The Impact of Rejection Sensitivity and Interpersonal Aggression on Social Network Characteristics in Individuals with Borderline Personality Disorder Features

Home , Trust (social science)

Thesis

Presented in Partial Fulfillment of the Requirements for the Degree Master of Arts in the Graduate School of The Ohio State University

Sophie Anna Lazarus

Graduate Program in Psychology

The Ohio State University

2011

Master's Examination Committee:

Dr. Jennifer S. Cheavens, Advisor

Dr. Daniel R. Strunk

Dr. Michael W. Vasey

Copyrighted by

Sophie Anna Lazarus

2011

Abstract

Borderline personality disorder (BPD) is a serious mental health problem, which is associated with high rates of health care utilization and cost (Skodol et al., 2005) and severe functional impairment (Skodol et al., 2002). Although various domains of functioning are affected, interpersonal dysfunction is often cited as central to the disorder

(Gunderson, 2007). In addition, interpersonal stress is related to increased likelihood of self-harm (Welch & Linehan, 2002) and has been cited a trigger for suicide attempts

(Brodsky, Groves, Oquendo, Mann, & Stanley, 2006). The aim of the present study was to investigate factors contributing to lower quality social networks in BPD. Specifically, we examined whether rejection sensitivity had its impact on social network quality (size, satisfaction, and stability) through interpersonal aggression, and whether BPD features moderated these relations. Participants completed self-report questionnaires assessing interpersonal aggression, BPD features, and rejection sensitivity over one month and provided information about the individuals in their social networks and characteristics of those relationships. As hypothesized, rejection sensitivity exerted an indirect effect on social network satisfaction through interpersonal aggression. However, this effect was not conditional upon levels of BPD symptoms. BPD features at baseline were related to some indices of instability, such as having cut off speaking to partners in one’s network at one month, and markers of network quality such as, closeness, and support among the partners listed in one’s network at one month. ii

Acknowledgments

First, I would like to express my sincerest gratitude to my advisor, Dr. Jennifer

Cheavens. I am extremely thankful for her guidance, support, and enthusiasm throughout all of the stages of this project. Jen, thank you for sharing your time, knowledge, and creativity with me, your investment in my personal and academic success has meant the world to me. I would also like to thank my committee members, Dr. Michael Vasey and

Dr. Daniel Strunk, for their time and consideration during this project. Their feedback on the design and analyses of the study, have improved it immensely. I also want to thank

Dr. Cudeck, for his time and patience in helping with the preparation of the social network data and his guidance in using SAS for data analysis. I also could not have completed this project without the help of Star Hess and Victoria Alexander, who played an important role data collection and follow-up over the past year. Finally, I would like to thank the graduate students of the MAPS lab for their help with data collection and their support and encouragement throughout this process.

iii

Vita

October 1985 ...... Born – Bronx, New York

2007...... B.A. Psychology, Suma Cum Laude, University of Delaware

2009 to present ...... Graduate Student and Graduate Research Assistant, Department of Psychology, The Ohio State University

Fields of Study

Major Field: Psychology

Minor Field: Quantitative Psychology

Table of Contents

Abstract ...... ii

Acknowledgments...... iii

Vita ...... iv

List of Tables ...... vii

List of Figures ...... viii

Chapters

1. Introduction ...... 1

1.1 Interpersonal Functioning in BPD ...... 3

1.2 Social Interaction and Characteristics of Social Networks in BPD ...... 8

1.3 Rejection Sensitivity ...... 14

1.4 Aggression in BPD ...... 21

1.5 Current Study ...... 26

2. Methods...... 28

2.1 Participants ...... 28

2.2 Measures/Instrumentation ...... 29

2.3 Study Procedure ...... 33

3. Results ...... 36

3.1 Data Analytic Plan and Preparation ...... 36

3.2 Descriptive Results ...... 41

3.3 Hypothesis Testing...... 42

3.4 Hypothesis 1...... 42

3.5 Hypothesis 2...... 42

3.6 Hypothesis 3...... 46

3.7 Supplementary Analyses ...... 48

4. Discussion ...... 51

References ...... 63

Appendix A: Social Network Assessment ...... 75

Appendix B: Tables ...... 80

Appendix C: Mediation and Moderated Mediation Models ...... 91

List of Tables

Table 1. Means, Standard Deviations, and Intercorrelations Among Network and

Personality Variables for Main Analyses ...... 81

Table 2. Network Characteristics Averaged Across Partners at Baseline and One Month

...... 82

Table 3. Network Composition and Overall Characteristics at Baseline and One Month

...... 83

Table 4. Summary of Simple Regression Analyses for Baseline Rejection Sensitivity

Predicting Social Network Quality Characteristics at One-Month ...... 84

Table 5. : Summary of Simple Regression Analyses for Rejection Sensitivity at Baseline

Predicting Aggression at One week ...... 85

Table 6. : Summary of Simple Regression Analyses for Aggression at One Week

Predicting Social Network Quality at One-Month...... 86

Table 7. : Test of Moderated Mediation of a1 Path by BPD Symptoms ...... 87

Table 8. : Test of Moderated Mediation of b1 Path by BPD Symptoms ...... 88

Table 9. : Intercorrelations between BPD Symptoms, Stability and Other Network

Characteristics for Supplementary Analyses ...... 89

Table 10. : Intercorrelations between BPD Symptoms, Stability, and Partner

Characteristics ...... 90

vii

List of Figures

Figure 1. Timing of Administration for Measures ...... 76

Figure 2. Model of Simple Mediation...... 92

Figure 3. Proposed Simple Mediation ...... 92

Figure 4. Model of Moderated Mediation...... 93

Figure 5. Proposed Model of Moderated Mediation ...... 93

viii

Chapter 1: Introduction

Borderline personality disorder (BPD) is a serious challenge for mental health professionals, those suffering from the disorder, and their families. The disorder is characterized by a constellation of debilitating symptoms. Diagnostic criteria include fear of abandonment, unstable interpersonal relationships, identity disturbance, impulsiveness, non-suicidal self-injury, affective instability, chronic emptiness, inappropriate intense anger, and transient dissociative symptoms (American Psychiatric Association, 2000).

The criteria for BPD touch on almost all facets of human functioning, including cognitive, behavioral, interpersonal, and emotional domains.

BPD affects from 1.2% to almost 6% of the population (Grant et al., 2008), mostly women (75%; American Psychiatric Association, 2000). Research on the course for the disorder yields varied results. The DSM-IV suggests that symptoms abate, or

“burn out”, with age (American Psychiatric Association, 2000), while others fail to find this pattern (Shea et al., 2009). However, one common finding is that even when symptoms are attenuated over time, the comprehensive constellation of BPD generally does not fully remit. Symptoms such as affective instability remain after individuals no longer meet criteria for BPD; and higher levels of BPD features appear to predict poorer outcomes in academic achievement and social adjustment (Bagge et al., 2004; Paris &

Zweig-Frank, 2001). The impact of BPD on multiple domains of functioning makes it a

1 highly impairing disorder with serious implications for the individuals’ social functioning and overall quality of life. Given the heterogeneity the disorder, specific targets are necessary for research and treatment. Thus, in addition to research efforts focused on the diagnosis of BPD, examining problem areas or symptom clusters that contribute to poor adjustment in this population may be a fruitful research area. While emotion dysregulation is a common focus of research, the interpersonal problems that characterize

BPD receive less attention.

Understanding the ways in which the interpersonal domain is both impacted by and impacts the experience of BPD is an important target as there is some evidence that problems in this area are related to serious outcomes such as suicide attempts and suicide

(e.g., Brown, Comtois, & Linehan, 2002). These outcomes are disturbingly common among those suffering from BPD. Approximately three quarters of those with BPD attempt suicide and there is a 10% lifetime suicide completion rate, which is 50% more than is observed in the general population (Black, Blum, Pfohl, & Hale, 2004; Soloff, Lis,

Kelly, Cornelius, & Ulrich, 1994). Of particular interest is that non-suicidal self-injury and suicide attempts in BPD are often related to interpersonal stressors or cues of abandonment that might seem minor to others. An example of this might be an individual threatening suicide in response to a romantic partners’ leaving or engaging in non- suicidal self-injury to relieve the tension associated with an unresolved interpersonal conflict. Furthermore, in one study of individuals with Major Depressive Disorder

(MDD) plus BPD or MDD only who had a history of at least one suicide attempt, those with co-morbid BPD were more likely to have suicide precipitants that were interpersonal

(Brodsky, Groves, Oquendo, Mann, & Stanley, 2006). This finding highlights the seriousness of interpersonal events for individuals with BPD.

In addition to specific interpersonal events, social adjustment in general is important in predicting suicide attempts (Soloff & Fablo, 2008). Individuals with BPD often experience a loss of support from family and friends, and may isolate themselves by ending relationships preemptively to avoid difficult feelings or interactions, creating few resources for building a positive social environment. In a study of individuals with BPD,

MDD, and both BPD and MDD, lower overall social adjustment was predictive of suicide attempter status, regardless of diagnosis. There was also a significant interaction between social adjustment and diagnostic status suggesting that those with BPD and low overall social adjustment were most likely to attempt suicide (Kelly, Soloff, Lynch, Haas,

& Mann, 2000). Consistent with these findings, clinical observations of individuals with

BPD suggest that they function more effectively when in secure, supportive relationships

(Linehan, 1993) and research findings indicate that remission from the disorder is often related to positive interpersonal events, such as entering a stable relationship (Links &

Heslegrave, 2000). Thus, understanding the factors that lead to poor interpersonal functioning and the deterioration of social support in BPD is an important direction to examine in future research on the disorder.

Interpersonal Functioning in BPD

Disturbed interpersonal relationships are often acknowledged as a central feature of BPD (Gunderson & Lyons-Ruth, 2008). Furthermore, interpersonal relationships in

BPD are known for being stormy and highly distressing for patients and others with 3 whom they interact. Of the nine criteria for BPD in the DSM-IV-TR (American

Psychiatric Association, 2000), two of them are interpersonally relevant; intense fears of abandonment in relationships and alternating between extreme idealization and devaluation of one’s partner. In addition, interpersonal features are central to the diagnostic criteria for the disorder in the Revised Diagnostic Interview for Borderlines

(DIB-R; Zanarini, Gunderson, Frankenburg, & Chauncey, 1989). Features listed in the

DIB-R that are not in the DSM-IV include intolerance of aloneness, counter-dependency, dependency/masochism, demandingness/entitlement, treatment regressions, and counter- transference problems. Similarly, Linehan (1993) cites interpersonal relations as one of the five areas considered to be dysregulated in BPD. Moreover, psychosocial functioning in BPD tends to be more impaired than in other Axis II disorders, and improvement in social symptoms is more gradual in BPD than in other disorders (Choi-Kain, Zanarini,

Frankenburg, Fitzmaurice, & Reich, 2010; Skodol et al., 2005). In fact, certain interpersonal symptoms such as negative affect when alone, fear of abandonment, discomfort with care, and dependency, are extremely slow to remit, with 15% to 25% of individuals with BPD who exhibited these symptoms at baseline failing to show improvement at 10-year follow-up (Choi-Kain Zanarini, Frankenburg, Fitzmaurice, &

Reich, 2010).

In addition to diagnostic criteria, all major theories of the etiology, maintenance, and treatment of BPD include some discussion of disrupted interpersonal functioning.

Extensive research in the area of BPD focuses on attachment style as a contributor to disturbed interpersonal functioning in the disorder (Kernberg, 1967). According to this

4 literature, feedback from early relationships with a caregiver sets up a working model for an individual’s expectations of others. Theorists posit that because of inconsistent, neglecting, and invalidating environments, individuals with BPD fail to form secure attachments with their caregiver, which contributes to problems with intolerance of aloneness and disturbed self-image (Gunderson & Lyons-Ruth, 2008). In a review of the literature on attachment, BPD was consistently associated with insecure attachment

(Agrawal, Gunderson, Holmes, & Lyons-Ruth, 2004). Despite some variation in the types of insecure attachment assessed, the most common finding was of unresolved and fearful attachment types, which are definitionally very similar to the description of interpersonal behavior in BPD. For example, fearful attachment type is defined as “longing for intimacy, but fearful of rejection and being hurt; mistrustful” on the Relationships

Questionnaire (Bartholomew & Horowitz, 1991) and the Relationships Scales

Questionnaires (Griffin & Bartholomew, 1994). This suggests that early environmental contexts, where attachment relationships are formed, may also be influential in later interpersonal behavior. In this way, research on attachment gives us one perspective on the development of problematic interpersonal patterns in BPD.

Although attachment still receives attention in the BPD literature, research on the disorder has moved towards a more biological/genetic perspective to help explain interpersonal behaviors that differ from the norm. In fact, interpersonal style has been viewed as such an important discriminator of BPD from other personality disorders that these symptoms are being investigated as a phenotype for the disorder (Gunderson &

Lyons-Ruth, 2008). Interpersonal behavior characteristic of individuals with BPD, such

5 as alternating between idealization and devaluation of partners and difficulty controlling anger, reflects an apparently contradictory strong need for connection and intense fears of rejection and there is evidence that the resulting instability in interpersonal relationships is at least partially biologically determined. In a study comparing relatives of individuals with BPD and other personality disorders, relatives of individuals with BPD were significantly more likely than those with other personality disorders to have the disorder’s particular disturbed interpersonal pattern of intense and unstable relationships (Zanarini et al., 2004), suggesting familial transmission.

There are multiple theories that synthesize both the environmental influences

(e.g., attachment difficulties) and biological vulnerabilities (e.g., heritability of interpersonal style) that have been used to explain the interpersonal problems of individuals with BPD. For example, Gunderson and Lyons-Ruth (2008) propose a psychobiological perspective of BPD which recognizes and integrates the contributions of early learning and care giving experiences with the biological predispositions of individuals who develop the disorder. This perspective suggests the existence of a diathesis in the form of hypersensitivity to interpersonal stressors that emerges due to genetic vulnerability transacting with aversive early care giving experiences. As a result, maladaptive social beliefs and patterns are developed which continue to interact with biological vulnerabilities and environmental stressors. According to this perspective, these factors contribute to, among other things, the seemingly contradictory interpersonal behaviors seen in individuals with BPD (including vacillation between idealization and devaluation) and eventually create chaos for the individual and their social network.

A similar biosocial theory of BPD is the framework for dialectical behavior therapy (DBT), an empirically supported treatment for BPD. It suggests a similar interplay between one’s biology and the environment in the development of BPD and the associated interpersonal and emotion regulation difficulties (Linehan, 1993). In this model, individuals with BPD are hypothesized to have biological vulnerabilities that manifest as high sensitivity to emotional stimuli, intense responses to emotional stimuli, and slow return to baseline after emotional arousal. The environmental contributions suggested in the biosocial theory are organized around aversive early experiences and an invalidating environment, which is proposed to be especially damaging to an individual with significant emotional vulnerability. This type of environment interferes with individuals’ social functioning and inhibits their ability to self-validate; theoretically, the child in such an environment does not learn how to correctly label, interpret, and regulate emotions and looks to the external environment for validation of their experience. This pattern is hypothesized to result in a disrupted sense of self and interpersonal relations.

Difficulty with self-validation and an unstable sense of self have obvious consequences for the maintenance of stable interpersonal relationships.

Linehan (1993) suggests that difficulties with asking for help in appropriate ways and with refusing requests in accordance with one’s values and needs are prevalent in

BPD, partially stemming from fears of rejection. According to this theory, problems balancing one’s wants and needs with other’s demands, along with trouble with anger expression when wants are not accommodated, often results in emotional outbursts and impulsive ending of relationships. Patterns such as this are prohibitive for the

7 development of stable and supportive relationships. As a result, many individuals with

BPD end up living in relative isolation because of difficulty building a supportive social network. Accordingly, one of the four modules in DBT is interpersonal effectiveness.

This skill set is stressed in the skills training component of the treatment in order to help individuals with BPD establish more adaptive patterns of interacting that are based in the values present in the relationships rather than aversive contingencies or behaviors that are reactions to previous invalidating experiences (Linehan, 1993).

Social Interaction and Characteristics of Social Networks in BPD

The interpersonal behaviors that characterize individuals with BPD, such as intense neediness, attempts to avoid abandonment, and difficulty controlling anger, make the navigation of their social world especially difficult. In past studies of interpersonal problems in BPD, broad measures, such as the DSM-IV Global Assessment of

Functioning (GAF), have been used to describe interpersonal functioning. More recently, researchers investigating social networks in BPD have recognized that interpersonal problems cannot be measured as a unidimensional construct (Hill et al., 2008). More detailed accounts of individuals’ social functioning should consider behavior in the context of different social settings and maintaining relationships and expectations appropriate to those settings as well as individuals’ experience of social interactions.

Hill et al. (2008) conducted one such study of social domain organization and functioning. The study examined the relationships of individuals with BPD, avoidant personality disorder (APD), and Axis I disorders without co-morbid personality disorders in six social domains, including work, romantic relationships, friendships, non-specific 8 social interactions, negotiations, and day-to-day coping. Information about functioning in these domains was measured during individual interviews with participants using the

Revised Adult Personality Disorder Functioning Assessment (RAPFA), which was adapted for the study from a previous version (Hill, Harrington, Fudge, & Rutter, 1989).

Domain dysfunction in this study was defined as, “the extent to which the demarcation between, and organization within, each domain is undermined.” This is posited to occur when a domain is incomplete, there is a lack of boundaries in terms of processes appropriate to a domain, or the intensity or intimacy across the domains is skewed. In this study, more domain dysfunction was associated specifically with BPD categorically as well as a dimensional symptom count. Individuals with BPD and APD had decreased overall social functioning relative to those with no personality disorder. However, differences in social functioning between these groups were found when broken down by domain. Specifically, compared to individuals with APD, individuals with BPD had more severe romantic dysfunction but did not differ from individuals with APD in other domains. It appears that decreased social functioning across domains was characteristic of personality disorders in general, while dysfunction in romantic relationships was specific to BPD. The study also found that BPD participants 40 years and older, which was the mean age of the sample, had more avoidant romantic and dysfunctional friend relationships than those below 40. This finding has several possible interpretations. It may suggest that individuals with BPD eventually exhaust their social resources by alienating the people close to them or that the interpersonal instability and turmoil may eventually lead individuals to social withdrawal and isolation. Either way, it supports the

9 idea mentioned earlier that many individuals with BPD end up living relatively isolated lives because of the difficulties they experience (Linehan, 1993).

In addition to assessment of interpersonal functioning within different domains, there is likely important information to be garnered from the examination of individual interactions. Russel, Moscowitz, Zuroff, Sookman, and Paris (2007) suggest that individuals with BPD may have different affective experiences during social interactions than non-personality disordered individuals. Over a 20-day event-contingent recording period, individuals with BPD and non-clinical control participants recorded information about their social interactions. Participants with BPD had higher mean levels of negative affect and greater levels of intraindividual variability in affect valence and behavior than control participants during recorded interactions. In addition, BPD participants reported less dominant, more submissive, more quarrelsome, and more extreme levels of overall behavior in social interactions than controls. These differences in affective experience in individuals with BPD such as more negative affect and greater affective variance may interfere with competent behavior by increasing the extremity of interpersonal actions in social interactions.

Using similar experience-sampling methodology, Sadikaj, Russell, Moskowitz, and Paris (2010) focused specifically on the reactions of individuals with BPD and controls to the communal (i.e., warm and agreeable) behavior of their interaction partners. Individuals with BPD experienced more negative affect than controls when they perceived their interaction partner behaving less agreeably than normal, and also reported smaller increases in positive affect than controls when they perceived their partner

10 behaving more communally. This suggests individuals with BPD may have a double emotional vulnerability in interpersonal interactions, such that they are experiencing both increased negative affect in response to a lack of communal behavior and attenuated positive affect when they do perceive such desirable behavior. Importantly, event level negative affect was greater for BPD participants overall, and the relationship between both negative and positive affect at two adjacent events was stronger in the BPD group.

These findings are consistent with the observations that individuals with BPD are extremely sensitive to cues of abandonment and that their emotional reactions linger to subsequent time points.

Another study assessing the nature of social interactions implicated the role of emotion in the differential interpersonal relations of individuals with BPD. Stepp,

Pilkonis, Yaggi, Morse, and Feske (2009) used social interaction diaries over seven days to assess social functioning in individuals with BPD versus those with other personality disorders (OPD) and a clinical control group with no personality disorders (no PD). The number of interactions and time spent in interactions did not differ between the three groups. However, BPD and OPD participants had contact with significantly fewer social partners than those in the no PD group. This may suggest that people in the networks of individuals with BPD were carrying a heavier load than those in the networks of individuals with no PD because fewer social partners were present while the number of interactions and time spent in interactions did not differ. When interaction partners were examined, participants in the BPD group reported fewer interactions with co-workers, and more interactions with “others” than participants in both the OPD and no PD groups.

They also reported significantly more interactions in the context of therapy than those in the OPD group but not the no PD group (6.24%, 2.99%, and 3.20% respectively). In terms of affective experience of interactions, the participants in the BPD group reported experiencing more negative emotions and disagreements, including more ambivalence, sadness, emptiness, and anger than the OPD and no PD participants. These emotional experiences were not specific to any one type of relationship, but were present in interactions across partners. BPD participants also experienced more anxiety and less positive affect during interactions than the no PD but not the OPD participants. The authors unexpectedly found no differences between groups in influence or closeness in romantic relationships. This may have been due to the fact that the study used a clinical control group rather healthy control group.

Clifton, Pilkonis, and McCarty (2007) used social network analysis to further quantify the interpersonal patterns and problems in BPD. This method assesses both the relationships of the participant with others and among the others in their network.

Participants listed thirty partners and provided ratings on a variety of positive and negative relationship aspects for each partner as well as qualities of the relationships they listed. The study used this method to compare individuals with BPD to participants also receiving psychiatric care but without a personality disorder (no PD). No significant differences were found in mean density of networks for the BPD and no PD groups.

However, composition of network did differ between groups; BPD participants identified more network members as former romantic partners and reported having cut off speaking to more network members than the participants in the no PD group. A trend (p < .07) was

12 found in the hypothesized direction in which participants with BPD reported greater levels of conflict in relationships than individuals in the no PD group. In addition, there was an interaction between positive relationship variables and centrality indicating that although for the no PD group relationships with central members were rated as closer and more positive, for the BPD group centrality and positive relationship variables were unrelated. Therefore, while the no PD participants were more likely to have positive relationships with, trust, and seek advice from central members in their network, for BPD participants the centrality of members was not associated with positive relationships or likelihood of having trusting, close relationships. The authors suggest that individuals with BPD may be less likely than individuals without PDs to differentiate between members of their social networks in terms of closeness and availability of support in the relationship (Clifton et al., 2007). This may reflect that individuals with BPD are not seeking out appropriate sources of support or utilizing their networks efficiently.

Researchers have demonstrated that interpersonal functioning in BPD differs from the norm in various ways including number of social partners, affective experience during interactions, and network composition. These data are consistent with clinical observations of individuals with BPD, which suggest that interpersonal relationships are often a struggle for them, and their behavior in these interpersonal situations makes forming stable social relationships challenging. What is less clear are what specific characteristics of the individual and their relationships influence the quality of their social network.

Rejection Sensitivity

The risk for rejection is a powerful motivator of behavior, especially because of the centrality of social connection for mental and physical health. Although social connection is obviously important to optimal functioning, it is also inherently associated with the risk for rejection and those who we wish to connect with the most have the most potential to inflict pain. To explain beliefs about the reliability of others and their likelihood of acceptance versus rejection, Downey and Feldman (1996) proposed a personality disposition, rejection sensitivity (RS), which represents the cognitive- affective processing biases that accompany attachment anxiety and low self-esteem. They posit that RS emerges in developmental contexts that are rejecting and where the child cannot expect to be supported or have their needs met. This learned expectation then manifests itself in situations where the individual feels that they are at risk for rejection in other relationships. Specifically, when high RS individuals seek support and acceptance from others, they believe that they will probably be rejected. These beliefs create negative expectations and avoidance of situations where the potential for rejection exists, as well as hyper-vigilance to rejection cues and over-interpretation of minimal or ambiguous cues of rejection (Downey & Feldman, 1996).

In a series of studies on RS, Downey and Feldman (1996) explicated the construct further by validating the Rejection Sensitivity Questionnaire (RSQ) and exploring the influence of RS on behavior in interpersonal situations. They found support for individual differences in the construct among college students, showing that high RS individuals had a tendency to perceive negative intentions in the ambiguous behavior of others more

14 than low RS individuals, and that this was not due to greater emotional distress in general

(Study 2). They also found that RS assessed prior to entry into a romantic relationship predicted the extent to which an individual would attribute a partner’s insensitive behavior to harmful intent rather than other possible explanations. This relationship between RS and an individuals’ attribution of their partner’s behavior persisted even when controlling for the possible confounding variables of social anxiety, social avoidance, self-esteem, attachment style, neuroticism, and introversion (Study 3). As a follow-up to this, the authors explored whether an increased tendency to perceive and expect rejection negatively impacted the quality of romantic relationships. They found that RS was detrimental in romantic relationships. In couples, partners high in RS felt more insecure and dissatisfied with their relationships than partners low in RS. Partners high in RS also overestimated their partner’s dissatisfaction and desire to leave the relationship (Study 4). These studies begin to show how the sensitivity to and anticipation of cues of rejection can undermine relationships.

Knowing that RS is related to insecurity in romantic relationships and pessimistic perceptions of relationship stability, the next step in this line of research was to examine the relation between RS and romantic relationship status over time. Downey, Freitas,

Michaelis, and Khouri (1998, Study 1) used a daily dairy design to assess the influence of

RS on romantic relationship satisfaction over 28 days and stability of the relationship at one year. For both men and women, RS had a significant effect on breakup status at one year, controlling for the other partners’ RS and commitment assessed at the beginning of the study. In addition to RS increasing the likelihood of relationship termination, the

15 study showed that the partners of high RS participants were more rejecting (according to self-report) than the partners of low RS participants. Thus, there is some evidence that the pessimistic perception of their partners’ levels of acceptance demonstrated in previous studies may be an accurate reflection of the state of the relationship. Moreover, on days following conflict, the partners of high RS women reported more relationship dissatisfaction and thoughts of ending the relationship than the partners of low RS women. This interaction between conflict and RS status was not significant for men

(Study 1).

This naturalistic finding of a rejecting stance post-conflict by the partners of high

RS women was further investigated in a laboratory study of partners’ conversations about an unresolved conflict (Downey et al, 1998). After discussing the conflict, controlling for pre-conflict self-reported anger, partners of high RS women were significantly angrier than partners of low RS women. Additionally, using the Marital Interaction Coding

System-IV (MICS-IV) of both verbal and nonverbal behavior during the conflict discussion, women with high RS behaved more negatively than low RS women. The authors created a negative behavior composite score by combining the following behaviors: negative mind read (a statement of fact assuming a negative mindset of the partner), tone of voice, denying responsibility, verbal or non-verbal put-downs, verbal or non-verbal indication of turn-off, and dysphoric affect. In addition, this negative behavior by high RS women helped explain the post-conflict increase in their partners’ anger

(Study 2). This suggests that when in conflict situations, high RS individuals may lack

16 the skills to resolve the issue skillfully and that this skill deficit has a negative impact on their partners’ mood and, perhaps ultimately, perception of the relationship.

Although the tendency to readily perceive rejection where it may or may not exist alone can be detrimental to relationships, RS is also conceptualized as a tendency to react intensely to real or perceived rejection (Romero-Canyas, Downey, Berenson, Ayduk, &

Kang, 2010). One well-documented consequence of rejection is an increase in hostility and reactive aggression towards others. Accordingly, those who are especially sensitive to this risk may end up showing apparently contradictory behavior reflecting this push and pull of fearing rejection, but also tending to react in a way that is hurtful to the relationship (i.e., aggressively). This behavior vacillates between extreme accommodation and attentiveness on the one hand, and hostility, negativity and withdrawal on the other (Romero-Canyas et al., 2010).

Consistent with the obvious risk that accompanies close relationships (i.e., potential rejection), Romero-Canyas et al. (2010) propose RS as a defensive motivation system. The system is activated by rejection experiences and the desire to protect against further rejection while still maintaining social connections with the source of the threat.

This system triggers a defensive response when threat exists, but can become maladaptive if this response is applied indiscriminately. This defensive response can be expressed in a variety of behaviors ranging from excessive avoidance to inappropriate approach, with the more adaptive reaction to a situation existing somewhere in between these extremes. This type of over-sensitive defensive system places highly rejection

17 sensitive individuals at greater risk of reacting with hostility and reactive aggression than low RS individuals in the same situation.

Physiological studies provide some support for the predicted increase in attention to cues of rejection in high RS individuals. In a study of high versus low RS individuals,

RS was associated with heightened arousal when presented with rejections cues; when controlling for general anxiety, high RS individuals showed greater skin conductance to angry faces relative to neutral stimuli and relative to low RS individuals (Olsson,

Carmona, Downey, Bolger, & Ochsner, 2007). Additional evidence for hyper-reactivity to threat cues was found in a study using an emotional Stroop task with either rejection related, negative, or neutral words. In this study, RS was associated with greater attentional interference by rejection related words compared to negative words not related to rejection (Study 1; Berenson et al., 2009). Difficulty ignoring or turning attention away from threat cues combined with an increased tendency to perceive threat in interpersonal relationships has negative implications for accurately interpreting and successfully navigating social interactions.

The fearful interpersonal expectations and sensitivity to threat cues that characterize high RS individuals are similar to the fears of abandonment and emotional sensitivity in BPD. This connection has prompted research focusing on RS in this population. Ayduk et al. (2008) examined high RS and low executive control (EC) as joint predictors of BPD features. In samples of both college students and community members, RS and EC interacted to cross-sectionally account for significant variance in

BPD features; at the high end of RS, EC was negatively associated with BPD features, whereas at low RS, EC was unrelated to BPD features.

Several studies have examined rejection sensitivity in the context of BPD, to begin to understand how the over-sensitive defensive system posited to exist in rejection sensitivity may relate to aggressive outcomes in the context of BPD. Tragesser, Lippman,

Trull, and Barrett (2008) investigated perceptual biases, emotional reactivity, and impulsivity in response to reading vignettes about being teased by friend or stranger, about a sensitive or non-sensitive topic, in college students. Individuals with high BPD features were more likely to feel both angry and sad in reaction to reading about being teased than those without BPD symptoms. They also examined the “action tendencies” of individuals with BPD features in response to reading about being teased. They found that individuals with high BPD features were more likely than those with low BPD features to predict engaging in aggressive behavior in reaction to being teased.

Berenson, Downey, Rafaeli, Coifman, and Paquin (2011) examined this rejection- aggression relationship in BPD using a laboratory task and experience sampling methodology in participants with BPD and controls with no Axis I or II disorders. The laboratory task used a priming-pronunciation assessment using rage, rejection, or negative primes and examined the latency to produce a word from one of these three categories. They found the participants in the BPD group responded significantly faster to rejection-primed rage words and that this relationship was unidirectional, so that the difference in latency between BPD and control groups for rejection words that were rage- primed was not significant. The experience sampling portion of the study lasted 21 days

19 and participants answered prompts related to their experience of rejection and rage at five intervals daily. Over the 21 days, BPD participants reported higher mean levels of rejection and rage. In addition, controlling for individuals mean level of perceived rejection, there was a significant interaction between diagnosis and perceived rejection such that a 1 standard deviation increase in perceived rejection was associated with a nearly significant increase in rage feelings for the control group, but this increase in rage associated with perceived rejection was associated with a significantly greater increase in rage for the BPD participants. These studies support the hypothesis that rejection sensitivity is associated with a tendency to react more intensely to perceived rejection. In addition, the tendency to experience more intense emotions and more reactive tendencies in response to rejection appear to be associated with BPD features and diagnosis.

Rejection sensitivity has even been proposed as a possible phenotype for BPD

(Gunderson, 2007). This is not surprising given the central role that learned expectations of rejection and fears of abandonment play in BPD. In addition, the anticipation of rejection and reactivity to these experiences are evident in the clinical presentation of individuals with BPD. Support for the presence of features consistent with RS in BPD comes from a study of disruption of social threat cues and RS. In a visual probe task with pleasant and threatening faces, attentional avoidance of threatening faces was related to

RS and BPD features, but not with fear of negative evaluation or APD features (Study 2;

Berenson et al., 2009). This finding supports that RS and BPD features may have similar behavioral manifestations, including the avoidance of cues of social threat. Additional support for RS as a factor to consider in BPD comes from studies of hypersensitivity to

20 facial affect (Lynch et al., 2006) and heightened physiological reactivity to abandonment scripts (Schmahl et al., 2004) in individuals with BPD. However, the construct as proposed by Downey and Feldman (Downey & Feldman, 1996) has received little attention in the context of the disorder. Greater focus on this relationship may be useful in furthering our understanding of the interpersonal behavior typical of these individuals and identifying factors impacting the instability of social relationships and networks in people with BPD.

Aggression in BPD

Aggression, which presents in various forms and can have several targets including the self and others, is another important construct in BPD. The prominence of aggression to the clinical picture of BPD is reflected in several of the diagnostic criteria for the disorder, including difficulty controlling inappropriate anger and extreme reactivity of mood (American Psychiatric Association, 2000). More specifically, interpersonal aggression is aggressive responding in the context of interpersonal interactions, and may be particularly important in the conceptualization of BPD. For example, research shows that that hostility, irritability, and more covert emotional types of aggression are common in BPD (Fossati et al., 2004; Gardner, Leibenluft, O’Leary, &

Cowdry, 1991) and it is these types of aggressive acts that are likely to negatively impact social networks. Furthermore, aggression is related to RS, being a common reaction to real or imagined rejection, and may play a role in social functioning in BPD by decreasing the likelihood of successful interpersonal interactions.

Aggression has been shown to be an important factor in identifying risk for BPD.

In developing a self-report screening tool for BPD, Lejuez et al. (2003) found that combining the interpersonal sensitivity and interpersonal aggression subscales of the

Inventory of Interpersonal Problems (Horowitz, Rosenberg, Baer, Ureo, & Villaseor,

1988) was a useful assessment tool for BPD. This was hypothesized to be the case as these two subscales map on to the proposed core components of BPD, negative affectivity and disinhibition/emotion dysregulation in an interpersonal context, and the combination of these two may uniquely characterize BPD (Trull, 2001). Lejeuz et al.

(2003) found that the interpersonal sensitivity and aggression subscales were correlated with core features of BPD, such as impulsivity and depressive symptoms, as well as the

Borderline Symptom List (Bohus et al., 2001).

Despite the acknowledgement of the importance of interpersonal aggression in

BPD and its implications for interpersonal functioning, this area has received much less attention than other aspects of the disorder (e.g., self-harm, impulsivity). Researchers have found elevated levels of various forms of aggression in BPD, as evidenced by both self-report measures and laboratory tasks (Gardner et al., 1991; McCloskey et al., 2009).

In the study mentioned earlier in which individuals with BPD and MDD were more likely to have suicide attempts with interpersonal precipitants than participants with MDD only, attempters with comorbid BPD also had higher lifetime aggression than those with MDD only (Brodsky et al., 2006). Similarly, one study addressing interpersonal aggression in

BPD assessed violent and aggressive acts in psychiatric inpatients using arrest records, informants, and self-report questionnaires. Individuals were assessed every four weeks

22 over 1 year. Those carrying a diagnosis of BPD were more likely than those without BPD to commit interpersonally violent and aggressive acts over the course of the study

(Newhill, Eack, & Mulvey, 2009). In a recent study using a college sample, we found that elevations in aggression are associated with BPD symptoms in nonclinical populations as well (Cheavens, Lazarus, Herr, 2011). Individuals classified as high BPD symptoms had significantly higher levels of interpersonal aggression than individuals in the high MDD symptoms and control groups. In addition, these groups had differences in their preferences for social partners. Given a choice between interacting with a family member or a novel partner, those with high BPD symptoms chose novel partners significantly more than those with high MDD symptoms and control participants and interpersonal aggression was associated with an increased likelihood of choosing a novel partner.

Although this finding needs further investigation, it suggests differences in partner preference are associated with BPD symptoms and specifically aggression.

Research on the correlates of interpersonal problems and identity disturbance in

BPD suggests that aggression is related to interpersonal symptoms in the disorder. In a sample of personality-disordered patients, Koenigsberg et al. (2001) found that impulsive aggression was related to the BPD criteria of unstable relationships, affective instability, and inappropriate anger. As mentioned, attachment has been used a framework for understanding many of the symptoms seen in BPD. In a study examining the relationships of underlying attachment style and hostility in individuals with BPD, all forms of aggression measured in the study were related to more fearful forms of attachment. Interestingly, these associations were strongest for measures that assessed the

23 tendency to anticipate hostility from others and to react aggressively (Critchfield, Levy,

Clarkin, & Kernberg, 2008).

Based on the clinical profile of BPD, interpersonal aggression may be more related to emotional dysregulation than to other more planful or “cold-blooded” types of aggression. Fossati et al. (2004) examined impulsivity and aggressiveness in individuals with borderline and antisocial personality disorder (ASPD) features in a nonclinical sample. The authors found that different types of aggressiveness characterized the two disorders. Although BPD and ASPD features as assessed by the Personality Diagnostic

Questionnaire-4+ (Hyler, 1994) both had a similar link to impulsivity, they differed in their relationships to aggressiveness. BPD traits were related to the more emotional components of aggressiveness, as measured by the Buss-Durkee Hostility Inventory

(BDHI; Buss & Durkee, 1957) subscales of resentment, guilt, and irritability. In contrast,

ASPD was related to the BDHI subscales of physical aggression, oppositional behavior, and indirect aggression.

Research using behavioral measures of aggression has added to the knowledge gained from self-report measures by assessing the construct in a potentially more ecologically valid way. Indeed, performance on these tasks can discriminate between

BPD and control participants (Dougherty, Bjork, Huckabee, Moeller, & Swann, 1999).

The authors assessed aggressive responding using the Point-Subtraction Aggression

Paradigm (PSAP), a program where participants interact with what they believe to be another player, but are really just computer-based provocations. Aggressive responding on this task was three times higher in women with BPD than healthy controls. Women

24 with BPD also had higher scores on self-report measures of aggression and self-reported history of aggressive acts than controls, suggesting some convergence between the behavioral and self-report measures.

In a study aiming to identify genetic correlates or endophenotypes of BPD,

McClonsky et al. (2009) examined behavioral measures of impulsivity and aggression as potential markers for BPD. Participants with BPD, a non-cluster B personality disorder

(OPD), and healthy volunteers (HV) completed self-report questionnaires and the PSAP laboratory paradigm. BPD participants reported more trait physical aggression, verbal aggression, anger, and hostility on the Buss-Perry Aggression Questionnaire (BPAQ;

Buss & Perry, 1992) than OPD participants, who in turn reported more than HV subjects.

Aggressive responding on the PSAP was also related to self-reported aggression among the BPD sample. Although both BPD and OPD groups showed elevated levels of aggressive responding on the PSAP compared to the HV group, self-reported aggression was not related to aggressive responding in the OPD group, suggesting aggressive responding on the PSAP for this group may reflect something other than trait aggression.

In addition, the authors suggested that laboratory tasks that increase negative affect within the task and recreated interpersonal and other contextual factors might better discriminate BPD from OPD individuals.

Interpersonal aggression in BPD seems counterintuitive given the intense need for interpersonal connection demonstrated by these individuals. During displays of aggression and hostility, the individual is alienating the very person they fear losing.

However, the counterintuitive nature of the aggression in BPD is not surprising when you

25 consider that their interpersonal behavior tends to swing from the more needy behavior to hostility and withdrawal. Interpersonal aggression may be the natural consequence of the interaction between the need for closeness and simultaneous fear of rejections. We believe that high sensitivity to threat (as measured by RS) may predict interpersonal aggression which may in turn lead to disruptions in social networks (e.g., smaller size and less satisfaction and stability) for individuals with BPD.

Current Study

Given the centrality of one’s social network to functioning in BPD, understanding the longitudinal course of interpersonal relationships and factors contributing to their maintenance is an area that deserves attention. The primary aim of the study was to examine how BPD symptoms are related to less stable and poorer quality social networks. Using a longitudinal design, we examined how the relationships among rejection sensitivity, interpersonal aggression, and social network characteristics are impacted by BPD features. Although diagnostic criteria, theory, and research support the presence of interpersonal disturbances in BPD, much less is known concerning the specific characteristics of the individual and the relationship that contribute to these disturbances (or, frankly, what these disturbances are). Also, much of the research to date on social networks in BPD has used cross sectional designs. The research that has looked at relationships over time has either been specific to romantic relationships, or has tracked social interaction over the period of a week, examining patterns in interactions rather than quality and stability of these networks. Given that social support and stability are theorized to be important in BPD, we hoped to fill a gap in the research and quantify 26 exactly how “unstable” relationships tend to be and what mechanisms, such as characteristics of BPD, predict lower quality networks.

We examined several models of how BPD features, interpersonal aggression, and rejection sensitivity may lead to lower quality social networks. The main model we proposed was one of moderated mediation. Specifically, we predicted that rejection sensitivity would have its impact on social network quality through interpersonal aggression. In addition we predicted that BPD features would moderate both legs of this model so that the relationship between rejection sensitivity and interpersonal aggression and the relationship between interpersonal aggression and social network quality would be stronger for individuals with higher levels of BPD features.

Chapter 2: Methods

Participants

Our sample (n = 156) was drawn from the Research Experience Program (REP) pool at The Ohio State University, which consists of students enrolled in the Introductory

Psychology course. Participants had a mean age of 19.80 years (SD = 3.76). The sample was mostly single (67.2%); 65.6% identified as Caucasian, 14.1% as African American,

11.8% as Asian American, 1% as Hispanic-American, and 6.3% as bi/multi-racial or other. Most of the participants were freshman (62%) and had a family income above

$50,000 (68%).

We used two sampling procedures. The first consisted of recruiting participants from the general pool of REP students. In addition, we prescreened the participant pool on the borderline personality subscale of the Personality Assessment Inventory (PAI-

BOR; Morey, 1991) and invited those scoring above 37 to participate in order to ensure an adequate number of participants with high BPD features in the sample. This cut-off is two standard deviations above the mean for the measure (Morey, 1991) and according to

Trull (1995) is related to poor functioning in multiple domains related to the disorder. In the 2010 – 2011 academic year, over three academic quarters, about 12% of females prescreened met this cutoff (72 of 605). In the final sample, 6% of participants at baseline and 14% at one month met this cut-off. Although we recruited based on “high BPD” status, we used a dimensional measure of BPD features for the analyses in the current 28 study as many argue that BPD can be better represented dimensionally than categorically, and significant pathology can be detected using this measure in college samples (Livesley

Schroeder, Jackson, & Jang, 1994; Trull, 1995).

Only female participants over the age of 18 were included in the current study. In past studies of undergraduates, we were not able to recruit sufficient sample sizes of men with high BPD features to make meaningful gender comparisons. Additionally, the disorder is primarily diagnosed in females (75%; American Psychiatric Association,

2000). There were no further inclusion or exclusion criteria. Of the 156 participants who completed the baseline assessment, seven participants failed to complete the one-week follow-up and an additional 21 participants failed to complete the one month follow-up, for a total attrition rate of 18%. Mean time elapsed between baseline and one-week was

7.31 days (SD = 1.59) an 29.48 (SD=2.46) days between baseline and one-month. After excluding one participant who appeared to have difficulty understanding the questionnaires, the final sample included 127 participants.

Measures/Instrumentation

Good validity and reliability estimates have been reported for the measures used in the study and were replicated in our sample. All measures included in the study, and the timing of their administration, are described below and a table of the timing of administration for the measures is included in Figure 1 (See Appendix A). In addition to two measures of BPD features, we included measures of rejection sensitivity and aggression. A social network questionnaire was created for the purpose of the study, in order to assess the stability and quality of individual’s networks. 29

Demographic Questionnaire.

We used a brief self-report questionnaire at baseline to gather basic information about participants’ age, sex, ethnicity, marital status, income, and education.

Life Events Checklist.

We used a checklist of a broad range of life events likely to occur for college- aged students adapted from Holmes and Rahe (1967). This instrument assesses for major positive and negative life events since the previous assessment. These may be important to consider when assessing social network stability as alternative explanations for marked changes in social networks. Examples of events include divorce of a parent, suspension from school, and marriage.

Personality Assessment Inventory- Borderline Personality Disorder subscale

(PAI-BOR).

The PAI-BOR (Morey, 1991) is derived from the PAI; it is a 24-item inventory designed to assess BPD features in adults. The PAI-BOR uses a 4-point Likert scale and was found to have good internal consistency with alpha coefficients ranging from .81 to

.86 and test-retest coefficients exceeding .83 over a four week period (Morey, 1991). It also demonstrates good test-retest reliability over two years (Trull, Useda, Conforti, &

Doan, 1997). This measure was given at prescreening, baseline, and one month to assess

BPD features. In the present sample Cronbach’s alpha was above .86 at all time points and test-retest reliability over four weeks was .75.

Structured Clinical Interview (SCID-II).

The Borderline Personality Disorder (BPD) module of the SCID-II (First, Gibbon,

Spitzer, Williams, & Benjamin, 1997) for the Diagnostic and Statistical Manual of

Mental Disorders (American Psychiatric Association, 1994) was used at baseline to assess BPD criteria met by participants. The BPD symptom count at baseline was significantly related to PAI-BOR total score (r = .66). Agreement between the SCID-II and PAI-BOR cutoff was in the low to moderate range (kappa = .42).

Rejection Sensitivity Questionnaire (RSQ).

The RSQ (Downey & Feldman, 1996) includes 18 hypothetical scenarios in which the individual imagines requesting something of a significant other that makes her vulnerable to rejection (e.g., asking your parents or other family member to come to an important occasion). For each scenario, the participant rated her concern/anxiety over the possibility that the other person would respond negatively to her request (anxiety over rejection) on a scale from 1 (very unconcerned) to 6 (very concerned). For each scenario, participants also rated the likelihood that the other person would respond positively to their request (expectation of acceptance) from 1 (very unlikely) to 6 (very likely). A rejection sensitivity score was calculated for each situation by multiplying the level of rejection concern (answer to part a) by the inverse of the level of acceptance expectancy

(answer to part b). The mean of the resulting 9 scores was taken as the individual’s rejection sensitivity score. The RSQ has been shown (Study 1; Downey & Feldman,

1996) to be normally distributed. In the validation paper, test-retest reliability for the

RSQ over a 2-3 week period was .83 and was .78 over a 4-month period, suggesting this

31 is a relatively stable and enduring construct. With respect to predictive validity, the measure was not redundant with other empirically and conceptually related constructs like introversion, neuroticism, adult attachment style, social anxiety, social avoidance, and self-esteem (Study 3; Downey & Feldman, 1996). The RSQ was administered at each assessment of this study. In our sample, Cronbachs’s alpha was above .84 at all three time points and test-retest reliability over one month was .81.

Buss-Perry Aggression Questionnaire (BPAQ).

The BPAQ (Buss & Perry, 1992) is a self-report measure of trait aggressiveness.

It consists of 29 items each scored using a 4-point Likert-type scale. The BPAQ consists of four scales: physical aggressiveness, verbal aggressiveness, anger, and hostility (i.e., suspiciousness and resentment). The BPAQ has well-known psychometric properties such as test-retest reliability of .80 over nine weeks and high internal consistency in college students (Cronbach’s alpha = .89). The BPAQ was administered at baseline and one week. The hostility subscale of the measure was used to measure interpersonal aggression (IA). Cronbach’s alpha for this subscale was above .84 at both time points.

Social Network Questionnaire.

The social network questionnaire (see Appendix A) was created for the purpose of the current study. It was completed at each time point and provided the data for our criterion variable, social network quality, in the main hypotheses. Participants were asked to list people with whom they had interacted in the past week in order of their frequency of interaction with that partner. This portion of the questionnaire was used to assess the size and stability hypotheses. In addition, for each partner listed, the participant

32 provided her relationship to that person as well as level of closeness, satisfaction with the relationship, amount of support received, and levels of conflict and criticism in the relationship. Participants also rated whether they had cut-off speaking to each partner at any time since the last assessment, and whether that partner was a current or former romantic partner. There were a total of 9 questions each for a maximum of 24 people. In addition to questions for specific partners, separate questions assessing overall satisfaction with, conflict in, and support by the social network were included. This questionnaire was administered at each assessment.

Interpersonal Support Evaluation List (ISEL).

Interpersonal Support Evaluation List consists of 40 statements about support available in different situations on a scale from 0 (definitely false) to 3 (definitely true).

The scale has four subscales: appraisal, belonging, tangible support, and self-esteem.

Cohen & Hoberman (1983) reported high internal consistency (alpha = .77 to .90), good test-retest reliability over a four-week interval (r = .87) and significant correlations between the scale and other measures of social support. For the current study, we used the belonging and tangible support subscales at baseline, which had Cronbach’s alphas of

.82 and .83, respectively.

Study Procedure

We used self-report questionnaires and interviews to collect information on BPD features, rejection sensitivity, aggression, and social network characteristics. Data were collected at baseline, one-week, and one-month follow-up. This study used a prospective longitudinal design to examine factors predicting social network quality in individuals 33 with varying levels of BPD features. The data were collected using Survey Monkey, an online service for creating and administering surveys. This service allowed us to collect follow-up assessments with participants via a link they received by email. In addition, it provided a secure network for data collection and transmission.

Students enrolled in the study through the REP website, which contained a brief description of the protocol. On the day of the initial assessment, study personnel accompanied participants into a private clinic room. Participants received detailed information about the study, including the nature of the content of the questionnaires, follow-up procedures, and reimbursement procedures. The study purpose was framed to participants as investigating personality and social network characteristics. Participants were informed that they would receive an e-mail containing a link to the follow-up questionnaires and a reminder via telephone, if necessary, at one week and four weeks following their initial appointment.

Once consent was obtained and any questions were answered, participants received a demonstration of how to access the online questionnaires followed by the baseline battery of questionnaires and the BPD module of the SCID-II. The initial session lasted 60-90 minutes and participants received REP credit at the rate of .5 credits per 30 minutes of participation. Compensation for follow-up questionnaires completed while participants were enrolled in Psychology 100 was REP credit at the rate of .5 credits for half-hour of participation. If participants were no longer enrolled in Psychology 100 at the time of follow-up, reimbursement was provided through a gift card at the rate of $5 per half-hour. Following the first two assessments, participants received contact

34 information for study personnel and referral information in case they experienced any distress as a result of the questionnaires and received referral information along with debriefing materials after their last assessment. Participants received an email with a link to complete the follow-up surveys one day before they were due to complete them. If they did not complete the surveys by one day after the day they were due, participants received a telephone reminder. Participants who partially completed a survey received a phone call reminder to complete them. Once a participant failed to complete a follow-up, they were not contacted for further assessments.

Chapter 3: Results

Data Analytic Plan and Preparation

As a first step, questionnaire data were examined for outliers and missing data. In order to examine the stability of social network composition and social network characteristics, the social network data were coded so that each partner listed for each participant received a unique code. This allowed us to identify whether a partner remained in the participant’s network, how their position changed, and whether new partners joined the network over time. Undergraduate research assistants double entered these data and any discrepancies in identifying partners across assessments were recorded and reconciled by consensus among three independent raters. Social network data were also examined for outliers and missing data. Next, primary hypotheses were examined.

Specifically, we examined the relationships among the key variables in a manner consistent with the causal steps model of mediation, and then tested a bootstrapping model for significance of the indirect effect. Finally, we examined whether the indirect effect was conditional upon level of BPD features.

Checking for Assumptions.

As mentioned above, the questionnaire and social network data were examined for multivariate outliers and missing data. We also examined descriptive data and patterns of relationships among the questionnaire variables (using correlational analyses), to ensure that the correlations were in the expected directions and the means and standard 36 deviations were within expected ranges based on previous research. At this step of data analyses, we excluded one participant who appeared not to understand the questionnaires based on several extreme scores on the social network assessment, leaving us with a final sample of 127 participants who completed the one-month follow-up. For all questionnaires, mean replacement was used on missing items if less than 15% of the questions in the measure were missing. If the number of missing items in the questionnaire exceeded this cut-off, the total score for the measure was coded as missing for that participant. Subsequently, the BPAQ-Hostility at Time 1 (N=125) and Time 2

(N=125) and satisfaction (N=126) at Time 3 had missing total scores. List-wise deletion was used, so that only participants with full data on all measures included in the model were included each analysis. As a result, the n varies slightly from model to model and the n for each specific model is listed in the subsequent table.

Because the regression analyses were performed on ungrouped data, rather than screening variables for normality prior to analysis, the distributions of the residuals were examined for normality (Tabachnick & Fidell, 2007). If the distribution of the residuals was not normally distributed, the variables were screened individually for deviations from the assumptions of linear regression. Using this procedure, the RSQ at Time 1, network count at Time 3, and BPAQ-Hostility at Times 1 and 2 were positively skewed/non-normal. These variables were transformed using square root, logarithmic, and inverse transformations and the transformation resulting in the most normal distribution was chosen for each. Ultimately, the logarithmic (log10) transformation was the best for RSQ at Time 1 and BPAQ-Hostility at Times 1 and 2, while the square root

37 transformation resulted in the closest approximation of normality for network count at

Time 3. All variables were found to be reasonably linear, independent, and homoscedastic. The transformed variables were not used for the bootstrapping analysis, as this type of analysis makes no assumptions about the shape of the distributions of the variables, or of the sampling distribution of the statistic (Efron & Tibshirani, 1993;

Mooney & Duval, 1993).

Social Network Quality.

The dependent variable, social network quality, was comprised of three main indices: size of one’s network, satisfaction, and stability. All three criterion variables are discussed below.

Size.

The size of an individual’s social network was determined by the number of people they reported interacting with on the SNA at each assessment. Specifically, the

SNA asks them to list anyone they have interacted with for five minutes or more, at least two times in the past week (see Appendix A for a full version of this measure).

Participants could list a maximum of 24 interaction partners in order of how frequently they interacted with that person (See Table 1 for means and SDs).

Satisfaction.

Satisfaction scores were calculated for each participant’s network at each assessment. Participants rated their level of satisfaction with the relationship with each partner on a 4-point scale, ranging from 1 (not at all) to 4 (very much), with higher scores indicating more satisfaction with the relationship. The mean satisfaction score for the

38 partners listed in a participant’s network was taken at each time-point as their overall satisfaction score (See Table 3 and for means and SDs for satisfaction and other network characteristics).

Stability.

We calculated two different stability scores reflecting the central components of network stability, which we hypothesized would be related to our key variables (See

Table 1 for descriptive statistics). The first component of stability is the degree to which an individual has same people in their network at both baseline and one-month. The other component of stability is the consistency of the rank order of frequency of interaction occupied by each individual in one’s network over time. We also assessed other variables, such as amount of change in relationship with a partner since the last assessment, amount of conflict in the relationship, and whether the participant cut off speaking to the partner at any time since the last assessment, that might also be considered measures of stability. However, for the purpose of this study we intended stability to reflect objective change and movement of the individuals in a participant’s network and believe that questions about conflict within the relationship may potentially be more reflective of an individual participant’s subjective experience; thus, only the two stability variables reflecting network composition were included as indices of stability for the primary analyses. Additionally, although we collected social network data at baseline, one week, and one month, we used only the data from baseline and one month to calculate stability ratings, as we believe that there would be very little change between baseline and one week in terms of network stability and that any change between baseline

39 and one week was more likely to reflect measurement error than true changes in social network composition.

Proportion Present.

This variable was created to reflect whether the same partners who were listed at baseline were still present in the social network (i.e., listed by the participant) one month later. We created a ratio of the partners listed at the one-month assessment who were also listed at baseline. Partners who entered the network at the one-month follow-up but were not present at baseline were not included in this variable. Higher scores on this variable (closer to 1) reflect more stability in the network.

Frequency Change.

Participants listed partners in their network in order of how frequently they interacted with them. Accordingly, we wanted to capture the change in the frequency with which participants interacted with partners in their network. For example, Joe Smith may be in a participant’s network at both time points; however, at baseline he was listed as the person the participant interacted with most, and one month later he moved down 4 positions, indicating there were now 4 people in the network with whom the participant interacted with more frequently than Joe Smith. To capture such moves within the network, partners were given a position score based on their particular position in the network (i.e., from 1 to 24) at baseline. This was converted to a frequency strength score by reverse scoring such that the first person listed in the network always had a score of

24, the highest possible rating. For those partners who were present at baseline and one month, difference scores were calculated by taking the absolute value of the difference

40 between their frequency strength score at baseline and one month. Higher scores are indicative of greater magnitude of change in frequency of interaction with the partners in one’s network. Partners who were in the network at only one time point did not receive scores on this variable. The mean of these difference scores for individual partners were calculated for each participant.

Descriptive Results

Next, we examined descriptive statistics for these social network variables and examined patterns of relationships among these variables and questionnaire data (see

Table 1). Using repeated measure ANOVA, we examined differences over one month for the questionnaire data and social network characteristics. Given that there were significantly more partners (M = 10.97, SD = 6.24) listed at Time 1 compared to Time 3

(M = 8.28, SD = 6.34), F(1, 126) = 52.15, p < .01, we controlled for partners listed at baseline when examining differences in network characteristics (see Table 2) and composition (see Table 3) from Time 1 to Time 3. In addition, we examined the data for differences between completers and non-completers on demographic, personality, and social network variables. There were no significant differences (all ps > .1) between participants who completed all three time-points and those who dropped out at Time 2 or

Time 3 on demographic, personality, or social network variables. Given that the data were collected over the entire academic year, we also examined whether there were differences on key variables by the quarter when participants were enrolled. There were no significant differences in personality or social network variables by quarter collected

(all ps > .09). We also examined bivariate correlations between life events over the one-

41 month period of the study, BPD features, and stability. As none of these relationships were significant (all ps > .09), we did not control for life events in subsequent analyses.

Hypothesis Testing

Hypothesis 1: Correlations at Baseline.

At baseline (Time 1), BPD features will be positively related to interpersonal aggression and rejection sensitivity and will be negatively related to social network quality (size and satisfaction).

To address our first hypothesis, we examined bivariate correlations between BPD features and interpersonal aggression, rejection sensitivity, social network size, and satisfaction with network at Time 1. This hypothesis was partially supported (see Table 1 for correlations, means, and standard deviations of these variables). There were significant positive correlations between BPD features and interpersonal aggression (r =

.53, p < .01) and rejection sensitivity (r = .27, p < .01). In addition, there was a significant negative correlation between BPD features and social network satisfaction (r = -.42, p <

.01), but BPD features and social network size were unrelated (r = .03, p = .71).

Hypothesis 2: Indirect Effects.

Rejection sensitivity exerts at least part of its effect on social network quality through interpersonal aggression (see Figures 2 and 3).

First, we tested for a significant indirect effect of rejection sensitivity on social network quality through interpersonal aggression. Much debate exists concerning the utility of different tests of mediation. We tested the relationships required for mediation

42 as suggested by Baron and Kenny (1986) for all three indices of social network quality.

Because an indirect effect seemed likely, we also used a bootstrapping model to test the significance of the indirect effect of rejection sensitivity on social network satisfaction through interpersonal aggression.

Hypothesis 2.1.

Rejection sensitivity at baseline (Time 1) will predict lower social network quality (size, stability, satisfaction) at one-month (Time 3; see path c of simple mediation model in Figure 3).

We used linear regression to evaluate the contribution of Time 1 rejection sensitivity to network size and satisfaction at Time 3 as well as to proportion present and frequency change. Rejection sensitivity at Time 1 did not account for significant variance in Time 3 satisfaction or either measure of stability (see Table 4). However, rejection sensitivity at Time 1 did explain a significant, although small, portion of the variance in

2 network size, R adj = .03, F(1, 126) = 4.29, p = .04. Specifically, greater rejection sensitivity at Time 1 was related to a smaller social network size at Time 3. This relationship was no longer significant when controlling for network size at Time 1 (p =

.24).

Hypothesis 2.2.

Rejection sensitivity at baseline (Time 1) will predict higher interpersonal aggression at one-week (Time 2; see path a1 of simple mediation model in Figure 3).

We used linear regression to examine the contribution of Time 1 rejection sensitivity to Time 2 interpersonal aggression (see Table 5). Rejection sensitivity at Time

2 1 explained significant variance in interpersonal aggression at Time 2, R adj = .15, F(1,

123) = 21.50 p < .01. This relation remained significant even when controlling for Time 1 interpersonal aggression. Time 1 interpersonal aggression strongly predicted Time 2 interpersonal aggression, ΔR2 = .62, F(1, 121) = 200.97, p < .01. When Time 1 rejection sensitivity was added to the model, it accounted for significant additional variance in

Time 2 interpersonal aggression, ΔR2 = .01, F(2, 120) = 104.98, p = .05 (see Table 5 for beta weights).

Hypothesis 2.3.

Interpersonal aggression at one week (Time 2) will predict lower social network quality (size, stability, and satisfaction) at four weeks (Time 3; see path b1 of simple mediation model in Figure 3).

We used linear regression analysis to evaluate the contribution of Time 2 interpersonal aggression to Time 3 social network quality (size, satisfaction, and stability). Aggression at Time 2 did not predict network size or stability at Time 3 but did predict satisfaction at Time 3 (see Table 6). Aggression accounted for 4% of the variance

2 in Time 3 network satisfaction, R adj = .04, F(1, 122) = 6.60, p = .01, such that higher aggression at one week was related to lower social network satisfaction at one month.

This relationship was no longer significant when controlling for satisfaction at Time 2 (p

= .84).

Given that an indirect effect between rejection sensitivity and network satisfaction through interpersonal aggression seemed likely, we tested the significance of the indirect effect using the un-transformed variables in a bootstrapping technique, which allows for non-normality of the data (Preacher & Hayes, 2007). Historically, the causal steps method test for mediation as described by Baron and Kenny (1986) has been the most used. This test requires that there be a significant overall effect between X and Y, which must become non-significant with the mediator variable in the model. However, in most other models of mediation, this step requiring a direct effect between X and Y is not required. Many argue that even in the context of a null direct effect between X and Y mediation, significant indirect effects can still exist, as the initial test of the relationships between X and Y is just a statistical test that is also subject to error. To this end, there is controversy over whether you would call this mediation or not. When discussing whether a mediator can be causal between X and Y in the absence of a direct effect between X and Y, some prefer to simply refer to X’s indirect effect on Y through M. We used the recommended bootstrapping procedure by Preacher and Hayes (2004) to test for an indirect effect in our model. This procedure has several benefits including greater power than the causal steps method, no assumptions about the sampling distribution of the indirect effect, and minimization of the number of tests required to support a claim. The bootstrap procedure creates 5,000 bootstrap samples from the original data by random sampling with replacement. The a and b values are estimated and their products are recorded, yielding 5,000 estimates of the indirect effect, which function as the sampling distribution for the statistic. A 95% confidence interval is constructed by sorting the

45 values of ab from smallest to largest, yielding a percentile based bootstrap confidence interval. The indirect effect is significant if the 95% bias corrected and accelerated confidence interval for the indirect effect does not include zero (Preacher & Hayes,

2004).

Hypothesis 2.

Rejection sensitivity exerts at least part of its effect on social network quality through interpersonal aggression.

Results based on 5,000 bootstrap samples indicated that the direct effect of rejection sensitivity at Time 1 on satisfaction at Time 3 was not significant, R2 = .00, F(1,

121) = .40, p = .53. However, the indirect effect of rejection sensitivity at Time 1 on satisfaction at Time 3 through interpersonal aggression at Time 2 was significant, as the

95% confidence interval did not contain zero (IE = -.0122, SE = .01, lower 95% CI = -

.0258, upper 95% CI = -.0010). As hypothesized, rejection sensitivity exerted an indirect effect on social network satisfaction through interpersonal aggression.

Hypothesis 3: Moderated Mediation.

The indirect effect of Time 1 rejection sensitivity on Time 2 interpersonal aggression and of Time 2 interpersonal aggression on Time 3 network satisfaction will each be conditional upon BPD features.

Moderated mediation is said to occur when the strength of an indirect effect depends on the level of some other variable or when the mediation relations are dependent on the level of a moderator. We tested that the indirect effect of rejection

46 sensitivity on social network satisfaction through interpersonal aggression would be conditional on the level of BPD features. We hypothesized that BPD features would moderate both legs of the supported mediation model; however, we tested each leg separately prior to examining the full model. Please see the figures of the proposed relationships in Appendix C.

Two main techniques are supported for testing for conditional effects. One uses ordinary least squares (OLS) regression to test the significance of an interaction term of the predictor and the moderator. This method involves picking values of the moderator and testing the effect of the predictor at those values of the moderator (Aiken & West,

1991; Cohen, Cohen, West, & Aiken, 2003). One argument against this approach is the arbitrary choosing of values of the moderator, especially when the moderator does not lend itself to this type of dichotomization. Another approach, the Johnson-Neyman

(1936) technique, avoids this problem by identifying values of the moderator at which the effect of the predictor on the outcome is significant and non-significant. Preacher and

Matthes (2009) have created macros for SPSS and SAS for both of these techniques.

Preacher, Rucker, and Hayes (2007) suggest an extension of the method proposed by

Johnson and Neyman (1936) where instead of choosing arbitrary values of W for which the simple slope of Y regressed on X is significant, you can instead determine values of

W for which the simple slope of Y regressed on X is significantly different from zero.

Confidence bands around W are plotted and W is said to moderate the relationship between X and Y for values of W where the confidence bands do not contain zero. We

47 used the macro provided by Preacher and colleagues (2007) to identify regions of significance for BPD features as a moderator in the abovementioned relationships.

Relying on the simple model of mediation (Figure 5, Appendix C), we proposed that the moderator (BPD features) affects both the a1 path (rejection sensitivity predicting interpersonal aggression) and the b1 path (interpersonal aggression predicting social network quality).

Hypothesis 3.1.

The proposed relationship between rejection sensitivity and aggression will be stronger at higher levels of BPD features.

The interaction between rejection sensitivity and BDP symptoms in predicting interpersonal aggression was not significant (p = .88; see Table 7)

Hypothesis 3.2.

The proposed relationship between network satisfaction and aggression will be stronger at higher levels of BPD features.

The interaction between aggression and BPD features in predicting satisfaction was not significant (p = .44; see Table 8).

Supplementary Analyses

Given that one of our primary aims was to examine the relation of BPD features and social network quality, we examined correlations between BPD features at baseline, and social network characteristics related to quality, composition, and stability at one month. BPD features at Time 1 were positively related to overall ratings for the network on conflict and negatively related to overall ratings of support and satisfaction at 48

Time 3 (all ps < .01, see Table 9 for all correlations). In addition, BPD features were negatively related to satisfaction, closeness, and support among the partners listed in one’s network. BPD features were also positively related to conflict and criticism with the partners in one’s network at Time 3. In terms of composition of networks, BPD features at Time 1 were positively related to the number of partners labeled as “others” in social networks at Time 3. In addition, BPD features at Time 1 were positively related to number of current or former romantic partners and having cut off speaking to partners in one’s network at Time 3 (See Table 10).

We also examined the concurrent validity of the SNA ratings of satisfaction and support with another measure of interpersonal support. Satisfaction and support among partners at Time 1 as well as overall network satisfaction and support on the SNA at Time 1 were correlated with the tangible and belongingness subscales of the ISEL administered at Time 11. As expected, correlations with satisfaction and support among partners were positively related to the tangible (r = .30, p < .01 and r = .25, p = .01, respectively) and belonging (r = .33, p < .01 and r = .34, p < .01, respectively) subscales; although the scales are significantly correlated, the strength of the correlations suggest that these measures are tapping into different aspects of social functioning. Correlations were slightly stronger between the ISEL tangible and belongingness subscales and overall ratings of satisfaction and support for one’s network rather than averaged across the partners present. Specifically, overall satisfaction and support were positively related

1 As the ISEL was added to the study late, N=103 for the all analyses using this measure. Participants completed the ISEL at baseline only. 49 to the tangible (r = .53, p < .01 and r = .41, p < .01, respectively) and belonging (r = .57, p < .01 and r = .52, p < .01, respectively) subscales.

Chapter 4: Discussion

The main purpose of the study was to examine how BPD features are related to social network quality by understanding the relationships between rejection sensitivity, interpersonal aggression, BPD features, and social network size, stability, and satisfaction. The results provide some insight into how rejection sensitivity leads to lower quality social networks. Specifically, we found that rejection sensitivity at baseline had an indirect effect on network satisfaction at one-month through interpersonal aggression.

Furthermore, although the hypothesized moderated mediation model including BPD features was not supported, the data do suggest that BPD features are related to various indicators of lower quality social networks over one month.

At baseline, there was a moderate correlation between BPD features and interpersonal aggression (r = .53), and a small correlation between BPD features and rejection sensitivity (r = .27). This finding replicates the relationship found by Adyuk

(2008), who found a correlation of .29 between RS and BPD features as measured by the

PAI-BOR. In terms of the hypothesized relationships between BPD features and social network quality, BPD features were related to social network satisfaction but not size at baseline. Surprisingly, BPD features were not related to stability, as we defined it, over one month.

As mentioned above, our hypothesis that rejection sensitivity would have its effect on social network size, stability, and satisfaction through interpersonal aggression 51 was partially supported by our data. Although the proposed relationship was not significant with stability or size as the criterion variable, it did exist for satisfaction with the partners in one’s network at one-month. This model indicates that although the direct effect of rejection sensitivity at baseline on satisfaction with the partners in one’s network at one-month was not significant, the indirect effect of this relationship through interpersonal aggression was significant. This suggests that although rejection sensitivity alone may not lead to lower network satisfaction, rejection sensitivity increases interpersonal aggression, which in turn lowers satisfaction with one’s network. This finding is consistent with research in healthy populations, which demonstrates a relationship between rejection sensitivity and aggression. Specifically, in one study

(Adyuk et al., 2008) the relationship between rejection and aggression in a laboratory task was moderated by rejection sensitivity. However, our results extend this finding to suggest that this relationship between rejection sensitivity and interpersonal aggression may be important for network satisfaction. Specifically, the predisposition of individuals high in rejection sensitivity to act aggressively may lead to social networks that are less satisfying for them.

Related to this, research on rejection sensitivity in romantic relationships suggests that rejection sensitivity may involve a “self-fulfilling prophesy,” whereby anticipation of rejection actually leads to more rejection from one’s partner and lower satisfaction with the relationship for high RS individuals and their partners (Downey &

Feldman, 1996; Downey, Freitas, Michaelis, & Khouri, 1998). Our findings suggest that in addition to or in combination with rejection sensitivity, interpersonal aggression is an

52 important potential mechanism to examine in predicting lower relationship satisfaction in such couples. However, the current findings cannot demonstrate that interpersonal aggression was preceded by actual rejection by network members. Future research using ecological momentary assessment (EMA) to examine rejection experiences may help explicate whether interpersonal aggression is a consequence of being highly rejection sensitive, or of the actual rejection experiences these individuals are likely to encounter.

Also, although this study suggests that interpersonal aggression influences satisfaction with ones’ partners, further research would be needed to examine whether a similar mechanism also influences partners’ satisfaction with the target.

The hypotheses that BPD features would moderate the relationships between rejection sensitivity and interpersonal aggression and between interpersonal aggression and social network satisfaction were not supported by the data. One possibility for the lack of BPD features as a moderator is that this relationship only exists for individuals with BPD features above a certain threshold and that there were too few participants with elevated BPD features to detect this in our sample. At baseline, there were only 6 participants who met the cut-off for high BPD features on the PAI-BOR. Furthermore, rejection sensitivity may manifest itself differently in those with high BPD features than in healthy individuals. For example, aggression may be a more enduring trait in individuals with high BPD features, and therefore not as closely related to rejection sensitivity specifically as in those with low levels of BPD features. In addition, BPD features are related not only to rejection sensitivity, but also significant fears of abandonment, which may actually attenuate the tendency to react aggressively to

53 perceived rejection. Research examining the relationship between rejection sensitivity and aggression in both healthy individuals and those with BPD features would help explicate these findings.

The lack of moderation in the second leg of the indirect effect, between interpersonal aggression and social network satisfaction, is difficult interpret. Although we hypothesized that the relationship between interpersonal aggression and social network satisfaction would be stronger at higher levels of BPD features, the interaction between BPD features and interpersonal aggression in predicting satisfaction may be less important than their individual main effects. That is, both interpersonal aggression and

BPD predict lower satisfaction, but their interaction does not explain unique variance in network satisfaction. In addition, although BPD features may not influence the relationship between interpersonal aggression and participants’ satisfaction with their networks, BPD features may influence their partners’ satisfaction with the network. One way of assessing this would be to examine both participant and partner provided ratings of satisfaction with the relationship and each other and examine whether interpersonal aggression influences these ratings similarly or not.

Another unexpected finding was that our stability ratings were not related to any of the personality variables in our sample. There are a few possible reasons for a lack of relationship between BPD features and our measures of stability. One is that the instability in relationships that is commonly reported by individuals with BPD and their partners is not captured by change in frequency of interaction or the actual dropping of partners from the individuals’ network. The finding that BPD features were related to

54 number of partners in the network at Time 3 who were cut-off at some point since the last assessment may suggest that individuals with BPD features are staying in relationships that are marked by more criticism, dissatisfaction, and short breaks in communication than those without such features. If individuals with BPD are experiencing these kinds of

“hopeless” relationships (Linehan, 1993) and staying in them, this may help explain the increased distress that they report in the interpersonal domain.

Alternately, it is possible that our measures of stability, which reflect change in the network over one month, are not related to BPD features because the time between assessments was too long to capture meaningful changes. For example, even though partners are being cut-off at some point during the month and this is related to BPD features, these partners are back in the network at one month in order for us to obtain this information. Hence, change in frequency and partners dropping out may occur over very short periods of time, which might not be captured by our assessment period. In this case, daily diary studies over a longer period of time may be better at catching these brief changes in the relationships that our method of assessment could not capture, as well as information about long-term stability of the composition of networks. In addition, discontinuing speaking to someone for an amount of time may be different than actually having that person drop out of the network completely. This is consistent with the observation that although individuals with BPD features often experience difficulty in interpersonal relationships, they also have trouble ending them. Furthermore, this lack of relationship may be related to the instructions given for listing partners. Specifically, our criteria included any partner who the participant interacted with for a specified amount of

55 time, which maybe have included partners with whom the participant was obligated to interact with, such as professors or co-workers. However, both measures of stability over one-week and one-month were unrelated to BPD features. This suggests that the lack of relationship between BPD features and instability may be less related to the time period of our assessment and more to there being a more subtle interpretation of instability than actually leaving the network.

In addition, although we considered many methods of measurement to capture stability prior to deciding on change in frequency and proportion present, there are some limitations to each of these. For example, partners who entered the network after baseline were not reflected in the proportion present variable. Although partners entering one’s network could potentially be categorized as contributing to “instability” in the network, it is difficult to combine the concepts of “drop-outs” with “drop-ins.” Moreover, for the purposes of stability in this study we considered a partner leaving one’s network as more indicative of lower social network quality than having new partners enter the network. In addition, frequency change was only calculated for those individuals who were in the network at both baseline and one month, therefore this variable only accounts for movement among individuals in one’s network and does not consider dropout, although dropout analyses were conducted separately. It could be argued that dropping out of the network is a clear example of change in frequency. However, in deciding how to weight drop-out in change of frequency (i.e., is dropping out of a network equal to a change in one position on the frequency variable or five or ten?), we decided on a more standardized measure rather than assigning an arbitrary penalty for having a partner

56 dropout. Similarly, size of the network was not controlled for when determining change in frequency of interaction. For example, moving from the first person listed to the second was weighted the same as moving from the second to last to the last in the list of partners.

Aside from stability, BPD features in our sample were also related to various other indicators of lower social network quality such as less closeness and support, and greater criticism and conflict. In terms of composition, BPD features were positively related to the number of partners listed as “other” and current/former romantic partners.

The finding of having more “others” in one’s network is consistent with previous research by Stepp et al. (2009), in which individuals with BPD interacted with significantly more “others” and “therapists” than healthy individuals over the course of one week. Although more “therapists” were not related to be BPD features in our sample, this may have been related to the two times a week criteria on the SNA for listing partners. The relationship between BPD features and number of current and former romantic partners in our sample is consistent with Clifton and colleagues’ (2007) finding that the networks of individuals with BPD contained more former romantic partners than individuals with no personality disorder.

Although our measures of stability were not significantly predicted by BPD,

RS, or interpersonal aggression, they were related to other measures of stability, suggesting some level of construct validity. For example, frequency change was related to having cut off speaking to partners in one’s network and change in relationship with the partners listed at one-month. This suggests that having people move around within the

57 network is related to reporting significant change within those relationships and having more people in the network who have been cut-off. In addition, although proportion present was not related to either of these measures of stability it was negatively related to conflict and positively related to having family, friends, and others in one’s network at one month, as would be expected.

A lack of the hypothesized relationship between BPD features and size may be due to various factors, including the explanation above regarding changes in the network happening over smaller periods of time. The hypothesis that BPD features would be related to size was based on the previous finding (Stepp et al., 2009) from a daily diary study over seven days in which individuals with BPD had contact with significantly fewer social partners than individuals with no PD. However, those data were collected using an adult population with diagnoses of BPD. Therefore, a lack of relationship between BPD features and network size in the current study may be related to our use of a college sample, whose social environments are likely very different from individuals in the general population. Although we were very specific about the criteria for listing partners, it may have been difficult for participants to retrospectively recall their social partners from the past week. Additionally, this may have been especially difficult for individuals with elevated BPD features to do. Lastly, given the format of the SNA (the opportunity to list up to 24 partners), there may have been some pressure to list more social partners than would have been recalled in a different format, and participants with elevated BPD features may have been more vulnerable to this pressure.

It is also possible that the size of one’s social network, as we measured it, is not a meaningful measure. Specifically, because we used the criteria of interacting with someone at least two times, for five minutes or more each time, in the past week, it is likely that participants ended up listing people who were not particularly important to them, but with whom they interacted as a result of school or work obligations. By using such a specific criteria, we may have weakened the relationship between size of the network and quality. Although participants also listed their closeness to each person, it is possible that the partners listed would be different if we had simply asked them to list those individuals in their social network. In support of this, network size at one month was not related to satisfaction with the network. In an attempt to operationalize the criteria for listing partners, we may have lost some of the external validity of size as a measure of quality. However, we thought it was important to minimize the interpretation of “social network” as personality characteristics are likely to influence this.

This potential difference between those people the participant interacts with frequently and those whom participants consider part of their social network may also be part of the reason for the weak relationship between level of social support measured by the ISEL and satisfaction based on the ratings of each partner at baseline. The potential discrepancy can also be seen in the weak relationship between satisfaction based on the mean rating across partners and overall rating of satisfaction with one’s social network.

Although these two measures were significantly related, the relationship was far weaker than one would expect. Future research that leaves which partners the participants

59 consider their social network up to them may help answer this question, but brings its own problems as well.

Another limitation of the study is that the use of college student may not be ideal for assessing size and stability of networks. There are several factors that might influence the content as well as quality of social networks. First, starting college is a transitional period when students are often separated from many of their friends and family from their hometowns and are placed in a new social environment. In this context, participants may or may not be successful in making new friends in college and losing contact with some old friends in service of making new ones may be adaptive. In addition, throughout each quarter there are breaks from school, during which the participants’ patterns of interactions may change. Although we attempted to address this possible limitation by counting alternative methods of communication such as email and phone conversation as

“interacting” with a partner, this instability in environment for participants may have made it difficult to assess true instability in relationships. For future follow-ups at three and six months, alternative statistical methods which assess the mean change in an individual’s network across a greater number of time points will be useful in assessing instability.

Overall, this research has important implications for understanding the influence of rejection sensitivity on one’s satisfaction with their network and implicates aggression as an important mechanism to focus on when understanding lower quality networks. In addition, the results are helpful in understanding the networks of individuals with BPD features. It suggests that although individuals with BPD features report more conflict and

60 instability and less satisfaction and support among the partners in their networks, these are not reflected in objective measures of stability or size. If individuals with BPD features are not making changes in the composition of their networks based on the quality of relationships, this has important implications for understanding their interpersonal difficulties and suggests that paying more attention to what kinds of partners the individual has in her social network may lead to less interpersonal distress. This is consistent with Linehan’s (1993) treatment model for BPD which emphasizes ways to be interpersonally effective, including asking for what one needs and ending “hopeless” relationships.

Another area for future research is to examine if BPD features at baseline predict network outcomes over a longer period of time, and to collect data from the partners within participant’s networks to assess whether and how BPD features influence their partners’ satisfaction with the relationship. Given that an interpersonal relationship involves a transaction between two people, collecting information from partners of individuals with BPD features would likely assist in understanding their dissatisfaction with their social networks and distress resulting from interpersonal difficulties.

Despite the limitations of the study, it represents an important step forward in understanding social network quality, composition, and stability, and their relation to

BPD features. In addition, we used novel methodology to examine the stability and dynamic of social networks longitudinally. Our results suggest that interpersonal aggression is one of the mechanisms by which rejection sensitivity leads to less satisfaction with social networks. It also confirms that BPD features are related to poorer

61 social network quality in an undergraduate population. Future research which refines this longitudinal method of assessment and extends this model to the partners in the networks of individuals with BPD features will be helpful in understanding the distress experienced in the interpersonal domain by individuals with BPD features.

References

Agrawal, H. R., Gunderson, J., Holmes, B. M., & Lyons-Ruth, K. (2004). Attachment

studies with borderline patients: A review. Harvard Review of Psychiatry, 12, 94-

104. doi:10.1080/10673220490447218

Aiken, L. S., & West, S. G. (1991). Multiple regression: Testing and interpreting

interactions.

American Psychiatric Association. (2000). Diagnostic and statistical manual of mental

disorders (Revised 4th ed.). Washington, DC: Author.

Ayduk, O., Zayas, V., Downey, G., Cole, A. B., Shoda, Y., & Mischel, W. (2008).

Rejection sensitivity and executive control: Joint predictors of borderline

personality features. Journal of Research in Personality, 42, 151-168.

doi:10.1016/j.jrp.2007.04.002

Bagge, C., Nickell, A., Stepp, S., Durrett, C., Jackson, K., & Trull, T. J. (2004).

Boderline personality disorder features predict negative outcomes two years later.

Journal of Abnormal Psychology, 113, 279-288. doi:10.1037/0021-

843X.113.2.279

Baron, R. M., & Kenny, D. A. (1986). The moderator-mediator variable distinction in

social psychological research: Conceptual, strategic, and statistical considerations.

Journal of Personality and Social Psychology, 51, 1173-1182. doi:10.1037/0022-

3514.51.6.1173

Bartholomew, K., & Horowitz, L. M. (1991). Attachment styles among young adults: A

test of a four-category model. Journal of Personality and Social Psychology, 61,

226-244. doi:10.1037/0022-3514.61.2.226

Berenson, K. R., Downey, G., Rafaeli, E., Coifman, K. G., & Paquin, N. L. (2011). The

rejection-rage contingency in borderline personality disorder. Journal of

Abnormal Psychology, 120, 681-690. doi:10.1037/a0023335

Berenson, K. R., Gyurak, A., Ayduk, O., Downey, G., Garner, M. J., Mogg, K., . . .

Pine, D.S. (2009). Rejection senistivity and disruption of attention by social threat cues.

Journal of Research in Personality, 43, 1064-1072. doi:10.1016/j.jrp.2009.07.007

Black, D. W., Blum, N., Pfohl, B., & Hale, N. (2004). Suicidal behavior in borderline

personality disorder: Prevalence, risk factors, prediction, and prevention. Journal

of Personality Disorders, 18, 226-239. doi:10.1521/pedi.18.3.226.35445

Bohus, M., Limberger, M. F., Frank, U., Sender, I., Grathwol, T., & Stieglitz, R. D.

(2001). Development of the borderline symptom list. Psychotherapie,

Psychosomatik, Medizinische, Psychologie , 51, 201-211. doi:10.1055/s-2001-

13281

Brodsky, B. S., Groves, S. A., Oquendo, M. A., Mann, J. J., & Stanley, B. (2006).

Interpersonal precipitants and suicide attempts in borderline personality disorder.

Suicide and Life-Threatening Behavior, 36, 313-322.

Brown, M. Z., Comtois, K. A., & Linehan, M. M. (2002). Reasons for suicide attempts

and nonsuicidal self-injury in women with borderline personality disorder.

Journal of Abnormal Psychology, 111, 198-202. doi:10.1037//0021-

843X.111.1.198

Buss, A. H., & Durkee, A. (1957). An inventory for assessing different kinds of hostility.

Journal of Consulting Psychology, 21, 343-349.

Buss, A. H., & Perry, M. (1992). The aggression questionnaire. Personality Processes

and Individual Differences, 63, 452-459.

Cheavens, J. S., Lazarus, S. A., Herr, N. R. Interpersonal Partner Choices by Individuals

with Elevated Features of Borderline Personality Disorder. Manuscript submitted

for publication.

Choi-Kain, L. W., Zanarini, M. C., Frankenburg, F. R., Fitzmaurice, G. M., & Reich, D.

B. (2010). A longitudinal study of the 10-year course of interpersonal features in

borderline personality disorder. Journal of Personality Disorders, 24, 365-376.

Clifton, A., Pilkonis, P. A., & McCarty, C. (2007). Social networks in borderline

personality disorder. Journal of Personality Disorders, 21, 434-441.

Cohen, S., & Hoberman, H. (1983). Positive events and social support as buffers of life

change stress. Journal of Applied Social Psychology, 13, 99-125.

doi:10.1111/j.1559-1816.1983.tb02325.x

Cohen, J., Cohen, P., West, S. G., & Aiken, L. S. (2003). Applied multiple

regression/correlation analysis for the behavioral sciences (3 ed.). Mahwah, NJ:

Lawrence Erlbaum Associates, Inc.

Critchfield, K. L., Levy, K. N., Clarkin, J. F., & Kernberg, O. F. (2008). The relational

context of aggression in borderline personality disorder: Using adult attachment

style to predict forms of hostility. Journal of Clinical Psychology, 64, 67-82.

doi:10.1002/jclp.20434

Dougherty, D. M., Bjork, J. M., Huckabee, H. C. G., Moeller, F. G., & Swann, A. S.

(1999). Laboratory measures of aggression and impulsivity in women with

borderline personality disorder. Psychiatry Research, 85, 315-326.

Downey, G. & Feldman, S. I. (1996). Implications of rejection sensitivity for intimate

relationships. Journal of Personality and Social Psychology, 70, 1327-1343.

Downey, G., Freitas, A. L., Michaelis, B., & Khouri, H. (1998). The self-fulfilling

prophecy in close relationships: Rejection sensitivity and rejection by romantic

partners. Journal of Personality and Social Psychology, 75, 545-560.

Efron, B., & Tibshirani, R. J. (1993). An introduction to the boostrap. Boca Raton, FL:

Chapman & Hall.

First, M. B., Gibbon, M., Spitzer, R. L., Williams, J. B., & Benjamin, L. S. (1997).

Structured Clinical Interveiw for DSM-IV-TR Axis I Disorders, Research Version,

Patient Edition (SCID-I/P). Washington, DC: American Psychiatric Press.

Fossati, A., Barratt, E. S., Carretta, I., Leonardi, B., Grazioli, F., & Maffei, C. (2004).

Predicting borderline and antisocial personality disorder features in nonclinical

subjects using measures of impulsivity and aggressiveness. Psychiatry Research,

125, 161-170.

Gardner, D. L., Leibenluft, E., O’Leary, K. M., & Cowdry, R. W. (1991). Self-ratings of

anger and hostility in boderline personality disorder. The Journal of Nervous and

Mental Disease, 179, 157-161.

Grant, B. F., Chou, P., Goldstein, R. B., Huang, B., Stinson, F. S., Saha, T. D., Smith, S.

M., et al. (2008). Prevalence, correlates, disability, and comorbidity, of DSM-IV

borderline personality disorder: Results from the Wave 2 National Epidemiologic

Survey on Alcohol and Related Conditions. Journal of Clinical Psychiatry, 69,

533-545. doi: 10.4088/JCP.v69n0404

Griffin, D. W., & Bartholomew, K. (1994). Models of the self and other: Fundamental

dimensions underlying measures of adult attachment. Journal of Personality and

Social Psychology, 67, 430-445. doi:10.1037/0022-3514.67.3.430

Gunderson, J. G. (2007). Disturbed relationships as a phenotype for borderline

personality disorder. The American Journal of Psychiatry, 164, 1637-1640.

Gunderson, J. G., & Lyons-Ruth, K. (2008). BPD’s interpersonal hypersensitivity

phenotype: A gene-environment-developmental model. Journal of Personality

Disorders, 22, 22-41.

Hill, J., Harrington, R., Fudge, H., Rutter, M., & Pickles, A. (1989). Adult Personality

Functioning Assessment (APFA); an investigator based standardised interview.

British Journal of Psychiatry, 155, 24–35. doi:10.1192/bjp.155.1.24

Hill, J., Pilkonis, P., Morse, J., Feske, U., Reynolds, S., Hope, H., . . . Broyden, N.

(2008). Social domain dysfunction and disorganization in borderline personality

disorder. Psychological Medicine, 38, 135-146. doi:10.1017/S0033291707001626

Holmes, T. H., & Rahe, R. H. (1967). The social readjustment rating scale. Journal of

Psychosomatic Research, 11, 213-218. doi:10.1016/0022-3999(67)90010-4

Horowitz, L. M., Rosenberg, S. A., Baer, B. A., Ureo, G., & Villaseor, V. S. (1988).

Inventory of interpersonal problems: Psychometric properties and clinical

applications, 56, 885-892. doi:10.1037/0022-006X.56.6.885

Hyler, S. E. (1994). PDQ-4 Personality Questionnaire. New York Psychiatric Institute.

Johnson, P. O., & Neyman, J. (1936). Tests of certain linear hypotheses and their

application to some educational problems. Statistical Research Memoirs, 1, 57-

93.

Kelly, T. M., Soloff, P. H., Lynch, K. G., Haas, G. L., & Mann, J. J. (2000). Recent life

events, social adjustment, and suicide attempts in patients with major depression

and borderline personality disorder. Journal of Personality Disorders, 14, 316-

326.

Kernberg, O. (1967). Borderline personality organization. Journal of American

Psychoanalystic Association, 641-685.

Koenigsberg, H. W., Harvey, P. D., Mitropoulou, V., New, A. S., Goodman, M.,

Silverman, J., . . . Siever, L. J. (2001). Are the interpersonal and identity

disturbances in the borderline personality disorder criteria linked to the traits of

affective instability and impulsivity? Journal of Personality Disorders, 15, 358-

370.

Lejuez, C. W., Daughters, S., B, Nowak, J., A, Lynch, T., Rosenthal, M. Z., & Kosson,

D. (2003). Examining the inventory of interpersonal problems as a tool for

conducting analogue studies of mechanisms underlying Borderline Personality

Disorder. Journal of Behavior Therapy and Experimental Psychiatry, 34, 313-

324.

Linehan, M. (1993). Cognitive-Behavioral Treatment of Borderline Personality Disorder.

New York, NY: The Guilford Press.

Links, P. S., & Heslegrave, R. J. (2000). Prospective studies of outcome: Understanding

mechanisms of change in patients with borderline personality disorder.

Psychiatric Clinics of North America, 23, 137-150.

Livesley, W. J., Schroeder, M. L., Jackson, D. N., & Jang, K. L. (1994). Categorical

distinctions in the study of personality disorder: Implications for classification.

Journal of Abnormal Psychology, 103, 6-17.

Lynch, T. R., Kosson, D., Lejuez, C. W., Rosenthal, M. Z., Cheavens, J. S., & Blair, R. J.

(2006). Heightened sensitivity to facial expressions of emotion in

borderlinepersonality disorder. Emotion, 6, 647-655. doi:10.1037/1528-

3542.6.4.647

McCloskey, M. S., New, A. S., Siever, L. J., Goodman, M., Koenigsberg, H. W., Flory, J.

D., & Coccaro, E. F. (2009). Evaluation of behavioral impulsivity and aggression

tasks as endophenotypesfor borderline personality disorder. Journal of

Psychiatric Research, 43, 1036-1048. doi:10.1016/j.jpsychires.2009.01.002

Mooney, C. Z., & Duval, R. D. (1993). Bootstrapping: A nonparametric approach to

statistical inference. Newbury Park, CA: Sage.

Morey, L. C. (1991). Personality Assessment Inventory: Professional Manual. Odessa,

FL: Psychological Assessment Resources.

Newhill, C. E., Eack, S. M., & Mulvey, E. P. (2009). Violent behavior in boderline

personality. Journal of Personality Disorders, 23, 541-554.

Olsson, A., Carmona, S., Remy, K., Downey, G., & Ochsner, K. (2007). Perceiving

threat and learning to fear: Linking rejection sensitivity to biases in social

perception and learning. Presented at the The annual meeting of the congnitive

neuroscience society, New York, NY.

Paris, J., & Zweig-Frank, H. (2001). A 27-year follow-up of patients with borderline

personality disorder. Comprehensive Psychiatry, 42, 492-497.

doi:10.1053/comp.2001.26271

Preacher, K. J., & Hayes, A., F. (2004). SPSS and SAS procedures for estimating indirect

effects in simple mediation models. Behavior Research Methods, Instruments &

Computers, 36, 717-731. doi:10.3758/BF03206553

Hayes, A. F., & Matthes, J. (2009). Computational procedures for probing interactions in

OLS and logistic regression: SPSS and SAS implementations. Behavior Research

Methods, 41, 924-936.

Preacher, K. J., Rucker, D. D., & Hayes, A. F. (2007). Addressing moderated mediation

hypotheses: Theory, methods, and prescriptions. Multivariate Behavioral

Research, 42, 185-227.

Romero-Canyas, R., Downey, G., Berenson, K., Ayduk, O., & Kang, N. J. (2010).

Rejection sensitivity and the rejection–hostility link in romantic relationships.

Journal of Personality, 78, 119-148. doi:10.1111/j.1467-6494.2009.00611.x

Russell, J. J., Moskowitz, D. S., Zuroff, D. C., Sookman, D., & Paris, J. (2007). Stability

and variability of affective experience and interpersonal behavior in borderline

personality disorder. Journal of Abnormal Psychology, 116, 578-588.

doi:10.1037/0021-843X.116.3.578

Sadikaj, G., Russell, J. J., Moskowitz, D. S., & Paris, J. (2010). Affect dysregulation in

individuals with borderline personality disorder: persistence and interpersonal

triggers. Journal of Personality Assessment, 92, 490-500.

doi:10.1080/00223891.2010.513287

Schmahl, C. G., Elzinga, B. M., Ebner, U. W., Simms, T., Sanislow, C., Vermetten, E., . .

. Bremner, J. D. (2004). Psychophysiological reactivity to traumatic and

abandonment scripts in borderline personality and posttraumatic stress disorders:

A preliminary report. Psychiatry Research, 126, 33-42.

doi:10.1016/j.psychres.2004.01.005

Shea, M. T., Edelen, M. O., Pinto, A., Yen, S., Gunderson, J. G., Skodol, A. E., . . .

Morey, L. C. (2009). Improvement in borderline personality disorder in

relationship to age. Acta Psychatr Scandinavica, 119, 143-148.

doi:10.1111/j.1600-0447.2008.01274.x

Skodol, A. E., Pagano, M. E, Bender, D. S., Shea, M. T., Gunderson, J. G., Yen, S., . . .

McGlashan, T. H. (2005). Stability of functional impairment in patients with

schizotypal, borderline, avoidant, or obsessive–compulsive personality disorder

over two years. Psychological Medicine, 35, 443-451.

doi:10.1017/S003329170400354X

Skodol, A. E., Gunderson, J. G., McGlashan, T. H., Dyck, I. R., Stout, R. L., Bender, D.

S., . . . Oldham, J. M. (2002). Functional impairment in patients with schizotypal,

borderline, avoidant, or obsessive-compulsive personality disorder. The American

Journal of Psychiatry, 159, 276-283. doi:10.1176/appi.ajp.159.2.276

Soloff, P. H., & Fablo, A. (2008). Prospective predictors of suicide attempts in borderline

personality disorder at one, two, and two-to-five year follow-up. Journal of

Personality Disorders, 22, 123-134. doi:10.1521/pedi.2008.22.2.123

Soloff, P. H., Lis, J., A, Kelly, T., Cornelius, J., & Ulrich, R. (1994). Risk factors for

suicidal behavior in borderline personality disorder. The American Journal of

Psychiatry, 151, 1316-1323.

Stepp, S. D., Pilkonis, P. A., Yaggi, K. E., Morse, J. Q., & Feske, U. (2009).

Interpersonal and emotional experiences of social interactions inborderline

personality disorder. The Journal of Nervous and Mental Disease, 197, 484-491.

doi:10.1097/NMD.0b013e3181aad2e7

Tabachnick, B. G., & Fidell, L. S. (2007). Using Multivariate Statistics (Fifth Edition.).

New York: Pearson.

Tragesser, S. L., Lippman, L. H., Trull, T. J., & Barrett, K. C. (2008). Borderline

personality disorder features and cognitive, emotional, and predicted behavioral

reactions to teasing. Journal of Research in Personality, 42, 1512-1523.

doi:10.1016/j.jrp.2008.07.003

Trull, T. J., Useda, D., Conforti, K., & Doan, B. T. (1997). Borderline personality

disorder features in nonclinical young adults: 2. Two-year outcome. Journal of

Abnormal Psychology, 106, 307-314. doi:10.1037/0021-843X.106.2.307

Trull, T., J. (1995). Boderline personality disorder features in nonclinical young adults: 1.

Indentificaion and validation. Psychological Assessment, 7, 33-41.

doi:10.1037/0021-843X.106.2.307

Trull, T. J. (2001). Structural relations between boderline personality disorder features

and putative etiological correlates. Journal of Abnormal Psychology, 110, 471-

481. doi:10.1037//0021-843x.110.3.471

Welch, S. S., & Linehan, M. M. (2002). High-risk situations associated with parasuicide

and drug use in borderline personality disorder. Journal of Personality Disorders,

16, 561-569. doi:10.1521/pedi.16.6.561.22141

Zanarini, M. C., Gunderson, J. G., Frankenburg, F. R., & Chauncey, D. L. (1989). The

revised diagnostic interview for borderlines: Discriminating BPD from other Axis

II disorders. Journal of Personality Disorders, 3, 10-18

Zanarini, M. C., Frankenburg, F. R., Yong, L., Raviola, G., Reich, D. B., Hennen, J., . . .

Gunderson, J. G. (2004). Borderline psychopathology in the first-degree relatives

of boderline and axis II comparison probands. Journal of Personality Disorders,

18, 439-447.

Appendix A: Timing of Measures and Social Network Assessment

Measures Baseline Week 1 Week 4 SCID II BPD module X Demographic Questionnaire X

Social Network Assessment X X X Life events checklist X X X

PAI-BOR X X RSQ X X X BPAQ-Hostility X X

ISEL X

Figure 1: Timing of Administration for Measures

Social Network Assessment

We are interested in knowing more about the important relationships in your life and your experience of those relationships. Please list the people with whom you have interacted with two or more times for at least five minutes each time IN THE PAST WEEK. List them in order of how often you interacted with them and answer the following questions about each person. An interaction can include spending time together, talking on the phone, electronic communication, or anything else that brings you in contact with the person. Use their FIRST AND LAST name. Remember to order them from the person you interacted with most frequently to the least. 1. ______2. How close do you feel to this person?

__1 (not at all) __2 (somewhat) __3 (moderately) __ 4 (very much) 3. What is this person’s relationship to you? __Parent __Sibling __Other family __Friend __Classmate/Acquaintance __Boyfriend/Girlfriend __Spouse __Therapist __Other

4. How much support do you receive from this person? __1 (not at all) __2 (somewhat) __3 (moderately) __ 4 (very much) 5. How much does this person criticize you?

__1 (not at all) __2 (somewhat) __3 (moderately) __ 4 (very much) 6. How frequently in the past year have you experienced conflict with this person? __1 (never)

__2 (very rarely) __3 (rarely) __4 (sometimes)

__5 (frequently) __6 (very frequently) __7 (always/daily)

7. Have you cut off or stopped speaking to this person at any time in the past month? Y/N 8. Have you been involved romantically with this person previously or currently?

Y/N

9. How satisfied are you with your relationship with this person?

__0 (not at all) __1 (somewhat) __2 (moderately) __ 3 (very much) 10. Has your relationship with this person has changed substantially since the last assessment. Y/N or Not applicable

Please list the first name and first two initials of the last name of the person you interact with next most frequently. 1. ______

2. How close do you feel to this person? __0 (not at all) __1 (somewhat) __2 (moderately) __ 3 (very much) 3. What is this person’s relationship to you?

__Parent __Sibling __Other family __Friend __Classmate/Acquaintance __Boyfriend/Girlfriend __Spouse __Therapist __Other 4. How much support do you receive from this person? __0 (not at all) __1 (somewhat) __2 (moderately) __ 3 (very much)

5. How much does this person criticize you? __0 (not at all) __1 (somewhat) __2 (moderately) __ 3 (very much) 6. How frequently in the past year have you experienced conflict with this person?

__0 (never) __1 (very rarely) __2 (rarely)

__3 (sometimes) __4 (frequently) __5 (very frequently)

__6 (always/daily)

7. Have you cut off or stopped speaking to this person at any time in the past month?

Y/N 78

8. Have you been involved romantically with this person previously or currently? Y/N

9. How satisfied are you with your relationship with this person? __0 (not at all) __1 (somewhat) __2 (moderately) __ 3 (very much)

10. Has your relationship with this person has changed substantially since the last assessment. Y/N or Not applicable

*leave the option to include 24 people

Please answer the following questions about your social network overall.

How much conflict is there in your current social network? __0 (not at all) __1 (somewhat) __2 (moderately) __ 3 (very much) How satisfied do you feel with your current social network?

__0 (not at all) __1 (somewhat) __2 (moderately) __ 3 (very much) How much support do you receive from your current social network? __0 (not at all) __1 (somewhat) __2 (moderately) __ 3 (very much)

Appendix B: Tables

Table 1: Means, Standard Deviations, and Intercorrelations Among Network and Personality Variables for Main Analyses Measure Mean SD 1 2 3 4 5 6 7 8 9 10 11

1. BPD 20.77 10.03 __ features T1 2. RS T1 8.85 3.33 .27** __

3. RS T2 8.61 3.76 .26** .85** __

4. IA T1 20.78 9.27 .53** .39** .36** __

5. IA T2 20.30 10.34 .48** .39** .38** .83** __

81 6. Size T1 10.97 6.24 .03 -.14 -.14 -.04 .05 __

7. Size T3 8.27 6.34 .08 -.14 -.15 -.05 .02 .78** __

8. Satisfaction 2.44 .40 -.42** -.29** -.23* -.28** -.37** -.26** -.23* __ T1 9. Satisfaction 2.50 .55 -.27** -.14 -.09 -.26** -.22* -.13 -.26** .50** __ T3 10. Proportion .56 .23 .05 -.11 -.11 -.00 .00 -.07 .40** .03 -.25** __ Present 11. Frequency .46 1.40 .06 -.05 -.07 -.07 -.01 .74** .60** -.18* -.19* -.03 __ Change Note. *p < .05. **p < .01.

Table 2: Network Characteristics Averaged Across Partners at Baseline and One-Month Measure T1 T3 M SD M SD p Satisfaction 2.44 .40 2.49 .55 .95 Conflict 1.37 .51 1.48 .68 .01 Support 2.38 .48 2.53 .57 .13 Closeness 2.42 .48 2.62 .62 .10 Criticism .85 .51 1.02 .61 <.01 Current/former romantic Partners 1.15 1.18 .94 1.09 .92 Partners Cut-off .91 1.39 .56 .95 .11

Change in relationships 1.65 2.28 1.44 2.90 .41 Note. n = 127, expect conflict at T3, where n = 126. Romantic partner, cut off speaking, and change were yes/no questions. Repeated measures ANOVAs were performed, controlling for count at T1. Change in relationship, partners cut-off, and current/former romantic partners were Yes/No questions. Conflict was rescaled from a 7 to 4-point scale with higher scores indicating more conflict.

Table 3: Network Composition and Overall Characteristics at Baseline and One-Month Measure T1 T3 M SD M SD p

Partners listed 10.97 6.24 8.28 6.34 < .01 Family 2.95 1.86 2.37 1.98 .06 Friend/acquaintance 7.24 5.54 5.19 5.20 .71 Romantic partner .40 .51 .40 .49 .51 Therapist .001 .09 .001 .09 .56 Other .52 .96 .31 .79 .30 Overall support 3.37 .71 3.25 .80 .33 Overall satisfaction 3.22 .80 3.18 .85 .51 Overall conflict 1.61 .59 1.66 .65 .54

Note. N = 127 except for total support, satisfaction, and conflict, N = 126. Repeated measures ANOVAs were performed, controlling for count at T1. Total support, satisfaction, and conflict ratings are asked separately for the network overall.

Table 4: Summary of Simple Regression Analyses for Baseline Rejection Sensitivity Predicting Social Network Quality Characteristics at One-Month (size, satisfaction, stability; N = 126) Outcome Variable B SE B β t p

T3 Network Size -1.06 0.51 -0.18 -2.07 .04*

T3 Satisfaction -0.27 0.28 -0.09 -0.95 .34

T3 Proportion Present 0.71 0.11 -0.12 -1.32 .19

T3 Frequency Change -0.85 0.94 -0.08 -0.91 .36

Note. *p < .05. **p < .01.

Table 5: Summary of Simple Regression Analyses for Rejection Sensitivity at Baseline Predicting Aggression at One week (N = 122) Predictor Variable B SE B β t p Model 1: T1 RS 0.49 0.11 0.39 4.65 <.01** Model 2: T1 Aggression 0.85 0.07 0.75 12.57 < .01**

T1 RS 0.15 0.07 0.12 2.00 .05*

Note. *p < .05. **p < .01. Model 1: RS predicting T2 Aggression. Model 2: RS predicting T2 aggression controlling for T1 aggression.

Table 6: Summary of Simple Regression Analyses for Aggression at One Week Predicting Social Network Quality at One-Month (size, satisfaction, stability; N = 124) Outcome Variable B SE B Β t p

T3 Network Size 0.23 0.41 0.05 0.56 .57

T3 Satisfaction -0.57 0.22 -0.23 -2.57 .01*

T3 Proportion Present -0.01 0.10 -0.01 -0.09 .93

T3 Frequency Change 0.19 0.75 0.02 0.25 .80

Note. *p < .05. **p < .01.

Table 7: Test of Moderated Mediation of a1 Path by BPD Symptoms (N=124) Mediator Variable Model (predicting aggression) Predictors B SE B t p Constant 3.51 5.13 0.68 .50

T1 RSQ 0.96 0.61 1.57 .12

T1 PAIBOR 0.44 0.21 2.06 .04

T1 RSQ X T1 PAIBOR -0.00 0.02 -0.15 .88

Dependent Variable Model (predicting network satisfaction) Predictors B SE B t p Constant 2.36 0.31 7.60 < .01

T2 Aggression -0.01 0.01 -1.09 .29

T1 RSQ 0.06 0.04 1.64 .10

T1 PAIBOR 0.01 .01 1.00 .32

T1 RSQ X T1 PAIBOR -0.00 0.0 -2.01 .05

Conditional Effects at PAIBOR = mean and ± 1 SD

PAI-BOR Indirect Effect SE z p

10.70 -0.01 0.01 -0.90 .37

20.72 -0.01 0.01 -0.98 .33

30.74 -0.00 0.01 -0.94 .34

Table 8: Test of Moderated Mediation of b1 Path by BPD Symptoms (N=124) Mediator Variable Model (predicting aggression) Predictors B SE B t p Constant 9.78 2.44 4.01 < .01

T1 RSQ 1.20 0.26 4.65 < .01

Dependent Variable Model (predicting network satisfaction) Predictors B SE B t p Constant 2.75 0.25 11.03 < .01

T1 RSQ -0.01 0.02 -0.49 .62

T2 IA 0.00 0.01 0.20 .85

T1 PAIBOR -0.00 0.01 -0.27 .79

T2 IA X T1 PAIBOR -0.00 0.00 -0.77 .44 Conditional Effects at PAIBOR = mean and ± 1 SD

PAI-BOR Indirect Effect SE z p

10.70 -0.01 0.01 -0.18 .86

20.72 -0.01 0.01 -0.84 .40

30.74 -0.01 0.01 -1.20 .23

Table 9: Intercorrelations between BPD Symptoms, Stability and Other Network Characteristics for Supplementary Analyses Measure 1 2 3 4 5 6 7 8 9 10 11

1. BPD __ features T1 2. overall .27** __ conflict T3 3. overall -.37** -.39** __ satisfaction T3 4. overall support -.27** -.31** .66** __ T3 5. total -.27** -.23* .28** .26** __ satisfaction T3 6. total closeness -.22* -.15 .06 .12 .65** __

89 T3

7. total support -.23 -.09 .17 .33** .67** .70** __ T3 8. total criticism .22* .33** -.25* -.20* .02 .24** .19* __ T3 9. total conflict .25** .34** -.30** -.31** -.10 .34** .13 .70** __ T3 10. Proportion .05 .03 .09 .15 -.25** -.39** -.35** -.17 -.25** __ Present 11. Frequency .06 .02 .14 .16 -.19* -.36** -.18* -.22* -.23* -.03 __ Change Note. *p < .05. **p < .01.

Table 10 : Intercorrelations between BPD Symptoms, Stability, and Partner Characteristics Measure 1 2 3 4 5 6 7 8 9 10 11

1. BPD __ features T1 2. Family T3 -.01 __

3. Friend T3 .04 .36** __ 4. Romantic Partner .03 .12 -.10 __ T3 5. Therapist T3 .10 -.06 .01 -.07 __

6. Other T3 .36** .25** .05 .13 .08 __

90 7. Current or former .22* .20* .41** .35** .08 .19* __ romantic T3 8. Cut-off speaking .23** -.02 .30** -.09 .04 .31** .27** __ T3 9. Change in .12 .49** .34** .09 -.01 .34** .33** .47** __ relationship T3 10. Proportion .05 .29** .36** .05 -.01 .26** .12 .15 .16 __ Present

11. Frequency .06 .36** .59** -.11 -.02 -.10 .30** .28** .34** -.03 __

Change Note. *p < .05. **p < .01. Family is combination of parent, sibling, and other family. Friend is combination of friend and classmate/acquaintance. Romantic partner is combination of boyfriend/girlfriend and spouse. For each partner listed, participant rated whether they were a current or former romantic partner, whether they had cut off speaking to that person at any time since the last assessment, and if the relationship had changed since the last assessment.

Appendix C: Mediation and Moderated Mediation Models

a 1 b

X Y 1

Figure 2: Model of Simple Mediation

Interpersonal

Aggression

a 1 b

Rejection Social 1 Sensitivity Network Quality c

Figure 3: Proposed Model of Simple Mediation

W W

a 1 b

X Y 1

Figure 4: Model of Moderated Mediation Model

Interpersonal BPD symptoms BPD symptoms Aggression

a 1 b Social Rejection Network Sensitivity 1 Quality c

Figure 5: Proposed Model of Moderated Mediation Model