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. Author manuscript; available in PMC: 2024 Mar 1.
Published in final edited form as: Womens Health Issues. 2022 Dec 27;33(2):208–214. doi: 10.1016/j.whi.2022.11.007

Is the Risk for Sexual Revictimization Cumulative? A Prospective Examination

Anna E Jaffe a, Alexandra N Brockdorf a, Terri L Messman b, Kim L Gratz c, David DiLillo a
PMCID: PMC10023376  NIHMSID: NIHMS1861220  PMID: 36581510

Abstract

Objective:

Sexual abuse during childhood is associated with risk for sexual assault as an adult, known as revictimization. Although multiple experiences of sexual assault in adulthood are also common, it is unclear how risk trajectories might continue to evolve in emerging adulthood, defined as ages 18 to 25. Clarifying risk trajectories is important to inform the development of targeted risk reduction interventions. To fill this gap, we examined cumulative risk for sexual assault in emerging adult women following multiple experiences of childhood sexual abuse (CSA) and adulthood sexual assault (ASA).

Methods:

Women (N = 447; aged 18–25 at enrollment) completed behaviorally specific assessments of unwanted sexual experiences at up to nine time points across three years. A logistic regression was used to predict any sexual assault during the three-year period as a function of victimization history at baseline. A multilevel logistic regression among ASA survivors was then used to determine whether each successive ASA increased risk for further victimization.

Results:

Extending prior research, findings revealed that risk for sexual assault during the three-year study was greater for women reporting more prior experiences of CSA and ASA. Unexpectedly, each ASA increased risk for a subsequent ASA to a lesser extent among women with more experiences of CSA.

Conclusions:

Findings suggest that risk for sexual revictimization can be cumulative, but that risk does not increase indefinitely. Future research should investigate the points at which survivors of multiple assaults may begin to experience reduced risk for later assaults, as well as the factors associated with change in risk status (e.g., removal from violent environments or relationships, changes in institutional policies). Such research could inform intervention targets.

Keywords: sexual violence, rape, abuse, revictimization

Introduction

Sexual assault, referring to sexual activity when consent is not given freely, is a prevalent public health problem that disproportionately impacts girls and women (Breiding et al., 2014). Sexual assault is associated with negative outcomes, including increased risk of depression, posttraumatic stress disorder (PTSD), and substance use disorders (Dworkin, 2020). Almost half of sexual assault survivors experience more than one episode of victimization (Walker et al., 2019). Known as revictimization, this phenomenon is especially concerning given the cumulative effects of multiple sexual assaults on mental health and substance use problems (Messman-Moore & Long, 2003). As posited by routine activity theory (Cohen & Felson, 1979), risk for victimization is elevated in contexts where there are potential perpetrators but not capable guardians. Accordingly, much work has focused on potential contextual reasons for revictimization, such as living in high-risk neighborhoods (Morris et al., 2019), having a violent partner (Mele, 2009), and efforts to cope with assault-related distress (e.g., drinking, sexual activity) that inadvertently place survivors in risky environments where potential perpetrators may be present (Lorenz & Ullman, 2016; Rinehart et al., 2014). However, current understanding of the mechanisms underlying revictimization is not yet comprehensive enough to inform effective interventions (Macy, 2008), perhaps in part because the full scope of the revictimization pattern is not well understood. Indeed, several temporal considerations might help to clarify revictimization risk, such as the survivor’s age and the specific time period during which revictimization is being studied. As a next step toward creating and improving interventions to reduce revictimization risk in women, we focus here on prospectively examining risk trajectories for women’s experience of sexual violence.

Traditionally, revictimization has been operationalized as increased risk for sexual assault in adulthood following sexual abuse in childhood (Classen et al., 2005). This association between childhood sexual abuse (CSA) and adulthood sexual assault (ASA) has been demonstrated across cross-sectional and prospective studies (Lau & Kristensen, 2010; Messman-Moore & Long, 2003; Noll et al., 2003). Further, this link is robust to variations in age of initial victimization, gender of the survivor, and definitions of sexual victimization (e.g., any unwanted sexual activity versus rape; Walker et al., 2019). In addition to associations between victimizations across discrete developmental periods (i.e., from childhood to adulthood), there are more proximal links between initial and subsequent victimization within developmental periods, including repeated sexual victimization in childhood (Swanston et al., 2002) and adulthood (Daigle et al., 2008; Ullman & Peter-Hagene, 2016). Together, findings suggest that a prior history of sexual victimization is one of the most robust predictors of subsequent sexual victimization.

However, extant research on revictimization has several methodological and conceptual limitations. Most work is retrospective and asks survivors to report on all past experiences of sexual violence, which may be subject to recall biases such as difficulty recalling the timing and order of events. Use of more frequent assessments that are closer in time to the experiences of victimization could help address these limitations by minimizing recall biases. Further, although many survivors experience more than two assaults (Tjaden & Thonnes, 2000; Walsh et al., 2020), women are often categorized based on history of any sexual victimization, without regard to the number of victimizations experienced (e.g., “survivors” and “non-survivors”; Briere et al., 2020; Smith et al., 2003). Other researchers have categorized participants based on whether they have previously experienced multiple victimizations (“revictimized,” “single-victimized,” or “none”; e.g., Walsh et al., 2012). Similarly, when examining revictimization prospectively, studies often focus on the presence of any new victimization during a follow-up period, rather than the number of new victimizations that occurred during the study. The distinctions made thus far are useful, but could go further to examine more than two assaults among women who may experience more chronic or repeated forms of revictimization. Indeed, many survivors experience multiple new assaults beyond a single instance of revictimization. For example, Fisher et al. (2010) found that 5.9% of women experienced 65.4% of sexual assaults reported, highlighting that some women are disproportionately affected by revictimization. Notably, those most at risk for multiple new victimizations may disproportionately include women with marginalized identities (e.g., Black women, LGBTQ+ women), who are particularly likely to experience revictimization (Coulter et al., 2017; Palmer et al., 2022) and lack of safety due to discrimination (e.g., racism, transphobia) or prejudice (e.g., antibisexual prejudice, McConnell & Messman-Moore, 2019). One possible explanation for multiple victimizations across time is that risk could accrue with each new victimization, underscoring the need to comprehensively examine the number of (re)victimizations to clarify when risk for future assault is greatest.

One period of elevated risk for (re)victimization is emerging adulthood—ages 18 to 25 (Rinehart et al., 2014; Smith et al., 2018). Because this period is characterized by the exploration of intimate and sexual relationships, increased autonomy, and decreased parental monitoring (Arnett, 2000), emerging adult women may encounter more potential perpetrators than women at other ages. Indeed, 38% of women who are sexually assaulted experience their first assault between the ages of 18 and 24 (Smith et al., 2018)—a finding that has implications for revictimization during emerging adulthood, given that repeat victimization often occurs soon after an initial sexual assault (Daigle et al., 2008). Moreover, CSA survivors are more likely to endorse more severe ASA experiences in emerging adulthood compared to women without a history of CSA (Rinehart et al., 2014). Thus, emerging adulthood is a critical period for understanding risk and revictimization trajectories.

In sum, although revictimization patterns have been established across developmental periods (e.g., childhood to adulthood; Messman-Moore & Long, 2003; Relyea & Ullman, 2017) and cross-sectional research indicates that ASA can occur repeatedly (Daigle et al., 2008), it remains unclear how patterns of revictimization naturally shift as women enter adulthood. Clarifying the nature of revictimization trajectories is a critical step in the development of more targeted interventions. Yet, accumulation of sexual revictimization risk has not been prospectively examined in emerging adulthood. To address this gap, the current study examined prospective risk for revictimization among emerging adult women who completed up to nine assessments across a three-year period. Specifically, we sought to replicate and extend prior work (e.g., Daigle et al., 2008; Lau & Kristensen, 2010; Walsh et al., 2020) by testing two main hypotheses:

Hypothesis 1: (a) ASA survivors would be more likely than non-survivors to report subsequent sexual victimization within a three-year timeframe. (b) Individuals who experienced CSA by more perpetrators would also have a greater risk of sexual victimization in emerging adulthood. (c) The association between ASA status and further victimization would be greater for those who experienced CSA by more perpetrators.

Hypothesis 2: (a) Among those who reported any sexual assault in adulthood, the number of ASA reports would prospectively increase the risk of revictimization during the study. (b) Individuals with more CSA perpetrators would also have a greater risk of revictimization. (c) The association between ASA reports and revictimization during the study would be greater for those who identified more CSA perpetrators.

Material and Methods

Participants and Procedures

A total of 491 women aged 18 to 25 were recruited from the community in three Midwestern and Southern U.S. states (Lincoln and Omaha, Nebraska; Oxford, Ohio; Jackson, Mississippi) for a larger multi-site prospective study (e.g., Charak et al., 2018; Jaffe et al., 2019). Recruitment took place through community advertisements at each of the sites, as well as recruitment letters sent to randomly selected women who were identified through Survey Sampling International. The study was described as focusing on “women’s life experiences.” The larger study involved online surveys completed once every four months for three years, for a total of nine assessments (“waves”), in addition to laboratory tasks unrelated to the current study completed at Waves 1, 3, 5, 7, and 9. Following completion of the online surveys at each wave, participants were provided with contact information for local rape crisis centers and sliding-fee counseling and psychotherapy services, as well as national sexual victimization and rape crisis hotlines. All procedures were approved by the institutional review boards of the participating universities (University of Nebraska-Lincoln, Creighton University, Miami University, University of Mississippi Medical Center).

For the current analyses, 457 participants were considered based on their completion of at least two assessments (giving them an opportunity to report new experiences of victimization during the study). Ten participants were excluded due to incomplete or inconsistent sexual assault data; chi-square tests and t-tests revealed no significant demographic differences between participants with missing and complete data on age, ethnicity, or student status. The final sample therefore consisted of 447 participants. Among these participants, mean age at enrollment was 21.7 (SD = 2.2). Recruitment was based on gender identity as a woman; one participant (0.2%) identified as transgender. Regarding sexual identity, 85.1% of participants identified as straight/heterosexual, 8.6% as bisexual, 4.1% as gay/lesbian, and 2.3% as questioning. Regarding race/ethnicity, 60.6% were European American, 35.8% African American, 5.6% Hispanic or Latina, 4.3% Asian, 3.4% American Indian, and 2.5% Other (multiple categories could be endorsed). Although women were recruited from the community at large, 62.6% were full- or part-time students.

Measures

Adulthood Sexual Assault

The Modified Sexual Experiences Survey (MSES; Messman-Moore et al., 2010), an expanded version of the Sexual Experiences Survey (Koss et al., 1987), was administered at each wave to assess unwanted sexual experiences. The presence of ASA was indicated by endorsement of behaviorally specific items assessing attempted or completed oral-genital contact, sexual intercourse, or other sexual activity involving penetration. At Wave 1, ASA since age 18 was assessed. Subsequent waves assessed ASA since the previous assessment.

Childhood Sexual Abuse

The Computer Assisted Maltreatment Inventory (CAMI; DiLillo et al., 2010) was administered at Wave 1. Behaviorally specific questions were used to assess the presence or absence of CSA, defined as having a sexual experience before age 18 that was: (a) against their will, (b) with a family member, or (c) with someone who was five or more years older. Those who reported CSA were asked to identify their relationship with up to five perpetrators. The number of perpetrators identified (coded as zero for participants with no CSA) was recorded. Prior research has indicated this subscale has good test-retest reliability, internal consistency, and criterion-related validity (DiLillo et al., 2010).

Data Analysis

Hypothesis 1

To determine whether survivor status at Wave 1 (i.e., presence or absence of ASA [H1a], number of CSA perpetrators [H1b], and their interaction [H1c]) predicted the presence or absence of further ASA victimization during the three-year study (Waves 2–9), a logistic regression was conducted in R version 4.1.3 (R Core Team, 2022). In recognition that sexual victimization rates decrease with age in adulthood (Ogle et al., 2013), participant age at enrollment was included as a covariate. To account for individual differences in the time covered by the study period, the number of months between the first and final assessment completed by each participant was included as a covariate. Although we also considered controlling for number of opportunities to make a report of ASA during the study (i.e., number of study assessments completed), this variable was redundant with the number of months between the first and final assessments (r = .88, p < .001) and therefore excluded from the model. No other correlations between predictors exceeded .70 (see Table 1), reducing concerns about multicollinearity (Harris, 2021).

Table 1.

Descriptive Statistics and Correlations (N = 447)

Range Mean (SD) 1. 2. 3.
1. Number of ASA reports per participant 0 – 8 1.11 (1.34)
2. Number of CSA perpetrators 0 – 5 0.74 (1.16) .24**
3. Age at study enrollment 18 – 25 21.73 (2.22) .08 .07
4. Months enrolled in study 3.42 – 35.89 28.22 (8.30) −.01 −.09 −.02
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Note:

*

p < .05

**

p < .01

ASA = adulthood sexual assault; CSA = childhood sexual abuse

Hypothesis 2

To determine whether each successive ASA reported over time was associated with increased risk of further victimization during the study period, we focused on those who reported at least one ASA (n = 259). Three of these participants were excluded because they did not endorse their first ASA until their last wave in the study and thus had no additional opportunity to report subsequent victimization. Analyses to examine Hypothesis 2 thus included 256 women who reported at least one ASA and completed at least one additional assessment following that report.

A multilevel model with a random intercept and a logit link was tested using the lme4 (Bates, Maechler, et al., 2015) and lmerTest (Kuznetsova et al., 2017) packages in R. The outcome was the likelihood of ASA being reported at any subsequent wave in the study (1 = at least one more ASA, 0 = no further ASA). An unconditional, intercept-only model was first examined to compute the intraclass correlation coefficient via the performance package (Lüdecke et al., 2021), which indicated 4.3% of the variance in the subsequent victimization outcome was attributable to between-person differences.

Regarding predictors, the cumulative number of ASA reports was computed at each successive victimization for each participant. That is, the number of waves at which ASA had been reported thus far was included as a predictor of ASA reported at a subsequent wave (H2a). To reduce the potential bias in estimates that may result from including repeated assessments with the same ASA and CSA values, we limited the dataset to observations (rows) in which a new ASA was reported. Based on the expectation that individuals who reported more CSA perpetrators would report more cumulative ASA reports during the study (H2b), as well as the hypothesis that the effect of ASA reports would be greater for those who identified more CSA perpetrators (H2c), we included the number of CSA perpetrators as a predictor and moderator. Similar to analyses for Hypothesis 1, current age was included as a covariate. To control for differences in the remaining opportunities to report victimization during the study, the number of months remaining in the study (i.e., months between the current and last assessment completed by each participant) was also included as a time-varying covariate. Correlations between model predictors ranged from −.49 to .22, reducing concerns about multicollinearity. However, this model resulted in a singular fit (Bates, Kliegl, et al., 2015); model overfitting appeared to occur because there were few participants who had a high number of both ASA reports and CSA perpetrators. Thus, ASA reports and CSA perpetrators were each capped at a maximum of 3 to achieve a model without a singular fit.

Results

Descriptives

Of the 447 women in the current study, 259 (57.9%) reported sexual assault in adulthood on at least one assessment. Of these survivors, 129 (49.8%) reported ASA once, 70 (27.0%) reported ASA twice, 34 (13.1%) reported ASA three times, 14 (5.4%) reported ASA four times, 7 (2.7%) reported ASA five times, and 5 (1.9%) reported ASA six or more times. Regarding sexual assault in childhood, 184 (41.2%) reported a history of CSA. Of CSA survivors, 106 (57.6%) identified one perpetrator; 36 (19.6%) identified two perpetrators, 27 (14.7%) identified three perpetrators, 3 (1.6%) identified four perpetrators, and 12 (6.5%) identified five or more perpetrators. A total of 312 (69.8%) participants reported either CSA or ASA. See Table 1 for additional descriptive data.

Prospective Comparison of ASA Survivors and Non-Survivors

Consistent with Hypothesis 1a, there was a conditional effect such that those who reported past ASA at Wave 1 were more likely than non-survivors to report a new experience of sexual victimization during the study (OR = 7.66, 95% CI: 4.35 – 13.93), holding CSA perpetrators at 0. Similarly, among those without a history of ASA, the risk for sexual victimization during the study was greater for those who identified more CSA perpetrators (OR = 1.69, 95% CI: 1.26 – 2.30), thus supporting Hypothesis 1b. Contrary to Hypothesis 1c, the interaction was not significant (OR = 0.79, 95% CI: 0.54 – 1.14), such that the association between ASA status and new victimization did not depend on the number of CSA perpetrators (Figure 1). Older age at enrollment was associated with lower likelihood of sexual victimization during the study (OR = 0.86, 95% CI: 0.77 – 0.96). The number of months between the first and final assessment (representing the window during which new sexual victimization was examined) was not a significant covariate (OR = 1.01, 95% CI: 0.99 – 1.04). Tjur’s (2009) R2 indicated 18.5% of the variance in sexual victimization during the study was accounted for by model predictors.

Figure 1.

Figure 1

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Probability for sexual victimization during the three-year study based on Wave 1 ASA status.

Note. ASA = adulthood sexual assault; CSA = childhood sexual abuse.

Longitudinal Assessment of ASA Survivors

Consistent with Hypothesis 2a, as the number of ASA reports increased during the study, so did the risk of revictimization for those with no CSA (OR = 1.59, 95% CI: 1.01 – 2.51). Similarly, consistent with Hypothesis 2b, among survivors who reported ASA once, identifying more CSA perpetrators was associated with a greater likelihood of revictimization during the study (OR = 1.47, 95% CI: 1.15 – 1.87). Contrary to Hypothesis 2c, the association between ASA reports and subsequent revictimization during the study was less positive for those who identified more CSA perpetrators (OR = 0.77, 95% CI: 0.62 – 0.96; Figure 2). This cross-level interaction of fixed effects indicates that the effect of ASA reports varies systematically as a function of CSA perpetrators (Hoffman, 2015). That is, the likelihood of revictimization following each successive ASA victimization was greater to the extent that there were fewer past CSA perpetrators. Time-related covariates were not significant, such that current age (OR = 0.96, 95% CI: 0.87 – 1.05) and months remaining in the study (OR = 1.02, 95% CI: 1.00 – 1.04) did not predict revictimization during the study. Nakagawa and colleagues’ (2017) conditional R2 indicated that 5.3% of the variance in revictimization during the study was accounted for by the fixed effects and random intercept in the model.

Figure 2.

Figure 2

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Probability of sexual victimization during the study among women with any ASA.

Note. ASA = adulthood sexual assault; CSA = childhood sexual abuse.

Discussion

This study examined prospective risk for revictimization over a three-year period among emerging adult women. Findings expand our understanding of revictimization patterns and suggest that although risk for victimization is higher among survivors compared to women who have not experienced sexual victimization previously, there may be an upper limit to the accumulation of risk over time with each new victimization. As detailed below, several findings were unexpected in light of past research and suggest the need to explore factors that protect women against revictimization.

First, we examined whether ASA was associated with increased risk for a new experience of sexual victimization. Consistent with expectations and prior literature (Walker et al., 2019), women who reported a history of ASA at the first assessment were more likely than those without prior ASA to report sexual victimization during the three-year period. Moreover, among ASA survivors, each successive ASA experience was associated with increased risk of revictimization during the study. Together, findings underscore that some women experience an escalating pattern of sexual victimization during young adulthood, but there is variability in revictimization risk. One possibility is that women who reported successive ASA experiences are in high-risk environments with greater exposure to perpetrators, such as women who live with a sexually violent partner (Mele, 2009; Tjaden & Thoennes, 2000).

A similar pattern was found when examining CSA histories, such that a greater number of CSA perpetrators was associated with a greater likelihood of reporting sexual victimization at any time in the study in both models. Findings align with prior literature supporting greater severity of CSA experiences in general as a risk factor for revictimization (Loeb et al., 2011; Werner et al., 2016), but go further to highlight the relevance of distinct CSA perpetrators in the accumulation of revictimization risk. One possible explanation for this finding is that women who have encountered more CSA perpetrators may have more difficulty trusting and identifying healthy relationship partners after experiencing betrayal from multiple individuals, consistent with well-established theories regarding the traumatic impact of CSA (Finkelhor & Browne, 1985; Noll, 2021). Alternatively, women who have experienced CSA by multiple perpetrators may feel greater shame in response to stigmatizing societal messages (Finkelhor & Browne, 1985), which, in turn, could lead to maladaptive efforts to cope with negative affect (e.g., drinking) and thus, greater exposure to environments that are more likely to have potential ASA perpetrators.

Although hypotheses regarding the unique effects of CSA and ASA on subsequent victimization were supported, findings regarding the interaction of CSA and ASA were unexpected. Specifically, we anticipated that the effect of ASA reports on further victimization would be greater for those who identified more CSA perpetrators. Yet, in our first model, the association between ASA status and sexual victimization during the subsequent three-year period did not differ based on the number of CSA perpetrators. Although this finding is unexpected, other studies have not found an interactive effect of CSA and ASA on trauma-related distress (Briere et al., 2020). Thus, CSA experiences might independently increase risk for negative outcomes such as revictimization and psychological distress, rather than exacerbating the impact of ASA. Further support for this suggestion comes from our second model examining all ASA reports among survivors across the study period, which revealed that the association between cumulative ASA experiences and risk for subsequent victimization was less positive for those who identified more CSA perpetrators. Although replication is needed, similar odds ratios (0.79 and 0.77, respectively) were detected across both models, lending confidence to the pattern of buffered risk over time.

Together, these findings suggest that, for individuals with fewer sexual assault experiences in one developmental period (childhood or adulthood), each new victimization in the other developmental period was associated with increased, cumulative risk. However, these effects were not synergistic. For those with more sexual assault experiences in one developmental period, risk for revictimization remained elevated but did not further increase with each additional victimization in the other developmental period. If the linear trends examined here hold past the three assaults examined in the second model, it is possible that revictimization risk in adulthood could eventually decline with each new victimization. However, because few women in this study reported four or more ASAs, future research should test for diminishing cumulative revictimization risk in larger samples.

We also examined age- and time-related covariates to isolate unique effects of CSA and ASA histories on prospective risk for revictimization. Interestingly, the time-related covariate was not a significant predictor in either model, indicating that the likelihood of reporting a new ASA was not driven by the duration of study participation. On the other hand, age at enrollment was a significant covariate in our first model, indicating that likelihood of victimization during the three-year period was lower for women who were older at enrollment. This pattern mirrors prior work indicating that risk for victimization decreases as age increases (Ogle et al., 2013), with most sexual assaults occurring before age 25 (CDC, 2011; Department of Justice, 1997). However, among ASA survivors in the second model, age was not associated with risk for revictimization. Taken together, findings suggest that age may be a more salient predictor of a first sexual victimization, whereas other factors related to prior victimization—perhaps including exposure to high-risk contexts—may be more important predictors of revictimization.

Limitations and Future Directions

Findings should be interpreted in the context of study limitations. First, our sample of young adult women was predominantly cisgender and heterosexual, and 96.4% identified as either European American or African American, which may limit generalizability. Future research should examine revictimization among older women, as well as transgender and gender expansive individuals and cisgender women with varied intersectional identities (e.g., those with minoritized sexual, racial, or ethnic identities), who may be at even greater risk of revictimization due to marginalization (e.g., Coulter et al., 2017). Although the MSES includes multiple behaviorally specific screening items assessing various assaultive experiences, these behaviors can occur within a single event (a limitation shared by other widely used and validated assessments of sexual assault; Koss et al., 2007). Therefore, the number of distinct ASA perpetrators and events was unknowable at each wave. Multiple ASA perpetrators or events could have been represented by a single ASA report, or multiple ASA reports could have occurred by the same perpetrator. In addition, although we assessed CSA and ASA with appropriate measures for each developmental period, these measures operationalized assault experiences differently (i.e., CSA perpetrators versus number of assessments in which recent ASA was reported), precluding these measures from being combined into one overall number of sexual assaults. Future research examining lifetime trajectories of sexual revictimization would benefit from assessing number of perpetrators and assaultive events for both CSA and ASA to establish one count across the lifespan. Such future research could also examine if there is a point at which risk for subsequent revictimization diminishes, and, if so, the factors associated with interrupting the cycle of accrued risk. Finally, our study focused on survivor-level experiences. Therefore, we do not have data on contextual risk factors that could be examined as mechanisms of revictimization. In future research, increased attention should be devoted to identifying high-risk environments where there is exposure to many or repeat perpetrators, as well as mechanisms underlying revictimization that could be leveraged to prevent perpetration, such as attitudes toward consent and use of aggressive or coercive rape tactics (Bergen & Bukovec, 2006; Jozkowski & Peterson, 2013).

Implications for Policy and/or Practice

Findings suggest that women who have experienced CSA by multiple perpetrators or multiple experiences of ASA are at elevated risk for revictimization in early adulthood and may benefit from targeted risk prevention strategies. More easily accessible trauma-informed interventions are needed to help mitigate the negative consequences survivors experience following sexual revictimization, including risk for additional assaults and PTSD (Messman-Moore & Long, 2003). Prevention and intervention efforts should also focus on identifying and changing high-risk contexts that contribute to revictimization. Of note, findings suggest revictimization patterns across multiple developmental periods do not continue indefinitely. Likewise, risk of victimization appeared to reduce as women aged out of emerging adulthood. These findings signal a potential natural reduction of risk over time in some survivors. Future research should investigate protective factors that might contribute to this natural reduction of risk.

Conclusions

Building on past revictimization research, the current prospective study revealed that CSA and ASA both uniquely predicted subsequent risk for sexual victimization in women during a three-year period beginning in emerging adulthood. Risk for repeated victimization in adulthood was cumulative based on past CSA and ASA experiences. Unexpectedly, CSA and ASA did not have a synergistic effect on revictimization risk. Although this sample of young adult women was recruited from the community without regard for sexual assault history, rates of assault were high, affecting nearly 70% of the sample. Despite this high risk, findings suggest revictimization risk did not accrue indefinitely, highlighting the need to understand factors that protect against future risk in survivors.

Author Note

This research was supported by a National Institute of Child Health and Human Development grant (R01HD062226, PI: DiLillo). Manuscript preparation was funded by grants from the National Institute of Alcohol Abuse and Alcoholism: K08AA028546 (PI: Jaffe), F31AA028996 (PI: Brockdorf, Sponsor: DiLillo). The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institute of Child Health and Human Development or the National Institute on Alcohol Abuse and Alcoholism.

Abbreviations:

CSA

childhood sexual abuse

ASA

adulthood sexual assault

Biographies

Anna E. Jaffe, PhD, is an Assistant Professor in the Department of Psychology at the University of Nebraska– Lincoln. Her research focuses on interventions for sexual assault, PTSD, and substance use, with an emphasis on recovery from alcohol-involved sexual assault.

Alexandra N. Brockdorf, MA, is a doctoral student in the Department of Psychology at the University of Nebraska–Lincoln. Her research examines the mental and physical health consequences of sexual violence.

Terri L. Messman, PhD, is a Professor of Psychology and University Distinguished Scholar at Miami University. Her research examines child maltreatment, interpersonal violence, emotion dysregulation, PTSD/Complex PTSD, depression, and shame, and the relation of mindfulness and self-compassion to trauma recovery.

Kim L. Gratz, PhD, is professor and chair of the Department of Psychology at the University of Toledo. Her laboratory and treatment outcome research focuses on the role of emotion dysregulation in borderline personality disorder, self-injury, and risky behaviors.

David DiLillo, PhD, is the chair and Willa Cather Professor in the Department of Psychology at the University of Nebraska–Lincoln. As a researcher, he is interested in understanding interpersonal violence, especially sexual assault, and intimate partner violence.

Footnotes

Drs. Jaffe and DiLillo had full access to all the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis.

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