, Department of Psychology, University of Potsdam, Potsdam, Germany.

Anja Berger, Department of Psychology, University of Potsdam, Potsdam, Germany.

Anderson CA, Berkowitz L, Donnerstein E, Huesmann LR, Johnson JD, Linz D, Wartella E. The influence of media violence on youth. Psychological Science in the Public Interest. 2003; 4 :81–110. [ PubMed ] [ Google Scholar ]
Anderson CA, Bushman BJ. External validity of “trivial” experiments: The case of laboratory aggression. Review of General Psychology. 1997; 1 :19–41. [ Google Scholar ]
Anderson CA, Bushman BJ. Effects of violent video games on aggressive behavior, aggressive cognition, aggressive affect, physiological arousal, and prosocial behavior: A meta-analytic review of the scientific literature. Psychological Science. 2001; 12 :353–359. [ PubMed ] [ Google Scholar ]
Anderson CA, Carnagey NL, Flanagan M, Benjamin AJ, Eubanks J, Valentine JC. Violent video games: Specific effects of violent content on aggressive thoughts and behavior. Advances in Experimental Social Psychology. 2004; 36 :199–249. [ Google Scholar ]
Anderson CA, Dill KE. Video games and aggressive thoughts, feelings, and behavior in the laboratory and in life. Journal of Personality and Social Psychology. 2000; 78 :772–790. [ PubMed ] [ Google Scholar ]
Anderson CA, Lindsay JJ, Bushman B. Research in the psychological laboratory: Truth or triviality. Current Directions in Psychological Science. 1999; 8 :3–9. [ Google Scholar ]
Anderson CA, Shibuya A, Ihori N, Swing EL, Bushman BJ, Sakamoto A, Saleem M. Violent video game effects on aggression, empathy, and prosocial behavior in Eastern and Western countries: A meta-analytic review. Psychological Bulletin. 2010; 136 :151–173. [ PubMed ] [ Google Scholar ]
Arriaga P, Esteves F, Carneiro P, Monteiro MB. Violent computer games and their effects on state hostility and physiological arousal. Aggressive Behavior. 2006; 32 :358–371. [ Google Scholar ]
Averill JR, Malstrom EJ, Koriat A, Lazarus RS. Habituation to complex emotional stimuli. Journal of Abnormal Psychology. 1972; 80 :20–28. [ PubMed ] [ Google Scholar ]
Ballard ME, Hamby RH, Panee CD, Nivens EE. Repeated exposure to video game play results in decreased blood pressure responding. Media Psychology. 2006; 8 :323–341. [ Google Scholar ]
Bandura A. Aggression: A social learning theory analysis. Englewood Cliffs, NJ: Prentice-Hall; 1973. [ Google Scholar ]
Bartholow BD, Bushman BJ, Sestir MR. Chronic violent video game exposure and desensitization to violence: Behavioral and event-related brain potential data. Journal of Experimental Social Psychology. 2006; 42 :532–539. [ Google Scholar ]
Bartholow BD, Sestir MA, Davis EB. Correlates and consequences of exposure to video game violence: Hostile personality, empathy, and aggressive behavior. Personality and Social Psychology Bulletin. 2005; 31 :1573–1586. [ PubMed ] [ Google Scholar ]
Berkowitz L. Some aspects of observed aggression. Journal of Personality and Social Psychology. 1965; 2 :359–369. [ PubMed ] [ Google Scholar ]
Bushman BJ, Huesmann LR. Short-term and long-term effects of violent media on aggression in children and adults. Archives of Pediatrics and Adolescent Medicine. 2006; 160 :348–352. [ PubMed ] [ Google Scholar ]
Bushman BJ, Rothstein HR, Anderson CA. Much ado about something: Violent video game effects and a school of red herring: Reply to Ferguson and Kilburn (2010) . Psychological Bulletin. 2010; 136 :182–187. [ Google Scholar ]
Buss AH, Perry M. The Aggression Questionnaire. Journal of Personality and Social Psychology. 1992; 63 :452–459. [ PubMed ] [ Google Scholar ]
Calvert SL, Tan SL. Impact of virtual reality on young adults’ physiological arousal and aggressive thoughts: Interaction versus observation. Journal of Applied Developmental Psychology. 1994; 15 :125–139. [ Google Scholar ]
Carnagey NL, Anderson CA, Bushman BJ. The effect of video game violence on physiological desensitization to real-life violence. Journal of Experimental Social Psychology. 2007; 43 :489–496. [ Google Scholar ]
Cleese J. Monty Python: Philosophers’ world cup. England: BBC; 1972. (Director). Retrieved from http://www.metacafe.com/watch/yt-92vV3QGagck/monty_python_philosophers_world_cup/ [ Google Scholar ]
Columbus C. Stepmom. 1998 (Director). United States: 1492 Pictures. [ Google Scholar ]
Fanti KH, Vanman E, Henrich CC, Avraamides MN. Desensitization to media violence over a short period of time. Aggressive Behavior. 2009; 35 :179–187. [ PubMed ] [ Google Scholar ]
Ferguson CJ. Evidence for publication bias in video game violence effects literature: A meta-analytic review. Aggression and Violent Behavior. 2007; 12 :470–482. [ Google Scholar ]
Ferguson CJ, Kilburn J. The public health risks of media violence: A meta-analytic review. Journal of Pediatrics. 2009; 154 :759–763. [ PubMed ] [ Google Scholar ]
Ferguson CJ, Kilburn J. Much ado about nothing: The misestimation and overinterpretation of violent video game effects in Eastern and Western nations: Comment on Anderson et al. (2010) . Psychological Bulletin. 2010; 136 :174–178. [ PubMed ] [ Google Scholar ]
Ferguson CJ, Rueda SM, Cruz A, Ferguson DE, Fritz S. Violent video games and aggression: Causal relationship or byproduct of family violence and intrinsic violence motivation? Criminal Justice and Behavior. 2008; 35 :311–332. [ Google Scholar ]
Fowles DC. Electrodermal hyporeactivity and antisocial behavior: Does anxiety mediate the relationship? Journal of Affective Disorders. 2000; 61 :177–189. [ PubMed ] [ Google Scholar ]
Fowles DC, Kochanska G, Murray K. Electrodermal activity and temperament in preschool children. Psychophysiology. 2000; 37 :777–787. [ PubMed ] [ Google Scholar ]
Funk JB, Baldacci HB, Pasold T, Baumgardner J. Violence exposure in real life, video games, television, movies, and the Internet: Is there desensitization? Journal of Adolescence. 2004; 27 :23–39. [ PubMed ] [ Google Scholar ]
Funk JB, Buchman DD, Jenks J, Bechtoldt H. Playing violent video games, desensitization, and moral evaluation in children. Applied Developmental Psychology. 2003; 24 :413–436. [ Google Scholar ]
Geuens M, de Pelsmacker P. Developing a short affect intensity scale. Psychological Reports. 2002; 91 :657–670. [ PubMed ] [ Google Scholar ]
Giancola PR, Parrott DJ. Further evidence for the validity of the Taylor aggression paradigm. Aggressive Behavior. 2008; 34 :214–229. [ PubMed ] [ Google Scholar ]
Grimes T, Anderson JA, Bergen L. Media violence and aggression: Science and ideology. Los Angeles, CA: Sage; 2008. [ Google Scholar ]
Hoffner CA, Levine KJ. Enjoyment of mediated fright and violence: A meta-analysis. Media Psychology. 2005; 7 :207–237. [ Google Scholar ]
Hubbard JA, Parker EH, Ramsden SR, Flanagan KD, Relyea N, Dearing KF, Hyde CT. The relations among observational, physiological, and self-report measures of children’s anger. Social Development. 2004; 13 :14–39. [ PubMed ] [ Google Scholar ]
Hubbard JA, Smithmyer CM, Ramsden SR, Parker EH, Flanagan KD, Dearing KF, Simons RF. Observational, physiological, and self-report measures on children’s anger: Relations to reactive versus proactive aggression. Child Development. 2002; 73 :1101–1118. [ PubMed ] [ Google Scholar ]
Huesmann LR. Television violence and aggressive behavior. In: Pearl D, Bouthilet L, Lazar J, editors. Television and behavior: Ten years of scientific programs and implications for the 80s. Vol. 2. Washington, DC: U.S. Government Printing Office; 1982. pp. 126–137. [ Google Scholar ]
Huesmann LR. An information processing model for the development of aggression. Aggressive Behavior. 1988; 14 :13–24. [ Google Scholar ]
Huesmann LR. Observational learning of violent behavior: Social and biosocial processes. In: Raine A, Brennen PA, Farrington DP, Mednick SA, editors. Biosocial bases of violence. London, England: Plenum; 1997. pp. 69–88. [ Google Scholar ]
Huesmann LR. The impact of electronic media violence: Scientific theory and research. Journal of Adolescent Health. 2007; 41 (Suppl. 1):S6–S13. [ PMC free article ] [ PubMed ] [ Google Scholar ]
Huesmann LR. Nailing the coffin shut on doubts that violent video games stimulate aggression: Comment on Anderson et al. (2010) . Psychological Bulletin. 2010; 136 :179–181. [ PMC free article ] [ PubMed ] [ Google Scholar ]
Huesmann LR, Guerra NG. Children’s normative beliefs about aggression and aggressive behavior. Journal of Personality and Social Psychology. 1997; 72 :408–419. [ PubMed ] [ Google Scholar ]
Huesmann LR, Kirwil L. Why observing violence increases the risk of violent behavior by the observer. In: Flannery DJ, Vazsonyi AT, Waldman I, editors. The Cambridge handbook of violent behavior and aggression. Cambridge, England: Cambridge University Press; 2007. pp. 545–570. [ Google Scholar ]
Huesmann LR, Moise J, Podolski CP, Eron LD. Longitudinal relations between childhood exposure to media violence and adult aggression and violence: 1977-1992. Developmental Psychology. 2003; 39 :201–221. [ PubMed ] [ Google Scholar ]
Huesmann LR, Taylor LD. The case against the case against media violence. In: Gentile D, editor. Media violence and children. Westport, CA: Praeger; 2003. pp. 107–130. [ Google Scholar ]
Jones HE. The longitudinal method in the study of personality. In: Iscoe I, Stevenson HW, editors. Personality development in children. Chicago, IL: University of Chicago Press; 1960. pp. 3–27. [ Google Scholar ]
Jones T. Monty Python’s Life of Brian. United Kingdom: HandMade Films; 1979. (Director) [ Google Scholar ]
Kirwil L. Effects of violent media on emotional arousal and proactive/reactive aggression in young adults. Paper presented at the International Congress of Psychology; Berlin, Germany: Jul, 2008. [ Google Scholar ]
Krahé B, Möller I. Playing violent electronic games, hostile attribution bias, and aggression-related norms in German adolescents. Journal of Adolescence. 2004; 27 :53–69. [ PubMed ] [ Google Scholar ]
Krahé B, Möller I. A German extension of the Aggression Questionnaire as a measure of dispositional aggression. 2010 Manuscript in preparation. [ Google Scholar ]
Lang A, Zhou S, Schwartz N, Bolls PD, Potter RF. The effects of edits on arousal, attention, and memory for television messages: When an edit is an edit can an edit be too much? Journal of Broadcasting & Electronic Media. 2000; 44 :94–109. [ Google Scholar ]
Larsen RJ, Diener E. Promises and problems with the circumplex model of emotion. In: Clark M, editor. Review of personality and social psychology. Vol. 13. Newbury Park, CA: Sage; 1992. pp. 25–59. [ Google Scholar ]
Lorber MF. Psychophysiology of aggression, psychopathy, and conduct problems: A meta-analysis. Psychological Bulletin. 2004; 130 :531–552. [ PubMed ] [ Google Scholar ]
Mehrabian A. Theory and evidence bearing on a scale of trait arousability. Current Psychology. 1995; 14 :3–28. [ Google Scholar ]
Moise-Titus J. The role of negative emotions in the media violence-aggression relation. Dissertation Abstracts International: Section A. Humanities and Social Sciences. 1999; 60 (5-A):1380. [ Google Scholar ]
Mullin CR, Linz D. Desensitization and resensitization to violence against women: Effects of exposure to sexually violent films on judgments of domestic violence victims. Journal of Personality and Social Psychology. 1995; 69 :449–459. [ PubMed ] [ Google Scholar ]
Murray JP. Media violence: The effects are both real and strong. American Behavioral Scientist. 2008; 51 :1212–1230. [ Google Scholar ]
Muthén LK, Muthén BO. Mplus user’s guide. 5th ed. Los Angeles, CA: Author; 2007. [ Google Scholar ]
Paik H, Comstock GA. The effects of television violence on antisocial behavior: A meta-analysis. Communication Research. 1994; 21 :516–546. [ Google Scholar ]
Patrick CJ, Verona E. The psychophysiology of aggression: Autonomic, electrodermal, and neuro-imagining findings. In: Flannery DJ, Vazsonyi AT, Waldman I, editors. The Cambridge handbook of violent behavior and aggression. New York, NY: Cambridge University Press; 2007. pp. 111–150. [ Google Scholar ]
Potts R, Dedmon A, Halford J. Sensation seeking, television viewing motives, and home television patterns. Personality and Individual Differences. 1996; 21 :1081–1084. [ Google Scholar ]
Ravaja N. Contributions of psychophysiology to media research: Review and recommendations. Media Psychology. 2004; 6 :193–235. [ Google Scholar ]
Ravaja N, Saari T, Salminen M, Laarni J, Kallinen K. Phasic emotional reactions to video game events: A psychophysiological investigation. Media Psychology. 2006; 8 :343–367. [ Google Scholar ]
Savage J, Yancey C. The effects of media violence exposure on criminal aggression: A meta-analysis. Criminal Justice and Behavior. 2008; 35 :772–791. [ Google Scholar ]
Scarpa A, Raine A. Biosocial bases of violence. In: Flannery DJ, Vazsonyi AT, Waldman I, editors. The Cambridge handbook of violent behavior and aggression. New York, NY: Cambridge University Press; 2007. pp. 151–169. [ Google Scholar ]
Scorsese M. Casino. United States: Universal Pictures; 1995. (Director) [ Google Scholar ]
Slater MD, Henry KL, Swaim RC, Anderson LL. Violent media content and aggressiveness in adolescents: A downward spiral model. Communication Research. 2003; 30 :713–736. [ Google Scholar ]
Tarantino Q. Reservoir dogs. United States: Live Entertainment; 1992. (Director) [ Google Scholar ]
Tyson PD. Physiological arousal, reactive aggression, and the induction of an incompatible relaxation response. Aggression and Violent Behavior. 1998; 3 :143–158. [ Google Scholar ]
Vossel G. Electrodermal lability, errors, and reaction times: An examination of the motor impulsivity hypothesis. International Journal of Psychophysiology. 1988; 6 :15–24. [ PubMed ] [ Google Scholar ]
Zefferelli F. The champ. 1979. (Director) United States: MGM Entertainment. [ Google Scholar ]
Zillmann D. The psychology of suspense in dramatic exposition. In: Vorderer P, Wulff HJ, Friedrichsen M, editors. Suspense: Conceptualizations, theoretical analyses, and empirical explorations. Mahwah, NJ: Erlbaum; 1996. pp. 199–231. [ Google Scholar ]

Comparing ‘New’ and ‘Old’ Media for Violence Monitoring and Crisis Response in Kenya

Economic and social research council.

VoR (Version of Record)

IDS Item Types

Creditor-on-Creditor Violence and Secured Debt Dynamics

Secured lenders have recently demanded a new condition in distressed debt restructurings: competing secured lenders must lose priority. We model the implications of this “creditor-on-creditor violence” trend. In our dynamic model, secured lenders enjoy higher priority in default. However, secured lenders take value-destroying actions to boost their own recovery: they sell assets inefficiently early. We show that this creates an ex-ante tradeoff between secured and unsecured debt that matches recent empirical evidence. Introducing the recent creditor-conflict trend in this model endogenously increases secured credit spreads. Importantly, it also increases ex-ante total surplus: restructurings endogenously introduce efficient state-contingent debt reduction.

We have nothing to disclose. The views expressed herein are those of the authors and do not necessarily reflect the views of the National Bureau of Economic Research.

MARC RIS BibTeΧ

Download Citation Data

More from NBER

In addition to working papers , the NBER disseminates affiliates’ latest findings through a range of free periodicals — the NBER Reporter , the NBER Digest , the Bulletin on Retirement and Disability , the Bulletin on Health , and the Bulletin on Entrepreneurship — as well as online conference reports , video lectures , and interviews .

2024, 16th Annual Feldstein Lecture, Cecilia E. Rouse," Lessons for Economists from the Pandemic" cover slide

arXiv's Accessibility Forum starts next month!

Help | Advanced Search

Statistics > Applications

Title: broad versus narrow research questions in evidence synthesis: a parallel to (and plea for) estimands.

Abstract: There has been a transition from broad to more specific research questions in the practice of network meta-analysis (NMA). Such convergence is also taking place in the context of individual registrational trials, following the recent introduction of the estimand framework, which is impacting the design, data collection strategy, analysis and interpretation of clinical trials. The language of estimands has much to offer to NMA, particularly given the "narrow" perspective of treatments and target populations taken in health technology assessment.

Comments:	6 pages, discussion paper based on Ades et al. (2024), accepted for publication by Research Synthesis Methods
Subjects:	Applications (stat.AP)
Cite as:	[stat.AP]
	(or [stat.AP] for this version)
	Focus to learn more arXiv-issued DOI via DataCite (pending registration)
:	Focus to learn more DOI(s) linking to related resources

Submission history

Access paper:.

HTML (experimental)
Other Formats

References & Citations

Google Scholar
Semantic Scholar

BibTeX formatted citation

Bibliographic and Citation Tools

Code, data and media associated with this article, recommenders and search tools.

Institution

arXivLabs: experimental projects with community collaborators

arXivLabs is a framework that allows collaborators to develop and share new arXiv features directly on our website.

Both individuals and organizations that work with arXivLabs have embraced and accepted our values of openness, community, excellence, and user data privacy. arXiv is committed to these values and only works with partners that adhere to them.

Have an idea for a project that will add value for arXiv's community? Learn more about arXivLabs .

Today's news
Reviews and deals
Climate change
2024 election
Newsletters
Fall allergies
Health news
Mental health
Sexual health
Family health
So mini ways
Unapologetically
Buying guides

Entertainment

How to Watch
My watchlist
Stock market
Biden economy
Personal finance
Stocks: most active
Stocks: gainers
Stocks: losers
Trending tickers
World indices
US Treasury bonds
Top mutual funds
Highest open interest
Highest implied volatility
Currency converter
Basic materials
Communication services
Consumer cyclical
Consumer defensive
Financial services
Industrials
Real estate
Mutual funds
Credit cards
Balance transfer cards
Cash back cards
Rewards cards
Travel cards
Online checking
High-yield savings
Money market
Home equity loan
Personal loans
Student loans
Options pit
Fantasy football
Pro Pick 'Em
College Pick 'Em
Fantasy baseball
Fantasy hockey
Fantasy basketball
Download the app
Daily fantasy
Scores and schedules
GameChannel
World Baseball Classic
Premier League
CONCACAF League
Champions League
Motorsports
Horse racing

New on Yahoo

Privacy Dashboard

German police hunt festival knife attack suspect

German police on Saturday hunted a man who stabbed three people to death and wounded eight others at a street festival in the city of Solingen, with a terror motive for the attack "not excluded".

The unidentified knifeman went on a rampage in the western town of Solingen late on Friday, as thousands had gathered for the first night of a "Festival of Diversity", part of a series of events to mark the town's 650th anniversary.

On Saturday, police announced they had detained a person as part of the probe, with a prosecutor later saying it was a 15-year-old suspected of "non-denunciation" of a criminal act.

Witnesses had allegedly seen the teen discussing the attack just before it happened with a man who could be the knifeman, said Markus Caspers, prosecutor of Duesseldorf that lies just west of Solingen.

"We have not been able to identify a motive for now, but in view of all of the circumstances, we are working under the assumption that the initial suspicion of a terrorist motive cannot be excluded," Caspers told a press conference.

The people killed were men of 56 and 67 years of age and a 56-year-old woman, officials said.

"The victims were completely unknown with no known ties between them, so based on this we're concluding that it could be a terror act," Caspers said, adding that "no other motive is evident at this time".

Four of the wounded were in a "serious" condition, officials said, revising down an earlier estimate of five.

"After analysing the first images, we're going on the principle that it was an attack targeted toward the neck," police chief Thorsten Fleiss told the press conference.

Interior Minister Nancy Faeser said Germany's "security authorities are doing everything they can to catch the perpetrator" of the "horrific act", while Chancellor Olaf Scholz said he "must be caught quickly and punished".

Thousands of people had gathered in front of a stage on the festival's first night when the killing started.

- 'A person fell' -

"Out of nowhere, a man armed with a knife stabbed people at random and killed them," regional interior minister Herbert Reul said in comments at the scene.

Witness Lars Breitzke told the Solinger Tageblatt newspaper he was a few metres from the attack, not far from the festival stage, and "understood from the expression on the singer's face that something was wrong".

"And then, a metre away from me, a person fell," said Breitzke, who at first thought it was someone who had too much to drink.

When he turned around, he saw other people lying on the ground amid pools of blood.

Solingen mayor Tim-Oliver Kurzbach said the whole city was in "shock, horror and great grief".

"We all wanted to celebrate our town's anniversary together and now we have to mourn the dead and injured," he said.

German Interior Minister Nancy Faeser called for the country to "remain united" as she denounced "those who want to stir up hatred" during a visit to the site of the tragedy. "Let us not be divided", she said.

- 'Brutal and senseless' -

Hendrik Wuest, the premier of North Rhine-Westphalia state, also expressed his "shock and grief" in a post on social media platform X.

"An act of the most brutal and senseless violence has struck at the heart of our state," he said.

Solingen is a city of some 150,000 people located between Duesseldorf and Cologne.

People had gathered in the town on Friday evening for the first day of the three-day "Festival of Diversity".

It was set to feature music, street theatre, variety shows and comedians in the city centre and several other areas, it said.

Up to 75,000 visitors had been expected to attend.

- Festival cancelled -

The Solinger Tageblatt said one of the festival organisers went on stage to announce it was cancelled.

Thousands of people cleared the area, the paper reported, with a journalist at the scene describing the atmosphere as "ghostly".

"People left the scene in shock, but calmly," Philipp Mueller, one of the organisers, told the newspaper.

Mueller said the rest of the festival would also be cancelled.

Germany has seen a series of knife attacks over the past 12 months, with the government promising to crack down on knife crime.

A police officer was killed and five people were wounded in a knife attack at a far-right rally in the city of Mannheim in May.

bur-kas/yad/gv

IMAGES

The History of Media Violence (400 Words)
Violence in Electronic Media Essay Example
(PDF) Media, Violence and the Culture of Victimization: A Sociological
Violence in The Media Promote Violent in Society
Violence in the Media
(PDF) Media Violence Research and Youth Violence Data: Why Do They

COMMENTS

Violent Media in Childhood and Seriously Violent Behavior in Adolescence and Young Adulthood
The current study aims to fill noted research gaps. First, while extant research examines exposure to violence on television and in video games, exposures through other media, such as music, are less well studied yet constitute a large part of youth media diets. ... In this paper, we examine data from baseline (Wave 1) and five years later ...
The Impact of Electronic Media Violence: Scientific Theory and Research
Theoretical Explanations for Media Violence Effects. In order to understand the empirical research implicating violence in electronic media as a threat to society, an understanding of why and how violent media cause aggression is vital. In fact, psychological theories that explain why media violence is such a threat are now well established.
Violence, Media Effects, and Criminology
There have been over 1000 studies on the effects of TV and film violence over the past 40 years. Research on the influence of TV violence on aggression has consistently shown that TV violence increases aggression and social anxiety, cultivates a "mean view" of the world, and negatively impacts real-world behavior. (Helfgott, 2015, p.
Violent media use and aggression: Two longitudinal network studies
ABSTRACT. Exposure to violent media has been widely linked to increased aggression. In the present research, we examined whether violent media exposure would be associated with increased aggression, which would then spread within social networks like a contagious disease. Two groups of first year psychology students completed a questionnaire ...
(PDF) The Influence of Media Violence on Youth
the short term, exposure to media violence causes increases in. children's, adolescents', and young adults' physically and ver-. bally aggressive behavior, as well as in aggression-related ...
Media violence and youth aggression
Most media violence research involves youth aggression rather than violence, noted Douglas Gentile (Iowa State University, Ames, IA, USA). Aggression is defined as any behaviour—physical, verbal, or relational—that is intended to do harm, he said, whereas violence is "a very narrow subtype of aggression that is physical and extreme, [and ...
Content Effects: Violence in the Media
Violent content appears frequently in screen and audio media and takes many forms, including physical and relational aggression, gory images, violent stereotypes, and cyberbullying. Over six decades of research demonstrates that different types of media violence have significant detrimental effects, both immediately and in the long term.
Media Violence: The Effects Are Both Real and Strong
Abstract. Fifty years of research on the effect of TV violence on children leads to the inescapable conclusion that viewing media violence is related to increases in aggressive attitudes, values, and behaviors. The changes in aggression are both short term and long term, and these changes may be mediated by neurological changes in the young viewer.
Ecologies of Violence on Social Media: An Exploration of Practices
Indeed, as access to and use of social media continue to expand across the world (), so does the violence enacted through these digital platforms become more common.For example, a report published by the Pew Research Center (Vogels, 2021) found that over 41% of people in the United States of America have suffered online harassment, from physical threats (14%) and sexual harassment (11%) to ...
Understanding Causality in the Effects of Media Violence
Abstract. This article places media violence research into a broader context than the typical public debate about whether violent video games (or TV programs, or movies) are "the" cause of school shootings and other extreme acts of violence. We describe how scientists today decide whether one variable (e.g., exposure to violent media ...
Reactions to Media Violence: It's in the Brain of the Beholder
Media portraying violence is part of daily exposures. The extent to which violent media exposure impacts brain and behavior has been debated. Yet there is not enough experimental data to inform this debate. We hypothesize that reaction to violent media is critically dependent on personality/trait differences between viewers, where those with the propensity for physical assault will respond to ...
The effects of violent media content on aggression
Abstract. Decades of research have shown that violent media exposure is one risk factor for aggression. This review presents findings from recent cross-sectional, experimental, and longitudinal studies, demonstrating the triangulation of evidence within the field. Importantly, this review also illustrates how media violence research has started ...
The influence of violent media on children and adolescents: a public
16. The aim of this review is to consider research evidence on the effects of violent media on children and adolescents from a public-health perspective. WHO has emphasised the necessity of adopting a public-health approach to the prevention of violence and the reduction of mortality and morbidity in societies. 17.
The Influence of Media Violence on Intimate Partner Violence
Introduction. In the United States, more than 12 million men and women become victims of domestic violence each year [].In fact, every minute, roughly 20 Americans are victimized at the hands of an intimate partner [].Although both men and women are abused by an intimate partner, women have a higher likelihood of such abuse, with those ages 18-34 years being at the highest risk of victimization.
The Impact of Media Violence on Child and Adolescent Aggression
As a result, children and adolescents frequently encounter violence in the media. in a variety of forms, which has an effect on their behavior. Previous research has found that. exposure to media ...
The role of media violence in violent behavior
Abstract. Media violence poses a threat to public health inasmuch as it leads to an increase in real-world violence and aggression. Research shows that fictional television and film violence contribute to both a short-term and a long-term increase in aggression and violence in young viewers. Television news violence also contributes to ...
PDF Media and Violence
The paper highlights where research is scarce, incomplete, or outdated; includes an assessment of the research findings; and offers some thoughts on promising ... Research on the amount of violence in media consumed by children and teenagers is woefully out of date and incomplete. The presence of violent images in advertising seen by chil-dren ...
The Role of Media Violence in Violent Behavior
Abstract Media violence poses a threat to public health inasmuch as it leads to an increase in real-world violence and aggression. Research shows that fictional television and film violence contribute to both a short-term and a long-term increase in aggression and violence in young viewers. Television news violence also contributes to increased violence, principally in the form of imitative ...
The Influence of Media Violence on Youth
A number of professional groups have also addressed the state of relevant research on media violence (e.g., Eron, Gentry, & Schlegel's, 1994, report for the American Psychological Association), as have other federal agencies (e.g., Federal Trade Commission, 2000). Indeed, six medical and public-health professional organizations held a ...
Violence in the media: Psychologists study potential harmful effects
However, later research by psychologists Douglas Gentile and Brad Bushman, among others, suggested that exposure to media violence is just one of several factors that can contribute to aggressive behavior. Other research has found that exposure to media violence can desensitize people to violence in the real world and that, for some people ...
The portrayal of violence in the media: impacts and implications for
Numerous research studies identify an association between exposure to violence in entertainment and violent behaviour, but do not prove that exposure causes violent behaviour. Rather, there is a risk that exposure to media violence will increase the likelihood of subsequent aggressive behaviour. This risk can be increased or decreased by a large number of other factors.
Desensitization to Media Violence: Links With Habitual Media Violence
The Current Study. The current study was designed to add to the existing body of evidence on the role of desensitization in the media violence- aggression link in four ways: (a) by looking at altered emotional reactions to a violent film clip as an outcome variable of long-term, habitual media violence exposure; (b) by looking at desensitization to violence both in terms of a decrease in ...
Comparing 'New' and 'Old' Media for Violence Monitoring and Crisis
This paper seeks to determine the comparative opportunities and limitations of 'new' and 'old' data sources for early warning, crisis response, and violence research. We compare the information set produced through social media violence reporting with conventional violence reporting around the August and October 2017 Kenyan elections.
Creditor-on-Creditor Violence and Secured Debt Dynamics
Secured lenders have recently demanded a new condition in distressed debt restructurings: competing secured lenders must lose priority. We model the implications of this "creditor-on-creditor violence" trend. In our dynamic model, secured lenders enjoy higher priority in default. However ...
[2408.12932] Broad versus narrow research questions in evidence
There has been a transition from broad to more specific research questions in the practice of network meta-analysis (NMA). Such convergence is also taking place in the context of individual registrational trials, following the recent introduction of the estimand framework, which is impacting the design, data collection strategy, analysis and interpretation of clinical trials. The language of ...
Crime News Consumption and Fear of Violence: The Role of Traditional
The aim of this research was to explore the association between consumption of news and information on violent crime and fear of violence in the forms of street violence, avoidance behavior, and perceiving terrorism as a threat to oneself in the contemporary context of the current cross-media landscape. Past research examining the relationship ...
German police hunt festival knife attack suspect
Pavel Durov, founder and CEO of messaging app Telegram, was arrested on Saturday evening while leaving his private jet at France's Bourget airport, according to French television network TF1.

Article contents

Media Exposure, Violence, and Aggression

Media Exposure and Copycat Crimes

Media Exposure and Violent Crimes

Theoretical Perspectives on Media Effects

Criminology and the “Media/Crime Nexus”

Further Reading

Related Articles

Reactions to Media Violence: It’s in the Brain of the Beholder

Introduction

Ethics Statement

Participants

Personality and Behavioral Measures

Imaging Conditions and State Reactivity

PET Imaging

Image and Data Analyses

Traits, Inhibitory Control, and Resting Metabolism

Glucose Metabolism and Mood Reactivity during Media Viewing

The Value of Pre-Selection Based on Abnormal Aggression Traits

Characterization of Trait Aggression through Resting Brain Metabolism

Brain Metabolism during Violent Media Viewing

Hypoactivity of the Orbitofrontal Cortex

Under-reactive Emotional and Autonomic Response to Violent Media

Acknowledgments

Author Contributions

Save citation to file

Add to My Bibliography

The role of media violence in violent behavior

Similar articles

Publication types

Related information

Annual Review of Public Health

Most Read This Month

Violence in the media: Psychologists study potential harmful effects

Television and video violence

Video game violence

Recommended Reading

Desensitization to Media Violence: Links With Habitual Media Violence Exposure, Aggressive Cognitions, and Aggressive Behavior

Ingrid Möller

Lucyna Kirwil

Juliane Felber

The Current Study

Participants

Measures: Online Questionnaire

Trait arousability

Trait aggression

Aggressive normative beliefs

Order variation

Measures: Laboratory Session

Funny clips

Physiological arousal

Self-reported affective responses and perceptions of film clips

Accessibility of aggressive thoughts

Aggressive behavior

Dispositional Measures (Time 1)

Laboratory Measures of Aggression and Self-Reported Emotional Arousal (Time 2)

Manipulation Checks for Film Clips

Bivariate Correlations Between Violence Exposure, Aggressive Norms, Arousal, and Aggression

Aggregate Scores of Physiological Arousal

Relations of Self-Reports of Emotional Arousal to SCL Indices of Arousal

Relation of Media Violence Exposure With Physiological Arousal to Film Clips (Hypothesis 1)

Relations of Media Violence Exposure With Self-Reports of Arousal to Film Clips (Hypothesis 2)

Relations of Self-Reports of Arousal to Violent Film Clip With Situational Aggression (Hypothesis 3)

Examining the Content Specificity of Desensitization (Hypothesis 4)

Self-reports of arousal to the different kinds of film clips

Self-reported arousal and situational aggression

Acknowledgments

Contributor Information

Comparing ‘New’ and ‘Old’ Media for Violence Monitoring and Crisis Response in Kenya

IDS Item Types

Creditor-on-Creditor Violence and Secured Debt Dynamics

More from NBER

Statistics > Applications

Submission history

References & Citations

BibTeX formatted citation

Bibliographic and Citation Tools

arXivLabs: experimental projects with community collaborators

Entertainment

New on Yahoo