A total of 30 peer-reviewed manuscripts were included in this review. Table 1 presents the descriptive characteristics and key findings from these studies.
Study Characteristics
Over half of the studies (n = 18) in this scoping review collected data from samples within the United States [2-4, 18-31]. Three articles came from Turkey [32-34], two came from South Africa [35, 36] and one article came from Germany [37], Ghana [38], Hong Kong [39], India [40], Malaysia [41], and Palestine [42]. A single article used data collected as part of a multi-country study of China, Cambodia, Papua New Guinea, and Sri Lanka [43].
Across the 30 studies, 17 unique datasets were used. Five studies used data from the Fragile Families and Child Wellbeing Study [4, 24-27, 30]. Adams and Beeble [18] and Adams et al. [3] looked at the same sample that was derived from a larger, longitudinal study evaluating a community-based advocacy intervention. Similarly, Davila et al. [22], Stylianou [44], and Cardenas et al. [21] used data collected as part of larger, longitudinal evaluation of the Moving Ahead financial empowerment program. Two studies by Voth Schrag et al. looked at data collected from a sample of women attending a community college [29, 31].
Approximately two-thirds of studies (n = 20) utilized cross-sectional designs [2, 4, 19-22, 28, 29, 31-40, 42-44]. Three studies looked at data with five time points [23, 25, 26], two had four time points [21, 24], three had three time points [3, 18, 27], and two had two time points [30, 41].
For approximately one-third of studies, participants were recruited from domestic violence organizations (n = 9); in one study participants were recruited from a domestic violence hotline [20]. Participants were also frequently recruited from their households (n = 8) and maternal health clinics or hospitals where participants had recently given birth (n = 8).
Sample
The sample size across studies ranged from 93 to 10,264 participants. All but two studies [39, 41] had entirely female samples. The race/ethnicity of the sample was not documented in 12 studies [30, 32-34, 36-43]. Six of the studies reported having a sample in which 50% or more identified as white [3, 4, 18, 28, 29, 31]. In 30% of the studies (n = 8) no one group had 50% or more of any one ethnicity in their sample [2, 19, 20, 23-27]. Two studies in the United States had entirely Latina samples [21, 22]. For almost all of the studies, the sexual orientation of the participant and/or the gender of their abuser was unclear. However, many used masculine pronouns in survey items (e.g., “he tried to prevent you from going to work/and or school” [24]), suggesting that these studies may have focused on opposite-sex relationships. Only one study clearly indicated that the abusers were all male [28] and another clearly indicated that the sample included individuals in both same and opposite-sex relationships [19].
Table 1. Study Characteristics and Key Findings
Author (Publication Year)
|
Sample &
Study Location
|
Nature of Study
|
Measurement of Economic Abuse
|
Economic Abuse Prevalence Rate
|
Outcome(s) of Interest
|
Key Finding(s)
|
Adams & Beeble (2019)
|
Women receiving services from DV and SA service agencies
(n = 94)
|
Survey data collected as part of a larger, longitudinal evaluation of an advocacy intervention
|
SEA
(28 items)
|
M = 1.91
Likert scale range: 0 (never) to 4 (quite often)
(since relationship began)
|
Quality of life
|
Within-woman change in EA was negatively associated with change in quality of life over time
|
United States
|
Adams et al. (2008)
|
Women receiving services from DV service agencies
(n = 103)
|
Cross-sectional survey focused on validating a measurement tool for EA
|
SEA
(28 items)
|
99%
(since relationship began)
|
Economic hardship
|
EA was positively associated with economic hardship
|
United States
|
Adams et al. (2015)
|
Women receiving services from DV and SA service agencies
(n = 93)
|
Survey data collected as part of a larger, longitudinal evaluation of an advocacy intervention
|
SEA
(28 items)
|
All reported some form of EA at baseline
(since relationship began)
|
Perceived financial resources
|
EA was negatively associated with baseline financial resources; Within-woman change in EA over time was negatively associated with change in financial resources
|
United States
|
Adams et al. (2020a)
|
Women receiving services from DV service agencies
(n = 248)
|
Cross-sectional survey focused on validating a measurement tool for EA
|
SEA2
(14 items)
|
96%
(at least one EA tactic since relationship began)
|
Material dependency
Outstanding debt
|
Economic restriction was positively associated with material dependence; EA was positively associated with outstanding debt
|
United States
|
Adams et al. (2020b)
|
Women who called the National DV Hotline
(n = 1,823)
|
Cross-sectional convenience sample using brief surveys
|
Three (3) items measuring coerced debt
|
52%
(lifetime coerced debt)
|
Credit damage
Financial dependence
|
Coerced debt significantly predicted credit damage and financial dependence
|
United States
|
Bulut et al. (2017)
|
Postpartum women receiving care in a family practice clinic
(n = 128)
|
Cross-sectional convenience sample using surveys
|
Not indicated
|
3%
(timeframe unclear)
|
Postpartum depression
|
No significant differences in postpartum depression among women exposed to EA compared to those who were not
|
Turkey
|
Cardenas et al. (2021)
|
Latina women receiving services from DV agencies
(n = 200)
|
Survey data collected as part of a larger, longitudinal evaluation of a financial empowerment program
|
SEA-12
(12 items)
|
M = 2.61
Likert scale range: 1 (never) to 5 (quite often)
(past 12 months)
|
Quality of life
|
Economic control was significantly and negatively associated with quality of life; however, relationship was no longer significant after controlling for economic empowerment indicators
|
United States
|
Davila et al. (2017)
|
Latina women receiving services from DV agencies
(n = 245)
|
Cross-sectional study using data collected from a longitudinal evaluation of a financial empowerment program
|
SEA-12
(12 items)
|
M = 2.60
Likert scale range: 1 (never) to 5 (quite often)
(past 12 months)
|
Depression
Anxiety
PTSD
|
EA did not lead to a significant increase in R2 for depression, anxiety, and PTSD
|
United States
|
Gibbs et al. (2018)
|
Women age 18-30 living in informal settlements
(n = 680)
|
Cross-sectional study using data collected from a longitudinal evaluation of a DV intervention
|
Four (4) items measuring EA
|
52%
(at least one EA tactic in past 12 months)
|
Depression
Suicidal ideation
|
Experiencing any EA was significantly associated with increased depression scores; experienced two or more forms of EA was significantly associated with suicidal ideation
|
South Africa
|
Gottlieb & Mahabir (2019)
|
Mothers interviewed in hospitals after giving birth
(n = 3,515)
|
Secondary analysis of longitudinal data from the FFCWB Study
|
Two (2) items measuring financial control and work/school sabotage
|
One-third of sample
(since the birth of their child)
|
Mother’s criminal justice involvement
|
Odds of experiencing criminal justice involvement were higher for mothers experiencing EA
|
United States
|
Gul et al. (2019)
|
Mothers of children referred for pediatric health services
(n = 336)
|
Cross-sectional convenience sample using surveys
|
One (1) item measuring EA
|
12.5%
(since relationship began)
|
Contentment with life
Physical or emotional abuse toward child
|
EA was not significantly associated with contentment with life nor physical or emotional abuse toward child
|
Turkey
|
Gurkan et al. (2020)
|
Pregnant women presenting to the antenatal polyclinic
(n = 370)
|
Cross-sectional convenience sample using surveys
|
One (1) item from DV Against Women Screening Form
|
25.9%
(during pregnancy)
|
Pregnancy symptoms
|
Fatigue and mental health symptom scores were higher for women experiencing EA
|
Turkey
|
Haj-Yahia (2000)
|
Married Palestinian women
(n = 1,334)
|
Cross-sectional systematic random sample using surveys
|
Two (2) items measuring financial control
|
44%
(past 12 months)
|
Self-esteem
Anxiety
Depression
|
The more EA experienced the lower their self-esteem and higher their anxiety and depression
|
Palestine
|
Huang et al. (2013)
|
Mothers interviewed in hospitals following giving birth
(n = 2,107)
|
Secondary analysis of longitudinal data collected from the FFCWB Study
|
Two (2) items measuring financial control and work/school sabotage
|
11.8% at baseline; 13.5% at Year 3;
15.1 at Year 5
(past 12 months)
|
Union formation
|
EA at Year 1 was associated with lower odds of being married or cohabiting at Year 5
|
United States
|
Huang et al. (2015)
|
Mothers interviewed in hospitals following giving birth
(n = 2,410)
|
Secondary analysis of longitudinal data collected from the FFCWB Study
|
Two (2) items measuring financial control and work/school sabotage
|
28%
(when their children was one or three years old)
|
Early delinquency
Parental involvement
Child neglect
Physical punishment
|
Experiencing EA was positively associated with child delinquency at 9 years old, as well as negatively associated with parental involvement
|
United States
|
Jewkes et al. (2003)
|
Women between the ages of 18-49 living in South Africa
(n = 1,164)
|
Cross-sectional representative sample using surveys
|
Items measuring financial control
(number of items unclear)
|
Not reported
|
Discussion of HIV in relationship
Condom use
|
Suggesting condom use in the past year was positively associated with financial abuse
|
South Africa
|
Kanougiya et al. (2021)
|
Ever-married women between ages 18-49 living in two informal settlements
(n = 4,906)
|
Cross-sectional systematic random sample
|
15 items measuring EA
|
23%
(at least one form over their lifetime)
|
Depression
Anxiety
Suicidal ideation
|
Women who experienced EA had higher odds of experiencing depression, anxiety, and suicidal ideation
|
India
|
Nicholson et al. (2018)
|
Mothers interviewed in hospitals birth
(n = 2,389)
|
Secondary analysis of longitudinal data collected from the FFCWB Study
|
Two (2) items measuring financial control and work/school sabotage
|
28%
(lifetime at Year 1 and Year 3)
|
Peer bullying
|
Presence of EA at Year1 and Year 3 was associated with higher levels of peer bullying at Year 9
|
United States
|
Postmus et al. (2012a)
|
Mothers interviewed in hospitals following giving birth
(n = 2,305)
|
Secondary analysis of longitudinal data collected from the FFCWB S
|
Two (2) items measuring financial control and work/school sabotage
|
Not reported
|
Parenting engagement
Use of spanking
Maternal depression
|
Mothers at Year 1 who experienced EA had higher odds of experiencing depression and using spanking as a form of punishment at Year 5
|
United States
|
Postmus et al. (2012b)
|
Women receiving services from DV programs
(n = 120)
|
Cross-sectional study using data collected from a longitudinal evaluation of a financial empowerment program
|
SEA
(28 items)
|
94.2%
(in current relationship or last 12 months of most recent relationship)
|
Economic self-sufficiency
|
Experiencing any form of EA compared to no EA was associated with a decrease in economic self-sufficiency
|
United States
|
Postmus et al. (2021)
|
Women between the ages of 18-49
(n = 3,105)
|
Cross-sectional study using multi-stage cluster sampling to survey participants
|
Four (4) items measuring EA
|
35.6%
(lifetime)
|
Food insecurity
Depression
|
Experiencing EA was associated with a greater likelihood of reporting food insecurity and an increase in depressive symptoms
|
Cambodia, China, Papua New Guinea,
Sri Lanka
|
Sauber et al. (2020)
|
Female DV survivors recruited through agencies providing services to survivors, as well as online
(n = 147)
|
Cross-sectional convenience sample using surveys
|
SEA-12
(12 items)
|
95%
(at least one experience in the past 6 months)
|
PTSD
Depression
Economic self-sufficiency
|
Economic control was positively associated with PTSD and negatively associated with economic self-sufficiency; Employment sabotage was positively associated with depressive symptoms
|
United States
|
Stockl & Penhale (2015)
|
Women between the ages of 16-86 who received a letter inviting them to participate
(n = 10,264)
|
Secondary analysis of cross-sectional nationally representative data collected as part of the Health, Well-Being and Personal Safety of Women in Germany study
|
Items measuring financial control (number of items unclear)
|
12% of participants 16-49;
14% 50-65; 13% 66-86
(occurred with current partner)
|
Physical health
Mental health
|
EA was associated with greater odds of experiencing gastrointestinal syndromes, psychosomatic symptoms, pelvic problems, allergies, and psychological problems in the past year, as well as problems to keep weight
|
Germany
|
Stylianou (2018)
|
Women receiving services from DV agencies
(n = 457)
|
Cross-sectional study using data collected from a longitudinal evaluation of a financial empowerment program
|
SEA-12
(12 items)
|
93%
(past 12 months)
|
Depression
|
EA was positively associated with depression
|
United States
|
Tenkorang & Owusu (2019)
|
Ever-married women aged 18 and older living within selected communities
(n = 2,289)
|
Cross-sectional study using multi-stage simple random sampling to survey participants
|
Seven (7) items measuring employment sabotage, economic exploitation, and economic depravation
|
8.5% employment sabotage;
24% economic exploitation; 42% economic deprivation
(timeframe unclear)
|
Cardiovascular health
Overall health
Psychosocial health
|
Employment sabotage was positively associated with psychosocial health issues; Economic exploitation was positively associated with worse psychosocial health and greater odds of cardiovascular diseases; Economic deprivation was positively associated with worse psychosocial health and greater odds of cardiovascular diseases
|
Ghana
|
Voth Schrag (2015)
|
Mothers interviewed in hospitals following giving birth
(n = 2,775)
|
Secondary analysis of longitudinal data collected from the FFCWB Study
|
Two (2) items measuring financial control and work/school sabotage
|
14%
(timeframe unclear)
|
Material hardship
Depression
|
Reporting EA was associated with a greater likelihood of depression and increased odds of experiencing material hardship
|
United States
|
Voth Schrag et al. (2019)
|
Women enrolled in community college
(n =435)
|
Cross-sectional study using simple random sample to survey participants
|
SEA-12
(12 items)
|
Not reported
|
PTSD
Depression
Economic hardship
|
EA was associated with increased depression, PTSD, and economic hardship
|
United States
|
Voth Schrag et al. (2020)
|
Women enrolled in community college
(n =435)
|
Cross-sectional study using simple random sample to survey participants
|
SEA-12
(12 items)
|
43.8%
(at least one form of EA in past 12 months)
|
Economic hardship
|
Higher levels of EA were associated with higher levels of economic hardship
|
United States
|
Yau et al. (2020)
|
Adults between the ages of 35-60
(n = 504)
|
Cross-sectional stratified systematic sample using surveys
|
Chinese
SEA-12
(C-SEA-12; 12 items)
|
36.5%
(past 12 months)
|
Anxiety
Depression
Psychosomatic symptoms
|
EA was associated with greater odds of anxiety, depression, and psychosomatic symptoms
|
Hong Kong
|
Yunus et al. (2016)
|
Adults aged 60 or older living within selected districts
(n = 1,927)
|
Longitudinal study using multi-stage cluster sampling strategy and administrative records
|
Adapted version of the Conflict Tactics Scale for Elder Abuse
|
8.1%
(experienced since turning age 60)
|
Mortality
|
Mortality was highest among individuals who experienced EA
|
Malaysia
|
Notes. DV = domestic violence, SA = sexual assault, EA = economic abuse, PTSD = post-traumatic stress disorder, FFCWB = Fragile Families and Child Well-Being Study, SEA = Scale of Economic Abuse
Defining and Measuring Economic Abuse
Economic abuse was not defined in seven of the studies. Although definitions of economic abuse were generally similar across the 21 studies that included them, there was some variation in the specific language used. Studies described economic abuse as a mechanism of coercive control [2, 3, 18-20, 22, 28, 40], an attitude or behavior [38], or an abusive behavior [30]. These strategies hinder a woman’s ability to acquire, use, and maintain economic resources [2-4, 18-20, 44], threatening her economic security [2, 3, 18-20, 38, 40, 43, 44], economic self-sufficiency [2, 3, 18, 19, 26, 29, 31, 38, 40, 44], and increasing financial dependence on their abusive partner [4, 22, 26, 40, 43]. Some studies described economic abuse in terms of the three constructs identified in theoretical and measurement literature [16]: economic control (n = 10), employment sabotage (n = 7), and economic exploitation (n = 4).
The most commonly used measure of economic abuse used across studies was the Scale of Economic Abuse (SEA) or one of its variations [2-4, 18]. The Scale of Economic Abuse is a 28-item measure of economic abuse that includes two subscales – economic control and economic exploitation [2]. Postmus et al. reduced the SEA from 28 items to 12 and identified a three-factor solution that included economic control, economic exploitation, and also employment sabotage [45]. This measure, named the SEA-12 was used in six of the studies [21, 22, 28, 29, 31, 44]. In addition, the SEA-12 was adapted for use in China; the Chinese SEA-12 was used in one study [39].
In 2020, Adams et al. revised the original SEA because the authors felt that the original scale did not adequately measure economic abuse as a form of coercive control and insufficiently addressed the role of the consumer credit system as part of economic abuse. This revised, 14-item scale was named the SEA2 and is used in one study [19].
Other scales used to measure economic abuse across studies included the Domestic Violence Against Women Screening Form (DVAWS) [46], used in one study [33]; a measure of domestic violence developed by Haj-Yahia (1998) for use with Arab survivors [42]; and an adapted version of the Conflict Tactics Scale for elder abuse [47] used in one study [41]. The studies that analyzed the Fragile Families and Child Wellbeing Study data measured economic abuse using two items: “He tried to prevent you from going to work and/or school” and “He withheld money, made you ask for money, or took your money” [24-27, 30]. Two studies used measures from the United Nations Multi-Country Study, which included four economic abuse tactics: preventing women from earning money, taking her money, throwing her out of the home, or spending money on alcohol, tobacco, or himself when it was needed for the household [36, 43].
The remaining studies either did not use a validated scale [20, 23, 34, 37, 38, 40] or did not indicate how economic abuse was measured [32].
Outcomes and Covariates
Outcomes. Study outcomes are presented in Table 1 and can be organized into six categories: (a) financial outcomes (e.g., financial resources, material hardship), (b) mental health (e.g., depression, anxiety), (c) physical health (e.g., mortality, pregnancy symptoms), (d) parenting and child-related outcomes (e.g., use of spanking, engagement in parent-child activities), and (f) quality of life, and (g) other (e.g., mothers’ future criminal justice involvement and union formation).
Covariates. The most commonly used covariates across studies were other forms of IPV. Physical abuse was included in approximately 65% of analyses, followed by psychological/emotional abuse (48%), and sexual abuse (28%). Other covariates tended to be demographic characteristics such as age, relationship status, education level, children (either whether the respondent had children (binary) or the number of children (continuous), and income. Race/ethnicity was included in almost every study conducted in the United States, but only in one study conducted outside of the United States (Ghana) [38]. Although used much less frequently, employment status was controlled for in 21% of studies. Only one study controlled for gender [39], as most studies included entirely female samples. Finally, five studies included no covariates [30, 32-34, 41]; this was typically due to the type of analytic strategy used.
Statistical Approaches
All but six studies used regression-based analytic methods to examine the impact of economic abuse on various outcomes. Three studies used longitudinal multilevel modeling to look at the effects of economic abuse over time [3, 18, 21]. Thirteen studies used hierarchical linear regression, ordinary least squares regression, multiple regression, or Taylor Linearization to predict the association between economic abuse and a continuous outcome variable [3, 4, 18, 22, 25-29, 31, 36, 38, 42, 44]. Eleven studies used logistic regression to predict the odds that survivors will experience a particular outcome based on experiencing economic abuse [20, 23-26, 30, 37-40, 43]. Other methods used included chi-square tests [32, 34, 41], t-tests [33, 34], and analysis of variance [42].
Findings on the Impact of Economic Abuse
Study findings are presented in Table 1. The majority of studies looked at financial and mental and physical health impacts of economic abuse, although some studies also examined parenting and child outcomes, and quality of life; a small number of studies included outcomes outside of these areas.
Financial. Economic or financial consequences of economic abuse were examined by 10 studies. Most studies found that economic abuse was associated with negative financial impacts. One longitudinal study by Adams et al. found that within-woman change in economic abuse over time was negatively associated with change in financial resources over time [3]. Four studies found that economic abuse was significantly associated with increased material [30] or economic hardship [2, 29, 31]. Voth Schrag found that depression partially mediated the association between economic abuse and material hardship [30]. Further, social support moderated the relationship between economic abuse and material hardship, such that at lower levels of economic abuse, higher levels of social support were associated with fewer material hardships [29].
Some studies looked at specific economic abuse tactics. Adams et al. found that economic abuse (measured as a scale) was not significantly associated with outstanding debt but the economic exploitation subscale was [19]. Similarly, the authors also found that the economic abuse scale was not significantly associated with material dependence, but the economic restriction subscale was. Adams et al. found that coerced debt was significantly associated with greater odds of credit damage and financial dependency (meaning survivors stayed in a relationship longer because of concerns about financially supporting themselves or their children) [20]. Experiencing any form of economic abuse [4] and economic control in particular [28] were both significantly associated with lower economic self-sufficiency.
Mental health. While there were some discrepancies, most studies found economic abuse to be associated with various facets of mental health. Depression was the most frequently examined mental health outcome. Two longitudinal studies examining the effects of economic abuse on maternal depression over time found that experiencing economic abuse was associated with greater odds of experiencing depression [27, 30]. Six of the cross-sectional studies found that economic abuse [31, 36, 39, 40, 42-44] and its associated tactics (i.e., employment sabotage) [28] was significantly and positively associated with depression. One study found no significant difference in depression among one-month postpartum women based on economic abuse exposure [32]. Three studies found economic abuse to be significantly and positively related to anxiety [39, 40, 42]; another two found economic abuse to be significantly positively related to PTSD [28, 31] and suicidal ideation [36, 40]. However, a study looking at an all-Latina sample of IPV survivors found that while economic abuse and depression were significantly positively correlated; however, economic abuse did not uniquely predict depression, anxiety, or PTSD after controlling for other forms of IPV [22]. Voth Schrag et al. found that material hardship partially mediated the relationship between economic abuse and depression, as well as economic abuse and PTSD [31].
Other components of mental health that studies looked at included self-esteem, psychosocial health, and psychological problems. Experiencing economic abuse was found to be significantly and negatively associated with self-esteem [42] and psychosocial health [38]. One study by Stockl and Penhale looked at the association between economic abuse and psychological problems by women’s age group [37]. Women between the ages of 66-86 had significantly greater odds of experiencing mild or strong psychological symptoms, whereas women between the ages of 16-49 had greater odds of experiencing strong psychological problems [37].
Physical health. Five studies looked at the association between economic abuse and physical health outcomes. One study by Stockl and Penhale looked at the association between economic abuse and several physical health outcomes by women’s age group. [37] Women between the ages of 16-49 experiencing economic abuse had greater odds of experiencing pelvic problems and difficulty keeping weight. Women between the ages of 50-65 had greater odds of experiencing psychosomatic symptoms, gastrointestinal symptoms, allergies, and difficulty keeping weight [37]. Yau et al. also found that women experiencing economic abuse had greater odds of psychosomatic symptoms [39]. Tenkorang and Owusu looked at physical health outcomes based on experiences with specific economic abuse tactics, specifically economic exploitation, employment sabotage, and economic deprivation [38]. Economic exploitation and economic deprivation were both significantly associated with cardiovascular disease and economic deprivation was associated with poorer perceptions of overall health [38]. Gurkan et al. explored the association between economic abuse and a range of pregnancy-related symptoms: gastrointestinal, reproductive, cardiovascular, mental health, neurological, dermatological, respiratory, urinary, and tiredness or fatigue [33]. Both fatigue and mental health symptom scores were significantly higher for women experiencing economic abuse [33]. Lastly, Yunus et al. looked at the associations between IPV and mortality among a sample of older adults and found that proportions of death were highest for survivors of economic abuse, although the number of mortalities in the sample was low overall [41].
Parenting and child outcomes. Some studies looked at associations between experiencing economic abuse and parenting behaviors and child-related outcomes. Three of these studies were longitudinal in nature and were, therefore, able to examine the impacts of economic abuse over time. However, a limitation of these analyses is that they all used the same dataset (i.e., Fragile Families). As part of the Fragile Families studies, mothers were surveyed in hospitals post-child birth (baseline) and then again when their children were ages 1, 3, 5, and 9, referred to as Y1, Y3, Y5, and Y9, respectively. Researchers found that mothers’ who experienced economic abuse in Y1 and Y3 had lower levels of parental involvement with their children and a greater likelihood of neglecting their child at Y5 [25]. Further, this economic abuse and neglect were associated with greater child delinquency in Y9; this relationship was partially mediated by parenting behaviors (i.e., physical punishment, parental involvement, child neglect). Postmus et al. (2012a) found that mother’s economic abuse at Y1 and Y3 had greater odds of using spanking to discipline child at Y5, but economic abuse was not significantly associated with engagement in parent-child activities in Y5. Nicholson et al. found that economic abuse at Y1 and Y3 were also associated with higher levels of peer bullying for children in Y9; this relationship was mediated by parental involvement and this was moderated by race/ethnicity [26]. The results showed that increased parental involvement was associated with increased peer bullying for boys [26]. One cross-sectional study looked at associations between mother’s experiencing economic abuse and their perpetration of child abuse, but found that economic abuse was not significantly associated with emotional or physical child abuse perpetration [34].
Quality of life. While a cross-sectional study conducted by Gul et al. did not find economic abuse to be significantly associated with survivors’ contentment with life score [34], a longitudinal study by Adams and Beeble found economic abuse was significantly, negatively associated with change in the quality of life over time [18]. A second longitudinal study also looked at the association between economic abuse; economic control was initially significantly and negatively associated with quality of life, however, the relationship was no longer significant after controlling for other indicators of financial empowerment (e.g., financial knowledge, economic self-sufficiency) [21].
Other. Four studies examined outcomes that did not fit well in the other thematic areas previously discussed. One longitudinal study using Fragile Families data looked at the association between experiencing economic abuse in Y1, Y3, and Y5 and mother’s criminal justice involvement, defined as whether mother was charged with a crime or booked by police for anything other than a minor traffic violation in the last four years, at Y9; odds of experiencing criminal justice involvement were higher for mother’s experiencing economic abuse when controlling for all other forms of IPV [23]. Another longitudinal study using Fragile Families data looked at the effect that economic abuse at Y1 had on union formation at Y5; mothers experiencing economic abuse had lower odds of being married or cohabiting with baby’s father at Y5 [24]. Jewkes et al. found that economic abuse was not significantly associated with women’s discussion of HIV with their partner, however, women who suggested condom use in the past year were more likely to be financially abused [35]. Finally, Postmus et al. found that economic abuse was indirectly associated with food insecurity, as the relationship was fully mediated by depression [43].