Sport Spectator Verbal Aggression: The Impact of Team Identification and Fan Dysfunction on Fans' Abuse of Opponents and Officials.
The current investigation was designed to further our understanding of two important personal input variables related to the aggressive actions of sport spectators: team identification and fan dysfunction. Team identification is commonly defined as the extent to which a fan feels a psychological connection with a team (Wann et al., 2001). Highly identified fans feel a strong allegiance to their team and the team's successes and failures are felt as their own. A large body of literature has examined the impact of team identification on spectator aggression (see Dietz-Uhler & Lanter, 2008; Wann, 2006) and this work suggests that team identification is a powerful predictor of fan violence. For instance, highly identified fans (relative to those with lower degrees of identification) are more likely to believe that verbal fan aggression is acceptable (Rocca & Vogl-Bauer, 1999) and these individuals tend to feel out-of-control when watching their favorite teams compete (Dimmock & Grove, 2005). Furthermore, highly identified fans are particularly likely to indicate that they would consider harming a rival player or coach if they could remain anonymous (Wann, Haynes, McLean, & Pullen, 2003; Wann, Peterson, Cothran, & Dykes, 1999). Research also indicates that team identification is an important predictor of fan (celebratory) rioting as persons higher in identification report participating in a greater number of riot-related behaviors and they report having more fun during the riot (Lanter, 2011).
One of the more in-depth studies to investigate the relationship between team identification and fan spectator aggression was conducted by Wann, Carlson, and Schrader (1999). These authors examined the verbally aggressive actions of spectators attending a college basketball contest. Prior to the game, participants completed a questionnaire assessing their level of identification with the home team. Then, subsequent to watching the game (won by the visiting team), the respondents completed an instrument assessing the degree to which they had acted in a verbally aggressive manner during the contest. This post-game questionnaire, labeled the Hostile and Instrumental Aggression of Spectators Questionnaire (HIASQ; see also Wann, Schrader, & Carlson, 2000), assessed aggression targeting officials as well as the opposition (players and coaches). Further, the HIASQ assessed both instrumental aggression (i.e., aggression designed to lead to a specific goal such as improved team performance) and hostile aggression (i.e., aggression intended simply to harm the target; see Dodge & Coie, 1987; Baron & Richardson, 1994; Wann, 1997). The results indicated that the spectators' verbal aggression was more frequently directed toward the officials than the opposition. In addition, aggression directed toward the officials was more likely to be hostile than instrumental in nature, while aggression focused on the opposing players and coaches did not differ by aggression type. Furthermore, and most germane to the current investigation, the authors found that highly identified fans were significantly more likely to those low in identification to exhibit all forms of verbal aggression (i.e., hostile and instrumental aggression directed toward both the officials and the opposition).
A second individual difference variable that is related to sport fan aggression is fan dysfunction. Wakefield and Wann (2006) described dysfunctional fans as those individuals who were particularly likely to complain about their spectating experience and were highly confrontational. These researchers found that fans high in dysfunction, relative to those with lower dysfunction scores, were particularly likely to verbally abuse the officials, consume alcohol at sporting events, desire to speak on sport-talk radio, and attend away games (where they could, presumably, find opportunities to confront rival fans). Several researchers have expanded on the Wakefield and Wann research in an attempt to further our understanding of dysfunction fans. For instance, Courtney and Wann (2010) examined the relationship between fan dysfunction and tendencies to have been a bully during one's youth. Consistent with expectations, level of bullying behavior as a child was a significant predictor of level of fan dysfunction as an adult. Additionally, Donahue and Wann (2009) found that level of fan dysfunction was a significant positive predictor of perceptions of the appropriateness of verbal aggression at sporting events.
Thus, both team identification and fan dysfunction have been found to be related to fan aggression. However, to date only one study has attempted to simultaneously examine the impact of team identification and dysfunction as predictors of aggression. This research, recently conducted by Wann and Waddill (2014), extended past research on fans' tendencies to consider anonymous acts of aggression (e.g., Wann et al., 2003; Wann, Peterson, et al., 1999) by simultaneously examining the impact of both identification and dysfunction as predictors of willingness to consider the aggressive actions. The relationships among team identification, fan dysfunction, and willingness to commit the violent acts were examined via a moderated regression. In the first step in the analysis, as expected, higher levels of willingness were associated with higher levels of both team identification and higher levels of fan dysfunction. However, the interaction term (introduced in the second step) accounted for a significant additional proportion of variance in anonymous aggression. Thus, the relationship between team identification and the willingness to consider acts of anonymous aggression was moderated by fan dysfunction. Exploration of the interaction via simple slope analyses (Aiken & West, 1991) revealed that, for highly dysfunctional persons, identification did not significantly predict anonymous aggression. However, among those with low dysfunction, greater team identification was associated with a significantly greater willingness to engage in anonymous aggression. Summarizing their findings, Wann and Waddill (2014) stated, "only persons with both low levels of fan dysfunction and low levels of team identification reported lower levels of willingness to commit the aggressive behaviors" (p. 149).
The current investigation was designed to extend past research on the aggressive actions of sport spectators by combining the work of Wann and Waddill (2014) with past work on the verbal aggression of fans at sporting events (e.g., Wann, Carlson, et al. 1999). Based on the aforementioned literature, the following hypotheses were tested.
The first series of hypotheses involved differences in aggression target (i.e., officials and opposing players/coaches) and aggression type (i.e., hostile and instrumental), regardless of level of team identification and fan dysfunction. With respect to aggression target (Hypothesis 1), we expected participants to report higher levels of aggression directed toward officials than toward the opposition, a pattern of responses that would replicate past research (Wann, Carlson, et al., 1999; Wann et al., 2000). In addition, both studies found a significant Aggression Target by Aggression Type interaction in which aggression toward officials was more likely to be hostile than instrumental, while aggression toward opposition was equally likely to be hostile and instrumental. Consequently, we predicted the same pattern of effects here (Hypothesis 2).
The second set of hypotheses involved the key individual difference variables studied in this research, namely, team identification and fan dysfunction. Past research has noted that both team identification (e.g., Rocca & Vogl-Bauer, 1999; Wann, 2006; Wann. Carlson, et al., 1999) and fan dysfunction (e.g., Donahue & Wann, 2009; Wakefield & Wann, 2006) are significantly related to displays of aggression. However, in the vast majority of instances, these individual difference variables have been studied in isolation (i.e., researcher have not simultaneously examined each as a predictor of spectator aggression). As noted above, the lone exception to this is work recently published by Wann and Waddill (2014). Thus, the findings reported by Wann and Waddill were used to inform predictions in the current investigation. The predictions and research question were generated for total aggression scores, aggression target (i.e., opponents and officials), and aggression type (hostile and instrumental). With respect to total aggression, Wann and Waddill found that both team identification and fan dysfunction were significant independent predictors of spectator aggression. Based on this, Hypothesis 3 predicted that both individual difference variables would be positively correlated with and account for a significant proportion of unique variance in total aggression. Predictions for aggression target and aggression type were more difficult to develop because researchers had yet to investigate the impact of fan dysfunction on these outcomes. Wann, Carlson, et al. (1999) examined the impact of team identification on aggression target and type, finding that highly identified fans (relative to those with lower levels of identification) reported greater levels of both types of aggression (i.e., hostile and instrumental) as well as greater levels of aggression directed toward both targets (i.e., the opposition and officials). However, it was deemed inappropriate to use these findings to guide predictions given that fan dysfunction was not included in their study. Thus, the potential independent impacts of identification and dysfunction on specific types and targets of aggression were examined within a research question which asked; "Which individual difference predictor variable (i.e., team identification and/or fan dysfunction) accounts for a significant proportion of unique variance in type of spectator aggression (i.e., hostile and/or instrumental) and target of spectator aggression (i.e., the opposition and/or officials)?"
Participants were 89 spectators (34 male, 52 female; 2 not reporting gender) attending a university men's basketball game between two NCAA Division I conference rivals. Participants had a mean age of 31.36 years (SD = 13.56; range = 18 to 77). With respect to seating location, 58 participants indicated that they had watched the game from an upper deck seat while 30 had watched from the lower deck (1 person did not report seating location).
Materials and Procedure
Participants were approached at various locations within the basketball arena approximately 45 minutes prior to the start of the contest. They were provided with general information about the study and asked if they would be willing to participate. Those agreeing to participate were then handed a cover letter providing details about the study. This letter indicated that the project involved two testing session, one occurring prior to the contest and one occurring immediately after the conclusion of the game. Further, participants read that the completion of the questionnaires was an indication of their consent to participate. Subsequent to providing their consent, the participants were handed the pre-game questionnaire, a pencil, and a clipboard. The pre-game questionnaire contained three sections. Section 1 contained demographic items assessing age, gender, and the last four digits of their social security number. The four digit number was used to match their pre-game and post-game questionnaires.
The next portion of the pre-game packet contained the Dysfunctional Fandom Questionnaire (DFQ; Wakefield & Wann, 2006). The DFQ contains five Likert-scale items assessing dysfunction as a fan (e.g., confrontation, complaining). Response options to the DFQ ranged from 1 (low dysfunction) to 10 (high dysfunction). Thus, higher numbers reflected greater levels of dysfunction as a fan. A sample item read, "When a coach or player makes mistakes, I let others know about it." Participants were asked to target the local university's men's basketball team (one of the teams competing in the target contest) when completing the DFQ.
The final section of the pre-game form contained the Sport Spectator Identification Scale (SSIS; Wann & Branscombe, 1993). The SSIS contains seven Likert-scale items with response options ranging from 1 (low identification) to 8 (high identification). Thus, higher numbers represented greater levels of identification. A sample item on the SSIS reads, "How important is being a fan of (target team) to you?" Participants again targeted the local university men's basketball team when completing the SSIS. Upon completion of the pre-game questionnaire (approximately 10-15 minutes), the questionnaires, pencils, and clipboards were returned to the researcher. The respondents were then given instructions on the post-game meeting location and they were excused to watch the contest.
At the conclusion of the contest, participants returned to the designated post-game questionnaire site at which point they were handed the two-section, post-game inventory, a pencil, and a clipboard. The first section of the post-game survey contained two informational items. Specifically, participants were asked to indicate the last four digits of their social security number (for matching purposes) and to indicate if they had been seated in the upper deck or lower deck when watching the game. Next, they completed the Hostile and Instrumental Aggression in Sport Questionnaire (HIASQ; Wann et al., 1999; Wann et al., 2000). The HIASQ is an eight-item Likert-scale inventory designed to assess the extent to which spectators' were verbally aggressive toward opposing players and game officials for hostile and instrumental reasons. Scores ranged from 1 (not at all) to 8 (a great deal). Thus, higher scores reflected greater levels of verbal aggression. A sample item assessing hostile aggression directed toward the officials read: "To what extent did you yell at the officials because you were mad at him/her and wanted to hurt him/her in some way?" A sample item assessing instrumental aggression directed toward the opposing team read: "To what extent did you yell at the opposing players and coaches because you believed it would help your team win?" In addition to utilizing the HIASQ to acquire a Total Aggression (TA) score, by combining various items on the HIASQ, one can arrive at assessments of several forms and targets of aggression: Hostile Aggression toward Officials (HAOFF; 2 items), Instrumental Aggression toward Officials (IAOFF; 2 items), Hostile Aggression toward Opponents (HAOPP; 2 items), Instrumental Aggression toward Opponents (IAOPP; 2 items), Total Instrumental Aggression (IA; instrumental aggression across target; 4 items), Total Hostile Aggression (HA; hostile aggression across target; 4 items), Total Aggression Directed at Officials (OFF; officials as targets across aggression type; 4 items), and Total Aggression Directed at Opponents (OPP; opponents as targets across aggression type; 4 items).
After completing the post-game questionnaire (approximately 10-15 minutes), participants were debriefed and excused from the testing session.
The target basketball contest involved NCAA Division I conference rivals. The home team entered the contest with an overall record of 23-1 and a conference record of 11 -1 (they were in first place in the conference). The visiting team had an overall record of 9-17 and a conference record of 6-6. The home team was comfortably ahead for most of the first half and led at the end of the first half by a margin of 37-24. The home team continued to stretch its lead throughout the second half with its biggest lead of 28 occurring with approximately six minutes left in the contest. The home team was victorious by a final score of 82-63. The stadium capacity is 8,600 and the announced attendance was 8,587 (99.9% of capacity).
Items on the DFQ, SSIS, HIASQ subscales, and HIASQ total scale (TA) were summed to form indices for each scale. Means, standard deviations, and Cronbach's alphas for all scales appear in Table 1 (all scales had acceptable reliability). Gender differences were examined via a Multivariate Analysis of Variance (MANOVA). Although this examination revealed a significant multivariate gender effect, Wilks' Lambda F(6, 79) = 2.95, p < .02, subsequent univariate tests revealed that scores differed by gender on only one measure, level of fan dysfunction. Consistent with past research (Courtney & Wann, 2010; Wakefield & Wann, 2006), males (M = 24.88; SD = 9.69) reported higher levels of fan dysfunction than females (M = 16.73; SD = 11.07). However, also consistent with other research endeavors (Wann & Waddill, 2014), gender was not related to any of the various forms of aggression examined here (i.e., HIASQ subscales and total scale) when other variables were included in the model. Thus, all subsequent analyses were collapsed across gender. With respect to seat location, a MANOVA failed to reveal a significant multivariate effect, Wilks' Lambda F(6, 81) = 1.12, p > .10. Thus, all additional analyses were collapsed across this variable as well.
Replication of Past Research
As noted above, the initial purpose of the current research was to replicate past work on spectators' hostile and instrumental aggression directed toward officials and opponents (Wann, Carlson, et al., 1999; Wann et al., 2000). Based on this research, it was hypothesized that spectators would report greater levels of aggression directed toward officials than opponents (Hypothesis 1) and that there would be a significant Aggression Type by Aggression Target interaction in which aggression toward officials was more likely to be hostile than instrumental, while aggression toward opposition was equally likely to be hostile and instrumental (Hypothesis 2).
To test the hypotheses, a MANOVA was computed on the HAOFF, IAOFF, HAOPP, and IAOPP subscales. As for Hypothesis 1, contrary to expectations and past research (Wann, Carlson, et al., 1999; Wann et al., 2000), spectators failed to report higher levels of aggression directed toward officials than the opposition, Wilks' Lambda F(1, 88) = 1.32,p = .26. Although the means were in the predicted direction (aggression directed at officials M = 12.38, SD = 7.61; aggression directed at opposition M= 11.96, SD = 8.27), the difference was not statistically significant.
With respect to Hypothesis 2, as expected, there was a significant interaction between aggression type and aggression target, Wilks' Lambda F(l, 88) = 26.56,p< .001. However, the pattern of effects was only partially supportive of predictions. Although, as expected, officials were more likely to be the targets of hostile aggression than instrumental aggression (see Table 1), a post hoc t-test indicated that this difference was not statistically significant, r(88) = 1.31, p = . 19. Further, although we had expected no differences in the type of aggression directed at opponents, in actuality these individuals were significantly more likely to be the targets of instrumental aggression than hostile aggression, t(88) = 2.34, p < .05 (see Table 1).
Team Identification, Fan Dysfunction, and Expressions of Hostile and Instrumental Verbal Aggression
Although the aforementioned replication analyses are informative, as noted above, the primary purpose of the current investigation was to expand on past efforts by examining the impact of both team identification and fan dysfunction on the hostile and instrumental aggression of spectators. Correlations among the variables can be found in Table 2. Separate moderated regression analyses were conducted on each of the dependent variables. Following the recommendations of Aiken and West (1991), the team identification and fan dysfunction variables were centered prior to entering them into the analysis and the interaction term was based on the centered scores. In the first step, the dependent variable was regressed on team identification and fan dysfunction; the interaction term was entered in the second step. The initial analysis evaluated the roles of identification and dysfunction in predicting overall aggression (i.e., collapsed across target and type). Hypothesis 3 predicted that both team identification and fan dysfunction would each be positively correlated with and account for a significant proportion of unique variance in total aggression. As revealed in Tables 2 and 3, this hypothesis was supported. Specifically, both team identification and fan dysfunction were positively correlated with total aggression (r = .44 and .36, respectively, both ps < .001). Further, identification and dysfunction each accounted for a significant proportion of unique variance in total aggression (the interaction was not significant).
The research question asked "Which individual difference predictor variable (i.e., team identification and/or fan dysfunction) would account for a significant proportion of unique variance in type of spectator aggression (i.e., hostile and/or instrumental) and target of spectator aggression (i.e., the opposition and/or officials)?" With respect to type and target, as can be seen in Tables 3 and 4, team identification was a significant predictor of the overall level of instrumental aggression but not hostile aggression. Team identification was also a significant predictor of overall aggression toward both officials and opponents. Fan dysfunction accounted for a significant proportion of variance in all of the dependent variables, including hostile aggression. The interaction term, however, did not account for a significant additional proportion of variance in any of these analyses.
To evaluate the roles of identification and dysfunction in more detail, a second set of regression analyses was conducted to evaluate each type of aggression as a function of the particular type and target of that aggression (i.e., separate analyses were run for each of the four combinations of aggression type and aggression target). The patterns presented in Table 4 mirrored those of the previous analyses. For instance, once again team identification was a significant predictor of instrumental but not hostile aggression, and this pattern held true for aggression directed at officials and aggression targeting opponents. Furthermore, fan dysfunction was again a significant predictor of both types of aggression and this held true when targeting both officials and opponents. There was no significant interaction of identification and dysfunction. Thus, fans who were more dysfunctional exhibited more hostile and instrumental aggression, and fans who were more highly identified with the team engaged in more instrumental aggression, and these patterns held for both officials and opponents.
For several decades, researchers have examined the situational and personal factors involved in sport spectator aggression. Although a number of critical factors have been identified (Wann et al., 2001), recent work suggests that two personal variables, team identification and fan dysfunction, are particularly powerful in predicting fan aggression (Wann, 2006; Wann & Waddill, 2014). The current investigation was designed to replicate and extend previous work (Wann, Carlson, et al., 1999; Wann et al., 2000) by investigation team identification and fan dysfunction as predictors of spectator hostile and instrumental verbal aggression directed at officials and opponents.
Hypothesis 1 predicted that spectators would be more likely to direct their aggression toward officials than toward the opposition. This expectation was based on prior work finding such a pattern of effects (Wann, Carlson, et al., 1999; Wann et al., 2000). This hypothesis was not supported as spectators failed to report differential levels of aggression as a function of target. The pattern of the findings was as expected, but the group difference was slight and not statistically significant. Given that the expected pattern of effects had been replicated in multiple samples in previous investigations, the failure to support this hypothesis is puzzling. One potential explanation might be that the current sample size was insufficient to detect an effect (i.e., a lack of power was present). At first glance, such an explanation appears to have merit, given that the sample size in the current work was roughly half of that tested previously (Wann, Carlson, et al., 1999; Wann et al, 2000). However, two points argue against this explanation. First, the within-subjects methodology employed in the current work should have led to sufficient power. And second, the mean" differences were much smaller in the current investigation than were previously reported. This suggests that the lack of significance was real and not simply an artifact of the sample size. Thus, we are left wondering about the current findings. One explanation may be the roughly two decades that have passed since the previous studies were completed. That is, it may be that fans are now more willing to act in a verbally aggressive fashion toward opposing players and coaches than they were previously. Given that theorists have cited a decrease in fan civility as an explanation for increased aggression and research shows empathy to be on the decline in our society (Konrath, O'Brien, & Hsing, 2011; Putnam, 1995; Wann et al., 2001), such an argument has merit. Of course, future research is needed to determine the feasibility of this explanation.
Hypothesis 2 predicted an interaction between aggression target and type in which aggression directed toward officials would be more hostile than instrumental and aggression toward the opposition would be equally hostile and instrumental. Although the predicted interaction was statistically significant, the pattern of effects was only partially supportive of expectations. Officials were more likely to be the targets of hostile aggression than instrumental aggression, but this difference was not statistically significant. Further, contrary to expectations, we found a significant difference in aggression type directed at opponents in which these persons were particularly likely to be the targets of instrumental aggression. The finding that opponents were especially likely to be the targets of instrumental aggression is particularly intriguing. This outcome suggests that fans were most often acting aggressively toward the opposition in an attempt to improve their team's chances of success. This result, which has not been noted previously (Wann, Carlson, et al, 1999; Wann et al, 2000), may also reflect a change in fan behaviors and attitudes as they relate to verbal aggression. That is, as noted above, it has been suggested that sport fans (and citizens in general) are less civil now than in decades past. Given this, fans in today's sporting environment may be more likely than before to feel that it is acceptable to act in a verbally aggressive fashion in an attempt to disrupt the opposition and, as a result, increase their team's likelihood of victory. As with the previous discussion of the lack of a predicted difference in aggression target, this explanation of the aggression type difference for opponents is purely speculative at this point. Additional research is needed to determine if the current pattern of effects can be replicated.
The main purpose of the current investigation was to expand on previous work by incorporating both team identification and fan dysfunction in the examination of spectators' hostile and instrumental verbal aggression. Based on prior work (Wann & Waddill, 2014), we predicted that team identification and fan dysfunction will both be positively correlated with and account for a significant proportion of unique variance in total aggression. This hypothesis was strongly supported. The interaction was not significant, indicating that both team identification and fan dysfunction independently contributed to total fan aggression. Thus, the current investigation replicates past research indicating that team identification (e.g., Dimmock & Grove, 2005; Rocca & Vogl-Bauer, 1999) and fan dysfunction (e.g., Courtney & Wann, 2010, Donahue & Wann, 2009) are each critical personal variables for predicting and understanding sport fan aggression. These findings fit well within the theoretical framework presented by Anderson (1997; Anderson et al., 1996). As noted earlier, Anderson's GAM predicts that personal input variables (as well as situational) will be influential in the aggression process. As applied to Anderson's framework and the aggressive actions of sport fans, the current work substantiates past efforts and reveals that both team identification and fan dysfunction must be included as key elements for understanding the violent actions of fans.
The research question examined the extent to which team identification and fan dysfunction predicted aggression type (i.e., hostile and/or instrumental) and target (i.e., the opposition and/or officials). A detailed examination of Tables 3 and 4 reveals an interesting pattern of effects, highlighting both consistencies and differences between team identification and fan dysfunction. First, both identification and dysfunction predicted levels of instrumental aggression, including aggression directed at both officials and opponents. However, only fan dysfunction predicted hostile aggression and it did so for aggression aimed at officials as well as aggression targeting opponents. Stated another way, fan dysfunction predicted both the expression of hostile and instrumental aggression while team identification was only significantly related to the display of instrumental aggression. Thus, it appears that highly dysfunctional fans aggress both to help their team (instrumental aggression) and to inflict harm (hostile aggression). Conversely, high identified fans reserve their aggressive actions for situations they believe will assist their team's performance. This difference appears to elucidate a critical distinguishing feature of highly identified and highly dysfunction fans. That is, this pattern of effects suggests that highly dysfunctional fans are less discerning, acting verbally aggressive in many situations. Conversely, highly identified persons are more selective, choosing to aggress only when, in their perception, it will assist their team. Future researchers could potentially test this hypothesis by expanding on the work of Donahue and Wann (2009). As noted above, these authors found that that level of fan dysfunction was a significant predictor of perceptions of the appropriateness of verbal aggression at sporting events, while team identification was not. However, they assessed perceptions of aggression in general rather than distinguishing between hostile and instrumental aggression. Given the data and logic presented here, it seems that dysfunctional fandom could be a positive predictor of the appropriateness of both hostile and instrumental aggression. On the other hand, team identification would be expected to predict appropriateness of instrumental aggression, but not hostile aggression. Future researchers should test the validity these predictions.
It is also interesting to note that the preliminary analyses failed to reveal an effect for seat location. That is, levels of aggression were not different for fans seated in various sections of the arena. Logically, one might have expected that persons sitting closer to the action would have reported higher levels of hostile and instrumental aggression. With respect to hostile aggression, the motive behind these verbal outbursts is to inflict psychological and emotional harm. Given this, one may have thought that persons sitting closer to the players and officials would have been more likely to report these actions because the targets of their aggression would be more likely to hear their rants. Similarly, one may have expected persons seated closer to the players and officials to exhibit greater amounts of instrumental aggression because there persons should be more likely to be heard and, thus, the verbally aggressive vocalizations would be more likely to affect the targets. However, as noted, this was not the case. Instead, fans were equally verbally aggressive (for both types of aggression) throughout the sporting environment. If one were to ask spectators seated far from the action if the players and officials could actually hear them (given their distance to the floor and the crowd noise-recall that the attendance as over 99% of the 8,600 capacity), most fans would probably state that this was unlikely.
One must wonder why these "distant" fans continue to display acts of aggression (if they readily admit that the target cannot hear them). Three possible explanations present themselves. First, perhaps those patrons seated far from the action attempted to join in the vocalizations of the entire crowd to increase the volume of the crowd noise. In fact, a fair number of persons may suggest that this was their motive. However, if their desire was simply to increase crowd noise, then there is little reason for their vocalizations to be aggressive. Rather, yelling anything would have sufficed (including yelling sounds rather than specific words). But their responses to the aggression questionnaire indicated that they were yelling specific things targeting specific people, not simply yelling for the sake of volume. Second, perhaps the aggressive verbalizations of fans far from the action represent another attempt by spectators to increase their control in a situation in which they have little. That is, because their team's performances have strong implications for the social identity of many fans (Wann et al, 2001), they attempt behaviors designed to influence the team (Wann et al, 1994). For example, many fans engage in superstitious behavior in an attempt to "assist" their team (Wann et al, 2013). Participants in the current study may have been exhibiting a similar effect by verbally assaulting persons who, logically, cannot hear them. Third, there may be educational and/or socioeconomic status differences between persons seated in various sections of an arena. For instance, it seems likely that those seated closer may have higher average incomes relative to spectators seated further away, given that seats closer to the action typically cost more. Further, many universities reserve seats close to the action for members of the student body. Given that each of the aforementioned explanations has some merit, future research is needed to assess the utility of each. This work could include items assessing the motivation behind the spectators' verbal aggression, correlating measures of need for control, and considering the potential impact of demographic differences among fans seated in various locations.
The current research adds to a growing body of recent literature indicating that fan dysfunction is a critical variable in the understanding of sport spectator aggression. Historically, psychological-based theories of sport fan aggression have typically (and appropriately) included team identification as a critical variable (e.g., Branscombe & Wann, 1992b; Simons & Taylor, 1992). However, based on the accumulating empirical evidence, it now appears that theorists should also incorporate fan dysfunction into their models. For example, consider the self-esteem maintenance model proposed by Wann (1993). Founded primarily on social identity theory and the self-esteem hypothesis (Rubin & Hewstone, 1998; Tajfel, 1981; Tajfel & Turner, 1979), this perspective argues that sport fan aggression is often rooted in a fan's desire to regain self-esteem lost as a result of his or her team's poor performance. That is, when a highly identified fan's team loses in a competition, he or she experiences a threat to a valued social identity (specifically, a value-competence threat, see Branscombe, Ellemers, Spears, & Doosje, 1999). As a consequence of the threatened identity and lost self-esteem, the fan will act in a hostile fashion toward others (e.g., opposing players and officials) in an attempt to restore the lost self-esteem. Low identified fans are not predicted to engage in the "blasting" of outgroups because these individuals can simply cut-off-reflected failure when the team loses (Snyder, Lassegard, & Ford, 1986). For these individuals, the role of team follower is only a peripheral component of their social identity and, as a consequence, poor team performances are not felt as a threat. Given that dysfunction also plays a key role in fan aggression, this person variable may need to be added to the self-esteem maintenance model Wann (1993). For example, because of their tendencies toward fan violence, highly identified fans who are also dysfunctional may be particularly likely to derogate outgroup individuals in an attempt at self-esteem restoration. Thus, fan dysfunction could be added as a moderating variable.
Limitations and Suggestions for Future Research
Several limitations of the current study warrant mention and suggest that further work on this topic is needed. First, the current study only examined reactions to a single sport (basketball). Future research should attempt to replicate the current findings with other sports, preferably in the same study, which would allow for comparisons across sport (e g Wann, Grieve, Zapalac, & Pease, 2008). In particular, investigators may want to examine the impact of fan dysfunction and team identification in reaction to an aggressive athletic event (e.g., football, rugby, and hockey). A number of studies have found that the sport in question can be an important factor in predicting fan aggression. Specifically, spectators at aggressive sporting events typically report higher levels of aggression than persons attending nonaggressive sporting competition (Arms, Russell, & Sandilands, 1979; Goldstein & Anns, 1971; Wann et al., 2000). Given this, replicating the present study within the confines of an aggressive sport is warranted to examine the generalizability of the current findings. Further, this study should be replicated for fans witnessing sports with a history of vocalizations and verbal aggression. For example, spectators attending English Premier League Football (soccer) matches have a long-standing tradition of singing well-established songs. These fans also frequently make up new songs they share on social media and in pubs for others to learn and sing at games. Often, these songs contain aggressive content targeting opposing players, managers, and teams as well as, on occasion, home town players/ managers. Researchers should replicate the current work with fans such as these, spectators with a clear tendency toward verbal aggression.
Additionally, future endeavors should examine fan reactions to games with a different outcome. In the current work, the participants witnessed a game that was won handily by the home team. In fact, the home team held a commanding lead throughout the contest and the outcome was never truly in jeopardy. The fact that only one type of game was tested is a limitation of the current work given that multiple studies have found that the outcome of a sporting event can have an impact on fan reactions (e.g., Sloan, 1989; Wann et al., 1994). This literature indicates that it is not simply success or failure that is critical but, in addition, the magnitude of the outcome (e.g., an easy, lopsided win can result in responses that differ from reactions to a difficult win). As a result, future examinations should investigate the impact of identification and dysfunction on hostile and instrument aggressive responses to games the favored team lost as well as games the favored team won with a high level of difficultly (e.g., a narrow margin of victory). Based on previous work on game outcome (Wann et al, 1994), one could predict that the reactions may be intensified in these types of contests (i.e., aggression would be more frequent at losses and close wins).
A third limitation that warrants mention concerns the fact that hostile and instrumental aggression were only assessed after the contest and not when the aggressive verbalizations occurred. In other studies, researchers have occasionally examined fan reactions over at multiple times during a game to assess a pattern of response (e.g., Wann, Schrader, & Adamson. 1998). Investigators may want to employ a similar longitudinal strategy to examine the hostile and instrumental aggression of highly identified and dysfunctional sport fans. Certain types of aggression may be more likely to occur at specific points during a competition. For instance, because hostile aggression involves anger, this form of aggression may be more common during the latter parts of a competition, after the fan has had ample time to become angered. Conversely, instrumental aggression may be more common earlier in the contest as fans attempt to influence a competition that has not yet been decided.
In conclusion, the current study was designed to expand previous efforts on the verbal aggression of sport fans (e.g., Wann, Carlson, et al. 1999; Wann et al., 2000) by incorporating fan dysfunction, as well as team identification, in the design. Data collected from college student spectators at a Division I men's basketball game indicated that highly identified and highly dysfunctional fans had both similarities and differences in their hostile and instrumental verbal aggression. Both identification and dysfunction were positive predictors of total aggression and instrumental aggression. However, only dysfunction predicted hostile aggression, as team identification was not reliably related to this type of aggression. Interactions between team identification and fan dysfunction were not found on any of the analyses. Future researchers should replicate and expand on the current investigation by examining different sports (particularly aggressive sports), different outcomes (particularly close wins and losses), and assessing the timing of fan aggression (e.g., early versus later in the contest).
Daniel L. Wann, Paula J. Waddill, Danielle Bono,
Holly Scheuchner and Kristen Ruga
Murray State University
Address correspondence to: Daniel L. Wann, Department of Psychology, Murray State University, Murray, KY 42071 or to firstname.lastname@example.org via Internet.
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Table 1 Means, Standard Deviations, and Cronbach Reliability Alphas for the Measures. Measure Mean SD Alpha Fan Dysfunction (DFQ) (a) 20.09 11.32 .850 Team Identification (SSIS) (b) 43.45 9.71 .885 Hostile Aggression toward 6.45 3.89 .645 Officials (HAOFF) (c) Instrumental Aggression toward 5.93 4.57 .899 Officials (1A0FF) (c) Hostile Aggression toward 5.52 3.91 .716 Opponents (HAOPP) (c) Instrumental Aggression toward 6.44 5.08 .964 Opponents (HAOPP) (c) Instrumental Aggression (IA) (d) 12.37 9.34 .953 Hostile Aggression (HA) (d) 11.97 7.57 .867 Aggression Toward Officials 12.38 7.62 .834 (ATOFF) (d) Aggression Toward Opponents 11.95 8.27 .881 (ATOPP) (d) Total Aggression (TA) (e) 24.34 15.51 .929 Notes: (a) potential range = 5 to 50; (b) potential range = 7 to 56; (c) potential range = 2 to 16; (d) potential range = 4-32; (e) potential range = 8 to 64. Table 2 Correlations among the Measures. Measure 1 2 3 4 Fan Dysfunction (DFQ) (1) -- Team Identification (SSIS) (2) .38 ** -- Hostile Aggression toward .43 ** .34 ** -- Officials (HAOFF) (3) Instrumental Aggression .41 ** .39 ** .62 ** -- toward Officials (IAOFF) (4) Hostile Aggression toward .38 ** .28 * .86 ** .65 ** Opponents (HAOPP) (5) Instrumental Aggression .36** .29 * .59 ** .87 ** toward Opponents (HAOPP) (6) Instrumental .39 ** .34 ** .62 ** .96 ** Aggression (IA) (7) Hostile Aggression (HA) (8) .42** .32 * .97 ** .66 ** Aggression Toward .67 ** .40 ** .88 ** .92 ** Officials (ATOFF) (9) Aggression Toward Opponents .40 ** .31 * .78** .85 ** (ATOPP) (10) Total Aggression (TA) (11) .44 ** .36 ** .85 ** .90 ** Measure 5 6 7 8 Fan Dysfunction (DFQ) (1) Team Identification (SSIS) (2) Hostile Aggression toward Officials (HAOFF) (3) Instrumental Aggression toward Officials (IAOFF) (4) Hostile Aggression toward -- Opponents (HAOPP) (5) Instrumental Aggression .69 ** -- toward Opponents (HAOPP) (6) Instrumental .69 ** .97 ** -- Aggression (IA) (7) Hostile Aggression (HA) (8) .97 ** .66 ** .68 ** -- Aggression Toward .84 ** .82 ** .90 ** .89 ** Officials (ATOFF) (9) Aggression Toward Opponents .90 ** .94 ** .93 ** .86 ** (ATOPP) (10) Total Aggression (TA) (11) .89 ** .91 ** .93 ** .90 ** Measure 9 10 11 Fan Dysfunction (DFQ) (1) Team Identification (SSIS) (2) Hostile Aggression toward Officials (HAOFF) (3) Instrumental Aggression toward Officials (IAOFF) (4) Hostile Aggression toward Opponents (HAOPP) (5) Instrumental Aggression toward Opponents (HAOPP) (6) Instrumental Aggression (IA) (7) Hostile Aggression (HA) (8) Aggression Toward -- Officials (ATOFF) (9) Aggression Toward Opponents .91 ** -- (ATOPP) (10) Total Aggression (TA) (11) .97 ** .98 ** -- Notes: * = p < .01; ** < .001. Table 3 The Roles of Identification and Dysfunction in Predicting Forms of Verbal Aggression and Target of Aggression Instrumental Hostile Predictors Step 1 Step 2 Step 1 Step 2 Team .23 * .28 * .18 .17 identification Fan dysfunction .31 ** .24 * .35 ** .37 ** Identification x .18 -.06 Dysfunction [R.sup.2] .20 .23 .21 .21 [DELTA][R.sup.2] .20 .03 .21 .00 Overall F 10.71 *** 8.27 *** 11.08 *** 7.44 *** Officials Opponents Predictors Step 1 Step 2 Step 1 Step 2 Team .26 *** .27 *** .18 .22 * identification Fan dysfunction .37 *** .36 ** .33 ** .28 * Identification x .02 .13 Dysfunction [R.sup.2] .28 .28 .19 .20 [DELTA][R.sup.2] .28 .00 .19 .01 Overall F 16.57 *** 19.94 *** 9.88 *** 7.11 *** Total Aggression Predictors Step 1 Step 2 Team .23 * .25 * identification Fan dysfunction .36 ** .33 ** Identification x .08 Dysfunction [R.sup.2] .24 .24 [DELTA][R.sup.2] .24 .01 Overall F 13.53 *** 9.16 *** Note. All regression coefficients are standardized values ([beta]). * p < .05. ** p< .01. *** p <. 001. Table 4 Moderated Multiple Regression Analyses Predicting Forms of Verbal Aggression as a Function of the Target Opponents Instrumental Hostile Predictors Step 1 Step 2 Step 1 Step 2 Team identification .27 * .32 ** .20 .16 Fan dysfunction .32 ** .26 * .36 ** .41 *** Identification x .14 -.13 Dysfunction [R.sup.2] .23 .25 .22 .24 [DELTA][R.sup.2] .23 .02 .22 .02 Overall F 12.87 *** 9.33 *** 12.32 *** 8.81 *** Officials Instrumental Hostile Predictors Step 1 Step 2 Step 1 Step 2 Team identification .18 .24 * .15 .16 Fan dysfunction .29 ** .22 * .33 ** .32 ** Identification x .20 .01 Dysfunction [R.sup.2] .13 .16 .17 .17 [DELTA][R.sup.2] .13 .03 .17 .00 Overall F 7.74 ** 6.45 ** 8.56 *** 5.65 ** Note. All regression coefficients are standardized values ([beta]). * p< .05. ** p < .01. *** p< .001.
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|Author:||Wann, Daniel L.; Waddill, Paula J.; Bono, Danielle; Scheuchner, Holly; Ruga, Kristen|
|Publication:||Journal of Sport Behavior|
|Date:||Dec 1, 2017|
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