Lifetime Revictimization: Evidence From the Wisconsin Longitudinal Study

Abstract

Despite the documented increasing prevalence of elder abuse victimization and its devastating health effects, a life-course view of the victimization experiences of older adults has rarely been adopted in the elder abuse literature. The current study investigated lifetime links between victimization experiences by examining the indirect effect of adverse childhood experiences (ACE) on elder abuse victimization via intimate partner violence (IPV) victimization in middle adulthood, and whether this indirect association would differ by gender. Using data from the Wisconsin Longitudinal Study, we analyzed the previous and current victimization experiences of a total of 5,391 older adults in their early 70s and estimated mediational and moderated mediation models. The key results indicated that a higher ACE score was associated with exposure to IPV victimization in middle adulthood, which was in turn associated with exposure to elder abuse victimization. This indirect association was stronger for women than for men. Regarding specific types of childhood victimization, parental physical abuse, sexual abuse, and witnessing domestic violence significantly predicted elder abuse victimization via IPV victimization. Our results support the phenomenon of lifetime victimization, whereby an individual experiences reoccurring forms of victimization across the life course from childhood to late adulthood. Findings highlight the compelling need for the assessment of cumulative victimization experiences and their impact on elder abuse victims. A life-course-based, trauma-informed approach would greatly enhance prevention and intervention services for elder abuse.

Keywords

adverse childhood experiences elder abuse intimate partner violence life course moderated mediation

Action on Elder Abuse in 1995 defines elder abuse as a “single or repeated act, or lack of appropriate action, occurring within a relationship where there is an expectation of trust which causes harm or distress to an older person” (Kaindl, 2008). This definition encompasses all those who are in a position of trust in relation to older people although the current study focuses on older adults living in community settings. Each year, approximately 1 in 10 community-residing older adults in the United States experience a form of elder abuse (Rosay & Mulford, 2017). Any exposure to elder abuse can have a devastating impact on the health and well-being of older adults (National Research Council, 2003). A recent study found significant longitudinal associations that older adults who experienced elder abuse reported higher rates of depression, anxiety, posttraumatic stress symptoms, and poor self-reported health compared to non-abused older adults (Acierno et al., 2017).

Several studies have examined and identified factors contributing to elder abuse victimization, such as gender, marital status, and functional impairments (Pillemer et al., 2016). In such research efforts, a relatively small number of studies have adopted the life-course assessment of older adults’ victimization experiences. Particularly, there has been little recognition in the empirical literature that some older adults are not only victims of elder abuse but also survivors of repeated violence across their life course. The concept of repeated experiences of violence has been examined in the existing literature (Tapia, 2014; Widom et al., 2008); however, these studies focused on samples of children and/or people in early or middle adulthood. Based on our review of the literature, no studies have yet explored the experiences of persistent victimization across childhood, adulthood, and older adulthood using a sample of older adults in the United States.

To address this gap in the literature, the current study examined the effects of adverse childhood experiences (ACE) on subsequent victimization experiences in mid-to-late adulthood. We used longitudinal data from the Wisconsin Longitudinal Study (WLS) and analyzed self-reports of 5,391 older respondents, all of whom were in their early 70s. The investigation of the phenomenon of lifetime revictimization will contribute to new approaches and insights into violence prevention and management for older adults.

Lifetime Revictimization: Review of Prior Conceptual and Empirical Studies

Despite a lack of systematic investigation of the persistent victimization experiences that precede elder abuse, the concept of repeated violence exposure has been well-established in the literature. The phenomenon of revictimization was initially examined and established in the area of child sexual abuse (CSA). The key notion is that child victims of sexual abuse, especially women, face an increased risk of sexual violence as an adult, which has been empirically supported by numerous studies (Messman-Moore & Long, 2003; Papalia et al., 2017). For example, Arata (2002) showed that about one-third of child victims of sexual abuse later reported experiencing sexual violence as an adult, and the risk of adult sexual victimization was two to three times higher for women with a history of CSA than those without such history.

The concept of revictimization has been extended to include other forms of childhood victimization, such as physical and psychological abuse and neglect (Dietrich, 2007; Finkelhor et al., 2007b). Finkelhor et al. (2007a, 2009) developed the concept of poly-victimization and identified a group of poly-victims, children who co-experience a large number of different types of victimization, such as physical abuse, peer bullying, and witnessing domestic violence. Based on analyses of national surveys, these scholars found that 22% of the children aged 2 to 17 years reported four or more different kinds of victimization in a single year and 10% reported seven or more (Finkelhor et al., 2009). Other relevant studies provided further support that poly-victimization is prevalent, involves a correlated set of risk factors, and likely leads to extremely high levels of psychological distress and symptoms (Codina et al., 2022; Finkelhor et al., 2007a, 2011).

Lifetime Revictimization: Childhood Until Adulthood

Much of Finkelhor et al’s work (2005, 2007a, 2007b) has utilized a short-term period for the studies (i.e., past year assessment) examining poly-victimization among children. Widom et al. (2008) examined the revictimization experience across a longer time period by linking childhood abuse histories with adulthood victimization experiences. Their study analyzed 496 adults with a history of childhood physical/sexual abuse and neglect and 396 matched counterparts, whose ages ranged from 30 to 47 years (M = 39.5, SD = 3.51). The key results showed that adults who were abused and neglected as children showed increased risks of interpersonal violence victimization, such as physical abuse or sexual assault, compared to matched controls (Widom et al., 2008). The authors also found a gender difference in the specific types of adult victimization affected by childhood abuse/neglect. For example, women with histories of child abuse and neglect were more likely to experience attempted forced sex, private parts touched, or being stalked later as an adult, compared to female counterparts without abuse histories. Interestingly, there was not a group difference for men.

In terms of the link between childhood and adulthood victimization, more research is available in terms of the effects of childhood victimization on intimate partner violence (IPV) (Hébert et al., 2021; Scoglio et al., 2021; Zamir et al., 2018). It is well-documented that women with a history of CSA have an increased risk of experiencing physical, psychological, and sexual victimization perpetrated by their intimate partners (Daigneault et al., 2009; Ihongbe & Masho, 2017). This association was also found among adults, especially women, who experienced non-sexual victimization. For example, using a sample of African American women, Lacey et al. (2021) found that women who experienced severe physical IPV reported higher rates of childhood abuse and witnessing domestic violence than non-abused women, and such childhood maltreatment histories significantly predicted severe physical IPV victimization in adulthood.

Lifetime Victimization Leading to Elder Abuse Victimization

In the elder abuse literature, a prior victimization experience has been identified as one of the key predictors of elder abuse victimization (Jackson & Hafemeister, 2011; Storey, 2020; Wiklund et al., 2022), although the specificity of the violence experience, such as intensity, victim-perpetrator relationship, and, more importantly, the timing of the violence, has not been considered. In one of the first studies that examined links between childhood abuse and risk of elder abuse, McDonald and Thomas (2013) conducted a cross-sectional, pilot study and found that a history of childhood abuse heightened the risk of being abused as an older adult. The work of Kong and Easton (2019) further supported the association using a population-based dataset of older adults, WLS. This study examined which specific types of child maltreatment (namely emotional and sexual abuse) increased the risks of elder abuse victimization. In a follow-up study using a longitudinal design, Easton and Kong (2020) demonstrated that a higher cumulative score of ACE was associated with greater risks for elder abuse victimization. The contribution of their work was to explore potential mechanisms through which child adversities were linked to elder abuse; results showed that the long-term association was explained by worsened physical health and heightened depressive symptoms in midlife.

A paucity of research exists regarding victimization experiences linking early/middle adulthood with later adulthood. A handful of studies on older female IPV victims indicated that their victimization tends to begin earlier in adulthood and continues into older age (Leisey et al., 2009). With advancing age, partners’ physical violence may abate, but psychological abuse may continue as the means to maintain power and control, such as denying medical care or isolating the victim from family and friends (Brossoie et al., 2012; Ramsey-Klawsnik, 2017). Other scholars in the field also noted that women are more likely to experience family violence throughout their lives than men, which may increase their risk for abuse in later life (Finfgeld-Connett, 2014; Miszkurka et al., 2016).

Current Study

The review of the prior studies and conceptual frameworks suggests a potential persistent experience of victimization across the life course, including childhood, adulthood, and late adulthood. The pattern of lifetime revictimization may be more apparent among women through IPV victimization. Despite the suggested associations, the phenomenon of lifetime revictimization has only been studied among relatively young adults; there is a dearth of research based on samples of older adults (Codina et al., 2022; Simmons & Swahnberg, 2021; Wiklund et al., 2022).

To address this gap in the literature, the current study examined lifetime links between victimization experiences that span across childhood, adulthood, and older adulthood, which may differ by gender. This novel, thorough empirical investigation of lifetime revictimization, has several strengths. First, the life-course approach allows for a broader, more holistic understanding of older victims, avoiding a narrow focus on contemporary life circumstances. Second, the current study relied on population-based, longitudinal data obtained by the WLS and the analysis of 5,391 older adults’ retrospective and prospective reports of their entire adulthood. Lastly, a gender comparison of lifetime revictimization is also a relevant, crucial approach. Prior studies have noted that older women are often marginalized due to the accumulated disadvantages experienced throughout their life course (Carmel, 2019; Walsh et al., 2017). Likewise, older women being the subject of violence can be the result of prior victimization experiences (Finfgeld-Connett, 2014; Miszkurka et al., 2016). The current study examined the following specific hypotheses:

ACE and IPV victimization would both be directly associated with greater elder abuse victimization.

ACE would be indirectly associated with greater elder abuse victimization via exposure to IPV.

The mediational association involving ACE, IPV victimization, and elder abuse victimization would be stronger for women than men.

Methods

Study Sample

Secondary data analyses were conducted using data from the WLS. The WLS is a long-term population-based study of a random sample of 10,317 men and women who graduated from Wisconsin high schools in 1957 and 5,823 of their siblings. The original purpose of the WLS was to assess the educational and career plans of each graduate, including social background, youth aspirations, labor market experiences, and social participation (Hauser, 2009). Data were collected in subsequent waves (i.e., 1964, 1975, 1993–1994, 2004–2005, 2010–2011) on an expanding range of topics through mail and telephone interviews. High retention rates characterize the WLS; across all waves, the overall response rate for surviving graduates was 73.8% for the telephone survey. The current study utilized the most recently available WLS data when respondents were in their early 70s. The study sample included 5,391 respondents who participated in the mail questionnaire of the 2010–2011 survey.

Measures

Elder Abuse Victimization

Elder abuse victimization was assessed in the 2010 to 2011 survey by five items that correspond with key items from the Abusive Behavior Inventory (Shepard & Campbell, 1992): “In the past 12 months, (a) have you felt there is someone who is too controlling over your daily decisions and life?; (b) has anyone insulted you or put you down?; (c) has anyone taken your money or belongings without your permission or prevented you from getting them even when you ask?; (d) has anyone hit, kicked, slapped, or thrown things at you?; (e) has anyone intentionally prevented you from having things you need, such as medication, food, money, or personal care?” Response choices for each item were binary: yes (1) and no (0). Respondents who responded yes to any of these five questions were coded as being victimized (1; no = 0).

Adverse Childhood Experiences

ACE was measured with items that corresponded with major categories within the original ACE questionnaire, most of which were asked in the 2004 to 2005 survey. The WLS contained items for nine ACE categories (Felitti et al., 1998): neglect, father’s verbal abuse, mother’s verbal abuse, father’s physical abuse, mother’s physical abuse, sexual victimization, parental divorce, witnessing domestic violence, and living with a household member with a substance problem.

Childhood neglect was measured by an item: “Up until you were 18, how often did you know that there was someone to take care of you and protect you?” Response choices were based on a 5-point Likert scale: never (1), rarely (2), sometimes (3), often (4), and very often (5). Participants who reported never, rarely, and sometimes were coded as being neglected as children (1, 0 = not neglected). Parental abuse was assessed using adapted items from the Conflict Tactics Scale (Straus et al., 1980). Childhood verbal abuse was measured by two items: “Up until you were 18, to what extent did (a) your mother, (b) father insult or swear at you?” Response choices were based on a 4-point Likert scale: not at all (1), a little (2), some (3), and a lot (4).

Childhood physical abuse was measured by two items: “Up until you were 18, to what extent did (a) your mother, (b) father treat you in a way that you would now consider physical abuse?” Response choices were based on a 4-point Likert scale: not at all (1), a little (2), some (3), and a lot (4). Consistent with prior research (Irving & Ferraro, 2006), respondents who reported some or a lot of the verbal abuse items were coded as being verbally abused as children. To assess physical abuse, those who reported a little, some, or a lot were coded as being physically abused as children (Goodwin et al., 2003).

To assess for CSA, we relied on four items from the WLS: “Up-until 18, to what extent (a) did your father have oral, anal, or vaginal sex with you against your wishes?; (b) did any other person have oral, anal, or vaginal sex with you against your wishes?; (c) did your father treat you in way that you consider sex abuse?; (d) did any other person treat you in way that you consider sex abuse?” Response choices were based on a 4-point Likert scale: not at all (1), a little (2), some (3), and a lot (4). Respondents who answered a little, some, or a lot for any item were coded as having been sexually abused during childhood (1; no = 0). Another ACE was measured with three questions that asked about having witnessed domestic violence), having lived with a problem drinker or alcoholic, and not having lived with both parents. The nine binary variables were then summed to produce a total score (range = 0–9). The Cronbach’s alpha coefficient for this scale was .66.

IPV Victimization

In the 2004 to 2005 data collection, the following item was asked to measure the respondent’s exposure to IPV victimization: “Has your spouse, or romantic partner, ever treated you in a way that some would think of as physical abuse?” Because the item was asked in the 2004 to 2005 survey when the respondents were in their mid-60s (range: 64–67 years), this item assessed the victimization experience throughout adulthood until the age of 65 years, on average. The item was assessed by a binary response choice: yes (1) and no (0).

Covariates

Based on a review of relevant literature, we included several covariates in the analyses, including gender (male vs. female), age, current marital status (married vs. non-married), educational attainment (years), father’s educational attainment (years) as a proxy for childhood socioeconomic status, depressive symptoms (2004–2005), self-rated health (2004–2005), and social support. Depressive symptoms were measured by the 20-item Center for Epidemiologic Studies Depression Scale (Radloff, 1977). Each item used an eight-point scale (0−7) to indicate the number of days in the past week that respondents experienced specific depression symptoms; the total score was calculated by averaging the 20 items. Self-rated health has been consistently linked to a range of objective health outcomes (e.g., Benyamini, 2011). A single item was asked (i.e., “How would you rate your health at the present time?”), and responses were rated by a five-point Likert scale: poor (1), fair (2), good (3), very good (4), and excellent (5). To be informed by the work of Easton and Kong (2020), we controlled for midlife mental and physical health, which were associated with elder abuse victimization. Thus, we used the measures of depressive symptoms and self-rated health from the prior data collection, the 2004 to 2005 survey. Social support was measured by the following two items: “Is there a person in your family, including a spouse, with whom you can really share your very private feelings and concerns?”; friend with whom you can really share your very private feelings and concerns?” Respondents who responded yes to either question were coded as having social support (1; no = 0).

Analytic Strategy

We estimated the mediational and moderated mediation models using Mplus software. To address the first hypothesis, we examined the main effects of ACE and IPV victimization on elder abuse victimization, as well as the interaction effect of ACE and IPV victimization. To address the second hypothesis, we estimated the mediational model in which ACE is the key independent variable, IPV victimization is the mediator, and elder abuse victimization is the outcome variable. A set of covariates were regressed on both IPV and elder abuse victimization. For the third hypothesis, we estimated the moderated mediational model by including gender as the moderator once identifying a significant indirect effect. We first included the three interactions predicting ACE * gender on IPV victimization, ACE * gender on elder abuse victimization, and IPV victimization * gender on elder abuse victimization (Figure 1). We then only retained statistically significant interaction terms and tested the conditional indirect effects in the final model. We used the product of coefficients strategy to gauge the extent and significance of indirect effects (Preacher et al., 2007). To address the missingness, the full information maximum likelihood approach was used. IPV victimization showed the most missingness (10.29%), and 80.06% of cases provided complete cases without any missingness.

Figure 1.

Hypothesized model: Moderated mediation by gender.

Results

Table 1 presents the descriptive statistics of the study sample. Slightly less than half of the respondents were men (n = 2,478, 45.97%). Respondents’ average age was 72 years, and more than 70% were married (n = 3,927, 72.84%). More than 80% reported that they had family members or friends who they could share very private feelings and concerns with. On average, respondents reported 1.04 ACE. About 7% reported IPV victimization, and 18.40% reported elder abuse victimization. Table 2 illustrates the gender difference in the descriptive characteristics of the study sample. In terms of the direct and interaction effects of ACE and IPV victimization on elder abuse victimization, both ACE and IPV victimization significantly predicted elder abuse victimization, and the interaction term between ACE and IPV victimization was not statistically significant (table not shown).

Table 1.

Descriptive Statistics of the Key Variables (N = 5,391).

Variables	N or mean (SD)	% or Observed Min./Max.
Male	2,478	45.97%
Age	72.14 (0.50)	71/74
Currently married	3,927	72.84%
Years of education	13.80 (2.37)	5/20
Father’s education	9.80 (3.44)	0/25
Depressive symptoms (2004–2005)	0.67 (0.67)	0/5.47
Self-rated health (2004–2005)	3.83 (0.92)	1/5
Social support	4,768	88.44%
ACE	1.04 (1.47)	0/9
Neglect	573	10.63%
Father’s verbal abuse	1,212	22.48%
Mother’s verbal abuse	721	13.37%
Father’s physical abuse	594	11.02%
Mother’s physical abuse	380	7.05%
Sexual abuse	292	5.42%
Witnessing domestic violence	377	6.99%
Parental divorce	515	9.55%
Parental substance use	959	17.79%
IPV victimization	366	6.79%
Elder abuse victimization	992	18.40%

Note. ACE = adverse childhood experiences; IPV = intimate partner violence.

Table 2.

Gender Difference in Key Variables (N = 5,391).

Variables	Men (n = 2,478)	Women (n = 2,913)	Bivariate tests
Age	72.20 (0.53)	72.08 (0.47)	p < .001
Currently married	0.82 (0.38)	0.65 (0.48)	p < .001
Years of education	14.19 (2.59)	13.46 (2.11)	p < .001
Father’s education	9.85 (3.48)	9.76 (3.40)	p = ns
Depressive symptoms (2004–2005)	0.62 (0.64)	0.72 (0.69)	p < .001
Self-rated health (2004–2005)	3.83 (0.92)	3.84 (0.93)	p = ns
Social support	0.90 (0.29)	0.95 (0.21)	p < .001
ACE	1.02 (1.42)	1.07 (1.52)	p = ns
IPV victimization	0.03 (0.18)	0.11 (0.31)	p < .001
Elder abuse victimization	0.16 (0.37)	0.21 (0.41)	p < .001

Note. Mean (standard deviation) is reported.

ACE = adverse childhood experiences; IPV = intimate partner violence.

Table 3 illustrates the summary results of the mediational analysis. First, ACE was positively associated with IPV victimization (b = 0.02, p < .001) and elder abuse victimization (b = 0.09, p < .001). IPV victimization was significantly associated with elder abuse victimization (b = 0.49, p < .001). The test of indirect effect was significant: ACE was associated with IPV victimization, which was in turn associated with elder abuse victimization (b = 0.01, p < .001). According to the unstandardized indirect effect coefficient, every additional ACE was associated with a 0.01 unit increase in elder abuse victimization via IPV victimization. Based on the standardized indirect effect coefficient, one standardized unit increase in ACE was associated with a 0.015 standardized unit increase in elder abuse victimization. Considering that the standard deviation of elder abuse victimization is 0.39, the effect size of the mediation is very small. We note, though, that multiple paths are simultaneously contributing to the risk of elder abuse victimization.

Table 3.

ACE Predicting Elder Abuse Victimization Via IPV.

	IPV victimization	Elder abuse victimization
	b (SE)
Direct effects
ACE	0.02 (0.00)***	0.09 (0.01)***
IPV victimization		0.49 (0.07)***
Male	−0.06 (0.01)***	−0.20 (0.04)***
Age	−0.01 (0.01)	−0.07 (0.04)
Currently married	−0.09 (0.01)***	0.17 (0.05)***
Years of education	0.00 (0.00)	0.04 (0.01)***
Father’s years of education	0.00 (0.00)	0.01 (0.01)
Depressive symptoms	0.02 (0.01)***	0.22 (0.03)***
Self-rated health	−0.00 (0.00)	−0.05 (0.02)*
Social support	−0.01 (0.01)	−0.23 (0.07)**
Test of indirect effect	Unstandardized	Standardized
ACE → IPV victimization → Elder victimization	0.010 (0.002)***	0.015 (0.003)***

Note. Standard errors in parentheses. Estimates and standard errors shown as 0.00 indicate the values that are very close to zero. ACE = adverse childhood experiences; IPV = intimate partner violence.

p < .05. **p < .01. ***p < .001.

Once we identified the significant indirect path involving ACE, IPV victimization, and elder abuse, we estimated the moderated mediational analyses by gender. Table 4 presents the summary of the results. The interaction term between ACE and males on IPV victimization was statistically significant (b = −0.02, p < .001), indicating that the effect of ACE on IPV victimization was weaker for men than for women. The index of the moderated mediation was statistically significant (b = −0.004, p < .001), indicating that gender significantly moderated the indirect effect of ACE on elder abuse victimization via IPV victimization. To examine this pattern of moderated mediation, we conducted a simple slope analysis, and its results are illustrated in Figure 2. We found that for older women, the indirect effect of ACE on elder abuse victimization via IPV victimization was statistically significant (b = 0.005, p < .001). The conditional indirect effect was weaker for men than for women and only marginally significant (b = 0.001, p = .08).

Table 4.

ACE Predicting Elder Abuse Victimization Via IPV: Moderated Mediational Analyses.

	IPV victimization	Elder victimization
	b (SE)
Direct effects
ACE	0.03 (0.00)***	0.03 (0.00)***
IPV victimization		0.17 (0.02)***
Male	−0.06 (0.01)***	−0.05 (0.01)***
ACE * male	−0.02 (0.01)***
Age	−0.01 (0.01)	−0.02 (0.01)
Currently married	−0.09 (0.01)***	0.05 (0.01)***
Years of education	0.00 (0.00)	0.01 (0.00)***
Father’s years of education	0.00 (0.00)	0.00 (0.00)
Depressive symptoms	0.02 (0.01)***	0.07 (0.01)***
Self-rated health	−0.00 (0.00)	−0.01 (0.01)*
Social support	−0.00 (0.02)	−0.07 (0.02)**
Index of moderated mediation	b (SE)	p
ACE * male → IPV victimization → Elder victimization	−0.004 (0.00)	p < .001
Conditional indirect effect by gender
Male: ACE → IPV victimization → Elder victimization	0.001 (0.00)	p = 0.083
Female: ACE → IPV victimization → Elder victimization	0.005 (0.00)	p < .001

p < .05. **p < .01. ***p < .001.

Figure 2.

Moderated mediation: simple slopes by gender.

Post-Hoc Analyses

To examine the dynamics associated with different types of ACE, we tested a mediational analysis involving nine different types of ACEs, IPV victimization, and elder abuse victimization, after reviewing the bivariate correlation among key variables (Supplemental Table 1) and the variance inflation factor (VIF) values of the variables. The multicollinearity among the violence variables did not happen based on the assessment that we did not find high Pearson’s R values and all the VIF values of the variables were less than 2. In the mediational analysis, paternal physical abuse, maternal physical abuse, sexual abuse victimization, and witnessing domestic violence significantly predicted elder abuse victimization via IPV victimization (Supplemental Table 2). In the moderated mediational analyses using each of the four predictors (i.e., paternal physical abuse, maternal physical abuse, sexual abuse victimization, and witnessing domestic violence), we found statistically significant indexes for moderated mediation. There was a consistent pattern that the mediational association for women was statistically significant and stronger than that for men (table not shown). The mediational association for men was not statistically significant at the significance level of .05.

Discussion

The primary aim of this study was to examine lifetime links between victimization experiences that span childhood, adulthood, and older adulthood. The concept of lifetime revictimization has been studied among relatively younger adults but has not been utilized to examine traumatic experiences in later life, such as elder abuse. In this study, a higher cumulative score of ACE was hypothesized to be associated with exposure to elder abuse via IPV victimization, and this mediational association was hypothesized to differ by gender.

We found that a higher cumulative score of ACE and IPV victimization independently predicted exposure to elder abuse, although the interaction term of the two predictors was not statistically significant. Rather, we found a significant indirect effect that a higher ACE score was associated with IPV victimization, which was, in turn, associated with exposure to elder abuse. These results support the findings of previous studies that a prior victimization experience is a predictor of elder abuse (Jackson & Hafemeister, 2011; McDonald & Thomas, 2013; Storey, 2020). Our addition is that repeated victimization may occur across the entire life course, and the pattern of lifetime revictimization may extend well into late adulthood.

Several possible interpretations may explain our findings about the persistent pattern of victimization across the life course. One stream of thought focuses on characteristics or risks in individuals, such as a sense of betrayal, psychological distress, and traumagenic dynamics (Finkelhor & Browne, 1985; Gobin & Freyd, 2009). Another stream focuses more on the contextual factors and risks embedded in individuals’ ecological environments, such as neighborhood context, societal values, and public policy (Pittenger et al., 2016; Strøm et al., 2020). According to Finkelhor et al. (2005), these risks, whether attributed to individuals or their environments, are interrelated and thus increase the potential of compounding risks and outcomes for children at the intersectional margins.

Alternatively, the cumulative disadvantage theory may be useful in interpreting findings. Rooted in the life course perspective, the theory asserts that disadvantages experienced during childhood, such as abuse and neglect, often accumulate and magnify over the life course (Crystal et al., 2017; Dannefer, 2003). Late adulthood is then when accumulated disadvantages result in wide divergence or disparity in key outcomes, such as health, economic status, and social network (Dannefer, 2003). When this concept of cumulative disadvantage is applied to the phenomenon of lifetime victimization, childhood adversities may plant the seeds of subsequent victimization experiences across adulthood into old age (Easton & Kong, 2020; Ferraro & Shippee, 2009). For example, relying on the cumulative disadvantage theory, Easton and Kong (2020) demonstrated the longitudinal pattern that a higher cumulative score of ACE was associated with worsened physical health and greater psychological distress in adulthood, which was in turn associated with greater risks of elder abuse victimization. As such, this concept of cumulative disadvantage could serve to understand patterns of lifetime revictimization and detect underlying processes and mechanisms over the life course.

Another key finding was that the indirect association involving ACE, IPV victimization, and elder abuse victimization was stronger for women than for men, suggesting a higher persistence in victimization for women. This result supports the findings of prior studies about women having predominantly high risks of interpersonal violence at different life stages (Carmel, 2019; Finfgeld-Connett, 2014; Miszkurka et al., 2016; Walsh et al., 2017). Our findings also emphasize the importance of adopting an intersectional approach (Morrissey et al., 2022) to research, mainly because marginalization based on the categories of social standing, such as gender in this study, can exacerbate the risk of lifetime revictimization. The WLS is a relatively homogenous sample in terms of race, educational level, and age (Herd et al., 2014), which may have helped demonstrate the apparent gender difference. Future research should explore factors and mechanisms that explain the pronounced pattern of lifetime revictimization for women, as well as the phenomenon of lifetime revictimization in different ethnic and racial groups. These investigations could untangle the lifetime process of cumulative disadvantages in victimization across marginalized sub-groups within the general population.

It is also notable that specific types of childhood victimization, namely those involving an interpersonal form of violence by a caretaker (e.g., parent perpetrated physical or sexual abuse and witnessing domestic violence) predicted exposure to elder abuse via IPV victimization. This result is consistent with the findings of Widom et al. (2008) who have shown that the risks of revictimization among a sample of young adults (average age: 39.5 years) were concentrated around interpersonal traumas such as physical/sexual assault and abuse. These congruent findings suggest that victimization clustering/persistency may occur more strongly when affected by interpersonal violence, underscoring the harmful, traumatic effects of betrayal, ruptured trust, and shattered safety (Finkelhor & Browne, 1985; Gobin & Freyd, 2009).

The current study has limitations that should be considered when interpreting findings from our models. WLS is largely representative of White, non-Hispanic American adults who have completed at least a high school education in the United States (Herd et al., 2014), limiting the representativeness of the findings of this study. Future studies should examine the hypothesized relationships in more diverse racial and ethnic groups (e.g., Kong et al., 2018). Additionally, there were measurement limitations inherent in secondary analyses. For example, childhood and adult victimization experiences were measured by retrospective self-reports, which may involve recall bias and/or the issue of underreporting due to a variety of factors, such as generational norms about child abuse, or social desirability. Dichotomizing Likert scale response options also involves the possibility of loss of information and misinterpretations (MacCallum et al., 2002). Relatedly, the current victimization measurement is limited in terms of capturing individuals’ subjective interpretations of the event, which might be the key mechanism determining the actual impact of the violence (Danese & Widom, 2023). There is a compelling need for qualitative design in future research on lifetime revictimization. Also, IPV victimization was measured by a single item that only captures the physical victimization from current spouses/partners. Lastly, we cannot rule out potential unmeasured confounders, such as poverty status, for the measures of ACE, IPV, and elder abuse (Vanderweele & Arah, 2011).

Despite the limitations, the current study makes significant contributions to the knowledge base. The present study is one of the first to examine the links between victimization experiences across childhood, adulthood, and late adulthood using a sample of U.S. older adults. This novel, thorough empirical investigation of lifetime revictimization will likely facilitate new studies and analyses related to elder abuse and other disparities in the older population. In terms of violence prevention, increased awareness and assessment of cumulative, lifetime revictimization can emphasize a timely intervention for childhood adversities and prevent subsequent adversities in later adulthood. Additionally, the current study underscores the importance of considering both proximal and distal risk factors for the revictimization of elder abuse. Particularly, employing a long-term view based on the life-course approach can help avoid a narrow focus or “band-aid” approach to address elder abuse issues. Identifying risk factors or intervening mechanisms can also inform creating targeted programs and interventions to prevent victimization across different life stages. For example, one goal of domestic violence support programs can be reflecting on underlying issues that persist from the past and addressing subsequent risks of revictimization.

Finally, the results highlight the importance of adopting a trauma-informed approach in elder abuse prevention and interventions. Practitioners and policymakers should consider the multi-layered, compounding impact of trauma from different life stages in designing prevention and treatment programs. Mental and physical health services for older adults should include more precise assessments for signs and symptoms of trauma that may have origins from earlier life stages. Treatment services must then respond by fully integrating knowledge about trauma, and resisting re-traumatization, of older adults (SAMHSA’s Trauma and Justice Strategic Initiative, 2014).

The issue of elder abuse has gained much attention coupled with increasing older populations and extended longevity. In regard to understanding, preventing, and tackling elder abuse, a life-course-based, trauma-informed approach is crucial and allows a whole-person understanding of older adults, which could lead to well-targeted interventions and solutions. As such, the current research has the potential to contribute to shifting a paradigm in dealing with the issue of elder abuse, ultimately improving the health and well-being of marginalized older adults. Our efforts in the current study were to lay the groundwork, and more research will be needed to confirm the pattern of lifetime revictimization and explore potential mechanisms and factors that persist in victimization.

Supplemental Material

sj-docx-1-jiv-10.1177_08862605241264534 – Supplemental material for Lifetime Revictimization: Evidence From the Wisconsin Longitudinal Study

Supplemental material, sj-docx-1-jiv-10.1177_08862605241264534 for Lifetime Revictimization: Evidence From the Wisconsin Longitudinal Study by Jooyoung Kong, Scott D. Easton and Jason M. Fletcher in Journal of Interpersonal Violence

Footnotes

Declaration of Conflicting Interests

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

Funding

The author(s) disclosed receipt of the following financial support for the research and/or authorship of this article: This study was supported in part by the National Institute on Aging grant no. K01AG076875.

ORCID iDs

Jooyoung Kong

Scott D. Easton

Supplemental Material

Supplemental material for this article is available online.

Author Biographies

Jooyoung Kong, PhD, is an assistant professor in the Sandra Rosenbaum School of Social Work at the University of Wisconsin-Madison. Guided by the life-course perspective, Professor Kong’s research focuses on the effects that childhood adverse experiences have on later-life health and well-being. Her work involves quantitative analyses of large-scale longitudinal surveys, such as the Wisconsin Longitudinal Study (WLS).

Scott D. Easton, PhD, is an associate professor at the Boston College School of Social Work. Professor Easton’s primary program of research investigates risk and protection factors for mental health outcomes of adults who experienced early life course trauma. He has focused on examining male survivors of child sexual abuse, including clergy abuse survivors.

Jason M. Fletcher, PhD, is a Vilas Distinguished Achievement Professor of Public Affairs with appointments in Applied Economics and Population Health Sciences at the University of Wisconsin-Madison. Professor Fletcher has extensive records of research in his areas of interest, including health economics, economics of education, social genomics, and child and adolescent health policy.

References

Acierno

Hernandez-Tejada

M. A.

Anetzberger

G. J.

Loew

Muzzy

(2017). The National Elder Mistreatment Study: An 8-year longitudinal study of outcomes. Journal of Elder Abuse & Neglect, 29, 254–269. https://doi.org/10.1080/08946566.2017.1365031

Arata

C. M.

(2002). Child sexual abuse and sexual revictimization. Clinical Psychology: Science and Practice, 9(2), 135–164. https://doi.org/10.1093/clipsy.9.2.135

Benyamini

(2011). Why does self-rated health predict mortality? An update on current knowledge and a research agenda for psychologists. Psychology and Health, 26(11), 1407–1413. http://doi.org/10.1080/08870446.2011.621703

Brossoie

Roberto

K. A.

Barrow

K. M.

(2012). Making sense of intimate partner violence in late life: Comments from online news readers. The Gerontologist, 52(6), 792–801. https://doi.org/10.1093/geront/gns046

Carmel

(2019). Health and well-being in late life: Gender differences worldwide. Frontiers in Medicine, 6, 218. https://doi.org/10.3389/fmed.2019.00218

Codina

Pereda

Guilera

(2022). Lifetime victimization and poly-victimization in a sample of adults with intellectual disabilities. Journal of Interpersonal Violence, 37(5–6), 2062–2082. https://doi.org/10.1177/0886260520936372

Crystal

Shea

D. G.

Reyes

A. M.

(2017). Cumulative advantage, cumulative disadvantage, and evolving patterns of late-life inequality. The Gerontologist, 57(5), 910–920. https://doi.org/10.1093/geront/gnw056

Daigneault

Hébert

McDuff

(2009). Men’s and women’s childhood sexual abuse and victimization in adult partner relationships: A study of risk factors. Child Abuse & Neglect, 33(9), 638–647. https://doi.org/10.1016/j.chiabu.2009.04.003

Dannefer

(2003). Cumulative advantage/disadvantage and the life course: Cross-fertilizing age and social science theory. The Journals of Gerontology: Series B, Psychological Sciences and Social Sciences, 58(6), S327–S337. https://doi.org/10.1093/geronb/58.6.s327

10.

Danese

Widom

C. S.

(2023). Associations between objective and subjective experiences of childhood maltreatment and the course of emotional disorders in adulthood. JAMA Psychiatry, 80(10), 1009–1016.

11.

Dietrich

(2007). Childhood maltreatment and revictimization: The role of affect dysregulation, interpersonal relatedness difficulties and posttraumatic stress disorder. Journal of Trauma & Dissociation, 8(4), 25–51. https://doi.org/10.1300/J229v08n04_03

12.

Easton

S. D.

Kong

(2020). Childhood adversities, midlife health, and elder abuse victimization: A longitudinal analysis based on cumulative disadvantage theory. The Journals of Gerontology: Series B, Psychological Sciences and Social Sciences, 76(10), 2086–2097. https://doi.org/10.1093/geronb/gbaa095

13.

Felitti

V. J.

Anda

R. F.

Nordenberg

Williamson

D. F.

Spitz

A. M.

Edwards

Koss

M. P.

Marks

J. S.

(1998). Relationship of childhood abuse and household dysfunction to many of the leading causes of death in adults. American Journal of Preventive Medicine, 14(4), 245–258. https://doi.org/10.1016/s0749-3797(98)00017-8

14.

Ferraro

K. F.

Shippee

T. P.

(2009). Aging and cumulative inequality: How does inequality get under the skin? The Gerontologist, 49(3), 333–343. https://doi.org/10.1093/geront/gnp034

15.

Finfgeld-Connett

(2014). Intimate partner abuse among older women: Qualitative systematic review. Clinical Nursing Research, 23(6), 664–683. https://doi.org/10.1177/1054773813500301

16.

Finkelhor

Browne

(1985). The traumatic impact of child sexual abuse: A conceptualization. The American Journal of Orthopsychiatry, 55(4), 530–541. https://doi.org/10.1111/j.1939-0025.1985.tb02703.x

17.

Finkelhor

Hamby

S. L.

Ormrod

Turner

(2005). The juvenile victimization questionnaire: Reliability, validity, and national norms. Child Abuse & Neglect, 29(4), 383–412. https://doi.org/10.1016/j.chiabu.2004.11.001

18.

Finkelhor

Ormrod

R. K.

Turner

H. A.

(2007a). Poly-victimization: A neglected component in child victimization. Child Abuse & Neglect, 31(1), 7–26. https://doi.org/10.1016/j.chiabu.2006.06.008

19.

Finkelhor

Ormrod

R. K.

Turner

H. A.

(2007b). Re-victimization patterns in a national longitudinal sample of children and youth. Child Abuse & Neglect, 31(5), 479–502. https://doi.org/10.1016/j.chiabu.2006.03.012

20.

Finkelhor

Ormrod

Turner

Holt

(2009). Pathways to poly-victimization. Child Maltreatment, 14(4), 316–329. https://doi.org/10.1177/1077559509347012

21.

Finkelhor

Shattuck

Turner

H. A.

Ormrod

R. K.

Hamby

S. L.

(2011). Polyvictimization in developmental context. Journal of Child & Adolescent Trauma, 4(4), 291–300. https://doi.org/10.1080/19361521.2011.610432

22.

Gobin

R. L.

Freyd

J. J.

(2009). Betrayal and revictimization: Preliminary findings. Psychological Trauma: Theory, Research, Practice, and Policy, 1(3), 242–257. https://doi.org/10.1037/a0017469

23.

Goodwin

R. D.

Hoven

C. W.

Murison

Hotopf

(2003). Association between childhood physical abuse and gastrointestinal disorders and migraine in adulthood. American Journal of Public Health, 93(7), 1065–1067. https://doi.org/10.2105/AJPH.93.7.1065

24.

Hauser

R. M

. (2009). The Wisconsin Longitudinal Study: Designing a study of the life course. In Elder

G. H.

Giele

J. Z.

(Eds.), The craft of life course research (pp. 29–50). The Guilford Press.

25.

Hébert

Lapierre

MacIntosh

H. B.

Ménard

A. D.

(2021). A review of mediators in the association between child sexual abuse and revictimization in romantic relationships. Journal of Child Sexual Abuse, 30(4), 385–406. https://doi.org/10.1080/10538712.2020.1801936

26.

Herd

Carr

Roan

(2014). Cohort profile: Wisconsin longitudinal Ssudy (WLS). International Journal of Epidemiology, 43(1), 34–41. https://doi.org/10.1093/ije/dys194

27.

Ihongbe

T. O.

Masho

S. W.

(2017). Child sexual abuse and intimate partner violence victimization in adulthood: Sex-differences in the mediating influence of age of sexual initiation. Journal of Child Sexual Abuse, 27(1), 53–69. https://doi.org/10.1080/10538712.2017.1361496

28.

Irving

S. M.

Ferraro

K. F.

(2006). Reports of abusive experiences during childhood and adult health ratings: Personal control as a pathway? Journal of Aging and Health, 18(3), 458–485. https://doi.org/10.1177/0898264305280994

29.

Jackson

S. L.

Hafemeister

T. L.

(2011). Risk factors associated with elder abuse: The importance of differentiating by type of elder maltreatment. Violence and Victims, 26(6), 738–757. https://doi.org/10.1891/0886-6708.26.6.738

30.

Kaindl

(2008). A global response to elder abuse and neglect: Building primary health care capacity to deal with the problem worldwide: Main report. https://extranet.who.int/agefriendlyworld/wp-content/uploads/2014/06/WHO-A-Global-Response-to-Elder-Abuse-and-Neglect-Building-Primary-Health-Care-Capacity-to-Deal-with-the-Problem-Worldwide.pdf

31.

Kong

Easton

S. D.

(2019). Re-experiencing violence across the life course: Histories of childhood maltreatment and elder abuse victimization. The Journals of Gerontology: Series B, 74(5), 853–857. https://doi.org/10.1093/geronb/gby035

32.

Kong

Roh

Easton

S. D.

Lee

Y. S.

Lawler

M. J.

(2018). A history of childhood maltreatment and intimate partner violence among Native American adults. Journal of Interpersonal Violence, 33(18), 2826–2848. https://doi.org/10.1177/0886260516632353

33.

Lacey

K. K.

Shahid

H. R.

Jeremiah

R. D.

(2021). Intimate partner violence and the role of child maltreatment and neighborhood violence: A retrospective study of African American and US Caribbean black women. International Journal of Environmental Research and Public Health, 18(5), 2245. https://doi.org/10.3390/ijerph18052245

34.

Leisey

Kupstas

P. K.

Cooper

(2009). Domestic violence in the second half of life. Journal of Elder Abuse & Neglect, 21(2), 141–155. https://doi.org/10.1080/08946560902779951

35.

MacCallum

Zhang

Preacher

K. J.

Rucker

D. D.

(2002). On the practice of dichotomization of quantitative variables. Psychological Methods, 7(1), 19–40.

36.

McDonald

Thomas

(2013). Elder abuse through a life course lens. International Psychogeriatrics, 25(8), 1235–1243. https://doi.org/10.1017/S104161021300015X

37.

Messman-Moore

T. L.

Long

P. J.

(2003). The role of childhood sexual abuse sequelae in the sexual revictimization of women: An empirical review and theoretical reformulation. Clinical Psychology Review, 23(4), 537–571. https://doi.org/10.1016/s0272-7358(02)00203-9

38.

Miszkurka

Steensma

Phillips

S. P.

(2016). Correlates of partner and family violence among older Canadians: A life-course approach. Health Promotion and Chronic Disease Prevention in Canada: Research, Policy and Practice, 36(3), 45–53. https://doi.org/10.24095/hpcdp.36.3.01

39.

Morrissey

M. B. Q.

Brownell

Caprio

(2022). Intersectionality of race, ethnicity, and culture in neglect, abuse, and violence against older persons: Human rights, global health, and systems approaches in pandemics. In Geffner

White

J. W.

Hamberger

L. K.

Rosenbaum

Vaughan-Eden

Vieth

V. I.

(Eds.), Handbook of Interpersonal Violence and Abuse across the Lifespan: A project of the National Partnership to End Interpersonal Violence Across the Lifespan (NPEIV) (pp. 4699–4719). Springer Nature Switzerland AG. https://doi.org/10.1007/978-3-319-89999-2_337

40.

National Research Council. (2003). Elder mistreatment: Abuse, neglect, and exploitation in an aging America. The National Academies Press. https://doi.org/10.17226/10406

41.

Papalia

N. L.

Luebbers

Ogloff

J. R. P.

Cutajar

Mullen

P. E.

Mann

(2017). Further victimization of child sexual abuse victims: A latent class typology of re-victimization trajectories. Child Abuse & Neglect, 66, 112–129. https://doi.org/10.1016/j.chiabu.2017.02.040

42.

Pillemer

Burnes

Riffin

Lachs

M. S.

(2016). Elder abuse: Global situation, risk factors, and prevention strategies. The Gerontologist, 56(Suppl 2), S194–S205. https://doi.org/10.1093/geront/gnw004

43.

Preacher

K. J.

Rucker

D. D.

Hayes

A. F.

(2007). Addressing moderated mediation hypotheses: Theory, methods, and prescriptions. Multivariate Behavioral Research, 42(1), 185–227. https://doi.org/10.1080/00273170701341316

44.

Pittenger

S. L.

Huit

T. Z.

Hansen

D. J.

(2016). Applying ecological systems theory to sexual revictimization of youth: A review with implications for research and practice. Aggression and Violent Behavior, 26, 35–45. https://doi.org/10.1016/j.avb.2015.11.005

45.

Radloff

(1977). The CES-D scale: A self-report depression scale for research in the general population. Applied Psychological Measurement, 1(3), 385–401. https://doi.org/10.1177/014662167700100306

46.

Ramsey-Klawsnik

(2017). Older adults affected by polyvictimization: A review of early research. Journal of Elder Abuse & Neglect, 29(5), 299–312. https://doi.org/10.1080/08946566.2017.1388019

47.

Rosay

A. B.

Mulford

C. F.

(2017). Prevalence estimates and correlates of elder abuse in the United States: The National Intimate Partner and Sexual Violence Survey. Journal of Elder Abuse & Neglect, 29(1), 1–14. https://doi.org/10.1080/08946566.2016.1249817

48.

SAMHSA’s Trauma and Justice Strategic Initiative. (July 2014). SAMHSA’s concept of trauma and guidance for a trauma-informed approach. US Department of Health and Human Services.

49.

Scoglio

A. A.

Kraus

S. W.

Saczynski

Jooma

Molnar

B. E.

(2021). Systematic review of risk and protective factors for revictimization after child sexual abuse. Trauma, Violence, & Abuse, 22(1), 41–53. https://doi.org/10.1177/1524838018823274

50.

Shepard

M. F.

Campbell

J. A.

(1992). The Abusive Behavior Inventory: A measure of psychological and physical abuse. Journal of Interpersonal Violence, 7(3), 291–305. https://doi.org/10.1177/088626092007003001

51.

Simmons

Swahnberg

(2021). Lifetime prevalence of polyvictimization among older adults in Sweden, associations with ill-heath, and the mediating effect of sense of coherence. BMC Geriatrics, 21, Article 129. https://doi.org/10.1186/s12877-021-02074-4

52.

Storey

J. E.

(2020). Risk factors for elder abuse and neglect: A review of the literature. Aggression and Violent Behavior, 50, Article 101339. https://doi.org/10.1016/j.avb.2019.101339

53.

Scoglio

A. A. J.

Kraus

S. W.

Saczynski

Jooma

Molnar

B. E

. (2021). Systematic Review of Risk and Protective Factors for Revictimization After Child Sexual Abuse. Trauma, Violence & Abuse, 22(1), 41–53. https://doi.org/10.1177/1524838018823274

54.

Straus

M. A.

Gelles

R. J.

Steinmetz

(1980). Behind closed doors: Violence in the American family. Anchor Books.

55.

Strøm

I. F.

Kristian Hjemdal

Myhre

M. C.

Wentzel-Larsen

Thoresen

(2020). The social context of violence: A study of repeated victimization in adolescents and young adults. Journal of Interpersonal Violence, 35(11–12), 2210–2235. https://doi.org/10.1177/0886260517696867

56.

Tapia

N. D.

(2014). Survivors of child sexual abuse and predictors of adult re-victimization in the United States: A forward logistic regression analysis. International Journal of Criminal Justice Sciences, 9(1), 64–73.

57.

Walsh

Scharf

Keating

(2017). Social exclusion of older persons: A scoping review and conceptual framework. European Journal of Ageing, 14(1), 81–98. https://doi.org/10.1007/s10433-016-0398-8

58.

Widom

C. S.

Czaja

S. J.

Dutton

M. A.

(2008). Childhood victimization and lifetime revictimization. Child Abuse & Neglect, 32(8), 785–796. https://doi.org/10.1016/j.chiabu.2007.12.006

59.

Wiklund

Ludvigsson

Nägga

Simmons

(2022). Elder abuse and life-course victimization in hospitalized older adults in Sweden: Prevalence and associations with mental ill-health. BMC Geriatrics, 22, Article 929. https://doi.org/10.1186/s12877-022-03638-8

60.

Vanderweele

T. J.

Arah

O. A

. (2011). Bias formulas for sensitivity analysis of unmeasured confounding for general outcomes, treatments, and confounders. Epidemiology (Cambridge, Mass.), 22(1), 42–52. https://doi.org/10.1097/EDE.0b013e3181f74493

61.

Zamir

Szepsenwol

Englund

M. M.

Simpson

J. A.

(2018). The role of dissociation in revictimization across the lifespan: A 32-year prospective study. Child Abuse & Neglect, 79, 144–153. https://doi.org/10.1016/j.chiabu.2018.02.001

Supplementary Material

Please find the following supplemental material available below.

For Open Access articles published under a Creative Commons License, all supplemental material carries the same license as the article it is associated with.

For non-Open Access articles published, all supplemental material carries a non-exclusive license, and permission requests for re-use of supplemental material or any part of supplemental material shall be sent directly to the copyright owner as specified in the copyright notice associated with the article.

0.00 MB

0.03 MB