Participants played a videogame using an Xbox 360 console through an LCD HD television. The games used were Half Life 2 for the highly violent condition and Halo
3 for the mildly violent condition. Both games used were First Person Shooter (FPS)
games. Justification for choosing these games derives both from the pilot study findings and that First Person Shooters are the most popular game genre in the commercial market. Halo 3 was played from the game onset whereas Half Life 2 was started at a suitable point within the game, since the onset included insufficient action (i.e., tutorial) to be adequately matched to Halo 3. Pre-test measures of trait aggression, psychological well-being, and affect were taken. A background questionnaire on gaming preferences, habits and motivations was also completed. Post-test measures of affect and flow were completed following the gameplay period. Please see Appendix 4 for a full copy of the questionnaire.
Background Questionnaire
The Background Questionnaire included measures of demographic information, gaming habits (how often participants played games, hours per week spent gaming, frequency of play in different gaming contexts), gaming preferences (i.e., consoles and genres), and gaming motivations.
The Life Satisfaction Questionnaire (Warr et al., 1979) and Affective Well-being
Questionnaire (Warr, 1990) were used as described in Study 1. The alpha coefficient
for Total Life Satisfaction was calculated as .65. The coefficients for the sub-scales of the Affective Well-being Questionnaire were: .71 for anxiety-contentment, and .81 for depression-enthusiasm.
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The Buss-Perry Aggression Questionnaire (BPAQ; Buss & Perry, 1992) was used as a pre-test measure of trait aggression. The sub-scales of this questionnaire are measures of physical aggression, verbal aggression, hostility and anger. Participants were asked to rate the extent to which a series of 29 statements were characteristic of themselves on a 7-point scale (1= extremely uncharacteristic of me, 7 = extremely characteristic of me). Items included: “sometimes I fly off the handle for no good reason” and “my friends say that I'm somewhat argumentative”. A score for trait aggression was obtained by calculating the total score for all the items. This was used in the subsequent analyses outlined in the following section. Further, total scores for each of the four sub-scales were calculated. Internal consistency of the BPAQ has shown to be acceptable for each of the separate sub-scales. (Physical aggression = .85, Verbal aggression = .72, Hostility = .77, Anger = .83) (Buss & Perry, 1992). Furthermore, test-retest correlations show acceptable levels of reliability (Physical aggression = .80, Verbal aggression = .76, Hostility = .72, Anger = .72 (Buss & Perry, 1992). These data therefore suggest adequate stability over time.Similarly, the current study found an overall alpha coefficient of .89, and all sub-scales to be .79 and above.
Positive and Negative Affect Schedule (PANAS; Watson, Clark, & Tellegen, 1988).
This scale was used as a pre and post test measure of positive and negative affect. Participants were asked to rate how well the 20 items of feelings and emotions described them at the present time on a 5-point scale (1 = very slightly or not at all, 5 = extremely). Positive items included “enthusiastic” and “alert”, and negative items included “hostile” and “nervous”. The mean scores for the two sub-scales of positive affect and negative affect were calculated and used in subsequent analyses. Research has revealed the PANAS scale to be reasonably high in internal consistency reliabilities, with Cronbach’s coefficient a ranging from .86 to .90 for Positive affect and .84 to .87 for Negative affect (Watson et al., 1988). Furthermore, test-retest reliability is acceptable, with the Positive Affect items being .86 and the Negative Affect items being .87 (Watson et al., 1988). The current study found similar reliability, as the alpha coefficients were calculated as .84 for Positive Affect and .79 for Negative Affect.
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This is a measure of mood states, primarily concerned with the feelings of activation and deactivation. It includes two dimensions of arousal: energetic arousal (EA) and tense arousal (TA). The EA dimension ranges from Energy to Tiredness, and the TA dimension ranges from Tension to Calmness. EA and TA are consistent, respectively, with dimensions of positive activation (positive affect) and negative activation (negative affect). Participants were asked to indicate the extent to which the mood adjective describe their present mood on a 4-point scale (1 = not at all, 4 = definitely feel like this). Items include “alert”, “calm” and “vigorous”. The current study used an adjusted version of the original checklist since some of the items had ambiguous terminology (e.g., “clutched-up” and “full-of-pep”) and would be misunderstood by the target sample. Additional adjectives were also added to the checklist, these being “excited”, “assertive”, “happy” and “exhilarated”, to supplement the removed items. A total of 20 adjectives were used, 10 measuring activation, and 10 measuring deactivation. Mean scores for the two sub-scales were calculated and were used in subsequent analyses. The reliability and construct validity of the AD ACL is well established (Lochbaum & Lutz, 2005; Thayer, 1989). Lochbaum and Lutz’s (2005) research on enjoyment of aerobic exercise found the internal reliabilities for EA and TA as .85 and .69, respectively across the three measurement times, suggesting the measure to be have adequate reliability. Along similar lines, the current study calculated Cronbach’s alpha as .75 for activation, and .68 for deactivation.
Flow State Scale-2 (Jackson & Eklund, 2002; Jackson & Marsh, 1996)
The Flow State Scale-2 (Jackson & Eklund, 2002; Jackson & Marsh, 1996) was used as the post-test measure of flow derived through the gameplay experience. Participants were asked to rate the extent to which they agreed with a series of 36 statements of flow on a 5-point scale (1 = strongly disagree, 5 = strongly agree). Items included “I felt in total control of what I was doing”; and “my abilities matched the high challenge of the situation.” There were four items for each of the nine flow dimensions. Means scores for each of the nine sub-scales were calculated, and an overall mean score, which formed the basis for subsequent analyses.
Jackson and Marsh (1996) conducted numerous factor analyses to establish the Flow State Scale as a global measure of flow. The criteria used to select the items in the scale included the goodness-of-fit measures for the nine first-order factor model and
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LISREL’s modification indices (Joreskog & Sorbom, 1989). It was found that the internal consistency estimates for the nine Flow State Scales were reasonable (alpha M = .83). Further research showed the alpha internal consistency estimates of all nine subscales of the scale to range from .79 to .86 (Tenenbaum, Fogarty, & Jackson, 1999) and from .80 to .92 (Jackson & Eklund, 2002). The current study calculated an alpha coefficient of .89 for the scale, suggesting adequate reliability.
5.3.4. Procedure
The study was conducted in a quiet lab room, with the Xbox 360 linked to a ViewPia® Lab LCD HD Television. Following briefing and consent, participants were issued with a series of questionnaires. Firstly, participants were asked to complete the background questionnaire. Next they were asked to complete the measures of psychological well-being, trait aggression and affect. On completion of these questionnaires, participants were then randomly assigned to one of two conditions (highly violent or mildly violent), in which they were required to play a videogame for a period of 40 minutes. Following gameplay, participants completed post-test measures of affect and flow.
5.4. Results