What Matters When Examining Attitudes of Economic Abuse? Gender and Student Status as Predictors of Blaming, Minimizing, and Excusing Economic Abuse.

Extensive research has been conducted regarding attitudes toward various types and patterns of violence against intimate partners, but there is a lack of research on attitudes toward economic abuse in general. In the current study, we examined attitudes toward economic abuse by examining how participants blamed the victim, minimized the economic abuse, and excused the perpetrator in hypothetical scenarios. We also examined two characteristics of participants: binary gender differences (i.e., woman, man) and differences between students and non-students. Participants (N = 239) were recruited via the SONA system of a private university (n = 120) and via Amazon's Mechanical Turk (n = 119). Participants were randomly assigned to read one of two hypothetical scenarios to evaluate how scenario condition (i.e., victim employed, victim unemployed), participant gender, and participant student status predicted attitudes toward economic abuse involving blaming, minimizing, and excusing. Moreover, we also examined ambivalent sexism and gender role ideology as predictors. A 2 (scenario condition: job, no job) × 2 (participant gender: woman, man) × 2 (student status: college student, non-college student) MANOVA indicated main effects of both participant gender and participant student status. Follow-up ANOVAs revealed that men were more likely to blame victims, minimize the economic abuse, and excuse perpetrators compared to women. Additionally, students were less likely to minimize the economic abuse compared to non-students. Moreover, both hostile sexism and traditional gender role ideology were significant predictors. Implications of the findings and future directions for researchers are discussed.

Introduction

Economic abuse is a type of intimate partner violence (IPV) in which methods of economic authority are used by perpetrators, and it is a phenomenon that affects victims internationally (Voth Schrag et al., 2019). Economic abuse has been described as the “tactics that hinder economic self-sufficiency and harm economic self-efficacy” (Voth Schrag et al., 2019, p. 222). Adams and Beeble (2019) add that economic abuse involves controlling a partner’s access to economic resources and compromising their financial stability, and Postmus et al. (2016) noted that economic abuse should be treated as its own unique form of abuse. In a study involving women who were victims of IPV, approximately 94% of the participants reported that they endured economic abuse (Postmus et al., 2012). Similarly, Stylianou (2018a) found that 93% of female victims of IPV experienced some form of economic abuse. Many of the studies conducted on this topic have been primarily focused on women in comparison to men (Postmus et al., 2020), and it has been found that women are more likely to be victims of economic abuse compared to men (Kutin et al., 2017). However, due to the limited information in the current literature, further research is needed to examine the attitudes individuals have toward economic abuse within intimate partner relationships.

Economic abuse can take many different forms including the overtaking of one’s funds and assets, the jeopardization of a partner’s source of income, and the misuse of another’s financial resources (Postmus et al., 2016; Voth Schrag et al., 2019). Other forms of economic abuse include hindering a partner’s ability to acquire monetary resources and threatening their economic stability (Adams & Beeble, 2019). The Revised Scale of Economic Abuse-12 instrument developed by Postmus et al. (2016) outlines specific examples of economic abuse among couples. Such examples include demanding that a partner asks for consent to use any funds, keeping track of a partner’s expenses, withholding important financial knowledge, pressuring a partner to work less or resign from their job, missing payments on bills under a partner’s name on purpose, and accumulating debt under a partner’s name (Postmus et al., 2016).

Some of the lasting impacts of economic abuse include psychological damage and detrimental effects on an individual’s economic well-being (Antai et al., 2014). Stylianou (2018a) discovered that economic abuse was linked to higher rates of depression among female victims, and Antai et al. (2014) found that both economic and psychological abuse were strong predictors of psychological distress and suicide attempts among women in the Philippines. Additionally, researchers found that economic abuse was correlated with substandard psychosocial health and higher rates of cardiovascular conditions in women in Ghana (Tenkorang & Owusu, 2019). Regarding economic well-being, Voth Schrag (2015) concluded that experiencing economic abuse makes it harder for victims to sustain economic stability. Economic abuse was also found to be linked to instability in employment and housing (Voth Schrag et al., 2019), and victims of economic abuse are likely to have more economic dependency on their partners and increased stress levels about finances (Antai et al., 2014).

Previous Research

Since researchers have previously found that participants’ gender identity and sex assigned at birth have been linked to their perceptions of violence against women, (e.g., An, 2021; Doran et al., 2019; Keller & Honea, 2016), it is possible that these gender and sex effects are present for attitudes toward economic abuse specifically. Researchers have consistently found that men reported higher levels of victim blaming attitudes than women in cases of intimate partner violence against women (IPVAW; Keller & Honea, 2016; Martín-Fernández et al., 2018; Yamawaki et al., 2018). Researchers have also found that women were less likely to blame the victim of IPVAW compared to men (Ivert et al., 2018). Furthermore, a lack of understanding about the nature and consequences of IPVAW was related to the tendency to sustain victim blaming attitudes toward violence in intimate partner relationships (Doran & Hutchinson, 2017).

In addition to victim blaming, both gender and sex assigned at birth also play a role in minimizing the seriousness of IPV. When participants were given vignettes that depicted women victims of IPV, males indicated a higher likelihood of disregarding the vignettes as IPV compared to females (An, 2021). Moreover, El Abani and Pourmehdi (2021) found that men were more likely to belittle domestic violence against women (DVAW) compared to women, and they found a positive association between low levels of education and a tendency to perceive DVAW as a personal issue. In cases of male victims, however, minimization of IPV was even greater. Violence perpetrated against males was linked with a perception of lower seriousness and higher justification (Erickson et al., 2017; Komazec & Farmer, 2021). Findings by Yamawaki et al. (2018) also aligned with these results and supported the findings that male victims were blamed more than female victims and male victims’ IPV was minimized more compared to female victims’ IPV; however, males still blamed the victim and minimized the abuse more than females.

Doran et al. (2019) demonstrated that male nursing students showed more violence-tolerant views in a case of DVAW compared to female students. Furthermore, these nursing students were more likely to justify and excuse domestic violence (DV) than midwifery students, and this underlines a possible link between a greater exposure to DV, a better understanding of DV, and a lower likelihood to excuse DV (Doran et al., 2019). Moreover, similar to victim blaming and minimizing attitudes, media reports presented cases of DVAW in a way that excused perpetrators of IPV (Lee & Wong, 2020; Leung, 2019; Uibu, 2021).

Employment versus Unemployment of Victims

Previous researchers have noted that one factor of economic abuse is employment sabotage (Adams et al., 2008; Postmus et al., 2012; Stylianou et al., 2013). Indeed, Stylianou and colleagues (2013) found that economic abuse victims highly endorsed an item of employment sabotage (i.e., “Do things to keep you from going to your job.”). As such, these victims commonly experienced their perpetrators preventing them from employment (Stylianou et al., 2013). Therefore, it is important to examine individuals’ attitudes toward economic abuse victims based on the victim’s employment status.

When women experience economic abuse by their intimate partners, they are economically dependent on their abuser (Adams et al., 2008). These victims have insufficient income and employment history, and this makes it difficult to leave their abuser because they have few alternatives (Adams et al., 2015). Due to the difficulty of leaving an abuser, many victims stay in economically abusive relationships, and this is commonly due to a lack of financial independence (Estrellado & Loh, 2014; Kim & Gray, 2008; Meyer, 2012; Rhodes & McKenzie, 1998). Additionally, even when victims of IPV do not encounter physical or sexual violence in a relationship, victims have reported that they still experienced having their finances controlled (Meyer, 2012). Therefore, economic abuse can be present in the absence of other forms of IPV.

Researchers have found that women being unemployed is a risk factor for them experiencing IPV (Sen & Bolsoy, 2017). However, other researchers have found that women being employed is also a risk factor for them experiencing IPV (Castro et al., 2017). Swanberg and Logan (2005) noted that both employed and unemployed women are at risk of IPV. While there are contradictory findings related to women’s employment, economic abuse can ultimately happen to women regardless of employment status. However, there may be differences in the attitudes that individuals have toward a woman who is experiencing economic abuse based on her employment status. It is possible that individuals will blame, minimize, and excuse differently based on a woman who is employed versus unemployed.

Predictors of Attitudes Toward IPV

One variable that has been linked to attitudes of IPV is ambivalent sexism. Ambivalent sexism theory posits that the maintenance of gender inequality in relationships between men and women is based on two different but complementary ideologies in relation to gender roles—hostile sexism and benevolent sexism (Glick & Fiske, 1996). Hostile sexism consists of insulting beliefs about women and justifying men’s dominant status and their control over women (Salomon et al., 2020) and helps justify treating women poorly when women deviate from traditional gender roles (Eldabli et al., 2022). On the contrary, benevolent sexism rewards women who fulfill traditional gender roles, and it consists of the belief that women need protection (Salomon et al., 2020). Benevolent sexism ultimately rewards women with protection once they have conformed to traditional gender roles (Eldabli et al., 2022). In general, ambivalent sexism has been repeatedly shown to be associated with aggression and violence perpetration. In a study examining men’s family-based aggression during the COVID-19 pandemic, Overall et al. (2021) found that men higher in hostile sexism were more aggressive toward their intimate partners when they experienced low power during interactions with their partners. The association of benevolent sexism and aggression revealed different results based on gender: men higher in benevolent sexism exhibited lower aggressive parenting while women higher in benevolent sexism exhibited higher aggressive parenting (Overall et al., 2021). In terms of IPV perpetration specifically, Renzetti et al. (2018) found that hostile sexism was positively associated with IPV perpetration.

Yamawaki et al. (2009) found that individuals higher in benevolent sexism had greater tendencies to blame victims of rape, and Notestine et al. (2017) found that ambivalent sexism was a significant predictor of blaming battered females. This may be because people who endorse benevolent sexism see women in need of protection when their actions align with stereotypical gender roles. Since keywords such as drinking and partying at night associated with the female rape victim in this previous study indicated a violation of traditional gender roles of women, participants tended to reverse the belief about women needing protection and blamed the victim as a result (Yamawaki et al., 2009). Furthermore, in a study about stalking victims, Yamawaki et al. (2020) found that both hostile and benevolent sexism were predictors of victim blaming and that hostile sexism was a predictor of minimizing the seriousness of the stalking. Additionally, researchers found that victim blaming was positively related to ambivalent sexism—particularly hostile sexism—in the context of IPV (Martín-Fernández et al., 2018). Overall, these findings indicate that ambivalent sexism is related to victim blaming (i.e., a dependent variable in the present study).

Another variable found related to IPV attitudes is gender role ideology. Two categories of gender role ideology are traditional gender roles and egalitarian gender roles. People who endorse traditional gender roles believe that there are distinct roles between men and women in relationships. Specifically, the belief is that men are breadwinners while women are homemakers, and individuals who do not live up to their traditional roles are seen as violating their respective gender roles (Gowda & Rodriguez, 2019). Egalitarian gender roles refer to interactions between men and women in which the power distinctions are less pronounced (Gowda & Rodriguez, 2019). Previous researchers have found that traditional gender role ideology was strongly associated with both DV and IPV (Erickson et al., 2017; Morash et al., 2000; Yamawaki et al., 2009, 2018; Yoshihama et al., 2020). Morash and colleagues (2000) examined wife abuse in Mexican-descent families and found that wife abuse was related to adherence to traditional gender roles of the husband.

Furthermore, Yoshihama et al. (2020) found that higher support for traditional gender roles was significantly related to a higher tendency of emotional aggression perpetration for men but not for women. In general, adherence to traditional gender roles is harmful to both male and female victims within the context of IPV perpetration (Yamawaki et al., 2018). Specifically, Erickson et al. (2017) found that traditional gender role ideology and a history of IPV perpetration predicted a higher likelihood of justifying IPV perpetrators’ actions. Within the scope of the present topic of IPV, a higher level of traditional gender role ideology has been found to be associated with a higher tendency to blame victims, minimize abuse, and excuse perpetrators of IPV (Yamawaki et al., 2009). Despite a myriad of previous findings showing the significance of traditional gender role ideology and violence perpetration, perceptions of outsiders on the victim and perpetrator of an economically abusive situation have not previously been studied. Indeed, when compared to IPV or other related physical abuse, economic abuse is more difficult to identify in relationships (Postmus et al., 2020).

Both ambivalent sexism and traditional gender role ideology can be viewed under feminist theory because “in male-dominated societies, patriarchal relationships are widely supported by stereotypical or traditional gender-role attitudes or expectations” (Herzog, 2007, p. 224). Feminist theory posits that the oppression of women and patriarchal privilege are primary causes of violence against women (e.g., IPV; McPhail et al., 2007). Ambivalent sexism and traditional gender role ideology both posit that men are dominant while women are submissive. Additionally, as reviewed by Herzog (2007), there is a positive relationship between having permissive attitudes toward IPV and a traditional gender role ideology. Because of this commonly found positive relationship, permissive attitudes toward IPV can include blaming the victim, minimizing the economic abuse, and excusing the perpetrator. Accordingly, based on the previous research discussed, ambivalent sexism and traditional gender role ideology may be predictor of these permissive attitudes specifically regarding economic abuse.

Purpose of Study

While there are many negative consequences that economic abuse victims experience, research related to economic abuse is scarce (Anitha, 2019; Stylianou, 2018a). Researchers have found that women are more likely to leave their perpetrators when they have a job (Borchers et al., 2016). However, according to Schneider et al. (2016), unemployment and economic stress in the family increase men's controlling attitudes toward their partners. As such, victim’s job status, including unemployment, may be a factor in others’ attitudes toward economic abuse and its victims. Therefore, the purpose of this study was to examine individuals’ attitudes toward economic abuse related to the victim’s job status by examining individuals’ tendencies to blame the victim, minimize the abuse, and excuse the perpetrator. Another purpose of this study was to investigate how participant gender impacts how participants view economic abuse victims and perpetrators. Additionally, we examined differences in attitudes between college students and non-college students. Since there is no study that has investigated the differing attitudes toward economic abuse between students and non-students to date, our analyses based on participant student status were exploratory. Lastly, we examined if ambivalent sexism and gender role ideology were predictors of blame, minimization, and excuse. To our knowledge, this is the first study to examine attitudes of blame, minimization, and excuse toward economic abuse victims and perpetrators and the first study to examine these two predictor variables related to economic abuse.

Within this article, the wording related to gender and/or sex assigned at birth of participants may vary when discussing different research articles (e.g., woman, female) depending on the original authors’ wording. However, in the current research study, we differentiate between both gender and sex assigned at birth, and the usage of gender indicates gender identity instead of sex assigned at birth. Information about participants’ gender identity can be found in the method section. Additionally, we have defined economic abuse as a part of IPV, but other researchers use various terms (e.g., domestic violence, domestic violence against women). Throughout this manuscript, we have used the terminology of other researchers when reviewing the literature, but for the context of the current study, we utilize IPV and include economic abuse within the realm of IPV.

Hypotheses

The hypotheses for the current study were as follows: (1) Participants will blame the victim more, minimize the economic abuse more, and excuse the perpetrator more when the victim is unemployed compared to when the victim is employed, (2) Men will blame the victim more, minimize the economic abuse more, and excuse the perpetrator more compared to women, (3) Participants higher in ambivalent sexism will blame the victim more, minimize the economic abuse more, and excuse the perpetrator more compared to participants lower in ambivalent sexism, and (4) Participants higher in traditional gender role ideology will blame the victim more, minimize the economic abuse more, and excuse the perpetrator more compared to participants lower in traditional gender role ideology.

Method

Participants

Participants were recruited via the SONA system (i.e., online, cloud-based product that allows researchers to collect data from a participant pool; www.sona-systems.com) at a private university in the Rocky Mountain area of the United States (n = 142) and from Amazon’s Mechanical Turk (i.e., online survey platform from Amazon.com that researchers can use to publish online surveys and recruit participants in return for monetary costs; Burnham et al., 2018; MTurk; n = 132). Thirty-four participants answered one or both attention checks in the survey incorrectly, and these responses were omitted from analyses. Moreover, one participant identified as agender, and this participant’s data was excluded from all analyses since binary gender identification is being used as a predictor in this study. As such, all data analyses were conducted with 239 participants (122 women, 117 men; SONA: n = 120; MTurk: n = 119). Participants recruited via the SONA system met the following inclusion criteria: (1) being at least 18 years of age or older and (2) having a SONA account to complete this survey online via Qualtrics. MTurk Workers met the following inclusion criteria: (1) having an MTurk account, (2) living in the United States, (3) having a previous HIT (i.e., survey) approval rating greater than 95%, (4) having a previous number of approved HITs greater than 500, and (5) being at least 18 years of age or older. The inclusion criteria regarding previous HIT approval ratings and previous number of approved HITs were utilized in the current study to ensure that MTurk workers were paying attention in our survey and had previously submitted accepted HITs.

There were two scenarios to which participants were randomly assigned. There were 125 participants (64 women, 61 men) in the “Job” condition scenario and 114 participants (58 women, 56 men) in the “No Job” condition scenario. Four participants inserted their birth year instead of their age in years, and one participant entered an invalid age. After estimating the four participants’ ages based on the time of data collection and omitting the invalid age entered, the age range of participants (n = 238) was 18–71 (M = 28.77, SD = 11.19). Participants selected their race as follows: American Indian or Alaska Native (n = 1; 0.42%), Asian (n = 12; 5.02%), Black or African-American (n = 12; 5.02%), White (n = 198; 82.85%), and more than one race (n = 16; 6.69%). Participants selected their ethnicity as follows: Hispanic, Latino, or Spanish (n = 37; 15.48%) and Not Hispanic, Latino, or Spanish (n = 202; 84.52%). Additional demographics can be found in Table 1.

Table 1

Demographics for sample by student status

Demographic	Student		Non-student
	n = 169	70.71%	n = 70	29.29%
Education (highest obtained)
High school diploma, GED, or Equivalent	n = 16	9.47%	n = 6	8.57%
Some college, no degree	n = 95	56.21%	n = 10	14.29%
Associate degree	n = 11	6.51%	n = 5	7.14%
Bachelor’s degree	n = 40	23.67%	n = 42	60.00%
Master’s degree	n = 6	3.55%	n = 7	10.00%
Prefer not to say	n = 1	0.59%	n = 0	0.0%
Relationship status
Single	n = 90	53.25%	n = 19	27.14%
In a relationship	n = 26	15.38%	n = 9	12.86%
Married	n = 52	30.77%	n = 37	52.86%
Divorced	n = 0	0.0%	n = 5	7.14%
Prefer not to say	n = 1	0.59%	n = 0	0.0%
LGBTQ + Identification
Yes	n = 36	21.30%	n = 7	10.00%
No	n = 131	77.51%	n = 58	82.86%
Prefer not to say	n = 2	1.18%	n = 5	7.14%
Employment
Full-time	n = 50	29.59%	n = 48	68.57%
Part-time	n = 75	44.38%	n = 6	8.57%
Seeking opportunities	n = 13	7.69%	n = 1	1.43%
Self-employed	n = 3	1.78%	n = 7	10.00%
Unemployed	n = 24	14.20%	n = 4	5.71%
Prefer not to say	n = 0	0.0%	n = 1	1.43%
Other	n = 4	2.37%	n = 3	4.29%
Perceived Income
Extremely poor	n = 10	5.92%	n = 3	4.29%
2	n = 43	25.44%	n = 10	14.29%
3	n = 43	25.44%	n = 13	18.57%
4	n = 29	17.16%	n = 30	42.86%
5	n = 22	13.02%	n = 9	12.86%
6	n = 17	10.06%	n = 3	4.29%
Extremely rich	n = 5	2.96%	n = 2	2.86%

All participants were presented with an informed consent form and were required to consent to participate in this study before being eligible to participate. Participation in this study was completely voluntary. Moreover, all participants were treated ethically according to the guidelines outlined by the American Psychological Association (American Psychological Association, 2017). This research study was approved in its entirety by the Institutional Review Board at Brigham Young University.

Measurements

Scenarios

There were two scenarios in the current study: “Job” and “No Job.” These two scenarios were created by including actual behaviors that are prevalent in economically abusive situations (e.g., Adams & Beeble, 2019; Postmus et al., 2012). These scenarios consisted of a married couple in which the husband perpetrated economic abuse toward his wife. Within both scenarios, the names of the perpetrator and victim and the victim’s job status (i.e., employed, unemployed) were all stated. Relationship status (i.e., married) was not manipulated and stayed constant in both scenarios. The “Job” condition scenario read as follows:

Anna is a mother in her mid-thirties with three young children. Her husband, John, controls the finances as head of the household. Anna has a job that she really loves, but John constantly insists that Anna quits her job because he wants her to focus on raising their children. However, she has not yet agreed to do so because she loves the company she works for. The house was purchased under John’s name, and John makes every investment decision for the family without discussing finances with Anna. John has complete access to Anna’s credit cards and bank accounts and takes out loans in her name, while Anna does not have access to any financial resources. Anna earns a modest income, but she is required to give the money to John. Anna has to ask for money every time she buys household items, food, and children’s items (clothes, etc.), and she is forced to use cash because according to John, cash is easier to manage than any other form of money. Anna feels stuck and hopeless because she has no say in their finances, and she is tired of getting approval from John every time she wants to buy something. Recently, Anna and John got into a huge argument because she asked for money to go out for a drink with her best friend whom she has not seen in a while.

Dependent Variables

The Victim-Blame Attribution Measure (Yamawaki et al., 2009) was modified to reflect the scenarios in the present study and was utilized to examine how participants blamed the victim in the two hypothetical scenarios. This measure consisted of five items, and no items were reverse scored. Items included “Anna had some fault in this argument.” and “Anna should be blamed for this argument.” Participants responded on a Likert-type scale from 1 (strongly disagree) to 7 (strongly agree), and higher scores indicated higher blame placed on victims. Previous researchers found Cronbach’s alphas of α = 0.73–0.82 (Yamawaki et al., 2009). The Cronbach’s alpha in the current study was α = 0.93.

The Perceived Seriousness of Violence Measure (Yamawaki et al., 2009) was modified to reflect the two hypothetical scenarios and was utilized to examine how participants minimized the seriousness of the economic abuse. There were five items, and all items were reverse scored. Items included “This is an economically abusive situation.” and “This argument left Anna with psychological scars.” Participants responded on a Likert-type scale from 1 (strongly disagree) to 7 (strongly agree), and higher scores indicated more minimization of the economic abuse. Previous researchers found Cronbach’s alphas of α = 0.82–0.84 (Yamawaki et al., 2009). The Cronbach’s alpha in the current study was α = 0.84.

The Excuse-Perpetrator Measure (Yamawaki et al., 2009) was modified for the scenarios in the current study and was utilized to examine the extent to which participants excused the actions of the perpetrator in the hypothetical scenarios. This measure consisted of four items, and two items were reverse scored. Items included “John had responsibility for this argument.” and “It is okay for John to control household finances.” Participants responded on a Likert-type scale from 1 (strongly disagree) to 7 (strongly agree), and higher scores indicated that participants excused the perpetrator’s actions more. Yamawaki et al. (2009) previously found Cronbach’s alphas of α = 0.58-0.68. The Cronbach’s alpha in the current study was α = 0.72.

Predictor Variables

The Ambivalent Sexism Inventory (Glick & Fiske, 1996) was utilized to measure participants’ sexist views. This measure consisted of 22 items, and six items were reverse scored. Items included “Most women interpret innocent remarks or acts as being sexist.” and “Women are too easily offended.” Participants responded on a Likert-type scale from 1 (strongly disagree) to 7 (strongly agree), and higher scores indicated that participants had higher levels of sexism. There were two subscales for this measure—hostile sexism (11 items) and benevolent sexism (11 items)—and the two subscales were separately used as predictors instead of the combined measure. Glick and Fiske (1996) previously found Cronbach’s alphas of α = 0.80–0.92 for hostile sexism and α = 0.73–0.85 for benevolent sexism. The Cronbach’s alphas in the current study were α = 0.90 for hostile sexism and α = 0.83 for benevolent sexism.

The Gender Role Ideology Measure (Fuwa, 2014) was utilized to measure participants’ traditional gender role ideologies. This measure consisted of five items, and no items were reverse scored. Items included “All in all, family life suffers when the woman has a full-time job.” and “A job is all right, but what most women really want is a home and children.” Participants responded on a Likert-type scale from 1 (strongly disagree) to 7 (strongly agree), and higher scores indicated that participants had higher levels of traditional gender role ideology. Fuwa (2014) previously found a Cronbach’s alpha of α = 0.70. The Cronbach’s alpha in the current study was α = 0.86.

Procedure

Participants who met the aforementioned inclusion criteria could view and participate in this study. After selecting to participate, participants received the consent form and consent form questions and then completed the study in the following order: randomly assigned to read one of the two scenarios, completed the dependent variable measures, completed the predictor variable measures, and answered demographics questions. Once participants who were recruited from the SONA system completed the study, these participants were awarded two SONA credits that could be used as extra credit in their courses. After the participants recruited via MTurk completed the study, these participants received a random ID to submit on MTurk to qualify for monetary compensation (i.e., $0.75).

Power Analyses

Two post hoc power analyses were conducted using G*Power (Version 3.1.9.7). Regarding the MANOVA, with the effect size set to 0.0625, alpha set to 0.05, and the number of groups and response variable both set to three, our sample of 239 participants reached a power of 0.99. Regarding the multiple regression analyses, with the effect size set to 0.0625, alpha set to 0.05, and the number of predictors set to three, our sample of 239 participants reached a power of 0.99. As such, this study was appropriately powered for the statistical analyses conducted.

Results

Effects of Scenario Condition, Participant Gender, and Participant Student Status

A 2 (scenario condition: job, no job) × 2 (participant gender: woman, man) × 2 (participant student status: college student, non-college student) MANOVA was performed on the dependent variables (i.e., blame, minimization, excuse). There was no main effect for scenario condition [Wilk’s Λ = 0.99; F(3, 229) = 0.47, p = 0.706], but there were significant main effects for participant gender and participant student status [Wilk’s Λ = 0.90; F(3, 229) = 8.84, p < 0.001 and Wilk’s Λ = 0.96; F(3, 229) = 2.84, p = 0.039, respectively]. Moreover, there were no interaction effects of scenario x gender [Wilk’s Λ = 0.99; F(3, 229) = 0.73, p = 0.536], scenario x student status [Wilk’s Λ = 0.99; F(3, 229) = 1.00, p = 0.395], or gender by student status [Wilk’s Λ = 0.99; F(3, 229) = 1.06, p = 0.368]. There was also no significant three-way interaction between scenario, gender, and student status [Wilk’s Λ = 1.00; F(3, 229) = 0.31, p = 0.818].

Univariate ANOVAs were conducted to examine participant gender and participant student status independently on the three dependent variables. Men were more likely to blame the victim, minimize the economic abuse, and excuse the perpetrator compared to women [F(1, 237) = 34.72, p < 0.001; F(1, 237) = 7.62, p = 0.006; and F(1, 237) = 33.27, p < 0.001, respectively]. Moreover, college students were less likely to minimize the economic abuse compared to non-students [F(1, 237) = 4.88, p = 0.028]. Means and standard deviations for the dependent variables by participant gender and participant student status can be found in Tables 2 and 3, respectively.

Table 2

MANOVA means and standard deviations by gender

DV	Women (N = 122)		Men (N = 117)
	Mean	Std. Dev	Mean	Std. Dev
Blame	10.39	5.61	16.48	9.87
Minimization	9.80	4.58	11.56	5.27
Excuse	7.86	3.67	11.07	4.87

DV Dependent Variable

Table 3

MANOVA means and standard deviations by student status

DV	Student (N = 169)		Non-student (N = 70)
	Mean	Std. Dev	Mean	Std. Dev
Blame	13.48	8.59	13.11	8.42
Minimization	10.20	4.51	11.76	5.09
Excuse	9.46	4.33	9.36	5.17

DV Dependent Variable

Multiple Regression Analyses

One-tailed, multiple regression analyses were conducted to examine the effects of the predictor variables (i.e., hostile sexism, benevolent sexism, gender role ideology) on the dependent variables. Intercorrelations for the predictor variables can be found in Table 4 respectively.

Table 4

Predictor Intercorrelations for Hostile Sexism, Benevolent Sexism, and Gender Role Ideology

Measure	HS	BS	GRIM
HS	–
BS	0.61***	–
GRIM	0.67***	0.54***	–

HS Hostile Sexism, BS Benevolent Sexism, GRIM Gender Role Ideology Measure

***p < 0.001

Blaming the Victim

Hostile sexism and traditional gender role ideology were both significant predictors of blaming the victim [β = 0.30, t (235) = 4.38, p < 0.001 and β = 0.50, t (235) = 7.68, p < 0.001, respectively]. Benevolent sexism was not a significant predictor of blaming the victim [β =  − 0.06, t (235) =  − 1.01, p = 0.157]. These findings explained a significant amount of variance [F(3, 235) = 74.76, p < 0.001, R2 = 0.49, R2 adj = 0.48].

Minimizing the Economic Abuse

Hostile sexism was a significant predictor of minimizing the economic abuse [β = 0.31, t (235) = 3.43, p < 0.001]. Neither benevolent sexism nor traditional gender role ideology were significant predictors of minimizing the economic abuse [β =  − 0.002, t (235) =  − 0.03, p = 0.490 and β =  − 0.004, t (235) =  − 0.05, p = 0.480, respectively]. These findings explained a significant amount of variance [F(3, 235) = 8.25, p < 0.001, R2 = 0.10, R2 adj = 0.08].

Excusing the Perpetrator

Hostile sexism and traditional gender role ideology were both significant predictors of excusing the perpetrator [β = 0.30, t (235) = 4.27, p < 0.001 and β = 0.44, t (235) = 6.59, p < 0.001, respectively]. Benevolent sexism was not a significant predictor of excusing the perpetrator [β =  − 0.02, t (235) =  − 0.40, p = 0.345]. These findings explained a significant amount of variance [F(3, 235) = 64.00, p < 0.001, R2 = 0.45, R2 adj = 0.44].

Discussion

Although economic abuse has been examined more recently, there are still gaps in the literature regarding individuals’ attitudes toward economic abuse victims. While research has been conducted on attitudes toward IPV in general, it is possible that attitudes toward economic abuse varies from other forms of IPV (e.g., physical abuse) due to economic abuse likely having little to no physical evidence of IPV compared to physical abuse (e.g., bruises, cuts). Therefore, the purpose of this study was to examine how participants blamed economic abuse victims, minimized economic abuse, and excused economic abuse perpetrators related to scenario condition, participant gender, and participant student status. Moreover, we examined two potential predictors (i.e., ambivalent sexism and gender role ideology) of the dependent variables.

There was no main effect of the scenario condition in the current study. Regardless of the employment status of the victim, participants still blamed the victim, minimized the abuse, and excused the perpetrator. This finding could indicate that, regardless of the efforts put forth by economic abuse victims (e.g., trying to work, being unhappy not working, begging the perpetrator to let them work), participants may still find the victim at fault and ultimately agree with the perpetrator. In one recent research study, researchers found no significant effects for scenario manipulations related to another form of IPV (i.e., stalking; Green & Yamawaki, 2021). Therefore, it is not uncommon to find null results based on scenario manipulations. However, due to the lack of previous researchers examining the employment status of victims, there is a need to examine various situations in which victims are blamed more than perpetrators. Indeed, differences in situations of blame, for example, may be due to participants’ attitudes (e.g., belief in a just world) instead of the situations manipulated within scenarios, and future researchers should examine not only scenario manipulations but also the preexisting attitudes that are held by participants.

There was a main effect of participant gender, and this has been found in previous researchers’ studies based on other forms of IPV regarding both blame (Angelone et al., 2015; Grubb & Harrower, 2008, 2009; Riley & Yamawaki, 2018) and minimization (Dunlap et al., 2015; McKeon et al., 2015; Yamawaki et al., 2012). As such, we found that men blamed the IPV victim more and minimized the economic abuse more compared to women. However, contrary to previous null findings (e.g., Yamawaki et al., 2012), we also found that men in the current study excused the perpetrator more compared to women. Overall, the current findings align similarly with other findings regarding main effects of participant gender. This indicates that economic abuse is viewed similarly to other forms of IPV and that there are gender differences related to how participants view both the victim and the perpetrator. In general, men tend to victimize the victim and minimize the seriousness of abuse compared to women, and Dunlap et al. (2012) found a similar pattern in a study related to stalking. These researchers found that men, compared to women, gave stalking perpetrators less guilty verdicts. As such, these results dovetail with other forms of IPV, and this indicates that research related to attitudes of economic abuse, including gender differences, is warranted to further understand differences in attitudes.

There was a main effect of participant student status. We found that students were less likely to minimize the economic abuse compared to non-students and that there is a difference in attitudes based on student status. This finding is similar to that of Rogers and Davies (2007). These researchers found that students judged victims of assault to be more credible and that students minimized the abuse less compared to non-students (Rogers & Davies, 2007). These researchers also found that students contributed more blame to the perpetrator than to the victim compared to non-students. These findings are similar to the current study’s findings even though a different type of abuse was being examined in the present study. This indicates that different types of abuse (e.g., child sexual abuse, economic abuse) are viewed similarly by outsiders and that victims are seen similarly as well. Moreover, students and non-students did not differ in their attitudes of blaming the victim or excusing the perpetrator. Vonderhaar and Carmody (2015) found that participants who were men, less educated, and younger were more likely to support rape myths. Therefore, it is possible that there are similar findings related to attitudes of economic abuse, but further research is needed. Future research regarding participant student status as well as being less educated, being younger, and being a man must be conducted specifically related to the issue of economic abuse to examine predictors of both blame and excuse.

There were no interaction effects in the current study. These null findings may be due to the demographics in the current study (e.g., predominantly White and religious) as well as the null findings for the scenario conditions. However, the current interactions were exploratory, and there were no hypotheses regarding the interactions. Moreover, the lack of previous research on interaction effects makes it difficult to determine the direction of these findings. Further observation is needed to continue examining any possible interaction effects regarding scenario condition, participant gender, and participant student status.

Hostile sexism and traditional gender role ideology were both significant predictors of victim blaming in the present study, and these findings are similar to other researchers’ findings of other types of IPV (Dunlap et al., 2015; Mckinlay & Lavis, 2020; Persson et al., 2018). Therefore, individuals higher in hostile sexism and traditional gender role ideology were more likely to blame the victim. In general, participants higher in hostile sexism and traditional gender role ideology tend to have negative views toward victims of abuse. Moreover, benevolent sexism was not a significant factor. This finding is contradictory to other researchers’ findings (e.g., Pedersen & Strömwall, 2013). The roles of both hostile and benevolent sexism, however, should continue to be examined as predictors of attitudes toward economic abuse since this research topic is newer in the literature.

We also found that hostile sexism was a significant predictor of minimizing the economic abuse, and this finding is similar to other researchers’ findings related to other forms of IPV (Yamawaki, 2007; Yamawaki et al., 2009). This finding indicates that individuals higher in hostile sexism were more likely to minimize the seriousness of the economic abuse described in the hypothetical scenarios. In general, individuals tend to minimize the effects abuse has on victims, and in relation to the present study, this finding indicates various types of abuse are minimized. However, neither gender role ideology nor benevolent sexism were significant predictors. These null findings replicate the findings of other researchers (e.g., Yamawaki, 2007). Although these two predictors were not significant in the current study, efforts should be made in future research studies to examine if gender role ideology and benevolent sexism are potential mediators or moderators that explain the relationship between scenarios of economic abuse victims and participants’ tendencies to minimize economic abuse.

Both hostile sexism and traditional gender role ideology were significant predictors of excusing the perpetrator. Indeed, individuals higher in hostile sexism and traditional gender roles excused the man perpetrator of violence. One particular reason for this could be the views hostile sexists have toward women. In general, hostile sexism is a form of antipathy toward women (e.g., Glick & Fiske, 1996). These views are predominantly gendered with the viewpoint that men are superior and that women should be submissive. As such, according to the present findings, upholding sexist views and adhering to a traditional gender role ideology suggests that individuals who view women as unequal to men tend to excuse perpetrators of abuse more compared to people who are less antipathic toward women and who have an egalitarian gender role ideology. Moreover, similar to the findings for both blame and minimization, benevolent sexism was not a significant predictor of excusing the perpetrator in the current study. It is likely that hostile sexism and gender role ideology carry the variance for excuse since we conducted multiple regression analyses. However, future research is warranted for the role of benevolent sexism.

Implications, Limitations, and Future Directions

Previous researchers have found that individuals who adhere to patriarchal ideologies blame women more for the IPV they experience (e.g., Tonsing & Tonsing, 2019). Based on the findings of the current study, our findings are supported under feminist theory: ambivalent sexism and traditional gender role ideology were both predictors of permissive attitudes toward economic abuse. As noted by Stylianou (2018b) regarding the various IPV definitions, economic abuse should be considered a part of IPV definitions due to individuals’ attitudes toward economic abuse victims and perpetrators being similar to victims and perpetrators of other forms of IPV (e.g., blaming the victim; Keller & Honea, 2016; Yamawaki et al., 2018). Therefore, we recommend examining economic abuse under a feminist theory lens to enhance theory development and to better understand attitudes toward economic abuse victims.

Our sample consisted of predominantly White, religious, and educated individuals—either currently or previously students with a higher education. To examine attitudes at a more generalizable level, future researchers should recruit a sample that consists of more non-White and non-religious individuals. While we created the two scenarios based on common behaviors that occur within economically abusive scenarios, we did not pilot the scenarios. Therefore, further usage of these scenarios is warranted in replication studies. Furthermore, differences between various educational obtainment levels (e.g., high school education vs. undergraduate education) should be examined for additional effects found related to education since we found a significant effect of minimization between students and non-students in the current study. Additionally, although we separated students and non-students based on their current student status, a majority of our non-student participants previously attended some form of higher education. As such, a majority of our sample had attended a higher education institution at some point in their lives, and this indicates the need to examine attitudes between people who have attended college and those who have never attended college. There were also differences in the mean ages based on current students and non-students. Current college students (M = 24.35, SD = 0.57) were younger than non-students (M = 39.37, SD = 1.40). As such, there is a need to examine age differences in general regarding attitudes toward economic abuse.

Additionally, participants’ job occupation and/or student status may have an impact on their attitudes toward economic abuse and how they perceive the severity of this type of IPV. For example, it is possible that individuals with high-paying careers (i.e., high socio-economic status) are less aware of the consequences of economic abuse for IPV victims and therefore their attitudes could differ from individuals with lower socio-economic statuses. Individuals who are supported by an intimate partner without the presence of economic abuse in their own relationship may also have attitudes that differ from individuals not being support by an intimate partner or individuals who are not in a relationship. Because of this, it will be important for researchers to examine job occupation—also examining socio-economic status, support by an intimate partner, and relationship status—and student status in future research studies as predictors of attitudes toward economic abuse.

While we examined attitudes toward a traditionally nuclear family in the present study and assigned the woman in both scenarios to be the victim and the man to be the perpetrator, there may be differences in blaming victims, minimizing economic abuse, and excusing perpetrators based on the gender of both the victim and the perpetrator. As such, it is recommended that researchers examine the manipulation of the gender of both the victim and the perpetrator in hypothetical scenarios. It is possible that victims who are men may be blamed more than victims who are women, and these differences should be evaluated. Hine et al. (2020) recently found that participants commonly labeled women as “victims” and men as “perpetrators.” Therefore, in economically abusive situations, it is crucial to understand who participants view as the victim and their reasons for attributing blame. Moreover, while we did not mention the race of the victim or the perpetrator in the current study, it is noteworthy that researchers should examine both the race of the victim and the perpetrator and any racist views held by participants when examining economic abuse. Moreover, while the dependent variable measures utilized in the current study have been utilized by other researchers in many IPV studies, there were no reverse scored items for two of the three measures (i.e., Victim-Blame Attribution Measure, Perceived Seriousness of Violence Measure). Future researchers should ensure that their measurements include reverse scored items to account for acquiescence bias.

Additional predictors should be evaluated as well. One predictor that should be examined is belief in a just world. High levels of belief in a just world may be a predictor in scenarios in which women do not work compared to scenarios in which women do work (e.g., belief that she “got what she deserved” by not working and maintaining personal income). Other predictors to be examined related to economic abuse include right-wing authoritarianism, stigmatization toward women, and stigmatization toward victims of IPV. Being conservative, having negative attitudes toward women, and having negative attitudes toward victims of IPV could all be predictors of blaming, minimizing, and excusing economically abusive situations. Last, a comparison of different forms of abuse (e.g., physical versus economic, psychological versus economic) should be evaluated to understand if blame, minimization, and excuse are attributed differently to abusive situations based on the type of abuse.

Moreover, these findings can influence policy. Economic abuse was commonly classified as a type of psychological abuse (Yau et al., 2021). However, there is a need to see economic abuse as a separate type of IPV due to the high prevalence rates found so far (e.g.,Postmus et al., 2012; Stylianou, 2018a) and due to to the negative attitudes individuals have toward economic abuse victims. As such, the legal definition should include economic abuse as a form of IPV instead of combined with psychological or emotional abuse. Including economic abuse in the legal definition of IPV could help with national education about the severity of this type of IPV. Additionally, we echo the recommendation of Adams and Beeble (2019) to assess for the occurrence of economic abuse in IPV victims. Because economic abuse is invisible to outsiders (Postmus et al., 2021) unlike physical abuse typically, economic abuse can go unnoticed. The recommendation by Adams and Beeble (2019) for counselors to assess their clients’ potential experiences with economic abuse by their abusive partners is crucial. It is also crucial to examine prevalence rates of economic abuse in general due to the nature of this invisible form of IPV and to help assess the overall need of resources for these IPV victims.

Conclusions

Economic abuse has been coined as a gendered issue that predominantly impacts women (Postmus et al., 2020). As such, there is a need for researchers to examine the attitudes that outsiders have of economic abuse victims within both heterosexual and homosexual dating, cohabitating, and married relationships in which women are the victims to understand how economic abuse is perceived (e.g., blaming the economic abuse victim). Moreover, there is also a need to examine individuals’ attitudes toward men victims of economic abuse since men are also victims of IPV in general. As the topic of attitudes about economic abuse receives more empirical attention, it will be important to understand the implications of this research in both gender and racial minority groups to examine differences in attitudes based on both perpetrators’ and victims’ genders and races. Victims of many types of abuse (e.g., economic, physical, psychological, sexual) seem to be blamed in similar ways, and certain characteristics of participants (e.g., hostile sexism, traditional gender role ideology) tend to contribute to blame, minimization, and excuse. We recommend a continuation of examining the scenarios, characteristics (e.g., gambling; Hing et al., 2021), and life situations (e.g., economic hardships; Lucero et al., 2016) that could impact individuals’ attitudes toward economic abuse victims.