Audience Activity and Reality Television: Identification, Online Activity, and Satisfaction

Transcription

1 Communication Quarterly Vol. 58, No. 2, April June 2010, pp Audience Activity and Reality Television: Identification, Online Activity, and Satisfaction Lisa R. Godlewski & Elizabeth M. Perse This study is an examination of audience activity in reality television. This genre was chosen because the program producers encourage activity with Web-based video footage, photos, program summaries and speculations, online discussions, and voting. Hypotheses predicted that audience viewing motives would be significant predictors of identification, online post-exposure activity, and satisfaction. In general, the study s hypotheses were supported. Identification was predicted by watching for social learning and cognitive and emotional involvement. Engaging in online activity after watching was predicted by elaboration and feeling negative emotion. Viewing satisfaction was predicted by viewing motive; cognitive and emotional involvement; and, surprisingly, less online activity after watching. Keywords: Audience Activity; Identification; Reality TV; Satisfaction; Uses and Gratifications Today s television hosts a range of popular reality television programs. No longer an off-season summer trend, reality television has become a leading prime-time program staple, often dominating the ratings in numerous coveted time slots (Andrejevic, 2004; Nielsen Media Research, 2006). Characteristically, these reality shows are unscripted programs, with nonprofessional actors as participants in a variety of situations that claim to present reality. One aspect of this genre is its interactivity. These programs not only entice viewers to watch, but they also call on the viewer to participate. Lisa R. Godlewski (M.A., University of Delaware, 2005) is now with the General Building Contractors Association, Philadelphia. Elizabeth M. Perse (Ph.D., Kent State University, 1987) is a professor and chair in the Department of Communication at the University of Delaware. This manuscript is based on Lisa R. Godlewski s M. A. thesis completed at the University of Delaware in An earlier version of this manuscript was presented at the annual conference of the National Communication Association, Chicago, Correspondence: Elizabeth M. Perse, Department of Communication, University of Delaware, Newark, DE 19716; eperse@udel.edu ISSN print/ online # 2010 Eastern Communication Association DOI: /

2 Communication Quarterly 149 Despite the sustained popularity of reality television programs (Gardyn, 2001), existent research regarding this burgeoning genre is limited, even lacking a clear definition (Hall, 2006; Nabi, Biely, Morgan, & Stitt, 2003). Instead, reality television can be described as a catch-all phrase, encompassing a host of television programs, from daytime television talk shows to unscripted game shows (Johnson-Woods, 2002). As a result, attempts to define reality television range from overly limited to overly inclusive. This article offers the following as an operational definition of reality television: unscripted programs that record real people as they live out events in their lives, as these events occur. More specifically, in an effort to define the format of reality television, two defining characteristics are proposed: Real people serve as characters, and the content is unscripted. Moreover, for some of these programs, audience participation is a central agent to the shared experience or lived reality of the program. The focus of this study is a theoretical examination of audience activity. Audience activity represents how selective people are when they approach media use and how involved they are with the content (Rubin, 1993). It is an important concept in media research because activity influences gratifications derived from media use, as well as media effects (e.g., Kim & Rubin, 1997; Perse, 1990; Rubin & Perse, 1987). Unlike many genres of television programs that allow the audience to watch without ever requiring interaction with the television program, reality programs offer the audience a participatory experience. These programs encourage activity while watching, as well as after the programs are over. Because of the nature of the programs, they encourage viewers to attend to and become involved with ordinary people in extraordinary settings (Hall, 2006; Nabi et al., 2003; Nabi, Stitt, Halford, & Finnerty, 2006). Therefore, audiences are more likely to become mentally and emotionally involved with them as they watch, and identify with the participants. The proliferation of Web sites allows viewers to review program video, watch unaired video, learn additional information about the program and the participants, discuss aspects of events and strategies with other viewers, and vote in various polls. A few interactive programs allow viewers to direct the program by voting. The focus of this study is on two types of audience activity: identification with participants and post-exposure online activity. As such, this study looks at the audiences of reality programs to test theoretical links between audience viewing motives, identification with the participants, cognitive and emotional involvement while watching the programs, and online activity after watching these programs. Based on the uses and gratifications perspective, we expect that higher levels of cognitive and emotional involvement during exposure and identification with the participants will be associated with more post-exposure activities (e.g., communicating and interacting with related program content and others via the Web). Our final focus is on how audience activity and participation are linked to audience s satisfaction with viewing the programs. Audience Activity As an audience-centered approach to mass communication research, audience activity is a central tenet of uses and gratifications. Audiences are active because they

3 150 L. R. Godlewski & E. M. Perse select media content that they believe will provide the gratifications that they are seeking. Therefore, viewing motives predict activity (Levy & Windahl, 1984; Perse, 1990; Rubin & Perse, 1987). Based on his analysis of television viewing patterns, Rubin (1984) identified two general types of television viewing: ritualistic and instrumental. A ritualistic viewer is a habitual viewer. The ritualistic viewer watches television out of habit; to pass time; for companionship, relaxation, arousal, and escape; and is characterized by a nonselective, uninvolved, and less-active use of television. In addition, ritualistic viewing focuses more on using television as a medium and less on the specific program content (Rubin, 1984; Rubin & Perse, 1987). Instrumental viewing, on the other hand, reflects selective and purposive exposure to specific television content. Research supports the idea that instrumental television is a more active and involving viewing experience (Perse, 1990; Rubin, 1984; Rubin & Perse, 1987). In other words, an instrumental use of television is reflected in planning to watch specific program content, attention to program content, cognitive and affective involvement with programs, and increased post-exposure activity (Perse, 1990; Rubin & Perse, 1987). Research has found evidence for both ritualistic and instrumental viewing of reality programs. Nabi et al. (2003), for example, found that regular viewers of the programs were more likely to watch because they were bored than were casual viewers. Other research, however, finds that reality television viewing is an instrumental experience. Hall s (2006) participants watched the programs for social utility and entertainment. Nabi et al. (2003) found that, compared to casual viewers, regular viewers of reality programs were more likely to watch the programs to learn, to compare themselves to the participants, and for entertainment. Audience activity is multidimensional (Levy & Windahl, 1984). Individuals are variably active along several dimensions and at different times in the media use process (Blumler, 1979; Kim & Rubin, 1997; Rubin & Perse, 1987). More specifically, audiences exhibit different levels of selectivity, utility, and involvement before, during, and after exposure to media content (Levy & Windahl, 1984). Different types of activity, then, contribute to different outcomes (Kim & Rubin, 1997). Involvement Involvement is a key aspect of audience activity and a central component of media effects research. Specifically, involvement as audience activity is indicative of personal engagement with the content (Perse, 1990). Involvement is defined as both the degree to which an audience member perceives a connection between him or herself and mass media content; and, second, the degree to which the individual interacts psychologically with a medium or its messages (Levy & Windahl, 1985, p. 112). Thinking about message content is a sign of cognitive involvement (Rubin & Perse, 1987). Cognitive involvement involves attention to the program, including allocating mental effort directed toward the program and to evaluating messages during reception (Perse, 1990). Elaboration or the way in which audiences interpret, attach meaning to, and respond to messages is a deeper dimension of cognitive

4 Communication Quarterly 151 involvement (Eveland, 2001; Perse, 1990; Rubin & Perse, 1987). Both attention and elaboration are suggestive of an instrumental use of media (Levy & Windahl, 1985; Rubin & Perse, 1987). Reality program viewers can be quite cognitively involved with the programs because of the suspense involved in the unfolding of the action, the novelty of the events, and the ability to peek voyeuristically into others lives (Hall, 2006; Nabi et al., 2006). A distinctive aspect of reality television is that the programs allow us to vicariously experience the real world through observation of others trials and tribulations. As a result, audience members become not only cognitively involved, but emotionally involved with the programs (Nabi et al., 2006). Emotional involvement involves a range of emotions from satisfaction and happiness, to frustration and anger (e.g., Nabi et al., 2006). Nabi et al. (2006) found that feeling happy, surprised, and relieved while watching reality programs enhanced enjoyment, whereas feeling angry lead to less enjoyment. Interactive Reality Programs and Activity This study was driven by two dominant (and somewhat innovative) aspects of reality programs that drive audience activity. The programs focus on real people acting out their real lives encourages audience interest and identification (e.g., Hall, 2006; Nabi et al., 2003; Nabi et al., 2006). The suspense, heightened interest in the programs, and availability of interactive Web technology encourages post-exposure online activity. Identification A distinctive aspect of reality television is that the programs allow viewers to vicariously experience a real world through observations of others trials and tribulations. These programs focus on the development of personal relationships, engagement in personal competitions, and the resolution of personal conflicts. Audiences are encouraged to become involved in the participants lives and to identify with them. Viewers natural curiosity about others is an important factor in the appeal and enjoyment of the programs (Nabi et al., 2003). Identification is a fleeting relationship that audiences form with a media character during exposure (Cohen, 2001). Cohen defined identification as having several aspects: imagining oneself as being the media character, adopting the perspective of the media character, becoming caught up in the action as experienced by the character, and viewing the media content from the perspective of the character. Eyal and Rubin (2003) posited identification to be linked with perceived similarity. Identification with media characters is a critical aspect of viewing involvement, and is a possible effect of active and purposive (i.e., instrumental) media use (Eyal & Rubin, 2003; Ward & Rivadeneyra, 1999). Identification is a sort of vicarious experience that occurs during media use, and is especially encouraged by reality programs. Through identification with characters, viewers experience suspense (e.g., Zillmann, 1980). As a vicarious media experience,

5 152 L. R. Godlewski & E. M. Perse identification is functional because it is a dimension of audience activity that signals that people are involved with the content (e.g., Rubin & Perse, 1987). Identification and suspense have been linked to heightened pleasure while watching media content (Zillmann, 1980) and satisfaction of arousal needs (Lawrence & Palmgreen, 1996). This study s first hypothesis focuses on the personal involvement that viewers can feel with reality show participants: H1: Identification with reality program characters will be predicted by (a) more instrumental viewing motives, (b) greater exposure to the programs, (c) perceived realism, and (d) cognitive and emotional involvement with the program. Post-Exposure Activity The second focus of this study was post-exposure activity. Reality programs offer several points of interaction using the Web. This interaction, in turn, might influence the gratifications viewers receive from these programs (Tincknell & Raghuram, 2002). Indeed, reality programs offer new forms of post-exposure activity and opportunities for additional gratifications previously unavailable to television audiences. This includes seeking additional gratifications using the Internet to participate in online activities or even through voting to influence the program s outcome. As such, interactivity creates involving experiences through the viewer s active control of the media. In addition, the use of reality programs involves not only active traditional participation of selecting and processing media messages, but also active participation in creating them as well. Therefore, in terms of voting, viewers who vote must exhibit higher levels of mental engagement in thinking about and paying attention to whom they chose to vote for. Viewers are now able to have a dialogue with the programs they watch and are no longer only message receivers, but are also active message creators (Liu & Schrum, 2002). In addition, prior research has shown that viewers are behaviorally affected based on feelings of identification. Viewers who identify with media characters are thus likely to be influenced by the character, are more satisfied with their viewing experience, and act as a result of this identification (Eyal & Rubin, 2003). Therefore, because instrumental use is marked by greater affective, cognitive, and behavioral involvement, this study assumes viewers who vote should exhibit instrumental viewing motives. Moreover, this study proposes that those motivated to explore online activities after viewing the programs would also identify with the people they see on reality programs. The real or ordinary people on these reality programs might stimulate a type of involvement that allows for deeper emotional and cognitive reactions, which, in turn, might lead to post-exposure online activity. Therefore, the second hypothesis of this study proposes the following: H2: Post-exposure activity will be predicted by (a) more instrumental viewing motives, (b) greater attention, (c) greater cognitive elaboration, (d) greater emotional involvement, (e) higher identification, and (f) greater perceived realism of the reality programs.

6 Satisfaction Satisfaction is an affective reaction to media use that reflects the gratification of viewers motives for viewing television programs. Satisfaction is an important concept because it is associated with personal fulfillment (e.g., Hecht, 1978), pleasure, positive evaluations of the program, and greater exposure to television (e.g., Perse & Ferguson, 1993). Research has shown that satisfaction is typically the result of more instrumental and active television use (Kim & Rubin, 1997; Perse & Rubin, 1988) that is, the more effort that viewers invest in watching certain programs, the more satisfied they are with viewing. Television reality programs encourage higher levels of audience activity than typical programs, primarily because of their focus on ordinary people competing for prizes, romance, and success. Therefore, audiences can become more emotionally and cognitively involved with the programs. Reality program producers have also made good use of Web resources, encouraging various types of online activity after watching the program. This study s research question explores audience s satisfaction with viewing reality programs: RQ1: What predicts satisfaction with viewing reality television programs? Method Procedure and Sample Communication Quarterly 153 In spring 2004, research assistants enrolled in an undergraduate introductory communication research methods course were given course credit for collecting the data for this study. Assistants, trained in questionnaire administration and ethics, were required to distribute and collect questionnaires. To ensure a broad sample, assistants were given two age quotas to fill (questionnaires to friends who watch reality television programs and questionnaires to non-college-age adults who watch these programs). All respondents were told that their responses were anonymous and confidential. The sample consisted of a total of 464 respondents, of which 223 were college students. Respondents were drawn from a wide geographic area. The sample was 51.9% (n ¼ 240) women (coded 2; men were coded 1). The sample respondents ranged in age from 18 to 83 (M ¼ 31.30, SD ¼ 14.21). The average education level (M ¼ 4.95) was equivalent to a college graduate (SD ¼ 1.29). The typical sample member watched an estimated 4.13 hr of television on a typical weekday (SD ¼ 2.28) and 4.28 hr of television on a typical weekend day (SD ¼ 2.57). Measurement Exposure to reality television. On a scale ranging from 1 (never) to5(always), respondents marked how often they watch each of 36 different reality programs that were either currently airing or had recently been on television. This list was compiled

7 154 L. R. Godlewski & E. M. Perse by culling television schedules, Nielsen ratings, industry publications, and Web sites. In addition, a pretest with 66 college students asked them to identify reality programs. American Idol was most watched out of all reality programs (M ¼ 2.84), followed by The Real World (M ¼ 2.79), and The Apprentice (M ¼ 2.98). Reponses to this list were summed to create a measure of exposure to reality television. Respondents were also asked to list their favorite reality television program. American Idol (n ¼ 76) was listed most often as a favorite program, followed by The Real World (n ¼ 73), The Apprentice (n ¼ 68), Survivor (n ¼ 57), and Newlyweds (n ¼ 33). The favorite program first chosen by the respondent was the focus for subsequent questions about viewing motives, attitudes, and activities. Viewing motives. On a scale ranging from 1 (exactly) to 5(not at all), respondents indicated their agreement with several statements about their own reasons for watching their favorite program they listed. More specifically, 27 of the statements measured nine types of television viewing motives consistently identified in previous research: habit, pastime, companionship, arousal excitement, relaxation, information learning, escape, entertainment, and social interaction (Rubin, 1981). Three additional items designed to measure the watching because of the sexual appeal of characters (Perse, 1986) were also included. To make sure that all potential motives for watching reality programs were included, a pretest of students (n ¼ 44) enrolled in a non-major Introduction to Communication course were asked why they watch reality programs. That pretest identified six additional motives for watching reality programs. The responses to the 36 motive statements were subject to principal access factoring with oblique rotation, recognizing the interrelated nature of motives for watching television. The criteria for a factor to be retained were an eigenvalue of at least 1.00 and two primary loadings of at least.40, with no secondary loadings above.25. Four primary motives, comprised of 20 items and accounting for 48.9% of the variance, were identified. Table 1 summarizes the factor analysis. Factor 1, Social Learning, had an eigenvalue of 9.49 and accounted for 26.41% of the common variance. It included three learning items and two items that concerned a personal focus on the program. This factor is an instrumental viewing motive (Rubin, 1984) and reflected watching the programs to learn. Factor 2, Exciting Entertainment, had an eigenvalue of 4.89 and accounted for 13.6% of the common variance. It included three entertainment items, two excitement items, and one habit item (e.g., I like to watch ). Entertainment is typically an instrumental viewing motive (Perse, 1986). Factor 3, Habit Pastime, had an eigenvalue of 2.10 and accounted for 5.8% of the common variance. It included three pastime items and two habit items. This factor is a ritualistic viewing motive (Rubin, 1984). Factor 4, Voyeurism, had an eigenvalue of 1.10 and accounted for 3.1% of the common variance. It included three voyeuristic items. Although there has been only modest research on voyeuristic viewing motives, that research suggests that voyeurism is an instrumental viewing motive (Nabi et al., 2006; Perse, 1986). A fifth marginal factor, Relaxation Escape, was included in the analyses because relaxation and escape are typical motives for watching television. It had an eigenvalue

8 Communication Quarterly 155 Table 1 Reality Television Viewing Motive Oblimin Factor Solution I watch reality TV Social Learning Exciting Entertainment Habit Pastime Voyeurism Relax Escape Because I can easily relate to the participants in the program Because it helps me learn about myself and others So I can learn about what could happen to me So I can learn to do things that I haven t done before Because I like to see people like me on television Because I would like to be a contestant on a program like this Because it s enjoyable Because it entertains me Because it amuses me Because it s exciting Because I like to watch Because it s thrilling Because I had nothing better to do Because it passes the time away, particularly when I m bored Just because it was on Because it gives me something to occupy my time Because it s a habit, just something that I do Because of the sex appeal in the program Because the characters are sexually attractive Because I find some of it sexually arousing Because it s a pleasant rest Because it allows me to unwind Because it relaxes me So I can forget about school, work, or other things (Continued )

9 156 L. R. Godlewski & E. M. Perse Table 1 Continued I watch reality TV Social Learning Exciting Entertainment Habit Pastime Voyeurism Relax Escape Eigenvalue M SD a of 0.92 and accounted for 2.6% of the common variance. As in past research (e.g., Perse, 1990), it included three relaxation items and one escape item. Relaxation and escape are typically ritualistic viewing motives (Rubin, 1984). Item scores were averaged to create viewing motives scores. Exciting Entertainment (M ¼ 3.70, SD ¼ 0.89; a ¼.87) was the most strongly endorsed motive, followed by Relaxation Escape (M ¼ 2.82, SD ¼ 0.97; a ¼.81), Habit Pastime (M ¼ 2.48, SD ¼ 0.93; a ¼.81), Voyeurism (M ¼ 1.88, SD ¼ 0.95; a ¼.87), and Social Learning (M ¼ 1.82, SD ¼ 0.78; a ¼.83). Exciting Entertainment (M ¼ 3.70, SD ¼ 0.89; a ¼.87) was significantly endorsed more strongly than Social Learning, t(461) ¼ 40.93, p <.001; Habit Pastime, t(461) ¼ 19.77, p <.001; Voyeurism, t(461) ¼ 32.23, p <.001; and Relaxation Escape, t(460) ¼ 21.17, p <.001. Relaxation Escape was significantly more endorsed than Social Learning, t(461) ¼ 22.45, p <.001; Habit Pastime, t(460) ¼ 6.42, p <.001; and Voyeurism, t(461) ¼ 17.60, p <.001. Habit Pastime was significantly more endorsed than Social Learning, t(461) ¼ 13.25, p <.001; and Voyeurism, t(461) ¼ 12.01, p <.001. There were no significant differences between Voyeurism and Social Learning, t(462) ¼ 40.93, p ¼.15. The viewing motives were interrelated (see Table 2). Social Learning was significantly and positively correlated with all other viewing motives: Exciting Entertainment (r ¼.30, p <.001), Habit Pastime (r ¼.23, p <.001), Voyeurism (r ¼.48, p <.01), and Relaxation Escape (r ¼.41, p <.001). Exciting Entertainment was significantly and positively linked to Voyeurism (r ¼.13, p <.01) and Relaxation Escape (r ¼.55, p <.001), but unrelated to Habit Pastime. Habit Pastime was correlated with Voyeurism (r ¼.35, p <.001) and Relaxation Escape (r ¼.25, p <.001). Voyeurism was positively related to watching for Relaxation Escape (r ¼.28, p <.001). All viewing motives, except Habit Pastime, were positively and significantly linked to exposure to reality television programs (see Table 2): Social Learning (r ¼.32, p <.001), Exciting Entertainment (r ¼.39, p <.001), Voyeurism (r ¼.26, p <.001), and Relaxation Escape (r ¼.36, p <.001). Identification. On a scale ranging from 1 (strongly disagree) to 5(strongly agree), respondents marked their agreement with 19 statements while keeping in mind their favorite reality television participant (or character ). These items were drawn from a range of writings about identification (Cohen, 2001; Eyal & Rubin, 2003). To explore

10 Table 2 Pearson Correlations among the Variables of the Study Social Variable Learning Exciting Entertainment Habit Pastime Voyeurism Relax Escape Identification Realism Attention Elaboration Positive Emotion Negative Emotion Post-Exposure Activity Satisfaction Exciting Entertainment.30 Habit Pastime Voyeurism Relax Escape Identification Realism Attention Elaboration Positive Emotion Negative Emotion Post-Exposure Activity Satisfaction Exposure Age Gender Note. N ranges from 458 to 463. p <.05 (two-tailed). p <. 01 (two-tailed). p <.001 (two-tailed). 157

11 158 L. R. Godlewski & E. M. Perse the dimension of viewers identification with the characters on their favorite reality programs, these 19 items were subjected to principal components analysis with oblique rotation. Three components, accounting for 66.2% of the common variance, were identified. Factor 1 (identification with people) had an eigenvalue of and accounted for 52.6% of the common variance. Included in this factor were 11 statements designed to measure involvement in the program, identification with participants in the program, and affinity felt toward the participants of the program. Together, the statements that loaded in this factor represented the identification people felt with the participants in reality programs. Because this study s hypotheses focused on identification with people in reality programs, only the items loading on this first factor were included in the analysis. These items were averaged to create an identification scale that ranged from 1.00 to 4.82 (M ¼ 2.49, SD ¼ 0.80; a ¼.94). 1 Perceived realism. Using a 5-point scale ranging from 1 (strongly disagree) to5 (strongly agree), drawn from Rubin (1981), which has been used reliably in past research, respondents indicated their agreement with the perceived realism of their favorite reality program. Responses were averaged to create a perceived realism scale that ranged from 1.00 to 4.60 (M ¼ 2.22, SD ¼ 0.80; a ¼.82). Attention. To measure self-reported attention to reality programs, participants marked their agreement on a set of five statements, using a previously reliable scale ranging from 1 (strongly disagree) to5(strongly agree), which described respondents typical thoughts and feelings when watching their favorite reality programs (Perse, 1990). Responses were averaged to create an attention scale that ranged from 1.00 to 5.00 (M ¼ 3.00, SD ¼ 0.75; a ¼.84). Cognitive involvement. On a scale ranging from 1 (strongly disagree) to5(strongly agree), respondents marked their level of agreement with four items used in prior research (Perse, 1990), which measured elaboration, or thinking about their favorite reality program information and relating it to existing knowledge. The items were averaged to create an elaboration scale that ranged from 1.00 to 4.40 (M ¼ 2.25, SD ¼ 0.70; a ¼.73). Emotional involvement. To assess the intensity of emotional reaction to reality programs, 20 items were drawn from Perse (1998). On a scale ranging from 1 (strongly disagree) to5(strongly agree), respondents marked their agreement with statements about how strongly they felt 10 different positive emotions (amused, at ease, calm, cheerful, content, delighted, happy, pleased, relaxed, and satisfied) and 10 negative emotions (angry, ashamed, bored, depressed, embarrassed, fearful, gloomy, miserable, sad, and worried) while they watched their favorite reality program. Responses were averaged to create a positive emotion scale that ranged from 1.00 to 5.00 (M ¼ 3.55, SD ¼ 0.65; a ¼.91) and a negative emotion scale that ranged from 1.00 to 4.56 (M ¼ 1.69, SD ¼ 0.59; a ¼.88). Positive emotional responses were significantly more likely to be reported by respondents, t(462) ¼ 43.61, p <.001. Post-exposure online activity. On a scale ranging from 1 (never) to5(always), respondents indicated the extent to which they participate in a variety of online

12 Communication Quarterly 159 post-exposure activities. 2 This list was derived from interactive reality television literature (Andrejevic, 2004; Bloxham, 2001; Johnson-Woods, 2002). Online postexposure was comprised of responses to eight items and was quite low, with 53.6% of the respondents indicating that they never went online after watching the programs. The scale ranged from 1.00 to 4.75 (M ¼ 1.32, SD ¼ 0.57; a ¼.90). 3 Satisfaction. On a scale ranging from 1 (not at all) to 5(completely), respondents marked how pleasing and how satisfying they found watching their favorite reality program to be. These items were drawn from prior research on television satisfaction (Ferguson & Perse, 2004) and were highly correlated (r ¼.86, p <.001). Responses to the items were averaged and ranged from 1.00 to 7.00 (M ¼ 4.87, SD ¼ 1.44). Statistical Analysis After scale construction and reliability analyses, several steps were taken to test H1 and H2 and to answer RQ1. Pearson correlations (one-tailed) were used to assess H1, which concerned the impact of motives and activities on the development of identification with reality program participants. Multiple regression analysis was also used to identify the multivariate relationships among motive, activity, and identification. Similar tests, one-tailed Pearson correlations, and multiple regression analyses, were used to test H2, which concerned how post-exposure online activity was linked to motives and activity while watching the programs. RQ1 was answered first by exploring the two-tailed correlations among motive, activity, and program satisfaction. Then, hierarchical multiple regression was used to assess the multivariate relationship among satisfaction and those variables. Gender and age were included in hierarchical regressions to control for any of the variance that these demographics might contribute to the dependent variables. Results Identification H1 predicted that identification with reality television characters would be predicted by more instrumental viewing motives, by greater exposure to reality television, by greater perceived realism, and by greater cognitive and emotional involvement with the programs. One-tailed Pearson correlations support this hypothesis. Identification was positively correlated with the Social Learning viewing motive (r ¼.56, p <.001), with the Exciting Entertainment viewing motive (r ¼.33, p <.001), with the Voyeuristic viewing motive (r ¼.37, p <.001), with perceived realism (r ¼.68, p <.001), with exposure to reality television programs (r ¼.28, p <.001), with attention to the programs (r ¼.41, p <.001), with elaboration with the content (r ¼.71, p <.001), with positive emotional responses (r ¼.36, p <.001), and with negative emotional responses (r ¼.24, p <.001). Contrary to expectations, the ritualistic viewing motives of Habit Pastime (r ¼.13, p <.01) and Relaxation Escape (r ¼.43, p <.001) were also positively correlated with identification.

13 160 L. R. Godlewski & E. M. Perse Hierarchical multiple regression was used to assess the multivariate relationships among motive, realism, and exposure in predicting identification with reality television characters. The regression is summarized in Table 3. The demographic variables (age and gender) entered in the first step accounted for a significant (p <.05) 1.5% of the variance in identification with reality participants. Only age was a significant negative predictor. At Step 2, the addition of the television viewing motives accounted for an additional 36.6% of the variance (p <.001). At this stage, age dropped out of the equation; and Social Learning, Voyeurism, and Relaxation Escape were all significant positive contributors to identification. Exposure, entered at Step 3, added no additional variance to the equation (p ¼.56). Perceived realism, attention, elaboration, and positive and negative emotions were added at Step 4 and contributed an additional 24.6% to the variance (p <.001). In the final analysis, the equation accounted for 62.8% of the variance in identification with reality program participants (R ¼.79) and partially supported H1. Elaboration (b ¼.37, p <.001), perceived realism (b ¼.32, p <.001), the Social Learning viewing motive (b ¼.10, p <.05), positive emotional reactions (b ¼.08, p <.05), and attention (b ¼.08, p <.05) were all significant positive predictors of identification. Post-Exposure Online Activity H2 predicted that greater post-exposure online activity would be predicted by instrumental viewing motives, greater attention to the programs while watching, greater Table 3 Regression Identification with Reality show Participants Variable Step R 2 R 2 change Final b Demographics Gender Age.03 Viewing Motives Social Learning Exciting Entertainment.04 Habit Pastime.02 Voyeurism.07 Relax Escape.05 Exposure Realism Attention.08 Elaboration 37 Positive emotion.08 Negative emotion.02 Note. Step 1: F(2, 453) ¼ 3.54, p <.05; Step 2: F(5, 448) ¼ 52.95, p <.001; Step 3: F(1, 447) ¼ 0.34, p ¼.56; Step 4: F(5, 442) ¼ 58.39, p <.001. p <.05. p <.001.

14 Communication Quarterly 161 cognitive elaboration while watching, greater emotional involvement while watching, and higher levels of perceived realism. One-tailed Pearson correlations provide initial support for this hypothesis. Post-exposure online activity was positively correlated with the instrumental viewing motive Social Learning (r ¼.36, p <.001), the instrumental viewing motive Exciting Entertainment (r ¼.14, p <.001), the instrumental voyeuristic viewing motive (r ¼.32, p <.001), to attention (r ¼.25, p <.001), cognitive elaboration (r ¼.48, p <.001), positive (r ¼.14, p <.001) and negative emotion (r ¼.42, p <.001), and perceived realism (r ¼.36, p <.001). Contrary to H2, post-exposure online activity was significantly and positively linked to the ritualistic Relaxation Escape motive (r ¼.20, p <.001). The ritualistic viewing motive Habit Pastime was not related to post-exposure activity (r ¼.07, p ¼.07). Again, hierarchical multiple regression was used to assess the multivariate relationships among post-exposure online activity and viewing motives, cognitive and emotional involvement while watching the programs, and perceived reality. The regression is summarized in Table 4. The demographic variables (age and gender) entered in the first step accounted for a significant 2.8% of the variance (p <.01) in post-exposure participation in online activity. Only age was a significant negative predictor at this stage of the analysis. At Step 2, the reality program viewing motives accounted for another 13.8% of the variance (p <.001). At this stage, age dropped out of the equation, and Social Learning and Voyeurism were both significant positive contributors to online activity. At Step Table 4 Regressing Post-Exposure Online Activity Variable Step R 2 R 2 change Final b Demographics Gender Age.16 Viewing Motives Social Learning Exciting Entertainment.06 Habit Pastime.08 Voyeurism.10 Relax Escape.01 Involvement variables Attention Elaboration.33 Positive emotion.04 Negative emotion.31 Realism.02 Identification.06 Note. Step 1: F(2, 454) ¼ 6.45, p <.01; Step 2: F(5, 449) ¼ 15.00, p <.001; Step 3: F(6, 443) ¼ 21.00, p <.001. p <.01. p <.001.

15 162 L. R. Godlewski & E. M. Perse 3, cognitive and emotional involvement (attention, elaboration, positive emotion, negative emotion, perceived realism, and identification) accounted for an additional 18.5% of the variance (p <.001). In the final analysis, the equation accounted for 35.0% of the variance in online activity (R ¼.60) and partially supported H2. Age (b ¼.11, p <.01) was a significant negative predictor of participation in online activity. The voyeuristic viewing motive (b ¼.10, p <.05), elaboration (b ¼.33, p <.001), and negative emotion (b ¼.31, p <.001) were significant predictors of participation in online activity. Reality Television Viewing Satisfaction RQ1 asked how viewing motive, cognitive and emotional involvement while watching, post-exposure online activity, and identification are linked to viewers satisfaction with watching reality television. Two-tailed Pearson correlations show several significant links with satisfaction. First, satisfaction is positively related to exposure to the programs (r ¼.36, p <.001). Satisfaction is also positively correlated with instrumental viewing motives: Social Learning (r ¼.30, p <.001) and Exciting Entertainment (r ¼.65, p <.001). It is negatively correlated with Habit Pastime (r ¼.15, p <.01) and unrelated to Voyeurism (r ¼.08, p ¼.08). Satisfaction is positively related to cognitive and emotional involvement while watching the programs: positive emotions (r ¼.55, p <.001), attention (r ¼.57, p <.001), cognitive elaboration (r ¼.33, p <.001), and identification with the characters (r ¼.35, p <.001). Satisfaction is negatively related to feeling negative emotions (r ¼.25, p <.001). Perceived realism is positively related to satisfaction (r ¼.30, p <.001). Post-exposure activity, however, was unrelated to program satisfaction (r ¼.03, p ¼.60). Hierarchical multiple regression assessed the multivariate relationship among the study s variables and program satisfaction. The regression is summarized in Table 5. The demographic variables (age and gender) entered in the first step accounted for a significant 8.1% of the variance (p <.001) in reality program satisfaction. At this stage, age was a significant negative predictor, and gender was a significant positive predictor. At Step 2, the reality program viewing motives accounted for another 40.4% of the variance (p <.001). At this stage, both age and gender dropped out of the equation. Social Learning, Exciting Entertainment, and Relaxation Escape were positive predictors. Habit Pastime viewing motive was a significant negative predictor. At Step 3, exposure to reality programs added an additional 0.6% to the variance in program satisfaction (p <.05). At this stage, exposure became a positive contributor to the equation. At Step 4, cognitive and emotional involvement (attention, elaboration, positive emotion, and negative emotion), perceived realism, identification, and post-exposure online activity accounted for an additional 11.3% of the variance (p <.001). In the final analysis, the equation accounted for 60.5% of the variance in reality program viewing satisfaction (R ¼.78). The Social Learning (b ¼.13, p <.01) and Exciting Entertainment (b ¼.26, p <.001) viewing motives, attention to the programs while watching (b ¼.26, p <.001), and feeling positive emotions while watching

16 Communication Quarterly 163 Table 5 Regressing Reality Program Viewing Satisfaction Variable Step R 2 R 2 change Final b Demographics Gender Age.06 Viewing motives Social Learning Exciting Entertainment.26 Habit Pastime.08 Voyeurism.00 Relax Escape.05 Exposure Involvement variables Attention Elaboration.05 Positive emotion.18 Negative emotion.17 Realism.02 Identification.06 Online activity.14 Note. Step 1: F(2, 450) ¼ 19.96, p <.001; Step 2: F(5, 445) ¼ 69.00, p <.001; Step 3: F(1, 444) ¼ 5.64, p <.05; Step 4: F(7, 437) ¼ 17.91, p <.001. p <.05. p <.01. p <.001. (b ¼.18, p <.001) were all positive predictors of program satisfaction. The Habit Pastime viewing motives (b ¼.09, p <.05), feeling negative emotions while viewing (b ¼.17, p <.001), and post-exposure online activity (b ¼.14, p <.001) were all negative predictors of viewing satisfaction. Discussion The goal of this study was to explore theoretical links between viewing motive and audience activity in a popular form of television content that encourages greater audience activity. We expected that reality programs, because of their focus on real people living their actual (if not typical) lives, would lead to identification with these characters. We also expected that greater use of the Web for additional program content (videos and summaries), discussion, elaboration, speculation, and polls by program producers and fans would be linked to greater cognitive, emotional, and personal engagement with the programs. Finally, we expected that greater involvement with the participants in the programs and greater use of online program resources after viewing would increase program viewing satisfaction. Identification has been an important concept in mass communication research for two reasons. Identification with the personalities in a program can enhance the

17 164 L. R. Godlewski & E. M. Perse emotional responses and pleasure of viewing (Cohen, 2001). Identification can also facilitate modeling and other media effects (Cohen, 2001; Eyal & Rubin, 2003). The results of this study support both of these. The bivariate correlations show that all viewing motives were significantly linked to identification that is, the more motivated viewers are to watch the programs, for any reason, the more likely they are to identify with the participants. Perhaps identification is an essential aspect of the entertainment experience. Future research should explore this connection among identification and both instrumental and ritualistic viewing motives. The multivariate relationships identified by the regression results show that identification with reality show participants grows out of watching the programs for social learning reasons, or a desire to learn new things while relating to the participants. Although this motive was the one least endorsed by our respondents, when those motives for watching are salient, identification is more likely. Future research should continue to explore how identification facilitates modeling and other behavioral effects. The regression results show that identification was also significantly predicted by mental engagement with a favorite program: both greater attention to the program and cognitive involvement while watching. It was also more modestly predicted by feeling positive emotional reactions while viewing. These results suggest that identification might be more a cognitive response to watching people on television, rather than an emotional one. Future research should explore the cognitive and affective aspects of identification (e.g., Cohen, 2001). Perceived realism was also a significant predictor of identification. Reality television highlights the exploits of real people. When viewers see the participants as real, they are more likely to identify with them. It is interesting to note that average levels of perceived realism were not very high (M ¼ 2.22 on a 5-point scale). Despite the fact that these programs use real people acting out their real (if not typical) lives, viewers did not see a good deal of realism in the programs. Is it that the artificial settings of the shows (e.g., talent contests, desert islands, and shared houses) are viewed as unreal? Do audiences see the participants as real or as adopting artificial personae to succeed? Past research has found that identification is enhanced by perceived similarity (Eyal & Rubin, 2003). Do the sometimes outrageous situations of reality programs detract from perceived homophily? Future research should explore the dimensions of and influences on perceived realism. Together, the results of H1 support a central tenet of uses and gratifications: Viewing motives and audience activity are important antecedents to identification. Moreover, identification with reality show participants clearly grows out of instrumental viewing. Watching to learn is a prime marker of instrumental motivation. Moreover, identification is marked by mental engagement with the programs, heightened attention to the program, and thinking about program content. Future research might explore how identification is linked to other cognitive outcomes of watching television, such as learning from content or attitude development. One surprising finding was that levels of online activity after watching one s favorite reality program were rather low. None of the means of the individual items

18 Communication Quarterly 165 reached 2.00 (which were labeled on the questionnaire as rarely ). There was a strong negative relationship between engaging in online activity and age (r ¼.66, p <.001). Clearly, online activity was more common in the younger viewers in our sample. Still, these low levels are surprising, as program producers and fans post a good deal of material on the Web: extra video footage, photos, program summaries and speculations, polls, and online discussions. We were also surprised by the low level of voting among our sample. Future research should explore how widely the extra program content on the Web is actually used by viewers and what the motives are for using that content. The bivariate correlations support H2, regarding online post-exposure activity. Consistent with expectations, all viewing motives, except the ritualistic habit pastime motive, were positively and significantly linked to engaging in online activity after watching a favorite program. Therefore, more motivated viewers are more likely to engage in online activity. The results of the regression, however, place greater emphasis on the influence of activity during viewing. The multivariate relationship between motive and activity shows that online activity is most strongly explained by elaboration, or thinking about program content while watching, and negative emotional reactions while watching a favorite program. Elaboration was a hypothesized antecedent to engaging in online post-exposure activity. Viewers who are more cognitively involved in a favorite program are more likely to continue their involvement and information search after the program is over. Involved television viewers not only pay attention to and think about the message, but they also get caught up in the action of the drama (Bryant & Comisky, 1978; Perse & Rubin, 1988). Findings that elaboration predicts post-exposure activity reinforces the idea that viewers get caught up in the program, and engage in post-exposure activity as a result. The results of this study support the prediction that the more involved viewers are with a favorite reality program, the more active they are likely to be after exposure to that program. The strong influence of negative emotion on post-exposure online activity, however, was unexpected. This suggests that viewers might go online after watching because of dissatisfaction with program outcomes. Viewers might go online because of negative actions toward their favorite participant; because of strong negative feelings toward other participants or toward the process itself; or because they do not want to see a particular participant win, remain in the game, or continue to interact with other members of the program. The role of negative emotion in reality television viewing is an area for future research. The bivariate relationships show that negative emotion is significantly linked to realism (r ¼.21, p <.001) and identification (r ¼.24, p <.001). Negative emotions might grow out of a personal focus on the program s participants. Negative emotions were also significantly linked to mental engagement with the programs (r ¼.30, p <.001). This finding is similar to those of research on negative media content that find heightened cognitive activity in the face of negative emotions. Perse (1998) found that viewers paid more attention to and elaborated more on content linked to negative emotions. Scholars have explained that negative