Young People With Borderline Personality Disorder Have an Increased Lifetime Risk of Being the Victim of Interpersonal Violence

Abstract

This study aimed to examine the lifetime risk of being the victim of criminal or violent offenses among young people with borderline personality disorder (BPD) features (1-9 DSM-IV criteria). Demographic and diagnostic data from 492 outpatients who attended a specialist public mental health service for 15- to 25-year-olds between January 1998 and March 2008 were linked with offending data from a state-wide police database, collected between March 1993 and June 2017, in order to establish victimization history. This included information on criminal offenses perpetrated against these young people and intervention orders implemented to protect them from being victimized by another person’s violent behavior. Logistic regression analyses, adjusted for sex and co-occurring mental state disorders, were conducted on n = 378 who had complete data (76.5% females). As hypothesized, BPD diagnosis and number of BPD criteria were both significantly associated with an increased risk of being the victim of a violent offense and the complainant of a family violence intervention order. Anger and impulsivity independently predicted a higher risk of being the victim of a violent offense, while unstable relationships, impulsivity, and affective instability independently predicted a higher risk of being the complainant of a family violence intervention order. No significant association was found between BPD and the risk of being the victim of a nonviolent offense. These findings indicate that young people with any BPD features (even below the DSM diagnostic threshold) are at increased risk for victimization by interpersonal violence. Moreover, this risk increases according to the number of BPD criteria. This issue needs to be addressed by prevention and early intervention programs (e.g., by working on self-assertion and interpersonal skills, taking into account the possible influence of previous traumatizing relationship experiences).

Keywords

aggression borderline personality disorder crime offenses victimization longitudinal

Introduction

Borderline personality disorder (BPD) is associated with severe and persistent impairments in interpersonal, educational, and vocational functioning (Gunderson, 2011; Skodol et al., 2005) and high economic costs (Van Asselt et al., 2007). Interpersonal dysfunction among people with BPD can increase their risk of becoming either the perpetrator and/or victim of violence. While most studies have focused on the link between BPD and violence perpetration (Arola et al., 2016; González et al., 2016; Newhill et al., 2012; Zanarini et al., 2017), relatively few studies have examined the risk of people with BPD becoming the victim of interpersonal violence. These studies have reported that people with BPD are at increased risk for violent victimization (Moore et al., 2018; Sansone et al., 2011; Scott et al., 2014; Stepp et al., 2012). Moreover, the risk is higher among females than males (Zanarini et al., 1999). When examining the mechanisms through which BPD is linked to violent victimization, emotional dysregulation (Buckholdt et al., 2015; Scott et al., 2014), verbal aggression and hostility, need for social approval (Stepp et al., 2012), and having experienced childhood trauma (Zanarini et al., 1999) were identified as risk factors, while interpersonal sensitivity was identified as a protective factor (Stepp et al., 2012).

Current research on the risk of being the victim of crimes and violence among people with BPD is limited by the utilization of self-report measures to assess victimization, exclusion of victimization by nonviolent crimes (e.g., property and deception offenses), and cross-sectional study designs or short follow-up periods in longitudinal studies. Strikingly, most studies have focused on adults with BPD and have included small and selective samples (e.g., prisoners or psychiatric inpatients), limiting the generalizability of their results. The few studies investigating young people did not examine the risk for violent victimization associated with BPD (Buckholdt et al., 2015; Hatkevich et al., 2017). Rather they examined the effects of violence exposure on either non-suicidal self-injury (among adolescent inpatients with low and high BPD features [Hatkevich et al., 2017]), or the development of emotion dysregulation and BPD pathology (among adolescents admitted to a psychiatric residential treatment centre [Buckholdt et al., 2015]). Clearly, more information is required about the relationships between BPD pathology and the risk of being the victim of criminal and violent offending among community-dwelling young people, who constitute the vast majority of young people with BPD. Such information would inform prevention and early intervention programs for young people with first-presentation or subthreshold BPD that have been shown to be effective (Chanen et al., 2017, 2020).

The current study aimed to examine the lifetime risk of being a victim of a criminal offense or the complainant seeking an intervention order (i.e., a court order to protect a person from the violent behavior of someone else) in outpatient young people aged 15–25 years with borderline pathology (1–9 DSM-IV BPD features). We hypothesized that: (a) young people with a categorical BPD diagnosis (≥ 5 criteria) would have a higher risk of being the victim of a criminal offense or the complainant seeking an intervention order than young people without BPD (≤ 4 criteria); and (b) young people with a greater number of BPD criteria (from 0 to 9) would have an increased risk of being the victim of a criminal offense or the complainant seeking an intervention order. In addition, we investigated the moderating effect of sex on the association between BPD and the risk for victimization, and explored the differential impact of individual BPD features on the risk of victimization.

Methods

Design

This was a data linkage study connecting demographic and diagnostic data with information regarding criminal offenses and intervention orders in order to establish victimization history.

Participants and Setting

The study utilized a convenience sample of 492 help-seeking young people who were assessed for clinical or research purposes at a single-site, government-funded specialist mental health service for 15–25- year-olds between March, 1998 and March, 2008. The service includes a specialist early intervention program for BPD. Referral sources include emergency departments and crisis services, self-referral, other healthcare agencies, family or friends, and educational services. The primary inclusion criterion for the BPD program is meeting three or more BPD criteria according to the 4th edition of the Diagnostic and Statistical Manual of Mental Disorders (DSM-IV), which was current at the time of data collection. Patients with a first episode of psychosis were allocated to the specialist early intervention program for psychosis of the service. There are no specific exclusion criteria for other forms of psychopathology.

Demographic and Diagnostic Data

Demographic and diagnostic information was sourced from client records collected as part of routine clinical practice, or from research data collected as part of a study (Chanen et al., 2004; Jennings et al., 2012). Demographic data included sex, age, socioeconomic status, education, and occupation. Residential postcode was used to determine socioeconomic status according to the Index of Relative Socio-economic Disadvantage (IRSD; Australian Bureau of Statistics, 2011b), with tertiles (i.e., low, medium, and high socioeconomic status) used in the analyses. BPD diagnosis according to the DSM-IV was assessed using the Structured Clinical Interview for Axis II Disorders (SCID-II; First et al., 1994). In the SCID-II, each DSM-IV BPD item is scored on a 3-point scale (1 = absent, 2 = subthreshold, or 3 = present). Categorical BPD diagnosis was made by counting the number of items scored as 3. Reliability of diagnoses was maintained through a consensus diagnosis process with a senior HYPE clinician for each DSM-IV-TR BPD criterion (Chanen et al., 2009). Acceptable interrater reliability scores were reported for the BPD data assessed as part of the research study (Chanen et al., 2004). Co-occurring mental state diagnoses were assessed in accordance with DSM-IV. They were categorized into depressive disorders (including major depressive disorder and dysthymic disorder), anxiety disorders (including generalized anxiety disorder, panic disorder, obsessive-compulsive disorder, posttraumatic stress disorder, and acute stress disorder), substance use disorders (including substance abuse and dependence), and other disorders (e.g., psychotic disorders, bipolar disorders, or conduct disorder). All assessments were conducted by trained clinicians or clinical researchers. Study participants were reimbursed AU$30 for their time and travel expenses.

Police Data

Information on victimization was obtained from the state-wide Victoria Police Law Enforcement Assistance Program (LEAP) database, Australia, as at June 30, 2017. The LEAP database is an administrative data system that documents crime-related information gathered by Victoria Police members during their day-to-day operations since March, 1993. The database includes offenses committed by individuals aged 10 years and older, and records all offenses regardless of whether the defendant is later found guilty or not guilty. We used charges as the measure of offending because charges are frequently combined or dropped during progress toward a criminal verdict. Victimization data used in the current study included whether a participant had ever been the victim of a criminal offense (yes/no) and the type of criminal offense (i.e., violent versus nonviolent). The offense categories specified by Victoria Police (Corporate Statistics, Corporate Strategy and Operational Improvement Department, Victoria Police, 2014) and the cross-jurisdictional Australian and New Zealand Standard Offence Classification System (Australian Bureau of Statistics, 2011a) were used to assist in operationalizing these two broad offense types. Specifically, violent offenses were defined as homicide offenses, acts intended to threaten or unlawfully deprive another person of their freedom of movement (e.g., abduction, harassment), acts intended to cause injury (e.g., unlawful assault, intentionally cause injury), all contact sexual offenses (e.g., rape, attempted rape, indecent assault, sexual penetration of a child), dangerous/negligent acts endangering persons (e.g., recklessly cause injury, reckless conduct endangering life), and armed/unarmed robbery. Nonviolent offenses were defined as property and deception offenses (e.g., arson, burglary, theft, fraud), drug offenses (e.g., possession, manufacturing, trafficking), public order and security offenses (e.g., disorderly conduct, possession of prohibited weapons/explosives), justice procedure offenses (e.g., breach of bail, failure to appear), and pornography offenses (e.g., make/produce/possess child pornography as part of “sexting” between peers). In addition, two other markers of victimization were taken from the LEAP database, namely the police or the complainant seeking a family violence intervention order or a personal safety intervention order. Family violence intervention orders are made to protect a person from a family member (i.e., anyone in a family or family-like relationship, including current and former intimate partners, relatives, same-sex partners and carers) who is using family violence, defined as any behavior, whether a criminal offense or not, that in any way controls or dominates a family member and causes them to feel fear for their own or other family members’ safety or well-being (Parliament of Victoria, 2008). Personal safety intervention orders can be made by a court to protect a person who has experienced violent, threatening or abusive behavior from someone who is not a family member. Family violence and personal safety intervention orders are both nonarrest law enforcement responses; however, a respondent who breaches the conditions of these orders can be charged with a criminal offense. Information on participants as offenders or recipients of a (family violence or personal safety) intervention order has been analyzed separately (Cavelti et al., accepted).

Procedure

Data linkage was performed by members of the Victoria Police data management unit. The extracted matches were subsequently provided to the researchers in de-identified and encrypted form to safeguard the participants’ anonymity. The study was conducted according to the World Medical Association Declaration of Helsinki, and approved by the local ethics and institutional committees (Melbourne Health Human Research Ethics Committee (2008.614) and Victoria Police Research Coordination Committee [823]). Consent for data linkage was waived in line with the Australian Government’s National Statement on Ethical Conduct in Human Research (The National Health and Medical Research Council, Commonwealth of Australia, 2015).

Statistical Analyses

Statistical analyses were performed using IBM® SPSS® Statistics for Windows, version 22.0 (IBM Corp., 2013). Missing value analysis on demographic and diagnostic variables revealed the following rates: 0.2% for age, 32.1% for socioeconomic status, 35.8% for occupation, 39.0% for education, 0.2% for affective instability (BPD criterion 6) and dissociation and paranoid ideation (BPD criterion 9), 0.4% for chronic emptiness (BPD criterion 7), and 22.8% for co-occurring mental state disorders. A subsample of n = 378 with complete data for sex, BPD criteria, and co-occurring mental state disorders was identified and used for further analyses. There were no other specific inclusion or exclusion criteria for the current study. Table 1 shows the demographic and diagnostic characteristics of the total cohort, and the subgroups with and without a BPD diagnosis.

Table 1.

Demographic and Diagnostic Characteristics of the Total Cohort (N = 378) and Separately by BPD (n = 139) and No BPD (n = 239) Groups.

	Total Cohort	BPD Group	No BPD Group
	M (SD), n(%)	M (SD), n(%)	M (SD), n (%)
SexMaleFemale	89 (23.5)289 (76.5)	25 (18.0)114 (82.0)	64 (26.8)175 (73.2)
Age at entry assessment (years)	18.20 (2.69)	18.86 (2.85)	17.82 (2.51)
Age at time of data linkage (years)	31.86 (2.82)	31.62 (2.98)	32.00 (2.74)
Duration of follow-up (years)	13.66 (2.67)	12.76 (2.17)	14.18 (2.80)
Education completedYear 7–10Year 11–12Tertiary education	(n = 298)157 (52.7)136 (45.6)5 (1.7)	(n = 112)61 (54.5)49 (43.8)2 (1.8)	(n = 186)96 (51.6)87 (46.8)3 (1.6)
Studying/employed	(n = 314)212 (67.5)	(n = 118)62 (52.5)	(n = 196)150 (76.5)
Socioeconomic statusLowMediumHigh	(n = 331)40 (12.1)125 (37.8)166 (50.2)	(n = 111)9 (8.1)37 (33.3)65 (58.6)	(n = 220)31 (14.1)88 (40.0)101 (45.9)
Total number of BPD criteria	3.76 (2.05)	5.91 (0.96)	2.52 (1.38)
Number of BPD criteria met0123456789	37 (9.8)20 (5.3)30 (7.9)86 (22.8)66 (17.5)59 (15.6)44 (11.6)27 (7.1)8 (2.1)1 (0.3)	0000059 (42.4)44 (31.7)27 (19.4)8 (5.8)1 (0.7)	37 (15.5)20 (8.4)30 (12.6)86 (36.0)66 (27.6)00000
Mental state diagnosisDepressive disorderAnxiety disorderSubstance abuse disorderOther	225 (59.5)102 (27.0)66 (17.5)107 (28.3)	87 (62.6)41 (29.5)28 (20.1)45 (32.4)	138 (57.7)61 (25.5)38 (15.9)62 (25.9)

Note. BPD group = ≥ 5 DSM-IV BPD criteria; no BPD group = 0–4 DSM-IV BPD criteria.

Hierarchical binomial logistic regression analyses were conducted to examine the associations of a BPD diagnosis (i.e., ≥ 5 criteria scored as 3 in the SCID-II), number of BPD criteria met (i.e., the number of BPD criteria scored as 3 in the SCID-II), and individual BPD criteria (i.e., if scored as 3 in the SCID-II) with the likelihood of being the victim of a violent or nonviolent offense, and the complainant of a family violence or a personal safety intervention order. The independent associations between each BPD criterion and the victimization outcomes were examined adjusting the logistic regression models for all other BPD criteria simultaneously. Covariates (i.e., common risk factors for victimization including sex and co-occurring mental state diagnoses (Latalova et al., 2014)) were entered in block 1, followed by the variable of interest (i.e., BPD diagnosis, number of BPD criteria, or all individual BPD criteria simultaneously) in block 2. In order to examine whether sex moderates the relationship between the number of BPD criteria and the likelihood of being the victim of a criminal offense or the complainant of an intervention order, logistic regression analyses were repeated with an interaction term (sex × number of BPD criteria) entered in block 3. The dimensional BPD score was chosen for the moderation analysis, as personality disorder dimensions have been found to be more reliable and valid than categorical diagnoses (Clark, 2007). As requested by a reviewer, the analyses were repeated, including the duration of follow-up (years) as an additional variable. The results remained unchanged.

For each logistic regression analysis, the assumptions of linearity between the continuous independent variables (i.e., number of BPD criteria met) and the logit transformation of the dependent variable (i.e., yes/no to being the victim of a violent or nonviolent offense, or being the complainant of a family violence or personal safety intervention order), and of multicollinearity between independent variables were checked and found to be met. For binary regression models, it is the number of events per variable (EPV), rather than the sample size, that matters regarding statistical power (Babyak, 2004). The recommended minimum for the EPV of 10:1 (Peduzzi et al., 1996) was met for all regression models, except from the models predicting personal safety intervention orders. Odds ratios (OR) and 95% CI of the OR were reported as effect sizes and interpreted as follows: 1.0–1.5 = small; 1.6–2.5 = moderate; 2.6–9.9 = large; ≥10.0 = very large (Fazel et al., 2018). An alpha level of <0.05 was adopted for all analyses. We did not correct for multiple comparisons, because the study focused on only a few planned, complementary comparisons (Feise, 2002; Rothman, 1990).

Results

Rates of Victimization

Table 2 shows the frequency of being the victim of a criminal offense or the complainant seeking an intervention order for the total cohort, and the subgroups with and without a BPD diagnosis. Rates of victimization for nonviolent offenses in the total cohort were high at nearly 60%. Victimization as a result of violent offenses was around 50% for the total cohort. Just over one-third of the total cohort had been a complainant seeking a family violence intervention order. Personal safety intervention orders were not common.

Table 2.

Rates of Being the Victim of a Criminal Offense or the Complainant of an Intervention Order for the Total Cohort (N = 378) and Separately By BPD (n = 139) and No BPD (n = 239) Groups.

	Total Cohort	BPD Group	No BPD Group
	n (%)	n (%)	n (%)
Victim of a violent offense	187 (49.5)	83 (59.7)	104 (43.5)
Victim of a nonviolent offense	226 (59.8)	83 (59.7)	143 (59.8)
Complainant of a family violence intervention order	134 (35.4)	69 (49.6)	65 (27.2)
Complainant of a personal safety intervention order	19 (0.5)	9 (6.5)	10 (4.2)

Note. BPD group = ≥ 5 DSM-IV BPD criteria; no BPD group = 0–4 DSM-IV BPD criteria.

Victimization and BPD Diagnosis

Participants who were diagnosed with BPD had a significantly higher risk of being the victim of a violent offense and the complainant seeking a family violence intervention order, compared with those who did not meet the diagnostic threshold for BPD, when adjusted for sex and co-occurring mental state disorders (see Table 3, left column). The effect sizes were moderate. No significant associations were found between being diagnosed with BPD and being the victim of a nonviolent offense or the complainant of a personal safety intervention order.

Victimization and BPD Severity

An increasing number of BPD criteria was significantly associated with an elevated risk of being the victim of a violent offense or the complainant seeking a family violence intervention order, when adjusted for sex and co-occurring mental state disorders (see Table 3, right column). The effect sizes were small. No significant associations were found between the number of BPD criteria and being the victim of a nonviolent offense or the complainant seeking a personal safety intervention order.

Table 3.

Logistic Regression to Predict the Likelihood of Being the Victim of a Criminal Offense or the Complainant of an Intervention Order By (a) BPD Diagnosis (Present: n = 139, Absent n = 239) and (b) Number of BPD Criteria (N = 378).

	BPD Diagnosis		Number of BPD Criteria
	OR	95% CI	OR	95% CI
Victim of a violent offense	1.86**	1.20, 2.87	1.23***	1.10, 1.37
Victim of a nonviolent offense	1.00	0.65, 1.53	0.97	0.87, 1.07
Complainant of a family violence intervention order	2.54***	1.60, 4.03	1.35***	1.20, 1.53
Complainant of a personal safety intervention order	1.66	0.65, 4.26	1.16	0.91, 1.48

Note. Adjusted for sex and co-occurring mental state disorders.

Significant at: **p < .01; ***p < .001.

Moderation by Sex

When testing the moderator effect of sex on the association between the number of BPD criteria and the likelihood of being the victim of a criminal offense or the complainant of an intervention order, the interaction (sex x number of BPD criteria) was only significant in the regression analysis predicting family violence intervention orders (see Table 4). The linear increase of the likelihood of being the complainant seeking a family violence intervention order with a greater number of BPD criteria was significantly higher for males, compared with females, when adjusted for co-occurring mental state disorders.

Table 4.

Testing Sex as a Moderator of the Relationship Between the Number of BPD Criteria and the Likelihood of Being the Victim of an Offense or the Complainant of an Intervention Order (N = 378).

	Interaction Term
	OR	95% CI	p
Victim of a violent offense	0.91	0.70, 1.18	.482
Victim of a nonviolent offense	0.94	0.74, 1.20	.607
Complainant of a family violence intervention order	0.55	0.33, 0.93	.024*
Males	2.32	1.41, 3.83	.001**
Females	1.28	1.23, 1.45	<.001***
Complainant of a personal safety intervention order	0.69	0.30, 1.57	.373

Note. Adjusted for co-occurring mental state disorders.

Significant at: * p < .05; ** p < .01; *** p < .001.

Victimization and BPD Features

When adjusted for sex and co-occurring mental state disorders, both impulsivity and anger predicted a significantly higher likelihood of being the victim of a violent offense. In addition, unstable relationships, impulsivity, and affective instability were associated with an increased likelihood of being the complainant seeking a family violence intervention order (see Table 5). The effect sizes were moderate. No significant associations were found between individual BPD features and being the victim of a nonviolent offence or the complainant seeking a personal safety intervention order.

Table 5.

Logistic Regression to Predict the Likelihood of Being the Victim of a Criminal Offense or the Complainant of an Intervention Order by Individual BPD Criteria (N = 378).

	Avoid Abandonment		Unstable Relationships		Identity Disturbance		Impulsivity		Suicidal Behavior		Affective Instability		Emptiness		Anger		Dissociation/Paranoid Ideation
	OR	95% CI	OR	95% CI	OR	95% CI	OR	95% CI	OR	95% CI	OR	95% CI	OR	95% CI	OR	95% CI	OR	95% CI
Victim of a violent offense	0.69	0.40, 1.18	1.28	0.80, 2.03	1.13	0.70, 1.84	1.70*	1.05, 2.73	1.15	0.73, 1.83	0.97	0.59, 1.59	1.26	0.78, 2.01	1.88*	1.17, 3.03	1.45	0.77, 2.71
Victim of a nonviolent offense	1.12	0.66, 1.91	1.28	0.81, 2.03	0.86	0.54, 1.37	1.13	0.70, 1.81	0.73	0.46, 1.15	0.72	0.44, 1.18	1.14	0.72, 1.81	0.94	0.59, 1.50	1.03	0.67, 1.89
Complainant of a family violence intervention order	0.96	0.54, 1.68	1.74*	1.06, 2.86	0.99	0.60, 1.65	1.96*	1.17, 3.30	0.99	0.59, 1.64	1.92*	1.11, 3.31	1.30	0.79, 2.15	1.28	0.76, 2.15	1.22	0.64, 2.31
Complainant of a personal safety intervention order	0.32	0.07, 1.47	1.56	0.57, 4.31	1.23	0.44, 3.42	1.66	0.59, 4.63	0.86	0.30, 2.43	1.41	0.44, 4.55	1.65	0.59, 4.59	1.39	0.46, 4.18	0.52	0.11, 2.51

Note. Adjusted for sex and co-occurring mental state disorders.

Significant at: * p < .05.

Discussion

Using data linkage, this study examined the risk of being the victim of a criminal offense or a violent incident that was attended by the police (from the age of 10 years to an age that ranged across participants between 25 and 38 years) among people assessed for BPD as outpatients when aged between 15 and 25 years. The main findings to emerge from this study were that the BPD diagnosis and BPD severity, defined as the number of BPD criteria, were both associated with being a victim of interpersonal violence, potentially mediated by individual features including intense and inappropriate anger, impulsivity, affective instability, and unstable interpersonal relationships.

Both having a categorical diagnosis of BPD and a greater number of BPD criteria was associated with an approximately 1.25- to 2.5-fold risk of being the victim of a violent offense (e.g., abduction, harassment, assault, rape, robbery) or family violence, when adjusted for sex and co-occurring mental state disorders. These results are in line with previous studies among samples of adults that found that patients with BPD reported high rates of victimization by physical and emotional aggression (Sansone et al., 2011; Scott et al., 2014; Stepp et al., 2012; Zanarini et al., 1999). The current findings extend previous research by demonstrating that the risk for violent victimization increases according to the number of BPD criteria. Additionally, BPD specifically increases the risk for victimization by interpersonal violence because there was no association between BPD and being the victim of a non-violent crime (e.g., property and deception offences).

Among the young people studied, males had a higher increase in the risk of being a victim of family violence with an increasing number of BPD criteria than did females (OR 2.32 vs. 1.28), when adjusted for co-occurring mental state disorders. This result stands in contrast to a study with adult patients with BPD (Zanarini et al., 1999) that found higher rates of physical and/or sexual assault during adulthood for females, compared with males (50% vs. 26%). Methodological differences between the studies might account for the diverging results. In the current study, police data were used to establish victimization history, while Zanarini et al. (1999) relied on self-report. Subjective measures are more likely to be affected by a gender difference in reporting violent victimization, with males tending to underreport (Carmo et al., 2011). Our finding also contradicts those from community studies reporting higher rates of violent victimization in close relationships for women compared with men (Hickman et al., 2004). A similar pattern has been found with regard to violence perpetration. In the general population, males are more likely than females to engage in aggressive behaviors, while among BPD patients the opposite was found (Arola et al., 2016; González et al., 2016). Thus, it could be argued that BPD attenuates, or even inverts, rather than aggravates sex differences in both perpetration of and victimization by interpersonal violence that are present in the general population (Mancke et al., 2015).

Intense and inappropriate anger and impulsivity were found to be associated with a 1.7- to 1.8-fold increased risk of being the victim of a violent offense, and unstable and intense interpersonal relationships, impulsivity, and affective instability were found to be associated with a 1.7- to 1.9-fold increased risk of being the complainant seeking a family violence intervention order, when adjusted for sex and co-occurring mental state disorders. These results are in line with previous research with adult samples reporting difficulties in emotional regulation (e.g., anger) that can lead to impulsive reactions, and interpersonal problems may be specific mechanisms by which BPD is linked with violent victimization (Scott et al., 2014; Stepp et al., 2012). The current findings may indicate that not all young people with BPD are at the same risk for becoming the victim of interpersonal violence, as those with emotion regulation difficulties, impulsivity, and unstable interpersonal relationships are at a higher risk.

Strengths and Limitations of the Study

The strengths of this study include the longitudinal design, the examination of young people with borderline pathology, the utilization of objective data regarding victimization, and the combination of the categorical approach towards BPD with dimensional and symptom-level approaches, which allowed quantification of the number of BPD criteria in addition to using diagnosis, and to study the specific correlates of each symptom of BPD.

The study has several limitations. First, we did not assess race/ethnicity of the participants. Second, a relatively high number of missing values was identified in the demographic and diagnostic data. As a result, the analyses were conducted on a subsample with complete data for the main variables. We cannot rule out that this strategy led to a selection bias. Additionally, due to the high number of missing values, socioeconomic status, education, and occupation were not included as covariates in the analyses. Second, personal safety intervention orders were rare events in the current sample, and the EPV ratio for this outcome variable was below the recommended minimum of 10:1 (Peduzzi et al., 1996). Having too many predictor variables in a model (i.e., overfitting) can result in reduced statistical power to detect true effects and limits the generalizability of results (Babyak, 2004). Thus, further research is needed to investigate whether BPD in young people is indeed not associated with the risk for violent victimization by people other than intimate partners and family members, or whether this only holds true for the current sample. Third, the police data utilized by this study might overestimate actual victimization rates as they include offenses for which a person is later found not guilty, or underestimate actual victimization rates because not all criminal or violent activities are detected by police. Future studies examining frequencies of and repetitive victimization (instead of dichotomous outcomes), the prospective risk for becoming the victim of an offense (instead of the lifetime risk), the characteristics of the young people with BPD features who become victims of violence during adolescence (compared to other periods of life), situational factors contributing to victimization (e.g., by applying an experience sampling method), the mechanisms (i.e., mediating variables) underlying the link between BPD and the risk of victimization, as well as the risk of being both victim and perpetrator of interpersonal violence are warranted.

Clinical Implications

The findings have several clinical implications. Clinicians working with young people with BPD pathology should be aware that these young people are not only more likely to engage in aggressive behaviors towards the self (e.g., nonsuicidal self-injury, suicidal threats, and attempts) and others (i.e., violence perpetration) but are also more likely to be the victim of aggression by others. This applies to patients of both sexes, but especially males. Prevention and early intervention for young people with BPD pathology (Chanen et al., 2020), regardless of whether they meet the BPD diagnostic threshold or not, should include the assessment and management of experiencing interpersonal violence. For example, in the context of empirically supported treatments for people with BPD pathology (e.g., Dialectical Behavioural Therapy for Adolescents (DBT-A; Mehlum et al., 2014) or Cognitive Analytic Therapy (CAT; Chanen et al., 2008)), the heightened risk for violent victimization could be addressed by working on self-assertion and interpersonal skills, taking into account the possible influence of previous traumatizing relationship experiences. Future research should investigate the effectiveness of such treatments to reduce the risk for violent victimization as well as potential adaptations needed to fit the special needs of those who have already experienced interpersonal violence (e.g., assessing and treating the emotional consequences of having experienced interpersonal violence, collaboration with specialized services for victims of interpersonal violence, support in communicating with the police and the justice system).

Footnotes

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship and/or publication of this article.

Funding

The author(s) disclosed receipt of the following financial support for the research, authorship and/or publication of this article: MC was supported by grants from the Bangerter-Rhyner-Foundation and the Janggen-Pöhn Foundation in Switzerland.

ORCID iD

Andrew Chanen

Author Biographies

Marialuisa Cavelti, PhD, is a researcher and clinician at the University Hospital for Child and Adolescent Psychiatry and Psychotherapy in Bern, Switzerland. Her current research focuses on borderline personality disorder in young people and auditory verbal hallucinations across diagnostic groups.

Katherine Thompson, BA, BAppSci(Hons), PhD(PsychMed), Btheol, BSW, MACSW, is a senior research fellow at Orygen in Melbourne, Australia. Her research interests include borderline personality disorder, youth mental health, and psychosis.

Jennifer Betts, DPsych(Clinical), is a senior research fellow and study coordinator at Orygen in Melbourne, Australia. Her research interests include borderline personality disorder and youth mental health.

Claire Fowler, graduated with a DPsych(Clinical) from Monash University in Australia. Her research interests include borderline personality disorder in youth and measurement of psychosocial functioning.

Stefan Luebbers, PhD, is a lecturer and clinical forensic psychologist. His clinical background includes experience in general and forensic mental health with children, adolescents, and adults, drug and alcohol dual diagnosis, youth justice, adult correctional settings, and military psychology. Research interests: youth mental health and violence, victimization and abuse, and adolescent service delivery.

Sue M. Cottton, PhD, MAppsSc, MPsych, GradDipAppSc, BBSc(Hons), is the head, health services and outcomes research at Orygen in Melbourne, Australia. Her current work is focused on measuring change and progress in young people with mental illness and particularly those with first episode psychosis, in order to improve outcomes.

Andrew Chanen, MBBS(Hons), B.Med.Sci(Hons), MPM, PHD, FRANZCP, is director of clinical programs and services at Orygen in Melbourne, Australia. His research, and clinical and training interests lie in prevention and early intervention for severe mental disorders, principally personality disorders, along with mood and psychotic disorders.

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