A Longitudinal Examination of Domestic Violence and Psychological Distress for Australian Women

Abstract

Whilst there is evidence suggesting that women have worse mental health outcomes after experiencing domestic violence (DV), there is a lack of investigation into the long-term effects of DV on psychological distress and risk factors that may exacerbate poor outcomes. To address this evidence gap, the current study analysed national data from the Australian Longitudinal Study on Women’s Health in relation to DV, psychological distress and potential risk factors for Australian women. Participants (n = 4,156) completed a pre and post DV Kessler Psychological Distress Scale (K10), DV measure, and measures of low self-esteem, financial stress, area of residence and perceived social support. Linear regression and linear regression with interaction effects were utilised for the analyses. The study found that experiencing DV was associated with greater psychological distress after experiencing DV when compared to participants who did not experience DV (B = 2.45, 95% CI [2.04, 2.86]). Risk factors of low self-esteem (B = 1.04, 95% CI [0.28, 1.80]) and financial stress (B = 1.52, 95% CI [0.26, 2.79]) were also associated with increased psychological distress after DV. However, contrary to expectations, there was no evidence that low social support (B = 1.66, 95% CI [−0.66, 3.98]) or remote area of residence (B = −0.52, 95% CI [−1.97, 0.94]) increased psychological distress. These findings highlight a temporal order of events, with experiencing DV being related to higher psychological distress over several years, which may be exacerbated by low self-esteem and financial stress. Recommendations for policy development include adopting a holistic approach that considers supporting financial wellbeing and enhancing self-esteem for women after experiencing DV. Future research should investigate the role of social support and area of residence as factors associated with differing psychological distress outcomes for women who experience DV.

Keywords

intimate partner violence/abuse mental health effects gender-based violence research methodology/measurement

Introduction

Violence against women is described as ‘any act of gender-based violence that results in, or is likely to result in, physical, sexual or psychological harm or suffering to women’ (OHCHR, 1993). Domestic violence (DV) is violence perpetrated by an intimate partner or family member, which has been linked to various mental health consequences. However, longitudinal literature that investigates the long-term association of experiencing DV on women’s psychological distress over time, as well understanding what risk factors may be associated with increased psychological distress, are limited. The current study investigates this relationship to further the current literature surrounding DV and how it impacts women’s psychological distress and wellbeing over time.

In Australia, it is estimated that after 15 years of age, one in four women (27%) experience violence by an intimate partner or family member (Australian Bureau of Statistics, 2021–2022). Whilst there is increased awareness surrounding violence against women and how it negatively impacts physical and mental wellbeing, the reporting of DV continues to rise (Webster et al., 2018). This increase is particularly seen in younger women, with women aged between 18 and 34 reporting higher rates of physical and sexual violence compared to women in older age groups (Australian Institute of Health and Welfare, 2019). The consequences of experiencing violence have also been documented, with violence against women being responsible for an estimated 5% of the burden of disease in Australia (Webster, 2016), with the largest proportion (70%) being attributed to depression and anxiety (Webster, 2016). For 18- to 44-year-old women, experiencing violence was the highest preventable risk factor for increased mortality and morbidity, ranking higher than smoking and obesity (Webster, 2016).

Experiencing Domestic Violence and Psychological Distress

DV has been associated with psychiatric disorders and higher rates of these disorders across the life span (Bacchus et al., 2018; Cirici Amell et al., 2023; Patton et al., 2022; Rees et al., 2011). Within Australia, research has suggested that approximately half of all women who have experienced DV are subsequently diagnosed with a mental health disorder or display symptoms of mental disorders (Moulding et al., 2021). Some of these disorders can include depression, anxiety, post-traumatic stress disorder, sleep disorders, eating disorders and an increased risk of suicide and self-harm (Patton et al., 2022; Rees et al., 2011; World Health Organization, 2021). Additionally, high levels of psychological distress, which is a term that is characterised by a variety of mental health issues including depression and anxiety, have been found to reflect an increased likelihood of being diagnosed and/or seeking assistance for depression and/or anxiety (Andrews & Slade, 2001).

Depression and its related symptoms are recognised as being responsible for a large proportion of the burden of disease in Australia (approximately 36%) for women who have experienced DV (Webster, 2016). A meta-analysis conducted on the impacts of DV on mental health outcomes found that, from 13 studies, nine reported a positive association between DV and symptoms of depression, with all but two being statistically significant (Bacchus et al., 2018). Another systematic review on longitudinal studies found that the onset of depressive symptoms during or after the violence typically decreased in severity over time (Patton et al., 2022). However, these findings directly contradict some evidence suggesting that DV is related to psychological harm experienced over several years (Moulding et al., 2021), with additional literature suggesting a relationship between women who experienced DV at 21 years of age and new cases of depression at 30 years (Ahmadabadi et al., 2020). This highlights that violence may lead to the onset of depressive symptoms and new diagnoses for women who had not been diagnosed with depression previously, however, is subject to conflicting evidence.

Anxiety is another common disorder related to increased psychological distress, with evidence showing that approximately 41% of women display anxiety symptoms as a result of experiencing DV (Moulding et al., 2021). A systematic review found a strong association between increased anxiety symptoms and a history of DV (Dillon et al., 2013). However, this study was limited by only 16 studies being eligible for analysis, with none examining anxiety independently. In contrast, a meta-analysis of longitudinal studies found that time after DV exposure led to higher quality of life and lower post-traumatic stress, but found inconclusive results as to whether anxiety also decreased over time (Patton et al., 2022). Of the 36 articles eligible for inclusion, only five studies tested changes in anxiety over time, with three reporting significant decreases in anxiety. However, Patton et al. (2022) noted that changes were no longer observed after an 8-month period, suggesting that anxiety-related distress may continue after this time.

Factors that Mitigate and Exacerbate Psychological Distress After Domestic Violence

The impact of financial stress on psychological wellbeing after experiencing DV can be seen throughout the literature. Moulding et al. (2021) found that 40% of women in Australia who experienced violence earned less than $30,000 a year. An international study reported that women who experienced DV had lower income than women who had not experienced DV, and this lower income was found to be associated with increased mental illness diagnoses after DV (Adams et al., 2012). However, there is limited evidence exploring difficulty managing on available income and psychological distress after experiencing DV, especially within Australia, highlighting an unclear trajectory for the association of financial stress and psychological distress after DV.

Remote area of residence is often discussed as a risk factor for exacerbating poor mental health after DV. The Australian Bureau of Statistics (ABS) reported that approximately 21% of women who experienced DV in 2013 lived outside of major cities, compared to women who lived in major cities having a 15% prevalence of DV (Australian Bureau of Statistics, 2013). This suggests higher risk of experiencing DV for women who live in regional, rural and remote Australia. A review of the literature has suggested that social isolation and rural location are key factors that influence women’s coping and help seeking behaviours (Wendt et al., 2015), with a USA study finding isolation to exacerbate the hidden nature of DV and access to related services (Lanier & Maume, 2009). In contrast, a qualitative Australian study found mixed evidence as to whether remote location is a barrier to accessing support or health services after DV, with rural women seeing their location as a barrier to social support, not health services (Wendt et al., 2017), conflicting with existing evidence (Lanier & Maume, 2009; Wendt et al., 2015). However, it is important to consider that whilst Wendt et al. (2017) is limited by a small sample size of rural Australian women, there is a lack of other recent empirical studies that investigate this population to consolidate these findings.

Perceived social support has consistently been associated with decreased psychological distress after DV, as it may mitigate the effects of poor mental wellbeing (Mburia-Mwalili et al., 2010). High levels of social support have been related to lower depressive symptoms and higher quality of life after DV, with these symptoms decreasing over time (Patton et al., 2022). Additionally, Moulding et al., (2021) found that women who experience DV seek out more support groups, and these rates increase when women have been diagnosed with a psychiatric illness (Moulding et al., 2021). Anxiety and post-traumatic stress have also been found to decrease with higher levels of social support; whilst life stressors have been consistently associated with higher levels of post-traumatic stress symptoms (Patton et al., 2022). Depressive symptoms after DV have also been associated with lower perceived social support, as well as impaired trust in others (Matheson et al., 2015). Whilst these studies highlight social support as a potential mitigating factor for psychological distress, the literature lacks longitudinal examination of the impact of low social support on psychological distress levels after experiencing DV.

Self-esteem has also been investigated as a risk factor for psychological distress after experiencing DV. One study with a sample of 496 women found low self-esteem to be associated with previous experiences of DV (Bigizadeh et al., 2021). Another longitudinal study found that experiencing DV predicted higher psychological distress and poor self-esteem (Shen & Kusunoki, 2019). However, both studies were conducted internationally and may not be generalisable to the Australian population. As a result, research into self-esteem in relation to psychological distress after experiencing DV in Australia is currently lacking.

The Current Study

The current understanding surrounding DV and its impact on psychological distress is lacking in some key areas. Whilst experiencing DV has been associated with poor mental health and increased psychiatric illness diagnosis (Bacchus et al., 2018), there is a lack of evidence exploring the impact and persistence of psychological distress over time for women who have experienced DV (Townsend et al., 2022), especially within Australia. It has also been recognised that there is a gap with respect to longitudinal studies that consider DV and that subsequently analyse the differential effects for psychological outcomes over time (Bacchus et al., 2018). Furthermore, existing studies have found conflicting results for the association of psychological distress and risk factors, including the influence of social, economic and mental health risk factors over time for women who experience DV (Bacchus et al., 2018; Sanz-Barbero et al., 2019). Once again, there is a lack of Australian research that analyse associations with risk factors, further demonstrating a need for more studies in the space.

This study aimed to investigate whether psychological distress changes over time for women who have experienced domestic violence, when compared to those who have not experienced domestic violence. Additionally, the current study also aimed to investigate whether the risk factors of remote area of residence, low social support, financial stress and low self-esteem further increased psychological distress for women who experienced domestic violence.

Methods

Study Design

The current study is a quantitative study that utilises longitudinal data collected by the Australian Longitudinal Study on Women’s Health (ALSWH) for participants born 1989 to 1995.

Participants and Procedure

ALSWH recruited the 1989 to 1995 birth cohort from the general population of women in Australia, utilising an open recruitment method. At time of recruitment in 2012 to 2013, the eligibility criteria included being a female Australian resident aged 18 to 23 years who consented to participate (including to linkage between their survey and administrative data). The cohort is overrepresented with participants who have a tertiary education and is underrepresented for women who speak English as a second or subsequent language (Loxton et al., 2017, 2019). Ethics approval was given by the University of Newcastle Human Research Ethics Committee (HREC) for the current study; approval number H-2023-0228, as well as approval from the ALSWH Data Access Committee to access and utilise the data.

Sampling Strategy

The sample analysed (n = 4,156) consisted of a test group (n = 1,818) and a control group (n = 2,338). Women in both groups must have completed the psychological distress scale (K10) at both Wave 1 and Wave 6 to be eligible. Women who had reported experiencing DV at Wave 1 were excluded from both the test and control groups (n = 7,557). The test group consisted of participants from the 1989 to 1995 cohort who reported experiencing DV at any time between Waves 2 (2014) and Wave 6 (2019/20), while the control group was comprised of participants who did not report experiencing DV between Wave 2 and Wave 6.

This approach allowed for direct comparison of women who experienced DV and those who did not. The sample sizes for the adjusted effect estimates in the first analysis and the effect estimates in the risk factor analysis were slightly lower due to low percentages of missing data on covariates. The exact numbers for each analysis are reported in the results.

Survey Measures

Domestic Violence, Psychological Distress and Risk Factors

Abbreviated Community Composite Abuse Scale

Experiencing DV was based on responses to the Abbreviated Community Composite Abuse Scale (ACCAS). The ACCAS measures sexual, physical and emotional violence, financial abuse and coercion. The ACCAS contained 12 items in Waves 1 to 4, and 21 items in Waves 5 to 6. This scale was developed by modifying the Community Composite Abuse Scale, which was created by modifying the Composite Abuse Scale. Both scales have been validated as highly reliable measures of abuse (Hegarty et al., 1999; Loxton et al., 2013). Any ‘Yes, in the last 12 months’ or ‘Yes, more than 12 months ago’ responses to items within the ACCAS through Waves 2 to 6 were treated as indicating DV. The ACCAS item ‘Became upset if dinner/housework wasn’t done when they thought it should be’ was excluded, as its face validity as a sole measure of DV is debatable and its inclusion may have artificially inflated the prevalence of DV.

Kessler Psychological Distress Scale

The study used participant scores for the Kessler Psychological Distress Scale (K10; Kessler et al., 2002), which measures psychological distress on a scale of 10 to 50, with higher scores equating to greater distress ranging on a 5-point Likert-type scale. The K10 has demonstrated high discriminate validity (Andrews & Slade, 2001; Kessler et al., 2002), and is a standardised measure of psychological distress recommended by the ABS for use in research (Australian Bureau of Statistics, 2012). The current study used K10 scores reported Wave 1 as the ‘pre’ measure, and Wave 6 as the ‘post’ measure. Both K10 scores and cut off points recommended by the Australian Bureau of Statistics (2012) were used in the analysis. These cut offs include ‘low’ (scores 10–15), ‘moderate’ (scores 16–21), ‘high’ (scores 22–29) and ‘very high’ (scores 30–50).

Accessibility/Remoteness Index of Australia

Area of residence was measured area of residence using Accessibility/Remoteness Index of Australia (ARIA+), which is determined based on a participant’s residential address. The current study treated ARIA+ as a categorical variable, with the categories ‘major cities’, ‘inner regional’ and ‘outer regional/remote/very remote’ (Australian Bureau of Statistics, 2023).

Managing on Income

Financial security was measured using the survey question, ‘How do you manage on the income you have available?’. Responses were collapsed to make a trichotomous variable: ‘difficult always/impossible’, ‘difficult sometimes’ and ‘not too bad/easy’.

MOS Social Support Survey

The MOS Social Support Survey is a 19-item questionnaire measured on a 5-point Likert-type scale, with higher scores indicating greater levels of social support. This scale also measures the various dimensions of social support, including emotional/informational, tangible, affectionate and positive social interaction (Sherbourne & Stewart, 1991). Scores were categorised based on mean scores of responses to having social support for the current study. This included ‘none of the time’ (mean scores ≤2), ‘some of the time’ (mean scores >2 and ≤3), ‘most of the time’ (mean scores >3 and ≤4) and ‘all of the time’ (mean scores >4 and ≤5; Russell & Smith, 2002). Mean scores were separately treated as continuous in an additional sensitivity analysis.

Rosenburg Self-Esteem Scale

Rosenburg Self-Esteem Scale (RSES) measures self-esteem, with higher scores indicating greater levels of self-esteem (scores ranging from 0 to 30). The scale measures self-competence and self-liking (Rosenberg, 1965), demonstrating predictive validity, internal consistency and reliability (Rosenberg, 1965; Schmitt & Allik, 2005). The current study categorised the RSES into three levels using the following cut offs: ‘low’ (scores 0–15), ‘average’ (scores 16–19) and ‘high’ (scores 20–30; García et al., 2019).

Sociodemographic Measures

Participants were asked questions relating to sociodemographic characteristics. These included: marital status, which was collapsed to ‘partnered’ or ‘non partnered’; country of birth, collapsed to ‘Australian born’, ‘other English-speaking country’ and ‘other’. Highest qualification, collapsed to ‘year 12 or below’, ‘certificate/diploma’ and ‘university’; fluency in English, either ‘yes’ or ‘no’; and language spoken at home, including ‘English’, ‘European language’, ‘Asian language’ and ‘other language’.

Data Analysis

StataBE 18 (StataCorp LLC, 2023) was utilised for all data analyses. For the first analysis, linear regression modelling was used to estimate the association of experiencing DV on psychological distress. This analysis aimed to determine whether there was an association between experiencing DV and psychological distress compared to those who did not experience DV. The study utilised K10 scores at Wave 6 as the dependent variable, DV reported or not reported in Waves 2 to 6 as the predictor, and K10 scores at Wave 1 as a covariate. The regression models controlled for potentially confounding sociodemographic factors that were plausibly associated with both the exposure (DV) and the outcome (psychological distress), in line with recommendations by Greenland et al. (1999). These factors included area of residence, country of birth, highest qualification, marital status and ability to manage on available income.

For the risk factor analyses, the study used a linear regression model with K10 scores at Wave 6 as the dependent variable, an indicator variable for DV reported in Waves 2 to 6, a categorical risk factor and an interaction term between DV reported in Waves 2 to 6 and a categorical risk factor. Each risk factor was measured at Wave 6 and included in a separate model to maximise sample size and statistical power. The study included the following risk factors: area of residence, self-esteem, social support and managing on income. K10 at Wave 1 was used as a covariate to control for psychological distress at baseline. The categorical variables, including those with more than two categories, were specified as factor variables in the regression modelling (using Stata’s factor-variable notation, i.variable). This produces a separate estimate for each level of the categorical variable, with Stata’s factor-variable notation avoiding the need to explicitly create dummy variables (Gould, n.d). These risk factor models were not adjusted for additional covariates in order to maximise power to detect evidence of interaction effects. The purpose of these analyses was to examine if there were any interactions between risk factors and DV on psychological distress.

Results

Sample Characteristics

As seen in Table 1, participants had diverse sociodemographic backgrounds at Wave 1 in 2012 to 2013. Most women lived in major cities (75%), and half had completed higher-level education (50%). Comparatively, there was only a small percentage of women who were born in a non-English speaking country (3%), did not speak fluent English (2%) and spoke another language at home (2%). Table 2 contains the demographics and responses for each Wave 6 risk factor.

Table 1.

Sociodemographic Characteristics of Participants at Wave 1.

Wave 1 characteristics	Yes DV in Waves 2 to 6		No DV in Waves 2 to 6		Overall
Wave 1 characteristics	n	%	n	%	n	%
Area of residence
Major cities	1,373	75.5	1,743	74.6	3,116	75.0
Inner regional	301	16.6	428	18.3	729	17.5
Outer regional/Remote/Very remote	143	7.9	165	7.1	308	7.4
Missing	1	0.1	2	0.1	3	0.1
Managing on income
Not too bad/easy	740	40.7	1,229	52.6	1,969	47.4
Difficult sometimes	679	37.3	778	33.3	1,457	35.1
Difficult always/impossible	398	21.9	331	14.2	729	17.5
Missing	0	0	1	0.1	1	0.0
Country of birth
Australian born	1,500	82.5	1,889	80.8	3,386	81.5
Other English-speaking country	74	4.1	101	4.3	175	4.2
Other	45	2.5	68	2.9	113	2.7
Missing	199	10.9	280	12.0	479	11.5
Highest qualification
Year 12 or below	930	51.2	1,137	48.6	2,067	49.7
Certificate/Diploma	449	24.7	386	16.5	835	20.1
University	439	24.1	815	34.9	1,254	30.2
Missing	0	0	0	0	0	0
Marital status
Partnered	454	25.0	509	21.8	963	23.2
Non partnered	1,364	75.0	1,829	78.2	3,193	76.8
Missing	0	0	0	0	0	0
Speaks fluent English
Yes	1,815	43.7	2,333	56.1	4,148	99.8
No	3	0.1	5	0.1	8	0.2
Missing	0	0	0	0	0	0
Language spoken at home
English	1,675	92.1	2,129	91.1	3,804	91.5
European language	5	0.3	5	0.2	10	0.2
Asian language	19	1.0	23	1.0	42	1.0
Other language	19	1.0	27	1.2	46	1.1
Missing	100	5.6	154	6.5	254	6.1

Note. DV = domestic violence.

Table 2.

Descriptive Statistics of Risk Factors at Wave 6.

Risk factor	Yes DV		No DV		Overall
Risk factor	n	%	n	%	n	%
N	1,818	43.7	2,338	56.3	4,156	100
Area of residence
Major cities	1,345	74.0	1,656	70.8	3,001	72.2
Inner regional	275	15.1	407	17.4	682	16.4
Outer regional/Remote/Very remote	131	7.2	177	7.6	308	7.4
Missing	67	3.7	98	4.2	165	4.0
Total eligible for analysis	1,751	43.9	2,240	56.1	3,991	100
Self-esteem
Low self-esteem	610	33.6	408	17.5	1,018	24.5
Average self-esteem	421	23.2	543	23.2	964	23.2
High self-esteem	766	42.1	1,373	58.7	2,139	51.5
Missing	21	1.2	14	0.6	35	0.8
Total eligible for analysis	1,797	43.6	2,324	56.4	4,121	100
Social support
Social support ‘None of the time’	86	4.7	37	1.6	123	3.0
Social support ‘Some of the time’	271	14.9	152	6.5	423	10.2
Social support ‘Most of the time’	589	32.4	603	25.8	1,192	28.7
Social support ‘All of the time’	842	46.3	1,519	65.0	2,361	56.8
Missing	30	1.7	27	1.2	57	1.4
Total eligible for analysis	1,788	43.6	2,311	56.4	4,099	100
Ability to manage on income
Difficult always/impossible	265	14.6	157	6.7	422	10.2
Difficult sometimes	528	19.0	493	21.1	1,021	24.6
Not too bad/easy	993	54.6	1,660	71.0	2,653	36.8
Missing	32	1.8	38	1.2	60	1.4
Total eligible for analysis	1,786	43.6	2,310	56.4	4,096	100

Note. DV = domestic violence.

Participants who experienced DV reported both higher mean K10 scores before experiencing DV at Wave 1 (mean = 21.74, 95% CI [21.39, 22.09]), and after experiencing DV at Wave 6 (mean = 21.63, 95% CI [21.28, 21.99]), compared to those who did not experience DV (Wave 1 mean = 19.32, 95% CI [19.05, 19.58]; Wave 6 mean = 18.05, 95% CI [17.80, 18.31]). Additionally, as seen in Table 3, women who had experienced DV had a greater prevalence of very high psychological distress scores (approximately 16% at Wave 1 and Wave 6), compared to women who did not experience DV (9% at Wave 1 and 7% at Wave 6).

Table 3.

Categorised K10 scores at Wave 1 and Wave 6.

K10 score	Yes DV		No DV
K10 score	n	%	n	%
Wave 1
Low	427	23.5	786	33.6
Moderate	590	32.5	843	36.1
High	505	27.8	493	21.1
Very high	296	16.2	216	9.2
Wave 6
Low	464	25.5	997	42.6
Moderate	529	29.1	762	32.6
High	533	29.3	427	18.3
Very high	292	16.1	152	6.5

Note. Categories are based on Australian Bureau of Statistics (2012) guidelines. DV = domestic violence.

Aim 1: Domestic Violence and Psychological Distress

Women who experienced DV between Waves 2 and 6 had K10 scores at Wave 6 that were 2.45 units higher (indicating greater psychological distress), compared to women who did not experience DV between Waves 2 and 6, after controlling for K10 score at Wave 1 and confounding factors (B = 2.45, 95% CI [2.04, 2.86]; see Table 4).

Table 4.

Domestic Violence and Psychological Distress Adjusted and Unadjusted Effect Estimates.

Predictor	Unadjusted effect estimates	Adjusted effects estimates
Predictor	Estimate [95% CI]	Estimate [95% CI]
Intercept	9.41 [8.84, 9.98]	9.71 [8.82, 10.50]
DV at Waves 2 to 6
No	Ref.	Ref.
Yes	2.49 [2.11, 2.88]	2.45 [2.04, 2.86]
K10 score at Wave 1
Continuous	0.45 [0.42, 0.47]	0.43 [0.40, 0.47]
Covariates
Area of residence at Wave 1
Major cities	–	Ref.
Inner regional	–	0.63 [0.10, 1.16]
Outer regional/Remote/Very remote	–	−0.10 [−0.88, 0.67]
Highest qualification at Wave 1
Year 12 or below	–	Ref.
Certificate/diploma	–	−0.24 [−0.77, 0.29]
University	–	−0.83 [−1.29, 0.36]
Country of birth at Wave 1
Australian born	–	Ref.
Other English-speaking	–	0.35 [−0.59, 1.28]
Other	–	1.10 [−0.08, 2.23]
Marital status at Wave 1
Partnered	–	Ref.
Non-partnered	–	−0.04 [−0.52, 0.44]
Managing on income at Wave 1
It’s not too bad/it is easy	–	Ref.
Difficult sometimes	–	0.40 [−0.52, 0.44]
Difficult always/impossible	–	1.12 [0.55, 1.70]

Note. Dependent variable: K10 at Wave 6.

Aim 2: Risk Factors and Psychological Distress After Experiencing Domestic Violence

Area of Residence

As seen in Table 2, the sample contained a very small number of participants in outer regional/remote/very remote locations, with only 308 participants (7% of our sample). Contrary to expectations, results showed no evidence for an interaction between area of residence at Wave 6 and experiencing DV on K10 score in Wave 6 (Table 5). This suggests that there was no evidence that the effect of DV on psychological distress differed according to area of residence. There was also no evidence for an effect of area of residence on psychological distress, irrespective of whether DV was experienced.

Table 5.

Effect Estimates for the Association Between Psychological Distress and an Interaction Between Domestic Violence and Risk Factors.

Predictor	Level	Estimate [95% CI]
Effect estimate for the association between psychological distress and an interaction between domestic violence and area of residence
Intercept	–	9.32 [8.72, 9.92]
K10 at Wave 1	–	0.45 [0.42, 0.48]
DV in Waves 2 to 6	No	Ref.
DV in Waves 2 to 6	Yes	2.48 [2.03, 2.92]
Area of residence	Major cities	Ref.
	Inner regional	−0.11 [−0.77, 0.56]
	Outer regional/Remote/Very remote	0.55 [−0.40, 1.50]
DV × Area of residence	No × Major cities	Ref.
	No × Inner regional	Ref.
	No × Outer regional/Remote/Very remote	Ref.
	Yes × Major cities	Ref.
	Yes × Inner regional	0.83[−0.21, 1.86]
	Yes × Outer regional/Remote/Very remote	−0.52 [−1.97, 0.94]
Effect estimates for the association between psychological distress and an interaction between domestic violence and self-esteem
Intercept	–	10.96 [10.48, 11.45]
K10 at Wave 1	–	0.24 [0.21, 0.26]
DV in Wave 2 to 6	No	Ref.
DV in Wave 2 to 6	Yes	1.10 [0.66, 1.54]
Self-esteem	High	Ref.
	Average	3.90 [3.40, 4.39]
	Low	9.11 [8.54, 9.68]
DV × Self-esteem	No × High	Ref.
	No × Average	Ref.
	No × Low	Ref.
	Yes × High	Ref.
	Yes × Average	0.35 [−0.42, 1.12]
	Yes × Low	1.04 [0.28, 1.80]
Effect estimates for the association between psychological distress and an interaction between domestic violence and social support
Intercept	–	9.20 [8.63, 9.78]
K10 at Wave 1	–	0.41 [0.38, 0.43]
DV in Wave 2 to 6	No	Ref.
DV in Wave 2 to 6	Yes	1.77 [1.27, 2.26]
Social support	All of the time	Ref.
	Most of the time	2.58 [2.02, 3.13]
	Some of the time	4.00 [3.02, 4.98]
	None of the time	5.46 [3.54, 7.38]
DV × Social support	No × All of the time	Ref.
	No × Most of the time	Ref.
	No × Some of the time	Ref.
	No × None of the time	Ref.
	Yes × All of the time	Ref.
	Yes × Most of the time	−0.08 [−0.92, 0.75]
	Yes × Some of the time	0.71 [−0.56, 1.98]
	Yes × None of the time	1.66 [−0.66, 3.98]
Effect estimates for the association between psychological distress and an interaction between domestic violence and mean social support score
Intercept	–	19.07 [17.54, 20.61]
K10 at Wave 1	–	0.40 [0.37, 0.43]
DV in Waves 2 to 6	No	Ref.
DV in Waves 2 to 6	Yes	3.16 [1.34, 4.98]
Social support (continuous)	–	−2.05 [−2.37, −1.72]
DV × Social support	No × Social support	Ref.
DV × Social support	Yes × Social support	−0.34 [−0.78, 0.10]
Effect estimates for the association between psychological distress and an interaction between domestic violence and managing on income
Intercept	–	9.56 [9.0, 10.12]
K10 at Wave 1	–	0.41 [0.38, 0.43]
DV in Waves 2 to 6	No	Ref.
DV in Waves 2 to 6	Yes	1.83 [1.36, 2.30]
Managing on income	Not too bad/easy	Ref.
	Difficult sometimes	1.82 [1.22, 2.42]
	Difficult always/impossible	3.95 [2.97, 4.93]
DV × Managing on income	No × Not too bad/easy	Ref.
	No × Difficult sometimes	Ref.
	No × Difficult always/impossible	Ref.
	Yes × Not too bad/easy	Ref.
	Yes × Difficult sometimes	0.32 [−0.55, 1.18]
	Yes × Difficult always/impossible	1.52 [0.26, 2.79]

Self-Esteem

As seen in Table 2, there was a more even distribution for participants who experienced DV across the levels of self-esteem when compared to those who did not experience DV, of which had a larger percentage of participants with high self-esteem. As seen in Table 5, there was an interaction between low self-esteem at Wave 6 and experiencing DV on K10 scores at Wave 6 (B = 1.04, 95% CI [0.28, 1.80]). This suggests that experiencing DV between Waves 2 to 6 and having low self-esteem at Wave 6 was associated with increased psychological distress scores after experiencing DV, compared to women who experienced DV but who had higher self-esteem. No other interactions were observed. It should also be noted that there was also evidence of a strong main effect of self-esteem on psychological distress, irrespective of whether DV was experienced or not.

Social Support

A very small number of participants were within the ‘none of the time’ category for this analysis, with 123 participants representing 3% of the sample (Table 2). Results found no evidence of an interaction between all levels of social support at Wave 6 and experiencing DV on psychological distress scores at Wave 6 (as seen in Table 5). However, there was a large effect size for the interaction of experiencing DV and reported social support ‘none of the time’ (B = 1.66, 95% CI [−0.66, 3.98]) on psychological distress. It should also be noted that there was evidence of a strong main effect of social support on psychological distress, irrespective of whether DV was experienced or not.

An additional analysis was conducted where social support was treated as a continuous variable to address any concerns about the low frequency of the ‘none of the time’ category. The mean social support score at Wave 6 was 4.27 (95% CI [4.24, 4.30]) among women who hadn’t experienced DV, and 3.88 (95% CI [3.84, 3.92]) among women who had experienced DV. However, once again there was no evidence for an interaction between social support scores at Wave 6 and experiencing DV on psychological distress at Wave 6.

Managing on Income

Among the women in the sample, 36% found it ‘not too bad/easy’ to manage on income, whilst only 10% found it ‘difficult always/impossible’ (Table 2). However, 15% of participants who experienced DV found it ‘difficult always/impossible’ to manage on their income compared to only 7% of participants who did not experience DV.

The results showed an interaction between responding ‘difficult always/impossible’ for managing on income and experiencing DV on K10 scores at Wave 6, as seen in Table 5 (B = 1.52, 95% CI [0.26, 2.79]). This suggests that experiencing DV between Waves 2 to 6 and finding it ‘difficult always/impossible’ to manage on income at Wave 6 increased psychological distress scores after experiencing DV, compared to women who had also experienced DV but who rated their ability to manage on the income they had available as ‘not too bad/easy’. There was also evidence of a main effect of greater difficulty managing on income being associated with greater psychological distress, irrespective of whether DV was experienced or not.

Discussion

Women who experienced DV were found to have higher levels of psychological distress that remained high over time when compared to women who did not experience DV, who had a reduction in psychological distress over time. This suggests that experiencing DV was associated with higher psychological distress over time when compared to those who did not experience DV. The effects of DV on psychological distress were greater among women with low self-esteem and income management difficulty, compared to women who had high self-esteem or were more financially secure. Additionally, there was no evidence that remote area of residence or low social support amplified the effects of DV on psychological distress, when compared to women who experienced DV but who lived in major cities or had high levels of social support.

The current results offer some insight into conflicts in the literature, where some, but not all, studies reported that psychological distress after experiencing DV reduced over time (Patton et al., 2022). The current study demonstrated that psychological distress did not decrease over time, rather, it remained persistently high for women who experienced violence. Additionally, the findings were consistent with DV experiences being associated with psychological harm (Beck et al., 2014), that may persist throughout women’s lives (Ahmadabadi et al., 2020; Moulding et al., 2021). As a result, the current study can infer a temporal order of events, with high psychological distress persisting for women who experience violence during a 7-year period.

Women who had higher psychological distress scores at Time 1 were more likely to go on to experience DV, in keeping with previous research (Dillon et al., 2013). Some evidence has suggested that women who later experience DV had higher levels of psychological distress beforehand (Dillon et al., 2013), which was supported by the current study findings. Similarly, it was found that women who did not experience DV had a decrease in psychological distress over time, suggesting that as women age their psychological distress decreases, which has been found by previous literature (Butterworth et al., 2020). Therefore, evidence from the present study suggests that experiencing DV may be associated with the persistence of higher levels of psychological distress over time, when compared to those who do not experience DV. The results highlight the need for more research in this area, in particular targeting the development of primary prevention activities for women experiencing psychological distress.

Risk Factors and Psychological Distress After Experiencing Domestic Violence

The current study found that low self-esteem and financial stress was associated with increased psychological distress after experiencing DV. However, contrary to expectations, there was no evidence that low social support and remote area of residence increased the effects of DV on psychological distress.

Low self-esteem was found to increase psychological distress after experiencing DV. Whilst literature supports this finding (Bigizadeh et al., 2021), there are limited studies available that observed this association. As a result, the current study provides further insight into this gap in the literature. Additionally, it has been found the presence of high self-esteem predicts increased wellbeing and success in relationships, work and health (Orth & Robins, 2014), suggesting that those with low self-esteem have reduced wellbeing. These results provide compelling evidence that reduced self-esteem may be associated increased psychological distress for women after DV experiences.

Additionally, finding it difficult to manage on income was associated with increased psychological distress after experiencing DV. This finding was consistent with previous studies where low income has been associated with experiencing DV and increased mental illness diagnoses after experiencing DV (Adams et al., 2012; Moulding et al., 2021). Furthermore, the current study highlights that experiencing financial stress and finding it difficult to manage on available income after DV may be an important risk factor to consider when developing recommendations and assisting women in their recovery after violence. It is also important to consider that financial abuse may additionally contribute to someone’s ability to manage on their income, with financial control limiting the amount of money an individual may have access to or available. However, financial abuse was not included in this study specifically.

Contrary to existing literature, the current study found no evidence that the effect of DV on psychological distress was exacerbated by low social support across both continuous and categorical measures. This was an unexpected finding, as the literature suggests that high levels of social support is a key factor for women recovering from DV, with low perceived social support being associated with depressive symptoms, psychological distress and lower quality of life after experiencing DV (Patton et al., 2022). Several factors may explain into these unexpected results. Only a small number of women who experienced DV indicated low social support within the current study, which limited the statistical power to detect an effect within this category. However, given the reasonable sample sizes amongst the women with greater levels of social support, there was sufficient statistical power to observe a positive effect of greater social support, but yet the current study did not find evidence of this. It is also possible that categorising the MOS Social Support Survey scores may not have been effective. However, further analysis with continuous mean scores additionally found no significant results, suggesting the findings may not have been a consequence of categorical scoring. Additionally, it is important to consider that new forms of social support have since arisen that are not captured in the MOS Social Support Survey, such as social media. However, it should be emphasised that although we did not find evidence for an interaction between DV and social support, there was evidence for lower levels of social support being associated with greater psychological distress generally, irrespective of whether DV was experienced or not.

Another unexpected finding was that outer regional/remote/very remote area of residence did not increase psychological distress after experiencing DV. This contradicts the literature, as studies have found that remote location acts as a barrier, further exacerbating the nature of DV (Lanier & Maume, 2009; Wendt et al., 2017). International studies have also suggested that remote women experience DV for longer periods of time, leading to poorer psychosocial health (Nur Hayati et al., 2013), which was not supported by the current study. However, the sample size for outer regional/remote/very remote participants was small for the current study, and this limited statistical power to detect an interaction between geographical remoteness and DV. Future research with a larger sample of women of non-urban women would be highly valuable.

Limitations

The current study has some limitations that should be considered. First, the sample only consisted of women born between 1989 and 1995, meaning the results may not be generalisable to the wider female population and experiences across generations. There was only a small number of women who were born in non-English speaking countries, with the overwhelming majority being born within Australia. Additionally, the study included very few women who lived in remote areas, and so the results may not have captured a fully representative sample of rural Australian women who have experienced violence. A potential alternative factor that may be associated with higher psychological distress preceding later DV exposure includes adverse childhood experiences (ACEs). Evidence has shown that ACEs can be associated with higher baseline psychological distress in women (Loxton et al., 2021) and has also been associated with experiencing DV later in life (Townsend et al., 2022).

Regarding social support, the MOS Social Support Survey was measured using a combined score of all sub scales (i.e. tangible, emotional/informational, affectionate and positive social interaction), with no investigation of the relationship between individual sub-scales and psychological distress after DV. Future research could investigate the different subscales of social support to better understand whether the absence of different types of social support increases psychological distress after experiencing DV. Additionally, this scale was developed in 1991 and does not measure new types of social support, such as through social media and the internet, which may be particularly relevant for this younger cohort.

Another limitation of the current study was that the exposure was defined based on whether the participant experienced DV at any timepoint between Wave 2 and Wave 6. The analysis did not account for precisely when during this time that the DV occurred, and so the exact time between experiencing DV and psychological distress at Wave 6 was not accounted for nor could the analysis account for whether the participant was still in a violent relationship at the time psychological distress was measured at Wave 6.

The nature of the data and the analysis methods used precluded the determination of any causative relationships. There were also potentially unknown confounding factors that may have been present at the time of data collection for each wave and for each participant. As a result, there are limitations on how the data can be interpreted as these unknown factors may have changed a participant’s responses to the various measures utilised within the study.

Implications and Recommendations

Whilst there are some limitations, the current study displays a national picture of the relationship between experiencing DV and later levels of psychological distress for young Australian women. Further, the current study also demonstrates a temporal order of events from pre- to post-experience of DV because of the longitudinal design.

One of the main implications from this study is the need for a holistic approach that accounts for all aspects of a woman’s life when discussing the risks associated with increased psychological distress after experiencing violence. This includes the impact on their psychological health, economic wellbeing and personal self-esteem. Additionally, services should engage with a life course approach when assisting women who have experienced DV. It is also recommended that women be provided financial support after experiencing DV, as the findings suggest financial stress is associated with poorer psychological outcomes.

The findings and implications of the study apply to many different sectors, including employment, mental health, health development and promotion and policy advisors. It offers insight into the impact of DV on psychological distress over a 7-year period, providing a better understanding of which risk factors should be addressed and reduced throughout policy and practice to best assist these women in their recovery.

Conclusion

DV is becoming better understood in Australian society. A significant challenge for women who experience violence is maintaining good mental health before, during and after DV, as increased poor psychological wellbeing may impact their recovery. The current study has demonstrated a temporal order of events, with DV being associated with higher levels of psychological distress over several years. Additionally, low self-esteem and financial stress are associated with increased levels of psychological distress after DV, hindering recovery. Policy and practice should aim to reduce the impact of experiencing DV on women’s psychological health and adequately address potential risks in their recovery.

Footnotes

Acknowledgements

The research on which this article is based was conducted as part of the Australian Longitudinal Study on Women’s Health (ALSWH) by the University of Queensland and the University of Newcastle. We are grateful to the Australian Government Department of Health and Aged Care for funding and to the women who provided the survey data.

ORCID iDs

Jemma Henderson

Nicholas Egan

Deborah Loxton

Ethical Considerations

Ethics approval was given by the University of Newcastle Human Research Ethics Committee (HREC) for the current study; approval number H-2023-0228, as well as approval from the ALSWH Data Access Committee to access and utilise the data. The ALSWH survey program has ongoing ethical approval from the Human Research Ethics Committees (HRECs) of the Universities of Newcastle and Queensland (approval numbers H076-0795 and 2004000224, respectively, for the 1973 to 1978, 1946 to 1951 and 1921 to 1926 cohorts; and H-2012-0256 and 2012000950, for the 1989 to 1995 cohort).

Consent to Participate

Participants have been informed at each survey that researchers will be comparing their information with that collected in earlier surveys. Completion of the survey was taken as consent. This method of consent was approved by the Australian Department of Health, the Australian Department of Human Services, and both the University of Queensland and the University of Newcastle Human Research Ethics Committees.

Consent for Publication

Not applicable.

Funding

The authors disclosed receipt of the following financial support for the research and/or authorship of this article: The Australian Longitudinal Study on Women’s Health is funded by the Australian Government Department of Health and Aged Care.

Declaration of Conflicting Interests

The authors declared no potential conflicts of interests with respect to the authorship and/or publication of this article.

Data Availability Statement

ALSWH survey data are owned by the Australian Government Department of Health and Aged Care and due to the personal nature of the data collected, release by ALSWH is subject to strict contractual and ethical restrictions. Ethical review of ALSWH is by the Human Research Ethics Committees at The University of Queensland and The University of Newcastle. De-identified data are available to collaborating researchers where a formal request to make use of the material has been approved by the ALSWH Data Access Committee. The committee is receptive of requests for datasets required to replicate results. Information on applying for ALSWH data is available from

Author Biographies

Jemma Henderson, BPsych (Hons), is a PhD candidate within the Centre for Women’s Health Research at the University of Newcastle, Australia. She has a background in psychological science and her research areas of interest include domestic violence, mental health, and how they can impact women over the lifetime.

Nicholas Egan, MBiostat, BBiomed, is a statistician within the Centre for Women’s Health Research at the University of Newcastle, Australia, with experience analysing data from the Australian Longitudinal Study on Women’s Health. He has been involved in several projects that have focused on women’s experiences of violence and abuse in Australia.

Jenny Bowman, PhD, MPsycClin, is a professor in the School of Psychological Sciences at The University of Newcastle, Australia. Her primary research interest is physical heath equity for people with a mental health condition, in particular improved chronic disease preventive care. Expertise includes co-developing and evaluating interventions within clinical and community mental health settings for the delivery of preventive care.

Deborah Loxton, PhD, is the director of the Centre for Women’s Health Research and Australian Longitudinal Study on Women’s Health at the University of Newcastle, Australia. Prof Loxton conducts research into women’s health over the life course, with a particular focus on the health impact of violence.

References

Adams

A. E.

Tolman

R. M.

Bybee

Sullivan

C. M.

Kennedy

A. C.

(2012). The impact of intimate partner violence on low-income women’s economic well-being: The mediating role of job stability. Violence Against Women, 18(12), 1345–1367. https://doi.org/10.1177/1077801212474294

Ahmadabadi

Najman

J. M.

Williams

G. M.

Clavarino

A. M.

d’Abbs

Tran

(2020). Intimate partner violence and subsequent depression and anxiety disorders. Social Psychiatry and Psychiatric Epidemiology, 55(5), 611–620. https://doi.org/10.1007/s00127-019-01828-1

Andrews

Slade

(2001). Interpreting scores on the Kessler Psychological Distress Scale (K10). Australian and New Zealand Journal of Public Health, 25(6), 494–497. https://doi.org/10.1111/j.1467-842x.2001.tb00310.x

Australian Bureau of Statistics. (2021–2022). Personal safety, Australia. https://www.abs.gov.au/statistics/people/crime-and-justice/personal-safety-australia/latest-release.

Australian Bureau of Statistics. (2012). Information paper: Use of the Kessler Psychological Distress Scale in ABS Health Surveys, Australia, 2007–2008. https://www.abs.gov.au/ausstats/abs@.nsf/lookup/4817.0.55.001chapter92007-08

Australian Bureau of Statistics. (2013). Personal safety, Australia. https://www.abs.gov.au/AUSSTATS/abs@.nsf/Lookup/4906.0Main+Features12012?OpenDocument

Australian Bureau of Statistics. (2023). Remoteness areas. https://www.abs.gov.au/statistics/standards/australian-statistical-geography-standard-asgs-edition-3/jul2021-jun2026/remoteness-structure/remoteness-areas

Australian Institute of Health and Welfare. (2019). Family, domestic and sexual violence in Australia: continuing the national story. https://www.aihw.gov.au/reports/family-domestic-and-sexual-violence/family-domestic-sexual-violence-australia-2019/contents/summary

Bacchus

L. J.

Ranganathan

Watts

Devries

(2018). Recent intimate partner violence against women and health: a systematic review and meta-analysis of cohort studies. BMJ Open, 8(7), e019995. https://doi.org/10.1136/bmjopen-2017-019995

10.

Beck

J. G.

Clapp

J. D.

Jacobs-Lentz

McNiff

Avery

Olsen

S. A.

(2014). The association of mental health conditions with employment, interpersonal, and subjective functioning after intimate partner violence. Violence Against Women, 20(11), 1321–1337. https://doi.org/10.1177/1077801214552855

11.

Bigizadeh

Sharifi

Javadpour

Poornowrooz

Jahromy

F. H.

Jamali

(2021). Attitude toward violence and its relationship with self-esteem and self-efficacy among Iranian women. Journal of Psychosocial Nursing and Mental Health Services, 59(4), 31–37. https://doi.org/10.3928/02793695-20201203-06

12.

Butterworth

Watson

Wooden

(2020). Trends in the prevalence of psychological distress over time: Comparing results from longitudinal and repeated cross-sectional surveys [Brief research report]. Frontiers in Psychiatry, 11, 595696. https://doi.org/10.3389/fpsyt.2020.595696

13.

Cirici Amell

Soler

A. R.

Cobo

Soldevilla Alberti

J. M

. (2023). Psychological consequences and daily life adjustment for victims of intimate partner violence. The International Journal of Psychiatry in Medicine, 58(1), 6–19. https://doi.org/10.1177/00912174211050504

14.

Dillon

Hussain

Loxton

Rahman

(2013). Mental and physical health and intimate partner violence against women: A review of the literature. International Journal of Family Medicine, 2013, 313909. https://doi.org/10.1155/2013/313909

15.

García

J. A.

y Olmos

F. C.

Matheu

M. L.

Carreño

T. P.

(2019). Self-esteem levels vs global scores on the Rosenberg Self-Esteem Scale. Heliyon, 5(3), e01378. https://doi.org/10.1016/j.heliyon.2019.e01378

16.

Gould

(n.d). How do I create dummy variables? Stata FAQ. StataCorp. https://www.stata.com/support/faqs/data-management/creating-dummy-variables/

17.

Greenland

Pearl

Robins

J. M.

(1999). Causal diagrams for epidemiologic research. Epidemiology, 10(1), 37–48.

18.

Hegarty

Sheehan

Schonfeld

(1999). A multidimensional definition of partner abuse: Development and preliminary validation of the Composite Abuse Scale. Journal of Family Violence, 14(4), 399–415. https://doi.org/10.1023/A:1022834215681

19.

Kessler

R. C.

Andrews

Colpe

L. J.

Hiripi

Mroczek

D. K.

Normand

S.-L.

Walters

E. E.

Zaslavsky

A. M.

(2002). Short screening scales to monitor population prevalences and trends in non-specific psychological distress. Psychological medicine, 32(6), 959–976.

20.

Lanier

Maume

M. O.

(2009). Intimate partner violence and social isolation across the rural/urban divide. Violence Against Women, 15(11), 1311–1330. https://doi.org/10.1177/1077801209346711

21.

Loxton

Forder

P. M.

Cavenagh

Townsend

Holliday

Chojenta

Melka

A. S.

(2021). The impact of adverse childhood experiences on the health and health behaviors of young Australian women. Child Abuse & Neglect, 111, Article 104771. https://doi.org/10.1016/j.chiabu.2020.104771

22.

Loxton

Harris

M. L.

Forder

Powers

Townsend

Byles

Mishra

(2019). Factors influencing web-based survey response for a longitudinal cohort of young women born between 1989 and 1995 [Original paper]. Journal of Medical Internet Research, 21(3), e11286. https://doi.org/10.2196/11286

23.

Loxton

Powers

Fitzgerald

Forder

Anderson

Taft

Hegarty

(2013). The Community Composite Abuse Scale: Reliability and validity of a measure of intimate partner violence in a community survey from the ALSWH. Journal of Women’s Health Issues Care, 2(4), 2–7. https://doi.org/10.4172/2325-9795.1000115

24.

Loxton

Tooth

Harris

M. L.

Forder

P. M.

Dobson

Powers

Brown

Byles

Mishra

(2017). Cohort profile: The Australian Longitudinal Study on Women’s Health (ALSWH) 1989–95 cohort. International Journal of Epidemiology, 47(2), 391–392e. https://doi.org/10.1093/ije/dyx133

25.

Matheson

F. I.

Daoud

Hamilton-Wright

Borenstein

Pedersen

O’Campo

(2015). Where did she go? The transformation of self-esteem, self-identity, and mental well-being among women who have experienced intimate partner violence. Women’s Health Issues, 25(5), 561–569. https://doi.org/10.1016/j.whi.2015.04.006

26.

Mburia-Mwalili

Clements-Nolle

Lee

Shadley

Yang

(2010). Intimate partner violence and depression in a population-based sample of women: Can social support help? Journal of Interpersonal Violence, 25(12), 2258–2278. https://doi.org/10.1177/0886260509354879

27.

Moulding

Franzway

Wendt

Zufferey

Chung

(2021). Rethinking women’s mental health after intimate partner violence. Violence Against Women, 27(8), 1064–1090. https://doi.org/10.1177/1077801220921937

28.

Nur Hayati

Eriksson

Hakimi

Högberg

Emmelin

. (2013). ‘Elastic band strategy’: women’s lived experience of coping with domestic violence in rural Indonesia. Global Health Action, 6(1), 18894. https://doi.org/10.3402/gha.v6i0.18894

29.

OHCHR. (1993). Declaration on the elimination of violence against women. United Nations. https://www.ohchr.org/en/instruments-mechanisms/instruments/declaration-elimination-violence-against-women

30.

Orth

Robins

R. W.

(2014). The development of self-esteem. Current Directions in Psychological Science, 23(5), 381–387. https://doi.org/10.1177/0963721414547414

31.

Patton

S. C.

Szabo

Y. Z.

Newton

T. L.

(2022). Mental and physical health changes following an abusive intimate relationship: A systematic review of longitudinal studies. Trauma, Violence, & Abuse, 23(4), 1079–1092. https://doi.org/10.1177/1524838020985554

32.

Rees

Silove

Chey

Ivancic

Steel

Creamer

Teesson

Bryant

McFarlane

A. C.

Mills

K. L.

(2011). Lifetime prevalence of gender-based violence in women and the relationship with mental disorders and psychosocial function. Jama, 306(5), 513–521. https://doi.org/10.1001/jama.2011.1098

33.

Rosenberg

(1965). Rosenberg self-esteem scale (RSE). Acceptance and Commitment Therapy. Measures Package, 61(52), 18.

34.

Russell

Smith

(2002). Medical outcomes study social support index: ALSWH data dictionary supplement. https://alswh.org.au/wp-content/uploads/2020/08/DDSSection2.7MOSSocialSupport.pdf

35.

Sanz-Barbero

Barón

Vives-Cases

(2019). Prevalence, associated factors and health impact of intimate partner violence against women in different life stages. PLoS One, 14(10), e0221049. https://doi.org/10.1371/journal.pone.0221049

36.

Schmitt

D. P.

Allik

(2005). Simultaneous administration of the Rosenberg Self-Esteem Scale in 53 nations: Exploring the universal and culture-specific features of global self-esteem. Journal of Personality and Social Psychology, 89(4), 623–642. https://doi.org/10.1037/0022-3514.89.4.623

37.

Shen

Kusunoki

(2019). Intimate partner violence and psychological distress among emerging adult women: A bidirectional relationship. Journal of Women’s Health, 28(8), 1060–1067. https://doi.org/10.1089/jwh.2018.7405

38.

Sherbourne

C. D.

Stewart

A. L.

(1991). The MOS social support survey. Social Science & Medicine, 32(6), 705–714. https://doi.org/10.1016/0277-9536(91)90150-B

39.

StataCorp LLC. (2023). StataBE: Release 18.

40.

Townsend

Loxton

Egan

Barnes

Byrnes

Forda

(2022). A life course approach to determining the prevalence and impact of sexual violence in Australia (Research report 14/2022). ANROWS. https://apo.org.au/node/319274

41.

Webster

(2016). A preventable burden – Measuring and addressing the prevalence and health impacts of intimate partner violence in Australian women: key findings and future directions (ANROWS Compass, 07/2016). ANROWS. https://apo.org.au/node/69652

42.

Webster

Diemer

Honey

Mannix

Mickle

Morgan

Parkes

Politoff

Powell

Stubbs

(2018). Australians’ attitudes to violence against women and gender equality. Findings from the 2017 National Community Attitudes towards Violence against Women Survey (NCAS) (Research report, 03/2018). ANROWS. https://www.anrows.org.au/publication/australians-attitudes-to-violence-against-women-and-gender-equality-findings-from-the-2017-national-community-attitudes-towards-violence-against-women-survey/

43.

Wendt

Bryant

Chung

Elder

(2015). Seeking help for domestic violence: Exploring rural women’s coping experiences: State of knowledge Paper (ANROWS Landscapes, 04/2015). ANROWS. https://www.anrows.org.au/publication/seeking-help-for-domestic-violence-exploring-rural-womens-coping-experiences-state-of-knowledge-paper/

44.

Wendt

Chung

Elder

Hendrick

Hartwig

(2017). Seeking help for domestic and family violence: Exploring regional, rural and women’s coping experiences: Final report. (ANROWS Horizons, 06/2017). ANROWS. https://www.anrows.org.au/publication/seeking-help-for-domestic-violence-exploring-rural-womens-coping-experiences-final-report/

45.

World Health Organization. (2021). Violence against women prevalence estimates, 2018: global, regional and national prevalence estimates for intimate partner violence against women and global and regional prevalence estimates for non-partner sexual violence against women. https://www.who.int/publications/i/item/9789240022256