An Application of the Societal Risk Reduction Motiv

Home , Influence of mass media

Media Use and Willingness to Engage in Activism Against Sexual Harassment: An

Application of the Societal Risk Reduction Motivation Model

Thesis

Presented in Partial Fulfillment of the Requirements for the Degree Master of Arts in the

Graduate School of The Ohio State University

Dinah Adams

Graduate Program in Communication

The Ohio State University

2018

Thesis Committee

Hyunyi Cho, Advisor

Siyue Li

Copyrighted by

Dinah Adams

2018

Abstract

This paper seeks to examine the relationship between media selection and use, societal risk perceptions, and actions taken to reduce societal risks. Through the lens of the

Societal Risk Reduction Motivation Model (SRRM), the introduction of social media use as a predictor of societal risk perceptions is examined. A cross-sectional survey of 277 women sought to examine the influence of both mass media and social media use, cognitive and emotional involvement, and efficacy beliefs on perceptions of and behavioral responses to the issue of sexual harassment. Furthermore, the relationship between online and offline societal risk reduction actions is examined in the context of the social movement #MeToo. Findings and implications for future research are discussed.

Dedication

This thesis is dedicated to all the individuals who have come forward to share their experiences of assault and harassment.

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Acknowledgments

I would like to express my sincere gratitude to my advisor, Dr. Hyunyi Cho, for her assistance and support through my Master’s degree. Her expertise was invaluable, and provided me with crucial guidance as I completed this thesis.

I would also like to thank Dr. Siyue Li for her insights and helpful comments as a member of my thesis committee.

Finally, I am grateful to the faculty and students in the School of Communication.

Their support and influence have afforded me countless opportunities to grow, not only as an academic, but also as an individual.

Vita

2015……………………………………….B.S. Psychology, Heidelberg University

2016 to present…………………………….Graduate Teaching Associate, School of

Communication, The Ohio State University

Publications

Fields of Study

Major Field: Communication

Table of Contents

Abstract ...... ii Dedication ...... iii Acknowledgments...... iv Vita ...... v List of Tables ...... vii List of Figures ...... viii Chapter 1. Introduction ...... 1 Chapter 2. Theoretical Framework ...... 4 Overview ...... 4 Media Exposure: Mass Media and Social Media ...... 5 Social Media and Societal Risk Reduction Action ...... 8 Mediators, Moderators, and Outcomes ...... 11 Chapter 3. Method ...... 23 Participants...... 23 Materials and Procedure...... 23 Chapter 4. Results ...... 33 Chapter 5. Discussion ...... 42 Implications...... 49 Limitations and Future Directions ...... 52 References……...... 56 Appendix A. Tables…………..………………………………………………………….73 Appendix B. Figures……………………………………………………………………..80 Appendix C. Construct Measures………………………………………………………..81

List of Tables

Table 1. Sample Characteristics………………………………………………………….73 Table 2. Moderated Serial Mediation (Facebook)…….…………………………………76 Table 3. Moderated Serial Mediation (Twitter)………………………………………….78

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List of Figures

Figure 1. Proposed Pathway Model……………………………………………………...80

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Chapter 1. Introduction

Increasing numbers of individuals participate in, and receive information from, online social networks. According to the Pew Research Center, as of 2016, 57% of

Americans got their news from television, 25% from radio, and 20% from print newspapers (Mitchell, Gottfried, Barthel, & Shearer, 2016). While television remains a popular news source, particularly among older adults, print media use has steadily fallen.

The decrease in print news consumption is contradicted by an increase in the number of

Americans who report getting their news online, with 81% sourcing news from online platforms (Mitchell, Gottfried, Barthel, & Shearer, 2016), and 67% of Americans getting their news on social media (Shearer & Gottfried, 2017).

In recent years, social media has also provided a platform for users to share their own messages. Viral hashtags and social media posts have been used to raise awareness of societal risk issues, such as the #MeToo and #YesAllWomen movements, which were used to bring awareness to the issues of sexual assault and harassment. While reports on sexual harassment scandals have been broken by traditional news outlets (such as The

New York Times coverage of allegations against Harvey Weinstein) discussions of sexual harassment have taken on new life online (Kantor & Twohey, 2017). Online movements to combat harassment have spread—as of November 2017, at least 1 in 5 Americans reported knowing someone who had used #MeToo on social media (Grinberg & Agiesta,

2017). This demonstrates that social media not only serves as a source of information, but also as a platform for users to participate in discourse about important risk issues.

The Societal Risk Reduction Motivation model (SRRM) (Cho & Kuang, 2015) argues that media exposure influences societal risk perceptions, which in turn influence the actions taken to address those risks at a societal level. The relationship between societal risk perceptions and societal risk reduction actions is mediated by involvement

(both cognitive and emotional) and moderated by efficacy beliefs (which encompass action, institutional, self, and collective efficacy). Depending upon the interplay of those factors, the societal risk reduction actions that are undertaken may be adaptive or maladaptive.

The SRRM has focused on mass media’s influence on societal risk perceptions and subsequent societal risk reduction actions. Now, examining the influence of social media is a crucial next step in understanding why and how individuals engage with societal risk issues and take action to reduce societal risks. The SRRM provides an empirically supported framework for understanding how media exposure influences risk perceptions at the societal level. Although Cho & Kuang (2015) suggest that social media may foster societal risk perceptions and influence societal risk reduction actions, to my knowledge these relationships have not been examined empirically.

This paper contributes to the existing literature by A) extending the application of the SRRM to social media, and by B) expanding the scope of its relevance to a variety of societal risk topics. Using the SRRM to understand the influence of media use on societal risk reduction behaviors is important for multiple reasons. First, it is important to identify

2 differential effects between mass media and social media on audiences’ societal risk perceptions, and whether those lead to online or offline societal risk reduction actions.

Furthermore, the SRRM’s societal risk reduction actions parallel the literature on social activism. To my knowledge, little research has examined the relationship between media consumption and social activism, whether online or offline. Additionally, scholars have lodged criticism against online activism behaviors (Gladwell, 2010) with seemingly little theoretical justification for those criticisms.

Not only will this examination shed light on how individuals perceive societal risk information, but also on how they respond to it. Examining social activism through the

SRRM framework will elucidate the relationships between media use and social activism, serving to bridge the gaps within and between these bodies of research. A model delineating these pathways can be found in Figure 1. This study seeks to examine societal risk perceptions of (and risk reduction actions taken to mitigate) sexual harassment. By doing so, this paper will expand both the application and scope of the SRRM.

Chapter 2. Theoretical Framework

Overview

The Societal Risk Reduction Motivation Model (SRRM) seeks to explain what factors motivate individuals to act against societal risks, identify the factors which mediate and moderate those relationships, and predict how individual actions for collective change may occur (Cho & Kuang, 2015). Within the SRRM, the integration of media effects theories suggests that media influence risk perceptions at the societal level.

In turn, societal risk perceptions influence how individuals act to reduce those risks.

Risk perceptions encompass an individual’s subjective assessment of the probability of a specified type of incident, and their personal concern with the potential consequences (Sjoberg, Moen, & Rundmo, 2004). Social groups construct reality through communication, interaction, and shared memory (Moscivici, 1984). Risk perceptions are created through the psychological, social, organizational, and cultural processes of individuals and groups (Kasperson, Kasperson, Pidgeon, & Slovic, 2003). Such perceptions extend beyond just the threat of individualized physical harm, or of fatality related to a risk, and are influenced by beliefs, attitudes, judgments and feelings

(Pidgeon, Hood, Jones, Turner, & Gibson, 1992).

This model differentiates societal risk perceptions from personal risk perceptions by adopting key features of mass communication theories. Beginning with agenda setting

4 theory, existing research suggests that media coverage demonstrates to audiences which issues are societally important (McCombs & Shaw, 1972). Furthermore, Gerbner and

Gross’s cultivation theory (1976) suggests media content informs individuals’ perceptions of the world to such an extent that their beliefs about the world become consistent with those media portrayals.

The SRRM also integrates the impersonal impact hypothesis which proposes that risk perceptions exist at both individual and societal levels (Tyler & Cook, 1984).

Furthermore, individuals believe that others are more likely to be affected by societal- level risks (Tyler & Cook, 1984; Coleman, 1993; Morton & Duck, 2001). By integrating core components of these theories, the SRRM suggests that the mass media are a crucial influence on societal risk perceptions. As Cho and Kuang posit, “societal risks are likely to be a product of the conflicts, negotiations, decisions, and actions of individuals, groups, and institutions and the interactions between and among them.” (2015; p. 120).

Therefore, in order to mobilize risk reduction actions, publics must be motivated by their societal risk perceptions. The SRRM draws upon this conceptualization of risk as a societal, rather than individual, issue to create a more formalized definition of societal risk perceptions.

Media Exposure: Mass Media and Social Media

Societies use communication practices to create a shared sense of the world around them; the channels through which information is shared can profoundly influence individuals’ perceptions of the world. Messages distributed through mass media channels can shape risk perceptions at both the personal (Brown & Basil, 1995) and societal (So,

Cho, & Lee, 2011) levels. Neither cultivation theory nor agenda setting theory directly address the media’s role in fostering societal risk perceptions. Reflecting the impersonal impact hypothesis, audiences may perceive those risks as affecting only others within society. This is not to suggest that it is impossible for mass media messages to influence personal risk perceptions; however, mass media messages may have differential impacts on audiences’ societal-level risk perceptions.

By their very nature, societal risks are those that affect large segments of society.

Mass media messages may be more effective in influencing individual’s perceptions of risks facing society at large. This suggests that media consumption not only informs audiences of what issues are important, but also leads audiences to adopt beliefs that are consistent with media representations of those issues. As sexual harassment has received coverage and generated conversation on many media channels, audiences’ consumption of mass media may inform their understanding of the topic of sexual harassment, and can lead to increased perceptions of that risk’s impact on society overall. As individuals consume media through television, newspapers, magazines, radio (through both offline and online formats), understanding the breadth of mass media channels through which individuals encounter risk information is important. From this, the following hypothesis is proposed:

H1: Mass media use related to sexual harassment will be associated with societal sexual harassment risk perceptions.

In its current form, the SRRM does not account for the influences that social media may have on societal risk perceptions. Like mass media, social media can be used

6 to disseminate risk information to a wide range of social contacts. Unlike mass media, social media allow users to construct profiles, connect with other users, and view their network’s connections with other users (boyd & Ellison, 2008). Notably, social media enables connections between users with “weak” offline connections (Haythornthwaite,

2002; Grabowicz, Ramasco, Moro, Pujol, & Eguiluz, 2012). Social media can serve as a conduit for risk information, even in contexts when face-to-face communication would be inconvenient or impossible (Rimal, Chung, & Dhungana, 2015). Experienced social media users seek out and share information with one another via those social networks

(Lee & Ma, 2011), rather than relying on centralized mass media channels (Lachlan,

Spence, & Lin, 2014; Gil de Zúñiga, Diehl, Huber, & Liu, 2017). Therefore, it is important to examine whether a relationship exists between individuals’ social media use and societal risk perceptions.

Social media may serve as a means through which to share information about risks that affect society, and therefore influence societal risk perceptions. However, this relationship has not been examined to my knowledge. These effects are especially pertinent as individuals can create their own social realities and share information about risks (even when mass media information is inaccessible, or is perceived as inadequate).

Social media may serve as a source of societal risk information, and may therefore shape audiences’ societal risk perceptions. From this, the following hypothesis is proposed:

H2: Social media use related to sexual harassment will be associated with societal sexual harassment risk perceptions.

Social Media and Societal Risk Reduction Action

According to the SRRM, concerted action must be taken to reduce societal risks.

This is accomplished by exerting pressure on upstream societal institutions (such as social, political, or economic systems) that that may more directly influence the severity of the societal risk. The SRRM seeks to look past individual risk behaviors and examine the societal-level contexts of risk and the societal actions taken to address those contexts

(Cho & Kuang, 2015). Societal risk reduction actions are undertaken by individuals as part of a collective to create societal change; therefore, they are a key component of this model.

Social media may enable societal risk reduction actions. Because social media allow users to create, edit, and share content, they enable the distribution of information between individual users and across space and time (Deibert, 2000). Furthermore, the accessibility of social media blurs the lines between private and public content (Bimber et al., 2005), provides a platform for online deliberation (Halpern & Gibbs, 2013), and overall creates a “public sphere” between social media users (Zheng & Wu, 2005). This ease and accessibility of access can empower users to share information, express opinions, or mobilize action to reduce societal risks using the affordances of social networking sites.

This is especially important because social media, and the affordances they provide, are influenced by the societal contexts in which they are situated and are assigned value according to the human agency that they enable (van Dijk, Berinds,

Jelinek, Romme, & Weggeman, 2011). To quote Zheng and Yu (2016), “technologies

8 thus always operate in the presence of other technologies, human actors, and other social, institutional, cultural elements, namely, a sociocultural assemblage” (p. 309). Social media can provide an accessible space for connection and engagement that is linked to the social, institutional, and political processes. These functions have been credited with lowering thresholds for civic participation (Postmes & Brunsting, 2002; Zheng & Yu,

2016). The affordances that social media enable reflect some essential components of social movements, which require institutional arrangement, resource mobilization, and mobilizing structures (McAdam et al., 1996, McAdam & Scott, 2005).

Social media and information technologies have been used for social activism in contexts ranging from political campaign promotion (Wills & Reeves, 2009) to opinion- sharing and community-building in South Africa (Steenkamp & Hyde-Clarke, 2012), and have played an organizing role in creating mediated emotional responses to political events and accelerating the formation of social movements (Castells, 2012). Information technologies have been demonstrated to “penetrate organizational boundaries and promote, impede, or influence social and political change” (Prince, Barrett, & Oborn,

2014). Online activism can serve to mobilize and organize social movements (Postmes &

Brunsting, 2002).

While significant criticisms of online activism exist, there is a paucity of research specifying what activism behaviors individuals tend to engage in; and furthermore, whether particular groups of people favor specific activism behaviors. Extant research on online activism has focused on organized activist movements. However, it is important to understand how individuals use social media to reduce societal risks. Social media may

9 be used to acquire risk-related information when mass media is viewed as an insufficient information source (Sutton, Palen, & Shklovski, 2008; Shklovski, Palen, & Sutton, 2008).

Social media may also be used to share risk information by reproducing information from mass media (Starbird, Palen, Hughes, & Vieweg, 2010), translating it to layperson’s terms (Stephens & Malone, 2009), or simply by disseminating individualized, citizen- generated information (Shklovski et al., 2008). Furthermore, the interactivity of social media may amplify individuals’ perceptions of risk, and thereby influence their subsequent behavioral responses (Rains, Brunner, and Oman, 2015).

Extant research on social movements tends to focus on social media’s uses for information sharing. Social media has been demonstrated as a powerful platform for sharing individual experiences and narrative, and can be used for strategic persuasive outcomes (Zhang & Lin, 2018). Furthermore, narratives shared within larger social movements tend to be context-specific, such as social media activism during the Arab

Spring uprisings (Knox, 2015) or #myNYPD (Jackson & Foucalt Welles, 2015). This disparity in the research is surprising, as individual narratives are powerful persuasive tools, and social media provide a platform for sharing those narratives. Therefore, understanding how individuals enact activism behaviors in the context of sexual harassment, is an important step in understand the role of social media in this movement, as well as understanding its impacts on offline behavior.

The influence of social media use on societal risk reduction actions should be examined in greater detail. On social media individuals can interact with, and react to, information shared within their online social networks (Dutta-Bergman, 2004; Alexander,

2014). Social media use may provide additional insights and opportunities to engage with risk information, and therefore influence the behavioral strategies that individuals undertake to reduce risk at the societal level. Examining this phenomenon through the lens of the societal risk reduction motivation model provides significant insights into social media’s effects on societal risk reduction actions. From this, the following hypothesis is proposed:

H3: Societal sexual harassment risk perceptions will be associated with online societal risk reduction actions.

Mediators, Moderators, and Outcomes

After accounting for the mediating influence of involvement and the moderating influence of efficacy beliefs on risk reduction strategies, the SRRM posits that societal risk reduction actions may be adaptive or maladaptive (Cho & Kuang, 2015).

Maladaptive actions are proposed to occur when individuals experience high involvement but low efficacy—in response to societal risk, maladaptive responses may encompass disenfranchisement from processes of change through inaction or fatalism, or even violence (Cho & Kuang, 2015). Adaptive actions are proposed to occur when individuals experience high involvement and high efficacy (Cho & Kuang, 2015). Regardless of whether they are adaptive or maladaptive, action outcomes are predicated on involvement, which suggests that audiences must be cognitively or emotionally involved with the societal risk issue in order to adopt strategies to reduce the risk. In this scenario, when individuals experience involvement with the issue and feel that they have the resources to affect change, adaptive actions are likely to occur. Following a discussion of

11 the influences of involvement and efficacy, potential outcomes of societal risk reduction actions (particularly those enacted in online contexts) will be examined in greater detail.

Cognitive Involvement

The first mediating influence proposed by the SRRM is involvement.

Involvement is a critical component of media consumption, and refers to audience activity following media consumption that shows both intellectual and emotional participation in message content. Within the SRRM, involvement can be stratified into two categories: cognitive and emotional. Societal risk issues may generate different involvement responses, which may subsequently result in variations in the actions taken to reduce societal risks.

Cognitive involvement refers to the societal risk issue’s perceived relevance to a person’s values, impressions, or outcomes (Johnson & Eagly, 1989; Cho & Boster,

2005). Value-relevance refers to the issue’s perceived relevance for how indivdiuals conduct themselves (Rokeach, 1968). Outcome-relevance refers to the issue’s perceived relevance for the individual’s goals. Impression-relevance refers to how a risk issue influences the individual’s social self-presentation. Cognitive involvement can vary between risk issues, depending on what the individual deems to be most relevant to a societal risk (Marshall, Reinhart, Feeley, Tutzauer, & Anker, 2008; Cho & Boster, 2005).

Additionally, the type of cognitive involvement with a risk may relate to the individual’s subsequent attitudes and actions. Prior research has found that other-directedness is more closely related to impression-relevant involvement, information seeking behaviors are

12 more closely related to outcome-relevant involvement, and attitude extremity is associated with value-relevant involvement (Cho & Boster, 2005).

These types of cognitive involvement may influence how individuals respond to risk information. For individuals with high cognitive involvement with the issue of sexual harassment, it is important to understand if a specific type of involvement is most salient.

For the purposes of this study, value-relevant and impression-relevant involvement will be examined. Value-relevant involvement is closely tied to strongly held values (Johnson

& Eagly, 1989). Those with high value-relevant involvement tend to report extreme attitudes toward a topic (Cho & Boster, 2005). Furthermore, high value-relevant involvement with an issue has been demonstrated to be a significant predictor of behavior

(specifically, individuals who reported high value-relevant involvement with the issue of organ donation were more likely to become organ donors themselves) (Marshall,

Reinhart, Feeley, Tutzauer, & Anker, 2008). Essentially, individuals who feel strongly about an issue are likely to report high value-relevant involvement and translate that attitude to issue-specific behavior. Applying this to the issue of sexual harassment, those with high value-relevant involvement with the issue of sexual harassment are likely to engage in actions to reduce sexual harassment as a societal risk. From this, the following hypothesis is proposed:

H4: Value relevant involvement will mediate the relationship between societal sexual harassment risk perceptions and online societal sexual harassment risk reduction actions.

Conversely, impression-relevant involvement is other-directed, and is related to an individual’s concern with how others perceive the opinions that they express (Cho &

Boster, 2005). Societal risk perceptions center upon an individual’s perceptions of the issues affecting society. As originally proposed by the SRRM, information on those risks can be gathered from media sources (Cho & Kuang, 2015). As this study proposes, those risk perceptions may also be shaped by social media. Due to the networked nature of social media, individuals may be encountering risk information from network contacts. If social media users perceive others in their network speaking out about a societal risk, they may feel that as a member of that same network, they should adhere to the network’s norms (Spears & Postmes, 2015). As such, individuals may use social media to voice their own opinions.

Impression-relevant involvement may influence actions taken to reduce societal risks, specifically in online contexts. Individuals often use social media for impression management, and to curate impressions of the self which will be interpreted favorably by network members (Dorethy, Fiebert, & Warren, 2014). Social media users who reported high self-efficacy about their own impression management strategies had more curated social media profiles (with greater detail in their public profiles and a more extensive list of network contacts) (Krämer & Winter, 2008; Ranzini & Hoek, 2017). Furthermore, content sharing (which involves making specific choices about the opinions that one expresses on a social networking site) has been identified as an impression management strategy among activist social media users (Dorethy, Fiebert, & Warren, 2014).

Social media users may not only prioritize impression management, but also have the tools with which to curate their self-presentations on social media. This study examines the mediating role that impression-relevant involvement plays between societal risk perceptions and societal risk reduction actions. This mediating relationship of impression-relevant involvement occurs within the context of the SRRM. Applying the

SRRM to online contexts, and therefore examining the mediating influence of impression management, provides insights into the influences of impression-relevant involvement with the issue of sexual harassment and subsequent actions undertaken to reduce that risk.

From this, the following hypothesis is proposed:

H5: Impression relevant involvement will mediate the relationship between societal sexual harassment risk perceptions and online societal sexual harassment risk reduction actions.

Emotional Involvement

Emotional involvement is also a mediating influence between societal risk perceptions and societal risk reduction actions. According to the SRRM, emotional involvement with a societal risk issue encompasses multiple factors, including sympathy or empathy for those impacted by a risk, as well as the discrete emotions associated with it, such as anger and fear. Empathy and sympathy involve concern emotions related to the emotional states of those affected by a risk (Wispe, 1986). Empathy for victims of sexual harassment has been found to be negatively correlated with sexual harassment myth acceptance (Lonsway, Cortina, & Magley, 2008; Diehl, Glaser, & Boehner, 2014) and may increase willingness to address the risk issue (Eisenberg & Miller, 1987).

Furthermore, anger and fear are strong predictors of intention to engage in societal risk reduction actions (Lerner & Keltner, 2000; Becker, Tausch, & Wagner, 2011). Through these processes, emotional responses may serve as a significant mediating influence on the type of societal risk reduction strategy that is adopted.

When accounting for the influence of emotional appraisals on individuals’ risk perceptions, shared online news content may have significant ramifications for societal risk perceptions. Emotionally provocative news content (especially content that elicits anger) tends to increase sharing behaviors among social network users (Hasell & Weeks,

2016). From this data, it can be inferred that individuals who share risk information through social media may not only share more frequently, but also share more emotionally charged content.

Now, social media may provide a conduit for risk information sharing between social network members. As social media capitalize on weak tie connections, users are better able to share the immediate, human impacts of a risk with network contacts with whom they may not interact every day (Veil, Buehner, & Palenchar, 2011). Empirical research has found that use of social networking sites is linked to increased empathy among users (Alloway, Runac, Querski, & Kemp, 2014). By providing a rich source of interpersonal connectedness, individuals may more strongly empathize with those affected by risk events, subsequently leading to stronger emotional reactions. This behavior may therefore influence the emotional responses that audiences have to societal risks.

These findings, when applied to the SRRM, suggest that social media use would likely generate high emotional involvement. While it is possible that emotional involvement with the issue of sexual harassment may influence social media behaviors, this study examines the mediating role that emotional involvement plays within the context of the SRRM. This allows for an examination of the pathways within the model, between societal risk perceptions and societal risk reduction actions related to sexual harassment. Discrete emotional responses toward the issue of sexual harassment, as well as empathy toward victims of sexual harassment, likely mediate the relationship between perceptions of sexual harassment as a societal risk and the actions undertaken to reduce that risk. From this, the following hypothesis is proposed:

H6: Emotional involvement will mediate the relationship between societal sexual harassment risk perceptions and online societal risk reduction actions.

Efficacy Beliefs

The SRRM proposes that media use influences risk perceptions at a societal level, which in turn influence societal motivations to address those risks. Before societal risk perceptions translate to societal risk reduction actions, it is important to account for the role that efficacy plays in influencing behavioral responses. Different types of efficacy beliefs can serve as moderators in the relationship between cognitive or emotional involvement and societal risk reduction action (Cho & Kuang, 2015).

Overall, the SRRM posits that four types of efficacy beliefs will moderate the connection between involvement and action: self-efficacy, collective efficacy, institutional efficacy, and action efficacy. Self-efficacy refers to the belief that

17 individuals can enact a course of action (Bandura, 1986). Collective efficacy refers to an individual’s belief that a larger group to which they belong can enact a course of action to reduce societal risk (Bandura, 1986; Bandura, 2004). Institutional efficacy refers to the belief that social institutions are fair, just, uncorrupt, trustworthy, and predictable

(Rothstein, 2003). Action efficacy refers to confidence in the effectiveness and efficiency of an action to reduce societal risk.

In sum, “the relative contribution of these efficacy beliefs toward societal risk control action may be contingent upon the kind of risk reduction action under consideration” (Cho & Kuang, 2015, p. 126). Depending on the type of action required to undertake societal change, types of efficacy beliefs may have differential effects on the strategies individuals use to mitigate risk. Some actions may require more collective efficacy to generate collaborative change, whereas some actions may require more self- efficacy. Those who use social media frequently will likely feel increased self-efficacy, better enabling them to engage in online risk reduction behaviors (Krämer & Winter,

2008). However, to fully understand the moderating influence of efficacy beliefs, all types of efficacy explicated in the SRRM should be examined. From this, the following hypothesis is proposed:

H7: Efficacy beliefs will moderate the relationship between both emotional and cognitive involvement and online societal risk reduction actions.

Societal Risk Reduction Actions

Societal risk reduction actions are contingent upon the complex interplay of antecedent factors. While the ultimate outcome is for media audiences to engage in risk

18 reduction behaviors, societal risk reduction actions may ultimately be adaptive or maladaptive. Whether those behaviors are adaptive or maladaptive is dependent on the interplay of societal risk perceptions, cognitive and emotional involvement, and efficacy beliefs. According to the SRRM, high issue involvement, coupled with high efficacy beliefs, will result in adaptive risk reduction actions. Contrarily, high involvement coupled with low efficacy beliefs, will result in maladaptive risk reduction actions. Both outcomes are predicated on involvement as a necessary component of societal risk reduction actions.

As the media environment evolves, scholars have argued that research should focus not only on whether new media are being used for political participation, but how they are being used (Verba, Schlozman, & Brady, 1995; Delli Carpini, 2004; Bakker & de Vreese, 2011). Della Porta & Diani (1999) argue that social movements involve formal networks with shared beliefs and solidarity, collective action, and use of protest.

When examining modern activism, Mertes (2004) argues that researchers need to emphasize regional, national, and international coalition building through a “movement of movements” because many individual groups lack a shared identity and vision that constitutes a distinct movement. By providing accessible, connective platforms for individuals to share information and perspectives, social networking sites are likely the next step for building such movements. As such, traditional evaluations of participation may no longer capture the full scope of participation behaviors (Grabe & Myrick, 2016).

With social media as a conduit for weak tie network connections, it is important to understand the influence of new media on societal risk response actions.

Both individuals and organizations have used online activism strategies to generate social change. Current literature on political participation and social activism addresses community responses to perceived societal risks. In these contexts, activism is described as “action on behalf of a cause that goes beyond what is conventional or routine” (Martin, 2007). However, some consider social media sites to be platforms for

“slacktivism” --an impulsive, noncommittal, and easily replicated decision to engage with a political object in an online context, without requiring advanced knowledge of political participation or organizational affiliation (Halupka, 2014; Rotman et al., 2011). A central criticism of “slacktivism” is that it provides more benefit to the individual performing the action than to the cause itself, and is therefore a selfish behavior (Gladwell, 2010; Karpf,

2010). The accessibility and amateur nature of these behaviors are, arguably, what devalues this form of political participation, particularly on social media (Lewis, Gray, &

Meihrenreich, 2014). Most importantly, critics argue that the ease of online activism may discourage individuals from engaging in more effective offline activism behaviors, such as attending protests (Van Laer, 2010).

Contrary to criticisms of online activism, a growing body of research defends the use of social media and online platforms as a means of inciting societal change. For example, social networking sites such as Facebook and Twitter are credited with the providing platforms for activists to share information about social protests (Shirky, 2011;

Tufekci & Wilson, 2012; Vaccari et al., 2015; Valenzuela, 2013; Van Laer, 2010).

Furthermore, signing an online petition may not be substantially different from sharing photocopied petitions for offline campaigns (Halupka, 2014; Rotman et al., 2011).

Additionally, recent research has found that participating in political exchanges online may increase individuals’ beliefs in their own efficacy, which then leads to offline participation (Vaccari et al., 2015).

These findings mirror the SRRM’s proposition high issue involvement coupled with high efficacy leads to adaptive societal risk reduction actions. While the SRRM does not directly encompass activist behaviors, activism’s relevance to this model is noteworthy. Slacktivism intended to reduce societal risk. may not necessarily be considered maladaptive, because action is being undertaken (although it is not “action” as is typically conceptualized in social movements research). Maladaptive actions are theorized to occur when involvement with an issue is high, but efficacy beliefs are low, and may result in negative responses such as fatalism or inaction (Cho & Salmon, 2006).

Online activism behaviors may not necessarily be negative (Mohlo et al., 2017) or maladaptive (Cho & Kuang, 2015); however, those conclusions are beyond the scope of this study. This study seeks to identify whether online activism behaviors, a form of societal risk reduction, are isolated in the online world (as critics suggest), or whether they also influence offline activism behaviors.

To understand the antecedents and outcomes of online activism, such behaviors may be examined through the lens of the SRRM. Social media has been identified as the platform through which slacktivism most often takes place, as it provides ample opportunities for involvement. However, to my knowledge there is no research which suggests that online activism entirely supplants offline activism; indeed, online actions may have significant ramifications in the real world (such as the consciousness-raising

21 efforts of the #MeToo movement). While the SRRM does not explicitly delineate the applications of these concepts to other fields, theoretical understandings of the antecedents and outcomes of societal risk reduction actions can be applied to other fields of research. As mentioned previously, this does not directly address the SRRM’s propositions about adaptive and maladaptive outcomes. However, understanding the relationship between online and offline societal risk reduction actions is a crucial first step. From this, the following hypothesis is proposed:

H8: Online societal risk reduction actions will be associated with offline societal risk reduction actions.

Chapter 3. Method

Participants.

Participants were recruited for a one-time, cross-sectional survey using Amazon’s

Mechanical Turk. Due to the subject matter of the study, only participants between ages

18 and 65 who self-identified as female were allowed to participate. This is because women sexual harassment at higher frequencies than men; therefore, limiting the participant sample to focus on women provided a clearer picture of the issue of sexual harassment (Graf, 2018). Analyses were conducted on N = 277 complete response sets.

Respondents were predominantly white (70.40%), with an average age of M = 36.39 years (SD = 10.87). All respondents had competed some level of formal schooling

(ranging from high school diploma to doctoral degree), with 47.7% having completed a bachelor’s degree. Additionally, 62.10% of participants were employed at the time of survey completion. Finally, 61.70% of participants reported that they had ever experienced sexual harassment. Additional information can be found in Table 1.

Materials and Procedure.

Overview. Existing recommendations for statistical analysis were used to guide the analysis of this data. For factor analyses, all final measures met or exceeded the recommended Kaiser-Meyer-Olkin value of .60 and reported a significant Bartlett’s test of sphericity (p < .05). Exceptions are noted where applicable. In principal analysis factoring, items with factor cross-loadings exceeding .30 were given additional examination and removed in order to clarify the construct measure. A complete list of construct measures and survey items can be found in Appendix A.

Mass Media Use: Sexual Harassment. To assess the frequency with which individuals engage with media related to sexual harassment on mass media channels, participants reported how frequently they watched, heard, or read news specifically related to sexual harassment on a variety of media sources in the past 6 months (adapted from Gil de Zúñiga, Jung, & Valenzuela (2012). This 6-month window was chosen because it encapsulates recent media coverage of harassment allegations against public figures, as well as commentary on the issue of sexual harassment (Grinberg & Agiesta,

2017; Kantor & Twohey, 2017). For the purposes of this survey, mass media sources were operationalized as broadcast TV network news, local TV news, cable TV news, radio, local and national print newspapers, local and national online newspapers, magazines (print and online), as well as online news sites generated by regular people.

Items were measured on a Likert-style scale ranging from (1) never to (7) always. The offline media use items were broken into a separate subscale, (α = .816) and focused on exposure to content on broadcast TV network news, local TV news, and cable TV news.

These items were averaged together to create a scale in which higher responses indicate greater frequency of exposure to offline content related to sexual harassment (M = 3.33,

SD = 1.55). The online media use items were broken into a separate subscale (α = .807) and focused on exposure to content on online national newspaper, online local newspapers, online magazines, and news sites generated by regular people. These items were averaged together to create a scale in which higher scores indicate greater frequency of exposure to online content related to sexual harassment (M = 2.95, SD = 1.36).

Social Media Use: Sexual Harassment. Participants who reported some use on a social networking site (Facebook, Twitter, Instagram, Reddit, and Tumblr) were asked to report how often in the past 6 months they had read content specifically related to sexual harassment on each social networking site (adapted from Gil de Zúñiga, Jung, &

Valenzuela, 2012). This 6-month window was chosen because it encapsulates recent media coverage of harassment allegations against public figures, as well as commentary on the issue of sexual harassment (Grinberg & Agiesta, 2017; Kantor & Twohey, 2017).

Responses were measured on a seven-point Likert style scale ranging from (1) never to

(7) always. An initial factor analysis revealed that social media use related to sexual harassment on Facebook and Twitter emerged on one factor, whereas social media use related to sexual harassment on Instagram, Reddit, and Tumblr emerged on another factor. However, reliability analyses run for these separate factors revealed Cronbach’s alphas of .561 and .508, respectively. In order to further examine construct reliability, all variables were run together, which revealed Cronbach’s alpha of .581. However, analyses revealed that reliability would be improved if the item evaluating social media use related to sexual harassment on Reddit were dropped. Following this recommendation, the final

Kaiser-Meter-Olkin value was .548, with a significant Bartlett’s test of sphericity (χ2(6),

24.15, p < .01), lower than the recommended value of .60. Ultimately, these items were evaluated separately. As such, for each measure higher responses indicate greater frequency of encountering content related to sexual harassment on Facebook (M = 3.45,

SD = 1.14), Twitter (M = 3.28, SD = 1.53), Instagram (M = 2.02, SD = 1.26), Reddit (M

= 2.71, SD = 1.65), and Tumblr (M = 2.42, SD = 1.36).

Societal Sexual Harassment Risk Perceptions. Participants reported the extent to which they believe that sexual harassment is “a serious problem in the United States” and

“a serious social problem in the United States” (adapted from Tyler & Cook (1984)).

Responses were measured on a seven-point Likert style scale ranging from (1) strongly disagree to (7) strongly agree. These items were averaged to create a scale in which higher responses indicate higher perceptions of sexual harassment as a societal risk issue

(M = 5.86, SD = 1.24, α = .956).

Emotional Involvement. Participants reported the extent to which they experience specific discrete emotions in response to sexual harassment. Items were preceded by the statement “How much does sexual harassment make you feel ____?” followed by answer options reflecting the emotional responses of anger, fear, sadness, and disgust. Reponses were measured on a five-point scale ranging from (1) not at all to (5) very much. An initial factor analysis was conducted, separating items into four factors. The initial

Kaiser-Meyer Olkin value was .878, with a significant Bartlett’s test of sphericity

(χ2(78), 2102.81, p < .01), higher than the recommended value of .6. Following further analysis, items corresponding to factors three and four were removed due to high cross- loadings. An additional principal factor analysis revealed a Kaiser-Meyer-Olkin value of

.803, with a significant Bartlett’s test of sphericity (χ2(28), 1292.83, p < .01). The first factor focused on the emotion of fear (specifically, scared, afraid, and fearful). These items were averaged to create a scale in which higher responses indicate stronger emotional responses of fear (α = .949, M = 2.59, SD = 1.33). The second factor included items related to anger (specifically, angry, irritated, aggravated, outraged), as well as one

26 item representative of the emotion of disgust, which was likely interpreted as anger.

These items were averaged to create a scale in which higher responses indicate stronger emotional responses of anger (α = .801, M = 4.03, SD = 1.13)

Emotional Involvement: Empathy. Participants reported the extent to which they agree or disagree with various statements relating to feelings of empathy for victims of sexual harassment, including items such as “When I think about sexual harassment, I experience the same emotions as the victim” and “I can see the point of view of sexual harassment victims” (adapted from Shen (2010)). Responses will be measured on a

Likert-style scale ranging from (1) strongly disagree to (7) strongly agree. These items were averaged to create a scale in which higher responses indicate higher empathy for victims of sexual harassment (M = 4.99, SD = 1.25 (α = .931).

Value-Relevant Cognitive Involvement. Participants reported the extent to which they agree or disagree various statements related to their value-relevant cognitive involvement, such as “The values that are the most important to me are what determine my stand on sexual harassment” (adapted from Cho & Boster (2005)). Responses were measured on a Likert-style scale ranging from (1) strongly disagree to (7) strongly agree.

These items were averaged to create a scale in which higher responses indicate higher levels of value-relevant cognitive involvement with the issue of sexual harassment (M =

5.06, SD = 1.14, (α = .881).

Impression-Relevant Cognitive Involvement. Participants reported their agreement with statements related to impression-relevant cognitive involvement with the issue of sexual harassment, such as “If I express the right kind of opinion on sexual

27 harassment, people will find me more effective” (adapted from Cho & Boster (2005)).

Reponses were measured on a Likert-style scale ranging from (1) strongly disagree to (7) strongly agree. These items were averaged to create a scale in which higher responses indicate higher levels of impression-relevant cognitive involvement with the issue of sexual harassment (M = 3.83, SD = 1.09, α = .745).

Self-efficacy Beliefs. Participants reported the extent to which they agree or disagree various statements related to their sense of self-efficacy in reducing sexual harassment as a societal risk. Items range from increasing awareness about sexual harassment as a societal issue, changing laws and policies about sexual harassment, and creating change within society about sexual harassment. Reponses were measured on a seven-point Likert style scale ranging from (1) strongly disagree to (7) strongly agree.

These items were averaged to create a scale in which higher responses indicate higher levels of self-efficacy to reduce the societal risk of sexual harassment (M = 4.63, SD =

1.51, α = .947).

Collective Efficacy Beliefs. Participants reported the extent to which they believe that women as a collective can increase awareness about sexual harassment as a societal issue, change laws and policies about sexual harassment, and create change within society about sexual harassment. Reponses were measured on a Likert-style scale ranging from (1) strongly disagree to (7) strongly agree. These items were averaged to create a scale in which higher responses indicate higher levels of self-efficacy to reduce the societal risk of sexual harassment (M = 5.83, SD = 1.05, α = .895).

Institutional Efficacy Beliefs. Participants reported the extent to which they believe that workplaces can reduce sexual harassment as a societal risk. Response items focused on whether participants believe that workplaces can increase awareness about sexual harassment as a societal issue, change laws and policies about sexual harassment, and create change within society about sexual harassment. Additionally, participants reported the extent to which they agree or disagree that workplaces can prevent sexual harassment before it occurs, address sexual harassment after it occurs, assist victims of sexual harassment, and punish perpetrators of sexual harassment. Reponses were measured on a Likert-style scale ranging from (1) strongly disagree to (7) strongly agree.

These items were averaged to create a scale in which higher responses indicate higher perceived levels of institutional efficacy to reduce the societal risk of sexual harassment

(M = 5.95, SD = 0.89, α = .883).

Action Efficacy Beliefs (Online). Participants reported the extent to which they agree or disagree that online behaviors are effective in reducing sexual harassment as a societal risk. with various statements related to their perceptions of action-efficacy in reducing sexual harassment as a societal risk. Relevant action outcomes included increasing awareness about sexual harassment as a societal issue, increasing awareness about sexual harassment a societal issue, and changing laws and policies about sexual harassment. For each of those action outcomes, participants rate the effectiveness of specific behaviors: contacting political leaders and decision makers about sexual harassment online, sharing with connections on social media about sexual harassment, mobilizing others on social media around the issue of sexual harassment, and using

29 online platforms to support offline causes related to sexual harassment. Reponses were measured on a Likert-style scale ranging from (1) not at all effective to (5) very effective.

A principal axis factoring was performed, revealing a Kaiser-Meyer-Olkin value of .912, with a significant Bartlett’s test of sphericity (χ2(66), 2979.08, p < .01). Two factors emerged, with items specifically relating to contacting political leaders and decision makers about sexual harassment emerging on both factors 1 and 2, with high cross- loadings. For this reason, these items were removed from subsequent analyses. From there, a reliability analysis was performed (α = .948). These items were averaged to create a scale in which higher responses indicated greater (M = 3.22, SD = 0.97).

Activism: Sexual Harassment (Online). Participants reported the ways in which they intend to engage in activism behaviors online, specifically related to the issue of sexual harassment. Items included behaviors such as “post a status about sexual harassment”, “sign an online petition about sexual harassment”, and “contact a political leader or decision maker through email or social media, specifically about sexual harassment” (adapted from Dookoo (2015)). Responses were measured on a Likert-style scale ranging from (1) extremely unlikely to (4) extremely likely. These items were averaged to create a scale in which higher responses indicated greater intention to engage in online action to reduce the societal risk of sexual harassment (M = 2.38, SD = 0.81, α

= .962).

Activism: Sexual Harassment (Offline). Participants reported the ways in which they intend to engage in activism behaviors related to sexual harassment offline. Items include behaviors such as “attend an in-person informational session about sexual

30 harassment”, “donate money to support a cause addressing sexual harassment”, and

“create posters or fliers about sexual harassment”. These items were adapted from

Dookhoo (2015) and Corning & Myers (2002) to create a more holistic scale measure for offline activism. Responses were measured on a Likert-style scale ranging from (1) extremely unlikely to (4) extremely likely. Following principal axis factoring, three factors emerged, which were then broken into smaller subscales. The first subscale reflects general offline societal risk reduction actions, including 14 items such as “participate in a boycott related to sexual harassment”, “distribute information offline about the issue of sexual harassment”, and “attend an in-person informational session about the issue of sexual harassment.” These items were averaged to create a scale in which higher responses indicated greater intention to engage in general offline sexual harassment societal risk reduction actions (M = 2.18, SD = 0.88, α = .964). The second subscale reflects interpersonal offline societal risk reduction actions, including 3 items such as

“confront jokes, statements, or innuendoes about sexual harassment”, “try to change a friend’s or acquaintance’s mind about the issue of sexual harassment”, and “try to change a relative’s mind about the issue of sexual harassment.” These items were averaged to create a scale in which higher responses indicated greater intention to engage in interpersonal offline sexual harassment societal risk reduction actions (M = 2.79, SD =

0.93, α = .904). The third subscale reflects active protest societal risk reduction actions, such as “engage in a political activity in which you knew you would be arrested”, “block access to a building or public area with your body”, and “engage in a physical confrontation at a political rally.” These items were averaged to create a scale in which

31 higher responses indicated greater intention to engage in offline active protest societal risk reduction actions (M = 1.54, SD = 0.84, α = .953).

For this study, data was collected through Amazon’s Mechanical Turk (MTurk), which affords a more diverse panel sample than other platforms (Sheehan, 2018).

Following data collection via MTurk, 417 total responses were recorded. Participant recruitment information called for participants who identified as female, between the ages of 18 and 65. Following completion of the screener questions, 310 participants began the survey. Only participants who successfully answered all three attention checks were included in the final data analysis (N = 277).

All analyses were conducted using the Statistical Package for Social Sciences

(SPSS). The PROCESS macro (Hayes, 2012) model 4 was used to assess mediation, model 1 was used to assess moderation, and model 87 was used to assess moderated serial mediation. Analysis of indirect effects in PROCESS begins by estimating multiple regression models. Then, a boot-strapping sampling procedure is used to calculate a bias- corrected 95% confidence interval to assess the significance of indirect effects. For moderated serial mediation, the boot-strapping procedure is used to determine the significance of three indirect effects models (IV on DV through mediator 1, IV on DV through mediator 2, IV on DV through both mediators in serial, and IV on DV with mediators in serial with moderation between mediator 2 and DV).

Chapter 4. Results

Hypothesis 1 (H1) proposed that mass media use related to sexual harassment will be associated with societal sexual harassment risk perceptions. To test this hypothesis, participants were asked how often they encountered content related to sexual harassment on a variety of mass media platforms, both offline and online. As online mass media use related to sexual harassment increased, societal sexual harassment risk perceptions did not increase, β = 0.10, t(275) = 1.62, p = .106, with an R2 of .001. Furthermore, as offline mass media use related to sexual harassment increased, societal sexual harassment risk perceptions did not increase, β = 0.04, t(275) = 0.623, p = .534, with an R2 of .010.

Therefore, Hypothesis 1 was not supported.

Hypothesis 2 (H2) proposed that social media use related to sexual harassment will be associated with societal sexual harassment risk perceptions. To test this hypothesis, participants were asked how often they encountered content related to sexual harassment on social media. Exposure to content related to sexual harassment was evaluated separately for Facebook, Twitter, Instagram, Reddit, and Tumblr. Facebook use related to sexual harassment was a significant predictor of societal sexual harassment risk perceptions, β = 0.312, t(259) = 5.28, p < .001, with an R2 of .097. Twitter use related to sexual harassment was a significant predictor of societal sexual harassment risk perceptions β = 0.246, t(194) = 3.53, p = .001, with an R2 of .061. Instagram use related to sexual harassment was not a significant predictor of societal sexual harassment risk perceptions, β = 0.040, t(180) = 0.54, p = .591, with an R2 of .002. Reddit use related to sexual harassment was not a significant predictor of sexual harassment risk perceptions, β 33

= 0.06, t(167) = 1.01, p = .316, with an R2 of .006. Finally, Tumblr use related to sexual harassment was not a significant predictor of sexual harassment risk perceptions, β =

0.02, t(54) = 0.167, p = .868, with an R2 of .001.

To further examine H1 and H2, societal sexual harassment risk perceptions were regressed on mass media use related to sexual harassment (online and offline, separately), social media use related to sexual harassment (Facebook and Twitter, separately), as well as the covariates of age, education level, and prior experience with sexual harassment. Due to the not significant results found for Instagram, Reddit, and Tumblr, subsequent analyses were performed only on the Facebook and Twitter variables. In this case, neither age (β =

-0.037, t(187) = -0.51, p = .613) nor education level (β = 0.038, t(187) = 0.60, p = .584) were significant predictors of sexual harassment risk perceptions. However, sexual harassment experience was significant predictor of sexual harassment risk perceptions (β

= 0.170, t(187) = 2.23, p < .05.

Overall, this model explained significant variance in sexual harassment risk perceptions F(6,275) = 38.58, p < .001. H1 was not supported for mass media use related to sexual harassment offline, β = -0.072, t(187), = -0.95, p = .342. H1 was not supported for mass media use related to sexual harassment online, β = -0.039, t(187), = -0.48, p =

.630. H2 was supported for Facebook use. As Facebook use increased, sexual harassment risks perceptions increased, β = .242, t(187) = 3.04, p = .003. However, H2 was not supported for Twitter use. As Twitter increased, sexual harassment risk perceptions did not increase, β = .117, t(187) = 1.45, p = .149. Therefore, Hypothesis 2 was partially supported.

Hypothesis 3 (H3) proposed that societal sexual harassment risk perceptions will be associated with online societal risk reduction actions. To test this hypothesis, participants reported their societal sexual harassment risk perceptions, as well as their intention to engage in online societal risk reduction actions. Societal sexual harassment risk perceptions was a significant predictor of intention to engage in online societal risk reduction actions, β = 0.414, t(275) = 7.54, p < .001. Intention to engage in online societal risk reduction actions increased .270 units for every one unit increase in societal sexual harassment risk perceptions. To further test H3, online societal risk reduction actions were regressed on societal sexual harassment risk perceptions, including covariates age, education level, and sexual harassment experiences. As societal sexual harassment risk perceptions increased, intention to engage in online societal risk reduction actions increased, β = 0.392, t(275) = 2.77, p < .01. In this case, neither age (β

= -0.07, t(275) = -1.16, p = .245), education level (β = 0.071, t(275) = 1.22, p = .222), nor sexual harassment experience (β = 0.04, t(275) = 0.80, p = .425) were significant predictors of intention to engage in online societal risk reduction actions.

Furthermore, societal sexual harassment risk perceptions mediate the relationship between exposure to content related to sexual harassment on Facebook and intention to engage in online societal risk reduction actions, Effect = 0.0612, Boot SE = 0.0150, 95%

CI 0.0345, 0.0941. Additionally, societal sexual harassment risk perceptions mediate the relationship between exposure to content related to sexual harassment on Twitter and intention to engage in online societal risk reduction actions, Effect = 0.0478, Boot SE =

0.0136, 95% CI 0.0238, 0.0762. Therefore, Hypothesis 3 was supported.

Hypothesis 4 (H4) proposed that value relevant involvement will mediate the relationship between societal sexual harassment risk perceptions and intention to engage in online societal risk reduction actions. The test of indirect effects was significant, Effect

= 0.0691, Boot SE = 0.0203, 95% CI 0.0349, 0.1154. Furthermore, a serial mediation analysis of the indirect effect of mediating variables societal sexual harassment risk perceptions and value-relevant cognitive involvement had a significant effect on the relationship between Facebook use related to sexual harassment and intention to engage in online societal risk reduction actions, Effect = 0.0153, Boot SE = 0.0058, 95% CI

0.0061, 0.0285. Additionally, the indirect effect of mediating variables societal sexual harassment risk perceptions and value-relevant cognitive involvement has a significant effect on the relationship between Twitter use related to sexual harassment and intention to engage in online societal risk reduction actions, Effect = 0.0104, Boot SE = 0.0047,

95% CI 0.0035, 0.0216. Therefore, Hypothesis 4 was supported.

Hypothesis 5 (H5) proposed that impression-relevant cognitive involvement will mediate the relationship between societal sexual harassment risk perceptions and intention to engage in online societal risk reduction actions. The test of indirect effects was not significant, Effect = 0.0063, Boot SE = 0.0068, 95% CI -0.0050, 0.0279.

Furthermore, a serial mediation analysis of the indirect effect of mediating variables societal sexual harassment risk perceptions and impression-relevant cognitive involvement did not have a significant effect on the relationship between Facebook use related to sexual harassment and intention to engage in online societal risk reduction actions, Effect = 0.0009, Boot SE = 0.0019, 95% CI . -0.0024, 0.0054. Additionally, the

36 indirect effect of mediating variables societal sexual harassment risk perceptions and impression-relevant cognitive involvement did not have a significant effect on the relationship between Twitter use related to sexual harassment and intention to engage in online societal risk reduction actions, Effect = 0.0010, Boot SE = 0.0017, 95% CI

-0.0017, 0.0052. Therefore, Hypothesis 5 was not supported.

Hypothesis 6 (H6) proposed that emotional involvement with the issue of sexual harassment will mediate the relationship between societal sexual harassment risk perceptions and intention to engage in online societal risk reduction actions. In this case, emotional involvement was operationalized as the discrete emotional responses of anger and fear, as well as feelings of empathy toward victims of sexual harassment.

Mediational analyses were performed on these variables. The test of indirect effects mediated by anger was significant, Effect = 0.0441, Boot SE = 0.0162, CI 0.0134, 0.0775, as well as the indirect effects mediated by fear, Effect = .0786, Boot SE = .0163, CI

0.0491, 0.1133. Furthermore, a serial mediation analysis revealed significant effect of societal sexual harassment risk perceptions and anger on the relationship between

Facebook use related to sexual harassment and intention to engage in online societal risk reduction actions, Effect = 0.0095, Boot SE = 0.0044, 95% CI 0.0018, 0.0192, as well as

Twitter use related to sexual harassment and intention to engage in online societal risk reduction actions, Effect = 0.0166, Boot SE = 0.0062, 95% CI 0.0065, 0.0307.

A serial mediation analysis revealed effect of societal sexual harassment risk perceptions and fear on the relationship between Facebook use related to sexual harassment and intention to engage in online societal risk reduction actions, Effect = 0.0192, Boot SE =

0.0058, 95% CI 0.0092, 0.0321, as well as Twitter use related to sexual harassment and intention to engage in online societal risk reduction actions, Effect = 0.0181, Boot SE =

0.0057, 95% CI 0.0081, 0.0304. The test of indirect effects mediated by empathy was significant, Effect = 0.1269, Boot SE = 0.0241, CI 0.0826, 0.1762. A serial mediation analysis revealed a significant effect of societal sexual harassment risk perceptions and empathy on the relationship between Facebook use related to sexual harassment and intention to engage in online societal risk reduction actions, Effect = 0.0329, Boot SE =

0.0095, 95% CI 0.0169, 0.0530, as well as Twitter use related to sexual harassment and intention to engage in online societal risk reduction actions, Effect = 0.0202, Boot SE =

0.0087, 95% CI 0.0063, 0.0401. Therefore, Hypothesis 6 was supported.

Hypothesis 7 (H7) proposed that feelings of efficacy would moderate the relationship between involvement and intention to engage in online societal risk reduction actions. In this case, efficacy was operationalized as self-efficacy, collective efficacy, institutional efficacy, and action efficacy. Moderation analyses were conducted on each form of emotional involvement (anger and empathy for victims of sexual harassment) and cognitive involvement (value-relevant and impression-relevant involvement). In sum, 40 moderated serial mediation analyses were used to evaluate this hypothesis. The results from these moderated mediation analyses are outlined in Tables 2 and 3. No test of moderation effects was found to be significant for any efficacy variable

(self, collective, institutional, or action), cognitive involvement variable (value-relevant or impression relevant), or emotional involvement variable (anger, fear, or empathy).

Therefore, Hypothesis 7 was not supported.

Hypothesis 8 (H8) proposed that intention to engage in online societal risk reduction actions will be associated with intention to engage in offline societal risk reduction actions. Intention to engage in online societal risk reduction actions was a significant predictor of intention to engage in general offline societal risk reduction actions,

(β = 0.834, t(275) = 25.03, p < .001), with an R2 of .696. Intention to engage in general offline societal risk reduction actions increased .907 units for every one unit increase in intention to engage in online societal risk reduction. To further test this effect, intention to engage in general offline societal risk reduction action was regressed on intention to engage in online societal risk reduction actions, intention to engage in interpersonal offline societal risk reduction action, and intention to engage in active protest societal risk reduction action.

Additionally, the of covariates age, sexual harassment experiences, and education level were included. H8 was supported for intention to engage in general offline societal risk reduction action, β = .600, t(275) = 15.97, p < .001. In this case, neither age (β = 0.07, t(275) = 0.22, p = .823), education level (β = 0.00, t(275) = 0.03, p = .974) nor sexual harassment experience (β = -0.05, t(275) = -1.70, p = .091),were significant predictors of intention to engage in offline general societal risk reduction actions.

Intention to engage in online societal risk reduction actions was a significant predictor of intention to engage in interpersonal offline societal risk reduction actions, (β

= 0.616, t(275) = 12.95, p < .001), with an R2 of .010. Intention to engage in interpersonal offline societal risk reduction actions increased .710 units for every one unit increase in intention to engage in online societal risk reduction actions. To further test this effect, intention to engage in interpersonal offline societal risk reduction action was regressed on

39 intention to engage in online societal risk reduction actions, intention to engage in general offline societal risk reduction action, and intention to engage in active protest societal risk reduction action. Additionally, the of covariates age, sexual harassment experiences, and education level were included. H8 was supported for intention to engage in interpersonal offline societal risk reduction action, b = .258, t(275) = 3.10, p < .01. In this case, neither age (β = 0.0, t(275) = 1.32, p = .188), education level (β = 0.00, t(275) = 0.03, p = .974), nor sexual harassment experience (β = -0.05, t(275) = -1.70, p = .091) were significant predictors of intention to engage in offline interpersonal societal risk reduction actions.

Intention to engage in online societal risk reduction actions was a significant predictor of intention to engage in offline active protest societal risk reduction actions, (β

= 0.450, t(275) = 8.35, p < .001) with an R2 of .203. Intention to engage in offline active protest societal risk reduction actions increased .470 units for every one unit increase in intention to engage in online societal risk reduction actions. To further test this effect, intention to engage in offline active protest societal risk reduction action was regressed on intention to engage in online societal risk reduction actions, intention to engage in general offline societal risk reduction action, and intention to engage in interpersonal offline societal risk reduction action. Additionally, the of covariates age, sexual harassment experiences, and education level were included. H8 was not supported for intention to engage in offline active protest societal risk reduction action, b = -0.20, t(275) = -2.36, p < .05. In this case, neither education level (β = -0.01, t(275) = -0.20, p =

.851), nor sexual harassment experience (β = -0.04, t(275) = -0.92, p = .360) were significant predictors of intention to engage in offline active protest societal risk

40 reduction actions. However, age was found to be a significant predictor of intention to engage in offline active protest societal risk reduction actions (β = -0.22, t(275) = -4.84, p

< .001). Therefore, Hypothesis 8 was partially supported.

Chapter 5. Discussion

This study examined how individuals engage with media sources, develop societal risk perceptions, and engage in behaviors to reduce those risks. By focusing on the issue of sexual harassment, this study provides a perspective on how individuals engage with issues using both online and offline channels. Furthermore, by examining the role of social networking sites, it provides empirical support for the SRRM and expands the model’s scope to online contexts. Results indicate that social media sites can be an important source for information about the societal risk of sexual harassment, particularly when that social media use is compounded by other individual and behavioral factors.

Furthermore, this research expands the domain of risk communication to that of activism and social movements. While online activism has received criticism for its ease and low levels of commitment, this study demonstrates that online societal risk reduction actions may be enacted as a response to societal risk issues, and may even bridge a gap between online and offline activism.

The hypotheses in this study sought to identify the mechanisms at play in the

SRRM, and test whether those mechanisms occur in both mass media and social media contexts. Analysis revealed that engagement with content related to sexual harassment on social media sites (specifically, Facebook and Twitter) was a significant predictor of societal sexual harassment risk perceptions (Hypothesis 2-Partially Supported). Mass media use related to sexual harassment was not a significant predictor of societal sexual harassment risk perceptions (Hypothesis 1-Not Supported). Additionally, these effects were only present for social media use on Facebook when controlling for age, 42 experiences with sexual harassment, and other forms of media consumption. This suggests that social media has particularly salient effects on societal risk perceptions, and those effects may be amplified or attenuated in the presence of other individual characteristics or behaviors.

These findings are noteworthy because they contradict the first proposition of the

SRRM, which argues that risk information consumed through mass media channels significantly influences societal risk perceptions (Cho & Kuang, 2015). This warrants a more detailed examination of how risk information is encountered, and whether mass media has a stronghold on risk perceptions in all topic areas. Furthermore, this warrants examination of whether coverage of a risk topic varies between media channels, and how that variation may influence audiences’ societal risk perceptions. Overall, these results provide important insights into the application of the SRRM to new media contexts— specifically focusing on the influence of social media use on societal risk perceptions.

These findings suggest that social media are not only a source for risk information, they also shape users’ perceptions of the severity of that risk. These results may be due, in part, to the fact that more experienced social media users tend to seek information on social media, rather than through mass media sources (Lachlan, Spence,

& Lin, 2014; Gil de Zúñiga, Diehl, Huber, & Liu, 2017). When the dual influences of mass media and social media are examined together, the results suggest that societal risk issues may receive differential coverage on mass media and social media channels. The affordances of social media enable the sharing of user-generated content. When created or shared by network contacts, this content may have a particularly salient influence on

43 societal risk perceptions (Haythornthwaite, 2002; Grabowicz, Ramasco, Moro, Pujol, &

Eguiluz, 2012). As such, the social affordances that different social media sites provide for users may influence how users engage with content across different platforms (Fox &

McEwan, 2017). As individuals increasingly turn to social media as an information source, understanding how risk information is created and disseminated is an important next step in strengthening conceptualizations of societal risk perceptions.

This research also found that societal sexual harassment risk perceptions are associated with intention to undertake online actions to reduce that societal risk

(Hypothesis 3-Supported). Furthermore, societal sexual harassment risk perceptions mediate the relationship between social media use specifically related to sexual harassment and intention to engage in societal risk reduction actions online. Notably, this outcome focused on the participants’ intention to engage in actions specifically online

(such as emailing representatives, posting status updates about the issue on social media, or changing their profile picture to reflect the cause). Those who encounter societal risk information on social media may then perceive social media to be a convenient or accessible platform on which to take action. This may occur if individuals feel that mass media coverage of the risk issue is inadequate (Sutton et al., 2008; Shklovski et al.,

2008), or if user-generated content about the societal risk issue is particularly salient.

Social media not only influence societal risk perceptions, they also provide a platform through which individuals can respond to societal risks. Furthermore, societal risk information shared on social media may encompass content shared directly from mass media sources (Starbird et al., 2010), content translated or reiterated from mass

44 media sources (Stephens & Malone, 2009), or individualized, user-generated information

(Shklovski et al., 2008). While this study did not seek to identify additional predictors of these outcomes, the ease and accessibility of social networking sites may influence individuals’ decision to engage in online societal risk reduction actions (van Dijk et al.,

2011; Postmes & Brunsting, 2002). Taken together, these findings suggest that societal risk information encountered on social media can shape not only societal risk perceptions, but also behavioral responses to those risks. Once again, this finding supports the propositions of the SRRM, and extends its applications to online contexts

(Cho & Kuang, 2015).

To further test the application of the SRRM to online contexts, this study examined the possible mediating effects of value-relevant and impression-relevant cognitive involvement with the societal risk issue of sexual harassment. It was found that value-relevant involvement significantly influenced intention to engage in online societal risk reduction actions (Hypothesis 4-Supported), whereas impression-relevant involvement did not (Hypothesis 5-Not Supported). Taken together, these results provide partial support for the SRRM’s proposition of value-relevant and impression-relevant involvement as predictors of societal risk reduction action, and demonstrates that cognitive involvement can influence actions undertaken online (Cho & Kuang, 2015).

These results suggest that as individuals form perceptions of a societal risk issue, their sense of who they are and what they care about significantly influences whether and how they choose to reduce that risk. This supports existing research, which has found value-relevant cognitive involvement to be a significant predictor of intention to engage

45 in societal risk reduction actions (Cho & Boster, 2005; Marshall, Reinhart, Feeley,

Tutzauer, & Anker, 2008). However, an individual’s sense that others’ perceptions of them are based on their stance on the risk issue does not significantly influence whether and how they choose to act. This contradicts existing research, which has found that impression-relevant cognitive involvement to be a significant predictor of intention to engage in societal risk reduction actions (Cho & Boster, 2005). Although social media use seems as though it would be related to impression-relevant involvement as an antecedent or an outcome, this relationship was not present in the current study.

These results suggest that individuals’ intention to engage in online societal risk reduction strategies is not driven by the individual’s desire to manage or manipulate their online presence (Dorethy, Fiebert, & Warren, 2014; Cho & Boster, 2015). Instead, the individual’s value-relevant involvement with the issue of sexual harassment is a more powerful influence on behavioral intention. Furthermore, cognitive involvement with the societal risk issue does not directly reflect the channel through which information about that risk issue is encountered. Therefore, these effects may be directly related to individuals’ perceptions of sexual harassment itself, excepting the perceived affordances of differing media channels.

Further extending the propositions of the SRRM, this study found that the discrete emotional responses of anger and fear, as well as empathy for victims of sexual harassment, significantly predicted intent to engage in online societal risk reduction actions (Hypothesis 6-Supported). These findings not only provide support for the

SRRM’s mechanisms even in online contexts, but also provide support for literature

46 examining the intersection between risk perceptions, emotions, and risk responses. The emotional responses of anger and fear have been shown to predict intent to engage with societal risk issues (Lerner & Keltner, 2000; Becker, Tausch, & Wagner, 2011).

Additionally, these findings stratify individuals’ specific emotional responses to the issue of sexual harassment itself, thereby providing insight into the discrete responses associated with this issue.

Societal risk issues are perceived as affecting society as a whole; therefore, it is helpful to identify how individuals perceive and respond to the threat of sexual harassment on generalized others in society. Feelings of empathy may increase individuals’ willingness to address a risk issue, which may account for empathy’s influences on online societal risk reduction actions (Wispe, 1986; Eisenberg & Miller,

1987). This finding reflects existing research which suggests that empathy is negatively associated with sexual harassment myth acceptance (Lonsway, Cortina, & Magley, 2008;

Diehl, Glaser, & Boehner, 2014). Feelings of empathy for those affected by a societal risk can not only influence perceptions of the risk issue itself, but also behavioral responses to that risk issue. In accordance with the SRRM, these findings demonstrate that anger, fear, and empathy predict individuals’ intention to engage in online behaviors to reduce that societal risk.

This study also examined the influence of efficacy perceptions on intention to engage in online societal risk reduction behaviors. The SRRM posits that self-efficacy, collective efficacy, institutional efficacy, and action efficacy significantly moderate the influence of emotional and cognitive involvement on societal risk reduction actions.

However, the results of this study do not demonstrate such effects (Hypothesis 7-Not

Supported). While this finding fails to support this application of the SRRM, it also poses important questions as to individuals’ perceptions of the influence and effectiveness of specific actors and actions when reducing societal risk. This contradicts literature which suggests that online engagement enhances efficacy beliefs, which then influence online political participation (Vaccari t al., 2015). This is particularly thought-provoking as online activism is criticized for being too easy and accessible (Gladwell, 2010; Karpf,

2010), which in theory should enhance perceptions of efficacy. Furthermore, this study is unable to determine whether the moderating effects of efficacy beliefs are absent due to the online context, the specific societal risk issue, or other factors. Regardless, these results demonstrate that further examination of the role of efficacy beliefs within the

SRRM is warranted, irrespective of risk topic or context.

Finally, this study found that individuals’ intention to engage in online societal risk reduction actions is associated with their intention to engage in general and interpersonal offline societal risk reduction actions, but not with offline active protest societal risk reduction actions. (Hypothesis 8-Partially Supported). This finding integrates extant literature on online and offline activism into the propositions of the SRRM that societal risk reduction actions that occur online do not occur in a vacuum, but are related to offline societal risk reduction actions. This finding supports the argument within existing social movements literature that new media are routinely integrated into formal activist networks and behaviors (Halupka, 2014; Rotman et al., 2011) and counters a common criticism of online activism, which argues that the accessibility and convenience

48 of online activism deters individuals from engaging in more effective offline activism

(Halupka, 2014; Rotman et al., 2011; Gladwell, 2010; Karpf, 2010). However, it is noteworthy that online societal risk reduction actions were negatively associated with offline active protest behaviors. These findings may indicate that online activism may serve as a viable alternative for individuals who are unwilling or unable to engage in street protests, without detracting from other forms of offline activism. Furthermore, this relationship may be particularly salient if individuals perceive risks associated with engaging in active protest behaviors, such as physical injury or arrest (DeLuca, Lawson,

& Sun, 2012).

While this finding does not delineate the SRRM’s dual concepts of adaptive and maladaptive actions (Cho & Salmon, 2006), it does provide insight into the theorized merits of different behaviors within the literature on activism. The insight that online societal risk reduction actions are associated with offline societal risk reduction actions counters the criticism that online activism is ineffective and limited to online contexts.

These findings add to a body of research which suggests that new media and technology can provide a powerful means to create social change (Wills & Reeves, 2009; Steenkamp

& Hyde-Clarke, 2012; Castells, 2012).

Implications

This study has implications for multiple areas of research. First, these findings provide support for many of the mechanisms underpinning the SRRM (Cho & Kuang,

2015). By understanding these pathways as they relate to risk information encountered online and societal risk reduction enacted online, this expands the application of the

SRRM beyond mass media channels and into the realm of social media. Social media has been credited with expanding the context for public discussion of societal issues (Halpern

& Gibbs, 2013, Zheng & Wu, 2005). These results suggest that social media sites may play a prominent role in shaping individuals’ perceptions of societal risks, and the strategies with which they respond to those risks.

This study also provides additional insights into the factors which mediate and moderate the pathways between media exposure, societal risk perceptions, and societal risk reduction actions. Anger, fear, empathy, and value-relevant involvement with the issue of sexual harassment all served as significant mediators between those relationships. Impression-relevant involvement did not demonstrate such significant effects. Overall, efficacy beliefs did not moderate the relationships between emotional involvement, cognitive involvement, and online risk reduction actions. These outcomes are somewhat surprising, considering that online resources and social networking sites are believed to lower the threshold for participation (Postmes & Brunsting, 2002; Zheng

& Yu, 2016) and that online political engagement is related to increased efficacy beliefs

(Vaccari et al., 2015). However, this may not necessarily increase users’ perceptions of self-efficacy, nor perceptions of collective, institutional, or action efficacy related to the societal risk issue of sexual harassment. This demonstrates that the mediating and moderating variables originally proposed by the SRRM do not exert effects in all media contexts, or on all societal risk issues. Going forward, understanding the differential effects that these moderators play will be important to develop greater understanding perceptions of societal risks, and the actions undertaken to reduce those risks.

This study also has implications for the study of activism and social movements.

In conjunction with the SRRM, these results suggest that engagement with social issues

(whether through mass media channels, online platforms, or social networking sites) shapes individuals’ perceptions of that issue and the risks it presents. Furthermore, individuals may select both online and offline strategies to address that issue and potentially take action to reduce the risks that it presents. A deeper understanding of how individuals select and utilize media will heighten understanding of the role of new media in civil activism.

These findings suggest a relationship between online and offline actions undertaken to reduce societal risks. While these outcomes do not directly reflect the adaptive and maladaptive responses originally proposed by the SRRM, they do shed light on the nuances in behavioral responses to risk. Critics of online activism question its ease and accessibility, suggesting that online activism detracts from offline activism, therefore undercutting the outcomes of the activism behaviors themselves (Gladwell, 2010; Karpf,

2010). The results of this study suggest that individuals do not consider online and offline actions to be in direct conflict with one another. Rather, these behaviors may serve to complement one another, creating a broader spectrum of strategies with which individuals can combat the risks that they perceive as being important.

Finally, this study has implications for those seeking to address the issue of sexual harassment. Sexual harassment is a pervasive issue in the United States and around the world, with individuals from all walks of life being affected. The emergence of the

#MeToo movement, which spread through social media to encourage women to share

51 their experiences of harassment and assault, demonstrate that individuals can share their stories using social media (Kantor & Twohey, 2017; Grinberg & Agiesta, 2017).

Understanding how social media can be used to amplify the voices of marginalized people may provide insight into how social media can be harnessed as a conduit for lasting societal change.

Limitations and Future Directions

The current study has limitations related to its participants and construct measurement. First, this study focused on individuals who self-identify as female, ranging from ages 18 to 65. Additionally, all participants in this survey reported completion of some level of formal schooling. This participant sample is not representative of the population as a whole. Future research should investigate how different populations learn about, experience, and respond to the issue of sexual harassment. Such research would be particularly beneficial to understand the effects of sexual harassment on marginalized individuals.

Second, reliance on self-report data may influence response bias, particularly for sensitive issues such as sexual harassment. Some participants may be hesitant to accurately report their own experiences, or may demonstrate desirability bias in their responses. Furthermore, individuals with strong opinions on the issue of sexual harassment may have self-selected into the study.

Third, due to the cross-sectional design of the survey, causality cannot be identified. It is important to note that while significant relationships emerge between variables in a way which empirically supports the theoretical predictions of the SRRM, is

52 it impossible to understand whether these variables directly cause one another.

Additionally, extraneous variables may influence the relationships identified in the study

(which were not directly measured).

Fourth, measures of engagement with risk-related content on various media channels should be examined in greater detail. While the findings of hypothesis one

(which predicted that engagement with content related to sexual harassment on social media would be associated with increased societal sexual harassment risk perceptions) were not significant. This may be attributed to issues of measurement within the study.

However, future research examining the influence of media channels on societal risk perceptions should identify nuances in media consumption that may not be easily captured. As broadcasters, newspapers, and magazines are expanding into online platforms, the distinctions in media consumption (as well as the additional affordances that online platforms may afford) should be examined in greater detail.

Additionally, patterns of social media use should be given further examination.

For this study, participants’ frequency of use (specifically, how often they use a social media site) and duration of use (specifically, how much time they spend on a social media site) were measured. However, these measures were not included in the final analysis, as the hypotheses focused on engagement with content related to sexual harassment. Intuitively, the more time an individual spends on social media, the more opportunities they have to engage with specific content. Identifying how frequency and duration of social media use influence risk perceptions and behavioral outcomes will be

53 an important next step in understanding social media’s role in shaping risk perceptions and responses.

Fifth, the outcome variable examined by this study focused on intention to engage in risk reduction actions. While behavioral intention is often a strong predictor of behavior, additional research should seek to identify actions that are most commonly undertaken to address societal risks. Doing so will provide deeper insight into the dynamic relationship between online and offline societal risk reduction actions.

Finally, the scope of behaviors and use on social media was not thoroughly examined in this study. In order to best understand the theoretical applications of the

SRRM, the measures instead focused on interaction with content related to sexual harassment on social networking sites. This does not encompass the scope of information-seeking behaviors that may lead individuals to engage with such content or the spread of such information through social networks. Similarly, the outcome variable of intention to engage in online risk reduction actions does not address the social affordances which may enable social networking site users to engage in such behaviors.

More thorough analysis of the role of social media sites, social network connections, and social affordances would provide additional insight into the role of social networking sites on societal risk perceptions and societal risk reduction actions (Granovetter, 1973;

Dutta-Bergman, 2004; Alexander, 2014, Fox & McEwan, 2017). Furthermore, the structure of social networks could lend themselves to more effective organizing of social movements (McAdam et al., 1996, McAdam & Scott, 2005). Although the issue being examined in this study, sexual harassment and the #MeToo movement, lacks formal

54 structure around a central organization, the implications for other social movements should be examined.

Overall, this study provides greater insight into individuals’ perceptions of sexual harassment as a societal risk, and their responses to those risks. Particularly as increasing numbers of people are getting news and information from online media and social networking sites, understanding how online information sources shape risk perceptions and risk reduction actions is a crucial step to strengthening understanding of societal risk issues. Furthermore, using the SRRM may provide a consistent, empirically supported lens through which to examine a variety of societal risk issues. The findings of this study can provide a deeper insight into these dynamic processes, and inform future studies on how social media influences our understandings of societal risk issues.

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Appendix A. Tables

Table 1.

Sample characteristics.

Variable Percentages M SD

Age (Years) N=276 36.36 10.87

Race N=276 2.83 1.02

African American (non- 14.5% Hispanic) Asian/Pacific Islander 5.4% Caucasian (non-Hispanic) 70.3% Hispanic or Latino 6.2% Native American or Aleut 0.0% Prefer to self-describe 2.9% Prefer not to say 0.7%

Highest Completed N = 276 4.29 1.21 Education

Some high school 0.0% High school diploma or 8.3% equivalent Some college, no degree 22.1% Associate’s degree (AA, 13.4% AS) Bachelor’s degree (BA, 48.2% BS, AB) Master’s degree (MA, 5.8% MS, MBA, etc.) Professional degree (MD, 1.1% DDS, etc.) Doctorate degree (PhD, 1.1% EdD)

Continued

Table 1 Continued.

Sample Characteristics

Variable Percentages M SD

Employment Status N = 276 1.88 1.70

Employed for wages 62.0% Self-employed 16.7% Out of work, looking for 3.3% work Out of work, not looking 0.7% for work Stay at home parent 6.2% Student 2.2% Retired 0.7% Unable to work 2.2% Other (self-describe) 0.4%

Is the organization in N = 276 3.50 1.57 which you work or attend school ...

Male-dominated 8.0% Mostly male 18.1% Equally male and female 37.0% Female-dominated 11.2% Not applicable 4.3%

Is the field in which you N = 276 2.83 1.10 work or attend school…

Male-dominated 13.7% Mostly male 21.7% Equally male and female 40.3% Female-dominated 16.8% Not applicable 7.5%

Continued

Table 1 Continued.

Sample Characteristics.

Variable Percentages M SD

Have you ever N = 276 0.62 .48 experienced sexual harassment?

Yes 61.6% No 38.4%

Table 2.

Moderated Serial Mediation (Facebook)

Mediating Variable 2 Moderating Variable Coefficient se t CI: LL CI: UL

Anger Self-efficacy 0.01 0.02 0.28 -0.0384 0.0513 Collective efficacy 0.06 0.04 1.52 -0.0164 0.1272 Institutional efficacy 0.07 0.04 1.59 -0.0158 0.1501 Action efficacy -0.01 0.04 -0.04 -0.0825 0.0589 Fear Self-efficacy 0.01 0.02 0.44 -0.0271 0.0428 Collective efficacy 0.02 0.03 0.55 -0.0400 0.0714 Institutional efficacy 0.02 0.04 0.70 -0.0439 0.0926 Action efficacy 0.04 0.03 1.32 -0.0172 0.0869 Empathy Self-efficacy 0.03 0.02 1.83 -0.0025 0.0668 Collective efficacy 0.04 0.03 1.21 -0.0222 0.0924 Institutional efficacy 0.05 0.04 1.30 -0.0259 0.1262 Action efficacy 0.02 0.03 0.62 -0.0419 0.0805 Note. Independent Variable: Facebook use related to sexual harassment. Dependent Variable: Intention to engage in online action to reduce societal risk. Mediating Variable 1: Societal sexual harassment risk perceptions. * = p < .05

Continued 76

Table 2 Continued.

Moderated Serial Mediation.

Mediating Variable 2 Moderating Variable Coefficient se t CI: LL CI: UL

Value-relevant involvement Self-efficacy -0.01 0.02 -0.37 -0.0434 0.0297 Collective efficacy 0.05 0.04 1.41 -0.0225 0.1264 Institutional efficacy 0.08 0.05 1.62 -0.0162 0.1675 Action efficacy 0.00 0.03 0.01 -0.0657 0.0667 Impression-relevant involvement Self-efficacy 0.00 0.02 0.52 -0.0262 0.0450 Collective efficacy 0.02 0.04 0.57 -0.0556 0.1009 Institutional efficacy -0.03 0.05 -0.50 -0.1232 0.0731 Action efficacy 0.04 0.03 1.16 -0.0274 0.1070 Note. Independent Variable: Facebook use related to sexual harassment. Dependent Variable: Intention to engage in online action to reduce societal risk. Mediating Variable 1: Societal sexual harassment risk perceptions. * = p < .05

Table 3.

Moderated Serial Mediation (Twitter)

Mediating Variable 2 Moderating Variable Coefficient se t CI: LL CI: UL

Anger Self-efficacy 0.02 0.03 0.65 -0.0369 0.0730 Collective efficacy 0.08 0.04 1.91 -0.0024 0.1660 Institutional efficacy 0.08 0.05 1.56 -0.0206 0.1769 Action efficacy 0.00 0.05 0.02 -0.0896 0.0913 Fear Self-efficacy -0.01 0.02 0.60 -0.0551 0.0320 Collective efficacy -0.00 0.03 -0.00 -0.0653 0.0651 Institutional efficacy -0.00 0.04 -0.04 -0.0761 0.0729 Action efficacy 0.03 0.03 0.96 -0.0330 0.0963 Empathy Self-efficacy 0.01 0.02 0.65 -0.0278 0.0550 Collective efficacy 0.02 0.04 0.55 -0.0531 0.0941 Institutional efficacy 0.05 0.05 1.00 -0.5512 0.3021 Action efficacy -0.04 0.04 -1.05 -0.1151 0.0351 Note. Independent Variable: Twitter use related to sexual harassment. Dependent Variable: Intention to engage in online action to reduce societal risk. Mediating Variable 1: Societal sexual harassment risk perceptions. * = p < .05

Continued 78

Table 3 Continued.

Moderated Serial Mediation (Twitter)

Mediating Variable 2 Moderating Variable Coefficient se t CI: LL CI: UL

Value-relevant involvement Self-efficacy -0.02 0.02 -0.72 -0.0569 0.0266 Collective efficacy 0.05 0.05 1.08 -0.0423 0.1447 Institutional efficacy -0.04 0.05 0.52 -0.0767 0.1314 Action efficacy -0.02 0.04 -0.40 -0.0934 0.0622 Impression-relevant involvement Self-efficacy -0.00 0.03 -0.04 -0.0433 0.0417 Collective efficacy 0.03 0.05 0.67 -0.0618 0.1253 Institutional efficacy 0.04 0.06 0.69 -0.0700 0.1455 Action efficacy 0.05 0.04 1.13 -0.0334 0.1227 Note. Independent Variable: Twitter use related to sexual harassment. Dependent Variable: Intention to engage in online action to reduce societal risk. Mediating Variable 1: Societal sexual harassment risk perceptions. * = p < .05

Appendix B. Figures

Figure 1.

Proposed pathway model. 80

Appendix C. Construct Measures

Mass Media Use Sexual Harassment (Offline) M = 3.33, SD = 1.55, α = .816 (1=Never, 7=Always) In the past 6 months, how often have you watched/heard/read news about sexual harassment on:

TV network news Local TV news Cable TV news

Mass Media Use: Sexual Harassment (Online) M = 2.95, SD = 1.36, α = .807 (1=Never, 7=Always) In the past 6 months, how often have you watched/heard/read news about sexual harassment on:

Online national newspapers Online local newspapers Online magazines News sites generated by regular people

Social Media Use: Sexual Harassment M = 2.97, SD = 1.11, α = .604 (1=Never, 7=Always) In the past 6 months, how often have you watched/heard/read news about sexual harassment on:

Facebook Twitter Instagram Tumblr

Societal Risk Perceptions: Sexual Harassment M = 5.87, SD = 1.24 α = .956 (1=Strongly Disagree, 7=Strongly Agree).

I think sexual harassment is a serious problem in the United States. Sexual harassment is an important problem in the United States.

Emotional Involvement: Anger M = 4.03, SD = 1.13, α = .801 (1=Not at all, 5=Very Much) 81

How much does news about sexual harassment make you feel ____?

Angry Irritated Aggravated Outraged Disgusted

Emotional Involvement: Fear M = 2.59, SD = 1.33, α = .801 (1=Not at all, 5=Very much) How much does news about sexual harassment make you feel ___?

Sad Afraid Fearful

Emotional Involvement: Empathy M = 4.99, SD = 1.25, α = .931 (1=Strongly Disagree, 7=Strongly Agree)

When I think about sexual harassment, I experience the same emotions as the victim. When I think about sexual harassment, I am in a similar emotional state as the victim. I can feel the emotions of sexual harassment victims. I can see the point of view of sexual harassment victims. When I think about sexual harassment, I can recognize the victim’s situation. Victims’ reactions to sexual harassment are understandable. I can understand what sexual harassment victims are going through. I can relate to what sexual harassment victims are going through. I can identify with sexual harassment victims.

Cognitive Involvement: Value-Relevant M = 5.06, SD = 1.13, α = .881 (1=Strongly Disagree, 7=Strongly Agree)

The values that are important to me are what determine my stand on sexual harassment. Knowing my position on sexual harassment is central to understanding the kind of person I am. My position on sexual harassment has little to do with my beliefs about how life should be lived. My position on sexual harassment is based on the values with which I try to conduct my life. The arguments for or against sexual harassment are relevant to the core principles that guide my life. 82

My beliefs about how I should live my life will determine my position on sexual harassment. My position on sexual harassment reflects who I am.

Cognitive Involvement: Impression-Relevant M = 3.83, SD = 1.09, α = .745. (1=Strongly Disagree, 7=Strongly Agree)

Talking about my beliefs concerning sexual harassment will have little effect on what others think of me. The impressions that other have of me will be very much affected when I talk with them about my position on sexual harassment. The kind of opinion that I express in public about sexual harassment will have little effect on what others think of me. People may judge me on the basis of the opinion that I express in public about sexual harassment. If I express the right kind of opinion on sexual harassment, people will find me more effective.

Self-Efficacy M = 4.63, SD = 1.51, α = .947 (1=Strongly Disagree, 7=Strongly Agree) Please indicate the extent to which you agree or disagree with each of the following statements.

I feel that I can contribute to increased awareness about sexual harassment as a societal issue. I feel that I can contribute to changing laws and policies about sexual harassment. I feel that I can contribute to change within society about sexual harassment.

Collective Efficacy M = 5.83, SD = 1.05, α = .895 (1=Strongly Disagree, 7=Strongly Agree) Please indicate the extent to which you believe that women can…

Increase awareness about sexual harassment as a societal issue. Change laws and policies about sexual harassment. Create change within society about sexual harassment.

Institutional Efficacy M = 5.95, SD = 0.89, α = .883 (1=Strongly Disagree, 7=Strongly Agree) Please indicate the extent to which you believe workplaces can…

Increase awareness about sexual harassment as a societal issue. Create laws and policies about sexual harassment. Create change within society about sexual harassment. Prevent sexual harassment before it occurs. Address sexual harassment after it occurs. Assist victims of sexual harassment. Punish perpetrators of sexual harassment.

Action Efficacy (Online) M = 2.38, SD = 0.81, α = .948 (1=Not at all effective, 5=Very effective) Please indicate how effective the following actions are in addressing sexual harassment as a societal issue:

Contacting political leaders and decision makers about sexual harassment online Sharing with connections on social media about sexual harassment. Mobilizing others on social media around the issue of sexual harassment. Using online platforms to support offline causes related to sexual harassment. Measures were repeated for ‘increasing awareness about sexual harassment as a societal issue’ and ‘changing laws and policies about sexual harassment.

Activism: Sexual Harassment (Online) M = 2.39, SD = 0.81, α = .809 (1=Extremely Unlikely, 4=Extremely Likely) Please indicate how likely it is that you will engage in each of the following behaviors in the future.

Post a social media status about sexual harassment. Like or favorite a social media post about sexual harassment. Comment on a social media post about sexual harassment. Share or retweet a social media post about sexual harassment. Use an activist hashtag (such as #MeToo or #YesAllWomen) in a social media post about sexual harassment. Generate awareness about sexual harassment using social media. Share your experience about participating in/supporting issues related to sexual harassment on social media. Share socially or politically charged images or photos about sexual harassment on social media. Change your social media profile picture surrounding sexual harassment. Unfriend or unfollow someone on social media because of their posts about sexual harassment. Friend or follow a political leader or decision maker on social media because of their stance or statements on sexual harassment. 84

Contact a political leader or decision maker about the issue of sexual harassment, through email or social media. Mobilize online support for causes related to sexual harassment. Sign an online petition about sexual harassment. Prompt social connections to sign an online petition about sexual harassment. Share information about a protest or boycott surrounding sexual harassment on social media. Donate money to a social-political cause related to sexual harassment that originated on social media. Raise money for a social-political issue related to sexual harassment using social media.

Activism: Sexual Harassment (Offline-General) M = 2.18, SD = 0.88, α = .946 (1=Extremely Unlikely, 4=Extremely Likely) Please indicate how likely it is that you will engage in each of the following behaviors in the future.

Contact a political leader or decision maker about the issue of sexual harassment, through the mail. Contact a political leader or decision maker about the issue of sexual harassment, via telephone. Attend an in-person informational session about sexual harassment. Invite a friend to attend an in-person information session about sexual harassment. Give a lecture or talk about the issue of sexual harassment. Sign a petition about the issue of sexual harassment. Encourage others to sign a petition about the issue of sexual harassment. Donate money to a social-political cause that addresses the issue of sexual harassment. Create posters, fliers, or t-shirts about sexual harassment. Display posters, fliers, or t-shirts about sexual harassment. Participate in a boycott related to sexual harassment. Participate in a rally, march, or public demonstration related to the issue of sexual harassment. Distribute information offline about the issue of sexual harassment.

Activism: Sexual Harassment (Offline-Interpersonal) M = 2.79, SD = 0.93, α = .903 (1=Extremely Unlikely, 4=Extremely Likely) Please indicate how likely it is that you will engage in each of the following behaviors in the future.

Confront jokes, statements, or innuendoes about sexual harassment. Try to change a relative’s mind about the issue of sexual harassment. Engage in a political activity in which you knew you would be arrested.

Activism: Sexual Harassment (Offline-Active Protest) M = 1.54, SD = 0.84, α = .953 (1=Extremely Unlikely, 4=Extremely Likely) Please indicate how likely it is that you will engage in each of the following behaviors in the future.

Engage in a political activity in which you knew you would be arrested. Block access to a building or public area with your body. Engage in a physical confrontation at a political rally. Engage in an illegal act as part of a political protest. Distribute information offline about a rally, march, or public demonstration related to the issue of sexual harassment