I have definitely needed their emotional support as the road to vi ...... deliberate infliction of harmâ, such as assault and terrorism, and non-intentional traumas.
ADVERSE CHILDHOOD EXPERIENCES AND COUPLE RELATIONSHIPS: IMPACTS ON RELATIONSHIP QUALITY AND PARTNER SELECTION
A Dissertation Presented to The Graduate Faculty of The University of Akron
In Partial Fulfillment of the Requirements for the Degree Doctor of Philosophy
Michael Redd December, 2017
ADVERSE CHILDHOOD EXPERIENCES AND COUPLE RELATIONSHIPS: IMPACTS ON RELATIONSHIP QUALITY AND PARTNER SELECTION
Michael Redd Dissertation
Approved:
Accepted:
______________________________ Dissertation Chair Dr. Karin Jordan
______________________________ School Director
______________________________ Committee Member Dr. Rebecca Boyle
______________________________ Dean of the College
______________________________ Committee Member Dr. Rikki Patton
______________________________ Dean of the Graduate School
______________________________ Committee Member Dr. David Tefteller
______________________________ Date
______________________________ Committee Member Dr. Wondimu Ahmed
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ABSTRACT The purpose of the present study was to replicate the Adverse Childhood Experiences (ACE) study framework, using relationship outcomes, and studied within the context of couple relationships. A thorough review of the literature on trauma, its prevalence, prior studies on ACEs, trauma and couples, and partner selection is presented. A secondary data analysis of 146 couples from a clinical source was used to test the present study’s hypotheses. Actor-Partner Interdependence Model (APIM) was used to test the hypothesis that an individual’s ACE exposure history would be negatively related to both their own and their partner’s reported relationship quality. A cluster analysis was used to test the hypothesis that couples could be statistically grouped by ACE score combinations, and an ANOVA was used to test average group differences on relationship quality. Regression analyses were used to test hypotheses about partner selection. Results from the analysis include: (1) a small but significant negative impact of an individual’s ACEs on their own reported relationship quality, but no finding of a significant impact on their partner’s reported relationship quality; (2) a small but significant relationship between partner ACE scores; (3) a preliminary ability to group couples by ACE score combinations into three clusters (Low-Low, High-Moderate, Moderate-High) and a small but significant difference between two of the clusters; (4) an increased likelihood that couples will be partnered with those who have more similar than different ACE scores, and a significant trend that as ACEs increase, the likelihood of iii
being partnered with someone who has similar ACEs will decrease; (5) a small but significant dose-response relationship between increasing ACEs and the likelihood of being partnered with someone who has more than minimal ACEs. Further discussion of the results, implications, limitations of the study, and future research directions are also included.
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DEDICATION I dedicate this work to all of the couples I have worked with clinically. Your life and relationship struggles as a consequence of trauma have motivated me to learn all I can about trauma, its systemic effects, and its healing.
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ACKNOWLEDGEMENTS I want to thank all of my committee members for their guidance and support throughout this process. They have contributed not just during the dissertation process but also throughout the doctoral program. I would specifically like to thank Dr. Karin Jordan for the many meetings, advice, support, and mentoring throughout the doctoral program. Her support has been invaluable and I will forever be grateful for her patience in sticking with me when I was stuck. Her encouragement for helping me to see my own strengths has been a growth experience for me, and I have appreciated her encouragement to me for both my clinical and research exploration of trauma and couples. I also want to specifically acknowledge Dr. Boyle for her support and mentoring as well, and for her genuine interest in helping students. I want to acknowledge Dr. Boyle and the Clinic for collecting the data that I was able to use in my dissertation. I would like to thank Dr. Wondimu Ahmed as my methodologist for his patience and willingness to keep meeting with me, for making sure I was on the right track and that I understood the research and statistical analysis process. I would also like to acknowledge Dr. Varley at Summa, whose interest in ACEs and the impact of trauma on couples and families, led to a joint research venture with the clinic, to the clinic beginning to assess for ACEs, and eventually to making this study possible. I would like to acknowledge my family, and their support and encouragement through this process. I have definitely needed their emotional support as the road to vi
finishing the dissertation and doctoral degree has not always been smooth. Finally, I would like to especially acknowledge my wife Sara for all of her support in numerous ways throughout this whole process. Her reassurance that I had what it took to finish was invaluable. Without the things she did to support me, such as editing drafts, listening to me discuss the dissertation over and over, asking clarifying questions to help me work through dilemmas, ‘holding down the fort’ at home, being willing to sacrifice so we could push through this last semester, and her encouragement and love, I am fairly certain I would never have finished. Thank you for always being there and supporting me.
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TABLE OF CONTENTS Page LIST OF FIGURES………………………………………………………...…………..xiii LIST OF TABLES………………………………………………………………..…….xiv CHAPTER I.
INTRODUCTION……………………………………………………………1 Childhood Trauma Exposure……………...………………………………………1 Adverse Childhood Experiences Studies...………………………………………..2 Trauma and Couple Relationships………………………………………………...6 Trauma and Partner Selection……………………………………………………..8 Statement of the Problem...………………………………………………………11 Overview of the Research Study……………………………………………........12 Research Questions..…………………………………………………..…12 Significance of the Study……..………………………………………………….13 Definition of Terms...…………………………………………………………….14 Organization of the Study…….………………………………………………….18
II.
REVIEW OF THE LITERATURE…….…………………………………………...20 Definitions of Trauma……………………………………………………………22 Defining Trauma and Traumatic Events…………………………………22 Posttraumatic Stress Disorder Definitions……………………………….23 viii
Critiques of Definitions………………………………………………..…24 Types of Trauma…………………………………………………………25 Posttraumatic Growth……………………………………………………27 Prevalence………………………………………………………………………..28 Adverse Childhood Experiences and Impact of Childhood Trauma on Adults….…………………………………………………………….32 Original ACE Study………………………………..……………………32 Follow-up ACE Studies…………………………………………………35 Critiques of ACE Study Methodology………………………………..…41 Summary…………………………………………………………………45 Posttraumatic Stress Impact on Individuals and Couples…..…………………...46 ACEs and Risk for PTSD….……………………………………….……46 Impacts of PTSD on General Individual Outcomes………….………….49 Impacts of PTSD on General Couple Relationship Outcomes...………...50 Impacts of Childhood Trauma Exposure on Couple Relationships…..….55 Summary…………………………………………………………………61 Trauma and Partner Selection…...……………………………………………….63 Research Relevant to Partner Similarity…………………………………64 Summary…………………………………………………………………68 Theoretical Foundation…………………………………………………………..69 Systems Theory…………………………………………………………..70 Developmental Models…...……………………………………………...71 Stress and Family-as-Context…...…...…………………………………..73 ix
Summary…………………………………………………………………74 Summary……………………...………………………………………………….75 III. METHODOLOGY…...…………………………………………………………….77 Restatement of the Problem……………………………………………….……..77 Research Purpose……………………………..………………………………….78 Research Questions and Hypotheses…………………..………………………...79 Research Design….…………………………………………………….………..81 Data Source and Sample…...………………………………………………….…83 Instruments…...…………………………………………………………………..84 Client Information Form...……………………………………………….84 Adverse Childhood Experiences (ACE) Questionnaire…..……………...84 Revised Dyadic Adjustment Scale (RDAS)…..…………………………85 Data Cleaning and Preparation…..………………………………………………87 Data Analysis…...………………………………………………………………..87 Summary…………………………………………………………………………90 IV. RESULTS…………………………………………...……………………………...91 Data Screening and Cleaning………………………………………….…………91 Missing Data……………………………………………………………..91 Assumption Testing……………………………………………...………………92 Univariate Outliers………………………………….……………………92 Normality and Multivariate Outliers………………………..……………93 Linearity…………………………………………………………….……95 x
Data Restructuring……………………………………….………………95 Multicollinearity…………………………………………………………96 Instrument Psychometrics………………………………………………..97 Properties of ACE……………………………………………..…97 Properties Of RDAS………………………..……………………97 Descriptive Statistics………………………….…………………………………98 Hypothesis 1: APIM…………………………..………………………………..102 Hypothesis 2: Cluster Analysis…………………………………………………106 Hypothesis 3: Logistic Regression……………………………………………...109 Hypothesis 4: Logistic Regression……………………………………………...111 Chapter Summary………………………………………………………………113 V.
DISCUSSION………………………………………..……………………………115 Summary of Present Study………………………..……………………………115 Results of Hypothesis Testing………………………..………………………...116 Hypothesis 1………………………..…………………………………..116 Hypothesis 2………………………..…………………………………..117 Hypothesis 3………………………..…………………………………..120 Hypothesis 4………………………..…………………………………..121 Implications for the Field………………………..……………………………..122 Limitations………………………..…………………………………………….123 Future Research Directions………………………..……………………………126 Summary………………………..………………………………………………127 xi
VI.
REFERENCES………………………………….…..……………………………129
APPENDICES………………………………………………………………………….145 APPENDIX A. CLIENT INFORMATION FORM……………………………146 APPENDIX B. ADVERSE CHILDHOOD EXPERIENCE (ACE) QUESTIONAIRE………………………………………………………………147 APPENDIX C. INSTITUTIONAL REVIEW BOARD (IRB) APPROVAL FOR STUDY……………..…………...…………………………148
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LIST OF FIGURES
Figure
Page
1
Histogram of ACE Score with Normal Curve……………………………...……94
2
Histogram of RDAS Score with Normal Curve……………………………...….95
3
Residual Plot Test for Linearity…………………………………………………95
4
Standard Fitted Model……………………………………………………….....103
5
Model with Standardized Parameter Estimates……………………………...…104
6
Actor and Partner Effects using Estimated Parameters……………………...…104
7
Results from TwoStep Cluster Analysis by Average ACE score………………106
8
Average Group RDAS Scores by Cluster………………………………………108
9
Percent of Partners with More than Minimal ACEs by ACE Score……………113
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LIST OF TABLES Table
Page
1
Central Tendency, Variance, and Standard Error for Variables…………………93
2
Pearson Correlation Matrix among ACE_Score1, ACE_Score2, RDAS_Score1, and RDAS_Score2 ...………….………………………………………………….95
3
Frequency of ACE Reported…………………………………………...………...96
4
Sample Demographic Frequencies (Full Sample)...….………………………… 98
5
Sample Demographic Frequencies (Partial Sample)………………………..…...99
6
APIM Results………………………………………………………………...…..95
7
Cluster Membership Frequencies and Means……………………………..……105
8
Cluster Membership Group RDAS Means…………………………………..…107
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CHAPTER 1 INTRODUCTION
Childhood Trauma Exposure Child maltreatment has been described as a significant public health concern with potentially severe lifelong consequences and with significant attending costs and burdens to the individual and to society (Campbell, Walker, & Egede, 2016; Norman et al., 2012). According to research on the economic burden of childhood maltreatment (Fang, Brown, Florence, & Mercy, 2012), there are an estimated 579,000 new substantiated cases of childhood abuse and neglect every year in the United States using Child Protective Services (CPS) 2008 data. This same study estimated that these yearly new cases of maltreatment, from short- and long-term health costs, productivity losses, child welfare costs, criminal justice costs, and special education costs, result in an estimated lifetime economic burden of $124 billion. A recent cross-sectional, national study of children and youth in the U.S. found that 1 in 4 children will experience some form of childhood maltreatment by a caregiver (such as any physical abuse, emotional abuse, sexual abuse, or neglect) within their lifetime (Finkelhor, Turner, Shattuck, & Hamby, 2013). However, even with the staggering numbers for both the costs and prevalence of childhood maltreatment, CPS data is widely thought to underestimate actual prevalence, and retrospective recall is likely to underestimate it as well for a variety of reasons (CDC,
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2014; Mersky, Topitzes, & Reynolds, 2013; Pereda, Guilera, Forns, & Gómez-Benito, 2009; Scott-Storey, 2011). In addition, childhood maltreatment is only a subset of potential childhood adversity that can severely and significantly impact the individual, families, and society. A very important line of research that has provided some of the most comprehensive views of the negative impacts of childhood maltreatment and adversity is the research on Adverse Childhood Experiences (ACE). The purpose of this chapter is to provide an introduction to the ACE research and to discuss the researched negative outcomes of childhood trauma exposure. In addition, significant research on individuals and negative outcomes is only now starting to be followed up with research on couples and families and the related negative impacts on these systems from childhood maltreatment and adversity. The purpose of this study was to replicate the ACEs framework in studying couple relationships, so an introduction to research on trauma and couple relationships is included in this chapter. Research on partner selection will follow, discussing it as a potential outcome of childhood trauma. A more comprehensive review of the research in these areas is included in Chapter II. The chapter will conclude with a summary of the proposed research and research questions. Adverse Childhood Experiences Studies Adverse Childhood Experiences studies have expanded beyond childhood maltreatment to include not just abuse and neglect, but also other forms of adversity, such as family or household dysfunction and instability, that children experience that may negatively impact them as well (Felitti et al., 1998). For example, ACE studies generally 2
ask adults about their exposure to different categories of adverse experiences during childhood, including emotional abuse, physical abuse, sexual abuse, neglect, parental separation/divorce, violence against their mother, and living with a family member who abused drugs/alcohol, had mental illness, or criminal behavior. Each type of adversity meeting the threshold for exposure adds one to a total summed ACE score (which can range from 0–10, depending on how many types of adversity are included in the study). The resulting ACE score is a measure of cumulative childhood trauma exposure. ACE studies have statistically examined the impact of the amount of childhood adversity exposure (ACE score) on later physical and mental health outcomes. A majority of these studies have found that not only does experiencing childhood trauma matter for later health as an adult, but perhaps what is more important for later health is the amount of exposure to different types of trauma. ACE studies have consistently found evidence to support the assertion that the more types of traumatic events that an individual is exposed to during childhood, the more likelihood of severe negative impacts on that individual throughout their lifespan. The existence of this "strong, graded relationship" (Dube et al., 2001, p. 3089), also called a dose-response relationship (Felitti et al., 1998), where each increase in ACE score predicts increased risk for negative outcomes, is a strong piece of evidence pointing towards a causal relationship. In addition, cumulative exposure seems to lead to cumulative negative effects (what is known as comorbidity or symptom complexity), with increased negative outcomes coinciding with increased ACE exposure (Cloitre et al., 2009; Mersky et al., 2013). Some studies have shown evidence that particularly negative consequences are 3
more strongly related to ACE scores of 4 or more (Anda et al., 2006; McKelvey, Selig, & Whiteside-Mansell, 2017). Another important finding from these studies is that ACEs are very common. The first ACE study, with a sample of predominately White, middle-aged, and collegeeducated individuals surprised researchers with about two-thirds of the sample reporting exposure to at least one ACE, and more than one in five reporting exposure to three or more ACEs. In comparison, minority samples have found elevated rates, with 80% in a sample of urban minority young adults having an ACE score of at least one and with 49% having an ACE score of at least two (Mersky et al., 2013), and with 78% in a sample of Native American adolescents and young adults having an ACE score of at least one and with 59% having an ACE score of at least two (Brockie, Dana-Sacco, Wallen, Wilcox, & Campbell, 2015). A recent report using data from the nationally representative 2011/12 National Survey of Children’s Health (NSCH) estimated that in the U.S. 46% of children have experienced at least one ACE (Sacks, Murphey, & Moore, 2014). Importantly, ACE framework studies have found evidence that the impacts of ACEs begin early and can significantly alter developmental trajectories from childhood carrying forward into adulthood (Nurius, Green, Logan-Greene, & Borja, 2015). For example, ACE studies with young children have found that the amount of exposure to ACEs predicts existence of chronic medical conditions and poorer health, problematic socioemotional development (including increased aggressive behaviors, decreased emotion regulation, and poorer mental health), and cognitive and learning deficits (Kerker et al., 2015; McKelvey et al., 2017). Correspondingly, studies with adolescents 4
and young adults have found that the amount of ACE exposure predicts increased odds of suicide attempts, drug use, depression symptoms, PTSD or anxiety symptoms, poorer self-reported health, lower life satisfaction, criminal behavior, and risky sexual behavior (Bellis et al., 2014; Brockie et al., 2015; Mersky et al., 2013; Rebbe, Nurius, Ahrens, & Courtney, 2017; Thompson et al., 2015). Perhaps one of the earliest contributions of the ACE studies was the finding that adversity in childhood does not just impact the child or adolescent but carries forward to adulthood as well. The first ACE study by Felitti et al. (1998) and studies since have made the connection between childhood exposure to adverse events and risk factors for leading causes of death in adults, such as smoking, illicit drug use, severe obesity, not being physically active, depressive episodes, poorer mental health, risky sexual behavior, and suicide attempts (Dube et al., 2001, 2003; Edwards, Holden, Felitti, & Anda, 2003; Font & Maguire-Jack, 2016; Gilbert et al., 2015; Norman et al., 2012). Important connections have been found between higher ACE exposure and disproportionate health services use throughout the lifespan (Bellis et al., 2017), as well as increased risk for later physical health problems such as heart disease, asthma, poor self-reported health, cancer, stroke, chronic bronchitis/emphysema, chronic obstructive pulmonary disease (COPD), diabetes, and disability (Anda et al., 2008; Felitti et al., 1998; Gilbert et al., 2015). These results have been found even after accounting for socioeconomic factors (Bellis et al., 2017; Font & Maguire-Jack, 2016; Ports, Ford, & Merrick, 2016). The significant and sometimes severe lifelong impacts and increased risks from cumulative childhood adversity exposure make studying and understanding this topic crucial. 5
Trauma and Couple Relationships ACE studies that measure relational outcomes are rare but do show some evidence of a link between early adversity and negative relational outcomes. For example, exposure to ACEs is associated with a significantly increased risk of a personality disorder diagnosis, intimate partner violence (of victimization among women and perpetration by men), and increased likelihood of frequent marital distress (Afifi et al., 2011; Gilbert et al., 2015; Whitfield, Anda, Dube, & Felitti, 2003). Other research studies outside of the ACE study framework have examined smaller subsets of childhood adversity, mostly abuse history, and found that childhood trauma is associated with later increased probability for marital disruption, lower marital satisfaction, lower relationship adjustment, higher psychological stress scores, lower relationship sexual satisfaction, and increased intimate partner violence (Bigras, Daspe, Godbout, Briere, & Sabourin, 2016; Daigneault, Hébert, & McDuff, 2009; Godbout et al., 2017; A. B. Miller, Schaefer, Renshaw, & Blais, 2013; Nelson & Wampler, 2000; Whisman, 2006). In addition, ACE studies have shown some evidence that childhood adversity significantly increases the risk for adult posttraumatic stress disorder (PTSD) symptoms (Brockie et al., 2015; Cabrera, Hoge, Bliese, Castro, & Messer, 2007; Rebbe et al., 2017). Existence of and severity of PTSD symptoms within couple relationships in turn, has been shown in numerous studies to have a significant associations with higher relationship discord, physical and psychological aggression, higher rates of divorce, intimacy problems, relationship dissatisfaction, and worse family adjustment (Fredman et al., 2010; Kessler, Walters, & Forthofer, 1998; Lambert, Engh, Hasbun, & Holzer, 2012; 6
A. B. Miller et al., 2013; Monson, Taft, & Fredman, 2009; D. S. Riggs, 2014; D. S. Riggs, Byrne, Weathers, & Litz, 1998; Taft, Watkins, Stafford, Street, & Monson, 2011). All of these studies combine to show growing evidence that trauma in general significantly negatively impacts couple relationship quality and stability. The case is building in the research literature that childhood adversity may also lead to enduring relationship impacts. These impacts may also be indirect, where childhood adversity leads to impacts on PTSD symptoms and vulnerability to adult PTSD, which then also negatively impacts couple relationships (Cabrera et al., 2007; Yehuda et al., 2010). ACE studies that measure couple outcomes are important not just because the ACE framework has been established through research with a broad range of health outcomes. They are also important because ACE scores are a measure of the amount or severity of childhood exposure, something that is often not measured in the studies that have so far attempted to look at links between specific childhood abuse histories and later relational outcomes. And although ACE studies are important in this regard, no ACE studies, to the knowledge of this author, have been done which examined both partners in couple dyads and their interconnections. Important information is missing in the research literature regarding the role of ACEs in affecting relationship quality for both partners as well as how the combination of ACE history in the couple dyad impacts the relationship quality. Further research using the ACE study framework to examine couple dyads and look at relationship outcomes could add significantly to the literature.
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Trauma and Partner Selection From a systemic perspective, looking at how an individual’s history of childhood trauma impacts the kinds of partners that individual chooses is potentially important for understanding not just the couple but intergenerational dynamics as well. Intergenerational transmission of trauma, or the processes by which experiencing trauma may create vulnerabilities in the family system that increases risk of recreating trauma in the next generation have been theorized extensively (Abrams, 1999; Balcom, 1996; Coulter, 2011; Murphy et al., 2014; Siegel, 2013). Actual studies have found small to moderate effect sizes for the impact of experiencing or witnessing childhood violence on becoming an adult victim or perpetrator of intimate partner violence, providing some evidence for an intergenerational transmission of violence (Smith-Marek et al., 2015; Stith et al., 2000). Yehuda, Halligan, and Grossman (2001) found that parental PTSD in Holocaust survivors increased the likelihood of emotional abuse and neglect experiences in their children and that self-reported childhood trauma in this next generation was associated with increased cortisol levels (a measure of stress) and severity of PTSD as adults. Though more research is needed to see if evidence truly supports the theory of intergenerational transmission of trauma, the theory that families are directly affected by, and may organize around trauma (Coulter, 2011) lends importance to understanding partner selection factors when trauma histories are present. The primary theory about partner selection and trauma, at present, revolves around partner similarity, or the theory that individuals with trauma histories are more likely to choose those with similar trauma histories as partners (Goff & Smith, 2005). 8
Some evidence suggests increased odds for individuals with a psychiatric diagnosis to partner with those who also have a diagnosis (same or different) (Nordsletten et al., 2016), including PTSD (D. S. Riggs, 2014). Limited research is also available showing increased odds for similarity in childhood physical abuse history between partners (Whisman, 2014). Thus individuals with psychiatric disorders, PTSD, and childhood physical abuse history may be more likely to partner with someone who also has a diagnosis, PTSD, or an abuse history than individuals who do not. Further research on childhood adverse experiences beyond childhood physical abuse is important to clarify these associations. This is especially the case since other research is suggestive that even when there is not similarity in the specific trauma experienced, there may be similarity in developmental histories (Chen & Carolan, 2010). In addition, studying childhood-only adverse events of both partners is methodologically stronger as these events necessarily occur prior to adulthood partnering, which may not be the case with psychiatric diagnoses. It has been hypothesized that partner similarity on trauma history could potentially lead to more relationship problems in dual trauma couples (or couples where both individuals have a history of trauma), due to both individuals being more likely to have negative outcomes (such as a mental illness), as well as increasing the risk of intergenerational transmission of mental illness or trauma through increased accumulation of genetic and environmental risk factors (Nordsletten et al., 2016). The current research seems to be mixed regarding whether dual trauma couples have measurably different relationship outcomes than couples where only one partner has a 9
trauma history, though few studies have been done in this area. There does seem to be some evidence that dual trauma couples have more trauma-related communication problems and triggers than single trauma couples (Nelson Goff et al., 2014), and that trauma-related symptoms from both partners independently contribute to distress in the relationship (D. S. Riggs, 2014). However, one study found no difference in marital adjustment or psychological stress when comparing couples where both had a history of childhood abuse and couples where only one had an abuse history (Nelson & Wampler, 2000). Perhaps with a broader measure of childhood adversity such as ACEs, the amount of exposure can be included in the analysis rather than using the binary variable of trauma history vs. no-trauma history, which combines all levels of exposure to trauma. Using ACEs allows an investigation into partner selection with regard to trauma history and also potential impacts of different combinations of amount of trauma exposure in the couple on relationship quality. Finally, current research on ACE studies and repeated findings of a dose-response relationship between the amount of ACE exposure and a number of outcomes, points towards potential dose-response relationships in other aspects. Risks seem to increase with each added dose of exposure. With regard to partner selection, Whisman (2014) found some evidence that the odds of an individual being partnered with someone who has a diagnosis goes up in a dose-response relationship with the number of diagnoses that the individual has. With potential impacts on intergenerational transmission of mental illness or trauma, it seems important to research the corresponding hypothesis that the odds of an individual partnering with someone who has more than minimal childhood 10
trauma exposure will go up in a dose-response relationship as an individual’s ACE score increases. In addition, the present study also attempted to find out if an increased “dose” of childhood trauma exposure in a couple relationship (accumulated between partners) would lead to more negative relationship quality. Statement of the Problem ACE studies have provided significant evidence to support the assertion that childhood adversity significantly impacts adult mental, behavioral, and physical outcomes but there is little research on potential relational outcomes. In addition, there are no ACE studies studying the couple dyad. Studies on trauma in general have found significant impacts on relationships, and studies of specific childhood traumas have likewise shown these impacts, but these studies typically have examined data at the individual level not making use of dyadic data, and not accounting for the interdependent nature of relationship outcome variables (Cook & Kenny, 2005). Dyadic research is needed that examines the potential relational outcomes of childhood adversity in order to inform on-going research, prevention efforts, and intervention with these populations. In addition, previous research has attempted to group individuals by ACE scores (Mersky et al., 2013; Rebbe et al., 2017) and couples by combinations of abuse/trauma exposure within both partners in the dyad (Nelson & Wampler, 2000) in order to better inform research on outcomes. Efforts to tailor intervention to couples could potentially be improved if couples could be grouped by combinations of trauma/no-trauma or by ACE score combinations between partners (such as low-low, low-high, high-high) and if such groupings were clinically relevant (i.e., were related to relational outcomes). Using a 11
well-established existing measure of childhood adversity exposure, the ACE Study questionnaire, will enable comparisons to individual outcomes as well as informing ongoing research, prevention, and intervention efforts. Some preliminary research exists on how adult trauma impacts relationships and how some forms of childhood trauma impact relationships, but research is lacking on how cumulative childhood trauma affects outcomes such as couple relationship quality and partner selection. Overview of the Research Study The goal of this research study was to replicate the Adverse Childhood Experiences research framework using couples instead of individuals, and to examine the impact of cumulative childhood trauma exposure (as measured by the Adverse Childhood Experiences [ACE] survey [Felitti et al., 1998]) on both couple relationship quality (as measured by the Revised Dyadic Adjustment Scale [RDAS] [Busby, Christensen, Crane, & Larson, 1995]) and partner selection (as measured by relationships between a subject’s and their partner’s ACE scores). The study used archival data to examine these relationships. Research Questions Research Question 1. What is the relative statistical contribution of a subject’s ACE scores on their own RDAS scores and their partner’s RDAS scores? What is the relative statistical contribution of the partner’s ACE scores on their own RDAS scores and the subject’s RDAS scores?
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Research Question 2. a. Can couples be grouped statistically into clusters based on combinations of ACE scores (such as low-low, low-high, and high-high)? b. If so, are there statistically significant differences between these clusters on average group RDAS scores? Research Question 3. Is there a statistically significant relationship between ACE scores of subjects and their partners? Specifically, are subjects statistically more likely to partner with those who have similar (as defined by 2 or less points apart) or different (as defined by >2 points apart) ACE scores? Research Question 4. Do higher ACE scores statistically significantly predict increased likelihood of partnering with someone who has more than minimal ACEs (as defined by ACE score >1)? If so, is there a statistically significant increase in likelihood as ACE scores increase? Significance of the Study It was hoped that the outcome of this research study would provide some evidence related to whether long-term impacts of adverse childhood experiences extend past physical and mental health outcomes to relationship outcomes as well. Results related to partner selection could potentially inform the work that clinicians do with couples who have childhood trauma exposure. In addition, it was hoped that this study would lead to more studies on the relational impacts of trauma, and especially childhood trauma.
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Definition of Terms For the purposes of the current study, the following operational definitions are used as a guideline for terms used in the text. Systemic is often used in this dissertation as an adjective synonymous with relational, interpersonal, or relationship-focused. Systemic also refers to treatments or theoretical models that rely on family systems theory and related theories that describe the interrelatedness of members in a family and the recursive nature of the interactions within family and couple relationships. Marriage and Family Therapists (MFT) is defined by the American Association for Marriage and Family Therapy (AAMFT) as “mental health professionals trained in psychotherapy and family systems, and licensed to diagnose and treat mental and emotional disorders within the context of marriage, couples and family systems. . . Marriage and Family Therapists broaden the traditional emphasis on the individual to attend to the nature and role of individuals in primary relationship networks such as marriage and the family,” (American Association for Marriage and Family Therapy, n.d.) The term trauma for this study stems from the definition used by The Substance Abuse and Mental Health Services Administration (SAMHSA), such that “individual trauma results from an event, series of events, or set of circumstances that is experienced by an individual as physically or emotionally harmful or life threatening and that has lasting adverse effects on the individual’s functioning and mental, physical, social, emotional, or spiritual well-being,” (2014, p. 7).
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Traumatic events are defined in this paper using SAMHSA’s definition which include events or sets of circumstances that are perceived as “physically or emotionally harmful or life threatening and that has lasting adverse effects on the individual’s functioning and mental, physical, social, emotional, or spiritual well-being,” (2014, p. 7). Other definitions in the literature for traumatic events and trauma are presented in Chapter II. Post-traumatic stress disorder, or posttraumatic stress disorder (PTSD) is defined by The Diagnostic and Statistical Manual of Mental Disorders (5th ed.; DSM–5; American Psychiatric Association, 2013) as a psychiatric disorder related to “the development of
characteristic symptoms following exposure to one or more traumatic events,” (p. 274). Childhood maltreatment is defined in this study as all types of abuse or neglect experienced by individuals before age 18. Cumulative childhood trauma is defined in this study as a construct related to the combined potentially traumatic adverse events experienced before age 18. Assessing ACE scores is one way of attempting to measure this construct. Traumatic stress is often used throughout this study to reference the actual impact of traumatic events and the negative posttraumatic reactions, symptoms, or outcomes. PTSD is one such outcome of traumatic stress. Toxic stress is defined in this study using The American Academy of Pediatrics definition, which labels toxic stress as a “strong, frequent, or prolonged activation of the body’s stress response systems in the absence of the buffering protection of a supportive, adult relationship,” (Shonkoff et al., 2012, p. e236). Adversity and trauma exposure 15
(especially cumulative trauma, repeated/frequent exposure, and early exposure) lead to this prolonged activation of the body’s stress response system (S. B. Johnson, Riley, Granger, & Riis, 2013). Complex trauma or complex PTSD has been defined as “the result of exposure to severe stressors that are repetitive and prolonged, involve harm or abandonment by caregivers or other ostensibly responsible adults, and occur at developmentally vulnerable times in the victim’s life, such as early childhood or adolescence,” (Nelson Goff et al., 2014) Adverse Childhood Experiences framework is a methodology in research studies that mostly retrospectively measures whether research participants have had certain adverse childhood experiences (ACEs) and then examines relationships with health outcomes. Adverse childhood experiences, or ACEs are defined as “potentially traumatic events that can have negative, lasting effects on health and well-being,” (Sacks et al., 2014, p. 1). The most commonly measured ACEs in these studies have been emotional abuse, physical abuse, sexual abuse, neglect, parental separation/divorce, violence against their mother, and living with a family member who abused drugs/alcohol, had mental illness, or criminal behavior. ACE score. Adverse childhood experiences studies typically sum the types of adverse experiences (with each experience being a binary variable, experienced or not experienced) in order to arrive at a total ACE score, thus examining the impact of varied or cumulative traumatic events rather than looking at frequency or severity of events. For this study, ACE scores can range from 0-10. 16
Childhood trauma exposure is exposure to potentially traumatic events as a child (under age 18). Early life stress, or childhood adversity are used as synonyms in this study with childhood trauma exposure. Dose-response relationship, is defined as a statistical relationship where increases in the independent variable predict increases in the dependent variable, also called a “strong, graded relationship” (Dube et al., 2001, p. 3089). In ACE research this has been found with risks for negative outcomes increasing with each ACE score increase. A couple for this study was defined as the self-selected romantic relationship between adults over age 18. For this study, those who presented to the clinic where the data was collected for marital, premarital, or couples therapy are defined as a couple. This includes married, remarried, dating, and cohabitating couples as self-reported at the time of data collection. Dyad is defined as a two-person relationship. Dual-trauma couples and single-trauma couples. These are the definitions used by Goff and others (2014), where single-trauma couples are those where only one partner has a history of trauma, and dual-trauma couples are those where both partners have trauma histories. Intergenerational/Transgenerational is defined as the process of being passed from one generation to the next.
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Partner selection is defined in this study as the process by which an individual chooses to pair off with a partner in a romantic relationship. In this study, a subject’s partner selection is defined as having chosen their current partner that they present with at the time of data collection. Length of current relationship could not be used in this study to further define partner selection due to the limitations of the pre-existing data set. Assortative mating or partner similarity are theories related to partner selection that primarily hypothesize that individuals are more likely to select partners based on similarity between partners on certain features or characteristics such as age, education, intelligence, attitudes, and so forth (Luo & Klohnen, 2005). In this study, it is hypothesized that one of the patterns of similarity in characteristics between partners will be the amount of cumulative childhood trauma exposure. Relationship quality is generally defined as the overall quality of a couple’s romantic relationship, as assessed point-in-time, which includes the degree of satisfaction, consensus, and cohesion, among other general factors, within the couple relationship. In the present study, relationship quality is operationalized by self-report responses to the RDAS. Organization of the Study Following this chapter, Chapter II will present a more comprehensive literature review related to trauma and post-trauma reactions, ACE studies research, impacts of trauma on individuals and couples, impacts of childhood trauma on couples, partner selection, and will include a theoretical framework for the study. Chapter III will discuss the methods and instruments used in the study to operationalize the research questions as 18
well as analyze the data. Chapter IV will provide a report of the statistical analyses used in this study. Chapter V will discuss the results of the study as they relate to the current literature and relevancy to its impact on the field.
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CHAPTER II REVIEW OF THE LITERATURE
The impact of traumatic stress on individuals, families and communities has been increasingly studied in recent years (Goff & Smith, 2005), and has been shown to have significant social, psychiatric, medical, and economic costs (Brunello et al., 2001). Researchers have increasingly highlighted the long-term physical and mental health impacts of childhood trauma on individuals over their lifetime (Fink & Galea, 2015; Norman et al., 2012). These research attempts have provided compelling evidence that there are important connections between the “enduring neurodevelopmental consequences of abuse and related adverse experiences during childhood” and many of the leading causes of death and poor health in the United States (Anda et al., 2006, p. 11). Although the social science field has a better understanding of the consequences of trauma on the individual over time, researchers have noted a lack of published research regarding the connection between traumatic stress and family relationships, especially research that utilizes a systemic lens (Coulter, 2011). Numerous researchers have noted that the trauma literature has mainly focused on intrapsychic rather than interpersonal effects of trauma (Dalton, Greenman, Classen, & Johnson, 2013; Henry et al., 2011; Maercker & Hecker, 2016; Nelson & Wampler, 2000). However, partly due to the clinical need to research and address the significant interpersonal distress in a whole new generation of traumatized veterans (A. B. Miller et al., 2013), there seems to be a 20
growing interest regarding the relational context and effects of trauma (MacIntosh & Johnson, 2008). This may be especially important as, according to Monson and Fredman (2012), there is no research support for the hypothesis that individual PTSD treatment significantly contributes to resolving couple/family problems. Researchers and clinicians have also stated the importance of an understanding of the systemic effects of traumatic stress for all marriage and family therapists (MFTs), however, those in the field have only more recently started to articulate more comprehensive systemic treatments for traumatized families (Coulter, 2011; Goff & Smith, 2005; Witting, Jensen, & Brown, 2016). For systemic treatments to be considered relevant and valid, they will need to be studied in a controlled manner, and based on a research foundation that includes both individual and systemic outcomes of trauma (Galovski & Lyons, 2004). Basic research regarding couples and the impact of trauma will be necessary to provide this foundation. This literature review will contribute to the purposes of this study by first reviewing the literature related to trauma and the measured prevalence of negative posttraumatic impacts, providing some conceptual definitions of trauma. Research related to the Adverse Childhood Experiences framework will be presented followed by literature related to the impact of trauma on individuals and couple relationships, noting any current gaps in the research regarding the systemic impacts of childhood trauma. Research on trauma and partner selection will then be examined, followed by a discussion of the theoretical framework being used in this study. Finally, the research questions for this study will be presented.
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Definitions of Trauma The phenomenon of traumatic stress has been studied and observed for many years prior to the more recent focus and most prominently came to awareness following significant events such as World Wars I and II and later the Vietnam war (Eagle & Kaminer, 2014). Eagle and Kaminer note that currently, research into traumatic stress has largely been equated with research on posttraumatic stress disorder (PTSD). Defining Trauma and Traumatic Events Posttraumatic stress disorder (PTSD) is a psychiatric disorder that was first added to the American Psychiatric Association’s official classification of mental disorders in the third edition of The Diagnostic and Statistical Manual of Mental Disorders (DSM-III; American Psychiatric Association, 1980). Unlike many other disorders that do not require a specified cause, PTSD as a syndrome is based on the premise that traumatic events can cause a specific debilitating symptom set (Breslau, 2009). Traumatic events that are relevant to a diagnosable condition (such as PTSD) have been defined by the DSM-5, Criterion A (5th ed.; DSM–5; American Psychiatric Association, 2013) as “exposure to actual or threatened death, serious injury, or sexual violence,” (p. 271). The WHO defines a traumatic event here as a “stressful event or situation (either short or long lasting) of exceptionally threatening or catastrophic nature, which is likely to cause pervasive distress in almost anyone,” (WHO, 1993, p. 120). The Substance Abuse and Mental Health Services Administration (SAMHSA), uses a more broad definition, noting that “individual trauma results from an event, series of events, or set of circumstances that is experienced by an individual as physically or emotionally harmful or life 22
threatening and that has lasting adverse effects on the individual’s functioning and mental, physical, social, emotional, or spiritual well-being,” (2014, p. 7). The SAMHSA definition of trauma seems to be sufficiently broad to cover a range of problematic experiences that may be experienced as a child that lead to lasting negative effects, and is the operational definition that will be used in this paper. Posttraumatic Stress Disorder Definitions Changes to the DSM diagnostic criteria have been recent, with increasing recognition that direct exposure to a traumatic event is not always necessary (APA, 2013). There also continues to be discussions and controversies regarding what should constitute a traumatic event for the purposes of diagnosing PTSD (Weathers & Keane, 2007). These and other controversies such as the inclusion of alternative definitions and phenotypes of PTSD such as complex PTSD (CPTSD) (Herman, 2012; Resick et al., 2012), make more revisions and refinements to the diagnostic criteria seem likely (for a short history of the revisions of PTSD criteria in the DSM, see Eagle & Kaminer, 2014). Current diagnostic criteria as defined by DSM-5 include four symptom groups: (1) intrusive re-experiencing of the trauma, (2) avoidance of internal/external reminders of the trauma, (3) negative changes in thoughts/beliefs and mood, and (4) hyperarousal symptoms (APA, 2013). According to the International Classification of Diseases, Tenth Revision (ICD-10; World Health Organization [WHO], 1992), diagnostic criteria for PTSD focus on similar criteria including reliving the trauma, avoidance of similar circumstances as the trauma, and hyperarousal symptoms.
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Critiques of Definitions The definitions of trauma used in the DSM have been critiqued along a number of lines (Spitzer, First, & Wakefield, 2007). Researchers have noted that the current definitions of trauma do not address the cumulative impact of multiple traumas throughout the lifespan (Cloitre et al., 2009; Kira et al., 2008), nor the expanding research pointing to the different ways people respond to trauma (Breslau, 2009), and so to the existence of a spectrum of posttraumatic disorders (Herman, 2012). In addition, as noted above, although the current definition of what constitutes a trauma under PTSD diagnostic criteria has expanded, it still does not include a recognition that stresses of a more moderate severity (such as harassments and oppressions that do not rise to the physical threat of self) can become traumatic when repeated and prolonged over time (Kira et al., 2008). It does not include a recognition that PTSD symptoms can be prevalent in those who report experiencing non-Criterion A events as traumatic (S. D. Gold, Marx, Soler-Baillo, & Sloan, 2005). Nor does the definition recognize the significant impact of partial PTSD symptoms which can be chronic and associated with many of the lifetime negative impacts that full PTSD is associated with (Grubaugh et al., 2005; Pietrzak, Goldstein, Southwick, & Grant, 2011). Another critique of the DSM definition of trauma is that it is almost entirely focused on the individual, even as evidence has continued to accrue that interpersonal factors are crucial for an understanding of PTSD and trauma (Maercker & Hecker, 2016). Several meta-analyses which examined risk factors for PTSD, one with 77 included studies on adults (Brewin, Andrews, & Valentine, 2000) and one with 64 included studies on children and 24
adolescents (Trickey, Siddaway, Meiser-Stedman, Serpell, & Field, 2012), both found that lack of social support consistently shows moderate to large effect sizes and is one of the strongest predictors of PTSD severity. Therefore, due to these critiques, it seems reasonable to continue to address these empirical questions and to attempt to expand our understanding of traumatic stress by using broader definitions and models. Types of Trauma Recent systematic reviews of the trauma literature have examined several broad types of traumatic events, distinguishing between intentional traumas that “involve deliberate infliction of harm”, such as assault and terrorism, and non-intentional traumas such as accidents and natural disasters (Santiago et al., 2013, p. 2). This review also looked at other distinctions such as natural vs. human-generated or interpersonal traumas. Charuvastra and Cloitre (2008) in their review of the literature concluded that humangenerated trauma significantly increased the risk of developing PTSD over noninterpersonal traumas. Although traumatic events can be defined in numerous ways, for this paper, we will be focusing more on interpersonal traumas. Trauma can also be defined by when it occurs, such as adult-onset vs. child onset. Researchers (Ogle, Rubin, & Siegler, 2013) who surveyed 1,995 older adults (average age of 60) in the community found that those who report that their currently most distressing traumatic event occurred in childhood as opposed to adulthood were more likely to report higher PTSD symptoms and lower subjective happiness. Increased risk for having a severe personality disorder also seems to be related to earlier age of trauma onset (Yen, Shea, Battle, & Johnson, 2002), thus showing additional evidence that childhood trauma is more likely to exert 25
severe impacts later in life. Trauma can also be defined by amount of exposure, on a continuum from a single event exposure to repeated and connected traumas, to the cumulative impact of many different, multiple traumas throughout the lifespan (Kira, 2001; Kira et al., 2008). One broader way of defining exposure to trauma has been through a line of research regarding adverse childhood experiences (Anda et al., 2006; Dube et al., 2001, 2003; Edwards et al., 2003; Felitti et al., 1998; Gilbert et al., 2015; Kerker et al., 2015; Norman et al., 2012; Ports et al., 2016; Thompson et al., 2015). As discussed in Chapter I, researchers studying adverse childhood experiences (ACEs) have primarily looked at a number of different stressors that occur during childhood (Felitti et al., 1998), some of which would not qualify as a Criterion A traumatic event as defined in the DSM-5 (i.e., experiences that are not exposure to or threatened death, sexual violence, or serious injury, which include verbal/emotional abuse, emotional/physical neglect, parental substance use, and maternal depression) but which are hypothesized to lead to a severe stress response. The American Academy of Pediatrics labels this kind of stress response as toxic stress, or the “strong, frequent, or prolonged activation of the body’s stress response systems in the absence of the buffering protection of a supportive, adult relationship,” (Shonkoff et al., 2012, p. e236). Research has examined how early toxic stress from adversity significantly affects the neuroendocrine-immune network which then creates vulnerability to disease (S. B. Johnson et al., 2013). Researchers have asserted that the Adverse Childhood Experiences studies show evidence to support the theory that there is a connection between cumulative stressors experienced during 26
childhood, and health and relationship impacts over the lifespan (Kerker et al., 2015). However, very little has been researched regarding the relational impacts in adulthood of higher adverse experiences exposure during childhood. Because of the growing body of research that uses this methodology, examining potential systemic impacts and their associations with adverse childhood experiences exposure could be a fruitful way to compare individual and relational impacts of cumulative stress. Posttraumatic Growth Another current trend in research that challenges how traumatic stress is equated with PTSD is the research on posttraumatic growth (PTG) (Tedeschi & Calhoun, 2004). Posttraumatic growth is defined as positive, as opposed to negative, individual psychological changes as a result of struggling with severe and stressful life experiences (Tedeschi & Calhoun, 2004). Tedeschi and Calhoun’s PTG model attempts to comprehensively explain how pre-trauma characteristics, stressor characteristics, social context, and individual cognitive/emotional processes can interact to lead to PTG in the individual. Relevant to the systemic focus of the current study, researchers (Berger & Weiss, 2009) have also started to articulate systemic models of PTG that account for changes in the family system following trauma. Although this research is important and should be recognized as adding to the literature on the impact of traumatic and stressful experiences on individuals/families, this present study will not focus on the PTG model. Expanding how to define the significant impacts of trauma exposure seems to be an important prerequisite towards accurately identifying impacts of trauma on couple relationships. Using only DSM-5 definitions of PTSD may underestimate the impacts on 27
relationships where adverse events occur (but not PTSD-criterion events). However using the broad category of self-defined trauma exposure may include people who were not significantly negatively impacted (e.g., Goff, Reisbig, & Bole, 2006). This dilemma is discussed later and shown through looking at the prevalence literature regarding PTSD. Prevalence Estimates of lifetime prevalence of exposure to traumatic events vary significantly ranging from 43% to 92% depending on the studies examined (Breslau, 2009). A recent internet-based research survey of a sample of U.S. adults (n = 2,953; consisting of 75% White, 12% Black, and 83% Non-Hispanic), which was based on DSM-5 PTSD criteria, estimated life-time traumatic event exposure in the U.S. to be 89.7% (Kilpatrick et al., 2013). In addition, although exposure to traumatic events according to this is very common, the same study estimated lifetime prevalence of PTSD at 8.3%, and past 12month prevalence of PTSD at 4.7%, indicating that only a minority of the people who experience traumatic events will meet criteria for PTSD. A recent meta-analysis of 72 peer-reviewed articles (n = 3,563) identified through a systematic literature search regarding PTSD prevalence in trauma-exposed children and adolescents showed rates of PTSD at 15.9% (Alisic et al., 2014). In addition, a recent, large, national study done in the U.S. and using a representative sample of adults (n = 34,653), found rates of lifetime prevalence for partial PTSD were similar to lifetime prevalence rates for full PTSD (Pietrzak et al., 2011). This study, which oversampled for Blacks, Hispanics, and young adults (age 18-24), and involved face-to-face interviews, utilized a computerized,
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structured instrument to assess for PTSD diagnosis (AUDADIS-IV; Grant, Dawson, & Hasin, 2004). A review of epidemiologic studies of PTSD indicated that there seems to be a higher lifetime prevalence of PTSD in women (13.0% or about 1 in 8) than men (6.2% or about 1 in 16)(Breslau, 2009). This finding was found despite similar levels of lifetime trauma exposure in women (87.1%) and men (92.2%). Regarding children and adolescents, there seems to be a gender gap as well, with trauma exposed boys much less likely to have PTSD (11.1%) than trauma exposed girls (20.8%) (Alisic et al., 2014). Twelve month PTSD prevalence also gives another view of the impact of disorders. A recent, large multinational survey covering 20 countries, with a sample size of 51,295, was done by the World Health Organization (Karam et al., 2014). Surveys were sent to countries classified as high income, upper-middle income, and low/lowermiddle income, and were distributed based on area probability household samples representative of each country. The study found a total-sample 12-month PTSD prevalence rate of 1.1%, and 2.5% prevalence for the United States (Karam et al., 2014). Of note in this study, the sample was surveyed for lifetime exposure to 29 types of traumatic events broken down into seven broad categories (war related, physical violence, sexual violence, accidents, death, witnessing, and other). One other notable finding in this study relates to the impact of cumulative trauma, in that 19.8% of those with 12-month PTSD reported symptoms associated with four or more traumatic event types. These individuals with four or more traumatic event types were found to have
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significantly greater functional impairment as compared to those who had exposure to fewer traumatic event types. A recent systematic review of the longitudinal prevalence literature indicates that overall, there is significant variability in PTSD rates when looking across the many different populations, types of trauma, and contexts where it occurs (Santiago et al., 2013). This review, which looked at published studies between 1998 and 2010 regarding trauma exposed populations, identified 58 out of 2,537 articles that met inclusion criteria and included trauma exposures of motor vehicle/plane crash, assault, terrorism, war as a combatant or civilian, natural disaster, severe injury, and serious, life-threatening medical condition. This review, which focused on studies that met the DSM-5 criteria for PTSD and measured the same sample two or more times, estimated that the median prevalence of PTSD one-month post-trauma is 28.8% (range 3.1-87.5%) decreasing to 17% twelvemonths post-trauma. This indicates that prevalence rates seem to be impacted by when posttraumatic symptoms are assessed. Some support for separating out intentional traumas from non-intentional traumas was shown in the findings of this review. When specifically delineated, PTSD prevalence rates for individuals exposed to intentional traumatic events actually reversed the general trend of decreasing symptoms over time, going from 11.8% PTSD one-month post-trauma to 23.3% PTSD twelve-months posttrauma. Also in the previously mentioned study on trauma exposed children and adolescents, researchers found that when broken down by type of trauma, the rate of PTSD was 25.2% from interpersonal traumas as compared to 9.7% from noninterpersonal traumas (Alisic et al., 2014). Furthermore, there is some evidence that 30
cumulative interpersonal trauma exposures are even more predictive of PTSD (Briere, Agee, & Dietrich, 2016). Researchers studied 490 individuals from a general population sample (54.3% Male, average age of 46.8, and 84% Caucasian, 5.7% Black/African American, 3.3% Hispanic, 3.1% Asian, and 2.7% Native American). They found that cumulative interpersonal trauma (operationalized in this study as the number of types of trauma experienced including threatened assaults, physical assaults, sexual assaults, childhood sexual abuse, having been shot or stabbed, having been robbed or mugged, and combat) was significantly predictive of PTSD status, whereas cumulative noninterpersonal trauma (including trauma types of motor vehicle accidents, natural disasters, and accidents at work or home) were not. Their results also indicated that those in this study that reported only one type of trauma exposure had a zero percent chance of current PTSD versus a 12% chance for those with six or more types of trauma exposure. The researchers concluded that this provides evidence that PTSD may need to be reconceptualized as resulting more from the “impacts of multiple psychological injuries” as opposed to single traumatic events, and especially from interpersonal traumas (Briere et al., 2016, p. 444). These data on the apparently more severe impacts of interpersonal trauma point to the need to better understand the relational impacts of this kind of trauma. The prevalence data listed above and other recent studies (e.g., Cloitre, Garvert, Brewin, Bryant, & Maercker, 2013) provide some evidence that there are several ways of grouping individuals related to impacts of trauma exposure. Groups could include individuals with trauma exposure but no lasting posttraumatic symptoms (would not be diagnosed with PTSD), those with trauma exposure but not chronic PTSD, and those with 31
trauma exposure who have chronic PTSD symptoms (perhaps more likely to be individuals with cumulative trauma or complex PTSD). The research on adverse childhood experiences provides additional information on those that might be included in this later group, those who had significant trauma exposure as children and have been impacted throughout their lifespan due to the exposure. Adverse Childhood Experiences and Impact of Childhood Trauma on Adults As noted above, an important line of research using one particular measure of childhood trauma or cumulative stress, the Adverse Childhood Experiences (ACE) studies, has provided some key evidence about the link between early trauma exposure and later physical and mental health outcomes in adults (Dube et al., 2001, 2003; Dube, Williamson, Thompson, Felitti, & Anda, 2004; Edwards et al., 2003; Felitti et al., 1998; Font & Maguire-Jack, 2016; Gilbert et al., 2015; Mersky et al., 2013; Norman et al., 2012; Rebbe et al., 2017). The seminal studies in this area and subsequent research have presented compelling evidence regarding the significant impact of childhood trauma exposure that is now gaining attention as a public health concern (Campbell et al., 2016). Original ACE Study The first ACE study (Felitti et al., 1998) was a large retrospective survey of adults who had previously completed standardized medical evaluations at Kaiser Permanente in San Diego. The purpose of the study was to examine potential connections between negative health outcomes and behaviors and childhood exposure to adverse events. In Wave 1 of the study for which this first article was written, 13,494 adults were mailed the ACE Study questionnaire, and 9,508 responded to the survey (70% response rate). The 32
final sample after exclusions was 8,056. Fifty-two percent of the sample were women, with a sample average age of 56, a high percentage of college graduates (43%), and consisting mostly of people who identified as White (79%), with approximately 4% as Black, 5% as Hispanic, 6% as Asian, and 4% as Other. All subjects who were mailed the survey had already undergone the standardized medical evaluation that included demographic and biopsychosocial information, individual and family medical history, and medical diagnoses. They were also asked questions regarding health behaviors and problems including smoking, physical activity, depression, and history of attempted suicide. The original ACE Study questionnaire was constructed for this study using content from previously published surveys and included seven different categories of adverse childhood experiences: emotional abuse, physical abuse, sexual abuse, violence against mother, and living with household members who had substance abuse, mental illness, or criminal behavior. Several categories had multiple questions, and the questions were binary, asking if those experiences had either happened or not (yes/no). For each category with at least one yes answer to a question the score would be increased by one (total score ranged from 0, no exposures, to 7, exposed to all categories). Descriptive results indicated that reported exposure to these adverse experiences was significant, with 52% of the sample reporting experiencing at least one category of exposure, and 6% reporting 4 or more (Felitti et al., 1998). The researchers used logistic regression analysis, accounting for differences in age, sex, race, and education to examine the association between the amount of childhood exposures and the different risk factors or health problems. They found that the more categories of childhood exposures that 33
were reported, the higher the prevalence of health risk factors of smoking, obesity, depression, suicide attempts, and low physical activity. They also found evidence for a significant dose-response relationship between the amount of exposure and a number of negative physical health outcomes including heart disease, cancer, emphysema, and low self-rated health (meaning, with each additional exposure, the risk of the negative health outcomes increases). Finding a dose-response relationship provides additional evidence for the assertion that repeated and varied exposure to negative events in childhood increases risk to a wider range of problems and to more severe problems. The study also provided evidence to support the assertion that risk for negative physical and mental health outcomes increased even with only one ACE being reported (e.g. the odds of having two weeks or more of depressed mood in the past year increased by 50% for those reporting 1 ACE compared with 0 ACEs). The study could be critiqued on the basis of having a less diverse sample, especially with regard to race/ethnicity and SES. The second wave of the same study was reported by Dube et al. (2001), which reported mostly regarding the relationship between amount of exposure to ACEs and risk for suicide. They used essentially the same methodology aside from adding a question related to parental separation/divorce. The sample in the second wave was 8,629, though the waves were combined for the analysis into 17,337 (95% of respondents) and had similar demographics reported for the combined total as in Wave 1 (54% female, average age of 57, and 75% with at least some college education). Sixty-four percent of the combined sample noted that they had experienced at least 1 ACE, and 3.8% of the sample reported having ever attempted suicide. The researchers used several logistic regression 34
models to examine, by category of exposure, the likelihood of attempting suicide. Results from the adjusted odds ratios indicated that the increased risk for having attempted suicide ranged anywhere from 2 to 5 times higher for exposure to different categories of ACEs (e.g., 5 times higher risk for those reporting exposure to emotional abuse). The dose-response relationship (here called a graded relationship) was also found indicating that the higher the reported ACE score, the greater likelihood of attempted suicide (from 2.3 times increased risk of adult suicide attempt for an ACE score of 1 compared to 0, up to 29.8 times increased risk for an ACE score of ≥7). Another finding supporting a graded relationship (where increased exposure is associated with increased risk) was that for every one point increase in reported ACE score the risk of suicide attempts increased by approximately 60% (Dube et al., 2001). Follow-up ACE Studies One way in which these studies have been critiqued is that measuring trauma exposure by simply counting up the types of adverse events may be too simplistic, precluding a more accurate idea of how frequent or repeated these events were (ScottStorey, 2011). In addition, it also treats all of these early childhood experiences essentially equally even though evidence seems to point to some types of adverse experiences, especially maltreatment as being more severe (Scott-Storey, 2011), and that more severe childhood traumas seem to be associated with more maladjustment and symptoms as an adult (Evans, Steel, & DiLillo, 2013). One recent ACE study (Font & Maguire-Jack, 2016) attempted to look at whether the type of ACE experienced was related to differing health risks as an adult. 35
Font and Maguire-Jack (2016) analyzed data taken from a large, multi-state retrospective survey done in the United States in 2012, based on the Behavioral Risk Factor Surveillance System (BRFSS), and done in collaboration with Centers for Disease Control and Prevention. The BRFSS is a telephone health survey done by random digit dial. In 2012, even though all states in the USA participated in the surveying, only five states included the ACEs questions in their surveys (Iowa, North Carolina, Wisconsin, Tennessee, and Oklahoma). The total number of completed surveys that included the ACE questions was 29,229. The sample consisted of approximately 51% male, sample average age of 48, 62% married or widowed, and 25% of the sample having a college degree. Eighty-one percent of the sample identified as White, 12% as Black, 5% as Hispanic, and 3% as Other race. In addition to the ACE questions that were measured, five health risks were included in the survey, which included responses to (1) ever been diagnosed with depression, (2) being a current tobacco user, (3) having one or more binge drinking episodes in the last month, (4) being obese (BMI >30), and (5) reporting suboptimal health (fair or poor). The surveys also assessed for a number of socioeconomic factors, which were used in this analysis to evaluate the presence of potential mediators between ACEs and health risks (including income, education, marital status, and health insurance status). After controlling for demographic characteristics, the researchers used structural equation modeling to estimate the size of direct and indirect effects of different levels of ACE scores (0, 1, 2-3, and 4+ ACEs) on these health risks. They obtained significantly similar results to past studies showing, in general, a dose-response relationship with increasing numbers of ACEs predicting higher probability of these 36
health risks. The main findings regarding the different types of ACEs and their relative impacts, included which types had direct vs. indirect associations with specific outcomes. Physical or emotional abuse, living with a person with mental illness or alcohol/drug abuse, and sexual abuse were all directly associated with depression (with 6.9, 9.8, and 14.9 percentage point increases in probabilities for depression respectively). Sexual abuse, living with a person with mental illness or alcohol/drug abuse, divorce or separation, and living with past incarcerated individual were all directly associated with tobacco use (with 3.9, 4.2, 6.0, and 9.3 percentage point increases in probabilities respectively). Living with a person with mental illness or alcohol/drug abuse and sexual abuse were directly associated with obesity (with 2.7 and 5.6 percentage point increases in probabilities respectively). Living with a person with mental illness or alcohol/drug abuse and physical or emotional abuse were directly associated with binge drinking (with 1.7 and 2.5 percentage point increases in probabilities respectively). According to these results, ACEs reflecting childhood maltreatment and having lived with a person with mental illness or alcohol/drug abuse seemed to be the most impactful on health risks. Chartier, Walker, and Naimark (2010) also found that when separated from the effects of other ACEs, although statistical relationships were attenuated, childhood abuse still seemed to have direct impacts on the development of poor health outcomes. This study also addressed another gap in these research studies, that of accounting for some other potential explanations for the correlation between early childhood adverse experiences and later outcomes. The researchers first looked at how ACEs impact socioeconomic (SES) factors, such as education level, income level, and marital status, 37
and then to what degree do these SES factors mediate the ACE-health risk relationship (Font & Maguire-Jack, 2016). They noted a similar dose-response relationship in that as ACE scores rose, there was an increased likelihood of being a high school dropout, not having a college degree, having lower income, having been divorced or separated, and not having been married later on. They reported that a small but statistically significant portion of the added risk of a depression diagnosis from ACEs scores could be accounted for by education, income, marital status, and health insurance status (8%, 11%, and 12% for 1, 2–3, and 4+ ACEs respectively). Similar results were found regarding the impact on being obese. They also reported a somewhat stronger mediation of SES factors on the relationship between ACE scores and tobacco use (between 18–27%). Most importantly, because only a small amount of the associations between abuse (sexual, physical and emotional) and health risks can be explained in their model by SES factors, this provides some evidence that being abused as a child has significant direct impacts on both health risks and SES as an adult (Font & Maguire-Jack, 2016). One important limitation of the above studies relates to the samples which tend to be more educated and less ethnically diverse in composition and therefore less generalizable. Mersky, Topitzes, and Reynolds (2013) examined ACE impacts on various outcomes in an urban, young adult, minority sample to address these limitations. The data for the study came from the Chicago Longitudinal Study (CLS) which tracked a cohort of minority, underprivileged children born into an urban setting, starting from kindergarten. This study included an analysis of those participants who completed a survey between the ages of 22 and 24 (2002-2004). The data sample was 1,129 (73% of 38
the full sample, which was 93% African American and 7% Hispanic), and was 55% female. The data was collected through a combination of mail, telephone, and in-person surveys to reduce non-response rates. ACE scores were calculated uniquely in this study through use of a combination of survey items and existing records such as Child Protective Service (CPS) records for the families. ACE variables measured in this study include CPS record of reported abuse/neglect, and self-reported answers in the Life Events Checklist (LEC; Johnson & McCutcheon, 1980) completed as noted from ages 22-24. Answers from the LEC were counted as an ACE only if they were reported to have experienced the event from ages 0-15. The ACE variables corresponding to the LEC items were: (1) having been a victim or witness of violent crime, (2) parental substance abuse, (3) parental extended absence, (4) parental divorce, (5) death of relative or friend, (6) frequent family conflict, and (7) family financial problems. It should be noted that these are a different set of ACE variables than those previously described (Dube et al., 2001; Felitti et al., 1998; Font & Maguire-Jack, 2016). This list includes being a victim of crime violence, death of a close person, and family financial issues which do not seem to be covered by the ACE questionnaire. The list does not seem to include items specifically aimed at measuring living with a family member who has criminal behavior or mental illness, violence against their mother, or distinguishing out additive effects of emotional, physical, and sexual abuse, presumably those being measured by CPS records, but not being counted as separate ACEs as they are in the other studies cited. As in previous studies, the dichotomous ACE variables were summed to create a cumulative ACE score. The outcome variables measured in this study were 39
taken from survey Likert-scale questions which asked about overall health, overall life satisfaction, and frequency of depressive symptoms, anxiety symptoms, tobacco use, alcohol use, and marijuana use (Mersky et al., 2013). In this sample of urban minority young adults, about 80% had an ACE score of at least one, and 49% with an ACE score greater than one (Mersky et al., 2013). In this sample, males had higher average ACE scores than females (2.2 vs. 1.4 respectively) and a higher percentage of males had higher ACE scores than did females (12% of males and 5% of females with an ACE score of 5 or more). The study used multivariate logistic regression to examine relationships between ACE scores and the dichotomous health, mental health, and substance use outcomes. When compared with those with an ACE score of 0, those with multiple ACEs (grouped into 2 ACEs, 3-4 ACEs, and 5 or more ACEs) reported significantly lower overall health and life satisfaction, and were more likely to report frequent depressive symptoms, frequent anxiety, frequent tobacco use, and frequent marijuana use. Those with an ACE score of 5 or more were the only group to differ significantly from those with an ACE score of 0 on frequent alcohol use. In general, the results showed a graded relationship between increasing ACE scores and poorer outcomes. However, the evidence was not as compelling as other studies and there were some exceptions, such as the 2 ACEs group having poorer outcomes than the 3-4 ACEs group specifically on overall health and frequent anxiety, and the 1 ACEs group never significantly differing from the 0 ACEs group (Mersky et al., 2013). The study also did not analyze any other cross-group comparisons other than the comparisons to 0 ACEs, so there was not enough evidence to show that each additional ACEs group 40
was significantly different from the one before it on these outcomes. Despite this, the study results do seem to show evidence of the strong negative impact of cumulative adversity during childhood on physical health, mental health, and risk behaviors, showing this impact is present for young adults, and still applicable to urban minority populations (Mersky et al., 2013). This outcome was also shown despite the somewhat different measuring of ACE items, showing that it is likely that current measurements of ACEs will likely need to continue to be refined to increase validity. It should be noted that within the ACE literature, it seems relatively common for studies to use a number of different measures and to extrapolate survey answers to fit ACE categories, however not using the actual wording or items from the ACE questionnaire. This practice, although one way to use existing surveys and on-going studies, may limit comparisons to the original ACE studies and those that use the same measures. Critiques of ACE Study Methodology A primary critique of the methodology of these ACE studies centers on them being retrospective studies that rely on self-report measures completed by adults with regard to their childhoods and so are subject to possible recall bias and potential reliability/validity problems as a result (Norman et al., 2012; Widom, Raphael, & DuMont, 2004). Methodologically speaking, researchers often view retrospective findings as less conclusive due to less researcher controls and not being able to show the same cause-before-effect ordering that gives more evidence to causal inferences (Kendall-Tackett & Becker-Blease, 2004; Norman et al., 2012). Although prospective longitudinal research may be very important for the research in this field (Pacella, 41
Hruska, & Delahanty, 2013; Thompson et al., 2015; Widom et al., 2004), it is important to know whether these retrospective reports can be relied upon for reasonably accurate and reliable results. Fortunately some studies have been done with regard to these issues. Regarding the issue of recall bias and validity, a recent study by Reuben and others (2016) in New Zealand of 1,037 adults used both retrospective and prospective measurements of ACEs and objective and subjective measurements of physical, mental, cognitive, and social health. This study was unique in that it also measured personality in order to examine the likelihood that certain personality factors may bias responses to the study variables. The researchers found that prospective ACE records generally confirmed the studied associations found between ACEs and negative health and life outcomes that were previously found in retrospective studies. They found some evidence that the ACEs-negative life outcomes association may be influenced by personality and those who overreported (comparing prospective records with retrospective reports) tended to have more neurotic personality traits and those who underreported tended to have more agreeable personality traits (Reuben et al., 2016). Hardt and Rutter (2004), completed a review of 56 studies, published between 1980 and 2001, that evaluated the validity of retrospective reports of childhood adverse events by also looking at corroborating, prospectively obtained evidence relating to those same events. Corroborating evidence included official records (clinical records, court documents, and child protective services records) as well as collaborative reports by siblings and contemporaneous parental reports. The researchers in their review noted several important implications of the then current state of the research. They noted that the 42
evidence seemed to show that retrospective reports may be likely to show bias, but more in the direction of underreporting as opposed to overreporting. These researchers estimated that up to a third of the adults in these studies reviewed will not report abuse having happened when asked specifically about it, despite that abuse being welldocumented. They concluded that there is little evidence to support the theory that there is a large amount of overreporting (false positives) in these studies, and that available evidence suggests that positive reports of abuse or neglect are likely to be valid especially where the variables of question are well operationalized. They also conclude that although positive reports of abuse occurring are likely to be valid, there is not corresponding evidence to suggest that detailed accounts of these events or reports of more subjective experiences are similarly valid (Hardt & Rutter, 2004). In addition, in a commentary on the relative importance of prospective and retrospective studies in the childhood maltreatment research, authors indicated that there may be non-overlapping populations between these types of studies, each catching different groups, and that even with the large amounts of underreporting with retrospective studies, there seems to be even higher amounts of underreporting with prospective studies which might miss even more cases (Kendall-Tackett & Becker-Blease, 2004). Finally, a recent study was done by Hardt, Vellaisamy, and Schoon (2010), which compared the strength of associations of childhood adversities and long-term psychological adjustment between a retrospective study (Mainz Adverse Childhood Experiences Study; N = 1,062) and a longitudinal study (the British National Child Development Study; N = 7,710). No significant differences were found between the two studies and their outcomes related to patterns of the impact 43
of childhood adversities on long-term psychological adjustment. This suggests that bias in retrospective studies of ACEs may be minimal and not enough to significantly alter the overall results. Regarding the issue of reliability, one study of reliability related to reporting of ACEs was completed by Dube, Williamson, Thompson, Felitti, and Anda (2004), that looked at test-retest reliability of retrospective reports of ACEs and was an analysis of data from Wave I and II of the original ACE study (Dube et al., 2001; Felitti et al., 1998). Due to an error, some study participants were inadvertently sent study material in both waves, and 658 participants completed both packets about 20 months apart. The researchers found moderate to substantial agreement between the ACE scores at both times, showing stability in reporting of these ACEs over time (Dube et al., 2004). In a study that used structured interviews to measure adverse childhood experiences at two points in time (an average time of 2.2 years apart), in a sample of 100 adults in Germany (76% female, average age of 40), they also found moderate to good reliability for reports of childhood divorce, sexual and physical abuse (Hardt, Sidor, Bracko, & Egle, 2006). In another study of 79 young adults from Northern Portugal with documented childhood abuse/neglect (CPS records), and using the 10-item ACE Study Questionnaire, researchers found good to excellent agreement of reports of ACEs when measured 6 months apart (Pinto, Correia, & Maia, 2014). Importantly, they also found no significant relationship between changes in self-reported ACEs and changes in symptoms over time, suggesting that reports of ACEs are not likely to be directly connected to the current health of the participants. This result was also confirmed by Edwards and others (2001) 44
who analyzed reports of childhood sexual abuse and found no evidence to support the assertion that the participants attributed current health problems to their negative experiences in childhood. In conclusion, although there seems to be some issues related to retrospective reports, available evidence does seem to suggest adequate reliability and validity of these retrospective ACE reports (Kendall-Tackett & Becker-Blease, 2004). Summary In summary, it is important to note the significant findings from these ACE studies and related research. First, all of these studies, from the original ACE studies and continuing with studies since, have shown compelling evidence of long-term negative physical health, mental health, and health-risk outcomes as a result of ACEs. The research results indicating negative long-term effects also consistently show a strong, graded relationship, such that there appears to be a cumulative impact of more childhood adversity and trauma on increasingly severe outcomes. Second, as noted previously, when examined, these studies seem to show adequate reliability and validity. Studies have been done on minority populations (Mersky et al., 2013) and have also been completed in other parts of the world, such as eastern European countries (Bellis et al., 2014) and poor, urban communities in a developing country (Ramiro, Madrid, & Brown, 2010), and have found the same general outcomes as the original ACE studies. Several researchers (Anda et al., 2006; Norman et al., 2012; Shonkoff et al., 2012) in reviewing the research and using separate models regarding the evidence suggesting causality, even make the argument that enough evidence exists to suggest a causal association between having experienced different forms of childhood adversity and long-term health 45
consequences as an adult. These studies importantly show how even long after childhood, the effects of early childhood adversity can be strong. However, as to the relationship of these ACE studies to this current study regarding the relational outcomes of childhood trauma, Gilbert and others (2015) was the only study out of these identified for this research review that measured a relational outcome, noting an increased likelihood of frequent marital distress as ACE scores increased. One clear gap in the research with ACE studies is in examining whether there are significant relational outcomes of ACEs. Posttraumatic Stress Impact on Individuals and Couples ACEs and Risk for PTSD As research has yet to be done regarding ACEs and couple relationship outcomes, current research on the impacts of PTSD on individuals and couples can be used to show evidence to support the link between trauma and important outcomes. However, before examining that evidence, research related to the link between childhood trauma/adversity and PTSD needs to be presented. ACE research has confirmed long-term general mental health impacts of early adversity and trauma (Dube et al., 2001; Felitti et al., 1998; Font & Maguire-Jack, 2016; Mersky et al., 2013). Norman et al. (2012), in a systematic review and meta-analysis of 124 studies looking at the long-term consequences of childhood physical abuse, emotional abuse, and neglect (all relational traumas), found significant associations between these forms of abuse and an increased risk for all kinds of mental disorders, problematic drug use, and suicide attempts. Although the evidence only rests on a few studies and so is not strong or conclusive as of yet, there are ACE 46
studies that show evidence moving beyond these general mental health outcomes to suggest specific impacts of higher amounts of ACEs on increased risk for PTSD symptoms (Brockie et al., 2015; Cabrera et al., 2007; Rebbe et al., 2017). In Rebbe and others (2017), in a study of 732 young adults aging out of foster care (52% female, 56% Black, 29% White, 8% Hispanic, 5% Mixed, and 2% Other Race), they used latent class analysis to distinguish between three different groups, those with higher ACEs relating mostly to home environment (Complex), those with ACEs relating more to environmental based harms (Environmental), and those with lower amounts of overall adversity (Lower). Both the Complex and Environmental groups with higher ACEs had much higher rates of PTSD symptoms when compared to the Lower adversity group (note that in this study PTSD symptoms were assessed through interviews but no cutoff point or diagnosis per se was established). This same overall trend was found by Brockie and others (2015) in their study of reservation-based Native American adolescents and young adults (N = 288; 15-24 years old; 51% female). Six ACEs were measured in this study intending to match those from the original ACE study (Felitti et al., 1998), including physical abuse, emotional abuse, sexual abuse, emotional neglect, physical neglect, and witnessing violence against mother. Five of these (all but violence against mother) were measured using subscales from the Childhood Trauma Questionnaire (CTQ; Bernstein & Fink, 1998). In this study two additional ACEs were measured including historical loss associated symptoms and discrimination. PTSD was assessed in this study using the Short Screening Scale for DSM-IV PTSD (Breslau, Peterson, Kessler, & Schultz, 1999) which is a 7-item survey that has shown high 47
concordance with diagnoses of PTSD from structured interviews. Using a sample of 1,830 community members, researchers indicated that a cutoff score of 4 on the scale led to a sensitivity of 80.3% and a specificity of 97.3%, and as noted by the authors, can be used to predict probable lifetime PTSD. The study used a logistic regression analysis to calculate adjusted odds ratios, estimating the relationship between ACE scores and likelihood of PTSD, after controlling for the effects of age, gender, and school attendance (Brockie et al., 2015). Participants with high ACE scores (3-6) had more than three times the odds of having PTSD than those with lower ACE scores, and each additional ACE increased the odds of having PTSD by 55%. This study provides evidence to support the connection between ACEs and added risk for PTSD, especially in younger adult populations. A study by Cabrera, Hoge, Bliese, Castro, and Messer (2007) provides some more evidence of a connection between ACEs and PTSD, this time in an older military sample. Cabrera and others (2007) studied childhood adversity and PTSD in male soldiers before and after deployment to combat overseas (N = 6,921; 69% White, 38% Married). Amount of exposure to ACEs in this sample was similar to that of previous studies which sampled civilian populations (Dube et al., 2001; Felitti et al., 1998). They measured childhood adversity using a modified version of the ACE questionnaire (Felitti et al., 1998) that asked about exposure to 1) a mentally ill person in the home, 2) alcoholic adult in the home, 3) sexual abuse, 4) physical abuse, 5) psychological abuse, and 6) violence against their mother. PTSD in this study was assessed using the PostTraumatic Stress Disorder Checklist (PCL; Weathers, Litz, Herman, Huska, & Keane, 48
1993) which is used as a screening tool for assessing presence and severity of posttrauma symptoms. The PCL has shown very high correlations with clinician ratings of PTSD symptoms (Blanchard, 1996), and high internal consistency and test-retest reliability (Pratt, Brief, & Keane, 2006). Logistic regression analyses showed a dose response relationship between ACEs and having a probable PTSD diagnosis both for the pre-deployment and post-deployment groups. For example, odds ratios for the predeployment group for increased likelihood of probable PTSD was 1.38 for one ACE, 1.93 for two ACEs, 3.90 for three ACEs, and 5.47 for four or more ACEs (all compared with those reporting zero ACEs). One other important finding in this study was that interaction analyses of ACEs and combat exposure as predictors of severity of PTSD (PCL scores) showed that although combat exposure predicted increased severity of symptoms, higher ACE scores predicted higher PTSD symptoms even after accounting for combat exposure. This study seems to show that ACEs have an impact on higher adult likelihood for PTSD and more severe symptoms even when adult trauma is present (Cabrera et al., 2007). It is possible then that ACEs create long-lasting vulnerabilities in adult mental health which can impact later outcomes. This hypothesis also seems to be supported by research into the neuroendocrine effects of early life stress (Yehuda et al., 2010). Impacts of PTSD on General Individual Outcomes As noted before, although not without methodological issues, PTSD does seem to be one measure of the significant impact of trauma on the individual, and in turn research on PTSD and its impacts is one area that is growing (Vermetten & Lanius, 2012). 49
Vermetten and Lanius (2012) in their review of PTSD research note that over 15,000 scientific papers on PTSD have been published in the last 40 years alone, representing a significant increase in our understanding of the disorder. In Kessler (2000) review of published reports on PTSD in the general population, the author noted that the literature supports the conclusion that individual impairment associated with PTSD is equivalent to, or greater than that of other serious mental disorders. The author also notes that evidence suggests that most people with PTSD do not get treated for the disorder (Kessler, 2000). This combined with evidence that childhood abuse is often not able to be reported until far after childhood (Hardt & Rutter, 2004), gives further rationale for studying trauma in adults. A recent, large, nationally representative sample from the U.S. indicated that PTSD was associated with increased rates of comorbidity with mood, anxiety, and substance use disorders, and suicide attempts (Pietrzak et al., 2011). Due to the sometimes severe and wide-spread impacts of posttraumatic stress on individuals, it seems to follow that this would likely translate to impacts on the relationships of the traumatized individuals. Impacts of PTSD on General Couple Relationship Outcomes Even though the research is not as extensive as for PTSD and impacts on the individual, there is an accumulation of evidence of an association between PTSD and relationship difficulties (Kessler et al., 1998; Lambert et al., 2012; A. B. Miller et al., 2013; Monson et al., 2009; D. S. Riggs, 2014; D. S. Riggs et al., 1998). Monson and others (2009) in their review of recent research on military PTSD and its reciprocal effects with couple relationships, note that there is a “well-established association 50
between [PTSD] and relationship problems,” (p. 708). They point to research that indicates associations between PTSD and higher rates of divorce, problems with intimacy, relationship dissatisfaction, worse family adjustment, and intimate partner aggression. Some of the studies that highlight these associations are discussed below. Research has shown that there is a link between PTSD and relationship distress (Taft et al., 2011). Taft and colleauges conducted a meta-analysis of 31 studies meeting inclusion criteria (out of 74 initially identified studies), all of which investigated the association between PTSD and relationship problems. Studies were excluded for not being quantitative, using too broad of a family functioning variable, and not using PTSD symptom severity or diagnosis (instead using reported trauma exposure alone). Of the 31 studies coded and analyzed, 19 were of military samples vs. 12 of civilian samples, and separately categorized, 18 had community samples, 9 had clinical samples, and 4 had mixed samples (total sample size of 7,973). Results of the estimation of effect sizes across the studies showed moderate magnitude relationships between PTSD and intimate relationship discord, physical aggression, and psychological aggression. Another metaanalysis by Lambert and others (2012) looked specifically at studies that measured relationship quality, and included 22 studies published between 1992 and 2012. A random effects analysis of the combined studies showed a small to moderate relationship between PTSD and relationship quality. The researchers also noted that effect sizes were larger for studies of military samples than they were for studies of civilian samples (Lambert et al., 2012). These meta-analyses of the studies to-date show an accumulation
51
of evidence regarding the negative impact of PTSD on relationship quality, other relationship problems, and relationship distress. Other individual studies have also borne this connection out, showing impacts on relationship stability and outcomes as well as relationship distress. For example, Kessler and others (1998) studied the relative impact of having different mental disorders prior to marriage on later marital stability. The data came from structured diagnostic interviews with a probability subsample (N = 5,877) of participants from the National Comorbidity Survey (a nationally representative population survey) that obtained age of onset of 14 different DSM disorders, as well as marriage and divorce dates. The data was used to create a model to estimate the relationship between these prior-to-marriage disorders and subsequent divorce. While mental disorders in general were associated with increased odds of divorce in this study, PTSD (odds ratio of 1.6) ranked in the top 4 of 14 disorders studied in terms of relative risk (range of odds ratios: 1.1-3.3), and similar to mood disorders (odds ratio of 1.7). Other research has shown similar relationship problems in military samples. In one of the earliest studies on PTSD and relationships, Riggs, Byrne, Weathers, and Litz (1998) studied differences in relationship outcomes between couples where Vietnam veterans had PTSD vs. couples where the veteran did not have PTSD (50 total couples; 90% White, 95% high school graduates). Couples in this study were recruited through a Veterans Affairs Medical Center, and had all been together for at least 1 year. PTSD was measured through the PCL self-report questionnaire, and based on DSM-IV criteria. Various self-report surveys were used to measure relationship problems and outcomes 52
including the 32-item Dyadic Adjustment Scale (DAS; Spanier, 1976) which is a measure of relationship satisfaction and distress, the Marital Status Inventory (MSI; Weiss & Cerreto, 1980) which is a measure of the likelihood of separation and divorce, and the Relationship Problems Scale (RPS; Riggs, 1993) which is a measure of relationship problem severity. The study used several stages of analyses (chi-square tests, ANOVAs, and correlation/regression analyses). The PTSD couples (N = 26; mean PCL = 58.7) were more likely than the non-PTSD couples (N = 24; mean PCL = 10.8) to have clinical levels of relationship distress as a binary outcome (75% vs. 32%), and severity of distress was correlated with severity of PTSD symptoms. In addition, in comparison to the nonPTSD couples, the PTSD couples reported significantly more difficulties with intimacy and with problems in their relationships, and had taken more steps towards relationship dissolution. In follow-up analyses of the same sample (D. S. Riggs, 2014), the author notes that in addition to 52% of veterans from the total sample of couples reporting symptoms consistent with a PTSD diagnosis, 28% of the partners also reported symptoms consistent with a PTSD diagnosis, all of which noted having at least one traumatic event other than relationship violence. In this analysis, marital satisfaction was found to be significantly negatively correlated with both husband and wife PTSD symptom severity (r = -.54 and -.29 respectively). This result shows the added complexity with regard to relationship outcomes when both partners in a couple have trauma histories. Another important study that has looked at PTSD and couple outcomes provides some evidence of the interaction between adulthood trauma and childhood trauma. Miller and others (2013) studied a military veteran sample of 218 members of the 53
National Guard/Reserve who had been deployed overseas. The sample was a convenience sample of volunteers recruited from marital relationship workshops and were all married, 98% male, 91% White, and 7% Hispanic. The participants completed self-report measures relating to their degree of combat exposure, having had childhood sexual abuse (CSA), PTSD symptom severity, and marital satisfaction. Severity of combat exposure was measured by several subscales of the Deployment Risk and Resilience Inventory (DRRI; King, King, Vogt, Knight, & Samper, 2006) that assess exposure to various combat activities and experiences. CSA was assessed using several responses from the Life Events subscale of the DRRI, which includes one set of questions asking whether participants had experienced “unwanted sexual activity as a result of force, threat of harm, or manipulation” during childhood. PTSD symptom severity was measured by the PCL (Weathers et al., 1993) which was discussed prior in this review. Marital satisfaction was measured by the Relationship Assessment Scale (RAS; Hendrick, 1988), a 7-item scale of Likert-style questions that assesses general satisfaction with the spousal relationship. The researchers used a path analysis model to estimate both direct and indirect (through PTSD symptom severity) effects of CSA and combat exposure on marital satisfaction. Similar to previous studies, the researchers found that PTSD symptom severity directly and negatively impacted marital satisfaction. They also found that combat exposure seemed to exert only an indirect negative effect on marital satisfaction, exerting all of its effects through PTSD symptoms. CSA on the other hand showed evidence of both direct and indirect effects on marital satisfaction, with significant direct impact independent of both combat exposure and PTSD symptom 54
severity. So, childhood sexual abuse seemed to account for additional PTSD symptom severity over and above combat exposure, as well as uniquely contributing to marital dissatisfaction. This result paralleled Cabrera and others (2007) in providing evidence that childhood exposure to trauma uniquely impacts PTSD symptoms above and beyond the impacts of adult trauma. This study also adds evidence that childhood trauma, in this case CSA, uniquely impacts marital satisfaction. These results add on to the increasing evidence that there is a need to study the long-lasting impacts of childhood trauma on relationships. The studies of PTSD and relationship outcomes discussed above, provide evidence to suggest that PTSD is associated with significant negative relational outcomes including intimate relationship discord, physical and psychological aggression, impaired intimacy, increased risk of relationship dissolution, and lower relationship satisfaction and quality. Put together, these studies seem to indicate a link between the sequelae of trauma (PTSD) and negative outcomes on couple relationships and thus could be a bridge towards looking at how experiencing trauma when young (i.e., ACEs) may negatively impact couple relationships. Impacts of Childhood Trauma Exposure on Couple Relationships As noted above, much of the current research on trauma/PTSD and its impact on couple relationships is done with military samples and on adult trauma exposure. Fewer studies have addressed the relationship specific outcomes of childhood trauma exposure, and none from the Adverse Childhood Experiences framework. As noted throughout this review, there is evidence in the literature that the negative impacts of childhood trauma 55
are more severe than the impacts of adolescent/adulthood-only trauma exposure (Lilly & Valdez, 2012; Ogle et al., 2013). This may be because of the potentially significant early impacts of the trauma on development (Cloitre et al., 2009). The following studies attempted to measure relational impacts from childhood trauma (Bigras et al., 2016; Nelson & Wampler, 2000; Whisman, 2006). One study analyzed associations between history of specific childhood traumas and general relationship outcomes including marital disruption and marital satisfaction (Whisman, 2006). The researcher used data collected from the National Comorbidity Survey (Kessler et al., 1998), Part II, a U.S. nationally representative, probability sample of the general population aged 15-54, who completed in-home, face-to-face interviews. For the analysis on marital disruption the sample included those who had been married at least once and completed the related questions, resulting in an analysis of 3,428 participants (54.5% women, average age of 36.8, 82.1% White, 8.2% African American, 7.3% Hispanic, and 2.5% Other). For the analysis on marital satisfaction, the sample included those who were currently married and who had completed related questions, resulting in an analysis of 2,526 participants (53.7% women, average age of 36.4, 83.6% White, 6.1% African American, 7.7% Hispanic, and 2.6% Other). Marital satisfaction in this study was measured through two Likert-type items asking about how satisfied they are with the relationship (very satisfied to not at all satisfied) and how they would rate their relationship (excellent to poor). Childhood traumatic events were measured through interview responses to questions about seven traumatic events (physical abuse, rape, sexual molestation, being threatened with a weapon, held captive or kidnapped, being 56
seriously physically attacked or assaulted, being involved in a life-threatening accident, and being involved in fire, flood, or natural disaster) and coded as childhood traumas if occurring before age 16. This interview process and questions are detailed in Kessler, Sonnega, Bronet, Hughes, and Nelson (1995). Probability of marital disruption was computed for each of the traumatic events and results indicated that those who had experienced physical abuse, rape, and serious physical attack or assault as a child had approximately two times the likelihood of marital disruption (defined in this study as currently separated or currently or previously divorced) than those who had not. These general results also held up when controlling for multiple traumatic events (for those 5.7% of individuals reporting two or more traumas). The researcher used linear regression analyses to estimate the relationships between the childhood traumatic events and marital satisfaction and found that those with childhood histories of rape or sexual molestation reported significantly lower marital satisfaction. The effect sizes for this finding were considered small-to-medium for sexual molestation (d = .35) and large for rape (d = .91). These results show evidence that traumatic events during childhood, especially sexual violence, have significant effects later in life on relationship stability even when accounting for the existence of other childhood traumas. One aspect this study may miss that could be captured by using ACE questions is the ability to examine the relationship between other more common forms of childhood trauma (that are less assaultive in nature) and couple relationships. One study by Nelson and Wampler (2000) used a sample of clinic couples to examine differences between couples who reported history of childhood physical or 57
sexual abuse and couples who did not. The study used a convenience sample of 161 heterosexual couples (average male age 33.4, and average females age 31.5, average length of relationship 6.9 years, 46% married, 25% remarried, 6% divorced or separated, and 23% dating, never married, or cohabitating) who were treated at a university marriage and family therapy clinic (96 couples with one or both members reporting on intake forms of having a history of childhood physical or sexual abuse, and 65 couples in the no-abuse group). The sample had a majority with at least some college education, and was 81% European American, 13% Hispanic, and 6% Other. The study measured general stress/psychological symptoms using the Brief Symptom Inventory (Derogatis, 1993), a 53-item self-report measure that has demonstrated good reliability and moderate to high construct validity as a general measure of psychological distress (Nelson & Wampler, 2000). Relationship quality was measured using the Dyadic Adjustment Scale (DAS; Spanier, 1976) previously cited in this review. Family adjustment was measured using the 20-item Family Adaptability and Cohesion Scale (FACES; Olson, Portner, & Lavee, 1985), a self-report questionnaire that attempts to measure levels of cohesion and adaptability in the couple system. Comparisons were made between the no-abuse group and the abuse group (which included those that reported abuse history in either or both partners) on the various measures, and further broken down by gender (male vs. female). Results indicated that there was a significant effect (small-to-medium effect size, d = .48) of reporting a history of childhood physical and/or sexual abuse in one or both partners on having lower relationship adjustment scores and higher psychological stress scores. When broken out by gender it was found that both male and female partners in the abuse 58
couples reported higher stress scores than those in the no-abuse couples, and that male but not female partners in the abuse couples reported lower relationship adjustment scores than those in the no-abuse group. In general, with some small exceptions, results indicated significant differences in both marital adjustment and psychological stress scores when comparing the abuse and no-abuse couple groups. Perhaps counterintuitively, the researchers also found no significant differences on these measures between the couples where both partners reported a history of childhood trauma and those where only one partner reported an abuse history. Finally, when looking at just the abuse couples, no significant differences in stress scores were found between the abuse and non-abuse partners (in couples where only one reported a history of abuse), suggesting some support for secondary trauma theory (Nelson & Wampler, 2000). Even though the sample used was a convenience sample, one strength of this study was using a control group of couples who did not report a trauma history. One limitation of this study was that the measured effect of childhood trauma was potentially decreased due to other forms of childhood trauma besides physical and sexual abuse not being measured. Another study, although not directly studying couples, attempted to look at the impact of a range of childhood maltreatment experiences on sexual satisfaction in relationships (Bigras et al., 2016). The researchers attempted to measure childhood cumulative trauma (CCT) which they define as “an amalgam of childhood maltreatment experiences that can lead to a range of symptoms and problems in adulthood” (p. 1), and which they relate to similar constructs such as complex childhood trauma and ACEs, discussed earlier in this review. This study, conducted in Canada, used a convenience 59
sample of 620 participants (85.5% women, average age of 27.4, 58.7% students, 42.1% university educated, 90% heterosexual, with 10.6% married, 26.4% cohabiting, 41% involved in relationship without cohabitation, and 22.1% single or having occasional partners). The study measured the impact of CCT on adult childhood sexual satisfaction. The study also included a mediational analysis of the impact of affect dysregulation and sexual anxiety on the relationship between CCT and adult sexual satisfaction, though those results will not be reported on here. CCT was operationalized in this study through answers to a 16-item questionnaire that asked about frequency of experiences related to eight types of childhood maltreatment including childhood sexual abuse, physical abuse, psychological abuse, psychological neglect, physical neglect, psychological interparental violence, physical interparental violence, and peer bullying. For emotional abuse, emotional neglect, witnessing emotional abuse, and bullying, these were only counted if they occurred more frequently than one standard deviation above the average for the sample in order to isolate the more severe cases. Total CCT score (0-8) was calculated similar to the ACE studies by summing the trauma types. Sexual relationship satisfaction was measured using the Global Measure of Sexual Satisfaction (GMSEX; Lawrance & Byers, 1995) a five-item self-report measure where participants rate their sexual relationships from good-bad, pleasant-unpleasant, positive-negative, satisfyingunsatisfying, and valuable-worthless. In this sample, 60.1% had experienced at least one type of childhood abuse, with an average of 2.51 types for those reporting at least one type. Results from path analyses indicated a significant negative relationship, where higher CCT predicted lower sexual satisfaction. Similar to the ACE studies there was 60
also a dose-response trend where each additional trauma type reported tended to additionally decrease reported sexual satisfaction. These results held even when modifying the model of CCT (such as using more conservative indicators of physical abuse, removing physical abuse, or removing sexual abuse). This study added to the literature in that it established that negative sexual outcomes in relationships are not just a result of childhood sexual abuse, but also an outcome of other childhood maltreatment (Bigras et al., 2016). The research in this area of studying the impact of childhood trauma on couple relational outcomes is still in its infancy and no study to date has attempted to measure the impact of ACEs or CCT on general relational outcomes. These studies do provide some evidence to suggest that experiencing childhood trauma has significant negative impacts on couple relationships and specifically on higher likelihood of marital disruption, lower marital satisfaction, and poorer relationship adjustment. The only study to-date on the concept of CCT (similar to ACEs) and couple relational outcomes has noted a connection between higher CCT and lower sexual relationship satisfaction, but studies are needed to see if experiencing more trauma predicts more difficulties in couples and if it impacts other outcomes besides sexual satisfaction. Summary In summary, the wider research base in traumatology and PTSD has shown significant evidence of the negative impact of PTSD on the individual and their functioning. Less evidence, but still compelling, has been given regarding the negative impact of PTSD on couple functioning and stability. Research has also provided 61
evidence that it is not just adult onset trauma that is significant in its impacts on adults but also childhood trauma. For example, childhood trauma seems to be connected to increased risk for PTSD as an adult. There is some preliminary evidence as well that experiencing childhood trauma provides unique negative impacts on the individual and relationships above and beyond that expected by adult trauma exposure. There is preliminary evidence only in the area of sexual relationship satisfaction, that more pervasive childhood trauma (CCT or ACEs) is related to more severe negative effects for couples. As the research evidence is still preliminary regarding the impacts of childhood trauma on couple relationships as an adult, further research is needed to establish this correlation. Furthermore, some of the current research looking at this question may be underestimating the impact of more significant trauma exposure by combining all levels of trauma exposure and by not separating out those couples who were not as effected by trauma exposure (since for many studies there was no measure of trauma severity such as a PTSD scale, or a measure of amount of exposure such as CCT or the ACE questionnaire). Since not all trauma exposure results in negative individual outcomes (Kilpatrick et al., 2013), it is possible that this pattern holds for relationships, and that not all trauma exposures will have significant negative impacts on couple relationships. This possibility points to the need to further study couples outcomes while also using measures of the severity of trauma exposure, something that could be accomplished in part by a study that examines the correlation between ACEs and couple outcomes.
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Trauma and Partner Selection Another way in which trauma has been hypothesized to impact couple relationships is through partner selection. The theory of assortative mating or spousal/marital similarity predicts that there are typical patterns in partner selection based on similarity on certain features of each partner, such as age, education, intelligence, attitudes, and so forth (Luo & Klohnen, 2005). As related to trauma, one theory is that trauma will be drawn to trauma such that individuals with trauma histories may be more likely to choose as partners other individuals with similar trauma histories and/or similar impairment (Goff & Smith, 2005). Theorists have discussed many potential mechanisms of such a bias in partner selection including such concepts as attachment, similarity to self, and differentiation (Klohnen & Luo, 2003). Balcom (1996), referencing Bowen’s theory of multigenerational transmission process, theorized that “[a] child who directly or vicariously witnessed parental trauma is likely to be less differentiated . . . [a]s an adult, this person may be drawn to other traumatized people as possible mates in an effort to be understood, to be helped, or to be helpful” (p. 434). Miller, Anderson, and Keala (2004) in their review of the research on basic concepts of Bowen theory noted a lack of evidence to support the marital similarity hypothesis at least as it had been studied using measures of differentiation of self. Research on attachment and partner preference in contrast has shown mixed results, some supportive and some not (Holmes & Johnson, 2009). However important looking at mechanisms of effect are, it is perhaps more important to establish whether the phenomenon of bias in partner selection is supported by findings from research. Specifically, there does seem to be some preliminary 63
evidence from basic research on comparing spouses based on psychiatric diagnoses and also histories of specific abuse that show evidence for the spousal similarity hypothesis at least as it concerns mental health/development (Chen & Carolan, 2010; Nordsletten et al., 2016; Whisman, 2014). Research Relevant to Partner Similarity Nordsletten and others (2016) examined patterns of partner similarity (described as nonrandom mating in the article) with regard to a number of psychiatric disorders. The sample was a population cohort of 707,263 individuals (45.7% Women) that came from nationwide Swedish population registers. Psychiatric disorders were derived from data in the Swedish National Patient Register which includes psychiatric records of inpatient and outpatient diagnoses which were linked by unique ID numbers to the population registers. Eleven psychiatric diagnoses were in the analysis. Mating relationships were established through both marriage and birth records (documenting biological parentage) in order to include married couples as well as other relationships such as cohabitating couples with children. Each partner in the mated case pairs were matched on age, sex, and area of residence with five population controls who did not have the diagnosis of interest. Within and across disorder correlations were calculated to examine the relationship between the presence of diagnoses in mate pairs, as well as odds ratios, to examine the odds of a mate having a similar or different diagnosis relative to the matched population controls. Results indicated a significant relationship (ranging from small to moderate) between mates and diagnostic status for each disorder. They generally found a 2-3 times increased odds for an individual with a disorder having a 64
mate that had that same or another disorder. They also found that as the number of diagnoses in an individual (male or female) increased, the proportion of partners with a diagnosis also increased (from about 15% of partners when having one diagnosis, to almost 30% of partners when having five or more diagnoses). These results, using a large population-based cohort and also using population controls, seem to show some evidence of similarity in partner selection related to psychiatric disorders. Although stress-related disorders were not measured in this study (such as PTSD or adjustmentdisorder), anxiety and mood-related disorders were, and the researchers report that the correlations that were found were typically higher than spousal correlations found for personality traits, height, or weight. In addition, these findings do fit with evidence from the previously discussed study by Riggs (2014), where the researcher noted that “in the present sample, there was a significantly greater likelihood that veterans with PTSD were partnered with females who also had PTSD compared with the non-PTSD veterans,” (p. 204). The implications of partner similarity on psychiatric condition relate to both the impact on the relationship itself (perhaps relationships are more troubled if both individuals have psychiatric problems), as well as, to the intergenerational transmission of mental illness through increased genetic and environmental risk factors (Nordsletten et al., 2016). Whisman (2014) completed a study on the impact of traumatic events on marital quality, which included an analysis of partner similarity in trauma history. The sample used for the analysis was a subset of the Health and Retirement Study, a multistate probability cohort sample of people in the United States over the age of 50 in 1998. The 65
subsample used was of 2,161 married couples (wives’ average age of 64.5, husbands’ average age of 67.8, with a racial distribution of approximately 89% White, 7% Black, and 4% Other). Five kinds of traumas were included in the study, including having experienced a life-threatening illness or accident, major natural disaster or fire, combat experience (taken out of the analysis due to low prevalence), serious physical attack or assault, and childhood physical abuse by parents. These events were measured by selfreport questionnaire where participants were asked whether each event had occurred at some point in their lives. Although there were analyses in this study regarding the relationship between having a history of any of these traumas and marital quality, only the results related to partner similarity will be reported here. Similarity in partner trauma history was tested using logistic regression analyses and odds ratios were calculated on each trauma. For every trauma studied, a partner reporting a positive history of that trauma increased the odds of their partner also reporting a history of that same trauma (odds ratios ranging from 1.53-7.85). In this study, the only measured childhood trauma was that of childhood physical abuse, which showed a 2.37 times greater odds for an individual with a history of physical abuse to have a partner with a history of physical abuse, than it was for an individual without a history of physical abuse to have a partner with a history of physical abuse. This general pattern of greater odds for similar partners on childhood physical abuse was found even after controlling for demographic variables such as age, gender, race, and years of education. According to the researcher, it is also relevant that childhood physical abuse necessarily occurs prior to marriage, so it is a similarity that is more likely to be evidence of assortative mating. That the results found 66
were stable after controlling for demographics provides even more evidence according to the researcher, that similarity of history of childhood physical abuse is “not primarily due to underlying demographic similarities but instead reflects active assortment,” (p. 213). Although limited to just childhood physical abuse and missing other childhood adverse events that are likely relevant to both marital quality and partner similarity (Whisman, 2014), this study does provide some evidence that individuals with trauma histories may be more likely to partner with those who also have trauma histories. Building from theories about attachment and partner selection and Bowen’s theory of mate selection and differentiation, Chen and Carolan (2010) examined what they termed comparative development between females who had a history of childhood sexual abuse (CSA) and their partners. The study was a phenomenological qualitative study that aimed to examine similarities and differences between CSA survivors and their partners regarding their developmental experiences with parents in their families of origin. Six couples (all heterosexual, with seven Caucasians, three African Americans, and two Hispanics, with average length of relationship of 10.4 years and average age of 36) participated in in-depth semi-structured interviews and in reflection diary writing. Interview questions were primarily about memories of experiences in developmental stages, parental reactions to significant events, and individual’s experiences of their parents reactions. Interviews were recorded and transcribed and then validated by a second author, with field notes used alongside the interviews and diaries to triangulate for validity purposes. Interviews and diaries were coded based on agreed upon codes by both authors and were coded based on developmental stage. Although the results cannot 67
be generalized past the limited sample used, the findings of this qualitative study inform about potentially significant similarity in background and development between spouses where there is a history of CSA. Significant similarities in each couple were generally found related to family of origin structure (including the existence of marital dissolution and similar parent relationships), relationships with biological parents (including similarities in valence and distance of relationships between each partner and their parents during childhood, as well as parental responses to developmental events), and significant developmental events (including similarity in impacts from adverse events and having experienced similar adverse events in similar developmental stages). Importantly, although this study was focused on CSA, most of the couples also reported significant adverse childhood events such as witnessing domestic violence, experiencing physical and emotional abuse, and substance abuse in the family. If it is the case that individuals may be more biased towards selecting partners based on similar developmental backgrounds, including on the history of similar adverse events occurring during childhood development, this may have significant ramifications on our understanding of the impact of childhood trauma on couple relationships. Further research regarding this kind of similarity is needed, perhaps using the framework of ACEs to measure the history of childhood adverse events and evaluate similarity/differences in histories between partners. Summary Although still very much preliminary, some initial research seems to indicate a greater likelihood for individuals with a psychiatric diagnosis to partner with others who 68
also have a psychiatric diagnosis, for individuals to partner with others who have a similar history of physical childhood abuse, and for there to be similarities within couples on developmental history and adverse childhood events at least where there is a history of CSA within the couple. Further research is needed to confirm and build from these initial findings. It is not known whether this assortative mating/similarity hypothesis would be supported relative to aggregate exposure to trauma, or whether it would also follow for other adverse childhood events in addition to physical abuse and CSA. Furthermore, although the study on psychiatric diagnoses is suggestive of important results, measuring lifelong diagnoses or trauma does not rule out competing hypotheses such as secondary traumatization as an alternate explanation for the relationship between problems in one spouse and problems in the other. Measuring childhood trauma, which occurs prior to partner selection, will enable researchers to better rule out this alternative hypothesis. This present study will attempt to further the research in this area through examining the hypothesis of higher likelihood for individuals with adverse childhood experiences to partner with individuals with adverse childhood experiences. Theoretical Foundation For the purposes of this study, a theoretical foundation is the a priori lenses through which this researcher makes sense of the literature review and research process. This researcher uses a number of concepts and theories to inform and make sense of the research as well as to guide hypotheses. Systems theory, developmental theory, and theories relating to the impact of trauma on the family system all inform the current research study. 69
Systems Theory As a marriage and family therapist an important base theory is that of family systems theory (Constantine, 1986). Family systems are theorized to evidence the following: interrelated elements and structure, patterned interactions, boundaries, holism, and use of messages and rules. Holism suggests that individuals, families, and communities are more than just the sum of their parts (Rigazio-DiGilio & McDowell, 2007). The principle of interrelated elements and structure point to the transactional nature of these relationships, where recursive or circular reasoning is used, thus making sense of behavior as both impacting and being impacted by others in the relationship and including a view of how those behaviors change over time and become patterned due in part to those recursive impacts (Rigazio-DiGilio & McDowell, 2007). This framework is needed in order to build a case that the couple subsystem is not just the sum of two individuals, but that what impacts one individual will impact the partner and impacts on the partner also recursively impact the individual. Traumatology has been explicitly integrated into systemic theory, at least regarding couples, in Goff and Smith’s (2005) Couple Adaptation to Traumatic Stress (CATS), which theorizes about the primary and secondary effects of trauma in each partner as well as the relational impacts within the couple subsystem. The theory discusses how predisposing factors and resources may modify the direct impact of trauma exposure. Although there is some validation of the concepts of the model (Oseland, Gallus, & Nelson Goff, 2016), the model primarily is concerned with trauma that occurs in already formed couple relationships. So, its
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primary use here is to show the interconnectedness of partners in couple relationships and how predisposing factors may influence current behaviors. Developmental Models A broad model of development that encompasses both individual and systemic changes over time is important for understanding the research questions of this study. As the overall goal of this research is to study how early childhood experiences may affect later outcomes within a systemic context, developmental theory is used here to bridge the gap in explaining how these different stages of life could be connected. Adlerian theory of development and the concept of teleology and human behavior, posits that human behavior is goal-directed, and that behavior makes sense within the context, history, and needs and strivings of the individual and system (Ivey, Ivey, Myers, & Sweeney, 2005). Hence behavior is theorized to be connected to individual cognitive, emotional, physical, social, cultural, and spiritual development and historical context. Family systems, which include couple relationships, are also thought to be impacted by their developmental process which involves adapting and changing arrangements of family roles, power structures, and boundaries (Walsh, 2012b). The family life-cycle model accounts for different developmental stages with which families may go through, such as the creation of new families through coupling, families with young children, families with adolescents, and so forth. The family life-cycle model also accounts for how families adapt to a range of both normative and non-normative events and how cumulative stressors and the way families respond to them ultimately impacts long-term adaptation.
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Other systemic developmental models point to ways of understanding family systems development that allow for less normative configurations of families and are not based on ages of family members (Rigazio-DiGilio, 2000a). Systemic Cognitive Developmental Therapy (SCDT) theorizes that there are phases of systemic development relating to a system’s boundaries, permeability, and meaning making that family systems cycle through over time in a non-linear way. These phases include system exploration, consolidation, enhancement, and transformation. In addition, theories such as SCDT move beyond looking at trauma and disorder through the lenses of either individual or family dysfunction and describe the interconnections between these and larger systems. “As an alternative relational therapy, SCDT incorporates a multi-level interpretation of distress and disorder ranging from encapsulated intrapsychic phenomena to individual and collective interactions with contextual constraints and potentials,” (Rigazio-DiGilio, 2000b, p. 1019). Combining individual and family developmental concepts into one theory allows a much broader understanding of how all of the separate parts combine into a much larger whole. Finally, and importantly for this study, SCDT considers "distress to be a natural and logical consequence of developmental and contextual history," which also provides the theoretical rationale for looking at developmental history in order to better understand current individual and relational distress (Rigazio-DiGilio, 2000b, p. 1019). One way in which childhood trauma has been theorized to impact development and then later outcomes has been through the concept of attachment. Early attachment experiences of children and their caregivers were first researched by Bowlby (1969). The 72
theory suggests that when caregivers are stable, responsive, and available, caregivers and their children develop secure attachment bonds that provides the base for cognitive/emotional/social development. Negative experiences such as separation, loss, violence, neglect, and abuse among others, make insecure attachment bonds much more likely with attendant negative impacts on the developmental process (Pearlman & Courtois, 2005). Although this paper does not use the attachment theory framework, the research is related and has already provided some evidence that childhood exposure to trauma, and especially to interpersonal trauma, predicts insecure adult attachment representations which seem to directly and indirectly influence negative individual and couple outcomes. Researched outcomes of insecure adult attachment include depression severity (Fowler, Allen, Oldham, & Frueh, 2013), trauma-related symptomatology and externalizing and internalizing symptomatology (Muller, Thornback, & Bedi, 2012), presence of domestic violence and higher marital distress (Godbout, Dutton, Lussier, & Sabourin, 2009), and relationship adjustment problems (Godbout, Lussier, & Sabourin, 2006; S. A. Riggs, Cusimano, & Benson, 2011). Attachment research provides an additional theoretical framework that shows the potential plausibility of connecting early childhood experiences of trauma and later impacts on adult relationships. Stress and Family-as-Context Another important theoretical perspective that connects individuals, their family context, and adaptation to stress is the family resilience framework (Walsh, 2012a). Walsh (2006) in discussing her family resiliency model noted that, “Crisis events and persistent stress affect the entire family and all its members, posing risks not only for 73
individual dysfunction but also for relational conflicts and family breakdown” (p. 26). This theory allows a better understanding of what is likely to occur within the family/support context when negative life events occur. As noted earlier regarding research on social support and trauma, relationships with families provide a salient and crucial role for reacting to trauma (Wagner, Monson, & Hart, 2016), and for healing from traumatic exposure (López-Zerón & Blow, 2015). Unfortunately, the family context can also be the place where much trauma exposure can occur. Experiencing trauma as a child may be theorized to create vulnerabilities in individuals who as adults may replicate traumatogenic environments leading to trauma in the next generation, a phenomenon labeled as intergenerational transmission of trauma (Balcom, 1996; Yehuda et al., 2001). Summary These theories discussed here, of systemic theory, developmental theories, attachment, and theories relating to stress and the family as context, provide the theoretical justification for this study. Systemic theory is especially a good fit for examining ACEs precisely because “both trauma sequelae and recovery always occur in the context of social-interpersonal contexts,” (Maercker & Hecker, 2016, p. 29303; Maercker & Horn, 2013) and systems theory is concerned with emphasizing how behavior and symptoms are interconnected in these contexts. Using systems theory to inform research studies into trauma and ACEs will help to bridge the gap in the research related to lack of studies that take interpersonal context into account. Developmental theories are an important way, in addition to biology and neuroscience (Shonkoff et al., 2012), of tracing the negative impacts of ACEs from childhood through the lifespan 74
(Cloitre et al., 2009). Theories relating to stress and family-as-context are appropriate for framing studies into ACEs because ACEs occur during childhood and therefore the adverse experience and/or its aftermath will occur in the context of families. Summary A review of the literature included data on the need for additional research on trauma and family relationships. The review covered key definitions and types of trauma as well as some of the ways trauma is defined diagnostically, which points to additional reasons for an interpersonal perspective on trauma. Data on prevalence of trauma exposure and PTSD were presented, as well as historical and current research using the Adverse Childhood Experiences framework. This review covered research relating to the impact of PTSD on individual and couple outcomes and research on the impact of childhood trauma on couples. The chapter also included research relating to the measured association between trauma exposure and partner selection. Finally, this review included the general theoretical concepts of systems theory, developmental theory, and theories on the impact of trauma on couples and families which form the theoretical background for the study. Previous research regarding ACEs has focused primarily on individuals which in this study will be extended to focus on couples. The author also acknowledges the multisystemic impact of trauma (Siegel, 2013), where the traumatized individual impacts and is impacted by partners and children (Dekel & Monson, 2010; Dekel & Solomon, 2006; Lambert et al., 2012; Lev-Wiesel & Amir, 2001; Ray & Vanstone, 2009; Renshaw et al., 2011), as well as broader systems such as peer groups, school/work, and the 75
community (Coulter, 2011). For the purposes of this study, however, focus was on the impacts of childhood trauma on the couple subsystem. The research questions for the study are as follows: 1. a. What is the relative statistical contribution of a subject’s ACE scores on their own RDAS scores and their partner’s RDAS scores? b. What is the relative statistical contribution of the partner’s ACE scores on their own RDAS scores and the subject’s RDAS scores? 2.
a. Can couples be grouped statistically into clusters based on combinations of
ACE scores (such as low-low, low-high, and high-high)? b. If so, are there statistically significant differences between these clusters on average group RDAS scores? 3. Is there a statistically significant relationship between ACE scores of subjects and their partners? Specifically, are subjects statistically more likely to partner with those who have similar (as defined by 2 or less points apart) or different (as defined by >2 points apart) ACE scores? 4. Do higher ACE scores statistically significantly predict increased likelihood of partnering with someone who has more than minimal ACEs (as defined by ACE score >1)? If so, is there a statistically significant increase in likelihood as ACE scores increase?
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CHAPTER III METHODOLOGY
This chapter consists of a discussion of the purpose, research questions, hypotheses, and the methods used to conduct the study. First a restatement of the research problem will be discussed, followed by the research questions and hypotheses that will be tested. Next, the study design and data source will be discussed. Lastly, the chapter will include a discussion of the instruments used in the study, an overview of the statistical analyses used, and a summary of the methodology. Restatement of the Problem Research is limited regarding potential associations between experiencing cumulative childhood trauma (operationalized as ACEs in this study) and negative relationship outcomes as an adult. Although the research linking adverse childhood experiences (ACEs) with a significantly increased risk for numerous health problems as an adult is compelling, there are few ACE studies that have measured relational outcomes and no apparent ACE studies that have analyzed the couple dyad (with instead studying one individual’s report of the relationship). More research is needed that examines the relationship from a systemic context (the context of the couple dyad) in order to get a more accurate view of how cumulative childhood trauma may lead to impacts in the relationship after accounting for both partners and their reciprocal interactions. Dyadic 77
research of this kind may benefit practitioners through informing the development of clinical models that embrace an interpersonal perspective on PTSD (Maercker & Horn, 2013) and that take into account how both partners’ trauma histories may relate to current relationship quality. In addition, there are some limited studies that seem to point towards potential ability to group individuals by ACE scores (Mersky et al., 2013; Rebbe et al., 2017) and couples by trauma exposure combinations (Nelson & Wampler, 2000). More research is needed to determine if couples could be statistically grouped by combinations of ACE scores between partners and if so, whether these groups seem to matter when examining relationship quality. Answering these questions could lead to a better understanding of the impact of childhood trauma on couple dynamics which could potentially inform the development of systemic clinical models used to treat posttraumatic stress disorder (PTSD). Furthermore, if valid, typologies such as these could become helpful heuristics that could be used as part of a larger strategy to tailor treatment to each couple rather than using a one-size-fits-all model (Snyder, Schneider, & Castellani, 2003). Research on partner selection in the context of cumulative childhood trauma is also limited, and may be relevant to intervention efforts to interrupt intergenerational transmission of abuse/trauma. Research Purpose The purpose of this study was to examine the effect of each partner’s reported ACE exposure on their own and their partner’s reported relationship quality. The study also examined whether couples could be grouped by ACE score combinations between partners and whether these statistically derived groups differed significantly in reported 78
relationship quality. In addition, the study examined if there was a significant relationship between reported ACE exposures within the couple dyad (partner selection factors). Research Questions and Hypotheses Research Question 1. a. What is the relative statistical contribution of a subject’s ACE scores on their own RDAS scores and their partner’s RDAS scores? b. What is the relative statistical contribution of the partner’s ACE scores on their own RDAS scores and the subject’s RDAS scores? Null Hypothesis 1: a. There are no significant effects of a subject’s ACE scores on their own or their partner’s RDAS scores. b. There are no significant effects of a partner’s ACE scores on their own or the subject’s RDAS scores. Alternative Hypothesis 1: It is hypothesized that there will be significant and negative direct effects of a subject’s ACE scores on their own RDAS scores and their partner’s RDAS scores, and of a partner’s ACE scores on their own RDAS scores and the subject’s RDAS scores. Research Question 2. a. Can couples be grouped statistically into clusters based on combinations of ACE scores (such as low-low, low-high, and high-high)?
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b. If so, are there statistically significant differences between these clusters on average group RDAS scores? Null Hypothesis 2: Couples cannot be statistically grouped by couple ACE score combinations. If they can be grouped, there are no significant group differences between groups of couples with regard to ACE score combinations on average RDAS scores. Alternative Hypothesis 2: It is hypothesized that couples will be able to be statistically grouped into clusters based on ACE score combinations within each couple. It is hypothesized that there will be statistically significant differences between groups of couples with regard to ACE score combinations on their average RDAS scores. Due to mixed results in the research, this is a non-directional hypothesis. Research Question 3. Is there a statistically significant relationship between ACE scores of subjects and their partners? Specifically, are subjects statistically more likely to partner with those who have similar (as defined by 2 or less points apart) or different (as defined by >2 points apart) ACE scores? Null Hypothesis 3: There is no significant relationship between the ACE scores of subjects and their partners. Subjects are equally likely to partner with those who have similar ACE scores and different ACE scores OR subjects are more likely to partner with those who have different ACE scores than similar ACE scores. Alternative Hypothesis 3: It is hypothesized that there will be a significant relationship between the ACE scores of subjects and their partners and that subjects will be significantly more likely to have a partner who has similar ACE scores than different ACE scores. 80
Research Question 4. Do higher ACE scores statistically significantly predict increased likelihood of partnering with someone who has more than minimal ACEs (as defined by ACE score >1)? If so, is there a statistically significant increase in likelihood as ACE scores increase? Null Hypothesis: Higher subject ACE scores do not significantly increase odds of having a partner with an ACE score greater than 1. Alternative Hypothesis 4: It is hypothesized that there will be a dose-response relationship between a subject’s increasing ACE scores and an increased likelihood (odds) of having a partner with an ACE score greater than 1. Research Design The research design that was used for this study is a quantitative, descriptive and correlational design to examine the relationships between ACEs and relationship quality, and ACEs and partner selection. This study design was chosen due to one of the main purposes of the research being to replicate the ACE study design with relational outcomes. This study presents an analysis of archival self-report survey data dating from Jan. 2016 – Aug. 2017. The archival data were collected at a Midwestern university training clinic where couples who presented for couples therapy completed instruments of interest during regular intake procedures. The University of Akron IRB approved the study (see Appendix C). The basic design being replicated from the ACE studies is the use of quantitative, self-report surveys including the ACE study questionnaire and outcome measures, as well as the examination of statistical relationships between ACEs and those outcomes. In the 81
original ACE studies, the primary outcomes were related to physical and mental health, and in this study, the primary outcome was relationship quality as measured by the Revised Dyadic Adjustment Scale (RDAS). The other relational variable of interest was partner selection, operationalized by the relationship of ACE scores between partners within couple dyads. The use of relational measures, combined with the dyadic data analysis that will be described below, extends this study beyond a replication to examining ACEs in a systemic/dyadic manner. Correlational survey study designs are used to examine relationships between variables, and typically have advantages of good external validity and enabling study of variables that are not able to be experimentally manipulated (Heppner, Kivlighan, & Wampold, 2008). A limitation of these designs are lower internal validity due to lack of controlling the variables of interest resulting in an inability to establish causation. The research design used for this study was also a retrospective design, where the study questionnaires ask participants to recall childhood experiences. Although prospective research designs are often seen as being “more rigorous, with less biased sample selection and better measurement of the natural history of a phenomenon,” an important argument can be made for the importance of retrospective designs in attempting to study childhood adverse experiences (Kendall-Tackett & Becker-Blease, 2004, p. 724). This argument includes some evidence that retrospective studies of childhood trauma are likely to catch some participants that would be missed by prospective designs (Kendall-Tackett & Becker-Blease, 2004), evidence that retrospective studies of childhood adversities do show adequate reliability and validity (Dube et al., 2004; Hardt & Rutter, 2004), and 82
evidence of similarity between retrospective and longitudinal studies on the strength of associations between childhood adversities and long-term outcomes (Hardt et al., 2010). Data Source and Sample The sample used for the study was a convenience sample consisting of couples who presented between January 2016 and August 2017 for couples therapy at a Midwestern university clinic, which provides outpatient services for individuals, couples, and families. The sample is from a clinical population of apparently distressed couples. The data set included approximately 150 couples who completed both the ACE questionnaire and the RDAS as part of regular intake assessments. The final sample was 50.7% Female (n = 148) and 49.0% Male (n = 143), with an average age of 35.3. A majority of participants reported their race/ethnicity as being White (66.4%), followed by African American/Black (21.6%), ‘More than one ethnicity/Multiracial’ (3.1%), Other (2.1%), Arab American (1.4%), Asian American (1.4%), Latino/a American/Hispanic (1.4%), and Native American (.3%). See Chapter IV for more detailed demographics regarding the sample. Survey data were collected by the clinic whenever a new couple presented to their first session and so the data were not all collected together. Even though data are collected in an on-going basis at the clinic to inform treatment, only the first initial intake assessments for each couple was used in order to minimize potential changes in the relationship between variables due to treatment. It is possible that other treatment prior to treatment at the clinic has occurred that would impact the outcome measure of interest. In addition, due to participants self-selecting into treatment and the use of a convenience 83
sample, generalizability of the study results beyond the study sample may be limited. Despite this, it was hoped that testing these preliminary and confirmatory hypotheses would inform future research efforts along these same lines. Instruments The current study used three self-report measures: (a) the Client Information Form (CIF), (b) the Adverse Childhood Experiences Questionnaire (ACE), (c) the Revised Dyadic Adjustment Scale (RDAS). Client Information Form The Client Information Form (see Appendix B) is used by the university clinic to collect client information including demographic information (gender, sexual orientation, race/ethnicity, religious/spiritual identification, employment status, education level) and family information (relationship status, number of people living in the home). All of the questions are open ended except for current relationship status, where the options are single, married, divorced, remarried, widowed, dating, cohabitating, or separated. Adverse Childhood Experiences (ACE) Questionnaire The ACE Questionnaire used in this study is a modification of the original ACE Study Questionnaire (Felitti et al., 1998). The original ACE Study Questionnaire operationalized adverse childhood experiences to include childhood abuse (psychological, physical, and sexual) and household dysfunction (exposure to substance misuse, mental illness or suicide attempts, violence towards their mother, and having a household member go to prison) that are experienced prior to age 18. In the second wave of the original study, several questions were added regarding parental separation or 84
divorce and experiences of neglect (emotional, physical) as well as some wording changes (Dube et al., 2001). The resulting questionnaire is a 10-item dichotomous response (‘yes or no’) survey, with some items having multiple questions (for items on emotional, physical, and sexual abuse, emotional and physical neglect, and violence against mother). Scoring is accomplished by summing all affirmative responses (for the case of items with multiple questions, any affirmative response makes that overall item also affirmative), resulting in a total ACE score ranging from zero to ten (higher scores indicating higher adverse experiences exposure). As noted in Chapter II, the ACE questionnaire has shown moderate to substantial test-retest reliability when measured 6 months (Pinto et al., 2014), and 20 months apart (Dube et al., 2004). Evidence also exists supporting the validity of retrospective reports of adverse childhood experiences especially when examining associations with health outcomes (Reuben et al., 2016). The ACE questionnaire used in this study (see Appendix C) will use the same 10 items (17 questions) and wording as the ACE Study Questionnaire with only minor wording changes, with the exception of the item on separation or divorce of parents. In the ACE Study Questionnaire it is worded “Were your parents ever separated or divorced?” whereas in the ACE Questionnaire used in this study, the item is worded “Was a biological parent ever lost to you through divorce, abandonment, or other reason?” Revised Dyadic Adjustment Scale The Revised Dyadic Adjustment Scale (RDAS; Busby et al., 1995) is a 14-item self-report survey used to measure general dyadic adjustment or relationship quality, and contains three subscales, Consensus, Satisfaction, and Cohesion. Research evidence 85
suggests that it can be accurately used to distinguish distressed from non-distressed couples (Busby et al., 1995). The RDAS is a revised version of the Dyadic Adjustment Scale (DAS; Spanier, 1976), which is considered to be one of the most widely used research instruments to measure relationship quality (Graham, Liu, & Jeziorski, 2006). The RDAS was created using construct hierarchy standards in order to correct some psychometric issues with the original instrument related to heterogeneity within subscales and validity issues with some subscales (Busby et al., 1995). Two of the subscales in the DAS, Dyadic Satisfaction and Affectional Expression showed validity problems when subjected to factor analysis (Busby et al., 1995), and the Affectional Expression subscale showed evidence that reliability varied significantly depending on sample characteristics (Graham et al., 2006). However, for the revised scale, Busby and others (1995) found evidence for construct and discriminant validity for the scale, and in their samples found acceptable internal consistency (ranging from .81 – .85 for subscales and .90 for the total scale) and split-half reliability. Graham and others (2006), in a reliability generalization meta-analysis of the DAS, have shown that the items and subscales retained by the RDAS show evidence of acceptable reliability and that those reliability estimates did not differ significantly across studies on the basis of sexual orientation, gender, marital status, or ethnicity of the sample. Total scores for the scale range from 0 – 69, with lower scores meaning more distressed. Crane, Middleton, and Bean (2000) established a cutoff score of 48 for the RDAS by converting from the established cutoff score on the DAS, so that a total score of 48 or above indicates nondistress and 47 and below indicates relationship distress. Anderson and others (2014) 86
determined a cutoff score of 47.31 through direct examination of the RDAS psychometrics. The RDAS has shown to be an accepted general measure of relationship adjustment vs. relationship distress. Similarly, although the DAS and RDAS have frequently been used as measures of relationship satisfaction in research studies, the measures are designed for and perhaps much better suited to measure relationship adjustment or quality which has been theorized as a composite of dyadic consensus, satisfaction, and cohesion (Ward, Lundberg, Zabriskie, & Berrett, 2009). Finally, the use of RDAS in this current study of the potential relational impacts of ACEs is supported by previous research use of the DAS to examine trauma and couples (Nelson & Wampler, 2000; D. S. Riggs et al., 1998). Data Cleaning and Preparation Data were cleaned using conventional techniques, including checking for outliers, out-of-range or invalid scores, and examining response patterns and missing data. Assumption testing followed to ensure that the data analysis techniques planned for use were appropriate for the data. In addition, where appropriate, data were reorganized into a dyadic structure to enable the dyadic data analysis. Data Analysis Descriptive and inferential statistics were used in this study. Descriptive statistics includes means, range, standard deviations, and frequencies. For Hypothesis 1, ActorPartner Interdependence Model (APIM; Cook & Kenny, 2005; Kashy & Kenny, 1999) was used to test a model of the relative impacts of subject and partner ACE scores on 87
their own and their partner’s RDAS scores. APIM “is a model of dyadic relationships that integrates a conceptual view of interdependence in two-person relationships with the appropriate statistical techniques for measuring and testing it” (Cook & Kenny, 2005, p. 101). APIM was used in this study to address the interdependence issue from a statistical perspective as well as allow for a more dyadic analysis. First, nonindependence of measurements is found in couple relationship data where the couples’ responses are more highly correlated than would be expected from two random individuals. This nonindependence violates the assumption of independence of measurement that is used in many common statistical procedures, biasing the results (Cook & Kenny, 2005; Kenny, 1995). APIM accounts for this interdependence. In addition, individual-centered analysis does not allow for examining how both partners’ childhood trauma exposure histories may interact to contribute to current relationship functioning. APIM accounts for both “actor” and “partner” effects of ACEs on each individual’s reported relationship quality while simultaneously accounting for interdependence between partners. Actor effects in this study are a measurement of how much an individual’s ACE history predicts their current reported relationship quality after controlling for their partner’s ACE history. Partner effects in this study are a measurement of how much the partner’s ACE history predicts the individual’s current reported relationship quality after controlling for their own ACE history. This analysis, which uses structural equation modeling (SEM), also estimated the relationship between both partners’ ACE scores. For Hypothesis 2, cluster analysis was used to look at meaningful score combinations of ACE scores in couple dyads and potential relationships of these groups 88
to RDAS scores. Cluster analysis is a data-driven approach to examining whether data can be meaningfully and usefully divided into groups, which can be useful for diagnostic or intervention purposes (Tan, Steinbach, & Kumar, 2006). For the purposes of this study, due to the limited research on partner selection, cluster analysis was chosen to enable a preliminary test of the ability to group couples meaningfully on ACE score combinations. This is a test of the hypothesis that there are patterns in partner selection relating to the variable of exposure to childhood adverse experiences. The second part of Hypothesis 2 was tested by using an ANOVA to examine whether the clusters (groups) were significantly different on average RDAS scores. This was a preliminary test of the clinical significance of the data-derived groups. For Hypothesis 2, the couple dyad was the unit of analysis. For Hypotheses 3 and 4, logistic regression analyses were used to test hypotheses about ACE scores within couple relationships. Regression analyses are often used to predict a dependent variable based on one or more independent variables (Heppner et al., 2008). More specifically, because the dependent variables were dichotomous, binary logistic regression was used to test Hypotheses 3 and 4. For Hypothesis 3, using logistic regression enabled testing the predictive power of an individual’s ACE scores in predicting their partner’s ACE scores as either more similar (2 or less points apart) or more different (greater than 2 points apart). Logistic regression analyses have been used in much of the ACE research to test for potential ACE-health risk relationships and to adjust for potential confounds (Felitti et al., 1998). These studies also used regression analyses to test for a dose-response relationship and to evaluate increased risk (adjusted 89
odds ratios) of problematic health outcomes for additional ACE exposure (Felitti et al., 1998). For Hypothesis 4, using logistic regression also enabled testing the increased risk of additional ACEs on the likelihood of partnering with someone who has more than minimal ACEs (>1). This analysis will also test whether there seems to be a doseresponse relationship (i.e., whether risk increases with each additional ACE). Both of these analyses were preliminary tests of partner selection on the variable of childhood adverse experiences and also extended Hypothesis 2. Summary This chapter described the research design, questions, and hypotheses, research setting and participants, and instruments that were used in this study. The data analyses that were used were also discussed. Due to limited research on the associations between adverse childhood experiences and later couple relationship outcome (including relationship quality and partner selection), this study was a next step in providing needed dyadic research that can hopefully inform further research efforts and efforts to tailor treatment to couples in distress that are similar to the ones being studied. It is hoped that the study provides some clarification regarding how exposure to childhood adversity can impact both partners’ relationship quality within a couple relationship. It is also hoped that the study provides additional insight regarding individuals’ tendencies to partner with others who have similar or different backgrounds regarding childhood adversity exposure.
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CHAPTER IV RESULTS
Chapter IV presents the results of the testing of the research hypotheses for the current study. This chapter includes (a) data screening and assumption testing, (b) participant demographics, and (c) analysis of the research hypotheses. Data screening, cleaning, and the statistical analyses for Hypotheses 2 – 4 were conducted using the IBM SPSS Statistics version 24. Data Screening and Cleaning Pre-analysis data screening procedures were completed in order to clean data and to ensure that relevant statistical assumptions were not violated. This included examining (a) missing or out-of-range data and likely data entry errors, (b) univariate outliers, (c) normality and multivariate outliers, (d) multicollinearity, and (f) instrument psychometrics. Missing Data Initially, data for 331 individuals (who were identified as having presented for couples therapy) were extracted from the database. Of those, three individuals were missing a partner in the data set and another 10 couples had at least one individual in the couple who was missing a complete measure (one or both of the ACE Questionnaire or RDAS). As the criteria for the study was determined to be couples who completed both 91
of the study measures, it was determined that these cases be removed. This resulted in 154 couples (308 individuals) with usable data. A missing values analysis was conducted to examine patterns of non-response. The results indicated that five participants had not completed four total items (ACE questions 3, 5, 9, and 10). These missing responses totaled between 0.3 – 1.0% for any given item. As the total ACE score was computed based on individual ACE items, the missing responses resulted in 1.7% of the total ACE scores missing. Moreover, Little’s missing completely at random (MCAR) test was not significant, χ2(16) = 12.552, p = .705, indicating that missing data were likely missing at random. Because less than 5% of the data were missing for any single variable and because Little’s MCAR test was non-significant, Expectation Maximization algorithm was used to impute missing values for total ACE scores. Expectation Maximization has been found to compare favorably to other methods such as full information maximum likelihood with regard to its ability to keep intact data variances and covariances regardless of sample size, proportion of data missing, and distributional characteristics of the data (M. S. Gold & Bentler, 2000). Assumption Testing Univariate Outliers Identification of outliers is important in data analysis as outliers may bias results and may make it difficult to generalize results (Stevens, 2002). Boxplots and Z-scores were examined for all variables and as a result, six univariate outliers were identified. Skewness for the variables ranged from -.22 – .77 and kurtosis ranged from -.63 – .33. The outliers were removed from the dataset. 92
Normality and Multivariate Outliers Using chart builder in SPSS, the variables of interest (ACE scores and RDAS scores) were inserted into a scatter/dot matrix. Several plots appeared elliptical in shape indicating potential multivariate outliers. Mahalanobis distance metric was computed to identify multivariate outliers statistically. Based on these Mahalanobis distance values, four cases were identified as multivariate outliers and removed from the dataset. Total number of couples in the final data set was 146. Information in Table 1 was obtained using frequency tests. Histograms of the two variables have also been included (see Figure 1 and Figure 2). Skewness and kurtosis values were within the ±1 range recommended by Meyers, Gamst, and Guarino (2006). When combined with a visual examination of the histograms and Q-Q plots, it was determined that both ACE scores and RDAS scores could approximate normal distributions.
Table 1. Central Tendency, Variance, and Standard Error for Variables Variable
Central Tendency M
ACE
RDAS
Variance
SEM
Med
SD
Skewness (SE)
Kurtosis (SE)
2.58
.127
2.00
2.172
.620 (.143)
-.554 (.284)
40.56
.567
41.00
9.682
-.267 (.143)
-.169 (.284)
Note. ACE = Adverse Childhood Experiences Questionnaire, RDAS = Revised Dyadic Adjustment Scale.
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Figure 1. Histogram of ACE Score with Normal Curve
Figure 2. Histogram of RDAS Score with Normal Curve 94
Linearity According to Kline (2015), linearity between variables is required for SEM analyses. In order to test for linearity a residual plots test was ran. Results indicated linearity, as the overall patterns of residuals was rectangular and not curved, approximating a more random pattern (see Figure 3).
Figure 3. Residual Plot Test for Linearity
Data Restructuring Following initial data screening and cleaning, data were restructured from individual to dyadic level data. This resulted in partners being linked horizontally as dyads in the dataset and separating the main variables into ACE_Score1 and ACE_Score2, and RDAS_Score1 and RDAS_Score2 with 1 and 2 indicating the partner number. This 95
data set was used in the APIM analysis to test Hypothesis 1, as well as in the cluster analysis to test Hypothesis 2. For Hypotheses 3 and 4, the dyadic data set was restructured into a pairwise data set as the unit of analysis changed to the individual for those tests. Multicollinearity According to Meyers and others (2006), multicollinearity can become a problem for the data analysis when bi-variate correlations rise above .75 for independent variables used together. In order to examine the relationship among these variables of interest we computed bi-variate correlations for ACE_Score1, ACE_Score2, RDAS_Score1, and RDAS_Score2 (see Table 2). All bi-variate correlations (-.25 – .43) are well below the .75 level.
Table 2. Pearson Correlation Matrix Among ACE_Score1, ACE_Score2, RDAS_Score1, and RDAS_Score2 ACE_Score1 ACE_Score1 ACE_Score2 RDAS_Score1 RDAS_Score2
.178* -.246* -.146
ACE_Score2
-.108 -.107
RDAS_Score1
RDAS_Score2
.426*
*. Correlation is significant at the 0.05 level. **. Correlation is significant at the 0.01 level.
In addition, variance inflation factor values (VIF) were calculated (ranging from 1.04 – 1.28) and were also well below the threshold of VIF < 10 indicated by Stevens (2002), also indicating that multicollinearity is not an issue for this analysis. 96
Instrument Psychometrics Properties of ACE. Internal reliability of the ACE Questionnaire for this sample was analyzed yielding a Chronbach’s alpha of .693, indicating acceptable internal consistency. Removal of any one item did not significantly improve the internal consistency (Chronbach’s alpha ranging from .639 - .694 for item removal). The mean ACE score was 2.58 (SD = 2.172), with scores ranging from 0 - 8. The frequency of responses for each ACE item is listed below in Table 3.
Table 3. Frequency of ACE Reported
ACE Item
Frequency Percent (n) (%)
1 2 3 4 5 6 7 8
Emotional Abuse 113 Physical Abuse 68 Sexual Abuse 54 Emotional Neglect 95 Physical Neglect 31 Parental Loss/Divorce 114 Maternal IPV 35 Household Alcohol/ 110 Drug Abuse 9 Household Mental 97 Illness/Suicide Attempt 10 Household Incarceration 38
38.7 23.3 18.5 32.5 10.6 39.0 12.0 37.7 33.2 13.0
Properties of RDAS. Internal reliability of the RDAS for this sample was analyzed yielding a Chronbach’s alpha of .809, indicating acceptable internal consistency. Removal of any one item did not significantly improve the internal consistency (Chronbach’s alpha ranging from .790 - .818 for item removal). The mean 97
RDAS score was 40.56 (SD = 9.682), with scores ranging from 14 – 63. Using the cutoff score of 47.31 as determined by Anderson and others (2014), approximately 74.7 % of the sample fell below the cutoff score and could be defined as distressed, and 25.3% of the sample fell above the cutoff score and could be defined as non-distressed. Descriptive Statistics The final sample included 292 adults (146 couples) who presented for couples therapy at a Midwestern university clinic between January 2016 and August 2017. The distribution of Age in the sample was positively skewed (skewness = 1.031, SEskewness = .143) with an average age of 35.3 (med = 32.9, SD = 11.1), and with ages ranging from 18 to 70 years old. A majority of participants reported their race/ethnicity as being White (66.4%), followed by African American/Black (21.6%), ‘More than one ethnicity/Multiracial’ (3.1%), Other (2.1%), Arab American (1.4%), Asian American (1.4%), Latino/a American/Hispanic (1.4%), and Native American (.3%). Due to the inclusion of same-sex couples (see Hypothesis 1 below for rationale), the sample was not split exactly by gender, with the sample being 50.7% Female (n = 148) and 49.0% Male (n = 143). A majority of the participants reported their sexual orientation as being Heterosexual (85.3%), followed by ‘Prefer not to answer’ (7.2%), Bisexual (2.4%), Lesbian (1.7%), and Gay (.3%). Most participants identified as being Married (38.0%), followed by Living Together/Cohabitating (28.4%), Dating (16.8%), Partnered (4.8%), Single (4.5%, and Separated (3.4%). See Table 4 for complete sample demographics. In addition to the above descriptive statistics, some additional demographics were collected and available in the database only after the first three months of data collection 98
(which were from January 2016 – March 2016). These demographics (including employment status, educational level, annual household income, and household size) were thus available for only a subset (n = 222) of the total sample. These categories of demographic information were able to be accessed from dates April 2016 – August 2017 and are included for the partial sample below in Table 5. As noted above, demographics that were collected for the entire sample (N = 292) are included in Table 4 below.
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Table 4. Sample Demographic Frequencies (Full Sample)
Variable
Frequency Percent (n) (%)
Gender Female Male Transgendered
148 143 1
50.7 49.0 .3
Sexual Orientation Heterosexual Prefer Not to Answer No response – Missing Bisexual Lesbian Gay
249 21 9 7 5 1
85.3 7.2 3.1 2.4 1.7 .3
Race/Ethnicity Caucasian/White 194 African American/Black 63 More than 1 Ethnicity/ 9 Multiracial Not Reported 7 Other 6 Arab American 4 Asian American 4 Latino/a American/ 4 Hispanic Native American 1 Relationship Status Married Living Together/ Cohabitating Dating Partnered Single Separated No Response Divorced Remarried No Response - Missing
66.4 21.6 3.1 2.4 2.1 1.4 1.4 1.4 .3
111 83
38.0 28.4
49 14 13 10 8 2 1 1
16.8 4.8 4.5 3.4 2.7 .7 .3 .3 100
Table 5. Sample Demographic Frequencies (Partial Sample). Partial Sample, n = 222, collected April 2016 – August 2017)
Variable
Frequency Percent (n) (%)
Employment Status Employed Full-Time Employed Part-Time Unemployed, seeking Student Unemployed, not seeking Retired Disabled Prefer not to answer
114 42 22 16 13 8 6 1
51.4 18.9 9.9 7.2 5.9 3.6 2.7 .5
Annual Household Income $20,000 - $50,000 Less than $20,000 $50,000 - $75,000 More than $75,000 Prefer not to answer
104 70 21 14 13
46.8 31.5 9.5 6.3 5.9
69 46 44
31.1 20.7 19.8
36 18 9
16.2 8.1 4.1
Household Size No Response 1 2 3 4 5 6 7
2 12 56 62 52 28 5 5
.9 5.4 25.2 27.9 23.4 12.6 2.3 2.3
Persons under Age 18 in Home 0 1 2 3 4 5
81 60 49 26 4 2
36.5 27.0 22.1 11.7 1.8 .9
Educational Level Some college Bachelor's degree Completed high school (or equivalent) Associate's degree Graduate degree Some high school
Note. Percentages are in reference to the partial sample size. 101
Hypothesis 1: APIM Prior to the analysis, gender in the sample was examined in order to determine whether it could be used to distinguish members in the APIM model. Mean differences across levels of gender were investigated using paired samples t-tests. There was no statistically significant difference between genders on RDAS scores, t(145) = -1.188, p = .237, with males and females scoring similarly (MRDAS for Females = 40.05, MRDAS for Males = 41.07). There was also no statistically significant difference between genders on ACE scores, t(145) = 1.292, p = .198, with males and females scoring similarly (MACE for Females = 2.74, MACE for Males = 2.44). In addition, preliminary analyses using APIM were completed in order to test for distinguishability, in other words, whether members can be statistically distinguished based on Gender. A model comparison test was made between a model with distinguishable members and a model with indistinguishable members. The test of distinguishability yielded a non-significant result, χ 2(6) = 9.88, p = .130. The paired t-tests combined with the test of distinguishability indicated that a model with indistinguishable members was more feasible. Using this model also allowed retaining couples in the data set that would otherwise be excluded (i.e., same-sex couples). The APIM model was tested with structural equation modeling and using APIM_SEM, a web-application for dyadic data analysis (Stas, Kenny, Mayer, & Loeys, n.d.) (see https://larastas.shinyapps.io/APIM_SEM/). APIM_SEM uses lavaan, an Rpackage for analyzing latent variables (Rosseel, 2012). APIM was chosen in order to model potential actor and partner effects of ACE scores on RDAS scores within the 102
couple dyad. This dyadic analysis accounted for non-independence of measurement between partners in a dyad on RDAS scores. A summary of the APIM results are included in Table 6 below. The lavaan model converged after 53 iterations. The variance of the errors was found to be 89.54. The R2 value was 0.04. The partial intraclass correlation for RDAS while controlling for the other predictor variables was 35.91 and was statistically significant (p < .001, 95% CI [19.63, 50.38]). This indicates that, after controlling for the predictor variables, when one member of the dyad scores high (low) on the RDAS, the other member also tends to have a high (low) score. The reported intercept (the predicted score on RDAS when the ACE Score equals zero) for indistinguishable members is statistically significant and equal to 43.55 (p < .001, 95% CI [41.07, 46.11]). Results from the analysis indicated a statistically significant actor effect equal to -0.73 (p = .004, 95% CI [-1.24, -0.25]). The standardized actor effect was found to be -0.16 (partial r = -.16). Results indicated a non-statistically significant partner effect equal to -0.42 (p = .09, 95% CI [-0.99, 0.02]), with an overall standardized partner effect of -0.10 (partial r = -.09). Figures 4 and 5 below show the standard model as well as the model with standardized parameter estimates. See Figure 6 below for a plot of the Actor and Partner effects that accounts for all estimated parameters. The relative effect sizes of the actor and partner effects were calculated by the model. The effect size value k, defined as the ratio of the partner effect to the actor effect, was able to be interpreted because the standardized actor effect was found to be greater than 103
.1 in absolute value and was statistically significant. The value of k was found to be 0.58. Regular bootstrapping with 500 samples was used in order to calculate the confidence interval of k. Given k’s calculated 95% CI [-0.05, 1.59], for the indistinguishable model, it can be concluded that both the couple (k = 1) and the actor-only models (k = 0) are plausible.
Table 6. APIM Results
Effect Intercept Actor Partner k
Estimate
95% Confidence Interval Lower Upper
43.55 -.73 -.42 .58
41.07 -1.24 -.99 -.05
to 46.11 to -.25 to .02 to 1.59
p value
Beta
r
Minimal ACEs
100 83.9 80
73.2 56.6
60
72.2 61.5
60 52.2
45 40
20
0
0
1
2
3
4
5
6
7
8
ACE Score Figure 9. Percent of Partners with More than Minimal ACEs by ACE Score
Chapter Summary This chapter included the results of data cleaning and preparation, statistical assumption testing, and demographic information. This chapter also included a presentation of the results of the statistical testing of the four hypotheses. No substantial violations to statistics assumptions were found. Descriptive statistics were reported. Results indicated evidence to support the role of childhood adversity exposure on current 113
relationship quality, though lack of partner effects in the analysis of this sample fails to provide evidence for significant interactive effects of an individual’s childhood adversity history on their partner’s current relationship quality. There was some preliminary evidence from the results that partner selection may be patterned by childhood adversity exposure history. There was also some preliminary evidence that an individual’s childhood adversity exposure is at least partially related to who they choose to partner with. In Chapter V, the results will be further discussed to include implications of the findings and future research.
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CHAPTER V DISCUSSION
This chapter will review the results of the statistical analyses compared with hypothesized results, and discuss the implications of the findings. The chapter will then include a discussion of the limitations of the research, future research directions, and a summary and conclusion for the study. Summary of Present Study The present study was conducted in order to attempt to address a gap in the research relating to the role of adverse childhood experiences (ACE) (cumulative childhood trauma) on later adult couple relationships and the lack of dyadic research related to trauma and its effects. The present study used secondary data from a clinical source in order to test relationships between adverse childhood experiences and the later adult relationship outcomes of relationship quality and partner selection. The data was screened and analyzed in preparation for the statistical analyses. A dyadic data analysis was completed using APIM to test hypotheses about dyadic patterns. A cluster analysis was used as a preliminary test of the ability to group couples by ACE score combinations. Regression analyses were used to test hypotheses about partner selection. Results for these data analyses were reported and presented. A detailed discussion of the hypothesis testing will be included below. 115
Results of Hypotheses Testing Hypothesis 1 Alternative Hypothesis 1 posited that there would be significantly negative direct effects of a subject’s ACE scores on their own RDAS scores (actor effects) and their partner’s RDAS scores (partner effects) and of the partner’s ACE scores on their own RDAS scores (actor effects) and the subject’s RDAS scores (partner effects). This hypothesis was only partially supported by the analysis. The structural equation model for APIM found significant actor effects for both partner 1 and partner 2, such that ACE scores had a negative direct effect on their own RDAS scores. No significant partner effects were found. The model effect sizes for the actor effects (partial r = -.16) are considered by (Ferguson, 2009) to be small and less than the .2 “recommended minimum effect size for a ‘practically’ significant effect for social science data,” also called the RMPE (p. 533). The finding of an actor effect fits with the general hypothesis that a history of childhood adversity will tend to have a negative effect on later adult relationship quality. This result also fits with the one extant study on ACEs that measured a relational outcome (Gilbert et al., 2015), which found a dose-response relationship between ACE scores and likelihood of frequent marital distress. The overall higher levels of distress in the sample may be partially responsible for the smaller size of the effect as a large majority of the couples were clinically distressed. The lack of a significant partner effect may also be partially due to sample characteristics (such as power, sample size, restricted range for RDAS). The partner effect, though not significant in this sample and model, was in the expected direction and similar in effect 116
size to the actor effects found (partial r = -.09). Further research with different samples may clarify whether evidence can support this part of the hypothesis. At present, with these preliminary results, evidence does not as yet support the hypothesized systemic model of interacting effects of ACE scores and RDAS scores within the dyad. The estimated effect size for the relationship between ACE scores of partners was found to be significant though also small (partial r = .17). This result provides partial support for the hypothesis that trauma history is similar between partners (Chen & Carolan, 2010; Goff & Smith, 2005), however, the size of the effect is small in this sample. One final finding of the APIM model was that of significant non-independence in RDAS scores in couple dyads (partial r = .4), a moderate to large effect size (Ferguson, 2009). The non-independence in this model means that RDAS scores between partners are more similar than they are between individuals and other members of the data set (violating the independence of measurements assumption). This nonindependence of dependent variables confirms the use of a dyadic data analysis and provides evidence that typical statistical procedures used with this kind of data (which do not account for this non-independence) will be biased (Kenny, 1995). Hypothesis 2 Alternative Hypothesis 2 posited that couples would be able to be statistically grouped by ACE score combinations and that if so, there would be group differences on average RDAS scores. This hypothesis was partially supported in that the cluster analysis was able to find an adequately fitting three cluster solution. There seemed to be a clustering around a predominately Low1-Low2 group with a group average of 117
approximately one ACE for each partner. Cluster two (High1-Moderate2) was a grouping of predominately high ACEs for partner number 1 (which was predominately female in gender) with an average of approximately 5 ACEs, and a moderate amount of ACEs for partner number 2 (which was predominately male in gender) with an average of 2 – 3 ACEs. Cluster three (Moderate1-High2) was a grouping of predominately moderate ACEs for partner number 1 with an average of approximately 2 ACEs, and a high amount of ACEs for partner number 2 with an average of 5 – 6 ACEs. This preliminary test of clustering found some evidence that couples could be statistically grouped by ACE score combinations, at least within this sample. As clustering can be sample dependent, in order to confirm these findings, they would need to be replicated in other samples. One preliminary interpretation of these findings is that on the whole, persons with low ACEs may tend to partner with those who also have low ACEs, and that those with high ACEs (both genders) may tend to partner with those who have more moderate ACEs. As there was no previous studies, to this researcher’s knowledge, that attempted to cluster couples based on ACE scores, there is no research at present with which to compare these findings. It does seem to provide at least some partial evidence of similarity with regard to trauma history (Chen & Carolan, 2010; Goff & Smith, 2005) although it appears more complicated than a simple one-to-one similarity. Finding whether couples do tend to have patterns with regard to partnering on ACE history could be clinically relevant for taxonomy purposes and for developing tailored treatments, as well as better understanding partnering in dual trauma couples.
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As noted in Chapter 2, increased health and mental health risks for higher ACEs mean that when they accumulate within couples (for example the High1-Moderate2 and Moderate1-High2 groups), it would make sense that there would also be an accumulation of potential genetic and environmental risk factors (Nordsletten et al., 2016) and potentially worse outcomes. This hypothesis was partially tested by testing for group differences on RDAS scores between the defined clusters. The second part of Alternative Hypothesis 2 was partially supported in the finding of a group difference between the Low1-Low2 and High1-Moderate2 groups. This indicated that the group of couples with predominately high ACE for mostly female partners and moderate ACEs for mostly male partners had the lowest overall RDAS scores (i.e., were the most distressed), followed by the Moderate1-High2 group then the Low1-Low2 group. No significant differences were found between the Low1-Low2 and Moderate1-High2 groups. Even though a significant group difference was found, it is unclear whether the difference is clinically meaningful. For this particular sample, all of the average group RDAS scores were below the distressed couple cutoff score (see Figure 8) including the Low1-Low2 group, and the absolute average difference in RDAS scores between the Low1-Low2 and High1Moderate2 groups was only 4.6. The partial η2 effect size for this difference was found to be .072, which according to Ferguson (2009), is between a small and moderate effect (.25), and greater than the .04 level for a RMPE. Although practically significant, if the group difference had spanned the distress/non-distress cutoff score, clinical relevance would be much clearer. This finding should be considered preliminary until further clarified by future research. The overall higher levels of distress in the sample may be 119
partially responsible for the lack of greater differences between the groups. If this is the case, then testing a more varied sample with regard to distress levels might reveal more conclusive findings. Similar to the first part of Hypothesis 2, there is no extant research that has been done that could be used to directly compare these results. Indirectly, these results partially fit with some of the research trends on the impacts of trauma on couples, where couples with some abuse history tended to report more relationship distress than those with no abuse history (Nelson & Wampler, 2000). Hypothesis 3 Alternative Hypothesis 3 posited that there would be a significant relationship between ACE scores of partners and that there would be more similarity than differences in ACE scores between partners. There was partial support for this hypothesis in the analysis. A one sample chi-square test confirmed that, according to the operational definition of similarity (ACE scores 2 or less apart) and difference (ACE scores 3 or more apart), more couples had similar scores than different scores (66% to 34%). In addition, a significant logistic regression test provided some evidence that similarity with partners depends partially on ACE scores. For lower levels of ACEs there was more likelihood of similarity of ACE scores in partners, however similarity in ACE scores tended to decrease in likelihood as an individual’s ACE score increased. The standardized odds ratio was 2.18, which is marginally more than the 2.0 RMPE suggested by Ferguson (2009), considered a small effect size. In addition, using different definitions of similar vs. different did seem to have an important impact on the findings, with a more stringent definition of similarity (ACE scores 1 or less apart) and difference 120
(ACE scores 2 or more apart) flipping the results to a finding of more difference than similarity in the sample (58% to 42%). Ultimately it may be up to clinicians or theoreticians to determine which definitions seem to make more sense. As there was no previous studies, to this researcher’s knowledge, that attempted to examine similarity and differences between couples on ACE scores, there is no research at present with which to compare these findings. These findings do appear to fit with the findings from Hypothesis 2, showing more similarity at lower levels of ACE scores. Hypothesis 4 Alternative Hypothesis 4 posited that there would be a relationship between increasing ACE scores and increased likelihood of having a partner with an ACE score greater than 1. This was a preliminary test of a dose-response relationship with regard to couple outcomes. This hypothesis was partially supported by the analysis. A significant logistic regression test provided some evidence that having a partner with more than minimal ACEs (ACEs greater than 1), depends partially upon the subject’s ACE score. The interpretation of this finding is that as individual ACE scores increases by one, they are somewhat more likely (22% more likely), to have a partner with more than minimal ACEs. The size of this effect (standardized odds ratio of 1.56) is small and less than the 2.0 RMPE suggested by Ferguson (2009). Results did not seem to vary significantly with a different definition of minimal ACEs. The overall trend towards increased likelihood of partnering with someone who has more than minimal ACEs builds upon ACE studies discussed that have found evidence of dose-response relationships (Felitti et al., 1998).
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No other studies to date have directly examined risk factors with ACEs and relationship outcomes. Future research will be needed to confirm these preliminary findings. Implications for the Field The results of this study, while intriguing, are still preliminary, due to the use of a sample which limits generalizability as well as the use of research questions that are new and have yet to be tested more broadly. Some implications however can be examined. One of the purposes of this study was to examine interactions within couple relationships. Relationships were found between partners on ACE scores and between partners on RDAS scores. Conversely, little evidence was found in this study to support the hypothesis of interactional effects from an individual’s ACE scores to their partner’s RDAS scores. However, lack of evidence in this case only means that statistical significance was not found in this sample with this methodology. Due to the implications for systemic theory and treatment, future systemic researchers should continue to examine this hypothesis until it is clearer whether the evidence supports it or not. There was however, evidence within the analysis to support the use of dyadic data analysis with couples. Couples researchers need to be aware that nonindependence of data between couples may bias statistical analyses and so dyadic analyses should be used wherever possible. There may also be some implications for clinical practitioners who see couples. There was some evidence from the findings that adverse childhood experiences have negative impacts far later on relationship quality. Couple therapists need to be assessing for ACEs and learn how to treat couples within the context of experiences of childhood 122
trauma. For example, Emotionally Focused Couple Therapy is a systemic and highly researched theory that has some initial evidence of effectiveness in treating couples with both PTSD and childhood abuse (Dalton et al., 2013; Greenman & Johnson, 2012; S. M. Johnson & Williams-Keeler, 1998; MacIntosh & Johnson, 2008). Cognitive-Behavioral Conjoint Therapy for PTSD is also a well-researched model for treating PTSD within the couple context (Brown-Bowers, Fredman, Wanklyn, & Monson, 2012; Fredman, Vorstenbosch, Wagner, Macdonald, & Monson, 2014; Monson & Fredman, 2012; Monson, Rodriguez, & Warner, 2005; Shnaider, Pukay-Martin, Fredman, Macdonald, & Monson, 2014). Models such as these encourage universal screening of childhood trauma when treating couples and having an in-depth understanding of both the intrapsychic and interpersonal effects of trauma. Limitations The present study had several limitations. Limitations regarding the methodology, sampling, secondary data set, and measurement issues used will be discussed. This section will be followed by future research directions, some of which may be used to address some of these limitations. This study was limited due to its use of a retrospective, correlational research design. These kinds of designs are limited in that they do not allow a determination of causality and are thus generally seen as less conclusive than experimental designs or prospective, longitudinal designs (Norman et al., 2012). Even though this may be the case, retrospective designs likely play an important role in social science research and
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may reach a different population than the prospective designs (Kendall-Tackett & Becker-Blease, 2004). The sampling technique used to generate the secondary data for this study was essentially non-probability convenience sampling. Convenience sampling can limit generalizability. In addition, convenience sampling often limits the diversity of the sample which may prevent in-depth analysis of subgroups (such as race/ethnicity, sexual minority couples, and so forth). Thus, although the sample did include same-sex couples, the lack of purposive sampling that would have been needed to increase representation of these couples meant that the number of these couples was too small to enable valid comparisons between groups. All participants also self-selected into couples counseling which likely introduced a selection bias in the sample. There are likely important differences between the clinical sample and other populations of interest which may then limit generalizability. For example, the sample used was more distressed than typical couples (74.7% of the sample fell below the cutoff for being defined as distressed). A more distressed sample may have weakened the effect of ACEs on relationship quality due to other potential causes for low relationship quality (i.e., presenting concerns unrelated to trauma history). Still, due to the exploratory nature of the hypotheses, a convenience sample could be considered appropriate at least as a preliminary test of the concepts. Another important limitation of the study is that the analysis was unable to include important covariates that may have influenced the variables of interest. As noted previously, a number of important demographic questions were only partially represented 124
in the database due to not being answered by the whole sample. Although some studies have found that important health risks and negative outcomes still exist even after accounting for socioeconomic factors (Bellis et al., 2017; Font & Maguire-Jack, 2016; Ports et al., 2016), it still remains to be seen whether this is the case when looking at relationship outcomes. Accounting for other potential explanations for relationships between variables by using covariates can strengthen the analysis and provide more evidence of a real relationship between variables (such as ACEs and relationship outcomes). In addition, because a secondary data set was used, the researcher could not add other variables that might be associated with the variables of interest. For instance, knowing length of relationship could have enabled examining, for example, longer term, committed relationships, as there are theoretical reasons to hypothesize that the impact of ACEs on relationship quality may depend on the developmental stage of the couple (Walsh, 2012b). Other measures that might be added in future research might include other relationship quality and adjustment measures that could be chosen based on their measuring of relationship outcomes that have specifically been hypothesized to be impacted by trauma in the relationship. In addition, the study relied exclusively on self-report measures which may be biased. As noted in the literature (Hardt & Rutter, 2004; Kendall-Tackett & BeckerBlease, 2004), retrospective reporting of childhood adversity may result in underreporting of trauma experiences which may bias estimates. In addition, in this study, both individuals in a couple dyad would typically complete the measures sitting together in close proximity in the waiting area prior to their first session. It is possible that being by 125
their partner while completing the measure may have biased their responses, particularly towards not reporting stigmatized elements or elements that they have previously not disclosed to their partner. If underreporting of ACEs was prevalent due to these factors, it is likely that the estimates found in the analyses may be higher. Future Research Directions One of the strengths of the ACE study framework is that there is a built in control group of individuals who report zero ACEs. Zero ACEs however does not mean notrauma, as individuals may have experienced trauma as an adult. Research has provided evidence that relationship quality is significantly impacted by adult-onset trauma (Monson et al., 2009), so inclusion of these couples in the analysis might reduce any statistical relationship between ACEs and relationship quality. In future studies of ACEs and couples, adult-only trauma participants may need to be assessed for and separated out from the sample so that zero ACEs is a valid control group from which to compare. Alternatively, future research could specifically explore the relationship between childhood and adult trauma. As previous research has indicated that there is a relationship between some forms of childhood abuse and increased likelihood of becoming an adult victim or perpetrator of intimate partner violence (Smith-Marek et al., 2015; Stith et al., 2000), future research could also focus on couples with a history of interpersonal violence and early childhood trauma and potential links between the two. Ultimately, research models will need to find a way to bridge both childhood and adult traumas, because separating them out may not be valid or generalizable due to the significant population of people who have both childhood and adult trauma histories. 126
In general, future studies should use random sampling to increase the ability to generalize the findings. In addition, due to the preliminary findings showing some impact of ACEs on relationship quality, future research should use a variety of samples to continue to test this main hypothesis, including using a nonclinical sample which would be more likely to have a broader range of relationship quality scores, with a better balance between distressed and non-distressed couples than in the current sample. Even replicating the study with other clinical samples would allow seeing if the present findings were typical for a clinical sample or if this particular sample is not well representative of clinical samples in general. Other diverse samples of interest should also be studied such as LGBT couples, diverse racial/ethnic couples, and economically disadvantaged populations. Summary The purpose of the present study was to examine patterns in couple relationships with regard to ACE scores and the relationship outcomes of relationship quality and partner selection. A dyadic data analysis of secondary data from a clinical source was used. Results of the dyadic data analysis indicated that ACE scores of individuals have a small but significant impact on their own reported relationship quality scores, and that there is a small but significant relationship between partner ACE scores. A cluster analysis of the data indicated that couples can be grouped by ACE score combinations and that there are some small but significant differences between at least two of the groups. A chi-square analysis indicated that couples are more likely to partner with those who have more similar than different ACE scores, and a follow-up regression analysis 127
indicated that as ACE scores increase, the likelihood of partnering with someone who is similar will decrease. Finally, a regression analysis indicated that there is a small but significant dose-response relationship between increasing ACE scores and the likelihood of partnering with someone who has more than minimal ACEs. These results suggest relationships between ACEs and relational outcomes. Adverse childhood experiences seem to impact not just health and mental health outcomes, but also later relationship quality and patterns of partner selection. The present study encourages the continued research of ACEs and trauma exposure on couple/family outcomes in order to continue to explore and build upon an existing literature base of individual outcomes. As the analyses done in this study are exploratory and preliminary, much more needs to be done in this field to examine if evidence will continue to build regarding the negative impacts of cumulative childhood trauma exposure on adult relationships. It is hoped that the present study will also encourage continued dyadic research on trauma that may be able to extend and provide evidence for MFT’s systemic theories. Ultimately it is hoped that this relational and systemic research lens will be able to contribute to research, clinical, and prevention efforts to help stem the tide of the public health crisis of childhood trauma (Campbell et al., 2016).
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APPENDICES
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APPENDIX A CLIENT INFORMATION FORM
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APPENDIX B ADVERSE CHILDHOOD EXPERIENCE (ACE) QUESTIONAIRE
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APPENDIX C INSTITUTIONAL REVIEW BOARD (IRB) APPROVAL FOR STUDY
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