Exploring Sports Television Viewers Judgments of Athletes Antisocial Behaviors

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1 ORIGINAL RESEARCH International Journal of Sport Communication, 2010, 3, Human Kinetics, Inc. Exploring Sports Television Viewers Judgments of Athletes Antisocial Behaviors Adam C. Earnheardt Youngstown State University, USA The extent to which television viewers are fans of sports and their motivation for viewing sports may affect their judgments of athletes antisocial behaviors. The uses and gratifications theoretical framework guided exploration of possible predictors of judgments. The sample (N = 347) consisted of sports television viewers. Fandom correlated significantly with motives for viewing televised sports, parasocial interaction, and identification. Fandom was negatively related to judgments of violent crime behaviors and uncharitable/dishonest behaviors. Women who were engaged in other activities while viewing televised sports were more likely to judge violent crime behaviors as most wrong, or negatively. Additional analyses suggested that women who reported lower degrees of fandom, weaker affinity for televised sports, weaker intention to watch sports, weaker self-esteem/achievement and entertaining relaxation motives, and paying less attention to televised sports were the viewers who tended to judge athletes violent crime behaviors, uncharitable behaviors, and drug- and steroid-use behaviors as most wrong. Keywords: athlete behaviors, uses and gratifications, fandom Stories of criminal activities and antisocial behaviors demonstrated by athletes have been well documented over the last 25 years. Athlete behaviors that have received news coverage include the use of recreational and performance-enhancing drugs, illegal gambling, sexual misconduct, and murder. The extent to which television viewers are fans of athletes may affect their judgments of antisocial behaviors exhibited by those athletes. There is concern that the antisocial behaviors of athletes will lead some fans to model those behaviors (Brown, Basil, & Bocarnea, 2003). Although some suggest that athletes have a responsibility to serve as role models for fans (Lines, 2001), questions concerning fans judgments of athletes behaviors have not been tested empirically. This study was conducted to examine the extent to which television viewers are fans of sports affects judgments of antisocial behaviors demonstrated by athletes. Understanding television viewers interest in individual athletes is important to the study of societal values and ideologies. Researchers have found that affective attachment with athletes led to certain beliefs about what behaviors fans would The author is with the Dept. of Communication, Youngstown State University, Youngstown, OH. 167

2 168 Earnheardt deem acceptable for their favorite athletes (Wenner & Gantz, 1989). There are a number of variables that may work together to mediate the relationship between fandom and judgments of athlete behaviors, including affinity for televised sports (Mahony & Moorman, 2000), activity before and during sports viewing (Melnick & Wann, 2004), involvement with televised sports (Shank & Beasley, 1998), exposure to sports (Gantz & Wenner, 1991), and interaction with athletes (Fink, Trail, & Anderson, 2002). Overall, this study examines possible predictors of television viewers judgments of athlete behaviors. It extends the theory of uses and gratifications research as it relates to viewers connections with athletes and motives for consuming sports on television. Furthermore, it explores sports television viewers perceptions of behaviors displayed by mediated characters. Literature Review Uses and gratifications theory is an audience-centered, media-effects perspective focusing on the individual factors that influence effects. It is built on five tenets: (a) Audience members are goal-directed, purposive, and motivated in their selection of media; (b) audience members actively select media based on coherent, self-perceived desires to fulfill goals, with an understanding that some media channels will fulfill certain goals and others will not; (c) audience members psychological and sociological differences affect media selection and the members abilities to fulfill goals; (d) audience members use different media to fulfill needs, suggesting that people will use other forms of media to fulfill the same goals when the desired (or primary) medium is not available; and (e) based on the level of audience initiative and individual characteristics, the audience has the power to be more influential than the media in the audience media relationship (Katz, Blumler, & Gurevitch, 1974; Rubin, 2002). Uses and gratifications theory provides media scholars with guiding tenets for understanding individual differences among audience members, media-use activities, motives for consuming media, and the outcomes, or effects, associated with media use. We know, for example, that uses and gratifications helps explain (1) the social and psychological origins of (2) needs, which generate (3) expectations of (4) the mass media or other sources, which lead to (5) differential patterns of media exposure (or engagement in other activities), resulting in (6) need gratification and (7) other consequences, perhaps unintended ones. (Katz et al., 1974, p. 20) Thus, uses and gratifications can offer practical directions for examining the relationships among fandom (i.e., social and psychological origin), motives for viewing sports, affinity for and intention to watch televised sports (i.e., expectations), exposure to televised (i.e., mass-media) sports, involvement and attention while viewing (i.e., patterns of exposure), interaction with athletes in the forms of parasocial interaction and identification, and the outcomes related to watching televised sports, such as viewers judgments of athlete behaviors (i.e., other consequences). Research guided by this perspective has revealed a variably engaged audience, selective in their media use and variably involved with media content. People display an affinity with specific media channels and content and participate in activities related to the media content before and during exposure, such as planning to view

3 TV Viewers Judgments of Athletes Behaviors 169 television shows and talking about television content with others (Levy & Windahl, 1984). In the audience media use effects relationship, it is the audience member who is most influential. Examining motives to watch television can help explain the process of media selection, use, and effects (Katz et al., 1974; Rubin, 1981). In the study of televised sports effects, it is important to look at degrees of fandom and individual differences that may influence opinions about athlete behaviors. Fandom Cohen (2001) argued that liking, being similar to, and having affinity with a mediated personality serve as indicators of fandom. However, Gantz and Wenner (1995) noted that a persistent problem in sports-media-effects research is the different descriptions of fandom and what constitutes a fan. Many studies have used the terms fan and spectator interchangeably. They identified three distinct fandom categories that included (a) fans, or true believers, deeply committed to their team and vested in the outcome of the contest; (b) spectators, or mere observers of the contest; and (c) nonfans, or those not necessarily interested in sports but watching to be with others and fulfill companionship motives. Fans often have favorite athletes, whereas nonfans often are not able to identify favorite athletes. Similar research has provided evidence of relationships between levels of fandom, exposure to sports, and other concepts related to sports television viewing. For example, researchers have examined links between fandom and motives for watching sports (Kahle, Kambara, & Rose, 1996; Trail & James, 2001), involvement and behaviors (Shank & Beasley, 1998), watching favorite and disliked athletes (Mahony & Moorman, 2000), and community integration (Wann & Robinson, 2002). It appears that fandom is a social and psychological characteristic that fits within the uses and gratifications theoretical framework for understanding outcomes related to television exposure. For example, other researchers have identified connections between fandom and perceptions of influence on contest outcomes (Wann, Dolan, McGeorge, & Allison, 1994), as well as fandom and gender (Melnick & Wann, 2004). Gender Just as with fandom, gender is a background characteristic that people bring with them to the sports-television-viewing experience. For example, we know that men more than women tend to describe themselves as fans of sports (Melnick & Wann, 2004). There are also differences between men and women in exposure to and interest in televised sports (Gantz & Wenner, 1991). For example, men more than women watch sports on television (Sargent, 2003) and favor sports news (Perse, 1990). Men tend to be more involved in sports than women (Gantz & Wenner, 1991), and the sports content that men consume tends to be more violent and combative, whereas women prefer content that is more graceful and stylistic (Sargent, 2003). Other studies have examined gender differences based on audience activity and the motives men and women have for watching sports (Melnick & Wann, 2004). Motives Motivation is a key concept in the study of media effects (Rubin, 2002). Uses and gratifications research has produced several motive typologies to guide research

4 170 Earnheardt of televised sports effects. Early uses and gratifications studies identified various motives for watching television, including entertainment, social utility, excitement, to pass time, companionship, and information (Rubin, 1983), as well as curiosity, diversion, and identity (Blumler, 1979). Later television-viewing-motives research used the same, or similar, typologies. The same cannot be said for studies of sportsviewing motives. Researchers have identified particular motives for sports viewing with little consistency among the motive typologies. Therefore, an examination of television-viewing-motives research, sports-viewing-motives research, and a comparison of the motives identified is required. Just as some researchers have linked motives to specific types of media genres (Rubin, 1983) such as news (Rubin & Perse, 1987), media channels such as radio (Rubin & Step, 2000), and the Internet (Papacharissi & Rubin, 2000), other researchers have focused on motives for consuming televised sports specifically, albeit with different motive typologies. If, as uses and gratifications theory suggests, media selection is purposive and motivated, it is necessary to examine connections between sports television viewing and viewing motives such as entertainment and information seeking. There have been studies of sports-viewing motives in which varied typologies were offered (Kahle et al., 1996; Trail & James, 2001). Rubin (1979) presented a media-use typology as part of an analysis of television-viewing motives and honed the motive typology in a later study to develop the Television Viewing Motives Scale (TVMS; Rubin, 1981). Of the motives that emerged as significant predictors of viewing specific content, Rubin (1981) found arousal to be a salient predictor of sports viewing. However, several other motives (e.g., escape, pass time, relaxation) were weaker but still significantly correlated with television sports viewing. Trail and James (2001) constructed a measure titled the Motivation Scale for Sports Consumption. Motives for watching sports on television included, in part, achievement (e.g., to feel accomplishment when an athlete wins), aesthetics (e.g., to experience the beauty of sports), and social utility (e.g., to watch with others). Robinson and Trail (2005) examined sports-viewing motives in relation to perceived levels of attachment to athletes. Of the motives that were examined, achievement, a significant predictor of sports viewing in previous studies, was found to be the strongest predictor of attachment to favorite athletes. This finding is significant because it suggests a connection between attachment to favorite athletes and motives for viewing televised sports. It is possible that increased fandom may lead to motives for viewing sports and stronger levels of attachment to favorite athletes. In addition to viewing motives and fandom, attraction to televised sports may provide some information on the judgments people make about athlete behaviors. Affinity Understanding affinity for television may help explain exposure to televised sports. The greater the intensity one reports for using television to fulfill daily goals, the greater the level of affinity one has for television (Greenberg, 1974). Mahony and Moorman (2000) examined affinity for televised sports by exploring connections between sports fandom, intention to watch televised sports, and perceived attachment to athletes. They found that even when neutral and disliked athletes are playing, sports fans had some level of affinity for sports and televised sports. It stands to

5 TV Viewers Judgments of Athletes Behaviors 171 reason then that some fans may be more likely than spectators and nonfans to watch televised sports when their favorite athlete is competing. Therefore, it is necessary to understand how affinity is related to exposure and the activities in which fans and nonfans participate before and during televised sporting events. Exposure and Audience Activity Exposure is perhaps the most important variable in media-effects research and is one of the most difficult concepts to measure. Wenner (1989) argued that differences in exposure to sports should be assessed, and experiences related to sports exposure should be studied. For example, stadium experiences may produce significantly different effects than viewing the same contest at home on television. Likewise, watching a game on television might provide a greater sense of gratification than searching for information on the Internet (Perse & Ferguson, 2000). Although sports continue to flourish on many media channels, television is the primary channel for broadcasting and consuming sports entertainment and information (Janis, 2001). Television viewers can order special events through payper-view and watch channels with specialized sports content (e.g., golf channel, racing channel). For many fans, television provides the main access to the stadium experience. For favorite athletes and stadium venues that are great distances from the sports fan, television serves as an outlet to view the live sporting event. Audience activity reflects the stages (intention to watch, attention while watching) through which people move in their voluntary use of the media. Levy and Windahl (1984) examined audience activity using a measure that assessed activity before watching television and during exposure. To better clarify the differences in activities, Rubin and Perse (1987) defined preexposure activity as intention, or the extent to which viewers purposively seek and plan media use (e.g., seek out and plan to watch specific television content). During exposure activity was defined as the amount of attention viewers paid to the television content and the extent to which they participated in distracting activities. Involvement Involvement has been defined as a person s perceived relevance of the object based on inherent needs, values, and interests (Zaichkowsky, 1985, p. 341). Shank and Beasley (1998) examined the relationship between sports involvement and sports television viewing. They found that involvement, or the extent to which televised sports are relevant and fulfill needs, was a good predictor of sports television viewing. Highly involved fans spent significantly more time watching sports on television. In addition, Shank and Beasley found that cognitive and affective dimensions of involvement were related to sports television viewing. This study shows that sports fans are active and aware of their behaviors and attitudes associated with watching televised sports. Involvement with televised sports may play an important role in the perceptions sports television viewers have of athlete behaviors. In addition, exposure, audience activity, and involvement may be linked to interaction with athletes, such as parasocial interaction and identification. For example, Rubin and Perse (1987) found links between the activities of television viewers and parasocial interaction.

6 172 Earnheardt Interaction With Athletes Television viewers vary in their relationships with television personalities and characters based on the level of interaction they have with those personalities and characters (Cohen, 2001; Cohen & Perse, 2003; Robinson & Trail, 2005). People may develop parasocial relationships (one-sided pseudo-friendships) and identify with particular television personalities. The same might be said for parasocial interaction and identification with athletes. Horton and Wohl (1956) originally coined the term parasocial interaction to define the relationships audience members develop with media personalities and characters. In relation to televised sports, another point of attachment is identification. In addition to parasocial interaction, identification may serve as a distinctly different form of interaction people have with athletes. It may be useful to understand identification as a form of attachment because it may serve as a link to fandom. Specifically, people who identify highly with athletes tend to be fans. Furthermore, the strength of the relationships fans have with athletes may provide an understanding of their judgments of athlete behaviors. Cohen (2001) noted that identification is a process that culminates in a cognitive and emotional state in which the audience member... imagines being one of the characters (p. 252). Identification, therefore, can be likened to a daydreaming state in which the identifier (i.e., viewer) becomes unaware of his or her own attributes (physical, emotional) and assumes the attributes of the identified personality. Cohen and Perse (2003) speculated that the merging of the viewer and the personality signaled an absence of viewer self-awareness. Understanding the relationship between fandom and judgments of athlete behaviors, while accounting for the influences of parasocial interaction and identification, is important before considering whether fans accept the behaviors of favorite athletes. For example, fans may have a qualitatively different, deeper, and more textured set of experiences (Gantz & Wenner, 1995, p. 57) than nonfans with televised sports. This suggests that fans may have stronger feelings about their connections to favorite athletes. In a sense, fandom is connected to parasocial interaction and identification. Judgments of Behaviors Consequences related to the audience experience with mediated sports (e.g., rioting, drug use, excessive drinking, gambling) are well documented in the literature (e.g., Wenner, 1989). Athlete antisocial behaviors referenced in the literature include gambling, drug use (recreational and performance enhancing), and sexual deviance (McChesney, 1989; Gantz & Wenner, 1991). Understanding these antisocial behaviors, as well as approval or disapproval of these behaviors among viewers, is greatly important to the overall study of televised sports effects. Before we can examine the effects of athlete behaviors, we must explore viewers judgments of those behaviors. The overall goal of this study was to explore how some antecedents may work in concert to explain judgments of antisocial behaviors.

7 TV Viewers Judgments of Athletes Behaviors 173 Hypotheses and Research Questions Several studies have been conducted in which researchers speculated about the effects of viewing televised sports. To date, uses and gratifications research, as well as studies specifically focusing on mediated sports effects, has yet to examine the effects of potential antecedents on viewers judgments of behaviors exhibited by athletes. Fandom studies often are focused on demographic variables such as gender and age and rarely explore the potential effects of viewing mediated sports. Therefore, the following research questions and hypotheses were proposed. First, it is important for mass-media scholars to know how fandom relates to motivation for viewing televised sports, because motives help predict affinity for and exposure to a medium (e.g., Greenberg, 1974). For example, strength of motives has been used to examine differences in fandom levels (Fink et al., 2002). People who identified with favorite athletes and teams were more likely to have strong motives for viewing sports. However, strength of motives is only one aspect of motive analysis in uses and gratifications research.rubin (2002) noted that an early criticism of motive research was the lack of clearly defined motives people have for using particular media content. It is still unclear what motives people have for watching televised sports when varying fandom levels are considered. Thus, the following question was proposed: RQ1: What are the motives people have for watching televised sports? Second, we know that various motives for watching television (e.g., arousal, entertainment, escape, relaxation, information seeking, pass time, and social utility) influence media use and effects (Rubin, 1983). Similar motives have been linked to watching televised sports (Gantz & Wenner, 1991; Kahle et al., 1996). Motives specific to watching televised sports included achievement, aesthetics, and selfesteem (Trail & James, 2001). Testing assumptions about sports-television-viewing motives is an important precursor to examining the antecedents of judgments of athletes antisocial behaviors. If, as the guiding tenets of uses and gratifications theory suggest, social and psychological origins (such as fandom) lead to needs and expectations (motivations), then it is possible that these variables serve as predictors of judgments of athlete behaviors. Therefore, the following hypothesis was proposed: H1: Higher levels of fandom are related positively to achievement, aesthetics, and self-esteem motives for watching televised sports. Third, people often feel connected with television personalities such as favorite athletes. Uses and gratifications theory suggests that social and psychological origins (e.g., fandom) lead, in part, to need gratifications and other consequences such as parasocial interaction and identification. This suggests that some television viewers watch to connect with television personalities and characters. Cohen (2001) described several types of connections, or interaction types, viewers have with mediated characters and personalities. It stands to reason that people may develop strong parasocial relationships and identify with favorite athletes much

8 174 Earnheardt the same way they do with other mediated characters and personalities. Those relationships are likely correlated with fandom. Thus, the following hypotheses were proposed: H2a: Higher levels of fandom are related positively to parasocial interaction with athletes. H2b: Higher levels of fandom are related positively to identification with athletes. Fourth, Dietz-Uhler, End, Demakakos, Dickirson, and Grantz (2002) noted that people with high levels of fandom may be more likely than nonfans to overlook criminal acts of favorite athletes. When sports fans were presented with scenarios in which an athlete was involved in a criminal act (experimental) and one with no criminal act (control), they were more likely than nonfans to overlook the criminal act. Nonfans may be less likely to overlook such antisocial behaviors. For example, highly avid fans may be willing to accept (e.g., have positive judgments of) athletes antisocial behaviors. Conversely, nonfans may be unwilling to accept (e.g., have negative judgments of) such behaviors. This proposed effect follows the tenets of uses and gratifications theory, which suggests there may be intended and unintended consequences based, in part, on a viewer s level of fandom (social and psychological origins). Therefore, the following hypothesis was proposed: H3: Higher levels of fandom are related positively to greater acceptance of antisocial behaviors exhibited by favorite athletes. Fifth, this study proposed to examine the relationship among fandom levels and judgments of antisocial behaviors. Previous research suggests that other factors associated with viewing televised sports (e.g., motives, affinity, exposure, audience activity, interaction), in addition to fandom, may be related to judgments of behaviors for both those who exhibit higher levels and those who exhibit lower levels of fandom. To assess whether the predictors proposed in this study may work in concert to influence judgments of antisocial behaviors, the following research question was proposed: RQ2: How do fandom levels, motives for viewing televised sports, affinity for televised sports, exposure to televised sports, audience activity before and during exposure to televised sports, involvement with televised sports, and interaction with athletes explain viewers judgments of athletes antisocial behaviors? Finally, to explore the general patterns of relationships among the levels of fandom, other antecedents in the study, and judgments of antisocial behaviors, the following research question was proposed: RQ3: What is the pattern of relationships among fandom, motives for viewing televised sports, affinity for televised sports, exposure to televised sports, audience activity before and during exposure to televised sports, involvement with televised sports, interaction with athletes, and judgments of athletes antisocial behaviors?

9 TV Viewers Judgments of Athletes Behaviors 175 Methodology A principal purpose of this study was to examine the relationship among the antecedents and judgments of antisocial behaviors. To do this, a survey was used to gather information from television viewers about the possible predictors of judgments of athletes antisocial behaviors. Uses and gratifications studies typically use a survey. The sample (N = 347) in this study consisted of undergraduate students at two Midwestern universities. Students received extra credit for participating in the study. Their mean age was years. There were more women (n = 197) than men (n = 149). The ethnic composition of the sample was primarily White (n = 286), followed by African American (n = 36), Asian (n = 7), Hispanic (n = 5), American Indian (n = 2), and other (n = 9). One participant did not report age and gender, and 2 chose not to report ethnicity. Several instruments were selected and, when necessary, adapted to collect required data. These included measures of fandom, motives, affinity, intention to watch, activities during exposure, involvement, exposure, athlete recognition, parasocial interaction, identification, judgments of athlete antisocial behaviors, and demographics. Fandom Fandom was considered the extent to which someone believes he or she is a fan of sports. Wann s (2002) Sports Fandom Questionnaire was used to gauge respondents fandom level. This survey assessed self-perception of sports fandom (i.e., the extent to which people consider themselves fans of sports). It is considered a reliable measure of fandom and has been used to study the psychological health of sports fans (Wann, 2002) and socialization (Melnick & Wann, 2004). Response options ranged from 5 (strongly agree) to 1 (strongly disagree). Sample items included I consider myself to be a sport fan and Being a sport fan is very important to me. Items were summed and averaged to get a fandom score (M = 3.23, SD = 1.15, α =.94). Motives Rubin s (1983) TVMS was adapted to measure motives for viewing televised sports. Respondents rated their reasons for watching sports on television using response options that ranged from 5 (exactly) to 1 (not at all). The revised scale assessed motives from the TVMS that included relaxation, companionship, habit, passing time, entertainment, social interaction, information, arousal, and escape. In addition to motives on the TVMS, motives gleaned from previous studies of sports television viewing were included (Melnick & Wann, 2004; Robinson & Trail, 2005). Motives that were added to the TVMS for this study included aesthetics, self-esteem, and achievement. The TVMS has proven to be a reliable measure of motives and has been adapted to measure motives for watching specific types of television content. A principal-components factor analysis with varimax rotation was conducted on the motive measure to extract the sports-television-viewing motive factors. There were 36 items on the scale consisting of 12 potential dimensions. Factors

10 176 Earnheardt with Eigenvalues of at least 1.0 and with at least two items meeting a loading criterion were deemed acceptable. Six motive factors explaining 67.62% of the variance after rotation were identified; the scree plot also indicated six motive factors. Responses to items that loaded on each factor were summed and averaged to create indexes of each viewing motive. The components can be thought of as representing (a) entertaining relaxation motivation, (b) self-esteem/achievement motivation, (c) companionship motivation, (d) learning/social-interaction motivation, (e) pass time/escape motivation, and (f) apathetic motivation. Results of the factor analysis are reported in Table 1. Affinity Rubin s (1981) Television Affinity Scale was adapted to measure affinity for televised sports. This scale has been adapted to examine affinity for different types of television content including news (Rubin, Perse, & Powell, 1985) and soap operas (Perse, 1986). Response options ranged from 5 (strongly agree) to 1 (strongly disagree). Sample items included It is important to see a sports contest from beginning to end and Whenever I m unable to watch sports on television, I really miss it. Scale items were summed and averaged to get an affinity score (M = 2.37, SD = 1.19, α =.94). Intentionality Rubin, Perse, and Taylor s (1988) Intentionality Scale (adapted from Levy & Windahl, 1984) was used to measure intention to watch televised sports. This scale has been used to measure the intentions of viewing various forms of television content (Perse, 1990; Rubin et al., 1988). Response options ranged from 5 (strongly agree) to 1 (strongly disagree). Items were summed and averaged for an intention score (M = 2.52, SD = 0.99, α =.91). Attentiveness Rubin and Perse s (1987) Attentiveness Scale was used to measure audience attention when viewing televised sports. Their scale measured how much attention people pay to the television when watching television. Viewing attention reflects the extent to which someone is engaged in (or distracted during) the televisionviewing process. Items were summed and averaged for an attention score (M = 3.27, SD = 0.54, α =.63). Involvement Shank and Beasley s (1998) Sports Involvement Inventory was used to measure involvement with televised sports. Involvement reflects the extent to which someone is involved, or interested, in viewing televised sports. Respondents indicated their interest in and the importance of sports on television using options that ranged from very closely related (either end of the scale) to neutral (middle of the scale). Scores for individual items on the scale ranged from 1 (low involvement) to 7 (high involvement). Items were summed and averaged for an involvement score (M = 5.04, SD = 1.25, α =.93).

11 Table 1 Factor Loadings of the Revised Television Viewing Motives Scale Sports-Television-Viewing Factors Motive items ENTR SELF COMP LEAR PASS APAT I watch sports on TV... Entertaining relaxation Because it s enjoyable Because it s exciting It entertains me I like to watch Because it s thrilling Because it amuses me Allows me to unwind Beauty of sports It s a pleasant rest Self-esteem/Achievement Sense of achievement So I can feel proud So I feel like I ve won Gives me confidence Increase self-esteem Companionship Won t be alone So I feel less lonely No one else to talk to Learning/Social interaction To learn about sports Learn more sports To be with family Pass time/escape To occupy my time To get away Apathetic Nothing better to do Just because it s there Eigenvalue Variance explained Cronbach s α Pearson s r.60***.59*** M SD Note. ENTR = entertaining relaxation; SELF = self-esteem/achievement; COMP = companionship; LEAR = learning/social interaction; PASS = pass time/escape; APAT = apathetic. ***p <

12 178 Earnheardt Exposure To gauge exposure, respondents were asked three questions concerning the number of hours and minutes they watch sports on television. It was important to understand how much sports television they watched on weekend days and weekdays because of the amount of sports typically aired on weekend days. First, respondents were asked how many hours and minutes they watched sports on television yesterday. Second, they were asked how many hours and minutes they watched sports on television on an average weekday. Third, they were asked to indicate how many hours and minutes of sports they watched on television during an average weekend day. This method of measuring exposure has proven to be reliable in previous studies (Bissell, 2004; Rubin et al., 1985). Hours and minutes for yesterday, average weekday, and average weekend day were averaged for an exposure score. The mean for televised sports exposure was min (SD = , α =.83) per day. Parasocial Interaction Rubin and McHugh s (1987) 10-item Parasocial Interaction Scale (PSI), adapted from Rubin et al. s (1985) original 20-item scale, was used to measure parasocial interaction with athletes. Parasocial interaction refers to the connection, and potential relationship, television viewers have with mediated characters or television personalities (Horton & Wohl, 1956). Response options ranged from 5 (strongly agree) to 1 (strongly disagree). The scale consisted of items that reflected those potential relationships. Items were adapted to reflect sports television content. Sample items included I miss seeing my favorite athlete when he or she is not on and I think of my favorite athlete as an old friend. To date, the PSI is the most-used measure of parasocial relationships. Responses to items on the PSI were summed and averaged to create a parasocial-interaction index (M = 3.35, SD = 0.79, α =.88). Identification Cohen and Perse s (2003) Identification Scale was used to assess identification with athletes. This 10-item measure was first proposed in a review that identified differences between parasocial interaction and identification (Cohen, 2001). Response options ranged from 5 (strongly agree) to 1 (strongly disagree). The scale consisted of items that assessed the extent to which a viewer identified with a television personality or character. Sample items were adapted for this study and included statements such as While watching my favorite athlete I forget myself and I can get into my favorite athlete s head. Items on the scale were summed and averaged to calculate an identification index (M = 2.96, SD = 0.95, α =.93). Judgments of Behaviors An adaptation of Crissman s (1942) Moral Behavior Scale was used to measure judgments of athletes antisocial behaviors. The scale has been used to measure perceptions of moral ideology (Bovasso, Jacobs, & Rettig, 1991). Respondents judged behaviors using wrongness response options ranging from 1 (least wrong) to 10 (most wrong). Lower scores reflected less negative judgments of behaviors.

13 TV Viewers Judgments of Athletes Behaviors 179 Sample items from the scale included illegally bets on sports and used profane language. For purposes of this study, respondents were asked to evaluate each act in terms of their favorite or best-known athlete. Because new items were added to the original scale (e.g., questions about steroid use, drug use), a factor analysis was conducted. Factors with Eigenvalues of at least 1.0 and with at least two items meeting a loading criterion were retained. Responses to items that loaded on each factor were summed and averaged to create indexes of each judgment factor. Data collected from the adapted Moral Behaviors Scale were analyzed by means of a principal-components analysis with varimax rotation. Four factors with Eigenvalues greater than 1.0 were found, explaining 63.09% of the variance after rotation. A scree plot confirmed the following four-factor solution: (a) violent crime, (b) drug/steroid use, (c) forging checks/ failing to keep promises, and (d) uncharitable/dishonest behaviors. Results of the factor analysis are reported in Table 2. Table 2 Factor Loadings of the Moral Behaviors Scale Moral-Behavior Factors Behavior items VIOL DRUG CHEK CHAR Violent crime Killed a person Raped a person Kidnapped a person Robbed a person Hit and run Drug use Used illegal drugs Used steroids Bad checks/promises Forged a check Failed to keep promises Uncharitable/Overcharge Kept overcharge Did not give to charity Eigenvalue Variance explained Cronbach s α.88 Pearson s r.59***.62***.49*** M SD Note. VIOL = violent crime; DRUG = drugs/steroids; CHEK = forging checks/failing to keep promises; CHAR = being uncharitable/dishonest. ***p <.001.

14 180 Earnheardt Results RQ1 inquired about the reasons fans watch televised sports. Answering this question required a two-step process. In the first step, a factor analysis of the revised TVMS was conducted (see Table 1). In the second step, tests were conducted to see whether fandom correlated with each of the six motives. There were significant positive correlations between fandom and entertaining relaxation (r =.79, p <.01), self-esteem/achievement (r =.58, p <.01), companionship (r =.35, p <.01), learning/social interaction (r =.42, p <.01), and pass time/escape (r =.52, p <.01) motivations. There was a significant negative correlation between fandom and apathetic motivation (r =.11, p =.05). These results suggest that people who exhibited higher levels of fandom were more likely than their counterparts to view sports for entertainment, relaxation, self-esteem, achievement, companionship, learning about sports, interacting socially with family and friends, passing time, and escape. On the other hand, people who exhibited higher levels of fandom were less likely than their counterparts to view televised sports out of apathy (i.e., nothing better to do). H1 posited that fandom would be related positively to motives of achievement, aesthetics, and self-esteem. There were significant positive correlations between fandom and achievement motivation (r =.53, p <.01), fandom and aesthetics motivation (r =.70, p <.01), and fandom and self-esteem motivation (r =.58, p <.01). These findings supported H1. H2a stated that fandom would be positively related to parasocial interaction with athletes. There was a significant positive correlation between fandom and parasocial interaction (r =.49, p <.01). H2b stated that fandom would be positively related to identification with athletes. There was a significant positive correlation between fandom and identification (r =.54, p <.01). These findings supported H2a and H2b. H3 suggested that fandom would be related to more positive judgments of antisocial behaviors exhibited by favorite or well-known athletes. Based on the results of the factor analysis, four separate correlations were conducted to test this hypothesis. There was a significant, but weak, negative correlation between fandom and violent-crime judgments (r =.12, p <.05). There also was a significant, but weak, negative correlation between fandom and uncharitable/dishonest judgments (r =.16, p <.01). However, there was no significant correlation between fandom and drug- and steroid-use judgments (r =.01, p =.80) or between fandom and judgments of forging checks/failing to keep promises (r =.02, p =.67). Therefore, because H3 posited that fandom would be related to more positive judgments of antisocial behaviors exhibited by favorite or well-known athletes, the hypothesis was only partially supported. These results suggest that people who reported greater fandom were less likely than their counterparts to judge violent crime and uncharitable/dishonest behaviors negatively. RQ2 inquired about the contributions of fandom, motives for viewing sports, affinity for televised sports, viewer intention to watch televised sports, exposure to televised sports, attention during exposure to televised sports, involvement with televised sports, and interaction with athletes (parasocial interaction, identification) to predicting judgments of athlete behaviors.

15 TV Viewers Judgments of Athletes Behaviors 181 Four path analyses were conducted to answer RQ2. However, only three relevant path analyses are shown (i.e., paths to violent crime, drug and steroid use, uncharitable behaviors). These analyses revealed significant paths among predictors. Figure 1 presents the results of the path analysis related to the sports television viewers judgments of athletes antisocial behaviors. Female gender (β =.24, p <.001) and attention (β =.13, p <.05) contributed directly to judgments of violent-crime behaviors. The path analysis for judgments of violent-crime behaviors explained 11.2% of the variance, R =.34, R 2 =.11, F(15, 330) = 2.77, p <.001. There were also several indirect paths between predictors and judgments of violent-crime behaviors. Learning/social-interaction motivation was linked directly with attention, which influenced judgments of violent-crime behaviors. Exposure was linked directly with attention, which influenced judgments of violent-crime behaviors. Thus, it appears that learning/social-interaction motivation and exposure indirectly influenced judgments of athletes violent-crime behaviors through lack of attention (distracting-type activities). The results of the path analysis of judgments of drug- and steroid-use behaviors are depicted in Figure 1. Only gender (β =.20, p <.01) contributed directly to judgments of drug/steroid-use behaviors. The path analysis for drug- and steroid-use judgments explained 10.1% of the variance, R =.32, R 2 =.10, F(15, 330) = 2.48, p <.01. There were no indirect paths to judgments of drug and steroid use. Gender (β =.18, p <.01) emerged as a significant predictor of judgments of athletes who were uncharitable and dishonest. The path analysis for judgments of uncharitable and dishonest behaviors explained 7.4% of the variance, R =.27, R 2 =.07, F(15, 330) = 1.76, p <.05. There were no indirect paths to uncharitable/ dishonest-behavior judgments. In summary, these results suggest that female gender and attention contributed directly to judgments of violent-crime behaviors. Indirect paths to judgments of violent-crime behaviors included learning/social-interaction motivation and exposure, both of which linked directly to attention, which influenced judgments of violent-crime behaviors. Female gender was the only predictor to contribute directly to judgments of drug and steroid use and judgments of uncharitable and dishonest behaviors. Figure 1 Direct and indirect paths to judgments of violent crime, drug and steroid use, and uncharitable/dishonest behaviors. *p <.05. **p <.01. ***p <.001.

16 182 Earnheardt RQ3 inquired about the pattern of relationships among fandom, motives for viewing televised sports, affinity for televised sports, exposure to televised sports, audience activity before and during exposure to televised sports, involvement with televised sports, interaction with athletes (parasocial interaction, identification), and judgments of antisocial behaviors. Once again, the influence of gender was considered during this analysis because of previous studies that stressed the importance of controlling for the differences between men and women in sports-media research (Wenner & Gantz, 1989). Canonical correlation was used to assess the relationship between and among the set of predictor variables (fandom, gender, affinity, intention, viewing motives, exposure, attention, involvement, parasocial interaction, identification) and the set of judgment outcomes. Items with loading values of.30 or higher were explored to draw inferences about the relationships among variables in each set, because loadings below.30 may not be stable (Lambert & Durand, 1975). Items with canonical loadings of.30 and higher are considered to significantly contribute to the relationship between the sets of variables. One significant root higher than.30 was identified (R c =.39, p <.001) and explained 13% of the variance shared by the canonical variates (see Table 3). Among the predictors (Set 1), gender and attention had positive loadings, whereas affinity, fandom, self-esteem/achievement motivation, intention, and entertaining relaxation motivation had negative loadings above.30. Among the judgment outcomes (Set 2), violent-crime, uncharitable/dishonest, and drug- and steroid-use behavior judgments had positive loadings above.30. The redundancy coefficient was.02 for the predictor set and.04 for the judgment outcome set. This suggests that although the root was statistically significant, it should be interpreted with caution because the predictors explained only 2% of the variance in the judgment outcomes, and the judgment outcomes explained only 4% of the variance in the predictors. To answer the question about the pattern of relationships among predictors and judgments of antisocial behaviors, it appears that women who reported lower degrees of fandom, weaker affinity for televised sports, weaker intention to watch sports, weaker self-esteem/achievement and entertaining relaxation motives, and paying less attention were the viewers who tended to judge athletes violent-crime behaviors, uncharitable/dishonest behaviors, and drug- and steroid-use behaviors as most wrong. Discussion This study was conducted, in part, to explore factors that may affect sports television viewers judgments of athletes antisocial behaviors. The findings in this study suggest that, regardless of fandom level, sports television viewers judged negatively most antisocial behaviors displayed by favorite athletes. It appears, then, that the concerns of critics who believe people will model antisocial behaviors of favorite athletes may be overstated and should be given more consideration in future studies. Earlier, it was proposed that the extent to which television viewers are fans of sports may affect their judgments of antisocial behaviors exhibited by their favorite or best-known athletes. As noted earlier, some critics suggest that people model athletes antisocial behaviors. However, there was little prior empirical evidence to warrant this concern.

17 TV Viewers Judgments of Athletes Behaviors 183 Table 3 Relationships Between Predictors and Behavioral Judgments Root 1 Set 1 predictors canonical loading gender.86 affinity.46 fandom.44 self-esteem/achieve motive.40 attention.33 intention.32 entertain/relax motive.31 involvement.27 exposure.27 identification.21 companionship motive.19 pass time/escape motive.18 apathy motive.08 parasocial interaction.07 learning/social motive.06 redundancy coefficient [.02] Set 2 behavioral judgments canonical loading violent crime.81 uncharitable/dishonest.64 drug use.45 forging checks/failed promises.12 redundancy coefficient [.04] Note. Root 1: R c =.39, R c 2 =.15, Λ =.73, χ 2 (60, N = 246) = , p <.001. We know from recent news stories that popular athletes continue to display antisocial behaviors. Recently, athletes have been accused of murder, convicted of rape, and found guilty of other illegal activities such as steroid use, drug use, and drunken driving. Some athletes have been accused of being dishonest, uncharitable, and untrustworthy. What was not known before this study is how viewers judge those behaviors. Judgments of what our society might consider the worst behaviors grouped together to form a violent-crime judgment factor. The behaviors on this factor included murder, rape, kidnapping, armed robbery, and hitting a pedestrian with a vehicle. This factor consisted of behaviors that traditionally lead to lengthy prison terms or capital punishment. It appears that respondents in this study were able to identify and classify behaviors based on social acceptability. It was expected that those with higher levels of fandom would judge athlete participation in violent crimes less negatively than would their counterparts. There was a significant

18 184 Earnheardt negative correlation between fandom and judgments of violent-crime behavior, suggesting that those who reported higher levels of fandom judged engagement in those activities less negatively. However, the relationship between fandom and judgments of athletes violent-crime behaviors was a weak one (r =.12). As noted earlier, drug and steroid use emerged on the next factor. It is possible that some people may perceive drug and steroid use as far less serious offenses than violent-crime behaviors in our society. However, this factor may be highly relevant to the exploration of judgments related to antisocial behaviors on the part of athletes because of the recent rise in steroid use among some athletes. Considering the amount of coverage athlete steroid use has received in the media it is no surprise to see that drug and steroid use loaded on the same factor. What is interesting, however, is that there was no significant correlation between fandom and judgments about drug and steroid use. Because there was no relationship between fandom and judgments of this behavior, it may be safe to assume that people, regardless of fandom, view steroid use as cheating and are unwilling to judge this type of antisocial behavior as acceptable (Verducci, 2005). The mean score for this factor (8.01) suggests that respondents generally rated this behavior as wrong. This is not surprising considering the number of fans who have distanced themselves from professional baseball players such as Barry Bonds, Roger Clemens, and Mark McGwire for their purported steroid use (Nightengale, 2006; Verducci, 2005). Uncharitable and dishonest behaviors grouped together. These types of behaviors suggest a level of dishonesty, but they may say something more about the perception of salaries of some professional athletes. Because some professional athletes make more money than average fans, some respondents may have perceived uncharitable and dishonest behavior negatively (Morrison, 1996). In this study, there was a significant negative correlation between fandom and judgments of uncharitable and dishonest behaviors. Although the correlation was negligible (r =.16), this relationship suggests that some respondents were unable to view their favorite athlete as uncharitable or dishonest. People who reported greater levels of fandom were more likely than their counterparts to judge violent crime and uncharitable/dishonest behaviors less negatively, suggesting that fans in this study may have been more willing to overlook these types of behaviors on the part of certain athletes. Furthermore, in relation to team sports, these fans may be judging the individual behaviors less negatively in support of the team. If the athlete is the star of the team, and the team is more likely to succeed when that athlete plays, prior research suggests that the fan may judge these behaviors less negatively for the benefit of the team (Dietz-Uhler et al., 2002). This speculation must be explored in future research. Exploring the Predictors Although fandom did not contribute significantly to judgments, the results of the path analysis reveal that it played a significant role. The path analysis revealed relationships among fandom and other predictors. When all antecedents were included in the model, fandom was a significant predictor of intention to watch televised sports and affinity for televised sports. Fandom also linked directly with entertaining relaxation motivation, learning/social-interaction motivation, pass time/escape motivation, exposure, and involvement. These findings lend support