Improving Quality of Life Among Latina Intimate Partner Violence Survivors Through Economic Empowerment

Abstract

This study examined the relationship between (1) quality of life and forms of intimate partner violence (IPV) (i.e., psychological abuse, physical violence, sexual violence, and types of economic abuse), and (2) quality of life and economic empowerment among Latina IPV survivors. The authors used data from the Moving Ahead financial literacy program evaluation (n = 200). Nested random-effects models were conducted. Findings indicated that psychological abuse and economic control were significantly and negatively associated with quality of life. Economic empowerment (i.e., financial knowledge, economic self-efficacy, and economic self-sufficiency) was significantly and positively related to Latinas’ quality of life. Financial strain was inversely associated with Latina’s quality of life. These findings highlight the importance of identifying strategies for increasing the overall well-being of Latina IPV survivors. Economic empowerment interventions can be an effective mechanism for improving their quality of life. As such, domestic violence organizations should include economic empowerment as part of the services offered to survivors.

Keywords

intimate partner violence Latinas economic empowerment quality of life economic abuse

Introduction

The World Health Organization (2020) defines quality of life as an individual’s perception of their life in relation to their goals and concerns. Quality of life, or the feeling of satisfaction or contentment with one’s life, is also referred to as subjective well-being. There is a positive association between quality of life and a range of health outcomes (De Neve et al., 2013), including better overall health (Chida & Steptoe, 2008) and longer life expectancy (Diener & Chan, 2011). Additionally, economic empowerment has shown a positive impact on individuals’ overall well-being (Chhay, 2011). Favorable perceptions of quality of life also improve social relationships, as individuals are more likely to be interested in social activities (Whelan & Zelenski, 2012) and engaged in community prosocial behaviors (Oishi et al., 2007). Interestingly, research suggests that there is no need to have a high positive quality of life all of the time to experience its beneficial effects (Diener et al., 2017); rather, having positive perceptions of subjective well-being most of the time is sufficient.

Despite the favorable outcomes of a positive quality of life, little research is available on how to improve quality of life among survivors of intimate partner violence (IPV). Given the long-term consequences of IPV on women’s health and social functioning (Bonomi et al., 2006), there is an urgent need to identify factors that can increase survivors’ positive perceptions of life. Of particular importance is the improvement of quality of life among Latina IPV survivors because they experience health and social disparities, putting them at a disproportionate disadvantage as they strive to enhance their well-being (National Center for Health Statistics, 2016). As such many have called to increase the evaluation of IPV services’ effectiveness among diverse survivors (e.g., Cardenas, 2020). This article addresses this need by examining the relationship between quality of life and economic empowerment over time among a sample of Latina IPV survivors.

Intimate Partner Violence and Quality of Life

IPV is a pervasive issue, with more than one in three women experiencing physical violence, sexual violence, and/or stalking and nearly half (47.1%) experiencing psychological abuse from a partner at some point in their life (Smith et al., 2017). IPV significantly impairs women’s quality of life (Leung et al., 2005). Tavoli et al. (2016) surveyed pregnant women who experienced physical or psychological partner abuse and found that both types of IPV were associated with lower perceived quality of life. The association between physical and psychological abuse and quality of life was also explored among women who sought help for IPV and women who did not (Alsaker et al., 2018). Results demonstrated the expected negative association between the experiences of psychological and physical abuse and quality of life for both groups of women. Interestingly, Alsaker et al. (2018) also reported that quality of life was lower among women who sought help for the violence as compared with women who did not. In another study, Asadi et al. (2017) explored not only the psychological and physical domains of IPV, but also sexual violence by an intimate partner. Their results support the inverse correlation between the three types of IPV and quality of life.

Only a few studies, however, have investigated the effects of IPV on quality of life over time. Beeble et al. (2009) tested the impact of psychological and physical IPV on quality of life over two years among women who sought help for the abuse. Their findings supported previous research on the negative relationship between psychological abuse and quality of life but not between physical violence and quality of life. Adams and Beeble (2019) further studied the impact of economic abuse over four months on women’s quality of life while controlling for psychological and physical violence. Cross-sectionally, they found that when women’s experiences of economic abuse were high, their perceived quality of life was low, and vice-versa. However, this statistically significant relationship was not detected over time.

Economic Empowerment and Quality of Life

According to Cattaneo & Chapman (2010), empowerment is “…an iterative process in which a person who lacks power sets a personally meaningful goal oriented toward increasing power, takes action toward the goal, and observes and reflects on the impact of this action, drawing on his or her evolving self-efficacy, knowledge, and competence related to the goal” (p. 647). Economic empowerment, as discussed in this article, is conceptualized as a form of psychological empowerment at the individual level (Johnson, 2020) and refers to the knowledge, skills, and confidence to manage one’s financial well-being (Postmus et al., 2013). Postmus (2010) conceptualized economic empowerment in the context of IPV. Her model includes measures of financial knowledge, economic self-efficacy, and economic self-sufficiency aimed at improving survivors’ financial stability. Additionally, the consideration of financial strain in assessments of economic empowerment is also essential since it plays a key role in one’s economic situation (Hetling et al., 2015). According to Morrison Gutman et al. (2005), financial strain “gives psychological meaning to the experience of economic difficulties” (p. 428) and considers the stress associated with financial insecurity (Hetling et al., 2015).

Postmus’ (2010) model also situates economic empowerment in a larger scheme, influencing individuals’ well-being. Indeed, women’s economic empowerment is central to improving their status in society (United Nations Entity for Gender Equality and the Empowerment of Women, 2018) and, thus, their quality of life. Studies have demonstrated the positive impact of women’s economic empowerment on their decision-making powers (Liliane & Mbabazi, 2015) and overall well-being (Chhay, 2011). Although the exploration between the measures of economic empowerment and quality of life among women has been limited, one cross-national study found that the financial literacy gender-gap and gender equality at the societal level were associated (Grohmann et al., 2016). Specifically, Grohmann et al. (2016) reported no financial literacy gender-gap existed in countries with high gender equality. On the other hand, some studies have found an increased in women’s economic empowerment to be an IPV risk factor (Eggers del Campo & Steinert, 2020). Men may exert violence to regain their status in the relationship if they feel women’s increased financial power threatens their authority. An increase in economic assets may also motivate abusive partners to use violence to control women’s financial resources (Postmus et al., 2016a). As such, economic empowerment may increase the risk for victimization in certain contexts, leading to a decreased quality of life.

Despite evidence supporting the effects of economic empowerment on quality of life, its impact among IPV survivors, particularly Latinas, is not documented in the literature. To date, no known longitudinal studies have investigated the effects of economic empowerment on quality of life in a sample of IPV survivors. This paucity in the literature is concerning given the importance of evidence-based practices. Additionally, women who experience IPV are more likely to endure health problems, greatly impacting their quality of life (Loxton et al., 2017). Latinas are notably at higher risk of experiencing the detrimental consequences of IPV due to the additional barriers they may face when leaving an abusive relationship (Postmus et al., 2014).

In a review of the Latinx literature, Klevens (2007) found that believing that the abuse should be tolerated, fear of deportation, unawareness of resources, and low English language proficiency were factors associated with staying in an abusive relationship. Cultural values such as familism, placing a substantial value on family unity (Murdaugh et al., 2004), and collectivism (i.e., prioritizing group over personal well-being) (Ohbuchi et al., 1999) may also prevent Latinas from leaving an abusive partner. In focus groups with Spanish-speaking Latinas, Ahrens et al. (2010) found that endorsing cultural norms of familism, keeping family matters to themselves, and traditional gender roles decreased their participants’ ability to identify and disclose IPV experiences. Latinas may also encounter additional barriers to increasing their economic autonomy, making them more dependent on their abuser. For example, immigrant Latinas may encounter discrimination based on their race/ethnicity and gender when trying to access work opportunities (Eggerth et al., 2012). Lack of legal status aggravates their situation due to limited access to financial institutions and an economic safety net (Drever & Blue, 2011). Consequently, Latinas may experience prolonged IPV, leading to more severe and persistent sequelae (Bent-Goodey, 2007). Indeed, Latina IPV survivors have been found to have higher rates of poor physical and mental health than non-Latina IPV survivors (Bonomi et al., 2009).

Given the damaging effects of IPV on Latina survivors’ health and social functioning, this study sought to answer the following research questions: (1) What forms of IPV are associated with perceived quality of life among Latina IPV survivors over time? (2) What is the association between economic empowerment factors and quality of life among Latina IPV survivors over time? Based on the available literature, we expected all forms of IPV to be associated with a decreased in perceived quality of life. We also hypothesized economic empowerment factors to be associated with an increase in perceived quality of life.

Methods

This study used data collected as part of a longitudinal randomized controlled trial evaluating the financial literacy program Moving Ahead, developed by The Allstate Foundation and the National Network to End Domestic Violence (2009) for IPV survivors. Survivors were recruited from 14 domestic violence organizations across seven states and Puerto Rico. Survivors randomly assigned to the control group received treatment as usual and survivors assigned to the treatment group participated in the five-session financial literacy program.

Survivors had the option of completing the interview in either English or Spanish. The interview instrument was translated from English to Spanish; researchers of both Puerto Rican and Mexican descent reviewed the Spanish survey to ensure an accurate translation across dialects. To ensure content validity, other Latina researchers, representing countries in Central and South America, then translated the Spanish survey back into English.

Interviews, lasting approximately one hour, were conducted at four time points across 14 months. The baseline interview (T1) was conducted in-person at the domestic violence organization before the start of the intervention. Follow-up interviews were conducted at two months (T2), eight months (T3), and fourteen months (T4) after completion of the program, either in-person or by phone as per the survivor’s preference. To maintain retention over time, a graduated incentive structure was used along with monthly contact made by the research team in a safe manner, dictated by the survivor. Institutional review board approval was obtained.

Participants.

A total of 456 IPV survivors participated in the study at T1. Of those, 211 participants did not identify as Latina or Hispanic and were therefore excluded from the sample for this study. An additional 46 participants were removed because they only completed one interview (T1). The final analytical sample contained data from 200 IPV survivors.

Overall, the majority of women in the analytic sample were between the ages of 30 and 49 and over one-quarter (27%) had no formal education. Approximately two-thirds of participants were born in the United States. Additionally, half of the sample was unemployed, more than half (52%) had an annual income of $10,000 or less, and more than half of participants (59%) reported receiving services. Descriptive statistics for the analytic sample are shown in Table 1.

Table 1.

Descriptive Statistics at Baseline (n = 200).

	% or Mean
Age
21–29 years old	20
30–39 years old	41
40–49 years old	32
50–59 years old	8
Education
No formal education	27
High school or less	50
Some college	17
College graduate	4
Graduate degree or some graduate education	3
U.S. born
No	35
Yes	64
Employment status
Unemployed	50
Part time	27
Full time	23
Annual income
$10,000 or less	52
Between $10,001 and $15,000	28
Between $15,001 and $25,000	10
Between $25,001 to $35,000	8
More than $35,000	3
Received services	59

Measures

Quality of life.

The dependent variable, quality of life, was assessed using the Quality of Life Scale (Bybee & Sullivan, 2005), which is an adapted version of Andrews and Withey’s (1976) Scale of Well-Being. This nine-item scale captures positive emotional health and well-being and has been validated with IPV survivors. Participants were asked to indicate how they were feeling in the past month on a range of items representing well-being using a seven-point Likert scale ranging from 1 (terrible) to 7 (extremely pleased). Examples of items include, “How do you feel about your life as a whole?” and “How do you feel about your emotional and psychological well-being?” An exploratory factor analysis was conducted during which one item was removed from the scale because it was not applicable to all survivors: “How do you feel about the responsibilities you have for members of your family?” Removing this item made minor improvements to the overall total variance explained (50.62 to 54.36), as well as the alpha (.867 to .870). As such, the final measure included eight items with good internal consistency (α = .87). Responses were averaged across all items.

Financial knowledge.

Financial knowledge was measured using the Financial Knowledge Scale (Postmus et al., 2013a), developed as part of the evaluation of the Moving Ahead financial literacy program. Therefore all 15-items were based on curriculum content. Participants were asked to indicate the extent to which they agreed or disagreed with a series of financial knowledge questions by indicating 1 (strongly disagree) to 5 (strongly agree). Their responses were averaged across all items to create the overall scale. Examples of items included, “I know how to improve my credit rating” and “I know how to plan for retirement and the different types of plans available.” The scale had excellent internal consistency (α = .89).

Economic self-efficacy.

Economic self-efficacy was measured using the Scale of Economic Self-Efficacy (Hoge et al., 2017). Participants indicated the extent to which they agreed or disagreed with statements related to their confidence in engaging in financial behaviors by indicating 1 (strongly disagree) to 5 (strongly agree). Responses to all 10 items were averaged to create an overall scale. Examples of items include, “If I am in financial trouble, I can usually think of something to do” and “No matter what financial problem comes my way, I’m usually able to handle it.” This scale demonstrated good internal reliability (α = .87).

Economic self-sufficiency.

Economic self-sufficiency was measured using the Scale of Financial Security-10 (SFS-10; Hetling et al., 2016). The SFS-10 is a 10-item scale that measures one’s ability to manage daily financial needs and the ability to have discretionary funds. Participants were asked to indicate the frequency in which they accomplished financially related tasks in the past one month by indicating 1 (not at all) to 5 (all of the time). Examples of items include, “Pay your own way without borrowing from friends” and “Stay on a budget.” Responses were averaged across all items to create an overall scale. This scale demonstrated good internal reliability (α = .85).

Financial strain.

Financial strain was measured using the Financial Strain Survey (Aldana & Liljenquist, 1998). This 18-item scale measures five dimensions of financial strain: poor financial education (three items), poor relationships (four items), physical symptoms (four items), poor credit card use (three items), and being unable to meet financial obligations (four items). Participants were asked to indicate how often they experienced a range of financial challenges over the past month by indicating 1 (never) to 5 (always). Participants’ responses were averaged across all items to create the overall scale. Examples of items include, “I find it difficult to pay my bills” and “There are disagreements about money in my home.” This scale demonstrated adequate internal reliability (α = .77).

Abuse experiences. Abuse experiences were measured using two scales. IPV victimization was measured using the Abusive Behavior Inventory—Revised (ABI-R; Postmus et al., 2016b). The ABI-R is a 25-item scale with three subscales: psychological abuse (13 items), physical abuse (9 items), and sexual abuse (3 items). Participants were asked to indicate the frequency in which they experienced a series of abusive tactics over the past year by indicating 1 (never) to 5 (very often). In subsequent interviews, participants were asked about abuse experiences since the previous interview. Examples of items include the following: “Said things to scare you,” “Pushed, grabbed, or shoved you,” and “Pressured you to have sex in a way you didn’t like.” The scale demonstrated excellent reliability (α = .94) and the subscales had good internal reliability with psychological (α = .92), physical (α = .92), and sexual (α = .82). Participants’ responses were averaged across all 25 items to create an overall scale.

Economic abuse was measured using the Scale of Economic Abuse-12 (SEA-12; Postmus et al., 2016a). The SEA-12 was used to examine the frequency in which participants experienced economic abuse in the past year. Response options ranged from 1 (never) to 5 (quite often). The 12-item scale has three subscales: economic control (five items), economic exploitation (three items), and employment sabotage (four items). Examples of items include the following: “Make important financial decisions without talking with you about it first” and “Demand that you quit your job.” The scale demonstrated good internal reliability (α = .88), as did the subscales with economic control (α = .81), employment sabotage (α = .83), and economic exploitation (α = .81). Responses for all 12 items from the SEA-12 were averaged to create an overall scale.

Control variables.

Control variables included in the regression models were markers of socioeconomic status (i.e., employment status and income) and emotional health. For employment status, survivors were asked to indicate whether they were currently employed full-time, part-time, or were unemployed. Participants were also asked to indicate their average annual income range.

Mental health indicators were also included in the model because mental health is associated with quality of life. PTSD was measured using revised questions from the National Comorbidity Survey (1992). Participants were asked to indicate how often they experienced a series of nine PTSD symptoms in the past one month from 1 (never) to 4 (very often). Anxiety was measured using the Generalized Anxiety Disorder-7 (Spitzer et al., 2006). Participants were asked to indicate how often they experienced a series of seven anxiety disorder symptoms in the past two weeks from 1 (not at all) to 4 (nearly every day). Lastly, depression was measured using the Center for Epidemiologic Studies—Depressed Mood Scale (CES-D; Frazier, 1977). Participants were asked to indicate how often they experienced a series of 20 depression symptoms in the past one week from 1 (less than one day) to 4 (5–7 days).

We also included services received from the recruiting domestic violence organization. Participants were asked whether they received emergency or short-term housing, transitional or long-term housing, counseling, employment assistance, and legal advocacy. Due to small sample size, we recoded as receiving services those who answered “yes” to at least one of these questions, and as not receiving services to those who answer “no” to all of the questions.

Analytical Approach

First, we examined descriptive statistics for the analytic sample at baseline. A repeated measures analysis of variance (ANOVA) was also performed to examine differences across time for the main variables of interest. We used the Greenhouse-Geisser correction because the Mauchly’s Test of Sphericity indicated that the assumption of sphericity had been violated (results not shown; Keselman et al., 1980). We proceeded with post hoc Tukey testing to localize the significant effects. Data was analyzed using Stata version 16. This study then used multiple imputation techniques to impute values for all variables with missing data, using Stata statistical software’s Imputation by Chained Equations program (Johnson & Young, 2011). Stata’s MIM command was used to analyze the imputed data sets and present results. The results were similar to those obtained when excluding imputed data (results not shown).

To examine the impact of variables that vary over time, while accounting for unobserved heterogeneity, we evaluated both unit and time-specific fixed effects and found that unit-specific was much more significant. Thus, our analyses were conducted exploring unit-specific effects. Fixed effects (FE) are known to remove shared and systematic (time-invariant) characteristics so that assessment of the effect of independent variables on the outcome variable is possible (Rabe-Hesketh & Skrondal, 2008). FE allows for the correlation between the unobserved effects and the explanatory variables, making unbiased estimates. However, FE is not suitable if the unobserved heterogeneity among individuals is uncorrelated with the independent variables. Random effects (RE) become a more efficient estimator since it assumes that the unobserved heterogeneity among individuals is uncorrelated with the independent variables.

To determine which analysis was appropriate, we constructed a random-effects unit specific model and performed the Hausman model specification test. The Hausman test evaluates whether the unobserved effects are correlated with the independent variables (Amini et al., 2012). That is, we tested whether the difference between the coefficients estimated by the FE and RE estimator is statistically significant. Results from this test suggested that no significant differences between the FE and RE models. Thus, we used generalized least squares (GLS) RE models to answer our research questions. We used nested models to test the effects of our main variables on quality of life. To isolate the unique effects of economic empowerment (as measured through financial knowledge, economic self-efficacy, and economic self-sufficiency), RE models controlled for various measures of participants’ characteristics. We added indicators of socioeconomic status (employment status and income), emotional health (PTSD, anxiety, and depression) and services received. Models used the robust standard errors option to reduce the risk of type 1 error, producing more conservative estimates.

Because these data were collected as part of a randomized controlled trial, it was necessary to ensure that study findings were not influenced by random assignment. To test this, random assignment was initially included in the models. Although initial results indicated a statistically significant association, we removed it from the models because it became statistically nonsignificant after the indicators of economic empowerment were added. This might indicate a mediation relationship since the control group was not involved in the financial literacy program. Nonetheless, such relationship is out of the scope of this study thus, no further exploration was conducted. Further, the analytic method chosen (i.e., RE models) is effective for controlling the effects of unobserved factors that are systematic, thereby eliminating potential sources of bias related to other personal characteristics associated with the variables of interest (Allison, 2005). As such, the influence that the intervention might have caused will still be controlled for even though random assignment was not included in the model.

Results

Table 2 provides descriptive statistics on key variables of interest for the analytical sample at baseline. On average, on a scale of 1-7, Latina IPV survivors’ quality of life was slightly above midpoint (M = 4.07, SD = 1.12). On a scale from 1 to 5, participants reported an average of 2.58 (SD = 0.80), 3.20 (SD = .071), 2.42 (SD = 0.84), and 2.84 (SD = 0.63) on financial knowledge, economic self-efficacy, economic self-sufficiency, and financial strain, respectively. Participants experienced psychological abuse (M = 3.47, SD = 1.00) and economic control (M = 3.11, SD = 1.17) more frequently than other types of IPV. PTSD, anxiety, and depression were all measured on a scale ranging from 1 to 4, with 4 indicating greater symptomology for the mental health issue. Women reported an average of 2.46 (SD = 0.73) for posttraumatic stress disorder, 2.34 (SD = 0.89) for anxiety and 2.24 (SD = 0.69) for depression.

Table 2.

Descriptive Statistics of Key Variables at Baseline (n = 200).

	M	SD
Quality of life (scale of 1–7)	4.07	1.12
Financial knowledge	2.58	0.80
Economic self-efficacy	3.20	0.71
Economic self-sufficiency	2.42	0.84
Financial strain	2.84	0.63
IPV victimization	2.93	0.92
Psychological abuse	3.47	1.00
Physical violence	2.26	1.06
Sexual violence	2.24	1.21
Economic abuse	2.61	0.96
Employment sabotage	1.99	1.08
Economic control	3.11	1.17
Economic exploitation	2.58	1.34
Post-traumatic stress disorder	2.46	0.73
Anxiety	2.34	0.89
Depression	2.24	0.69

The repeated measures ANOVAs demonstrated that there were statistically significant differences in mean scores across time on all of the variables of interest. Participants showed a significant increase in their scores of quality of life, F(3,485) = 59.59, p < .001, ω² = .70; financial knowledge, F(3,485) = 114.64, p < .001, ω² = .72; economic self-efficacy, F(3,485) = 19.22, p < .001, ω² = .66; and economic self-sufficiency, F(3,485) = 47.85, p < .001; ω² = .64. A significant decrease in mean scores was found for financial strain, F(3,485) = 83.29, p < .001, ω² = .71; IPV victimization, F(3,481) = 190.15, p < .001, ω² = .68; and economic abuse, F(3,482) = 127.30, p < .001; ω² = .62. Post hoc comparisons revealed that participants had significantly different scores in Time 2, Time 3, and Time 4 when compared to Time 1, in all the variables. Participants had significantly different scores in Time 4 compared to Time 2 in quality of life, economic self-sufficiency, financial strain, and abusive behaviors and significantly different scores in Time 4 than in Time 3 in abusive behaviors. Table 3 presents the means and F values for the seven ANOVAs. It also shows the effect size (ω²) and post hoc test results.

Table 3.

Means and F Values for ANOVAs Between Main Variables and Time.

		Time
	1	2	3	4	F	ω ²
Quality of life	4.07	4.81^{^}	4.99^{^}	5.17^{^+}	59.59***	0.70
Financial literature	2.58	3.46^{^}	3.44^{^}	3.50^{^}	114.64***	0.72
Economic self-efficacy	3.20	3.49^{^}	3.52^{^}	3.59^{^}	19.22***	0.66
Economic self-sufficiency	2.42	2.83^{^}	3.04^{^}	3.08^{^+}	47.85***	0.64
Financial strain	2.84	2.37^{^}	2.25^{^}	2.15^{^+}	83.29***	0.71
Abusive behaviors	2.93	1.57^{^}	1.53^{^}	1.30^{^+#}	190.15***	0.68
Economic abuse	2.60	1.49^{^}	1.47^{^}	1.28^{^}	127.30***	0.62

Note. ***p < .001. ω² = omega squared (effect size). Tukey’s tests used for post hoc comparisons; ^: significantly different than Time 1; +: significantly different than Time 2; #: significantly different than Time 3; all cases p < .05.

Results for the RE models examining forms of IPV and economic empowerment on Latinas’ quality of life are displayed in Table 4. In Model 1, only psychological abuse and economic control were found to be significantly and negatively associated with their quality of life. Specifically, results suggested a decrease of .27 in participants’ quality of life for each unit increase in psychological abuse (p < .01). Each unit increase in participants’ experience of economic control was associated with a .13 decrease in their quality of life (p < .05). Interestingly, after accounting for the economic empowerment factors, psychological abuse and economic control were no longer significantly associated with participants’ quality of life.

Table 4.

Nested RE Models of IPV and Economic Empowerment on Quality of Life (n = 200).

	Model 1	Model 2	Model 3	Model 4
	Forms of IPV	Economic Empowerment	SES variables	All Variables
Psychological abuse	–0.27***	–0.07	–0.08	–0.08
	(0.07)	(0.06)	(0.06)	(0.05)
Physical violence	0.14	0.10	0.11	0.14
	(0.10)	(0.07)	(0.07)	(0.06)
Sexual violence	0.03	–0.02	–0.04	0.00
	(0.07)	(0.05)	(0.05)	(0.04)
Employment sabotage	–0.03	–0.01	–0.01	–0.05
	(0.08)	(0.06)	(0.06)	(0.06)
Economic control	–0.13**	–0.07	–0.06	–0.05
	(0.06)	(0.05)	(0.05)	(0.04)
Economic exploitation	–0.05	0.02	0.02	0.05
	(0.05)	(0.04)	(0.04)	(0.03)
Financial knowledge		0.09**	0.10**	0.12***
		(0.04)	(0.04)	(0.04)
Economic self-efficacy		0.30***	0.30***	0.21***
		(0.08)	(0.08)	(0.07)
Economic self-sufficiency		0.26***	0.24***	0.17***
		(0.06)	(0.06)	(0.06)
Financial strain		–0.64***	–0.63***	–0.35***
		(0.07)	(0.07)	(0.07)
Employment status (ref. = unemployed)
Part time			0.13*	0.10
			(0.08)	(0.07)
Full time			0.17*	0.10
			(0.09)	(0.09)
Annual income (ref. less than $10,000)
Between $10,001 and $15,000			0.01	–0.04
			(0.08)	(0.06)
Between $15,001 and $25,000			–0.09	–0.11
			(0.10)	(0.10)
Between $25,001 and $35,000			–0.30**	–0.33***
			(0.13)	(0.11)
More than $35,000			0.00	0.00
			(0.23)	(0.17)
Post-traumatic stress disorder				–0.28***
				(0.07)
Anxiety				–0.15**
				(0.07)
Depression				–0.36***
				(0.08)
Services received				0.09
				(0.06)
Constant	5.43***	4.39***	4.30***	5.58***
	(0.12)	(0.36)	(0.36)	(0.35)
R ²	0.14	0.53	0.54	0.66
Joint f test	15.78***	72.40***	49.55***	71.64***
Hausman test	χ² = 30.31; p = .17

Note. Robust standard errors in parentheses.

***p < .01. **p < .05. *p < .1.

Findings from the full model (Model 4) suggested that factors related to economic empowerment (i.e., financial knowledge, economic self-efficacy, and economic self-sufficiency) were significantly related to Latinas’ quality of life, even after controlling for employment status, annual income, emotional health (PTSD, anxiety, and depression), and services received. Holding all else constant, each unit increase in Latinas’ financial knowledge was associated with a .12 increase in their quality of life (p < .01). Each unit increase in participants’ economic self-efficacy and economic self-sufficiency was associated with a .21 (p < .01) and .17 (p < .01) increase, respectively, in their quality of life. Results also indicated a .35 decrease in Latinas’ quality of life for each unit increase in their financial strain (p < .01).

Some control variables in the full model were significantly associated with quality of life. Interestingly, reporting an income between $25,001 and $35,000 was associated with a .30 decrease on quality of life compared with those reporting less than $10,000. Finally, emotional health variables were significantly associated with quality of life. This model was significant and explained 66% of the variation in Latinas’ quality of life.

Discussion

Quality of life has been found to influence a range of health outcomes (De Neve et al., 2013) and improve social relationships (Whelan & Zelenski, 2012). Not surprisingly, IPV is associated with decreased quality of life (e.g., Asadi et al., 2017). Yet, few studies examine ways to increase quality of life among IPV survivors, broadly, as well as Latina survivors more specifically. Although all IPV survivors experience increased vulnerability and face a number of barriers to leaving, Latinas face additional challenges as a result of the health and social disparities they already face (Bent-Goodey, 2007; Bonomi et al., 2009). As such, the improvement of quality of life among Latina IPV survivors is particularly important.

This study sought to answer two research questions: (1) What forms of IPV are associated with perceived quality of life among Latina IPV survivors over time? (2) What is the association between economic empowerment factors and quality of life among Latina IPV survivors over time? By exploring this area, this study adds to the knowledge base by building on what is already known about the associations between IPV, quality of life, and economic empowerment, as well as expanding it. This study is among the first to provide scientific evidence of the effectiveness of economic empowerment among Latina IPV survivors.

Our findings showed that psychological abuse and economic control were both significantly and negatively associated with quality of life, partially supporting our hypothesis. While previous studies have found this association between psychological abuse and quality of life (Tavoli et al., 2016), only one study has looked at the relationship between economic abuse and quality of life (Adams & Beeble, 2019). Given that economic control is associated with quality of life, it is important to identify strategies for increasing subjective well-being for Latina IPV survivors. Our results also indicated that other forms of IPV were not significantly related to quality of life. It might be that psychological abuse and economic control possess unique characteristics impacting survivors’ feeling of satisfaction with their life. Future research should explore the mechanisms through which these forms of IPV affect subjective well-being.

This study’s findings suggested that economic empowerment factors (i.e., financial knowledge, economic self-efficacy, and economic self-sufficiency) and financial strain were significantly related to Latinas’ quality of life, even after controlling for employment status, annual income, and emotional health. This finding supports our hypothesis and builds on previous research, which showed that economic empowerment is important for increasing women’s role in society through increased decision-making power (Liliane & Mbabazi, 2015), greater gender equality (Grohmann et al., 2016), and therefore by extension their overall well-being and quality of life. Further, when controlling for economic empowerment factors, psychological violence and economic control were no longer significantly associated with quality of life. This might be because abusive partners may use tactics that diminish women’s confidence and ability to become economic self-sufficient (Postmus et al., 2012). Thus, it is possible that leaving an abusive relationship improves women’s confidence and skills or that women who decide to leave an abusive partner have already experienced an increase in their confidence and abilities. As such, it might be that survivors’ perceived quality of life improves the longer they are away from their abuser. Despite this potential improvement, IPV survivors need and benefit from formal services to enhance their overall well-being. Future research should examine the mechanism through which indicators of economic empowerment affect quality of life among IPV survivors and the extent of such relationship. Taken together, our study findings suggest that economic empowerment interventions can be effective at increasing survivors’ quality of life.

Economic empowerment interventions range in scope and objective. While some, like individual development accounts, microfinance programs, and resource transfer programs aim to increase survivors’ access to tangible resources, other economic empowerment interventions aim to increase survivors’ ability to take control over their financial situation by increasing financial knowledge, economic self-efficacy, and economic self-sufficiency. This study looked at the latter and found these three components effective at increasing Latina IPV survivors’ quality of life over time, even after controlling for other markers of financial support. This suggests that interventions that engage these components can be effective at increasing Latina survivors’ ability to take control of their financial situation, despite their financial circumstances. However, we should also consider the potential unintended consequence of economic empowerment. Although all forms of abuse decreased over time in our study, we cannot discard the possibility that it might increase the risk for IPV in future implementations. Thus, we recommend caution when incorporating interventions aimed at increasing IPV survivors’ autonomy. Such efforts should assess the context-specific characteristics of participants and ensure the appropriate physical, emotional, and financial safety planning strategies are in place.

Latina survivors may be particularly vulnerable to prolonged IPV exposure and its subsequent health consequences as a result of structural factors such as discrimination and poverty, and cultural factors (Bent-Goodley, 2007). Cultural factors may include traditional beliefs around gender norms and marriage, familism, and the desire to maintain secrecy about marital issues (Ahrens et al., 2010). For immigrant Latina survivors, help seeking may be further hindered due to fears of deportation, a lack of understanding of the service systems in the country of relocation, language barriers, and social isolation (Alvarez & Fedock, 2018). Immigration status may also impose barriers to accessing work opportunities (Eggerth et al., 2012), financial institutions, and services to improve their economic situation (Drever & Blue, 2011). As such, Latina survivors may benefit from community-based economic empowerment programs like financial education because they provide knowledge around financial management and planning behaviors, while also providing an opportunity to consider how to implement these strategies safely within the context of their family situations. To strengthen the impact of such programs, however, macrolevel interventions are necessary. Broadening labor market opportunities and access to financial institutions will enhance and maintain Latinas’ economic empowerment. Future research should examine what components of economic empowerment interventions Latina survivors found to be most useful and explore the multiplicative effects of micro and macro level economic empowerment interventions.

Although not specifically focused on Latina survivors, research has found that quality of life is also associated with stronger personal relationships and prosocial behaviors (Oishi et al., 2007; Whelan & Zelenski, 2012). Social support networks are particularly important to IPV survivors, as such supports can help to mitigate the mental health impacts of IPV, and connect survivors with financial opportunities, such as jobs, which can be crucial to supporting survivors as they navigate their abusive relationships and keep themselves safe (Rothman et al., 2007).

Limitations

The findings presented must be considered in light of certain limitations. First, this sample mostly comprised of low-income Latina IPV survivors who sought help for the violence from a domestic violence organization. It is unclear how these results would generalize to other samples and subsets of Latina IPV survivors. Additional research is needed to examine the relationship between economic empowerment and quality of life among other Latina and non-Latina populations. Second, we did not address the causal direction of the association between economic empowerment and quality of life. It is possible that a positive quality of life increases the economic empowerment of Latina IPV survivors or that effects exist in both directions. However, given the dearth of literature on the association between economic empowerment and quality of life among Latina IPV survivors, we first examined whether such a relationship existed and demonstrated how these variables changed together across time. Further research should address the issue of directionality. Finally, limitations related to the methods are worth noting. Confounds to the relationship between economic empowerment and quality of life that did change over time and were not measured in the data are possible—for example, changes in the employment status of other household members. Additionally, because we used secondary data, we were limited to the measures of economic empowerment and quality of life found in the original study. Further research should explore the association between other indicators of economic empowerment and quality of life. Although this study used a widely accepted conceptualization of quality of life (i.e., WHO’s definition), there might be a difference between perceived quality of life and other measures of quality of life that needs further investigation.

Conclusion

This study sheds light on the relationship between economic empowerment and quality of life over time among a sample of Latina survivors of IPV. Such findings provide a roadmap to improving survivors’ quality of life by improving their financial knowledge, economic self-efficacy (i.e., confidence), and economic self-sufficiency (i.e., skills) as well as decreasing their financial strain. Domestic violence organizations should include economic empowerment as part of the services offered to survivors which, in turn, will improve their quality of life. Additionally, service providers should consider such programs for Latina survivors, ensuring these programs are offered in a culturally appropriate and language specific manner.

Footnotes

Declaration of Conflicting Interests

Funding

The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This project was supported by The Allstate Foundation.

ORCID iDs

Iris Cardenas

Laura Johnson

Judy L. Postmus

Author Biographies

Iris Cardenas, LSW, is a PhD candidate in the school of social work at Rutgers University and graduate research assistant at the Center on Violence Against Women at Rutgers. Her research focuses on intimate partner violence among diverse individuals, specifically with the Latinx population. Her research interest also includes increasing help-seeking behaviors of IPV survivors and validation of IPV related scales.

Laura Johnson, MSW, PhD, is an assistant professor in the school of social work at Temple University. Her research is to support the health of survivors of interpersonal violence, and their safety and empowerment, through the development and adaptation of measures and interventions. She is also interested in community-based evaluations, and research focused on intervention implementation and strengthening interagency collaborations.

Judy L. Postmus, PhD, ACSW, is the dean of the School of Social Work at the University of Maryland, Baltimore. Her research is on physical, sexual, and economic victimization experiences of women including an examination of strategies to economically empower survivors. She has given many local, national, and international presentations on the impact of policies and interventions for survivors of violence.

References

Adams

, & Beeble

(2019). Intimate partner violence and psychological well-being: Examining the effect of economic abuse on women’s quality of life. Psychology of Violence , 9(5), 517–525. https://doi.org/10.1037/vio0000174

Ahrens

, Rios-Mandel

, Isas

, & Del Carmen Lopez

(2010). Talking about interpersonal violence: Cultural influences on Latinas’ identification and disclosure of sexual assault and intimate partner violence. Psychological Trauma: Theory, Research, Practice, and Policy , 2(4), 284–295. https://doi.org/10.1037/a0018605

Aldana

S. G.

, & Liljenquist

(1998). Validity and reliability of a financial strain survey. Financial Counseling and Planning , 9(2), 11–19.

Allison

P. D.

(2005). Fixed effects regression methods for longitudinal data using SAS. SAS Institute, Inc.

Allstate Foundation and the National Network to End Domestic Violence (NNEDV). (2009). Moving ahead through financial management . The Allstate Foundation.

Alsaker

, Moen

, Morken

, & Baste

(2018). Intimate partner violence associated with low quality of life—A cross-sectional study. BMC Women’s Health , 18(1), 148. https://doi.org/10.1186/s12905-018-0638-5

Alvarez

, & Fedock

(2018). Addressing intimate partner violence with Latina women: A call for research. Trauma, Violence, & Abuse , 19(4), 488–493. https://doi.org/10.1177/1524838016669508

Amini

, Delgado

M. S.

, Henderson

D. J.

, & Parmeter

C. F.

(2012). Fixed vs random: The Hausman test four decades later. In Essays in honor of Jerry Hausman . Emerald Group Publishing Limited.

Andrews

, & Withey

(1976). Social indicators of well-being: Americans’ perceptions of life quality . Plenum Press.

10.

Asadi

, Mirghafourvand

, Yavarikia

, Mohammad-Alizadeh-Charandabi

, & Nikan

(2017). Domestic violence and its relationship with quality of life in Iranian women of reproductive age. Journal of Family Violence , 32(4), 453–46l. https://doi.org/10.1007/s10896-016-9832-0

11.

Beeble

, Bybee

, Sullivan

, & Adams

(2009). Main, mediating, and moderating effects of social support on the well-being of survivors of intimate partner violence across 2 years. Journal of Consulting and Clinical Psychology , 77(4), 718–729. https://doi.org/10.1037/a0016140

12.

Bent- Goodley

T. B.

(2007). Health disparities and violence against women: Why and how cultural and societal influences matter. Trauma, Violence, & Abuse , 8(2), 90–104. https://doi.org/10.1177/1524838007301160

13.

Bonomi

, Anderson

, Cannon

, Slesnick

, & Rodriguez

(2009). Intimate partner violence in Latina and non-Latina women. American Journal of Preventive Medicine , 36(1), 43–48.e1. https://doi.org/10.1016/j.amepre.2008.09.027

14.

Bonomi

, Thompson

, Anderson

, Reid

, Carrell

, Dimer

, & Rivara

(2006). Intimate partner violence and women’s physical, mental, and social functioning. American Journal of Preventive Medicine , 30(6), 458–466. https://doi.org/10.1016/j.amepre.2006.01.015

15.

Bybee

, & Sullivan

C. M.

(2005). Predicting re-victimization of battered women 3 years after exiting a shelter program. American Journal of Community Psychology , 36(1–2), 85–96. https://doi.org/10.1007/s10464-005-6234-5

16.

Cattaneo

L. B.

, & Chapman

A. R.

(2010). The process of empowerment: A model for use in research and practice. American Psychologist , 65(7), 646–659. https://doi.org/10.1037/a0018854

17.

Cardenas

(2020). Advancing intersectionality approaches in intimate partner violence research: A social justice approach. Journal of Ethnic and Cultural Diversity in Social Work . https://doi.org/10.1080/15313204.2020.1855494

18.

Chhay

(2011). Women’s economic empowerment through microfinance in Cambodia. Development in Practice , 21(8), 1122–1137. https://doi.org/10.1080/09614524.2011.606891

19.

Chida

, & Steptoe

(2008). Positive psychological well-being and mortality: A quantitative review of prospective observational studies. Psychosomatic Medicine , 70(7), 741–756. https://doi.org/10.1097/PSY.0b013e31818105ba

20.

De Neve

J. E.

, Diener

, Tay

, & Xuereb

(2013). The objective benefits of subjective well-being. In Helliwell

, Layard

, & Sachs

, (Eds.), World happiness report 2013 . UN Sustainable Development Solutions Network.

21.

Diener

, & Chan

(2011). Happy people live longer: Subjective well-being contributes to health and longevity. Applied Psychology: Health and Well-Being , 3(1), 1–43. https://doi.org/10.1111/j.1758-0854.2010.01045.x

22.

Diener

, Heintzelman

, Kushlev

, Tay

, Wirtz

, Lutes

, & Oishi

(2017). Findings all psychologists should know from the new science on subjective well-being. Canadian Psychology/Psychologie Canadienne , 58(2), 87–104. https://doi.org/10.1037/cap0000063

23.

Drever

A. I.

, & Blue

S. A.

(2011). Surviving sin papeles in post-Katrina New Orleans: An exploration of the challenges facing undocumented Latino immigrants in new and re-emerging Latino destinations. Population, Space and Place , 17(1), 89–102.

24.

Eggers del Campo

, & Steinert J.

(2020). The effect of female economic empowerment interventions on the risk of intimate partner violence: A systematic review and meta-analysis. Trauma, Violence, & Abuse . Advance online publication. https://doi.org/10.1177/1524838020976088

25.

Eggerth

D. E.

, DeLaney

S. C.

, Flynn

M. A.

, & Jacobson

C. J.

(2012). Work experiences of Latina immigrants: A qualitative study. Journal of Career Development , 39(1), 13–30. https://doi.org/10.1177/0894845311417130

26.

Frazier

E. L.

(1977). Center for epidemiologic studies—depressed mood scale (CES-D).

27.

Grohmann

, Hübler

, Kouwenberg

R. R. P.

, & Menkhoff

(October 2016). Financial literacy: Thai middle class women do not lag behind (DIW Berlin Discussion Paper No. 1615). German Institute for Economic Research.

28.

Hetling

, Hoge

G. L.

, & Postmus

J. L.

(2016). What is economic self-sufficiency? Validating a measurement scale for policy, practice, and research. Journal of Poverty , 20(2), 214–235. https://doi.org/10.1080/10875549.2015.1094768

29.

Hetling

, Stylianou

, & Postmus

(2015). Measuring financial strain in the lives of survivors of intimate partner violence. Journal of Interpersonal Violence , 30(6), 1046–1064. https://doi.org/10.1177/0886260514539758

30.

Hoge

G. L.

, Stylianou

A. M.

, Hetling

, & Postmus

J. L.

(2017). Developing and validating the scale of economic self-efficacy. Journal of Interpersonal Violence , 35(15–16), 3011–3033. https://doi.org/10.1177%2F0886260517706761

31.

Johnson

, & Young

(2011). Toward best practices in analyzing datasets with missing data: Comparisons and recommendations. Journal of Marriage and Family , 73(5), 926–945. https://doi.org/10.1111/j.1741-3737.2011.00861.x

32.

Johnson

(2020). Increasing financial empowerment among survivors of intimate partner violence: A growth curve analysis. American Journal of Community Psychology . https://doi.org/10.1002/ajcp.12491

33.

Keselman

H. J.

, Rogan

J. C.

, Mendoza

J. L.

, & Breen

L. J.

(1980). Testing the validity conditions of repeated measures F tests. Psychological Bulletin , 87(3), 479–481.

34.

Klevens

(2007). An overview of intimate partner violence among Latinos. Violence Against Women , 13(2), 111–122. https://doi.org/10.1177/1077801206296979

35.

Leung

, Leung

, Ng

, & Ho

(2005). Quality of life of victims of intimate partner violence. International Journal of Gynecology & Obstetrics , 90(3), 258–262. https://doi.org/10.1016/j.ijgo.2005.05.010

36.

Liliane

U. K.

, & Mbabazi

(2015). The impact of women economic empowerment projects on their socio-economic development in Rwanda: The case of Agaseke project. European Journal of Business and Social Sciences , 4(06), 59–87.

37.

Loxton

, Dolja-Gore

, Anderson

A. E.

, & Townsend

(2017). Intimate partner violence adversely impacts health over 16 years and across generations: A longitudinal cohort study. PloS One , 12(6), Article e0178138. https://doi.org/10.1371/journal.pone.0178138

38.

Morrison Gutman

, McLoyd

V. C.

, & Tokoyawa

(2005). Financial strain, neighborhood stress, parenting behaviors, and adolescent adjustment in urban African American families. Journal of Research on Adolescence , 15(4), 425–449.

39.

Murdaugh

, Hunt

, Sowell

, & Santana

(2004). Domestic violence in Hispanics in the Southeastern United States: A survey and needs analysis. Journal of Family Violence , 19(2), 107−115. https://doi.org/10.1023/B:JOFV.0000019841.58748.51

40.

National Center for Health Statistics. (2016). Health, United States, 2015: With special feature on racial and ethnic health disparities . National Center for Health Statistics. https://www.ncbi.nlm.nih.gov/books/NBK367640/

41.

Ohbuchi

, Fukushima

, & Tedeschi

J. T.

(1999). Cultural values in conflict management: Goal orientation, goal attainment, and tactical decision. Journal of Cross-Cultural Psychology , 30(1), 51–71.

42.

Oishi

, Diener

, & Lucas

(2007). The optimum level of well-being can people be too happy? Perspectives on Psychological Science , 2(4), 346–360. https://doi.org/10.1111/j.1745-6916.2007.00048.x

43.

Postmus

J. L.

(2010 October). Economic empowerment of domestic violence survivors. In VAWnet. Applied Research Forum, National Resource Center on Domestic Violence.

44.

Postmus

J. L.

, Hetling

, & Hoge

G. L.

(2013a). Evaluating the impact of the “Moving Ahead curriculum: Through Financial Management” A randomized control study: Final report—Survivor interview data . Rutgers University, School of Social Work, Center on Violence Against Women & Children.

45.

Postmus

J. L.

, Mcmahon

, Silva-Martinez

, & Warrener

(2014). Exploring the challenges faced by Latinas experiencing intimate partner violence. Affilia , 29(4), 462–477. https://doi.org/10.1177/0886109914522628

46.

Postmus

J. L.

, Plummer

S. B.

, McMahon

, Murshid

N. S.

, & Kim

M. S.

(2012). Understanding economic abuse in the lives of survivors. Journal of Interpersonal Violence , 27(3), 411–430. https://doi.org/10.1177/0886260511421669

47.

Postmus

J. L.

, Plummer

S. B.

, McMahon

, & Zurlo

(2013). Financial literacy: Building economic empowerment with survivors of violence. Journal of Family and Economic Issues , 34(3), 275–284. https://doi.org/10.1007/s10834-012-9330-3

48.

Postmus

J. L.

, Plummer

S. B.

, & Stylianou

A. M.

(2016a). Measuring economic abuse in the lives of survivors: Revising the Scale of Economic Abuse. Violence Against Women , 22(6), 692–703https://doi.org/10.1177/1077801215610012

49.

Postmus

J. L.

, Stylianou

A. M.

, & McMahon

(2016b). The abusive behavior inventory—Revised. Journal of Interpersonal Violence , 31(17), 2867–2888. https://doi.org/10.1177%2F0886260515581882

50.

Rabe- Hesketh

, & Skrondal

(2008). Multilevel and longitudinal modeling using Stata . STATA press.

51.

Rothman

E. F.

, Hathaway

, Stidsen

, & de Vries

H. F.

(2007). How employment helps female victims of intimate partner violence: A qualitative study. Journal of Occupational Health Psychology , 12(2), 136–143. https://doi.org/10.1037/1076-8998.12.2.136

52.

Smith

S. G.

, Chen

, Basile

K. C.

, Gilbert

L. K.

, Merrick

M. T.

, Patel

, Walling

, & Jain

(2017). The National Intimate Partner and Sexual Violence Survey (NISVS): 2010-2012 state report . National Center for Injury Prevention and Control, Centers for Disease Control and Prevention.

53.

Spitzer

R. L.

, Kroenke

, Williams

J. B.

, & Löwe

(2006). A brief measure for assessing generalized anxiety disorder: the GAD-7. Archives of Internal Medicine , 166(10), 1092–1097. https://doi.org/10.1001/archinte.166.10.1092

54.

Tavoli

, Tavoli

, Amirpour

, Hosseini

, Montazeri

, & Tavoli

(2016). Quality of life in women who were exposed to domestic violence during pregnancy. BMC Pregnancy and Childbirth , 16(19), 1–7. https://doi.org/10.1186/s12884-016-0810-6

55.

United Nations Entity for Gender Equality and the Empowerment of Women. (2018). Facts and figures: Economic empowerment . https://www.unwomen.org/en/what-we-do/economic-empowerment/facts-and-figures

56.

Whelan

, & Zelenski

(2012). Experimental evidence that positive moods cause sociability. Social Psychological and Personality Science , 3(4), 430–437. https://doi.org/10.1177/1948550611425194

57.

World Health Organization. (2020). Health statistics and information systems . https://www.who.int/healthinfo/survey/whoqol-qualityoflife/en/