Education, Faculty of
Educational and Counselling Psychology, and Special Education (ECPS), Department of
DSpace
UBCV
Baitz, Rachel
Doctor of Philosophy - PhD
University of British Columbia
Background: Young adulthood is often characterized as a time of rapid individuation away from family relationships toward more adult romantic partner relationships. In the current technological climate, young adult relationships begin, grow, and develop both in-person and online in a seamless fashion. Unfortunately, problems that have always plagued young adult relationships, such as dating violence, also occur via electronic mediums. Given that technological factors that relate to relationships are still emerging, little is known about how a variety of experiences across the childhood and adolescent trajectory relate to the emergence of cyber dating violence in young adulthood. Objectives: The current research seeks to understand how early childhood traumatic experiences predict cyber dating violence, and whether this relationship is mediated by insecure attachment, and moderated by problematic internet use, internalizing symptoms, limerence, cyberbullying perpetration and victimization, and limerence. Methods: Using a cross-sectional design, 1354 adults aged 18 to 51 were recruited via Amazon’s Mechanical Turk to answer a questionnaire about their experiences with cyber dating violence victimization and perpetration, as well as their experiences with cyberbullying and victimization, internalizing symptoms, problematic internet use, attachment styles, and limerence. Results: Results indicated partial mediations for higher scores on measures of insecure attachment (anxious, avoidant) on the relationship between traumatic experiences recalled from early in life and cyber dating violence victimization and perpetration in young adulthood. Moderation results indicated that cyberbullying, cyber victimization, and problematic internet use moderated the influence of traumatic experiences recalled from early life on cyber dating violence experiences in young adulthood. Hierarchical regression analyses indicated several predictors of limerence, such as anxious attachment, internalizing symptoms, and vulnerable experiences. Discussion: Findings from the current work move the body of literature forward by illustrating important links between early experiences, attachment styles, cyberbullying, cybervictimization, internalizing symptoms, problematic internet use, limerence, and cyber dating violence perpetration and victimization.
YOUNG ADULT CYBER VIOLENCE: AN INVESTIGATION OF THE ASSOCIATIONS WITH VULNERABLE EXPERIENCES, ATTACHMENT PATTERNS, PROBLEMATIC INTERNET USE, LIMERENCE, AND INTERNALIZING SYMPTOMS by Rachel Baitz B.A., Kwantlen Polytechnic University, 2011 M.A., University of British Columbia, 2015 A DISSERTATION SUBMITTED IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF DOCTOR OF PHILOSOPHY in The Faculty of Graduate and Postdoctoral Studies (Human Development, Learning, and Culture) THE UNIVERSITY OF BRITISH COLUMBIA (Vancouver) July 2023 ã Rachel Baitz, 2023 ii The following individuals certify that they have read, and recommended to the Faculty of Graduate and Postdoctoral Studies for acceptance, the dissertation entitled: Young Adult Cyber Violence: An Investigation of the Associations with Vulnerable Experiences, Attachment Patterns, Problematic Internet Use, Limerence, and Internalizing Symptoms submitted by Rachel Baitz in partial fulfilment of the requirements for the degree of Doctor of Philosophy in Human Development, Learning, and Culture Examining Committee: Jennifer Shapka, Professor, Educational, Counselling Psychology, and Special Education, UBC Supervisor Marla Buchanan, Professor, Educational, Counselling Psychology, and Special Education, UBC Supervisory Committee Member Johanna Sam, Assistant Professor, Educational, Counselling Psychology, and Special Education, UBC Supervisory Committee Member Daniel Cox, Professor, Educational, Counselling Psychology, and Special Education, UBC University Examiner Sheila Marshall, Professor, School of Social Work, UBC University Examiner iii Abstract Background: Young adulthood is often characterized as a time of rapid individuation away from family relationships toward more adult romantic partner relationships. In the current technological climate, young adult relationships begin, grow, and develop both in-person and online in a seamless fashion. Unfortunately, problems that have always plagued young adult relationships, such as dating violence, also occur via electronic mediums. Given that technological factors that relate to relationships are still emerging, little is known about how a variety of experiences across the childhood and adolescent trajectory relate to the emergence of cyber dating violence in young adulthood. Objectives: The current research seeks to understand how early childhood traumatic experiences predict cyber dating violence, and whether this relationship is mediated by insecure attachment, and moderated by problematic internet use, internalizing symptoms, limerence, cyberbullying perpetration and victimization, and limerence. Methods: Using a cross-sectional design, 1354 adults aged 18 to 51 were recruited via Amazon’s Mechanical Turk to answer a questionnaire about their experiences with cyber dating violence victimization and perpetration, as well as their experiences with cyberbullying and victimization, internalizing symptoms, problematic internet use, attachment styles, and limerence. Results: Results indicated partial mediations for higher scores on measures of insecure attachment (anxious, avoidant) on the relationship between traumatic experiences recalled from early in life and cyber dating violence victimization and perpetration in young adulthood. Moderation results indicated that cyberbullying, cyber victimization, and problematic internet use moderated the influence of traumatic experiences recalled from early life on cyber dating violence experiences in young adulthood. Hierarchical regression analyses indicated several predictors of limerence, such as anxious attachment, internalizing symptoms, and iv vulnerable experiences. Discussion: Findings from the current work move the body of literature forward by illustrating important links between early experiences, attachment styles, cyberbullying, cybervictimization, internalizing symptoms, problematic internet use, limerence, and cyber dating violence perpetration and victimization. v Lay Summary The experience of traumatic events before age of 18 can have a profound impact on relationships throughout life. Specifically, compared to those who report few traumatic experiences early in life, those who report having experienced more trauma in their childhood tend to have greater struggles with relationships in young adulthood, and are more likely to report experiencing, and engaging in, problematic behaviour such as cyber dating violence. This study investigated the relationships between early traumatic experiences, attachment relationships, anxiety and depression, limerence, problematic internet use, cyberbullying and cybervictimization as they relate to cyber dating violence experiences. Findings from this work illustrate that young adults who report experiencing more traumatic experiences before the age of 18 also report more higher levels of cyber dating violence victimization and perpetration. This pattern is worse for those who also report higher levels of insecure attachment styles, problematic internet use, cyberbullying, and cybervictimization. vi Preface The research work of this dissertation is an original intellectual product of the author, Rachel Baitz, conducted under the supervision of Dr. Jennifer Shapka. The research presented in this doctoral work was approved by the University of British Columbia’s Behavioural Research Ethics Board, certificate #H21-02187. vii Table Of Contents Abstract ...................................................................................................................................... iii Lay Summary ............................................................................................................................... v Preface ......................................................................................................................................... vi Table of Contents ...................................................................................................................... vii List of Tables ................................................................................................................................ x List of Figures ............................................................................................................................. xi Acknowledgments ..................................................................................................................... xii Dedication .................................................................................................................................. xiv Chapter 1: Introduction .............................................................................................................. 1 Chapter 2: Review of Literature ................................................................................................ 7 2.1. Cyber Dating Violence ......................................................................................................... 7 2.1.1 Cyber Dating Violence Prevalence ............................................................................... 8 2.1.2 Cyber Dating Violence and Gender Differences ........................................................ 10 2.1.3 Predictors of and Motivations for Cyber Dating Violence Perpetration ..................... 12 2.3 Theories of Aggressive Behaviour ...................................................................................... 15 2.4 Attachment Theory and Aggression .................................................................................... 17 2.5 Vulnerable Childhood Experiences ..................................................................................... 20 2.5.1 Vulnerable Experiences and Dating Violence .................................................................. 22 2.6 Consequences of Vulnerable Experiences and Insecure Attachment Patterns – Links to individual characteristics in predicting Cyber Dating Violence ................................................ 23 viii 2.6.1 Vulnerable Experiences, Cyberbullying, Cybervictimization, and Cyber Dating Violence ............................................................................................................................. 24 2.6.1.1 Cyberbullying Perpetration and Cybervictimization ...................................... 25 2.6.1.2 Cyberbullying, Cybervictimization, and Internalizing Symptoms ................. 27 2.6.1.3 Vulnerable Experiences, Attachment, and Internalizing Symptoms .............. 28 2.6.1.4 Internalizing Symptoms and Cyber Dating Violence ..................................... 30 2.6.2 Limerence ................................................................................................................. 31 2.6.3 Young Adult Internet Use ................................................................................................. 33 2.7 The Current Study ............................................................................................................... 37 Chapter 3: Methods ................................................................................................................... 39 3.1 Measures .............................................................................................................................. 41 3.1 Demographic Variables ....................................................................................................... 41 3.2 Cyber Dating Violence ........................................................................................................ 42 3.3 Vulnerable Experiences ....................................................................................................... 43 3.4 Young Adult Attachment Styles .......................................................................................... 44 3.5 Cyberbullying and Cybervictimization ............................................................................... 45 3.6 Internalizing Symptoms ....................................................................................................... 45 3.8 Problematic Internet Use ..................................................................................................... 48 Chapter 4: Results ..................................................................................................................... 50 4.1 Analyses ............................................................................................................................... 50 Chapter 5: Discussion ................................................................................................................ 68 5.1 Strengths and Limitations .................................................................................................... 77 ix Chapter 6: Conclusions ............................................................................................................. 81 References ................................................................................................................................... 83 Appendix 1 ................................................................................................................................ 118 Appendix 2 ................................................................................................................................ 120 x List of Tables Table 1. Demographic Information ............................................................................................. 42 Table 2. Exploratory Factor Analysis Of The Items Of The Limerence Scale ........................... 47 Table 3. Study Measures .............................................................................................................. 49 Table 4. Descriptive Statistics ..................................................................................................... 50 Table 5. Bivariate Correlations Of Study Variables .................................................................... 51 Table 6. Logistic Regression Analysis Of Variables Affecting Cyber Dating Violence Victimization Membership ................................................................................................. 62 Table 7. Logistic Regression Analysis Of Ves, Cyberbullying, Age, And Gender Affecting Cyber Dating Violence Perpetration Membership ............................................................. 63 Table 8. Logistic Regression Analysis Of Ves, Problematic Internet Use, Age, And Gender Affecting Cyber Dating Violence Perpetration Membership ............................................. 65 Table 9. Hierarchical Regression Predicting Limerence By Avoidant Attachment, Anxious Attachment, Internalizing Symptoms, Vulnerable Experiences, And Problematic Internet Use. ..................................................................................................................................... 67 xi List of Figures Figure 1. Relationships between childhood Vulnerable Experiences, Attachment, Problematic Internet Use, Limerence, Cyberbullying, Cybervictimization, and Internalizing Symptoms on the Relationship Between VEs and CDV Perpetration and Victimization ..................... 6 Figure 2. Mediation path model for avoidant attachment on the relationship between VEs and CDV victimization, over and above gender assigned at birth and age. ............................. 55 Figure 3. Mediation path model for anxious attachment on the relationship between VEs and CDV victimization, over and above gender assigned at birth and age. ............................. 56 Figure 4. Mediation path model for avoidant attachment on the relationship between VEs and CDV perpetration, over and above gender assigned at birth and age. ............................... 58 Figure 5. Mediation path model for anxious attachment on the relationship between VEs and CDV perpetration, over and above gender assigned at birth and age. ............................... 59 Figure 6. Probability of CDV victimization group membership based on the moderation of cybervictimization on the relationship between VEs and CDV victimization. .................. 62 Figure 7. Probability of CDV perpetration group membership based on the moderation of cyberbullying on the relationship between VEs and CDV perpetration. ........................... 64 Figure 8. Probability of CDV perpetration group membership based on the moderation of problematic internet use on the relationship between VEs and CDV perpetration. ........... 66 xii Acknowledgments This work was conducted in a variety of unceded Indigenous territories across North America, and written on the traditional, ancestral, and unceded Indigenous territories of the Kwantlen, Á,LEṈENEȻ ȽTE (W̱SÁNEĆ), S’ólh Téméxw (Stó:lō), sc̓əwaθenaɁɬ təməxʷ (Tsawwassen), sq̓əc̓iy̓aɁɬ təməxʷ (Katzie), Semiahmoo, and Coast Salish First Nations. Though this work does not directly investigate the lived experiences of Indigenous individuals, we must remain aware of how our work as researchers impacts, and is impacted by, colonialism. Further, due to embedded racism, we must also acknowledge that the topics covered in this dissertation, such as traumatic experiences and cyber dating violence, are disproportionately experienced intergenerationally by Indigenous peoples. “It does not matter how slowly you go so long as you do not stop.” Confucius Though a dissertation is attributed to one author, its work is supported by many others in the background who guide, champion, console, and celebrate the person completing the work. Firstly, I would like to thank my supervisor, Dr. Jennifer Shapka, who remained my cheerleader during the inundation of health challenges throughout the doctoral process. You have left an indelible mark and I have so appreciated your support through this process. Secondly, thank you to my faculty committee members, Dr. Shelley Hymel, Dr. Johanna Sam, and Dr. Marla Buchanan, for your guidance. You have deeply impacted me as a researcher, mentor, and person. Thank you for the many meetings and your excitement about this work. Thirdly, I would like to thank Dr. Brett Holfeld for his steadfast support and mentorship as I navigated the numerous health challenges during my doctoral degree. Your influence has been immeasurable. xiii Next, I would also like to thank the wonderful past and present members of the Developmental Change and Technology Lab (DCTech) at UBC for the teamwork, friendship, and support. To Hezron, Joanna, Leigh, Monique, Michaela, Beck, Rose, Shereen, Tierney, Danielle, Rubab, Takara, Cassandra, Louai, Natasha, and Bowen: I have so appreciated the quiet hours studying side-by-side, the dinners and adventures in cities all over the world, the collaboration, the laughs, the hard work, and the relationships we have built. This dissertation would not have been possible without a several wonderful people. To J. Weiser – your ardent support has been immeasurable in championing me towards exploring the research ideas contained within this dissertation. To K. Bhutia, N. Szucs, K. Annets, B. Gill, and many others who have supported me – each of you has provided me tremendous care. I would also like to thank L. Wourms, J. Hofmann, and W. Belter for their steadfast encouragement, contributing a sounding board on dissertation topics, and holding me up in very challenging times. To my friends and family – thank you for your patience, check ins, and kind words. I would also like to extend a special thank-you to each of the wonderful people who participated in my research. My deepest gratitude for your time and honesty in your responses. I am also grateful for the financial support of the Social Sciences and Humanities Research Council of Canada, UBC Faculty of Graduate Studies Graduate Student Awards, and the UBC Department of Educational and Counselling Psychology and Special Education. Finally, to my husband, Graeme. There are truly no words to convey the support you have provided me as I navigated this process. Your belief in me, every moment of every day, has been vital in helping me complete this work. This road has been just as long for you, and I know your excitement matches mine as I complete this journey and move on to the next adventure! xiv Dedication This dissertation is dedicated to anyone who has experienced childhood trauma. It is for every person who, as an adult, is struggling in their relationships and working to uncover their healing and truth. I hope that this dissertation can provide clarity, validation, and inspiration – healing is possible. 1 Chapter 1: Introduction Today’s young adults, recently referred to as both Millennials (born after 1980; Dimock, 2019) and Generation Z (born after 1996; Dimock, 2019), are the first group of young people to have fully grown up in the technological generation. The advent of social media in the early 2000s changed the trajectory of the way young people access information and entertainment, as well as connect to others. Indeed, many of today’s young adults’, or those between the ages of 18 and 40, digital lives first began on early social networking and social media sites on desktop computers, followed closely by smartphones. This has resulted in a current generation of young adults whose lives have been online long before they reached adulthood. For this generation, the online world is not “technologically advanced” as it has been for previous generations. It is simply their world. Unlike previous generations, access to technology has become easier for the general population of young people. As many as 96% of American young adults report owning their own digital device capable of accessing the internet (Anderson & Jiang, 2018). The ease of access to technology can have many benefits for young adults, as it creates an environment in which young people deepen and maintain relationships (Lenhart, 2015; Mishna, McLuckie, & Saini, 2009; Temple & Choi, 2014), explore the self (Beals, 2010), and access social support (Lenhart, Anderson, & Smith, 2015). Importantly, technology allows for ongoing conversations and self-disclosure between friends – an essential milestone of development (Buhrmester & Prager, 1995; Temple & Choi, 2014; Valkenburg & Peter, 2007). As technology becomes increasingly engrained in the everyday lives of young people, there is less and less distinction between “online” and “IRL”(in real life). 2 Given that young people do not necessarily separate online interactions with those that occur face-to-face in real life, the ways in which relationships are built and maintained go beyond technology itself. Early adulthood is a time of rapid individuation, identity development, and change (Arnett, 2000). Like generations before, Millennials and Generation Z are currently making big transitions into more “adult” lives. For example, the transition into and out of college/university or new job/career transitions can bring about large changes to the living arrangements, social contacts, and relationships for young adults (Wood, Voth Schrag, & Busch-Armendariz, 2020). As young adults continue to psychologically (and physically) move away from familial relationships (Nelson, Padilla-Walker, Christensen, Evans, & Carroll, 2010) towards peer and romantic relationships, a greater number of social interactions are occurring via digital devices (Draucker & Martsolf, 2010). In the current technological age, mobile devices play a critical role in connecting young adults to their peers (Lenhart, 2015), particularly in the time of Covid-19 (Cai et al., 2021). In this way, digital communication is enhancing relationships (Lenhart, 2015; Mishna, McLuckie, & Saini, 2009; Temple & Choi, 2014; Valkenburg & Peter, 2007), as technology facilitates social interaction, even in the physical absence of one’s peers. Unfortunately, there are also drawbacks to the increased use of technology among young adults. The ease of use facilitates the ability for users to engage in nefarious behaviour and yet remain anonymous (Hinduja & Patchin, 2013), which provides an opportunity for aggressive acts to occur online. Indeed, spending more time engaging with screens is linked to increased risk for being victimized by others online (Mosley & Lancaster, 2019). Unsurprisingly, this illustrates that typical problems that arise in real life for young adults, such as bullying (Howard, Debnam, & Strausser, 2019; Reed, Tolman, & Ward, 2016, Wright, 2017) and dating violence (Draucker & Martsolf, 2010), have moved online. The issues of being victimized online are particularly 3 grievous (Stonard, 2019) as they are highly associated with experiences of internalizing symptoms, such as anxiety, depression, and even suicide (Cripps & Stermac, 2018; Hinduja & Patchin, 2010; Medrano, Rosales, & Gámez-Guadix, 2018; Juvonen & Gross, 2008; Medrano, Rosales, & Gámez-Guadix, 2018; Pabian & Vandebosch, 2016; Wood, Voth Schrag, & Busch-Armendariz, 2020). Unlike traditional forms of victimization, such as physical bullying, victims of cyber forms of violence are unable to escape their perpetrators, as posts and comments follow victims into their homes and bedrooms (Mishna, Regehr, Lacombe-Duncan, Daciuk, Fearing, & Van Wert, 2018). Further, online forms of aggression that are shared and posted multiple times remain online, in various forms, forever. These factors make cyber forms of aggression distinct from traditional face-to-face forms, and may contribute to the comparatively worse mental health impacts seen in the literature (Cripps & Stermac, 2018; Juvonen & Gross, 2008; Wood, Voth Schrag, & Busch-Armendariz, 2020). Relationships moving into online contexts have created new ways to perpetrate aggression against romantic partners (Draucker & Martsolf, 2010), leading to cyber dating violence (CDV). To this point, emerging research has found that technology is often used as a way to control others, particularly dating partners (Stonard, Bowen, Walker, & Price, 2017). Online communication may also increase the opportunity for other less understood romantic phenomena. Specifically, limerence is an overwhelming experience akin to falling in love, often leading to stalking and self-harm (Willmott & Bentley, 2015). It is not well understood how these experiences are impacted by the increased use and access to technology, and more specifically, how motivations to stalk a potential romantic partner play out in the anonymity and accessibility of online worlds. While digital contexts are new, aggressive behaviour and 4 relationship problems are certainly not. The current study explored the understudied factors that are associated with CDV in order to better understand CDV in young adults. Though decades of research has been poured into understanding dating violence and aggressive behaviour, much is still unknown about how it develops and sustains across childhood and into young adulthood, particularly in a digital context. Theories of social development do well to explain trajectories of development that lead to aggressive behaviour online. For example, the importance of caregiver influence is emphasized by Attachment Theory (Bowlby, 1969). Specifically, those people with whom a child forms the closest bonds have the greatest influence on a myriad of relational outcomes, such as aggressive behaviour (Lowell, Renk, & Adgate, 2014) and even mental health problems and internalizing symptoms (Bakermans-Kranenburg & IJzendoorn, 2009; Bowlby, 1977; Doumas, Pearson, Elgin, McKinley, 2008; Roisman, Holland, Fortuna, Fraley, Clausell, & Clarke, 2007), that are sustained across the lifespan (Bowlby, 1977, Brumbaugh & Fraley, 2006). Early on in life, if the caregiver-child relationship becomes volatile, problems in development arise (Khan, Chong, Theisen, Fraley, Young, & Hankin, 2020) that impact relationships throughout life (Roisman, Holland, Fortuna, Fraley, Clausell, & Clarke, 2007). In fact, in a meta-analysis, researchers have found links between traumatic experiences in childhood (before the age of 18), such as psychological, physical, and sexual forms of abuse, or substance use, mental illness, and criminal behaviour within the family home, and aggressive behaviour later in life (Assink, van der Put, Hoeve, de Vries, Stams, & Oort, 2015). More generally, researchers have consistently found a significant positive relationship between early vulnerable experiences, such as those listed above, and both physical and mental health issues in adulthood (Campbell, Walker, & Egede, 2016; Mostoufi, et al., 2013; Sahle et 5 al., 2021; Zarse, Neff, Yoder, Hulvershorn, Chambers, & Chambers, 2019). Early experiences before the age of 18 that put youth at increased risk of maladaptive outcomes will be described in the current work as Vulnerable Experiences (VEs). In other words, VEs are events or experiences that occur early in life (typically before the age of 18) that leave a child more vulnerable to maladaptive outcomes later in life, for example, anxiety and depression (Felitti et al., 1998; Sahle et al., 2021) and aggressive behaviour (Assink, van der Put, Hoeve, de Vries, Stams, & Oort, 2015). These experiences, such as those mentioned above, increase the vulnerability to maladaptive outcomes for the individual as an adult (Felitti et al., 1998; Sahle et al., 2021). As such, they will be discussed as they relate to attachment, individual psychosocial factors, and CDV victimization and perpetration. The current work focuses on understanding cyber forms of dating violence as a function of early experiences, attachment patterns in adulthood, and other variables that have been shown to increase the risk and opportunity for cyber forms of aggression in early adulthood. Specifically, the current work investigated the poorly understood mechanisms through which early VEs translate to later aggressive behaviour that occurs online. Given the new technological world in which young people have found themselves, the overarching objective of the current work is to investigate (1) how digital outcomes, such as cyber dating victimization and perpetration, occur as a function of early experiences; (2) how insecure attachment styles mediate the effect of early experiences on cyber dating violence; and (3) how individual-level factors, such as internalizing symptoms, problematic internet use, limerence, and cyberbullying/cybervictimization moderate the relationships between VEs and cyber dating violence victimization and perpetration, respectively (Figure 1). 6 Figure 1. Relationships between childhood Vulnerable Experiences, Attachment, Problematic Internet Use, Limerence, Cyberbullying, Cybervictimization, and Internalizing Symptoms on the Relationship Between VEs and CDV Perpetration and Victimization 7 Chapter 2: Review of Literature 2.1. Cyber Dating Violence As young adults begin to move away from home and distance themselves from their families physically, they also continue to emotionally and psychologically distance, a process that continues from adolescence (Arnett, 2000). During this time, they also begin to form deeper bonds with peers, including close friends, roommates, and importantly, romantic partners (Arnett, 2000). Particularly concerning during this transitional time is the violence that can occur between romantic partners, known as dating violence. Historically speaking, acts of dating violence include physical and emotional harm to a dating partner (Koss, Gidycz, & Wisniewski, 1987). Considering the ubiquity with which young people utilize technology for everyday social interactions, it is unsurprising that acts of aggression between young adult dating partners has moved online, a phenomenon known as cyber dating violence (CDV). Cyber forms of dating violence occur in a myriad of ways, ranging along a spectrum from benign to very serious. For example, at the benign end of the spectrum, it can include seemingly innocuous behaviours, such as viewing the social media accounts of partners. While viewing the accounts of one’s partner can be somewhat normalized and unoffending in many relationships (Howard, Debnam, & Strausser, 2019; Reed, Tolman, & Ward, 2016), such behaviour can quickly escalate when a partner begins to demand to view messages (texts, social media) and have password access to online accounts, sending aggressive text messages, controlling contacts or deleting others from partners accounts, or non-consensual/obsessive checking in with partners via messages or geographical tracking (Burke, Wallen, Vail-Smith, & Knox, 2011; Stonard, Bowen, Walker, & Price, 2017). Recently, more egregious ways of online sexual victimization have emerged, for 8 example, nonconsensual pornography (also known as “revenge pornography”), or the wide distribution of co-created explicit video/images created by former romantic partners (Lonardo, Martland, & White, 2016), which is viewed as more of an aggressive online act rather than pornography (Myers & Cowie, 2017). It appears that this type of aggression almost exclusively targets women in heterosexual relationships (Uhl, Rhyner, Terrance, & Lugo, 2018), and experiences with nonconsensual pornography can have disastrous impacts on women (Walker & Sleath, 2017). For example, perpetrators often reveal names, addresses, employment information, along with other private details that trace directly to the victim (Franklin, 2014). Further, the explosive increase in the wide use of “deep fake” technology (creating pornographic videos of women from a fully-clothed photo) and artificial intelligence (AI) has also been shown to almost exclusively target women (Ajder, Patrini, & Cavalli, 2020), which makes them particularly vulnerable to CDV. 2.1.1 Cyber Dating Violence Prevalence CDV has emerged as a major issue among young adults, with as many as half reporting having experienced it (Watkins, Benedicto, Brockdorf, & DiLillo, 2020). For young adults currently in a relationship, estimates of CDV victimization are alarmingly high, with some studies reporting up to 75% of young adults having experienced at least some form of CDV in the past (Marganski & Melander, 2018; Toplu-Demirtaş, Akcabozan-Kayabol, Araci-Iyiaydin, & Fincham, 2022; Trujillo, Cantu, & Charak, 2020). Reported prevalence rates vary widely due to differences in measurement approaches (Fernet, Lapierre, Hébert, & Cousineau, 2019), though the high rates of CDV reported in some studies illustrate the pervasiveness of the problem. The emergent nature of research on cyber forms of dating violence and the research methods to investigate it have relied on a variety of recently-developed measures (Borrajo, Gámez-Guadix, 9 Pereda, & Calvete, 2015; Brown & Hegarty, 2018) that often differ in a variety of ways. For example, measures differ in terms of criteria considered part of CDV, whether participants are actively involved in a committed relationship at the time of the CDV perpetration or victimization, and whether the measures intended use is for adolescents versus young adults (given their age, young adults are more likely to report being in a relationship compared to adolescents; Peskin et al., 2017). The current work adds to the current body of literature in understanding CDV prevalence in the American young adult population. Given that research investigating CDV is emergent and has only recently started to occur with increased technology use, it is also necessary to understand how CDV relates to traditional forms of dating violence, which has been studied for decades. For example, recent research by Stonard (2020) found that CDV preceded offline dating violence in that adolescents reported having experienced cyber forms of dating violence in their romantic relationships before instances of physical violence began. While there are several differences between traditional dating violence and CDV in terms of methods of perpetrating violence, several studies have shown links between the two types of dating violence. For example, Reed, Tolman, and Ward (2016) found that CDV was associated with physical, sexual, and psychological dating violence. Similarly, Marganski and Melander (2018) found that cyber dating violence was positively related to in-person psychological, physical, and sexual aggression in-person. While it might be true that physically, sexually, and psychologically aggressive partners also use digital means to perpetrate aggression, given the high number of young people who report only experiencing CDV (and not traditional forms of dating violence; Hellevik, 2019; Wood, Voth Schrag, & Busch-Armendariz, 2020), as well as data illustrating CDV may precede experiences of 10 traditional dating violence, the current work moves the body of literature forward in understanding cyber forms of dating violence as they relate to the young adult population. In terms of age, preliminary research on CDV has found the prevalence to be higher among young adults (in this study, ages 22 to 25) compared to those who have recently left high school (Van Ouytsel, Ponnet, & Walrave, 2017). Interestingly, research on traditional forms of dating violence have also reported differences in prevalence based on age. For example, Tyler and Melander (2012) found that young adults closer to age 25 experience more traditional forms of dating violence compared to teens at the age of 19, whereas White and Smith (2009) found that acts of dating aggression decrease between adolescence and early adulthood, and average rates of dating abuse were found to be higher among adolescents (Bonomi, Anderson, Nemeth, Rivara, & Buettner, 2013; Bonomi, Anderson, Nemeth, Bartle-Haring, Buettner, & Schipper, 2012) compared to young adults (ages 18-25), on average. These findings illustrate there may be importance differences between traditional forms of dating violence and cyber forms of dating violence, and given the alarmingly high rates of CDV in young adult populations (Watkins, Benedicto, Brockdorf, & DeLillo, 2020), the current work focusses on CDV victimization and perpetration as a function of age throughout young adulthood. 2.1.2 Cyber Dating Violence and Gender Differences As mentioned above, it appears that women are exclusively targeted for certain types of CDV, such as revenge pornography and deep fakes; however, they are also disproportionately targeted for all other forms of CDV (Wood, Voth Schrag, & Busch-Armendariz, 2020). This is regardless of whether they are in a current relationship, which is a pattern that mimics traditional forms of dating violence (Humphrey & White, 2000; Koss, Gidycz, & Wisniewski, 1987; Sutherland, Fantasia, & Hutchinson, 2016; Tyler & Melander, 2012). In terms of perpetration, 11 researchers have consistently reported that men are more often the perpetrators of CDV (Deans & Bhogal, 2019; Er, Murat, Yílmaz, & Buzlu, 2022; Shorey, Brasfield, Zapor, Febres, & Stuart, 2015), though one group of authors have reported slightly more perpetration among women (Toplu-Demirtaş, Akcabozan-Kayabol, Araci-Iyiaydin, & Fincham, 2022), a difference that may also be attributable to differences in how cyber dating perpetration is measured in different studies. Researchers have also found gender differences in victimization in that more women than men report having been victimized (Jennings, Okeem, Piquero, Sellers, Theobald, & Farrington, 2017; Sánchez-Jiménez, Rodríguez-deArriba, & Muñoz-Fernández, 2022; Zweig, Dank, Yahner, & Lachman, 2013; Zweig, Lachman, Yahner, & Dank, 2014), and that compared to women, men are more likely to view their own aggressive behaviour as neutral, or nonharmful (Stonard, 2020). Further, men who report perpetrating physical violence against their partner are also more likely to perpetrate cyber forms of violence, a pattern not shown among women (Watkins, Benedicto, Brockdorf, & DeLillo, 2020). In fact, to date, no study has found that men experience higher rates of CDV, and only two found no gender differences (Reed, Tolman, & Ward, 2017; Smith, Cénat, Lapierre, Dion, Hébert, & Côté, 2018). It should be no surprise, then, that women experience disproportionately more physical and psychological harm from CDV than men (Dardis, Dixon, Edwards, & Turchik, 2015; Reed, Tolman, & Ward, 2016; Stonard, 2020; Sánchez-Jiménez, Rodríguez-deArriba, & Muñoz-Fernández, 2022). In particular, female victims of CDV are more likely to report experiencing internalizing mental illnesses and symptoms, for instance, depression, stress, anxiety, and Post Traumatic Stress Disorder (PTSD), in response to having been victimized online by a romantic partner (Cripps & Stermac, 2018; Wood, Voth Schrag, & Busch-Armendariz, 2020). This is in line with findings regarding 12 traditional forms of dating violence, for which living in fear is often reported by women who have experienced dating violence, a pattern not seen among men (Burton, Halpern-Felsher, Rehm, Rankin, & Humphreys, 2013). Moreover, women who report being victimized by partners are significantly less likely than those who have not been victimized to advocate for their sexual health within the dating relationship (Peasant et al., 2018). These findings consistently illustrate the fact that women are disproportionately victimized in acts of online violence by their partners relative to men, including through egregious acts such as revenge pornography (Uhl, Rhyner, Terrance, & Lugo, 2018), as well as upskirt videos (videos secretly shot with cellphone cameras up a person’s skirt) and deep fake videos (Chesney & Citron, 2019; Kirchengast & Crofts, 2019). It should be mentioned, that the abovementioned acts of violence are one of the more distressful and damaging CDV experiences that a woman can experience (Stonard, 2020). Interestingly, little is known about LGBTQIA+ (sexual and gender minority) youth and their experiences of CDV in young adulthood. Specifically, no research has been conducted to date to help better understand how gender expansive young adults (anyone who does not identify as cisgender, such as nonbinary, transgender, or agender people) experience CDV. Given the disproportionately female victimization rates of relationship violence and the lack of understanding of CDV among gender expansive individuals, the current research will addresses the gap in the literature to better understand the mechanisms that underly CDV perpetration and victimization in men, women, and gender expansive individuals. 2.1.3 Predictors of and Motivations for Cyber Dating Violence Perpetration To date, the underlying etiologies of CDV among young people remains unclear. Preliminary correlational work has found that jealousy and hostility (Deans & Bhogal, 2019) as well as problematic internet use (Mosley & Lancaster, 2019), predict CDV. To date, a lack of 13 both correlational and longitudinal research has investigated predictors of CDV that relate to a person’s own experiences with aggression. To better understand potential predictors, it may be helpful to investigate the literature on traditional forms of dating violence. For example, in a review of findings from research on traditional forms of dating violence, Jennings and colleagues (2017) identified a number of risk factors related to traditional forms of dating violence, including depression, exposure to violence, anger problems, and peer violence. Leisring (2013) found that the very small percentage of female perpetrators of traditional forms of dating violence report having perpetuated aggression out of anger, retaliation for emotional hurt at the hands of their partner, and jealousy, rather than self-defense. Further, this finding is interesting in terms of cyber forms of dating violence in that online self-defense may look a lot like perpetrating aggressive acts if the victim engages in any retaliatory behaviour, for example, sending aggressive messages to the perpetrator requesting them to stop, or monitoring the accounts of partners in order to catch or stop the sharing of private videos, etc. What isn’t known is whether other factors, such as the personal histories of abuse or trauma might also be related to CDV perpetration, a question that is addressed in the current work. A 2015 review of the traditional dating violence literature by Dardis, Dixon, Edwards, and Turchik confirmed differences between men and women’s dating violence perpetration. Young men’s dating violence perpetration related to low socioeconomic status (SES), lower level of education, antisocial personality traits as well as increased relationship length. For women, they found that perpetration was related to internalizing symptoms, trait anger, and having experienced dating violence perpetration, a finding that is in line with Leisring’s (2013) work. Unfortunately, no other studies have investigated CDV perpetration in terms of gender 14 differences or other individual factors that may predict CDV perpetration. The current research addresses the gap in the literature for CDV perpetration by investigating a myriad of risk factors for CDV among young adults, especially as they relate to memories of early VEs. Specifically, it investigated the relationship between VEs and CDV victimization and perpetration. 2.2 Other forms of Cyber Violence Given the focus of the current work on factors that predict CDV perpetration and victimization, it is necessary to also consider other forms of cyber violence. Online violence does not just occur within dating relationships; cyberbullying and cybervictimization (also known as cyber-aggression, online aggression, or electronic bullying), defined as aggressive behaviours carried out via electronic mediums that are intended to harm another person or group of persons (Corcoran, McGuckin, & Prentice, 2015; Tokunaga, 2010), are also commonplace. Cyberaggression occurs across the social spectrum - among friends, acquaintances, and unknown others (Tokunaga, 2010). Though cyberbullying and cybervictimization are often considered issues of most concern during the grade school years, researchers have increasingly emphasized that both are also highly problematic for young adults in the years after high school (Brody & Vangelisti, 2016; Lee, 2017; Wong, Cheung, & Xiao, 2018), and may even lead to CDV (Turner, Mitchell, & Jones, 2020). In fact, links have also been found between traditional forms of bullying and offline relationship violence (Connolly, Pepler, Craig, & Taradash, 2000). While the mechanisms linking cyberaggression and CDV are still unknown, like CDV, women are more likely to experience cyber forms of victimization (AI-Qudah et al., 2020; Lee, 2017; Reyns, Burek, Henson, & Fisher, 2013). Similar to the findings in the literature on cyber forms of dating violence, not only are young women more likely to be targeted on the topic of sexual activity (Brody & Vangelisti, 2016), they are more likely than men to experience negative reactions to 15 sexual messaging (Reed, Tolman, & Ward, 2016) and suffer poorer body image following experiences of having been cyber victimized (Calvete, Orue, & Gámez-Guadix, 2016). Fortunately, links between CDV and other forms of online aggression, such as cyberbullying and cybervictimization, are beginning to emerge in the literature on CDV (Caridade, Braga, & Borrajo, 2019; Peskin et al., 2017). Given that previous research illustrates cyberbullying and cybervictimization as a temporal predictor of CDV, the current study explores these variables as predictors of CDV victimization and perpetration. 2.3 Theories of Aggressive Behaviour Aggressive online behaviours among young adults does not occur in a vacuum. There are often multiple motivations and events that occur in a young person’s life to increase leanings towards aggressive behaviour in the case of both cyberbullying and CDV (Deans & Bhogal, 2019; Fanti, Demetriou, & Hawa, 2012; Kokkinos & Voulgaridou, 2017; Lazuras, Barkoukis, Ourda, & Tsorbatzoudis, 2013; Marganski & Melander, 2018; Reed, Tolman, & Ward, 2016). Even before researchers were investigating etiologies of cyber forms of violence, they were trying to understand aggressive behaviour. As such, theories of aggressive behaviour have been developed and have been very helpful in understanding how aggressive behaviour emerges over time. Typically speaking, the majority of theories that explain traditional aggressive behaviours focus on the histories and past experiences of individuals. Social Learning Theory (Bandura, 1977) and Intergenerational Transmission of Violence (O’Leary, 1988) are two theories that have often been used to describe the process of younger generations learning aggressive behaviours from watching the aggressive actions of their caregivers. Both of these theories emphasize the impact of modelling behaviour of caregivers. In other words, children are likely to repeat the actions and behaviours that they witness within the 16 family as they grow up, and in particular, their closest caregivers. While it might be true that young people learn general aggressive behaviour via the modelling of adults, and translate that into cyber domains, such arguments may not be fully sufficient in explaining online forms of aggressive behaviour for several reasons. First, compared to traditional forms of violence wherein young people are privy to the aggressive acts among caregivers in the home (Temple, et al., 2018), younger generations are unlikely to witness online aggressive behaviours (personal text and direct messages, online posts on various sites, a caregiver using a partners passwords to access accounts, revenge pornography) of their caregivers, and they are unlikely to see physical manifestations such as scars and marks as one might in cases of physical violence. Paradoxically, instead of traditional types of physically aggressive acts which often occur in the privacy of one’s family home, digital forms of violence are less likely to be detected by children to the same degree, as they are occurring in cyberspace. Second, theories that focus on the witnessing of violence in explaining later violent behaviour neglect consideration of the individual effects of stress from witnessing violence on young people. The stress of witnessing violence at a young age is certain to initiate irreversible changes in the individual, resulting in a cascade of changes to the brain and associated behaviours (Danese & McEwen, 2011; Jones-Mason, Allen, Bush, & Hamilton, 2016). The element of stress on the developmental trajectory is essential in understanding behaviour (Jones-Mason, Allen, Bush, & Hamilton, 2016). It is therefore necessary to investigate the myriad of experiences young people have in their relationships with their caregivers from an early age, and how those experiences predict later aggressive online behaviours. While longitudinal research has yet to look at early experiences and later CDV, it has investigated the relationships between early experiences and later traditional forms of dating 17 violence to inform the current research. For example, Narayan, Labella, Englund, Carlson, & Egeland (2017) found that individuals whose parents reported tumultuous parental relationships also reported more relationship violence when they reached adulthood. Further, a recent cross-sectional study investigating the early life experiences of women found that those who reported higher levels of traditional forms of dating violence also reported histories of parental neglect, violent experiences, and sexual abuse during childhood (Cale, Tzoumakis, Leclerc, & Breckenridge, 2017). Finally, in one of the few studies exploring digital cyber aggression, researchers in Belgium found that young women who observed intrusive and controlling behaviour by their fathers were more likely to engage in problematic digital monitoring of their partners (Van Ouytsel, Ponnet, & Walrave, 2017). While the mechanism behind the relationships between early experiences and later victimization is unclear, understanding aggression in young adulthood must look deeper into the mechanisms that underlie aggression to better understand the relationships between caregivers and children. As such, the current study sought to understand CDV as it relates to problems within the caregiver-child relationship in predicting later violence in an online setting. 2.4 Attachment Theory and Aggression One of the fundamental mechanisms of the caregiver-child interactions, as well as within adult romantic partnerships, is attachment, defined as the affectional bonds formed early in life with primary caregivers (Bowlby, 1969) that in turn shape affectional bonds, known as attachment styles, with others (Bakermans-Kranenburg & IJzendoorn, 2009; Bowlby, 1977). These affectional bonds or attachment styles set the stage for all later relationships, including those during young adulthood (Brumbaugh & Fraley, 2006; Jensen, Willoughby, Holman, Busby, & Shafer, 2015; Lowell, Renk, & Adgate, 2014), and most often, remain stable across the 18 lifespan (Bowlby, 1977; Brumbaugh & Fraley, 2006). In the current work, attachments can form as a result of early life experiences and impact later relationships (Figure 1). Attachment theory states that children who grow up with caregivers who are in tune with their needs and able to predictably respond to needs are more likely to be securely attached. Securely attached children are able to predict the behaviour of their caregivers, and rely on their caregivers to be attuned to their needs (Bowlby, 1977). Conversely, problems in attachment, known as attachment trauma or attachment injury, begin to arise in cases where caregivers are not able to reliably attune to the needs of the child (Spinazzola, Kolk, & Ford, 2021). Caregivers who are unresponsive to the needs of a child, threatening towards the child, controlling, rejecting, or abandoning, create an environment in which a child cannot predict or depend on their caregiver to be a secure base from which to explore the world. When this occurs, it is known as insecure attachment (Bowlby, 1977). Unfortunately, in cases where secure attachments do not emerge, higher levels of insecure attachment can form in one of two relatively uncorrelated ways (Simpson & Rholes, 2012). For example, if a child begins living in constant fear of losing the attachment figure, an anxious attachment pattern can develop (Bowlby, 1977). Higher levels of anxious forms of attachment lead to adults who are often labelled as “needy”. This type of attachment style has been shown to be more common in female than in male young adults and tends to influence relationships the most during young adulthood (Del Guidice, 2011). Alternatively, in instances where the caregiver exerts extreme levels of guilt on a child and requires the child to act as an attachment figure for the parent, the child grows up to become an adult who has the expectation that they must be responsible for others (Bowlby, 1977). Higher levels of this form of attachment insecurity is termed avoidant attachment. Those who have higher levels of avoidant attachment report that they are less invested in their romantic 19 relationships as adults (Simpson & Rholes, 2012), which has been shown to be more common in young adult men (Del Guidice, 2011). By the time the child reaches adulthood, higher levels of anxious styles of attachment can present as immaturity, neediness, neurotic behaviour, depression, or fearfulness (Bowlby, 1977), while higher levels of avoidant styles of attachment in childhood often lead to adults who are overly conscientious, struggle with feelings of guilt, as well as the same markers of anxious attachments (Bakermans-Kranenburg & van IJzendoorn, 2009; Bowlby, 1977; Doumas, Pearson, Elgin, & McKinley, 2008). High levels of insecure attachment (both anxious and avoidant) has been linked to increased aggression during the teenage years and in young adulthood. A study by Doumas, Pearson, Elgin, and McKinley (2008) found that compared to other types of pairings, the romantic pairing of a highly anxiously attached female with a highly avoidantly attached male significantly predicted traditional forms of dating violence. Their research also found that, for males only, having higher levels of insecure attachment predicted later traditional forms of partner violence. Further illustrating the importance of parental relationships, a study by Sutton, Simons, Wickrama, and Futris (2014), found that higher levels of insecure attachment styles mediated the relationship between experiencing parental hostility as a child and later dating violence. Finally, results of a cross-sectional study by de Vries, Hoeve, Stams, Asscher, and Dekovic (2016) indicated that greater levels of insecure attachment styles predicted traditional types of aggressive behaviour for adolescents as old as 19, though this study did not specifically investigate partner violence. Given what is known about attachment patterns across the lifespan, it is clear that early experiences and relationships set the stage for later relationships in young adulthood. Indeed, when the relational environment in which a child grows up is filled with turmoil, attachment is negatively affected (Frías, Brassard, & Shaver, 2014; Murphy et al., 2014; 20 Thomson & Jaque, 2017) and a variety of mental health and relationship problems arise later in life (Anda, et al., 2005; Felitti et al., 1998; Metzler, Merrick, Klevens, Ports, & Ford, 2017). While the abovementioned findings illustrate links between early experiences, attachment, and dating violence, the studies did not look at relationships between all three of the factors together and did not consider cyber forms of dating violence. The current research filled this gap in the literature by taking a greater number of factors into account in investigating their links to CDV. Specifically, the current work investigated the mediating effects of higher levels of insecure attachment on the relationship between self-reported memories of early relational experiences, or Vulnerable Experiences (VEs) on later CDV victimization and perpetration to explore how the effects of early bonds between caregiver and child are linked to CDV victimization and perpetration. 2.5 Vulnerable Childhood Experiences Over the last three decades, researchers have begun to investigate the impact of early experiences with caregivers within the family home, called Adverse Childhood Experiences (Felitti et al., 1998), in understanding maladaptive outcomes later in life. The earliest adverse childhood experiences studies involved researchers investigating a series of 17 events occurring during childhood, including psychological, physical, or sexual abuse, and/or household dysfunctions such as incarcerated caregivers, mental illness/substance abuse within the home, or one’s mother being treated violently by a member of the household. They found a cumulative effect for those who had experienced a greater number of adverse childhood experiences before the age of 18 and maladaptive outcomes later in life. Specifically, they found that individuals with greater than 4 adverse childhood experiences were significantly more likely to experience depression, drug abuse, suicide attempts poorer physical and mental health across the lifespan, 21 findings which have been replicated in subsequent research (Felitti et al., 1998; Mersky, Topitzes, & Reynolds, 2013; Murphy et al., 2014). The adversities listed above are events that occur between the person and their caregivers and within the family home. In other words, with those whom a person is most closely attached, before the age of 18. More recently, researchers have looked beyond the original 17 adverse childhood experiences and associated health outcomes to investigate links between a slightly wider variety of early experiences and later psychosocial outcomes outside of the immediate family. In the current work, these adversities are predicted to disrupt the family relationships and affect attachment patterns (Figure 1). Beyond the family, adversities within the community, such as racism, low socioeconomic status, and housing precarity, and neighbourhood violence, can result in similar outcomes later life, such as aggression, poorer mental health, and poorer physical health outcomes (Cronholm et al., 2015; Finkelhor, Shattuck, Turner, & Hamby, 2013; Tyler & Melander, 2012). Further, peer victimization and neglect have recently been proposed as VEs for Lesbian, Gay, Bisexual, Transgender, Questioning, Intersex, and Asexual (LGBTQIA+) individuals (Schnarrs, Stone, Bond, Salcido, Dorri, & Nemeroff, 2022; Schnarrs, Stone, Salcido, Baldwin, Georgiou, & Nemeroff, 2019). To date, little is known about gender expansive and sexual minority young adults and their unique experiences of VEs. Given the paucity of research on the impact of the community in the experiences of VEs and later CDV, links between adversities within the community that are most likely to impact the individual were investigated in the current research. Given that the current work goes beyond adverse childhood experience investigation to evaluate additional risk factors within the community, the current work will refer to adverse childhood experiences/early adversities as Vulnerable Experiences (VEs). 22 2.5.1 Vulnerable Experiences and Dating Violence Research has specifically illustrated that a greater number of VEs in early life are associated with aggressive behaviour in dating relationships later in life. For example, Davis, Ports, Basile, Espelage, and David-Ferdon (2019) found an association between adverse experiences (such as sexual, physical, emotional violence, experiences of victimization, violence/substance use within the home) early in life and later traditional forms of dating violence during the teen years. While their work did not investigate cyber forms of dating violence or attachment patterns specifically, they did find buffering effects related to parental relationships in that parental monitoring reduced the trajectory between adverse experiences and later dating violence. Similarly, in a large-scale study of early childhood experiences and later partner aggression, Brown, Perera, Masho, Mezuk, and Cohen (2015) also found links between a greater number of VEs and later dating violence, though the authors also did not investigate cyber forms of violence or attachment relationships. Another study that looked at cyber forms of dating violence found that young people who had experienced more adverse experiences earlier in life were more likely to engage in CDV (Gilchrist, Canfield, Radcliffe, & D’Oliveira, 2017). Recent research by Celsi, Paleari, and Fincham (2021) not only found that emotional abuse during childhood predicted CDV perpetration in adulthood, but also exposure to intimate partner violence of opposite-sex parents predicted CDV perpetration later in life. A similar study by Fereidooni, Daniels, and Lommen (2022) found that childhood maltreatment by caregivers predicted CDV victimization in early adulthood. While each of the abovementioned studies investigated the various factors associated with early experiences and later aggression occurring within relationships, to date, no research that has investigated the effect of VEs and attachment on CDV in young adults. 23 Given the fact that VEs early in life most often occur within those relationships closest to the individual, such as caregivers (described earlier), it stands to reason that the attachment relationships a person has with their caregivers plays a role in not only understanding how VEs impact a person, but also how VEs impact attachment patterns. While the current study did not investigate past attachments to caregivers, it did investigate adult attachment patterns, which have been show to remain stable from childhood into young adulthood and closely mimic the attachment patterns an adult previously had with caregivers (Brumbaugh & Fraley, 2006; Jensen, Willoughby, Holman, Busby, & Shafer, 2015; Lowell, Renk, & Adgate, 2014). Indeed, this dissertation proposes that problems within the early relational mechanisms often then lead to making choices that in turn lead to negative repercussions in one’s dating relationships. For the current generation of young people, those choices often emerge as partner aggression online. Understanding CDV based on early experiences is about more than just vulnerable experiences that a person might have had in their past. Vulnerable experiences create instability within a lifetime of relationships, resulting in higher levels of insecure attachments with others. When a young person learns that he or she cannot rely on those around them for emotional, physical, and psychological safety, they are forced to develop mechanisms, such as aggressive online behaviour, to cope. 2.6 Consequences of Vulnerable Experiences and Insecure Attachment Patterns – Links to individual characteristics in predicting Cyber Dating Violence Given that VEs and attachment styles develop very early in life compared to CDV (Felitti et al., 1998), the current work explores individual level characteristics that emerge later in life and relate to CDV victimization and perpetration in young adults. Though it is beyond the scope of the current dissertation to deeply explore a myriad of individual level characteristics in a 24 longitudinal fashion, the current research focused on individual level characteristics that have been shown to predict and relate to CDV as moderators of the relationship between both early vulnerable experiences and attachment in predicting CDV. Specifically, cyberbullying and cybervictimization, internalizing symptoms, limerence, and problematic internet use were investigated (Figure 1). Given the paucity of research on each of the variables together in concert (VEs, attachment, cyberbullying/cybervictimization, internalizing symptoms, limerence, problematic internet use, and CDV), little is known about how each of the factors relate among young adults. 2.6.1 Vulnerable Experiences, Cyberbullying, Cybervictimization, and Cyber Dating Violence Very little is understood about how VEs, attachment, cyberbullying, and cybervictimization directly relate to CDV in young adulthood. To date, researchers have yet to investigate all four phenomena together. Instead, links between all four phenomena can be found by investigating various pockets of research that illustrate the possible relationships between one or two of the above-listed variables (VEs, attachment, cyberbullying and cybervictimization, and CDV). For example, while a recent study found that adolescents who had reported experiencing sexual abuse in childhood (one type of VE) were significantly more likely to report having engaged in cyberbullying perpetration (Hébert, Cénat, Blais, Lavoie, & Guerrier, 2016), however, this work did not investigate attachment styles or CDV. An abovementioned study that did investigate attachment styles by Sutton, Simons, Wickrama, and Futris (2014), found that high levels of both anxious and avoidant attachment styles mediated the relationship between experiencing parental hostility (one type of VE) as a child and later dating violence. Unfortunately, this study did not investigate cyberbullying or cybervictimization, though studies 25 that have done so have reported positive relationships between cyberbullying, cybervictimization and CDV (Caridade, Braga, & Borrajo, 2019; Peskin et al., 2017). Finally, findings from research on traditional forms of violence have found that young adolescents (grades 5 to 8) who bully are more likely to also start dating younger and view dating partners as less equitable than their peers (Connolly, Pepler, & Craig, 2000). This illustrates the complicated relationships between VEs, attachment, cyberbullying, cybervictimization, and CDV. For ease of reading, the next section will explore cyberbullying and cybervictimization generally, followed by examining the links between cyberbullying and cybervictimization and internalizing symptoms. The section following will incorporate attachment styles with cyberbullying/cybervictimization and internalizing symptoms, before connecting all three variables (cyberbullying/cybervictimization, internalizing symptoms, and attachment styles) to CDV. 2.6.1.1 Cyberbullying Perpetration and Cybervictimization Given that opportunities to engage in cyberbullying/cybervictimization over CDV are higher in childhood and adolescence due to the fact that serious dating is not as prevalent among younger age groups compared to older (only 35% of teens aged 13 to 17 have dated or even “hooked up”; Lenhart, Anderson, & Smith, 2015), understanding cyberbullying and cybervictimization from a younger age might help illustrate a pattern of aggressive online behaviour starting in early adolescence. Developmentally, aggressive online behaviours begin to appear (DePaolis & Williford, 2019), and peak, in elementary school (Lebrun-Harris, Sherman, Limber, Miller, & Edgerton, 2019), suggesting an early start to online aggressive acts. The vast majority of longitudinal research that has investigated etiologies of cyberbullying perpetration has invested middle and high school students and have tended to focus on shorter term longitudinal work in determining predictors of cyberbullying perpetration. For example, early 26 work by Fanti, Demetriou, and Hawa (2012) found that both violent media exposure and callous unemotional traits predicted later cyberbullying perpetration among middle-schoolers one year later. Similarly, a study by den Hamer and Konjin (2015) found that violent media exposure predicted cyberbullying perpetration across a single school year. Finally, Sticca, Ruggieri, Alsaker, and Perren (2013) found that antisocial behaviour predicted cyberbullying perpetration 6 months later in 7th graders. None of the abovementioned studies investigated very early precursors, such as VEs or high levels of insecure attachment, in predicting cyberbullying behaviour. Cross-sectional work has also neglected to investigate cyberbullying as a function of VEs. A meta-analysis by Guo (2016) that analyzed 77 studies made no mention of early or traumatic experiences investigated in any of the studies. O’Conner, Sullivan, Ross, and Marshall (2021) found that early adolescents who experienced the most trauma also reported the greatest aggressive behaviour. Unfortunately, empirical work to date investigating cyberbullying perpetration among young adults has been correlational in nature. For example, cross-sectional research of college-aged adults has found that who report cybervictimization are also more likely to report higher levels of social anxiety (Fahy, Stansfeld, Smuk, Smith, Cummins, & Clark, 2016; Pabian & Vandebosch, 2016), lower levels of both social efficacy (Heiman, Olenik-Shemesh, & Liberman, 2018) and resilience (Hinduja & Patchin, 2017), as well as poorer emotion regulation (Hemphill, Tollit, Kotevski, & Heerde, 2015). Interestingly, cyberbullying and cybervictimization tend to be highly correlated; those who report victimization also report engaging in perpetration (Mishna, Khoury-Kassabri, Gadalla, & Daciuk, 2012; Udris, 2015; Várnai et al., 2020). While little is known about cyberbully-victims among young adults, a meta-analysis by Lozano-Blasco, Cortés-Pascual, and Latorre-Martínes (2020) found that, among adolescents, the correlation between participants being both a bully and a victim was high. In 27 many cases, young people who are victimized fight back against their aggressors with similar acts of cyberbullying perpetration in a “flame war” (Mishna, Khoury-Kassabri, Gadalla, & Daciuk, 2012), a phenomenon that is not seen in traditional types of bullying. Unfortunately, there is a large gap in the literature in understanding how VEs relate to cyberbullying/cybervictimization and CDV, and the current study investigates both cybervictimization and cyberbullying in better understanding CDV among young adults.. The current work addresses the gap in the literature by investigating links between VEs, cyberbullying/cybervictimization, and CDV. 2.6.1.2 Cyberbullying, Cybervictimization, and Internalizing Symptoms Internalizing symptoms have been consistently linked with both cyberbullying and cybervictimization experiences (Holfeld & Baitz, 2020; Holmgren, Dworkin, & Keyzers, 2020). To date, very little research has longitudinally investigated the specific links between young adult internalizing symptoms and cyberbullying and cybervictimization experiences across the lifespan. A deep-dive into the literature produced a dissertation by McComas (2019), which found that emotion dysregulation mediated the relationship between cybervictimization and internalizing symptoms. A qualitative study of four Canadian universities looking at cyberbullying behaviour across students and faculty (Cassidy, Faucher, & Jackson, 2017) found that university students who had reported experiencing cybervictimization described severe mental health impacts, such as anxiety and depression. Investigating the adolescent literature provides a more comprehensive understanding of the relationships between internalizing problems and cyberbullying/cybervictimization, and further illustrates the cyberbullying/cybervictimization at an earlier age than CDV. It has been well-established that cyberbullying/cybervictimization are consistently linked to internalizing 28 symptoms among adolescents (Bonanno & Hymel, 2013; Calvete, Orue, & Gámez-Guadix, 2016; Chang et al., 2015; Fahy, Stansfeld, Smuk, Smith, Cummins, & Clark, 2016; Kircaburun, Demetrovics, Király, & Griffiths, 2020; Tennant, Demaray, Coyle, & Malecki, 2015; Trompeter, Bussey, & Fitzpatrick, 2018; Wright, 2017). Longitudinal research has helped unpack the mechanisms behind the cybervictimization and internalizing symptoms cycle. Research by Rose and Tynes (2015) found reciprocal relationships between both anxiety and depression and cybervictimization over time. Those who were more depressed at time 1 were more likely to be cyberbullied later, resulting in more depressive symptoms at later time points. Likewise, those who reported cybervictimization at time 1 also reported significantly more anxiety at time 2, which predicted more cybervictimization at time 3. While links between cybervictimization and depression and anxiety offer some clues into mental health impacts of cybervictimization, unfortunately, Rose and Tynes’ (2015) study did not investigate anxiety symptoms or links to later CDV. Similar findings by Calvete, Orue, and Gámez-Guadix (2016) and Gámez-Guadix, Orue, Smith and Calvete, (2013) illustrate patterns of poor mental health following experiences of cybervictimization. In fact, findings by Gámez-Guadix, Orue, Smith, and Calvete (2013) further illustrate a reciprocal relationship with mental health outcomes and cybervictimization in a longitudinal study in which they found that depressive symptoms at time 1 predicted more cybervictimization at time 2. What remains unknown is the role of cyberbullying/cybervictimization and internalizing symptoms in the relationship between VEs, and CDV in young adults. The current work addresses this gap in the literature. 2.6.1.3 Vulnerable Experiences, Attachment, and Internalizing Symptoms Research into early experiences and their relationship with internalizing symptoms is well documented. Specifically, Felitti et al. (1998) found associations between maladaptive early 29 experiences (e.g., ACEs) before the age of 18 and internalizing symptoms later on in life. More recently, a longitudinal research study by Schilling, Aseltine, and Gore (2007) confirmed these findings in a group of young adults. Their work also found a cumulative effect in that young adults who recalled having ever experienced adverse events were more likely to report depression two years later. In addition, work by Hamdullahpur, Jacobs, and Gill (2018) found that young adults who experience a greater number of VEs are also more likely to experience mental health issues later in life, such as suicide ideation. In addition to longitudinal work, cross-sectional work has also illustrated links between VEs and anxiety (Reiser, McMillan, Wright, & Asmundson, 2014), depression (Nelson, Padilla-Walker, Christensen, Evans, & Carroll, 2010), and suicide ideation (Hamdullahpur, Jacobs, & Gill, 2018). Clearly, vulnerable experiences early on in life set the stage for mental health issues, though more work is needed to understand the trajectories of mental health between the experiences of VEs and later mental health internalizing symptoms. Beyond VEs, it has also been well-documented that problems that arise within parent-child attachment relationships have been shown to increase both internalizing and externalizing symptoms (Allen, Porter, McFarland, McElhaney, & Marsh, 2007; Brown & Wright, 2003). For example, compared with secure attachment styles, higher levels of insecure styles of attachment have been linked to poor mental health outcomes such as depression (Hortaçsu, Cesur, & Oral, 1993), and suicidal ideation (Lessard & Moretti, 1998; Nunes & Mota, 2017). A review by Mullen (2018) found that, across 17 studies, higher levels of insecure attachment was consistently linked to poorer mental health. Interestingly, recent work has found that one’s own attachments are not the only risk factor that predict later problems with aggression and that the attachment patterns of mothers might also contribute to the aggressive behaviour of their 30 children in a transgenerational fashion (Cooke, Racine, Plamondon, Tough, & Madigan, 2019). Despite the fact that researchers have examined attachment styles as they relate to internalizing and externalizing symptoms, few studies have examined the mechanisms of higher levels of insecure attachment and internalizing symptoms among young adults. Although attachment patterns typically remains stable throughout the lifespan (Bowlby, 1977; Brumbaugh & Fraley, 2006), the current research addressed this gap in the literature by investigating attachment patterns and internalizing symptoms, each as functions of the relationship between VEs and later cyber dating violence. 2.6.1.4 Internalizing Symptoms and Cyber Dating Violence To date, little is known about the relationship between internalizing symptoms and CDV among young adults. Research on the adolescent age group has illustrated strong relationships between depressive symptoms, over and above traditional forms of dating violence (Hinduja & Patchin, 2020; Zweig, Lachman, Yahner, & Dank, 2014). Indeed, mental health impacts exist for university students as well. Wood, Voth Schrag, and Busch-Armendariz, (2020) found that women in university who experienced cyber dating violence also reported greater internalizing symptoms. More recent work has also supported links between CDV and mental health impacts in that those who report having experienced dating violence also report higher levels of depression (Cantu & Charak, 2020). Other researchers have found evidence that support these findings in that, compared to young adults who report experiencing cyber forms of dating violence and cyberbullying, those who report experiencing little or no such forms of aggression report higher wellbeing (Víllora, Yubero, & Navarro, 2020). For the current study, links between internalizing symptoms and CDV will be investigated. 31 To date, research findings have illustrated both correlational links between VEs, higher levels of insecure attachment, and CDV with internalizing symptoms, as well as internalizing symptoms as outcomes of all three variables. What remains unknown is how internalizing symptoms fit within the larger picture of these phenomena. To fill the gap in research, the current research investigated internalizing symptoms as an outcome of VEs and a predictor of cyber dating violence in a moderating relationship. 2.6.2 Limerence Limerence is a temporary state of being, characterized by an obsessive fixation on an object of sexual and romantic attraction, known as the Limerent Object (Tennov, 1978). While the experience of limerence can happen regardless of one’s relationship status, it does not necessarily happen for everyone and affects approximately 50% of the population (Tennov, 1978). It is an extremely intense experience, overtaking nearly all other aspects of one’s life. Symptoms include: cognitive preoccupation about the limerent object, where thoughts interrupt one’s everyday productivity and any thought not connected to the limerent object somehow is brought to thoughts of them; stalking behaviours previously uncharacteristic of the individual experiencing limerence; extreme anxiety and self-consciousness in the anticipated presence of the limerent object that can take the form of extreme shyness, physical shakes, increased heart rate, and/or sweating; emotional dependence on romantic cues from the limerent object, including an acute desire for reciprocation from the limerent object, picking apart past interactions with the limerent object, and anticipation/daydreaming about future interactions; aching sensation in the chest, with relief only found through imagining reciprocation from the limerent object; complete inability to recognize negative features of the limerent object and idealization of positive features; mood changes based on perceptions of limerent object feelings 32 – euphoria when reciprocation is interpreted, despair and/or self-harm when disinterest or neutrality is interpreted; and intensification of symptoms in the presence of adversity towards a developing romantic relationship. Limerence is not infatuation, a crush, or simply falling in love. Individuals experiencing limerence are unable to manage the involuntary nature of their symptoms or to engage productively in their lives. In a word, limerence is debilitating. In cases where the limerent object shares similar feelings, the experience can be euphoric. If the limerent object does not share the same feelings, extreme reactions, such as suicidality is often seen (Willmott & Bentley, 2015). In most cases, the adversity towards a developing romantic relationship occur due to limerent person experiencing uncertainty around the reciprocal romantic feelings of the limerent object (Wolf, 2017). Importantly, the uncontrollable nature of limerence often leaves those experiencing it to engage in extreme behaviours they might not otherwise engage in if they were not limerent, such as consider suicide or to engage in stalking behaviour (Tennov, 1978). Given the fixation on an object of romantic interest, individuals experiencing limerence will often refer to their experience as simply being in or falling in love. When individuals who have never experienced limerence are asked questions about the behavioural and cognitive experiences of limerence, however, non-limerent individuals also describe their experiences with romantic interests as love. Therefore, addressing limerence via the behavioural and cognitive symptoms are essential in determining whether or not an individual is experiencing limerence. Given that many young adults are actively engaged in dating behaviours (Arnett, 2000), and that they spend a large amount of time socializing in online contexts (Lenhart, 2015), understanding limerence may be important for understanding more about aggressive online acts, such as CDV, in young adults. 33 Empirical research investigating limerence is emerging and therefore limited. To date, no studies have investigated limerence in relation to CDV. Preliminary studies, however, point towards an important relationship between limerence and attachment, internalizing symptoms, and early trauma experiences among young adults. A phenomenological analysis by Willmott and Bentley (2015) investigated the lived experience of six individuals who had reported experiencing limerence. Qualitative analysis of interviews in their work indicated possible connections between limerence and higher levels of anxious attachment styles, depressive symptoms, anxiety, and more severe experiences, such as reports of symptoms of PTSD. Further, a recent short-term longitudinal dissertation by Wolf (2017) found that individuals who reported higher relative to lower anxious attachment styles were also more likely to report experiencing limerence. Limerence is likely not however, simply an extreme presentation of anxious attachment, considering that individuals who report having experienced it can only experience it towards one person at a time, whereas high levels of insecure attachment can be present in a multitude of relationships. Given the emergent nature of limerence research, the current research sought to explore how limerence relates to VEs, attachment, and young adult psychosocial factors such as internalizing symptoms, cyberbullying/cybervictimization, and problematic internet use. 2.6.3 Young Adult Internet Use Given that CDV occurs via digital devices and that being connected digitally is considered a function of normal development among young adults (Lenhart, 2015), especially during the COVID-19 pandemic (Cai et al., 2021), internet use is an important behaviour investigated in this study. Despite widely expressed concerns about technology use among young adults, links between technology use and well-being are not decidedly negative. For example, 34 research by Merrill and Liang (2019) also found that social media did not contribute to risky sexual behaviours or poor mental health (see Orben, 2020 for a review). In fact, researchers have recently found that technology has become somewhat of a facilitator in strengthening social relationships, with evidence of positive impacts on relationships (Stonard, Bowen, Walker, & Price, 2017). However, findings in this area are mixed. For example, Mosley and Lancaster (2019) found that amount of time online (upwards of 6 hours per day) predicted both positive relationship quality, as well as digital dating abuse. Further, Kim, Kim & Kang (2016) found that push notifications affected task performance for young adults. Given the mixed findings, a simple metric such as the amount of time spent online may not be the best predictor of CDV. Given the importance of digital connection for young adults (Lenhart, 2015), the compulsion behind the desire to go online, rather than a simple summation of time online, might better explain the online behaviour of young adults and how their online habits predict CDV. The stress about going online is so pervasive that researchers have recently coined the term “nomophobia” (no more phone) to describe increased anxiety around simply being away from one’s digital device (King, Valença, & Nardi, 2010). Furthermore, emerging research has illustrated possible links between mental health concerns, such as increased general anxiety in the presence of nomophobia (King, Valença, Silva, Baczynski, Carvalho, & Nardi, 2013). Difficulty resisting going online might increase the likelihood of engaging in aggressive acts towards dating partners, for those who are inclined to do so (Mosley & Lancaster, 2019). Problematic Internet Use has become more prevalent among young adults (AI-Qudah, 2019), with recent studies having found that young adults spend an average of 6 or more hours a day on social media alone (Vannucci, Flannery, & Ohannessian, 2018). Spending excessive amounts of time online has been shown to predict several maladaptive outcomes among both adolescents and young adults, 35 such as poor self-regulation (Kim, 2016; Spada, 2014), depression (Lup, Trub, & Rosenthal, 2015; Zink, Belcher, Imm, & Leventhal, 2020), cyberbullying (AI-Qudah, 2019; Holfeld & Sukhawathanakul, 2017; Kircaburun, Demetrovics, Király, & Griffiths, 2020; Zsila et al., 2018), internalizing symptoms, (Arrivillaga, Rey, & Extremera, 2020; Cripps & Stermac, 2018; Wood, Voth Schrag, & Busch-Armendariz, 2020), and CDV (Mosley & Lancaster, 2019). While the current research did not seek to evaluate clinical levels of addiction among young adults, it sought to understand the relationships between higher internet use relative to lower internet use, and how internet use moderates the relationship between VEs and CDV. 2.6.3.1 Problematic Internet Use and Attachment Styles Interesting links have also been found between attachment styles and problematic internet use. For example, research by Monacis, De Palo, Griffiths, and Sinatra, (2017) found that higher levels of insecure attachment within adult relationships significantly predicted addiction to social networking. Likewise, Stavropoulos, Mastrotheodoros, Burleigh, Papadopoulos, and Gomez (2018) found that problematic internet use negatively predicted secure attachment styles in young adults. This finding was supported by Schimmenti, Passanisi, Gervasi, Manzella, and Famà’s (2014) work, who found a correlation between problematic internet use and higher levels of both insecure attachment styles and VEs among young adults. The current research addresses the gap in the literature by assessing VEs as a predictor of problematic internet use as it relates to CDV perpetration. 2.6.3.2 Problematic Internet Use, Cyberbullying, and Cybervictimization In the cyberbullying and cybervictimization literature, recent work by Lin et al. (2020) found that adolescents who report cybervictimization experiences also report higher rates of problematic internet use and worse mental health. A recent systematic review by Elhai, Dvorak, 36 Levine, and Hall (2016) also looked at the relationship between problematic internet use and internalizing symptoms. Their findings illustrated possible directional relationships between problematic internet use and internalizing symptoms in that a variety of the longitudinal studies they examined seemed to suggest that anxiety and depression might spur higher rates of problematic internet use as young people seek relief from their internalizing symptoms via the internet. The authors also highlight a smaller body of research pointing to a bidirectional relationship between problematic internet use and internalizing symptoms, where the symptoms of one may spur symptoms of the other. Certainly, the negative impacts of technology use on young adults warrant a deeper understanding in order to work to protect the mental health of young people. The current research addressed this gap in the literature by investigating problematic internet use and internalizing symptoms as moderators of the relationship between VEs and CDV perpetration. Vulnerable early experiences and insecure patterns of attachment impact the relationships we form, such as with romantic partners (Brumbaugh & Fraley, 2006; Jensen, Willoughby, Holman, Busby, & Shafer, 2015; Lowell, Renk, & Adgate, 2014). People who have experienced more VEs relative to fewer earlier in life and insecure attachment patterns within their relationships are at higher risk of person-level characteristics, such as internalizing symptoms, cyberbullying, cybervictimization, problematic internet use, and limerence (Holfeld & Baitz, 2020; Schimmenti, Passanisi, Gervasi, Manzella, & Famà 2014; Willmott & Bentley 2015). The current research seeks to better understand the mechanisms and relationships between VEs, attachment, person-level characteristics, as predictors of CDV victimization and perpetration. 37 2.7 The Current Study To date, no study has investigated how early experiences, attachment, mental health, cyberbullying/cybervictimization, problematic internet use and limerence are related to CDV victimization and perpetration. The current research fills the gap in the literature by investigating the relationships between the aforementioned variables in moving the literature on CDV forward. Bringing together adverse experiences and Attachment Theory in the context of online outcomes, what remains unknown is how CDV victimization and perpetration are related to VEs a young adult may have experienced, and how those experiences relate to attachments and person-level factors. More specifically, the current work seeks to understand how attachment patterns affect the process through which VEs affect CDV victimization and perpetration respectively, while also understanding how person-level factors, such as cyberbullying/cybervictimization, internalizing symptoms, limerence and problematic internet use strengthen the direction of the relationship between VEs and CDV victimization and perpetration, respectively. As such, the objective of the current study was to explore the relationship between vulnerable experiences and CDV in young adulthood with a focus on attachment patterns and person-level psychosocial factors. The current study was conducted via an online questionnaire that was administered to a general population of young adults, via Amazon’s Mechanical Turk. The purpose of the questionnaire was to understand the general mechanisms in the relationships between early VEs, attachment, individual psychosocial factors and later CDV. The goal of the current work was to gain more in-depth insight into the relationship between early experiences and later cyber outcomes. To accomplish the objectives of the current study, the central research questions that guide this work are as follows: 38 1. Are reports of past VEs related to later CDV victimization and perpetration, respectively, among young adults? Does experiences in close relationships mediate this relationship (anxious attachment, avoidant attachment)? Are there differences between genders? 2. Do psychosocial factors (internalizing symptoms, cybervictimization) moderate the influence of VEs on CDV victimization, and what are the differences between young adult cisgender men, cisgender women, or gender expansive individuals? 3. Do psychosocial factors (problematic internet use, cyberbullying perpetration, limerence) moderate the influence of VEs on CDV perpetration, and what are the differences between genders? 39 Chapter 3: Methods The current study used a sample of 1354 young adults, (1328 from the United States of America, 15 from Canada, and 11 from outside North America). The sample included participants between ages of 18 and 51 (M = 28, SD = 4.11), and 55% reported their gender as male. Reported ethnicities were 78% white, 10% Black, and 12% other ethnicity. After obtaining ethical approval from the University of British Columbia ethics board, participants were recruited virtually via Amazon’s Mechanical Turk (MTurk) from December 2021 to January 2022 (during the beginning of the Omicron wave of the COVID19 Pandemic in North America). Constraints for participation were set in that participants in the United States of American, Canada, or the UK within the age range specified for the study (19-30) only were invited to take part in the study via an advertisement created by MTurk. These constraints were paid for at a rate of $0.50 each per participant, per constraint, at a total rate of $2.50 cents for completion of the questionnaire, per person. Despite constraints set, 34 participants between the ages of 35 and 51 also filled out the questionnaire and were included in the analyses (model tests excluding these participants did not change results). Before beginning the questionnaire, participants were redirected to fill out a consent form via Qualtrics software (Appendix 1). The average time to complete the survey among all participants was 22 minutes. To determine the number of participants necessary for the analysis, an apriori power analysis was conducted for structural equation models (Soper, 2021) and revealed an N of 1252. Power analysis was conducted based on an alpha level of .05, a large effect size of 0.8, three observed predictors (age, gender) and seven latent predictors (VEs, insecure attachment, cyberbullying, cybervictimization, internalizing symptoms, limerence, problematic internet use). To account for participants who did not successfully answer “attention-check” items (Hauser & 40 Schwarz, 2015; described below), bot (e.g. robot) responses, or those who do not finish their survey (and thus, were not paid), a total of 1965 responses were collected, resulting in 1354 usable responses. Responses were removed from analysis for a variety of reasons. First, any respondent who failed two or more attention checks were eliminated from the sample. Second, if participants took fewer than 350 seconds (5.8 minutes) to complete the questionnaire (Qualtrics predicted 38.9 minutes to completion of the questionnaire), or any TWO of the following: finished in under 400 seconds (6.7 minutes); failed at least one attention check; had a nonsensical answer in the qualitative box that appeared repeatedly (bots); inconsistencies in gender reporting (cisgender man with she/her pronouns and assigned intersex at birth), were eliminated. Those who did not complete their questionnaire were also not included as incomplete surveys could not be paid (participants were requested to enter a code for payment at the end). In order to maintain validity of responses via MTurk, the questionnaire contained items designed to determine that participants are (a) human, and (b) attentive to the questionnaire. To assist in determining whether participants were human, Completely Automated Public Turing Test to Tell Computers and Humans Apart (CAPTCHA) were assigned at the end of the consent form. CAPTCHA items are challenge-response tests that humans can typically solve but computers cannot, such as identifying only images that contain a crosswalk in a series of images presented to the user. To determine that human users were attentive to the questionnaire, instructed-response “attention-check” questions (ACQs) were administered at 6 points in the questionnaire. Instructed-response ACQs indicate the answer within the question, such as “please select the ‘Likely’ as the response for this question”, and is designed to determine whether the participant is attentive to the questionnaire. Recent research has determined that instructed-response ACQs do not affect the validity of scales used within the questionnaire (Kung, Kwok, 41 & Brown, 2018), especially when administered through means such as MTurk (Hauser & Schwarz, 2015). Due to the sensitive nature of the topics within the questionnaire, at two points in the consent form, two points throughout the questionnaire, as well as at the end of the questionnaire, participants were provided a list of resources available in Canada, Europe, and the United States to access additional mental health support, should they need it. Finally, upon completion of the questionnaire in Qualtrics, participants were asked to enter a special code in MTurk that has been provided by Qualtrics to prompt MTurk to pay the participant. Each participant received $2USD ($2.56CAD) for completing the questionnaire, calculated based on other similar studies that have used MTurk (Kujawa, Green, Compas, Dickey, & Pegg, 2020). The remaining $0.50 was paid to MTurk for questionnaire constraints. 3.1 Measures 3.1 Demographic Variables Various questions relating to demographic information were included in the questionnaire. Questions were assessed to determine participant’s age, gender assigned at birth, and gender identity (cisgender male, cisgender female, gender expansive) (Appendix 2). For assessing gender expansive individuals, participants were asked whether they were cisgender (their gender assigned at birth aligns with who they are), transgender (gender assigned at birth is different than who they are), nonbinary (they identify as more than one gender), agender (they identify with neither gender or no gender), or Two-Spirit (for Indigenous folx). Those who identified as any category outside of cisgender where categorized as gender expansive. Participants were also asked whether they were currently in a relationship, even casually, whether they had experience in a serious relationship, their marital status, and age (Table 1). 42 Table 1. Demographic Information Men Women Gender Expansive Total Variable n % n % n % Currently in Relationship 737 83% 552 77% 66 86% 1354 Experience in Serious Relationship 737 90% 552 88% 66 88% 1354 Primarily Monogamous 735 85% 547 82% 66 65% 1348 Married 399 54% 237 43% 20 30% 656 Age 18-23 58 4% 43 3% 9 <1% 24-29 445 33% 298 22% 42 3% 30-35 221 16% 189 14% 15 1% 36+ 13 1% 21 2% 0 0% 1354 3.2 Cyber Dating Violence Cyber Dating Violence was assessed via the Cyber Dating Abuse Questionnaire (CDAQ) (Borrajo, Gámez-Guadix, Pereda, & Calvete, 2015), as it has been widely used and one of the few instruments recommended for use in young adults (Martínez Soto & Ibabe, 2022). The CDAQ contains 20 items in parallel in that each item is asked in terms of perpetration as well as victimization for a total of 40 items. Items are assessed on a 6-point Likert scale that asks participants to indicate whether the item had occurred in the last year. Questions include items that assess control behaviours “checking partner’s mobile phone without permission” as well as direct aggression behaviours “threats through new technologies to physically harm”. Scores were averaged with scores closer to 6 being high on measures of cyber dating violence victimization 43 and perpetration. Chronbach’s alpha for the current sample was good at 0.99 for the perpetration scale, and 0.98 for the victimization scale. The internal consistency for the Direct Aggression Perpetration scale was reported at a =.73, for the Direct Aggression Victimization scale was .84; for the Control Perpetration scale was .81 and for the Control Victimization scale was .87 (Borrajo, Gámez-Guadix, Pereda, & Calvete, 2015). Validity for the scale was assessed via both factorial and convergent validity, with acceptable results reported by the original authors (Borrajo, Gámez-Guadix, Pereda, & Calvete, 2015). 3.3 Vulnerable Experiences Vulnerable experiences were assessed via a widely expanded version of the Adverse Childhood Experiences questionnaire (ACE; Felitti et al., 1998). The original ACE scale contains 17 items that address psychological, physical, and sexual abuse, as well as household dysfunctions such as substance abuse, mental illness, mother having been treated violently, and criminal behaviour (such as family, partners, or house mates). Based on recent literature, the measure was expanded to include items such as experiencing racism, living in an unsafe neighbourhood, housing precarity, (Cronholm et al, 2015; Finkelhor, Shattuck, Turner, & Hamby, 2013), as well as peer victimization and cybervictimization (Cronholm at al., 2015; Schnarrs et al., 2019). Finally, a question relating to parents sharing of non-consented images of them online was included to address other technological traumas within the family environment. Given the context of the study, it felt prudent to include items such as “did a parent or other adult in the house post and share about you online, even if it embarrassed you?” Traditionally, the ACE questionnaire would have participants respond in a yes/no fashion. In line with other large scale studies (Brown, Perera, Masho, Mezuk, & Cohen, 2015), and order to encourage participants to answer positively for something they have only experienced once or twice, but 44 have still experienced, the measure was adapted to a 0-100 scale slider bar. The adapted ACEs questionnaire is summative in that higher scores on the scale indicate a greater number of past vulnerable experiences. In the analyses, averages were used with scores closer to 100 being high on experiences of ACEs. Given that the items in the measure are each individual types of adverse experiences, the items do not illustrate a factor structure. Thus, an average score of the 23 items was used in the analyses. Given a large number of low scores for many items within each participant (floor effect), Cronbach’s alpha for the measure in the current sample was 0.98. 3.4 Young Adult Attachment Styles Attachment styles were investigated via the Experience in Close Relationships Scale – Short Form (ECR-S; Wei, Russell, Mallinckrodt, & Vogel, 2007), which has been shown to have sound psychometric properties as a self-report measure to assess attachment (Fraley, Waller, & Brennan, 2000; Roisman, Holland, Fortuna, Fraley, Clausell, & Clarke, 2007). The ECR-S contains a total of 12 items (6 items for anxious attachment and 6 items for avoidant attachment), among young adults, has been shown to have nearly identical psychometric properties of the full 36-item version (Wei, Russell, Mallinckrodt, & Vogel, 2007). The items of the ECR-S are measured on a 7-point Likert scale with lower scores indicating lower levels of insecure (either anxious or avoidant) attachment. Items to assess insecure attachment styles include “My desire to be very close sometimes scares people away” and “I am nervous when partners get too close to me”. Cronbach’s alphas for the scales in the current sample were reported as 0.74 for anxious attachment and 0.78 for avoidant attachment. The internal consistencies for the scales were reported as r = .82 and r = .89, respectively. In terms of validity, construct validity was assessed by the authors of the scale and determined to be acceptable (Wei, Russell, Mallinckrodt, & Vogel, 2007). 45 3.5 Cyberbullying and Cybervictimization To assess experiences of both cyberbullying and cybervictimization, the cyber-aggression and cyber-victimization Scale (CAV; Shapka & Maghsoudi, 2017) was used. The sale includes 24 items assessing cyberbullying (12 items) and cybervictimization (12 items) on a 5-point Likert scale ranging from 0 = never; to 4 = all the time. Questions relating to cyberbullying perpetration include “how often have you posted or re-posted something embarrassing or mean about another person online?”. For cybervictimization, questions include “How often have you had something embarrassing or mean posted or re-posted about you online?”. In terms of reliability, Cronbach’s alpha for the 40-items scale is 0.97 for the cyberbullying scale and 0.97 for the cybervictimization scale in the current sample of participants. In terms of validity, convergent validity, construct validity, and discriminant validity were assess with acceptable results (Shapka & Maghsoudi, 2017). 3.6 Internalizing Symptoms Experiences of symptoms such as anxiety and depression were measured via a shortened version of the Depression, Anxiety, Stress Scale (DASS-21; Antony, Bieling, Cox, Enns, & Swinson, 1998). The DASS-21 contains 7 items each for both depression and anxiety, which was combined for one 14-item measure of internalizing symptoms. The remaining 7 items of the original scale related to stress and were not used. Questions ask participants to report how often in the past week they experienced each state on a 4-point severity scale, with scores closer to 4 indicating greater internalizing symptoms than scores closer to 1. For depression, questions include “I felt that life was meaningless” and “I was unable to become enthusiastic about anything”. For anxiety, questions include “I felt I was too close to panic” and “I was worried about situations in which I might panic and make a fool of myself”. Scores were averaged for 46 analysis, with scores closer to 4 being high in internalizing symptoms. In terms of reliability, Cronbach’s alphas for the depression subscale was 0.92, and the anxiety subscale was 0.91 for the current sample of participants. In terms of validity, concurrent validity was assessed with acceptable results (Antony, Bieling, Cox, Enns, & Swinson, 1998). 3.7 Limerence Limerence was evaluated using the 30-item Limerence Measure (Wolf, 2017). Techniques employed by other researchers was used. For example, participants were asked to imagine the person they feel the strongest romantic feelings for and attraction to right now, regardless of whether or not they are in a relationship with that person (Wolf, 2017). Measure items include “I cannot seem to get this person out of my mind” and “I have a hard time speaking and cannot think clearly around this person”. Items are assessed on a 7-point scale from 1 = “Strongly Disagree” to 7 = “Strongly Agree”. Higher average scores on the measure indicate a stronger experience of limerence compared to lower scores on the scale (range = 7-210). Validity was assessed via convergent validity, construct validity, and discriminant validity, and found to be acceptable for the measure (Wolf, 2017). Unfortunately, exploratory factor analysis for the measure in the current work revealed a poor model fit for 8 factors, as reported in Wolf, (2017) (Table 2) (CFI = .98, RMSEA = .04, SRMR = .01, ꭓ2 = , df = 223, p <.001, AIC = 134252.34, BIC = 135670.01. A composite measure was created using items with the highest factor loadings for each of the 8 categories established by Wolf (2017), resulting in an 8-item measure of limerence. The 8-item measure included items 3, 7, 12, 14, 19, 23, 26, and 30. The composite measure of the 8 items illustrated acceptable reliability at α = .846. 47 Table 2. Exploratory Factor Analysis of the items of the Limerence Scale Items Factor Dimension 1 2 3 4 5 6 7 8 1 .12 .05 .20 .14 .27 -.01 -.02 -.01 Exclusivity 2 .69 .03 .01 -.05 .03 .16 -.04 -.06 3 .14 .00 .06 -.01 .78 .00 .01 -.12 4 .74 .04 .01 -.03 .04 .04 .07 .05 5 .01 .14 .71 -.03 .10 -.04 -.05 -.04 Intrusive Thinking 6 .49 .24 .09 .02 -.03 .02 -.02 .23 7 .78 -.07 -.06 .15 -.05 -.02 .05 .03 8 .20 -.03 .00 .01 -.15 .11 .32 -.11 9 .43 .07 -.01 .11 .04 .02 .23 -.08 Uncertainty 10 .03 .14 .01 .61 .12 -.01 .01 -.14 11 .06 .67 .00 .10 .03 -.02 -.03 .06 12 -.04 .88 .01 -.03 .01 .06 .00 -.13 13 .21 .51 .00 .11 .07 -.05 .00 .08 Idealization 14 -.00 .71 .03 .08 -.01 .02 .06 .02 15 .10 .16 .02 .09 -.18 .52 .07 -.03 16 0.5 .12 .06 .69 -.06 .00 .03 -.03 17 .03 .50 -.02 .00 -.07 .24 .06 .00 Ache in the Chest 18 -.02 .08 -.01 -.04 .12 .05 .47 .05 19 -.04 -.02 .86 -.02 .04 .01 .06 .00 20 .00 .00 -.02 -.03 .06 .81 -.04 .06 48 21 -.05 .00 .78 .03 .05 -.01 .06 .04 Elation 22 .06 .03 .01 .07 -.01 .71 .01 .03 23 .03 -.04 .86 .06 -.07 .01 -.02 .00 24 .32 .31 -.01 .00 .01 .06 .04 .41 Apprehension 25 .02 .00 -.02 .71 .18 .02 -.07 .03 26 -.04 .00 .05 .16 .76 .06 .05 .01 27 -.03 .03 .01 .09 .15 -.01 .64 .01 Inability to Become Nonlimerent 28 .00 .01 .00 .09 .65 -.10 .06 .03 29 .04 .02 .07 .00 .02 -.14 .79 .10 30 -.05 .00 -.04 .76 .04 .06 .10 .06 Notes. Extraction method; maximum likelihood; Rotation method; Geomin. Loadings larger than .60 are in bold. 3.8 Problematic Internet Use To assess problematic internet use, the Generalized Problematic Internet Use Scale 2 (Problematic Internet Use; Caplan, 2010), comprised of 15 items, was used. Items assess typical internet use and problematic internet use on a 8-point Likert scale from “definitely disagree” to “definitely agree”, with higher scores indicating more problematic internet use. Items include “I prefer online social interaction over face-to-face communication” and “My internet use has created problems for me in my life”. Cronbach’s alpha for the scale is acceptable at 0.92 for the current sample of participants. In terms of validity, construct validity was assessed and determined to be acceptable (Caplan, 2010). Information for all study measures can be found in Table 3. 49 Table 3. Study Measures Name of Measure Subscales Number of Items Scale of Measurement Section 1: Aggressive Online Outcomes Cyber Dating Abuse Questionnaire Victimization 20 items 6-point Likert Perpetration 20 items 6-point Likert Cyber-aggression and Cyber-Victimization Scale Cyberbullying 20 items 5-point Likert Cybervictimization 20 items 5-point Likert Section 2: Vulnerable Experiences ACE-Expanded 17 items 5-point Likert Section 3: Adult Attachment relationships Experience in Close Relationships Scale-Short Form 12 items 7-point Likert Section 4: Individual-level risk factors Limerence Measure 8 items 7-point Likert Depression, Anxiety, Stress Scale Depression 7 items 4-point Likert Anxiety 7 items Generalized Problematic Internet Use Scale 2 15 items 8-point Likert 50 Chapter 4: Results 4.1 Analyses The descriptive statistics for all means and standard deviations of study variables are presented in Table 4. Compared to men and women, gender expansive people experienced significantly less cyber dating violence perpetration (Ms = 1.59 vs. 2.39), t(4.04) = 8.53, p < .00, and victimization (Ms = 1.90 vs. 2.55), t(3.95) = 5.86, p < .001, as well as less cyberbullying (Ms = 1.63 vs. 2.10), t(3.04) = 5.64, p < .001. Table 4. Descriptive Statistics Men Women Gender Expansive Total Variable M SD M SD M SD M SD Vulnerable Experiences 35.82 28.55 34.13 29.71 36.55 23.79 35.20 28.83 Anxious Attachment 4.34 1.13 4.01 1.22 4.59 1.31 4.22 1.19 Avoidant Attachment 3.25 1.18 3.27 1.08 3.11 1.17 3.25 1.14 Cybervictimization 2.18 1.07 2.16 1.08 2.14 .92 2.17 1.06 Cyberbullying 2.07 1.12 2.12 1.13 1.63 .92 2.07 1.12 Internalizing Symptoms 2.13 .78 2.08 .79 2.38 .77 2.12 .79 Problematic Internet Use 4.82 1.46 4.71 1.51 4.81 1.38 4.77 1.46 Limerence 4.74 1.12 4.69 1.12 4.80 1.20 4.73 1.13 Cyber Dating Violence Victimization 2.55 1.52 2.54 1.46 1.90 1.23 2.51 1.48 Cyber Dating Violence Perpetration 2.38 1.52 2.39 1.51 1.59 1.07 2.34 1.51 Valid N (listwise) 731 546 66 568 51 Bivariate correlations were also computed to determine interrelations among variables (Table 5). Cyber dating violence perpetration was positively associated with higher scores of anxious attachment (r = 0.370), avoidant attachment (r = 0.507), vulnerable experiences (r = 0.786), problematic internet use (r = 0.609), internalizing symptoms (r = 0.669), cyberbullying (r = 0.953), cybervictimization (r = 0.919), and limerence (r = 0.230). Cyber dating violence victimization was positively associated with higher scores of anxious attachment (r = 0.411), avoidant attachment (r = 0.534), vulnerable experiences (r = 0.785), problematic internet use (r = 0.606), internalizing symptoms (r = 0.678), cyberbullying (r = 0.908), cybervictimization (r = 0.910), and limerence (r = 0.219). Table 5. Bivariate Correlations of Study Variables Variable 1. 2. 3. 4. 5. 6. 7. 8. 9. 10. 1. Vulnerable Experiences 1 .453** .485** .810** .772** .713** .264** .549** .785** .786** 2. Anxious Attachment 1 .404** .425** .373** .549** .220** .482** .411** .370** 3. Avoidant Attachment 1 .516** .511** .515** -.144* .423** .534** .507** 4. Cybervictimization 1 .932** .707** .250** .607** .910** .919** 5. Cyberbullying 1 .675** .217** .606** .908** .953** 6. Internalizing Symptoms 1 .269** .601** .678** .669** 7. Limerence 1 .336** .219** .230** 8. Problematic Internet Use 1 .606** .609** 9. Cyber Dating Violence Victimization 1 .934** 52 10. Cyber Dating Violence Perpetration 1 **. Correlation is significant at the 0.01 level (2-tailed). To begin assessment of the results, assumptions for multiple regression were tested for homoscedasticity, multicollinearity, and linearity. First skewness and kurtosis were evaluated. Normality was assessed by plotting the unstandardized residuals for the outcome variables of cyber dating violence perpetration and victimization, respectively. The Kolmogorov-Smirnov test of normality was significant (p < 0.001), but upon inspection of the histogram and Q-Q plots, the residuals were evenly distributed with a slight deviation from the normal distribution at the top of the distribution of the Q-Q plot for both victimization and perpetration. Given the large sample size of the data (n = 1354), tests for normality are of less concern compared to smaller data sets, and can often indicate significance while inspection of the data illustrate normality. Thus appears to be the case with the current data, but even so, the Maximum Likelihood Robust (MLR) estimator was used in mediation path model analyses (RQ 1), as it is more robust to non-normality in the data compared to other methods (Maximum Likelihood; Muthén & Muthén, 2017). Second, homoscedasticity was tested and both CDV victimization and perpetration were found to violate the homogeneity of variance. Upon inspection of the distribution of the scores, it was evident that the distribution illustrates a small floor effect and slightly flatter distribution given an increase in responses also on the higher end. Again, the MLR method was chosen for mediation analyses as it is robust to this issue (Muthén & Muthén, 2017). To handle missing data, the full information maximum likelihood estimator was used (Muthén & Muthén, 2017). For moderation analyses (RQ 2 and 3), CDV victimization and CDV perpetration were transformed into binary variables for analyses and will be described below. To begin to address 53 RQ 1, confirmatory factor analyses were first performed to determine model fit for potential latent constructs. Given that model fit indices (factor loadings, etc.) for several of the variables was not sufficient, composite versions of the variables were used in all analyses. Wrights rules of tracing were used to identify the saturated and over-identified causal mediation models (Wright, 1934). To evaluate fit of the mediation models, unbiased parameter estimates provided by Mplus will be assessed (Muthén & Muthén, 2017). Specifically, the comparative fit index (CFI; values ≥ 0.95 acceptable), root-mean square error of approximation (RMSEA; values ≥ 0.05 excellent model fit, ≥ 0.10 acceptable fit), and standardized root-mean of the residual (SRMR) were assessed (Kenny, Kaniskan, & McCoach, 2015). Given that there was less than 1% missing data, listwise deletion was used in the moderation analyses addressing research questions 2 and 3. An initial test of the direct pathway between both VEs and cyber dating violence victimization and perpetration were conducted. VEs were positively associated with both cyber dating violence victimization (β = 0.785 p <0.001) and perpetration (β = 0.786 p <0.001). To address RQ 1, path models were conducted in Mplus to assess the mediating effects of anxious and avoidant attachment, respectively, on the association between VEs and cyber dating violence victimization and perpetration, respectively (Geiser, 2013). The path models evaluated the associations with both age as well as gender as covariates. In the current sample, the number of gender expansive individuals was small (n = 66), comprising of 5% of the total sample in the study, which is higher than the 1% advised for analysis by King and Zeng (2003), and therefore, robust. Given that attachment styles begin very early on in life and remain stable across time (Bowlby, 1977; Brumbaugh & Fraley, 2006), the binary covariate of gender assigned at birth provides the most robust estimation of gender differences among participants in the current sample. In order to include the experiences of gender expansive individuals, they were included 54 in the analyses under their gender assigned at birth. Gender assigned at birth differs slightly from sex assigned at birth, as sex can be assigned as male, female, or intersex, while gender assigned at birth includes a binary of male/female for the American population. Analyses were also run leaving out gender expansive individuals and produced extremely similar results to those presented below. 4.1.1 Mediation Analysis for VEs, Avoidant Attachment, CDV Victimization To test the mediation of avoidant attachment on the relationship between VEs and CDV victimization over and above gender and age, a path model was performed (Figure 2). Given the use of the MLR estimation method, the values generated via the chi-square test cannot be evaluated in the regular way. Instead, the Santorra-Bentler Scaled Chi-Square Difference Test was calculated and was significant (TRd = 1501.07, Ddf = 7, p < 0.001). Adding age and gender assigned at birth as covariates (described above), as well as avoidant attachment to the model to test its mediating effects on the association between VEs and cyber dating violence victimization, over age and above gender assigned at birth, resulted in good model fit indices: CFI = 0.995, RMSEA = 0.052 (90% CI [0.022, 0.088]), SRMR = 0.012. Standardized model pathways were significant for both VEs (β = 0.69, p < 0.001) and avoidant attachment (β = 0.20 , p < 0.001). The direct pathway between VEs and age (β = -0.11, p < 0.001) was significant, with younger young adults reporting significantly more VEs. Direct pathways between VEs and avoidant attachment was also significant (β = 0.47, p < 0.001), suggesting that greater reports of VEs is associated with higher rates of avoidant attachment. The indirect effect of avoidant attachment on the association between VEs and CDV victimization was significant (β = 0.10, p < 0.001). Covariate effects were significant for age (β = -0.11, p < 0.001), with younger young 55 adults reporting significantly higher rates of avoidant attachment compared to older adults. Gender assigned at birth was nonsignificant. Figure 2. Mediation path model for avoidant attachment on the relationship between VEs and CDV victimization, over and above gender assigned at birth and age. 4.1.2 Mediation Analysis for VEs, Anxious Attachment, CDV Victimization To test the mediating effects of anxious attachment on the relationship between VEs and CDV victimization over and above gender and age, a second path model was performed (Figure 3). The Santorra-Bentler Scaled Chi-Square Difference Test was significant (TRd = 1453.98, Ddf = 7, p < 0.001). Adding age and gender assigned at birth as covariates, as well as anxious attachment to the model to test its mediating effects on the association between VEs and cyber dating violence victimization, over age and above gender assigned at birth, resulted in good model fit indices: CFI = 0.988, RMSEA = 0.081 (90% CI [0.051, 0.115]), SRMR = 0.018. 56 Standardized model pathways were significant for both VEs (β = 0.75, p < 0.001) and anxious attachment (β = 0.07 , p < 0.001). Direct pathways between VEs and anxious attachment was also significant (β = 0.44, p < 0.001), suggesting that greater reports of VEs is associated with higher rates of anxious attachment. The indirect effect of anxious attachment on the association between VEs and CDV victimization was significant (β = 0.03, p < 0.001). Covariate effects were significant for age on VEs (β = -0.11, p < 0.001) and anxious attachment (β = -0.08, p < 0.001), with younger young adults reporting significantly more VEs and anxious attachment styles than older young adults. Gender assigned at birth was significant, with individuals assigned female at birth reporting significantly higher anxious attachment compared to those assigned male at birth (β = -0.11, p < 0.001). Figure 3. Mediation path model for anxious attachment on the relationship between VEs and CDV victimization, over and above gender assigned at birth and age. 4.1.3 Mediation Analysis for VEs, Avoidant Attachment, CDV Perpetration 57 To test the mediation of avoidant attachment on the relationship between VEs and CDV perpetration over and above gender and age, a third path model was performed (Figure 4). The Santorra-Bentler Scaled Chi-Square Difference Test was significant (TRd = 1531.78, Ddf = 7, p < 0.001). Adding age and gender assigned at birth, as covariates, as well as avoidant attachment to the model to test its mediating effects on the association between VEs and cyber dating violence perpetration, resulted in good model fit indices: CFI = 0.995, RMSEA = 0.052 (90% CI [0.022, 0.088]), SRMR = 0.012. Standardized model pathways were significant for both VEs (β = 0.71, p < 0.001) and avoidant attachment (β = 0.16 , p < 0.001). Direct pathways between VEs and avoidant attachment was also significant (β = 0.47, p < 0.001), suggesting that greater reports of VEs is associated with higher rates of avoidant attachment. The indirect effect of avoidant attachment on the association between VEs and CDV perpetration was significant (β = 0.08, p < 0.001). Covariate effects were significant for age on both VEs (β = -0.11, p < 0.001) and avoidant attachment (β = -0.14, p < 0.001), with younger young adults reporting significantly more VEs and avoidant attachment styles than older young adults. Gender assigned at birth was not significant. 58 Figure 4. Mediation path model for avoidant attachment on the relationship between VEs and CDV perpetration, over and above gender assigned at birth and age. 4.1.4 Mediation Analysis for VEs, Anxious Attachment, CDV Perpetration To test the mediating effects of anxious attachment on the relationship between VEs and CDV perpetration over and above gender and age, a fourth path model was performed (Figure 5). The Santorra-Bentler Scaled Chi-Square Difference Test was significant (TRd = 1455.65, Ddf = 7, p < 0.001). Adding age and gender assigned at birth as covariates, as well as anxious attachment to the model to test its mediating effects on the association between VEs and cyber dating violence perpetration, resulted in good model fit indices: CFI = 0.989, RMSEA = 0.077 (90% CI [0.047, 0.111]), SRMR = 0.017. Standardized model pathways were significant for VEs (β = 0.78, p < 0.001) but not anxious attachment (β = 0.16 , p < 0.001) on CDV perpetration. Direct pathways between VEs and anxious attachment was also significant (β = 0.44, p < 0.001), suggesting that greater reports of VEs is associated with higher rates of anxious attachment. The 59 indirect effect of anxious attachment on the association between VEs and CDV perpetration was significant (β = 0.01, p < 0.001). Covariate effects were significant for age on both VEs (β = -0.11, p < 0.001) and anxious attachment (β = -0.08, p < 0.001), with younger young adults reporting significantly more VEs and anxious attachment styles than older young adults. Gender assigned at birth was significant, with individuals assigned female at birth reporting significantly higher anxious attachment compared to those assigned male at birth (β = -0.269, p < 0.001). Figure 5. Mediation path model for anxious attachment on the relationship between VEs and CDV perpetration, over and above gender assigned at birth and age. 4.1.5 Moderating Effects of Internalizing Symptoms and Cybervictimization on Cyber Dating Violence Victimization Given issues with normality and homoscedasticity of the outcome variable (CDV victimization) mentioned above, the dependent variable was assessed and a floor effect was noted. Despite attempts to transform the variable, skewness and kurtosis continued to be an issue 60 with new transformations. Upon closer inspection of the distribution, it was noted that a large group of individuals were either above or below an average score of 1.65. Thus, the variable was transformed into a categorical variable – those who have never experienced cybervictimization (average score under 1.65), and those who have experienced it (average score of 1.65 or above). Analyses run for the categorical outcome produced similar results to those run with CDV victimization as a continuous variable. Given issues with normality and kurtosis for the continuous variable, the analyses from the categorical outcome variable were retained for the current results reviewed here. To answer RQ 2 and test the moderating effects of internalizing symptoms and cybervictimization on the association between VEs and CDV victimization, logistic regression analyses were performed with statistical software IMB SPSS version 28 via the PROCESS macro version 4.1 (Hayes, 2014). Significant interaction effects were probed via probability plots of the significant interactions involving the moderators (Dawson, 2014) to investigate relationships among the variables. The model containing VEs as the predictor, age and gender (cisgender man, cisgender woman, gender expansive) as covariates, and internalizing symptoms and cybervictimization as moderators to test whether internalizing symptoms and cybervictimization moderated the relationship between VEs and CDV victimization. Unfortunately, despite centering variables, given that internalizing symptoms and cybervictimization are very highly correlated in the sample (r = .707), the single model had problems with multicollinearity. Thus, two separate models were performed with a single moderator in each model. In both of the models, CDV victimization was the outcome and VEs was the predictor, age and gender (cisgender man, 61 cisgender woman, gender expansive) as covariates, with internalizing symptoms and cybervictimization as moderators in each respective model. First, the logistic regression model with internalizing symptoms as a moderator was performed to test whether internalizing symptoms moderated the relationship between VEs and CDV victimization, over and above age and gender. The logistic regression model with internalizing symptoms as a moderator fit better than the baseline model (df = 5) = 773.10, p < .001, however, the interaction between VEs and internalizing symptoms predicting CDV victimization was nonsignificant (Table 6). Next, the logistic regression model with cybervictimization as a moderator was performed to test whether cybervictimization symptoms moderated the relationship between VEs and CDV victimization, over and above age and gender. The logistic regression model with cybervictimization as a moderator also fit better than the baseline model (df = 5) = 1065.16, p < .001. The interaction between VEs and cybervictimization was significant b = -.0144, p = 0.039. The negative coefficient for the interaction indicates that the effect of cybervictimization becomes more negative (i.e., it reduces or has less effect) at low levels of VEs. Upon inspection of the graph depicting the probability of membership to the CDV victimization groups (experienced CDV victimization; did not experience CDV victimization) with the moderator indicated that the probability of being in the no CDV victimization group was significantly lower for individuals who reported low victimization and low VEs (Figure 6). In other words, at low levels of cyber victimization, participants reported that they were more likely to be in the non-CDV victimization group and have low levels of VEs, while those who reported high levels of cybervictimization were more likely to report high levels of CDV victimization and high levels of VEs. 62 Table 6. Logistic regression analysis of variables affecting cyber dating violence victimization membership Estimate SE z value Pr(>|z|) 95% CI Intercept 2.04 .712 2.87 .041 [.65, 3.44] Vulnerable Experiences .019 .006 3.20 .014 [.01, .03] Cybervictimization 2.69 .203 13.22 .000 [2.29, 3.08] Interaction - .014 .007 -2.06 .039 [-.03, -.001] Gender -.091 .143 -.633 .526 [-.37, .19] Age -.026 .023 -1.11 .268 [-.07, .02] Note. CI = confidence interval Figure 6. Probability of CDV victimization group membership based on the moderation of cybervictimization on the relationship between VEs and CDV victimization. 4.1.6 Moderating Effects of Cyberbullying, Problematic Internet Use, and Limerence on Cyber Dating Violence Perpetration To answer RQ 3 and test the moderating effects of cyberbullying, problematic internet use, and limerence on the association between VEs and CDV victimization, logistic regression 63 models were performed. Given the high correlations between the moderators (Table 5), each moderation was conducted in separate logistic regression analyses. Thus, in each of the models, CDV perpetration was the outcome and VEs was the predictor, age and gender (cisgender man, cisgender woman, gender expansive) as covariates, with internalizing symptoms, cybervictimization, and limerence as moderators in each respective model. First, the logistic regression model with cyberbullying as a moderator was performed to test whether cyberbullying moderated the relationship between VEs and CDV perpetration, over and above age and gender (Table 7). Results indicated that the model with the cyberbullying moderator fit better than the baseline model (df = 5) = 1332.48, p < .001. The interaction between VEs and cybervictimization was significant b = .0239, p = 0.030. The positive coefficient for the interaction indicates that the effect of cybervictimization becomes more positive (i.e., it increases) as VEs increase. Upon inspection of the graph depicting the probability of membership to the CDV perpetration group (engaged in CDV perpetration; did not engage in CDV perpetration) with the moderator indicated that the probability of being in the no CDV perpetration group was significantly lower for individuals who reported low cyberbullying and low VEs (Figure 7). In other words, at high levels of cyberbullying, participants reported that they were more likely to be in the high CDV perpetration group, regardless of whether they reported high versus low levels of VEs, while those who reported low levels of cyberbullying significantly less likely to report high levels of CDV perpetration if they regardless whether they reported high versus low levels of VEs (Figure 7). Table 7. Logistic regression analysis of VEs, cyberbullying, age, and gender affecting cyber dating violence perpetration membership 64 Estimate SE z value Pr(>|z|) 95% CI Intercept 2.24 .940 2.15 .031 [.18, 3.86] Vulnerable Experiences .05 .007 5.62 .000 [.03, .06] Cyberbullying 3.23 .253 12.78 .000 [2.73, 3.73] Interaction .024 .011 2.17 .029 [.02, .05] Gender -.393 .198 -1.98 .047 [-.78, -.01] Age -.031 .031 -1.00 .318 [-.92, .03] Note. CI = confidence interval Figure 7. Probability of CDV perpetration group membership based on the moderation of cyberbullying on the relationship between VEs and CDV perpetration. Next, the logistic regression with problematic internet use as a moderator was performed (Table 8) to test whether problematic internet use moderated the relationship between VEs and CDV perpetration, over and above gender and age. The model also fit better than the baseline model (df = 5) = 901.46, p < .001. The interaction between VEs and cybervictimization was significant b = .063, p = 0.490. The positive coefficient for the interaction indicates that the 65 effect of problematic internet use becomes more positive (i.e., it increases) as VEs increase. Upon inspection of graph depicting the probability of membership to the CDV perpetration group (engaged in CDV perpetration; did not engage in CDV perpetration) with problematic internet use as a moderator indicated that the probability of being in the no CDV perpetration group was lower for those who reported significantly lower VEs and low levels of problematic internet use. In other words, at high levels of problematic internet use, participants reported that they were significantly more likely to be in the CDV perpetration group and have high levels of VEs, while those who reported low levels of problematic internet use were significantly less likely to report high levels of CDV perpetration if they also reported low levels of VEs (Figure 8). Table 8. Logistic regression analysis of VEs, problematic internet use, age, and gender affecting cyber dating violence perpetration membership Estimate SE z value Pr(>|z|) 95% CI Intercept 1.95 .619 3.15 .002 [.738, 3.166] Vulnerable Experiences .07 .004 16.54 .000 [.058, .073] Problematic Internet Use .61 .072 8.44 .000 [.469, .753] Interaction .01 .003 1.97 .049 [.000, .126] Gender - .31 .136 -2.28 .223 [-.577, -.044] Age -.062 .021 -3.06 .022 [-.103, -.023] Note. CI = confidence interval 66 Figure 8. Probability of CDV perpetration group membership based on the moderation of problematic internet use on the relationship between VEs and CDV perpetration. The logistic regression model with limerence as a moderator was performed last to test whether limerence moderated the relationship between VEs and CDV perpetration over and above gender and age. The model fit better than the baseline model (df = 5) = 754.90 p < .001. The interaction between VEs and limerence in predicting CDV perpetration was nonsignificant. In order to better understand limerence, a hierarchical regression was performed using the ‘enter’ method in SPSS to evaluate the pertinent study variables in predicting limerence. Step 1 of the model included covariates of age and gender – neither of which was significant in predicting limerence. Step 2 of the model contained main effects of anxious attachment, avoidant attachment, internalizing symptoms, VEs, and problematic internet use to test direct effects on limerence controlling for age and gender. This resulted in a significant increase to R2: Finc (7, 1339) = 74.88, p < .001, R2 = .281 (Table 9). Results indicated that, over and above gender, anxious attachment, internalizing symptoms, VEs, and problematic internet use all significantly positively predicted limerence, while anxious attachment significantly negatively predicted limerence. 67 Table 9. Hierarchical regression predicting limerence by avoidant attachment, anxious attachment, internalizing symptoms, vulnerable experiences, and problematic internet use. Predictor B SE B b R2 Step 1 .001 Age .006 .007 .022 Gender -.022 .052 -.012 Step 2 .281* Avoidant Attachment -.468 .028 -.472* Anxious Attachment .102 .027 .108* Internalizing Symptoms .216 .054 .151* Vulnerable Experiences .007 .001 .174* Problematic Internet Use .235 .024 .304* Note. N = 1347. *p < .001 68 Chapter 5: Discussion The current work is the first study to investigate both early vulnerable experiences and relational attachment patterns together in better understanding patterns of cyber dating violence victimization and perpetration in young adults. Consistent with previous work on adverse experiences and cyber dating violence (Fereidooni, Daniels, & Lommen, 2022), the current study further supports a pattern of experiencing early traumatic experiences, or VEs, and later cyber dating violence victimization and perpetration. Taken together, the work of this dissertation helps explore and better understand the romantic relationships of young adults in a digital context, and moves the literature relating to cyber dating violence victimization and perpetration forward. The main findings illustrated empirically significant links between VEs and CDV victimization and perpetration. While it was expected that VEs would be significantly related to CDV victimization and perpetration, the current work confirmed significant relationships between the two variables across all models tested. This finding expands on recent research that has illustrated links between early experiences and CDV victimization and perpetration. For example, Fereidooni, Daniels, and Lommen (2022) found that, for Dutch women in the Netherlands, severe childhood maltreatment at the hands of caregivers predicted CDV victimization in early adulthood. Similarly, in an Italian sample, Celsi, Giorgia Paleari, & Fincham (2021) found direct significant associations between intimate partner violence in childhood and later CDV perpetration in early adulthood. While the Italian study broke VEs down into categories in predicting CDV (such as neglect, physical abuse, and emotional abuse, for example), the current work expands on these findings by investigating a primarily American sample and including individual-level factors in predicting both CDV perpetration and victimization, such as attachment patterns, cyberbullying, cybervictimization, problematic 69 internet use, limerence, and internalizing symptoms, age and gender. Given that participants in the current study were asked to retrospectively report their experiences with VEs prior to the age of 18, along with their current experiences with CDV victimization and perpetration, the main findings of this work have important developmental implications. First, the current work alongside the current published literature illustrates important cross-sectional links between VEs and CDV. Taken together, these findings suggest that young adults who recall more VEs in their past might be at higher risk of experiencing CDV victimization and perpetration. Further, the expansion of the ACE scale with six additional items to create the VE measure illustrates the importance of understanding a wider variety of factors (such as housing precarity, neighbourhood violence, peer victimization, and parental online sharing) in understanding traumatic experiences that may predict maladaptive outcomes in young adulthood. In order to determine whether experiencing higher numbers of VEs compared to lower numbers, or none at all, longitudinal research is needed to better understand whether VEs in childhood are indeed temporally linked to experiences of CDV victimization and perpetration later in life. The current work suggests a potential developmental pathway wherein abuse and trauma co-occur across a lifetime – starting from an early age, and continuing through young adulthood. Based on previous literature (Jennings, Okeem, Piquero, Sellers, Theobald, & Farrington, 2017; Sánchez-Jiménez, Rodríguez-deArriba, & Muñoz-Fernández, 2022; Zweig, Dank, Yahner, & Lachman, 2013; Zweig, Lachman, Yahner, & Dank, 2014), it was expected that women would report significantly higher incidences of CDV victimization compared to men, while men would report significantly more CDV perpetration. Surprisingly, it was gender expansive individuals who reported significantly less cyber dating violence victimization and perpetration, compared to cisgender men and cisgender women, who both reported similar rates of cyber dating violence 70 victimization and perpetration. Interestingly, this finding is supported by other studies that have found similar rates among cisgender individuals during adolescence (Smith, Cénat, Lapierre, Dion, Hébert, Côté, 2018). Further, a study by Smith and Reidy (2021) found that sexual identity did not moderate the relationship between bullying and suicide risk. While sexual identity and gender identity are separate and distinct identity constructs, taken together, these findings illustrate that LGBTQIA+ individuals are not necessarily at increased risk of CDV victimization. Although previous research has indicated that gender expansive individuals report significantly more cyber dating violence victimization, these studies investigated adolescents under the age of 18 (Espelage, Merrin, & Hatchel, 2016), with findings also indicating that cyber dating violence victimization did not differ across age (Smith, Cénat, Lapierre, Dion, Hébert, Côté, 2018). Though surprising, the findings of this work might indicate a different pattern of CDV victimization and perpetration in adulthood compared to adolescence for online experiences in dating. For example, gender expansive individuals might be more likely to truly understand the experience of being victimized online, and thus, be less likely to engage in such kinds of perpetration or to remain in a relationship where they are victimized as adults. Interestingly, in contrast to previous research (Zhao et al, 2021), gender expansive individuals were no more likely to report VEs than cisgender individuals in the current study. This is somewhat in contrast to previous research, which proposed that LGBTQIA+ individuals might be at increased risk of experiencing VEs in the form of victimization at school (Schnarrs, Stone, Bond, Salcido, Dorri, & Nemeroff, 2022; Schnarrs, Stone, Salcido, Baldwimn, Georgiou, & Nemeroff, 2019). More research is needed to better understand different types of VEs and their respective traumatic effects for LGBTQIA+ youth separate from cisgender and straight youth. Taken together, the 71 findings from this dissertation move the body of literature around LGBTQIA+ youth and their experiences of VEs and CDV victimization and perpetration forward. Unsurprisingly, CDV victimization and perpetration were extremely highly correlated with cybervictimization and cyberbullying. These findings illustrate that both types of aggressive online behaviour is likely to occur within romantic and platonic relationships together. Given that online aggressive acts are more likely to occur among friendships before they occur within dating relationships as dating relationships begin later on in adolescence (Peskin et al., 2017), these findings illustrate the importance of programs designed to target cyberbullying and cybervictimization behaviours at a younger age – before adolescents and young adults begin serious dating relationships. Findings from the mediation models performed to probe the effect of insecure attachment (anxious, avoidant) on the relationship between VEs and CDV victimization and perpetration illustrated an important relational mechanism that is new to the literature. First, the current work found that anxious and avoidant attachment partially mediated the relationship between VEs and CDV victimization and perpetration, and that greater reports of VEs significantly predicted both types of insecure attachment. In other words, young adults who reported a greater number of experiences with VEs also reported experiencing high levels of either anxious and avoidant attachment styles, which in turn predicted higher reports of CDV victimization and perpetration. This finding is in line with recent research by Toplu-Demirtaş, Akcabozan-Kayabol, Araci-Iyiaydin, and Fincham (2022), who found links between anxious styles of attachment and CDV perpetration. The current work extends the body of literature forward by investigating higher levels of insecure attachment styles as a function of VEs and CDV, as well as links between VEs, higher levels of insecure attachment, and CDV victimization. Therefore, these findings 72 expand on the current literature outlining mechanisms that predict CDV victimization and perpetration among young adults and illustrates the importance of attachment relationships in understanding the relationship between trauma experiences and cyber forms of aggression and victimization in adulthood. This work is also the first to developmentally investigate VEs, attachment, cyberbullying, cybervictimization, internalizing symptoms, problematic internet use and limerence together in better understanding CDV victimization and perpetration. Interestingly, results from the main effect of the mediation analysis indicated that women in the current work were more likely to report higher levels of anxious attachments in the context of CDV victimization – but not perpetration. These results are in line with previous research findings which indicated that women were more likely than men to report greater levels of anxious attachment (Del Giudice, 2011), and extends findings to CDV victimization. Given that higher levels of anxious attachment are linked to concern over losing an attachment figure (Bowlby, 1977), it is likely the case that those who are more anxiously attached are more likely to tolerate being cyber victimized by dating partners out of fear of losing their partner. Further, for young adults who report having experienced VEs that related to the loss of a parent (whether through death, incarceration, or neglect, for example), attachment anxiety might be amplified (Widom, Czaja, Kozakowski, & Chauhan, 2017). In other words, a young adult’s memories of losing an attachment figure not only influences their attachment style (in this case, increased likelihood that the young adult will report a higher level of anxious attachment to their dating partner), but also that they are more willing to accept CDV perpetration from their dating partner, thus being victimized. This finding is the first to connect CDV victimization experiences to higher levels of anxious attachment to illustrate the mediating effect of higher levels of anxious attachment on the relationship between VEs and CDV victimization. 73 Interestingly, the current study found that younger adults were significantly more likely to report higher levels of both anxious and avoidant attachment styles compared to older adults. Though attachment styles can remain stable throughout life (Bowlby, 1977; Brumbaugh & Fraley, 2006), this difference might be accounted for by the fact that many young adults choose to seek therapy and heal childhood traumas as they get older – an activity that increased significantly since the start of the COVID-19 pandemic (Pace, Usai, Bizzi, Minetto, Alcetti, & Zanobini, 2022). Developmentally, this finding illustrates a potential resiliency among young adults in that they are able to heal their attachment traumas across the lifespan. This may be in line with findings from a meta-ethnography by Leung, Chan, and Ho (2020), who found that young adults who reported experiencing high levels of adverse childhood experiences also reported high levels of resiliency. Findings from the moderation analyses indicate that, for young adults who reported experienced high levels of cybervictimization, a person is only likely to be in the high CDV victimization group if they also have experienced high VEs. Further, it was surprising that internalizing symptoms did not moderate the relationship between VEs and CDV victimization, given that both VEs and CDV victimization are often so heavily linked to internalizing symptoms (Bonanno & Hymel, 2013; Calvete, Orue, & Gámez-Guadix, 2016; Chang et al., 2015; Fahy, Stansfeld, Smuk, Smith, Cummins, & Clark, 2016; Kircaburun, Demetrovics, Király, & Griffiths, 2020; Rose & Tynes, 2015; Tennant, Demaray, Coyle, & Malecki, 2015; Trompeter, Bussey, & Fitzpatrick, 2018; Wright, 2017), and that internalizing symptoms and traditional forms of cybervictimization have been shown to occur in a cyclical pattern over time (Rose & Tynes, 2015). This may be an encouraging strength-based finding, suggesting that individuals who suffer from anxiety and depression are not more likely than those who do not 74 suffer with anxiety and depression, to be victims of CDV victimization at the hands of their dating partner. Interestingly, recent research by Duerksen and Woodin (2021) found that CDV victimization did not predict depression, suggesting that individuals who are victim of CDV are not more likely to report higher levels of depression compared to those who are not victims of CDV. The findings of the current work may be attributable to the fact that CDV victimization is so highly prevalent in young adults (Marganski & Melander, 2018; Toplu-Demirtaş, Akcabozan-Kayabol, Araci-Iyiaydin, & Fincham, 2022; Trujillo, Cantu, & Charak, 2020), and given that it is heavily normalized among young people (Howard, Debnam, & Strausser, 2019), might not result in as much subjective distress, and subsequent anxiety and depression, as either in-person forms of dating violence or cyberbullying/cybervictimization. Future work is needed to better understand links between CDV victimization and perpetration, and internalizing for young adults who have experienced a high number of VEs in order to better understand protective factors that may be at play. The moderation analyses investigating cyberbullying behaviours as a function of VEs and CDV perpetration also moves the literature forward in a number of ways. For those who reported perpetrating cyberbullying behaviours, both those who report high and low levels of VEs are likely to belong to the CDV perpetration group. These findings were surprising, given that it was expected that the effect would be significant only for those in the high VE group. These findings could indicate that VEs are not a significant risk factor for the relationship between VEs and CDV perpetration. In other words, VEs early on in life might not be a mechanism via which those who engage in cyberbullying their peers also engage in victimizing their dating partners via CDV perpetration. Given that the opposite mechanism was found for the moderation of 75 cybervictimization on the relationship between VEs and CDV victimization, more research is needed to better understand differences between perpetration and victimization experiences. For those who report higher scores on problematic internet use, those who also report high levels of VEs are significantly more likely to belong to the CDV perpetration group. Future research is needed to better understand the mechanisms at play between VEs, problematic internet use, and CDV perpetration. For example, longitudinal research is needed to better understand how problematic internet use over time is related to CDV perpetration, or whether it is a matter of opportunity in that those who spend more time online are more likely to engage in CDV perpetration as a function of their time online. In other words, more time spent online simply creates opportunities for a greater number of exchanges with others; and more exchanges with dating partners increase the likelihood that some of those interactions will include those of a CDV perpetrating nature, such as GPS tracking. These findings also have important implications for practice. For example, public health campaigns would do well to inform young adults about the links between time online and CDV perpetration, as a recent study has illustrated the importance of understanding and being aware of CDV as an important predictor of reduced CDV behaviours (Er, Murat, Yílmaz, & Buzlu, 2022) Surprisingly, findings indicated that limerence did not moderate the relationship between VEs and CDV perpetration. Although it was expected that limerent individuals would be more likely to engage in stalking types of behaviours due to their symptoms of limerence (Tennov, 1977), the hierarchical analysis illustrated an interesting finding. While anxious attachment positively predicted limerence over and above age and gender, this finding was expected based on previous research (Willmott & Bentley, 2015). Interestingly, avoidant attachment significantly negatively predicted limerence over and above age and gender. In other words, 76 participants who scored highly on avoidant attachment were significantly less likely to report experiencing limerence. This finding moves the field of limerence forward in that it illustrates that limerence is not only related to insecure attachment, but to attachment styles that relate to anxiety and not avoidance. Further, internalizing symptoms also significantly positively predicted limerence, illustrating a link between anxiety and depression and the experience of limerence. This is supported by early limerence research that found links between limerence and mania (Feeney & Noller, 1990), and more recent research that illustrated the effectiveness of exposure treatments seen in cognitive behavioural therapy in the treatment of the obsessive behaviours of limerence (Wyant, 2021). Given that the study of limerence is still emerging, future qualitative research is needed to better understand the mechanisms that underly limerence. For example, while the current work found that limerence is positively predicted by anxious attachment and negatively predicted by avoidant attachment, future research is needed to unpack the ways in which anxious attachment functions to create a supportive environment for limerence to emerge. These kinds of findings are important in treating individuals with limerence – it may be that the experience of limerence needs to be treated alongside the symptoms of anxious attachment. Taken together, the current dissertation illustrates important relationships between VEs, and CDV victimization and perpetration. It moves the field forward in understanding the relationships between individual factors, such as cyberbullying, cybervictimization, internalizing symptoms, problematic internet use, limerence, and attachment. These findings are essential in better understanding how to support young people in their relationships so that they might avoid engaging or experiencing cyber forms of violence at the hands of their dating partners. Unfortunately, the vast majority of programs that address cyber dating violence are often 77 ineffective (Galende, Mzamiz-Etxebarria, Jaureguizar, & Redondo, 2020). The findings of the current work illustrate a very complex system related to CDV victimization and perpetration, which may indicate that other factors may need to be addressed in reducing CDV behaviours. For example, given that VEs significantly predicted CDV victimization and perpetration cross-sectionally in the current work, more emphasis may need to be placed on supporting young people through their traumas related to childhood in an effort to more wholistically address factors that may be related to CDV behaviours. Fortunately, simply knowing about and understanding dating violence predicts fewer incidences of both perpetration and victimization (Er, Murat, Yílmaz, & Buzlu, 2022). Given that CDV is so normalized (Sánchez-Jiménez, Rodríguez-deArriba, & Muñoz-Fernández, 2022), counsellors, therapists, educators and policymakers would do well to increase education around what constitutes CDV so that by the time adolescents begin dating, they have a better understanding of not only what to watch out for in relationships, but also how their own behaviour might be harmful towards their dating partners. 5.1 Strengths and Limitations Although many strengths exist in the study, there are limitations, particularly within the design. First, the study involved self-report measures of all study variables, which may suffer problems due to recall bias (Choi & Noseworthy, 1992). Second, given that data was collected via Amazon’s Mechanical Turk, participants may have been well-motivated and interested in the content area, which may affect generalizability of the findings. Third, using cross-sectional design in the current work reduces the ability to make causal claims about the impact of VEs on later CDV victimization and perpetration. Fortunately, asking participants to retrospectively report their experiences of VEs before the age of 18 helps to increase the possibility that VEs 78 may precede CDV victimization and perpetration, suggesting a possible directional relationship between VEs early in life and CDV victimization and perpetration after the age of 18. Further, the hypothesized pathways investigated in the current work is supported by research literature that mediation and moderation models can investigate causal relationships (Schumacker & Lomax, 2016). Another limitation in the current work relates to how traumatic experiences were retrospectively reported in the current work. Longitudinal research by Colman (2016), found that adults over the age of 18 were more likely to report more incidences of traumatic experiences when asked again 12 years later. In their work, they found that individuals who reported greater experiences of depression were significantly more likely to report a new event of childhood trauma at retest, 12 years later. Thus, the responses of the older adults in the current work might be slightly less reliable than those who are younger, though, in the current zeitgeist of normalizing therapy and treatment for past traumas (Pace, Usai, Bizzi, Minetto, Alcetti, & Zanobini, 2022), it might also be the case that new traumas are identified at an older age when older adults come to realize that the traumatic experiences they have had, that they may have previously been perceived as normal (such as spanking or verbal abuse), in fact traumatized them. Colman’s work (2016), however, tested adults in a greater age range (12% of participants were over the age of 60 at initial testing), while the current study contained only 37 participants over the age of 34, reducing the concern over over-reporting of trauma. There were also limitations to the data, given that the outcome variables (CDV victimization and CDV perpetration) appeared to be non-normal representing a floor effect. Participants generally reported that they did not experience high levels of either CDV victimization or perpetration, and may have done so due to socially desirable responding (Jackson & Messick, 79 1962). Fortunately, this is a common problem in the study of online aggressive behaviours (Lozano-Blasco, Cortés-Pascual, & Latorre-Martínes, 2020), and many transformations and estimations methods, such as those applied in the current work, reduce the effects of non-normality in data. While the transformations and estimations reduce the chances of overestimating results, more research involving larger samples of people who have experienced CDV victimization and perpetration is needed to confirm the current findings. Further, given that gender expansive individuals made up such a small proportion of the sample, logistic regression analyses must be interpreted with care. In analyses with groups containing less than 1% of study samples (King & Zeng, 2003), invalid inferences may occur. Though the gender expansive group in the current work comprised 5% of the sample, care must be taken in interpreting results. Further work is needed with larger samples of gender expansive individuals to confirm the findings outlined in the current work, as well as to better understand the CDV experiences of gender expansive individuals. Finally, traditional dating violence was not assessed in the current work. This reduces the ability to determine whether the results from the current work are directly attributable to cyber forms of violence. While research has shown that traditional forms of cyber victimization are separate from cyber forms (Gini, Card, & Pozzoli, 2018), the availability of data on traditional forms would have assisted in comparing the unique contributions of each type of violence in the current work, as well as help identify factors that might predict when someone engages in both. In terms of strengths, the current work is the first study to investigate CDV victimization and perpetration in the context of both VEs and other factors, such as attachment, and psychosocial factors (cyberbullying, cybervictimization, problematic internet use, internalizing symptoms, and limerence). It is also the first study to begin to understand the experiences among 80 gender diverse individuals in their experiences with VEs, and CDV victimization and perpetration. 81 Chapter 6: Conclusions The current dissertation sought to determine the relationship between self-reported vulnerable experiences, attachment patterns, psychosocial factors, and later CDV victimization and perpetration. The current work achieved this in two ways. First, it investigated the mediating effects of attachment insecurity on the relationship between VEs and CDV victimization and perpetration. Second, it investigated the moderating roles of cyberbullying/cybervictimization, limerence, problematic internet use, and internalizing symptoms on the relationship between VEs and CDV. Understanding the larger developmental patterns of these phenomena are much needed to better determine how to protect young people from risks associated with aggressive behaviour and victimization in young adulthood, particularly in a time when aggressive online behaviour among dating partners is widely normalized among young adults. Given that increased experiences with VEs may actually encourage the cultivation of protective factors such as support and higher education (Thomson & Jaque, 2017), the current work is needed to better inform intervention programming that is geared toward reducing aggressive online behaviour among young adults. Ideally, protecting children from experiencing VEs would lead to more optimal outcomes for young adults, such as more secure attachments and less cybervictimization, cyberbullying, CDV perpetration and victimization in relationship. This work illustrates the importance of supporting young adults in their relationships to reduce harm associated with cyber forms of aggression. Therapists, counsellors, educators, and policymakers would do well to ensure programming and therapeutic approaches targeted towards young adults are created and available for those who are most vulnerable, particularly individuals navigating young adulthood. Further, counselling therapists should ensure treatment of individuals on a wholistic 82 level, taking into consideration memories of previous traumas, in their work supporting young adults. 83 References AI-Qudah, M. F., Al-Barashdi, H. S., Hassan, E. M. A. H., Albursan, I. S., Heilat, M. Q., Bakhiet, S. F. A., & Al-Khadher, M. A. (2020). 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People in charge of this project: Dr. Jennifer Shapka from the Department of Educational and Counselling Psychology and Special Education is the principal investigator for this project. If you have any questions you can email them to her at [redacted]. You can also call Dr. Shapka at [redacted]. Why we are doing this project: You are one of the first groups of young adults in the world to grow up using computers and internet. We want to learn more about what it is like for you to interact with current or potential romantic and/or sexual partners online, as well as some of the kinds of things you experienced when you were growing up. To help us learn more about these things, we will be asking you questions about your relationships, your technology use, and your past experiences with your family. What this project means for you: If you want to take part in this project, then you will be asked to fill out a questionnaire via Mechanical Turk. The entire process should take no more than 50 minutes total. Your answers will be kept safe and private: We want to make sure you feel safe answering questions as honestly as you can, so we will be doing all we can to make sure your answers remain private and anonymous. This means that for the study, your name and personal information will never be connected with your answers to the survey. All your answers will be kept private and will never be shared with your parents, friends, or teachers. Questions or concerns: If you have any concerns or complaints about your rights as a research participant and/or your experiences while participating in this study, contact the Department of Educational and Counselling Psychology, and Special Education The University of British Columbia Faculty of Education 2125 Main Mall Vancouver BC Canada V6T 1Z4 Tel [redacted] Fax [redacted] www.ecps.educ.ubc.ca 119 Research Participant Complaint Line in the UBC Office of Research Services at [redacted] or if long distance e-mail [redacted]. Consent: Your decision to take part in this study is completely up to you. This means that if you do not want to take part, or if you change your mind in the middle, you can stop at any time and it will not affect you in any way. If you want to help us out and take part in this project, please fill out the form below: _________________________________________________________________________________________________________ Printed Name of Participant _________________________________________________________________________________________________________ Email address cell number _________________________________________________________________________________________________________ Participant Signature Date 120 Appendix 2 Emerging Adults and Relationships in a Digital Era Questionnaire (EARDE) Emerging Adults and Relationships in a Digital Era Survey Flow Page Break 121 Start of Block: CNSNT EMERGING ADULTS AND RELATIONSHIPS IN A DIGITAL ERA PARTICIPANT INFORMED CONSENT FORM Dear participant, You are being invited to help us, at the University of British Columbia (UBC), learn more about how young adults interact with dating partners online, as well as previous experiences they may have had. Please read the information below to learn more. People leading this project: Rachel Baitz, Doctoral Candidate, is leading this project as part of her dissertation for a doctoral degree, which is funded by Social Sciences and Humanities Research Counsel of Canada. The Principal Investigator of this project is Dr. Jennifer Shapka, a professor from the Department of Educational and Counselling Psychology and Special Education. If you have any questions you can email them to Rachel at [redacted], or Jennifer at [redacted]. You can also call Dr. Shapka at [redacted]. Why we are doing this project/purpose: You are one of the first groups of young adults in the world to grow up using computers and internet. We want to learn more about what it is like for you to interact with current or potential romantic and/or sexual partners online, especially during the COVID-19 pandemic, as well as some of the kinds of things you experienced when you were growing up. To help us learn more about these things, we will be asking you questions about your relationships, your technology use, and your past experiences with your family. What happens if you say “Yes, I want to be in the study”: If you want to take part in this project, then you will be asked to fill out a questionnaire via Mechanical Turk. The entire process should take no more than 35-40 minutes total. The data you provide will be saved and hosted in Qualtrics survey software. Your answers will be kept safe and private: We want to make sure you feel safe answering questions as honestly as you can, so we will be doing all we can to make sure your answers remain private and anonymous. This means that for the study, your name and personal information will never be connected with your answers to the survey. All your answers will be kept private and will never be shared with your parents, friends, or educators. Study results: The results of this study will be reported in a graduate dissertation and may be published in journal articles and/or books. Sometimes, journals and granting agencies require researchers to make their data available before publishing work from the research project. If this happens, none of your identifying information will be connected to the data shared with journals or granting agencies. Is there any way being in this study could be bad for me? We do not think there are any risks to taking part in the study. The questionnaire will ask you some questions about your experiences in the past, which may bother you. For example, the study will ask you about your experiences with cyberbullying and cybervictimization, online dating experiences, and stressful events that happened in your childhood. If you’re bothered by answering any of the questions, we provide referrals to resources at the end of the questionnaire. What are the benefits of the study? There may be benefits to you participating in this study. It may help you reflect on your relationships and how you interact with dating partners online. This study will also help people by giving us a better understanding of how digital communications play a role in relationships. Payment. You will be paid $2 for the completion of the questionnaire and questions that prove you are an attentive human completing the questionnaire, and not inattentive or a computer/bot (Completely Automated Public Turing test to tell Humans and Computers Apart; CAPTCHA). Payment will be administered following confirmation of the above, within 48 hours. Questions or concerns: If you have any concerns or complaints about your rights as a research participant and/or your 122 experiences while participating in this study, contact the Research Participant Complaint Line in the UBC Office of Research Ethics at [redacted] or if long distance e-mail [redacted] or call toll free [redacted] citing reference #H21-02187 . Consent: Your decision to take part in this study is completely up to you and totally voluntary. This means that if you do not want to take part, or if you change your mind in the middle, you can stop at any time and it will not affect you in any way. You may also skip any questions you are uncomfortable answering. Given that this study is totally anonymous, once the survey is submitted, it cannot be withdrawn. By completing this questionnaire, you are consenting to participate in the research. If at any point during the questionnaire you feel bothered by thinking about the things that happened in your past, please visit the any of the following resources: USA & Worldwide: National Suicide Prevention Lifeline 1-800-273-8255 Canada: Crisis Service Canada: Call 1-833-456-4566 or text 45645 India Aasra 91-9820466726 Europe: 116 123 o Yes, I Consent (1) o No, I do not Consent (2) Q128 Please answer the following: End of Block: CNSNT Start of Block: CDV CDVVict SECTION 1: YOUR ONLINE DATING ACTIVITIES The following questions relate to your activities online. Please select the response that best fits with your experiences. For this section “new technology” means any device you use to connect with your dating 123 partner. Rate how many times in the last year a dating partner engaged in the following behaviour towards you. 124 Never (1) Not in last year, but has occurred before (2) Rarely (1 or 2 times) (3) Sometimes (between 3 and 10 times) (4) Often (between 10 and 20 times) (5) Always (More than 20 times) (6) a. They spread rumours, gossip and/or jokes about me through new technologies with the intention of ridiculing (1) o o o o o o b. They made threats through new technologies to physically harm me (2) o o o o o o c. They created a fake profile on a social network to cause problems (3) o o o o o o d. They spread secrets and/or compromising information about me using new technologies (4) o o o o o o 125 e. They threatened to spread secrets or embarrassing information about me using new technologies (5) o o o o o o f. They wrote comments on a social network to insult or humiliate me (6) o o o o o o g. They used new technologies to pretend to be me or my (ex) partner and create problems (7) o o o o o o h. They sent and/or uploaded photos, images and/or videos with intimate or sexual content of me without permission (8) o o o o o o i. They pretended to be another person using new technologies to test me (9) o o o o o o 126 j. They posted music, poems, phrases, memes...etc., on a social networking site with the intent to insult or humiliate me (10) o o o o o o k. They sent insulting and/or demeaning messages about me using new technologies (11) o o o o o o l. They controlled my friends on social networks (12) o o o o o o m. They used new technologies to control where I am and with whom (13) o o o o o o n. They checked my mobile phone/device without permission (14) o o o o o o o. They checked my social networks, Whatsapp or email without permission (15) o o o o o o 127 p. They made excessive calls to control where I am and with whom (16) o o o o o o q. They controlled status updates on my social networks (17) o o o o o o r. They checked the last connection in my mobile applications (18) o o o o o o s. They used my passwords (phone, social networking, email) to browse messages and/or contacts without my permission (19) o o o o o o t. They threatened to answer calls or messages immediately using new technologies (20) o o o o o o 128 CDVVictCovid How have your personal circumstances around the COVID-19 pandemic (quarantining, living away from partners, for example) affected how often you experienced the behaviors above from a dating partner? o It's Much Worse Since COVID (1) o It's Slightly Worse Since COVID (2) o No Change Since COVID (3) o It's Slightly Better Since COVID (4) o It's Much Better Since Covid (5) Page Break 129 130 CDVPerp SECTION 1: YOUR ONLINE DATING ACTIVITIES Rate how many times in the last year you engaged in the following behaviour towards a dating partner: 131 Never (1) Not in last year, but has occurred before (2) Rarely (1 or 2 times) (3) Sometimes (between 3 and 10 times) (4) Often (between 10 and 20 times) (5) Always (More than 20 times) (6) u. I spread rumours, gossip and/or jokes through new technologies with the intention of ridiculing a dating partner (1) o o o o o o v. I made threats through new technologies to physically harm a dating partner (2) o o o o o o w. I created a fake profile on a social network to cause problems (3) o o o o o o x. I spread secrets and/or compromising information about a dating partner using new technologies (4) o o o o o o 132 y. I threatened to spread secrets or embarrassing information about a dating partner using new technologies (5) o o o o o o z. I wrote comments on a social network to insult or humiliate a dating partner (6) o o o o o o aa. I used new technologies to pretend to be my (ex) partner and create problems (7) o o o o o o bb. I sent and/or uploaded photos, images and/or videos with intimate or sexual content of a dating partner without permission (8) o o o o o o cc. I pretended to be another person using new technologies to test a partner (9) o o o o o o 133 dd. I posted music, poems, phrases, memes...etc., on a social networking site with the intent to insult or humiliate a dating partner (10) o o o o o o ee. I sent insulting and/or demeaning messages about a dating partner using new technologies (11) o o o o o o ff. I controlled a dating partner's friends on social networks (12) o o o o o o gg. I used new technologies to control where a dating partner was and with whom (13) o o o o o o hh. I checked a dating partner’s mobile phone without permission (14) o o o o o o 134 ii. I checked a dating partner's social networks, Whatsapp or email without permission (15) o o o o o o jj. The answer to this question is "Rarely", please choose that option for this line. (21) o o o o o o kk. I made excessive calls to control where a dating partner was and with whom (16) o o o o o o ll. I controlled a dating partner's status updates on social networks (17) o o o o o o mm. I checked the last connection in a dating partner's mobile applications (18) o o o o o o 135 nn. I used passwords (phone, social networking, email) to browse a dating partner's messages and/or contacts without permission (19) o o o o o o oo. I threatened to answer a dating partner's calls or messages immediately using new technologies (20) o o o o o o CDVPerpCOVID If you engaged in any of the behaviors mentioned above, did circumstances around the COVID-19 pandemic (quarantining, living with or away from partners, etc.) change how often you did the things above? o I did these things a lot more (1) o I did these things slightly more (2) o No Change (3) o I did these things slightly less (4) o I did these things a lot less (5) End of Block: CDV Start of Block: CBCV 136 CB SECTION 2A: CYBERBULLYING Question 1: Cyberbullying The following questions are interested in your experiences with cyberbullying. Think about the times you are online and respond to the following 137 statements. How often have you: 138 Has never happened (1) Has happened rarely (once or twice) (2) Happens sometimes (once a week) (3) Happens often (several times a week) (4) Happens every day (5) a. Posted or re-posted something embarrassing or mean about another person online? (1) o o o o o b. Sent or forwarded a hurtful message electronically to someone (by email, text, on Facebook, etc.)? (2) o o o o o c. Posted, re-posted, or texted an embarrassing photo or video of someone that he or she did not want others to see? (3) o o o o o d. Posted or texted a hurtful comment about an online photo or video of somebody else (for example, made fun of how they look). (4) o o o o o 139 e. Posted or sent messages to purposely exclude a certain person or group of people. (5) o o o o o f. Posted or re-posted something private about another person that he or she did not want others to know? (6) o o o o o g. Used email or text, or direct messaging to spread rumours or gossip about someone? (7) o o o o o h. Texted or made hurtful comments about somebody’s race or ethnicity? (8) o o o o o i. Texted or made hurtful comments about somebody’s perceived sexual orientation? (9) o o o o o 140 j. Texted or made hurtful comments about somebody’s perceived sexual behaviours (for example, called somebody a slut or a pervert). (10) o o o o o k. Said something sexual to somebody else online to embarrass them or to be mean? (11) o o o o o l. Sent sexual content (photos or jokes) to somebody else online to embarrass them or to be mean? (12) o o o o o Page Break 141 CV SECTION 2B: CYBERVICTIMIZATION Question 2: Cybervictimization The following questions are interested in your experiences about being cyberbullied. Think 142 about the times you are online and respond to the following statements. How often have you: 143 Has never happened (1) Has happened rarely (once or twice) (2) Happens sometimes (once a week) (3) Happens often (several times a week) (4) Happens every day (5) a. Had something embarrassing or mean posted or re-posted about you online? (1) o o o o o b. Received a hurtful message from someone (by email, text, or chat)? (2) o o o o o c. Had an embarrassing photo or video of you posted or re-posted online that you didn’t want others to see? (3) o o o o o d. Had hurtful comments made about an online photo or video of you? (4) o o o o o e. Been purposely excluded online? (5) o o o o o f. Had something personal posted or re-posted about you online that you didn’t want others to know? (6) o o o o o 144 g. Had gossip or rumours spread about you online? (7) o o o o o h. Received hurtful comments or messages about your race or ethnicity? (8) o o o o o i. Received hurtful comments or messages about your perceived sexual orientation? (9) o o o o o j. Received hurtful comments about your perceived sexual behaviours (for example, been called a slut or a pervert)? (10) o o o o o k. Received a sexual message from somebody who was trying to be mean to you or to embarrass you? (11) o o o o o 145 l. Had sexual content (photos or jokes) sent to you from somebody who was trying to be mean to you or embarrass you? (12) o o o o o End of Block: CBCV Start of Block: EARLYEX EEXSwear SECTION 3: YOUR EARLY EXPERIENCES Please read the following statements. Please rate how often each of these events occurred in your childhood (0 = Never; 100 = Happened everyday), as well as how much the event affected you, by using the slider bar (0 = Never affected me; 100 = Had an extreme affect on me). Has never happened Happened every day 0 50 100 a. Did a parent or other adult in the household often or very often swear at, insult, or put you down? () EEXSwearaff Please rate how much it affected you Never affected me Had an extreme affect on me 0 50 100 a. How much it affected you () Page Break 146 EEXPhyshurt SECTION 3: YOUR EARLY EXPERIENCES Please read the following statements. Please rate how often each of these events occurred in your childhood (0 = Never; 100 = Happened everyday), as well as how much the event affected you, by using the slider bar (0 = Never affected me; 100 = Had an extreme affect on me). Has never happened Happened every day 0 50 100 b. Did a parent or other adult in the household often or very often act in a way that made you afraid that you would be physically hurt? () EEXPhyshurtaff Please rate how much it affected you Never affected me Had an extreme affect on me 0 50 100 b. How much it affected you () Page Break 147 EEXPARPHYSVIOL SECTION 3: YOUR EARLY EXPERIENCES Please read the following statements. Please rate how often each of these events occurred in your childhood (0 = Never; 100 = Happened everyday), as well as how much the event affected you, by using the slider bar (0 = Never affected me; 100 = Had an extreme affect on me). Has never happened Happened every day 0 50 100 c. Did a parent or other adult in the household often or very often push, grab, shove, or slap you? () EEXPARPHYSVIOLAFF Please rate how much it affected you Never affected me Had an extreme affect on me 0 50 100 c. How much it affected you () Page Break 148 EEXPARPHYSVIOLINJ SECTION 3: YOUR EARLY EXPERIENCES Please read the following statements. Please rate how often each of these events occurred in your childhood (0 = Never; 100 = Happened everyday), as well as how much the event affected you, by using the slider bar (0 = Never affected me; 100 = Had an extreme affect on me). Has never happened Happened every day 0 50 100 d. Did a parent or other adult in the household often or very often hit you so hard that you had marks or were injured? () EEXPARPHYSVIOLINJAFF Please rate how much it affected you Never affected me Had an extreme affect on me 0 50 100 d. How much it affected you () Page Break 149 ATTCHECKEEX1 SECTION 3: YOUR EARLY EXPERIENCES Please read the following statements. Please rate how often each of these events occurred in your childhood (0 = Never; 100 = Happened everyday), as well as how much the event affected you, by using the slider bar (0 = Never affected me; 100 = Had an extreme affect on me). Has never happened Happened every day 0 50 100 e. Please set this bar and the next bar to 100% () ATTCHECKEEX2 Please rate how much it affected you Never affected me Had an extreme affect on me 0 50 100 e. Set this bar to 100% () Page Break 150 EEXSEXUALTOUCHYOU SECTION 3: YOUR EARLY EXPERIENCES Please read the following statements. Please rate how often each of these events occurred in your childhood (0 = Never; 100 = Happened everyday), as well as how much the event affected you, by using the slider bar (0 = Never affected me; 100 = Had an extreme affect on me). Has never happened Happened every day 0 50 100 f. Did an adult or person at least 5 years older ever touch or fondle you in a sexual way? () EEXSEXUALTOUCHYOUAFF Please rate how much it affected you Never affected me Had an extreme affect on me 0 50 100 f. How much it affected you. () Page Break 151 EEXSEXUALTOUCHTHEM SECTION 3: YOUR EARLY EXPERIENCES Please read the following statements. Please rate how often each of these events occurred in your childhood (0 = Never; 100 = Happened everyday), as well as how much the event affected you, by using the slider bar (0 = Never affected me; 100 = Had an extreme affect on me). Has never happened Happened every day 0 50 100 g. Did an adult or person at least 5 years older ever have you touch their body in a sexual way? () EEXSEXUALTOUCHTHEMAF Please rate how much it affected you Never affected me Had an extreme affect on me 0 50 100 g. How much it affected you. () Page Break 152 EEXATTEMPINTERCRS SECTION 3: YOUR EARLY EXPERIENCES Please read the following statements. Please rate how often each of these events occurred in your childhood (0 = Never; 100 = Happened everyday), as well as how much the event affected you, by using the slider bar (0 = Never affected me; 100 = Had an extreme affect on me). Has never happened Happened every day 0 50 100 h. Did an adult or person at least 5 years older ever attempt oral, anal, or vaginal intercourse with you? () EEXATTEMPINTERCRSAFF Please rate how much it affected you Never affected me Had an extreme affect on me 0 50 100 h. How much it affected you. () Page Break 153 EEXHAVEINTERCRS SECTION 3: YOUR EARLY EXPERIENCES Please read the following statements. Please rate how often each of these events occurred in your childhood (0 = Never; 100 = Happened everyday), as well as how much the event affected you, by using the slider bar (0 = Never affected me; 100 = Had an extreme affect on me). Has never happened Happened every day 0 50 100 i. Did an adult or person at least 5 years older ever actually have oral, anal, or vaginal intercourse with you? () EEXHAVEINTERCRSAFF Please rate how much it affected you Never affected me Had an extreme affect on me 0 50 100 i. How much it affected you. () Page Break 154 EEXALCOHOLIC SECTION 3: YOUR EARLY EXPERIENCES Please read the following statements. Please rate how often each of these events occurred in your childhood (0 = Never; 100 = Happened everyday), as well as how much the event affected you, by using the slider bar (0 = Never affected me; 100 = Had an extreme affect on me). Has never happened Happened every day 0 50 100 j. Did you ever live with anyone who was a problem drinker or alcoholic? () EEXALCOHOLICAFF Please rate how much it affected you Never affected me Had an extreme affect on me 0 50 100 j. How much it affected you. () Page Break 155 EEXFDRUGSINHOME SECTION 3: YOUR EARLY EXPERIENCES Please read the following statements. Please rate how often each of these events occurred in your childhood (0 = Never; 100 = Happened everyday), as well as how much the event affected you, by using the slider bar (0 = Never affected me; 100 = Had an extreme affect on me). Has never happened Happened every day 0 50 100 k. Did you ever live with anyone who used street drugs? () EEXDRUGSINHOMEAFF Please rate how much it affected you Never affected me Had an extreme affect on me 0 50 100 k. How much it affected you. () Page Break 156 EEXMENTALHLTHHOME SECTION 3: YOUR EARLY EXPERIENCES Please read the following statements. Please rate how often each of these events occurred in your childhood (0 = Never; 100 = Happened everyday), as well as how much the event affected you, by using the slider bar (0 = Never affected me; 100 = Had an extreme affect on me). Has never happened Happened every day 0 50 100 l. Was a household member depressed or mentally ill? () EEXMENTALHLTHHOMEAFF Please rate how much it affected you Never affected me Had an extreme affect on me 0 50 100 l. How much it affected you. () Page Break 157 EEXSUICIDEATTEMP SECTION 3: YOUR EARLY EXPERIENCES Please read the following statements. Please rate how often each of these events occurred in your childhood (0 = Never; 100 = Happened everyday), as well as how much the event affected you, by using the slider bar (0 = Never affected me; 100 = Had an extreme affect on me). Has never happened Happened every day 0 50 100 m. Did a household member attempt suicide? () EEXSUICIDEATTEMPAFF Please rate how much it affected you Never affected me Had an extreme affect on me 0 50 100 m. How much it affected you. () Page Break 158 EEXMOTHERHIT SECTION 3: YOUR EARLY EXPERIENCES Please read the following statements. Please rate how often each of these events occurred in your childhood (0 = Never; 100 = Happened everyday), as well as how much the event affected you, by using the slider bar (0 = Never affected me; 100 = Had an extreme affect on me). Has never happened Happened every day 0 50 100 n. Was your mother (or stepmother) sometimes, often, or very often pushed, grabbed, slapped, or had something thrown at her? () EEXMOTHERHITAFF Please rate how much it affected you Never affected me Had an extreme affect on me 0 50 100 n. How much it affected you. () Page Break 159 EEXMOTHRHITOBJECT SECTION 3: YOUR EARLY EXPERIENCES Please read the following statements. Please rate how often each of these events occurred in your childhood (0 = Never; 100 = Happened everyday), as well as how much the event affected you, by using the slider bar (0 = Never affected me; 100 = Had an extreme affect on me). Has never happened Happened every day 0 50 100 o. Was your mother (or stepmother) sometimes, often, or very often kicked, bitten, hit with a fist, or hit with something hard? () EEXMOTHRHITOBJECTAFF Please rate how much it affected you Never affected me Had an extreme affect on me 0 50 100 o. How much it affected you. () Page Break 160 EEXMOTHRHITRPEATD SECTION 3: YOUR EARLY EXPERIENCES Please read the following statements. Please rate how often each of these events occurred in your childhood (0 = Never; 100 = Happened everyday), as well as how much the event affected you, by using the slider bar (0 = Never affected me; 100 = Had an extreme affect on me). Has never happened Happened every day 0 50 100 p. Was your mother (or stepmother) ever repeatedly hit over at least a few minutes? () EEXMOTHRHITRPEATDAFF Please rate how much it affected you Never affected me Had an extreme affect on me 0 50 100 p. How much it affected you. () Page Break 161 EEXMOTHERTHREATGUN SECTION 3: YOUR EARLY EXPERIENCES Please read the following statements. Please rate how often each of these events occurred in your childhood (0 = Never; 100 = Happened everyday), as well as how much the event affected you, by using the slider bar (0 = Never affected me; 100 = Had an extreme affect on me). Has never happened Happened every day 0 50 100 q. Was your mother (or stepmother) ever threatened with, or hurt by, a knife or gun? () EEXMOTHERTHREATGUNAF Please rate how much it affected you Never affected me Had an extreme affect on me 0 50 100 q. How much it affected you. () Page Break 162 EEXFAMILYPRISON SECTION 3: YOUR EARLY EXPERIENCES Please read the following statements. Please rate how often each of these events occurred in your childhood (0 = Never; 100 = Happened everyday), as well as how much the event affected you, by using the slider bar (0 = Never affected me; 100 = Had an extreme affect on me). Has never happened Happened every day 0 50 100 r. Did a household member go to prison? () EEXFAMILYPRISIONAFF Please rate how much it affected you Never affected me Had an extreme affect on me 0 50 100 r. How much it affected you. () Page Break 163 EEXVICTIMIZATION SECTION 3: YOUR EARLY EXPERIENCES Please read the following statements. Please rate how often each of these events occurred in your childhood (0 = Never; 100 = Happened everyday), as well as how much the event affected you, by using the slider bar (0 = Never affected me; 100 = Had an extreme affect on me). Has never happened Happened every day 0 50 100 s. Did you ever experience being victimized, bullied, or physically hurt by your peers? () EEXVICTIMIZATIONAFF Please rate how much it affected you Never affected me Had an extreme affect on me 0 50 100 s. How much it affected you. () Page Break 164 EEXCYBERBULLIED SECTION 3: YOUR EARLY EXPERIENCES Please read the following statements. Please rate how often each of these events occurred in your childhood (0 = Never; 100 = Happened everyday), as well as how much the event affected you, by using the slider bar (0 = Never affected me; 100 = Had an extreme affect on me). Has never happened Happened every day 0 50 100 t. Did you ever experience being victimized in acts of cyberbullying? () EEXCYBERBULLIEDAFF Please rate how much it affected you Never affected me Had an extreme affect on me 0 50 100 t. How much it affected you. () Page Break 165 EEXCHILDONLINE SECTION 3: YOUR EARLY EXPERIENCES Please read the following statements. Please rate how often each of these events occurred in your childhood (0 = Never; 100 = Happened everyday), as well as how much the event affected you, by using the slider bar (0 = Never affected me; 100 = Had an extreme affect on me). Has never happened Happened every day 0 50 100 u. Did you ever experience having your parents post a lot of information about you online that made you uncomfortable, despite pleas to stop? () EEXCHILDONLINEAFF Please rate how much it affected you Never affected me Had an extreme affect on me 0 50 100 u. How much it affected you. () Page Break 166 EEXNEIGHBOURHOOD SECTION 3: YOUR EARLY EXPERIENCES Please read the following statements. Please rate how often each of these events occurred in your childhood (0 = Never; 100 = Happened everyday), as well as how much the event affected you, by using the slider bar (0 = Never affected me; 100 = Had an extreme affect on me). Has never happened Happened every day 0 50 100 v. Did you ever experience living in a neighbourhood where it felt unsafe to go outside alone, at night, or with/without an adult? () EEXNEIGHBOURHOODAFF Please rate how much it affected you Never affected me Had an extreme affect on me 0 50 100 v. How much it affected you. () Page Break 167 EEXHOMELESSNESS SECTION 3: YOUR EARLY EXPERIENCES Please read the following statements. Please rate how often each of these events occurred in your childhood (0 = Never; 100 = Happened everyday), as well as how much the event affected you, by using the slider bar (0 = Never affected me; 100 = Had an extreme affect on me). Has never happened Happened every day 0 50 100 w. Did you ever experience homelessness, even for a short time? () EEXHOMELESSNESSAFF Please rate how much it affected you Never affected me Had an extreme affect on me 0 50 100 w. How much it affected you. () Page Break 168 EEXRACISM SECTION 3: YOUR EARLY EXPERIENCES Please read the following statements. Please rate how often each of these events occurred in your childhood (0 = Never; 100 = Happened everyday), as well as how much the event affected you, by using the slider bar (0 = Never affected me; 100 = Had an extreme affect on me). Has never happened Happened every day 0 50 100 x. Did you ever experience racism? () EEXRACISM Please rate how much it affected you Never affected me Had an extreme affect on me 0 50 100 x. How much it affected you. () Q10 If you answered 70-100 on any of the “how much it affected me” scales, and/or you feel bothered by thinking about the things that happened in your past, please visit the any of the following resources: USA & Worldwide: National Suicide Prevention Lifeline 1-800-273-8255 Canada: Crisis Service Canada: Call 1-833-456-4566 or text 45645 India Aasra 91-9820466726 Europe: 116 123 End of Block: EARLYEX Start of Block: RLSHPS 169 RLSHPSATT SECTION 4: YOUR RELATIONSHIPS Please rate how well each statement describes your typical feelings in romantic relationships: 170 Disagree Strongly (1) Disagree (2) Somewhat Disagree (3) Neutral (4) Somewhat Agree (5) Agree (6) Agree Strongly (7) a. It helps to turn to my romantic partner in times of need. (1) o o o o o o o b. I need a lot of reassurance from my partner. (2) o o o o o o o c. I want to get close to my partner but I keep pulling back. (3) o o o o o o o d. I find that my partner(s) don’t want to get as close as I would like. (4) o o o o o o o e. I turn to my partner for many things, including comfort and reassurance. (5) o o o o o o o f. My desire to be very close sometimes scares people away. (6) o o o o o o o 171 g. I try to avoid getting too close to my partner (7) o o o o o o o h. I do not often worry about being abandoned. (8) o o o o o o o i. I usually discuss my problems and concerns with my partner. (9) o o o o o o o j. I get frustrated if romantic partners are not available when I need them. (10) o o o o o o o k. I am nervous when partners get too close to me. (11) o o o o o o o l. I worry that romantic partners won’t care about me as much as I care about them. (12) o o o o o o o End of Block: RLSHPS Start of Block: FEELGNS 172 ANXDEP SECTION 5: MY FEELINGS Please read each statement and select the option that best indicates how much the 173 statement applied to you over the past week. There are no right or wrong answers. Do not spend too much time on any statement. 174 Did not apply to me at all (1) Applied to me to some degree, or some of the time (2) Applied to me to a considerable degree or a good part of time (3) Applied to me very much or most of the time (4) a. I was aware of dryness of my mouth (1) o o o o b. I couldn’t seem to experience any positive feeling at all (2) o o o o c. I experienced breathing difficulty (e.g. excessively rapid breathing, breathlessness in the absence of physical exertion) (3) o o o o d. I found it difficult to work up the initiative to do things (4) o o o o e. I experienced trembling (e.g. in the hands) (5) o o o o f. I was worried about situations in which I might panic and make a fool of myself (6) o o o o g. I felt that I had nothing to look forward to (7) o o o o h. I felt down-hearted and blue (8) o o o o i. I was intolerant of anything that kept me from getting on with what I was doing (9) o o o o 175 j. I felt I was close to panic (10) o o o o k. I was unable to become enthusiastic about anything (11) o o o o l. I felt I wasn’t worth much as a person (12) o o o o m. I was aware of the action of my heart in the absence of physical exertion (e.g. sense of heart rate increase, heart missing a beat) (13) o o o o n. I felt scared without any good reason (14) o o o o o. I felt that life was meaningless (15) o o o o End of Block: FEELGNS Start of Block: LIM LIM1 SECTION 6: CURRENT EXPERIENCES OF ROMANTIC ATTRACTION Please imagine the person you feel the strongest romantic connection to right now (this 176 may or may not be your partner). Please select the response that best fits with your experience around this person. 177 Disagree Strongly (1) Disagree (2) Somewhat Disagree (3) Neutral (4) Somewhat Agree (5) Agree (6) Agree Strongly (7) a. It is hard to imagine feeling romantic towards anybody else but this person (1) o o o o o o o b. I have a hard time speaking and cannot think clearly around this person (74) o o o o o o o c. Nobody else but this person could make me feel the way I do. (75) o o o o o o o d. I never seem to be 100% sure of how this person feels about me (76) o o o o o o o e. I know that, even if I wanted to, I could not change the way I feel about this person (77) o o o o o o o f. This person is the only person for me (78) o o o o o o o 178 g. This person’s shortcomings do not bother me (79) o o o o o o o h. Matters concerning this person are more important to me than any other concern that I have in my life (80) o o o o o o o i. The way I feel about this person leaves an aching sensation in the center of my chest (81) o o o o o o o j. I cannot control when or how often I think of this person (82) o o o o o o o k. I begin thinking of this person even when I do not will myself to do so (83) o o o o o o o l. I feel like I am powerless to change the way that I feel towards this person (84) o o o o o o o 179 m. I cannot seem to get this person out of my mind (85) o o o o o o o n. I am extremely happy when I believe this person feels strongly towards me (86) o o o o o o o o. When this person leaves, I develop an ache in the center of my chest (87) o o o o o o o Page Break 180 LIM2 SECTION 6: CURRENT EXPERIENCES OF ROMANTIC ATTRACTION Please imagine the person you feel the strongest romantic connection to right now (this may 181 or may not be your partner). Please select the response that best fits with your experience around this person. 182 Disagree Strongly (1) Disagree (2) Somewhat Disagree (3) Neutral (4) Somewhat Agree (5) Agree (6) Agree Strongly (7) p. Most of my thoughts concerning this person come about suddenly and without effort (1) o o o o o o o q. I do not pay any attention to this person’s negative attributes (4) o o o o o o o r. I could be wrong about how this person feels about me (5) o o o o o o o s. If this person felt the same way about me as I do for him/her I would be extremely happy (6) o o o o o o o t. I am unsure of how this person feels about me (7) o o o o o o o 183 u. I become overjoyed when I believe this person feels the same way about me as I do for him/her (8) o o o o o o o v. It is possible that this person could feel differently towards me than what I have been led to believe (9) o o o o o o o w. I cannot change the way I feel about this person (10) o o o o o o o x. When I think about this person, I develop an ache in the center of my chest (11) o o o o o o o y. I become extremely jittery and nervous around this person (12) o o o o o o o 184 z. To me, this person’s negative attributes are charming (13) o o o o o o o aa. When I am around this person, I become uneasy (14) o o o o o o o bb. None of this person’s negative attributes bother me (15) o o o o o o o cc. I experience the longing to be with this person as an aching sensation in the center of my chest (16) o o o o o o o dd. The feelings I have for this person are impossible to change (17) o o o o o o o End of Block: LIM 185 Start of Block: INTERNETUSE 186 INTUSE SECTION 7: INTERNET USE Please rate the extent to which you agree with the following statements: 187 Definitely Disagree (1) Disagree (2) Somewhat Disagree (3) Slightly Disagree (4) Slightly Agree (5) Somewhat Agree (6) Agree (7) Definitely Agree (8) a. I prefer online social interaction over face-to-face communication (1) o o o o o o o o b. Online social interaction is more comfortable for me than face-to-face interaction (16) o o o o o o o o c. I prefer communicating with people online rather than face-to- face (2) o o o o o o o o d. I have used the Internet to talk with others when I was feeling isolated (3) o o o o o o o o e. I have used the Internet to make myself feel better when I was down (4) o o o o o o o o f. I have used the Internet to make myself feel better when I’ve felt upset (5) o o o o o o o o 188 g. Please select slightly disagree as the answer to this question (15) o o o o o o o o h. When I haven’t been online for some time, I become preoccupied with the thought of going online (6) o o o o o o o o i. I would feel lost if I was unable to go online (7) o o o o o o o o j. I think obsessively about going online when I am offline (8) o o o o o o o o k. I have difficulty controlling the amount of time I spend online (9) o o o o o o o o l. I find it difficult to control my Internet use (10) o o o o o o o o m. When offline, I have a hard time trying to resist the urge to go online (11) o o o o o o o o 189 n. My internet use has made it difficult for me to manage my life (12) o o o o o o o o p. I have missed social engagements or activities because of my Internet use (13) o o o o o o o o q. My Internet use has created problems for me in my life (14) o o o o o o o o End of Block: INTERNETUSE Start of Block: DEMOGRAPHICS GENDER SECTION 8: ABOUT ME 1. Please select the gender that best describes you: o Cisgender Man Woman (I was assigned Male at birth, this aligns with who I am) (1) *Fixed after Sept 27 2022 data set o Cisgender Woman Man (I was assigned Female at birth, this aligns with who I am) (2) o Transgender Man (I was assigned Female at birth but my gender is actually Male) (3) o Transgender Woman (I was assigned Male at birth but my gender is actually Female) (4) o Non-Binary/Genderqueer (a bit of both genders) (5) o Agender (neither or no gender) (6) o Two-Spirit (Indigenous folx only) (7) 190 Display This Question: If GENDER != 1 And GENDER != 2 GENDERPRONOUNUSE 2. If you are NOT cisgender, do your bosses/teachers/professional contacts use your correct pronouns, or do they use pronouns you were assigned at birth? o Yes (they do use my correct pronouns, or they try to use my correct pronouns). (1) o No, I let them assume my pronouns as this feels safer for me. (2) o No, they refuse to use my correct pronouns. (3) PRONOUNS 3. Which pronouns best capture your true gender identity? o She/her (1) o He/him (2) o She/They (3) o He/They (4) o They/them (5) o It (6) o Other: please specify (7) __________________________________________________ 191 SEXATBIRTH 4. Please select one. I was: o Assigned Female at birth (1) o Assigned Male at birth (2) o Assigned Intersex at birth (3) SEXATTRACTION 5. Please select the option that best describes your romantic and sexual attractions: o Heterosexual/Straight (attracted to another gender that's different than yours) (1) o Homosexual/Gay/Lesbian (attracted to same gender as yourself) (2) o Bisexual/Pansexual (attracted to all people, regardless of their gender) (3) o Asexual/Ace (I do not desire sex) (4) INRELATSHP 6. Are you currently seeing someone, even just casually? o Yes (1) o No (2) SERIOUSRELATSHP 7. Have you been in a serious relationship in the past? o Yes (1) o No (2) 192 MONOGAMY Please select the option that best describes the majority of the types of relationships you have been in. If you haven't been in a relationship before, please select the option that corresponds with your preferred future relationship. o Monogamous (two partners exclusive to one another) (1) o Non-monogamous/Open (two partners in a relationship together, open for romantic or sexual contact with others outside of relationship) (2) o Polyamorous (multiple partners in committed relationship together) (3) o Situationship (casual relationship with multiple people) (4) BIRTHMONTH 8. What month were you born in? ▼ January (1) ... December (12) BIRTHYEAR 9. What year were you born in? ▼ 2010 (1) ... 1970 (41) Q132 Country of Residence o United States (1) o Canada (2) o Other (please list) (3) __________________________________________________ 193 POPULATION1 10. What is the approximate population of the town you grew up in? o 0-10,000 people (1) o 10,001-100,000 people (2) o 100,001- 500,000 people (3) o 500,001-1,000,000 people (4) o 1,000,001 or higher people (5) POPULATION2 11. I currently live in a town with: o Fewer than 50,000 people (1) o More than 50,000 people (2) o I'm not sure (Name town & State/Province) (3) __________________________________________________ ACADEMICPURSUITS 12. What are your academic and professional pursuits? o Complete high school or GED (1) o Complete certificate, trade school, or diploma (2 years) (2) o Complete Bachelor Degree (4 years) (3) o Complete Master’s Degree (4) o Doctorate Degree, Law Degree, or Medical School (5) 194 SESBEDROOMS SES1 13. How many bedrooms (including guest bedrooms and bedrooms used as offices, etc.) are/were in the house you spent the most time growing up in? ▼ 1 (1) ... 15 (15) SESVACATION SES214. During a typical year (pre-COVID), do you usually take at least one out-of-town vacation? o Yes (1) RECODED IN SPSS SEPT 14, 2022 NO = 1, YES = 2 o No (2) SESVEHICLE SES3 15. Do you have your own vehicle (car, truck, van, SUV)? o Yes - If yes, how many do you own?SES4 (1) __________________________________________________ o No (2) 195 ETHNICITY 16. What is your ethnic background? (please check the one you most closely identify with) o Indigenous origins (for example, First Nations, Inuit, Metis) (1) o South Asian origins (for example, East Indian, Sri Lankan, Pakistani) (2) o East Asian origins (for example, Chinese, Japanese, Korean) (3) o Southeast Asian origins (for example, Filipino, Thai, Vietnamese, Malaysian) (4) o West Asian origins (for example, Iranian, Afghan) (5) o Mexican (6) o South American origins (for example, Brazilian, Argentinian, Columbian, Chilean) (7) o White (8) o Black (9) o I don’t know (10) o Other (please list): (11) __________________________________________________ MARITALSTATUS 17. What is your marital status? o Single (1) o Engaged (2) o Married (3) o Common law/cohabitating with a partner (4) o Other (please list): (5) __________________________________________________ 196 RELIG1 18. How often do you think about religious issues? o Never (4) o A few times a year (5) o Once a week (6) o More than once a week (7) o Several times a day (8) RELIG2 19. To what extent do you believe that God, dieties or something divine exists? o Not at all (1) o Not very much (3) o Moderately (4) o Quite a bit (5) o Very much so (6) 197 RELIG3 20. How often do you take part in religious services? o Never (1) o A few times a year (6) o One or three times a month (7) o Once a week (8) o More than once a week (9) RELIG4 21. How often do you pray? o Never (1) o A few times a year (4) o Once a week (5) o More than once a week (6) o Several times a day (7) 198 RELIG5 22. How often do you experience situations in which you have the feeling that God or something divine intervenes in your life? o Never (1) o Rarely (4) o Occasionally (5) o Often (6) o Very often (7) POLITICS Please use the slider to indicate where your political beliefs lie on a spectrum between Democrat/Left/Liberal on the left (0), Republican/Right/Conservative on the right (100), and Center in the middle (50). Democrat/Left/Liberal Republican/Right/Conservative 0 50 100 My political compass () COVIDINFECTION 23. Have you been infected with, or have reason to believe you've been infected (close family member or friend was infected) with COVID-19? o Yes (1) o No (4) o I don't know (8) 199 COVIDVACCINE 24. Have you been vaccinated against COVID-19? o Yes, 2 or more doses (1) o Yes, 1 dose (9) o No (4) COVIDLIFEIMPACT 25. How have restrictions around the COVID-19 pandemic affected your life? o Did not affect me at all (1) o Affected me some degree, or some of the time (9) o Affected me to a considerable degree, or a good part of the time (4) o Affected me very much or most of the time (10) COVIDRELATIMPACT 26. How has the COVID-19 pandemic affected your romantic relationships? ________________________________________________________________ ________________________________________________________________ ________________________________________________________________ ________________________________________________________________ ________________________________________________________________ End of Block: DEMOGRAPHICS Start of Block: ID Q131 Here is your ID number: ${e://Field/Random%20ID} 200 Please copy this number. Once you've copied your ID, click submit to finish the survey. End of Block: ID
Thesis/Dissertation
eng
Human Development, Learning, and Culture
Vancouver : University of British Columbia Library
Attribution-NonCommercial-NoDerivatives 4.0 International
Graduate
Shapka, Jennifer
Young adult cyber violence : an investigation of the associations with vulnerable experiences, attachment patterns, problematic internet use, limerence, and internalizing symptoms
Text