EXAMINING THE TRANSMISSION OF ADVERSE CHILDHOOD EXPERIENCES IN A SAMPLE OF RURAL FAMILIES USING A PATH ANALYSIS By Gianna Casaburo A DISSERTATION Submitted to Michigan State University in partial fulfillment of the requirements for the degree of Human Development and Family Studies – Doctor of Philosophy 2023 ABSTRACT Exposure to adverse childhood experiences (ACEs) have been associated with numerous poor physical and mental health outcomes across the lifespan. As such, the goals of ACE research have shifted from delineating how ACEs negatively affect health outcomes to developing strategies for preventing ACEs. Yet, understanding how ACEs are transmitted, within the context of families, is underdeveloped. Relatively little research has examined factors contributing to ACE transmission across generations, with most existing research focused on how ACE exposure contributes to poorer health outcomes across generations. As the study of ACEs continues to broaden, I argue that it is critical to understand how parent characteristics may protect against transmission of ACEs across generations. This dissertation adds to the growing body of literature addressing ACE transmission in families. This study has two research aims. The first aim examined the associations between parent ACE score and child ACE score, parent emotion regulation (ER), and coercive parenting behaviors. I hypothesized that parent ACE score would be associated with higher child ACE scores, ER difficulties, and more coercive parenting behaviors. The second aim examined potential mediating variables across three models. My main hypothesis was that parent ER and coercive parenting behaviors would mediate the association between parent ACE score and child ACE score. A total of 125 respondents participated in this study. A path analysis was used to evaluate the research aims. Findings for aim one showed that parent ACE score was positively and significantly associated with parent ER difficulties. Findings for aim two identified that parent ER and coercive parenting behaviors were statistically significant as mediating variables between parent ACE score and child ACE score. Findings from this study suggest a potential pathway of ACE transmission between parents and children operating through parent ER difficulties and coercive parenting. The role of parent ER difficulties was most salient in the findings, suggesting that efforts to support parent ER may be one avenue for mitigating the transmission of ACEs in families. The results suggest therapists working with parents and children with ACE exposure should work to increase ER skills. Future research should continue to investigate the unique dimensions of parent ER and coercive parenting behaviors as mechanisms of ACE transmission as these findings suggest this may be one avenue in buffering ACE exposure in families. These findings should also encourage researchers to consider alternative mechanisms of transmission. To my family, my friends, and my partner- Thank you for always supporting and believing in me. iv ACKNOWLEDGMENTS First, I would like to acknowledge the participants of this study who disclosed adverse experiences with hope to expand the understanding of ACE transmission and promote the necessity of interventions for families. Second, I would like to acknowledge the therapists who provided essential support for the recruitment efforts of this study and continue to provide such necessary services to these children and parents. I am also extremely grateful for the funding that supported this research from the MSU Graduate School, the MSU HDFS Department, and the AAMFT Minority Fellowship Program. I am also immensely grateful to a number of people who have contributed to this work and to my growth at MSU. First, to my primary advisor, Dr. Kendal Holtrop, thank you for believing in me and my purpose at MSU. Words cannot adequately convey how much your unconditional support has meant to me throughout my journey. No question, concern, or need went unanswered and you embody all that it means to be a mentor. Thank you to my committee members, Drs. Holly Brophy-Herb, Yijie Wang, and Robey Shah for your mentorship and support of my research. Your compassion and care in helping me develop my method and analyses and reading many pages of my dissertation work is invaluable. Thank you for allowing me to learn from you and providing opportunities to grow as a researcher, therapist, and teacher. Above all, thank you to my committee members for leading with kindness. I am grateful to the numerous couple and family therapy faculty members who invested in me more ways than I knew were possible. Thank you to my clinic supervisors, Drs. Temple Odom, Kendal Holtrop, and Saila Subramaniam for believing in my clinical abilities and empowering me as a therapist. Thank you to Andrea Wittenborn for supporting my scholarship, and in time of great need, caring for me personally. It has been a privilege to be surrounded by v incredible scholars and leaders. Additionally, I would like to acknowledge Dr. Brett Wilkinson at Purdue Fort Wayne who encouraged me to pursue a PhD and changed the trajectory of my career. Thank you for believing in me even when I did not believe in myself. To my family and friends who have loved and supported me through this process, your endless encouragement, unconditional support, and joy are a true testament to the importance of community amidst the darkness of a PhD. To my colleagues, Dr. Deb Miller, Dr. Melissa Yzaguirre, and Kirsten Greer, you have inspired me in so many ways. Deb and Melissa thank you for welcoming me into the research group with open arms. You taught me the true meaning of friendship and what it means to dive into the literature. Kirsten, your bold ideas, desire for adventure, and true love of life continue to remind me to be unapologetically myself. To my parents, Shari and Jim, thank you for always encouraging me and for your unwavering love and support. To my grandparents, Sharon and Tom, thank you for always believing in me and encouraging me to pursue my goals. To my brother, sibling-in-laws, and nephew and nieces, Trey, Masie, Anna, Brian, Jamie, Kat, and Sophia, thank you for your continuous love and support, especially Jamie, Kat, and Sophia, for always asking me to play. And most importantly, to my partner, Kevin. Nothing I’ve accomplished would have been possible without you. Your patience, understanding, and flexibility gave me the confidence to persevere. Your willingness to learn about my research endlessly is the true embodiment of love. Go Green! vi TABLE OF CONTENTS CHAPTER I: INTRODUCTION .................................................................................................... 1 CHAPTER II: LITERATURE REVIEW ..................................................................................... 11 CHAPTER III: METHODOLOGY .............................................................................................. 29 CHAPTER IV: RESULTS ............................................................................................................ 53 CHAPTER V: DISCUSSION ....................................................................................................... 76 REFERENCES ............................................................................................................................. 91 APPENDIX A: SAMPLE RECRUITMENT FLYER ................................................................ 109 APPENDIX B: SAMPLE RECRUITMENT EMAIL ................................................................ 110 APPENDIX C: SAMPLE RECRUITMENT EMAIL ................................................................ 111 APPENDIX D: INFORMED CONSENT FORM ...................................................................... 112 APPENDIX E: PARTICIPANT DEMOGRAPHIC QUESTIONNAIRE .................................. 113 vii CHAPTER I: INTRODUCTION Significance and Background More than two decades of research show that adverse childhood experiences (ACEs) are predictive of mental, emotional, and physical health problems, such as substance use, anxiety, depression, suicidality, and even premature death (e.g., Anda et al., 2006; Felitti et al., 1998). ACEs are stressful or potentially traumatic events that occur before the age of 18, and include instances of abuse (physical, emotional, and sexual), neglect (physical and emotional), and household dysfunction (parental substance use, parental mental illness, domestic violence, divorce, and incarceration) (Felitti et al., 1998; See Table 1). Recent estimates suggest that ACEs are incredibly common, with over 60% of United States adults reporting exposure to four or more ACEs (Merrick et al., 2018). Table 1 Ten Adverse Childhood Experiences (ACEs) Category ACE Type Abuse Neglect Household Dysfunction 1. Physical Abuse 2. Sexual Abuse 3. Emotional Abuse 4. Physical Neglect 5. Emotional Neglect 6. Domestic Violence 7. Parent Mental Illness 8. Parent Substance Use 9. Parent Incarceration 10. Parent Separation Note. Original ACEs identified by Felitti et al. (1998) These statistics are alarming, as early exposure to adverse experiences in childhood are linked to various health problems across the lifespan (Anda et al., 2006; Merrick et al., 2018). As 1 such, there is evidence to suggest that ACEs may be transmitted across generations (Narayan et al., 2021; Thornberry, Knight, & Lovegrove, 2012). In other words, ACEs experienced by adults may have critical implications for ACE exposure in their children. For example, ACEs can result in lasting effects of toxic stress, which alter neural functioning and emotion regulation (ER) abilities (Bowers & Yehuda, 2016). Consequently, this process may increase the likelihood of ACE transmission between adults and children. Although a large body of research has established the detrimental consequences of ACE exposure, a noteworthy gap exists in examining the potential generational effects of ACEs in families. To respond to this limitation, this study seeks to extend the literature by identifying potential pathways of ACE transmission between parents and their children. By investigating this relationship, we may be better able to understand early points of intervention to mitigate child ACE exposure. Prevalence and Distribution of ACE Exposure in Children Population-based studies document high rates of ACE exposure across children in the United States (Sacks & Murphy, 2018). However, differences exist in ACE exposure in families across levels of socioeconomic status, racial and ethnic subgroups, gender, and geographic location (Berger, 2004; Merrick et al., 2018; Mersky, Topitzes, & Reynolds, 2013). For example, children are more likely to experience ACEs if they experience economic oppression compared to children with greater socioeconomic security (Berger, 2004). Additionally, there are noticeable differences across studies by race and ethnicity in the number of ACEs experienced (Felitti et al., 1998; Merrick et al., 2018). For example, recent work has found that Black and Hispanic children are more likely to experience two or more ACEs compared to White children (Slopen et al., 2016). Differential susceptibility to ACE exposure has also been suggested across genders. Some studies indicate that rates of ACE exposure may be higher for boys than girls 2 (e.g., Mersky, Topitzes, & Reynolds, 2013); however, there is mixed evidence as to whether boys or girls are more negatively affected by ACE exposure. Our limited understanding suggests that more research is needed to examine subgroup differences in ACE exposure across populations and genders. Although ACE exposure may be greater in more vulnerable families (e.g., families experiencing economic hardship or low educational attainment), there has been limited research dedicated to potential differences in geographic location. One study suggests that compared to urban children, rural children are at greater risk for overall ACE exposure (Crouch et al., 2020). However, other studies (Crouch et al., 2017; Talbot, Szlosek, & Ziller, 2016; U.S. Department of Health and Human Services, 2015) report similar ACE exposure patterns in rural and urban children. Overall, studies identifying the prevalence and distribution of ACE exposure in children are lacking and more attention is required to understand the transmission of ACEs between parents and their children. Consequences of ACE Exposure in Children While a multitude of studies have examined the outcomes of ACE exposure into adulthood, the literature regarding outcomes in children remains limited. Yet, evidence suggests that children exposed to ACEs have an increased risk of emotional and behavioral health problems (Center for Disease Control and Prevention, 2019). Similarly, mental health diagnoses in childhood have been shown to have a greater likelihood of emerging after ACE exposure (Burke et al., 2011). For example, children with ACE exposure are more likely to experience poorer academic achievement (Bethell et al., 2014; Jimenez et al., 2016), attention and behavioral problems (Burke et al., 2011; Jimenez et al., 2016; McKelvey et al., 2016), suicidality (Brodsky & Stanley, 2008; Dube et al., 2003), peer problems (Kerker et al., 2015), emotion dysregulation (Bielas et al., 2016), and delinquency (Baglivio et al., 2014). Although literature 3 on the effects of ACEs on child outcomes remains scarce, it is evident that children with early ACE exposure are more likely to develop behavioral health problems later in life (Felitti et al., 1998). Importantly, this evidence suggests that children are vulnerable to a variety of poor health outcomes, which necessitates more research focused on the prevention of ACEs in families. ACE Transmission Between Parents and Children Little is known about the pathways that contribute to ACE transmission between parents and children, subsequently leading to poorer health outcomes across generations. In response to this limitation, research assessing and addressing ACEs in child and family contexts is beginning to emerge (Bethell et al., 2017; Vu et al., 2017). To date, researchers have predominantly examined the associations between specific ACE exposure in parents and child behavioral outcomes (e.g., Folger et al., 2018). For example, studies have found that maternal exposure to abuse in childhood is linked to greater behavioral problems in their children (McDonnell & Valentino, 2016). Another study found that mothers with a history of abuse predicted poorer socio-emotional development in their children (Harris et al., 2021). Other studies have found that parent exposure to ACEs predicts child conduct problems (Adkins et al., 2020), lower levels of behavior regulation (Bouvette-Turcot et al., 2015), and the development of internalizing and externalizing behaviors (Fredland et al., 2018). This work, while important, leaves the relationship between parent ACE exposure and child ACE exposure largely unexamined. Consequently, our understanding of the pathways associated with ACE transmission in families is quite limited. However, a smaller but growing body of literature shows that parents with ACE exposure are more likely to have poorer ER capabilities and parenting behaviors than those without ACE exposure, thus increasing the likelihood of ACE exposure in their children (Thurston, Bell, & 4 Induni, 2018). For example, parent ER can influence parental stress and coercive parenting behaviors, which are well-documented risk factors for child abuse and neglect (Kim & Cicchetti, 2010). In turn, their children are at greater risk for experiencing ACEs. Thus, examining these potential pathways is important for informing intervention and prevention efforts. As the study of ACEs enters its third decade, I argue that in order to translate ACE research into preventative action, it is crucial to gain a better understanding of the transmission of ACEs between parents and their children. This study builds on emerging research examining the generational effects of ACEs and the underlying pathways related to ACE exposure in children. More specifically, this study adds to the literature by: 1) investigating the association of parent ER and coercive parenting behaviors on the transmission of ACEs, and 2) investigating two alternative models of potential pathways of transmission to further expand our understanding of ACE transmission between parents and children. Understanding pathways of transmission holds promise for identifying modifiable factors to inform intervention research and practice. Bowen Family Systems Theory Theoretical Framework Bowen family systems theory provides a framework for understanding ACE transmission between parents and their children. Bowen family systems theory was developed by Murry Bowen (1978) and has been expanded upon by others through extensive research (e.g., MacKay & Brown, 2013; Peleg-Popko, 2002; Titelman, 2014). Bowen was initially interested in learning more about patterns that develop in families in order to defuse distress (Bowen, 1978), and how those patterns were transmitted across generations. Scientific evidence suggests that individual and relational levels of functioning are transmitted from one generation to the next. For example, several studies have demonstrated a multigenerational process of violence (Alexander, Moore, & 5 Alexander, 1991), divorce (Amato, 1996), marital quality (Feng et al., 1999), and substance use (Sher et al., 1997). In addition, Bowen (1978) discovered that a key generator of distress in families is the perception of either too much closeness or too great a distance in relationships. This means that the interactions between parents and children are especially critical in perpetuating or managing adverse events. Likewise, the degree of distress in any one family is determined by the current levels of external stress and exposure to adverse experiences across generations (i.e., between parents and children). For instance, when family members do not have the capacity to think through their responses to adverse situations, but rather react anxiously to perceived emotional demands, a state of chronic distress (e.g., anxiety) or emotional reactivity may be experienced (Bowen, 1978). From this research, Bowen (1978) concluded that in order to manage responses to adverse events, families would need to develop awareness of how emotional systems function, which would allow them to focus on developing new and healthier patterns of interactions. Several studies (Bohlander, 1995; Haber et al., 1993; Skowron & Friedlander, 1998; Tuason & Friedlander, 2000) have found that an individual’s level of ER is directly related to the level of anxiety experienced. For example, lower levels of ER are associated with greater levels of anxiety, while greater levels of ER are associated with lower levels of anxiety (Tuason & Friedlander, 2000). Further, according to the Bowen perspective, ACEs can be conceptualized as a facet of family functioning, in which there is ‘insufficient emotional separation’ between family members and the ability to solve problems (Bowen, 1978). As such, Bowen would theorize that families would respond to adverse experiences from a place of emotional reactivity (Bowen, 6 1978). This means that parents would exhibit greater levels of emotional reactivity when parenting, which would influence the likelihood of their children experiencing an adverse event and subsequent health problems. Thus, Bowen’s theory provides a conceptual framework of how parents’ functioning plays a critical role in child ACE exposure. It further assists in unpacking the important elements that may allow ACEs to remain unchallenged and transmitted across generations. Sample Context: Rural Families Present Study The focal population for this study is rural families receiving behavioral health services at a small rural health clinic in Indiana. Research examining the prevalence and patterns of ACEs in rural populations is limited. Yet, several studies have shown that ACEs are common in rural and under-resourced communities (e.g., Crouch et al., 2020; Schofield et al., 2018). Recent estimates from the Behavioral Risk Factor Surveillance System Survey (Centers for Disease Control and Prevention, 2022) revealed that 55.4% of rural adults reported exposure to at least one ACE and 14.7% experienced four or more ACEs (Chanlongbrutra et al., 2018). In addition, among young people under the age of 17, the National Survey on Children’s Health 2011-2012 (Centers for Disease Control and Prevention, 2012) found that 28.9% of children living in small rural areas experienced two or more ACEs compared to 21.3% of urban children. Although there is limited research specific to rural and urban differences in the prevalence and severity of ACEs (e.g., ACE type, frequency, and length of exposure), these findings suggest a similar pattern: that rural children and adults are at a greater risk of experiencing ACEs and poorer health outcomes (Crouch et al., 2020). Likewise, the assessment of ACEs in rural families and the ability to examine the transmission of ACEs between parents 7 and children is a serious gap in the current research. With nearly 13 million children living in rural areas across the United States (United States Census Bureau, 2016) and with rural populations experiencing greater levels of poverty, child maltreatment, and lower life expectancies (Centers for Disease Control and Prevention, 2022), the prevention of ACEs among this population is critical. Approach: Community-Academic Research Partnership The current research literature indicates the need for increased dissemination and implementation of research in community settings (National Institutes of Health, 2018). Community-academic research partnerships involve collaboration between universities and communities to conduct research (National Institutes of Health, 2018). Although there may be differences in their research designs (e.g., participatory action research, community-based participatory research, community-partner research), community-academic research is based on the principles of equitable decision making in order to improve the wellbeing of communities by conducting research that addresses their needs (Israel et al., 2019; National Institutes of Health, 2018). As such, engagement in a community-academic partnership for this study supports enhancing behavioral health services for families with ACE exposure at a rural health clinic. These expressed needs are the foundation of the community-academic partnership formed in 2022 between me and the Bowen Health Clinic – a large community health clinic in Indiana providing services to individuals, families, and children with behavioral health needs. This community-academic partnership will bridge scholarship and collaboration and generate mutually beneficial research to support families receiving behavioral health services. This partnership will allow for collaboration in study development activities, including recruitment 8 efforts, and engagement in ongoing feedback throughout the research process. Findings from this study will be shared with the Bowen Health Clinic to better inform prevention and intervention efforts for families. Purpose of the Study and Aims Although existing research substantiates that early exposure to ACEs is associated with poorer health outcomes across the lifespan (Felitti et al., 1998; Merrick et al., 2018), the underlying pathways that explain the association between parent ACE exposure and child ACE exposure are not well understood. Thus, the purpose of this quantitative study is to address this gap by investigating the potential mediating role of parent ER and coercive parenting behaviors as well as two alternative mediation models on the transmission of ACEs exposure between parents and children (see Method Section). This study will explore these research objectives in a sample of under-resourced rural families at the Bowen Health Clinic in the state of Indiana. The following specific aims will be addressed: Aim 1. Investigate the associations between parent ACE exposure and three outcomes: (a) child ACE exposure, (b) coercive parenting behaviors, and (c) parent emotion regulation. Hypothesis 1a. Greater levels of parent ACE exposure will be associated with greater child ACE exposure as measured by the Pediatric ACEs and Related Life Events Screener (Koita et al., 2018) among a sample of rural families. Hypothesis 1b. Greater levels of parent ACE exposure will be associated with more coercive parenting behaviors as measured by the Parenting Behaviors Inventory (Lovejoy et al., 1999). 9 Hypothesis 1c. Greater levels of parent ACE exposure will be associated with more parental emotion regulation difficulties as measured by the Difficulties in Emotion Regulation Scale (Victor & Klonsky, 2016). Aim 2. Test whether parent ER and coercive parenting behaviors mediate the relationship between parent ACE exposure and child ACE exposure. Hypothesis 2. A path model in which parent ER and coercive parenting behaviors serve as mediators of the relationship between parent ACE score and child ACE score will demonstrate a significant specific indirect effect. 10 CHAPTER II: LITERATURE REVIEW To provide support for the research aims and hypotheses of this study, in this chapter I will review research on adverse childhood experiences (ACEs), parenting behaviors, parent emotion regulation (ER), and child ACE exposure. I will first briefly review ACEs literature. I will then argue that adopting the Bowen family systems theory provides a useful explanatory framework for understanding the complex pathways of ACE transmission in families. Next, I will review and summarize the empirical research on the association between parent ACE exposure and child ACE exposure. Finally, I will conclude by reviewing the empirical research on parent ACE exposure, parenting behaviors and emotion regulation (ER). Brief Review of ACEs Adversities experienced in childhood are identified as potential risk factors that lead to poorer health outcomes beginning in childhood and continuing into adulthood (Felitti et al., 1998). Most ACE definitions include experiences of abuse, neglect, and household dysfunction (Felitti et al., 1998) and are also commonly identified as potentially traumatic experiences that occur before the age of 18 and impact overall well-being (Centers for Disease Control and Prevention, 2019). Although ACEs are common across populations, patterns of adversity are disproportionately prevalent across socioeconomic status, race and ethnicity, gender, and geographic location (Merrick et al., 2018). Rural communities, in particular, are vulnerable to greater ACE exposure (Crouch et al., 2020; Schofield et al., 2018). Recent estimates suggest that rural children are more likely to experience parental divorce or separation and live with someone with an alcohol or substance use disorder (Talbot, Szloek, & Ziller, 2016) compared to children in urban communities. Broad outcomes include significantly heightened risk for social, 11 emotional, and cognitive impairment; health-risk behaviors; and disease and disability (Chapman, Dube, & Anda, 2007; Merrick et al., 2017). In addition, a significant dose-response effect has also been shown across the literature with regard to ACEs (Felitti et al., 1998; Merrick et al., 2018). This means that greater ACE exposure predicts more deleterious effects into adulthood (Hughes & Tucker, 2018). For example, one study found that participants who reported exposure to four or more ACEs were found to have a wide variety of heightened health risks compared to those who reported no childhood ACEs (Anda et al., 2002). Another study found that four or more ACEs were associated with a 4 to 12-time increased risk for smoking, poor self-rated health, increased risk for physical inactivity, and obesity (Felitti et al., 2009). These findings illustrate how the consequences of multiple ACEs are strong and cumulative and extend into adulthood (Felitti, 2009; Felitti et al., 1998). Beyond physical health outcomes, research has examined the associations between poorer mental and emotional health outcomes and exposure to ACEs in children and adults. Childhood is a key time for developing ER abilities (Nanni, Uher, & Danese, 2012), and early ACE exposure has been associated with poorer ER (England-Mason et al., 2017). In sum, there is a strong body of literature showing that ACEs have long-lasting effects on physical, mental, and emotional health outcomes across the lifespan (Merrick et al., 2018). Likewise, parents and children with early ACE exposure are more likely to experience poorer socioemotional development (McDonnell & Valentino, 2016), developmental delays (Folger et al., 2018), and behavioral problems (Jimenez et al., 2016). However, it is important to remember that early ACE exposure is probabilistic and not deterministic in its relation to future outcomes; 12 thus, more research is needed to examine pathways of ACE transmission across generations in order to mitigate subsequent negative outcomes. Theoretical Framework Bowen Family Systems Theory Bowen family systems theory (1978) provides a theoretical framework in understanding how adverse childhood experiences are managed through family relationships as part of the family emotional process. Bowen theorized that each family has an emotional system which seeks to reduce tension and maintain stability. Bowen developed eight interlocking concepts (see Table 2) which describe the inevitable chronic emotional states of families as the source of family dysfunction. This study will specifically focus on how the differentiation of self and the multigenerational transmission process contribute to the development of ER abilities in families with ACE exposure. Table 2 Bowen Family Systems Theory Key Terms Key Terms Definition 1. Individuality and togetherness 2. Unresolved emotional attachment 3. Differentiation of self Individuality refers to a family members’ ability to function autonomously; togetherness refers to emotional closeness between family members The degree of attachment with one’s parents that drives the ability to adapt and manage adverse experiences The ability to be in emotional contact with other family members yet still autonomous in one’s own emotional functioning 13 Table 2 (cont’d) 4. Chronic anxiety 5. Multigenerational transmission process 6. Triangles 7. Cutoff 8. Sibling position A response to an imagined threat - has a more enduring quality; stressful events may disturb the balance in the family system; chronic anxiety can exceed a person or family’s ability to cope The process of how family members develop and interact with each other describes how differences in differentiation between parents and children lead to changes across generations When a three-person system can no longer contain the anxiety, it involves more people and forms a series of interlocking triangles The way people manage the intensity of fusion across generations; a ‘cutoff’ can be achieved through physical distance or through forms of emotional withdraw The sibling position can provide useful information in understanding the roles individuals tend to take in relationships The key concept of Bowen theory is the differentiation of self, which refers to a person's ability to distinguish themselves from their family of origin (Bowen, 1978). In other words, this refers to family members’ abilities to be in emotional contact with other family members yet still autonomous in their own emotional functioning (Kerr & Bowen, 1988). Bowen proposed that family members who have greater ER abilities function more effectively during times of stress compared to individuals with less ER abilities. As such, family members with lower levels of differentiation might experience greater levels of emotional reactivity and anxiety (Bowen, 1978). Because ACE exposure in childhood activates toxic stress, which can impair brain development and the ability to emotionally regulate (Shonkoff & Garner, 2012), parents with 14 ACE exposure will likely demonstrate lower levels of differentiation and ER. From this perspective, children may be more likely to experience an adverse event based on the influence of their parents' ER. In addition, Bowen theorized that parents’ abilities to manage their own emotional reactivity guides how they manage stressful experiences with their children. This is one reason why it is important to examine parent ER in the transmission of ACEs in families. It is further theorized that parents’ ability to regulate their emotions would also influence their parenting behaviors with their children (Bowen, 1978). For example, Bowen would theorize that greater levels of ACE exposure are linked to more emotional reactivity and thus greater levels of coercive parenting behaviors. As such, to manage chronic emotional states (e.g., distress and anxiety) and emotional reactivity, Bowen proposed that families generally use four mechanisms: (1) family conflict, (2) health or emotional problems, (3) health or emotional problems of a child, or (4) triangulation of family members (Bowen, 1978). Each family may exhibit a different management strategy which can potentially perpetuate or mitigate the transmission of ACE exposure across generations. Subsequently a family's ability to manage adverse events will likely determine how future generations respond. This process is known as the multigenerational transmission process. The multigenerational transmission process is the process in which family members develop interaction patterns (Kerr & Bowen, 1988). This describes how differences in differentiation (i.e., ER) between parents and children lead to the transmission of ACEs across generations. The transmission occurs on several interconnected levels, ranging from the conscious teaching and learning of information between parents and children to the automatic and unconscious emotional reactions and behaviors (Kerr & Bowen, 1988). As such, children 15 develop ER abilities similar to their parents. Thus, the impact on overall life functioning explains the marked similarity that typically exists in the lives of family members across generations. Highly differentiated families have stable nuclear families, while poorly differentiated families experience greater levels of anxiety and emotional reactivity, and heavily depend on others to manage their emotional responses (Bowen, 1978). A key implication of the multigenerational concept is that the roots of many ACEs are generations deep. This means that ACEs are often transmitted across generations by sustained pathways (e.g., emotion regulation, parenting behaviors) and inform not only individuals, but also family members on how to interact with each other (Bowen, 1978). When parents are unsuccessful in managing their emotional responses, the likelihood of experiencing an ACE event in childhood increases. As a result, children may have a difficult time learning how to resolve stressful situations. When family members are unable to resolve stressful experiences, a greater level of cortisol is often released which sends the message that they are in danger and they need to emotionally react to manage the situation (Arbel, Rodriguez, & Margolin, 2016). Even though cortisol is known to help during stressful situations, the repeated release of cortisol can develop toxic stress and impair mental, emotional, and behavioral development across the lifespan (Shonkoff & Garner, 2012). Thus, the family’s management of adverse experiences may determine generational transmission. Transmission of ACEs Between Parents and Children Parent ACE Exposure and Child ACE Exposure Although specific parent ACEs, such as abuse and neglect in childhood, have been linked with social, emotional, and behavioral problems in their children (Andrews, Brown, & Creasey, 1990; Lange, Callinan, & Smith, 2019), one area that receives less attention is the crucial role of 16 a parent’s own early life adversity as a risk factor for ACE exposure in their children (Narayan, Lieberman, & Masten, 2021). For example, mothers with childhood exposure to abuse or neglect are more likely to expose their children to experiences of abuse and neglect (Fogler et al., 2018). As such, it is important to investigate the link between parent ACEs and child ACE exposure because many of the sequalae of ACEs in parents have critical implications. While a large concentration of the literature focuses on the link between parent ACEs and child health outcomes (see Le-Scherban et al., 2018), growing evidence indicates parent ACE exposure as a risk factor for ACE exposure in children (Narayan et al., 2017; Narayan et al., 2021). For example, Schofield and colleagues (2018) found that rural children of parents who experienced ACEs were more likely to experience ACEs. This suggests that greater levels of parent ACE exposure increase the risk of ACE transmission between parents and their children. Thus, parent ACEs, as well as ACE exposure in prior generations, may activate and sustain generational pathways of ACE exposure that pose substantial risk for ACEs in children (Narayan et al., 2021). This is likely because parents’ ability to care for their children and mitigate experiences of adversity, are rooted in parents’ own childhood experiences. This means that parents’ exposure to ACEs may contribute to pathways of ACE exposure in the next generation of children (Narayan et al., 2021). Although narrow in scope, pathways of ACE transmission between parents and their children have been explored across the literature. For example, Renner & Slack (2006) investigated the transmission of intimate partner violence and other forms of child maltreatment from childhood to adulthood. They found some evidence of exposure to intimate partner violence in childhood as a predictor for victimization in adulthood. In addition, Egeland, Jacobvitz, and Sroufe (1988) examined maternal childhood abuse as a predict for child ACE exposure. This 17 study found, in cases in which abuse was transmitted between mother and child, that those mothers were experiencing significantly more life stress and had more mental health concerns. Another study examined the pathway between maternal substance use and child ACE exposure (Appleyard et al., 2011). This study found no significant mediating pathway between maternal substance use and child ACE exposure. Another study investigated community factors such as socioeconomic status, perceived social cohesion, and access to community services as predictors of child ACE exposure (Schofield et al., 2018). Schofield and colleagues (2018) found a significant association between community resources and ACE exposure. The findings indicate that less access to community resources is associated with more ACE exposure in parents and their children. Lastly, although not within the scope of this dissertation, an emerging body of literature highlights the potential influence of epigenetics (e.g., Narayan et al., 2021; Scorza et al., 2023). For example, a recent study conducted by Scorza and colleagues (2020) found that adverse parental environments affected gene expression in parents and their children. This preliminary finding supports the notion that changes in DNA sequences could be a marker for another pathway of generational transmission of ACEs in families and requires further investigation. The present study makes an important research contribution by extending our knowledge on potential pathways of transmission. This study strengthens our understanding of the mediating roles of parent ER and coercive parenting behaviors on the pathways of ACE transmission between parent ACEs and child ACEs. By identifying pathways of transmission between parents and children we are better able to advance prevention and intervention efforts necessary to mitigate poorer health outcomes in families. 18 Parent ACE Exposure and ER ACE transmission between parents and children may also operate through parent ER. ER refers to the ability to recognize, express, and manage emotional responses (Gratz & Roemer, 2004). Said another way, ER is a multidimensional construct that includes environmental and behavioral responses (Grazt & Roemer, 2004). The ability to develop ER skills begins in childhood and continues into adulthood. As such, parents with ACE exposure may be at risk of developing maladaptive emotion regulation strategies early on and thus consequently disrupting their parenting (Marusak et al., 2015; Naragon-Gainey et al., 2017). Yet, much of the current work on ER does not disentangle the process of ACE transmission between parents and children. Findings on ER in parents exposed to ACEs are almost universally consistent, generally concluding that parents with ACE exposure have poorer ER abilities compared to parents with no ACE exposure (e.g., Milojevich, Lindquist, & Sheridan, 2021). For example, several studies have found that adversity-exposed parents have stronger emotional reactions and are more prone to more intense reactions compared to those without ACE exposure (e.g., Haskett et al., 2012; Lavi et al., 2019). Another study found that parents who experienced abuse in childhood demonstrated more emotional intensity and persistence (Shackman & Pollak, 2014). Other studies have found that exposure to violence in childhood is linked to ER deficits across the lifespan and greater self-reports of anger (e.g., Lambert et al., 2017; Maschi et al., 2008). Moreover, ACEs in childhood often exceed a child's ability to evaluate or cope with the event (Pechtel & Pizzagalli, 2011). Likewise, early adverse events are more likely to be perceived as uncontrollable and more debilitating (Arnsten, 2015). As a result, parents and children may develop maladaptive strategies that help them cope with adverse events (Dube et al., 2001). In addition, parents exposed to ACEs in childhood demonstrate greater neural 19 activation in the brain regions associated with emotional reactivity and unpleasant affect (McLaughlin et al., 2015). These findings indicate that exposure to ACEs in childhood is associated with poorer ER. Further, studies show that exposure to ACEs in childhood is associated with less adaptive emotion regulation strategies, such as disengagement, expressive suppression, and rumination (Maughan & Cicchetti, 2002; Milojevich, Lindquest, & Sheridan, 2021). Thus, these early adverse experiences and maladaptive ER responses may account for the increased likelihood of emotional impairment experienced across the lifespan (Dube et al., 2001). These findings suggest that exposure to chronic adverse events might set the stage for long-term challenges in ER. As such, exposure to ACEs in childhood may increase the susceptibility of developing toxic stress and elevated cortisol levels which manage ER abilities (Gee et al., 2013). Parent ACEs and Toxic Stress Chronic exposure to adverse events has long-term negative effects on the physiological stress regulatory systems (Lupien et al., 2000). The National Scientific Council on the Developing Child (2014) defines toxic stress as the intense and prolonged activation of the stress response system. When a child experiences a prolonged stress response, they experience a state of sustained threat which alters brain development and potentially impairs regulatory capabilities across the lifespan (National Scientific Council on the Developing Child, 2014). Growing evidence suggests that chronic exposure to ACEs produces lasting neurobiological changes (Boyce et al., 2021). In other words, the stress response system is activated more frequently and for longer periods of time influencing ER. 20 Further, a dose-response effect exists with the increasing number of ACEs making it more likely a child will experience toxic stress and its harmful consequences (Felitti et al., 1998; Gilbert et al., 2015). The amygdala and prefrontal cortex play a critical role in managing stress. The prefrontal cortex is widely considered as a top-down region that regulates the amygdala, while the amygdala detects and responds to threats from the environment, activating a physiological stress response (Rodrigues, LeDoux, & Sapolsky, 2009). More specifically, the ventrolateral prefrontal cortex, dorsolateral prefrontal cortex, and medial prefrontal cortex implement strategies involved in ER (Ochsner, Silvers, & Buhle, 2012). Likewise, when these areas of the brain are injured due to repeated ACE exposure, the ability to respond and emotionally regulate is compromised. As such, ACEs increase the levels of stress hormones in the body, and over time, exposure to these high levels of stress alters the biology of the stress response system, thus affecting long-term physical and mental health (Shonkoff & Garner, 2012). This means that the body responds at lower thresholds to situations that may not be considered stressful to others. The brain is altered so that a person’s physiological stress response converts to toxic stress. When this happens, normal events can be perceived as life-threatening (Shonkoff & Garner, 2012). In turn, early exposure to ACEs might lay the foundation for ER abilities across the lifespan and subsequently impact parenting behaviors in adulthood. Parent ACE Exposure and Parenting Behaviors Early adverse experiences in childhood can impact how adults later parent their own children (Letourneau et al., 2019). Parenting behaviors are an essential and yet complex variable to examine in the ACE literature. Positive parenting refers to several parenting behaviors, including consistent discipline, praise, and monitoring (Ryan, O’Farrelly, & Ramchandani, 21 2017). Whereas coercive parenting behaviors are characterized as harsh, hostile, and inconsistent (e.g., Belsky, Conger, & Capaldi, 2009). Given the pernicious outcomes for both parents and children that result from ACEs, several research studies have sought to examine how parent ACE exposure may impact parenting behaviors. Research suggests that parenting might be one mechanism through which ACEs are transmitted to subsequent generations (Chung et al., 2009). The common goal of parenting is to provide safety and support the well-being of the child; however, these goals can be difficult to achieve for parents with ACE exposure (Rowell & Neal-Barnett, 2021). While researchers widely support positive parenting behaviors, it can be challenging for parents to use the skills needed to enforce these behaviors during times of stress (Reece, 2013). This can be especially true for parents with a history of ACEs because they often had ineffective models of parenting in childhood and, thus, lack the necessary skills to implement positive parenting behaviors (Madigan et al., 2006). Often parents with ACE histories tend to use frequent punishment and control in parenting (Nieman et al., 2004). As such, these parents often rely on more aggressive and inconsistent forms of parenting including yelling, hitting, and threatening the child (Zubizarreta, Calvete, & Hankin, 2019). Other studies have found that parents with histories of child maltreatment often exhibit more harshness, aggression, and hostility towards their children (Conger et al., 2013; Newcome & Locke, 2001). Another study found that mothers' exposure to sexual abuse in childhood was associated with aggressive parenting behaviors (Newcomb & Locke, 2001). Similarly, another study found that maternal physical abuse in childhood was associated with poorer parenting behaviors, and maternal childhood exposure to sexual abuse was associated with reduced parenting involvement (Lyons-Ruth et al., 1989). In addition, two studies found that parental exposure to ACEs was associated with parental stress, which negatively impacted parenting 22 behaviors (Ammerman et al., 2013; Steele et al., 2016). Further, another study found that parents who had exposure to four or more ACEs were more likely to have difficulty parenting their children, which resulted in increased risk for child neglect or abuse (Murphy et al., 2014). In sum, early ACE exposure for parents increases the risk of using more coercive parenting behaviors with their children. Yet despite this recognition and the essential role of parents, the current research is fairly limited in understanding how specific pathways such as parenting behaviors and parent ER contribute to ACE exposure in children. Parent ER and Parenting Behaviors Most parenting behaviors are integrally connected to ER (Chen et al., 2020). As such, deficits in ER induced by ACEs could hamper parenting behaviors. There is considerable evidence for the importance of positive parenting behaviors for children. While there are many determinants of parenting, studies have shown that parents with lower levels of distress appear better able to manage their parenting, compared to parents who have greater levels of emotional reactivity (e.g., Crandall, Deater-Deckard, & Riley, 2015). As such, parent ER may influence coercive parenting behaviors by making it more difficult to manage and regulate emotions (Gross & Thompson, 2007). For example, findings from the literature reveal that parents who were exposed to adverse events struggle with ER and therefore tend to have interactions with their children that are characterized by increased disengagement, intrusiveness, hostility and decreased responsivity, sensitivity, and structure (Fuchs et al., 2015). While there is not yet enough longitudinal research to speak definitively about the direction of the relationship between ACE exposure and ER (Compas et al., 2017), there is theoretical and empirical suggestion that disruptions in ER may proceed coercive parenting behaviors. For instance, poorer parent ER skills accounts for more coercive and inconsistent 23 parenting behaviors (Metcalfe et al., 2020). Likewise, difficulties in regulating negative emotions associated with ACE exposure may lead to more harsh, punitive parenting behaviors (Crandall, Deater-Deckard, & Riley, 2015). Thus, it may be that parents who have ACE exposure are at a disadvantage in their ability to emotionally regulate which is associated with their ability to parent. While there is considerable empirical support for the theory that emotions impact parenting behavior (Dix, Moed, & Anderson, 2014; Dix & Yan., 2014), extant examinations of ER and parent behaviors are still mostly theoretical (Jones, Cassidy, & Shaver, 2015), and formally examined even less in families with ACE exposure. Some work has suggested that parents with ACE exposure often display difficulty with ER and experience worse psychological outcomes that impact their parenting behaviors (Naragon-Gainey et al., 2017; Poole, Dobson, & Pusch, 2017). For example, Kim and Cicchetti (2010) found that parents with early exposure to maltreatment in childhood experienced greater levels of emotional reactivity in adulthood which contributed to poorer child outcomes. Although understanding the pathways by which ER affects parenting is important for all families, these pathways are critically important among families that have ACE exposure and are at greater risk for psychosocial problems (Conger et al., 2013). Finally, while the research on ER and parenting behaviors is sparse in general, it is especially lacking for low-income rural parents and children (Crandall, Deater-Deckard, & Riley, 2015; Crouch et al., 2020). For the reasons above, parent ER and parenting behaviors should be included when risks for child ACEs are assessed. Therefore, more specific and thorough consideration of the role of parent ER and parenting behaviors in the transmission of ACEs between parents and children is necessary. 24 Parent ER, Parenting Behaviors, and Child ACE Exposure Recent research suggests that one in ten children nationally has experienced three or more ACEs (Sacks `& Murphy, 2018). This is alarming as ACEs are associated with a number of negative health outcomes. As such, there is an increasing need to establish the prevalence of ACE exposure across developmental domains. According to the National Survey of Children’s Health (U.S. Census Bureau, 2016), the most common ACE experienced by children is divorce or parent separation. Examining ACE exposure in children is important because ACE exposure disrupts the brain’s development, structure, and functioning (Enlow et al., 2012; Kerker et al., 2015), yet the understanding of the pathways contributing to this exposure are underdeveloped. Several studies have examined the association between ACEs and behavioral issues in children and have shown a dose-response relation between cumulative ACE exposure and behavioral problems (see Liming & Grube, 2018). Among these studies, children with three or more ACEs were significantly more likely to exhibit externalizing and internalizing behaviors than children with no ACEs. As stated above, exposure to adversity in early childhood disrupts multiple facets of brain development (Enlow et al., 2012; Kerker et al., 2015). Such neurological disruptions significantly impair mental, emotional, and behavioral development (Cooper, Masie, & Vick, 2009), which can have implications across the lifespan (Keiley et al., 2001). For example, Flaherty and colleagues (2006) found that children with exposure to one ACE at the age of four were 1.89 times more likely to have poor health at age six. Similarly, Kerker and colleagues (2015) revealed that children with chronic medical issues were more likely to be exposed to ACEs compared to their peers. Although studies have established a significant association between child ACE exposure and behavioral outcomes, less research has explored links between parent ER, parenting 25 behaviors, and child ACE exposure. One study found that parents with fewer community resources were more likely to experience ACE exposure and use coercive parenting behaviors and their children were also more likely to experience ACE exposure (Thurston, Bell, & Induni, 2018). Another study found that parents with ACE histories experiencing homelessness were more likely to experience disruptions in parenting and less likely to buffer ACE exposure for their children (Conger & Donnellan, 2007). Similarly, greater levels of parent ACE exposure were linked to more coercive parenting practices such as harsh and inconsistent practices and thus expected to predict more ACE exposure in their children (Narayan et al., 2017). Finally, another study focused on the association of parent ER and parenting behaviors on child ACE exposure. This study found that parents who used more coercive parenting practices increased the likelihood of ACE exposure in their children (Deater-Deckard, Li, & Bell, 2016). Therefore, the present study seeks to explore specific, potential pathways (e.g., parent ER and coercive parenting behaviors) of ACE transmission between parents and children in order to advance prevention and intervention efforts. An Alternate Pathway: Child ACE Exposure and Parenting Behaviors While there has been increasing research efforts to unpack the impact of parent ACE exposure on the intergenerational transmission of ACEs more research is necessary to identify alternative models of transmission. Therefore, this study sought to compare alternative models of ACE transmission. One potential model of transmission is understanding the association between child ACE exposure and coercive parenting behaviors in an effort to understand the transmission of ACEs between parents and their children. Current theories include the concept of bidirectional or transactional processes between children and their environments. Transactional processes are mutual and reciprocal exchanges between individuals and their environments 26 (Bronfenbrenner & Morris, 2006). Conceptual models of parenting often include the bidirectional relationship between parenting behaviors and the development of child behaviors (e.g., Sameroff, 2009). Yet much of the current literature focuses on a unidirectional relationship of parent effects on child behaviors. However, according to Patterson (2002), children who exhibit oppositional behaviors tend to elicit hostile reprimands and punishment from their parents as part of a mutually reinforcing cycle. Although studies on the bidirectional association are limited, evidence supports this framework. For example, child behavioral problems have been associated with ineffective parenting, increased physical punishment, and poor parental monitoring (Snyder et al., 2005; Vuchinich, Bank, & Patterson, 1992; Laird et al., 2003). Thus, emerging literature supports this bidirectional relationship. Further, this conceptual approach is important in understanding the transmission of ACEs in families, because children who are exposed to ACES are at an increased risk for behavioral problems in childhood (Hunt, Slack, Berger, 2016). Internalizing (e.g., anxiety, depression) and externalizing (e.g., aggression) problems are more likely to emerge after exposure to ACEs (Burke et al., 2011; Jimenez et al., 2016). For example, one study found that children with exposure to 4 or more ACEs were more likely to experience learning or behavioral problems compared to children with no ACE exposure (Burke et al., 2011). Another study found increased attention and behavioral problems in children as young as 5 after ACE exposure (McKelvey et al., 2016). As such, it is important to consider this bidirectional influence when examining the transmission of ACEs between parents and children. This study sought to enrich the literature by further understanding bidirectional influences of ACE transmission by examining two alternative models of potential pathways. Thus unpacking potential pathways of ACE transmission offers 27 targeted and actionable steps for practitioners and policymakers to develop effective interventions to disrupt the transmission of ACEs in families. 28 CHAPTER III: METHODOLOGY The purpose of this study was to investigate if parent emotion regulation (ER) and coercive parenting behaviors could serve as potential mediators of the transmission of ACEs between parents and children. Based on prior research, over 55% of rural adults have been exposed to at least one ACE (Centers for Disease Control and Prevention, 2022); likewise, many children in rural communities are likely being cared for by adults with ACE exposure. Therefore, it is believed that ACE exposure will be reported for parents and children at the Bowen Health Clinic. Specifically, this study used a non-experimental cross-sectional quantitative design to achieve two research aims: (1) investigate the associations between parent ACE exposure and three outcomes: parent ER, coercive parenting behaviors, and child ACE exposure, and (2) test whether parent ER and coercive parenting behaviors mediate the relationship between parent ACE exposure and child ACE exposure. In addition to the primary hypothesized mediation model, I tested two alternative mediation models to strengthen support for the hypothesized pathway. Eligibility Criteria To be eligible for this study, participants were required to meet the following inclusion criteria: (a) be a legal adult (age 18 or older), (b) be a parent or primary caregiver of one or more children between the ages of four and twelve years, and (c) be comfortable reading and responding to survey items in English. Participants were excluded if they (a) were diagnosed with a severe mental illness, (b) had an intellectual or developmental disability that diminished their ability to provide informed consent, or (c) declined to accept expectations of informed consent. Only one parent per family was eligible to participate in the study to avoid collecting non-independent data. 29 Recruitment I recruited parents with a child between the ages of four and twelve years old from the Bowen Health Clinic located in Indiana. The health clinic provides physical and behavioral health care services to under-resourced rural families. In the last year alone, the Bowen Health Clinic provided behavioral health services to over 7,000 individuals (Bowen Health Clinic Annual Report, 2022). This community-academic partnership supported data collection efforts, and my goal is for the study findings to improve services for families at the health clinic. To ensure sufficient statistical power and adequate precision in parameter estimates for a path analysis, a sample size between 100 to 200 is necessary (Kline, 2015; Tabachnick, Fidell, & Ullman, 2013). Due to the sample being recruited from a rural community, which is often understudied in the literature, a sample size of 100 was deemed an appropriate first step in the research process and is sufficient in supporting further research. Participants were recruited using a homogeneous convenience sampling method (Creswell & Creswell, 2017; Jager, Putnick, & Bornstein, 2017). Convenience sampling is a common sampling method employed in social science research (Jager, Putnick, & Bornstein, 2017) because it is often easy to implement and is cost-effective (Bornstein, Jager, & Putnick, 2013). Convenience sampling is a specific type of non-probability sampling method that relies on data collection from population members who are conveniently available to participate (Saunders et al., 2012). More specifically, homogeneous convenience sampling is a precise form of convenience sampling that refers to collecting data with a specific sociodemographic subgroup (Jager, Putnick, & Bornstein, 2017). By intentionally constraining the sampling frame and producing a more homogenous sample, it is easier to reduce the likelihood of sample bias (Jager, Putnick, & Bornstein, 2017). This is because a homogenous sample should have a 30 sociodemographic distribution that more closely reflects the target population. Given my study focus on rural families receiving behavioral health services in the midwestern United States, a convenient sample of respondents from the Bowen Health Clinic was recruited to achieve the research aims. Several methods were used to recruit participants. First, research recruitment flyers (Appendix A) were distributed at the health clinic. The recruitment flyer briefly described the study, detailed the research study inclusion criteria, compensation, and provided a link to a quick response (QR) code to the consent form and survey. Second, I sent a recruitment email (Appendix B) to health providers at the clinic asking for support in recruiting participants. The email described the research study, detailed research participant inclusion criteria, compensation, and provided a link to the survey QR code. Finally, I created study recruitment cards (Appendix C) for health providers to give to participants who met the inclusion criteria. Sample Characteristics Parent Demographics The Bowen Health Clinic reports providing services to 4,385 patients in the past year. The Bowen Health Clinic reports similar statistics of engagement for female (n = 2,329; 53%) and male (n = 2,056; 47%) patients. The majority of patients (n = 2,895; 66%) seen over the past year were patients between the ages of 18-64. Out of the 4,385 patients served, 90% (n = 3, 808) identified as White and 80% (n = 3,452) identified as Non-Hispanic. Lastly, the Bowen Health Clinic reports a slightly higher average household income ($34,000), compared to the majority of participants in this study reported a household income to be less than $15,000. Overall, the sample included in this study closely resembles to make up of patients receiving services at the Bowen Health Clinic. 31 A total of 125 parents participated in this study. Parent demographic information is displayed in Table 3. The sample include 87 (69.6%) men and 36 women (28.8%), while two (21.6%) participants preferred not to disclose their gender identity. The average age was 36.89 years (SD = 8.11) and parents’ age ranged from 19 to 65 years. Most participants identified as White (n = 119; 95.2%), followed by three (2.4%) participants identifying as Black or African American. Of the 125 participants, 121 (96.8%) identified as non-Hispanic. The most common education level reported in this study was the completion of high school (n = 58; 46.4%), followed by some college or technical school (n = 30; 24%). In addition, 72 (57.6%) participants reported working full-time. The largest group of participants (n = 38; 30.4%) reported an annual household income of under $15,000, followed by 23 (18.4%) participants reporting an annual household income between $15,000 to $24,000. In addition, most participants identified their relationship status as married (n = 45; 36%), followed by single (n = 36; 28.8%), followed by dating and living together (n = 16; 12.8%). The majority of respondents who participated in this study identified as biological caregivers (n = 93; 74.4%), followed by 19 (15.2%) participants who identified as a multi-type caregiver meaning they occupied more than one parent time (e.g., foster parent and sibling caregiver). Table 3 Parent Demographics (N = 125) Variable Gender Male Female N % 87 69.6 36 28.8 32 Table 3 (cont’d) Prefer not to say 2 1.6 Race White Black/African American Asian Other Parent Education Level 119 95.2 3 1 2 2.4 .8 1.6 High school 58 46.4 Less than high school 12 9.6 Some college/technical school 30 24 2-year associates 4-year or higher Parent Employment Status Full time Part time Unemployed Unable to work 12 9.6 13 10.4 72 57.6 13 10.4 17 13.6 16 12.8 33 Table 3 (cont’d) Contract/temporary Other Parent Marital Status Married Single Divorced Separated Engaged 2 5 1.6 4.0 45 36.0 36 28.8 9 4 2 7.2 3.2 1.6 Dating and living together 16 12.8 Dating and not living together Widowed 6 3 4.8 2.4 Divorced and dating and living together 4 3.2 Parent Type Biological caregiver 93 74.4 Stepparent caregiver Sibling caregiver Other caregiver type 4 3 6 3.2 2.4 4.8 34 Table 3 (cont’d) Multi-type caregiver 19 15.2 Parent Income Under $15,000 $15,000 to $24,999 38 30.4 23 18.4 $25,000 to $34, 999 20 16.0 $35,000 to $49,999 18 14.4 $50,000 to $74,999 11 8.8 $75,000 to $99,999 $100,000 to $149,999 $150,000 and over 9 5 1 7.2 4.0 .8 Child Demographics As part of this study, caregivers were also asked to provide demographic information regarding a focal child. In terms of gender, 55 children (44%) were reported as male and 68 (54.4%) reported as female. Three (1.6%) parents preferred not to respond about their child’s gender. The average child age was 8.39 years (SD = 2.62). Nearly all children (n = 117; 93.6%) were identified as White, followed by four (3.2%) children identified as Black. In addition, most children (n = 121; 96.8%) were described as non-Hispanic, while four (3.2%) children were described as Hispanic. See Table 4 below for complete child demographic information. 35 Table 4 Child Demographics (N = 125 ) Variable Gender Male Female N % 55 44.0 68 54.4 No-Response 2 1.6 Race White Black Asian 117 93.6 4 1 3.2 .8 American Indian/Alaska Native 1 .8 Other Ethnicity 2 1.6 Non-Hispanic 121 96.8 Hispanic 4 3.2 Age 4 14 11.2 36 Table 4 (cont’d) 5 6 7 8 9 10 11 12 11 8.8 6 4.8 16 12.8 14 11.2 15 12.0 14 11.2 18 14.4 17 13.6 Procedures All study procedures were reviewed and approved by the Michigan State University Institutional Review Board (IRB) and representatives from the Bowen Health Clinic. Data Collection Participants used the QR code provided on the study recruitment materials to access the study survey. The survey was conducted through the secure survey management system Qualtrics. The first page of the electronic survey asked participants to answer inclusion and exclusion criteria questions to determine their eligibility. If participants did not meet study inclusion criteria, the survey directed them to the final page, and they were thanked for their time and not enrolled in the study. Ten parents were excluded from the study due to not meeting 37 eligibility criteria. If participants were eligible to participate (n = 125), they advanced to the second page of the survey which included the consent form (Appendix D). Participants then reviewed the informed consent page. The informed consent page outlined study information as well as advised participants that they could end their participation at any time they chose. Participants’ endorsement of consent was obtained by clicking “next” to the following language: “By clicking the next button I provide my informed consent to participate in this study.” Next, participants answered a set of survey questions. The survey took an average of 15 minutes to complete. Participants received a $40.00 gift card after they completed the survey. All gift cards were sent electronically by email. Measures The following measures were used to collect data to address the research aims. Demographic Information Participants provided information pertaining to common demographic variables including age, gender, race, and ethnicity of the participant and the focal child (see Appendix E). Participants were also asked to indicate their present educational level, employment status, marital status, parent type, and household income range. Parent Variables Parent Age. A single item measured parent age. Age was treated as a continuous variable. Parent Gender. Eight options were provided for parents to reports on their gender: (a) cis-gender female, (b) cis-gender male, (c) transgender female, (d) transgender male, (e) non- binary (f) prefer to self-describe, (g) prefer not to say (h) other (with write-in option). 38 Parent Race. A race item was categorized as (a) African American/Black, (b) American Indian or Alaskan Native, (c) Asian, (d) Native Hawaiian or Pacific Islander, (e) White, and (f) Other (with write-in option). Parent Ethnicity. Participants were asked to identify their ethnicity by indicating (a) Hispanic or (b) Non-Hispanic. Parent Education Level. Participants were asked to report their education level. Four options were provided: (a) less than high school, (b) high school or GED, (c) some college or technical school, and (d) college degree or higher. Parent Employment Status. Participants were asked to report their employment status. Six options were provided: (a) full- time, (b) part-time, (c) contract/temporary, (d) unemployed, (e) unable to work, and (f) other (with write-in option). Parent Marital Status. Participants were asked to report their marital status. Eight options were provided: (a) single, (b) dating and living together, (c) dating and not living together, (d) married, (e) widowed, (f) divorced, (g) separated, and (h) other (with write-in option). Parent Type. Participants were asked to report their caregiver type. Seven options were provided: (a) biological caregiver, (b) grandparent, (c) step-parent caregiver, (d) foster parent caregiver, (e) sibling caregiver, (f) other family member (with write-in other), and (g) other type of caregiver (with write-in option). Parent Household Income. Participants were asked to report their annual household income based on the United States Census Bureau (2021) income distribution. Eight options were provided: (a) under $15,000, (b) $15,000 to $24,999, (c) $25,000 to $34,999, (d) $35,000 to 39 $49,999, (e) $50,000 to $74,999, (f) $75,000 to $99,999, (g) $100,000 to $149,999, and (h) $150,000 and over. Child Variables Child Age. The child’s birth month and year (MM/YYYY) measured child age. Child Gender. Parents reported child gender using (a) cis-gender female, (b) cis-gender male, (c) transgender female, (d) transgender male, (e) non-binary (f) prefer to self-describe, (g) prefer not to say (h) other (with write-in option). Child Race. A race item was categorized as (a) African American/Black, (b) American Indian or Alaskan Native, (c) Asian, (d) Native Hawaiian or Pacific Islander, (e) White, and (f) Other (with write-in option). Child Ethnicity. Parents were asked to identify their child’s ethnicity by indicating (a) Hispanic or (b) Non-Hispanic. Adverse Childhood Experiences Questionnaire Parent ACEs were measured using the Adverse Childhood Experiences Questionnaire (Felitti et al., 1998). Parents completed the ACE questionnaire, which consists of a total of 10 items reflecting the ACE categories (e.g., abuse, neglect, household dysfunction). Parents answered five questions about exposure to different types of maltreatment (e.g., Did a parent or other adult in the household often push, grab, slap or throw something at you?). The other five questions focused on household dysfunction (e.g., Were your parents ever separated or divorced?). Appendix F provides an overview of the ACE questions included in the survey. All questions regarding ACEs pertain to the first 18 years of an individual’s life. Parents were asked to read each item and indicate a “yes” or “no” if the event occurred during their childhood. For 40 every “yes” to a question 1 point is given. The 10 questions are then summed, and the total number is the ACE score. Greater ACE scores indicate more ACE exposure. The ACE questionnaire has demonstrated good test-retest reliability in adult populations with no evidence of significant bias in retrospective assessment (Dube et al., 2003). Good predictive validity was found with ranges of .41-.64 (Hardt & Rutter, 2004). Test-retest reliability was found using weighted-kappa statistics in the range of .52 to .72 for each item, indicating a good to excellent test-retest reliability (Dube et al., 2003). The test-retest reliability study was done with 655 participants from the initial sample of Felitti et al. (1998) study and cited multiple other prior studies with similar reliability reports (Dube et al., 2003). Hardt and Rutter (2004) also demonstrated medium to long term reliability of recall by following up with their sample six months later. The internal reliability of this measure is also strong, with reports of Cronbach’s alpha =.88 (Murphy et al., 2013). In this study, Cronbach’s alpha was α = .84. Difficulties in Emotion Regulation Scale Parent emotion regulation difficulties were measured using the Difficulties in Emotion Regulation Scale (DERS-18) across six domains of emotion regulation (Appendix G). The DERS-18 was developed to reduce the original DERS assessment from 36 items to 18 items (Gratz & Roemer, 2004) and assesses emotion regulation in various populations (Skutch et al., 2019; Victor & Klonsky, 2016). The DERS-18 was selected to measure parent ER because this measure has shown to reduce participants’ survey fatigue while retaining the reliability and validity of the original 36 item emotion regulation questionnaire developed in 2004 (Victor & Klonsky, 2016). The DERS-18 uses self-report information to assess difficulties in emotion regulation across six domains: (a) lack of acceptance of emotional responses (3 items; e.g., When I’m upset, 41 I become embarrassed for feeling that), (b) having a hard time establishing goal-directed behavior (3 items; e.g., When I’m upset, I have difficulty getting work done), (c) difficulties with impulse control (3 items; e.g., When I’m upset, I become out of control), (d) deficit in emotion awareness (3 items; e.g., I pay attention to how I feel), (e) shortage of emotion regulation strategies (3 items; e.g., When I’m upset, I believe I will remain that way for a long time), and (f) inadequate emotional clarity (3 items; e.g., I have no idea how I am feeling). Items are scored on a 5-point Likert scale with 1 for almost never, 2 for sometimes, 3 for half the time, 4 for most of the time, and 5 for almost always (Victor & Klonsky, 2016). The three items assessing deficits in emotion awareness are reversed coded (e.g., 1 = 5, 2 = 4, 3 = 3, 4 = 2, 5 = 1). The six domains (i.e., acceptance of emotional responses, establishing goal-directed behavior, difficulties with impulse control, deficit in emotion awareness, shortage of emotion regulation strategies and inadequate emotional clarity) are summed to create the total ER score. The DERS-18 demonstrates high levels of reliability across the six subscales, with a total alpha of .91 and factor loadings of .61 to 1.00 (Victor & Klonsky, 2016). In this study, the total Cronbach’s alpha was α = .95. Parenting Behavior Inventory The Parenting Behavior Inventory (PBI; Lovejoy et al., 1999) is a 20-item questionnaire that assesses positive and coercive parenting behaviors (Appendix H). It has been used successfully with preschool and young school-age children (see Mowder, Shamah, & Zeng, 2010). Based on a confirmatory factor analysis of this measure, Lovejoy and colleagues (1999) suggested that the PBI contains two factors: supportive/engaged parenting and hostile/coercive parenting. Each item is rated on a 6-point Likert scale ranging from 0 (not at all true/I do not do this) to 6 (very true/I often do this). To investigate if parents with greater ACE exposure employ 42 more coercive parenting practices, I used the 10-items assessing hostile and coercive parenting behaviors (e.g., “I lose my temper when my child doesn’t do something I ask him/her to do”). Higher scores indicate more frequent coercive parenting behaviors. In eight studies assessing the psychometric properties of the PBI, Lovejoy and colleagues (1999) reported the PBI retained high internal validity (Cronbach’s alpha = .83 for the supportive/engaged factor and .81 for the hostile/coercive factor). In the present study, the Cronbach’s alpha was α = .70. Pediatric ACEs and Related Life Events Screener At the time this study was conducted, there were no validated ACEs screening tools for use with the youth population (Koita et al., 2018). To address this concern, researchers from the Bay Area Research Consortium on Toxic Stress and Health designed the Pediatric ACEs and Related Life Events Screener (PEARLS; Koita et al., 2018) to screen for ACEs and other potential risk factors (Appendix H; Koita et al., 2018). The PEARLS was written at a sixth-grade reading level, which aligns with health literacy recommendations for written materials (Koita et al., 2018). The PEARLS demonstrates high face validity and has been undergoing a longitudinal study to evaluate reliability and validity (Koita et al., 2018). The PEARLS was chosen as the measure for assessing child ACEs in this study because it was the most conducive for a health clinic setting in that it allows for screening of children, encompassess the three main ACE categories, has an administration time of five minutes or less, and utilizes parent report versus an interview format. The PEARLS has two sections (see Appendix I). Section one screens for the ACEs tied to the original ACEs investigated by Felitti and colleagues (1998). This includes ten questions (e.g., Has your child ever lived with a parent/caregiver who went to jail or Has a parent/caregiver ever insulted, humiliated, or put down your child?) assessing for abuse, neglect, and household 43 dysfunction. For every “yes” to a question, 1 point is given. The 10 questions are summed, and the total number reflects the child ACE score. Scores can range from 0 to 10. The second section of the PEARLS includes other risk factors for toxic stress not in the original ACE study but that have been found to show impact on child and adult health. For the purpose of this study, section two was not used. The child ACE score was created only from section one (i.e., the original ACE questions). The PEARLS is available in both identified and de-identified formats. The identified format asks the respondent to specify which ACEs the child has experienced. The de-identified format asks the respondent for only the total number of ACEs experienced. The de-identified PEARLS was used for this study. Analytic Plan To best examine the research aims and hypotheses, several analytic steps were used. First, using RStudio version 4.1 (RStudio Team, 2020), the data were cleaned. Before proceeding further, missing data were examined and the statistical assumptions underlying the planned analyses were tested. Following that, the data analysis began with preliminary analyses to understand the characteristics of each variable. Next, I investigated aim one by examining the associations between parent ACE exposure and (a) parent ER, (b) coercive parenting behaviors, and (c) child ACE exposure. Aim two was then investigated using a path analysis. A path analysis allowed me to examine both direct and indirect predictors (i.e., ACEs, ER, coercive parenting behaviors) of child ACE exposure. The terms direct and indirect effects, mediators, and moderators are used herein to maintain consistency across literatures; however, the non- experimental and cross-sectional design of this study precludes any causal interpretation of these effects. All substantive analyses were conducted using Mplus version 8.4 (Muthén & Muthén, 1998-2019). Statistical significance level was predetermined using a value of p < 0.05. 44 Missing Data Both the proportion of missing data and the nature of missing data were evaluated. I evaluated the data to determine the type of missingness (e.g., structurally missing, missing completely at random, missing at random, and missing not at random) and if it was appropriate to proceed with handling missing data using full information maximum likelihood estimation (FIML). FIML is the optimal missing data estimation approach for structural equation modeling and related approaches because it produces unbiased parameter estimates and standard errors (Enders & Bandalos, 2001). FIML requires that missing values are at least missing completely at random or missing at random (Enders & Bandalos, 2001). Under FIML, missing data are not replaced or imputed, but are managed within the analysis model with all the available information. The process works by estimating a likelihood function for each individual based on the variables that are present so that all the available data are used. FIML was selected because it will yield similar (Collins, Schafer, & Kam, 2001), or even better results as multiple imputation (Allison, 2012), and it involves fewer steps of implementation. Preliminary Analyses Descriptive data were examined using R Studio version 4.1 (RStudio Team, 2020). Preliminary analyses provided information on frequency, missingness, mean, standardized deviation, bivariate correlations, and range for study variables. Statistical Assumptions All statistical procedures have underlying assumptions, some more stringent than others. Before proceeding with the primary analyses, I evaluated the data to ensure they did not violate the assumptions needed to draw meaningful research conclusion. 45 Normal distributions take the form of a symmetric bell-shaped curve. The standard normal distribution is one with a mean of 0 and a standard deviation of 1. However, various transformations can be used to correct non-normally distributed data (Vickers, 2005). Normality was assessed using the skewness and kurtosis z-scores. Skewness and kurtosis scores should be within the +2 to –2 range when data are normally distributed. Homogeneity of variance was evaluated using the Levene’s test of homogeneity of variance. This is the most common test, and it tests the assumption that each group of one or more categorical independent variables has the same variance on an interval dependent variable (Garson, 2012). If the Levene statistic was significant at the .05 level or better, I rejected the null hypothesis that the groups have equal variances. In addition, the Levene’s test is robust when dealing with non-normality. Linearity was inspected by examining a scatter plot of the standardized residuals of the predicted and observed values. The variables of interest (the dependent variable, the independent variable, and the mediation variables) should have a linear relationship. Hypothesis Testing Aim One I investigated the associations between parent ACE exposure and three outcomes: parent ER, coercive parenting behaviors, and child ACE exposure. I hypothesized that greater parent ACE exposure will be associated with (a) more parent ER difficulties, (b) more coercive parenting behaviors, and (c) greater child ACE exposure. Figure 2 represents this model. 46 Figure 1 Aim One Hypothesized Model Parent ACE Exposure Parent ER Difficulties Coercive Parenting Child ACE Exposure A path model was used to estimate the associations between parent ACE exposure, parent ER difficulties, coercive parenting behaviors, and child ACE exposure. The variables were entered into the model in two steps: (1) the predictor variable (parent ACE exposure) and (2) parent ER difficulties, coercive parenting behaviors, and child ACE exposure. The null hypotheses were rejected if the coefficient estimates did not achieve statistical significance of p < 0.05. All results were reported using standardized estimates. Aim Two I used a path analysis to test the hypothesized model and two alternative models using the Mplus software package (Version 8.4; Muthén & Muthén, 1998-2019). I hypothesized in aim two that parent ER and coercive parenting behaviors would mediate the relationship between parent ACE exposure and child ACE exposure. To test this hypothesis, I fit three separate models. I evaluated the paths by testing my models directly, rather than following the casual steps approach recommended by Baron and Kenny (1986), which can lead researchers to 47 unnecessarily forego testing of indirect effects in the absence of a direct effect between the X and Y variables (Hayes & Rockwood, 2017). To minimize multi-collinearity, all model predictors were standardized. Figure 3 represents the first model testing parent ER and coercive parenting behaviors as mediators between parent ACEs and child ACEs. This is the hypothesized model. For model one, child ACEs as the outcome variable was regressed onto parent ER and coercive parenting behaviors (mediator variables) and parent ACEs (independent variable). Model two and model three represent alternative models. For model two (Figure 4) coercive parenting behaviors as the outcome variable was regressed onto parent ER and child ACE exposure (mediator variables) and parent ACE exposure (independent variable). For model three (Figure 5) parent ER as the outcome variable was regressed onto coercive parenting behaviors and child ACE exposure (mediator variables) and parent ACE exposure (independent variable). For all pathways, standardized direct, specific indirect, total indirect, and total effects were estimated. All results were reported using standardized estimates; significant hypothesized paths and their standardized coefficients are depicted in the final path models. Figure 2 Aim Two Hypothesized Model Parent ER Difficulties Coercive Parenting Behaviors Parent ACE Score Child ACE Score 48 Figure 3 Hypothesized Alternative Model One Parent ER Difficulties Child ACE Score Parent ACE Score Figure 4 Hypothesized Alternative Model Two Coercive Parenting Behaviors Coercive Parenting Behaviors Child ACE Score Parent ACE Score Parent ER Difficulties I tested mediation using bias-corrected bootstrapping running 1000 bootstrap replications. The hypothesis that both parent ER and coercive parenting practices would mediate the relationship between parent ACEs and child ACEs was assessed by examining the statistical significance of the specific indirect effect in the path model. The statistical significance of the standardized regression coefficients for the indirect effects was assessed using 95% bias- correlated bootstrapped confidence intervals; mediation occurs when the confidence interval for the indirect effect is completely above or below zero (Hayes & Rockwood, 2017). The statistical significance of the direct effects were also examined, as it may provide further insight into the 49 nature of the mediation. When the direct and indirect effects are both significant, this suggests that the association between the predictor and outcome variables is not entirely attributable to the presence of the mediator, suggesting that there exists a partial mediation (Baron & Kenny, 1986). In contrast, when an indirect effect is significant, but the direct effect is not, it suggests that the association between the predictor and outcome variables is entirely attributable to the mediator, providing support for a complete mediation (Baron & Kenny, 1986). Goodness of fit was assessed using multiple fit indices because no single fit index provides unbiased estimates of fit under a range of sample size and data distribution conditions. I evaluated model fit using fit indices that align with best practice (McDonald & Ho, 2002; Hu & Bentler, 1999) using the following: chi-square minimization p-value greater than .05, a comparative fit index (CFI) greater than .95, a root mean square error approximation (RMSEA) of less than .08, and a standardized root mean square residual (SRMR) of less than .06 (Hu & Bentler, 1999). To determine the best fitting model, I compared fit statistics across the hypothesized sequential mediation models. Ethical Considerations This study was approved by the IRB at Michigan State University, the human resources department at the Bowen Health Clinic, and I followed the Marriage and Family Therapy Association Code of Ethics Standard V (American Association for Marriage and Family Therapy [AAMFT], 2019). The AAMFT Code of Ethics Standard V (AAMFT Code of Ethics, 2019) states an ethical researcher must receive institutional approval (AAMFT Code of Ethics, Standard 5.1), must protect research participants (AAMFT Code of Ethics, Standard 5.2), provide informed consent to participants (AAMFT Code of Ethics, Standard 5.3), provide participants the capability to decline or withdraw from the study (AAMFT Code of Ethics, 50 Standard 5.4), maintain confidentiality of research data (AAMFT Code of Ethics, Standard 5.5), and publish factual results (AAMFT Code of Ethics, Standard 5.6). Further, the National Commission for the Protection of Human Subjects of Biomedical and Behavioral Research (1979) reports that there should be no more than the minimal risk associated with participants for all research aspects (U.S. Department of Health and Human Services, 2013). As such, I have taken the appropriate steps to minimize harm to research participants. For example, the participants recruited for this study are all 18 years of age or older, as determined by the informed consent and inclusion criteria. In addition, this study used fair inclusion and exclusion criteria to avoid unfair burdens on research participants and to protect vulnerable populations (AAMFT Code of Ethics, Standard 5.2). As such, the inclusion requirements for this study required participants to be at least 18. The exclusion criteria included diagnoses of intellectual or developmental disabilities and severe mental illness. In addition, the survey asks about ACEs, which asks participants to reflect upon potentially traumatic experiences. However, this should not be more than minimal risk, thus minimizing harm. Information about mental health services was provided before the survey and after the survey was completed. In addition, the consent form informed participants about this minimal risk and additional support service information was provided out of caution. Research participants were also notified in the informed consent that they could stop the survey at any time with no penalty (AAMFT Code of Ethics, Standard 5.4). Participants were provided with a $40.00 gift card incentive for completing the survey. The incentive offered is not excessive, so participants were not likely to experience coercion to participate (AAMFT Code of Ethics, Standard 5.4). The data collected remained anonymous and there were no identifying mechanisms, so the participant’s data was secure (AAMFT Code of 51 Ethics, Standard 5.5). Security further occurred through a two-step process. The first level of security was that the data was stored on a password protected laptop. The second level of security was that the Excel file was password protected. Finally, the results published will be factual and honestly reflect the data collected (AAMFT Code of Ethics, Standard 5.6). The findings will be shared with the Bowen Health Clinic to support prevention and intervention efforts for families. As a result, participants of this study may indirectly benefit from this community-academic partnership, as the findings will be used to inform interventions and treatment approaches for families with ACE exposure. 52 CHAPTER IV: RESULTS The primary purpose of this cross-sectional, exploratory study is to investigate the potential mediating effects of parent ER and coercive parenting behaviors on the transmission of ACE exposure between parents and children. This study investigated two research aims. The first research aim examined the associations between parent ACEs, parent emotion regulation, parenting behaviors, and child ACEs. It was hypothesized that parent ACEs would be significantly associated with more ER difficulties, more coercive parenting behaviors, and higher child ACE exposure. The second aim explored pathways of three alternative models to examine potential mediating effects between parent ACE score, parent emotion regulation, parenting behaviors, and child ACE score. It was hypothesized that parent emotion regulation difficulties and coercive parenting behaviors would act as mediators between parent ACE score and child ACE score. Missing Data Analysis A univariate missing data analysis showed that the survey was completed by all 125 participants (100%) of the analytic sample. However, one participant (.8%) did not have responses for the coercive parenting behaviors measure. Overall, the very low level of missing data supported the appropriateness of using sum scores for key study variables (e.g., parent ACES, child ACEs). Full information maximum likelihood estimation (FIML) was used before running the path models for the main analyses. Examination of Statistical Assumptions The assumptions of normality, homogeneity of variance, and linearity were checked. Homoscedasticity assumes that the scores are normally distributed around the regression line (Obsorne, & Waters, 2019) and normality assumes that the data will depict a bell-shaped 53 distribution and is assessed with skewness and kurtosis scores. Scores should fall within the +2 and -2 range. For skewness, the distribution for coercive parenting behaviors was somewhat left skewed. For kurtosis, the value distribution for parent ACE score was platykurtik, meaning that the distribution has a negative kurtosis. However, the skewness and kurtosis values for all study variables were within the acceptable range of +2.0 to -2.0, indicating a normal data distribution. See Table #5 for skewness and kurtosis scores. Table 5 Skewness and Kurtosis Variable Skewness Kurtosis Parent ACE Score Child ACE Score .15 .30 Coercive Parenting Behaviors -2.0 Parent Emotion Regulation .31 -1.12 -.99 .24 .17 The Levene’s test was used to check for equal variances. See Table 6 below. The p-value for the Levene test is greater than .05 meaning that the variances are not significantly different from each other (i.e., the homogeneity assumption of variance is met). 54 Table 6 Test of Homogeneity of Variances Variable Leven df1 df2 p Statistic Child ACE Score 1.27 10 113 .254 Coercive Parenting 1.216 10 113 .288 Behaviors Parent Emotion Regulation .680 10 113 .741 Linearity assumes that there should be an approximate straight-line relationship between the outcome variables (parent emotion regulation, coercive parenting behaviors, and child ACE score) and the predictor variable (parent ACE score) (Field, 2018). I created scatterplots to examine the linearity between variables (see Figure 5-7 below). 55 Figure 5 Scatterplot of Parent ACEs and Child ACEs Note. PACE = Parent ACE Score, CACE = Child ACE Score Figure 6 Scatterplot of Parent ACEs and Coercive Parenting Behaviors Note. PACE = Parent ACE Score, PB = Coercive Parenting Behavior 56 Figure 7 Scatterplot of Parent ACEs and Parent Emotion Regulation Note. PACE = Parent ACE Score, ER = Parent Emotion Regulation Descriptive Statistics Descriptive statistics, including means, standard deviations, minimum, and maximum values are presented in Table 7. Bivariate correlations among all study variables were calculated in R Studio version 4.1 (RStudio Team, 2020) and are presented in Table 8. Parent ACE score was not significantly correlated to coercive parenting behaviors or child ACE score. However, as expected parent ACE score had a significant positive correlation to parent emotion regulation difficulties. Given the significant associations between key study variables (i.e., parent ACE score, child ACE score) and parent income and parent type, these variables were subsequently included as covariates in the hypothesized mediational model. 57 Table 7 Descriptive Statistics Mean SD Min Max Parent ACE Score 4.28 3.10 0 10.00 Child ACE Score 3.91 2.91 0 10.00 Coercive Parenting 51.69 6.5 34.00 71.00 Behaviors Parent Emotion Regulation 89.82 28.43 10.00 174.00 Note. Scores range from 0-10 on the ACE and Pediatric ACE Questionnaire; scores range from 0-100 on the Parenting Behavior Inventory; the Difficulties in Emotion Regulation score ranges from 10-180. 58 Table 8 Bivariate Correlations Among Study Variables 1 2 3 5 6 7 8 9 11 12 13 15 16 17 18 1 - .05 -04 .13 1 -.03 1 -.04 -.04 1 .19 * -.22 * -.10 -.08 -.13 1 -0.7 1 - .03 - .02 Variable 1 Parent Age 2 Parent Gender 3 Parent Race 4 Parent Education Level 5 Parent Employment Status 6 Parent Marital Status 7 Parent Type 8 Parent Income 9 Child Age 10 Child Gender 11 Child Race - .02 .24 ** .19 * .38 ** .12 .08 -.11 .02 .29 ** -.06 -.11 -.06 .15 .16 -.02 1 .20 * -.02 .47 ** .15 -.17 -.13 .12 1 .00 .00 .09 .01 1 12 Parent ACE Score -.22 * -.06 .03 .48 ** - .09 .28 ** -.09 .06 -.08 .03 -.03 -.08 - .08 .01 .03 .02 1 .10 - .08 -.00 1 .08 -.02 -.27 ** .30 ** - .05 -.10 -.07 1 59 Table 8 (cont’d) 13 Child ACE Score 14 Coercive Parenting Behaviors 15 Parent ER Difficulties .08 -.11 -.05 -.15 -.12 - .04 -.18 * -.20 * -.06 .27 ** .07 - .13 -.13 .12 -07 .06 .18 * .09 .27 ** - .15 .10 -.02 -.07 .08 1 .08 - .04 - .21* .04 .12 1 .09 -.01 - .02 - .13 - .14 -.08 .01 .35 ** .20 * .15 1 Note. * = p < .05. ** = p < .001. (two-tailed). Parent Gender (0 = Male, 1 = Female), Parent Race (0 = White, 1 = Not White), Parent Education Level (0 = High School or Less, 1 = College or Technical School), Parent Employment Status (0 = Employed, 1= Not Employed), Parent Marital Status (0 = Married, 1= Not Married), Parent Type (0 = Biological Parent, 1 = Not Biological Parent), Parent Income (0 = Less Than $50,000, 1 = More Than 50,000), Child Gender (0 = Male, 1 = Female), Child Race (0 = White, 1= Not White) 60 Frequency of Adverse Childhood Experiences For this sample, the mean number of ACEs calculated for parents was 4.28 and for children was 3.91. Table 9 details the frequency and percentage of ACE scores for parents and children and Table 10 details ACE exposure by child age. Table 9 Parent and Child Total ACE Scores (N = 125) Parent ACEs Child ACES ACE Scores N % N % 0 1 2 3 4 5 6 7 8 9 10 21 16.8 21 16.8 11 8.8 10 8.0 9 7.2 14 11.2 12 9.6 15 12.0 13 10.4 15 12.0 13 10.4 12 9.6 14 11.2 7 5.6 9 8 7.2 6.4 11 8.8 10 8.0 8 6 6.4 4.8 8 2 6.4 1.6 61 Table 10 ACEs by Child Age ACE Scores Age Age 5 Age 6 Child Age Age 7 0 1 2 3 4 5 6 7 8 9 10 Average 4 0 2 0 2 2 1 4 1 0 1 1 4.00 1 2 1 0 1 1 1 0 1 0 0 3.00 1 1 0 1 0 2 0 0 1 0 0 4.67 3 1 1 0 2 3 2 1 0 0 3 2.56 Age 8 Age 9 Age 10 1 1 0 1 2 2 0 1 4 2 0 5.29 5 2 1 1 1 1 2 1 0 0 0 3.86 3 2 1 2 2 1 0 1 2 1 0 3.86 Age 11 4 0 0 2 3 1 0 2 1 3 2 4.28 Age 12 3 0 5 3 0 1 5 0 0 0 0 4.00 An ACE score of zero (n = 21; 16.8%) was most commonly reported for parents, followed by an ACE score of six (n = 14; 11.2%), five (n = 13; 10.4%), and four (n = 13; 10.4%). Similarly, an ACE score of zero (n = 21; 16.8%) was most commonly reported for children, followed by an ACE score of four (n = 15; 12%), three (n = 15; 12%), and two (n = 14; 11.3%). In addition, 104 (83%) parents reported exposure to at least one ACE, with nearly 93 (74%) reporting exposure to two or more ACEs. Furthermore, 104 (83%) children were reported to have exposure to at least one ACE, with 94 (75%) children experiencing two or more ACEs. Table 11 details the frequency of endorsement for each ACE category for parents. Emotional abuse (n = 72; 57.6%) and parent separation (n = 72; 57.6%) were most frequently reported by participants, followed by household substance use (n = 70; 56%), then emotional neglect (n = 62; 49.6%). The least commonly reported ACE for parents was sexual abuse (n = 33; 26.4%). Table 12 provides a breakdown of child ACE exposure by parent type. 62 Table 11 Frequency of ACE Category for Parents (N = 125) Variable Emotional Abuse Physical Abuse Sexual Abuse Emotional Neglect Physical Neglect Parent Separation Caregiver Domestic Violence Household Substance Use Household Mental Illness Table 12 Child ACEs by Parent Type N 72 57 33 62 36 72 37 70 56 % 57.6 45.6 26.4 49.6 28.8 57.6 29.6 56.0 44.8 Child ACE Scores 0 1 2 3 4 5 6 7 8 9 10 Average Biological parent 17 8 13 11 12 10 5 6 4 5 1 3.52 Step- parent 1 0 0 0 1 1 1 0 0 0 0 3.75 Parent Type Sibling 1 0 0 2 0 0 0 0 0 0 0 2.00 Other type 1 0 1 1 0 0 0 0 1 1 1 5.33 Multi- type 1 2 0 1 2 1 3 2 5 2 0 5.68 Aim 1 Hypothesis Testing The first aim examined the associations between parent ACE score and (1) parent emotion regulation, (2) coercive parenting behaviors, and (3) child ACE score. A preliminary path model examining the direct effects of the independent variable (parent ACE score) on the three 63 dependent variables (parent ER, coercive parenting behaviors, and child ACE score) was run. Results for the analysis are presented in Figure 9. Parent ACE scores were significantly and positively associated with greater parent ER difficulty scores (B = .04, SE = .01, t (123), p < .001). Parent ACE scores were not significantly associated with coercive parenting behaviors (B = -.04, SE = .03, t (123), p = .19) or child ACE exposure (B = .04, SE = .09, t (123), p = .65). Figure 8 Path Analysis of Aim 1 Parent ACE Exposure -.047 (.036) Parent ER Difficulties Coercive Parenting Behaviors Child ACE Exposure Note. *p < .05 Aim 2 The second research aim used path modeling to examine one main model and two alternative models. The main model, Model 1, specified an indirect pathway between parent ACE score and child ACE score with parent emotion regulation and coercive parenting behaviors as mediating variables. It was hypothesized that parent emotion regulation difficulties and coercive parenting behaviors would mediate the association between parent ACE score and child ACE score. 64 For the two alternative models, Model 2 examined an indirect pathway parent ACE score and coercive parenting behaviors with parent emotion regulation difficulties and child ACE score as mediating variables. The third model examined an indirect pathway between parent ACE score and parent emotion regulation difficulties with coercive parenting behaviors and child ACE score as mediating variables. Hypothesized Model (Model 1) Model 1 achieved acceptable model fit, with X2 (6, N = 52.93) = 0.00, p = .00, CFI = 1.00, RMSEA = 0.00, SRMR = .00. Full Model. All paths reached statistical significance (Figure 10), except the paths from parent ACE score to child ACE score (B = .03, SE = .096, p =.60), parent emotion regulation difficulties to child ACE score (B = .009, SE =.01, p =.41), and parent ACE score to parenting behaviors (B = -.28, SE = .21, p = .18). There was a significant, direct relationship between parent ACE score and parent emotion regulation difficulties (B = 3.43, SE =.78, p = <.01). In addition, parent emotion regulation difficulties had a significant direct effect on coercive parenting behaviors (B = .11, SE =.02, p = <.01), and coercive parenting behaviors had a significant direct effect on child ACE score (B = .10, SE = .03, p = <.01). Analyses of Indirect Effects. Indirect effects from parent ACE score to child ACE score were assessed in the full model through two hypothesized mediators (parent emotion regulation and coercive parenting behaviors). Using 5000 bootstrapped samples with 95% bias correct confidence intervals suggest that parent ER and coercive parenting behaviors significantly mediated the association between parent ACE score and child ACE score (B = .04, SE = .01 p = .01). See Table 12 of confidence intervals below and Table 13 for specific indirect effects. 65 Figure 9 Path Analysis of Parent ACE Score, Parent Emotion Regulation, Parenting Behaviors, and Child ACE Score Parent ER Difficulti es .113 (.027)** 3.432 (.78) ** Coercive Parenting Behaviors .009 (.01) -.28 (.21) .039 (.09) Parent ACE Score Note. ** p < .001. Table 12 Confidence Intervals of Model Results .105 (.03) ** Child ACE Score Lower 2.5% Lower 5% Estimate Upper 5% Upper 2.5% 1.853 Parent Emotion Regulation ON Parent ACE Score Coercive Parenting Behaviors ON Parent ACE Score Parent Emotion Regulation Child ACE Score ON Parent ACE Score -0.153 -0.013 Parent Emotion Regulation Coercive Parenting Behaviors 0.054 -0.702 0.063 2.152 3.432 4.695 4.897 -0.610 0.069 -0.280 0.113 0.082 0.158 0.153 0.168 -0.119 0.039 -0.009 0.009 0.105 0.061 0.194 0.027 0.166 0.223 0.030 0.182 66 Table 12 (cont’d) Confidence Intervals of Total, Total Indirect, and Direct Effects Estimate Upper Lower 2.5% -0.097 -0.039 Lower 5% -0.071 0.080 -0.025 0.041 5% 0.228 0.116 Upper 2.5% 0.251 0.129 -0.153 -0.119 0.039 0.194 0.223 Total Total Indirect Direct Parent ACE Score Table 13 Total, Total Indirect, Specific Indirect, and Direct Effects Estimate SE p Effects from Parent ACE to Child ACE Total .08 .09 .37 Total Indirect .04 .04 .32 Specific Indirect 1 Child ACE Score Coercive Parenting Behaviors Parent ACE Score -0.02 .02 .18 Specific Indirect 2 67 Table 13 (cont’d) Child ACE Score Parent Emotion Regulation Parent ACE Score .03 .03 .42 Specific Indirect 3 Child ACE Score Coercive Parenting Behaviors Parent Emotion Regulation Parent ACE Score .04 .01 .01 Direct Child ACE Score Parent ACE Score .03 .09 .68 Post-Hoc Analysis. In further post-hoc analysis, I added two covariates (i.e., parent income, parent type) to the model to explore whether these characteristics may be acting as confounding factors. The addition of these covariates did not change the substantive results. Alternative Model One Alternative Model 1 achieved acceptable model fit, with X2 (6, N = 52.93) = 0.00, p = .00, CFI = 1.00, RMSEA = 0.00, SRMR = .00. 68 Full Model. All paths achieved statistical significance, except parent ACE score to child ACE score (B = .01, SE = .9, p =.68) and parent ACE score to coercive parenting behaviors (B = -0.28, SE = .21, p =.18). See Figure 11. There was a significant, direct effect between parent ACE score and parent emotion regulation difficulties (B = 3.42, SE =.78, p = <.01), and parent emotion regulation had a significant direct effect on child ACE score (B = 0.21, SE = 0.01, p = .039). In addition, child ACE score had a significant direct effect on coercive parenting behaviors (B = .69, SE = .22, p = .002), and parent emotion regulation had a significant direct effect on coercive parenting behaviors (B = .09, SE = .025, p = <.01). Analyses of Indirect Effects. Indirect effects from parent ACE score to coercive parenting behaviors were assessed in the full model through two hypothesized mediators (parent emotion regulation and child ACE score). Table 14 shows the confidence intervals for the full model. Using 5000 bootstrapped samples with 95% bias correct confidence intervals suggest that parent emotion regulation and child ACE score did not significantly mediate the relationship between parent ACE score and coercive parenting behaviors (B = .04, SE =.03, p = .11). In addition, the indirect effect of parent ACE score on coercive parenting behaviors with parent emotion regulation as the mediating variable was significant (B = .44, SE = .11, p = .004). See Table 15 below. 69 Figure 10 Path Analysis of Parent ACE Score, Parent Emotion Regulation, Child ACE Score, and Parenting Behaviors .02 (.10) ** Parent ER Difficulty Child ACE Score 3.43 (.78) ** Parent ACE Score Note. ** p < .001. Table 14 .01 (.97) ** -.28 (.21) ** Confidence Intervals of Model Results .69 (.22) ** .09 (.02) ** Coercive Parenting Behaviors Parent Emotion Regulation ON Parent ACE Score Child ACE Score ON Parent ACE Score Parent Emotion Regulation Coercive Parenting Behaviors ON Parent ACE Score Parent Emotion Regulation Child ACE Score Lower 2.5% Lower 5% Estimate Upper 5% Upper 2.5% 1.853 2.152 3.432 4.695 4.897 -0.184 0.001 -0.147 0.010 0.021 0.004 0.169 0.037 0.197 0.039 -0.706 0.052 0.278 -0.637 0.057 0.352 -0.287 0.099 0.696 0.056 0.139 1.057 0.148 0.148 1.151 Confidence Intervals of Total, Total Indirect, and Direct Effects Total Total Indirect Direct Parent ACE Score Estimate Upper Lower 2.5% -0.287 0.158 Lower 5% -0.216 0.108 0.181 0.394 5% 0.430 0.639 Upper 2.5% 0.494 0.709 -0.706 -0.637 -0.287 0.056 0.148 70 Table 15 Total, Total Indirect, Specific Indirect, and Direct Effects Estimate SE p Effects from Parent ACE to Coercive Parenting Behaviors Total .10 .19 .58 Total Indirect .39 .14 .007 Specific Indirect 1 Coercive Parenting Behaviors Child ACE Score Parent ACE Score .007 .07 .92 Specific Indirect 2 Coercive Parenting Behaviors Parent Emotion Regulation Parent ACE Score .33 .11 .004 Specific Indirect 3 Coercive Parenting Behaviors Child ACE Score Parent Emotion Regulation 71 Table 15 (cont’d) Parent ACE Score .04 .03 .11 Direct Coercive Parenting Behaviors Parent ACE Score -.02 .21 .17 Alternative Model Two Alternative Model 2 achieved acceptable model fit, with X2 (6, N = 52.93) = 0.00, p = .00, CFI = 1.00, RMSEA = 0.00, SRMR = .00. Full Model. All paths achieved statistical significance except parent ACE score to parent emotion regulation difficulties, parent ACE score to coercive parenting behaviors, and child ACE score to parent emotion regulation. See Figure 12. Coercive parenting behaviors had a significant direct effect on child ACE score (B = .11, SE =.03, p = <.01) and parent emotion regulation difficulties (B = 1.16, SE = .37, p = .002). In addition, parent ACE score had a direct effect on parent emotion regulation difficulties (B = 3.25, SE = 0.71, p = <.01). Analyses of Indirect Effects. Indirect effects from parent ACE score to parent emotion regulation were assessed in the full model through two hypothesized mediators (coercive parenting behaviors and child ACE score). Table 16 shows the confidence intervals for the full model. Findings from the indirect effects suggest that coercive parenting behaviors and child ACE score did not significantly mediate the relationship between parent ACE score and parent ER (B = .009, SE = .03, p =.77). See Table 17. 72 Figure 11 Path Analysis of Parent ACE Score, Parenting Behaviors, Child ACE Score, and Parent Emotion Regulation Coercive Parenting Behaviors .06 (.08) .11 (.03) ** Child ACE Score 1.16 (.37) ** .68 (.83) Parent ER Difficulty 3.25 (.71) ** .10 (.19) Parent ACE Score Note. ** p < .001. Table 16 Confidence Intervals of Model Results Coercive Parenting Behaviors ON Parent ACE score Child ACE Score ON Parent ACE Score Coercive Parenting Behaviors Parent Emotion Regulation ON Parent ACE Score Coercive Parenting Behaviors Child ACE Score Lower 2.5% Lower 5% Estimate Upper 5% Upper 2.5% -0.287 -0.216 0.108 0.430 0.494 -0.097 0.069 -0.079 0.068 0.116 0.075 0.210 0.174 0.231 0.187 1.917 0.621 2.099 0.735 3.252 1.163 4.440 1.933 4.601 2.097 -0.993 -0.693 0.681 2.069 2.264 73 Table 16 (cont’d) Confidence Intervals of Total, Total Indirect, and Direct Effects Lower 2.5% 1.853 -0.382 Total Total Indirect Direct Parent ACE Score 1.917 Table 17 Estimate Upper Lower 5% 2.152 3.432 -0.286 0.180 5% Upper 2.5% 4.695 4.897 0.645 0.731 2.099 3.252 4.440 4.601 Total, Total Indirect, Specific Indirect, and Direct Effects Estimate SE p Effects from Parent ACE to Parent Emotion Regulation Total 3.42 .78 .00 Total Indirect .18 .28 .52 Specific Indirect 1 Parent Emotion Regulation Child ACE Score Parent ACE Score .04 .10 .67 Specific Indirect 2 Parent Emotion Regulation 74 Table 17 (cont’d) Coercive Parenting Behaviors Parent ACE Exposure .12 .25 .61 Specific Indirect 3 Parent Emotion Regulation Child ACE Score Coercive Parenting Behaviors Parent ACE Score .009 .03 .77 Direct Parent Emotion Regulation Parent ACE Score 3.25 .71 .00 75 CHAPTER V: DISCUSSION Individuals who are exposed to multiple ACEs are at an increased risk of poorer health outcomes (Anda et al., 2006; Chapman, Dube, & Anda, 2007). As such, there is an increasing call for research to examine the transmission of ACEs in families to better inform prevention efforts (Larken, Shields, & Anda 2012). Little empirical research has examined the transmission of ACEs between parents and children, and even fewer studies have specifically examined potential factors mediating this association. In response, the purpose of this dissertation was to investigate the potential mediating effects of parent ER and coercive parenting behaviors on the transmission of ACE exposure between parents and children in a sample of rural parents. To accomplish this overall objective, this dissertation took place as part of a community-academic research partnership. This study was guided by two aims: 1) to investigate the associations between parent ACE exposure and three outcomes: (a) child ACE score, (b) coercive parenting behaviors, and (c) parent ER; and 2) to test whether parent ER and coercive parenting behaviors mediate the relationship between parent ACE exposure and child ACE exposure. A total of 125 respondents participated in this study. Overall, study findings demonstrated partial support of Aim 1 hypotheses, showing that parent ACE scores were positively and significantly associated with parent ER difficulties (Hx 1c). Additionally, Aim 2 was supported demonstrating a significant mediation effect such that parent ER and coercive parenting behaviors were indicated as mediators between parent ACE score and child ACE score. Descriptive Data: Ace Exposure Among Study Sample Prior to investigating the two study aims, I engaged in preliminary analysis of the data, which included examining ACE exposure statistics for the study sample. This data on ACE exposure is important because understanding ACE prevalence between parents and children may 76 enhance the ability of healthcare providers to mitigate the exposure to ACEs through early detection and intervention, thus reducing the potential for poor life outcomes for future generations (Schilling, Aseltine, & Gore, 2007). The majority of participants (n = 104; 83%) in the present study reported ACE exposure and ACE exposure in their child (n = 104; 83%). Parents experienced an average ACE score of 4 and children experienced an average of 3 ACEs. This is significant given that an ACE score of 4 is considered high and significantly increases the likelihood of poorer health outcomes across the lifespan (Anda et al., 2006; Bethell et al., 2017; Felitti et al., 1998). Rates of exposure to ACEs experienced by participants in this study were higher than those reported in much of the existing literature. For instance, Merrick and colleagues (2018) collected data through the Behavioral Risk Factor Surveillance System, which is an annual nationally representative health-related survey. Of the 214,157 participants, at least 61% of respondents reported exposure to at least 1 ACE and only 24.6% reported exposure to four or more ACEs. Giano and colleagues (2020) conducted a follow up study using the Behavioral Risk Factor Survey System to examine the frequency and disparity of ACE exposure in 376 adults across 34 states. The majority of participants reported exposure to at least one ACE (57.8%) with only 13% of respondents experiencing an ACE score of 4 or more. Both of these studies, to my knowledge, are the largest and most diverse collection of ACE data to date. It is possible that higher ACE scores were reported in my study due to the presence of more sociodemographic risk factors such as lower socioeconomic status and lower educational attainment than in other studies. The majority of participants (n = 81; 64%) reported a household income below $35,000 and many participants (n = 58; 46%) reported educational attainment at a high school level. This is notable given that prior studies have found significant associations 77 between socioeconomic status, educational attainment, and ACE exposure (see Houtepen et al., 2020). This finding is important given that researchers have called for more studies to identify individuals and groups that are exposed to disproportionately higher rates of ACEs to better understand health disparities. These findings add to the emerging literature examining the interconnections of intersectionality in association to unequal ACE exposure (Crenshaw, 1991; McCall, 2005). A large share of ACE distribution experienced by marginalized groups may be better explained by structurally embedded social determinants of health and thus requires more research. In addition to the social determinates of health, it should also be acknowledged that although these ACE characteristics represent this rural sample, there may be subgroup variations (e.g., parent gender, child gender, and child age) that should be considered as potential contributing factors to different levels of ACE exposure observed across different populations. Overall, relative to rates of exposure to ACEs among samples in the literature, the present study observed a relatively higher prevalence of ACEs, both at the level of cumulative exposure, as well as in specific categories (e.g., emotional abuse, parent separation, and parent substance use). In an effort to obtain a sample comparable to those in existing literature on ACEs, the current sample was selected on a number of factors (e.g., rural context, excluding participants with a serious mental illness). As such the findings of this study have focused on extending information on ACEs among rural families as well as extending the understanding of ACE prevalence by reporting estimates different than what is generally reported in the research. Aim One: Associations between Parent ACE Score and Child ACE Score, Parent ER, and Coercive Parenting Behaviors Given the growing body of evidence demonstrating significant lifelong effects of ACE exposure on health outcomes (Felitti et al., 1998), mental health professionals have begun to 78 address these issues more directly from a prevention lens (Finkelhor, 2018). In the present investigation, in partial support of study hypotheses, parent ACE scores were positively and significantly associated with parent ER difficulties (Hx 1c). As such, this study provides support that parents who report experiencing higher levels of ACEs may also have a greater likelihood of experiencing ER difficulties. This finding is consistent with prior research that shows that a higher level of ACE exposure is associated with poorer ER tendencies (Cameron, Carroll, & Hamilton, 2018). This finding is further supported in the literature as it is well-documented that the elevations in cortisol associated with ACE exposure interfere with the brain’s ability to effectively manage stress over time and regulate emotional reactions thus increasing the likelihood of using less effective emotion regulation strategies (e.g., Heim & Binder, 2012; Sciaraffa et al., 2018). Research further supports that ACE exposure disrupts the development of brain regions associated with ER (Teocher et al., 2016) and this is thought to contribute to poor ER skills and the development of mental health problems. This relationship is of further importance due to its association with poorer health outcomes (Poole et al., 2017). For example, early exposure to ACEs is associated with risk for depression, anxiety, and substance use - all of which are related to ER difficulties (McLaughlin et al., 2010). This finding adds to the literature by documenting this association in a sample of rural families as research on this population is limited. In addition, these findings highlight the utility of considering the nuanced role of parent ER in mediating the relationship between parent ACE score and child ACE exposure. Further, no significant association was found between parent ACE score and coercive parenting behaviors (i.e., Hx 1b was not supported). This was unexpected, given that prior research demonstrates that parents with ACE exposure often exhibit more harshness and hostility towards their children (Conger et al., 2013; Newcome & Locke, 2001). The lack of findings 79 involving coercive parenting may pertain to the type of parenting that was measured. Coercive parenting behaviors are composed of multiple types of behaviors, including verbal ineffectiveness in addition to physical interventions (e.g., harsh contact). It is possible that more specific coercive parenting behaviors (e.g., physical discipline, hostility) would show direct associations with ACEs. An alternative explanation is the possibility that unmeasured risks co-occurring with coercive parenting behaviors (e.g., community violence, neighborhood safety) are more salient predictors than ACE exposure. It is also possible that due to social desirability bias, parents could have over-reported on positive parenting behaviors described in the questionnaire, perhaps believing that not endorsing such items as “giving a hug, spending time together, or praising” could be viewed unfavorably. However, given these potential explanations as to the non- significant findings, it is also possible that the level of coercive parenting behaviors improved when families began receiving services from the Bowen Health Clinic and thus could accurately represent their current parenting behaviors. Future research should continue to investigate whether parenting behaviors are an essential factor for the generational transmission of ACEs or if specific parenting behaviors (e.g., physical discipline) are more salient. Exploring the subtle nuances of parenting behaviors will help continue to expand our understanding of the role of parenting in ACE transmission. Finally, hypothesis 1a, theorizing that level of parent ACE exposure would be significantly associated with child ACE exposure, was not supported by the data in this study. This association is not well described in the prior literature, and no significant association was found between parent ACE score and child ACE score in the present study. This finding could be due to social desirability bias. That is, parents may have been less willing to report ACE 80 exposure of their child for fear of social stigma or exposure. Is it also possible that parents may have been unable (e.g., lacking insight or reflective capacity or knowledge) to accurately report ACE exposure in some cases. Even though this study found no support for the association between parent ACE exposure and child ACE exposure, prior literature shows that certain kinds of adversity such as physical abuse and mental health problems are linked across generations within families (Schickedanz et al., 2021) and require overall more attention. Future research should continue to examine the association between parent and child ACEs as this may enable early targeted interventions for children (Randall, O’Malley, & Dowd, 2015). If these associations prove to be predictive, screening for parental ACE exposure would allow for early intervention to potentially improve family outcomes. Aim Two: Examining Potential Models of Mediation Hypothesized Mediated Model Findings from this study showed support for the hypothesis (Hx 2) that parent ER and coercive parenting behaviors mediate the relationship between parent ACE score and child ACE score. These findings are important because they may indicate that parent ER difficulties and coercive parenting behaviors may present useful targets for interventions aiming to disrupt transmission of ACEs. Given that childhood is a critical period of development for ER skills, it is not surprising that this model found that parent ACE score was positively and significantly associated with parent ER difficulties. One explanation for this association is that exposure to ACEs during childhood likely disrupts the development of ER skills for that individual (Cloitre et al., 2019; England-Mason et al., 2017). In fact, prior research shows that the experience of more ACEs has been associated with more ER difficulties (Cameron et al., 2018). As such, this study reflects that a potential pathway of ACE transmission may be through parent ER. 81 Further, the results suggested that this mediational pathway also extended through coercive parenting behaviors, such that parent ER difficulties were positively associated with coercive parenting behaviors, which were in turn were positively associated with child ACE scores. These findings are in line with existing research that parent ER difficulties influence parenting behaviors (Zimmer-Gembeck et al., 2022). Prior findings demonstrate that parents with less ER skills are more likely to use negative parenting behaviors (e.g., Shaw & Starr, 2019). In addition, the study results also extend what is known about potential pathways of ACE transmission by providing evidence for parent ER and coercive parenting behaviors as important factors to consider when understanding the transmission of ACEs in families. At the same time, the cross-sectional, exploratory nature of this study precludes any firm conclusions about the causal direction of these processes. Nonetheless, these findings help provide further evidence that establishes parent ER and coercive parenting behaviors as important links in the transmission of ACEs in families. Given that parent ER and coercive parenting behaviors are multidimensional, it is important to consider how alternative factors such as child behavioral problems (e.g., Zang & Mersky, 2020) or parenting stress (e.g., Lange, Callinan, & Smith, 2019) contribute to parent ER difficulties and coercive parenting behaviors. As such, it is encouraged for future research to consider alternative mechanisms of ACE transmission. The evidence from the present study provides a glimpse in considering early intervention points in reducing ACE transmission through parent ER and coercive parenting behaviors. These findings are further grounded in Bowen Family Systems theory in recognizing how the intricate interactions in families influence other member’s actions and behaviors (Bowen, 1978). Therefore, parent ER and coercive parenting behaviors could be potential factors influencing the 82 transmission of ACEs from one generation to the next. Although Bowen Family Systems theory provides a framework in understanding ACE transmission, it is also necessary to acknowledge the influence of an ecological perspective (Bronfenbrenner, 2005) on the generational transmission of family patterns. A large body of research recognizes the intersection of the influence of contextual factors (e.g., economic, political, cultural, and social) on exposure to adversity (e.g., Baglivio et al., 2014). Thus, continued efforts are warranted to better understand different factors that contribute to the ACE transmission process. Alternative Model One To strengthen the trustworthiness of my findings I additionally examined two alternative models. I examined alternative models because it allowed me to identify the model that best aligns with the underlying data patterns, thus improving the confidence in my conclusions. I believe testing the alternative models bolsters the integrity of my research and also fosters transparency and a deeper understanding of my research aims. As such, the first alternative model I tested investigated parent ER and child ACE scores as mediators between parent ACE score and coercive parenting behaviors. Findings from the first alternative model showed no support of parent ER and child ACE score mediating the relationship between parent ACE score and coercive parenting behaviors. The lack of evidence supporting parent ER and child ACE score as potential mediators of ACE transmission furthers strengthens the importance in understanding the role parent ER and coercive parenting behaviors play in the transmission of ACEs. Alternative Model Two Alternative model two showed no support for coercive parenting behaviors and child ACE score as mediating variables between parent ACE score and parent ER. As such, the second 83 alternative model was rejected in further support of the findings from the hypothesized model. Although the alternative mediational pathway was not supported, this model did confirm significant paths identified in the first two models (i.e., coercive parenting behaviors are associated with child ACE score and parent ER, and parent ER is associated with parent ACE score). Future research is needed to identify factors that reduce or buffer the effects of the intergenerational transmission of ACEs from parents to children. Implications for Couple and Family Therapists There are multiple clinical implications for this study for therapists working with parents and children with ACE histories. Findings from this study provide evidence supporting the relationship between parent ACE score, parent ER, coercive parenting behaviors, and child ACE score. These findings suggest several potential avenues of intervention for therapists. First, findings from this study suggest parent ER to be an important mechanism of intervention. Therapists working with parents and children who have experienced ACEs, must be aware that they may experience challenges with ER. Therefore, it is important that therapists consider assessing a parent’s level of ER. Children whose parents have greater ER skills may be at lower risk for ACE exposure. This is of particular importance as prior research shows that exposure to multiple ACEs can lead to increased ER difficulties (Cooke et al., 2021; Hays-Grudo et al., 2021). Further, ER difficulties may be characterized by an increase in stress response which, in turn, could lead to difficulties in other areas of functioning such as parenting (Lange, Callinan, & Smith, 2019), family conflict (Guss et al., 2020), or poor physical or mental health (Felitti et al., 1998). Therefore, interventions that target improving ER skills may be beneficial for parents and children with ACE exposure. Targeting parent ER is further supported as research has shown 84 that ER skills can be taught; and therefore, improving these skills indicates a promising intervention when developing preventative efforts to decrease ACE transmission (Cameron, Carroll, & Hamiliton, 2018). There are many evidence-based interventions that therapists can draw from to assist in the development of ER skills such as Mindfulness-Based Cognitive Therapy (Sipe & Eisendrath, 2012), Dialectical Behavior Therapy (Linehan, 2014), Acceptance and Commitment Therapy (Harris, 2006), and Attachment-Based Family Therapy (Diamond, Russo, & Levy, 2016). By strengthening a parent’s ER skills, they will have a better ability to model healthy coping skills for their children and manage their own emotional responses, thus providing a framework to minimize the transmission of ACEs. These implications are in need of direct testing but hold promise for improving the well-being of children and families. Next, although this study did not find a significant relationship between ACEs and coercive parenting behaviors, this study did find coercive parenting behaviors to mediate the relationship between parent ACE score and child ACE score. Considering the importance of parenting behaviors in child development (e.g., McKelvey et al., 2009), this could hold significant implications for families with ACE exposure. Parents with ACE exposure may be more likely to display fewer positive parenting behaviors (Lange, Callinan, & Smith, 2019), potentially impacting their child’s development. As such, parents with ACE exposure likely face unique challenges in parenting, which could be addressed through interventions such psychoeducation, home visiting programs, or evidence-based parenting programs (Bethell et al., 2016). Therefore, targeting parenting behaviors should be an important intervention considered. Efforts to improve parenting behaviors may lead to responsive parenting and in turn decrease coercive parenting behaviors which may reduce exposure to ACEs. Research on multiple 85 evidence-based parenting programs have demonstrated success at increasing parental competence and skills (Biglan, Van Ryzin, & Hawkins, 2017). Effective parenting programs such as Parent Management Training - Oregon (PMTO; Patterson, 2005), Triple P (the Positive Parenting Program; Sanders et al., 2012), Parent-Child Interaction Therapy (PCIT; Thomas et al., 2017) and the Incredible Years (Webster-Stratton, 1992), provide parents with effective parenting strategies and offer promise in reducing ACE transmission. Finally, it is important to consider alternative implications for ACEs outside of the focus of this study. The findings from this study encourage researchers and therapists to consider alternative mechanisms of ACE transmission in families. Thus, it may be helpful to consider another route of intervention in reducing ACE transmission. Given that this study examined factors of transmission between parents and their children, it might be beneficial to target new or expecting parents as recipients of preventative interventions via ACE-focused psychoeducation. In addition to fostering a greater sense of understanding among parents of how one’s past has the potential for informing the future, such educational components may also provide effective in improving parent ER and parenting behaviors. Further, it may also be advantageous to consider incorporating a trauma-informed framework when working with parents and children. In conclusion, findings from this study suggest multiple avenues of intervention and highlight the importance of expanding preventative efforts. Considering these results alongside those in the existing literature (e.g., Bethell et al., 2017; Crouch et al., 2020) suggest that transmission of ACEs is multidimensional, with relevant contributions across parent and child factors. As such, although effective evidence-based interventions exist in strengthening ER skills and parenting behaviors, it is not clear as to how the role of ACEs may influence outcomes and requires more attention. 86 Implications for Future Research Empirical implications of the current study identify multiple avenues for future research. First, the understanding of ACE transmission is in its infancy and requires more attention. It is important that studies are replicated in larger samples and in different samples such as clinical populations and contexts outside of the United States. Future research should also examine patterns of ACE transmission among different levels of ACE exposure. For example, perhaps experiencing a specific number of ACEs (e.g., an ACE score of 4) may predict greater likelihood of child ACE exposure. Furthermore, it would be informative to examine patterns of ACE transmission among different demographic subgroups. In addition, studies examining ACEs and mediating variables have explored few mediating factors (e.g., Schickedanz et al., 2021) or have used cross-sectional data (e.g., Goodman et al., 2020). While these studies provide preliminary evidence for mitigating the transmission of ACEs, they are not able to capture the complexity of how mediating variables may affect ACE transmission via causal processes. Thus, it would be helpful to further explore potential mediating variables through longitudinal designs. This would help provide evidence of causation and not just correlation and further support the importance of these factors in reducing ACE exposure in families. Finally, the frameworks that account for ACE transmission should be further refined to understand what factors contribute to the pathways linking ACE exposure in families. More research is needed to identify protective factors that buffer the continuity of ACEs. Ongoing prospective research following the transmission of ACEs into the second generation is needed to more clearly understand the development of ACE transmission and the impact on mental and physical health outcomes in families. 87 Study Strengths and Limitations Notable strengths of this study include both its study sample and partnership with a community health clinic. Prior parenting literature largely focuses on maternal history, ER, and parenting behaviors. However, it is important to understand whether relations between these constructs vary by gender. The present study included mothers and fathers in the sample and supports the growing literature examining the unique experiences of parents. An additional strength of this study is that it took place as part of a community-academic research partnership. Community-academic research is said to generate richer data over time (Greenwood, Whyte, & Harkavy, 1993) and support the translation of research findings into action to improve the health outcomes of children and parents. A balanced attention to community partner feedback and research literature was valuable in developing research aims and provided the opportunity for critical discussion with Bowen Health Clinic members. This partnership is key to ensuring the results of this study move forward at an organizational level in working with families. In addition, findings are applicable to service providers at the Bowen Health Clinic who hope to improve their intervention efforts with parents and children. Another strength of this study is that it focused on extending information about ACEs in a sample of rural families. Rural communities, in particular, are at greater risk for ACE exposure (Crouch et al., 2020). One reason for this is that these communities are often disproportionately exposed to ACE risk factors such as lower socioeconomic status and educational attainment (Giano, Wheeler, Hubach, 2020). Further, rural communities are often under resourced meaning they do not have access to resources (e.g., physical and mental health care) needed to buffer the effects of ACEs (Douthit et al., 2015). Given these concerning factors, it is unfortunate that rural communities are understudied in the ACE literature. As such, this dissertation sought to increase 88 representation of rural families in the literature and further argue for the importance of including this population when investigating the unique mechanisms of ACE transmission. Study findings must be considered in light of the research limitations. Given the cross- sectional nature of this study design, all findings are limited at the correlational level and do not reveal causations. Thus, although data provided support for the notion that parent ER is an appropriate target for interrupting the generational transmission of ACEs, replicating these findings using a longitudinal dataset would lend more support for this assertion. Despite efforts to increase the generalizability of findings by including fathers, the present sample is still relatively homogeneous in terms of race, with the majority (i.e., over 90%) of parents identifying as White. In addition, the study draws on a nonrepresentative sample of parents from one rural health clinic and may not be generalizable to other rural communities. Future research would benefit from recruitment strategies that prioritize the inclusion of diverse participants in terms of race, ethnicity, and gender identity and target a more representative sample. In addition, it should also be acknowledged that the way in which ACEs were measured for this study limits the understanding of adversity. For example, the ACE Questionnaire (Felitti et al., 1998) measures the intensity and frequency of all ACEs as equal weight when that may not be reflective of individual ACE differences as well as unique exposure based on population differences. Further, use of this measure may have excluded other forms of adversity (e.g., community violence, neighborhood safety, microaggressions) beginning to emerge in the literature as potential mechanisms contributing to generational transmission. Lastly, concerns regarding the validity of self-report data underscore the importance of using a multimethod approach to data collection. For example, the inclusion of physiological 89 measures of ER and behavioral observations of parenting behaviors would potentially provide data that are less susceptible to these forms of bias and improve confidence in the study findings. Thus, the nature of results found between ACEs and coercive behaviors should be viewed in light of these limitations in measurement. Conclusion This study examined the relationships between parent ACE score, parent ER, coercive parenting behaviors, and child ACE score. Findings indicate a significant relationship between parent ACE score and parent ER difficulties. Further, parent ER and coercive parenting behaviors were investigated as potential mediators between parent ACE score and child ACE score. Evidence for the mediation was found and further strengthens the importance of exploring avenues of mediation in the transmission of ACEs in families. 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Journal of Child and Family Studies, 28(1), 233-244. https://doi.org/10.1007/s10826-018-1258-2 108 APPENDIX A: SAMPLE RECRUITMENT FLYER What is the study about? • This study seeks to understand adverse experiences in families • This study will help inform family-based prevention and intervention efforts Who can participate? • Parents or caregivers with a child between the ages of 4-12 • Must be 18 years or older • The caregiver has not been diagnosed with a serious mental illness such as schizophrenia, schizoaffective disorder, or another psychotic disorder What will participants do? • Complete an electronic survey that will take 15-20 minutes • Participants will answer questions about adverse childhood experiences, emotion regulation, and parenting behaviors Will participants be compensated? • Participants will receive a $40.00 electronic Amazon gift card • After finishing the survey, participants will be directed to a different survey page to enter an email address to receive a gift card • The participant email address will not be connected to their survey responses and there will be no way to identify participant responses Who has access to the information? • Only dissertation personnel will have access to collected data Where will the information be stored? • The information will be stored on a password protected excel file on a password protected laptop • The data will be secured on MSU OneDrive system 109 APPENDIX B: SAMPLE RECRUITMENT EMAIL Dear Providers, My name is Gia Casaburo, and I am a doctoral candidate at Michigan State University in East Lansing, MI. With the support of my advisor, Dr. Kendal Holtrop, I am conducting a research study entitled: Examining the transmission of adverse childhood experiences in a sample of under-resourced rural families using a path analysis, in partial fulfillment of the requirements for the degree of Doctor of Philosophy. I am specifically reaching out to you for participant recruitment support. As a provider at the Bowen Health Clinic you work in direct contact with families receiving behavioral health services. The purpose of this study is to understand the generational transmission of adverse childhood experiences in families. I am recruiting a minimum of 100 parents to participant in my study. Parents are eligible to participate in the study if they: (a) be a legal adult (age 18 or older), (b) be a parent or primary caregiver of one or more children between the ages of four and twelve years, and (c) be comfortable reading and responding to survey items in English. Parents will be asked to complete a short survey that should require no more than 20 minutes. I am providing gift cards for reimbursement of time and effort (up to $40.00) Would you be willing to distribute recruitment cards to parents on your caseloads that meet the inclusion criteria? I have copies of study materials and an informational document to support you in talking about the study. Please connect with me if you have parents on your caseloads that you think would be interested in participating in the study. I can provide you with more information. This study has been approved by the MSU IRB and representative of the Bowen Health Clinic. Thanks in advance for your support. I look forward to having the families we serve represented as a part of this study! 110 APPENDIX C: SAMPLE RECRUITMENT EMAIL 111 APPENDIX D: INFORMED CONSENT FORM Explanation of the research and what you will do: You are being asked to participate in a research study. The purpose of the study is to explore generational experiences in families. You will be asked to complete an electronic survey. All survey responses will be anonymous, and we will not collect data in a way that will allow us to link your responses with any identifying information. You will be asked to respond to questions about adverse experiences during your childhood (for example: experiences of abuse, neglect, divorce, or incarceration), ways in which you manage your emotions, and your parenting practices. You will also be asked to indicate the number of adverse experiences your child has been exposed to based on a list of 10 possible experiences. Your participation in this study is expected to take between 15-20 minutes. Your participation is voluntary. You can skip any question you do not wish to answer or withdraw at any time. You must be 18 years or older to participate. If you have any questions please contact the researcher, Gia Casaburo, at (260) 355- 5751 or email casabur1@msu.edu. Your rights to participate, say no, or withdraw: Participation in this research project is completely voluntary. You have the right to say no. You may change your mind at any time and withdraw. You may choose not to answer specific questions or to stop participating at any time. Whether you choose to participate or not will have no effect on your services at the Bowen Health Clinic. There are no anticipated risks from your participation in this study. However, some people may become anxious or upset when answering questions about difficult experiences they have had in the past (for example: experiencing physical abuse as a child) or when reflecting on the difficult things that their child has experienced. We will provide a list of resources at the completion of the survey if you wish to seek support services. Costs and compensation for being in the study: There are no costs for participating in this study. You will receive a $40.00 electronic Amazon gift card for completing this study. After completing the electronic survey, you will be directed to a separate page not connected to your survey responses to enter an email address to receive a gift card. Your email address will not be tied back to your survey responses. Contact information for questions and concerns: If you have concerns or questions about this study, such as scientific issues, how to do any part of it, or to report an injury, please contact the researcher, Gia Casaburo, at (260) 355-5751 or email casabur1@msu.edu. If you have questions or concerns about your role and rights as a research participant, would like to obtain information or offer input, or would like to register a complaint about this study, you may contact, anonymously if you wish, the Michigan State University’s Human Research Protection Program at 517-355-2180, Fax 517-432-4503, or e- mail irb@msu.edu or regular mail at 4000 Collins Rd, Suite 136, Lansing, MI 48910. By clicking the button below to move forward, you indicate your voluntary agreement to participate in this online survey. 112 APPENDIX E: PARTICIPANT DEMOGRAPHIC QUESTIONNAIRE Parent Variables 1. Parent Age. How old are you? a. [text entry 1] 1. Parent Gender. What is your gender? a. Cis-gender Female b. Cis-gender Male c. Transgender Female d. Transgender Male e. Non-binary f. Prefer to Self-describe: [text entry1] g. Prefer not to say 3. Parent Race. Please indicate your race (choose all that apply) a. African American/Black b. American Indian or Alaskan Native c. Asian d. Native Hawaiian or Pacific Islander e. White f. Other: [text entry1] 4. Parent Ethnicity. Please indicate your ethnicity. a. Hispanic b. Non-Hispanic 5. Parent Educational Level. Please indicate your highest educational level. a. Less than high school b. High school or GED c. Some college or technical school d. College degree or higher 6. Parent Employment Status. Please indicate your employment status. a. Full-time b. Part-time c. Contract/temporary d. Unemployed e. Unable to work f. Other: [text entry1] 7. Parent Marital Status. Please identify your marital status. a. Single b. Dating and living together c. Dating and not living together d. Married 113 e. Widowed f. Divorced g. Separated h. Other: [text entry1] 8. Parent Household Income. Please indicate your annual household income. a. Under $15,000 b. $15,000 to $24,999 c. $25,000 to $34,999 d. $35,000 to $49,999 e. $50,000 to $74, 999 f. $75,000 to $99,999 g. $100,000 to $149,999 h. $150,000 and over Child Variables 1. Child Age. What month and year was your child born? a. [text entry 1] 2. Child Gender. What is your gender? a. Cis-gender Female b. Cis-gender Male c. Transgender Female d. Transgender Male e. Non-binary f. Prefer to Self-describe: [text entry1] g. Prefer not to say 3. Child Race. Please indicate your race (choose all that apply) a. African American/Black b. American Indian or Alaskan Native c. Asian d. Native Hawaiian or Pacific Islander e. White f. Other: [text entry1] 4. Child Ethnicity. What is your child’s ethnicity? a. Hispanic b. Non-Hispanic [1] Qualtrics validation tool will be used to specify content type (i.e., number, text). 114