( = 303)
Note . Values for final sample are M (SD ).
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.
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.
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.
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.
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.
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.
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 ).
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.
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.
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.
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 |
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.
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.
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.
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).
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.
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.
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 ).
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.
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.
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.
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.
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.
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.
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.
Economic and social research council.
Copyright holder, project identifier, identifier isbn, identifier issn, usage metrics.
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.
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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) |
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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.
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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 ...
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.
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.
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 ...
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 ...
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 ...
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.
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.
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 ...
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 ...
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 ...
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 ...
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.
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.
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 ...
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 ...
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 ...
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 ...
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 ...
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 ...
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.
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 ...
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.
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 ...
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 ...
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 ...
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.