Abstract
The goal of this study was to understand the prevalence of intimate partner violence (IPV) among South Asian women during COVID-19, and to identify predictors of IPV presence and severity. We recruited South Asian women (n = 132) to complete an online survey about their mood, experiences with COVID-19, and IPV. 47% of South Asian women (n = 132) reported experiencing any IPV, most commonly economic abuse. Women experiencing IPV had higher rates of COVID-19 related worry (t=-1.3, p = .001) and anxiety (t=-2.2, p = .027). The following variables were associated with greater odds of experiencing IPV: COVID-19 related worry (OR: 1.44 [1.11, 1.87]) and full-time employment status (OR: 0.13 [0.02, 0.99]). Depressive symptoms were a significant positive predictor of economic abuse severity (b = 0.80, p = .002). Future research should examine cultural and environmental factors that interact with the experience of IPV among South Asian women to better inform interventions for survivors.
Keywords: South Asian, Intimate partner violence, Depression, Culture
Introduction
Intimate partner violence (IPV) is an act of physical, sexual, or psychological aggression perpetrated by a relationship partner; approximately 25% of women in the United States have experienced IPV in their lifetime [1, 2]. There are many long-term negative consequences of IPV, one of the most common being depression [3, 4]. Generally, women who have experienced IPV during their lifetime are at least twice as likely to develop major depressive disorder, with research suggesting that one-fourth of women who reported lifetime IPV also met criteria for depression. [5, 6]. Depression is highly prevalent among women currently experiencing IPV, but can also develop and continue to persist over time [7, 8].
South Asian Americans represent one ethnic and racial minority group that is disproportionately impacted by relationship violence [9]. Recent surveys have demonstrated that a significant proportion of South Asian women have witnessed violence between their parents and have experienced violence in their own relationships [10–12]. Several factors contribute to rates of IPV in this community. South Asian women who are threatened regarding their immigration status in the United States by their partner, or depend on their partner for their visa, are more likely to report experiencing IPV [13]. Compared to those who had immigrated earlier, South Asian women who immigrated to the United States within the past two years were far less likely to be aware of IPV-related services available to them. Further, non-US born women were more likely to report having experienced physical abuse and IPV-related injuries [14]. Additionally, many South Asian families consider in-laws to be a member of the nuclear family, and multigenerational housing is common in South Asian cultures. This presents potential for in-law abuse, a phenomenon less widely examined in US measures of IPV, where it is less common for in-laws and couples to live together. In a survey of South Asian women who reported experiencing IPV, approximately 15% also indicated experiencing emotional abuse from in-laws [15]. Therefore, in-law abuse is one form of interpersonal violence that should be further explored in this population as it may reveal that current IPV rates are underestimated.
Other sociodemographic variables have been linked to IPV more broadly but are less explicitly examined in South Asian American women. Data from the 1995 National Alcohol Survey (NAS) Black and Hispanic heterosexual couples with lower reported incomes were more likely to endorse male-perpetrated violence [16]. This difference was not reported in White couples, signaling that societal factors related to race and ethnicity, in conjunction with economic stress, may perpetuate IPV. It is possible that South Asian Americans experience similar income-related differences in IPV as Black and Hispanic couples. Other factors that have been linked to IPV are education, a protective factor, and the number of children, which is positively associated with IPV [17]. However, these studies did not conduct analyses specifically on Asian ethnic groups, so it is unclear if a South Asian subsample would have unique predictors.
The COVID-19 pandemic has impacted the nationwide occurrence of IPV. Government mandated lockdowns have helped mitigate the transmission of disease while increasing the proximity between abusers and their partners. With partners spending increased amounts of time in the same living space, it may be difficult to find private space to seek support or speak to a provider about their concerns [18]. Data indicates that such stay-at-home orders and lockdowns have increased the incidence of domestic violence reports in US households. For example, data from Dallas, Texas indicates that domestic violence calls increased in the first two weeks after the stay-at-home order began in 2020. However, call rates appear to have returned to baseline after this two-week period, possibly indicating the increase in domestic violence incidents did not persist [19]. However, other data has suggested a more enduring increase in IPV. Several major cities in the United States have highlighted elevated rates of domestic violence reports, such as Portland, OR, San Antonio TX, and Jefferson County, AL [20]. Further, a systematic review of 12 published studies concluded that there has been an 8% increase in domestic violence incidents after stay-at–home orders went into effect [21].
In addition to worsening IPV, the pandemic has exacerbated mental health problems nationwide. The AmeriSpeak standing panel, a representative sample of the United States population, reported that prior to the onset of the COVID-19 pandemic, 9% of respondents endorsed depressive symptoms. After the pandemic began, this rate increased by three-fold, with 28% of respondents reporting experiencing depressive symptoms [22]. This finding is echoed by a Kaiser Health survey which compared rates of depression before and after the onset of the pandemic. While 10% reported experiencing symptoms of depression or anxiety between January and June of 2019, this number quadrupled to about 40% after the pandemic began [23]. Similar effects have been noted from adolescents and young adults to perinatal women [24, 25].
The pandemic has had a marked effect on the South Asian American population. Analysis of the New York City public hospital electronic record database revealed that out of all Asian patients who were tested for COVID-19, nearly half (48%) were South Asian. South Asians also had the highest rates of positive COVID-19 tests and the mortality rate was nearly 25% [26]. It was hypothesized that this elevated rate is due to South Asians having higher exposure to factors promoting the spread of COVID, such as essential worker jobs and crowded housing. The pandemic also appears to have had a significant effect on depression in the South Asian American population. Prior to the pandemic, estimated depression rates among South Asian Americans were 9% and 11% [27, 28]. After the onset of the pandemic, it was found that the prevalence of depression was nearly 40% [28].
While depression has been revealed to have significantly worsened among South Asian adults during the pandemic, there is less research about changes in IPV rates in this population. The aim of the current study was to understand the current prevalence of IPV in its various forms among South Asian women. Secondly, we sought to identify if sociodemographic factors or clinical symptoms were related to the experience of IPV in this population.
Methods
Participants
A variety of outreach methods were used to recruit a sample of South Asian women (n = 132) across the United States. A study advertisement was shared with several South Asian American organizations; the study was also advertised on a recruitment site affiliated with a large hospital system in a metropolitan city in New England, as well as on local Craigslist pages. South Asian participants were encouraged to share the survey with peers, as snow-ball sampling is a commonly used recruitment method among understudied populations [29]. To be eligible to participate in the study, participants had to meet the following inclusion criteria: (a) at least 18 years of age; (b) identifying as a woman; (c) in a romantic relationship; (d) access to Internet to complete the study; (e) able to provide informed consent and complete the study accurately. Participants were excluded if they did not meet one or more inclusion criteria, or if they did not consent to participate.
Measures
Demographics
The following demographic information was collected: gender, sexual orientation, age, ethnicity, race, highest level of education completed, employment, status, income, duration of time in the United States, if English is the language spoken at primarily home, if they have children, and if they are religious.
Relationship Information
Participants reported the duration of their relationship and the type (married, living with current partner, not living with current partner, or separated). The Romantic Partner Conflict Scale (RPCS) was also administered to better understand how participants engage in conflict with their partners. The RPCS assesses the extent to which participants engage in the following behaviors when faced with romantic conflict: submission, domination, separation, reactivity, avoidance, and compromise [30].
Mental Health
The following measures were administered to assess participants’ anxiety, depression, and COVID-19 related stress:
Patient Health Questionnaire-2 (PHQ-2)
The PHQ-2 is a validated two-item measure of depressed mood, measuring the frequency the respondent felt depressed and experienced anhedonia over the past two weeks [31].
Generalized Anxiety Disorder-2 (GAD-2)
The GAD-2 is a validated two-item measure of anxiety symptoms experienced by the respondent over the past two weeks [32].
COVID-19 Related Worry Scale
The COVID-19 Related Worry Scale is a novel six-item measure that examines the severity of respondents’ pandemic-related worries related to employment, personal health, and the well-being of loved ones [33].
Relationship Violence
Two measures of relationship violence were administered to assess the prevalence and severity of economic, physical, emotional, and in-law abuse. In both measures, if a participant responded that they had experienced any of the abusive behaviors, they were noted as having abuse prevalent in the relationship. The total score of each scale was also calculated.
Scale of Economic Abuse (SEA)
The SEA is a 12-item measure of economically abusive activities experienced in a relationship with the following three sub-scales: economic control, sabotage, and exploitation. This assessment has been validated as a reliable instrument to assess economic abuse (34).
South Asian Violence Screen (SAVS)
The SAVS is a 14-item assessment of relationship violence developed and validated for use among South Asian women in the United States. The SAVS is divided into three subscales: emotional violence, physical violence, and in-law perpetrated violence, which were analyzed in this study [12].
Procedures
After participants read and electronically provided informed consent, they completed the survey measures. All data was collected and stored using REDCap. After completing all items, participants were provided with a list of free mental health and IPV-related resources. Participants also had the option to complete an unlinked form where they could provide their email address to be randomly selected to receive a $20 Amazon gift card. The study was reviewed by the Mass General Brigham Institutional Review Board and determined as exempt from further review.
Results
There were 132 participants who enrolled into the study and progressed past the consenting portion of the study. Participants were predominantly heterosexual (83%), employed full-time (52%), and nearly half had lived in the United States since birth (47%; Table 1). The average relationship duration among the sample was 5.28 years (SD = 6.86). Of the 130 women who reported their country of origin, the majority (82%) were of Indian origin. The rest of the sample was composed of individuals from Bangladesh (3%), Pakistan (6%), Sri Lanka (4%), and other or not reported (5%).
Table 1.
Sociodemographic and clinical characteristics of participants
| Characteristic | (N = 132) | |
|---|---|---|
| n/M | %/SD | |
| Age | 28.6 | 8.7 |
| Sexual orientation | ||
| Heterosexual | 110 | 83.3 |
| Bisexual | 11 | 8.3 |
| Lesbian | 2 | 1.5 |
| Other | 5 | 3.8 |
| Missing | 4 | 3.0 |
| Education | ||
| Bachelor’s degree or less | 46 | 34.8 |
| More than Bachelor’s degree | 86 | 65.2 |
| Relationship status | ||
| Married to current partner | 40 | 30.3 |
| Living with current partner | 27 | 20.5 |
| Not living with current partner | 64 | 48.5 |
| Separated/divorced | 1 | 0.8 |
| Missing | 0 | 0 |
| Relationship duration (years) | 5.3 | 6.9 |
| Employment a | ||
| Full-time | 69 | 52.3 |
| Part-time | 21 | 15.9 |
| Student | 45 | 34.1 |
| Other | 13 | 9.8 |
| Income | 138,181 | 246,851 |
| English as primary language b | 94 | 71.2 |
| Children b | 21 | 15.9 |
| Religiosity b | 92 | 69.7 |
| Duration in the United States | ||
| Less than 15 years | 34 | 25.8 |
| 15 or more years | 94 | 71.2 |
| Missing | 4 | 3.0 |
| Mental Health | ||
| GAD-2 | 2.4 | 2.0 |
| PHQ-2c | 1.9 | 1.7 |
| COVID-19 related worry | 11.5 | 4.9 |
| Romantic Partner Conflict Scale | ||
| Compromise | 4.0 | 0.7 |
| Avoidance | 3.0 | 1.1 |
| Reactivity | 1.9 | 0.8 |
| Separation | 2.9 | 1.0 |
| Domination | 2.3 | 0.9 |
| Submissionc | 2.5 | 1.1 |
aParticipants could select more than one employment option so percentages will not sum to 100.0%
bReflects the number and percentage of participants answering “yes” to this question
The prevalence of any IPV among the sample was 47%. The rates of economic, physical, emotional, and in-law abuse were 31%, 10%, 29%, and 13%, respectively (Table 2). We conducted independent samples t-tests to assess differences in clinical characteristics among South Asian women who either did or did not report the presence of any IPV (Table 3). Participants experiencing IPV had higher levels of COVID-19 related worry and anxiety, but not depression. Additionally, women experiencing IPV reported significantly lower levels of compromise, and higher levels of submission, domination, and reactivity when confronted with conflict.
Table 2.
Prevalence and severity of intimate partner violence in sample
| Characteristic | (N = 98) | |
|---|---|---|
| n/M | %/SD | |
| Economic Abuse | ||
| Total severity | 13.3 | 3.3 |
| Presence (yes vs. no) | 30 | 30.6 |
| Exploitation subscale | 3.1 | 0.6 |
| Control subscale | 6.1 | 2.4 |
| Sabotage subscale | 4.1 | 0.8 |
| South Asian Violence Scale | ||
| Total severity | 15.5 | 3.5 |
| Emotional Abuse | ||
| Total severity | 7.0 | 2.4 |
| Presence | 28 | 28.6 |
| Physical Abuse | ||
| Total severity | 5.2 | 0.5 |
| Presence | 10 | 10.2 |
| In-Law Abuse | ||
| Total severity | 3.3 | 1.0 |
| Presence | 13 | 13.3 |
| Any IPV Present | 46 | 46.9 |
Table 3.
Characteristics of south asian women who did or did not report IPV
| Characteristic | Any IPV | No IPV | t(45) | p | ||
|---|---|---|---|---|---|---|
| M | SD | M | SD | |||
| IPV Severity | ||||||
| Economic | 14.9 | 4.4 | 12.0 | 0.00 | -4.5 | > 0.000 |
| Emotional | 8.2 | 3.2 | 6.0 | 0.00 | -4.7 | > 0.000 |
| Physical | 5.3 | 0.7 | 5.0 | 0.00 | -3.1 | 0.003 |
| In-Laws | 3.7 | 1.4 | 3.0 | 0.00 | -3.6 | 0.001 |
| Mental Health | ||||||
| GAD-2 | 2.9 | 2.1 | 2.0 | 2.0 | -2.2 | 0.027 |
| PHQ-2 | 2.2 | 1.7 | 1.8 | 1.8 | -1.3 | 0.214 |
| COVID-19 related worry | 13.5 | 5.3 | 10.1 | 4.1 | -3.5 | 0.001 |
| Romantic Partner Conflict Scale | ||||||
| Compromise | 3.7 | 0.8 | 4.2 | 0.5 | 3.6 | 0.001 |
| Avoidance | 3.1 | 1.1 | 2.8 | 1.1 | -1.7 | 0.095 |
| Reactivity | 2.2 | 0.9 | 1.6 | 0.6 | -3.2 | 0.002 |
| Separation | 2.9 | 0.9 | 2.9 | 1.1 | -0.4 | 0.655 |
| Domination | 2.6 | 0.9 | 2.1 | 0.9 | -2.6 | 0.010 |
| Submission | 3.0 | 1.0 | 2.2 | 1.0 | -3.9 | 0.000 |
We tested separate multiple regression models to identify demographic and clinical factors that predicted the severity of each form of IPV. As age and relationship duration were highly correlated, relationship duration was omitted from the models to avoid overfitting. None of the four models were significant overall. Depressive symptoms were a significant positive predictor of economic abuse severity (β = 0.80, p = .002). There were no statistically significant predictors of physical, emotional, in-law perpetrated abuse.
We performed multiple logistic regression analysis to identify risk factors of the presence of any IPV in a relationship among South Asian women (Table 4). In Model 1, only basic demographic information was included: age, income, education, employment. None of these demographic variables were significant predictors of the presence of IPV. In Model 2, the following more detailed demographic information was added: relationship status, sexual orientation, duration of time in the United States, if English was the primary language at home, if the participant was religious, and if they had children. With these variables in the model, we found that living in the United States for less than 15 years, as opposed to 15 or more years, was associated with a higher odds of experiencing IPV. Finally, in Model 3, we included the three mental health variables (depression, anxiety, and COVID-19 related worry). In this final model, we found that COVID-19 related worry positively increased one’s odds of experiencing IPV, as well as a lack of full-time employment.
Table 4.
Multiple logistic regression models to predict the presence of IPV
| IPV Experience | |||
|---|---|---|---|
| Characteristics | Model 1 | Model 2 | Model 3 |
| Age | 1.02 (0.95, 1.09) | 0.99 (0.90, 1.09) | 1.0 (0.90, 1.11) |
| Income | 1.00 (1.00, 1.00) | 1.00 (1.00, 1.00) | 1.00 (1.00, 1.00) |
| Education | |||
| Bachelor’s or less | Reference | Reference | Reference |
| Greater than Bachelor’s | 0.47 (0.16, 1.37) | 0.54 (0.14, 2.06) | 0.85 (0.17, 4.32) |
| Employment status | |||
| Full-time employment vs. no full-time employment | 0.33 (0.08, 1.32) | 0.25 (0.04, 1.53) | 0.13 (0.02, 0.99)* |
| Part-time employment vs. no part-time employment | 0.25 (0.04, 1.68) | 0.15 (0.01, 1.93) | 0.05 (0.00, 1.63) |
| Student status vs. no student status | 0.57 (0.12, 2.64) | 0.35 (0.04, 2.85) | 0.20 (0.02, 1.81) |
| Sexual orientation | |||
| Heterosexual | Reference | Reference | |
| Lesbian | 0.00 (0.0, Inf) | 0.00 (0.0, Inf) | |
| Bisexual | 0.43 (0.06, 3.23) | 0.28 (0.03, 2.69) | |
| Other | 0.26 (0.02, 4.11) | 0.10 (0.00, 2.57) | |
| Duration in the United States | |||
| 15 or more years | Reference | Reference | |
| Less than 15 years | 5.05 (1.0, 25.64)* | 5.30 (0.65, 43.39) | |
| English as primary language vs. not primary language | 1.07 (0.25, 4.62) | 1.44 (0.24, 8.58) | |
| Religion vs. not religious | 1.61 (0.39, 6.64) | 2.81 (0.50, 15.70) | |
| Children vs. no children | 0.72 (0.08, 6.77) | 1.07 (0.08, 13.61) | |
| Relationship status | |||
| Married | Reference | Reference | |
| Living with partner | 1.25 (0.20, 7.84) | 0.61 (0.07, 5.51) | |
| Not living with partner | 1.12 (0.17, 7.44) | 1.05 (0.11, 9.76) | |
| Separated | 0.00 (0.0, Inf) | 0.00 (0.0, Inf) | |
| Mental Health | |||
| Depression | 0.75 (0.45, 1.26) | ||
| Anxiety | 1.12 (0.76, 1.67) | ||
| COVID-19 related worry | 1.44 (1.11, 1.87)* | ||
Odds ratios are presented with 95% confidence intervals. ‘No IPV experience’ is the odds ratio reference category
* p < .05
Discussion
In this study, we examined IPV among South Asian women in the United States during COVID-19 and sought to identify predictors of violence in this population. We identified a concerningly high prevalence of IPV among South Asian women in the sample, with nearly half of respondents reporting having experienced any violence in their current relationship. This percentage was higher than literature from previous years reporting percentages of 23% and 40% [10, 14]. When comparing the clinical characteristics of South Asian participants who either did or did not experience IPV, COVID-19 related worry was significantly higher among the group with IPV present, but there were no significant differences in anxiety and depression. We also found that compared to those who did not report IPV, women who did experience violence reported lower levels of compromise when experiencing relationship conflicts. Interestingly, women experiencing IPV also reported higher levels of both submission and domination. This finding may indicate that in different situations, IPV survivors resort to one of these responses for their safety. Such a finding merits additional exploration of the cultural factors that may contribute to one’s response to relationship conflict, as well as day-to-day experiences of IPV survivors.
We also found that COVID-19 related worry was associated with a higher odds of experiencing IPV, while those experiencing IPV had elevated rates of both anxiety and COVID-19 related worry. These findings align with previous research indicating that survivors of IPV have elevated psychiatric symptoms [2, 3]. Interestingly, more severe anxiety and depression did not predict a higher odds of experiencing IPV. It is possible that many South Asian women are experiencing more anxiety and depression due to the pandemic, but that COVID-19 related worry is especially elevated in those also experiencing IPV.
In our regression models, we found that depressive symptomatology was positively associated with economic abuse among the South Asian sample, while neither anxiety nor COVID-19 related worry predicted the severity of any abuse. There were also no associations between any of the inputted predictor variables and either physical, in-law, or emotional abuse; however, this may be due to a lack of participants who reported any physical or in-law abuse. Our finding emphasizes the important relationship between depressive symptoms and experiences of IPV among South Asian women. Future research should further explore this relationship, particularly in understanding rates of suicidality and depressive episodes among South Asian IPV survivors. This can help inform more effective therapeutic interventions for IPV survivors by ensuring that co-occurring depression and/or suicidality is properly addressed.
In terms of predicting the presence of IPV, we found that once mental health variables were introduced into the logistic regression model, COVID-19 related worry and full-time employment were both significantly related to the odds of experiencing IPV. Full-time employment may indicate that the respondent had a sense of independent financial security, lowering the risk of manipulation and control by a partner due to their lack of financial independence. Additionally, a full-time job may provide an external social support network, providing women with the opportunity to seek out help and assistance when faced with conflict inside the household. Previous literature in this population has established that a lack of social support is an important risk factor for experiencing IPV [35]. Taken together with our findings, it appears that financial advocacy and community support are an important means of supporting South Asian IPV survivors and should be further explored in a healing context.
Our study had several strengths worth noting. First, we were able to recruit a relatively large sample of South Asian women, a population not typically represented in IPV research. Four presentations of IPV were measured using two different validated assessments, allowing for multiple dimensions of abuse to be measured. Many IPV-related research studies do not account for cultural relevance; however, the South Asian Violence Screen (SAVS) is a culturally validated measure for detecting IPV in South Asian populations.
There are also several key limitations that merit discussion. Our South Asian sample was predominantly Indian, so our analysis did not allow for a detection of differences among different South Asian groups. There are unique characteristics of mental health and IPV among Asian Indian individuals that may not apply to other ethnicities. Among South Asian American undergraduates, Bangladeshi and Pakistani Americans had lower rates of suicidal ideation compared to Indian Americans [36]. It is possible that facets of Asian Indian ethnicity make one more vulnerable to suicidality compared to other South Asian ethnicities. There are also facets of Indian culture that may uniquely contribute to experiencing IPV. Previous research has identified a positive association between enculturation and acceptance of IPV among Indian Gujurati individuals [37]. Future research could help to clarify if such cultural values also affect views towards IPV in different South Asian ethnic groups. Other limitations to this study were that we used self-reported measures of IPV, introducing the risk of reporting bias. Our sample was cross-sectional since we did not have pre-COVID comparison data; we cannot make any determinations regarding the causal effects of the pandemic on IPV.
Future research should explore the effects of interactions between cultural factors and environmental stressors on the prevalence of IPV among understudied populations such as South Asian women. This approach could inform the development of more effective screening tools in health settings to assess IPV in different cultural contexts. Research should continue exploring the nuances through which South Asian culture may affect one’s experiences with IPV, as well as co-occurring psychiatric disorders among survivors. A greater understanding of the most common forms of IPV in South Asian communities can also inform the development of culturally-relevant therapeutic interventions for survivors.
Footnotes
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References
- 1.Breiding M, Basile KC, Smith SG, Black MC, Mahendra RR. (2015). Intimate partner violence surveillance: Uniform definitions and recommended data elements. Version 2.0.
- 2.Smith SG, Zhang X, Basile KC, Merrick MT, Wang J, Kresnow MJ, Chen J. (2018). The national intimate partner and sexual violence survey: 2015 data brief– updated release. [DOI] [PMC free article] [PubMed]
- 3.Coker AL, Davis KE, Arias I, Desai S, Sanderson M, Brandt HM, Smith PH. Physical and mental health effects of intimate partner violence for men and women. Am J Prev Med. 2002;23(4):260–8. doi: 10.1016/S0749-3797(02)00514-7. [DOI] [PubMed] [Google Scholar]
- 4.Stubbs A, Szoeke C. (2021). The effect of intimate partner violence on the physical health and health-related behaviors of women: a systematic review of the literature.Trauma, Violence, & Abuse,1524838020985541. [DOI] [PubMed]
- 5.Mburia-Mwalili A, Clements-Nolle K, Lee W, Shadley M, Yang W. Intimate partner violence and depression in a population-based sample of women: can social support help? J interpers Violence. 2010;25(12):2258–78. doi: 10.1177/0886260509354879. [DOI] [PubMed] [Google Scholar]
- 6.Beydoun HA, Beydoun MA, Kaufman JS, Lo B, Zonderman AB. Intimate partner violence against adult women and its association with major depressive disorder, depressive symptoms and postpartum depression: a systematic review and meta-analysis. Soc Sci Med. 2012;75(6):959–75. doi: 10.1016/j.socscimed.2012.04.025. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 7.Nixon RD, Resick PA, Nishith P. An exploration of comorbid depression among female victims of intimate partner violence with posttraumatic stress disorder. J Affect Disord. 2004;82(2):315–20. doi: 10.1016/j.jad.2004.01.008. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 8.Chuang CH, Cattoi AL, McCall-Hosenfeld JS, Camacho F, Dyer AM, Weisman CS. Longitudinal association of intimate partner violence and depressive symptoms. Mental health in family medicine. 2012;9(2):107. [PMC free article] [PubMed] [Google Scholar]
- 9.Stockman JK, Hayashi H, Campbell JC. Intimate partner violence and its health impact on ethnic minority women. J Women’s Health. 2015;24(1):62–79. doi: 10.1089/jwh.2014.4879. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 10.Hurwitz EJH, Gupta J, Liu R, Silverman JG, Raj A. Intimate partner violence associated with poor health outcomes in US south asian women. J Immigr Minor Health. 2006;8(3):251–61. doi: 10.1007/s10903-006-9330-1. [DOI] [PubMed] [Google Scholar]
- 11.Robertson HA, Chaudhary Nagaraj N, Vyas AN. Family violence and child sexual abuse among South Asians in the US. J Immigr Minor Health. 2016;18(4):921–7. doi: 10.1007/s10903-015-0227-8. [DOI] [PubMed] [Google Scholar]
- 12.Soglin LF, Ragavan MI, Li JC, Soglin DF. (2019). A validated screening instrument for identifying intimate partner violence in South Asian immigrant women.Journal of Interpersonal Violence. [DOI] [PubMed]
- 13.Raj A, Liu R, McCleary-Sills J, Silverman JG. South asian victims of intimate partner violence more likely than non-victims to report sexual health concerns. J Immigr Health. 2005;7(2):85–91. doi: 10.1007/s10903-005-2641-9. [DOI] [PubMed] [Google Scholar]
- 14.Raj A, Silverman JG. Immigrant south asian women at greater risk for injury from intimate partner violence. Am J Public Health. 2003;93(3):435–7. doi: 10.2105/AJPH.93.3.435. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 15.Raj A, Livramento KN, Santana MC, Gupta J, Silverman JG. Victims of intimate partner violence more likely to report abuse from in-laws. Violence Against Women. 2006;12(10):936–49. doi: 10.1177/1077801206292935. [DOI] [PubMed] [Google Scholar]
- 16.Cunradi CB, Caetano R, Schafer J. Socioeconomic predictors of intimate partner violence among White, Black, and hispanic couples in the United States. J family violence. 2002;17(4):377–89. doi: 10.1023/A:1020374617328. [DOI] [Google Scholar]
- 17.Acevedo BP, Lowe SR, Griffin KW, Botvin GJ. Predictors of intimate partner violence in a sample of multiethnic urban young adults. J interpers Violence. 2013;28(15):3004–22. doi: 10.1177/0886260513488684. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 18.Gosangi B, Park H, Thomas R, Gujrathi R, Bay CP, Raja AS, Seltzer SE, Chadwick Balcom M, McDonald ML, Orgill DP, Harris MB, Boland GW, Rexrode K, Khurana B. Exacerbation of physical intimate Partner violence during COVID-19 pandemic. Radiology. 2021;298(1):E38–E45. doi: 10.1148/radiol.2020202866. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 19.Piquero AR, Riddell JR, Bishopp SA, Narvey C, Reid JA, Piquero NL. Staying home, staying safe? A short-term analysis of COVID-19 on Dallas domestic violence. Am J criminal justice. 2020;45(4):601–35. doi: 10.1007/s12103-020-09531-7. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 20.Boserup B, McKenney M, Elkbuli A. Alarming trends in US domestic violence during the COVID-19 pandemic. Am J Emerg Med. 2020;38(12):2753–5. doi: 10.1016/j.ajem.2020.04.077. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 21.Piquero AR, Jennings WG, Jemison E, Kaukinen C, Knaul FM. (2021). Evidence from a systematic review and meta-analysis: Domestic Violence during the COVID-19 Pandemic.Journal of Criminal Justice,101806. [DOI] [PMC free article] [PubMed]
- 22.Ettman CK, Abdalla SM, Cohen GH, Sampson L, Vivier PM, Galea S. Prevalence of depression symptoms in US adults before and during the COVID-19 pandemic. JAMA Netw Open. 2020;3(9):e2019686–6. doi: 10.1001/jamanetworkopen.2020.19686. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 23.Panchal N, Kamal R, Orgera K, Cox C, Garfield R, Hamel L, Chidambaram P. (2020). The implications of COVID-19 for mental health and substance use.Kaiser family foundation,21.
- 24.Hawes MT, Szenczy AK, Klein DN, Hajcak G, Nelson BD. (2021). Increases in depression and anxiety symptoms in adolescents and young adults during the COVID-19 pandemic.Psychological Medicine,1–9. [DOI] [PMC free article] [PubMed]
- 25.Liu CH, Erdei C, Mittal L. Risk factors for depression, anxiety, and PTSD symptoms in perinatal women during the COVID-19 pandemic. Psychiatry Res. 2021;295:113552. doi: 10.1016/j.psychres.2020.113552. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 26.Kalyanaraman Marcello R, Dolle J, Tariq A, Kaur S, Wong L, Curcio J, Thachil R, Yi SS, Islam N. Disaggregating asian race reveals COVID-19 disparities among asian american patients at New York City’s Public Hospital System. Public Health Rep. 2022;137(2):317–25. doi: 10.1177/00333549211061313. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 27.Misra S, Wyatt LC, Wong JA, Huang CY, Ali SH, Trinh-Shevrin C, Islam NS, Yi SS, Kwon SC. Determinants of depression risk among three asian american subgroups in New York City. Ethn Dis. 2020;30(4):553. doi: 10.18865/ed.30.4.553. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 28.Lozano P, Rueger SY, Lam H, Louie N, Southworth A, Maene C, Mo Y, Randal F, Kim K. (2021). Prevalence of depression symptoms before and during the CoViD- 19 pandemic among two Asian American ethnic groups.Journal of immigrant and minority health,1–9. [DOI] [PMC free article] [PubMed]
- 29.Sadler GR, Lee HC, Lim RSH, Fullerton J. Recruitment of hard-to‐reach population subgroups via adaptations of the snowball sampling strategy. Nurs Health Sci. 2010;12(3):369–74. doi: 10.1111/j.1442-2018.2010.00541.x. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 30.Zacchilli TL, Hendrick C, Hendrick SS. The romantic partner conflict scale: a new scale to measure relationship conflict. J Social Personal Relationships. 2009;26(8):1073–96. doi: 10.1177/0265407509347936. [DOI] [Google Scholar]
- 31.Löwe B, Kroenke K, Gräfe K. Detecting and monitoring depression with a two- item questionnaire (PHQ-2) J Psychosom Res. 2005;58(2):163–71. doi: 10.1016/j.jpsychores.2004.09.006. [DOI] [PubMed] [Google Scholar]
- 32.Kroenke K, Spitzer RL, Williams JB, Monahan PO, Löwe B. Anxiety disorders in primary care: prevalence, impairment, comorbidity, and detection. Ann Intern Med. 2007;146(5):317–25. doi: 10.7326/0003-4819-146-5-200703060-00004. [DOI] [PubMed] [Google Scholar]
- 33.Liu CH, Zhang E, Hahm HC. (2020). COVID-19-Related Worry and Grief Scales.
- 34.Postmus JL, Plummer SB, Stylianou AM. Measuring economic abuse in the lives of survivors: revising the scale of economic abuse. Violence Against Women. 2016;22(6):692–703. doi: 10.1177/1077801215610012. [DOI] [PubMed] [Google Scholar]
- 35.Carlson BE, McNutt LA, Choi DY, Rose IM. Intimate partner abuse and mental health: the role of social support and other protective factors. Violence Against Women. 2002;8(6):720–45. doi: 10.1177/10778010222183251. [DOI] [Google Scholar]
- 36.Lane R, Cheref S, Miranda R. Ethnic differences in suicidal ideation and its correlates among south asian american emerging adults. Asian Am J Psychol. 2016;7(2):120. doi: 10.1037/aap0000039. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 37.Yoshihama M, Blazevski J, Bybee D. Enculturation and attitudes toward intimate partner violence and gender roles in an asian indian population: implications for community-based prevention. Am J Community Psychol. 2014;53(3):249–60. doi: 10.1007/s10464-014-9627-5. [DOI] [PubMed] [Google Scholar]