Measuring Intimate Partner Violence in Sexual and Gender Minority Populations: A COSMIN Psychometric Review

Abstract

Intimate partner violence (IPV) is a significant public and mental health concern, yet much of its research and measurement have been developed through a cisgender, heterosexual lens. Sexual and gender minority (SGM) populations experience IPV at rates equal to or higher than their cisgender, heterosexual counterparts and experience unique forms of abuse, including identity-based and transphobia-driven violence. However, the lack of IPV measures validated for SGM populations raises concerns about the accuracy and inclusivity of existing tools, contributing to inconsistent prevalence estimates. This study presents a two-tiered review of self-report IPV measures for SGM populations. Tier 1 evaluated psychometric properties of scales using COnsensus-based Standards for selecting health Measurement INstruments (COSMIN), while Tier 2 examined the broader application of IPV measures in empirical research. Eligible studies were original, English-language research measuring IPV in SGM populations, scale development or validation (Tier 1) or reported a reliability statistic (Tier 2). A systematic search identified 9 scale development/validation studies and 72 studies using IPV scales. Notably, SGM-specific measures remain underutilized, with most studies continuing to rely on heterocentric measures. Structural validity and internal consistency were adequate across scales, but evidence for content validity, cross-cultural validity, reliability, and hypothesis-testing was often limited or indeterminate, with no measure achieving full COSMIN recommendations. While several promising SGM-specific IPV tools exist, further refinement, validation, and development of a set of consensus-driven gold standard measures are needed to support accurate assessment, prevalence estimates, and effective interventions for IPV in SGM populations.

Keywords

intimate partner violence sexual and gender minorities 2SLGBTQI+measurement psychometric evaluation review

Introduction

Over the last six decades, research investigating intimate partner violence (IPV) has become a priority in both public and mental health (Kubicek, 2016). As a subset of interpersonal violence, IPV describes any abusive behavior resulting in physical, sexual, or psychological harm, and often includes emotional abuse and controlling behaviors that occur within the setting of an intimate relationship (World Health Organization, 2013). Although the IPV literature is extensive, it has previously focused on cisgender women’s disproportionate experiences of victimization and on cisgender men’s perpetration in heterosexual relationships, a focus consistent with prevalence data indicating that women in these relationships are more often victimized (Etaugh, 2020; Follingstad & Rogers, 2013). Despite this historical focus on and definition of cisgender and heteronormative experiences of IPV, there has been a surge in research concerning IPV in sexual and gender minorities (SGMs), defined as those identifying within the 2SLGBTQI+ community, over the last few decades (Decker et al., 2018; Edwards et al., 2015; Hillman, 2020; Longobardi & Badenes-Ribera, 2017; Rodrigues et al., 2024; Whitfield et al., 2018). Although prevalence rate estimations are largely variable (Etaugh, 2020), there is consistent evidence suggesting that SGM individuals experience IPV at similar, if not higher rates than their cisgender, heterosexual counterparts (Dank et al. 2014; Edwards et al. 2015). Only recent attention has been given to psychometrically screening or measuring IPV occurrence within SGM populations (Dyar et al., 2021; Etaugh, 2020) resulting in more attention being given to the misuse of measures of IPV that have been designed for and validated with cisgender and heterosexual samples (Calton et al., 2016; Dyar et al., 2021). Screening for IPV may therefore prove more challenging and complex for SGM individuals. For instance, existing screening tools and measures of IPV are rarely psychometrically validated with SGM populations, contributing to concerns about their reliability and validity (Dyar et al., 2019; Follingstad & Rogers, 2013).

IPV in SGM Populations

In adulthood, lifetime prevalence of IPV is currently estimated to be between 14% and 61% within lesbian, gay, and bisexual couples compared to 14% to 24% of heterosexual couples (Ard & Makadon, 2011; Parry & O'Neal, 2015). Additionally, transgender and gender diverse people are three times more likely to experience IPV victimization compared to other SGM individuals (Peitzmeier et al., 2020). However, due to heterogeneity in measurement practices, true prevalence rates are nearly impossible to capture across the SGM community, though they are still considered to be high (Kelleher et al., 2025).

The differences between heteronormative and the range of SGM relationships are critical to consider when informing best practices for IPV identification and intervention, for a few reasons. First, SGM individuals are uniquely vulnerable to IPV victimization compared to their heterosexual counterparts due to minority stressors; the chronic stress experienced by marginalized groups as a result of their identity stemming from prejudice, discrimination, and social inequality (Longobardi & Badenes-Ribera, 2017; Meyer, 2003; Whitton et al., 2019). The experience of these stressors can increase risk of both victimization and perpetration of IPV, through mechanisms such as internalized stigma, heightened aggression, and impaired coping (Decker et al., 2018; Edwards & Sylaska, 2013; Rodrigues et al., 2024). This increase in vulnerabilities for both victimization and perpetration may subsequently increase the likelihood of bidirectional IPV within SGM relationships (Kirschbaum et al., 2023; Ronzón-Tirado et al., 2022) as a form of retaliation, self-defence, or difficulties coping or self-regulating. Recognizing the potential for bidirectional IPV underscores the importance of measurement tools that capture both victimization and perpetration within SGM relationships.

Second, several SGM-specific IPV constructs have been identified that do not appear in cisgender and heteronormative relationships. These include transphobia-driven IPV (i.e., a set of abuse tactics directly related to one’s transgender identity; Maclin et al., 2024) and identity abuse (IA; a set of abuse and controlling tactics within IPV that more broadly leverages both heterosexism and cissexism against SGM survivors; Woulfe & Goodman, 2021). Transphobia-driven IPV tactics include leveraging transphobia by intentionally using the wrong pronouns, controlling one’s transition, and belittling someone based on their transgender identity (Maclin et al., 2024; Peitzmeier et al., 2021) Some IA tactics involve “outing” or threatening to disclose a partner’s SGM status without their consent (Woulfe & Goodman, 2021), withholding access to gender-affirming medical treatment, purposefully misgendering, and restricting gender expression, which could result in further harassment and violence, or introduce employment and housing instability (Ard & Makadon, 2011; Dank et al., 2014; Scheer et al., 2019; Woulfe & Goodman, 2021). Recognizing that both minority stressors and SGM-specific forms of IPV can be weaponized by perpetrators against SGM individuals highlights the need for research that accurately captures these experiences and their consequences in SGM populations (Rodrigues et al., 2024).

Past research has identified a robust correlation between IPV victimization and subsequent mental health symptomatology across the SGM community (Laskey et al., 2019; Reuter et al., 2017; Stults et al., 2025). A systematic review by Rodrigues et al. (2024) identified significant relationships between IPV victimization in SGM populations and PTSD, depression, anxiety, suicidality, loneliness, and maladaptive coping styles. Moreover, IPV victimization was found to be associated with negative physical health outcomes through an increase in risk behaviors, such as substance use, sexual behaviors, and sexually transmitted infections (Rodrigues et al., 2024). Although heterosexual survivors of IPV share many of the same adverse outcomes to their health because of IPV, these resulting psychological consequences of IPV compound pre-existing vulnerabilities to increased prevalence of mental health disparities among SGM individuals, due to their minoritized status (Whitton et al., 2019). These pre-existing vulnerabilities include disproportionate exposure to minority stress, discrimination, and stigma, which contribute to higher baseline rates of depression, anxiety, suicidality, and PTSD among SGM populations (Marchi et al., 2023; Mongelli et al., 2019). Therefore, effective screening and identification of IPV for SGM survivors is crucial to appropriately intervene or mitigate these negative outcomes.

Importance of Valid IPV Measurement

It is important to acknowledge that the extent of our knowledge on IPV is only as good as our measurement practices (White et al., 2024). If IPV is measured poorly or inconsistently, our understanding of the phenomenon may be fundamentally flawed. It is therefore critical to evaluate and challenge existing IPV measures, as inaccurate measurement hinders our ability to effectively intervene, mitigate harm, and prevent future violence (Craig et al., 2008; Follingstad & Bush, 2014; Yakubovich et al., 2022). Furthermore, inaccurate measurement will perpetuate ongoing issues with underreporting (Hillman, 2020; Whitton et al., 2024). Most measures of IPV were developed within frameworks assuming cisgender men as perpetrators and cisgender women as victims (Edwards et al., 2015; Follingstad & Rogers, 2013). Similarly, they have only been minimally adapted (i.e., minor language changes) to try to fit research with SGM populations (Dyar et al., 2021). However, without proper construct validation, it is unclear if these measures accurately capture the construct of IPV within an SGM population, especially as they experience IPV in distinct ways (Flake et al., 2017; Whitfield et al., 2018).

Unlike other well-defined constructs that maintain gold standard instruments, such as posttraumatic stress disorder, which is measured through the Clinician-Administered PTSD Scale for DSM-5 (CAPS-5; Hunt et al., 2018), IPV lacks a widely accepted definition and standardized measurement, due to the complex, multidimensional nature of abuse and sociocultural variability (Follingstad & Bush, 2014). Variability exists in definitions, ways to measure violence (i.e., discrete incidents vs. patterns), and constructs assessed (e.g., physical, sexual, psychological, emotional, controlling, financial, etc.), and no widely agreed upon “gold standard” instrument currently exists (Follingstad & Bush, 2014; Yount et al., 2022). For instance, one review article identified 87 unique measures of IPV within cisgender heterosexual research and recommended only 18 as having suitable psychometric properties (Alexander et al., 2022). Alexander et al. (2022) referred to the Revised Conflict Tactics Scale (CTS; Straus et al., 1996) as a possible “gold standard” instrument, but psychometric properties for this scale remain mixed and is critiqued as lacking additional context that would be useful in both mitigation and prevention planning (Jones et al., 2017). Although some studies use validated tools, a large proportion of studies continue to utilize binary or single-item, non-validated IPV measurement, limiting the ability to capture nuance and rich data (Chatterji et al., 2023). The inconsistent use of measures and underutilization of psychometric validation complicates comparisons of IPV prevalence rates and underscores the need for reliable measurement (Kelleher et al., 2025; Yakubovich et al., 2022).

Present Review

A handful of psychometric reviews evaluating screening tools for IPV have been completed (Alexander et al., 2022; Arkins et al., 2016; Li et al., 2024), but none of these have included or focused solely on measurement tools developed for and validated with SGM populations. A recent review by Kelleher et al. (2025) highlights IPV measurement tools used with SGM individuals. However, the Kelleher et al. (2025) study included scales that had not been psychometrically developed for, nor validated with, this target population, which may limit the validity of the measures (Boateng et al., 2018). Given the high prevalence of IPV victimization and perpetration in SGM communities and the relatively recent growth of this research area, identifying psychometrically robust screening and measurement tools has important implications for both future research and clinical practice. Accordingly, this review aimed to evaluate the methodological quality and use of IPV measurement tools developed for or validated with SGM populations. Specifically, we asked: (a) What is the methodological quality and psychometric properties of IPV measures developed for or validated with SGM populations? and (b) How have these measures been applied across empirical research involving SGM participants? To address these concerns, we conducted a two-tiered psychometric review of self-reported IPV measurement tools used with SGM populations. The first tier evaluated the development and validation of psychometric tools to analyze their key validity and reliability indicators. The second tier aimed to synthesize the application and overall use of IPV measurement tools across empirical SGM IPV research. In doing so, we evaluated both the methodological quality and real-world use of IPV scales and screening tools in SGM research, with the goal of supporting more inclusive, accurate, and equitable measurement practices.

Methods

Study Design

The present psychometric review followed COnsensus-based Standards for the selection of health Measurement INstruments (COSMIN) for systematic reviews of measurement instruments including evaluating the validity of Patient-Reported Outcome Measures (PROMs) (Mokkink et al., 2018; Prinsen et al., 2018; Terwee et al., 2018). Given that IPV is not technically classified as a PROMs due to victimization being a lived event or exposure rather than a subjective assessment of health status, functioning, or quality of life, only relevant COSMIN psychometric properties were considered. The review was registered on PROSPERO (CRD42024619770). Notably, at the time of registration, this was the first review focused on IPV measurement tools validated with SGM populations.

Search Strategy

A comprehensive systematic literature search was finalized in consultation with a research librarian and performed across four databases: PsycINFO, PubMed/MEDLINE, Embase, and CINAHL. Consistent Boolean key words were utilized for all databases: (“intimate partner violence” OR “IPV” OR “domestic violence” OR “gender-based violence”) AND (“queer” OR “lesbian” OR “gay” OR “transgender” OR “LGBTQ+” OR “non-binary” OR “sexual minority” OR “bisexual” OR “MSM” OR “SGM”) AND (“scale” OR “measurement” OR “checklist” OR “testing” OR “psychometrics” OR “screening” OR “development” OR “validation”). The initial search included studies published up until December 2024. A secondary search was conducted on July 31, 2025, to remain as up to date as possible.

Eligibility Criteria

Eligibility criteria required studies that: (a) were written in English; (b) were original peer-reviewed research (i.e., no reviews, commentaries, conference abstracts, book chapters); (c) measured IPV within the 2SLGBTQI+/SGM populations; (4.1) Tier 1: was a scale development or validation study within the population of interest; (4.2) Tier 2: used a psychometric scale and reported a reliability statistic (i.e., Cronbach’s α, KR-20). We excluded studies that could not be accessed, were not written in English, were not original or empirical research, did not focus on the 2SLGBTQI+/SGM population, did not use a psychometric scale to measure IPV, or did not report a reliability statistic for the scale used.

Screening and Study Selection

The main study author (AP) conducted the first phase of the review and imported the references into HubMeta, a web-based meta-analytic and review platform. We removed study duplicates prior to screening. In line with PRISMA-COSMIN guidelines (Elsman et al., 2024), two authors (SH and JV) independently screened titles and abstracts to determine eligibility for the full-text review and a third reviewer (AP) resolved disagreements. Similarly, two authors (JV and VB), independently conducted the full-text review (kappa = .77), with the consensus of a third reviewer (AP). Prior to the data extraction phase, studies that met the inclusion criteria were further categorized into two sub-groups: Tier 1, scale development and validation studies and Tier 2, empirical studies that used a psychometric scale with a reported reliability statistic (refer to 4.1 and 4.2 of the inclusion criteria).

Data Extraction

Data were extracted and organized into two tiers; the first tier was a scale psychometric extraction per COSMIN guidelines (Mokkink et al., 2018; Prinsen et al., 2018; Terwee et al., 2018), which included scale development and validation studies (sub-group 4.1). The second tier was a descriptive synthesis, which included studies that used a psychometric scale with a reported reliability statistic (sub-group 4.2). For Tier 2, data including (a) author name and year of publication, (b) country, (c) IPV measure used, (d) sample description, (i.e., sample size, SGM identity), and (e) reliability statistic (i.e., Cronbach’s α or KR-20) were extracted by one reviewer (VB) and verified by a second reviewer (JV).

Assessment of Methodological Quality and Measurement Properties

Each scale development and validation study was rated according to the COSMIN updated criteria for strong measurement properties (Mokkink et al., 2018; Prinsen et al., 2018; Terwee et al., 2018). We evaluated the methodological quality of each study using the COSMIN Risk of Bias checklist (Mokkink et al., 2018), which assesses how well each measurement property was tested. As IPV is not considered a PROM in the traditional sense, this rating of methodological quality and measurement properties was based on evaluating the scale development, content validity, structural validity, internal consistency, cross-cultural validity, reliability, and construct validity (i.e., hypothesis testing; Mokkink et al., 2018; Prinsen et al., 2018; Terwee et al., 2018). Measurement properties such as responsiveness, measurement error, and interpretability were excluded, as they may be less applicable to IPV measures. Ratings were completed by two reviewers (AP and JV), with consensus reached on any discrepancy, and assigned a final property rating on a four-point scale: very good, adequate, doubtful, or inadequate (see Mokkink et al., 2018). For each property, the lowest item score for each property category determined the overall methodological quality rating for that property using the “worst score counts” principle.

Next, we evaluated the results of each study’s psychometric testing using COSMIN criteria (Prinsen et al., 2018; Terwee et al., 2018). Each result was rated as sufficient (+), insufficient (−), or indeterminate (?), based on predefined thresholds (e.g., Cronbach’s α ≥.70 for internal consistency; see Supplemental Table S1). The measurement properties assessed similarly included content validity, structural validity, internal consistency, cross-cultural validity, reliability, and hypothesis testing, where applicable.

Finally, recommendations for each measure were conducted using COSMIN’s classification system. Measures were classified as: Category A (recommended for use, evidence for sufficient content validity, and at least low-quality evidence for sufficient internal consistency); Category B (has the potential but requires further validation before recommendation); or Category C (not recommended, there is high-quality evidence for an insufficient measurement property) (Prinsen et al., 2018).

Results

Study Selection

We identified a total of 716 studies from the initial literature search after deduplication. After removing ineligible articles at the title/abstract screening phase, we reviewed 331 studies in full. Of these, 2 were not in English, 5 were not original peer-reviewed research, 9 did not measure IPV in some way, 122 had no use of a psychometric scale (i.e., used a binary measure), 111 reported no reliability statistic (i.e., Cronbach’s α, KR-20), and 6 were inaccessible (Figure 1). The secondary search conducted on July 31, 2025, across all original databases yielded a total of eight new studies that were included. No new scale development or validation studies were identified from the secondary search. A total of six scale development studies and three scale validation studies (Tier 1) of psychometric measures specifically designed or validated with SGM populations were included in the present COSMIN review. In total, 75 studies that used any sort of psychometric scale to measure IPV within an SGM population (Tier 2) met eligibility criteria and were included in the review (see Supplemental Materials S2 and S3).

Figure 1.

PRISMA flow diagram.

Study Characteristics (Tier 1)

A total of nine studies met inclusion criteria for the Tier 1 review phase, comprising six scale development studies and three validation studies published between 2002 and 2024 that identified seven unique psychometric measures. All studies used cross-sectional survey designs and quantitative methods, with sample sizes ranging from 78 (McClennen et al., 2002) to 2,486 (Martínez-Bacaicoa et al., 2024) participants. All studies but one were conducted in the United States (Martínez-Bacaicoa et al., 2024). Scales were developed for a range of SGM individuals, including cisgender gay and bisexual men (n = 4 scales), cisgender lesbian and bisexual women (n = 4 scales), transgender people (n = 4 scales), and nonbinary people (n = 3 scales).

Measures Overview

To support future research, Table 1 summarizes the constructs measured and the populations for which each IPV scale has been developed or validated. Identified psychometric scales for measuring IPV specifically within an SGM context included the Sexual and Gender Minority Adapted Conflict Tactics Scale 2 (SGM-CTS2; Dyar et al., 2021), the Intimate Partner Violence for Gay and Bisexual Men Scale (IPV-GBM Scale; Stephenson & Finneran, 2013), the Intimate Partner Violence for Gay and Bisexual Men Screening Tool (IPV-GBM Screening Tool; Stephenson et al., 2013), the Transgender-Specific Intimate Partner Violence Scale (T-IPV Scale; Peitzmeier et al., 2019), the Identity Abuse Scale (IA Scale; Woulfe & Goodman, 2021), the Technology-Facilitated Sexual Violence Scale (TFSV Scale; Martínez-Bacaicoa et al., 2024), and the Lesbian Partner Abuse Scale Revised (LE-PAS-R; McClennen et al., 2002). Validation studies included a study validating and new item development to the T-IPV Scale (Peitzmeier et al., 2021), a validation of the IA Scale (Scheer et al., 2019), and a validation and short-form development study of the LE-PAS-R (McClennen et al., 2002).

Table 1.

Overview of IPV Measurement Tool Constructs Developed or Validated with Sexual and Gender Minority Populations.

	Construct
Scale	Physical	Sexual	Psychological/emotional	Controlling/monitoring*	SGM-specific*	Other	SGM identity (validated with)
SGM-CTS2 Scale	X	X	X (Psych)	X (Coercive control)	X	X (Injury)	Assigned female at birth (mainly cisgender women), transgender men, non-binary folks, lesbian, bisexual women, pansexual, queer
IPV-GBM Scale	X	X	X (Emotional)	X (Both)	X		Gay and bisexual men
IPV-GBM Screening Tool	X	X	X (Emotional)	X (Both)	X		Gay and bisexual men
IA Scale					X		Cisgender men and women (mainly), transgender, gender non-conforming, queer or pansexual, gay, lesbian, bisexual
T-IPV Scale			X	X	X		Transgender men
LE-PAS-R Scale					X	X	Lesbian
TFSV Scale		X		X (Sexual coercion)	X	X	Cisgender women (mainly), transgender men and women, nonbinary folks, gay, lesbian, bisexual

Note. IPV = intimate partner violence; SGM = sexual and gender minority; IPV-GBM = Intimate Partner Violence for Gay and Bisexual Men Scale. Blank cells indicate that the construct was not explicitly measured or validated in the referenced scale, an “X” indicates that it has been.

Controlling/Monitoring also includes elements of coercive control, SGM-specific denotes inclusion of items directly addressing identity-based or SGM-specific domains (e.g., HIV-related).

Unique Constructs of IPV Measured

SGM-Specific

Six out of seven scales identified measured an SGM-specific construct of IPV. These included identity abuse (Woulfe & Goodman, 2021), transgender-specific IPV (Peitzmeier et al., 2019), HIV-related IPV and abuse among gay and bisexual men (Stephenson & Finneran, 2013), technology-facilitated sexual violence—specifically gender and sexuality-based violence (Martínez-Bacaicoa et al., 2024), internalized homophobia (McClennen et al., 2002), and adaptations of a general IPV measure to reflect SGM experiences (Dyar et al., 2021).

Other IPV Constructs

A total of three scales captured additional constructs of IPV not identified by these other more general categories. These include injury (Dyar et al., 2021), technology-facilitated sexual violence (Martínez-Bacaicoa et al., 2024), and power imbalances and abusive behaviors (i.e., communication and social skills, substance abuse, intergenerational transmission of violence, faking illness, and status differentials) within lesbian relationships (McClennen et al., 2002).

Quality Assessment and Evaluation of Psychometric Scales

Both scale development and validation studies were included to generate an overall appraisal of each instrument where applicable (Table 2). In terms of PROM development, no scale received a rating above “Doubtful,” most commonly due to lack of SGM persons’ involvement in the item generation process. Where multiple studies were available for a given scale, findings were synthesized to determine an overall rating for each psychometric property (i.e., +, ?, −). Methodological quality ratings (e.g., very good, adequate, doubtful, inadequate) indicate how well each property was tested, whereas the symbols in parentheses (+, ?, –) represent the result of that test. Thus, a study may show very good methodology but an indeterminate (?) result if evidence was inconclusive, or doubtful methodology yet a sufficient result (+) if findings supported validity despite design limitations.

Table 2.

Methodological Quality and Measurement Property Results.

Scale	Reference(study type)	PROM development	Content validity	structural validity	Internal consistency	Cross-cultural validity	Reliability	Hypothesis testing
SGM-CTS2 Scale	Dyar et al. (2021) (Development)	Inadequate	Doubtful	Very good (+)	Very good (+)	N/A(?)	N/A (?)	Adequate (+)
IPV-GBM Scale	Stephenson and Finneran (2013) (Development)	Doubtful	Inadequate	Adequate (?)	Very good (?)	Doubtful (+)	N/A(?)	Doubtful (?)
IPV-GBM Screening Tool	Stephenson et al. (2013) (Development)	Doubtful	Doubtful	Very good (?)	Very good (?)	Very good (?)	N/A (?)	Doubtful (?)
IA Scale	Woulfe and Goodman (2021) (Development)	Inadequate	Inadequate	Adequate (?)	Very good (?)	Doubtful (?)	N/A (?)	Adequate (?)
	Scheer et al. (2019) (Validation)		N/A	Very good (+)	Very good (+)	Very good (+)	N/A (?)	Very good (+)
T-IPV Scale	Peitzmeier et al. (2019) (Development)	Inadequate	Doubtful	Inadequate (?)	Very good (?)	N/A (?)	Inadequate (?)	Adequate (?)
	Peitzmeier et al. (2021) (Validation + new items)		Inadequate	Very good (+)	Very good (+)	N/A (?)	N/A (?)	Very good (+)
LE-PAS-R	McClennen et al. (2002) (Validation + short-form development)		Inadequate	Inadequate (?)	Doubtful (?)	N/A (?)	N/A (?)	N/A (?)
TFSV Scales	Martínez-Bacaicoa et al. (2024) (Development)	Doubtful	Doubtful	Very good (+)	Very good (+)	N/A (?)	N/A (?)	Doubtful (+)

Note. IPV = intimate partner violence; SGM = sexual and gender minority; IPV-GBM = Intimate Partner Violence for Gay and Bisexual Men Scale. Methodological quality ratings (e.g., very good, adequate, doubtful, inadequate) indicate how well each property was tested, whereas the symbols in parentheses (+, ?, –) denote the result of that test (sufficient, indeterminate, insufficient). It is therefore possible for a study to demonstrate very good methodology but an indeterminate result if evidence was inconclusive, or doubtful methodology yet a sufficient result if findings supported validity despite design limitations.

Sexual and Gender Minority Adapted Conflict Tactics Scale 2

The SGM-CTS2 (Dyar et al., 2021) is a 100-item measure assessing both IPV victimization and perpetration in SGM populations. It retains the original five-factor structure of the CTS-2 subscales and introduces two subscales including one on coercive control and the other on SGM-specific tactics. Structural validity was rated as very good based on confirmatory factor analyses (CFAs) of the non-adapted CTS2, with strong model fit for victimization (χ²[485] = 628.95, p < .001; RMSEA = .03; CFI = .98; TLI = .98) and perpetration (χ²[424] = 619.39, p < .001; RMSEA = .04; CFI = .94; TLI = .93) resulting in a COSMIN rating of (+). Internal consistency was acceptable for all subscales (α = .63–.88) except for sexual IPV, which showed a lower Cronbach’s alpha (α = .48) due to one item. However, omega coefficients supported adequate reliability (w = .76–.97), resulting in a very good (+) rating. Content validity was rated as doubtful due to limited participant involvement in item generation (?). Hypothesis testing for construct validity was rated as adequate, supported by correlations in expected directions with relevant constructs (+). Test–retest reliability and cross-cultural validity were not reported.

Identity Abuse Scale

The IA Scale is a 7-item unidimensional measure of exposure to identity abuse (e.g., outing or threatening to disclose one’s SGM identity, denying or attacking a partner’s identity, using slurs or derogatory language, or isolating them from the SGM community) that has been examined in both a development study (Woulfe & Goodman, 2021) and a validation study (Scheer et al., 2019). In the development phase, content validity was rated inadequate (?), as item generation relied primarily on literature review and expert opinion with limited target population involvement. Structural validity was rated adequate (?), supported by EFA (KMO = .85; Bartlett’s χ² = 1,697.73, df = 21, p < .001), with factor loadings from .52 to .77 and acceptable communalities (M = .50). Internal consistency was very good (?), although based only on Cronbach’s alpha and structural validity was not fully established. Cross-cultural validity was rated doubtful (?), reflecting limited testing across diverse subgroups. Hypothesis testing for construct validity was rated adequate (?), with some correlations observed in expected directions.

In the validation study (Scheer et al., 2019), structural validity was rated very good (+), supported by CFA (χ²[14] = 110.24, p < .01; RMSEA = .081; CFI = .977). Internal consistency was very good (+) for past-year identity abuse (α = .90). Cross-cultural validity was very good (+), with EFAs showing a unidimensional factor structure across diverse subgroups, including LGBTQ people of color, White LGBTQ people, transgender and gender non-conforming individuals, and cisgender sexual minority women, all with acceptable to strong factor loadings. Hypothesis testing for construct validity was very good (+), with moderate-to-strong correlations with related constructs, including psychological abuse (r = .68–.72) and physical abuse (r = .67–.70), supporting convergent validity and confirming the IA construct is distinct. Reliability was not reported and rated indeterminate (?). Overall, the Identity Abuse Scale demonstrates strong psychometric evidence, particularly from the validation study, with very good (+) structural validity, internal consistency, cross-cultural validity, and construct validity, although some domains from the development study remain indeterminate (?), resulting in an overall rating of adequate to very good.

Intimate Partner Violence for Gay and Bisexual Men Scale

The IPV-GBM Scale (Stephenson & Finneran, 2013) is a 23-item measure assessing five domains of IPV among gay and bisexual men (physical and sexual, monitoring behaviors, controlling behaviors, HIV-related IPV, and emotional IPV). While item generation included focus groups with gay and bisexual men about defining IPV, content validity was rated inadequate (?), reflecting limited consultation with professionals regarding item relevance. Structural validity was rated adequate (?), supported by EFA (KMO = 0.903; Bartlett’s test p < .001), which identified five factors with eigenvalues >1, though five items did not load on any factor (α < .50). Internal consistency was very good (α = .71–.92), but because structural validity was not fully established, COSMIN guidelines do not allow a formal rating for this domain (?). Cross-cultural validity was rated doubtful (?), based on subgroup EFAs by race without multiple-group CFA or DIF analyses, and hypothesis testing for construct validity was also rated doubtful (?), as no explicit hypotheses were defined and only implicit associations were examined.

The IPV-GBM Screening Tool (Stephenson et al., 2013) is a 6-item measure designed for rapid identification of IPV in gay and bisexual men. Content validity was rated doubtful (?), due to limited reporting of qualitative rigor despite target population input and expert review. Structural validity was very good (?), supported by EFA for the five-domain structure, though the absence of CFA limits certainty. Internal consistency was very good (α > .70), but rated indeterminate (?), given limited evidence for structural validity. Cross-cultural validity was very good (?), based on subgroup factor analyses by race without formal measurement invariance testing. Reliability was not applicable, and hypothesis testing for construct validity was doubtful (?), as no explicit hypotheses were defined.

Transgender-Specific Intimate Partner Violence Scale

The T-IPV Scale (Peitzmeier et al., 2019; 2021) is a brief measure designed to screen for controlling behaviors and psychological abuse directed at transgender and gender non-conforming individuals by their intimate partners. In the development study, content validity was rated doubtful (?), as items were primarily derived from a literature review, and structural validity was inadequate (?), with no EFA or CFA conducted. Internal consistency was very good (?), with a KR-20 of 0.56 for the 4-item scale, while cross-cultural validity was not assessed and reliability was inadequate (?). Hypothesis testing for construct validity was rated adequate (?), as the T-IPV construct was compared to other forms of IPV, though no explicit hypotheses were stated. In the subsequent validation study (Peitzmeier et al., 2021), the scale was expanded to 8 items, and structural validity was rated very good (+), supported by EFA (KMO = 0.87, p < .001, factor loadings 0.494–0.734, variance explained = 62%) and CFA (CFI = 0.994; TLI = 0.992; RMSEA = 0.052; SRMR = 0.049), yielding a unidimensional factor structure. Internal consistency was very good (+) with KR-20 = 0.827. Cross-cultural validity and reliability were deemed not applicable. Hypothesis testing for construct validity was very good (+), with lifetime T-IPV significantly associated with psychological distress (aPR = 1.32), PTSD (aPR = 1.50), alcohol abuse (aPR = 1.21), and drug use disorder (aPR = 1.30), supporting convergent validity. Nearly half of the validation sample (48.7%) reported experiencing at least one item.

Lesbian Partner Abuse Scale Revised

The LE-PAS-R (McClennen et al., 2002) is a 25-item measure developed from the original 135-item LE-PAS to assess power imbalances between lesbian couples that may result in partner abuse. This scale measures communication and social skills, substance abuse, intergenerational transmission of violence, faking illness, internalized homophobia, and status differentials. Content validity was rated inadequate (+), as item generation procedures were unclear and limited to quantitative methods, with only advisory council and faculty/clinician review for readability and content. Structural validity was rated indeterminate (?). EFA identified six factors accounting for 77.32% of variance using accepted criteria, but the factor structure was not confirmed with CFA, replicated in an independent sample, or supported by theoretical rationale. Internal consistency was rated doubtful (?), with the authors reporting high internal consistency (r = .94), but without evidence of unidimensionality. Hypothesis testing for construct validity was rated adequate (−), as the scale differentiated abuse from non-abused participants (M = 91 vs. 39.38, t(76) = −11.03, p < .01, R² = 0.68), but no pre-specified hypotheses were described. Cross-cultural validity and test–retest reliability were not assessed.

Technology Facilitated Sexual Violence Scale

The TFSV Scale (Martínez-Bacaicoa et al., 2024) assesses perpetration and victimization across multiple dimensions of digital sexual violence, including online gender-based violence, online gender- and sexuality-based violence, digital sexual harassment, online sexual coercion, and nonconsensual pornography. Content validity was rated doubtful (?), as limited methodological details were provided regarding the qualitative interviews and analytical methods used to inform item generation. Structural validity was rated very good (+). CFA indicated adequate model fit for the three-factor victimization and perpetration models, with RMSEA values initially high (.097 and .108) but reduced to acceptable levels (.079 and .082) after correlating residuals between similarly worded items; CFI and SRMR indicated good fit, and the modifications were theoretically justifiable, though some minor misfit may remain. Internal consistency was rated very good (+), with Cronbach’s α consistently above .71 and omega values ranging from .68 to .74. Cross-cultural validity and reliability were not assessed. Hypothesis testing for construct validity was rated doubtful (+), as the factor structure largely supported a priori expectations, with some limitations in reporting.

COSMIN Recommendations

Because all but two measures were evaluated in only a single study, a formal GRADE-based synthesis across multiple studies was not feasible. Therefore, overall recommendations were assigned using the COSMIN classification system (Prinsen et al., 2018) based on the combined evidence available for each measure. For instruments with multiple studies such as the IA Scale (Scheer et al., 2019; Woulfe & Goodman, 2021) and the T-IPV Scale (Peitzmeier et al., 2019, 2021), findings from development and validation were synthesized. Although validation studies demonstrated strong evidence for certain measurement properties (Peitzmeier et al., 2021; Scheer et al., 2019), limitations in content or structural validity from development phases moderated their ratings. As a result, both scales, as well as all other measures, were assigned Category B, reflecting promising tools with potential usefulness that require further psychometric evaluation before full endorsement. Notably, no measures met criteria for Category A, which requires sufficient content validity and internal consistency, and none were rated Category C, as no high-quality evidence showed inadequate measurement properties.

Applications of IPV Measures in SGM Research (Tier 2)

The second section of this review identified 72 original studies that used at least one psychometric measure of IPV and reported a reliability statistic (i.e., Cronbach’s α, KR-20). Of these studies, most (n = 57) were based in the United States (see Table 3). Sample sizes ranged from 40 (Pepper & Sand, 2015) to 3,783 (Metheny et al., 2024) across all studies and contained variability of SGM identities. A total of 22 psychometric scales were identified and used in data collection. The Revised Conflict Tactics Scale (CTS2; Straus et al., 1996) was the most frequently used measure (n = 27 studies), despite not being developed or validated with an SGM population. The next two most common non-SGM IPV measures were the original CTS (n = 5; Straus, 1979) and the Psychological Maltreatment of Women Inventory (PWMI, n = 5; Tolman, 1999). Reported internal consistency for these measures ranged from acceptable to excellent; CTS2 (α = .63–.95), CTS (α = .71–.95), and PWMI (α = .71–.96).

Table 3.

Descriptive Synthesis of Studies Using IPV Psychometric Scales.

Study	Country	IPV measure (coefficient)	N	Sexual identity	Sex/gender identity
Antebi-Gruszka and Scheer (2021)	United States	CTS2-S (α = .88)PMWI (α = .95)IA Scale (α = .91)	298	Heterosexual (1.7%), lesbian (15.8%), gay (16.4%), bisexual (23.8%), queer (24.2%), other identity (18.1%)	Cisgender woman (46.6%), cisgender man (11.7%), transwoman (6.0%), transman (6.4%), non-binary (23.8%), other (5.4%)
Ayhan Balik and Bilgin (2021)	Turkey	CTS2 (α = .95)	149	Homosexual women (100%)	N/A
Blackburn et al. (2024)	United States	CADRI-S (α = .86)IA Scale (α = .84)	324	Bisexual (75%), heterosexual (25%)	Cisgender woman (100%)
Chen et al. (2019)	Taiwan	DAS (α = .86)	120	Men who have sex with men (100%)	N/A
Chong et al. (2013)	Hong Kong	CTS2 (α = .75–.87)	306	Lesbians (49.4%), gay men (33.3%), bisexual women (13.4%), and men (3.9%)	Female (62.7%), male (37.3%)
Convertino et al. (2021)	United States	HITS (α = .92)	81	Gay (79%), bisexual (19.8%), pansexual (1.2%)	Men (100%)
Craft and Serovich (2005)	United States	CTS2 (α = .70–.92)	51	Homosexual men (100%)	N/A
Do et al. (2022)	United States	CTS2 (8-items) (α = .93)	206	Lesbian (81%), bisexual (7.8%), Not listed (11.2%)	Woman (100%)
Dyar et al. (2020)	United States	SGM-CTS2 (α = .47–.82)	368	Lesbian/gay (24.7%), bisexual (39.7%), queer (10.3), pansexual (18.2%), other (7.1%)	Cisgender women (77.4%), transgender or male (7.1%), genderqueer/nonbinary (15.5%)
Fortunata and Kohn (2003)	United States	CTS2 (α = .83–.85)	100	Lesbian (100%)	women (100%)
Fournier et al. (2023)	United States	CTS2 (α = .84)	1,199	Heterosexual (84.65%), bisexual (7.59%), homosexual (3.75%), unsure (1.83%), asexual (0.50%)	Female (63%), male (37%)
Frankland and Brown (2014)	Australia	CTS2 (α = .76–.91)	184	Gay and lesbian (% N/A)	Female (57 %), male (43%)
Gates et al. (2025)	United States	CTS2-S (α = .95)	234	Gay (37.6%), lesbian (21.4%), bisexual (35.9%), other (5.1%)	Man-identifying (59.8%), woman-identifying (40.2%)
Gerke et al. (2022)	United States	IPV-GBM (α = .72–.93)	168	Gay (78.57%), bisexual 19.05%), queer/pansexual (2.38%)	Man-identifying (100%)
Gray et al. (2023)	United States	CTS2 (α = .92)	212	Heterosexual (47.6%), bisexual (18.4%), queer (14.6%), gay (13.7%), lesbian (5.6%)	Transwomen (100%)
Guo et al. (2023)	China	IPV-GBM (α = .57)	608	Homosexual (74.5%), heterosexual (0.5%), bisexual (20.6%), other (4.4%)	Male-identifying (100%)
Harris and Mahalik (2023)	United States	SGM-CTS2 (α = .71)	275	Gay (48.2%), bisexual (44.6%), queer (4.3%), pansexual (2.5%)	Cisgender men (97.4%), gender nonconforming (1.5%), transmen (1.1%)
Jacobson et al. (2015)	United States	VDR (α = .97)SD-PAV (α = .95)PDR (α = .98)SD-PAP (α = .96)	266	Gay (39.2%), lesbian (36.3%), bisexual (24.5%)	cisgender (38.1%, 58.6% female), bigender (21.6%), transgender (24.1%), genderless (7.6%), genderqueer (6.8%), two-spirit (1.8%)
Kahle et al. (2020)	United States	IPV-GBM (α = .75)	659	Men who have sex with men (100%)	Cisgender men (100%)
Kelley et al. (2015)	United States	CTS2 (α = .89)	819	Only homosexual/lesbian (71.1%), mostly homosexual/lesbian (26.7%), other (2.2%),	Female-identified (100%)
Kline et al. (2022)	United States	CTS2 (α = .75–.94)	323	Heterosexual (47.1%), gay (10.5%), lesbian (4.6%), bisexual (28.2%), asexual (2.8%), pansexual (4.0%), queer (2.2%)	Male (50.5%), female (44.3%), non-binary (3.1%), gender queer (2.2%)
Lewis et al. (2014)	United States	CTS2 (α = .72–.86)	220	Only homosexual/lesbian (79%), mostly homosexual/lesbian (21%)	Female-identified (100%)
Li and Zheng (2021)	China	CTS2-S (α = .63–.74)	272	Homosexual (85.7%), bisexual (14.3%)	Male-identifying (100%)
Li et al. (2021)	United States	CTS-CF-R (α = .72–.79)	144	Same-sex couples (100%)	Female (75.7%)
Li et al. (2022)	United States	CTS-CF-R (α = .72–.79)	288	Homosexual only (74.0%), queer (7.6%), bisexual (12.6%), pansexual (2.5%), asexual (0.4%), other (2.9%)	Male dyads (24.3%), female dyads (75.7%)
Mak et al. (2010)	Hong Kong	CTS2 (α = .72–.88)	398	Homosexual (79.6%), bisexual (20.4%)	Female (64.3%)
Mason et al. (2016)	United States	CTS2 (α = .91)	342	Only lesbian (83.3%), mostly lesbian (16.7%).	Female-identified (100%)
McMillan et al. (2024)	United States	CADRI (α = .60 = .87)	1,140	Heterosexual (80.9%), gay or lesbian (4.6%), bisexual (13.7%), questioning (0.6%), Other (e.g., asexual) (0.3%)	Male (45.8%), female (54.2%)
Metheny et al. (2024)	United States	E-HITS (α = .71)	3,783	Asexual (11.6%), bisexual (30.3%), gay (34.1%), lesbian (22.2%), pansexual (15.9%), queer (45.9%), questioning (2.3%), Same-gender loving (4.6%), heterosexual (1.9%), two-spirit (0.8%),other orientation (4.3%)	Agender (5.5%), cisgender man (17.0%) and woman (23.6%), genderqueer (14.5%), man (20.7%), non-binary (25.9%), questioning (4.7%), transmen (13.7%), transwomen (5.7%), two-spirit (1.1%), women (21.4%), other identity (6.8%)
Miller et al. (2008)	United States	CTS (α = .90–.96)	284	Involved in lesbian relationship (100%)	Female (100%)
Moino et al. (2024)	United States	SGM-CTS2 (α = .97)	349	Bisexual (59.6%), gay or lesbian (38.7%), heterosexual or straight (0.6%), pansexual (6.3%)	Man (43%), woman (57%)
Moskowitz et al. (2020)	United States	ABI (α = .96–.98)	449	Bisexual (47.9%), gay (20.0%), lesbian (17.6%), queer (4.2%), flexible (4.0%), pansexual (2.0%), androsexual (0.9%), fluid (0.9%), questioning (0.9%), polysexual (0.7%), asexual (0.4%), biromantic (0.4%)	Male (57%), female (37.6%), transman (1.3%), transwoman (0.7%), genderqueer (1.1%)
Neppl et al. (2024)	United States	CTS2-S (α = .55–.82)	1,249	Gay (12.2%), lesbian (7.5%), bisexual (47.7%), asexual (1.2%), other (31.4%)	Man (31.6%), woman (18.2%), nonbinary (3.0%), transgender (32.6%), other (13.3%)
Oringher and Samuelson (2011)	United States	CTS (α = .78–.79)	117	Gay (86.3%), bisexual (8.5%), other (5.1%)	Male (100%)
Parrot et al. (2025)	United States	SGM-CTS2 (α = .98)	349	Bisexual (56.9%), gay/lesbian (38.7%)	Cisgender female (57%), cisgender male (43%)
Pantalone et al. (2012)	United States	CTS2 (α = .89–.94)	168	Men who have sex with men (100%)	Male (100%)
Pepper and Sand (2015)	United States	CTS2 (α = .79–.95)	40	Lesbian (72.5%), bisexual (12.5%), heterosexual (2.5%), not self-identified (10%), other (2.5%)	Women (100%)
Pepping et al. (2025)	United States	4-item measure of Dating Violence Victimization (α = .85)	288	Man (13.2%), woman (9.0%), non-binary, and/or gender diverse (77.8%)	Heterosexual (4.5%), lesbian (16.0%)gay (6.3%), bisexual (27.1%)queer (19.1%), pansexual (14.6), asexual (10.4%), another sexual identity (2.1)
Pless and Gibbs (2025)	United States	IPV-GBM Scale (α = .92)	168	Bisexual (12.12%), gay (81.21%), pansexual (2.42%), heterosexual (0.61%), queer (2.24%), questioning (0.61%), other (0.61%)	Male (99.39%), other (0.61%)
Pollitt and Martin-Storey (2024)	United States	SGM-CTS2 (α = .61–.87)	538	Not specified	Cisgender men (17.1%), cisgender women (55.9%), transgender/nonbinary (27.0%)
Ragavan et al. (2024)	United States	CTS (3-items) (α = .73)	383	Plurisexual (29.8%), heterosexual (70.2%)	Girl/woman (99%), nonbinary (0.5%)
Robles et al. (2022)	United States	IPV-GBM (KR-20 = .78–.93)	530	Gay (87.5%), bisexual (9.1%), queer (3.4%)	Cisgender male (100%)
Ronzon-Tirado et al. (2022)	United States	CARS (α = .84–.92)CTS2-SF (α = .84–.93)	288	Bisexual (58.3%), gay (25.0%), lesbian (16.7%)	Cisgender women (58.3%), cisgender men (37.8%), transgender and nonbinary person (3.8%)
Rusow et al. (2024)	United States	IPV-GBM (α = .58–.80)	414	Gay (83%), bisexual (11%), other identity (6%)	Assigned-male sex at birth (100%)
Scheer and Baams (2021)	United States	CTS2 (α = .86)PMWI (α = .95)IA Scale (α = .89)	354	Bisexual (25.7%), queer (20.9%), lesbian (17.5%), gay (14.1%), pansexual (12.1%), other (5.7%), asexual (4.0%), heterosexual (2.3%)	Cisgender woman (50.8%), cisgender man (13.6%), transgender and gender non-conforming (35.6%)
Scheer and Pachankis (2019)	United States	CTS-S (α = .88)PMWI (α = .95)IA Scale (α = .91)	298	Lesbian (15.8%), gay (16.4%), bisexual (23.8%), pansexual (10.1%), queer (24.2%), asexual (5.7%), other (4%)	Cisgender woman (46.6%), cisgender man (11.7%), transwoman (6%), transman (6.4%), gender non-conforming (23.8%), other (5.4%)
Scheer and Mereish (2021)	United States	CTS-28 (α = .89)PMWI (α = .95)IA (α = .90)	149	Heterosexual (1.3%), lesbian (15.4%), gay (10.7%), bisexual (28.9%), queer (22.1%), other (21.4%)	Cisgender woman (48.3%), cisgender man (9.4%), transwoman (4.7%), transman (5.4%), gender nonbinary (30.2%), other (2.0%)
Schramm et al. (2024)	United States	CTS2 (α = .73–.93)	198	Heterosexual (7.6%), gay (45.5%), bisexual (45.5%)	Cisgender men (100%)
Schroeder et al. (2024)	United States	CPI (α = .72)	661	Heterosexual (70.0%), mostly but not exclusively heterosexual (13.6%), homosexual (4.8%), bisexual (8.2%), pansexual (3.3%)	Female assigned sex at birth (63.6%), male assigned sex at birth (36.4%)
Sharma et al. (2020)	United States	IPV-GBM (α = .82–.93)	772	Gay (91%), bisexual (6.7%), other (2.2%)	Male-identifying (100%)
Stephenson et al. (2023)	United States	IPV-GBM (α = .76–.91)	318	Gay (72.2%), bisexual (18.0%), Other (9.8%)	Cisgender male (74.5%), trans/nonbinary (25.5%)
Stults et al. (2025)	United States	T-IPV (α = .82–.86)IA (α = .88–.89)	200	Queer (27.5%), pansexual (20.0%), gay or lesbian (14.0%), bisexual (14.0%),straight (12.5%), other (12.0%)	Genderqueer/fluid/non-conforming/agender (34.5%), Nonbinary (26.0%), Female (23.5%),Male (16.0%)
Swann et al. (2022)	United States	SGM-CTS2 (α = .51–.83)(ω = .78–.96)	249	Lesbian (26.1%), bisexual (40.2%), pansexual (15.7%), queer (8.0%), gay (3.2%), questioning (4.0%), asexual (0.8%), not listed (2.0%)	Female (79.5%), gender non-conforming (5.2%), genderqueer (4.8%), non-binary (2.4%), transgender (3.2%), male (3.2%)
Taber et al. (2025)	United States	T-IPV (KR-20 = .82)IA (KR-20 = .89)	200	Straight (12.5%), gay/lesbian (14.0%), bisexual (14.0%), pansexual (20.0%), queer (27.5%), asexual/not listed/prefer not to say (12.0%)	Transman (16%), transwoman (23.5%), nonbinary (26%), genderqueer-non-conforming/agender (34.5%)
Tognasso et al. (2022)	Italy	CTS2-S (ω = .33–.85)	325	Lesbian (100%)	Cisgender females (95.4%), transgender women (0.6%), other (3.7%)
Trombetta et al. (2023)	Italy	CBS-R (α = .71)	120	Lesbian (39.2%), gay (60.8%)	Woman (37.5%), man (59.2%), transgender (1.7%), other (1.7%)
Trujillo et al. (2020)	United States	CTS2 (α = .81–.95)CARS (α = .86–.90)	277	Lesbian (16.6%), gay (25.6%), bisexual (43%)	Males (37.9%), females (61.6%), intersex (0.4%)
Tubman and Galo (2025)	United States	CASR-SF (α = .89)	248	Heterosexual (11.3%), lesbian/queer (8.5%), gay/queer (26.6%), bisexual (30.6%), pansexual (13.7%), asexual (2.8%), fluid (4.4%), other (1.2%)	Transman (69.4%), Transwoman (30.6%)
Ummak et al. (2023)	Denmark and Turkey	MMEDenmark (α = .71–.87)Turkey (α = .78–.84)	449	Denmark:Lesbian (62.40%), bisexual (37.60%)Turkey:Lesbian (42.10%), bisexual (57.90)	Denmark :Cisgender (93.3%), transgender (3.7%),Turkey:Cisgender (93.3%), transgender (5.1%)
Vail et al. (2025)	United States	CTS2 (α = .76–.87)	289	Heterosexual (86.9%), gay (5.5%), bisexual (5.5%), pansexual (1.7%)	Self-reported men (100%)
Webermann et al. (2023)	United States	CTS (α = .82–.95)NVAWS (α = .74–.84)	263 and 190	T2: Heterosexual (90.1%), lesbian, bisexual, or questioning (9.9%)T3: Heterosexual (90.1%), LBQ (9.9%)	Women (100%)
Wei et al. (2020)	China	IPV-GBM (α = .71)	578	Homosexual (81.3%), bisexual (15.7%)	Men (100%)
Wei et al. (2021)	China	IPV-GBM (α = .70)	431	Bisexual (16.2%), homosexual (77.7%)	Men (100%)
Whitton et al. (2021)	United States	SGM-CTS2 (α = .49 = .85)	308	Gay/lesbian (27.6%), bisexual/pansexual (55.5%), other identity (16.9%)	Cisgender female (77.9%), gender minority (22%)
Williams et al. (2003)	Canada	CTS (α = .80–.84)	130	Bisexual (38.5%), questioning (52.3%), gay or lesbian (9.2%)	Male (46.2%), female (53.8%)
Wong et al. (2019)	China	CTS (α = .71)	1,015	Heterosexual (86.7%), sexual minority (13.3%)	Male (41.3%), female (58.75)
Woulfe and Goodman (2020)	United States	CTS2 (α = .89)PMWI (α = .87)	734	Bisexual (13.6%), gay (23.6%), lesbian (22.8%), queer/pansexual (39.2%)	Man (27.4%), woman (53.1%), transgender/ nonbinary (19.4%)
Wu (2018)	United States	CTS2 (α = .72–.81)	1,002	Men who have sex with men (100%)	Male (100%)
Yang et al. (2023)	United States	DDA (α = .59–.79	491	Gay (63%), bisexual (35%), non-heterosexual identity (e.g., queer; 2%)	Cisgender male (100%)
Yu et al. (2024)	China	DVQ (α = .82)	232	Gay (65%), bisexual (35%)	Men (100%)
Zepf et al. (2020)	United States	HITS (α = .77)	281	Gay (89.0%), bisexual (10.00%)	Male-identifying (100%)
Zhu et al. (2021)	China	IPV-GBM (α = .71)	578	Gay (81.3%), bisexual (15.7%), Other (2.9%)	Male-identifying (100%)

Note. IPV = intimate partner violence; SGM = sexual and gender minority; IPV-GBM = Intimate Partner Violence for Gay and Bisexual Men Scale. List of scales: ABI (Shepard & Campbell, 1992); CTS (Straus, 1979); CTS-2 (Straus et al., 1996); CTS2-S (Straus & Douglas, 2004); PMWI (Tolman, 1999); IA Scale (Woulfe & Goodman, 2021); T-IPV Scale (Peitzmeier et al., 2019); HITS (Sherin et al., 1998); IPV-GBM (Stephenson & Finneran, 2013); Danger Assessment Scale (Campbell et al., 2009); SGM-CTS2 (Dyar et al., 2019); VDR, SD-PAV, PDR, & SD-PAP (Foshee, 1996); CTS-CF-R (Straus et al., 1996); CADRI Scale (Wolfe et al., 2001); CARS (Watkins et al., 2018); CPI (Burke et al., 2011); Composite Abuse Scale (Revised)—Short Form (CASR-SF; Ford-Gilboe et al., 2016); MMEA Scale (Murphy & Hoover, 1999); NVAWS (Tjaden & Thoennes, 1998). For full reference list of studies and scales identified, please see Supplemental Materials (S1 and S2).

Of the identified IPV scales listed in Tier 1, the IPV-GBM (n = 11), SGM-CTS2 (n = 7), T-IPV (n = 2), and IA (n = 4) scales were used across a total of 25 studies. Based on identified studies, a range for internal consistency ratings was made possible for each SGM-specific IPV scale. This included the T-IPV Scale (α = .82–.86; KR-20 = = .82), SGM-CTS2 (α = .54–.98; lowest for sexual IPV), IPV-GBM Scale (α = .57–.95), and IA Scale (α = .84–.91). These scales were used in diverse SGM samples, but most research (n = 47 studies) continued to rely solely on instruments not specifically developed or validated for SGM populations.

Discussion

The present COSMIN review is one of the first comprehensive evaluations of psychometric tools for measuring IPV specifically developed or validated within SGM populations. Findings were divided into two tiers, the first including psychometric tools specifically designed for SGM individuals, and the second, which evaluated how psychometric tools are applied across empirical IPV research. Seven unique SGM-specific IPV measures were identified in the present study, several of which demonstrated promising psychometric properties (e.g., the IA, T-IPV, IPV-GBM, and SGM-CTS2 scales). All measures were given a Category B recommendation, which calls for continued use, but requires further evaluation (Prinsen et al., 2018). Consistent with concerns about heteronormativity in IPV research (Calton et al., 2016; Dyar et al., 2021; Woulfe & Goodman, 2020) and the need for psychometrically valid tools for SGM populations, findings highlight both encouraging progress and ongoing challenges.

Across nine Tier 1 studies, the majority of scales targeted SGM-specific IPV constructs, including identity abuse (Woulfe & Goodman, 2021), transgender-specific IPV (Pietzmeier et al. 2019; 2021), HIV-related IPV (Stephenson & Finneran, 2013; Stephenson et al., 2013), and technology-facilitated sexual violence (Martínez-Bacaicoa et al., 2024), highlighting recognition of the unique experiences of IPV within these populations. However, methodological rigor and psychometric evidence varied considerably, often with many properties rated as indeterminate due to lack of available data, per COSMIN guidelines (Mokkink et al., 2018; Prinsen et al., 2018; Terwee et al., 2018). Consistent with critiques raised by Kelleher et al. (2025), a notable limitation across scale development studies was inadequate participant involvement in the development process. Content validity also was often insufficiently addressed, with limited evidence that tool development incorporated input from IPV-affected SGM populations. Structural validity and internal consistency were generally the strongest psychometric domains, with seven psychometric studies demonstrating adequate to very good ratings for both factor structure and reliability. Importantly, cross-cultural validity, test–retest reliability, and hypothesis-driven construct validity were often unreported or indeterminate, reflecting a critical gap in scale evaluation (see Table 4 for critical findings).

Table 4.

Summary of Critical Findings.

Critical findings
Tier 1
SGM-specific IPV constructs measured	Identity abuse (IA Scale), transgender-specific IPV (T-IPV), HIV-related IPV (IPV-GBM), technology-facilitated sexual violence (TFSV), adaptations of general IPV scales (SGM-CTS2).
Methodological rigor	For seven unique measures across nine studies, participant involvement in scale development often inadequate, content validity frequently insufficient, structural validity and internal consistency generally strongest, cross-cultural validity, test–retest reliability, and hypothesis-driven construct validity often unreported or indeterminate.All given Category B COSMIN rating (promising but need further evaluation).
Tier 2
Underutilization of SGM-specific scales	72 studies applied psychometric scales to SGM populations; most relied on non-SGM-specific instruments; SGM-specific scales used inconsistently; internal consistency ranged α = .54–.98.Despite availability of promising scales (IA, T-IPV, IPV-GBM, SGM-CTS2), usage remains limited, risking under-identification or mischaracterization of IPV in SGM populations.
Geographic coverage	Majority of studies (Tier 1 and Tier 2) conducted in the United States; cross-cultural generalizability limited.

In Tier 2 studies examining the application of psychometric tools for measuring IPV, the review identified 72 empirical studies using such measures. Most studies relied on instruments originally developed for cisgender heterosexual populations, consistent with earlier critiques of the literature (Calton et al., 2016; Dyar et al., 2021). When SGM-specific scales were used, their application remained limited and inconsistent, with variability in subscale reporting and reliability estimation. Among the reported scales (i.e., IPV-GBM, T-IPV, IA, SGM-CTS2 scales), internal consistency ranged from questionable to very good (α = .54–.98), presenting some preliminary evidence for good psychometric properties. Few studies were published prior to the development of SGM-specific scales. However, most continued to rely on non-SGM-specific instruments, highlighting the ongoing underutilization of SGM-appropriate tools.

Our findings raise concerns and substantiate claims about the heterocentric psychometric approaches taken in the literature and their lack of suitability for research with SGM populations. Practically, reliance on measures not designed for SGM populations may result in under-identification or mischaracterization of IPV experiences, limiting the ability of researchers and clinicians to accurately assess risk, inform interventions, and tailor supports to the unique needs of SGM individuals. Taken together, these findings underscore a paradox in the field; despite the availability of several promising SGM-specific IPV instruments, they remain underutilized. This underuse therefore systematically screening for IPV haphazardly, missing out on SGM-specific IPV data, developing inaccurate prevalence rates, and increasing the risk of false negatives. Moreover, no instrument meets all criteria for full recommendation (i.e., Category A) under COSMIN standards in this review or others (e.g., Li et al., 2024).

Limitations and Future Directions

Although COSMIN-style psychometric reviews are powerful tools offering rigorous evaluation of measurement instruments, the present study is not without limitations. First, the inclusion criteria were limited to studies and scales published in English, potentially excluding relevant studies and scales in other languages and cultural contexts. Second, the review may be subject to selection bias, as included studies might not fully capture all relevant research (Drucker et al., 2016). To mitigate these risks, the review protocol was preregistered on PROSPERO, specifying eligibility criteria, search strategies, and analytic methods in advance to enhance transparency and an unbiased review process (Drucker et al., 2016). Third, although COSMIN guidelines were adapted to the context of IPV tools, some psychometric properties (e.g., responsiveness, interpretability) were excluded due to limited applicability. Fourth, this review limited studies to those that reported an internal consistency statistic, therefore not capturing all empirical research that utilized psychometric IPV scales. It is important to note that internal consistency is sometimes not reported in IPV research due to low variance on certain items, which is a common psychometric challenge in this field (Ryan, 2013). Finally, most included studies were conducted in the United States, which may limit cross-cultural generalizability of findings.

Future research should prioritize the development of IPV scales in close collaboration with diverse SGM communities, ensuring content validity and cultural relevance. Psychometric testing should extend beyond internal consistency to include longitudinal reliability, measurement invariance across subgroups, and cross-cultural adaptation. Given the heterogeneity of the SGM population, intersectional approaches that account for race, ethnicity, socioeconomic status, and other identities are critical. While measures such as the IPV-GBM scale offer strong content validity within specific subgroups, particularly gay and bisexual men, the SGM-CTS2 may represent the most comprehensive tool to date for capturing a wide range of IPV constructs (Dyar et al., 2021). It also retains comparability with the original CTS2, a widely used measure in cisgender heterosexual IPV research (Alexander et al., 2022). Further validation of the SGM-CTS2 and other promising measures, such as the T-IPV and IA scales, is needed across diverse SGM populations before these tools can be recommended as core measures.

Developing consensus is needed to establish a set of “gold standard” IPV measures for SGM research, ensuring both broad coverage and comparability across studies and bolster best practices (Follingstad & Bush, 2014; Yount et al., 2022). This emphasis on a “set” of gold standard measures recognizes that no single measure could adequately capture the range of SGM identities, relationships, experiences of abuse, and sociocultural contexts. Future work should focus on developing a coordinated set of adaptable and well-validated measures can function as an evidence-based gold-standard approach to measuring IPV in SGM communities. Future research should also prioritize large-scale studies with balanced samples of cisgender heterosexual and SGM participants using both the SGM-CTS2 and CTS2. This approach would enable more accurate between-group comparisons, reliable prevalence estimates, testing of measurement invariance, and identification of predictors of IPV across diverse populations. Collectively, these efforts will support the evidence base for psychometrically robust and culturally relevant IPV measurement in SGM research (see Table 5).

Table 5.

Summary of Implications for Practice, Policy, and Research

Practice	Researchers and clinicians should prioritize use of SGM-specific IPV scales to improve accurate identification and characterization of IPV.Reliance on non-SGM measures may under-detect IPV and limit tailored interventions.
Policy	Findings highlight the importance of ensuring inclusive IPV assessment practices for SGM populations, which may inform future policy and guidance around screening, prevention, and intervention strategies.
Research	Future scale development should involve SGM communities for content validity.Further validation of promising scales (SGM-CTS2, T-IPV, IA, IPV-GBM) is needed across diverse SGM populations.Conduct longitudinal reliability testing, measurement invariance, and cross-cultural adaptation.Aim for consensus on “gold standard” SGM IPV measures for comparability across studies

Note. IPV = intimate partner violence; SGM = sexual and gender minority; IPV-GBM = Intimate Partner Violence for Gay and Bisexual Men Scale; SGM-CTS2; Sexual and Gender Minority Adapted Conflict Tactics Scale 2.

Conclusion

The current COSMIN review provides a comprehensive evaluation of psychometric tools developed or validated to measure IPV within SGM populations, identifying key methodological gaps and priorities for improving psychometric rigor in this field. While several promising instruments exist, overall methodological quality and psychometric evidence remain limited. Across studies, evidence for reliability and validity was generally preliminary, with few instruments meeting COSMIN standards for robust psychometric testing. Internal consistency was the strongest methodological property across measures, with many lacking reported reliability, cross-cultural validity, and varied content and structural validity. Importantly, very few measurement development studies included active engagement from SGM individuals in item development, questioning the cultural relevance of existing tools. Across the broader SGM IPV literature, most studies continue to use measures developed and validated for cisgender or heterosexual populations, limiting accuracy and comparability of findings. The field of SGM-specific IPV measurement appears to be in its early stages. Future work that prioritizes the inclusion of diverse SGM communities, intersectional approaches, and large-scale studies will be essential to establish reliable, culturally relevant, and widely applicable IPV measures. Rather than a single gold-standard tool, a coordinated set of adaptable, context-sensitive measures may offer the most feasible and inclusive approach to capturing the diverse experiences of IPV across SGM populations. Collectively, these efforts will support accurate prevalence estimation, meaningful between-group comparisons, and ultimately, more effective identification and intervention strategies for IPV in SGM populations.

Supplemental Material

sj-docx-1-tva-10.1177_15248380251412520 – Supplemental material for Measuring Intimate Partner Violence in Sexual and Gender Minority Populations: A COSMIN Psychometric Review

Supplemental material, sj-docx-1-tva-10.1177_15248380251412520 for Measuring Intimate Partner Violence in Sexual and Gender Minority Populations: A COSMIN Psychometric Review by Aaron Palachi, Vesna Beljo, Sarah L. Martin, Joey Vong, Shania S. Hossain and David M. Day in Trauma, Violence, & Abuse

Footnotes

ORCID iD

Aaron Palachi

Funding

The authors received no financial support for the research, authorship, and/or publication of this article.

Declaration of Conflicting Interests

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

Data Availability Statement

The datasets generated and analyzed during the current study are available from the corresponding author on reasonable request.

Supplemental Material

Supplemental material for this article is available online.

Author Biographies

Aaron Palachi, MA, is a PhD student in clinical psychology at Toronto Metropolitan University in Toronto, Canada. Currently his doctoral research includes improving measurement practices for intimate partner violence among sexual and gender minority populations, examining the influence of human agency and mental health on help-seeking, and identifying strategies to enhance service provision.

Vesna Beljo, BA, is a recent graduate in psychology from Toronto Metropolitan University in Toronto, Canada. Her research interests include protective factors related to risk and vulnerability, the influence of relationships on mental health and well-being, intimate partner violence, emotion regulation, and the promotion of equality and diversity in research with sexual and gender minority populations.

Sarah L. Martin, MA, is a PhD student in psychological science at Toronto Metropolitan University in Toronto, Canada. Her doctoral research investigates the stigma that attaches to false criminal accusations, with a particular focus on how sexual crimes differ compared to other crime types in terms of public reactions.

Joey Vong, MA, is a recent graduate in psychological science from Toronto Metropolitan University in Toronto, Canada. Her master’s thesis explored dimensions of perceived authenticity and belongingness in queer racialized women within the Greater Toronto Area. She is broadly interested in identity-based research and working with queer and racialized communities.

Shania S. Hossain, BA, is a recent graduate in psychology from Toronto Metropolitan University in Toronto, Canada. Her research interests include intimate partner violence, substance use, and risky behaviours, with a focus on promoting equity in care and reducing barriers faced by marginalized communities.

David M. Day, PhD, is a professor in the Department of Psychology at Toronto Metropolitan University in Toronto, Canada. His research interests include areas of developmental criminology, criminal trajectories, and antisocial behavior in both children and youth.

References

Ard

K. L.

Makadon

H. J.

(2011). Addressing intimate partner violence in lesbian, gay, bisexual, and transgender patients. Journal of General Internal Medicine, 26(8), 930–933. https://doi.org/10.1007/s11606-011-1697-6

Alexander

E. F.

Backes

B. L.

Johnson

M. D.

(2022). Evaluating measures of intimate partner violence using consensus-based standards of validity. Trauma, Violence, & Abuse, 23(5), 1549–1567. https://doi.org/10.1177/15248380211013413

Arkins

Begley

Higgins

(2016). Measures for screening for intimate partner violence: A systematic review. Journal of Psychiatric and Mental Health Nursing, 23(3–4), 217–235. https://doi.org/10.1111/jpm.12289

Boateng

G. O.

Neilands

T. B.

Frongillo

E. A.

Melgar-Quiñonez

H. R.

Young

S. L.

(2018). Best practices for developing and validating scales for health, social, and behavioral research: A primer. Frontiers in Public Health, 6, 149. https://doi.org/10.3389/fpubh.2018.00149

Calton

J. M.

Cattaneo

L. B.

Gebhard

K. T.

(2016). Barriers to help seeking for lesbian, gay, bisexual, transgender, and queer survivors of intimate partner violence. Trauma, Violence, & Abuse, 17(5), 585–600. https://doi.org/10.1177/1524838015585318

Chatterji

Boyer

Sharma

Abramsky

Levtov

Doyle

Harvey

Heise

(2023). Optimizing the construction of outcome measures for impact evaluations of intimate partner violence prevention interventions. Journal of Interpersonal Violence, 38(15–16), 9105–9131. https://doi.org/10.1177/08862605231162887

Craig

Dieppe

Macintyre

Michie

Nazareth

Petticrew

(2008). Developing and evaluating complex interventions: The new Medical Research Council guidance. BMJ, 337, a1655. https://doi.org/10.1136/bmj.a1655

Dank

Lachman

Zweig

J. M.

Yahner

(2014). Dating violence experiences of lesbian, gay, bisexual, and transgender youth. Journal of Youth and Adolescence, 43(5), 846–857. https://doi.org/10.1007/s10964-013-9975-8

Decker

Littleton

H. L.

Edwards

K. M.

(2018). An updated review of the literature on LGBTQ+ intimate partner violence. Current Sexual Health Reports, 10(4), 265–272. https://doi.org/10.1007/s11930-018-0173-2

10.

Drucker

A. M.

Fleming

Chan

A. W.

(2016). Research techniques made simple: Assessing risk of bias in systematic reviews. The Journal of Investigative Dermatology, 136(11), e109–e114. https://doi.org/10.1016/j.jid.2016.08.021

11.

*Dyar

Messinger

A. M.

Newcomb

M. E.

Byck

G. R.

Dunlap

Whitton

S. W.

(2021). Development and initial validation of three culturally sensitive measures of intimate partner violence for sexual and gender minority populations. Journal of Interpersonal Violence, 36(15–16), NP7878–NP7913. https://doi.org/10.1177/0886260519846856

12.

Edwards

K. M.

Sylaska

K. M.

(2013). The perpetration of intimate partner violence among LGBTQ college youth: The role of minority stress. Journal of Youth and Adolescence, 42(11), 1721–1731. https://doi.org/10.1007/s10964-012-9880-6

13.

Edwards

K. M.

Sylaska

K. M.

Neal

A. M.

(2015). Intimate partner violence among sexual minority populations: A critical review of the literature and agenda for future research. Psychology of Violence, 5(2), 112–121. https://doi.org/10.1037/a0038656

14.

Elsman

E. B.

Mokkink

L. B.

Terwee

C. B.

Beaton

Gagnier

J. J.

Tricco

A. C.

Baba

Butcher

N. J.

Smith

Hofstetter

Aiyegbusi

O. L.

(2024). Guideline for reporting systematic reviews of outcome measurement instruments (OMIs): PRISMA-COSMIN for OMIs 2024. Journal of Clinical Epidemiology, 173, 111422.

15.

Etaugh

(2020). Prevalence of intimate partner violence in LGBTQ individuals: An intersectional approach. In Intimate partner violence and the LGBT+ community: Understanding power dynamics (pp. 11–36). Springer International Publishing.

16.

Flake

J. K.

Pek

Hehman

(2017). Construct validation in social and personality research: Current practice and recommendations. Social Psychological and Personality Science, 8(4), 370–378. https://psycnet.apa.org/doi/10.1177/1948550617693063

17.

Follingstad

D. R.

Bush

H. M.

(2014). Measurement of intimate partner violence: A model for developing the gold standard. Psychology of Violence, 4(4), 369–383. https://doi.org/10.1037/a0037515

18.

Follingstad

D. R.

Rogers

M. J.

(2013). Validity concerns in the measurement of women’s and men’s report of intimate partner violence. Sex Roles, 69(3–4), 149–167. https://doi.org/10.1007/s11199-013-0264-5

19.

Hillman

(2020). Intimate partner violence among older LGBT adults: Unique risk factors, issues in reporting and treatment, and recommendations for research, practice, and policy. In Intimate partner violence and the LGBT+ community: Understanding power dynamics (pp. 237–254). Springer. https://doi.org/10.1007/978-3-030-44762-5_13

20.

Hunt

J. C.

Chesney

S. A.

Jorgensen

T. D.

Schumann

N. R.

deRoon-Cassini

T. A.

(2018). Exploring the gold-standard: Evidence for a two-factor model of the Clinician Administered PTSD Scale for the DSM-5. Psychological Trauma: Theory, Research, Practice and Policy, 10(5), 551–558. https://doi.org/10.1037/tra0000310

21.

Jones

R. T.

Browne

Chou

(2017). A critique of the revised Conflict Tactics Scales-2 (CTS-2). Aggression and Violent Behavior, 37, 83–90. https://doi.org/10.1016/j.avb.2017.08.005

22.

Kelleher

Audoin

C. D. N.

Callaghan

Travers

. (2025). Evaluating measures of LGBTQIA+ intimate partner violence using consensus-based standards of validity. Clinical Psychology Review, 120, 102620. https://doi.org/10.1016/j.cpr.2025.102620

23.

Kirschbaum

A. L.

Metheny

Skakoon-Sparling

Grace

Yakubovich

A. R.

Cox

Palachi

Sang

J. M.

O’Campo

Tan

D. H. S.

Hart

T. A.

(2023). Syndemic factors and lifetime bidirectional intimate partner violence among gay, bisexual, and other sexual minority men. LGBT Health, 10(Suppl 1), S89–S97. https://doi.org/10.1089/lgbt.2023.0117

24.

Kubicek

(2016). Setting an agenda to address intimate partner violence among young men who have sex with men: A conceptual model and review. Trauma, Violence & Abuse, 19(4), 473–487. https://doi.org/10.1177/1524838016673599

25.

Laskey

Bates

E. A.

Taylor

J. C.

(2019). A systematic literature review of intimate partner violence victimisation: An inclusive review across gender and sexuality. Aggression and Violent Behavior, 47, 1–11. https://doi.org/10.1016/j.avb.2019.02.014

26.

Wang

Chen

Xia

Chen

Tang

(2024). Evaluation of the measurement properties of intimate partner violence screening instruments for the general population: A COSMIN-based international systematic review. PloS One, 19(11), e0310297. https://doi.org/10.1371/journal.pone.0310297

27.

Longobardi

Badenes-Ribera

(2017). Intimate partner violence in same-sex relationships and the role of sexual minority stressors: A systematic review of the past 10 years. Journal of Child and Family Studies, 26(8), 2039–2049. https://doi.org/10.1007/s10826-017-0734-4

28.

Maclin

B. J.

Peitzmeier

Krammer

N. K.

Todd

K. P.

Bonar

E. E.

Gamarel

K. E.

(2024). Toward the conceptualization and measurement of transphobia-driven intimate partner violence. Social Science & Medicine, 341, 116532. https://doi.org/10.1016/j.socscimed.2023.116532

29.

Marchi

Travascio

Uberti

De Micheli

Grenzi

Arcolin

Pingani

Ferrari

Galeazzi

G. M.

(2023). Post-traumatic stress disorder among LGBTQ people: A systematic review and meta-analysis. Epidemiology and Psychiatric Sciences, 32, e44. https://doi.org/10.1017/S2045796023000586

30.

*Martínez-Bacaicoa

Sorrel

M. A.

Gámez-Guadix

(2024). Development and validation of technology-facilitated sexual violence perpetration and victimization scales among adults. Assessment, 31(8), 1580–1597. https://doi.org/10.1177/10731911241229575

31.

*McClennen

J. C.

Summers

A. B.

Daley

J. G.

(2002). The lesbian partner abuse scale. Research on Social Work Practice, 12(2), 277–292. https://psycnet.apa.org/doi/10.1177/104973150201200205

32.

*Metheny

Tran

N. K.

Scott

Dastur

Lubensky

M. E.

Lunn

M. R.

Obedin-Maliver

Flentje

. (2024). Intimate partner violence is related to future alcohol use among a nationwide sample of LGBTQIA+ people: Results from the PRIDE Study. Drug and Alcohol Dependence, 260, 111342.

33.

Meyer

I. H.

(2003). Prejudice, social stress, and mental health in lesbian, gay, and bisexual populations: Conceptual issues and research evidence. Psychological Bulletin, 129(5), 674. https://doi.org/10.1037/0033-2909.129.5.674

34.

Mokkink

L. B.

de Vet

H. C. W.

Prinsen

C. A. C.

Patrick

D. L.

Alonso

Bouter

L. M.

Terwee

C. B.

(2018). COSMIN Risk of Bias checklist for systematic reviews of Patient-Reported Outcome Measures. Quality of Life Research, 27(5), 1171–1179. https://doi.org/10.1007/s11136-017-1765-4

35.

Mongelli

Perrone

Balducci

Sacchetti

Ferrari

Mattei

Galeazzi

G. M.

(2019). Minority stress and mental health among LGBT populations: An update on the evidence. Minerva Psichiatrica, 60(1), 27–50. https://doi.org/10.23736/S0391-1772.18.01995-7

36.

Parry

M. M.

O'Neal

E. N

. (2015). Help-seeking behavior among same-sex intimate partner violence victims: An intersectional argument. Criminology, Criminal Justice Law & Society, 16, 51.

37.

*Peitzmeier

S. M.

Hughto

J. M.

Potter

Deutsch

M. B.

Reisner

S. L.

(2019). Development of a novel tool to assess intimate partner violence against transgender individuals. Journal of Interpersonal Violence, 34(11), 2376–2397. https://doi.org/10.1177/0886260519827660

38.

Peitzmeier

S. M.

Malik

Kattari

S. K.

Marrow

Stephenson

Agénor

Reisner

S. L.

(2020). Intimate partner violence in transgender populations: Systematic review and meta-analysis of prevalence and correlates. American Journal of Public Health, 110(9), e1–e14. https://doi.org/10.2105/ajph.2020.305774

39.

*Peitzmeier

S. M.

Wirtz

A. L.

Humes

Hughto

J. M.

Cooney

Reisner

S. L.

Women

A. T.

(2021). The transgender-specific intimate partner violence scale for research and practice: Validation in a sample of transgender women. Social Science & Medicine, 291, 114495. https://doi.org/10.1016/j.socscimed.2021.114495

40.

*Pepper

B. I.

Sand

(2015). Internalized homophobia and intimate partner violence in young adult women’s same-sex relationships. Journal of Aggression, Maltreatment & Trauma, 24(6), 656–673. https://doi.org/10.1080/10926771.2015.1049764

41.

Prinsen

C. A. C.

Mokkink

L. B.

Bouter

L. M.

Alonso

Patrick

D. L.

de Vet

H. C. W.

Terwee

C. B.

(2018). COSMIN guideline for systematic reviews of patient-reported outcome measures. Quality of Life Research, 27(5), 1147–1157. https://doi.org/10.1007/s11136-018-1798-3

42.

Reuter

T. R.

Newcomb

M. E.

Whitton

S. W.

Mustanski

(2017). Intimate partner violence victimization in LGBT young adults: Demographic differences and associations with health behaviors. Psychology of Violence, 7(1), 101–109. https://doi.org/10.1037/vio0000031

43.

Rodrigues

Neaman

Ditzer

Talmon

(2024). The impact of intimate partner violence on the mental and physical health of sexual and gender minorities: A comprehensive review of quantitative research. Archives of Sexual Behavior, 54(2), 433–447. https://doi.org/10.1007/s10508-024-03023-z

44.

*Ronzón-Tirado

Charak

Cano-Gonzalez

Karsberg

Schnarrs

P. W.

(2022). Latent classes of bidirectional face-to-face and cyber intimate partner violence among lesbian, gay, and bisexual emerging adults: The role of minority stressors. Journal of Interpersonal Violence, 37(21–22), NP21092–NP21118. https://doi.org/10.1177/08862605211055158

45.

Ryan

K. M.

(2013). Issues of reliability in measuring intimate partner violence during courtship. Sex Roles: A Journal of Research, 69(3–4), 131–148 https://doi.org/10.1007/s11199-012-0233-4

46.

*Scheer

J. R.

Woulfe

J. M.

Goodman

L. A.

(2019). Psychometric validation of the identity abuse scale among LGBTQ individuals. Journal of Community Psychology, 47(2), 371–384. https://doi.org/10.1002/jcop.22126

47.

*Stephenson

Finneran

(2013). The IPV-GBM scale: A new scale to measure intimate partner violence among gay and bisexual men. PLoS One, 8(6), e62592. https://doi.org/10.1371/journal.pone.0062592

48.

*Stephenson

Hall

C. D.

Williams

Sato

Finneran

(2013). Towards the development of an intimate partner violence screening tool for gay and bisexual men. Western Journal of Emergency Medicine, 14(4), 390. https://doi.org/10.5811/westjem.3.2013.15597

49.

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

50.

Stults

C. B.

Gao

Brandt

S. A.

Taber

J. L.

Lynn

S. G.

Kaczetow

Lee

Cruise

Krause

K. D.

(2025). Intimate partner violence and mental health among transgender and gender diverse young adults. Journal of Family Violence, 40(1), 165–179. https://doi.org/10.1007/s10896-023-00579-7

51.

Terwee

C. B.

Prinsen

C. A. C.

Chiarotto

Westerman

M. J.

Patrick

D. L.

Alonso

Bouter

L. M.

de Vet

H. C. W.

Mokkink

L. B.

(2018). COSMIN methodology for evaluating the content validity of patient-reported outcome measures: a Delphi study. Quality of Life Research, 27(5), 1159–1170. https://doi.org/10.1007/s11136-018-1829-0

52.

White

Bearne

Sweeney

Mantovani

(2024). Examining the measurement of severity of intimate partner violence and its association to mental health outcomes: A narrative synthesis. Frontiers in Public Health, 12, 1450680. https://doi.org/10.3389/fpubh.2024.1450680

53.

Whitfield

D. L.

Coulter

R. W. S.

Langenderfer-Magruder

Jacobson

(2018). Experiences of intimate partner violence among lesbian, gay, bisexual, and transgender college students: The intersection of gender, race, and sexual orientation. Journal of Interpersonal Violence, 36(11–12), NP6040–NP6064. https://doi.org/10.1177/0886260518812071

54.

Whitton

S. W.

Dyar

Mustanski

Newcomb

M. E.

(2019). Intimate partner violence experiences of sexual and gender minority adolescents and young adults assigned female at birth. Psychology of Women Quarterly, 43(2), 232–249. https://doi.org/10.1177/0361684319838972

55.

Whitton

S. W.

Devlin

E. A.

Lawlace

Newcomb

M. E.

(2024). Disclosure and help-seeking experiences of sexual and gender minority victims of intimate partner violence: A mixed-methods study. Journal of Interpersonal Violence, 39(7–8), 1373–1397. https://doi.org/10.1177/08862605231207618

56.

World Health Organization. (2013). Responding to intimate partner violence and sexual violence against women: WHO clinical and policy guidelines. World Health Organization.

57.

*Woulfe

J. M.

Goodman

L. A.

(2020). Weaponized oppression: Identity abuse and mental health in the lesbian, gay, bisexual, transgender, and queer community. Psychology of Violence, 10(1), 100–109. https://doi.org/10.1037/vio0000251

58.

*Woulfe

J. M.

Goodman

L. A.

(2021). Identity abuse as a tactic of violence in LGBTQ communities: Initial validation of the Identity Abuse Measure. Journal of Interpersonal Violence, 36(5–6), 2656–2676. https://doi.org/10.1177/0886260518760018

59.

Yakubovich

A. R.

Heron

Metheny

Gesink

O’Campo

(2022). Measuring the burden of intimate partner violence by sex and sexual Identity: Results from a random sample in Toronto, Canada. Journal of Interpersonal Violence, 37(19–20), NP18690–NP18712. https://doi.org/10.1177/08862605211037433

60.

Yount

K. M.

Cheong

Y. F.

Khan

Bergenfeld

Kaslow

Clark

C. J.

(2022). Global measurement of intimate partner violence to monitor Sustainable Development Goal 5. BMC Public Health, 22(1), 465. https://doi.org/10.1186/s12889-022-12822-9

Supplementary Material

Please find the following supplemental material available below.

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