PERSUADING THROUGH FICTIONAL TELEVISION: A MIXED METHODS INVESTIGATION OF GENRE EXPECTATIONS By Sharon-Nicole McClaran A DISSERTATION Submitted to Michigan State University in partial fulfillment of the requirements for the degree of Information and Media—Doctor of Philosophy 2022 ABSTRACT PERSUADING THROUGH FICTIONAL TELEVISION: A MIXED METHODS INVESTIGATION OF GENRE EXPECTATIONS By Sharon-Nicole McClaran Genres provide an effective way for viewers to categorize, select, and evaluate entertainment television (TV) programs (Bilandzic & Rössler, 2004; Hawkins et al., 2001). People tend to know, for example, whether they will enjoy a medical drama or animated comedy based on their prior experience watching shows of that genre. Despite growing interest in entertainment media as a vehicle for persuasion, minimal research has considered how genre may influence receptivity to and acceptance of persuasive appeals in fictional TV programming (J. Cohen & Weimann, 2000; Grabe & Drew, 2007). Even less work has offered theoretical explanations for why genre may impact the persuasion process. Across three studies, this dissertation, guided by expectancy-violations theory (Burgoon, 1993, 2015), offers a thorough investigation into how audiences consider fictional TV genres and whether those expectations influence the success of subsequent persuasive attempts. In Study 1, qualitative interviews were conducted to gauge how viewers feel about using fictional TV shows for persuasion and whether genre is an influential factor in their assessments. The results provided preliminary evidence that viewers hold strong expectations for the likelihood and appropriateness of persuasive appeals in certain genres. In Study 2, persuasion-relevant expectations, including content credibility, learning potential, and likelihood of distributing an educational message, were tested for ten fictional TV genres (animated comedy, animated drama, comedy, crime comedy, crime drama, general drama, historical drama, medical comedy, medical drama, science-fiction/fantasy). Results of the online survey provided strong statistical support that viewers consider the content of TV genres differently and that these expectations influence hypothetical acceptance of an educational appeal. Lastly, Study 3 offered an experimental manipulation of genre (historical fiction vs. science- fiction/fantasy) to test whether genre expectation violations and message resistance explain the success of entertainment media in facilitating persuasion. Although the hypotheses were not supported in Study 3, post-hoc analyses found genre to influence participants’ perceived persuasive intent, which in turn, influenced attitudes, descriptive norms, and behavioral intention toward daily stretching. The cumulative results of this dissertation stress the importance of genre study in the entertainment media persuasion scholarship and offer several avenues for future research. iv To Dad, the source of my work ethic, curiosity, and ambition. To Mom, my example of bravery, patience, and hope. iv ACKNOWLEDGMENTS I first wish to thank the members of my dissertation committee. To Nancy Rhodes, it is not an exaggeration to say that I would not be here without you. Your work is what drew me to MSU, but it is your mentorship, kindness, and graciousness that will make it so hard to leave. Thank you for forcing me use “while” more selectively, patiently listening to all my rants, and ultimately making me a better scholar, teacher, and person. To the rest of my committee- Allison Eden, Morgan Ellithorpe, and Dave Ewoldsen- thank you for being what can only be described as the dream team of committees. I feel honored to have received your time, guidance, feedback, and patience for the past five years. To Patricia Huddleston and Teresa Mastin- thank you for the constant support and guidance throughout my time at MSU. You both represent the kind of leadership I hope to embody one day. To my family or what I like to refer to as “that group of people who unapologetically post every miniscule accomplishment of mine on social media only to ask minutes later ‘what is it you do, again, exactly?’” - you all made this feel worth it every step of the way. To my friends, both in and outside of academia- this journey can feel incredibly lonely at times, but you all kept me rooted. I owe a particular thanks to Julia, Skyler, Rena, Sam, Shay, Iago and Craig. Thank you for sticking with me. To Sherlock and Marla- writing this massive document wouldn’t have been the same without picking out your hair from my keyboard (or your constant cuddles). Finally, to Connor- for eight years, four states, and three tiny apartments, you have been my biggest provider of the three S’s: support, safety, and soda (read: Diet Coke). Your sacrifice is what gave me the freedom to do this in first place, and it is your encouragement that has taken me to the end. If I could thank you on every page, it still wouldn’t be enough. Thank you for your endless patience. I love you. v TABLE OF CONTENTS LIST OF TABLES viii LIST OF FIGURES ix CHAPTER ONE: INTRODUCTION 1 CHAPTER TWO: LITERATURE REVIEW 3 Overview of Entertainment Persuasion 3 The Variability of Entertainment TV 9 The Role of TV Genres on Persuasion 11 Expectations of TV Genres 15 Expectancy-Violations Theory 17 The Current Research 19 CHAPTER THREE: STUDY 1 21 Study 1 Method 23 Participants 23 Procedure 24 Analytic Procedure 25 Study 1 Results 25 Perceived Accuracy of Fictional TV Content 25 Prevalence of Persuasive Content in Fictional TV 27 Reception to Persuasive Content in Fictional TV 29 Expectations of Persuasive Content in Fictional TV 29 Study 1 Discussion 30 CHAPTER FOUR: STUDY 2 35 Study 2 Method 37 Participants 37 Procedure 39 Measures 40 Study 2 Results 43 Descriptive Statistics 43 Main Analyses 43 Study 2 Discussion 50 CHAPTER FIVE: STUDY 3 54 Study 3 Method 57 Participants 57 Procedure 59 Stimuli 60 The Behavior of Daily Stretching 61 Stimuli Pilot Test 62 Measures 64 Intervening Variables 64 Dependent Variables 64 Covariates 65 vi Study 3 Results 67 Main Analyses 69 Mediation Analyses 70 Study 3 Discussion 73 CHAPTER SIX: OVERALL DISCUSSION 78 Conclusion 84 APPENDICES 85 Appendix A: Study 1 Screener Questionnaire 86 Appendix B: Study 1 Interview Guide 89 Appendix C: Study 2 Questionnaire Items 91 Appendix D: Correlation Matrixes for Study 2 Variables 101 Appendix E: Study 3 Questionnaire 103 REFERENCES 116 vii LIST OF TABLES Table 1. Study 1 Participants and Demographic Information. 24 Table 2. Study 2 (N = 593) Sample Characteristics. 37 Table 3. Reliability and Descriptive Statistics of Study 2 Measures. 42 Table 4. Study 2 Descriptive Statistics for Genre Watching. 43 Table 5. Study 2 Pairwise Comparisons for Perceived Credibility by Genre. 44 Table 6. Study 2 Pairwise Comparisons for Perceived Learning Potential by Genre. 45 Table 7. Study 2 Pairwise Comparisons for Perceived Appeal Likelihood by Genre. 45 Table 8. Study 2 Structure Matrix from Exploratory Factor Analysis (EFA). 47 Table 9. Study 2 Regression Results for Hypothetical Acceptance (N = 593). 50 Table 10. Study 3 (N = 188) Sample Characteristics . 58 Table 11. Study 3 Pilot Test Measures and Descriptive Statistics. 63 Table 12. Correlation Matrix for Study 3 Variables. 68 Table 13. Study 3 Descriptive Statistics and ANCOVA Results by Condition. 70 Table 14. Results of Study 3 Hypothesized Structural Equation Model (N = 188). 71 Table 15. Results of Study 3 Post-Hoc Structural Equation Model (N = 188). 72 Table D1. Study 2 Correlation Matrix for Perceived Credibility by Genre. 101 Table D2. Study 2 Correlation Matrix for Learning Expectations by Genre. 101 Table D3. Study 2 Correlation Matrix for Perceptions of Appeal Likelihood by Genre. 102 Table D4. Study 2 Correlation Matrix for Acceptance of Educational Message by Genre. 102 viii LIST OF FIGURES Figure 1. Aims, Method and Sample of All Studies. 20 Figure 2. Study 2 Means of Persuasion-Relevant Expectations by Genre. 46 Figure 3. Study 2 Scree Plot for Perceived Credibility. 48 Figure 4. Study 2 Scree Plot for Learning Potential. 48 Figure 5. Study 2 Scree Plot for Appeal Likelihood. 48 Figure 6. Proposed Hypothesis Model for Study 3. 57 Figure 7. Post-Hoc Model Tested for Study 3. 72 ix CHAPTER ONE: INTRODUCTION Entertainment media has had a long and rich history of study, such as with research explaining audiences’ selection (e.g., mood management theory, Zillmann & Bryant, 1985), evaluation (e.g., the narrative enjoyment and appreciation rationale; Tamborini et al., 2021), and processing of entertainment media (e.g., disposition theory, Zillmann & Cantor, 1976). Entertainment media as a means of persuasion, though, has been less investigated. The past two decades have seen an increased interest in entertainment media’s persuasive capabilities but even now, with a more established body of literature, its documented ability to influence beliefs and behaviors has been inconsistent (T. Chen & Lin, 2014; E. L. Cohen, 2016; Igartua, 2017; Nera et al., 2018; Riley et al., 2020; Sharma, 2022). An explanation repeatedly offered yet rarely tested is that genre may substantially impact the persuasion process (Frazer et al., 2021; Moyer-Gusé, 2010). Our current understanding of entertainment persuasion hinges on the assumption that audiences neither expect nor want persuasive appeals in entertainment- focused media (Slater & Rouner, 2002). Yet, this assumption has not been formally examined for modern audiences or for specific genres of fictional television (TV), a popular type of entertainment media used for persuasive purposes (Beck, 2004; Poindexter, 2004; Sabido, 2004; Shrum & Lee, 2012; Singhal et al., 2013). Combining these needs in the literature, the following question guides the present dissertation: how do the expectations audiences have about the content of fictional TV genres influence receptivity to and acceptance of embedded persuasive messages? Three contributions are made by the present research. First, the assumptions and expectations audiences have of whether and when fictional TV contains persuasive messages, in general and in the context of different TV genres, are documented (Study 1). Second, the differences in receptivity to and acceptance of embedded persuasive appeals in different fictional TV genres are tested (Study 2). Lastly, an expectancy-violation approach is used to understand the causal relationship between genre expectations, message resistance, and 1 persuasive outcomes, including attitudes, social norms, perceived behavioral control and behavioral intention (Study 3). Across three studies using mixed methods (qualitative interviews, a survey, and an experiment), the results provide theoretical clarity for why TV is effective for persuasion in certain narrative contexts, such as for different genres, and contributes several avenues for future research. This dissertation begins with a brief historical overview of how entertainment TV has been studied for persuasion and the current resistance-reduction theoretical approach to entertainment persuasion. Next, the variability of TV programming is discussed with a particular focus on genre studies. Lastly, pulling from expectancy-violations theory (Burgoon, 2015; Burgoon & Hale, 1988), the importance of understanding viewers’ expectations of the content of different genres is emphasized. 2 CHAPTER TWO: LITERATURE REVIEW Overview of Entertainment Persuasion The study of entertainment media as a vehicle for communicating persuasive messages, such as those related to health, environmental and social issues, has followed four main trajectories. First, work in cultivation theory has documented TV’s ability to inform and change viewers’ construction of the real world by repeatedly depicting a mediated version of reality (Gerbner, 1969; Morgan et al., 2017; Romer et al., 2014; Shanahan & Morgan, 1999). The original focus of cultivation theory was on TV, specifically, as it was considered “the most concentrated, homogenized, and globalized medium” (Gerbner, 1998, p. 176). The centralized depiction of issues in TV media was thought to create a cultivation effect, wherein viewers’ perceptions of the world became aligned with the media’s (Hermann et al., 2021; Morgan et al., 2017; Potter, 1991; Shrum, 2017). Therefore, in the cultivation literature, a persuasive outcome is not typically attributed to a specific source or campaign but as a consequence of the homogenization of issue depictions in mainstream TV media (Hammermeister et al., 2005; Potter, 2014). Altered perceptions of crime and violence have dominated the cultivation literature as an outcome of interest (Gerbner & Gross, 1976; Morgan & Shanahan, 1997, 2010; Pollock et al., 2022; Romer et al., 2014; Shrum, 2017), such as whether depictions of violence on primetime TV positively predict viewers’ fear of crime (Jamieson & Romer, 2014). Although early cultivation theory was criticized for not delineating the explanatory mechanisms responsible for a cultivation effect, several models have since been put forth (Hawkins & Pingree, 1981; Shapiro & Lang, 1991; Shrum, 2017). For example, Shrum's (1995, 2009) accessibility model of cultivation effects suggests TV consumption to increase accessibility of exemplars and beliefs which may guide subsequent behavior. Shrum emphasized the cultivation effect to occur via the heuristic or peripheral processing route (i.e., quickly and without thorough deliberation; Chaiken, 1980) and that systematic (i.e., effortful) processing of the information would diminish or eliminate the effect (Shrum, 2001, 2017). Social 3 reality judgements, such as the prevalence of a behavior, have been the main variable of interest in the accessibility model of cultivation effects and cultivation research, as a whole (Gerbner, 1998; Shanahan & Morgan, 1999; Shrum, 2017). Second, social cognitive theory was and remains a prominent theory for understanding why TV and other entertainment media impacts viewers’ beliefs and behaviors (Bandura, 1986, 2002b, 2002a, 2004, 2010; Slater, 2002a). Focusing on the tenants relevant to the present research, social cognitive theory proposes that in addition to direct experience, people learn from social modeling or vicarious learning (Bandura, 2002b, 2004). When another person, such as a fictional character, performs a behavior, audiences can observe the rewards (or punishments) received which may provide incentives (or disincentives) for initiating that behavior in their own lives (Bandura, 2004; Bandura et al., 1963). Entertainment media is expected to be most conducive to vicarious learning if (a) the character is viewed positively or as similar to the viewer, (b) the behavior is relevant to the viewer, and (c) the viewer has little to no direct experience with the behavior (Bandura, 2002b; Nabi & Clark, 2008). Important to social cognitive theory is the process that by observing a character successfully engage in the target behavior, audiences’ belief of their own capabilities, labelled as their perceived self- efficacy, will be bolstered (Bandura, 1986, 2004, 2006, 2010). For example, social cognitive theory would predict that if a viewer watched a character be praised for becoming sober throughout a TV series, they may feel more confident and motivated to stop drinking alcohol in their own life, especially if they already have a substance abuse issue. Characters shown to model the behavior change, called transitional characters, are thought to be more effective than simple positive (e.g., sober character) or negative (e.g., alcoholic character) role models (Bandura, 2004). Although cultivation theory and social cognitive theory were both used to predict post- exposure changes in audiences, neither pertained to the intentional and targeted use of fictional TV for persuasion. That is, both theories explained how and why TV may influence beliefs and 4 behaviors but not how it could be utilized. Rather, it was Miguel Sabido’s development of the entertainment-education strategy (EE) that institutionalized the strategic use and application of fictional TV for persuasion (Bandura, 2004; Poindexter, 2004; Sabido, 2004; Singhal et al., 1993, 2004; Singhal & Rogers, 1999, 2002). The entertainment-education strategy, also called prosocial entertainment, edutainment, social impact entertainment, and infotainment (Borum Chattoo et al., 2021), has been implemented worldwide to promote a range of behaviors (Bandura, 2004; Piotrow & de Fossard, 2004; Poindexter, 2004; Shen & Han, 2014). For example, EE campaigns have been successful in communicating about substance abuse (K. Kim et al., 2014; Shin et al., 2018), family planning (Rogers et al., 1999; Shelus et al., 2018; Vaughan, Regis, et al., 2000), HIV/AIDS prevention (Cardey et al., 2013; Glik et al., 2002; Vaughan, Rogers, et al., 2000), and sustainability efforts (Flora et al., 2014; Reinermann et al., 2014). Instead of a theory itself, EE is considered a methodology for how to develop and evaluate prosocial-driven entertainment media. Sabido formed the EE methodology by combining and integrating principles of five different theories and models, one of which being social cognitive theory (Singhal & Rogers, 1999; Sood et al., 2004). Indeed, the EE methodology has been credited for pioneering the translational and implementational model of social cognitive theory, or in other words, applying the theoretical model of social cognitive theory to produce society-wide change (Bandura, 2004). In short, the EE strategy encompasses elements of character modeling, archetypical characters (i.e., positive role models, negative role models, and transitional characters), a precise sequence of events depicting behavioral adoption (e.g., two transitional characters separately adopting the behavior one-third and two- thirds of the way through the series, respectively), and an epilogue emphasizing the persuasive messages (Chatterjee et al., 2017; Singhal et al., 1993, 2004). Of relevance to the current research, the EE strategy was deliberately designed for telenovelas or serial drama programs 5 which have remained the dominant genre for implementation (Poindexter, 2004; Singhal et al., 1993; Singhal & Rogers, 1999, 2002). The work in cultivation theory, social cognitive theory, and EE initiated a monumental shift in the field. Although TV had long been considered an inconsequential media, the robust findings that it was impacting viewers’ beliefs and behaviors, across nations and topics, institutionalized it as a viable and meaningful communication vehicle (Shanahan & Morgan, 1999; Singhal et al., 2004). The sufficiency of these longstanding theories to explain TV’s persuasive impact, however, has been questioned in recent decades (Moyer-Gusé, 2008; Nabi & Clark, 2008; Singhal & Rogers, 2002; Slater, 2002a). Cultivation theory supports TV’s persuasiveness as a media vehicle but is still primarily concerned with general media effects (vs. to understand the persuasion process for different outcomes). Social cognitive theory provides a useful framework for understanding why audiences may be motivated to take action from entertainment media but its emphasis on self-efficacy as the main explanatory mechanism and its over-generalization of character involvement variables has been criticized (Moyer-Gusé, 2008; Nabi & Clark, 2008; Slater & Rouner, 2002). Furthermore, as previously stated, EE was never suggested as a theory itself but as a method for how to incorporate different psychological and drama theories to bolster the success of a persuasive entertainment program. To address to the lack of theory specific to entertainment persuasion, the extended-elaboration likelihood model (E-ELM; Slater & Rouner, 2002) and the entertainment overcoming resistance model (EORM; Moyer-Gusé, 2008; Moyer-Gusé & Nabi, 2010) were proposed. Although distinct models, they share similar propositions. Specifically, the E-ELM and EORM both posit entertainment to influence attitudes, beliefs, and behaviors to the extent that audiences are less able and motivated to reject the message. Thus, the fourth and most recent trajectory of research adopts a resistance-reduction approach to entertainment persuasion. The E-ELM implements a dual-process framework and stipulates narrative absorption (i.e., vicariously experiencing a character’s emotions and thoughts) and subsequent character 6 identification (i.e., perceived homophily with the characters or a social bond) to mediate the relationship between entertainment exposure and persuasive outcomes by reducing audiences’ ability to resist the persuasive message.1 By exerting cognitive resources to engage with the narrative and its characters, audiences are less able and motivated to expend resources counterarguing the persuasive message, therefore reducing the chances that it will be rejected. Thus, unlike explicit persuasive appeals (e.g., public service announcements) where elaboration of the message is beneficial for establishing more longstanding persuasion (Chaiken, 1980; Chaiken et al., 1989; Petty & Cacioppo, 1979b, 1986), it is the passive consumption of the persuasive content that elicits persuasion in an entertainment media context (Slater & Rouner, 2002). This proposition aligns with the accessibility model of cultivation effect (i.e., cultivation occurs via heuristic processing; Shrum, 2017) yet the E-ELM focuses on attitudes and behaviors (vs. social perceptions) and includes entertainment-specific processes, such as narrative absorption. The E-ELM galvanized research on entertainment persuasion by specifying its main power as reducing message resistance. However, the theory was thought to be, at times, operationally murky (Moyer-Gusé, 2008; Moyer-Gusé & Nabi, 2010). The E-ELM utilizes extant variables in the narrative persuasion literature, such as absorption and character identification, but the definition, impact and relationship of those variables in the persuasion process remained unclear. Slater and Rouner (2002) indeed acknowledged in their presentation of the E-ELM that character identification is overwhelmingly complex and as a result, difficult to conceptualize. For example, there is conflicting research on the impact of character identification on persuasive outcomes (de Graaf et al., 2012; Lane et al., 2013), homophily as an antecedent (E. L. Cohen et 1 It should be noted that the definitions offered for narrative absorption and character identification by Slater and Rouner (2002) differ from definitions provided elsewhere. Rather than be specific to a character’s experiences, absorption is often treated synonymously with Green and Brock’s (2000) variable of transportation and is considered a state of cognitive, affective, and physical immersion into the narrative. Character identification, on the other hand, has been defined as a state in which viewers adopt the goals and identify of a character and has been argued as separate from perceived homophily and parasocial bonds (J. Cohen, 2001). 7 al., 2018; Hoeken et al., 2016), its functional difference between similar concepts, such as parasocial relationships and character liking (J. Cohen, 2001), and its causal relationship with absorption or transportation (van Laer et al., 2014). Moyer-Gusé (2008) sought to explicate how variables related to narrative and character involvement may influence persuasion differently and, in the process, laid the foundation for the entertainment overcoming resistance model (EORM). The EORM maintains the E-ELM’s proposition that absorption and character identification will reduce counterarguing but offers two main advancements (Moyer-Gusé, 2008). First, the EORM expands the E-ELM’s conceptualization of persuasion resistance as counterarguing to include psychological reactance (i.e., a negative motivational state in response to one’s freedom being threatened with elimination or eliminated entirely; Brehm, 1966; Miron & Brehm, 2006), selective avoidance, and other biases (optimistic, false consensus, and pluralistic ignorance). Second, the EORM specifies eight propositions about the relationships between several character involvement variables and persuasion outcomes that prior theories had otherwise muddled (Moyer-Gusé, 2008). For example, reactance is thought to be reduced by the narrative structure, parasocial interaction, and character liking, whereas identification is hypothesized to reduce counterarguing, selective avoidance, and an optimistic bias (i.e., the belief that one is less likely to be vulnerable to the negative effects of a behavior than others; Taylor & Gollwitzer, 1995). The EORM also reconceptualizes the role of transportation, or absorption in the E-ELM, by not specifying any causal relationship between transportation and identification, instead treating all involvement variables as independent predictors (Moyer-Gusé, 2008). A central tenant of both models is that perceived persuasive intent will mitigate a persuasive effect (Moyer-Gusé, 2008; Slater & Rouner, 2002), a common relationship found in the broader persuasion literature (e.g., Chen et al., 1996). It is when a viewer is made aware that there is a message aimed to educate or persuade, signaling persuasive intent, that they will be prompted to resist and reject the message (Ashbeek Brusse et al., 2015; W. Wang & Shen, 8 2019). It is thus recommended that a persuasive message embedded in entertainment TV should be subtle so that viewers do not detect it and subsequently feel like they were “tricked” or “manipulated” into message exposure (Ashbeek et al., 2015; Slater & Rouner, 2002). However, scant research has directly explored how audiences feel about persuasive messages embedded in entertainment TV and whether there is an expectation that TV programming will not contain such messages (Ashbeek et al., 2015; Holbert et al., 2013; Tchernev et al., 2021). The E-ELM and EORM have been tested in recent years with varying levels of support. Some studies have demonstrated entertainment to successfully persuade audiences by reducing their resistance to the message (Brusse et al., 2017; Green & Clark, 2013; Igartua & Barrios, 2012; McQueen et al., 2011), while others have found no change after exposure (E. L. Cohen, 2016; Futerfas & Nan, 2017; Guttman et al., 2008), a boomerang effect to occur (Moyer- Gusé & Nabi, 2011; Nabi et al., 2007) or a lack of support for the models’ proposed mechanisms (Billard, 2019; Frazer et al., 2021; Igartua & Vega Casanova, 2016; Jensen et al., 2011; Niederdeppe et al., 2012). A potential reason for the lack of consistency is the variability of entertainment media. Despite the growing interest in entertainment persuasion, there remains a deficit of knowledge regarding message features that influence audiences’ response to a persuasive message (Kato et al., 2017; Shen & Han, 2014). Recent calls have specifically noted the lack of research regarding how genre impacts the persuasion process (Bilandzic & Rössler, 2004; Grabe & Drew, 2007; Kato et al., 2017; Painter et al., 2020). The Variability of Entertainment TV In 2020, 1,665 original TV series were released by U.S. production companies with nearly a third of those being scripted programs (Motion Picture Association, 2020). When accounting for the vast number of cancelled and syndicated series still available, such as on streaming services and through rebroadcasts, the amount of programming for consumers to choose from becomes extraordinary and, in many cases, overwhelming (Fitzgerald, 2020). A product of such excess is the vast variability of TV programming. Shows can differ in length 9 (e.g., 25 minutes vs. 45 minutes), format (e.g., live action vs. animated), topic (e.g., medicine vs. crime), and emotional tone (e.g., drama vs. comedy), among other variables. To manage the selection process, viewers and production companies, alike, have long implemented processes and systems to help refine and identify shows that are most likely to be enjoyed (Bilandzic & Rössler, 2004; Hawkins et al., 2001; Webster & Wakghlag, 1983). Netflix, for example, has a patented machine learning system that aggregates data on previously watched content, including factors such as actors, geographic location, and release date, to provide show recommendations to viewers (Su, 2017). Genre has notably been argued as the most common classifier of TV programming (Mittell, 2001). The concept of genre dates to when Aristotle, under the assumption that a literary work was intrinsically linked to a writer’s character, classified poetry as either “noble” or “inferior” (Farrell, 2003). Despite the longevity of genre’s existence and the extension of genre study into other disciplines, such as film (Altman, 1984), linguistics (Martin, 2014), composition (Dean, 2008), rhetoric (Paré, 2014), art (Čuljak et al., 2011) and music (Rabinowitz, 2004) studies, a universal definition does not exist (Mittell, 2001). In fact, genre has largely been considered “problematic and unstable” due to its seemingly limitless bounds and dependence on interpretation (Duff, 2000, p. 1). One person’s genre, for example, may be someone else’s sub- genre or not a genre at all according to another. In the communication literature, TV genre has commonly been defined by its textual features with a focus on the narrative structure and depicted topics and stereotypes (Bilandzic & Rössler, 2004, p. 298). Conversely, recent work in genre theory emphasizes genre as a social construct (Feuer, 1992; Freedman & Medway, 2003; Mittell, 2001). Originally developed in literary studies, genre theory is a collective term used to encompass the theoretical approaches to defining genres (Dean, 2008; Duff, 2000; Farrell, 2003; Paré, 2014). Overall, modern genre theorists do not rely on textual components (e.g., contains humor) but consider the discourse between texts, entertainment industries, audiences and historical contexts during the definition 10 process (Devitt, 1993; Duff, 2000; Mittell, 2001). Genre categories are therefore socially negotiated and are thought to be constantly evolving (Altman, 1984; Devitt, 1993; Mittell, 2001). Regardless of one’s orientation, a great struggle exists in succinctly and effectively defining genre categories, especially when using human subjects (Feuer, 1992; Morgan & Shanahan, 1997). For the sake of this dissertation, genre will be conceptualized as a category of media content defined by its structural, thematic and/or functional criteria (Duff, 2000) and operationalized as distinct TV show categories used in past literature, the entertainment industry, and by study participants (further clarification is offered in the Study 2 methods section, pp. 37-40). The Role of TV Genres on Persuasion The previously discussed trajectories of research were fundamental in establishing TV as a persuasive vehicle, yet none deeply explored the role that genre plays in the persuasion process. For cultivation theory, the original tenets did not merit consideration of genres as it assumed popular TV, regardless of a program’s genre, would reinforce the same worldview (Gerbner, 1998; c.f., Potter, 2014). Highlighting the unique effects of specific genres would suggest a fragmented mediated reality and thus contradict cultivation theory’s basic premise (Shanahan & Morgan, 1999). In the EE literature, the original conceptualization of the strategy solely concerned serial dramas and, in consequence, other genres were largely ignored (Chatterjee et al., 2017). Interpretations of social cognitive theory for persuasive entertainment media considered EE as its own genre and therefore did not emphasize genre study (Sabido, 2004). Lastly, although the resistance-reduction models acknowledge that genre may play a role in the persuasion process, neither offer detailed predictions. Rather, both broadly consider genre as an antecedent to absorption as it could influence how appealing the story would be to its audiences (Moyer-Gusé, 2010; Slater & Rouner, 2002). In consequence, despite some work embracing a genre study perspective, particularly in cultivation (e.g., Hawkins & Pingree, 1981; 11 Lee & Niederdeppe, 2011) and EE (e.g., Singhal & Rogers, 2002) studies, such work remains undeveloped (Frazer et al., 2021). The research that has focused on TV genres has mostly been contained within the goals-based processing and entertainment motivation literatures, such as with the uses and gratifications paradigm (Grabe & Drew, 2007; Hawkins et al., 2001; Katz et al., 1974; Katz & Blumer, 1974; Rubin, 1983; Webster & Wakghlag, 1983). To briefly summarize, a uses and gratifications perspective considers viewers as active participants of entertainment consumption who select media to fulfill or meet certain needs (Katz & Blumer, 1974; Rubin, 1983; Webster & Wakghlag, 1983). Genre is thought to play an important role by allowing users to quickly identify media likely to gratify their need(s) for watching (Bilandzic & Rössler, 2004; Rubin, 1983). The emphasis of uses and gratifications research is on the selection process and not the persuasive effects that may incur after a show is selected and watched. That is, uses and gratifications research is motivated by why a certain genre is watched rather than to what effect. There are exceptions. Lin and Xu (2017) examined the relationship between different uses (information seeking, social interaction, habitual pastime, entertainment, and relaxation) and viewership of medical dramas. The authors found that uses, or motives, of social interaction (TV as a facilitator of social connection), entertainment (TV as an enjoyable activity), and relaxation (TV as a way to unwind) positively predicted medical drama watching. In contrast, those who reported a strong information-seeking motivation (TV to learn and think) were less likely to watch medical dramas. Yet, when looking at post-exposure effects, it was the information- seeking motive that resulted in the most successful persuasion. Those who used entertainment media for knowledge acquisition where more likely to pay attention to medical-related information in medical dramas, which subsequently led to a greater use of that information. The authors suggested that motives not only function in predicting what genres may be watched but how that content is processed, which may ultimately influence the media’s persuasiveness. 12 Situated outside of the uses and gratifications literature, Slater (1997, 2002b) proposed six goals for watching entertainment media (entertainment, information/skill acquisition, surveillance, self-interest assessment, value defense, and value reinforcement) and specified associated media genres, processing determinants, and processing strategies for each. A person motivated to watch entertainment media for information attainment, for instance, would likely turn to documentaries or history-based media and process the message didactically, wherein the persuasive message would be thoroughly processed to retain relevant information. Processing of the message would be determined by the perceived task importance (i.e., rewards associated from learning) and intrinsic interest (i.e., self-motivation to acquire knowledge from the media; Slater, 1997). Viewers with an entertainment goal, on the other hand, would be motivated to watch media like fictional TV and process the content hedonically (i.e., for vicarious social relations or excitement and distraction; Rubin et al., 1985; Zillmann & Bryant, 1994) with narrative interest and identification playing key roles (Slater, 1997). It is this later processing goal that served as the foundation for the E-ELM (Slater, 2002b) thus situating its propositions within a context of hedonic-motivated consumption. Yet, entertainment media such as fictional TV programming are not only consumed for hedonic motives. Zillmann and Bryant (1986) early on acknowledged entertainment as “any activity designed to delight and, to a smaller degree, enlighten” (p. 303). The enlightenment aspect of entertainment has been exemplified by the growing research on eudaimonic gratifications, in which entertainment media is consumed to gain meaningful experiences or to reveal truth about the greater human existence (Oliver et al., 2012; Oliver & Bartsch, 2010, 2011; Oliver & Raney, 2011; Wirth et al., 2012). Although the majority of this work has been situated outside of a persuasion context, there are some exceptions (E. L. Cohen, 2016; Das et al., 2018; Feldman & Borum Chattoo, 2019; Hamby et al., 2017). For example, E.L. Cohen (2016) tested how eudaimonic and hedonic motivations, as stable preferences, impacted responses to an embedded persuasive message about organ donation in a fictional TV crime 13 drama. The results indicated narrative processing to vary as a function of motivation preference. Contrary to what was expected, eudaimonic motivation negatively predicted processing of inferred or interpreted (i.e., subtext) messages about the donation storyline. The author suggested that those with strong eudaimonic motivations may have been disinclined to process subtext messages in a crime drama, in the first place, because it was not considered a meaningful media type, thus inadvertently highlighting the importance of genre study. Beyond the motivation-based literature, there is an ample amount of research predicting who is most likely to consume a particular genre based on demographic and psychological factors. For example, studies have investigated the links between voyeurism and reality programs (Bagdasarov et al., 2010), neuroticism and soap operas (Shim & Paul, 2007), trait anxiety and crime-focused programming (Nabi & Riddle, 2008), narcissism and suspense- inducing shows (Lull & Dickinson, 2018), and trait aggression and horror TV (Lin & Xu, 2017). Regarding demographic variables, Rentfrow et al. (2011) found gender, race and/or ethnicity, education and age to significantly predict TV genre preference. Like the majority of uses and gratifications research, though, this work treats genre as an outcome of pre-existing factors rather than as an antecedent or moderator to persuasion, providing little contribution to the current research aim. The research that has explored TV genres through a persuasion lens, regardless of theoretical orientation, has been isolated to specific genres, such as medical programs (e.g., Chung, 2014), has compared fictional to non-fictional programs, such as crime dramas against news (e.g., J. Cohen & Weimann, 2000; Grabe & Drew, 2007), or has examined overly broad genre categories (E. L. Cohen, 2016; Frazer et al., 2021; Slater, 2002b; So et al., 2011). Little work has compared specific categories of fictional TV genres in a single study for genre-specific effects (Moyer-Gusé et al., 2011; So et al., 2011). Unfortunately, the observed lack of consistency and representation of fictional TV genres is reflective of the broader TV literature. In a systematic review of TV watching by genre, Record (2018) included genres of news, crime- 14 related shows, reality shows, medical dramas, soap operas, and talk shows. Genres that could not fit into these categories were listed as “unique” genres, such as romantic programming. Although this review was not meant to serve as an exhaustive list of possible TV genres, there are obvious omissions from what is currently watched, such as with science-fiction/fantasy (e.g., Stranger Things) and historical fiction (e.g., Peaky Blinders) shows, in addition to comedies (The Office) and dramas (This is Us) un-related to crime and medicine (Motion Picture Association, 2020). This review serves as just one example of the many studies that exclude popular genre categories (Bilandzic & Rössler, 2004; E. L. Cohen, 2016; J. Cohen & Weimann, 2000; Frazer et al., 2021; Grabe & Drew, 2007; C. J. Lee & Niederdeppe, 2011; Moyer-Gusé, 2010, 2010; Painter et al., 2020; Record, 2018; Slater, 1997, 2002b; So et al., 2011). In sum, research observing genre differences in fictional TV media would benefit the current literature as has been evidenced by recent calls from communication scholars. Mittell (2001) questioned the scant theoretical work dedicated to TV genre when genre is a fundamental aspect at each stage of the entertainment media experience (i.e., production, selecting, watching, and response). Record (2018)’s systematic review of TV genre study ultimately stressed the need for more work in understanding individual genres’ unique effects. Painter et al. (2020) noted the difference between genres on subsequent persuasion to be severely undervalued in current research. Most recently, Frazer et al. (2021) called for an examination of “how humans may approach different types/genres of fiction with varying expectations” (p. 14). That is, more than just determining how different genres influence any subsequent attitude or behavior change, understanding why genres may have such an influence is needed. One consideration is that people not only have different motives for watching specific genres but that they hold different expectations for the type of information the genre will provide. Expectations of TV Genres It has been well-established that before one tests for differences between genres, one should first understand the motivations and goals audiences bring to the entertainment 15 experience (E. L. Cohen, 2016; Katz et al., 1974; Lin & Xu, 2017; Rubin et al., 1985; Slater, 1997, 2002a). The work in goals-based processing and entertainment motivation clearly address this qualification. It is argued here, however, that motivation only constitutes one possible dimension of beliefs that may influence the processing and evaluation of entertainment content. Although related, motivation and expectancy are two distinct concepts. Motivation represents a psychological state of goal pursual (Vroom, 1964) and has typically been used to examine why audiences may choose one genre over another (Guo, 2019; T. K. Lee & Taylor, 2014; Lin, 1993; Rubin, 1981, 1983; Rubin & Perse, 1987; Weaver, 2003). An expectation, on the other hand, refers to the belief that a particular outcome will befall an action and is often considered an antecedent to motivation (Feather & Newton, 1982). People hold, for example, expectations for the type of content that will be present in different genres (Bilandzic & Rössler, 2004; Mittell, 2001; Nabi & Clark, 2008). Indeed, the justification for genre study in the cultivation paradigm was that different genres did not present different versions of reality but focused on different aspects (J. Cohen & Weimann, 2000). Take the example of alcohol consumption. While a comedy show may be more likely to show alcohol in the context of having fun with friends, a medical drama may be more inclined to cover the consequences of alcohol poisoning. This is a product of the themes and events commonly presented in those genres: comedies emphasize absurd and exciting situations, such as partying, whereas medical dramas feature the diagnosis and treatment of health issues (Lee & Taylor, 2014). The two genres do not necessarily promote contradictory worldviews (pro-vs. anti-drink) but merely reflect different aspects of the behavior (J. Cohen & Weimann, 2000). If watching a medical drama, it is likely that audiences will expect to receive information about health behaviors, as it is the focus of the program, and likewise for other genres (e.g., crime = crime content). But how does that expectation influence subsequent acceptance of the information provided? Is the content of fictional TV shows thought to be more or less accurate 16 based on the nature of the genre, such as if it is a medical drama or a situational comedy? Viewers may not be primarily motivated to watch entertainment TV for information-seeking, but there may still be variations in their expectancies for knowledge acquisition even in entertainment-driven media. That is, if people continually learn new information from certain shows that are deemed applicable to their own lives, they may begin to anticipate learning from shows of that genre in the future. The current research pulls from the work in expectancy- violations theory to clarify how and why expectations may influence the persuasion process. Expectancy-Violations Theory Originally developed in the interpersonal communication scholarship for nonverbal situations, expectancy-violations theory (EVT) predicts what may happen when people act in unusual or unexpected ways (Burgoon, 1993, 2015; Burgoon & Hale, 1988). The basic premise of EVT is that people hold different expectancies for social situations based on previously observed patterns of behavior. If, for example, a person named Max is known to dislike bodily contact, their friends would not expect Max to initiate physical touch. An expectancy violation could occur, however, if Max acts counter to the expectation, such as by giving a hug to everyone before leaving a social event. When a person’s expectation is violated, their arousal will increase as they analyze what occurred and contemplate how to respond. The valence of the violation (i.e., whether the violation was unpleasant or pleasant) and the relationship felt with the violator (i.e., proxemics or personal space) will ultimately guide a person’s response to the violation (Burgoon et al., 2016). In the present example, the violation committed by Max would likely be seen as a positive deviance and would strengthen their relationship with their friends. Hence, unlike many other interpersonal theories that tend to dissuade against violating a person’s expectations or norms in a social encounter, EVT states violations can be preferable if the violence is considered positive (Burgoon, 2015). For example, positive violations have been found to increase liking (Bettencourt et al., 1997; Burgoon & Le Poire, 1993) and perceived 17 credibility (Dunbar & Segrin, 2012; Hackett et al., 2008) of others, and to promote student learning (Mazer et al., 2007). Expectancy-violations theory has been studied in a range of media contexts such as regarding social networking sites (Bevan et al., 2014; Bullock & Hubner, 2020; Rui & Stefanone, 2018; Tomasi et al., 2021), computer-mediated communication (Burgoon et al., 2016; Kalman & Rafaeli, 2011; Nicholls & Rice, 2017; Ramirez & Wang, 2008; Waddell, 2018), mass media campaigns (Campo et al., 2004; Siegal & Burgoon, 2002), and corporate marketing (S.-Y. Park et al., 2021; Rim et al., 2020). Less research has investigated entertainment media from an EVT perspective (Bonus et al., 2021; E. L. Cohen, 2010; Hong et al., 2021; Matthews & Bonus, 2021). In line with EVT’s interpersonal communication origins, most of the research that has focused on entertainment media has tested how expectancy violations function with mediated characters. For example, E. L. Cohen (2010) tested whether moral, trust, and social expectancy violations influenced subsequently perceived relationship closeness to real friends and media figures. Regarding film, Bonus and colleagues (2021) tested how violations of audiences’ expectations of a character’s morality influenced the parasocial relationship (PSR) formed with different characters. To date, only one known study has moved beyond an interpersonal context to explore how expectations of messages features, such as genre, influence subsequent appraisals. Hong et al. (2021) found expectancy violations of music genre to influence participants’ evaluation of artificial intelligence-generated music. As predicted, violations in a positive valence (music was better than expected) resulted in much higher evaluations of the music than if the violation was in the negative direction (music was worse than expected). The present dissertation extends this research into the area of TV genres and questions how genre expectancy violations may influence subsequent persuasion attempts in the media. Despite the lack of persuasion research in genre expectations, speculations can be made. Viewers have been found to hold expectations of the anticipated sequence of events (Katz & Liebes, 1990; Nabi & Clark, 2008). If viewers hold expectations of the content in 18 different fictional TV genres, it is likely that a violation should incur some sort of reaction. Yet, the direction of that relationship and the nature of the expectations held for different TV genres is unknown. The first step toward determining whether a relationship exists between genre expectations and effective persuasion is to understand whether audiences have different expectations about the content reflective of certain genres in the first place. The Current Research In sum, entertainment TV has been established as an effective vehicle for spreading messages to inform and persuade. The pervasiveness of TV media and popularity of serial TV programming creates a suitable medium to communicate persuasive messages through, such as by being able to use characters that viewers have formed strong bonds with to relay the information (Bandura, 2004; Gerbner, 1998; Sabido, 2004; Shrum, 1995). Despite genre being a defining aspect of TV programming, much is still unknown about how genre impacts the persuasion process. Genre, a system of categories used to anticipate the theme, topics, and/or feeling derived from TV shows (Dean, 2008; Devitt, 1993; Duff, 2000; Farrell, 2003), is a known motivating factor when choosing what to watch, but the implications it has for the processing of persuasive messages has only recently been questioned (Frazer et al., 2021; Painter et al., 2020; Record, 2018). The present dissertation offers insights into the role that genre expectations play in the persuasion process across three studies. Study 1 provides results from qualitative interviews on the expectations and perceptions viewers have about different fictional TV genres, including factors of content credibility, learning potential, and the likelihood and appropriateness of a persuasive message being integrated. Guided by the results of Study 1, Study 2 quantitively catalogues through a survey of U.S. adults viewers’ perceptions regarding a stable set of TV genre categories and determines distinct expectation differences between the genres. Lastly, Study 3 experimentally tests the causal relationship between genre expectancy violations, message resistance, and acceptance of a persuasive message for two types of fiction TV genres (science-fiction/fantasy and historical fiction). The implications the results have 19 for our current understanding of entertainment persuasion as a resistance-reduction strategy is discussed, in addition to how these findings can aid practitioners communicating through fictional TV. Figure 1 provides a visual representation of the methods and aims of each study conducted. Figure 1. Aims, Method and Sample of All Studies. •Aim: Exploratively assess assumptions and expectations of whether and when TV contains persuasive messages and the role that genre has in those beliefs. •Method: Qualitative interviews Study 1 •Sample: N = 19 •Aim: Statistically determine audiences' expectations (credibility, learning, persuasive liklihood, and anticipated acceptance) of specific fiction TV genres. •Method: Online survey Study 2 •Sample: N = 593 •Aim: Experimentally test the causal relationship between TV genres, expectancy violations, message, resistance, and persuasive outcomes. •Method: Online experiement Study 3 •Sample: N = 188 20 CHAPTER THREE: STUDY 1 Study 1 had five research aims. First, I sought to understand whether viewers considered the content of fictional TV to be factual or accurate. Many studies have objectively examined the accuracy of TV content (Cowley et al., 2017; Foss, 2011; Gordon et al., 1998; Polk et al., 2016; Yaguchi et al., 2022), but few studies have investigated audiences’ perceptions of the accuracy of fictional TV programs (Funk et al., 2017; Green, 2006; Wright et al., 1994). A common assumption is that audiences do not expect fictional TV to present credible information (Appel & Richter, 2007; Burzyńska et al., 2015). Yet, psychological research has found people to approach information with initial credulity as it takes additional cognitive resources to discount or disbelieve the content, which many are unwilling to exert by default (Gilbert, 1991; Gilbert et al., 1990, 1993). Extending this logic to fictional media, Busselle and Bilandzic (2008) argued that the fictionality of a media is unlikely to be readily active and instead functions as tacit knowledge, or information not used in a conscious way but may influence perceptions if activated. Thus, if the fictionality of fictional TV is not automatically salient, information obtained from fictional TV is likely to be deemed accurate unless otherwise challenged. In simpler terms, “fiction” may not always be equated with “false” content (Green, 2006). The present study sought to explore how viewers, in their own words, considered the issue. RQ1: How accurate do viewers believe the content presented in fictional TV to be? Next, the perceived prevalence of persuasive or educational messages in fictional TV was determined. Historically, EE programs have been conducted outside of the U.S. and the highly privatized and competitive U.S. media environment has made EE programming unpopular in primetime TV (Chatterjee et al., 2017; Kato et al., 2017; Moyer-Gusé, 2008; Singhal & Rogers, 2002). The lack of EE programming available in the U.S. suggests that people may be less expecting of educational content in entertainment programming (Chatterjee et al., 2017). Indeed, Tchernev et al. (2021) recently conducted focus groups assessing viewers’ 21 perceptions of a political satire comedy with a pro-environmental story-arc. Despite the episode having an explicit persuasive appeal, participants did not detect a persuasive intent. Rather, participants seemed to hold stringent perceptions of what constitutes persuasion, i.e., “persuasion” only exists if attempting to change a person’s mind and not for pro-attitudinal or educational messages. Because most participants agreed with the pro-environmental message, they did not consider it a persuasive appeal. Thus, it may be possible that people have higher expectations of educational and persuasive content in entertainment programming, but that it must be framed as education, attitude reinforcement and attitude change. RQ2: How often do viewers think fictional TV contains persuasive appeals? If persuasive messages are identified, it is important to learn how audiences would react. Our current theoretical models suggest a negative relationship between perceived persuasive intent and persuasion in entertainment media (Ashbeek Brusse et al., 2015; Holbert et al., 2013; Moyer-Gusé, 2010; Moyer-Gusé & Nabi, 2010; Slater & Rouner, 2002). Yet, the research supporting this relationship is mixed. Some studies have found perceived persuasive intent to diminish successful persuasion (Moyer-Gusé et al., 2019; Moyer-Gusé & Nabi, 2010; W. Wang & Shen, 2019), while others have found it to have no effect on persuasion (Frazer et al., 2021; Ma & Nan, 2018). Rather than test the effectiveness of explicitly persuasive content, the present study sought to determine how viewers felt about the tactic, in general. Indeed, little research has actually explored how audiences qualitatively think about such attempts (Ashbeek Brusse et al., 2015; Tchernev et al., 2021). Ashbeek Brusse and colleagues (2015) found a survey of Netherlands TV watchers to judge embedded persuasive messages as immoral and in bad taste, however, the study focused solely on medical dramas and on controversial health topics (abortion and cosmetic surgery). It is possible that if persuasion is framed beyond attitude change and to include different kinds of genres and topics, participants may be more accepting of persuasive appeals in fictional TV. RQ3: How do viewers feel and think about persuasive appeals in fictional TV? 22 Lastly, as genre expectations are a main interest of this dissertation, I questioned whether audiences held expectations or assumptions about whether certain TV genres were more or less likely and appropriate to contain persuasive messages. To date, no known research has directly explored audience expectations of different fictional TV genres for persuasive information. RQ4: Do viewers perceive differences in the likelihood and appropriateness of persuasive appeals in fictional TV based on genre? Study 1 Method Participants Twenty participants were recruited from the College of Communication Arts and Sciences’ (CAS) SONA community research pool at Michigan State University (MSU) and interviewed between March and May 2021. The interviews lasted between 26 – 62 minutes and took an average of 41.79 minutes (SD = 10.07) to complete. One participant was removed from the data set due to lack of data quality, resulting in a total sample size of 19 participants.2 Participants ranged in age between 20 – 42 years (M = 25.26; SD = 5.76), identified mostly as female (78.95%), and spent between 1–6 hours watching TV a day. Participants identified as being White/Caucasian (52.63%), South Asian (10.52%), East Asian (31.58%) and Biracial (5.26%). Table 1 contains participant identifiers and demographic information. 2 Despite attempts to move the interview along, the participant spent approximately 35 minutes answering the first question, which was not relevant to the main analysis of the current study. Due to the lack of data quality, the participant was removed from the data set during the transcription stage. 23 Table 1. Study 1 Participants and Demographic Information. Participant ID Sex Age Race/ethnicity Daily hours spent watching TV P1 Female 23 White 1 P2 Female 24 White 3 P3 Female 25 White 3–6 P4 Female 24 White 1–3 P5 Female 33 South Asian 1 – 1.5 P6 Male 35 South Asian 1 – 1.5 P7 Male 26 Biracial 1–4 P8 Female 26 East Asian 3–4 P9 Female 22 White 2–4 P10 Male 23 East Asian 2–4 P11 Male 22 White 2–3 P12 Female 20 White 2–3 P13 Female 27 East Asian 1–2 P14 Female 22 East Asian 1–2 P15 Female 19 White 1–2 P16 Female 20 East Asian 4 P17 Female 21 East Asian 2–3 P18 Female 26 White 4–5 P19 Female 42 White 2–3 Procedure Participants first completed an online questionnaire to determine eligibility and to provide demographic information. Participants were contacted to schedule an interview if they reported watching at least one hour of fictional TV a week (excluding reality, sports, and news programming). After providing informed consent, semi-structured interviews were conducted online via Zoom. The first two sections of questions regarded participants’ TV watching behaviors and their preferences, asking questions such as how often they watch fictional TV and what inclines them to watch a particular show over others. The third section included questions specific to persuasive content in fictional TV, such as asking participants if they could recall a time in which they were successfully educated or persuaded by a show. To address the observation that people have a difficult time recognizing persuasive messages in fictional TV (Tchernev et al., 2021), the terms “persuasive” and “educational” were not used. Rather, participants were specifically asked about instances in which fictional TV content changed their mind about an issue or educated them about a topic. Lastly, participants reflected on any 24 expectations or preferences they had about fictional TV, including whether persuasive messages were specific to certain types or genres of shows. The complete interview guide can be found in Appendix B. Those who completed an interview were thanked and compensated for their participation. Analytic Procedure. The interviews were recorded and transcribed verbatim. To identify key patterns in the data, a thematic analysis was performed using Braun and Clarke's (2006) suggested procedure. Each interview transcript was first coded for repeated sentiments, potential themes, and unexpected answers. Then, for each research question of the current study, themes were identified and reviewed for internal consistency across the interviews. Only themes at the semantic or explicit level were sought. That is, I recorded and interpreted what was said by the participants rather than attempt to identify underlying ideologies or systems- level influences. Thus, an essentialist epistemology approach (i.e., merely reporting the reality and experience of the individuals interviewed) was employed (Braun & Clarke, 2006). Illustrative examples and quotes were selected to help define and explain the identified themes. Study 1 Results Perceived Accuracy of Fictional TV Content RQ1 asked how accurate audiences consider the information provided in fictional TV programming to be. Although many participants acknowledged fictional TV to dramatize certain aspects of reality, they overall felt the information presented to be factually accurate. For example, one participant said, “I generally feel that they’re pretty accurate because all these shows are well researched and pretty well done” (P5). Another participant stated, “I think it’s relatively accurate. Obviously, some things are going to be skewed a little bit for entertainment purposes in trying to make, you know, like more viewers watch the show and things like that, but I think the basis of what they’re talking about has truth to it” (P2). 25 The recency or age of a TV program was considered an important factor when gauging informational accuracy with newer shows being deemed more accurate than older shows. For example, a participant stated, “I think if we’re looking at TV shows that are out today, that are still creating new episodes today, I think they’re more prone to have accurate information, versus not accurate information at all. Like, I don’t think any show that’s out today would give something that’s not accurate” (P10). When probed for an explanation as to why newer shows would be more likely to present accurate information, the participant clarified, “I feel like they might have some kind of feeling of responsibility that they don’t want to portray it in a false way because otherwise people will be mad at them and not want to watch” (P10). In addition to the timing of a show, participants’ perceptions of accuracy were dependent on the context or genre of the programming. It should be noted that the distinction of informational accuracy by genre was not initiated by the interviewer. Participants, on their own, began distinguishing different types of genres they identified and defined when answering the questions. The overall assumption was that sitcoms or comedy-oriented shows were less likely to contain accurate information compared to procedural and historical dramas. One participant explained, “I think with like the medical dramas and the crime shows… they try to be as accurate as possible… more so than like sitcoms and things like that. So I think there’s not necessarily as much continuity when it comes to sitcoms, it’s just kind of there for the laughs and keeping you entertained, but like medical shows, crime shows, law shows, things like that try to be as accurate as possible, because I think they kind of think that if they’re not, the public will kind of point out those, those things that they do incorrectly and that’ll kind of tarnish their credibility of the show a little bit” (P2). 26 Using specific shows as examples, one participant hinted that they would trust health information from medical-oriented shows more than comedies, even if education was not an aim of the program: “Yeah, I would say medical shows… Especially if there’s a show like Grey’s or Scrubs, they’re not like, the whole point of that show is not like, ‘let’s make a really medically accurate show.’ Like it’s about the people and their relationship, so… it’s not always the main focus, which is understandable. But yeah, I would trust them to get it more right than like if somebody from Friends was in the hospital with something. I think Grey’s would probably do a better job portraying that then Friends would” (P5). Thus, although participants thought content in fictional TV was accurate, the age and genre of a show were cited as key factors when making the assessment. Prevalence of Persuasive Content in Fictional TV RQ2 asked about participants’ perceived prevalence of persuasive and educational messaging in fictional TV. If discussing fictional TV, in general, it was difficult to determine a unified perception regarding the frequency of embedded persuasive appeals. Participants reported strong views of its prevalence in both directions, with some expressing, “Yes, they definitely do” (P19) and others responding, “I would say, I would say rarely” (P11). Instead, participants framed their responses around certain types of programs and shows, such as by saying, “I think it depends on the show, but I think a lot of shows have some sort of education purpose” (P17). Like perceptions of content accuracy, the presence of persuasive content in fictional programs was thought to be a characteristic of newer TV shows and of specific genres. For example, when discussing fictional TV shows having educational storylines, one participant said, “I would say a lot of shows like recently, that are coming out, are definitely trying to do that” (P15). Furthermore, medical, crime, and historical dramas were thought to have more persuasive messages than comedy shows. A participant elaborated on medical dramas saying, 27 “I'd say that some of the medical shows have definitely been pushing things like, for example, I just watched an episode of The Resident where they talked about how black women are disproportionately victims of medical neglect when they're having children. And that really made me think. So like, you know, there was this whole plot around making that point and then at the end, they had an ending screen just saying like ‘this is real blah, blah, blah.’ So yeah, I'd argue that medical shows kind of make more of an overt point of that” (P14). It is noteworthy that nearly all of the examples that participants provided either brought awareness to a new social or health issue (e.g., racial health disparities) or provided further information about an issue they were already supportive of. No participant cited an instance in which fictional TV changed their views about an issue. Indeed, one participant stated, “I wouldn't say it is ever like changed my mind that drastically. But yeah, no, I… I learned more about like the intricacies of that statistic and like, there was an episode of Grey's semi-recently that was like talking about how, how like PTSD in a lot of healthcare workers can really mess them up. And like seeing the more specifics of that” (P14). Participants cited two reasons for why it was unlikely for them to have their minds changed from a fictional TV narrative. First, participants generally thought the messages currently being distributed in popular media were already pro-attitudinal to their own beliefs. Second, participants thought it was unlikely they would be watching a show that would hold a counter-attitudinal message to begin with. In other words, participants watched shows that aligned with their own values, lessening the chance that they would be exposed to a counter- attitudinal message. To illustrate, a participant explained, “I tend to watch TV shows that display content that I tend to agree with, as opposed to one I didn’t…In general, though, most of culture, pop culture, will create TV shows that I agree with” (P11). 28 Reception to Persuasive Content in Fictional TV RQ3 asked how participants have responded in the past or would respond in the future to a fictional TV show having a persuasive or educational appeal. In general, participants were largely supportive of the tactic. For example, P6 expressed enthusiasm for the integration of educational content into fictional TV, saying, “Uh, I totally advocate that. I totally do. Yeah, more power to those shows.” Others highlighted how they respected and appreciated shows that made explicit efforts to promote prosocial messages and/or educated its audience about an issue. Example responses included: “I think it's good. I think, unfortunately, so many people including myself, are glued to the TV nowadays. So, if we're going to teach, you know, if we're going to teach people these important messages like it's not necessarily a bad thing to incorporate it into the TV shows that they're watching” (P18), and “I think, in general, it usually makes me like the show more because it shows me that they’re actually trying to do something with their show… I feel like these shows are actually trying to make a difference” (P4). Expectations of Persuasive Content in Fictional TV Lastly, RQ4 questioned whether participants held different expectations for whether certain genres would be more or less likely and appropriate for persuasive appeals to occur in. Participants readily stated that they had different expectations for whether persuasive content would appear in a show based on genre, such as by stating, “I think people have different expectations based on like the content of the show that they watch, for sure.” (P4). In line with what was observed regarding content accuracy and perceived prevalence, procedural and historical dramas were cited as being the most likely and appropriate for persuasive appeals to be embedded in. Specifically, because procedural dramas are often based in the medical and crime fields, their context is naturally more conducive to exploring 29 real-world issues and events rather than comedies, which are less constrained by realism. For example, P2 stated, “I think for comedies, like in sitcoms, that it's a little harder to take those stances because it [the target behavior] is a lot of times more serious than what the show is about. So, I think it is easier for medical dramas or law, or historical things like that to kind of incorporate these aspects, more so than sitcoms and comedies.” Relatedly, the topic of a procedural drama was thought to indicate what type of message would be communicated. One participant explained, “I would expect something medical related with a medical drama, crime related with a crime drama, etc.” (P10). Study 1 Discussion The current study explored the perceptions of fictional TV content and how viewers anticipate and feel about the tactic of integrating persuasive and educational appeals into entertainment TV. Through the analysis of interview data, this study provides preliminarily support that audiences hold distinct expectations about the content of fictional TV programs and that genre plays a significant role in those beliefs. It was observed that audience generally believe fictional TV to present accurate information about the world, especially in newer shows, procedural dramas, such as those set in the medical and crime fields, and historically based shows. This finding supports prior research indicating fictional TV to not be automatically discredited for factual information (Busselle & Bilandzic, 2008; Green, 2006) and offers additional insights into viewers’ rationalization of this belief. To the participants interviewed, the likelihood of a TV show containing accurate information was discussed as a response to the rise of misinformation and fake news (Figueira & Oliveira, 2017; Jang & Kim, 2018). Whereas participants thought it was more acceptable and common for older TV shows to dramatize situations and facts, current TV shows were held to a higher standard for combating or, at the minimum, not contributing to misinformation. For example, some participants elaborated that because “fact checking” is such a common practice, a current TV show distributing inaccurate 30 information would be judged as low quality and ultimately looked down upon by its audience. It should be noted, however, that the sample was relatively young and may therefore not be a suitable demographic for generalizing about the content of “older” TV shows (e.g., I Love Lucy). Regardless, participants were observed to hold strong expectations about current TV programming, namely that its content is considered factually accurate more often than not. Audiences are generally thought to be resistant towards persuasive appeals in entertainment media (Ashbeek Brusse et al., 2015; Holbert et al., 2013; Moyer-Gusé & Nabi, 2010; Slater & Rouner, 2002; W. Wang & Shen, 2019), yet the current study found little support of this assertion. Instead, when persuasion was explained to extend beyond attitude and behavior change and to include other forms, such as knowledge gain and attitude reinforcement, participants positively reflected on times in which they learned from fictional TV or had their pre-existing beliefs reinforced. Participants specifically used the language of appreciation, as in, they would appreciate or respect a fictional TV show more if it took a firm stance on an issue or managed to educate them about a topic. The lack of negative resistance is likely due to participants not being able to recall a time in which they were confronted with a counter-attitudinal message. Recent research has suggested that the disruptive effect of an explicit persuasive appeal may be isolated to counter-attitudinal messages and that pro-attitudinal messages may not incur a negative reaction, even if audiences are made aware of the persuasive intent (Frazer et al., 2021; Moyer-Gusé et al., 2019, 2019; Tchernev et al., 2021). The present research seems to support this assertion. Yet, our current theoretical understanding of the explanatory mechanisms of entertainment persuasion are rooted in attitude change. For instance, the E- ELM is founded upon the principles of the elaboration likelihood model, a persuasion model predicting attitude change, thus inherently positioning its logic in a context where message rejection is expected from the on-set (Petty & Cacioppo, 1986; Slater & Rouner, 2002). Indeed, both the E-ELM and EORM attribute entertainment media’s persuasion success to the extent 31 that it reduces message resistance, such as by lessening the chance for counterarguing and reactance (Moyer-Gusé & Nabi, 2010; Slater & Rouner, 2002). It should be noted that even when participants were asked how they would react to a TV show promoting a belief or message they disagreed with, the majority answered neutrally. Participants responded with statements such as, “Unless it’s something really offensive then I feel like I’m not really too bothered” (P8) and “I wouldn’t really care that much” (P1). Further inquiry revealed that the lack of an anticipated negative response was due to participants believing that they would not naturally encounter such messages, in general, due to their entertainment media preferences. People have long been found to limit their exposure to information that favors their own beliefs and values, such as in the work on selective exposure (Klapper, 1960), confirmation bias (Nickerson, 1998), and echo chambers (Sunstein, 2009). Indeed, in the current research, participants explicitly acknowledged their inclination to only watch TV shows that align with their current values and beliefs. The notion that audiences chose entertainment TV selectively is not novel (Zillmann & Bryant, 1985), but does further stress the need to re-evaluate the sole reliance on a resistance- reduction approach in a persuasion context. If people do not naturally believe they are exposed to counter-attitudinal messages, in the first place, should resistance-reduction be the primary mechanism in which we interpret successful persuasion? Even if viewers are exposed to a counter-attitudinal message, it is not for certain whether message resistance would still be the primary driver of influence. For example, Frazer et al. (2021) found that even after signaling explicit persuasive intent across four controversial topics (immigration, abortion, healthcare, and the death penalty), a reduction of counterarguing was not found to explain why a fictional narrative was more effective than a news article. Further research testing resistance reduction as the explanatory mechanism of entertainment persuasion for pro-attitudinal and prosocial behaviors hence seems needed. 32 This dissertation suggests expectancy violations as a mechanism in which to add further understanding for how entertainment facilitates persuasion. The present study initiates this inquiry by establishing viewers to have strong expectations about the content of different fiction TV genres. Even before the role of genre in entertainment perceptions was introduced in the interviews, participants began contextualizing their answers using genre labels, such as by saying certain genres were more likely to contain educational content than others. Genres are inherently formed by a shared expectation and understanding of the type of content encompassed within a certain label (Devitt, 1993; Feuer, 1992; Mittell, 2004; Record, 2018), but up to this point, the use of TV genres to categorize persuasion expectations has not been empirically documented. Participants not only held strong expectations for the type of information they would receive from genres but had expectations for if the information would be accurate and whether intentional persuasive messages would be appropriate to that kind of programming. Medical, crime, and historical dramas were most referenced when discussing suitable media to contain educational and persuasive messages, whereas comedies were largely considered the least suitable. Relatedly, comedies were also referenced as less factually accurate than other genres. Comedies have been successful in narrative persuasion attempts in the past (Collins et al., 2003; Futerfas & Nan, 2017; Moyer-Gusé et al., 2018) but a main concern is that the severity of the issue may be trivialized, discounted or diminished by the humor in the narrative (Moyer-Gusé et al., 2011). In the current study, participants noted the lack of realism as the main contributor to their skepticism: comedies were thought to exaggerate situations to the point that its applicability to their own lives became unclear. Although perceived realism has been shown to influence media effects across a range of topics (Bilandzic & Busselle, 2011; Huesmann et al., 2003; Landreville & LaMarre, 2013; L. M. Ward & Carlson, 2013), it was not directly investigated in the current study, so it can only be speculated as an influential aspect in how people differentiate between genres. 33 A main limitation of this study is that because the genres discussed were self-initiated rather than provided from a set list, the distinctions between different genres were quite broad (e.g., dramas vs. comedies) and, at times, inconsistent. For example, some participants referred to medical shows broadly when answering the questions while others distinguished between medical comedies and medical dramas. Thus, while this study supports that people hold different expectations for specific genres, the results were unable to provide a direct comparison of different genres categories. Instead, a quantitative testing of how different pre-determined TV genres compare with one another in terms of persuasion-relevant expectations is needed. Furthermore, the lack of a set list of genres for participants to evaluate may have contributed to the unclarity of whether entertainment programs were believed to contain persuasive and educational messages. Some participants strongly said it was common for fictional TV shows to contain persuasive messages while others said it was not common. Yet, when this question was asked, it was not in context to specific genres but of fictional TV, in general. Participants, themselves, began answering using specific shows and genres. Subsequent research assessing the perceived likelihood of fictional TV containing persuasive and education appeals should therefore be precise in the different types of programming asked about. Lastly, in consideration that participants were most likely to recall instances of knowledge acquisition from fictional TV and that there is theoretical unclarity regarding the explanatory mechanism for pro-attitudinal and prosocial appeals, the remainder of this dissertation focuses on genre expectations for learning. This decision is consistent with the longstanding goals of the EE strategy (Bandura, 2004; Sabido, 2004; Singhal & Rogers, 2002). Rather than facilitate attitude change, EE has been argued to be most effective in informing, enabling, and motivating audiences to perform a behavior (Bandura, 2004). When isolating specific expectations audiences hold for fictional TV genres, their expectations for learning thus seemed the most appropriate variable to consider moving forward. 34 CHAPTER FOUR: STUDY 2 Guided by the results of Study 1, the current study sought to statistically determine whether there were distinct differences between fictional TV genres regarding persuasion- relevant expectations. Specifically, the current study sought to measure expectations of content credibility, learning potential, and perceived likelihood of an educational message appearing in a genre, and to determine the specific genres ranked highest and lowest in those expectations. It was observed that audiences generally believed the content of fictional TV to be factually accurate. The current study extends this finding by investigating the perceived credibility of such content, a variable that has long been found as a determinant of persuasion in non-narrative (Foy et al., 2017; Kopfman et al., 1998; Mutti-Packer et al., 2017) and narrative contexts (E. Kim et al., 2022; Kreuter et al., 2007). By testing for differences in perceived credibility, the current study investigates the dimension of factual accuracy while accounting for perceptions of believability and perceived realism of fictional TV genres as well (Appelman & Sunday, 2016). H1: Participants’ expectations of content credibility in fictional TV will vary by genre. RQ1: From what genres will participants have the highest and lowest expectations of content credibility? Regarding the perceived learning potential of different TV genres, only one known study has measured learning expectations of fictional TV. Moyer-Gusé (2010) conducted an experiment testing how preference for watching an episode would vary by program genre (i.e., news vs. scripted drama) and learning expectations (i.e., episode created purely for entertainment vs. to promote a healthy behavior). It was found that learning expectations mediated the effect of program genre on preference for watching. Participants held higher learning expectations for the news program, which led to an increased desire for watching. The current research expands this research by investigating audiences’ pre-existing learning expectations for entertainment TV rather than observing it as a manipulated variable (i.e., signaling persuasive intent). Additionally, whereas Moyer-Gusé (2010) compared a fictional TV 35 drama to a news program, the present research contributes a comparison of different genres within fictional TV. H2: Participants’ expectations of learning from fictional TV will vary by genre. RQ2: From what genres will participants have the highest and lowest expectations of learning? In addition to learning expectations, participants’ expectations for the likelihood of an education attempt occurring in the genres was measured. That is, whether participants believed a certain genre would be more or less likely to intentionally place an educational message into its programming. Prior research has assumed audiences do not expect entertainment TV to have persuasive messages (Chatterjee et al., 2017; Tchernev et al., 2021), but the qualitative interviews in Study 1 were inconclusive. Although there appeared to be clear expectations about the likelihood of an educational message occurring in specific genres, a direct test of participants’ expectations by genre was warranted. H3: Participants’ expectations of the likelihood of a fictional TV show containing an educational message will vary by genre. RQ3: For what genres will participants have the highest and lowest expectations of education likelihood? Lastly, the overall goal of this dissertation is to determine how genre expectations, and their violations, impact the persuasion process in an entertainment TV context. Up to this point, there has been an assumed relationship between genre expectations and eventual acceptance of a message. However, this assumption has not been directly tested. Before testing how violations of expectations may impact the persuasion process, it was first important to establish a relationship between expectations and acceptance in general. Thus, the relationship between expectations (of credible content, learning potential, and education likelihood) and hypothetical acceptance of a persuasive message was tested. 36 H4: Participants’ expectations of credibility, learning potential, and appeal likelihood will be positively associated with hypothetical acceptance of an educational message embedded in fictional TV programming. Study 2 Method Participants Participants (N = 593) were recruited through Prolific, an online crowdsourcing research pool, in February 2022. According to a G*Power analysis, a sample size of 547 participants was needed to detect an effect size of Cohen’s d = 0.123 with 80% power (alpha = 0.05, two-tailed) for one sample t-tests to be conducted. Initially, 600 participants completed the study, however seven participants were removed due to failing the attention check (i.e., “please select ‘disagree’). To be eligible for participation, participants had to be fluent in English, reside in the U.S. and watch fictional TV on a weekly basis at the minimum. Participants ranged in age between 19 – 72 years (M = 35.50, SD = 12.89) and were mostly white (71.20%), female (56.80%) and formally educated (59.30% holding an associate degree or higher). The most frequently reported household income and state of residence was $20,000 - $29,999 (11.30%) and California (20.60%), respectively. Table 2 provides all demographic information for the sample. Table 2. Study 2 (N = 593) Sample Characteristics. Variable Min – Max M (SD) % Age 19 – 72 35.50 (12.89) - Gender - Male 39.80 Female 56.80 Non-binary 3.20 Prefer not to say 0.02 Race/ethnicity White or Caucasian 71.20 Black or African American 6.01 3 The effect size of interest was set based on Shen and Han’s (2014) systematic analysis of TV entertainment for health communication. 37 Table 2 (cont’d) Race/ethnicity Min – Max M (SD) % Hispanic or Latino 2.20 Asian 13.50 Native American or Alaska Native 0.80 Native Hawaiian or Pacific Islander 0.00 Two or more races 5.70 Prefer not to say 0.50 Education Less than high school degree 0.80 High school graduate 14.30 Some college but no degree 35.60 Associate degree 10.50 Bachelor’s degree 38.30 Master’s degree 8.30 Doctoral degree 0.70 Professional degree (JD, MD) 1.50 Income Less than $10,000 10.00 $10,000-$19,999 7.80 $20,000-$29,999 11.30 $30,000-$39,999 10.20 $40,000-$49,999 9.30 $50,000-$59,999 7.30 $60,000-$69,999 7.80 $70,000-$79,999 8.50 $80,000-$89,999 4.20 $90,000-$99,999 4.90 $100,000-$149,999 10.30 $150,000 or more 8.50 State of residence Alabama 1.50 Alaska 0.20 Arizona 2.00 Arkansas 1.00 California 20.60 Colorado 1.70 Connecticut 1.00 Delaware 0.30 District of Columbia 0.20 Florida 5.90 Georgia 2.20 Hawaii 0.50 Idaho 0.30 Illinois 4.70 Indiana 1.90 Iowa 1.00 Kansas 1.00 Kentucky 1.30 Louisiana 1.20 38 Table 2 (cont’d) State of residence Min – Max M (SD) % Maine 0.20 Maryland 1.50 Massachusetts 1.50 Michigan 3.00 Minnesota 1.00 Mississippi 0.80 Missouri 1.30 Montana 0.20 Nebraska 0.20 Nevada 1.70 New Hampshire 0.00 New Jersey 1.90 New Mexico 0.20 New York 5.10 North Carolina 2.40 North Dakota 2.40 Ohio 3.00 Oklahoma 0.80 Oregon 2.70 Pennsylvania 2.90 Rhode Island 0.30 South Carolina 1.20 South Dakota 0.00 Tennessee 2.50 Texas 7.90 Utah 1.30 Vermont 0.20 Virginia 1.90 Washington 3.70 West Virginia 0.20 Wisconsin 1.70 Wyoming 0.20 Procedure After providing informed consent, participants answered the measures listed below, in the order they are presented, ending with demographic items. Most participants completed the study using a laptop or computer (88.70%), followed by a tablet (7.60%) and cellphone (3.70%). The survey took an average of 13.22 minutes (SD = 15.02) to complete. A primary aim of this study was to assess how participants perceived different TV genres. To generate a list of genres, the labels and terminology participants used in Study 1 were compiled. Afterward, industry reports (e.g., TiVo, 2019) and past scholarship (Hawkins et 39 al., 2001; Lull & Dickinson, 2018) were consulted to identify any missing genres. This process resulted in ten genres: animated comedy, animated drama, comedy, crime comedy, crime drama, historical fiction, general drama, medical comedy, medical drama, science- fiction/fantasy. Participants were provided the genre label and exemplar shows but allowed to infer their own precise definitions (see Table 3). Through this method, the perceived discursive nature of genre suggested by genre theory was maintained (Dean, 2008; Duff, 2000). Some have questioned whether the lack of precise boundaries cause participants to define the same genre differently (Morgan & Shanahan, 1997), but many scholars have disregarded this concern (Bilandzic & Rössler, 2004; Grabe & Drew, 2007). Viewers are regularly forced to choose and communicate about TV genres in their daily lives, such as when selecting a show or communicating their preferences to others, and are thus quick to recognize the meaning of different genre labels (Bilandzic & Rössler, 2004). By providing a consistent list of genres with example shows, it is reasonable to assume that participants inferred similar definitions of the genres asked about. Measures Reliability and descriptive statistics for all measures can be found in Table 3. TV Watching Behaviors. Television watching behavior was measured with two items typical of the literature (e.g., Lee & Taylor, 2014). Participants were asked to report how often they watched fictional TV in an average day during the work week and weekend (0 hours – 6+ hours). Additionally, viewing behavior for each genre was assessed by asking participants to report how often they watched episodes from the provided genres during an average week (J. Cohen & Weimann, 2000). Participants responded on a 7-point scale (1 = never, 2 = rarely, 3 = occasionally, 4 = sometimes, 5 = frequently, 6 = often, 7 = a lot). Lastly, participants indicated which genre they watched the most of. Perceived Credibility. Perceived credibility was measured using an adapted version of Appelman and Sunday's (2016) message credibility scale. Participants rated how (1) believable, 40 (2) accurate and (3) realistic content of TV shows typical of the provided genres were on a 7- point scale (1 = not at all; 7 = very). A credibility score was averaged for each genre. Learning Expectations. Learning expectations of different genres was measured with two items adapted from Moyer-Gusé (2010). Participants were asked to respond to the following questions on a 7-point scale (1 = not at all; 7 = very much): “How much do you expect to learn new information from shows typical of [genre]?” and “How informative do you expect shows typical of [genre] to be?” A learning expectation score was averaged for each genre. Likelihood of an Education Appeal. Perceived likelihood of an educational message appearing in shows of different genres was measured with a single item. Participants responded on a 7-point Likert scale (1 = very unlikely; 7 = very likely) to the following statement: “If a fictional, entertainment TV show were to contain an educational message in an episode, how likely or unlikely would it be for the show to be classified as one of the following genres?” A perceived likelihood score was averaged for each genre. Acceptance of Educational Content. Acceptance of educational content in TV shows of different genres was measured with a single item. Participants responded on a 7-point Likert scale (1 = very unlikely; 7 = very likely) to the following statement: “If a fictional, entertainment TV show were to contain an educational message in an episode, how accepting or unaccepting would you be of it based on the show being in the following genres?” An acceptance score was averaged for each genre. 41 Table 3. Reliability and Descriptive Statistics of Study 2 Measures. Genre & Exemplar Shows Perceived Learning Perceived Acceptance Credibility Expectations Likelihood α M r M α M α M (SD) (SD) (SD) (SD) Animated comedy .86 2.50 .77*** 2.22 . 3.08 . 4.20 BoJack Horseman, South Park, (1.30) (1.33) (1.68) (1.73) Bob’s Burgers Animated drama .87 2.73 .76*** 2.47 . 3.42 . 4.31 Castlevania, Love Death + (1.31) (1.36) (1.62) (1.60) Robots, Justice League Comedy .87 3.38 .76*** 2.49 . 3.39 . 4.54 The Big Bang Theory, Schitt’s (1.38) (1.41) (1.67) (1.56) Creek, Friends Crime comedy .87 3.21 .75*** 2.94 . 3.84 . 4.36 Brooklyn-Nine-Nine, Psych, (1.30) (1.43) (1.53) (1.55) Castle Crime drama .86 4.40 .79*** 4.11 . 5.07 . 5.08 Law & Order, NCIS, Criminal (1.37) (1.56) (1.35) (1.40) Minds General drama .89 4.19 .77*** 3.50 . 4.69 . 4.94 This is Us, Euphoria, The (1.34) (1.53) (1.40) (1.40) Haunting of Hill House Historical fiction .86 4.77 .77*** 4.80 . 5.15 . 5.19 Queen’s Gambit, Peaky Blinders, (1.31) (1.49) (1.45) (1.39) Bridgerton Medical comedy .89 3.21 .76*** 3.04 . 4.03 . 4.47 Scrubs, Royal pains, Nurse (1.29) (1.44) (1.50) (1.55) Jackie Medical drama .90 4.13 .74*** 3.98 . 5.19 . 5.07 Grey’s Anatomy, Chicago Med, (1.43) (1.51) (1.32) (1.42) The Good Doctor Sci-Fi/fantasy .88 2.73 .77*** 2.99 . 3.84 . 4.42 Stranger Things, Wanda Vision, (1.41) (1.53) (1.64) (1.64) The Walking Dead Note: * p < .05; ** p < .01, *** p < .001. 42 Study 2 Results Descriptive Statistics On an average day, participants reported watching TV for two hours during the work week (25.3%) and six or more hours during the weekend (23.8%). Participants reported watching comedies the most (20.7%), followed by sci-fi/fantasies (20.2%), general dramas (12.6%), crime dramas (10.4%), animated comedies (9.3%), animated dramas (4.1%), historical fiction dramas (3.9%), medical dramas (2.2%), crime comedies (1.0%), and medical comedies (0.2%). Table 4 provides descriptive statistics for TV watching by genre. Table 4. Study 2 Descriptive Statistics for Genre Watching. Genre Frequency (%) of Reported Weekly Watching M(SD) Never Rarely Occas- Some- Freq- Often A lot ionally times uently Animated comedy 25.1 21.1 17.4 14.3 10.6 5.7 5.7 3.04 (1.80) Animated drama 44.2 25.6 11.6 8.8 5.4 2.7 1.7 2.20 (1.49) Comedy 7.6 18.0 17.0 17.2 19.2 11.5 9.4 3.95 (1.75) Crime comedy 39.6 20.2 18.9 11.8 5.4 2.0 2.0 2.37 (1.50) Crime drama 23.9 19.9 16.0 16.4 11.3 6.2 6.2 3.15 (1.82) Genera drama 14.0 20.2 16.7 21.9 14.3 7.1 5.7 3.47 (1.70) Historical fiction 24.3 22.1 20.6 17.5 8.4 4.4 2.7 2.88 (1.59) Medical comedy 54.5 21.8 11.8 7.8 2.2 1.7 0.3 1.88 (1.23) Medical drama 44.0 23.4 13.7 8.9 5.2 2.7 2.0 2.24 (1.51) Sci-Fi/fantasy 13.2 15.5 17.4 19.7 18.2 8.9 7.1 3.69 (1.75) Main Analyses To test for differences in how participants perceived the credibility of content (H1), their expectations for learning (H2), and their perceived likelihood of an education appeal (H3) based on genre, three separate within-subjects (repeated measures) MANOVAs (multivariate analysis of variance) were conducted. All pairwise comparisons were assessed for statistical significance using Bonferroni corrective alpha levels. For expectations of content credibility, the Mauchly’s test indicated a violation for the sphericity assumption, χ2(44) = 2033.06, p < .001, so the Greenhouse-Geisser (ε = .55) corrected results are reported: perceived credibility was found to 43 differ significantly based on genre, F(4.98, 2947.57) = 395.76, p < .001, η2 = .40. All Bonferroni- corrected pairwise comparisons were statistically significant (p < .001) with three exceptions (see Table 5): no differences were found between (1) animated dramas and sci-fi/fantasies, (2) crime comedies and medical comedies, and (3) general dramas and medical dramas. H1 was mostly supported. Table 5. Study 2 Pairwise Comparisons for Perceived Credibility by Genre. 1 2 3 4 5 6 7 8 9 1 Animated . comedy 2 Animated drama -0.23* . 3 Comedy -0.88* -0.65* . 4 Crime comedy -0.71* -0.45* 0.17* . 5 Crime drama -1.90* -1.67* -1.02* -1.19* . 6 Drama -1.69* 1.46* -0.81* -0.98* 0.21* . 7 Historical fiction -2.27* -2.04* -1.39* 1.57* -0.37* -0.59* . 8 Medical comedy -0.71* -0.48* 0.17* -0.00 1.19* 0.98* 1.56* . 9 Medical drama -1.63* -1.40* -0.75* -0.92* 0.27* 0.06 0.64* -0.92* . 10 Sci-fi/fantasy -0.23* 0.00 0.65* 0.48* 1.67* 1.46* 2.05* 0.48* 1.40* Note: Mean differences based on column variable as reference. Non-significant differences are bolded. * p < .05 with Bonferroni correction (p < .001). For learning potential expectations, the sphericity assumption was violated, χ2(44) = 1797.14, p < .001, so the Greenhouse-Geisser (ε = .58) corrected results are reported: learning expectations were found to significantly differ based on genre, F(5.18, 2067.36) = 442.01, p < .001, η2 = .43. All Bonferroni-corrected pairwise comparisons were statistically significant (p < .001) with two exceptions (see Table 6): no differences were found between (1) crime comedies and medical comedies, and (2) sci-fi/fantasy and medical comedies. H2 was mostly supported. 44 Table 6. Study 2 Pairwise Comparisons for Perceived Learning Potential by Genre. 1 2 3 4 5 6 7 8 9 1 Animated . comedy 2 Animated drama -0.25* . 3 Comedy -0.27* -0.02* . 4 Crime comedy -0.72* -0.47* -0.45* . 5 Crime drama -1.87* -1.63* -1.61* -1.17* . 6 Drama -1.28* -1.03* -1.00* -0.56* 0.61* . 7 Historical fiction -2.58* -2.34* -2.31* -1.86* -0.69* -1.30* . 8 Medical comedy -0.82* -0.56* -0.54* -0.10 1.07* 0.46* 1.76* . 9 Medical drama -1.76* -1.50* -1.48* -1.04* 0.13* -0.48 0.82* -0.94* . 10 Sci-fi/fantasy -0.78* -0.52* -0.50* -0.06* 1.11* 0.50* 1.80* 0.04 0.98* Note: Mean differences based on column variable as reference. Non-significant differences are bolded. * p < .05 with Bonferroni correction (p <.001). For likelihood expectations, the sphericity assumption was violated, χ2(44) = 1485.18, p < .001, so the Greenhouse-Geisser (ε = .61) corrected results are reported: perceived likelihood of education appeals appearing in a fictional TV program was found to significantly differ based on genre, F(5.53, 3273.88) = 250.33, p < .001, η2 = .30. All Bonferroni-corrected pairwise comparisons were statistically significant (p < .001) with four exceptions (see Table 7): no difference were found between (1) crime comedies and sci-fi/fantasies, (2) crime dramas and historical fiction, (3) historical fiction and medical dramas, and (4) medical comedies and sci- fi/fantasies. H3 was mostly supported. Table 7. Study 2 Pairwise Comparisons for Perceived Appeal Likelihood by Genre. 1 2 3 4 5 6 7 8 9 1 Animated . comedy 2 Animated drama -0.34* . 3 Comedy -0.31* 0.03* . 4 Crime comedy -1.76* -0.42* -0.45* . 5 Crime drama -1.98* -1.64* -1.67* -1.22* . 6 Drama -1.61* -1.27* -1.30* -0.85* 0.37* . 7 Historical fiction -2.07* -1.73* -1.76* -1.31* -0.01 -0.46* . 8 Medical comedy -0.95* -0.60* -0.63* -0.19 1.04* 0.66* 1.13* . 9 Medical drama -2.11* -1.77* -1.80* -1.35* -0.13* -0.50* -0.04 -1.16* . 10 Sci-fi/fantasy -0.76* -0.41* -0.44* -0.01 1.23* 0.86* 1.32* 0.19 1.35* Note: Mean differences based on column variable as reference. Non-significant differences are bolded. * p < .05 with Bonferroni correction (p < .001). 45 RQ1 – RQ3 asked which fiction TV genres would be perceived as highest and lowest in credibility, learning potential and education appeal likelihood. Figure 2 provides a visual representation of the differences between genres across these variables (means and standard deviations can be found in Table 3). Overall, historical fiction was rated the highest for credibility of content and expectations for learning, whereas medial drama was rated highest for the likelihood of an education appeal occurring. Animated comedies were ranked lowest for all variables. Figure 2. Study 2 Means of Persuasion-Relevant Expectations by Genre. 6 5 4 3 Credibility 2 Learning potential 1 Appeal likelihood 0 Note: Items were measured on a 1-7 Likert scale. When observing the means for the expectation variables, there seemed to be patterns or grouping of genres that were consistently ranked highest and lowest in expectations. Thus, a post-hoc exploratory factor analysis (EFA) was conducted for each variable (credibility, learning potential, appeal likelihood) to examine whether there were any underlying patterns or factors among the genres. Following suggested procedure (Costello & Osborne, 2005; Matsunaga, 2010; H. S. Park et al., 2002), the maximum likelihood estimation and promax (oblique) rotation were used in the analysis as the data were mostly normally distributed. As can be observed in 46 Table 8, each analysis yielded a Kaiser-Meyer-Olkin (KMO) measure of sample adequacy greater than .60 and a statistically significant Bartlett’s test of sphericity (p < .001). Two factors were extracted for each variable with Eigenvalues > 1, which were supported in the scree plots (see Figures 3-5). The first factor, labelled low expectation genres, tended to include (across all variables) the genres of animated comedies, animated dramas, comedy, crime comedies, medical comedies, and sci-fi/fantasies. The second factor, labelled high expectation genres, tended to include (across all variables) the genres of crime dramas, medical dramas, historical fiction, and general dramas. Yet, there were observed cross-loadings, particularly regarding crime comedies and medical comedies. Table 8. Study 2 Structure Matrix from Exploratory Factor Analysis (EFA). Credibility Learning potential Appeal likelihood Factors 1 2 1 2 1 2 Low expectation Animated comedy .96 .94 .47 .92 Animated drama .84 .41 .85 .59 .78 Comedy .73 .45 .87 .51 .81 Crime comedy .67 .69 .74 .73 .64 .51 Medical comedy .65 .72 .74 .72 .56 .58 Sci-fi/fantasy .61 .42 .66 .55 .47 High expectations Crime drama .91 .53 .94 .84 Medical drama .41 .89 .53 .87 .83 Historical fiction .74 .43 .76 .50 General drama .45 .64 .62 .74 .49 Eigenvalue 1.68 5.35 6.16 61.58 4.28 1.81 % of variance explained 16.83 53.12 1.35 13.49 42.79 18.05 KMO .79 .86 .77 Bartlett’s Test X2 4502.95 2958.77 2958.77 df 45 45 45 p < .001 < .001 < .001 Note: Extraction method: Maximum likelihood. Rotation method: Promax with Kaiser normalization 47 Figure 3. Study 2 Scree Plot for Perceived Credibility. Figure 4. Study 2 Scree Plot for Learning Potential. Figure 5. Study 2 Scree Plot for Appeal Likelihood. 48 Lastly, H4 predicted that the measured genre expectations would predict hypothetical acceptance of an embedded educational message. To test this hypothesis, items were created for the high and low expectation genres, separately, for perceived credibility (αhigh = 0.88, Mhigh = 4.37, SDhigh = 1.16; αlow = 0.85, Mlow = 2.83, SDlow = 1.12), learning potential (αhigh = 0.90, Mhigh = 4.09, SDhigh = 1.33; αlow = 0.89, Mlow = 2.54, SDlow = 1.22), appeal likelihood (αhigh = 0.75, Mhigh = 5.03, SDhigh = 1.05; αlow = 0.83, Mlow = 3.44, SDlow = 1.34), and hypothetical acceptance (αhigh = 0.87, Mhigh = 5.07, SDhigh = 1.18; αlow = 0.88, Mlow = 4.36, SDlow = 1.40). Because of the observed cross loadings, medical comedies and crime comedies were not included in the groupings. Therefore, the two groups of genres contained four genres each (high expectations = general drama, crime dramas, medical dramas and historical fiction; low expectations = animated comedies, animated dramas, sci-fi/fantasy, and comedies). Two linear regression models were calculated to predict hypothetical acceptance of an embedded educational message based on genre expectations. Covariate of age, sex, race/ethnicity, education, and TV watching behavior were added to the models in consideration of these variables being identified as relevant to genre study in past literature (Hawkins et al., 2001; Rentfrow et al., 2011). A significant model was found for the high expectation genres (F(8, 592) = 36.71, p < .001, r2 = .33) and for the low expectation genres (F(8, 592) = 35.27, p < .001, r2 = .32). As can be seen in Table 9, perceived credibility and likelihood of a genre having an educational message positively predicted hypothetical acceptance in high expectations genres. Expected learning potential was not found to statistically predict hypothetical acceptance for either genre category. H4 was mostly supported. 49 Table 9. Study 2 Regression Results for Hypothetical Acceptance (N = 593). High Expectation Genres Low Expectation Genres b(SE) b(SE) Predictorsa Constant 1.82 (0.23)*** 2.49 (0.22)*** Perceived credibility 0.18 (0.05)*** 0.11 (0.06)t Learning potential 0.01 (0.05) 0.01 (0.06) Appeal likelihood 0.51 (0.05)*** 0.52 (0.04)*** Covariates Age -0.01 (0.00)t -0.01 (0.00) Female 0.24 (0.08)** 0.09 (0.10) White/Caucasian -0.13 (0.09) -0.21 (0.11)t 4-year degree+ 0.06 (0.08) 0.04 (0.10) Heavy TV watchers (12+ hours 0.13 (0.11) 0.24 (0.13)t weekly) Note: a All items are on a 1-7 Likert-scale. t p < .10, *p < 0.05, **p < 0.01, ***p < .001. Study 2 Discussion The current study surveyed a national, non-representative sample of U.S. adults to test whether the content of TV genres varied in terms of three expectations: perceived credibility, learning potential and likelihood of an education appeal. Additionally, the ability for genre expectations to predict acceptance of a persuasive message in fictional TV programs was tested. The results substantially support participants to view the content of TV genres differently. Of the 435 tested comparisons, 426 or 97.9% were statistically significant at a p < .05 level with Bonferroni correction (i.e., p < .001). When looking at the mean scores, there appeared to be a consistent pattern for which genres were ranked highest and lowest in credibility, potential learning, and appeal likelihood expectations. For example, historical fiction, crime dramas, general dramas, and medical dramas had the highest means for each variable category. Animated comedies and animated dramas, on the other hand, were consistently rated the lowest in persuasion-relevant expectations. Guided by this observation, I attempted to determine whether there were actual patterns among the variables that distinguished the genres regarding audience expectations. The post-hoc EFA revealed a few notable findings. 50 Overall, there appeared to be distinct groupings of genres that have high expectations and low expectations regarding its content. For example, drama programs (excluding animated dramas) tended to encompass one factor whereas animated, comedy, and sci-fi/fantasy grouped into another. Although beyond the bounds of this dissertation’s aim, there is preliminary support that the presence of humor may offset or alter audiences’ expectations of learning in TV shows. There were observed cross-loadings regarding crime comedies and medical comedies in the EFA across all three expectation variables. As these two genres often include procedural programs, it is possible that audiences had difficultly determining whether the content would be accurate and likely for persuasive communication. Although procedural dramas were noted as being most likely to contain accurate and persuasive messages in Study 1, the comedic nature may have offset those perceptions, causing participants to be less clear in their expectations. Thus, while humor’s role in discounting a persuasive appeal has been investigated in fictional TV (Futerfas & Nan, 2017; Moyer-Gusé et al., 2011, 2018), further research may benefit from considering its influence on viewers’ expectations as well. Additionally, animated programs produced low expectations for content credibility, learning potential and likelihood of an education appeal, regardless of whether it was comedy or drama oriented. The persuasive power of animated programs and cartoons for targeting children has been widely documented (Jenkin et al., 2014; Kraak & Story, 2015; Parvin & Islam, 2020), in addition to influencing adult perceptions and behaviors, such as for war-time propaganda (e.g., P. Ward, 2005). However, in this study, participants consistently had low persuasion-relevant expectations regarding adult-focused animation programs. It may be of merit for future studies to investigate how animation influences audiences’ perceptions of persuasive messages. For example, LaMarre et al. (2014) found different types of satire (Horatian vs. Juvenalian) to influence processing of persuasive messages in animated and live- action TV programs. Rather than observing the difference in processing within these two genres, separately, it would be of interest to see if there are any differences in processing 51 between animated and live-action programs, and to determine the explanatory mechanism behind any observed differences. Of most importance is the finding that genre expectations predict hypothetical acceptance of an embedded persuasive message. For both genre categories, perceived credibility and likelihood of an education appeal positively predicted anticipated message acceptance. Perceived likelihood of an education appeal particularly emerged as the strongest predictor for whether an embedded message would be accepted in a fictional TV program. In result, if a practitioner plans to integrate a message into an animated or comedy program, it may be beneficial, and potentially necessary, to increase viewers’ expectations of the likelihood of an education appeal appearing. Tactics to build viewers’ likelihood expectations may be to (a) forewarn the educational content, and (b) employ repeated and consistent messaging in the target genre. However, neither of these suggestions have been formally tested for increasing likelihood expectations and should therefore be tested before message implementation. Expectations of learning potential, on the other hand, were not found to predict message acceptance for either genre category. In general, learning expectations had the lowest mean scores compared to the other two expectations, indicating that while participants believed fictional TV to contain educational and credible content, they did not expect to learn from it themselves. A possible explanation is that a third-person effect occurred (Davison, 1983; Klein, 2013). Participants may have under-estimated their learning potential from fictional TV compared to others, which in turn, may have lessened its effect on reported acceptance of the message. This assertion is purely speculative, so future research should consider how third- person effects influence expectations of persuasion regarding fictional TV programming. There are a few limitations to Study 2 that should be noted. First, although this study surveys a national U.S. sample, it is not representative of the U.S. population. Second, a large portion of the sample reported “never” watching medical comedies (54.5%), medical dramas (44.0%), and animated dramas (44.3%). It is then possible that participants were reflecting on 52 these genres with little to no experience with that genre’s content. However, because this study was concerned with the expectations audiences have about these genres, rather than what they actually contain, this limitation is not expected to alter the main findings of this study. Additionally, the list of genres studied was meant to be extensive by using categories derived from past research and literature (Hawkins et al., 2001; TiVo, 2019), but it cannot be considered exhaustive. Genre study is notoriously complex and there are bound to be numerous sub- genres and categories that were not explored here. Lastly, this study uses cross-sectional survey data. Any interpretations of a causal relationship should be made with caution. Before testing how violations of genre expectations may influence the persuasion process, it was first imperative to support that viewers have expectations about TV genres in the first place. In conjunction with Study 1, the present study further demonstrates through survey data that people hold distinct expectations for fiction TV genres regarding persuasion-relevant factors and that these expectations predict hypothetical acceptance of an embedded persuasive message. This study thus sets the foundation to experimentally test the role that genre expectancy violations have on the success of entertainment TV persuasion appeals. 53 CHAPTER FIVE: STUDY THREE The present study had three aims. First, recent calls have been in made in the EE and greater narrative persuasion literature to better understand the influence of genre in the persuasion process (Frazer et al., 2021; Painter et al., 2020; Record, 2018). As evidenced by the results of Study 1 and Study 2, genre appears to play a significant role in how viewers think and feel about fictional TV communicating persuasive messages. The primary aim of this study, therefore, was to test the impact of genre on common persuasion variables. It was specifically tested whether attitudes, social norms, perceived behavioral control, and behavioral intention varied when a persuasive message was communicated through a sci-fi/fantasy or historical fiction drama and to determine the explanatory mechanisms operating. The genres of sci-fi/fantasy and historical fiction were chosen for two reasons. First, both genres are highly popular with the success of TV shows such as The Mandalorian (Disney+), Ghosts (CBS) and Yellowstone (Paramount Network) (Schneider, 2022). Indeed, at the time of this writing, seven of the top 10 watched (English-language) Netflix TV seasons of all time are sci-fi/fantasy (e.g., Stranger Things) and historical fiction (e.g., Bridgeton) series (Stroll, 2022). Second, to observe differences in genre expectations, it was necessary to choose two genres that distinctly vary in the expectations regarding them. As indicated in Study 2, sci-fi/fantasy and historical fiction were shown to significantly differ in expectations with historical fiction ranking higher in perceived content credibility, learning potential, and likelihood of containing an educational message than sci-fi/fantasy. Although animated programs and comedies were the lowest ranked genres in terms of persuasion-relevant expectations, the potential and unknown influence of animation and humor made sci-fi/fantasy a better alternative to reduce extraneous factors. Thus, to further support the results from Study 1 and Study 2, the following hypothesis was tested: 54 H1: Participants exposed to a sci-fi/fantasy episode with an educational message will report greater violations of their genre expectations than those in the historical fiction condition. Regarding persuasive outcomes, the variables of attitudes, social norms, perceived behavioral control and behavioral intention have long been shown as predictors of health behavior, a common area investigated in the EE and narrative persuasion literature (Ajzen, 1991; Ajzen & Albarracin, 2008; Armitage & Conner, 2001; Catalano et al., 2017; Fishbein, 2008; Fishbein & Ajzen, 2011; McEachan et al., 2016; Tonglet et al., 2004). In particular, the reasoned action approach (RAA) delineates attitudes, social norms, and perceived behavioral control to predict behavioral intention which ultimately leads to behavior performance (Fishbein & Ajzen, 2011). Support for the RAA and its propositions has mostly been observed for health issues (Hagger et al., 2018) but has also been applied to environmental (Y. Wang et al., 2019) and economic (Doanh & Bernat, 2019) behaviors. Attitudes refer to a person’s valanced evaluation of a behavior, such as whether engaging in daily stretching would be positive or negative (for historical overview of attitudes, see Brińol & Petty, 2012). Social norms are broadly understood as the unwritten rules of society (Turner, 1991) and are often distinguished as being either descriptive or injunctive (Cialdini et al., 1990, 1991; Rimal & Real, 2003, 2005). Descriptive norms refer to what others are doing and relate to the concept of social proof (i.e., if others are doing it, it must be right; Cialdini, 2001). Injunctive norms, on the other hand, refer to what is (dis)approved of by others and stem from the anticipated social rewards or punishments that would be received (Bendor & Swistak, 2001; Shaffer, 1983). Social norms of daily stretching, for example, may be that most others stretch daily (descriptive norm) and that certain referent groups, such as medical professionals, would approve of one performing it (injunctive norms). Perceived behavioral control (PBC) is defined as the level of control one believes they have in executing a behavior (Ajzen, 2002; 55 Fishbein & Ajzen, 2011). Lastly, behavioral intention refers to one’s motivation to perform the behavior in the near future (Fishbein & Ajzen, 2011). At this point, because of the lack of EVT research in an entertainment persuasion context, it is unclear which direction a violation of genre expectations should have on persuasive outcomes. It is possible that a violation could be seen positively, such as participants being surprised and grateful for the episode taking on an education goal, or it could be perceived as a negative violation, in which the genre is thought to not be suitable for such messaging. To determine the valence of a violation in which an educational message appears in a genre that generally has low expectations for educational content, the following two competing hypotheses are posed: H2a: Participants in the sci-fi/fantasy condition will report more story consistent attitudes, descriptive norms, injunctive norms, and PBC compared to those in the historical fiction condition. H2b: Participants in the sci-fi/fantasy condition will report less story consistent attitudes, descriptive norms, injunctive norms, and PBC compared to those in the historical fiction condition. In addition to demonstrating a persuasive effect, the current study aims to further test the psychological mechanisms responsible for entertainment TV persuasion in pro-attitudinal contexts. In line with the current dominant theoretical models, it is expected that a reduction in message resistance should lead to higher persuasion (Moyer-Gusé & Nabi, 2011; Slater & Rouner, 2002). The current study additionally tests whether genre expectancy violations may explain the persuasive success of an entertainment narrative. H3: Message resistance will mediate the effect of genre on story consistent attitudes, descriptive norms, injunctive norms, and PBC. H4: Genre expectancy violations will mediate the effect of genre on story consistent attitudes, descriptive norms, injunctive norms, and PBC. 56 Lastly, a parallel mediation model is posed to test the relationship between genre, processing mechanisms (message resistance and genre expectancy violations), RAA predictor variables (attitudes, social norms, and PBC), and behavioral intention. H5: Message resistance and genre expectancy violations will mediate the relationship between genre and RAA predictor variables (attitudes, social norms, and PBC) which will, in turn, predict behavioral intentions. Figure 6. Proposed Hypothesis Model for Study 3. Processing variables RAA predictors Message resistance Attitudes Genre Behavioral Social norms intention Genre expectancy violations Perceived behavioral control Study 3 Method Participants Participants (N = 188) were recruited through Prolific during June 2022. A G*Power analysis indicated a sample size of at least 62 participants was needed to detect an effect size of Cohen’s d = 0.124 with 80% power (α = 0.05) for a multivariate analysis of variance (MANOVA) with two groups, 12 predictors, and five response variables. Initially, 200 participants completed the study, however 12 were removed due to failing both attention checks (e.g., “please select ‘disagree’). Participants ranged in age between 18 – 82 years (M = 34.99, SD = 4 The effect size of interest was based on Shen and Han’s (2014) systematic analysis of TV entertainment for health communication. 57 12.57) and were mostly white (69.70%) and female (59.0%). The most frequently reported household income and state of residence was $20,000 - $29,999 (14.40%) and California (17.40%), respectively. Table 10 provides a complete overview of the sample’s demographics. Table 10. Study 3 (N = 188) Sample Characteristics. Variable Min – Max M (SD) % Age 18 – 82 34.99 (12.57) Gender - Male 41.00 Female 59.00 Race/Ethnicity White or Caucasian 69.70 Black or African American 9.20 Hispanic or Latino 14.40 Asian 13.80 Native American or Alaska Native 2.10 Native Hawaiian or Pacific Islander 0.00 Two or more races 2.10 Income Less than $10,000 4.10 $10,000-$19,999 10.80 $20,000-$29,999 14.40 $30,000-$39,999 9.20 $40,000-$49,999 7.70 $50,000-$59,999 11.30 $60,000-$69,999 6.70 $70,000-$79,999 8.70 $80,000-$89,999 6.70 $90,000-$99,999 2.10 $100,000-$149,999 9.20 $150,000 or more 9.20 State of residence Alabama 1.00 Alaska 0.50 Arizona 3.10 Arkansas 1.00 California 17.40 Colorado 2.60 Connecticut 0.00 Delaware 0.50 District of Columbia 0.00 Florida 3.60 Georgia 5.10 Hawaii 1.00 Idaho 0.00 Illinois 6.20 58 Table 10 (cont’d) State of residence Min – Max M (SD) % Indiana 0.00 Iowa 0.50 Kansas 0.00 Kentucky 0.50 Louisiana 1.50 Maine 0.00 Maryland 1.50 Massachusetts 1.50 Michigan 1.50 Minnesota 1.50 Mississippi 0.50 Missouri 2.10 Montana 0.50 Nebraska 1.00 Nevada 2.60 New Hampshire 0.50 New Jersey 3.10 New Mexico 0.00 New York 4.60 North Carolina 2.60 North Dakota 0.00 Ohio 1.00 Oklahoma 1.00 Oregon 2.10 Pennsylvania 3.10 Rhode Island 1.50 South Carolina 1.50 South Dakota 0.50 Tennessee 3.60 Texas 6.20 Utah 2.10 Vermont 0.00 Virginia 2.10 Washington 5.10 West Virginia 1.0 Wisconsin 1.50 Wyoming 0.00 Procedure A single factor (genre: historical fiction vs. sci-fi/fantasy), between-subjects, online experiment was conducted. To be eligible for participation, participants had to be fluent in English, reside in the U.S. and watch fictional TV on at least a weekly basis. Participants were 59 recruited under the assumption that they were pilot testing a potential episode for a new TV show. After providing informed consent, participants reported their attitudes, social norms, perceived behavioral control and prior behavior for two behaviors (stretching and eating meat), in addition to their entertainment watching habits and preferences. These questions were introduced as a way for the researchers to get to know the participants as an audience group. Participants were then randomly assigned to an episode described as either historical fiction (N =93) or science-fiction/fantasy (N = 95). Immediately after viewing the video, participants’ expectancy violations and motivated resistance to persuasion were measured, followed by transportation and character identification, and then, the outcome variables of interest (attitudes, social norms, PBC and behavioral intentions for stretching). Participants lastly answered items regarding manipulation checks, prior exposure to stimuli, metacognition toward the stimuli, and demographics, before being debriefed and compensated. Most participants completed the study using a laptop or computer (88.7%), followed by a tablet (7.7%) and cellphone (3.6%). The study took an average of 15.53 minutes (SD = 7.56) to complete. Stimuli Two videos were created adapting the episode, Jameston (season 1, episode 7), from the cancelled TV show, Firefly (2002). As a space western TV drama, Firefly incorporated both sci-fi/fantasy and historical fiction elements into its programming, providing a unique opportunity for the current study: images could be taken from the show to reflect both a historical and sci- fi/fantasy setting using the same narrative and characters. To mimic a typical TV drama, each video included an introduction to the TV series and a recap of the previous episode. The storyboard format consisted of a series of images with narrated dialogue between the characters and descriptive text of the actions. Captions and background music were additionally present in the video (stimuli can be found at https://osf.io/t6r97/). The narrative followed Captain Roy and his crew as they arrived in an unfamiliar town to trade cattle. Rather than meet with the prospective traders, Captain Roy sends Doc John, the 60 crew’s resident physician, into town to gather supplies. It is during this interaction that the persuasive message of stretching for at least 5 daily minutes is given. Doc John urges Captain Roy to not forget to stretch that day, especially as they could encounter trouble with the traders. Doc John specifically tells Captain Roy that stretching for even five minutes a day will help his daily movement, alleviate stress, and increase his blood flow. The conflict occurs when both Doc John and Captain Roy are attacked. Doc John is kidnapped by local townspeople to perform medical services for the community while Captain Roy encounters bandits attempting to steal their cattle. After successfully thwarting the bandits, Captain Roy saves Doc John from the townspeople, concluding the episode. The genre of the episode was manipulated in two ways. First, participants were explicitly told the episode’s TV genre in the instructions before watching. Second, changes were made in the text and images to support the respective genre. For example, in the historical fiction episode, the year is said to be 1870, the crew are shown riding horses, and the location occurs in a distant town. In the sci-fi/fantasy episode, the year is 2870, the crew uses a spaceship, and the location occurs on a distant planet. In general, though, the episodes were created to be as similar as possible. In total, only 8 of the 36 images differed across the videos. The historical fiction stimuli lasted 4 minutes and 12 seconds and the sci-fi/fantasy episode lasted 4 minutes and 14 seconds. The Behavior of Daily Stretching. As argued previously, there is a need in the literature for more testing of the E-ELM and EORM’s propositions of entertainment as a resistance-reduction strategy for pro-attitudinal and prosocial behaviors (Frazer et al., 2021; Moyer-Gusé, 2010; Tchernev et al., 2021). Although neither model is specific to attitude change, their proposed mechanisms appear most suited for counter-attitudinal messages. It is assumed that participants will be inclined to argue against a persuasive message in entertainment media regardless of if it is pro- or counter-attitudinal, yet further research is warranted (Frazer et al., 2021; Moyer-Gusé, 2010). The present study therefore uses the innocuous behavior of daily 61 stretching to further test the E-ELM and EORM in a pro-attitudinal context. It is not expected for a message promoting daily stretching to be considered controversial but rather as an educational or attitude reinforcement appeal. Daily stretching is often promoted in regard to exercise (e.g., Shrier, 2005) but is beneficial in reducing risk of bodily injuries outside of exercise (Stone et al., 2006), increasing muscle blood flow (Bisconti et al., 2020), and reducing anxiety (Montero-Marín et al., 2013). Stimuli Pilot Test. A pilot study of the stimuli was conducted with an undergraduate student sample (N = 58) recruited from the CAS SONA student research pool at MSU. The intent was for the stimuli to differ in perceived genre but to not differ in other relevant variables, such as perceived persuasive intent and transportation. Participants were randomly assigned to either watch the historical fiction (N = 28) or sci-fi/fantasy (N = 30) episode before answering items measuring clarity, entertainment value, perceived persuasive intent, transportation (adapted from Green & Brock, 2000) and character identification with Captain Mal (adapted from J. Cohen, 2001). Participants additionally answered a manipulation check regarding the episode’s depicted genre. All measures, reliability statistics, and descriptive statistics can be found in Table 11. As expected, independent samples t-tests showed the videos were equivalent in perceived clarity (t(56) = -1.26, p = .08), transportation (t(56) = -0.25, p = .38), identification (t(56) = -0.15, p = .39), entertainment value (t(56) = -1.81, p = .21), and persuasive intent (t(56) = 0.35, p = .94). On the other hand, chi-square analysis showed a significant association between condition and perceived genre, X2(2, 58) = 46.29, p < .001. Those in the historical fiction condition were more likely to consider their watched episode as historical fiction whereas those in the sci-fi/fantasy condition considered their watched episode as sci-fi/fantasy. 62 Table 11. Study 3 Pilot Test Measures and Descriptive Statistics. Reliability Descriptive Variables and Items1 statistics statistics α r M (SD) % Clarity .76 4.53 (1.43) 1. The episode I watched was confusing - clear 2. The episode I watched was hard to understand – easy to understand 3. The episode I watched was hard to watch – easy to watch 4. The episode I watched was unrealistic – realistic Entertainment value .91*** 3.98 (1.63) 1. The episode I watched was not entertaining - entertaining 2. The episode I watched was not engaging - engaging Persuasive intent .41*** 3.41 (1.24) 1. The episode I watched was not educational – educational 2. The episode I watched was not persuasive – persuasive Transportation .73 4.08 (1.11) 1. I was mentally involved in the episode while watching it 2. While watching the episode I could easily picture the events taking place 3. I could easily picture myself in the scenes of the episode described 4. I found my mind wandering while watching the episode (reverse-coded) Character identification .75 4.41 (0.84) 1. I tend to understand the reasons why the Captain did what he did 2. I am similar to what I think the Captain represents 3. I think I have a good understanding of the Captain 4. The image I have of the Captain overlaps with my self image Genre Manipulation Check 1. What genre of television was the episode you watched? Science fiction/fantasy 48. 3 Historical fiction 43. 1 Crime drama 6.9 Medical drama 1.7 Comedy Note: 1 All items were measured on a 7-point scale. * p < .05, ** p < .01, *** p < .001. 63 Measures Intervening Variables. Message resistance and genre expectancy violations were measured as the intervening variables. Message Resistance. Message resistance was operationalized as Nisbet et al.'s (2013) 11-item measure of motivated resistance to persuasion. The motivated resistance to persuasion scale covers various dimensions, including cognitive counterarguing, reactance, and general message resistance, and thus seemed a suitable measure to capture multiple forms of resistance without overly taxing participants. Participants indicated their level of (dis)agreement (1 = strongly disagree; 7 = strongly agree) to statements such as “The episode tried to force its opinions on me” and “I found myself thinking of ways I disagreed with the information in the episode.” An added affective component (“I felt angry while watching the episode”) was added to the scale, resulting in a total of 12-items that were condensed into a single measure (α = 0.87, M = 3.37, SD = 0.97). Genre expectancy violation. Genre expectancy violations were measured using an adapted 3-item scale from Walther-Martin (2015), asked participants to indicate their level of (dis)agreement (1 = strongly disagree; 7 = strongly agree) to statements such as, “The content of the episode felt appropriate for the genre” and “The content was what I expected from the genre.” The items were averaged into a single item (α = 0.77, M = 4.37, SD = 1.31). Dependent Variables. Attitudes, descriptive norms, injunctive norms, perceived behavioral control, and behavior were measured as the dependent variables on interest. Attitudes. Attitudes toward the target behavior were measured with six items (Petty & Wegener, 1998), asking participants to rate how not important-important, bad-good, harmful- beneficial, foolish-wise, not fun-fun, and boring-exciting stretching for 5 minutes daily is on a 7- point scale. Attitudes for the pre-test (α = 0.71, M = 5.55, SD = 0.74) and post-test were averaged (α = 0.77, M = 5.53, SD = 0.81). 64 Descriptive Norms. Descriptive norms were measured with a single item in the pre-test (M = 3.85, SD = 1.61) and post-test (M = 3.79, SD = 1.58). Participants indicated on a 7-point Likert scale (1 = strongly disagree; 7 = strongly agree) their response to the follow statement: “Most other people like me stretch at least 5 minutes daily.” Injunctive Norms. Injunctive norms were measured with 4-items in the pre-test (α = 0.83, M = 3.64, SD = 1.40) and post-test (α = 0.84, M = 3.78, SD = 1.45), asking participants to indicate their level of agreement (1 = strongly disagree; 7 = strongly agree) that their (1) friends, (2) family, (3) doctor, and (4) significant other approved of them stretching 5 minutes daily. Perceived Behavioral Control. Perceived behavioral control was measured with a single item in the pre-test (M = 6.59, SD = 0.75) and post-test (M = 6.60, SD = 0.76). Participants indicated on a 7-point bipolar scale how possible or impossible it would be for them to stretch for 5 minutes a day. Behavior. Past behavior and behavioral intention for the target behavior were measured in the pre-test and post-test, respectively, each with a single item. In the pre-test, participants indicated how many days (0 – 7) in the past week they had stretched for at least 5 minutes (M = 2.70, SD = 3.64). In the post-test, participants indicated how many days (0 – 7) they planned to stretch for at least 5 minutes (M = 3.64, SD = 2.39). Covariates. Narrative involvement, including transportation and character identification, in addition processing fluency, prior exposure to the stimuli, and TV watching behavior were measured as covariates. Transportation. To account for how absorbed or transported participants were into the narrative, transportation was measured using an adapted 4-item scale from Green and Brock (2000). Participants indicated their level of (dis)agreement (1 = strongly disagree; 7 = strongly agree) to statements such as, “I was mentally involved in the episode while watching it” and “I found my mind wandering while watching the episode” (reverse-coded). The items were averaged into a single item (α = 0.80, M = 4.50, SD = 1.30). 65 Character identification. Identification with the two main characters of the narrative, Captain Mal and Doc John, were measured using an adapted 4-item version of J. Cohen’s (2001) scale. Character identification was chosen over other character-related variables (e.g., perceived homophily) due to its common use in the E-ELM (Slater & Rouner, 2002) and EORM (Moyer-Gusé & Nabi, 2010). For each character, participants indicated their level of (dis)agreement (1 = strongly disagree; 7 = strongly agree) to statements such as, “I tend to understand the reasons why Captain Mal/Doc John did what he did” and “I think I have a good understanding of Captain Mal/Doc John.” The items were averaged into a single item for Captain Mal (α = 0.79, M = 4.05, SD = 1.09) and Doc John (α = 0.79, M = 4.06, SD = 1.05). Processing fluency. A concern when studying the effects of different narratives is that the complexity of the story and/or characters may have been altered in the process (Li, 2021; Vaughn et al., 2010). In consequence, scholars have suggested measuring processing fluency (i.e., the reported ease of processing information; Schwarz, 2010) when using narrative stimuli (Bullock et al., 2021; Vaughn et al., 2010). A 3-item scale was adapted from Shulman and Sweitzer (2018) asking participants to indicate their level of (dis)agreement (1 = strongly disagree; 7 = strongly agree) to statements such as, “Overall, I found the language in the episode to be difficult to understand” (reverse-coded) and “It was easy for me to provide my opinions when thinking about the episode.” However, the items were not found to be reliable (α = 0.33) nor were any of the correlations between the items strong enough to combine (r < .32 for all combinations). Thus, processing fluency was dropped as a covariate in this study. Prior exposure to stimuli. Although participants were told that the images used in the videos were meant to assist in visualizing the events of the narrative, prior exposure to Firefly was still measured to account for any variations due to stimuli familiarity. Participants reported on a 7-point bipolar scale how (un)familiar they were with the show Firefly (M = 2.90, SD = 2.29). 66 TV watching behavior. The same items for measuring general fictional TV watching (r = .75, p < .001, M = 2.90, SD = 1.44) and genre TV watching from Study 2 were used. Study 3 Results Correlations were used to observe any relationships between the covariates, explanatory, and outcome variables (see Table 12). None of the anticipated covariates were found to have a significant relationship with the outcome variables, thus, they were excluded from the analyses. A manipulation check item asked participants to identify which genre of episode they watched (historical fiction, sci-fi/fantasy, medical comedy, and medical drama). A chi-square test of independence was performed to support successful manipulation of genre. The relationship between genre condition and perceived genre of the program was statistically significant, X2(3, 195) = 156.64, p < .001. Those in the historical fiction condition were more likely to consider the episode watched historical fiction (96.7%), and likewise for the sci-fi/fantasy condition (94.7%) for the genre of sci-fi/fantasy. Additionally, before getting into the main analysis, it was of interest to support whether daily stretching was considered a pro-attitudinal behavior. Indeed, a one-sample t-test found pre-test attitudes toward stretching to be significantly higher than the mid-point of the scale (3.5), t(194) = 45.70, p < .001. Therefore, it was safely assumed that any positive changes in attitudes from the stimuli would be reflective of attitude reinforcement (vs. attitude change). 67 Table 12. Correlation Matrix for Study 3 Variables. Variables 1 2 3 4 5 6 7 8 9 10 11 12 13 14 1 Tv watching - 2 Historical TV watching .09 - 3 Sci-fi/fantasy TV watching .25** .30** - 4 Transportation -.08 .16* .22** - a 5 CI: Captain Mal .14* .19* .19** .43** - a 6 CI: Doc John .04 .15* .10 .36** .61** - 7 Persuasive intent -.04 -.01 -.07 -.11 .07 -.00 - 8 Genre expectancy violations .03 -.05 .18* .25** .34** .28** -.09 - 9 Message resistance -.02 -.08 -.13 -.47** -.22** -.24** .43** -.33** - 10 Attitudes .08 .12 .07 .14 .15* .13 .00 -.05 -.12 - 11 Descriptive norms -.03 .14 .07 -.00 .10 .19** .06 .04 -.09 .41** - 12 Injunctive norms .10 .19* .07 .15* .32** .29** -.02 .11 -.09 .41** .42** - 13 Perceived behavioral control -.02 .09 .06 .09 .03 .00 -.05 -.08 -.08 .30** .02 .04 - 14 Behavior -.04 .17* .09 .10 .12 .18* -.06 .07 -.14 .54** .62** .48** 0.11 - Note: a CI = character identification. * p < .05, ** p < .01. 68 Main Analyses H1 proposed that those who watched a sci-fi/fantasy episode with an educational message would report greater genre expectancy violations than those who watched a historical fiction episode with the same message. An independent samples t-tests did not find a statistically significant difference between condition on genre expectancy violations, t(186) = 3.47, p = .13. H1 was not supported. However, a follow-up analysis revealed a significant difference between conditions regarding perceived persuasive intent, t(186) = 2.27, p = 0.02. It was assumed that perceived persuasive intent5 of the videos would not significantly differ between conditions as the educational messages were identical in both videos. In other words, although participants may have had different expectations of the genres, after watching the episodes with an educational message, both conditions should have reported perceived persuasive intent that would not vary across videos. Yet, unlike the stimuli pilot test which found no difference between the two conditions, the present study did. Specifically, those in the historical fiction condition thought the video was intended to persuade more (M = 4.24, SD = 1.48) than those in the sci-fi/fantasy condition (M = 3.71, SD = 1.70). Thus, it appears that while participants’ expectations of the genres were not violated, genre affected how persuasive participants thought the video was intended to be. Five analyses of covariance (ANCOVA) were performed to test for differences in condition on attitudes, descriptive norms, injunctive norms, PBC and behavioral intentions for stretching daily (H2). Pretest measures of attitudes, social norms, PBC and past behavior were controlled for in each respective analysis so that results could be viewed as whether genre produced any changes in RAA variables. As can be seen in Table 13, no observed differences 5 Perceived persuasive intent was measured using two items adapted from Moyer-Gusé and Nabi (2010) asking participants on a 7-point bipolar scale whether the episode they watched was intended not to persuade- persuade and not to educate- educate (r = .68, p < .001; M = 3.97, SD = 1.67). The items were measured in the same block as genre violation expectations. 69 were found between conditions for any of the outcome variables. Although post-test scores increased between pre-test and post-test assessments for descriptive norms, injunctive norms, PBC, and behavioral intention, the differences were not a result of genre condition. Neither H2a nor H2b were supported. Table 13. Study 3 Descriptive Statistics and ANCOVA Results by Condition. Attitudes Descriptive Injunctive PBC Behavior M (SD) M (SD) M (SD) M (SD) M (SD) Genre Pre Post Pre Post Pre Post Pre Post Pre Post Historical 5.59 5.60 4.02 4.04 3.69 3.85 6.49 6.49 2.82 3.87 (0.76) (0.74) (1.59) (1.53) (1.27) (1.35) (0.86) (0.86) (2.36) (2.39) Sci-fi 6.67 5.45 3.49 3.59 3.59 3.72 6.67 6.69 2.58 3.45 /Fantasy (0.63) (0.88) (1.56) (1.66) (1.47) (1.50) (0.63) (0.65) (2.43) (2.39) Total 5.55 5.23 3.76 3.81 3.64 3.78 6.59 6.60 2.70 3.66 (0.74) (0.81) (1.59) (1.61) (1.37) (1.43) (0.75) (0.76) (2.39) (2.40) Fcondition 1.23 0.20 0.17 0.80 1.22 η2condition 0.19 0.07 0.07 0.14 0.20 Note: *p < .05 Mediation Analyses H3 – H5 were tested with structural equation modeling in R using the Lavaan package (Version 06-3; Rosseel, 2012). Saturated models were estimated, and thus, no fit indices are reported. Simple mediation models were estimated to test H3 – H4 and a serial-parallel mediation model was estimated for H5. Pre-test measures of attitudes, social norms, PBC, and behavioral intention were included as covariates in the analyses. Table 14 provides the path results. Unstandardized regression coefficients are reported with 95% confidence intervals with 5,000 bootstrap samples. None of the hypotheses were supported. That is, neither message resistance (H3) nor genre expectancy violations (H4) mediated the relationship between condition exposure and the RAA predictors. Additionally, message resistance and genre expectancy violations were not found to mediate the relationship between condition and RAA predictors to behavioral intention (H5). 70 Table 14. Results of Study 3 Hypothesized Structural Equation Model (N = 188). Estimated paths b 95% CI Simple Mediation Message resistance Sci-fi/fantasy -> message resistance -> attitudes .01 [-.00, .05] Sci-fi/fantasy -> message resistance -> injunctive .01 [-.01,.06] norms Sci-fi/fantasy -> message resistance -> descriptive .03 [-.01, .13] norms Sci-fi/fantasy -> message resistance -> PBC .03 [-.01, .04] Genre expectancy Sci-fi/fantasy -> genre expectancy violations -> .01 [-.00, .06] violations attitudes Sci-fi/fantasy -> genre expectancy violations -> .00 [-.03, .02] injunctive norms Sci-fi/fantasy -> genre expectancy violations -> .03 [-.01, .13] descriptive norms Sci-fi/fantasy -> genre expectancy violations -> PBC .01 [-.00, .05] Serial Mediation Message resistance Sci-fi/fantasy -> message resistance -> attitudes -> .00 [-.00, .02] behavioral intentions Sci-fi/fantasy -> message resistance -> injunctive .00 [-.00,.02] norms-> behavioral intentions Sci-fi/fantasy -> message resistance -> descriptive .01 [-.00, .04] norms-> behavioral intentions Sci-fi/fantasy -> message resistance -> PBC .00 [-.02, .00] Genre expectancy Sci-fi/fantasy -> genre expectancy violations -> .00 [-.00, .02] violations attitudes-> behavioral intentions Sci-fi/fantasy -> genre expectancy violations -> .00 [-.01, .00] injunctive norms-> behavioral intentions Sci-fi/fantasy -> genre expectancy violations -> .01 [-.00, .04] descriptive norms-> behavioral intentions-> behavioral intentions Sci-fi/fantasy -> genre expectancy violations -> PBC- .00 [-.02, .00] > behavioral intentions Note: Unstandardized regression coefficients reported with 95% confidence intervals (5,000 bootstrap samples). Coefficients outside of the sampling error of zero are bolded. Pre-test attitudes, injunctive norms, descriptive norms, and past behavior were controlled for. In consideration that perceived persuasive intent varied between the two conditions, a post-hoc model was tested with persuasive intent as an antecedent to the processing mechanisms (see Figure 7). As can be seen in Table 15, three significant indirect paths were found. First, those who watched a sci-fi/fantasy episode reported less perceived persuasive intent (b = -0.53(0.23), p = .02), less message resistance (b = 0.25(0.04), p < .001), and greater 71 story-consistent attitudes (b = -0.07(0.04), p = .05). Second, those who watched a sci-fi/fantasy episode reported less perceived persuasive intent, less message resistance, and greater story- consistent descriptive norms (b = -0.25(0.10), p = .01). For this latter path, behavior was further positively predicted (b = 0.26 (0.09), p < .01). Figure 7. Post-Hoc Model Tested for Study 3. Processing variables RAA predictors Message Attitudes Persuasive resistance Genre Behavioral intent intention Social norms Genre expectancy Perceived violations behavioral control Table 15. Results of Study 3 Post-Hoc Structural Equation Model (N = 188). Estimated paths b 95% CI Predicting RAA mediators Message Sci-fi/fantasy -> persuasive intent -> message .01 [.00, .04] resistance resistance -> attitudes Sci-fi/fantasy -> persuasive intent -> message .01 [-.01,.04] resistance -> injunctive norms Sci-fi/fantasy -> persuasive intent -> message .03 [.01, .09] resistance -> descriptive norms Sci-fi/fantasy -> persuasive intent -> message .03 [-.01, .03] resistance -> PBC Genre Sci-fi/fantasy -> persuasive intent -> genre expectancy .00 [-.02, .00] expectancy violations -> attitudes violations Sci-fi/fantasy -> persuasive intent -> genre expectancy .00 [-.01, .01] violations -> injunctive norms Sci-fi/fantasy -> persuasive intent -> genre expectancy -.01 [-.03, .00] violations -> descriptive norms Sci-fi/fantasy -> persuasive intent -> genre expectancy .00 [-.01, .00] violations -> PBC Predicting behavior Message Sci-fi/fantasy -> persuasive intent -> message .00 [-.00, .01] resistance resistance -> attitudes -> behavioral intentions 72 Table 15 (cont’d) Estimated paths b 95% CI Message Sci-fi/fantasy -> persuasive intent -> message .00 [-.00,.01] resistance resistance -> injunctive norms-> behavioral intentions Sci-fi/fantasy -> persuasive intent -> message .01 [.00, .03] resistance -> descriptive norms-> behavioral intentions Sci-fi/fantasy -> persuasive intent -> message .00 [-.01, .00] resistance -> PBC Genre Sci-fi/fantasy -> persuasive intent -> genre expectancy .00 [-.01, .00] expectancy violations -> attitudes-> behavioral intentions violations Sci-fi/fantasy -> persuasive intent -> genre expectancy .00 [-.00, .00] violations -> injunctive norms-> behavioral intentions Sci-fi/fantasy -> persuasive intent -> genre expectancy .00 [-.01, .00] violations -> descriptive norms-> behavioral intentions-> behavioral intentions Sci-fi/fantasy -> persuasive intent -> genre expectancy .00 [-.00, .00] violations -> PBC-> behavioral intentions Note: Unstandardized regression coefficients reported with 95% confidence intervals (5,000 bootstrap samples). Coefficients outside of the sampling error of zero are bolded. Pre-test attitudes, injunctive norms, descriptive norms, and past behavior were controlled for. Study 3 Discussion The present study experimentally manipulated the genre of an educational entertainment narrative (historical fiction vs. sci-fi/fantasy) to observe any differences in post-exposure attitudes, social norms, perceived behavioral control (PBC), and behavioral intentions. Additionally, it tested the explanatory power of message resistance and genre expectancy violations in the entertainment persuasion process. Overall, the hypotheses of Study 3 were not supported. Those who watched an educational message in the sci-fi/fantasy genre condition did report significantly different attitudes, social norms, PBC or behavioral intentions for the target behavior than those who watched a historical fiction episode. Furthermore, message resistance and genre expectancy violations did not mediate the effect of genre on any persuasive outcomes. Yet, exploratory analyses of the data revealed significant mediation results if perceived persuasive intent was entered into the model as an antecedent to message resistance. 73 There are several possibilities for the lack of hypothesis support in this study. First, it is possible that the narratives created were not powerful enough in their educational messages to significantly alter perceptions and behavior. Short storyboard videos were used as stimuli in the current study which offered great experimenter control. Yet, the format may have subsequently limited the potential persuasive effects that could be observed. Entertainment TV has been hallmarked as a powerful persuasion vehicle due to its ability to show a behavior being performed on-screen by characters audiences have developed parasocial bonds with (Bandura, 2004; Singhal et al., 2004, 2013). The current stimuli were presented to participants as a new TV show with unfamiliar characters and did not visually show the behavior being performed. Thus, while it communicated an educational message in an audio-visual narrative context, the strengths of an entertainment TV narrative were not leveraged. Future research may consider using stimuli that grant audiences the ability to form strong connections with the characters, such as through a longitudinal experiment with multiple episodes of the program, and to develop stimuli that visually show the behavior being performed on-screen. Second, the chosen target behavior likely incurred a ceiling effect, subsequently limiting any observable changes in the persuasive outcomes. Indeed, pre-test attitudes of daily stretching were noticeably high at 5.55 (SD = 0.74) on a 7-point scale. In result, the behavior of stretching daily may have been too pro-attitudinal for a narrative to reinforce in any substantial capacity. The goal behind using a pro-attitudinal message was to test how audiences would respond to an embedded message in a fictional TV format that they were not pre-disposed to resist. If resistance was observed, it would lend support that audiences do not want persuasive messages in entertainment media, in general, thus reinforcing the need for resistance-reduction approaches to entertainment persuasion. If resistance was not observed and the entertainment message still had a persuasive effect, the results would have supported recent research highlighting the need for other explanatory mechanisms (Frazer et al., 2021; Tchernev et al., 2021). 74 Although there were no observed differences in genre expectancy violations and message resistance- the primary mechanisms tested in the current study- between genre conditions, there was a significant difference in perceived persuasive intent. That is, despite both videos containing the same educational messages in nearly identical narratives, participants inferred the historical fiction narrative to have higher persuasive intent than the sci- fi/fantasy narrative. Perceived persuasive intent was then found to predict message resistance, ultimately predicting attitudes, descriptive norms, and behavioral intent (via descriptive norms). These results lend support to the notion that participants hold strong expectations of genres that influence their later perceptions of its content. As was observed in Study 1 and Study 2, educational and persuasive messages are thought to be more prevalent in historical fiction programs than other genres, such as sci-fi/fantasy. In the present study, it is possible that these expectations bolstered the persuasive intent in the historical fiction condition more than in the sci-fi/fantasy condition: participants expected historical fiction shows to be likely to contain education messages, so when there was one, they recognized the persuasive intent more easily. Yet, for those in the sci-fi/fantasy condition, because the genre is not often expected to contain educational messages, participants were less inclined to report it having persuasive intent. The expectations audiences brought into the experiment were inferred from past research (Study 1 and Study 2), but future research should assess genre expectations before stimuli exposure and not rely solely on post-test expectancy violation measures. For example, a future study could measure genre expectancies in a pre-test and then perform a 2 (genre: sci- fi/fantasy vs. historical fiction) x 2 (educational message: present vs. absent) experiment. Expectancy violations could be evaluated by whether participants’ pre-existing expectations were violated from the stimuli assigned. The post-hoc finding that persuasive intent was negatively associated with message resistance, which in turn negatively predicted RAA variables, for a pro-attitudinal behavior could be interpreted as support for a resistance reduction approach to entertainment persuasion. That 75 is, although message resistance was not found to mediate the relationship between genre condition and RAA predictors, a significant indirect relationship was found if perceived persuasive intent was added as an antecedent. Thus, even in a pro-attitudinal context, message resistance was still found to predict RAA predictors if it was preceded by perceived persuasive intent. I return to the important of perceived persuasive intent as it relates to genre and message resistance in the general discussion to follow. Instead, here, I would like to highlight the relationship between entertainment TV exposure and story-consistent behavioral intentions occurring by increasing participants’ descriptive norms of the behavior. Most of the work regarding entertainment persuasion and EE focus on changes in attitudes, beliefs (e.g., self-efficacy) and behavior (Bandura, 2004; Bilandzic & Busselle, 2012; Poindexter, 2004; Singhal & Rogers, 2002). The present research instead highlights the importance of evaluating normative perceptions derived from entertainment media as it was the increase of descriptive norms that predicted behavioral intention after message exposure. There is a growing body of literature on how social norms influence entertainment media appraisals (Kryston & Eden, 2021; S. Park et al., 2021) and most germane to this study, subsequent persuasion (Riley et al., 2017, 2020). In the present study, the stimuli appeared to bolster participants’ perceived frequency of the behavior being performed by others. The descriptive normative influence of entertainment is implied in the cultivation theory literature (i.e., TV shapes viewers’ social reality by showing them what others do; Gerbner, 1998; Hermann et al., 2021) but little research has directly tested entertainment media’s persuasive influence by a change in individual normative perceptions (Riley et al., 2017; Riley & Borum Chattoo, 2019; Singhal et al., 2006; Wakefield et al., 2010). The present research thus calls for more work examining not only how entertainment media may shape and inform descriptive norms, but how those norms subsequently influence behavioral adoption. In general, however, these results should be taken with caution due to their exploratory (i.e., post-hoc) nature. 76 The current study had several limitations. First, only two genres were examined in a storyboard format and can therefore not be generalized to other genres or entertainment media formats. The stimuli were structured to resemble a fictional TV episode but are unlikely to have fully represented the experience of TV watching. Additionally, because this study was completely online, participants likely watched the video in many different contexts (e.g., in public, while distracted, etc.). It is impossible to know how these differences in viewing experience impacted the results of the study. Regarding measures, I was unable to compute a reliable measure for processing fluency. Because this measure was adapted from items originally meant for non-narrative stimuli (Shulman & Sweitzer, 2018a, 2018b), it is possible that in changing the wording for a narrative context, I altered the reliability of the scale. Nevertheless, a metacognitive variable was not examined in the present study. Lastly, due to time and space considerations, several single-item measures were used such as for perceived behavioral control, descriptive norms, and behavioral intentions. Although prior RAA research has also measured these variables with single-items (e.g., Hillhouse, 2000; Mullan et al., 2013; Shmueli, 2021), future research should consider using more sophisticated measures. 77 CHAPTER SIX: OVERALL DISCUSSION The past couple of decades have seen an increased interest in research regarding entertainment media’s persuasive capabilities (Moyer-Gusé & Nabi, 2010; Singhal & Rogers, 2002; Slater & Rouner, 2002). Despite the growth in entertainment persuasion scholarship, the unique influence of genre- a system of categories to differentiate and consolidate content based on structural, thematic and/or functional criteria (Bilandzic & Rössler, 2004; Duff, 2000)- has been largely ignored. Much research has acknowledged that genre likely influences the persuasion process (e.g., C. J. Lee & Niederdeppe, 2011; Moyer-Gusé, 2010; Slater & Rouner, 2002), but the current literature lacks a thorough investigation of how and to what effect genre influences receptivity to entertainment media with persuasive goals. To address this need, three studies were conducted to document (a) whether viewers perceive fictional TV genres differently, (b) what expectations viewers have for fictional TV genres, and (c) how those expectations influence subsequent acceptance of a persuasive message. This section begins with a brief overview of each study conducted, offering several avenues for future research in the process, and concludes with a discussion of how future researcher may benefit from incorporating audience genre expectations into entertainment persuasion research. Study 1 provided a qualitative exploration into how current viewers think about fictional TV content and their reactions to educational and persuasive attempts in their consumed entertainment media. Overall, participants reported learning from fictional TV programs. Their perceptions particularly varied based on the genre of program discussed, with participants citing crime, medical, and historical dramas as most likely to contain factually accurate information and as the most appropriate genres for persuasive campaigns to occur in. This finding may be of relevance to scholars identifying educational content in current programming or when looking for entertainment programs to collaborate with. The privatized and competitive entertainment industry in the U.S. has made it difficult for traditional entertainment-education (EE) programs to be developed and distributed domestically 78 (Chatterjee et al., 2017; Kato et al., 2017; Riley & Borum Chattoo, 2019). In consequence, rather than create and implement intentional EE programs, U.S.-based scholars have had to rely on incidental messages, such as if an entertainment show naturally includes educational content in its programming, or work with existing shows to integrate a persuasive message and/or storyline (Frank & Falzone, 2021; Hursting & Comello, 2021; Moyer-Gusé, 2008). Historically, telenovelas or soap operas have been the primary genre used to communicate persuasive messages (Beck, 2004; Chatterjee et al., 2017; Poindexter, 2004; Singhal et al., 1993, 2013; Singhal & Rogers, 1999; Slater, 2002a). Recently, medical dramas have emerged as a common genre for EE message placement and study. (Ashbeek Brusse et al., 2015; Chung, 2014; Davin, 2003; Hoffman et al., 2017; T. K. Lee & Taylor, 2014). The present research suggests historical fiction and crime dramas as additional popular genres audiences report learning from. For example, participants described gaining knowledge about mental health issues, drug addiction, and post-traumatic stress disorder from crime dramas they had watched in the past. The use of entertainment media to communicate and unite social justice movements may be particularly relevant for these types of programs. Many participants in Study 1 identified content regarding social issues, such as the Black Lives Matters movement, as a persuasive message. Although the current research was focused on individual-level behaviors, the EE strategy is, at its core, a strategy of societal change (Frank & Falzone, 2021). A fruitful avenue for future scholars and practitioners may be to consider historical fiction and crime dramas when searching for persuasive message to investigate and when forming future collaborations, such as those relating to social justice issues (Borum Chattoo, 2021; Klein, 2013) The ethicality of entertainment-education and entertainment persuasion is a common concern of the strategy (Brown & Singhal, 1993; Greenberg et al., 2004). When using a popular media marketed as an entertainment program for education and persuasion, questions of whether it is deceitful or manipulative naturally arise (Brown & Singhal, 1993). Previous 79 qualitative research has tended to support that audiences are wary of intentionally placed messages in entertainment TV (Ashbeek Brusse et al., 2015). Klein (2013) observed, for example, that TV watchers in the United Kingdom believe it to be “inappropriate” for educational messages to appear in certain genres. It was not elaborated upon, though, which genres would be considered more or less appropriate. The results of Study 2 offer further insight. Study 2 surveyed TV watchers in the U.S. for their expectations and hypothetical acceptance of educational messages in ten fictional TV genres: animated dramas (e.g., Castlevania), animated comedies (e.g., Family Guy), comedies (e.g., The Office), crime comedies (e.g., Psych), crime dramas (e.g., NCIS), general dramas (e.g., This is Us), historical fiction (e.g., Bridgerton), medical comedies (e.g., Scrubs), medical dramas (e.g., Grey’s Anatomy), and sci-fi/fantasy (e.g., Stranger Things). Results found participants’ expectations of content credibility, learning potential, and perceived likelihood of an educational message appearing to significantly differ based on genre. As suggested by Study 1, historical fiction, medical dramas, crime dramas, and general dramas were the highest ranked genres across all persuasion-relevant expectations. In observing the means, it was notable how high participants ranked the likelihood of education appeals appearing in these fictional TV genres. For example, on a 7-point scale, historical fiction, crime dramas, and medical dramas all averaged above a scale point of 5 when estimating the likelihood of an educational appeal appearing in shows typical of those genres. Furthermore, expectations of content credibility and perceived likelihood positively predicted anticipated acceptance of an embedded educational message. These results, in conjunction with Study 1, suggest current audiences to have greater expectations of educational and persuasive content in fictional TV than may have otherwise been expected (Chatterjee et al., 2017; Klein, 2013). The presence of education expectations regarding entertainment TV was thought to have implications for our current understanding of entertainment persuasion as a resistance- reduction strategy. The extended-elaboration likelihood model (E-ELM; Slater & Rouner, 2002) 80 and entertainment overcoming resistance model (EORM; Moyer-Gusé & Nabi, 2010) are the leading theoretical models for understanding entertainment media’s persuasive effects on individuals and both posit entertainment narratives to be successful to the extent that they do not incur message resistance from the audience. The logic stems from a dual-process perspective of cognition (Slater & Rouner, 2002; Moyer-Gusé, 2008; Moyer-Gusé & Nabi, 2010). Entertainment narratives tend to require high cognitive resources to fully comprehend the storyline and its characters. When watching an episode, for example, viewers must keep track of all the characters, their backstories, and their current actions to stay engaged with the narrative. In consequence, if a persuasive message is embedded within the narrative, participants are unlikely to be motivated or able to effortfully process the persuasive information. In a statistical or argument-based message, heuristic or peripheral processing of the message may result in unsuccessful or unreliable persuasion (Petty & Cacioppo, 1986), but in a narrative- context, this mode is preferred. Drawing attention to the persuasive message in an entertainment narrative is thought to incur message resistance and negative affect toward the program, such as viewers being annoyed that it tried to “manipulate” them (Slater & Rouner, 2002). There are two main reasons why it is assumed that audiences will resist a persuasive message if made aware of it: (a) they are motivated to resist it based on issue-relevant factors or (b) it activated reactance. People are known to generally accept information given to them unless they have a motivated reason to reject it, such as if the message is counter-attitudinal or if they have high issue involvement with the target behavior (Petty & Cacioppo, 1979b, 1979a). Additionally, if viewers are exposed to a persuasive message they were not expecting to attend to, they may feel that their freedom was violated (either in message exposure or regarding the target behavior), encouraging a rejection of the message (Moyer-Gusé, 2008). Yet, as evidenced in Study 1 and Study 2, people (a) tend to only view pro-attitudinal/prosocial messages in their selected entertainment TV and (b) appear to hold high expectations for 81 educational content appearing in certain genres of programming. If audiences expect certain genres to have educational messages, in general, and if that message is pro-attitudinal, there is not much reason to suspect message resistance would incur (Frazer et al., 2021; Moyer-Gusé, 2010). Study 3 tested this assertion by experimentally manipulating a pro-attitudinal message to appear in either a historical fiction or sci-fi/fantasy TV episode. The power of message resistance to explain any changes in post-exposure outcomes was tested. Additionally, the mechanism of expectancy violations, informed by expectancy violations theory (Burgoon, 2015), was offered and evaluated. Neither proposed mechanism was found to mediate the relationship between the message and persuasive outcomes, though this null finding is likely due to the lack of differences between pre- and post-test scores overall. Although the original hypotheses were not supported, post-hoc analyses revealed an interesting finding regarding perceived persuasive intent. The historical fiction episode was thought to have significantly higher persuasive intent than the sci-fi/fantasy episode. It should be noted that the conditions differed minimally in plot details (e.g., the year being 1870 vs. 2870) and were identical in context and presentation of the educational message. When persuasive intent was considered, the expected relationship between message resistance and persuasive outcomes was found (Slater & Rouner, 2002; Moyer-Gusé, 2008). Thus, even in a pro-attitudinal context, message resistance was maintained as an important mechanism in how entertainment media facilitates persuasion. The impact of perceived persuasive intent in entertainment narratives has been mixed (Frazer et al., 2021; Moyer-Gusé et al., 2019; Moyer-Gusé & Nabi, 2010; W. Wang & Shen, 2019). Although some studies have found persuasive intent to negatively affect persuasion by increasing message resistance (Moyer-Gusé et al., 2019; W. Wang & Shen, 2019), others have found no effect when persuasive intent is signaled (Frazer et al., 2021; Moyer-Gusé et al., 2012). Of the studies that have investigated the impact of perceived persuasive intent of entertainment narratives, the majority have manipulated it prior to message exposure, thus 82 signaling to participants that the entertainment narrative contains a persuasive message (Frazer et al., 2021; Moyer-Gusé et al., 2012, 2019; W. Wang & Shen, 2019). The present research suggests participants’ expectations of persuasive intent coming into the narrative as an important variable to consider in future work, particularly if comparing messages across different genres. Research testing (a) whether expectations of educational content in a genre creates stable perceptions of persuasive intent of that genre and (b) how those stable expectations influence receptivity to subsequent persuasive appeals would particularly benefit the literature. Lastly, the lack of findings regarding expectancy violations should be acknowledged. The present dissertation attempted to offer expectancy violations as a potential mechanism for why certain genres may be more successful at persuasion than others. Prior work in expectancy violations theory has found the (un)fulfillment of expectations toward a situation or media to influence reactions to that encounter (Bonus et al., 2021; E. L. Cohen, 2010; Hong et al., 2021; Matthews & Bonus, 2021). For example, if a character behaves in a way a viewer would not expect due to pre-existing schemas associated with traditional character archetypes, the response to the narrative and those characters may be altered (Bonus et al., 2021; Matthews & Bonus, 2021). Applying that logic to genres, it was expected that if people hold certain expectations about the education likelihood of a genre, a violation of that expectation should incur some effect on persuasion success. Unfortunately, in the present study, I was unable to successfully measure and/or manipulate genre expectations. Regardless of these findings, one would be remiss to discredit the potential influence of genre expectations and their violations. This dissertation provides support that viewers hold persuasion-relevant expectations for fiction TV genres, and that these expectations may influence subsequent perceptions of entertainment narratives, such as its perceived persuasive intent. Further research is needed in understanding what occurs when these expectations are violated and the impact those violations have on persuasion outcomes. 83 Conclusion Taken together, this dissertation underscores the importance of considering genre when studying entertainment persuasion. Across three studies using various methods, genre remained a consistent factor for how people thought about fictional TV for educational information. Expectations about the likelihood of a genre containing educational and persuasive communication specifically emerged as a consistent finding which may have implications for how messages communicated in those genres are received. Although the present research was unable to account for the explanatory processes responsible for entertainment’s persuasive effects as it relates to genre, it does offer several avenues of research for those wishing to explore genre expectations and their violations in the future, such by testing genre’s role in forming perceived persuasive intent. 84 APPENDICES 85 APPENDIX A: Study 1 Screener Questionnaire [Q1] Research Participants Information and Consent Form You are being asked to participate in a research study. Researchers are required to provide a consent form to inform you about the research study, to convey that participation is voluntary, to explain the risks and benefits of participation, and to empower you to make an informed decision. You should feel free to ask the researcher any questions you may have. Study: An Exploration of Viewers Expectations of Entertainment Media [Screener Survey] 1. Purpose of Research The purpose of this research study is to better understand people's expectations and experiences of persuasive messages within entertainment media. This could include, for example, advertising placements or educational information integrated within the entertainment program. 2. What You Will Do You will be asked to fill out this short survey to see if you are eligible to participate in one-on- one interviews with a trained researcher of this study. The survey is expected to take less than 5 minutes. If you are eligible, you will be contacted to participate in the interview, which will take approximately 60 minutes. 3. Potential Benefits and Risks You may not benefit personally from being in this study, however, we hope that the knowledge gained may help others. There are no more than minimal psychological, emotional, physical, legal, financial, or privacy risks associated with this study. 4. Privacy and Confidentiality Your privacy will be protected to the maximum extent allowable by law. If selected for the interview, an audio recording will be kept, but no personally identifying information will be reported. A full description of the procedures will be provided before you participate in the interview. 5. Your Rights to Participate, Say No, or Withdraw You have the right to say no to participate in this research. You can stop at any time after it has already started with no consequence. You will not lose any benefits that you normally receive. 6. Costs and Compensation for This Study There are no associated costs for participating in this study, except in your time. If selected for the interviews, you will receive $20 in compensation after the interviews. Please note that this survey, alone, does not qualify for monetary compensation. More information about the compensation will be provided if selected for the interviews. 7. Alternative Options You may find alternative research studies on the SONA system. 8. Contact Information If you have any concerns or questions about this study, please contact the study coordinator, 86 Nikki McClaran, at mcclaran@msu.edu. If you have any questions or concerns about your role and rights as a research participant, would like to obtain information or offer input, or would like to register a complaint about this study (anonymously, if you wish), contact the Michigan State University's Human Research Protection Program at (517) 355-2180 by phone, (517) 432-4503 by fax, or email irb@msu.edu or regular mail at 4000 Collins Rd, Suite 136, Lansing, MI 48910. 9. Documentation of Informed Consent By choosing "I agree to participate," you are indicating that you have read and understood this form, are agreeing to participate in this research, and have your answers included in the dataset. ( ) I agree to participate ( ) I do not agree to participate [skip logic: skip to end of survey if selected] [Q2] How often on average do you watch the following types of television programs in a day? 0 hours 1-2 hours 3-4 5-6 More hours hours than 6 hours Medical dramas (ex: Grey’s () () () () () Anatomy) Family dramas (ex: This is Us) () () () () () Crime dramas (ex: Law & Order) () () () () () Supernatural/fantasy dramas (ex: () () () () () Stranger Things) Cartoon/Animated (ex: Rick & Morty) () () () () () Non-competition reality (ex: The () () () () () Real Housewives) Competition reality (ex: Bachelor) () () () () () Sitcoms (ex: Big Bang Theory) () () () () () [Q3] How often on average do you watch the following types of television programs over the course of a week? 0 hours 1-2 hours 3-4 5-6 More hours hours than 6 hours Medical dramas (ex: Grey’s () () () () () Anatomy) Family dramas (ex: This is Us) () () () () () Crime dramas (ex: Law & Order) () () () () () Supernatural/fantasy dramas (ex: () () () () () Stranger Things) Cartoon/Animated (ex: Rick & Morty) () () () () () Non-competition reality (ex: The () () () () () Real Housewives) Competition reality (ex: Bachelor) () () () () () Sitcoms (ex: Big Bang Theory) () () () () () 87 [Q4] What is your birth year? ___________ [Q5] What gender do you identify as? ( ) Male ( ) Female ( ) Non-binary/other gender ( ) Prefer not to say [Q6] How do you identify regarding race and ethnicity? Select all that apply. ( ) White or Caucasian ( ) Black or African-American ( ) Asian ( ) Native American or Alaska Native ( ) Native Hawaiian or Pacific Islander ( ) Other: ___________ [Q7] If you are found to qualify, you may be contacted to participate in a on-on-one, virtual interview (via Zoom) for monetary compensation ($20). Please indicate whether you'd like to be considered for the interview portion of this study. If selected, you will receive an email from the researchers with a unique code in order to sign up for Part 2 of this study (also in the paid SONA system). ( ) I do not want to be considered ( ) I do want to be considered 88 APPENDIX B: Study 1 Interview Guide Introduction: Hello and thank you for participating in this research study. In this interview, we are going to ask you about your thoughts and behaviors about TV shows. We want to know about TV shows you watch just for fun, so we are NOT interested in things you watch to learn about the world, such as the news. I do want to remind you that this conversation will be recorded but no personally identifying information will be attached to it. Do you have any questions before we get started? Section One: Television Behavior Questions 1. To start, tell me how much television you typically watch? 2. When you are watching TV just for fun, how do you watch it? This could include, for example, the type of electronic device used and the kinds of platforms (e.g., cable, Netflix, etc.) you use? Section Two: Television Preference Questions 3. What are your favorite kinds of TV shows? 4. What are some of your top watched or favorite shows? 5. What do you look for when considering watching a new show or continuing to watch a show? 6. What might make you decide not to watch a new show or stop watching a show once you’ve started? a. Are there any genres you do not watch? Section Three: General Television and Persuasion Questions 7. How often do you think TV shows try to change people’s mind or educate them about a topic? a. Can you give an example? b. How does this make you feel? 8. Has there been a time when TV has changed your mind about something or maybe given you new information? a. Can you tell me about it? b. Did this change how you think or feel about the show? 9. Has there been a time when you’ve thought a TV show was trying to change your mind, but it didn’t work? a. What made you stick to your original opinion? b. Did this change how you think or feel about the show? Section Four: Prosocial Content Questions 10. Do you ever seek out TV programming to learn something or be more informed, aside from the news? 89 11. When you get information from a TV show, how accurate do you think it is? a. Can you provide some examples when you thought the information was accurate or not? b. Do you think certain types of shows care more about their informational accuracy than others? 12. When there is information in a TV show, who do you think decides to put it in? Why do you think they put it in there? a. How do you feel about the partnerships between government or non-profit organizations regarding this? b. Do you think certain types of shows are more appropriate to have this type of content than others? 13. Can you describe a time when you were grateful for the information you got from a show that you were not expecting? a. Can you describe a time where it irritated you? Conclusion: That’s all the questions I have for you today. Thinking back on what we’ve talked about, is there anything you’d like to follow-up on or clarify? (Pause) Well, thank you for your participation and feel free to reach out to me regarding any questions in the future. 90 APPENDIX C: Study 2 Questionnaire Items [Q1] Research Participant Information and Consent Form You are being asked to participate in a research study. Researchers are required to provide a consent form to inform you about the research study, to convey that participation is voluntary, to explain risks and benefits of participation, and to empower you to make an informed decision. You should feel free to ask the researchers any questions you may have. Study Title: An Exploration of Viewer Expectations of Entertainment Media and Persuasion Survey 1. PURPOSE OF RESEARCH The purpose of this research study is to better understand people’s expectations and experiences of persuasive messages within entertainment media. This could include, for example, advertising placements or educational information integrated within entertainment programs. 2. WHAT YOU WILL DO You will be asked to complete a questionnaire survey. The survey will evaluate your (a) expectations of persuasion in entertainment and (b) your response when confronted with persuasion in entertainment. The survey is expected to last approximately 30 minutes. 3. POTENTIAL BENEFITS You may not benefit personally from being in this study. However, we hope that, in the future, other people might benefit from this study by better understanding how entertainment media is approached and can be utilized for successful persuasion. 4. POTENTIAL RISKS There are no more than minimal psychological, emotional, physical, legal, financial, or privacy risks associated with this study. 5. PRIVACY AND CONFIDENTIALITY Your privacy will be protected to the maximum extent allowable by law. No personally identifying information will be reported in any research product, and your IP address will be removed to not link your responses with any computer you may have used in participation in this study. Your results will be kept confidential to the trained research staff of this study and will be securely kept for at least three years after the project closes. You will create a unique code known only to you in the case that you want your results removed from the data set. 6. YOUR RIGHTS TO PARTICIPATE, SAY NO, OR WITHDRAW You have the right to say no to participate in the research. You can stop at any time after it has already started. There will be no consequences if you stop, and you will not be criticized. You will not lose any benefits that you normally receive. 7. COSTS AND COMPENSATION FOR BEING IN THE STUDY There are no associated costs for participating in this research study except for your time, which you will be compensated monetarily for. You will receive $10 for your participation in this study and will be issued after completion of the interview. The compensation will be issued through 91 the email provided to SONA in order to maintain participant confidentiality. 8. ALTERNATIVE OPTIONS You may find alternative research studies on the SONA system. 9. CONTACT INFORMATION If you have concerns or questions about this study, such as scientific issues, how to do any part of it, or to report an injury, please contact the study coordinator (Nikki McClaran, email: mcclaran@msu.edu, or the principle investigator (Nancy Rhodes, email: rhodesn3@msu.edu, phone: 517-353-9909) If you have questions or concerns about your role and rights as a research participant, would like to obtain information or offer input, or would like to register a complaint about this study, you may contact—anonymously if you wish—the Michigan State University’s Human Research Protection Program at (517) 355-2180 by phone, (517) 432-4503 by fax, or e- mail irb@msu.edu or regular mail at 4000 Collins Rd, Suite 136, Lansing, MI 48910. 11. DOCUMENTATION OF INFORMED CONSENT. By choosing "I agree to participate,” you are indicating that you have read this form, are agreeing to participate in this research, and have your answers included in the dataset. ( ) I have read the consent form and do not agree to participate [skip logic: skip to end of survey if selected] ( ) I have read the consent form and agree to participate [Q2] In an average week, how often do you watch TV for entertainment purposes (excluding news and sports)? ( ) Never [skip logic: skip to end of survey if selected] ( ) A little ( ) A moderate amount ( ) A lot ( ) A great deal [Q3] In an average week, how often do you watch TV for educational purposes (excluding news and sports)? ( ) Never ( ) A little ( ) A moderate amount ( ) A lot ( ) A great deal [Q4] In an average week, how often do you watch fictional TV programming (shows set in fictionalized settings and/or with fictional characters)? ( ) Never [skip logic: skip to end of survey if selected] ( ) A little ( ) A moderate amount ( ) A lot ( ) A great deal [Q5] How many days during an average week do you watch TV, including live and time-shifted programming, such as streaming? Please exclude news and sports watching. ( ) 0 days 92 ( ) 1 day ( ) 2 days ( ) 3 days ( ) 4 days ( ) 5 days ( ) 6 days ( ) 7 days [Q6] On a typical weekday, how many hours do you watch TV, including live and time-shifted programming, such as streaming? Please exclude news and sports watching. ( ) 0 hours ( ) 1 hour ( ) 2 hours ( ) 3 hours ( ) 4 hours ( ) 5 hours ( ) 6+ hours [Q7] On a typical weekend, how many hours do you watch TV, including live and time-shifted programming, such as streaming? Please exclude news and sports watching. ( ) 0 hours ( ) 1 hour ( ) 2 hours ( ) 3 hours ( ) 4 hours ( ) 5 hours ( ) 6+ hours [Q8] During an average week, how often do you watch episodes from the following program genres? Genre: Example shows (examples are not a complete representation of possible shows) Comedies: The Big Bang Theory, Schitt's Creek, Friends Animated Comedies: BoJack Horseman, South Park, Bob's Burgers Animated Dramas: Castlevania, Love Death + Robots, Justice League Medical Dramas: Grey's Anatomy, Chicago Med, The Good Doctor Medical Comedies: Scrubs, Royal Pains, Nurse Jackie Crime Dramas: Law and Order franchise, NCSI, Criminal Minds Crime Comedies: Brooklyn-Nine-Nine, Psych, Castle Historical Dramas: Queen's Gambit, Peaky Blinders, Bridgerton SciFi-Fantasy: Stranger Things, Wanda Vision, The Walking Dead General Dramas: This is Us, Euphoria, The Haunting of Hill House Docu-series: The Devil Next Door, Planet Earth, Chef's Table Reality: Love Island, Master's Chef, The Bachelor franchise Never Rarel Occasio Som Frequently Ofte A lot y nally etim n es Comedies () () () () () () () Animated Comedies () () () () () () () 93 Animated Dramas () () () () () () () Medical Dramas () () () () () () () Medical Comedies () () () () () () () Crime Dramas () () () () () () () Crime Comedies () () () () () () () Historical dramas () () () () () () () SciFi/Fantasy () () () () () () () General Dramas () () () () () () () Docu-series () () () () () () () Reality () () () () () () () [Q9] In general, which TV genre would you say you watch the most of? Click here to revisit example shows in each genre. ( ) Comedy ( ) Animated Comedy ( ) Animated Drama ( ) Medical Drama ( ) Medical Comedy ( ) Crime Drama ( ) Crime Comedy ( ) Historical Drama ( ) SciFi/Fantasy ( ) General Drama ( ) Docu-series ( ) Reality ( ) None of the above [Q10: Display online if “None of the above” from Q18 is selected] In your own words, please describe what kind of TV genre are you most likely to watch? ________________ [Q11] For the remainder of the survey, we are only interested in your thoughts regarding fictional, entertainment TV shows. In other words, we want you to focus on shows that are (1) mostly fictionalized (even if based on real-life events), and (2) primarily watched for its entertainment value. We are not interested in sports, news, documentary, or reality TV programming. If you do not watch fictional, entertainment TV shows, please indicate so now. ( ) I do not watch fictional, entertainment TV shows [skip logic: skip to end of survey if selected] ( ) I watch fictional, entertainment TV shows [Q12] To the best of your knowledge, please use the following scales to complete this sentence: The content of recent TV shows (shows with new episodes released 2010 and beyond) generally is: Not at all believable ( ) ( ) ( ) ( ) ( ) ( ) ( ) Very believable Not at all accurate ( ) ( ) ( ) ( ) ( ) ( ) ( ) Very accurate Not at all realistic ( ) ( ) ( ) ( ) ( ) ( ) ( ) Very realistic [Q13] To the best of your knowledge, please use the following scales to complete this sentence: 94 The content of older TV shows (shows with new episodes released only before 2010) generally is: Not at all believable ( ) ( ) ( ) ( ) ( ) ( ) ( ) Very believable Not at all accurate ( ) ( ) ( ) ( ) ( ) ( ) ( ) Very accurate Not at all realistic ( ) ( ) ( ) ( ) ( ) ( ) ( ) Very realistic [Q14] To the best of your knowledge, please indicate how believable the content is in shows typical of the following genres, where 1 = not at all believable and 7 = very believable. Click here to revisit example shows in each genre. 1 2 3 4 5 6 7 (not at all (very believable believable ) ) Comedies () () () () () () () Animated Comedies () () () () () () () Animated Dramas () () () () () () () Medical Dramas () () () () () () () Medical Comedies () () () () () () () Crime Dramas () () () () () () () Crime Comedies () () () () () () () Historical dramas () () () () () () () SciFi/Fantasy () () () () () () () General Dramas () () () () () () () [Q15] To the best of your knowledge, please indicate how accurate the content is in shows typical of the following genres, where 1 = not at all accurate and 7 = very accurate. Click here to revisit example shows in each genre. 1 2 3 4 5 6 7 (not at all (very accurate) accurate) Comedies () () () () () () () Animated Comedies () () () () () () () Animated Dramas () () () () () () () Medical Dramas () () () () () () () Medical Comedies () () () () () () () Crime Dramas () () () () () () () Crime Comedies () () () () () () () Historical dramas () () () () () () () SciFi/Fantasy () () () () () () () General Dramas () () () () () () () [Q16] To the best of your knowledge, please indicate how realistic the content is in shows typical of the following genres, where 1 = not at all realistic and 7 = very realistic. 95 Click here to revisit example shows in each genre. 1 2 3 4 5 6 7 (not at all (very realistic) realistic) Comedies () () () () () () () Animated Comedies () () () () () () () Animated Dramas () () () () () () () Medical Dramas () () () () () () () Medical Comedies () () () () () () () Crime Dramas () () () () () () () Crime Comedies () () () () () () () Historical dramas () () () () () () () SciFi/Fantasy () () () () () () () General Dramas () () () () () () () [Q17] How often do you feel that watching fictional, entertainment TV gives you new information or a new perspective of an issue? Never ( ) ( ) ( ) ( ) ( ) ( ) ( ) Always [Q18] How often do you feel that watching fictional, entertainment TV gives other people new information or a new perspective of an issue? Never ( ) ( ) ( ) ( ) ( ) ( ) ( ) Always [Q19] how much do to learn from a program in the following genres, on a scale from 1 to 7 where 1 = not at all to 7 = very much. Click here to revisit example shows in each genre. 1 2 3 4 5 6 7 (not at all) (very much) Comedies () () () () () () () Animated Comedies () () () () () () () Animated Dramas () () () () () () () Medical Dramas () () () () () () () Medical Comedies () () () () () () () Crime Dramas () () () () () () () Crime Comedies () () () () () () () Historical dramas () () () () () () () SciFi/Fantasy () () () () () () () General Dramas () () () () () () () [Q20] How informative do you think a program would be in the following genres, on a scale from 1 to 7 where 1 = not at all to 7 = very much. Click here to revisit example shows in each genre. 1 2 3 4 5 6 7 (not at all) 96 (very much) Comedies () () () () () () () Animated Comedies () () () () () () () Animated Dramas () () () () () () () Medical Dramas () () () () () () () Medical Comedies () () () () () () () Crime Dramas () () () () () () () Crime Comedies () () () () () () () Historical dramas () () () () () () () SciFi/Fantasy () () () () () () () General Dramas () () () () () () () [Q21] If a popular TV show were to have an informative storyline, such as about a health, environmental, or social issue, how likely do you think it would be for that storyline to be initiated by the following people? Very Unlikely Somewh Unsur Some Likely Very unlikely at e what likely unlikely likely Producer(s) () () () () () () () Director(s) () () () () () () () Outside non-profit () () () () () () () organization(s) Outside corporate () () () () () () () organization(s) Actors/Actresses () () () () () () () Network/Owning () () () () () () () Company [Q22] Imagine you were watching an episode of a popular TV show that you regularly watch. It is clear this episode has an educational message, such as about an ongoing health crisis or an environmental issue to provide new information or a certain perspective of an issue. After watching the show, you learn the message was put into the show due to the entertainment staff (directors, products, actors) wanting to spread the message to a large audience. Please indicate your level of (dis)agreement to the following statements regarding the above scenario. Strongl Disagre Somew Neither Some Agree Strongl y e hat agree what y agree disagre disagre nor agree e e disagree d I would be wary of watching future () () () () () () () episodes from this show 97 I would think more positively about the () () () () () () () show The educational message would not () () () () () () () affect my thoughts about the show [Q23] Imagine you were watching an episode of a popular TV show that you regularly watch. It is clear this episode has an educational message, such as about an ongoing health crisis or an environmental issue to provide new information or a certain perspective of an issue. After watching the show, you learn the message was put into the show due to a partnership with an organization wanting to spread the message to a large audience. Please indicate your level of (dis)agreement to the following statements regarding the above scenario. Strongl Disagre Somew Neither Some Agree Strongl y e hat agree what y agree disagre disagre nor agree e e disagree d I would be wary of watching future () () () () () () () episodes from this show I would think more positively about the () () () () () () () show The educational message would not () () () () () () () affect my thoughts about the show [Q24] If a fictional, entertainment TV show were to contain an educational message in an episode, how likely or unlikely would it be for the show to be classified as one of the following genres? Click here to revisit example shows in each genre. Very Unlikely Somewh Unsur Somew Likely Very unlikely at e hat likely unlikely likely Comedies () () () () () () () Animated Comedies () () () () () () () Animated Dramas () () () () () () () Medical Dramas () () () () () () () Medical Comedies () () () () () () () Crime Dramas () () () () () () () Crime Comedies () () () () () () () 98 Historical dramas () () () () () () () SciFi/Fantasy () () () () () () () General Dramas () () () () () () () [Q25] If a fictional, entertainment TV show were to contain an educational of informational message in their episode, how accepting would you be of it based on the show being in the following genres? Click here to revisit example shows in each genre. Very Unacce Somewh Unsur Somewh Acce Very unacce pting at e at pting acceptin pting unaccepti acceptin g ng g Comedies () () () () () () () Animated Comedies () () () () () () () Animated Dramas () () () () () () () Medical Dramas () () () () () () () Medical Comedies () () () () () () () Crime Dramas () () () () () () () Crime Comedies () () () () () () () Historical dramas () () () () () () () SciFi/Fantasy () () () () () () () General Dramas () () () () () () () [Q26] What is your birth year? ________ [Q27] What gender do you identify as? ( ) Male ( ) Female ( ) Non-binary/other gender ( ) Prefer not to say [Q28] How do you identify regarding race and ethnicity? Select all that apply. ( ) White or Caucasian ( ) Black or African-American ( ) Asian ( ) Native American or Alaska Native ( ) Native Hawaiian or Pacific Islander ( ) Other: ___________ [Q29] In which state do you currently reside? _______ [Q30] What is the highest level of school you have completed or the highest degree you have received? ( ) Less than high school ( ) High school graduate (high school diploma or equivalent including GED) ( ) Some college but no degree ( ) Associate degree in college (2-year) ( ) Bachelor’s degree in college (4-year) ( ) Master’s degree 99 ( ) Doctoral degree ( ) Professional degree (JD, MD) [Q31] Information about income is very important to understand. Would you please give your best guess? Please indicate the answer that includes your entire household income in 2021 before taxes. ( ) Less than $10,000 ( ) $10,000 – 19,999 … ( ) $150,000 or more [Q32] Through what device did you complete this survey? ( ) Laptop or computer ( ) Tablet ( ) Cellphone ( ) Other ________ 100 APPENDIX D: Correlation Matrixes for Study 2 Variables Table D1. Study 2 Correlation Matrix for Perceived Credibility by Genre. 1 2 3 4 5 6 7 8 9 1 Animated comedy - 2 Animated drama .82*** - 3 Comedy .69*** .53*** - 4 Crime comedy .55*** .50*** .63*** - 5 Crime drama .21*** .31*** .36*** .58*** - 6 General drama .33*** .39*** .45*** .46*** .59*** - 7 Historical fiction .18*** .27*** .27*** .45*** .70*** .54*** - 8 Medical comedy .52*** .51*** .57*** .85*** .55*** .44*** .46*** - 9 Medical drama .24*** .36*** .33*** .53*** .83*** .53*** .64*** .67*** - 10 Sci-fi/fantasy .56*** .58*** .38*** .45*** .33*** .40*** .35*** .43*** .32*** Note: * p < .05, ** p < .01, *** p < .001 Table D2. Study 2 Correlation Matrix for Learning Expectations by Genre. 1 2 3 4 5 6 7 8 9 1 Animated comedy - 2 Animated drama .81*** - 3 Comedy .83*** .69*** - 4 Crime comedy .62*** .60*** .67*** - 5 Crime drama .38*** .45*** .43*** .67*** - 6 General drama .50*** .60*** .55*** .53*** .69*** - 7 Historical fiction .31*** .40*** .35*** .49*** .73*** .59*** - 8 Medical comedy .63*** .65*** .62*** .83*** .61*** .52*** .48*** - 9 Medical drama .39*** .53*** .38*** .58*** .82*** .63*** .65*** .70*** - 10 Sci-fi/fantasy .59*** .62*** .55*** .54*** .48*** .56*** .49*** .52*** .42*** Note: * p < .05, ** p < .01, *** p < .001 101 Table D3. Study 2 Correlation Matrix for Perceptions of Appeal Likelihood by Genre. 1 2 3 4 5 6 7 8 9 1 Animated comedy - 2 Animated drama .73*** - 3 Comedy .78*** .58*** - 4 Crime comedy .52*** .48*** .51*** - 5 Crime drama .14*** .30*** .16*** .43*** - 6 General drama .23*** .39*** .27*** .24*** .43*** - 7 Historical fiction .09* .17*** .06 .21*** .43*** .23*** - 8 Medical comedy .46*** .45*** .48*** .73*** .41*** .22*** .25*** - 9 Medical drama .10* .26*** .11** .31*** .70*** .42*** .41*** .49*** - 10 Sci-fi/fantasy .40*** .42*** .35*** .38*** .22*** .32*** .28*** .28*** .14*** Note: * p < .05, ** p < .01, *** p < .001 Table D4. Study 2 Correlation Matrix for Acceptance of Educational Message by Genre. 1 2 3 4 5 6 7 8 9 1 Animated comedy - 2 Animated drama .83*** - 3 Comedy .77*** .65*** - 4 Crime comedy .65*** .63*** .69*** - 5 Crime drama .40*** .46*** .47*** .62*** - 6 General drama .45*** .53*** .52*** .49*** .61*** - 7 Historical fiction .35*** .45*** .41*** .41*** .60*** .55*** - 8 Medical comedy .64*** .58*** .66*** .75*** .54*** .48*** .43*** - 9 Medical drama .40*** .48*** .47** .53*** .74*** .60*** .60*** .65*** - 10 Sci-fi/fantasy .58*** .59*** .51*** .51*** .44*** .48*** .48*** .42*** .37*** Note: * p < .05, ** p < .01, *** p < .001 102 Appendix E: Study 3 Questionnaire [Q1] Research Participant Information and Consent Form Study Title: An exploration of viewer’s assessment of entertainment television Researcher and Title: Nikki McClaran, Doctoral Candidate and Nancy Rhodes, Ph.D., Associate Professor Department and Institution: Department of Advertising + Public Relations, Michigan State University Contact Information: mcclaran@msu.edu and rhodesn3@msu.edu Sponsor: N/A BRIEF SUMMARY You are being asked to participate in a research study. Researchers are required to provide a consent form to inform you about the research study, to convey that participation is voluntary, to explain risks and benefits of participation including why you might or might not want to participate, and to empower you to make an informed decision. You should feel free to discuss and ask the researchers any questions you may have. You are being asked to participate in a research study of how audiences’ expectations influence subsequent perceptions of entertainment television content. Your participation will take about 15 minutes. You will be asked to complete survey questions about your entertainment consumption and perceptions, watch a short television episode, and lastly, answer questions about the video you watched. There are no more than minimal psychological, emotional, physical, legal, financial, or privacy risks associated with this study. You will not directly benefit from your participation in this study but your participation will hopefully benefit those in the future. PURPOSE OF RESEARCH The purpose of this research study is to investigate how people’s pre-existing expectations and beliefs about television content influences their reception of different television content, such as the plot or information provided. WHAT YOU WILL BE ASKED TO DO First, you will be asked questions about how much entertainment television you consume on a regular basis and your expectations of the type of information you will receive from different types of shows. Next, you will be asked to watch a short video (less than 5 minutes) summarizing a television show episode. The video will include visual and audio components. Last, you will answer questions about your thoughts on what you watched, in addition to questions about your regular life, such as how often you engage in different health behaviors and demographic information. You will be asked to complete all steps of the research during one session online at a time of your choosing. You are allowed to skip any questions that you would not prefer to answer, however, if more than 50% is not completed, compensation may be revoked. POTENTIAL BENEFITS You may not benefit personally from being in this study. However, we hope that, in the future, other people might benefit from this study by gaining greater understanding of how entertainment television influences real life behaviors. This information may be instrumental for 103 those working in the entertainment industry in creating pro-social content. POTENTIAL RISKS There are no foreseeable psychological, emotional, physical, legal, financial, or privacy risks associated with this study. The television episode you will be asked to watch is what is reflective of what is commonly distributed on prime-time television. No sexual or violent scenes will be depicted. PRIVACY AND CONFIDENTIALITY Your privacy will be protected to the maximum extent allowable by law. No personally identifying information will be reported in any research product, and your computer IP address will not be recorded. Your results will be kept confidential to the trained research staff of this study and will be securely kept for at least three years after the project closes on a password protected computer. Your rights to participate, say no, or withdraw You have the right to say no to participate in the research. You can stop at any time after it has already started. There will be no consequences if you stop and you will not be criticized. You will not lose any benefits that you normally receive. COSTS AND COMPENSATION FOR BEING IN THE STUDY There are no associated costs with participating in this research study. You will be monetarily compensated for your participation in this research, which will be solely handled through the research panel company used, such as Prolific, Qualtrics, or Dynata. The exact amount of money earned will be determined through the research panel company and listed in the recruitment materials of this study. All transactions will occur via the research panel website. Alternative Options You may find alternative research studies through the research panel website. Contact Information If you have concerns or questions about this study, such as scientific issues, how to do any part of it, or to report an injury, please contact the study coordinator, Nikki McClaran (email: mcclaran@msu.edu) or the principle investigator, Nancy Rhodes (email: rhodesn3@msu.edu, phone: 517-353-9909) If you have questions or concerns about your role and rights as a research participant, would like to obtain information or offer input, or would like to register a complaint about this study, you may contact, anonymously if you wish, the Michigan State University’s Human Research Protection Program at 517-355-2180, Fax 517-432-4503, or e-mail irb@msu.edu or regular mail at 4000 Collins Rd, Suite 136, Lansing, MI 48910. Documentation of Informed consent. By choosing "I agree to participate,” you are indicating that you have read this form, are agreeing to participate in this research, and have your answers included in the dataset ( ) I have read the consent form and do not agree to participate [skip logic: skip to end of survey if selected] ( ) I have read the consent form and agree to participate 104 [Q2] How many days during an average week do you watch TV, including live and time-shifted programming, such as streaming? Exclude news, sports watching, and non-fiction programming, such as documentaries. ( ) 0 days [skip to end of survey] ( ) 1 day ( ) 2 days ( ) 3 days ( ) 4 days ( ) 5 days ( ) 6 days ( ) 7 days [Q3] First, we want to get an understanding of you as a person. You will be asked a set of questions that will refer to your daily routine and health behaviors (2 out of 10 behaviors will be randomly asked about). [Q4] Please complete the following statement: Stretching for at least 5 minutes a day is _____. Bad ( ) ( ) ( ) ( ) ( ) ( ) ( ) Good Not at all important ( ) ( ) ( ) ( ) ( ) ( ) ( ) Important Harmful ( ) ( ) ( ) ( ) ( ) ( ) ( ) Beneficial Foolish ( ) ( ) ( ) ( ) ( ) ( ) ( ) Wise Not fun ( ) ( ) ( ) ( ) ( ) ( ) ( ) Fun Boring ( ) ( ) ( ) ( ) ( ) ( ) ( ) Fun Impossible ( ) ( ) ( ) ( ) ( ) ( ) ( ) Possible [Q5] Please complete the following statement: Eating meat everyday is _____. Bad ( ) ( ) ( ) ( ) ( ) ( ) ( ) Good Not at all important ( ) ( ) ( ) ( ) ( ) ( ) ( ) Important Harmful ( ) ( ) ( ) ( ) ( ) ( ) ( ) Beneficial Foolish ( ) ( ) ( ) ( ) ( ) ( ) ( ) Wise Not fun ( ) ( ) ( ) ( ) ( ) ( ) ( ) Fun Boring ( ) ( ) ( ) ( ) ( ) ( ) ( ) Fun Impossible ( ) ( ) ( ) ( ) ( ) ( ) ( ) Possible [Q6] In the past week, how many days did you: 0 1 2 3 4 5 6 7 Stretch for at least 4 () () () () () () () () minutes Eat meat () () () () () () () () Choose “2” option [Q6] Please complete the following sentence: My _____ approve(s) of me to stretch for at least 5 minutes a day. 105 Note: If you do not have a person in a category asked about, please think about a person(s) who'd most fulfill that role in your life. Strongly Disagre Somewhat Neither Some Agree Strongl disagree e disagree agree nor what y agree disagree agree d Doctor () () () () () () () Family () () () () () () () Friends () () () () () () () Significant other () () () () () () () [Q7] Please complete the following sentence: My _____ approve(s) of me eating meat daily. Note: If you do not have a person in a category asked about, please think about a person(s) who'd most fulfill that role in your life. Strongly Disagre Somewhat Neither Some Agree Strongl disagree e disagree agree nor what y agree disagree agree d Doctor () () () () () () () Family () () () () () () () Friends () () () () () () () Significant other () () () () () () () [Q8] Please complete the following sentence: Most other people like me ____ daily. Strongly Disagre Somewhat Neither Some Agree Strongl disagree e disagree agree nor what y agree disagree agree d Stretch at least 5 () () () () () () () minutes Eat meat () () () () () () () [Q9] On a typical day during the week (Monday-Thursday), how many hours do you watch fictional TV, including live-broadcast and streaming? ( ) 0 hours ( ) 1 hour ( ) 2 hours ( ) 3 hours ( ) 4 hours ( ) 5 hours ( ) 6+ hours 106 [Q9] On a typical day during the weekend (Friday-Sunday), how many hours do you watch fictional TV, including live-broadcast and streaming? ( ) 0 hours ( ) 1 hour ( ) 2 hours ( ) 3 hours ( ) 4 hours ( ) 5 hours ( ) 6+ hours [Q10] During an average week, how often do you watch episodes from the following genres? Example shows are provided below to help distinguish the genres, but this list is not complete. Animated Comedies: BoJack Horseman and South Park Animated Dramas: Castlevania and Justice League Comedies: The Big Bang Theory and Schitt's Creek Crime Comedies: Brooklyn-Nine-Nine and Psych Crime Dramas: Law & Order and NCIS General Drama: This is Us and Euporia Historical Fiction: Queen's Gambit and Peaky Blinders Medical Comedies: Scrubs and Royal Pains Medical Dramas: Grey's Anatomy and Chicago Med Science-Fiction/Fantasy: Stranger Things and Wanda Vision Never Rarely Occassio Someti Frequ Oft Alot naly mes ently en Animated comedies () () () () () () () Animated dramas () () () () () () () Comedies () () () () () () () Crime comedies () () () () () () () Crime dramas () () () () () () () General dramas () () () () () () () Historical fiction () () () () () () () Medical comedies () () () () () () () Medical dramas () () () () () () () Sci-fi/Fantasy () () () () () () () [Q11] On the next screen, you will be asked to watch a storyboard mock-up of an episode from the historical fiction TV show, Lightstone. You are being asked to watch this episode to pilot test its cohesiveness, clarity, and characterization. Pay attention to the dialogue as the images are only meant to assist in comprehension. Before moving on, please make sure your computer sound is working and that you will be free from distractions for at least 5 minutes. Do not speed up the video. Failure to watch the video and recall information from it may result in a loss of compensation. [Q11b] On the next screen, you will be asked to watch a storyboard mock-up of an episode from the science-fiction/fantasy TV show, Lightstone. 107 You are being asked to watch this episode to pilot test its cohesiveness, clarity, and characterization. Pay attention to the dialogue as the images are only meant to assist in comprehension. Before moving on, please make sure your computer sound is working and that you will be free from distractions for at least 5 minutes. Do not speed up the video. Failure to watch the video and recall information from it may result in a loss of compensation. [Q12] Please indicate your level of (dis)agreement to the following statements. Strongly Disagre Somewhat Neither Some Agree Strongl disagree e disagree agree nor what y agree disagree agree d The content of the episode felt appropriate for the () () () () () () () genre I was surprised about the content presented in the () () () () () () () episode The content was what I expected () () () () () () () from the genre [Q13] The TV episode I watched was intended... Not to entertain ( ) ( ) ( ) ( ) ( ) ( ) ( ) To entertain Not to educate ( ) ( ) ( ) ( ) ( ) ( ) ( ) To educate Not to persuade ( ) ( ) ( ) ( ) ( ) ( ) ( ) To persuade [Q14] Please indicate your level of (dis)agreement to the following statements. Strongly Disagre Somewhat Neither Some Agree Strongl disagree e disagree agree nor what y agree disagree agree d The episode was very objective () () () () () () () The episode tried to pressure me to () () () () () () () think a certain way 108 The episode did not try to force its () () () () () () () opinion on me The episode was () () () () () () () very believable [Q15] Please indicate your level of (dis)agreement to the following statements. Strongly Disagre Somewhat Neither Some Agree Strongl disagree e disagree agree nor what y agree disagree agree d The episode was very credible () () () () () () () The episode tried to manipulate me () () () () () () () Sometimes I wanted to “argue back” against what () () () () () () () I watched I found myself thinking off ways I disagree with the () () () () () () () content in the episode [Q16] Please indicate your level of (dis)agreement to the following statements. Strongly Disagre Somewhat Neither Some Agree Strongl disagree e disagree agree nor what y agree disagree agree d I couldn't help thinking about ways that the content in the () () () () () () () episode was inaccurate or misleading I found myself looking for flaws in the way content () () () () () () () was presented in the episode 109 I felt like the episode was trying () () () () () () () to persuade me [Q17] Please indicate your level of (dis)agreement to the following statements. Strongly Disagre Somewhat Neither Some Agree Strongl disagree e disagree agree nor what y agree disagree agree d I felt angry while watching the () () () () () () () episode I felt happy while watching the () () () () () () () episode [Q18] Please indicate your level of (dis)agreement to the following statements. Strongly Disagre Somewhat Neither Some Agree Strongl disagree e disagree agree nor what y agree disagree agree d I was mentally involved in the () () () () () () () episode while watching it While watching the episode, I could easily picture the () () () () () () () events taking place I could easily picture myself in () () () () () () () the scenes of the episode described I found my mind wandering while () () () () () () () watching the episode 110 [Q19] Please indicate your level of (dis)agreement with the following statements regarding the Captain Strongly Disagre Somewhat Neither Some Agree Strongl disagree e disagree agree nor what y agree disagree agree d I tend to understand the reasons why the () () () () () () () Captain did what he did I am similar to what I think the () () () () () () () Captain represents I think I have a good () () () () () () () understanding of the Captain The image I have of the Captain () () () () () () () overlaps with my self image [Q19] Please indicate your level of (dis)agreement with the following statements regarding the Doctor Strongly Disagre Somewhat Neither Some Agree Strongl disagree e disagree agree nor what y agree disagree agree d I tend to understand the reasons why the () () () () () () () Doctor did what he did I am similar to what I think the () () () () () () () Doctor represents I think I have a good () () () () () () () understanding of the Doctor The image I have of the Doctor () () () () () () () overlaps with my self image 111 [Q20] Please complete the following statement: Stretching for at least 5 minutes a day is _____. Bad ( ) ( ) ( ) ( ) ( ) ( ) ( ) Good Not at all important ( ) ( ) ( ) ( ) ( ) ( ) ( ) Important Harmful ( ) ( ) ( ) ( ) ( ) ( ) ( ) Beneficial Foolish ( ) ( ) ( ) ( ) ( ) ( ) ( ) Wise Not fun ( ) ( ) ( ) ( ) ( ) ( ) ( ) Fun Boring ( ) ( ) ( ) ( ) ( ) ( ) ( ) Fun Impossible ( ) ( ) ( ) ( ) ( ) ( ) ( ) Possible [Q21] Please complete the following sentence: My _____ approve(s) of me stretching for at least 5 minutes a day. Note: If you do not have a person in a category asked about, please think about a person(s) who'd most fulfill that role in your life. Strongly Disagre Somewhat Neither Some Agree Strongl disagree e disagree agree nor what y agree disagree agree d Doctor () () () () () () () Family () () () () () () () Friends () () () () () () () Significant other Select “disagree” () () () () () () () option [Q22] Please complete the following sentence: Most other people like me ____ daily. Strongly Disagre Somewhat Neither Some Agree Strongl disagree e disagree agree nor what y agree disagree agree d Stretch at least 5 () () () () () () () minutes [Q23] In the next week, how many days will you: 0 1 2 3 4 5 6 7 Stretch for at least 5 () () () () () () () () minutes [Q24] The episode that I watched was… Strongly Disagr Somew Neither Som Agree Stro Stron disagree ee hat agree ewh ngly gly nor at 112 disagre disagre agre agr disag e ed e ee ree Fun () () () () () () () () A good time () () () () () () () () Entertaining () () () () () () () () Moving () () () () () () () () Meaningful () () () () () () () () Thought-provoking () () () () () () () () [Q25] Please indicate your level of (dis)agreement with the following statements. Strongly Disagre Somewhat Neither Some Agree Strongl disagree e disagree agree nor what y agree disagree agree d A lot of the information presented in the () () () () () () () episode I watched was new to me Overall, I found the language used in the episode to () () () () () () () be difficult to understand It was easy for me to provide my opinions when () () () () () () () thinking about the episode [Q26] Please indicate your level of (dis)agreement with the following statements. Strongly Disagre Somewhat Neither Some Agree Strongl disagree e disagree agree nor what y agree disagree agree d I enjoy learning about health () () () () () () () I enjoy talking about health with () () () () () () () others I often seek out health information () () () () () () () I find health () () () () () () () interesting 113 [Q27] Was there background music in the episode you watched? ( ) Yes ( ) No ( ) I can’t recall [Q28] What was the genre of the episode you watched? ( ) Historical fiction ( ) Science fiction/fantasy ( ) Medical comedy ( ) Medical drama [Q29] What health behavior was discussed in the episode you watched? ( ) Eating less meat ( ) Stretching daily ( ) Flossing teeth ( ) Drinking alcohol [Q30] How familiar are you with the show, Firefly (2002)? Very unfamiliar ( ) ( ) ( ) ( ) ( ) ( ) ( ) Very familiar [Q31] What is your birth year? ________ [Q32] What gender do you identify as? ( ) Male ( ) Female ( ) Non-binary/other gender ( ) Prefer not to say [Q33] How do you identify regarding race and ethnicity? Select all that apply. ( ) White or Caucasian ( ) Black or African-American ( ) Asian ( ) Native American or Alaska Native ( ) Native Hawaiian or Pacific Islander ( ) Other: ___________ [Q34] In which state do you currently reside? _______ [Q35] What is the highest level of school you have completed or the highest degree you have received? 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