Beyond the Shooter Game

Beyond the Shooter Game Examining Presence and Hostile Outcomes Among Male Game Players

Communication Research Volume 33 Number 6 December 2006 448-466 © 2006 Sage Publications 10.1177/0093650206293249 http://crx.sagepub.com hosted at http://online.sagepub.com

Matthew S. Eastin Robert P. Griffiths The Ohio State University, Columbus

Investigating male game players, this study explores how game interface (virtual reality [VR] and standard console), game content (fighting, shooting, and driving), and game context (human and computer competition) influence levels of presence and hostile expectation bias—the expectation others will think, feel, speak, and act aggressively during social conflict. In addition to game interface and game content influencing hostile expectations, significant interactions were detected for hostile expectations. Presence, although not as predicted, also significantly differed across game interface and game content. Through the development and testing of each gaming experience, this study demonstrates that simply testing violent and nonviolent game situations underestimates the complexity of contemporary video-game play. Keywords: video games; violence; presence; hostility; expectations; bias; general aggression model; priming; competition; Internet use; online gaming; multiuser

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s video-game violence becomes more complex and realistic, parents, politicians, and researchers press forward to understand its impact on the player and society. Research as early as 1983 found 85% of games required players to physically attack other characters to win the game (Bowman & Rotter, 1983). A 2003 analysis of 60 popular games revealed 90% of teen- or mature-rated games featured violence and 57% of games rated for all audiences contained violence (Smith, Lachlan, & Tamborini, 2003). To understand the effects of playing such violent games, researchers have begun to examine how individual differences, including trait aggression, and situational variables, such as violent video-game play, operate as routes to internal states and, ultimately, aggressive behavior (Anderson & Dill, 2000; Bushman & Anderson, 2002). The current project extends traditional research that has investigated the influence that playing standard console violent and nonviolent games has on aggression. Research and technological advancements have introduced new opportunities for development in this area, including the potentially important role of presence. The current study advances the video-game research agenda by investigating three routes to presence and aggressive cognition. Specifically, game interface, game content, and 448

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game context are conceptually developed and tested as unique media experiences influencing game presence and hostile expectation bias.

Aggression and Game Play With a proliferation in violent content, the number and type of research projects examining antisocial video-game effects has increased. Several meta-analyses (Anderson, 2004; Anderson & Bushman, 2001; Sherry, 2001) and recent research projects support the connection between violent game play and increased level of aggression (Bushman & Anderson, 2002; Lynch, Gentile, Olson, & van Brederode, 2001; Tamborini, Eastin, Skalski, Lachlan, Fediuk, & Brady, 2004). For instance, speaking generally to the topic, Bushman and Anderson (2002) suggested that repeated exposure to violent video games is linked to aggression and violence. More specifically, children who played violent games were shown to imitate those behaviors later during free play (Schutte, Malouff, Post-Garden, & Rodasta, 1988). Lynch et al. (2001) revealed that violent video-game play is positively correlated with hostile attribution bias, arguments with teachers, and trait hostility. Using a self-report state hostility measure, Ballard and Wiest (1996) found males displayed greater hostility after playing Mortal Kombat (a violent martial arts game) than they did after playing a nonviolent control game. Moreover, participants demonstrated more hostility playing the gore-enhanced version of Mortal Kombat than they did the censored version. Looking specifically at male game play, violent video-game play by men may increase their punitive behavior and decrease their reward behavior toward others (Ballard & Lineberger, 1999). Game researchers have used a variety of theories including arousal (Ballard & Wiest, 1996; Calvert & Tan, 1994) and priming (Anderson & Dill, 2000; Kirsh, 1998) in an attempt to explain hypothesized effects. Most recently, using social learning, arousal, priming, and cognitive processing theories, Anderson and Bushman (2002) empirically developed the general aggression model (GAM) to better understand why exposure to violent media increases human aggression. As a conceptual platform, the GAM is used in the current study to examine the effects of violent video-game play on hostile expectation bias by incorporating media-related routes as predictors of aggressive cognition.

Understanding Game-Play Outcomes The GAM provides a framework for understanding violent media effects through the activation of aggression-related knowledge structures (Bushman & Anderson, 2002). Specific to the current study, it demonstrates how first-person game play, and decisions to aggress during game play, influence aggressive outcomes. The singleepisode model (Anderson & Bushman, 2002) indicates that during violent videogame play personal and situational inputs combine to prime aggressive cognition


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(e.g., hostile thoughts, scripts, and so on), aggressive affect, and arousal. Each gameplay session (a single episode) represents a learning forum for real-world behavior. For instance, aggressive responses during game play generate knowledge structures that direct behavioral responses inside and outside the game environment. Therefore, during each game-play experience, “well-learned scripts come to mind relatively easily and quickly and can be emitted fairly automatically” (Anderson & Dill, 2000, p. 774). Similar to Berkowitz’s (1984, 1990) cognitive neoassociation model, aggressive ideas found during video-game play involuntarily prime other semantically related ideas—prompting game players to experience aggressive thoughts outside the game environment. The current research examines how the media routes of game content and interface, as well as game context, influence how individuals interpret ambiguous social interactions as hostile. Crick and Dodge (1994) presented this as attribution bias, which is often observed in aggressive children. Hostile attribution bias suggests aggressive individuals interpret the harmful actions of others as intentional rather than accidental. The current study predicts a single gaming episode can temporarily create a hostile expectation bias as an outcome of primed aggressive cognition (Berkowitz, 1990)—or the expectancy for others to think, speak, feel, and act aggressively during social conflict. Supporting this relationship, Dill, Anderson, Anderson, and Deuser (1997) and Anderson and Bushman (2002) linked hostile expectation bias to aggressive individuals.

The Experience of Game Play Tamborini et al. (2004) suggested the attributes of video games associated with a first-person point of view and a user’s active role in decisions to aggress are powerful conditional forces that influence aggressive outcomes. First-person games are thought to increase identification with the gaming character through involvement and immersion, which subsequently increases short-term outcomes such as aggression (Leyens & Picus, 1973; Schneider, Lang, Shin, & Bradley, 2004). Involvement, defined as a psychological state in which attention and energy are focused on the medium, and immersion, defined as the extent to which the player or person perceives being in and interacting with the mediated environment, are considered necessary components to the larger construct of presence (Witmer & Singer, 1998). Presence, which is further explicated below, is then defined as “the subjective experience of being in one place or environment, even when one is physically situated in another” (Witmer & Singer, 1998, p. 225). The decision to shoot, punch, and so on “as” a character in a firstperson game rather than “with” a character leads to greater presence—as defined through involvement and immersion. It is the decision to aggress that creates or activates existing aggressive scripts that subsequently result in aggressive outcomes. Attributes inherent to advanced technologies such as virtual reality (e.g., increased vividness and interactivity) also are thought to increase presence beyond traditional



console and passive-watching environments (Klimmt & Vorderer, 2003; Tamborini et al., 2004). According to this logic, the violent gaming situation eliciting the greatest levels of presence should have the greatest short-term effect on aggression. Tamborini et al. (2004) found some support for the connection between presence, interactivity, and aggression; however, overall levels of presence did not predict aggression and were relatively low among virtual reality (VR) participants. The researchers suggest the findings were due to a lack of experience using VR systems and a potential disengagement between firing a gun and the respondent’s existing real-world scripts for aggression (Tamborini et al.). Simply put, a violent behavior resembling more common social violence, such as punching, kicking, and so on, would increase the behavior salience (and potentially aggressive cognition) more than a shooting-type game. The current study offers new avenues for understanding the development of presence and hostile expectations through game content, interface, and context. Although concepts such as involvement (Klimmt & Vorderer, 2003; Regenbrecht & Schubert, 2002) and immersion (Witmer & Singer, 1998) are used to explain presence, during the past several years no clear definition has emerged across disciplines. Lombard and Ditton (1997) defined it as the perceptual illusion of nonmediation that occurs when a person fails to perceive or acknowledge the existence of a medium in his or her communication environment and responds as he or she would if the medium were not there (see also IJsselsteijn, de Ridder, Freeman, & Avons, 2000). Taking a slightly more simplistic approach, the immersive quality of technology rests in its ability to make the person believe he or she is “being there” in the environment (Slater & Usoh, 1994) or feeling perceptually surrounded (Blascovich et al., 2002). Lee (2004) defined presence as “a psychological state in which virtual (paraauthentic or artificial) objects are experienced as actual objects in either sensory or nonsensory ways” (p. 37). Further describing the subjective experience, Lee explicated three typologies of presence—physical, social, and self. Physical presence represents a psychological state in which virtual objects are experienced as actual. In this regard, presence can occur in any locale because it is a psychological feeling rather than the actuality of being in the environment. Social presence is a state where virtual social actors are experienced as actual. Finally, self-presence describes a state where the virtual self is experienced as actual. Speaking across definitions, the perception of presence experienced is to some extent based on the media’s ability to deceive the human senses into believing mediated sensory as reality (Heeter, 1992). Through person-centered routes, the mediated environment becomes the focus and simulates the sensation of real life. Thus, presence is experienced through the interaction between the individual and mediated technology (Klimmt & Vorderer, 2003; Tamborini et al., 2004), where involvement and immersion are important interrelated components (Witmer & Singer, 1998). Similarly, Steuer (1992) and Tamborini et al. (2004) inferred that presence, in part, occurs through the combination of vividness (relating to the user’s senses) and interactivity (the ability to



alter environment). Presence in this regard is dependent on the number of sensory channels activated simultaneously and the saliency of each sensory channel (Steuer, 1992). Technology that increases sensory engagement should ease a player’s mental strain by enabling greater focus on the content and action, subsequently increasing the effects of game content. Based on the tendencies of previous work, the current researchers used Witmer and Singer’s (1998) conceptual and empirical definition of presence that broadly captures the subjective experience of being in one place even when physically in another. In today’s mediated environments, presence often is discussed within the capabilities of immersive technologies or VR. VR is defined as a three-dimensional, computer-simulated scenario in which a person can look at, move around in, and experience an imaginary world (Pimentel & Teixeira, 1993, cf. Calvert & Tan, 1994). VR has the ability to create the illusion that a player is part of the game through character hand and body manipulation during game play (Calvert & Tan, 1994). Within the current framework, the ability to pull a gun trigger or throw a punch represents a level of engagement that strengthens the effects of violent game play. Thus, as predicted by Tamborini et al. (2004), VR environments, by the features inherent to the technology as the gaming interface, should increase levels of presence. In addition to presence, past research has shown aggression was higher for participants of a VR game than for observers (Calvert & Tan, 1994). The decision to aggress and the engaging nature of the medium interacts to increase aggressive cognitions (Tamborini et al.) and hostile expectations. Extending prior research that has primarily examined traditional game play, the current study investigates two technologically driven game interfaces: VR and standard (or traditional) console game play. Among these media inputs, presence and hostile expectation bias are examined. To control the skill confounds previously identified by Tamborini et al. (2004),1 the current study trained all participants prior to gaming exposure. Based on the rationale presented, it is predicted that Hypothesis 1: Presence will be greatest in the VR environment compared to the standard console. Hypothesis 2: Hostile expectations will be greatest in the VR environment compared to the standard console.

The Influence of Content In addition to interface attributes, the salience of game content (Witmer & Singer, 1998) can influence presence levels and hostile expectations. When behaviors performed in an environment are more salient to the user, reported levels of presence and hostile expectations are increased. For example, as Witmer and Singer (1998) investigated environmental properties to help develop a presence questionnaire, they found that as the virtual environment more resembled real life, greater levels of presence were achieved.



Furthermore, Schneider et al. (2004) and Tamborini et al. (2004) believed firstperson shooter games increase presence and aggressive cognition for the player. Although in agreement, the current authors contend the generally weak but consistent relationship between first-person shooter games and various measures of aggression can be partly attributed to the salience of shooter games for the gamer. Most research examining violent versus nonviolent game play has assumed all violent game play is equivalent in terms of influence. The logic behind cognitive scripting is that when choosing to aggress, the player creates and then reinforces knowledge scripts of reactive behavior. The current researchers believe shooter games are not as salient to most users as a “violent reaction script,” thus levels of immersion and short-term aggression comparatively lessen when playing shooter games because the action of firing a gun is not a salient reaction to provocation in the user’s reality. Using a more salient action such as fist fighting should provide an opportunity for players to more easily develop or activate preexisting knowledge scripts, thus allowing for stronger and potentially “transferable” behavioral responses outside the game environment—for the current study, greater hostile expectation bias toward common social situations. So although past research has consistently demonstrated a relationship between firstperson shooter games and aggressive outcomes, it is believed that first-person games requiring a fist fight will comparatively elicit greater levels of presence and short-term aggressive responses. Thus, extending the context of video-game violence to include playing a first-person shooting game, a fist-fighting game, and a driving game, the relationship among game content (or action salience), presence, and hostile expectation bias are examined. It is predicted that Hypothesis 3: Playing a fighting game will produce greater levels of presence compared to a shooting game. Hypothesis 4: Hostile expectations will be greatest when playing a fighting game followed, in order, by a shooting game and driving game.

The Context of Game Play Past research has employed games where the player is playing against the computer. However, when a person experiences an environment with another person, research suggests levels of presence are heightened. Schubert, Regenbrecht, and Friedmann (2000) found that when participants “perceive some possibility to be part of the action, to interact with the characters” (p. 4), inside a virtual environment, levels of perceived presence rose. Few video-game researchers (Eastin, 2006) have examined how levels of presence are influenced when playing another person in an aggressive environment. Therefore, the current study extends Schubert et al.’s results to suggest if the possibility of interacting with illusory others in mediated environments increases levels of presence, then interacting with real others in a violent environment should increase presence and hostile expectations more than when merely interacting with a computer opponent.



Competitively speaking, research suggests a positive relationship between competition and aggression (Anderson & Morrow, 1995; Berkowitz, 1962, 1989). According to Berkowitz (1962), aggression increases through frustrations, and competition between opponents who seek the same goal is thought to be frustrating (Berkowitz, 1989). Furthering this idea, research has shown competitive situations, or simply priming participants toward competition, increases indices of aggression (Anderson & Morrow, 1995). That said, not all opponents may be equivalent in generating perceived competition levels. For instance, when looking at face-to-face stranger interactions versus computer opponents during nonviolent game play (e.g., Monopoly), computer opponents increased aggression beyond human opponents (Williams & Clippinger, 2002). However, focusing on violent female game play, Eastin (2006) indicates that human opponents did increase aggressive thoughts compared to computer opponents. To further understanding in this area, the current study suggests that when males confront another player through aggression interaction (i.e., violent game play) individual hostile expectations will be greater when the salience of the competitor is increased. Simply put, playing against another person will incite stronger hostile expectations than playing against the computer. The current study placed gamers in situations where they were playing against another person or against the computer. In these situations, the following research questions are asked: Research Question 1: Does playing against another person increase the level of presence experienced? Research Question 2: Does playing against another person increase hostile expectations?

Methods Sample Data were gathered from 219 male participants from a large midwestern university. Male participants were selected, as research suggests that males are more likely to play (Gentile & Anderson, 2006), prefer (Entertainment Software Association, 2005; Gentile, Lynch, Linder, & Walsh, 2004; Lucas & Sherry, 2004), and be portrayed in violent games than females (Smith et al., 2003). Furthermore, a central goal of the current study is to examine how game competition influences hostile expectations. Research by Maccoby (1990, 1998) shows that men are generally more competitive than women, thus making male players of particular interest within a competitive violent gaming context. All participants were recruited from large introductory communication classes, some of which provided general education credits for all students. Ages ranged from 18 to 31 years (M = 21.38, SD = 2.51). Eighty-five percent were White, 8% were



African American, 3% were Asian, 2% were Latino, and the remaining 2% were Native American or Other. Thirty-nine percent were seniors, 29% juniors, 23% sophomores, and the remaining 9% were first-year students. Of the participants, 95% indicated they had played a video game in the past, and on average participants played video games for 70 mins per day.

Procedure The current study used a 2 (game interface) × 3 (game content) × 2 (game context) experimental design. Three games were chosen for this research project to manipulate game-action saliency. The first was a first-person shooting game named Unreal Tournament: Game of the Year Edition (UT). The second was a first-person fighting game named Knockout Kings 2002 (KK). Finally, the control condition consisted of a first-person driving game named Gran Tourismo 3: A-Spec (GT3).2 All three games incorporated the ability to play against an opponent. The posttest showed that 90% of participants considered all three games as “action”.3 The current study investigated two gaming environments—VR and standard console. The VR interface was made possible through a head mount display (HMD) run through a personal computer (PC), which included headphones and a free-rotating sensor to capture movement. The HMD provided an isolated viewing experience such that the video feed was the only view players had. For the VR interface, UT consisted of a HMD and a joystick manipulated to look and feel like a gun. Movement was controlled through the HMD and the joystick gun. KK consisted of wearing the same HMD, and movement was controlled through wireless radiocontrolled sensors placed on the participants’ wrists. A receiver placed on the ground captured the movements of the sensors, and a gaming mat captured foot movement. The wireless sensors allowed participants to throw punches without cumbersome wires or button pushing. GT3 also used the HMD and utilized a steering wheel and pedals for movement. In the standard console condition, also run through a PC, participants utilized a consistent joystick for all three games—a directional pad on the left and buttons on the right and top—while viewing the game on a 17” flat panel computer screen. Although “god mode” (i.e., invincibility) was not employed, game characters used by participants were developed so they could suffer from the violent interactions without there being an ultimate loser or winner. This allowed for competition to exist within continuous game play. In addition, gender (male humans only), character (physical appearance), and options to aggress (type of punches, gun, or car) remained constant within game exposure. As to the third and final manipulation, game context, participants were told they were either playing against the computer or another person. To maintain consistency, though, all game players played versus a computer-operated opponent—the difference between conditions remained in the perception of the opponent type. The



manipulation “against another player” included a fabricated log-in session so users believed they were part of a multiuser online community. Participants engaged in two distinct sessions for the current study. During the first session, they were given consent forms and an initial questionnaire on video-game use. After completing the questionnaire, participants were randomly assigned to one of six conditions (shooting, fighting, or driving games in either the standard console or VR condition). Participants were permitted to “train” on the game until they felt they had a handle on how to successfully manipulate the controls of the game. This rarely exceeded 20 mins. The training environments were designed to be similar to but not duplicates of the final testing environments. The only purpose for training was to give participants the opportunity to develop the necessary skills for game play, subsequently allowing them to focus on content and action (as suggested by Tamborini et al., 2004). When the participants felt comfortable with the game’s controls, they were asked to sign up for another session and thanked for participating in the study. The second session of the study positioned the players in the same condition and environment in which they were trained. However, this time participants were told they would be playing against either a computer agent or another participant. Previous game-play treatments varied from 5 to 75 mins (Sherry, 2001); however, longer game time does not signify increased aggression. Because the researchers are interested in short-term effects, the players played for two 10-min sessions (Anderson & Dill, 2000). As a manipulation check, after the second session all gamers were asked to indicate whether they were playing against the computer or another person. Only those consistent with the manipulation were included in analyses.

Outcome Measures Presence experienced was measured with the 32-item Presence Questionnaire (PQ; Witmer & Singer, 1998). Each item is measured through a 7-point semantic differential scale and comprises four empirically driven categories—control, sensory, realism, and distraction (Witmer, Jerome, & Singer, 2005; Witmer & Singer, 1998). Similar to Witmer and Singer (1998), we labeled the environment’s responsiveness as control, the extent of engagement and involvement as sensory, the extent of connectedness to sensory information as realism, and the saliency of control devices as distraction. Each category was originally developed through a cluster analysis of the items. When Witmer and Singer analyzed the structure and utility of the PQ scale they found that the “results support the role of these [four] factors in enabling the experience of presence, and suggest that the PQ items measure a single construct called presence” (p. 231). Similar to previous research (Bormann, 2005; Sallnas, Rassmus-Grohn, & Sjostrom, 2000; Witmer & Singer, 1998), the current study summed and averaged the all items to create a measure of presence experienced (α = .92, M = 4.61, SD = .90).



Hostile expectation bias was measured using the story completion protocol (Bushman & Anderson, 2002; Rule, Taylor, & Dobbs, 1987). This protocol required participants to complete three ambiguous story stems.4 These story stems asked participants to list what they thought the main character would do or say, think, and feel next. The main character expectations are referred to as aggressive behaviors, aggressive thoughts, and aggressive feelings (Bushman & Anderson, 2002). To complete each story, 5 mins and a piece of paper with three columns containing 20 rows each were provided. Column 1 allowed for participants to indicate what the main character will do or say (defined as aggressive behavior), Column 2 allowed for participants to indicate what the main character will think, and Column 3 allowed for participants to indicate what the main character will feel. Stories were randomly presented throughout experimentation to avoid an order effect. As mutually exclusive categories, each column was content analyzed based on the protocol provided by Bushman and Anderson (2002). Coding of responses was conducted by two graduate students, both of whom were trained on fictitious completions until sufficient reliability was achieved. Once reliable, each coder content analyzed about 10% of the stories included in the sample (n = 30), and then Scott’s pi reliability was calculated for each of the three areas. From this, adequate reliability was achieved for the aggressive behavior (Scott’s pi = .91, M = 4.24, SD = 3.16),5 aggressive thoughts (Scott’s pi = .88, M = 3.41, SD = 2.28),6 and aggressive feelings (Scott’s pi = .94, M = 4.13, SD = 2.45)7 categories. When reliability was deemed adequate, the remaining sample was coded by a single coder. All numeric values represent the summed average for each hostile expectation across the three story stems. The number of aggressive responses for each of the three categories was consistent with previous research (Bushman & Anderson, 2002).8 For all analyses, the three hostile expectation biases were collapsed to create a composite hostile expectation bias score (M = 11.78, SD = 6.01). In addition to looking at the composite measure, aggressive behaviors, thoughts, and feelings will be examined separately.

Data Analyses All hypotheses and research questions were examined so that main and interaction effects among the independent variables could be observed. To test Hypotheses 1, 2, and 3 and Research Questions 1 and 2, a 2 (game interface) × 2 (game content) × 2 (game context) experimental design was used. Hypothesis 4 was tested with a 2 (game interface) × 3 (game content—fighting, shooting, and driving) × 2 (game context) experimental design. These designs were broken out because Hypothesis 4 included a nonviolent control group. The nonviolent control is only applicable when comparing across games. Where applicable comparisons were conducted to test mean differences. Raw means and standard deviations for each tested model can be found in Table 1.



Table 1 Raw Means and Standard Deviations for Tested Models

Fighting Virtual reality Standard console Computer opponent Human opponent Shooting Virtual reality Standard console Computer opponent Human opponent Driving Virtual reality Standard console Computer opponent Human opponent

Hostile Expectation (Overall) M (SD)

Hostile Expectation (Behaviors) M (SD)

Hostile Expectation (Thoughts) M (SD)

Hostile Expectation (Feelings) M (SD)

Presence M (SD)

15.42 (7.05) 12.34 (5.29) 13.86 (1.05) 14.27 (5.97)

5.85 (4.08) 4.59 (2.95) 5.75 (4.03) 4.86 (3.26)

4.59 (2.66) 3.25 (1.59) 3.56 (2.25) 4.43 (2.38)

4.98 (2.89) 4.50 (2.49) 4.56 (2.93) 4.97 (2.50)

4.18 (.87) 4.76 (.89) 4.27 (.92) 4.59 (.90)

11.86 (5.57) 11.16 (5.48) 11.15 (4.27) 11.83 (6.47)

4.29 (2.48) 3.72 (2.84) 3.59 (2.15) 4.38 (3.05)

3.34 (2.34) 3.53 (2.25) 3.47 (1.83) 3.41 (2.65)

4.23 (2.52) 3.92 (2.26) 4.09 (2.45) 4.05 (2.34)

4.49 (.77) 5.07 (.60) 4.78 (.69) 4.79 (.80)

9.05 (5.44) 10.84 (5.92) 10.48 (5.72) 9.06 (4.67)

2.91 (2.19) 4.13 (3.40) 3.60 (3.04) 3.23 (2.56)

2.63 (2.15) 3.06 (2.05) 3.10 (2.25) 2.49 (1.90)

3.51 (2.27) 3.66 (1.94) 3.78 (2.21) 3.34 (2.03)

NA NA NA NA

Results Although presence significantly varied across game environments, findings were not as predicted in Hypothesis 1, F(1, 136) = 19.64, p < .01, partial η2 = .13. It was thought the VR environment would produce the greatest overall levels of presence, followed by the standard console group. However, despite training participants before game play, data indicate the standard console condition (M = 4.93, SD = .76) produced significantly greater levels of presence than the VR condition (M = 4.32, SD = .83). Hypothesis 2 examined the relationship between hostile expectations and game environments. Data indicate that hostile expectations did significantly differ, F(1, 136) = 3.80, p < .05, partial η2 = .03, across the VR (M = 13.80, SD = 6.61) and standard console (M = 11.70, SD = 5.38) environments as predicted. Looking at the three hostile expectations separately, aggressive behavior, F(1, 136) = 3.10, p > .05, aggressive thoughts, F(1, 136) = 2.20, p > .05, and aggressive feelings, F(1, 136) = 1.00, p > .05, did not differ between the VR and standard console groups. Thus, only the composite hostile expectation bias score differed across game environment. Although a significant difference for presence was detected between the fighting and shooting games, it was not as predicted in Hypothesis 3, F(1, 136) = 5.75, p < .05,



partial η2 = .04. Here, presence levels were greater for participants playing the shooting game (M = 4.80, SD = .74) compared to those playing the fighting game (M = 4.43, SD = .92). Supporting Hypothesis 4, hostile expectations did significantly differ by game content as predicted, F(2, 207) = 9.71, p < .01, partial η2 = .09. Post hoc mean comparisons indicate the fighting game produced significantly greater hostile expectation biases (M = 14.06, SD = 6.48) than the shooting (M = 11.50, SD = 5.50) and driving games (M = 9.81, SD = 5.27). The shooting and driving games did not differ significantly from each other. Looking at hostile expectations individually, data indicate the fighting game produced significantly greater hostile expectations (M = 5.30, SD = 3.66) than the shooting (M = 4.00, SD = 2.67) and driving games (M = 3.42, SD = 2.81) for aggressive behavior, F(2, 207) = 6.41, p < .01, partial η2 = .06. Again, post hoc comparisons indicate the shooting and driving games did not differ from each other. Data also show that aggressive thoughts, F(2, 207) = 4.88, p < .05, partial η2 = 05, differed across the three games. However, the fighting game (M = 4.01, SD = 2.34) only significantly differed from the driving game (M = 2.81, SD = 2.10). The shooting game (M = 3.44, SD = 2.29) failed to demonstrate a significant difference for aggressive thoughts from either the fighting or driving groups. Finally, data demonstrated a significant effect for aggressive feelings, F(2, 207) = 4.79, p < .05, partial η2 = .04. Again, although the fighting game (M = 4.76, SD = 2.71) did not differ from the shooting (M = 4.07, SD = 2.38), it did significantly differ from the driving game, as predicted (M = 3.57, SD = 2.13). The shooting and driving games did not differ from each other. In addition to the main effects reported, data indicate an interaction between game interface and game content for hostile expectation biases, F(2, 207) = 3.79, p < .05, partial η2 = .04. Using ANOVA to compare within group means, this interaction demonstrates that hostile expectations for the fighting (M = 12.34, SD = 5.29), shooting (M = 11.16, SD = 5.48), and driving (M = 10.84, SD = 5.92) games were not significantly different in the standard console environment, F(2, 97) = .73, p > .05, but were relatively high and significantly different in the VR environment, F(2, 116) = 11.54, p < .05. Data from the VR participants show that the fighting game produced significantly greater hostile expectations (M = 15.42, SD = 7.05) than the shooting (M = 11.86, SD = 5.57) and driving games (M = 9.05, SD = 5.44). The shooting and driving games failed to differ significantly from each other. Separately, while aggressive behavior, F(2, 207) = 3.51, p < .05, partial η2 = .03, and aggressive thoughts, F(2, 207) = 3.68, p < .05, partial η2 = .03, produced this significant interaction, aggressive feelings, F(2, 207) = .46, p > .05, did not. Mean patterns were similar to those found for the composite hostile expectation bias measure. Research Question 1 asked if playing against another person increased the level of presence experienced. Results indicate no significant main effect for presence by opponent type, F(1, 136) = .96, p > .05. Similarly, hostile expectations did not differ between human and computer competitors, F(1, 136) = .45, p > .05, thus answering



Research Question 2. Furthermore, aggressive behaviors, F(1, 136) = .01, p > .05, aggressive thoughts, F(1, 136) = 1.10, p > .05, and aggressive feelings, F(1, 136) = .40, p > .05, all failed to differ between human and computer competitors.

Discussion The current study suggests not all gaming experiences influence levels of presence and hostile expectation biases equally. In fact, games that require more common forms of aggressive behavior, such as fighting in immersive environments, elicit greater hostile expectations beyond that of shooter games. Interactions suggest that as gaming technology continues to advance, the complexity of the video-game research agenda needs to be examined beyond simple console games and broad categories of violence. In this regard, the current study moves the general experience of game play toward newer, more immersive technology and advances the video-game effects literature through differing categories of violent content and competition. Following Tamborini et al. (2004), the VR interface was believed to elicit greater perceptions of presence compared to the console interface. According to this reasoning, the VR environment would produce the greatest levels of presence. Despite achieving high levels of presence in the standard console and VR environments (i.e., group means were approximately one full point above the scale mean), presence results were not as predicted. Even after training participants 2 weeks prior to experimentation in the game environment, data still show the standard console condition produced significantly greater overall presence. Although this finding is now consistent across two studies, we still contend the VR condition has greater immersive potential. However, as noted by Tamborini et al., and consistent with Sundar, Kalyanaraman, and Brown’s (2003) definition of functional interactivity, the visual connection to game play through simple joystick use (navigation and firing controls) and comfort with standard console game play could have produced a greater presence connection when playing in the standard console environment through routes of involvement (Klimmt & Vorderer, 2003). Moreover, any additional effects from isolating participants in the HMD could have been attenuated as players in the standard console condition were not exposed to traditional distractions found in many home-gaming situations. So, even though attempts were made to reduce the novelty of the VR gaming interface through training, barriers to typical game play with VR technology, such as cost and general use, may have added an unexpected component to the current research. This aspect of the current study may provide insight into future commonplace gaming environments. It was thought the violent game content eliciting the greatest levels of presence would also produce the greatest hostile expectations. Contrary, data indicate that although the shooting game produced greater presence, the fighting game produced significantly greater hostile expectations. Moreover, while the standard console



produced greater presence than the VR, the VR environment elicited greater hostile expectations. Thus, for the current study, presence and hostile expectations appear to operate independently from each other. A potential explanation for these findings can be found within the GAM and presence literature previously outlined. For instance, following Witmer and Singer’s (1998) definition of presence, although the behavior of throwing a punch does elicit greater hostile expectations as predicted, the physical aspect of punching could make participants more aware of self and surroundings. When virtual and real-world environments are competing during game play, players are not able to focus attention and thus immerse in one place or environment. Simply put, throwing a punch is more demanding than simply firing a gun (button pushing). Through awareness of outside factors, including the physical self, presence could decrease while still increasing hostility. Moreover, because of greater popularity of first-person shooter games versus first-person boxing games, the general level of experience associated with shooter games could increase the level of functional interactivity, thus affecting presence but not cognitive scripting. Conversely, rivaling current hypotheses, it also could be argued that presence increases game enjoyment. As game enjoyment increases, hostility decreases due to greater desensitization toward game violence (Schneider et al., 2004; Tamborini et al., 2004). This could also explain the relatively small effect sizes found for hostile expectations. Given that presence was relatively high across conditions, the influence of violent game play on hostile outcomes could have been attenuated by enjoyment. Future research should continue to examine the influence of presence when presence is absent or at least relatively low before concluding that it decreases hostility. Regardless, consistent with the logic presented, data indicate the interface and game (prompting what were presented as more salient actions, such as those related to fighting) had a greater influence on hostile expectations. Interaction effects between game interface and game content also were consistent with the conceptual development of the current study. Hostile expectations did not differ by game content in the standard console environment but did differ in the more interactive VR environment. Levels of hostile expectations were significantly greater in the fighting VR condition, followed by the shooting and driving groups, suggesting that game content and interface do matter when examining hostile expectations. Thus, as gaming environments advance to increase the active or behavioral participation of game players, understanding the type of violence becomes increasingly important when examining hostile game-play outcomes. Finally, although prior research had examined the relationship between competition and aggression, extending this to hostile expectation bias was new to the gaming literature. Looking at competition, presence and hostile expectations indicated no significant main effects. However, as discussed below, research in this area should continue with a focus on player and opponent attributes including avatar and agent race and gender to better understand competitive game play. For instance, Eastin (2006) found identification cues could be a moderating variable to competition. In his study, he



found female game players attend to self and others during game play. Gamers playing with a same-gender avatar experienced greater connectedness with game play and competitiveness.

Future Research Although the current research demonstrates that game interface and game content in combination do influence hostile expectation biases, these findings can only be applied to male game play. Future research should examine female participants and how aggressive feelings are influenced when male and female players see male and female agents and avatars. Presence was not greatest in the VR condition as expected, thus additional factors beyond technological attributes are influencing presence. For example, the relationship between the player and his or her character might be underestimated as an influencing component to presence (Eastin, 2006; Schneider et al., 2004). The avatar or virtual self can serve as a surrogate identity, making the user aware of his or her physical attributes and limitations and, in some cases, of his or her role within the environment (Biocca, 1997). Biocca (1997) noted the avatar representation interacts with the user’s body schema and thus forms the user’s mediated self-representation and increases presence. This identity is literally forced on the user because of the nature of the media system. As examined by Eastin (2006), if the avatar portrays the user’s surrogate physical self within the environment, then seeing physical connections between the self and the avatar increases one’s sense of presence. Here, self as a construct is user centered and could warrant additional research on character attributes including race. Second, research should focus on how children are influenced by violent gaming. The fighting game used for the current study was rated “T” for teen, meaning it was deemed acceptable for teenagers. Given that many younger children prefer and use these games (Gentile et al., 2004; Gentile & Walsh, 2002), future research investigating children and gaming should not be limited to predefined age groups as defined by the gaming industry. If younger children are playing games that define behavioral scripts, as suggested by the current research, how youth react to violent situations outside the mediated context could be defined through actions or decisions made during the gaming process.

Limitations and Conclusions It should be noted that game players were put into a manipulation in which they encountered constant action for two 10-min sessions. Although they could die in the shooter game, get knocked down in the fighting game, or be passed in the driving game, the natural fluxes within the game never ended, and the players never returned to a menu screen. This makes potentially aberrant gaming conditions because naturalistic play may or may not have ended within 10 mins. Likewise, although steps



were taken to conceal the purpose of the current study because participants had to be instructed to play the game and game context required that participants know if they were playing against another person, it is unknown within the current study if expectations or motivations developed from study procedures. If motivations were increased through the manipulation, presence (Klimmt & Vorderer, 2003) and perhaps aggression could have been influenced. From this research it is clear that game interface and game content do influence presence and hostile expectations. Videogame researchers still have much to learn about the growing and dynamic environments presented through video games.

Notes 1. Immersion is only realized if the player is able to focus on content and action—which can only be achieved if the player is not concentrating on the fundamental skills of the game and technology. 2. Although past research (Ballard & Lineberger, 1999) suggests driving games are not the same as other action games because controls and movement are different and because the competition is against other cars rather than characters, the current research contends driving games are similar to other games because in the standard game environment the directional pad and buttons were used similarly throughout the games (steering left and right as well as acceleration and braking utilized the same buttons as walking around and shooting or punching) and participants were told they were racing another person or a car controlled by a computer-directed agent. 3. UT and KK were the only games considered violent; whereas, all three games were generally considered action games. 4. Story 1: Todd was on his way home from work one evening when he had to brake at an intersection for crossing pedestrians. The person on the bike behind him must not have known he needed to stop for the pedestrian because he crashed into the back of Todd’s bike, causing a lot of damage to both bicycles. Fortunately, there were no injuries. Todd got off of his bike and surveyed the damage. He then walked over to the other rider. What happens next? Note: This story was originally a car accident; however, given that one of our conditions was a racing game, the word car was removed and replaced with bike. Story 2: Fred had worked all summer long, and now, a couple of weeks before school started, he felt he deserved a holiday. After a bit of thought, he decided on a vacation to the coast would be ideal. After all, what could be better than heading to the beach and ocean? The problem was that he did not want to go alone. He knew his best friend Sam would go if he could; however, Sam had been saving his money to buy a new stereo. Fred decided to go over to Sam’s place and try to convince him to come to the coast. What happens next? Story 3: George had worked hard all day long cleaning his apartment. He was tired but decided to reward himself with a meal in one of the restaurants down the street. On entering the restaurant George decided on Caesar salad, French onion soup, and a filet mignon. Some 15 mins later, a waiter came around to take his order. Time slowly passed, and George was getting hungrier and hungrier. Finally, about 45 mins after his order had been taken, George was about to leave when he saw the waiter approaching with his food. What happens next? 5. Example comments include (a) “punch the guy,” (b) “you asshole,” (c) “what is your fucking problem.” 6. Example comments include (a) “no tip for this guy,” (b) “Fred is a pussy if he doesn’t go,” (c) “idiot.” 7. Example comments include (a) “angry,” (b) “I hate Sam,” (c) “pissed.” 8. Relative to previous video-game research (Bushman & Anderson, 2002) using the hostile expectation bias protocol, the current study raw mean scores by hostile expectation categories were reasonably consistent for aggressive behavior (M = 3.79), aggressive thoughts (M = 2.00), and aggressive feelings (M = 6.17). In addition, the three hostile expectations were significantly correlated at p < .05 (rbehavior, thoughts = .40; rbehavior, feelings = .29; rthoughts, feelings = .45).



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Matthew S. Eastin (PhD, Michigan State University, 2001) is an assistant professor in the School of Communication at The Ohio State University. His research focuses on the social and psychological mechanisms that influence the uses and effects of new media. Robert P. Griffiths (MA, The Ohio State University, 2004) is a doctoral candidate at The Ohio State University. His research interests include new media effects and organizational use of communication technology.
