Skip to main content
NIHPA Author Manuscripts logoLink to NIHPA Author Manuscripts
. Author manuscript; available in PMC: 2025 Aug 25.
Published before final editing as: J Aggress Maltreat Trauma. 2025 Aug 17:10.1080/10926771.2025.2548442. doi: 10.1080/10926771.2025.2548442

Determinants of Suicidal Ideation Among Immigrant Women With Cumulative Exposures to Violence: The Role of Resilience and Social Support

Bushra Sabri a, Jian Li a, Sara Butter a, Sarah Murray b, Chakra Budhathoki a
PMCID: PMC12377220  NIHMSID: NIHMS2105497  PMID: 40857496

Abstract

Lifetime exposures to violence and related psychosocial stressors can increase the risk of suicidal ideation among immigrant women. This study examined the impact of cumulative childhood and adulthood victimization, along with key psychosocial stressors, on suicidal ideation among 1265 immigrant women who experienced intimate partner violence (IPV). It also explored the mediating role of coping resources, specifically resilience and social support, in the relationship between lifetime violence exposure and suicidal ideation. Secondary data drawn from an intervention study involving immigrant survivors of IPV were analyzed using descriptive statistics and regression analysis procedures. The findings revealed that women who experienced multiple forms of violence in childhood and adulthood were 157% more likely to report suicidal ideation, highlighting the profound, long-lasting psychological impact of such experiences. Additionally, those who faced financial stress were 74% more likely to experience suicidal ideation, underscoring the connection between financial hardship and suicidal ideation. Mediation analysis showed that resilience and social support partially mediated the relationship between violence and suicidal ideation. Higher levels of social support and resilience were associated with 3% and 40% lower likelihood of suicidal ideation, respectively. These results suggest that emotional and social resources and abilities to cope with adversity play a crucial role in mitigating the risks of suicidal ideation, even in the face of significant life stressors. These findings highlight the need for comprehensive, trauma-informed interventions that address psychosocial stressors, strengthen social support, and promote resilience to reduce the risk of suicidal ideation in immigrant women affected by lifetime violence exposures.

Keywords: Exposures to violence, resilience, social support, suicide, women


Immigrant women face a range of challenges that may heighten their risk for suicidal ideation. These challenges can arise from both personal experiences and broader structural conditions that shape their daily lives. Many of these challenges reflect the social determinants of health - the broader conditions in which individuals are born, raised, live, and work (Kemmak et al., 2021). These include factors such as financial stress, exposure to violence, racial discrimination, and limited access to resources. For immigrant women, these challenges are often compounded by immigration-related stressors such as cultural adaptation, language barriers, economic difficulties, and social isolation (Campbell et al., 2016; Forte et al., 2018; Montesinos et al., 2013; Sabri et al., 2021). These stressors, compounded by systemic inequities - such as racial discrimination and limited access to healthcare - intensify mental health risks (Coimbra et al., 2022; Forte et al., 2018; Kemmak et al., 2021; Vroegindewey & Sabri, 2022), particularly suicidal ideation.

Racial discrimination, in particular, is a pervasive form of chronic stress that negatively affects mental health by fostering feelings of exclusion, rejection, and invalidation (Mikrut, 2020; Pascoe & Richman, 2009). These experiences can undermine self-worth and contribute to feelings of being a burden to others and believing that one’s situation is unlikely to improve - key psychological factors associated with suicidal ideation (Joiner, 2005; Joiner et al., 2009). For instance, studies indicate that repeated encounters with discrimination, such as being maltreated in public spaces, can lead to heightened depressive symptoms and reduced coping capacity, increasing the risk of suicidal thoughts (Lee et al., 2022; Oh et al., 2018). Among immigrant women, these effects may be magnified by intersecting racial and gender-based biases, as well as preexisting social and economic vulnerabilities, which can increase the risk of suicidal ideation.

Financial strain is another significant source of chronic stress that can heighten the risk for suicidal ideation among immigrant women. Stress resulting from economic instability can undermine immigrant women’s ability to meet personal or familial responsibilities and foster feelings of inadequacy and uncertainty (Elbogen et al., 2021; Llamocca et al., 2023; Mathieu et al., 2022). This enduring instability can strain relationships and intensify mental health burdens, making suicidal ideation more likely. Immigrant women may face pronounced financial pressures due to spousal dependence, underemployment, wage disparities, and precarious work conditions marked by low wages, job insecurity, limited legal protections, and lack of benefits (De Anda & Sabczak, 2011; De Jong & Madamba, 2002; Premji & Shakya, 2017; Ryabov, 2024). These structural vulnerabilities can not only strain daily functioning but also increase exposure to personal safety risks, particularly violence.

Exposure to violence is a critical determinant of suicide risk, particularly among immigrant women (Sabri et al., 2021). Lifetime exposure - whether through childhood abuse or IPV - can lead to lasting trauma, fear, and a diminished sense of safety or autonomy (Corley & Sabri, 2021; Sabri et al., 2018). Immigrant women may be at increased risk of experiencing violence due to factors such as immigration status, cultural and linguistic barriers, limited support networks, and systemic discrimination (Sabri et al., 2018). Studies have shown that individuals with higher lifetime exposures, such as childhood victimization and IPV, face substantially elevated risks for suicidal ideation (Brignone et al., 2018; Jiwatram-Negron et al., 2023; Moe et al., 2022; Villaveces et al., 2022). Violence can occur both before and after migration. Pre-migration experiences may include family or gender-based abuse, while post-migration risks can arise from isolation, economic dependence on partners, and heightened stress (Corley & Sabri, 2021; Weitzman et al., 2024). The severity and range of IPV experiences further compound this risk, with women exposed to multiple or severe forms of IPV facing a heightened risk for suicidal ideation (Jiwatram-Negron et al., 2023). Notably, while the prevalence of suicidal ideation among IPV survivors in general ranges from 25% to 50% (Devries et al., 2011), immigrant women experience a rate that is as high as 62.8% (Butter et al., 2024). The cumulative effect of enduring multiple forms of abuse can intensify trauma and limit their ability to cope (Taylor & Stanton, 2007), further elevating the risk of suicidal ideation.

In addition to the direct impact of violence, immigrant women often experience profound social isolation (Sabri et al., 2018), which can significantly increase the likelihood of suicidal ideation. This isolation may arise from the ongoing stress of cultural adaptation as immigrant women navigate unfamiliar norms, expectations, and environments. Language barriers further exacerbate these challenges by limiting social interactions, restricting access to vital information, and reducing the ability to advocate for oneself - factors that contribute to a profound sense of disempowerment (Cho & Haslam, 2010; Hovey, 2000; Sabri et al., 2018). Moreover, social isolation driven by factors such as geographic relocation, the loss of established community ties, and limited access to resources - including healthcare, mental health services, and social support networks (Cho & Haslam, 2010; Hovey, 2000; Sabri et al., 2018, 2020) - deprives immigrant women of critical emotional support. This isolation, often exacerbated by unmet mental healthcare needs and societal stigma, can amplify feelings ofloneliness, helplessness, and burdensomeness, which in turn can increase the risk of suicidal ideation (Joiner, 2005).

Coping and protective factors of suicidal ideation

While understanding the risk factors of suicidal ideation is critical, it is equally important to identify the protective factors that mitigate suicidal ideation among immigrant women exposed to violence. Social support and resilience are key protective factors (Parnell et al., 2022) that can mitigate the negative impacts of lifetime exposure to violence. Social support consistently emerges as one of the significant protective factors against suicidal ideation. Supportive relationships, whether with family, peers, community leaders, or service providers, can reduce feelings of isolation, foster a sense of belonging, and provide resources that help survivors cope, reducing the likelihood of suicidal ideation, particularly among survivors of IPV (Coker et al., 2002; Jiwatram-Negron et al., 2023; Pickover et al., 2021; Thompson et al., 2002). For immigrant women, community-based support networks can play a vital role in counter-acting the disempowering effects of violence and related stressors (Moniz et al., 2024), significantly reducing the risk of suicidal ideation (Kheni et al., 2024).

Resilience, defined as the ability to adapt and recover from adversity by leveraging both internal strengths and external resources (Ungar, 2015) - can further buffer the mental health impacts of violence and other adverse life experiences. Resilient individuals tend to demonstrate better emotional regulation, cognitive flexibility, and adaptive coping strategies, all of which reduce vulnerability to suicidal ideation (Sher, 2019). Among immigrant women, resilience may be cultivated through comprehensive approaches that strengthen psychological resources such as self-esteem and optimism and foster supportive social and policy environments (Gagnon & Stewart, 2014; Macdonnell et al., 2012). Collectively, social support and resilience may serve as complementary protective factors that help immigrant women cope with trauma, sustain psychological strength and empowerment, and reduce their risk of suicidality.

While prior research has established a link between IPV and suicidal ideation, further research is needed to understand how varying levels of cumulative exposure to both childhood and partner violence - along with key psychosocial stressors - contribute to suicidal ideation among immigrant women in the U.S. Additionally, the specific pathways through which these experiences influence suicidal ideation in this population remain underexplored. Although coping resources such as resilience and social support have been identified as potential protective factors, their specific roles - particularly as mediators between violence exposure and suicidal ideation among immigrant women - are not yet well understood.

This study aims to address these gaps by examining the cumulative effects of childhood victimization (CV) and IPV, key psychosocial stressors (such as discrimination, social support, length of time in the US and financial stress), and coping resources (social support and resilience) on suicidal ideation among immigrant women survivors of IPV. The objectives of the study are to (1) examine the relationship between cumulative exposure to CV and IPV and suicidal ideation; (2) investigate the associations between psychosocial stressors and suicidal ideation; (3) assess the contributions of coping resources to suicidal ideation; and (3) explore whether resilience and social support mediate the relationship between violence exposure and suicidal ideation. We hypothesize that greater cumulative exposure to CV and IPV, in combination with adverse social psychosocial stressors, will be associated with increased risk of suicidal ideation. In contrast, protective factors such as stronger social support and higher resilience are expected to be associated with reduced risk. Additionally, we hypothesize that resilience and social support will mediate the relationship between lifetime violence exposure and suicidal ideation, such that lower levels of these coping resources will be associated with greater risk. Understanding these dynamics is crucial for informing interventions that reduce suicide risk and promote mental well-being among immigrant women survivors of IPV.

Theoretical frameworks

This study integrates the Social Determinants of Health Framework, the Cumulative Stress Theory, and the Resilience Portfolio Model to examine both risk and protective factors for suicidal ideation. The Social Determinants of Health Framework provides a lens to examine how structural and systemic factors, such as financial stress, violence exposure, and discrimination, shape mental health disparities (Centers for Disease Control and Prevention [CDC], 2021; Kirkbride et al., 2024) The Cumulative Stress Theory posits that continued exposure to adverse life experiences over time can have a cumulative negative impact on mental health, particularly among marginalized populations with limited resources for coping (Lacey et al., 2021; McClendon et al., 2021; Nederhof & Schmidt, 2012; Simons et al., 2018). By highlighting the broader social context, this framework underscores immigrant women’s heightened vulnerability to suicidal ideation due to the compounding effects of life stressors. Complementing this perspective, the Resilience Portfolio Model emphasizes identifying protective factors across individual, relational, and community domains that buffer against such risks (Grych et al., 2015; Hamby et al., 2018; Yule et al., 2019). Protective factors, including social support, emotional regulation, and adaptive coping strategies - such as finding meaning in adverse events or maintaining a sense of purpose - are essential for improving mental health outcomes (Sher, 2019). For immigrant women facing significant adversity, protective mechanisms are critical in mitigating the adverse effects of risk factors. The integration of these frameworks provides a comprehensive approach to understanding the interplay of risk and resilience pathways in shaping suicidal ideation among immigrant women, particularly those experiencing systemic disadvantages.

Materials and methods

Participants and procedures

This study was a secondary analysis of baseline data collected from a randomized controlled trial (RCT) evaluating a technology-based intervention for immigrant women with exposures to IPV. The original RCT aimed to assess the effectiveness of the intervention in improving safety, mental health, and empowerment outcomes among this population. Baseline data were collected between January 2021 and April 2023 from a sample of 1,265 immigrant women. Participants were eligible if they were foreign-born women between the ages of 18 and 64 who had experienced IPV within the past year and had access to a safe computer or smartphone (i.e., a phone with internet access). The response rate for the baseline survey was 99%. Participants were recruited from multiple states across the US. Specifically, study information was disseminated nationwide through various organizations, including immigrant-specific service providers, health clinics, and immigrant IPV support agencies. Women were also recruited via listservs and social media platforms (e.g., Facebook, Twitter, Instagram) to reach a broader range of participants. Women were directed to the study website, which detailed study expectations, incentives, and eligibility. Those interested completed an online eligibility screener, and if eligible, they were asked to provide secure contact information (phone number and e-mail). The study team reviewed the registration details and contacted eligible participants by phone for validation (to prevent false or duplicate registrations) before enrollment and the baseline survey. Verbal consent was obtained during the phone call, and participants also provided electronic consent on the study website before accessing the survey. Data were collected through a web-based questionnaire using a Clinical Trials Management System. Participants were compensated $40 for their time. All study procedures were reviewed and approved by the institutional review board (IRB) of the investigators’ home institution (IRB00224324; Johns Hopkins University).

Measures

Outcome

Suicidal ideation.

Suicidal ideation was measured using a single item from the Patient Health Questionnaire (PHQ-9; Spitzer et al., 1999) (Cronbach’s α = 0.91). The question posed to participants was- “Over the last two weeks, how often have you been bothered by thoughts that you would be better off dead or hurting yourself.” The response scale ranged from 0 (not at all) to 3 (nearly every day). For our analysis, we dichotomized this item to clearly differentiate between participants who did and did not experience suicidal ideation. Specifically, responses of 1 (several days), 2 (more than half the days), and 3 (nearly every day) were combined into a single “yes” category (coded as 1), while a response of 0 (not at all) was retained as “no” (coded as 0). This dichotomization allowed us to create a clinically meaningful distinction based on the presence or absence of suicidal ideation.

Correlates

Race and ethnicity.

Race was grouped into four categories: Asian, White/Caucasian, Black, and Other, while ethnicity was classified as Hispanic or non-Hispanic.

Marital status.

Marital status included four categories: currently married, formerly married, single, and partnered. Regions of origin were divided into six groups: Asia, Latin America, Europe and the Middle East, Africa, U.S. nearby regions, and unknown.

Employment.

Employment was categorized into four levels: full-time, part-time, seeking opportunities, and others.

Education.

Education was grouped into three levels: associate degree (2-year degree following high school) or lower, bachelor’s degree, and master’s degree or higher.

Immigration status.

Immigration status was classified as immigrant, refugee, visitor, or other.

Duration of residence.

Duration of residence in the U.S. ranged from: less than one year, 1-to 4 years, 5-to 10 years, and more than 10 years.

Financial stress.

For financial stress, participants were asked, “How often do you run out of money for necessities like housing or food for yourself or/and your children?” with responses ranging from 1 (never) to 5 (every day or daily) with a do not know option (which was treated as missing). To distinguish between those who experienced consistent, recurrent financial stress and those who did not, the responses of l(never) and 2 (once or twice) were combined into 0 (no) to represent minimal or infrequent stress. In contrast, responses of 3 (every month), 4 (every week), and 5 (every day) were combined into 1 (yes), representing ongoing, more regular financial stress. This single-item measure has been used in prior research (Sabri et al., 2017, 2023) and is consistent with similar items used by other researchers (e.g., Institute of Medicine, 2014; Kahn & Pearlin, 2006; Okechukwu et al., 2012; Pearlin et al., 1981) that have demonstrated reliability in capturing financial hardship.

Immigration stress.

The Revised Stress of Immigration Survey (SOIS) (Sternberg et al., 2016) (7 items; α= 0.88) was used to assess immigration-related stress. The responses were rated from 0 (not applicable) to 5 (severe stress). Items were summed, and the mean value was calculated by dividing the total sum by the number of items. Higher mean scores indicated a higher immigration stress.

Everyday discrimination.

The Everyday Discrimination Scale (EDS) (9 items; Williams et al., 1997) = 0.87) was used to measure subjective experiences of daily discrimination against the minority population. The responses ranged from 0 (never) to 5 (almost every day), with an option for respondents to indicate they did not want to answer (treated as missing). The EDS was scored using the sum of the items. A higher total score indicated a higher level of discrimination.

Intimate partner violence.

Physical and sexual IPV.

Physical and sexual IPV were measured using 15 items from the Revised Conflict Tactics Scale 2 (CTS2) (Straus et al., 1996) = 0.93), a reliable and valid instrument to measure IPV. The items were rated on a 5-point Likert scale from 0 (never) to 4 (very frequently). The response options were dichotomized: responses of 1 (rarely), 2 (occasionally), 3 (frequently), and 4 (very frequently) were combined into one category labeled as 1 (yes), while the response of 0 (never) was labeled 0 (No). To facilitate interpretation and analysis, responses were dichotomized: any experience of physical and sexual IPV (responses of 1–4) was categorized as 1 (yes), while the absence of physical and sexual IPV (response of 0) was categorized as 0 (no). This dichotomization was chosen to distinguish women who had experienced physical or sexual IPV from those who had not.

Psychological Abuse.

Psychological abuse was measured using the Womens Experience with Battering (WEB) (IO items; P.H. Smith et al., 1995) (α= 0.93). The WEB was scored using the sum of items rated on a 6-point Likert scale ranging from 1 (disagree strongly) to 6 (strongly agree). The total scores were dichotomized, with scores equal to or greater than 20, indicating the presence of psychological abuse (Community Solutions, n.d.). This threshold was based on established scoring guidelines for the WEB, which identify 20 as the cutoff for meaningful experiences of battering (Community Solutions, n.d.).

Childhood victimization (CV).

CV experiences were measured using five items from the Adapted Juvenile Victimization Questionnaire (JVQ) (Finkelhor et al., 2005) (α= 0.80). The items focused on physical, sexual, and psychological abuse by anyone, neglect, and experiences in which one felt unsafe or in danger during childhood. Responses were dichotomous (0 = no, l = yes), and the total CV score was calculated by summing all five items. The score was then dichotomized, with 0 indicating no CV or fewer than three types of victimization and 1 indicating three or more types of CV. This cutoff was selected based on the median CV score, allowing for meaningful differentiation between lower and higher exposure to childhood victimization.

Cumulative exposures to violence.

To capture the cumulative and compounded impact of multiple forms of violence across the lifespan and to provide a nuanced understanding of how childhood victimization (CV) and intimate partner violence (IPV) exposures intersect to influence women’s suicidal ideation, women were categorized as follows: (1) Multiple types of CV and multiple types of IPV exposures: Women with experiences of three or more types of childhood victimization and all three types of IPV (physical, sexual, and psychological). This category identified women with significant and varied violence in both childhood and adulthood, emphasizing the compounded effects of trauma throughout their lives. (2) Multiple types of CV and fewer IPV exposures: Experiences of three or more types of CV and one or two types of IPV. This category highlighted the unique impact of early victimization, where women had considerable childhood trauma but limited exposure to IPV in adulthood. (3) No CV or fewer CV exposures among IPV-exposed women: Experiences of one, two, or three types of IPV with no CV or fewer than three types of CV. This category isolated the effects of IPV by examining women without significant childhood trauma. Dichotomizing these variables allowed for the creation of distinct categories of lifetime exposure to violence, facilitating clearer group comparisons and simplifying the analysis of complex and multifaceted experiences

Social support.

Perceived sources of support were measured using a brief form of the Perceived Social Support Questionnaire (6 items; Kliem et al., 2021) (α= 0.91) using a five-point Likert scale ranging from 1 (not true at all) to 5 (very true). The items were summed, with higher scores indicating higher levels of perceived social support.

Resilience.

The Brief Resilience Scale (BRS) (B. W. Smith et al., 2008) (6 items; α = 0.84) was used to assess participants’ ability to bounce back or recover from stress and adversity. Responses were provided on a 5-point scale ranging from 1 (strongly disagree) to 5 (strongly agree). The items were evenly divided between positively and negatively worded statements to reduce response bias. For example, a positively worded item was: “I tend to bounce back quickly after hard times.” In contrast, negatively worded items - such as “I have a hard time making it through stressful events” (reverse scored) - were included to counterbalance potential biases. The final resilience score was computed by reverse coding items 2, 4, and 6 and finding the mean of the six items (B. W. Smith et al., 2008). Higher mean scores indicated a higher level of resilience.

Data analysis

Bivariate logistic regression analyses were conducted to examine relationships between each potential correlate and suicidal ideation. Variables with a p-value <.05 were assessed for multicollinearity using variance inflation factor (VIP), with a cutoff of <5 indicating no multicollinearity (Craney & Surles, 2002). Statistically significant (p <.05) and non-collinear variables were included in the final model. These included violence exposure, age, marital status, resilience, social support, everyday discrimination, financial stress, immigration stress, and length of time in the U.S.

A four-step hierarchical logistic regression was conducted to examine the effects of violence and other psychosocial stressors (e.g., immigration stress, discrimination), as well as coping resources (resilience and social support), on suicidal ideation. In the first step, socio-demographic variables (age and marital status) were entered. The second step added psychosocial stressors: duration of residence in the U.S., discrimination, immigration stress, and financial stress. In the third step, cumulative exposures to violence were included. The final step introduced coping resources, specifically social support and resilience. We excluded depression and PTSD from the models because of the overlap with suicidal ideation as a measured outcome. The suicide item was drawn from the depression measure, and almost all women with suicidal ideation had depression and PTSD. Including these could have obscured the relationship between a broad range of risk factors and suicidal ideation. Model fit was evaluated using the Hosmer-Lemeshow test, Nagelkerke R2, and the Omnibus test. Higher Nagelkerke R2 values indicated better model fit (Nagelkerke, 1991), while the Omnibus test assessed whether adding variables improved model fit (Hosmer et al., 2013). Adjusted odds ratios (AORs) with 95% confidence intervals were reported. Analyses were performed using SPSS 27.

In further analysis, we examined if resilience and social support mediated the relationship between lifetime exposures to violence and suicidal ideation. The PROCESS macro with bootstrapping approach by Andrew F. Hayes (2012) was used to repeatedly resample the data and estimate the direct and indirect effects between the categorical independent variable of lifetime violence and the dichotomous dependent variable (suicidal ideation). PROCESS is a computational tool designed by Andrew F. Hayes for conducting mediation, moderation, and conditional process analyses using ordinary least squares (OLS) regression (Hayes, 2013). RID, the indirect to direct effect (RID) ratio, was also calculated to estimate the mediation effect size (ES). The RID mediation ES are categorized as small (0.01), medium (0.09), and large (0.25) (Preacher & Kelley, 2011)

Statistical power

With a sample size of 1,265, an alpha level of 0.05, an assumed odds ratio of 1.50 (small effect size), and an estimated 20% prevalence of suicidal ideation in the reference group (i.e., no CV or fewer than three types of exposures and IPV), we had over 86% power to detect significant effects in the binary logistic regression analysis. For the mediation analysis, traditional power calculations are not well-suited for the bootstrapping approach, as bootstrapping does not rely on distributional assumptions (Kimber, 1994). Instead, we referred to Fritz and MacKinnon’s (2007) simulation-based sample size recommendations for mediation analysis. Based on our standardized regression coefficients (a = −0.15, b = −0.50), which fall within the small to medium effect size range, the required sample sizes for adequate power using the bias-corrected (n = 391) and percentile bootstrap (n = 404) methods were well below our total sample size (n = 1,265). This suggests that our study had sufficient power (> 80%) to detect mediation effects. All analyses were conducted using SPSS (version 27) and R Studio.

Results

Sample characteristics

Table 1 presents the characteristics of the sample. The average age of women was 37.0 years (SD= 9.8). Most women identified as non-Hispanic (58.0%, n = 725), with the largest racial group being Asian (30.5%, n = 386). Regarding socioeconomic factors, 60.3% (n = 752) had a bachelor’s degree or higher, and 41.5% (n = 507) were employed full-time. Financial stress was common, with most women (55.9%, n = 678) reporting frequent financial difficulties, such as struggling to afford essentials like housing or food. Half of the sample (50.0%, n = 631) was married, and the majority resided in urban (58.9%, n = 743) areas.

Table 1.

Sample characteristics.

Women With Suicide Ideation (N = 295) Unadjusted OR (95% CI) p value Total Sample (N = 1265)
Socio-Demographic Characteristics
Age (Mean, SD) 34.7 (10.1) 0.97 (0.95–0.98) <.001* 37.0 (9.8)
Race .195
 – Asian 105 (35.6%) 386 (30.5%)
 – White or Caucasian 75 (25.4%) 1.08 (0.69–1.68) 356 (28.2%)
 – Black 38 (12.9%) 1.40 (1.00–1.97) 171 (13.5%)
 – Other 77 (26.1%) 1.05 (0.74–1.51) 351 (27.8%)
Region (N, %) .337
 – US Nearby Regions 18 (6.1%) 87 (6.9%)
 – Asia 77 (26.1%) 1.21 (0.68–2.15) 322 (25.5%)
 – Latin America 84 (28.5%) 0.98 (0.55–1.73) 413 (32.6%)
 – Europe and Middle East 21 (7.1%) 1.22 (0.60–2.49) 87 (6.9%)
 – Africa 21 (7.1%) 1.17 (0.57–2.38) 90 (7.1%)
 – Unknown 74 (25.1%) 1.49 (0.83–2.68) 266 (21.0%)
Ethnicity (N, %) .342
 – Non-Hispanic 177 (60.4%) 725 (58.0%)
 – Hispanic 116 (39.6%) 0.88 (0.67–1.15) 524 (42.0%)
Marital Status (N, %) <.001*
 – Currently Married 134 (45.4%) 631 (50.0%)
 – Formerly Married 28 (9.5%) 1.42 (1.00–2.00) 136 (10.8%)
 – Currently single or had a former relationship 70 (23.7%) 0.96 (0.61–1.52) 268 (21.2%)
 – Partnered 63 (21.4%) 1.32 (0.95–1.84) 228 (18.1%)
Immigration Status (N, %) .624
 – Immigrant 145 (52.2%) 613 (51.6%)
 – Refugee 20 (7.2%) 1.24 (0.72–2.14) 82 (6.9%)
 – Visitor 55 (19.8%) 0.85 (0.60–1.21) 278 (23.4%)
 – Other 58 (20.8%) 1.02 (0.72–1.45) 216 (18.1%)
Employment Status (N, %) .691
 – Employed Full-time 116 (40.4%) 507 (41.5%)
 – Employed Part-time 68 (23.7%) 1.14 (0.81–1.61) 269 (22.0%)
 – Seeking Opportunities 64 (22.3%) 1.10 (0.78–1.57) 259 (21.2%)
 – Other 39 (13.6%) 0.89 (0.59–1.34) 186 (15.2%)
Education (N, %) .053
 – Associate Degree or Lower 129 (44.2%) 495 (39.7%)
 – Bachelor’s Degree 93 (31.8%) 0.91 (0.67–1.23) 385 (30.9%)
 – Master’s Degree or higher 70 (24.0%) 0.67 (0.48–0.93) 367 (29.4%)
Mental Health
PTSD (N, %) 210 (71.2%) 5.00 (3.76–6.66) <.001* 530 (41.9%)
Depression (N, %) 238 (80.7%) 7.27 (5.30–10.00) <.001* 591 (46.8%)
Both PTSD and Depression (N, %) 189 (64.1%) 8.74 (6.03–12.67) <.001* 425 (33.6%)
Psychosocial Stressors
Immigration Stress (Mean, SD)
(Range 0 to 5)
2.2 (1.3) 1.19 (1.06–1.34) .003* 2.0 (1.2)
Frequent Financial Stress (N, %) 202 (69.7%) 2.16 (1.63–2.86) <.001* 678 (55.9%)
Everyday Discrimination (Mean, SD)
(Range 0 to 45)
16.67 (9.20) 1.04 (1.02–1.05) <.001* 14.2 (8.9)
Duration of Residence in the US (N, %) <.001*
 – Less than one year 22 (7.5%) 91 (7.2)
 – 1–4 years 73 (24.7%) 1.53 (0.88–2.66) 223 (17.6)
 – 5–10 years 66 (22.4%) 1.05 (0.60–1.83) 263 (20.8)
 – More than 10 years 134 (45.4%) 0.76 (0.46–1.28) 687 (54.4)
Coping Resources
Social Support (Mean, SD)
(Range 6 to 30)
16.9 (6.4) 0.95 (0.93–0.97) <.001* 18.7 (6.6)
Resilience (Mean, SD)
(Range 0 to 5)
2.6 (0.8) 0.57 (0.49–0.67) <.001* 2.9 (0.9)
Cumulative Exposures to Violence
IPV and Childhood Victimization (CV) (N, %) <0.001*
 – Multiple types of CV and IPV 110 (37.8%) 2.86 (2.09–3.90) 290 (24.1)
 – Multiple types of CV and fewer IPV 68 (23.4%) 1.55 (1.10–2.18) 274 (22.7)
 – No CV or fewer CV exposures among IPV-exposed women 113 (38.8%) 641 (53.2)

Percentages represented within column added for each variable;

*

p <.05;

The p-value indicated statistically significant differences between suicidal ideation and each independent variable, as determined by separate logistic regression analyses. The OR (odds ratio) represents the unadjusted measure of the strength of the association between each variable and suicidal ideation without controlling for any other covariates.

Regarding lifetime violence exposure, 24.1 % (n = 290) of IPV survivors reported experiencing multiple forms of childhood victimization (CV) and IPV, including all three types of IPV (physical, sexual, and psychological) and three or more types of CV. An additional 23% (n = 274) experienced multiple forms of CV but fewer IPV exposures. The remaining 53.2% (n = 641) had IPV experiences but either no CV exposure or fewer than three types of CV.

Bivariate associations between women with and without suicidal ideation

Women with suicidal ideation (M = 34.7 years) were significantly younger than those without suicidal ideation (M = 37.7 years) (p < .01). A significantly higher proportion of women with suicidal ideation (32.2%, n = 95) had lived in the U.S. for less than five years compared to those without suicidal ideation (22.6%, n = 219) (p < .01). Financial stress was also significantly more prevalent among women with suicidal ideation (69.7%, n = 202) compared to their counterparts (51.5%, n = 476) (p < .01). In addition to these demographic and financial differences, significant psychosocial disparities were observed. Women with suicidal ideation reported lower resilience (M = 2.6vs. M = 3.0) and perceived social support (M = 16.9vs. M = 19.3) than those without suicidal ideation (p < .01). They also experienced higher levels of discrimination (M = 16.7vs. M = 13.4) and immigration stress (M = 2.2vs. M = 2.0) (p < .01).

Among women with suicidal ideation, 81 % (n = 238) reported symptoms of depression, 71 % (n = 210) had PTSD, and 64% (n = 189) experienced co-occurring depression and PTSD - significantly higher rates than those without suicidal ideation (36.5%, 33.0%, and 24.0%, respectively) (p < .01). Exposure to violence was also a key factor distinguishing the two groups. Over one-third (37.8%, n = 110) of women with suicidal ideation had experienced multiple forms of CV and IPV, nearly double the proportion of those without suicidal ideation (19.7%) (p < .01).

Multivariate predictors of suicidal ideation

Table 2 presents results from the hierarchical logistic regression analysis. The initial model, which included demographic variables (age and marital status), did not significantly explain the variance in suicidal ideation (Step Chi-square = 7.94, p < .094), accounting for only 1.8% of the variability (R2 = 0.02). The model demonstrated a good fit based on the Hosmer-Lemeshow test (p = .306). Among these variables, age was significantly associated with suicidal ideation, with older age associated with a decreased likelihood of reporting suicidal ideation (OR = 0.98, 95% CI= 0.96–1.00, p = .015).

Table 2.

Hierarchical logistic regression analysis for variables predicting suicidal ideation.

Independent Variable Model 1
OR (95% CI)
Model2
OR (95% CI)
Model3
OR (95% CI)
Model4
OR (95% CI)
Step1: Socio-Demographic Variables
Age 0.98 (0.96–1.00)* 0.98 (0.96–1.01) 0.98 (0.96–1.00) 0.99 (0.96–1.01)
Marital Status
 Married (Ref)
 Partners/Coupled 1.05 (0.64–1.72) 0.98 (0.59–1.63) 0.97 (0.57–1.62) 1.08 (0.63–1.84)
 Formerly Married 1.00 (0.52–1.91) 0.93 (0.48–1.81) 0.85 (0.43–1.68) 0.95 (0.47–1.90)
 Single/Former Relationship 1.06 (0.65–1.74) 1.07 (0.65–1.77) 1.02 (0.61–1.71) 1.13 (0.66–1.92)
Step2: Psychosocial Stressors
Duration of Residence in the US
 Less than one year (Ref)
 1–4 years 1.40 (0.65–3.01) 1.37 (0.62–3.03) 1.30 (0.58–2.92)
 5–10 years 0.90 (0.42–1.93) 0.90 (0.41–1.99) 0.84 (0.37–1.90)
 More than 10 years 0.85 (0.42–1.76) 0.80 (0.38–1.69) 0.74 (0.34–1.58)
Financial Stress
 No (Ref)
 Yes 1.79 (1.22–2.62)* 1.64 (1.11–2.43)* 1.74 (1.16–2.60)*
Immigration Stress 1.02 (0.87–1.20) 1.00 (0.85–1.18) 0.93 (0.78–1.10)
Everyday Discrimination 1.03 (1.01–1.06)* 1.02 (1.00–1.05)* 1.01 (0.99–1.04)
Step3: Cumulative Exposures to Violence
Intimate Partner Violence (IPV) and Childhood Victimization (CV)
 None or Fewer CVs and Any IPV (REF)
 Multiple Types of CV and Fewer IPV 1.85 (1.16–2.93)* 1.84 (1.15–2.94)*
 Multiple Types of CV and IPV 2.87 (1.83–4.53)* 2.57 (1.61–4.11)*
Step4: Coping Resources
Social Support 0.97 (0.94–1.00)*
Resilience 0.60 (0.47–0.77)*
R 2 0.018 0.070 0.116 0.169
R2 Change 0.018 0.052 0.046 0.053
Chi-square (Omnibus Test) 7.936 31.712* 53.510* 79.162*
Chi-square (Hosmer-Lemeshow Test) 9.446 4.976 9.350 16.435
*

p < .05.

When financial stress, immigration stress, everyday discrimination, and duration of residence in the U.S. were added to the model, overall fit improved significantly (Step Chi-square= 23.78, p < .001), and explained variance increased by 5.2% (R2 = 0.070). Model fit remained adequate (Hosmer-Lemeshow p = .760). In this model, financial stress emerged as a significant predictor, with women frequently experiencing financial stress having 78% higher odds of suicidal ideation than those who seldom experienced it (OR = 1.79, 95% CI= 1.22–2.62, p = .003). Higher levels of everyday discrimination were also significantly associated with increased odds of suicidal ideation (OR = 1.03, 95% CI= 1.01–1.06, p = .005).

The subsequent inclusion of violence further improved the model (Step Chi-square = 21.80, p < .001), increasing the explained variance by an additional 4.6% (Nagelkerke R2 = 0.116), with continued good fit (Hosmer-Lemeshow p = .314). Compared to those with no or limited violence exposure, women who had experienced multiple types of both CV and IPV had significantly higher odds of suicidal ideation (OR= 2.87, 95% CI= 1.83–4.53, p < .001) Women with multiple types of CV but fewer IPV exposures also had elevated odds (OR= 1.85, 95% CI= 1.16–2.93, p = .009). Financial stress (OR= 1.64, 95% CI= 1.11– −2.43, p = .013) and discrimination (OR= 1.02, 95% CI= 1.00–1.05, p = .048) remained significantly associated with suicidal ideation.

In the final model, coping resources - specifically social support and resilience - were added, resulting in a significant improvement in model fit (Step Chi-square = 25.65, p < .001) and a total explained variance of 16.9% (R2 = 0.169). The final model was highly significant overall (Model Chi-square= 79.16, p < .001). Financial stress remained a strong predictor (OR= 1.74, 95% CI= 1.16–2.60, p = .007), as did exposure to violence. Women with multiple types of CV and IPV had 157% higher odds of suicidal ideation (OR= 2.57, 95% CI= 1.61–4.11, p < .001), and those with multiple types of CV but fewer IPV exposures had 84% higher odds of suicidal ideation (OR= 1.84, 95% CJ= 1.15–2.94, p = .011) than IPV-exposed women with no or fewer CV exposures. In contrast, social support and resilience remained protective. Increased level of social support (OR= 0.97, 95% CI= 0.94–1.00, p = .027) and resilience (OR= 0.60, 95% CI= 0.44–0.70, p < .001) were associated with decreased odds of experiencing suicidal ideation.

Mediation analysis

Results from the mediation model examining suicidal ideation indicated that exposure to violence was indirectly related to suicidal ideation through its effects on resilience and social support. As shown in Figure 1, experiencing multiple forms of CV and multiple types of IPV was significantly associated with lower resilience (a1 = −0.29, p < .001) and reduced social support (a2 = −3.10, p < .001). In turn, lower resilience (b1 = −0.47, p < .001) and lower social support (b2 = −0.03, p = .007) were significantly linked to increased odds of suicidal ideation. The direct effect of this high-level violence exposure on suicidal ideation remained significant (c’ = 0.87, p < .001). Significant indirect effects were found through both mediators: resilience (effect= 0.13, 95% CI [0.07, 0.21]) and social support (effect= 0.09, 95% CI [0.02, 0.17]). The ratios of indirect to direct effects (RID) were 0.13 for resilience and 0.09 for social support, both indicating moderate mediation effect sizes.

Figure 1.

Figure 1.

Role of resilience and social support in the relationship between multiple types of CV and IPV exposure and suicidal ideation.

As shown in Figure 2, for women exposed to multiple types of CV but fewer IPV types, there was also a significant association with lower resilience (a1 = −0.16, p = .008), which in turn significantly increased the odds of suicidal ideation (b1 = −0.47, p < .001). However, this exposure level was not significantly related to social support (a2 = −0.70, p = .132), though social support remained a significant predictor of suicidal ideation (b2 = −0.03, p = .007). The direct effect of this exposure level on suicidal ideation remained significant (c’ = 0.36, p = .042). The bootstrapped indirect effect through resilience was significant (effect= 0.08, 95% CI [0.02, 0.14]), with a RID of 0.22, suggesting moderate mediation. In contrast, the indirect effect through social support was not significant (effect= 0.02, 95% CI [−0.01, 0.06]), with a low RID of 0.06.

Figure 2.

Figure 2.

Role of resilience and social support in the relationship between multiple types of CV but fewer types of IPV exposures and suicidal ideation.

Discussion

This study examined risk and protective factors of suicidal ideation among immigrant women exposed to IPV. It further explored the mediating role of resilience and social support in the association between levels of violence exposure and suicidal ideation. The Social Determinants of Health Framework, Cumulative Stress Theory, and the Resilience Portfolio Model guided the conceptualization and interpretation of these factors, offering a multi-level understanding of structural inequities and individual strengths. Women who frequently experienced financial stress showed a significantly greater likelihood of suicidal ideation compared to those with less financial stress, consistent with prior research that links financial hardship or stress to suicidal ideation (Carr et al., 2018; Fiksenbaum et al., 2017). From a Social Determinants of Health perspective, financial stress indicates structural inequities, such as economic disadvantage and poverty, that shape the well-being of individuals, families, and communities (National Academies of Sciences, Engineering, Medicine, Health, Division, Medicine Board on Population Health and Public Health Practice, & Committee on Community-Based Solutions to Promote Health Equity in the U.S. et al., 2017). Chronic financial instability can lead to a cumulative psychological burden, often resulting in extreme stress, emotional exhaustion, and diminished self-worth. These effects are exacerbated by the inability to meet daily needs or navigate financial crises, fostering feelings of helplessness that increase the risk of suicidal ideation (Zapata & Morell, 2024). Addressing this critical social determinant underscores the importance of economic empowerment initiatives, including financial counseling and assistance programs, within intervention plans for women with lifetime exposures to violence. These initiatives could play a transformative role in reducing the mental health burden and suicidal ideation among immigrant women, a group disproportionately affected by systemic inequities (Sabri & Lee, 2024).

Our study highlights the compounded effects oflifetime violence exposures, including CV and IPV, on suicidal ideation. Women facing multiple forms of CV and IPV reported significantly higher odds of suicidal ideation compared to those with fewer or no childhood exposures. This aligns with prior research demonstrating a significant relationship between early-life trauma or CV and suicidal ideation in adulthood (Angelakis et al., 2019; Bruffaerts et al., 2010; Sachs-Ericsson et al., 2013). Research has also established a link between IPV and an increased risk of suicidal thoughts and behaviors (McManus et al., 2022; Rasmussen et al., 2023). Abusive relationships can disrupt emotional regulation, increase feelings of helplessness and worthlessness, and contribute to chronic stress, all of which are strongly associated with suicidal ideation (Roley-Roberts et al., 2021; Wolford-Clevenger & Smith, 2017). Within the Social Determinants of Health framework, immigrant women’s exposures to violence reflect structural vulnerabilities linked to systemic inequities, such as unequal access to safety, justice, and support services (Sabri & Lee, 2024). Addressing these vulnerabilities requires comprehensive, trauma-informed approaches that integrate interventions for early-life trauma, IPV, and mental health care to mitigate the lasting psychological effects of CV and IPV.

Social support emerged as a protective factor, significantly reducing the likelihood of suicidal ideation. Social support, a key element of the Resilience Portfolio Model, provides psychological and material resources that buffer against stress and enhance overall well-being (Kleiman & Riskind, 2013). By fostering connections and reinforcing self-esteem, social support can mitigate the adverse effects of violence exposure and financial stress, thereby reducing vulnerability to suicidal ideation (Kleiman & Riskind, 2013; Pate et al., 2023). Notably, in our findings, social support partially mediated the relationship between multiple types of CV and IPV exposure and suicidal ideation, suggesting that its protective role extends beyond direct effects. In this way, social support acts as both a buffer and a bridging mechanism, disrupting the pathway from trauma to suicidal ideation. Thus, intervention plans for immigrant women with cumulative violence exposures and suicidal ideation should include components that strengthen social networks and community ties. Connecting women with culturally relevant support groups and other needed resources in the community may offset the detrimental effects of lifetime violence exposures and other life stressors on overall mental health, including suicidal ideation.

In line with the principles of the Resilience Portfolio Model and prior research (Sher, 2019), our findings suggest that resilience is a protective buffer against suicidal ideation. Specifically, we found that resilience partially mediated the relationship between multiple types of CV and IPV exposure and suicidal ideation, with a moderate mediation effect. This indicates that building resilience - defined as the ability to adapt and thrive despite adversity (Southwick et al., 2014) - can disrupt the pathway from trauma to suicidal ideation. The protective role of resilience underscores the importance of fostering psychological resilience to reduce the odds of suicidal ideation among survivors of IPV with CV experiences. Promoting resilience in intervention plans for abused women should involve strategies such as enhancing coping skills, fostering a positive self-concept, and increasing access to supportive resources. These approaches address not only individual psychological impacts but also the broader structural determinants of health that perpetuate cycles of adversity.

According to the Resilience Portfolio Model, supporting women with IPV and CV involves strengthening assets in three key domains: (1) Regulatory strengths, such as active coping, emotional regulation, psychological endurance, and the ability to persevere despite challenges. (2) Interpersonal strengths, including developing and maintaining close, supportive relationships. (3) Meaning-making strengths, such as cultivating a sense of purpose, optimism, and positive interpretations of life events, which counteract self-blame and helplessness (Gonzalez-Mendez & Hamby, 2021). Intervention plans for survivors ofIPV and CV must entail resilience-building via strengthening assets and resources in these domains to reduce feelings of helplessness and increase their ability to thrive (Gonzalez-Mendez & Hamby, 2021).

Study implications

The interplay of violence exposure, financial stress, social support, and resilience illustrates the complex influence of social determinants of health and the protective mechanisms described by the Resilience Portfolio Model. These findings highlight the need for interventions adopting a holistic, multilevel approach to address structural inequities driving risk factors and individual capacities that foster resilience. Practitioners working with abused immigrant women at risk for suicidal ideation must consider the heightened vulnerability caused by lifetime exposure to violence. Intervention plans should account for violence experienced in both childhood and adulthood, along with stressors such as financial struggles and a lack of social support. Safety plans for survivors should focus on protection from abusive partners and address the risks of self-harm by incorporating comprehensive assessments for suicidal ideation and suicide attempts. Given that ideation can be a precursor to suicide attempts, clinical evaluations must include inquiries about past and present suicide attempts as part of a thorough risk assessment and safety planning process. The mental health of IPV survivors is critical, as their ability and readiness to implement safety plans depend heavily on their psychological well-being and self-efficacy (Sabri et al., 2013). Prevention and intervention efforts must be culturally informed to effectively connect with abused women at risk for suicide, especially those facing barriers to accessing resources. Such efforts should focus on resilience-building strategies, including enhanced coping skills, fostering a positive self-concept, and improving access to supportive resources. Addressing these areas can empower women to recover and thrive despite their adversities.

Limitations and strengths

Our study has several limitations, including a cross-sectional design which limits the ability to establish causality or the temporal sequence of variables. Consequently, our findings are suggestive but not demonstrative of mediation, and our observed associations are subject to reverse causation. Additionally, the reliance on self-reported data may introduce bias, as participants’ responses could be influenced by social desirability or recall bias. Another key limitation is the modest explanatory power of our final model, which accounted for only 17% of the variance in suicidal ideation. Although this might seem modest, it is important to recognize that suicidal ideation is shaped by a complex interplay of factors, many of which may not have been captured in our study model. Unmeasured variables, such as individual coping strategies or acute situational stressors, could also contribute to the unexplained variance. Finally, the use of a single-item measure for suicidal ideation represents another limitation. A single-item measure may not fully capture the complexity, intensity, severity, or variability of suicidal ideation. Therefore, the findings should be interpreted with caution, as they may not reflect the multidimensional nature of suicidal ideation (e.g., its duration and frequency).

Despite these limitations, our study has several strengths. Notably, it draws from a large, geographically diverse sample of immigrant survivors of IPV, a critically understudied population in the context of suicide research. By focusing on this vulnerable group, the study offers critical insights into the key correlates of suicidal ideation and lays a foundation for further exploration in this area.

Conclusion

This study contributes valuable insights into the correlates of suicidal ideation among immigrant women survivors of IPV with histories of CV exposure. By examining a large, diverse sample across the United States, it underscores the urgent need for comprehensive, multilevel interventions to address the compounded effects of violence exposure and mitigate suicide risk. Overall, our findings highlight the need for comprehensive interventions that (a) incorporate resilience-building strategies, particularly by improving access to resources that effectively address their mental and physical health and safety needs, (b) account for psychosocial stressors that exacerbate suicide risk, and (c) strengthen social support networks that help women overcome their experiences of CV and IPV. These findings, alongside similar research, can inform the development of multi-level prevention and intervention efforts aimed at protecting immigrant survivors of CV and IPV from self-harm and its devastating consequences. In sum, these findings emphasize the need for multi-faceted interventions that simultaneously address financial stress, enhance resilience, tackle the compounded effects of violence exposure, and promote social support systems to reduce suicide risk in vulnerable women. Future research should prioritize longitudinal designs to better examine causal relationships and incorporate additional risk and protective factors at multiple levels. Moreover, multi-item scales or continuous measures would be valuable for providing a more comprehensive understanding of suicidal ideation. Further research is also needed to assess the correlates of suicide attempts and understand the trajectory from ideation to attempts, thereby informing more targeted interventions for those at risk.

Funding

This work was supported by the National Institute on Minority Health and Health Disparities [R01MD013863 and R01MD018503]. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.

Footnotes

Disclosure statement

No potential conflict of interest was reported by the author(s).

Data availability statement

The authors confirm that the data supporting the findings of the study are available within the paper.

References

  1. Angelakis I, Gillespie EL, & Panagioti M (2019). Childhood maltreatment and adult suicidality: A comprehensive systematic review with meta-analysis. Psychological Medicine, 49(7), 1057–1078. 10.1017/S0033291718003823 [DOI] [PMC free article] [PubMed] [Google Scholar]
  2. Brignone E, Sorrentino AE, Roberts CB, & Dichter ME (2018). Suicidal ideation and behaviors among women veterans with recent exposure to intimate partner violence. General Hospital Psychiatry, 55, 60–64. 10.1016/j.genhosppsych.2018.10.006 [DOI] [PubMed] [Google Scholar]
  3. Bruffaerts R, Demyttenaere K, Borges G, Haro JM, Chiu WT, Hwang I, Karam EG, Kessler RC, Sampson N, Alonso J, Andrade LH, Angermeyer M, Benjet C, Bromet E, de Girolamo G, de Graaf R, Florescu S, Gureje O, Horiguchi I, … & Nock MK (2010). Childhood adversities as risk factors for onset and persistence of suicidal behaviour. British Journal of Psychiatry, 197(1), 20–27. 10.1192/bjp.bp.109.074716 [DOI] [PMC free article] [PubMed] [Google Scholar]
  4. Butter SE, Sabri B, Hanson GC, & Campbell JC (2024). Empowerment moderates the relationship between partner abuse and suicidal ideation for immigrant women. Journal of Psychosocial Nursing and Mental Health Services, 62(9), 19–28. 10.3928/02793695-20240308-01 [DOI] [PMC free article] [PubMed] [Google Scholar]
  5. Campbell DW, Campbell JC, Yarandi HN, O’Connor AL, Dollar E, Killion C, Sloand E, Callwood GB, Cesar NM, Hassan M, & Gary F (2016). Violence and abuse of internally displaced women survivors of the 2010 Haiti earthquake. International Journal of Public Health, 61 (8), 981–992. 10.1007/s00038-016-0895-8 [DOI] [PMC free article] [PubMed] [Google Scholar]
  6. Carr MM, Ellis JD, & Ledgerwood DM (2018). Suicidality among gambling helpline callers: A consideration of the role of financial stress and conflict. American Journal of Addictions, 27(6), 531–537. 10.1111/ajad.12787 [DOI] [PubMed] [Google Scholar]
  7. Centers for Disease Control and Prevention. (2021). Social determinants of health: Know what affects health. https://www.cdc.gov/socialdeterminants/index.htm
  8. Cho YB, & Haslam N (2010). Suicidal ideation and distress among immigrant adolescents: The role of acculturation, life stress, and social support. Journal of Youth Adolescence, 39(4), 370–379. 10.1007/s10964-009-9415-y [DOI] [PubMed] [Google Scholar]
  9. Coimbra BM, Hoeboer CM, Yik J, Mello AF, Mello MF, & Olff M (2022). Meta-analysis of the effect of racial discrimination on suicidality. Social Science & Medicine: Population Health, 20, 101283. 10.1016/j.ssmph.2022.101283 [DOI] [PMC free article] [PubMed] [Google Scholar]
  10. Coker AL, Smith PH, Thompson MP, McKeown RE, Bethea L, & Davis KE (2002). Social support protects against the negative effects of partner violence on mental health. Journal of Women’s Health & gender-Based Medicine, 11(5), 465–476. 10.1089/15246090260137644 [DOI] [PubMed] [Google Scholar]
  11. Community Solutions. (n.d.). Relationship assessment tool instructions. https://www.communitysolutionsva.org/files/E.9
  12. Corley A, & Sabri B (2021). Exploring African immigrant women’s pre- and post-migration exposures to stress and violence, sources of resilience, and psychosocial outcomes. Issues in Mental Health Nursing, 42(5), 484–494. 10.1080/01612840.2020.1814912 [DOI] [PMC free article] [PubMed] [Google Scholar]
  13. Craney TA, & Surles JG (2002). Model-dependent variance inflation factor cutoff values. Quality Engineering, 14(3), 391–403. 10.1081/QEN-120001878 [DOI] [Google Scholar]
  14. De Anda RM, & Sabczak M (2011). Underemployment among Mexican-origin women. Social Science Journal, 48(40), 622–629. 10.1016/j.soscij.2011.03.005 [DOI] [Google Scholar]
  15. De Jong GF, & Madamba AB (2002). A double disadvantage? Minority group, immigrant status, and underemployment in the United States. Social Science Quarterly, 82(1), 117–130. 10.1111/0038-4941.0001l [DOI] [Google Scholar]
  16. Devries K, Watts C, Yoshihama M, Kiss L, Schraiber LB, Deyessa N, Heise L, Durand J, Mbwambo J, Jansen H, Berhane Y, Ellsberg M, & Garcia-Moreno C (2011). Violence against women is strongly associated with suicide attempts: Evidence from the WHO multi-country study on women’s health and domestic violence against women. Social Science and Medicine, 73(1), 79–86. 10.1016/j.socscimed.2011.05.006 [DOI] [PubMed] [Google Scholar]
  17. Elbogen EB, Lanier M, Blakey SM, Wagner HR, & Tsai J (2021). Suicidal ideation and thoughts of self-harm during the COVID-19 pandemic: The role of COVID-19-related stress, social isolation, and financial strain. Depression and Anxiety, 38(7), 739–748. 10.1002/da.23162 [DOI] [PMC free article] [PubMed] [Google Scholar]
  18. Fiksenbaum L, Marjanovic Z, Greenglass E, & Garcia-Santos F (2017). Impact of economic hardship and financial threat on suicide ideation and confusion. The Journal of Psychology, 151(5), 477–495. 10.1080/00223980.2017.1335686 [DOI] [PubMed] [Google Scholar]
  19. Finkelhor D, Hamby SL, Ormrod R, & Turner H (2005). The juvenile victimization Questionnaire: Reliability, validity, and national norms. Child Abuse and Neglect, 29(4), 383–412. 10.1016/j.chiabu.2004.11.001 [DOI] [PubMed] [Google Scholar]
  20. Forte A, Trobia F, Gualtieri F, Lamis DA, Cardamone G, Giallonardo V, Fiorillo A, Girardi P, & Pompili M (2018). Suicide risk among immigrants and ethnic minorities: A literature overview. International Journal of Environmental Research and Public Health, 15 (7), 1438. 10.3390/ijerphl5071438 [DOI] [PMC free article] [PubMed] [Google Scholar]
  21. Fritz MS, & MacKinnon DP (2007). The required sample size is required to detect the mediated effect. Psychological Science, 18(3), 233–239. 10.1111/j.1467-9280.2007.01882.x [DOI] [PMC free article] [PubMed] [Google Scholar]
  22. Gagnon AJ, & Stewart DE (2014). Resilience in international migrant women following violence associated with pregnancy. Archives of Women’s Mental Health, 17(4), 303–310. 10.1007/s00737-013-0392-5 [DOI] [PubMed] [Google Scholar]
  23. Gonzalez-Mendez R, & Hamby S (2021). Identifying women’s strengths for promoting resilience after experiencing intimate partner violence. Violence & Victims, 36(1), 29–44. 10.1891/VV-D-18-00178 [DOI] [PubMed] [Google Scholar]
  24. Grych J, Hamby S, & Banyard V (2015). The resilience Portfolio model: Understanding healthy adaptation in victims of violence. Psychology of Violence, 5, 343–354. 10.1037/a0039671 [DOI] [Google Scholar]
  25. Hamby S, Grych J, & Banyard V (2018). Resilience portfolios and poly-strengths: Identifying protective factors associated with thriving after adversity. Psychology of Violence, 8(2), 172–183. 10.1037/vio0000135 [DOI] [Google Scholar]
  26. Hayes AF (2012). PROCESS: A versatile computational tool for observed variable mediation, moderation, and conditional process modeling [White paper]. http://www.athayes.com/public/process2012.pdf
  27. Hayes AF (2013). Introduction to mediation, moderation, and conditional process analysis: A regression-based approach. Guilford Press. [Google Scholar]
  28. Hosmer DW, Lemeshow S, & Sturdivant RX (2013). Applied logistic regression (3rd ed.). Wiley. [Google Scholar]
  29. Hovey JD (2000). Acculturative stress, depression, and suicidal ideation in Mexican immigrants. Cultural Diversity & Ethnic Minority Psychology, 6(2), 134–151. 10.1037/1099-9809.6.2.134 [DOI] [PubMed] [Google Scholar]
  30. Institute of Medicine. (2014). Capturing social and behavioral domains and measures in electronic health records: Phase 2. National Academies Press. [PubMed] [Google Scholar]
  31. Jiwatram-Negron T, Brooks MA, Ward M, & Meinhart M (2023). Systematic review of interventions to address suicidal behavior among people with a history of intimate partner violence: Promises and gaps across the globe. Aggression & Violent Behavior, 73, 1–15. 10.1016/j.avb.2023.101871 [DOI] [Google Scholar]
  32. Joiner TE (2005). Why people die by suicide. Harvard University Press. [Google Scholar]
  33. Joiner TE, Van Orden KA, Witte TK, Selby EA, Ribeiro JD, Lewis R, & Rudd MD (2009). Main predictions of the interpersonal-psychological theory of suicidal behavior: Empirical tests in two samples of young adults. Journal of Abnormal Psychology, 118(3), 634–646. 10.1037/a0016500 [DOI] [PMC free article] [PubMed] [Google Scholar]
  34. Kahn JR, & Pearlin LI (2006). Financial strain over the life-course and health among older adults. Journal of Health & Social Behavior, 47(1), 1–93. 10.1177/002214650604700102 [DOI] [PubMed] [Google Scholar]
  35. Kemmak AR, Nargesi S, & Saniee N (2021). Social determinant of mental health in immigrants and refugees: A systematic review. Medical Journal of the Islamic Republic of Iran, 35, 196. 10.47176/mjiri.35.196 [DOI] [PMC free article] [PubMed] [Google Scholar]
  36. Kheni N, Lee JJ, Maselka C, Murray S, & Sabri B (2024). Addressing suicide risk among immigrant women survivors of intimate partner violence. Issues in Mental Health Nursing, 45(3), 311–321. 10.1080/01612840.2023.2291685 [DOI] [PMC free article] [PubMed] [Google Scholar]
  37. Kimber A (1994). An introduction to the bootstrap [review of an introduction to the bootstrap]. Journal of the Royal Statistical Society: Series D (The Statistician), 43(4), 600. 10.2307/2348146 [DOI] [Google Scholar]
  38. Kirkbride JB, Anglin DM, Colman I, Dykxhoorn J, Jones PB, Patalay P, Pitman A, Soneson E, Steare T, Wright T, & Griffiths SL (2024). The social determinants of mental health and disorder: Evidence, prevention, and recommendations. World Psychiatry, 23(1), 58–90. 10.1002/wps.21160 [DOI] [PMC free article] [PubMed] [Google Scholar]
  39. Kleiman EM, & Riskind JH (2013). Utilized social support and self-esteem mediate the relationship between perceived social support and suicide ideation: A test of a multiple mediator model. The Crisis, 34(1), 42–49. 10.1027/0227-5910/a000159 [DOI] [PubMed] [Google Scholar]
  40. Kliem S, Krieg Y, Beller J, Brähler E, & Baier D (2021). Psychometric properties of the somatic symptom scale 8 (SSS-8) in a representative sample of German adolescents. Journal of Psychosomatic Research, 149, 110593. 10.1016/j.jpsychores.2021.110593 [DOI] [PubMed] [Google Scholar]
  41. Lacey KK, Parnell R, Drummond-Lewis SR, Wood M, & Powell Sears K (2021). Physical intimate partner violence, childhood physical abuse and mental health of U.S. Caribbean women: The interrelationship of social, contextual, and migratory influences. International Journal of Environmental Research and Public Health, 19(1), 150. 10.3390/ijerphl9010150 [DOI] [PMC free article] [PubMed] [Google Scholar]
  42. Lee YH, Liu Z, Fatori D, Bauermeister JR, Luh R, Clark CR, Bauermeister S, Brunoni AR, & Smoller JW (2022). Association with everyday discrimination with depressive symptoms and suicidal ideation during the COVID-19 pandemic in the all of us research program. JAMA Psychiatry, 79(9), 898–906. 10.1001/jamapsychiatry.2022.1973 [DOI] [PMC free article] [PubMed] [Google Scholar]
  43. Llamocca EN, Yeh HH, Miller-Matero LR, Westphal J, Frank CB, Simon GE, Owen-Smith AA, Rossom RC, Lynch FL, Beck AL, Waring SC, Lu CY, Daida YG, Fontanella CA, & Ahmedani BK (2023). Association between adverse social determinants of health and suicide death. Medical Care, 61(11), 744–749. 10.1097/MLR.0000000000001918 [DOI] [PMC free article] [PubMed] [Google Scholar]
  44. Macdonnell JA, Dastjerdi M, Bokore N, & Khanlou N (2012). Becoming resilient: Promoting the mental health and well-being of immigrant women in a Canadian context. Nursing Research & Practice, 2012, Article 576586. 10.1155/2012/576586 [DOI] [PMC free article] [PubMed] [Google Scholar]
  45. Mathieu S, Treloar A, Hawgood J, Rõss V, & Kolves K (2022). The role of unemployment, financial hardship, and economic recession on suicidal behaviors and interventions to mitigate their impact: A review. Frontiers in Public Health, 10, Article: 907052. 10.3389/fpubh.2022.907052 [DOI] [PMC free article] [PubMed] [Google Scholar]
  46. McClendon J, Chang K, Boudreaux MJ, Oltmanns TF, & Bogdan R (2021). Black-White racial health disparities in inflammation and physical health: Cumulative stress, social isolation, and health behaviors. Psychoneuroendocrinology, 131, 105251. 10.1016/j.psyneuen.2021.105251 [DOI] [PubMed] [Google Scholar]
  47. McManus S, Walby S, Barbosa EC, Appleby L, Brugha T, Bebbington PE, Cook EA, & Knipe D (2022). Intimate partner violence, suicidality, and self-harm: A probabilitysample survey of the general population in England. Lancet Psychiatry, 9(7), 574–583. 10.1016/s2215-0366(22)00151-l [DOI] [PMC free article] [PubMed] [Google Scholar]
  48. Mikrut EE (2020). The effects of interpersonal discrimination on social cognition and depressive symptoms [Master’s thesis, St. John’s University; ]. https://www.proquest.com/dissertations-theses/effects-interpersonal-discrimination-on-social/docview/2467553306/se-2 [Google Scholar]
  49. Moe CA, Villaveces A, Rivara FP, & Rowhani-Rahbar A (2022). Self-harming behavior in relation to exposure to inter-personal violence among youth and young adults in Colombia. International Journal of Injury Control and Safety Promotion, 29(1), 76–85. 10.1080/l7457300.2021.2001830 [DOI] [PMC free article] [PubMed] [Google Scholar]
  50. Moniz MV, Conde MJ, Dulce M, & Ornelas J (2024). Fostering participation of women survivors of violence in community-based advocacy and prevention networks: Contributions towards a collaborative model. Community Psychology in Global Perspective, 10(1–2), 93–115. [Google Scholar]
  51. Montesinos AH, Heinz A, Schouler-Ocak M, & Aichberger MC (2013). Precipitating and risk factors for suicidal behavior among immigrant and ethnic minority women inEurope: A systematic review. Suicidology, 4, 60–80. https://api.semanticscholar.org/CorpusID:28056282 [Google Scholar]
  52. Nagelkerke NJD (1991). A note on a general definition of the coefficient of determination. Biometrika, 78(3), 691–692. 10.1093/biomet/78.3.691 [DOI] [Google Scholar]
  53. National Academies of Sciences, Engineering, Medicine, Health, Division, Medicine Board on Population Health and Public Health Practice, & Committee on Community-Based Solutions to Promote Health Equity in the U.S. (2017). Communities in action: Pathways to health equity (Baciu A, Negussie Y, & Geller A, Eds.). National Academies Press. https://www.ncbi.nlm.nih.gov/books/NBK425845/ [PubMed] [Google Scholar]
  54. Nederhof E, & Schmidt MV (2012). Mismatch or cumulative stress: Toward an integrated hypothesis of programming effects. Physiology & Behavior, 106(5), 691–700. 10.1016/j.physbeh.2011.12.008 [DOI] [PubMed] [Google Scholar]
  55. Oh H, Stickley A, Koyanagi A, Yau R, & DeVylder JE (2018). Discrimination and suicidality amongst racial and ethnic minorities in the United States. Journal of Affective Disorders, 245, 517–523. 10.1016/j.jad.2018.11.059 [DOI] [PMC free article] [PubMed] [Google Scholar]
  56. Okechukwu CA, El Ayadi AM, Tamers SL, Sabbath EL, & Berkman L (2012). Household food insufficiency, financial strain, work-family spillover, and depressive symptoms in the working class: The work, family, and Health network study. American Journal of Public Health, 102(1), 126–133. 10.2105/ajph.2011.300323 [DOI] [PMC free article] [PubMed] [Google Scholar]
  57. Parnell RN, Lacey KK, & Wood M (2022). Coping and protective factors of mental health: An examination of African American and US Caribbean black women exposed to IPV from a nationally representative sample. International Journal of Environmental Research and Public Health, 19(22), 15343. 10.3390/ijerphl92215343 [DOI] [PMC free article] [PubMed] [Google Scholar]
  58. Pascoe EA, & Richman LS (2009). Perceived discrimination and health: A meta-analytic review. Psychological Bulletin, 135(4), 531–554. 10.1037/a0016059 [DOI] [PMC free article] [PubMed] [Google Scholar]
  59. Pate AR, DeShong HL, Stafford TWD, & Nadorff MR (2023). Impact of social supporton suicide ideation and attempts among gender minority adults. International Journal of Aging and Human Development, 96(1), 117–130. 10.1177/00914150221128972 [DOI] [PubMed] [Google Scholar]
  60. Pearlin LI, Elizabeth GM, Morton AL, & Mullan JT (1981). The stress process. Journal of Health & Social Behavior, 22(4), 337–356. 10.2307/2136676 [DOI] [PubMed] [Google Scholar]
  61. Pickover AM, Bhimji J, Sun S, Evans A, Allbaugh LJ, Dunn SE, & Kaslow NJ (2021). Neighborhood disorder, social support, and outcomes among violence-exposed African American women. Journal of Interpersonal Violence, 36(7–8), NP3716–NP3737. 10.1177/0886260518779599 [DOI] [PMC free article] [PubMed] [Google Scholar]
  62. Preacher KJ, & Kelley K (2011). Effect size measures for mediation models: Quantitative strategies for communicating indirect effects. Psychological Methods, 16(2), 93–115. 10.1037/a0022658 [DOI] [PubMed] [Google Scholar]
  63. Premji S, & Shakya Y (2017). Pathways between under/unemployment and health among racialized immigrant women in Toronto. Ethnicity & Health, 22(1), 17–35. 10.1080/13557858.2016.1180347 [DOI] [PubMed] [Google Scholar]
  64. Rasmussen V, Spangaro J, Steel Z, Briggs N, & Torok M (2023). Trajectories to suicide following intimate partner violence victimization: Using structural equation modeling to examine suicide and PTSD in female emergency department users. Journal of Family Violence, 40(4), 811–825. 10.1007/sl0896-023-00640-5 [DOI] [Google Scholar]
  65. Roley-Roberts ME, Charak R, Jeffs AJ, & Hovey JD (2021). The unique relationship between childhood sexual abuse, self-injury and suicide ideation: The mediating role of emotion dysregulation. Child Abuse Review, 32(2), e2787. 10.1002/car.2787 [DOI] [Google Scholar]
  66. Ryabov I (2024). Employment, precarious employment, and unemployment among female immigrant youth in the United States. Journal of Immigrant & Refugee Studies, 1–15. 10.1080/15562948.2024.2315144 [DOI] [Google Scholar]
  67. Sabri B, Bolyard R, McFadgion AL, Stockman JK, Lucea MB, Callwood GB, Coverston CR, & Campbell JC (2013). Intimate partner violence, depression, PTSD, and use of mental health resources among ethnically diverse black women. Social Work in Healthcare, 52(4), 351–369. 10.1080/00981389.2012.745461 [DOI] [PMC free article] [PubMed] [Google Scholar]
  68. Sabri B, Budhathoki C, McFall AM, Mehta SH, Celentano DD, Solomon SS, Srikrishnan AK, Anand S, Vasudevan CK, & Lucas GM (2023). Cumulative violence exposures among men who have sex with men living with HIV in India: Psychosocial correlates of HIV care continuum outcomes. PLOS ONE, 18(12), e0295225. 10.1371/journal.pone.0295225 [DOI] [PMC free article] [PubMed] [Google Scholar]
  69. Sabri B, Campbell JC, & Messing JT (2021). Intimate partner homicides in the United States, 2003–2013: A comparison of immigrants and nonimmigrant victims. Journal of Interpersonal Violence, 36(9–10), 4735–4757. 10.1177/0886260518792249 [DOI] [PMC free article] [PubMed] [Google Scholar]
  70. Sabri B, Hartley M, Saha J, Murray S, Glass N, & Campbell JC (2020). Effect of COVID-19 pandemic on women’s health and safety: A study of immigrant survivors of intimate partner violence. Health Care for Women International, 41(11–12), 1294–1312. 10.1080/07399332.2020.1833012 [DOI] [PMC free article] [PubMed] [Google Scholar]
  71. Sabri B, & Lee JJ (2024). Impact of COVID-19 on family violence among marginalized communities in the United States. In Sinha R & Basu P (Eds.), Families and gendered violence and Conflict. Social work (pp. 273–296). Springer. 10.1007/978-3-031-42602-5_9-1 [DOI] [Google Scholar]
  72. Sabri B, McFall AM, Solomon SS, Srikrishnan AK, Vasudevan CK, Anand S, Celentano DD, Mehta SH, Kumar S, Lucas GM, & Vermund SH (2017). Gender differences in factors related to HIV risk behaviors among people who inject drugs in North-East India. PLOS ONE, 12(1), e0169482. 10.1371/journal.pone.0169482 [DOI] [PMC free article] [PubMed] [Google Scholar]
  73. Sabri B, Nnawulezi N, Njie-Carr V, S P, Messing J, Ward-Lasher A, Alvarez C, & Campbell JC (2018). Multilevel risk and protective factors for intimate partner violence among African, Asian, and latina immigrant and refugee women: Perceptions of effective safety planning interventions. Race and Social Problems, 10(4), 348–365. 10.1007/s12552-018-9247-z [DOI] [PMC free article] [PubMed] [Google Scholar]
  74. Sachs-Ericsson N, Corsentino E, Rushing NC, & Sheffler J (2013). Early childhood abuse and late-life suicidal ideation. Aging and Mental Health, 17(4), 489–494. 10.1080/13607863.2012.758236 [DOI] [PubMed] [Google Scholar]
  75. Sher L (2019). Resilience as a focus of suicide research and prevention. Acta Psychiatrica Scandinavica, 140(2), 169–180. 10.1111/acps.13059 [DOI] [PubMed] [Google Scholar]
  76. Simons RL, Lei M-K, Beach SRH, Barr AB, Simons LG, Gibbons FX, & Philibert RA (2018). Discrimination, segregation, and chronic inflammation: Testing the weathering explanation for the poor health of black Americans. Developmental Psychology, 54(10), 1993–2006. 10.1037/dev0000511 [DOI] [PMC free article] [PubMed] [Google Scholar]
  77. Smith BW, Dalen J, Wiggins K, Tooley E, Christopher P, & Bernard J (2008). The brief resilience scale: Assessing the ability to bounce back. International Journal of Behavioral Medicine, 15(3), 194–200. 10.1080/10705500802222972 [DOI] [PubMed] [Google Scholar]
  78. Smith PH, Earp JA, & DeVellis R (1995). Measuring battering: Development of the women’s experience with battering (WEB) scale. Womens Health, 1(4), 273–288. https://pubmed.ncbi.nlm.nih.gov/9373384/ [PubMed] [Google Scholar]
  79. Southwick SM, Bonanno GA, Masten AS, Panter-Brick C, & Yehuda R (2014). Resilience definitions, theory, and challenges: Interdisciplinary perspectives. European Society for Traumatic Stress Studies. 10.3402/ejpt.v5.25338 [DOI] [PMC free article] [PubMed] [Google Scholar]
  80. Spitzer RL, Kroenke K, Williams JBW, & the Patient Health Questionnaire Primary Care Study Group. (1999). Validation and utility of a self-report version of PRIME-MD: The PHQ primary care study. JAMA: The Journal of the American Medical Association, 282(18), 1737–1744. 10.1001/jama.282.18.1737 [DOI] [PubMed] [Google Scholar]
  81. Sternberg RM, Nápoles AM, Gregorich S, Paul S, Lee KA, & Stewart AL (2016). Development of the stress of immigration survey: A field test among Mexican immigrant women. Family & Community Health, 39(1), 40–52. 10.1097/FCH.0000000000000088 [DOI] [PMC free article] [PubMed] [Google Scholar]
  82. Straus MA, Hamby SL, Boney mccoy S, & Sugarman DB (1996). The revised conflict tactics scales (CTS2): Development and preliminary psychometric data. Journal of Family Issues, 17(3), 283–316. 10.1177/019251396017003001 [DOI] [Google Scholar]
  83. Taylor SE, & Stanton AL (2007). Coping resources, coping processes, and mental health. Annual Review of Clinical Psychology, 3(1), 377–401. 10.1146/annurev.clinpsy.3.022806.091520 [DOI] [PubMed] [Google Scholar]
  84. Thompson MP, Kaslow NJ, Short LM, & Wyckoff S (2002). The mediating roles of perceived social support and resources in the self-efficacy-suicide attempts relation among African American abused women. Journal of Consulting & Clinical Psychology, 70(4), 942–949. 10.1037/0022-006X.70.4.942 [DOI] [PubMed] [Google Scholar]
  85. Ungar M (2015). Resilience and culture: The diversity of protective processes and positive adaptation. In Theron LC, Liebenberg L, & Ungar M (Eds.), Youth resilience and culture: Commonalities and complexities (pp. 37–48). Springer Science + Business Media. 10.1007/978-94-017-9415-2_3 [DOI] [Google Scholar]
  86. Villaveces A, Shankar V, Palomeque F, Padilla M, & Kress H (2022). Association between violence and mental distress, self-harm and suicidal ideation and attempts among young people in Malawi. Injury Prevention, 28(5), 446–452. 10.1136/injuryprev-2021-044510 [DOI] [PMC free article] [PubMed] [Google Scholar]
  87. Vroegindewey A, & Sabri B (2022). Using mindfulness to improve mental health outcomes of immigrant women with experiences of intimate partner violence. International Journal of Environmental Research and Public Health, 19(19), 12714. 10.3390/ijerphl91912714 [DOI] [PMC free article] [PubMed] [Google Scholar]
  88. Weitzman A, Swindle J, & Brenes-Camacho G (2024). Gendered family violence among migrants seeking international protection: A life course perspective. Social Forces, 102(3), 1004–1025. 10.1093/sf/soadl11 [DOI] [Google Scholar]
  89. Williams DR, Yu Y, Jackson JS, & Anderson NB (1997). Racial differences in physical and mental health: Socio-economic status, stress and discrimination. Journal of Health Psychology, 2(3), 335–351. 10.1177/135910539700200305 [DOI] [PubMed] [Google Scholar]
  90. Wolford-Clevenger C, & Smith PN (2017). The conditional indirect effects of suicide attempt history and psychiatric symptoms on the association between intimate partner violence and suicide ideation. Personality & Individual Differences, 106(2017), 46–51. 10.1016/j.paid.2016.10.042 [DOI] [PMC free article] [PubMed] [Google Scholar]
  91. Yule K, Houston J, & Grych J (2019). Resilience in children exposed to violence: A meta-analysis of protective factors across ecological contexts. Clinical Child & Family Psychology Review, 22, 406–431. 10.1007/sl0567-019-00293-l [DOI] [PubMed] [Google Scholar]
  92. Zapata K, & Morell M (2024, August 13). How debt affects mental health-and what can you do about it. Health. https://www.health.com/money/financial-stress-suicide-risk [Google Scholar]

Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Data Availability Statement

The authors confirm that the data supporting the findings of the study are available within the paper.

RESOURCES