Sage Journals: Discover world-class research

Abstract

The longitudinal effects of distinct intimate partner violence (IPV) types on neurocognition among South African women with HIV are unknown. Mixed linear models determined between-group (IPV exposed vs IPV unexposed) differences in domain-specific and global deficit scores (GDS) and associations with IPV types. There were no between-group differences in cognition (GDS and domain-specific) at baseline or 1-year follow-up. There were significant time*IPV type interaction effects (physical assault, sexual coercion, injury) in attention/working memory. IPV exposure was associated with a lack of cognitive improvement. IPV-screening among women with HIV is important for improved support and targeted interventions.

Keywords

attention and working memory gender-based violence gender equality HIV/AIDS neurocognition

Introduction

In South Africa, the HIV epidemic disproportionately affects women, particularly women of a younger age (Human Sciences Research Council, 2023). Women are also disproportionately affected by an equally devastating and under-recognized epidemic of violence. Intimate partner violence (IPV), defined as any physical or sexual violence, threats of violence, and emotional or psychological abuse by an intimate partner (World Health Organization, 2021), is a global public health concern (Sardinha et al., 2022). South Africa has the highest rate of IPV among women (Gass et al., 2011), with an estimated lifetime prevalence of 24% (World Health Organization, 2019) and high rates of associated femicide (O’Regan, 2022). IPV significantly contributes to the disease burden as it is associated with various physical and mental health problems (Hansrod et al., 2015; Sardinha et al., 2022; World Health Organization, 2013), including neurocognitive impairments (Esopenko et al., 2021). For example, Daugherty et al. (2019) found significant differences in attention and executive function in women with IPV exposure compared to unexposed women, with approximately 25% of women who experienced IPV experiencing mild neurocognitive impairment and 5% severe impairment. Similarly, Williams et al. (2017) in their longitudinal study reported decreased performance on a measure of attention in female IPV victims over time. Additionally, IPV is associated with an increased risk of sexually transmitted infections (Sullivan, 2019). There is a well-documented bidirectional relationship between HIV and IPV (Sullivan, 2019; World Health Organization, 2013). Women with HIV are more likely to experience IPV than their uninfected counterparts (Iliyasu et al., 2011), with prevalence rates of 56.3% (South Africa: Matseke et al., 2016) and 64.2% (Ethiopia Alemie et al., 2023) reported among women with HIV. Disclosure of a positive HIV status can lead to either an extension of former violence or new conflict specifically associated with the disclosure (Colombini et al., 2016). Moreover, women who are in violent and unstable relationships are more likely to become infected with HIV due to decreased capacity to make decisions about their own reproductive and sexual lives (Benoit et al., 2015), reduced condom use (Gibbs et al., 2019), and coercion or forced sexual initiation (Stockman et al., 2013). Similar to IPV, HIV infection can negatively affect neurocognitive performance (Daneman & Prat, 2015). HIV-associated neurocognitive disorders (HAND) are prevalent in South African people with HIV (Joska et al., 2010; Robbins et al., 2011) and typically affect executive functions (Heaton et al., 2011), attention (Maki et al., 2015; Su et al., 2015), concentration and memory (Smail & Brew, 2018), information processing and psychomotor speed (Kanmogne et al., 2020), language (Hoare et al., 2016), verbal learning (Maki et al., 2015), and sensory perception. The syndemic nature (Closson et al., 2016; Tsai, 2018) of HIV and IPV may have profound neurocognitive sequelae, particularly among South African women who are disproportionately affected by trauma exposure (StatsSA, 2022) and HIV infection (23.5% for females vs. 12.1% for males in 2022 (UNAIDS, 2022)). However, there is a dearth of literature investigating how different IPV subtypes (e.g., injury, sexual coercion, physical assault, and psychological aggression) affect neurocognitive performance over time. We addressed this by investigating whether IPV (including sub-types) negatively impacts neurocognitive function in women with HIV over time. This is relevant for the prevention and management of women dually affected by HIV and IPV.

Using population-adjusted neurocognitive performance scores (Deist et al., 2023) for the HIV Neurobehavioral Centre's (HNRC) (HIV Neurobehavioral Research Center, 2022) International Neurobehavioral Battery (HNRC Battery), we evaluated:

Differences, if any, in global deficit scores (GDS) and domain-specific deficit scores between IPV-exposed versus IPV-unexposed women with HIV; and

Associations between IPV sub-types (i.e., injury, sexual coercion, physical assault, and psychological aggression) and neurocognitive performance over one year.

Method

Sample and Procedure

A purposive convenience sample of women with HIV was directly recruited from the community and through healthcare centers for the parent study on biological endophenotypes of HIV and childhood trauma in South African women with HIV (ethics reference number: N07/07/153). Inclusion criteria were: (i) ability to read and write in English, Afrikaans, or isiXhosa at 5th grade level; (ii) no current or past diagnoses of schizophrenia, bipolar disorder, other psychotic disorders, or current seizure disorder of any cause; (iii) no current substance/alcohol use/dependence and/or psychotropic medication use; (iv) no history of central nervous system infections of neoplasms or significant head injury; and (v) a negative hepatitis B/C status. We confirmed participants’ HIV status through enzyme-linked immunosorbent assay.

Participants completed neuromedical, neurocognitive, and neuroimaging assessments at Stellenbosch University (Tygerberg campus). We collected data at baseline (n = 140; IPV-exposed n = 118, 84.3%) and 1-year follow-up (n = 73; IPV-exposed n = 58, 79.5%). At each time-point, we provided participants with refreshments and reimbursed them for transportation to and from the campus. Before data collection, participants provided written informed consent.

Measures

At baseline, participants self-reported their sociodemographic information. In addition to the main outcome measure (HNRC Battery), participants completed the Revised Conflict Tactics Scale 2 for Couples (RCTS: Straus et al., 1996) at each visit. Participants completed the measures in Afrikaans, English, or isiXhosa based on personal preference. We translated measures using forward- and back-translation techniques.

HNRC Battery

A trained research psychologist and research nurse administered the HNRC Battery to assess for HAND. The HNRC battery distinguishes between: (i) asymptomatic neurocognitive impairment; (ii) HIV-associated mild neurocognitive disorder; or (iii) HIV-associated dementia (HIV Neurobehavioral Research Centre, 2022). The HNRC Battery is widely used internationally (Cherner et al., 2007; Michael et al., 2021; the HNRC Group et al., 2018) and assesses learning, delayed recall, processing speed, attention/working memory, executive function, verbal fluency, and motor ability (Heaton et al., 2010). Where necessary, we adapted test instructions and stimuli to fit the South African cultural context (see Spies et al., 2017 for details). We computed HAND using recently generated South African norms (Deist et al., 2023). Specifically, we converted the raw scores for each neurocognitive test into scaled scores. Thereafter, we used the scaled scores to generate prediction equations using a multiple fractional polynomial (MFP) procedure. The MFP procedure (Royston & Altman, 1994) includes entering demographic variables known to account for significant variance in raw scores (including age, education, ethnicity, and neurocognitive test language) into the regression equation. Next, we used the adjusted MFP model to generate predicted test scores, after which we calculated residual scores for each participant. Thereafter, we converted the residual scores to demographically corrected T scores. We then converted the demographically corrected T scores to deficit scores as an estimate of the severity of neurocognitive impairment. The deficit scores were categorized as 0 (T score ≥ 40) = normal cognition; 1 (T score 35–39) = mild neurocognitive impairment; 2 (T score 30–34) = mild-to-moderate neurocognitive impairment; 3 (T score 25–29) = moderate neurocognitive impairment; 4 (T score 20–24) = moderate-to-severe NC impairment; and 5 (T score < 20) = severe neurocognitive impairment. We determined a GDS by averaging the deficit scores across all tests. A GDS ≥ 0.50 is indicative of poor neurocognitive performance.

Revised Conflict Tactics Scale 2 for Couples

We used the 78-item RCTS (Straus et al., 1996) to determine past-year IPV prevalence. The RCTS consists of subscales measuring injury, sexual coercion, physical assault, and psychological aggression. Scale items are considered as “less severe” or “more severe.” For example, for physical assault, items are considered “more severe” if they pose a greater risk of injury that may require medical attention as compared to “less severe” items. Importantly, “less severe” acts should not be mitigated and considered as a lesser problem to the victim or society (Hansrod et al., 2015). Subscales are also ranked on a continuum from least to most severe. Following the prevalence estimate scoring method, we calculated a dichotomous score (1 = present, 0 = not present) for each subscale to indicate whether at least one violent act from the scale had occurred in the past year. These subscale scores were then used to examine whether specific types of IPV influenced neurocognitive outcomes over time across all participants. The negotiation subscale was not included in these analyses, given that negotiation is typically understood as a positive conflict resolution strategy rather than a form of abuse. Furthermore, we calculated an RCTS total score to indicate if IPV was present overall (i.e., in one or more of the subscales) or not. The total RCTS score was used to categorize participants into two groups: IPV-exposed or IPV-unexposed. Thus, participants were classified as IPV-exposed if they were exposed to at least one form of IPV. This scoring method was previously applied to this sample and demonstrated high reliability (α=.90: Hansrod et al., 2015).

Secondary Measures

To control for the impact of other potentially traumatic events, posttraumatic stress symptoms (PTSS), and depression symptoms, participants completed the Life Events Checklist (LEC: Gray et al., 2004), the Childhood Trauma Questionnaire short form (CTQ-SF: Bernstein & Fink, 1998), the Davidson Trauma Scale (DTS: Davidson et al., 1997), and the Centre for Epidemiological Studies Depression Scale (CES-D: Radloff, 1977). These measures were described in detail in prior publications from the same cohort (see for example Deist et al., 2023; Hansrod et al., 2015; Spies et al., 2023; Spies & Seedat, 2014; Van der Watt et al., 2025). We provide a brief description of each.

The LEC (Gray et al., 2004) reliably measures exposure to potentially traumatic events to facilitate the diagnosis of posttraumatic stress disorder. It has proven reliability in the South African setting (e.g., Van der Watt et al., 2023; Ventimiglia et al., 2020). The CTQ-SF (Bernstein & Fink, 1998) is a standardized, retrospective 28-item self-report inventory measuring the severity of different types of childhood trauma including emotional abuse, physical abuse, sexual abuse, emotional neglect, and physical neglect. The CTQ-SF has proven reliability (α=.879) in the same sample population (Hansrod et al., 2015). In our sample, the Cronbach's α was .879. The DTS (Davidson et al., 1997) is a 17-item self-report measure of PTSS frequency and severity. The DTS has proven reliability (α=.885) in the same sample population (Hansrod et al., 2015). In our sample, the Cronbach's α was .981. The CES-D (Radloff, 1977) is a 20-item self-report measure of depression. The CES-D has proven reliability (α=.96) in the same sample population (Spies & Seedat, 2014). In our sample, the Cronbach's α was .964.

Analysis Plan

We analyzed the data using SPSS and Statistica. In addition to descriptive statistics, we used chi-square tests (for categorical variables) and Analysis of Variance (ANOVA: for continuous variables) to compare groups (IPV-exposed vs IPV-unexposed) on sociodemographic variables. We included variables with statistically significant group differences as potential covariates in subsequent analyses. Given the high rate of trauma exposure in the South African female population (e.g., Okafor et al., 2021; Yemeke et al., 2020), the known association between trauma exposure and neurocognitive function (e.g., Kavanaugh et al., 2017; Spies et al., 2017), and the association between PTSS and neurocognition (e.g., Jacob et al., 2019; Jak et al., 2016), we controlled for LEC, CTQ-SF, DTS, and CES-D scores. We used mixed linear models (MLM, Kenward-Rogers type III) to determine neurocognitive profiles over time (using the GDS and domain-specific deficits scores, respectively). Additional covariates included age, education, and home language. MLM allows for the use of all data points and the inclusion of incomplete cases, increasing the analysable sample size. We conducted LSD post hoc analyses to determine between-group and within-group differences at the different time points. We corrected for multiple comparisons throughout using Fisher LSD within each MLM. We used Eta-square to determine effect size. Statistical significance was set at p = .05.

Results

At baseline, there was a significant between-group difference in age (F(1) = 6.95, p < .01, η² = 0.05). IPV-exposed participants were younger (mean = 32.43 years, SD = 6.54 years) compared to IPV-unexposed participants (mean = 36.50 years, SD = 7.21 years). There were significant between-group differences (see Table 1) in education (p = .01, Cramer's V = 0.30) and home language (p = .05, Cramer's V = 0.23) at 1-year follow-up.

Table 1.

Baseline and 1-Year Follow-up Sample Characteristics and Between-Group Differences.

Variable		Baseline			1-year follow-up
Variable		IPV-exposed (n = 118)	IPV-unexposed (n = 22)	p(Cramer's V)	IPV-exposed (n = 58)	IPV-unexposed (n = 15)	p(Cramer's V)
Sociodemographic data		n(%)	n(%)	p(Cramer's V)	n(%)	n(%)	p(Cramer's V)
Highest education obtained	Grade 8 or less Grade 9 and above	18(15.3) 100(84.7)	5(22.7) 17(77.3)	.39(0.07)	7(12.1) 51(87.9)	6(40.0) 9(60.0)	.01(0.30)
Marital status	Single Non-single	90(76.3) 28(23.7)	21(95.5) 1(4.5)	.04(0.17)	38(65.5) 20(34.5)	12(80.0) 3(20.0)	.28(0.13)
Home language	English Afrikaans Xhosa Other	2(1.7) 4(3.4) 111(94.1) 1(0.8)	2(9.1) - 20(90.9) -	.21(0.18)	- - 58(100.0) -	- - 14(93.3) 1(6.7)	.05(0.23)
Language of neuropsychiatric evaluation	English Afrikaans Xhosa	66(55.9) 4(3.4) 48(40.7)	15(68.2) - 7(31.8)	.45(0.11)	14(24.1) - 44(75.9)	3(20.0) - 12(80.0)	.74(0.04)
Household income	Less than ZAR 40,000 More than ZAR 40,000	112(94.9) 6(5.1)	22(100.0) -	.28(0.09)	58(100.0) -	15(100.0) -	NA
Employment status	Unemployed Employed	78(66.1) 40(33.9)	15(68.2) 7(31.8)	.85(0.12)	40(69.0) 18(31.0)	11(73.3) 4(26.7)	.74(0.04)
Handedness	Left Right	6(5.1) 112(94.9)	- 22(100.0)	.28(0.09)	1(1.7) 57(98.3)	- 15(100.0)	.61(0.06)
Trauma exposure and PTSS data		M(SD)	M(SD)	p(η²)	M(SD)	M(SD)	p(η²)
LEC total		5.27(3.23)	5.36(3.16)	.90(0.00)	4.72(2.51)	4.67(2.82)	.94(0.00)
CTQ-SF	TotalPhysical abuseSexual abuseEmotional abuseEmotional neglectPhysical neglect	53.81(18.96)10.07(6.09)7.99(5.15)12.30(6.43)12.58(5.07)10.88(5.07)	50.00(15.27)9.05(5.01)8.05(5.94)11.18(5.56)11.86(5.27)9.86(3.14)	.38(0.01).46(0.00).97(0.00).45(0.00).55(0.00).29(0.01)	-	-	-
Davidson Trauma Scale total	Scale totalFrequency totalSeverity total	20.69(32.32)10.55(16.49)10.14(16.02)	26.41(38.55)13.32(19.10)13.09(19.50)	.46(0.00).48(0.00).44(0.00)	12.52(24.06)6.52(12.96)6.00(11.68)	7.93(15.56)4.00(7.34)3.93(8.32)	.49(0.01).47(0.01).52(0.01)
CES-D total	Total	14.31(16.17)	17.36(21.03)	.44(0.00)	10.45(16.19)	10.40(14.10)	.99(0.00)
HIV clinical data		M(SD)	M(SD)	p(η²)	M(SD)	M(SD)	p(η²)
	CD4 countRangeViral loadRange	435.57(253.56)46–78684 702.65(328 687.24)0–1 800 000	367.38(184.68)25–1 529108 009.55(401 463.12)0–3 200 000	.24(0.01).78(0.00)	483.20(277.65)74–1 26432 918.55(73 265.08)0–370 852	517.13(282.934)86–1 1675 987.93(16 494.55)0–63 857	.68(0.00).16(0.03)
ARV treatment		n(%)	n(%)	p(Cramer's V)	n(%)	n(%)	p(Cramer's V)
	YesNo	50(42.4)68(57.6)	8(36.4)14(63.6)	.60(0.04)	44(75.9)14(24.1)	12(80.0)3(20.0)	.74(0.04)

Note. Cramer's V ≤ 0.2 = weak, 0.2 < Cramer's V ≥ 0.6 = moderate, Cramer's V > 0.6 = strong; η² > 0.01 = small, η²> 0.06 = medium, η²> 0.14 = large; CTQ-SF = Childhood Trauma Questionnaire short form; LEC = Life Events Checklist; PTSS = posttraumatic stress symptoms

There were no between-group differences in GDS or domain-specific deficit scores at baseline or 1-year follow-up (see Table 2). However, there was a trend towards a between-group difference in attention/working memory deficit scores, with IPV-unexposed participants performing poorer compared to IPV-exposed participants. Further analysis indicated a trend towards a time*group interaction effect (F(1,111) = 3.20, p = .08) within the attention/working memory domain (see Figure 1). Attention/working memory slightly improved over time for IPV-unexposed participants (p = .07) but remained unchanged for IPV-exposed participants (p = .71).

Figure 1.

Between-group difference in longitudinal attention/working memory deficit scores.

Table 2.

Longitudinal Neurocognitive Profiles and Between-Group Differences.

Neurocognitive deficit score	Baseline			1-year follow-up
	IPV-exposed(n = 118)	IPV-unexposed(n = 22)	LSD post hoc p	IPV-exposed(n = 58)	IPV-unexposed(n = 15)	LSD post hoc p
	LS mean (SE)	LS mean (SE)	LSD post hoc p	LS mean (SE)	LS mean (SE)	LSD post hoc p
Global	0.37(0.04)	0.42(0.07)	.51	0.30(0.04)	0.30(0.07)	.99
Verbal fluency	0.44(0.06)	0.27(0.12)	.16	0.47(0.07)	0.29(0.12)	.18
Learning	0.30(0.05)	0.21(0.10)	.40	0.13(0.06)	0.24(0.11)	.35
Delayed recall	0.36(0.22)	0.22(0.12)	.26	0.15(0.07)	0.20(0.13)	.73
Executive function	0.33(0.05)	0.40(0.12)	.61	0.24(0.07)	0.18(0.14)	.71
Processing speed	0.42(0.05)	0.58(0.11)	.17	0.28(0.06)	0.35(0.11)	.66
Motor ability	0.37(0.07)	0.42(0.14)	.73	0.41(0.14)	0.34(0.08)	.71
Attention/working memory	0.39(0.07)	0.64(0.15)	.11	0.40(0.09)	0.30(0.16)	.71

Types of IPV Exposure and Neurocognition

Table 3 presents the prevalence of the distinct types of IPV exposure at baseline and 1-year follow-up. Following a generalized estimating equation (GEE), we found significant proportionate decreases in physical assault (p < .01) and sexual coercion (p = .03) over time.

Table 3.

Type of IPV Exposure at Baseline and 1-Year Follow-up.

Type of intimate partner violence exposure		Baseline(n = 140)	1-year follow-up(n = 73)	Wald(1)	p
Type of intimate partner violence exposure		n(%)	n(%)	Wald(1)	p
Psychological aggression	No	96(68.6)	40(54.8)	3.28	.07
Psychological aggression	Yes	44(31.4)	33(45.2)	3.28	.07
Physical assault^a	No	66(47.1)	18(25.0)	9.65	<.01
Physical assault^a	Yes	74(52.9)	54(75.0)	9.65	<.01
Sexual coercion^a	No	60(42.9)	18(25.0)	6.54	.01
Sexual coercion^a	Yes	80(57.1)	54(75.0)	6.54	.01
Injury	No	40(28.6)	13(17.8)	3.43	.06
Injury	Yes	100(71.4)	60(82.2)	3.43	.06

One case missing at 1-year follow-up.

There were no significant time*IPV type interaction effects when considering GDS (see Supplementary Table A); however, there was a trend toward a significant time*IPV type interaction effect for physical assault (F(1,88) = 3.67, p = .06, η² = 0.04; see Figure 2). Post hoc analysis indicated a significant difference in GDS at 1-year follow-up (p = .04), with physical assault exposure associated with higher GDS (i.e., poorer performance). Over one year, there was a significant decrease in GDS (i.e., improved performance, p < .01) in participants not exposed to physical assault. In contrast, GDS remained unchanged (p = .69) in participants exposed to physical assault. Physical assault exposed participants’ baseline GDS was significantly higher (i.e., poorer performance) compared to the 1-year follow-up GDS of physical assault unexposed participants (p = .02).

Figure 2.

Between-group difference (physical assault exposure) in GDS over time.

Types of IPV Exposure and Attention/Working Memory

Given the above findings regarding attention/working memory and physical assault exposure, we conducted an MLM to determine if there was a significant time*IPV type interaction effect within the attention/working memory domain (see Supplementary Figure A). Results indicated a significant interaction effect (F(1,11) = 6.50, p = .01). Over 1 year, there was a strong trend toward a significant decrease in attention/working memory deficit scores (i.e., improved performance; p = .06) in participants not exposed to physical assault. In contrast, attention/working memory deficit scores slightly increased (i.e., poorer performance; p = .06) in participants exposed to physical assault. Further analysis of the attention/working memory domain and IPV type showed a significant time*IPV type interaction effect for sexual coercion (F(1,87) = 5.37, p = .02, η² = 0.07) and injury (F(1,113) = 4.31, p = .02, η² = 0.05), respectively (see Supplementary Figures B and C). Based on post hoc analysis, sexual coercion unexposed participants’ deficit scores slightly decreased (i.e., improved performance; p = .10) over time, while sexual coercion exposed participants’ deficit scores marginally increased (i.e., poorer performance; p = .09). Lastly, injury unexposed participants’ deficit scores slightly decreased (i.e., improved performance; p = .18) over time, while injury exposed participants’ deficit scores marginally increased (i.e., poorer performance; p = .08).

Discussion

In our sample of women with HIV, there was no significant between-group difference in GDS of IPV-exposed and IPV-unexposed participants at baseline or 1-year follow-up, yet we noted a trend for between-group differences in attention/working memory deficit scores. Analyses considering the different IPV types within the attention/working memory domain revealed significant time*IPV type interaction effects for physical assault, sexual coercion, and injury, respectively.

The Effect of IPV Exposure on Global and Domain-Specific Cognition

Given that both HIV (e.g., Daneman & Prat, 2015) and IPV (e.g., Clark, 2019; Esopenko et al., 2021) are associated with poorer cognition, we expected that IPV-exposed women with HIV would have significantly higher GDS (i.e., poorer performance) compared to IPV-unexposed women with HIV. However, our results revealed no significant difference in the present sample. Similarly, previous research in the same population examining longitudinal neurocognitive outcomes among women with and without HIV reported no significant differences in GDS, but did identify significant differences in domain-specific deficits, particularly in learning and attention/working memory (Van der Watt et al., 2025). These findings underscore the importance of considering the sensitivity and discriminative power of composite measures like the GDS compared to evaluating individual tests or specific cognitive domains separately (see also Van der Watt et al., 2025). Additionally, the results may be influenced by the application of the recently developed South African norms for the HNRC Battery (Deist et al., 2023), which were also used by Van der Watt et al. (2025). The importance of country- and population-specific norms in neurocognitive assessment cannot be overemphasized (Kiselica et al., 2024; Raudeberg et al., 2021; Villalobos et al., 2023).

However, consistent with Van der Watt et al. (2025), who observed significant differences in domain-specific deficit scores, including learning and attention/working memory, we also identified a trend toward between-group differences in the attention/working memory domain. This is in line with previous research linking specific neurocognitive domains to IPV perpetration (Chiu et al., 2022), where poorer working memory was significantly associated with greater aggression during conflict discussions among couples (Godfrey et al., 2020). Similarly, female victims of psychological IPV have demonstrated deficits in attention and decision-making (Daugherty et al., 2019). Collectively, these findings emphasize the importance of considering the sensitivity and discriminative capacity of composite measures like the GDS, in addition to evaluating individual tests or cognitive domains separately (see also Van der Watt et al., 2025).

Surprisingly, IPV-unexposed participants had higher baseline attention/working memory deficit scores (i.e., poorer performance), compared to IPV-exposed participants. This contradicts findings that IPV is associated with memory loss (Potter et al., 2021; Zieman et al., 2017). Yet, the time*IPV interaction effect indicated that IPV-unexposed women's attention/working memory deficit scores declined over time (i.e., improved performance), while the IPV-exposed women's deficit scores remained the same. This suggests that IPV exposure is a barrier to improvements in attention/working memory time (likely driven by antiretroviral use (e.g., Spies et al., 2017; Van der Watt et al., 2025)) among women with HIV. Future research incorporating objective measures of antiretroviral therapy adherence is needed to better understand its influence on the longitudinal neurocognitive functioning of women with HIV who have also been exposed to IPV.

Type of IPV Exposure and Neurocognition

Physical assault exposed participants’ GDS was significantly higher (i.e., poorer performance) compared to physical assault unexposed participants’ GDS at 1-year follow-up. Physical assault unexposed participants’ GDS significantly declined over time (i.e., improved performance), while the GDS of physical assault exposed participants remained unchanged. This supports findings from a multicountry study that specific types of IPV differentially affect health outcomes among female IPV victims (Potter et al., 2021).

Regarding physical assault as an IPV subtype, there is the possibility of traumatic brain injury (TBI: Haag et al., 2022) as measured by RCTS items (i.e., “beat up,” “choked,” and “slammed against wall”: Straus et al., 1996). Research indicates poorer executive functions in women with IPV-related TBI, compared to IPV-related sexual assault victims (Raskin et al., 2024). Yet, one would expect similar findings of higher GDS (i.e., poorer performance) for the injury subscale (as it may also indicate TBI)—which was not the case for GDS in our cohort. Additional item-specific analyses within a larger sample that also incorporates TBI data may help to clarify our findings.

Types of IPV Exposure and Attention/Working Memory

We found significant time*IPV type interaction effects within the attention/working memory domain for physical assault, sexual coercion, and injury, respectively. For all these IPV types, attention/working memory deficit scores remained the same over time for exposed women, while deficit scores decreased (i.e., improved performance) for unexposed women. This suggests that physical assault, sexual coercion, and injury, respectively, are significant barriers to improvements in attention/working memory performance over time among women with HIV. In accordance with the above, the findings of physical assault exposure may be related to potential TBI. Research indicates poorer memory in women who experienced IPV-related TBI, compared to women who experienced IPV-related sexual assault (Raskin et al., 2024). Specifically, the presence of ‘chocking’ was associated with poorer Hopkins Verbal Learning Test (HVLT: Brandt, 1991) recall performance (Raskin et al., 2024). Yet, it is important to note that Raskin et al. (2024) excluded sexual assault victims who experienced a blow to the head or strangulation. This is not necessarily the case in our cohort. Further analyses controlling for specific items (such as “choked”) within a larger sample are necessary to determine if sexual coercion exposure without the possibility of TBI will remain significantly associated with poorer attention/working memory over time.

The slight increase in attention/working memory deficit scores (i.e., poorer performance) over time among women exposed to physical assault, sexual coercion, and injury suggests that all IPV types (except for psychological aggression) as measured by the RCTS pose a risk for poorer longitudinal attention/working memory among women with HIV. Research supports the association between IPV victimization and poorer attention (Daugherty et al., 2019).

Notably, the dichotomous scoring approach of the RCTS assesses IPV exposure without distinguishing between victimization and perpetration (see Straus et al., 1996 for scoring instructions). Evidence suggests that male IPV perpetrators often display cognitive deficits, particularly in attention and memory domains (Romero-Martinez et al., 2021). Specifically, violent IPV perpetrators perform worse than nonviolent controls on measures of attention, sustained attention, and working memory. A recent meta-analysis further confirmed that IPV perpetrators exhibit poorer neuropsychological functioning—including working memory, attention switching, cognitive flexibility, planning, and phonemic fluency—compared to nonviolent men (Romero-Martinez et al., 2024). Consequently, it is not possible to determine whether the observed effects in the attention/working memory domain in our sample were driven by victimization, perpetration, or both, as our sample likely included individuals who were perpetrators of IPV. Indeed, South African studies commented on the underreported prevalence of male victims of domestic abuse, their silence (Barkhuizen, 2015; Kgatle & Mafa, 2021; Modau, 2016; Tshoane et al., 2024), and the inadequacies of the criminal justice system in protecting them (Tshoane et al., 2023). Victims of violence are also more likely to become perpetrators of violence (e.g., Kurniawan et al., 2019). While we found no difference in LEC among IPV-exposed and unexposed women within our sample, we did not isolate the physical and sexual assault items of the LEC. Combined, this warrants further analyses within a larger sample, which considers the IPV status (i.e., perpetrator or victim) to fully understand our findings regarding attention/working memory and the potential circular effect.

Implications

Prior research among the same cohort of women with HIV found a significant decrease in GDS (i.e., improved performance) over one year after controlling for childhood adverse events, lifetime trauma exposure, and PTSS (Van der Watt et al., 2025). The authors hypothesized that this may be due to the increased antiretroviral use (between baseline and 1-year follow-up), which possibly facilitated improved cognitive function (Cross et al., 2013; Nakasujja et al., 2010; Sacktor et al., 2006). Yet, among our sample with comparable antiretroviral use, IPV-related physical assault exposure hindered longitudinal cognitive improvement. This highlights how different IPV profiles may differentially impact health over time and should be considered when developing interventions (Potter et al., 2021). For instance, our findings showed that both injury and sexual coercion were associated with a decline in attention/working memory over time; however, the effect of sexual coercion was of medium magnitude, whereas the effect of injury was small. Further research is needed to clarify the mechanisms through which different forms of IPV uniquely affect attention/working memory. The high prevalence of IPV in our sample (ranging from 79.45% to 84.29%) reinforces the need for healthcare professionals to screen for IPV among women with HIV (Hansrod et al., 2015). These rates exceed previous estimates reported for South African women with HIV (56.3%: Matseke et al., 2016), highlighting the urgency of training HIV care providers in comprehensive trauma screening, linking at-risk women to appropriate services and interventions (Yemeke et al., 2020), and delivering trauma-informed care (Brown & Adeagbo, 2022). Women with HIV who have experienced IPV should receive additional counseling and ongoing support to reduce the impact of IPV as a barrier to longitudinal neurocognitive improvement. Interventions should particularly target women exposed to IPV-related physical assault, as all forms of IPV (including physical assault, sexual coercion, and injury) except psychological aggression were found to specifically hinder attention and working memory improvement over time. Therefore, healthcare professionals should monitor changes in attention and working memory in women with HIV, as such changes may indicate IPV exposure. These findings further emphasize the importance of broader implementation of IPV screening in HIV care settings and the integration of trauma-focused interventions into HIV treatment (Yemeke et al., 2020). Lastly, our findings highlight the importance of educating women with HIV about IPV. This includes working toward greater gender equality within South Africa to reduce the prevalence of IPV (Falb et al., 2015).

Limitations, Future Recommendations, and Strengths

The small sample, especially at 1-year follow-up, limits the statistical power of our findings, despite the strength of the longitudinal design. However, MLM allowed us to use all data points and to include incomplete cases, increasing the analyzable sample size. Nonetheless, we encourage future research with a larger sample.

The exclusion of women using psychotropic medication at study entry in the parent study may have unintentionally introduced selection bias. Women exposed to IPV often present with symptoms of depression (e.g., Woolhouse et al., 2019) and anxiety (Chandan et al., 2020), conditions that are frequently managed with psychotropic medication. Consequently, those experiencing more severe mental health effects of IPV may have been underrepresented, and exclusion of these women may have resulted in an attenuation of observed associations with cognitive outcomes.

We acknowledge that the difference in sample size between IPV-exposed and IPV-unexposed participants may have affected the assumption of equal variances and the possibility of a Type 1 error (Parra-Frutos, 2013). However, dichotomous scoring was previously proven to be reliable within the same cohort (Hansrod et al., 2015) and another multi-country IPV study (Potter et al., 2021). Also, the prevalence scoring method allowed for the direct comparison of IPV-exposed versus IPV-unexposed HAND data and served as an accurate representation (and reminder) of the high IPV exposure rates among South African women in general (24%: World Health Organization, 2019) and South African women with HIV (56%: Matseke et al., 2016). Nevertheless, we recommend future research with more balanced sample distributions and/or the use of IPV as a continuous variable to validate our findings. Applying the chronicity scoring method (Straus et al., 1996) could further clarify the effects of cumulative IPV and polyvictimization, which may differentially influence longitudinal neurocognitive functioning.

IPV is a multifaceted and complex phenomenon which is not necessarily accurately captured by the use of a single measure such as the RCTS (Hansrod et al., 2015). The RCTS does not consider the context, meaning, and motives behind IPV. Further, the dichotomous scoring method does not differentiate between victims and perpetrators. This limits our interpretation of the findings and precludes us from drawing definitive conclusions. Thus, research using the RCTS can benefit from supplemental interviews to provide contextual information (Chapman & Gillespie, 2019) which must be considered to minimize the possibility of inflating IPV rates (Lehrner & Allen, 2014). Future research should consider using multiple IPV measures, including qualitative interviews, to provide better contextual information.

The use of self-report demographic, trauma, and IPV exposure measures possibly contributed to social desirability bias. While objective measures such as medical and social service records may reduce social desirability bias, South African women are reluctant to officially report IPV, given experiences of insufficient support by public services (TEARS, 2022) and the normalization of abuse in South Africa (Gordon, 2016). This highlights the importance of using multiple sources of information to determine IPV prevalence.

Lastly, our sample was mostly Xhosa-speaking (with only one participant reporting a different home language at 1-year follow-up), limiting the generalizability of our findings to women with a different home language. While we did control for home language in all analyses, future research should include women with different home languages to reflect the South African population (Statista, 2024).

Despite the above limitations, our research provides valuable insights into the progression of HAND and the effect of IPV on this progression. Specifically, we added to the work of Potter et al. (2021) in providing a basis from which to better understand how different IPV types may impact women's health, with a specific focus on women with HIV. Our findings are further strengthened by the use of longitudinal data as opposed to the cross-sectional data of Potter et al. (2021). Lastly, our research aligns with the 5th Goal (Gender Equality and Women and Girls’ Empowerment) of the Sustainable Development Goals (United Nations, n.d.), which is especially important within the South African context, where women are disproportionately affected by IPV exposure (O’Regan, 2022) and HIV (UNAIDS, 2022).

Conclusion

Among our sample of women with HIV, IPV-related physical assault exposure was a barrier to longitudinal neurocognitive improvement. Further IPV-related physical assault, sexual coercion, and injury were barriers to longitudinal attention/working memory improvement. Our findings highlight the importance of screening for IPV and IPV subtypes among women with HIV for improved support and targeted interventions focusing on improving attention/working memory. We encourage the continued effort towards educating people about IPV and gender equality within South Africa to decrease the prevalence of IPV.

Supplemental Material

sj-docx-1-vaw-10.1177_10778012251397969 - Supplemental material for Longitudinal Neurocognitive Performance in South African Women With HIV and Domestic Violence

Supplemental material, sj-docx-1-vaw-10.1177_10778012251397969 for Longitudinal Neurocognitive Performance in South African Women With HIV and Domestic Violence by A. S. J. Van der Watt, G. Spies and S. Seedat in Violence Against Women

Footnotes

Acknowledgments

We thank the women who participated in this study. We thank Professor Martin Kidd for assisting with the statistical analyses and norming of the neurocognitive data.

ORCID iDs

A. S. J. Van der Watt

G. Spies

Funding

AvdW received funding from the National Institutes of Health Pittsburgh & Stellenbosch Universities HIV-Associated Cardio-Metabolic, Chronic Kidney and Neuropsychiatry Diseases Research Training Fellowship Programme to write this manuscript. Additional research support was provided by a CFAR grant awarded to S Seedat [P30-AI036214] and the HIV Neurobehavioral Research Center (HNRC; National Institutes of Health [grant number P30-MH62512]). This work is supported by the South African PTSD Research Programme of Excellence and the South African Medical Research Council/Stellenbosch University Genomics of Brain Disorders Research Unit.

Authors’ Contributions

SS contributed to study conception and writing the manuscript. GS contributed to study conception, recruitment, data collection and management, and writing the manuscript. AvdW contributed to data cleaning, data analysis, and manuscript writing.

Declaration of Conflicting Interests

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

Supplemental Material

Supplemental material for this article is available online.

Author Biographies

Alberta S. J. van der Watt is a research psychologist, conducting mixed-method research focusing on trauma, traumatic stress, and posttraumatic stress symptoms. She has a keen interest in interpersonal trauma, including attachment trauma. Alberta's trauma-focused research encompasses various topics, including mood monitoring, traditional and faith healing, and HIV and neurocognition. She is currently part of the South African Posttraumatic Stress Disorder Research Programme of Excellence hosted by Stellenbosch University and headed by Prof Soraya Seedat.

Georgina Spies is a Psychology lecturer at the University of Cape Town, South Africa. Her interests lie more broadly in cognitive and affective neuroscience and neuropsychology. Her research primarily focuses on NeuroAIDS and brain and behavioral outcomes of coexisting epidemics, such as HIV, harmful alcohol use, SARS-CoV-2, and traumatic stress. She is a member of the Child Trauma Network of the Global Collaboration on Traumatic Stress, which aims to improve the transcultural understanding of emotional, behavioral, cognitive, physiological, and societal factors underlying well-being and social functioning in individuals affected by childhood maltreatment.

Soraya Seedat is Professor of Psychiatry and Executive Head of the Department of Psychiatry at Stellenbosch University. Her expertise lies in posttraumatic stress disorder, anxiety disorders, and neuroHIV.

References

Alemie

A. S.

Yeshita

H. Y.

Zeleke

E. G.

Mekonnen

B. D.

(2023). Intimate partner violence and associated factors among HIV positive women attending antiretroviral therapy clinics in gondar city, northwest Ethiopia. BMC Women’s Health, 23(1), 43. https://doi.org/10.1186/s12905-023-02193-7

Barkhuizen

(2015). ‘Cowboys don’t cry…’—the male victim of domestic violence. Acta Criminologica: African Journal of Criminology & Victimology, 28(2), 47–61. https://journals.co.za/doi/abs/10.10520/EJC185958

Benoit

Shumka

Phillips

Kennedy

M. C.

Belle-Isle

(2015). Issue Brief: Sexual violence against women in Canada (pp. 1–55) [Issue Brief]. Federal Provincial Territorial Senior Officials for the Status of Women. chrome-extension://efaidnbmnnnibpcajpcglclefindmkaj/https://cfc-swc.gc.ca/svawc-vcsfc/issue-brief-en.pdf.

Bernstein

Fink

(1998). Childhood Trauma Questionnaire: A retrospective self-report manual. The Psychological Corporation.

Brandt

(1991). The hopkins verbal learning test: Development of a new memory test with six equivalent forms. Clinical Neuropsychologist, 5(2), 125–142. https://doi.org/10.1080/13854049108403297

Brown

M. J.

Adeagbo

(2022). Trauma-Informed HIV care interventions: Towards a holistic approach. Current HIV/AIDS Reports, 19(3), 177–183. https://doi.org/10.1007/s11904-022-00603-3

Chandan

J. S.

Thomas

Bradbury-Jones

Russell

Bandyopadhyay

Nirantharakumar

Taylor

(2020). Female survivors of intimate partner violence and risk of depression, anxiety and serious mental illness. The British Journal of Psychiatry, 217(4), 562–567. https://doi.org/10.1192/bjp.2019.124

Chapman

Gillespie

S. M.

(2019). The revised conflict tactics scales (CTS2): A review of the properties, reliability, and validity of the CTS2 as a measure of partner abuse in community and clinical samples. Aggression and Violent Behavior, 44, 27–35. https://doi.org/10.1016/j.avb.2018.10.006

Cherner

Cysique

Heaton

R. K.

Marcotte

T. D.

Ellis

R. J.

Masliah

Grant

(2007). Neuropathologic confirmation of definitional criteria for human immunodeficiency virus–associated neurocognitive disorders. Journal of Neurovirology, 13(1), 23–28. https://doi.org/10.1080/13550280601089175

10.

Chiu

Gnall

Pless Kaiser

Taft

C. T.

Franz

M. R.

Lee

L. O.

Vasterling

J. J.

(2022). Neurocognitive performance predicts future partner violence among U.S. Iraq- and Afghanistan-deployed army soldiers and veterans. Psychology of Violence, 12(3), 160–169. https://doi.org/10.1037/vio0000408

11.

Clark

(2019). Cognitive Development in the Context of Trauma: Longitudinal Implications of Intimate Partner Violence for Women and Children [Doctoral dissertation, University of Michigan]. https://deepblue.lib.umich.edu/handle/2027.42/151615.

12.

Closson

Dietrich

J. J.

Nkala

Musuku

Cui

Chia

Gray

Lachowsky

N. J.

Hogg

R. S.

Miller

C. L.

Kaida

(2016). Prevalence, type, and correlates of trauma exposure among adolescent men and women in soweto, South Africa: Implications for HIV prevention. BMC Public Health, 16(1), 1191. https://doi.org/10.1186/s12889-016-3832-0

13.

Colombini

James

Ndwiga

., Integra team, & Mayhew

S. H.

(2016). The risks of partner violence following HIV status disclosure, and health service responses: Narratives of women attending reproductive health services in Kenya. Journal of the International AIDS Society, 19(1), 20766. https://doi.org/10.7448/IAS.19.1.20766

14.

Cross

H. M.

Combrinck

M. I.

Joska

J. A.

(2013). HIV-associated neurocognitive disorders: Antiretroviral regimen, central nervous system penetration effectiveness, and cognitive outcomes. South African Medical Journal, 103(10), 758. https://doi.org/10.7196/SAMJ.6677

15.

Daneman

Prat

(2015). The blood–brain barrier. Cold Spring Harbor Perspectives in Biology, 7(1), a020412. https://doi.org/10.1101/cshperspect.a020412

16.

Daugherty

J. C.

Marañón-Murcia

Hidalgo-Ruzzante

Bueso-Izquierdo

Jiménez-González

Gómez-Medialdea

Pérez-García

(2019). Severity of neurocognitive impairment in women who have experienced intimate partner violence in Spain. The Journal of Forensic Psychiatry & Psychology, 30(2), 322–340. https://doi.org/10.1080/14789949.2018.1546886

17.

Davidson

J. R. T.

Book

S. W.

Colket

J. T.

Tupler

L. A.

Roth

David

Hertzberg

Mellman

Beckham

J. C.

Smith

R. D.

Davidson

R. M.

Katz

Feldman

M. E.

(1997). Assessment of a new self-rating scale for post-traumatic stress disorder. Psychological Medicine, 27(1), 153–160. https://doi.org/10.1017/S0033291796004229

18.

Deist

Suliman

Kidd

Franklin

Cherner

Heaton

R. K.

Spies

Seedat

(2023). Neuropsychological Test Norms for the Assessment of HIV-Associated Neurocognitive Impairment Among South African Adults. AIDS and Behavior, 27(9), 3080–3097. https://doi.org/10.1007/s10461-023-04029-9

19.

Esopenko

Meyer

Wilde

E. A.

Marshall

A. D.

Tate

D. F.

Lin

A. P.

Koerte

I. K.

Werner

K. B.

Dennis

E. L.

Ware

A. L.

De Souza

N. L.

Menefee

D. S.

Dams-O’Connor

Stein

D. J.

Bigler

E. D.

Shenton

M. E.

Chiou

K. S.

Postmus

J. L.

Monahan

Hillary

F. G.

(2021). A global collaboration to study intimate partner violence-related head trauma: The ENIGMA consortium IPV working group. Brain Imaging and Behavior, 15(2), 475–503. https://doi.org/10.1007/s11682-020-00417-0

20.

Falb

K. L.

Annan

Gupta

(2015). Achieving gener equality to reduce intimate partner violence against women. The Lancet Global Health, 3(6), E302–E303. https://doi.org/10.1016/S2214-109X(15)00006-6

21.

Gass

J. D.

Stein

D. J.

Williams

D. R.

Seedat

(2011). Gender differences in risk for intimate partner violence among South African adults. Journal of Interpersonal Violence, 26(14), 2764–2789. https://doi.org/10.1177/0886260510390960

22.

Gibbs

Dunkle

Willan

Jama-Shai

Washington

Jewkes

(2019). Are women’s experiences of emotional and economic intimate partner violence associated with HIV-risk behaviour? A cross-sectional analysis of young women in informal settlements in South Africa. AIDS Care, 31(6), 667–674. https://doi.org/10.1080/09540121.2018.1533230

23.

Godfrey

D. A.

Kehoe

C. M.

Bastardas-Albero

Babcock

J. C.

(2020). Empathy mediates the relations between working memory and perpetration of intimate partner violence and aggression. Behavioral Sciences, 10(3), 63. https://doi.org/10.3390/bs10030063

24.

Gordon

(2016). Intimate partner violence is everyone’s problem, but how should we approach it in a clinical setting? South African Medical Journal, 106(10), 962. https://doi.org/10.7196/SAMJ.2016.v106i10.11408

25.

Gray

M. J.

Litz

B. T.

Hsu

J. L.

Lombardo

T. W.

(2004). Psychometric properties of the life events checklist. Assessment, 11(4), 330–341. https://doi.org/10.1177/1073191104269954

26.

Haag

H. (Lin).

Jones

Joseph

Colantonio

(2022). Battered and brain injured: Traumatic brain injury among women survivors of intimate partner violence—A scoping review. Trauma, Violence, & Abuse, 23(4), 1270–1287. https://doi.org/10.1177/1524838019850623

27.

Hansrod

Spies

Seedat

(2015). Type and severity of intimate partner violence and its relationship with PTSD in HIV-infected women. Psychology, Health & Medicine, 20(6), 697–709. https://doi.org/10.1080/13548506.2014.967702

28.

Heaton

R. K.

Cysique

L. A.

Jin

Shi

Letendre

Franklin

Ake

Vigil

Atkinson

Marcotte

Grant

, & HNRC group. (2010). Neurobehavioral effects of human immunodeficiency virus infection among former plasma donors in rural China. Journal of Neurovirology, 16(2), 185–188. https://doi.org/10.3109/13550284.2010.481820

29.

Heaton

R. K.

Franklin

D. R.

Ellis

R. J.

McCutchan

J. A.

Letendre

S. L.

LeBlanc

Corkran

S. H.

Duarte

N. A.

Clifford

D. B.

Woods

S. P.

Collier

A. C.

Marra

C. M.

Morgello

Mindt

M. R.

Taylor

M. J.

Marcotte

T. D.

Atkinson

J. H.

Wolfson

Gelman

B. B.

Grant

(2011). HIV-associated neurocognitive disorders before and during the era of combination antiretroviral therapy: Differences in rates, nature, and predictors. Journal of NeuroVirology, 17(1), 3–16. https://doi.org/10.1007/s13365-010-0006-1

30.

HIV Neurobehavioral Research Center. (2022). HIV Neurobehavioral Research Center International Neurobehavioral Battery [Test]. HIV Neurobehavioral Research Center. https://hnrc.hivresearch.ucsd.edu/index.php .

31.

Hoare

Phillips

Joska

J. A.

Paul

Donald

K. A.

Stein

D. J.

Thomas

K. G. F.

(2016). Applying the HIV-associated neurocognitive disorder diagnostic criteria to HIV-infected youth. Neurology, 87(1), 86–93. https://doi.org/10.1212/WNL.0000000000002669

32.

Human Sciences Research Council. (2023). New HIV survey highlights progress and ongoing disparities in South Africa’s HIV epidemic. Human Sciences Research Council. https://hsrc.ac.za/press-releases/phsb/new-hiv-survey-highlights-progress-and-ongoing-disparities-in-south-africas-hiv-epidemic/#:∼:text=Compared%20to%20males%20of%20the,)%2C%E2%80%9D%20said%20Professor%20Zuma.

33.

Iliyasu

Abubakar

I. S.

Babashani

Galadanci

H. S.

(2011). Domestic violence among women living with HIV/AIDS in kano, northern Nigeria. African Journal of Reproductive Health, 15(3), 41–49.

34.

Jacob

S. N.

Dodge

C. P.

Vasterling

J. J.

(2019). Posttraumatic stress disorder and neurocognition: A bidirectional relationship? Clinical Psychology Review, 72, 101747. https://doi.org/10.1016/j.cpr.2019.101747

35.

Jak

A. J.

Crocker

L. D.

Aupperle

R. L.

Clausen

Bomyea

(2016). Neurocognition in PTSD: Treatment insights and implications. In Vermetten

Baker

D. G.

Risbrough

V. B.

(Eds.), Behavioral neurobiology of PTSD (Vol. 38, pp. 93–116). Springer International Publishing. https://doi.org/10.1007/7854_2016_62

36.

Joska

J. A.

Fincham

D. S.

Stein

D. J.

Paul

R. H.

Seedat

(2010). Clinical correlates of HIV-associated neurocognitive disorders in South Africa. AIDS and Behavior, 14(2), 371–378. https://doi.org/10.1007/s10461-009-9538-x

37.

Kanmogne

G. D.

Fonsah

J. Y.

Umlauf

Moul

Doh

R. F.

Kengne

A. M.

Tang

Tagny

C. T.

Nchindap

Kenmogne

Franklin

Njamnshi

D. M.

Kuate

C. T.

Mbanya

Njamnshi

A. K.

Heaton

R. K.

(2020). Effects of HIV infection, antiretroviral therapy, and immune status on the speed of information processing and complex motor functions in adult Cameroonians. Scientific Reports, 10(1), 14016. https://doi.org/10.1038/s41598-020-70981-4

38.

Kavanaugh

B. C.

Dupont-Frechette

J. A.

Jerskey

B. A.

Holler

K. A.

(2017). Neurocognitive deficits in children and adolescents following maltreatment: Neurodevelopmental consequences and neuropsychological implications of traumatic stress. Applied Neuropsychology: Child, 6(1), 64–78. https://doi.org/10.1080/21622965.2015.1079712

39.

Kgatle

M. O.

Mafa

(2021). Absent voices: Help-seeking behaviour among South African male victims of intimate partner violence. Technium Social Sciences Journal, 24, 717–728.

40.

Kiselica

A. M.

Karr

J. E.

Mikula

C. M.

Ranum

R. M.

Benge

J. F.

Medina

L. D.

Woods

S. P.

(2024). Recent advances in neuropsychological test interpretation for clinical practice. Neuropsychology Review, 34(2), 637–667. https://doi.org/10.1007/s11065-023-09596-1

41.

Kurniawan

L. S.

Aryani

L. N. A.

Chandra

G. N.

Mahadewa

T. G. B.

Ryalino

(2019). Victims of physical violence have a higher risk to be perpetrators: A study in high school students population. Open Access Macedonian Journal of Medical Sciences, 7(21), 3679–3681. https://doi.org/10.3889/oamjms.2019.797

42.

Lehrner

Allen

N. E.

(2014). Construct validity of the conflict tactics scales: A mixed-method investigation of women’s intimate partner violence. Psychology of Violence, 4(4), 477–490. https://doi.org/10.1037/a0037404

43.

Maki

P. M.

Rubin

L. H.

Valcour

Martin

Crystal

Young

Weber

K. M.

Manly

Richardson

Alden

Anastos

(2015). Cognitive function in women with HIV: Findings from the women’s interagency HIV study. Neurology, 84(3), 231–240. https://doi.org/10.1212/WNL.0000000000001151

44.

Matseke

Rodriguez

V. J.

Peltzer

Jones

(2016). Intimate partner violence among HIV positive pregnant women in South Africa. Journal of Psychology in Africa, 26(3), 259–266. https://doi.org/10.1080/14330237.2016.1185912

45.

Michael

H. U.

Naidoo

Mensah

K. B.

Ramlall

Oosthuizen

(2021). The impact of antiretroviral therapy on neurocognitive outcomes among people living with HIV in low- and middle-income countries (LMICs): A systematic review. AIDS and Behavior, 25(2), 492–523. https://doi.org/10.1007/s10461-020-03008-8

46.

Modau

A. B.

(2016). The silence of male victims in relation to domestic violence in heterosexual relationships in Makhando Municipality, Limpopo, South Africa: An exploratory study. GAI International Academic Conferences Proceedings, 8–49. chrome-extension://efaidnbmnnnibpcajpcglclefindmkaj/https://www.researchgate.net/profile/Adnan-Shoaib-2/publication/348235762_GAI_International_Academic_Conference_Istanbul_Turkey_ISBN_978-0-9965808-5-4/links/5ff4898992851c13feefa91f/GAI-International-Academic-Conference-Istanbul-Turkey-ISBN-978-0-9965808-5-4.pdf.

47.

Nakasujja

N. L.

Skolasky

Musisi

Allebeck

Robertson

Ronald

Katabira

Clifford

D. B.

Sacktor

(2010). Depression symptoms and cognitive function among individuals with advanced HIV infection initiating HAART in Uganda. BMC Psychiatry, 10(1), 44. https://doi.org/10.1186/1471-244X-10-44

48.

Okafor

C. N.

Barnett

Zar

H. J.

Nhapi

Koen

Shoptaw

Stein

D. J.

(2021). Associations of emotional, physical, or sexual intimate partner violence and depression symptoms among South African women in a prospective cohort study. Journal of Interpersonal Violence, 36(9–10), NP5060–NP5083. https://doi.org/10.1177/0886260518796522

49.

O’Regan

(2022). ‘Unacceptable’ spike in gender-based violence and femicide as lawlessness continues to grip South Africa. Daily Maverick. https://www.dailymaverick.co.za/article/2022-11-23-unacceptable-spike-in-gender-based-violence-and-femicide-as-lawlessness-continues-to-grip-south-africa/.

50.

Parra-Frutos

(2013). Testing homogeneity of variances with unequal sample sizes. Computational Statistics, 28(3), 1269–1297. https://doi.org/10.1007/s00180-012-0353-x

51.

Potter

L. C.

Morris

Hegarty

García-Moreno

Feder

(2021). Categories and health impacts of intimate partner violence in the world health organization multi-country study on women’s health and domestic violence. International Journal of Epidemiology, 50(2), 652–662. https://doi.org/10.1093/ije/dyaa220

52.

Radloff

L. S.

(1977). The CES-D scale: A self-report depression scale for research in the general population. Applied Psychological Measurement, 1(3), 385–401. https://doi.org/10.1177/014662167700100306

53.

Raskin

S. A.

DeJoie

Edwards

Ouchida

Moran

White

Mordasiewicz

Anika

Njoku

(2024). Traumatic brain injury screening and neuropsychological functioning in women who experience intimate partner violence. The Clinical Neuropsychologist, 38(2), 354–376. https://doi.org/10.1080/13854046.2023.2215489

54.

Raudeberg

Iverson

G. L.

Hammar

(2021). The importance of clinical normative data for conceptualizing neuropsychological deficits in people with schizophrenia spectrum disorders. Applied Neuropsychology: Adult, 28(6), 752–760. https://doi.org/10.1080/23279095.2019.1699098

55.

Robbins

R. N.

Remien

R. H.

Mellins

C. A.

Joska

J. A.

Stein

D. J.

(2011). Screening for HIV-associated dementia in South Africa: Potentials and pitfalls of task-shifting. AIDS Patient Care and STDs, 25(10), 587–593. https://doi.org/10.1089/apc.2011.0154

56.

Romero-Martínez

Lila

Vitoria-Estruch

Moya-Albiol

(2021). Can attention and working memory impairments of intimate partner perpetrators explain their risky decision making? Journal of Interpersonal Violence, 36(11–12), NP6492–NP6507. https://doi.org/10.1177/0886260518814263

57.

Romero-Martínez

Sarrate-Costa

Moya-Albiol

(2024). A meta-analysis of cognitive functioning in intimate partner violence perpetrators. Neuropsychology Review, 34(4), 1191–1212. https://doi.org/10.1007/s11065-023-09628-w

58.

Royston

Altman

D. G.

(1994). Regression using fractional polynomials of continuous covariates: Parsimonious parametric modelling. Applied Statistics, 43(3), 429. https://doi.org/10.2307/2986270

59.

Sacktor

Nakasujja

Skolasky

Robertson

Wong

Musisi

Ronald

Katabira

(2006). Antiretroviral therapy improves cognitive impairment in HIV+ individuals in sub-saharan Africa. Neurology, 67(2), 311–314. https://doi.org/10.1212/01.wnl.0000225183.74521.72

60.

Sardinha

Maheu-Giroux

Stöckl

Meyer

S. R.

García-Moreno

(2022). Global, regional, and national prevalence estimates of physical or sexual, or both, intimate partner violence against women in 2018. Lancet (London, England), 399(10327), 803–813. https://doi.org/10.1016/S0140-6736(21)02664-7

61.

Smail

R. C.

Brew

B. J.

(2018). HIV-associated neurocognitive disorder. In Handbook of clinical neurology (Vol. 152, pp. 75–97). Elsevier. https://doi.org/10.1016/B978-0-444-63849-6.00007-4

62.

Spies

Deist

Suliman

Seedat

(2023). Screening for HIV-associated neurocognitive impairment: Development and validation of an abbreviated neuropsychological test battery for use in South African clinical settings. Neuropsychology, 37(2), 166–180. https://doi.org/10.1037/neu0000872

63.

Spies

Fennema-Notestine

Cherner

Seedat

(2017). Changes in cognitive function in women with HIV infection and early life stress. AIDS Care, 29(1), 14–23. https://doi.org/10.1080/09540121.2016.1204417

64.

Spies

Seedat

(2014). Depression and resilience in women with HIV and early life stress: Does trauma play a mediating role? A cross-sectional study. BMJ Open, 4(2), e004200. https://doi.org/10.1136/bmjopen-2013-004200

65.

Statista. (2024). Distribution of languages spoken by individuals inside and outside of households in South Africa 2018. https://www.statista.com/statistics/1114302/distribution-of-languages-spoken-inside-and-outside-of-households-in-south-africa/.

66.

StatsSA. (2022). Statistical Release: P0341 Victims of Crime. Department of Statistics South Africa: Republic of South Africa.

67.

Stockman

J. K.

Lucea

M. B.

Campbell

J. C.

(2013). Forced sexual initiation, sexual intimate partner violence and HIV risk in women: A global review of the literature. AIDS and Behavior, 17(3), 832–847. https://doi.org/10.1007/s10461-012-0361-4

68.

Straus

M. A.

Hamby

S. L.

Boney-McCoy

Sugarman

D. B.

(1996). The revised conflict tactics scales (CTS2): Development and preliminary psychometric data. Journal of Family Issues, 17(3), 283–316. https://doi.org/10.1177/019251396017003001

69.

Schouten

Geurtsen

G. J.

Wit

F. W.

Stolte

I. G.

Prins

Portegies

Caan

M. W. A.

Reiss

Majoie

C. B.

Schmand

B. A.

(2015). Multivariate normative comparison, a novel method for more reliably detecting cognitive impairment in HIV infection. Aids (London, England), 29(5), 547–557. https://doi.org/10.1097/QAD.0000000000000573

70.

Sullivan

T. P.

(2019). The intersection of intimate partner violence and HIV: Detection, disclosure, discussion, and implications for treatment adherence. Topics in Antiviral Medicine, 27(2), 84–87.

71.

TEARS. (2022). Violence against women—A problem in South Afirca. https://tears.co.za/news-articles/violence-against-women-a-problem-in-south-africa/#:∼:text=Victims%20of%20violence%20are%20not,legal%20consequences%20for%20the%20perpetrators.

72.

The HNRC Group, De Almeida

S. M.

De Pereira

A. P.

Pedroso

M. L. A.

Ribeiro

C. E.

Rotta

Tang

Umlauf

Franklin

Saloner

R. G.

Batista

M. G. R.

Letendre

Heaton

R. K.

Ellis

R. J.

Cherner

(2018). Neurocognitive impairment with hepatitis C and HIV co-infection in southern Brazil. Journal of NeuroVirology, 24(3), 339–349. https://doi.org/10.1007/s13365-018-0617-5

73.

Tsai

A. C.

(2018). Syndemics: A theory in search of data or data in search of a theory? Social Science & Medicine, 206, 117–122. https://doi.org/10.1016/j.socscimed.2018.03.040

74.

Tshoane

S. M.

Bellow

P. O.

Mofokeng

J. T.

, & Olutola. (2023). The inadequacies of the South African criminal justice system against male victims of domestic abuse. OIDA International Journal of Sustainable Development, 16(06), 21–34.

75.

Tshoane

S. M.

Olutola

A. A.

Bello

P. O.

Mofokeng

J. T.

(2024). Domestic violence against men: Unmuting the reality of the forgotten gender. Cogent Social Sciences, 10(1), 2304990. https://doi.org/10.1080/23311886.2024.2304990

76.

UNAIDS. (2022). HIV and AIDS Estimates: South Africa 2022 [Data set]. UNAIDS. https://www.unaids.org/en/regionscountries/countries/southafrica.

77.

United Nations. (n.d.). The 17 Goals. Retrieved 23 September 2024, from https://sdgs.un.org/goals.

78.

Van der Watt

Kidd

Roos

Lesch

Seedat

(2023). Romantic relationship dissolutions are significantly associated with posttraumatic stress symptoms as compared to a DSM-5 criterion A event: A case-case–control comparison. European Journal of Psychotraumatology, 14(2), 2238585. https://doi.org/10.1080/20008066.2023.2238585

79.

Van Der Watt

A. S. J.

Spies

Seedat

(2025). A longitudinal analysis of neurocognitive profiles in South African women with HIV. AIDS Care, 37(3), 396–409. https://doi.org/10.1080/09540121.2025.2454340

80.

Ventimiglia

Van der Watt

Kidd

Seedat

(2020). Association between trauma exposure and mood trajectories in patients with mood disorders. Journal of Affective Disorders, 262, 237–246. https://doi.org/10.1016/j.jad.2019.10.057

81.

Villalobos

Torres-Simón

Pacios

Paúl

Del Río

(2023). A systematic review of normative data for verbal fluency test in different languages. Neuropsychology Review, 33(4), 733–764. https://doi.org/10.1007/s11065-022-09549-0

82.

Williams

M. R.

Murphy

C. M.

Dore

G. A.

Evans

M. K.

Zonderman

A. B.

(2017). Intimate partner violence victimization and cognitive function in a mixed-sex epidemiological sample of urban adults. Violence and Victims, 32(6), 1133–1148. https://doi.org/10.1891/0886-6708.VV-D-16-00118

83.

Woolhouse

Gartland

Papadopoullos

Mensah

Hegarty

Giallo

Brown

(2019). Psychotropic medication use and intimate partner violence at 4 years postpartum: Results from an Australian pregnancy cohort study. Journal of Affective Disorders, 251, 71–77. https://doi.org/10.1016/j.jad.2019.01.052

84.

World Health Organization. (2013). Global and regional estimates of violence against women: Prevalence and health effects of intimate partner violence and non-partner sexual violence. World Health Organization. https://iris.who.int/handle/10665/85239

85.

World Health Organization. (2019). Global Data Base on the Prevalence of Violence Against Women. World Health Organization. https://vaw-data.srhr.org/data?chart1%5Bviolence_type%5D=ipv&chart1%5Bregion%5D=Africa&chart1%5Bregion_class%5D=WHO&chart1%5Bcountries%5D%5B%5D=ZAF .

86.

World Health Organization. (2021). Violence against women. World Health Organization. https://www.who.int/news-room/fact-sheets/detail/violence-against-women

87.

Yemeke

T. T.

Sikkema

K. J.

Watt

M. H.

Ciya

Robertson

Joska

J. A.

(2020). Screening for traumatic experiences and mental health distress among women in HIV care in Cape Town, South Africa. Journal of Interpersonal Violence, 35(21–22), 4842–4862. https://doi.org/10.1177/0886260517718186

88.

Zieman

Bridwell

Cárdenas

J. F.

(2017). Traumatic brain injury in domestic violence victims: A retrospective study at the barrow neurological institute. Journal of Neurotrauma, 34(4), 876–880. https://doi.org/10.1089/neu.2016.4579

Supplementary Material

Please find the following supplemental material available below.

For Open Access articles published under a Creative Commons License, all supplemental material carries the same license as the article it is associated with.

For non-Open Access articles published, all supplemental material carries a non-exclusive license, and permission requests for re-use of supplemental material or any part of supplemental material shall be sent directly to the copyright owner as specified in the copyright notice associated with the article.

0.00 MB

0.06 MB