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. 2026 Jun 15;14:1234. doi: 10.1186/s40359-026-04907-6

Psychometric properties and network analysis of the brief Adverse Childhood Experiences Abuse Short Form (ACE-ASF) in homosexual and heterosexual

Andrés Ramírez 1,✉, Luis Burgos-Benavides 2, Venus Medina-Maldonado 3, Hugo Sinchi-Sinchi 4, Noelia Aguilera-Jiménez 5, Francisco Javier Rodríguez-Díaz 2
PMCID: PMC13495175  PMID: 42298618

Abstract

Background

The Adverse Childhood Experiences Abuse describes the physical, emotional, and sexual abuse undergone in childhood, which is associated with negative effects on mental, emotional, and relational health later in adulthood.

Objective

To assess the psychometric properties of the ACE-ASF (Adverse Childhood Experiences Abuse Short Form) in homosexual, and heterosexual in Ecuador, with a special focus on reliability, validity, measurement invariance, and network analysis of self-perceived abuse (fear, trapped and abused).

Methods

Instrumental study with 520 participants (nHomosexual = 260 and nHeterosexual = 260). The ACE-ASF was implemented along with confirmatory factor analysis, reliability, validity, and network analysis.

Results

The ACE-ASF offered excellent internal consistency (α = 0.845—0.883; ω = 0.856—0.876), convergent validity (AVE = 0.606—0.661), and discriminant validity (HTMT = 0.437). The two-factor model had ideal fit (CFI = 0.999; RMSEA = 0.000). Measurement invariance was verified across groups (ΔCFI ≤ 0.001). Network analysis showed differences by sexual orientation and abuse perception, highlighting the centrality of item A3 (betweenness = 1.67) and denser networks in lesbian (sparsity = 0.07) versus more fragmented networks in gay (sparsity = 0.67).

Conclusion

The ACE-ASF is a validated, reliable, invariant measure for sexual orientation and self-perceptions of abuse. Its use may help in the design targeted prevention and intervention methods to deal with the long-term consequences of childhood abuse for all relationship contexts.

Supplementary Information

The online version contains supplementary material available at 10.1186/s40359-026-04907-6.

Keywords: Childhood Abuse, Perception of Abuse, Psychometrics, Network

Introduction

Childhood violence is a major public health issue, with around a billion children affected worldwide each year [21, 22, 63]. Adverse Childhood Experiences (ACEs) such as physical, emotional, and sexual abuse as well as neglect are associated with negative lifelong well-being outcomes that last into adulthood [40, 41, 53]. Traumatic events of adverse childhood experiences are associated with severe effects on physical, mental, and reproductive health, as well as risk of chronic diseases: cardiovascular diseases, obesity, diabetes [2, 27, 65]. Secondly, ACEs are related to a reduced quality of cognitive and social development, leading to poor academic performance, emotional dysregulation, and problems in forming healthy relationships in childhood [5, 24, 31, 50].

ACEs make a deep-rooted neurobiological impact in their lives: they impair brain development, disrupt stress-response systems, and impair emotional regulation and decision-making. Such disruptions linger into adulthood, modifying emotional and cognitive functioning which may affect academic performance, work performance, and relationships based on social and work situations [30, 34]. Adolescents and young adults with a history of childhood violence commit more risky behaviors like smoking, alcohol and drug misuse, and unsafe sexual practices that raise the risk of NCDs, cancer, and sexually transmitted infections across adolescence and adulthood [43, 46, 52]. Regarding different types, whether the neurobiological and behavioral consequences of ACEs may play out differently between in gay, lesbian and heterosexual relationships is of particular interest when considering dating violence [68] and perceptions of personal abuse [14].

In addition to individual health effects, ACEs help make long-term violence cycle a reality beyond the childhood years. From a young age, maltreatment is associated with a higher likelihood of later victimization and perpetration of violence [8]. Unfortunately, such a dynamic does not only pose a threat to their personal welfare but contributes to the intergenerational transmission of aggression and a social and family context where violence is normalized [67]. Moreover, the long-term psychological, emotional, and behavioral consequences of ACEs can impact the development of a healthy romantic relationship, affect emotional regulation, promote increased risks towards risky behavior, and strengthen the continuation of violent patterns [72]. Resolving these negative influences by means of early intervention, trauma-informed approach and positive policies at societal level such as supportive social structures are necessary for preventing such a harmful cycle and creating safety in communities [28, 37, 57, 61].

Research on child abuse and adverse childhood experiences has relied on multiple methodological approaches to understand their prevalence, consequences, and developmental impact. Large cross-sectional studies, such as the Violence Against Children Surveys and the Optimus Studies, have been essential for estimating the magnitude of victimization and identifying immediate outcomes associated with abuse in children and adolescents [38, 39].

Repeated cross-sectional designs have also contributed to monitoring changes in abuse prevalence over time, offering valuable evidence for evaluating prevention strategies and public policies. In parallel, longitudinal studies, including those conducted by the LONGSCAN Consortium, have provided deeper insight into how early maltreatment shapes mental health, behavior, and well-being across the life course, while also showing the cumulative burden of multiple adverse experiences on adult health, socioeconomic outcomes, and interpersonal functioning [25, 41, 42, 45, 64].

Despite these important contributions, methodological challenges remain, particularly regarding the validity and reliability of child maltreatment measures across culturally diverse settings [73]. Cultural differences in how abuse is understood and reported may affect data quality and limit comparability between populations [69, 74].

Underreporting, often influenced by fear, shame, or limited recognition of maltreatment, further complicates assessment. In this context, the Adverse Childhood Experiences questionnaire has become one of the most widely used tools for assessing childhood trauma, covering abuse, neglect, and household dysfunction as major domains of early adversity [20–22, 33, 36, 44, 63]. Its later adaptations, including the ACE-IQ and the ACE-ASF, have expanded its applicability across diverse cultural and research settings, although further psychometric evaluation remains necessary to ensure robust cross-cultural use [3, 26, 41, 49, 62, 66, 70, 71].

The primary objective of this study is to examine the psychometric properties of the abbreviated version of the Adverse Childhood Experiences Questionnaire (ACE-ASF) in homosexual, and heterosexual, with a special focus on reliability, validity, measurement invariance, and network analysis of self-perceived abuse. This evaluation aims to confirm that the instrument appropriately measures the dimensions of childhood abuse within each of these groups, ensuring that it consistently captures the intended constructs without bias.

First, the reliability of the ACE-ASF will be analyzed across the three target populations to verify the internal consistency and stability of the instrument when assessing adverse childhood experiences. Second, the structural validity of the ACE-ASF will be assessed through Confirmatory Factor Analysis (CFA), examining whether the dimensions of physical-emotional abuse and sexual abuse cluster according to the expected theoretical structure in homosexual (gay and lesbian), and heterosexual. Third, the convergent and discriminant validity of the ACE-ASF will be evaluated to confirm that each dimension of abuse is accurately and distinctly measured, ensuring the differentiation between various adverse experiences. Fourth, measurement invariance of the ACE-ASF will be tested based on sexual orientation and self-perception of abuse (feelings of fear, feeling trapped, mistreatment). Finally, as a fifth objective, a Network Analysis of Self-Perceived Abuse will be conducted, focusing on key variables such as feelings of fear, feeling trapped, mistreatment, and the number of breakup attempts, as well as examining differences between groups according to sexual orientation (gay, lesbian, and heterosexual). This analysis aims to identify the central and peripheral nodes within the network of abuse perception, offering new insights into the complex interrelationships between adverse childhood experiences, and self-perception of abuse.

Methods

Research design

An instrumental study was conducted in two sequential phases, following contemporary guidelines for validating educational and psychological instruments [4] and best practices for adapting and translating preexisting measures [7, 13, 47, 48, 54]. In the first phase, the original ACE-ASF was linguistically adapted through an iterative translation and back-translation process carried out by specialists in psychometrics and cross-cultural research [18, 41].

To ensure both semantic and conceptual equivalence, the source text (English) and the target text (Spanish) were meticulously compared at each stage of the process (Muñiz et al., 2015). Once the Spanish version was completed, it was subjected to a small pilot review with a select group of participants to verify its clarity, cultural relevance, and readability in Ecuador. The second phase concentrated on collecting empirical evidence regarding the reliability, validity, and measurement consistency of the instrument across three groups: homosexual (gay and lesbian), and heterosexual.

Participants

A total of 520 participants were recruited through non‐probabilistic convenience sampling methods [15]. Participants were divided into three groups according to self‐identified sexual orientation: 260 in the homosexuality group (130 individuals in the gay group, 130 in the lesbian group), and 260 in the heterosexual group (Table 1). Exclusion criteria eliminated any individual who failed to complete the instruments fully or did not meet the age and enrollment requirements.

Table 1.

Sociodemographic characteristics and relationship experiences by sexual orientation (n = 520)

Homosexual (n = 260) Heterosexual Total
Gay
(n = 130)
Lesbian
(n = 130)
(n = 260) (n = 520)
n (%) n (%) n (%) n (%)
Sex
 Male 63 (48.5%) 63 (48.5%) 130 (50.0%) 256 (49.2%)
 Female 67 (51.5%) 67 (51.5%) 130 (50.0%) 264 (50.8%)
Ethnicity
 Mestizo 124 (95.4%) 117 (90.0%) 258 (99.2%) 499 (96.0%)
 Montubio 4 (3.1%) 4 (3.1%) 0 (0.0%) 8 (1.5%)
 White 2 (1.5%) 8 (6.2%) 1 (0.4%) 11 (2.1%)
 Indigenous 0 (0.0%) 1 (0.8%) 1 (0.4%) 2 (0.4%)
Economic Level
 High 4 (3.1%) 3 (2.3%) 0 (0.0%) 7 (1.3%)
 Upper Middle 30 (23.1%) 25 (19.2%) 56 (21.5%) 111 (21.3%)
 Middle 85 (65.4%) 78 (60.0%) 166 (63.8%) 329 (63.3%)
 Lower Middle 11 (8.5%) 23 (17.7%) 35 (13.5%) 69 (13.3%)
 Low 0 (0.0%) 1 (0.8%) 3 (1.2%) 4 (0.8%)
Fear
 No 113 (86.9%) 119 (91.5%) 212 (81.5%) 444 (85.4%)
 Yes 17 (13.1%) 11 (8.5%) 48 (18.5%) 76 (14.6%)
Trapped
 No 104 (80.0%) 106 (81.5%) 195 (75.0%) 405 (77.9%)
 Yes 26 (20.0%) 24 (18.5%) 65 (25.0%) 115 (22.1%)
Mistreated
 No 116 (89.2%) 119 (91.5%) 231 (88.8%) 466 (89.6%)
 Yes 14 (10.8%) 11 (8.5%) 29 (11.2%) 54 (10.4%)
Age
 Mean (SD) 18.3 (3.4) 18.7 (4.6) 22.8 (2.5) 20.7 (4.0)
 Median 17 18 23 21
 Range 14–27 14–49 18–33 14–49
Number of Attempts
 Mean (SD) 0.5 (1.1) 0.7 (1.6) 0.7 (1.3) 0.7 (1.4)
 Median 0 0 0 0
 Range 0–5 0–10 0–8 0–10

SD Standard Deviation, Fear Have you ever felt afraid of your partner?, Trapped Do you feel or have you ever felt trapped in your relationship?, Mistreated Have you ever felt mistreated?, Number of attempts If you have tried to break up with your partner, indicate the number of attempts. Homosexuals same-sex relationship (includes gays and lesbians) and heterosexuals = different sex relationships (Man with women or vice versa). Gay relationship between men, Lesbian relationship with women and Heterosexual = relationships between different sexes

To achieve a gender balance within the population, approximately 49%—51% of participants were male, while around 49%—51% were female (49.2% male and 50.8% female). Based on ethnicity, 96% were mestizo, with small numbers of Montubio (1.5%), White (2.1%) and Indigenous (0.4%). The socioeconomic strata were mainly middle class (63.3%), upper‐middle (21.3%), lower‐middle (13.3%), high (1.3%) and low (0.8%) strata. The heterosexual group was older on average (mean = 22.8 years, SD = 2.5, range = 18–33) than the gay group (mean = 18.3 years, SD = 3.4, range = 14–27) and the lesbian group (mean = 18.7 years, SD = 4.6, range = 14–49). For more information, refer to Table 1.

Measures

Ad‐hoc sociodemographic survey

The participants filled out a short, study-specific questionnaire collecting age, sex, ethnicity, and socioeconomic level. Three more yes/no items evaluated experiences of relational dynamics: whether they had been afraid of their partner, felt trapped in the relationship, or felt mistreated by their partner.

Adverse Childhood Experiences Abuse Short Form (ACE‐ASF)

The ACE‐ASF covers eight Likert‐type items (0 = never to 4 = always) about abuse‐related childhood experiences. In previous publications [41], exploratory factor analysis reported two subscales: physical/emotional abuse (items 1- 4) and sexual abuse (items 5—8). Confirmatory factor analysis demonstrated strong fit of this two‐factor structure with χ2 (19) = 60.526,RMSEA = 0.036; CFI = 0.990; TLI = 0.986 and demonstrated metric invariance across sexes. Internal consistency coefficients were previously reported to be acceptable for the sexual abuse subscale (α = 0.83) and moderate for the physical/emotional abuse subscale.

Self-perceived abuse

We asked about the self-perception of abuse, including whether the relationship left you trapped, which helps assess whether the ability to leave that relationship was felt. In pursuit of this, three yes/no questions were asked: “Do you feel, or have you ever felt afraid of your partner?”, “Do you feel, or have you ever felt trapped in your relationship?”, “Have you ever felt mistreated in your relationship?” [1].

Procedure

Data were collected in person following approval from the Pontificia Universidad Católica del Ecuador’s Human Research Ethics Committee (Protocol No. PV‐14‐2022) and in compliance with the Declaration of Helsinki. University administrators allowed for invitation of students to undergo organized group sessions. Researchers at each session provided an explanation of the study’s objectives, stressed that participation was voluntary and informed participants of their right to withdraw at any time with no penalties. A unique anonymous code for each participant was created after completing the written informed consent form and receiving the information written in writing. At first, the participants took an ad hoc sociodemographic survey, which comprised the 3 yes/no questions regarding fear, feeling trapped and being mistreated in their current romantic relationship. Next, they completed the eight‐item ACE‐ASF, which took approximately five minutes. Finally, the DVQ‐VP (victimization and perpetration) subscales were given, taking an additional 5 min on average. As childhood abuse and dating violence are sensitive issues the research team members had undergone training in trauma‐informed approaches to minimize possible distress. Confidentiality and data protection procedures were observed and a list of psychological support resources for those participants who experienced emotional distress when responding was accessible. After completion, all questionnaires were stored and analyzed in the OpenClinic data management system. Each form was checked through via research assistants who ensured that all completed forms were checked correctly prior to data entry.

Statistical analysis

All statistical analyses were performed with R (version 4.4.3; [51] and JASP (version 0.19.3). One, sociodemographic variables including sex, ethnicity, socioeconomic status and relationship items (i.e., having ever felt fear of one’s partner, feeling trapped, or feeling mistreatment) were presented as frequencies and percentages. Continuous variables (age, number of breakup attempts) were reported with means, standard deviations, medians, and ranges, and their distributional properties were assessed with skewness and kurtosis. Shapiro–Wilk [58] tests for univariate normality were conducted formally in each of the questionnaires (including overall scale score,see Table 2) to see if the subsequent analyses needed parametric or nonparametric tests. Item‐level descriptive statistics for the ACE‐ASF were computed, including mean, SD, skewness, and kurtosis for each of the eight items. Following this, Guttman’s Lambda 2 (λ₂) and Lambda 6 (λ₆), Greatest Lower Bound (GLB), McDonald’s omega, and Composite Reliability (CR) measures were estimated for internal consistency. For every reliability coefficient, a confidence interval of 95% was given for precision.

Table 2.

Descriptions of the items of the Adverse Childhood Experiences Abuse Short Form (ACE-ASF) in homosexual (gay and lesbian), and heterosexual in Ecuador (n = 520)

A1 A2 A3 A4 A5 A6 A7 A8
Median 3 2 3 2 2 2 2 2
Mean 3.281 2.496 3.008 2.513 2.238 2.123 2.083 2.040
Std. Deviation 1.238 0.982 1.213 1.005 0.795 0.675 0.626 0.586
Coefficient of variation 0.377 0.393 0.403 0.400 0.355 0.318 0.301 0.287
Variance 1.532 0.963 1.472 1.009 0.633 0.455 0.392 0.343
Skewness −0.166 1.011 0.206 0.987 1.437 1.701 1.878 2.014
Std. Error of Skewness 0.107 0.107 0.107 0.107 0.107 0.107 0.107 0.107
Kurtosis −1.110 0.471 −1.105 0.206 2.627 4.719 6.875 8.685
Std. Error of Kurtosis 0.214 0.214 0.214 0.214 0.214 0.214 0.214 0.214
Shapiro–Wilk 0.896 0.801 0.889 0.788 0.714 0.634 0.606 0.563
p-value of Shapiro–Wilk  <.001  <.001  <.001  <.001  <.001  <.001  <.001  <.001
Range 4 4 4 4 4 4 4 4
Minimum 1 1 1 1 1 1 1 1
Maximum 5 5 5 5 5 5 5 5
25th percentile (Q1) 2 2 2 2 2 2 2 2
50th percentile (Q2) 3 2 3 2 2 2 2 2
75th percentile (Q3) 4 3 4 3 2 2 2 2

Additionally, the Average Inter‐Item Correlation (AIC) indicated to measure the average interrelatedness between items was calculated, to gain more information about the scale's cohesiveness. A Confirmatory Factor Analysis (CFA) was performed to assess the structural validity by the implementation of Lavaan package in R [56]. Since multivariate normality assumptions were violated [17, 60], the diagonally weighted least squares (DWLS) estimator was selected. A two‐factor model a factor for physical or emotional abuse (items 1–4) and a factor for sexual abuse (items 5—8) was determined as well with the Comparative Fit Index (CFI), Tucker-Lewis Index (TLI), and Standardized Root Mean Square Residual (SRMR) to assess model reliability [54].

If the CFI and TLI were at least 0.95 and SRMR at most 0.08 [11, 32, 59], the fit was considered good. Once model fit was confirmed, factor reliability was enhanced by calculating Cronbach’s alpha and McDonald’s omega for each latent dimension [55].

Convergent validity was investigated through calculating the Average Variance Extracted (AVE) for each factor, in which the AVE of 0.50 or greater indicated that items shared an average of at least half variance with the latent construct. For discriminant validity, correlations between factors were assessed using the Heterotrait-Monotrait Ratio (HTMT) with HTMT values of 0.95 or lower [10].

Variance inflation factors (VIF) were computed to remove significant multicollinearity between indicators and less than 10 were considered acceptable. Spearman’s rank‐order correlations indicated how the physical/emotional abuse subscale and sexual abuse subscale scored together, quantifying that each dimension represented a discrete yet related nature of adverse childhood experience and the sum up of the two factors [16]. Measurement invariance across sex groups was evaluated by obtaining a number of nested CFAs [59].

The first model evaluated configural invariance by checking that the identical two‐factor structure was represented in both groups without equality constraints. Metric invariance: metric loadings between variables needed to be equal to be in place between sexes, and scalar invariance: item intercepts being equal. Last though not the least, strict invariance restricted residual variances to be the same. Comparisons among nested models were assessed at each step to understand whether invariance between nested models (ΔCFI ≤ 0.01 and ΔSRMR ≤ 0.015) were maintained [32, 54, 60].

A network analysis was performed to investigate the relationships among the eight ACE‐ASF items [6, 12, 19, 29]. Centrality indices (i.e., betweenness, closeness, strength and expected influence) determined which items were most influential in the network. Furthermore, clustering was implemented (Barrat, Onnela, WS, and Zhang), which helped to identify any potential subclusters between items, thus providing complementary evidence about the internal structure of the scale and illustrating the top types of the abuse items which were most central to respondents’ overall experience.

Results

Within a sample of 520 participants (nHomosexual = 260 and nHeterosexual = 260) in Ecuador, in terms of the central tendencies and dispersion of each of the eight items with ACE-ASF, we observed that the medians varied between 2 and 3 from 1 to 5, meaning in general that responses were observed to fall into a similar clustering around the medium range. Medians of 3 for the two items A1 and A3; whereas, for the remaining items (A2, A4, A5, A6, A7 and A8) median 2. Means of A1 (3.281) and A3 (3.008) were marginally greater than 3, indicating that participants experienced the items more often or with stronger feelings related to those items.

Table 3 and Fig. 1 reported the psychometric characteristics of the original two-factor model of the Adverse Childhood Experiences Abuse Short Form (ACE-ASF) in a sample of homosexual (gay and lesbian), and heterosexual in Ecuador (n = 520). The model consisted of two factors: Physical and Emotional Abuse (F1) and Sexual Abuse (F2). Standardized factor loadings for the indicators of Physical and Emotional Abuse (A1-A4) were between 0.682 and 0.888, while for Sexual Abuse (A5-A8) they were between 0.766 and 0.829; which implies that the two factors had good correlations with their respective latent constructs. For both factors, internal consistency was high at Cronbach's alpha of 0.845 for F1 and 0.883 for F2, and McDonald's omega values of 0.856 and 0.876, respectively. For both factors, composite reliability (CR) was good indeed, surpassing 0.84.

Table 3.

Loadings, reliability and validity of the original Model of the Adverse Childhood Experiences Abuse Short Form (ACE-ASF) in homosexual (gay and lesbian), and heterosexual in Ecuador (n = 520)

Factor Items Std. Est. (all) α ω CR VIF ω Total α Total F1 F2
F1 A1 0.767 0.845 0.856 0.849 2.765 0.896 0.838 0.606a
A2 0.711
A3 0.888
A4 0.682
F2 A5 0.823 0.883 0.876 0.884 1.539 0.437b 0.661a
A6 0.818
A7 0.829
A8 0.766

F1 Physical and Emotional Abuse, F2 Sexual Abuse, aAVE (Convergent Validity), Boldb HTMT (Discriminant Validity), ω McDonald's Omega, α Cronbach's alpha, CR Composite Reliability, VIF Variance Inflation Factor. CFI =.999, TLI =.999, RMSEA =.000, and SRMR =.034

Fig. 1.

Fig. 1

Psychometric model of the ACE-ASF in homosexual (gay and lesbian) and heterosexual in Ecuador. Note. F1 = Physical and Emotional Abuse, and F2 = Sexual Abuse

The Average Variance Extracted reflected acceptable convergent validity for both F1 (AVE = 0.606) and F2 (AVE = 0.661). The discriminant validity between the two factors was further supported by HTMT of 0.437, which was below the 0.85 threshold in the literature. The variance inflation factor (VIF) values were also below 3, proving the absence of multicollinearity. The model fit overall was excellent, with the CFI and TLI at 0.999, RMSEA at 0.000 and SRMR at 0.034 (Table 3). The results corroborated that the original two-factor model of ACE-ASF was significantly reliable and valid for measuring childhood abuse experiences of the various sexual orientation groups within the Ecuadorian context. Figure 1 showed that the psychometric model of the ACE-ASF was structured around two clearly defined latent dimensions, physical abuse and sexual abuse, with their respective items loading consistently onto each factor. The model suggested an adequate conceptual organization of the instrument, as the observed indicators were coherently linked to their underlying constructs.

The results of the factorial invariance tests of the ACE-ASF were reported in Table 4 for sexual orientation, and self-perception of abuse. The fit indices across all models under evaluation (configural, metric, scalar, and strict) were excellent (CFI and TLI equal to or greater than 0.999), and it shows that factorial structure of the ACE-ASF was stable and similar both at sexual orientation level and at self-perceiving abuse level. For the comparison between homosexual and heterosexual participants and between gay, lesbian, heterosexual people, all measurements of the invariance showed low chi-square values, adequate degrees of freedom, and non-significant p-values, which means that no significant difference in the structure of the instrument existed between these participants. SRMR values also were below the recommended threshold (0.08), strengthening the models robustness. In terms of self-perception of abuse (fear, feeling trapped or mistreated) the analyses were also show configural, metric, scalar and strict invariance [54] and great fit indices of the models were found in most cases.

Table 4.

Measures of invariance by sexual orientation and self-perception of abuse (n = 520)

Model X2 df p CFI TLI RMSEA SRMR
Sexual Orientation (Homosexual and Heterosexual)
 MI ↔ CO 12.860 38 1 .999 .999 .000 (.000—.000) .040
 MI ↔ ME 14.494 44 1 .999 .999 . 000 (.000—.000) .043
 MI ↔ SC 21.226 50 1 .999 .999 . 000 (.000—.000) .045
 MI ↔ ST 31.567 58 .998 .999 .999 . 000 (.000—.000) .060
Sexual Orientation (Gay, Lesbian, and Heterosexual)
 MI ↔ CO 14.052 38 1 .999 .999 .000 (.000—.000) .046
 MI ↔ ME 16.771 44 1 .999 .999 . 000 (.000—.000) .052
 MI ↔ SC 22.897 50 1 .999 .999 . 000 (.000—.000) .054
 MI ↔ ST 34.622 58 .994 .999 .999 . 000 (.000—.000) .074
Fear (Yes and No)
 MI ↔ ME 20.857 44 .999 .999 .999 .000 (.000—.000) .035
 MI ↔ SC 21.612 50 1 .999 .999 .000 (.000—.000) .035
 MI ↔ ST 27.994 58 1 .999 .999 . 000 (.000—.000) .042
 MI ↔ STR 86.722 63 .025 .984 .987 . 038 (.014—.057) .064
Trapped (Yes and No)
 MI ↔ CO 17.946 38 .998 .999 .999 .000 (.000—.000) .039
 MI ↔ ME 23.239 44 .994 .999 .999 .000 (.000—.000) .042
 MI ↔ SC 24.187 50 .999 .999 .999 .000 (.000—.000) .043
 MI ↔ ST 29.204 58 .999 .999 .999 . 000 (.000—.000) .050
 MI ↔ STR 63.743 63 .045 .984 .987 . 007 (.000—.038) .063
Mistreated (Yes and No)
 MI ↔ CO 18.078 38 .997 .999 .999 .000 (.000—.000) .036
 MI ↔ ME 20.792 44 .999 .999 .999 .000 (.000—.000) .038
 MI ↔ SC 22.552 50 1 .999 .999 .000 (.000—.000) .039
 MI ↔ ST 29.509 58 .999 .999 .999 . 000 (.000—.000) .046
 MI ↔ STR 101.020 63 .002 .974 .977 . 048 (.030—.065) .075

MI Measures of Invariance, CO Configural, ME Metric, SC Scalar, ST Strict, and STR Structural

But for the Structural invariance (STR) model that included the Fear, trapped, and mistreated groups, although the fit slightly decreased, CFI and TLI remained good (0.974–0.987), while RMSEA also increased but stayed within acceptable range.

Figure 2 showed that the ACE-ASF network differed between homosexual and heterosexual participants. In the homosexual group, the structure appeared more interconnected, with stronger associations among several items, whereas in the heterosexual group the network was somewhat more distributed. In addition, the centrality and clustering analyses suggested that some adverse childhood abuse experiences played a more prominent role depending on relationship type.

Fig. 2.

Fig. 2

Network centrality plot and clustering plot of the items of the Adverse Childhood Experiences Abuse Short Form (ACE-ASF) in homosexual, and heterosexual in Ecuador (n = 520)

Figure 3 showed that the ACE-ASF network was not identical across gay, lesbian, and heterosexual participants. The gay and lesbian groups presented more interconnected patterns, whereas the heterosexual group showed a less dense structure. In addition, the centrality and clustering results suggested that some experiences were more influential depending on sexual orientation. Overall, these findings indicated that adverse childhood abuse experiences were organized differently across groups in this Ecuadorian sample.

Fig. 3.

Fig. 3

Network centrality plot and clustering plot of the items of the Adverse Childhood Experiences Abuse Short Form (ACE-ASF) in gay, lesbian, and heterosexual in Ecuador (n = 520)

Figure 4 showed that fear, feeling trapped, and feeling mistreated were organized through relatively similar but not identical network structures. In the three models, the strongest connections were concentrated in a few specific links, suggesting that these experiences did not operate in isolation but rather as part of closely connected emotional and relational patterns. The centrality plots indicated that some nodes had a more prominent role within each network, meaning that certain adverse childhood abuse experiences were more influential in shaping these perceptions in adulthood.

Fig. 4.

Fig. 4

Network, centrality plot and clustering plot of the items of the Adverse Childhood Experiences Abuse Short Form (ACE-ASF) in fear, trapped, and mistreated in Ecuador

Figure 5 showed that the network of associations between adverse childhood experiences and perceptions of abuse within the relationship varied according to sexual orientation. Among gay participants, the structure was simpler and reflected more specific links, particularly between feeling mistreated, trapped, and afraid. Among lesbians, the network appeared more interconnected, suggesting a closer integration between early adverse experiences and current perceptions of abuse. In heterosexual participants, the network was denser and more cohesive, indicating a more consolidated pattern of associations. Across all three groups, feeling mistreated and feeling trapped emerged as the most central experiences, suggesting that these perceptions played a key role in understanding intimate partner abuse in this Ecuadorian sample.

Fig. 5.

Fig. 5

Network of the Adverse Childhood Experiences Abuse (Sexual, Physical and Emotional) in fear, trapped, and mistreated in Ecuador (n = 520). Note: Number of attempts = If you have tried to break up with your partner, please indicate the number of attempts

Discussion

The focus of the present study was on a study on the psychometric properties, reliability, validity, measurement invariance and network analysis of self-reported abuse of the abbreviated version of the Adverse Childhood Experiences Questionnaire (ACE-ASF) among homosexual, and heterosexual in Ecuador.

The results were largely consistent with the hypotheses and provided strong empirical support for the use of the instrument in a wide range of contexts. First, as in its first hypothesis, the ACE-ASF had good internal consistency among all three groups. The Cronbach’s alpha coefficients were found to be high for both the physical-emotional abuse dimension (α = 0.845) and the sexual abuse dimension (α = 0.883), both > the acceptable cut off for an alpha = 0.70 (Nunnally & Bernstein, 1994). Likewise, McDonald's omega coefficients were high (ωFactor 1 = 0.856 and ω Factor 2 = 0.876), and composite reliability indices were excellent (CRFactor 1 = 0.849 and CRFactor 2 = 0.884 for).

These findings agree with previous data from other countries [9], α = 0.83) and Romania [41], α = 0.80), thus supporting the generalizability of the ACE-ASF to other cultures. Second, supporting the second hypothesis is also confirmatory factor analysis (CFA), which confirmed the theoretical two-factor structure of the ACE-ASF and effectively separated the dimensions of physical-emotional abuse and sexual abuse. Factor loadings were standardized and ranged from 0.682 to 0.888 for physical-emotional abuse and from 0.766 to 0.829 for sexual abuse. Its model fit was excellent (χ2 = 19.587, p = 0.420,CFI/TLI = 0.999,RMSEA = 0.000; SRMR = 0.034) and this attested that the instrument structure was adequate to detect the relevant constructs [32]. This is consistent with Ford et al. previous discovery [23] and [35] across cultures.

With respect to the third hypothesis, findings validated satisfactory convergent and discriminant validity. The Average Variance Extracted (AVE) was 0.606 for physical-emotional abuse and 0.661 for sexual abuse, which was higher than a threshold of 0.50. In addition, the ratio of HTMT between factors was 0.437, supporting adequate discriminant validity and well below the critical cut-off of 0.85 [10]. Noticing no multicollinearity issues (VIF = 2.765 for physical-emotional abuse, VIF = 1.539 for sexual abuse) indicates the distinctiveness of the constructs collected.

The fourth hypothesis regarding measurement invariance was also realized. Multigroup studies demonstrated that the configural, metric, scalar, and strict models had ideal fit indices for sexual orientation groups (CFI = 0.999; RMSEA = 0.000; SRMR = 0.045) as well as for self-perception of abuse (CFI = 0.999; RMSEA = 0.000; SRMR = 0.043). Even in the most restrictive models, divergences in CFI (ΔCFI ≤ 0.001) and SRMR (ΔSRMR ≤ 0.015) were acceptable (Chen, 2007). This suggests that the ACE-ASF measures its actions equivalently in different individuals and groups so that group analyses can be consistent across the different populations. For the fifth hypothesis, network analyses revealed new perspectives and verified substantial contrasts in the group’s accounts of abuse. For example, homosexual had a significantly denser network (23 connections out of 28 possible, sparsity = 0.179), while heterosexual had slightly less density (22 connections, sparsity = 0.214). In both cases, item I3 (mild physical abuse) was the most influential node where the centrality value had the highest magnitude (betweenness = 1.67; closeness = 1.41; strength = 1.41; expected influence = 1.53 in non-trapped). These results are in line with prior research indicating the central nature of physical abuse in the portrayal of childhood adversity [6].

In addition, the high correlation between feeling trapped and the number of breakups attempts on all networks (weights from 0.33 to 0.63) is also evidence for the continued stability of such variables in violent and traumatic relationships. This emphasizes the importance of interventions directed at childhood abuse history and modern relational patterns.

Although this research offers a number of important perspectives in the health field, significant limitations are noted. Limitations include a non-probabilistic sample restricting the generalizability of the findings to the population. Samples (from regions and sociocultural backgrounds that are larger, more diverse and so on) are needed to make sure that the findings are reflective of the population of interest and not based on the experiences of individual children. Also, the self-report-based measurement could be subject to potential biases, particularly those of selective recall and, if the topic is sensitive such as sexual abuse, social desirability. Use of qualitative approaches or triangulation of sources of data could offer a more nuanced view on adverse childhood experience and their impact.

There are however, some critical limitations that need to be appreciated such as the use of a non-probabilistic type of sample, and the intrinsic bias in self-report instruments and, in certain scenarios, in sensitive subjects. Longitudinal analysis, larger and more heterogeneous sample sizes, and mixed methods designs are needed in the future to further investigate these relationships. In addition, the cross-sectional design of these studies limits causal inferences from childhood adversities on adult relational outcomes. Longitudinal studies would be required to examine the long-term outcomes of early adversity and its impact on psychological well-being and on relational patterns. Researchers could also add in additional risk to the adult outcomes from childhood abuse by exploring such protective factors as resilience, social support, socioeconomic status, and cultural beliefs. Cross-cultural comparisons with populations from other Latin American countries would increase the comparative validity of the ACE-ASF and inform the development of interventions to prevent violence and enhance mental health and wellbeing in at-risk populations.

Conclusions

The study focused on the psychometric measure of the short version of the Adverse Childhood Experiences Questionnaire (ACE-ASF) within homosexual and heterosexual in Ecuador. The first objective consisted of evaluation of the instrument reliability. The results validated the ACE-ASF as a reliable instrument that consistently measures the constructs of childhood abuse across sexual orientations. The stability and internal consistency we have shown indicates that the instrument can be used in various relational contexts and has good reliable measurement for use in different types of relational groups and that results can guide both clinical and research use. A third concern assessed convergent and discriminant validity. The results showed that the ACE-ASF is able to distinguish the various domains of abuse, indicating the accurate distinction of the multiple forms of adversity. This is so that the instrument allows for clear and meaningful assessments with no conceptual overlap that might impede the finding of specific experiences of abuse and the development of appropriate approaches. The fourth aim was to assess for measurement invariance by sexual orientation and self-perception of abuse.

The fifth aim was to perform network analysis of self-perceived abuse. There were patterns of interlinkages of important relationships observed between fear, feeling trapped, mistreatment, and number of breakup attempts. The patterns differed according to sexual orientation, providing new perspectives on the intricate relational relationship-based perception of abuse and adverse childhood experience with reference to the construct of sexual orientation. Recognizing central and peripheral factors in these networks underscores the need to comprehend how people engage with and process their experiences in a manner that can be used to make prevention and intervention strategies more appropriate and specific.

Supplementary Information

Supplementary Material 1. (426.9KB, docx)

Acknowledgements

The authors would like to thank the Universidad Politécnica Salesiana, Ecuador, and especially Dr. Juan Cárdenas Tapia, Sdb. Ph.D.

Abbreviations

ACE

Adverse Childhood Experiences Questionnaire

ACE-ASF

Adverse Childhood Experiences Abuse Short Form

AVE

Average Variance Extracted

HTMT

Heterotrait-Monotrait Ratio

CR

Composite Reliability

VIF

Variance Inflation Factor

CFI

Comparative ft index

TLI

Tucker-Lewis Index

GFI

Goodness of Fit Index

RMSEA

Root Mean Square Error of Approximation

SRMR

Standardized Root Mean Square Residual

Homosexuals

Same-sex relationship (includes gays and lesbians)

Heterosexuals

Different sex relationships (Man with women or vice versa)

Appendix

Table 5.

Adverse Childhood Experiences Abuse Short Form (ACE-ASF) Spanish version of Ecuador

Ítem Rechazo a contestar (1) Nunca (2) Una vez (3) Pocas veces (4) Muchas veces (5)
1. ¿Tu padre, madre, tutor u otro miembro del hogar te gritó, insultó o humilló?
2. ¿Tu padre, madre, tutor u otro miembro de la familia amenazó con abandonarte o echarte de la casa, o de hecho te lo hizo?
3. ¿Tu padre, madre, tutor u otro miembro de la familia te azotó, abofeteó, pateó o golpeó?
4. ¿Tu padre, madre, tutor u otro miembro de la familia te golpeó o cortó con un objeto, como un palo (o bastón), una botella, un garrote, un cuchillo, un látigo, etc.?
5. ¿Alguien te tocó o acarició de manera sexual cuando no querías que lo hiciera?
6. ¿Alguien te hizo tocar su cuerpo de manera sexual cuando no querías?
7. ¿Alguien intentó tener relaciones sexuales orales, anales o vaginales cuando tú no querías que lo hicieran?
8. ¿Alguien realmente tuvo relaciones sexuales orales, anales o vaginales contigo cuando usted no querías que lo hicieran?

Instructions: Below you will find a series of questions. Read each of them carefully and answer according to your criteria, placing an X in the option you consider appropriate

Sum of items 1 to 4 = Physical and Emotional Abuse, and sum of items 5 to 8 = Sexual Abuse

Authors’ contributions

Contribution to the conception and design: A.R.; contribution to data collection: A.R., L.B.-B., V. M-M., H.S.-S., N.A.-J. and F.J.R.-D.; contribution to data analysis and interpretation: A.R. and L.B.-B.; drafting and/or revising of the article: A.R., L.B.-B., V. M-M. and N.A.-J. Approval of the final version for publication: A.R., L.B.-B., F.J.H.D. and F.J.R.-D.; obtaining authorization for the scale: F.J.H.D. All authors have read and agreed to the published version of the manuscript.

Institutional review board statement

All procedures conducted in this study involving human participants adhered to the ethical standards established by the ethics committee. This study was approved by the Human Research Ethics Committee of the Pontifical Catholic University of Ecuador (code 046-UIO-2022; approval date:10 January 2023). This research is derived from the research project entitled “Prevalence and risk factors of dating violence among Ecuadorian adolescents and university students and evaluation of the effectiveness of psychological intervention with virtual reality in reducing anxiety, depression and post-traumatic stress derived from violence”, with the support of the Grupo de Investigación en Neurociencia Clínica Aplicada (GINCA) of the Salesian Polytechnic University (Universidad Politécnica Salesiana), sede Cuenca, Ecuador.

Funding

This research was financed by the Universidad Politécnica Salesiana Sede Cuenca, Ecuador.

Data availability

The data presented in this study are available on request from the corresponding author due to ethical approval requirements.

Declarations

Ethics approval and consent to participate

This study was approved by the Human Research Ethics Committee of the Pontifical Catholic University of Ecuador (code 046-UIO-2022; approval date:10 January 2023). The committee approved that the study be carried out in accordance with the Declaration of Helsinki. Participants provided written informed consent to participate in this study.

Competing interests

The authors declare no competing interests.

Footnotes

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

References

  • 1.Aguilera-Jiménez N, Rodríguez-Franco L, Rodríguez-Díaz FJ, Alameda-Bailén JR, Paíno-Quesada SG. Victimization and perception of abuse in adolescent and young homosexual and heterosexual couples in Spain. Healthcare. 2023;11(13):1873. 10.3390/healthcare11131873. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 2.Ali S, Pasha SA, Cox A, Youssef E. Examining the short- and long-term impacts of child sexual abuse: a review study. SN Soc Sci. 2024;4(2):56. 10.1007/s43545-024-00852-6. [Google Scholar]
  • 3.Almuneef M, Qayad M, Aleissa M, Albuhairan F. Adverse childhood experiences, chronic diseases, and risky health behaviors in Saudi Arabian adults: a pilot study. Child Abuse Negl. 2014;38(11):1787–93. 10.1016/j.chiabu.2014.06.003. [DOI] [PubMed] [Google Scholar]
  • 4.Arias A, Sireci S. Validez y validación para pruebas educativas y psicológicas: Teoría y recomendaciones. Rev Iberoam Psicol. 2021;14(1):11–22. 10.33881/2027-1786.rip.14102. [Google Scholar]
  • 5.Bhutta ZA, Bhavnani S, Betancourt TS, Tomlinson M, Patel V. Adverse childhood experiences and lifelong health. Nat Med. 2023;29(7):1639–48. 10.1038/s41591-023-02426-0. [DOI] [PubMed] [Google Scholar]
  • 6.Borsboom D, Deserno MK, Rhemtulla M, et al. Network analysis of multivariate data in psychological science. Nat Rev Methods Primers. 2021;1:58. 10.1038/s43586-021-00055-w. [Google Scholar]
  • 7.Brauer K, Ranger J, Ziegler M. Confirmatory factor analyses in psychological test adaptation and development: A nontechnical discussion of the WLSMV estimator. Psychol Test Adapt Dev. 2023;4(1):4–12. 10.1027/2698-1866/a000034. [Google Scholar]
  • 8.Butler N, Quigg Z, Bellis MA. Cycles of violence in England and Wales: the contribution of childhood abuse to risk of violence revictimisation in adulthood. BMC Med. 2020;18:1–13. 10.1186/s12916-020-01788-3. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 9.Chegeni M, Haghdoost A, Shahrbabaki ME, Shahrbabaki PM, Nakhaee N. Validity and reliability of the Persian version of the Adverse Childhood Experiences Abuse Short Form. J Educ Health Prom. 2020;9:140. 10.4103/jehp.jehp_15_20. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 10.Cheung GW, Wang C. Current approaches for assessing convergent and discriminant validity with SEM: Issues and solutions. Acad Manag Proc. 2017;2017(1):12706. 10.5465/AMBPP.2017.12706abstract. [Google Scholar]
  • 11.Cho G, Hwang H, Sarstedt M, Ringle CM. Cutoff criteria for overall model fit indexes in generalized structured component analysis. J Market Anal. 2020;8(4):189–202. 10.1057/s41270-020-00089-1. [Google Scholar]
  • 12.Christodoulou A, Michaelides M, Karekla M. Network analysis: a new psychometric approach to examine the underlying ACT model components. J Context Behav Sci. 2019;12:285–9. 10.1016/j.jcbs.2018.10.002. [Google Scholar]
  • 13.Cruchinho P, López-Franco MD, Capelas ML, Almeida S, Bennett PM, Miranda da Silva M, et al. Translation, cross-cultural adaptation, and validation of measurement instruments: a practical guideline for novice researchers. J Multidiscip Healthc. 2024;17:2701–28. 10.2147/JMDH.S419714. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 14.Dank M, Lachman P, Zweig JM, Yahner J. Dating violence experiences of lesbian, gay, bisexual, and transgender youth. J Youth Adolesc. 2014;43(5):846–57. 10.1007/s10964-013-9975-8. [DOI] [PubMed] [Google Scholar]
  • 15.Dantas Sartori TJ. Determining the confidence interval for non-probabilistic surveys: Method proposal and validation. Commun Stat Theory Methods. 2024. 10.1080/03610926.2024.2423815. [Google Scholar]
  • 16.De Winter JC, Gosling SD, Potter J. Comparing the Pearson and Spearman correlation coefficients across distributions and sample sizes: a tutorial using simulations and empirical data. Psychol Methods. 2016;21(3):273–90. [DOI] [PubMed] [Google Scholar]
  • 17.DiStefano C, Shi D, Morgan GB. Collapsing categories is often more advantageous than modeling sparse data: investigations in the CFA framework. Struct Equ Modeling. 2021;28(2):237–49. 10.1080/10705511.2020.1803073. [Google Scholar]
  • 18.Elosua P, Mujika J, Almeida LS, Hermosilla D. Judgmental-analytical procedures for adapting tests: adaptation to Spanish of the Reasoning Tests Battery. Rev Latinoam Psicol. 2014;46(2):117–26. 10.1016/S0120-0534(14)70015-9. [Google Scholar]
  • 19.Epskamp S, Maris G, Waldorp LJ & Borsboom D. Network psychometrics. In The Wiley handbook of psychometric testing: A multidisciplinary reference on survey, scale and test development. 2018; 953–986. 10.1002/9781118489772.ch30.
  • 20.Felitti VJ, Anda RF, Nordenberg D, Williamson DF, et al. Adverse childhood experiences and health outcomes in adults: The ACE Study. J Fam Consum Sci. 1998;90(3):31–2. [Google Scholar]
  • 21.Ferrara P, Cammisa I, Zona M, Corsello G, Giardino I, Vural M, et al. The global issue of violence toward children in the context of war. J Pediatr. 2024;269:114007. 10.1016/j.jpeds.2024.114007. [DOI] [PubMed] [Google Scholar]
  • 22.Flor LS, Stein C, Gil GF, Khalil M, Herbert M, Aravkin AY, et al. Health effects associated with exposure of children to physical violence, psychological violence and neglect: a burden of proof study. Nat Hum Behav. 2025;9:1217–36. 10.1038/s41562-025-02143-3. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 23.Ford DC, Merrick MT, Parks SE, Breiding MJ, Gilbert LK, Edwards VJ, et al. Examination of the factorial structure of adverse childhood experiences and recommendations for three subscale scores. Psychol Violence. 2014;4(4):432–45. 10.1037/a0037723. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 24.Ford K, Bellis MA, Hughes K, Barton ER, Newbury A. Adverse childhood experiences: a retrospective study to understand their associations with lifetime mental health diagnosis, self-harm or suicide attempt, and current low mental wellbeing in a male Welsh prison population. Health Justice. 2020;8(1):13. 10.1186/s40352-020-00115-5. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 25.Fry D, McCoy A, Swales D. The consequences of maltreatment on children’s lives: a systematic review of data from the East Asia and Pacific region. Trauma Violence Abuse. 2012;13(4):209–33. 10.1177/1524838012455873. [DOI] [PubMed] [Google Scholar]
  • 26.Goodman ML, Raimer-Goodman L, Chen CX, Grouls A, Gitari S, Keiser PH. Testing and testing positive: childhood adversities and later life HIV status among Kenyan women and their partners. J Public Health. 2017;39(4):720–9. 10.1093/pubmed/fdw135. [DOI] [PubMed] [Google Scholar]
  • 27.Güler A, Maas MK, Mark KP, Kussainov N, Schill K, Coker AL. The impacts of lifetime violence on women’s current sexual health. Womens Health Rep. 2024;5(1):56–64. 10.1089/whr.2023.0089. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 28.Herrenkohl TI, Fedina L, Roberto KA, Raquet KL, Hu RX, Rousson AN, et al. Child maltreatment, youth violence, intimate partner violence, and elder mistreatment: a review and theoretical analysis of research on violence across the life course. Trauma Violence Abuse. 2022;23(1):314–28. 10.1177/1524838020939119. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 29.Hevey D. Network analysis: a brief overview and tutorial. Health Psychol Behav Med. 2018;6(1):301–28. 10.1080/21642850.2018.1521283. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 30.Holden GW, Gower T, Chmielewski M. Methodological considerations in ACEs research. In: Adverse childhood experiences. Academic Press; 2020:161–82. 10.1016/B978-0-12-816065-7.00009-4. [Google Scholar]
  • 31.Horino M, Abu-Rmeileh NME, Yang W, Albaik S, Al-Khatib L, Seita A. Exploring the link between adverse childhood experiences and mental and physical health conditions in pregnant Palestine refugee women in Jordan. Public Health. 2023;220:179–86. 10.1016/j.puhe.2023.05.005. [DOI] [PubMed] [Google Scholar]
  • 32.Hu L, Bentler PM. Cutoff criteria for fit indexes in covariance structure analysis: conventional criteria versus new alternatives. Struct Equ Model. 1999;6(1):1–55. 10.1080/10705519909540118. [Google Scholar]
  • 33.Hulme PA. Psychometric evaluation and comparison of three retrospective, multi-item measures of childhood sexual abuse. Child Abuse Negl. 2007;31(8):853–69. 10.1016/j.chiabu.2007.03.016. [DOI] [PubMed] [Google Scholar]
  • 34.Jewkes R, Dunkle K, Nduna M, Jama PN, Puren A. Associations between childhood adversity and depression: substance abuse and HIV and HSV2 incident infections in rural South African youth. Child Abuse Negl. 2010;34(11):833–41. 10.1016/j.chiabu.2010.05.002. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 35.Kovács-Tóth B, Oláh B, Kuritárné Szabó I, Fekete Z. Psychometric properties of the adverse childhood experiences questionnaire 10 item version (ACE-10) among Hungarian adolescents. Front Psychol. 2023;14:1161620. 10.3389/fpsyg.2023.1161620. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 36.Liebschutz JM, Buchanan-Howland K, Chen CA, Frank DA, Richardson MA, Heeren TC, et al. Childhood trauma questionnaire (CTQ) correlations with prospective violence assessment in a longitudinal cohort. Psychol Assess. 2018;30(6):841–5. 10.1037/pas0000549. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 37.Marshall C, Langevin R, Cabecinha-Alati S. Victim-to-victim intergenerational cycles of child maltreatment: a systematic scoping review of theoretical frameworks. Int J Child Adolesc Resil. 2022;9(1):95–115. 10.54488/ijcar.2022.283. [Google Scholar]
  • 38.May-Chahal C, Cawson P. Measuring child maltreatment in the United Kingdom: a study of the prevalence of child abuse and neglect. Child Abuse Negl. 2005;29(9):969–84. 10.1016/j.chiabu.2004.05.009. [DOI] [PubMed] [Google Scholar]
  • 39.May-Chahal C, Bertotti T, Di Blasio PACM, Cerezo MA, Gerard M, Grevot A, et al. Child maltreatment in the family: a European perspective. Eur J Soc Work. 2006;9(1):3–20. 10.1080/13691450500480706. [Google Scholar]
  • 40.Meinck F, Steinert J, Sethi D, Gilbert R, Bellis M, Alink L, et al. Measuring and monitoring national prevalence of child maltreatment: a practical handbook. World Health Organization; 2016. http://www.euro.who.int/__data/assets/pdf_file/0003/317505/Measuring-monitoring-national-prevalence-child-maltreatment-practical-handbook.pdf.
  • 41.Meinck F, Cosma AP, Mikton C, Baban A. Psychometric properties of the adverse childhood experiences abuse short form (ACE-ASF) among Romanian high school students. Child Abuse Negl. 2017;72:326–37. 10.1016/j.chiabu.2017.08.016. [DOI] [PubMed] [Google Scholar]
  • 42.Meinck F, Murray AL, Dunne MP, Schmidt P, Nikolaidis G, Petroulaki K, et al. Measuring violence against children: the adequacy of the International Society for the Prevention of Child Abuse and Neglect (ISPCAN) child abuse screening tool–child version in 9 Balkan countries. Child Abuse Negl. 2020;108:104636. 10.1016/j.chiabu.2020.104636. [DOI] [PubMed] [Google Scholar]
  • 43.Meinck F, Woollett N, Franchino-Olsen H, Silima M, Thurston C, Fouché A, et al. Interrupting the intergenerational cycle of violence: protocol for a three-generational longitudinal mixed-methods study in South Africa (INTERRUPT_VIOLENCE). BMC Public Health. 2023;23(1):395. 10.1186/s12889-023-15168-y. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 44.Midei AJ, Matthews KA, Chang Y-F, Bromberger JT. Childhood physical abuse is associated with incident metabolic syndrome in mid-life women. Health Psychol. 2013;32(2):121–7. 10.1037/a0027891. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 45.Mikton C, Power M, Raleva M, Makoae M, Al Eissa M, Cheah I, et al. The assessment of the readiness of five countries to implement child maltreatment prevention programs on a large scale. Child Abuse Negl. 2013;37(12):1237–51. 10.1016/j.chiabu.2013.07.009. [DOI] [PubMed] [Google Scholar]
  • 46.Miller GE, Chen E, Parker KJ. Psychological stress in childhood and susceptibility to the chronic diseases of aging: moving toward a model of behavioral and biological mechanisms. Psychol Bull. 2011;137(6):959–97. 10.1037/a0024768. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 47.Moore GF, Campbell M, Copeland L, Craig P, Movsisyan A, Hoddinott P, et al. Adapting interventions to new contexts—The ADAPT guidance. BMJ. 2021;374:n1679. 10.1136/bmj.n1679. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 48.Muñiz J, Elosua P, Hambleton RK. Directrices para la traducción y adaptación de los tests: Segunda edición. Psicothema. 2013. 10.7334/psicothema2013.24. [DOI] [PubMed] [Google Scholar]
  • 49.Pace CS, Muzi S, Rogier G, Meinero LL, Marcenaro S. The adverse childhood experiences–international questionnaire (ACE-IQ) in community samples around the world: A systematic review (Part I). Child Abuse Negl. 2022;129:105640. 10.1016/j.chiabu.2022.105640. [DOI] [PubMed] [Google Scholar]
  • 50.Qu G, Shu L, Liu H, Ma S, Han T, Zhang H, et al. Association between adverse childhood experiences and academic performance among children and adolescents: A global meta-analysis. Trauma Violence Abuse. 2024;25(4):3332–45. 10.1177/15248380241246758. [DOI] [PubMed] [Google Scholar]
  • 51.R Core Team. R: A language and environment for statistical computing (Version 4.1) [Computer software]. R Foundation for Statistical Computing; 2022. [Google Scholar]
  • 52.Ramiro LS, Madrid BJ, Brown DW. Adverse childhood experiences (ACE) and health-risk behaviors among adults in a developing country setting. Child Abuse Negl. 2010;34(11):842–55. 10.1016/j.chiabu.2010.02.012. [DOI] [PubMed] [Google Scholar]
  • 53.Ramírez A, Burgos-Benavides L, Quito-Calle JV, Sinchi-Sinchi H, Herrero Díez J, Rodríguez-Díaz FJ. Psychometric properties of the adverse childhood experiences abuse short form (ACE-ASF) for Ecuadorian youth. Eur J Investig Health Psychol Educ. 2025;15(4):63. 10.3390/ejihpe15040063. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 54.Ramírez A, Burgos-Benavides L, Sinchi-Sinchi H, Quito-Calle JV, Muñoz-Arteaga PA, Herrero Díez J, et al. Adaptación y Validación de Cuestionarios de Evaluación Psicológica mediante Análisis Factorial Confirmatorio: Un Tutorial para la Planificación y la Presentación del Análisis. Rev Cient Psicol Eureka. 2026;23(1):125–56. 10.63707/Eureka.v23n1a26p125-156. [Google Scholar]
  • 55.Revelle W. Psych: Procedures for psychological, psychometric, and personality research [R package]. Northwestern University; 2019. [Google Scholar]
  • 56.Rosseel Y, Loh WW. A structural after measurement approach to structural equation modeling. Psychol Methods. 2024;29:561–88. 10.1037/met0000503. [DOI] [PubMed] [Google Scholar]
  • 57.Sansone A, Limoncin E, Colonnello E, Mollaioli D, Ciocca G, Corona G, et al. Harm reduction in sexual medicine: How to manage patients with sexual dysfunction caused by substance use. Sex Med Rev. 2024;12(3):422–9. 10.1016/j.sxmr.2024.03.004. [DOI] [PubMed] [Google Scholar]
  • 58.Shapiro SS, Wilk MB. An analysis of variance test for normality (complete samples). Biometrika. 1965;52(3–4):591–611. 10.1093/biomet/52.3-4.591. [Google Scholar]
  • 59.Shi D, Maydeu-Olivares A. The effect of estimation methods on SEM fit indices. Educ Psychol Meas. 2020;80(3):421–45. 10.1177/0013164419885164. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 60.Shi D, DiStefano C, Zheng X, Liu R, Jiang Z. Fitting latent growth models with small sample sizes and non-normal missing data. Int J Behav Dev. 2021;45(2):179–92. 10.1177/0165025420979365. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 61.Shields M, Tonmyr L, Hovdestad WE, Gonzalez A, MacMillan H. Exposure to family violence from childhood to adulthood. BMC Public Health. 2020;20:1–15. 10.1186/s12889-020-09709-y. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 62.Soares ALG, Howe LD, Matijasevich A, Wehrmeister FC, Menezes AM, Gonçalves H. Adverse childhood experiences: prevalence and related factors in adolescents of a Brazilian birth cohort. Child Abuse Negl. 2016;51:21–30. 10.1016/j.chiabu.2015.11.017. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 63.Stanton B, Davis B, Laraque-Arena D. Global burden of violence. Pediatr Clin North Am. 2021;68(2):339–49. 10.1016/j.pcl.2020.12.001. [DOI] [PubMed] [Google Scholar]
  • 64.Steele B, Neelakantan L, Jochim J, Davies LM, Boyes M, Franchino-Olsen H, et al. Measuring violence against children: a COSMIN systematic review of the psychometric and administrative properties of adult retrospective self-report instruments on child abuse and neglect. Trauma Violence Abuse. 2024;25(1):183–96. 10.1177/15248380221145912. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 65.Swift A, Berry M, Fernandez-Pineda M, Haberstroh A. An integrative review of adverse childhood experiences and reproductive traumas of infertility and pregnancy loss. J Midwifery Womens Health. 2024;69(2):258–78. 10.1111/jmwh.13585. [DOI] [PubMed] [Google Scholar]
  • 66.Tran QA, Dunne MP, Vo TV, Luu NH. Adverse childhood experiences and the health of university students in eight provinces of Vietnam. Asia Pac J Public Health. 2015;27(8_suppl):26S-32S. 10.1177/1010539515589812. [DOI] [PubMed] [Google Scholar]
  • 67.Turanovic JJ. Victimization and its consequences over the life course. Crime Justice. 2023;52(1):265–342. 10.1086/727029. [Google Scholar]
  • 68.Vives-Cases C, Pérez-Martínez V, Davó-Blanes M, Sánchez-SanSegundo M, Gil-González D, Abiétar MG, et al. Dating violence and associated factors among male and female adolescents in Spain. PLoS ONE. 2021;16(11):e0258994. 10.1371/journal.pone.0258994. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 69.Wadji DL, Oe M, Bartoli E, Martin-Soelch C, Pfaltz MC, Langevin R. How are experiences and acceptability of child maltreatment related to resilience and posttraumatic growth? A cross-cultural study. Eur J Psychotraumatol. 2023;14(2):2264119. 10.1080/20008066.2023.2264119. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 70.Wingenfeld K, Schäfer I, Terfehr K, Grabski H, Driessen M, Grabe H, et al. The reliable, valid and economic assessment of early traumatization: first psychometric characteristics of the German version of the Adverse Childhood Experiences Questionnaire (ACE). Psychother Psychosom Med Psychol. 2011;61(1):e10–4. 10.1055/s-0030-1263161. [DOI] [PubMed] [Google Scholar]
  • 71.World Health Organization. Adverse Childhood Experiences International Questionnaire (ACE-IQ). World Health Organization; 2020. https://www.who.int/publications/m/item/adverse-childhood-experiences-international-questionnaire-%28ace-iq%29.
  • 72.Ye Z, Wei X, Zhang J, Li H, Cao J. The impact of adverse childhood experiences on depression: the role of insecure attachment styles and emotion dysregulation strategies. Curr Psychol. 2024;43(5):4016–26. 10.1007/s12144-023-04613-1. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 73.Yoon S, Speyer R, Cordier R, Aunio P, Hakkarainen A. A systematic review evaluating psychometric properties of parent or caregiver report instruments on child maltreatment: Part 2: internal consistency, reliability, measurement error, structural validity, hypothesis testing, cross-cultural validity, and criterion validity. Trauma Violence Abuse. 2020;22(5):1296–315. 10.1177/1524838020915591. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 74.Zark L, Satyen L. Cross-cultural differences in student attitudes toward intimate partner violence: A systematic review. Trauma Violence Abuse. 2021;23(3):1007–22. 10.1177/1524838020985565. [DOI] [PubMed] [Google Scholar]

Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

Supplementary Material 1. (426.9KB, docx)

Data Availability Statement

The data presented in this study are available on request from the corresponding author due to ethical approval requirements.


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