Psychometric evidence of the Female Sexual Function Index (FSFI) in a Chilean representative sample

doi:10.21203/rs.3.rs-3903081/v1

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Psychometric evidence of the Female Sexual Function Index (FSFI) in a Chilean representative sample

https://doi.org/10.21203/rs.3.rs-3903081/v1

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Inconsistencies in the Female Sexual Function Index (FSFI) factor structure and current research and clinical guidelines highlight the need for continued exploration of its psychometric evidence. Furthermore, only one study has assessed its measurement invariance (MI), while the only FSFI validation conducted in Chile lacks quality and representativity. Therefore, this study aimed to evaluated the FSFI in a Chilean sample (n = 2595), examining MI across relationship status, age groups, regions of the country, BDSM practices, and paraphilic interests. Confirmatory factor analysis supported a six-factor structure. Criterion-related validity indicated modest-to-moderate effects in satisfaction differences based on relationship status, regions, and BDSM practices. MI was achieved across socio-demographic variables at the factor covariance level. While acknowledging the absence of a clinical group for female sexual dysfunction (FSD) diagnosis, potential pandemic-related impact on scores, online methodology biases, and limited diversity in gender and sexual orientation, our findings supports the FSFI as a valuable research tool for female sexual function and wellbeing. This study significantly expands the applicability of the FSFI and underscores its measurement invariance across sociodemographic factors, as well as its applicability in the Chilean context.

Sexual function

Psychometrics

Measurement invariance

CSSS

Chile

Sexual health is an integral component of women's overall well-being, and understanding their sexual function is essential in providing comprehensive healthcare to women of all ages and backgrounds (WHO, 2022). In turn, female sexual dysfunction (FSD) is estimated to affect over 40-45% of reproductive-age women worldwide (McCool et al., 2016; Shifren et al., 2008), making its accurate and valid assessment paramount. Whereas a clinical diagnosis is the gold-standard when determining who suffers from a particular sexual dysfunction, researchers rely heavily on psychometric tools to screen the presence of these conditions for their studies.

Amongst the several tools available to evaluate female sexual disorders (see Grover & Shouan, 2020), the female sexual function index (FSFI) has emerged as a widely utilized instrument for assessing various dimensions of female sexual function (FSF), including desire, arousal, lubrication, orgasm, satisfaction, and pain during sexual activity. Originally developed by Rosen et al. (2000), the FSFI has demonstrated good psychometric properties in diverse populations and contexts (Meston et al., 2019; Neijenhuijs et al., 2019). Studies replicating other latent structures have reported two-, three-, four-, and five-factor solutions. However, the five-factor structure, where arousal and desire are combined, has been reported more frequently than the six-factor solution (Neijenhuijs et al., 2019). Furthermore, despite its popularity, another fundamental psychometric property, measurement invariance, is yet to be determined across studies.

Measurement invariance pertains to the extent to which the measurement of the latent underlying construct is comparable across the dimensions within a variable (e.g., genders, age groups, relationship status, etc.) so as to meaningfully compare across them (Putnick & Bornstein, 2016). Whereas this concept was introduced more than 50 years ago (Meredith, 1964; Struening & Cohen, 1963), it has only become accessible and a standard technique to report in validation studies more recently. Peixoto (2021) is the only study that has validated the FSFI while evaluating its measurement invariance, in its case, by sexual orientation in Portuguese women (i.e., heterosexual vs. lesbian women). While replicating the six-factor structure with solid reliability, Peixoto's results provided evidence of 'strong' measurement invariance across both sub-groups. That is, the meaning of the latent construct (i.e., factor loadings, also known as configural invariance), the item loading on the factors (i.e., also known as metric invariance), and the levels of the underlying manifest variables (i.e., intercepts, also known as scalar invariance) are equivalent—not the same—in both sub-groups. Therefore, if researchers wish to meaningfully compare the sub-dimensions or total score of the FSFI (or any scale) across groups or repeated measures, they are required to provide evidence of its measurement invariance while able to compare only to the degree of invariance attained (see Vandenberg & Lance, 2000).

Chilean female sexual function

Given that the etiology of sexual function and dysfunction is undeniably multifactorial (Bancroft, 2008), sociocultural aspects become of particular importance not only for the comprehensive understanding of these phenomena (Ahmed & Bhugra, 2004; Rowland & Jannini, 2020), but also to determine the culturally-sensitive recommendations in clinical management and research, ethically sound sexual health care, as well as counseling and medical decision-making from country to country (Atallah et al., 2016). Particularly, when it comes to understanding Chilean sociocultural nuances of sexual function and dysfunction, sex research is considered limited and outdated (Quintana, 2023). Aside from studies that have analysed different dimensions of sexual function in isolation in this population (e.g., Contreras et al., 2016; Mella et al., 2015; Oyanedel et al., 2021), studies on women' sexual function consist of only twelve peer-reviewed studies across mainstream databases (i.e., Web of Science, PubMed, Scopus, and SciELO). These studies have evaluated the sexual function of women in the general population (Águila et al., 2022; Blümel, Binfa, et al., 2004), middle age (Blümel, Castelo-Branco, et al., 2004; Blümel et al., 2009), in different reproductive stages (Castelo-Branco et al., 2003; Figueroa et al., 2009; Morin Chaparro et al., 2013), clinical samples (Antúnez-García & Muñoz-Mendoza, 2019; Flores et al., 2012; Osorio et al., 2018), as well as in health (Valenzuela et al., 2014) and sex workers (Del Valle et al., 2015). Most of these studies recruited women from Santiago—Chile's capital city—where total FSFI scores ranged between 21 and 30, and the highest scores were more commonly reported by women between 35 and 40 years old. At the same time, sexual dysfunction percentages fluctuated between 32% and 57%. Finally, 44 and older women who have given birth to two or more children, of lower education level, who give in to a partner's desire to engage in sexual intercourse, and lack of a stable relationship are at higher risk for FSD.

The use of the FSFI as the chosen psychometric tool across these studies is based on the study of Blümel et al. (2004). They described the sexual function scores of women across different age groups, analysing FSD risk factors. However, the study did not perform any psychometric validation analysis beyond just offering the reliability score for each dimension. Furthermore, the study was conducted more than 20 years ago, using a small and age-limited sample of women (n = 371; 20–59 years old) only from Santiago, while using an inclusion criterion of being sexually active during the last three shown to increase rates of FSD, which is different than the one established by Wiegel et al. (2005; i.e., four weeks).

Therefore, in light of the limited literature available in Chile regarding women's sexual function and its valid assessment, and given the lack of a validation study for the FSFI that represents Chilean women all around the country from a wider age range, and that is able to compare across different attributes, the following study had three goals: 1) to validate the FSFI using a representative sample of Chilean women; 2) to perform a measurement invariance analysis by sociodemographic variables of interest. Finally, in combination with the validation of the International Index of Erectile Function (IIEF), this study aimed 3) to provide the Chilean National Sex and Sexuality Study (NSSS) with a valid psychometric tool to assess female sexual function and dysfunction in Chile.

Study design

This study was part of the CSSS, a cross-sectional, broader project conducted by 26 collaborators from 13 universities across Chile, using a cross-sectional design. This study was pre-registered in the open science framework website (https://osf.io/yp792), just like the NSSS project (https://osf.io/7yve8/).

Participants

This study sample was initially composed of 2595 participants. However, after excluding people who did not meet the inclusion criteria (see "Procedure" section below), the final sample was composed of 1871 people (M_age = 32.10, SD_age = 10) between 18 and 77 years of age. Aside from sex (i.e., female = 99.1%), gender (i.e., women = 98.8%), sexual orientation (i.e., heterosexual = 85.2%), and aboriginal ethnicity (i.e., none = 82.7%), the sample was well distributed amongst most dimensions of the sociodemographic variables: age, marital status, level of education, provinces of the country (except for the last southern provinces), income, employment/studying status, religion, political orientation (see Table 1).

[Insert Table 1 here]

Measures

Sexual function

As the CSSS assessed the sexual function of individuals of diverse gender identities, and in order to redirect all people to the proper sexual function questionnaire, four alternatives were given that included answers related to their external and internal genitalia, and those with whom they prefer to have sex. Additionally, the following statement was included: "If you prefer to have sex equally with people with a penis or vulva, choose any alternative that best represents your genitals." The research team acknowledges the limitation for those who are intersex or have ambiguous external genitals. Unfortunately, to our knowledge, there are no adapted questionnaires for this population to measure their sexual function, particularly those with ambiguous genitalia.

Female Sexual Function

We used the Female Sexual Function Index (FSFI; Rosen et al., 2000), composed of 19 items grouped into six dimensions: desire (two items; "how often have you experienced sexual desire or interest?"), arousal (four items; "how frequently did you experience sexual arousal during sexual activity or intercourse?"), lubrication (4 items; "how often did you feel vaginal lubrication or moisture during sexual activity or intercourse?"), orgasm (three items; "when you had sexual stimulation or intercourse, how often did you achieve an orgasm or climax?"), satisfaction (three items; "how satisfied have you been with your sexual relationship with your partner?"), and pain (three items; "how often have you felt discomfort or pain after vaginal penetration?"). Items are scored on a five-point Likert-type scale (1 = Never; 5 = Always), whereas 15 items contain a zero-scored option indicating no sexual activity ("no sexual activity" or "did not attempt sexual intercourse"). Scores in each domain are summed and multiplied by a domain factor to produce a domain score while ensuring equal weight in contributing to the total score. Higher scores indicate higher sexual function, and scores below 26.55 were considered indicative of FSD, according to Wiegel et al. (2005) cut-off.

While the FSFI has been translated into Spanish (Blümel, Binfa, et al., 2004), we followed formal guidelines for cross-cultural adaptations of self-report measures (Beaton et al., 2000). The translated questionnaire is available on the CSSS OSF page (https://osf.io/sy9u5).

Procedure

The CSSS project utilized a non-probabilistic sampling method of recruitment stratified by macro zones (i.e., north, Santiago, and south country areas), drawing its sample from a wide range of the main cities from all provinces. Data was collected through a Google Forms survey between June 2021 and March 2022. After explaining the purpose of the study, all willing participants continue to sign the informed consent and completed the questionnaire. Participation was anonymous, voluntary, and could be terminated at any point. Participants did not receive any compensation for participating. Quintana (2023) provides a more comprehensive description of the complete CSSS project sample and other relevant details.

Inclusion criteria were twofold: being 18 years or older, and have been sexually active during the last four weeks previous to completing the questionnaire (Meston et al., 2019). Therefore, we decided to exclude anyone who responded zero (i.e., no sexual activity) to at least one of the questions with such alternative, in order to improve the representativity of this validation study results, instead of treating these responses as missing values.

Statistical analyses

Missing data

We employed the Full Information Maximum Likelihood (FIML) approach to handle missingness. FIML estimates the model parameters by utilizing all available information from observed variables, accommodating missing values through an iterative procedure. This method allows for the inclusion of all participants in the analysis, regardless of missing data, and provides unbiased estimates under the assumption that the missing data mechanism is missing at random (Newman, 2014). Missing values on the FSFI items were minimal (1.12%) and missing completely at random (MCAR), as assessed through Little's MCAR Test (Little, 1988; χ2 = 71.6, df = 72, p = 0.491).

Evidence of construct validity

To examine the factor structure underlying the FSFI, we compared the statistical fit of five- and six-factor correlated models using Confirmatory Factor Analysis with the Maximum Likelihood Restricted (MLR) estimator (Barrett et al., 2008; Brown, 2006; see Supplementary Table 1).

The goodness of fit of the estimated models was evaluated using the comparative fit index (CFI), the Tucker–Lewis fit index (TLI), the root mean square error of approximation (RMSEA), and the standardized root mean square residual (SRMR). For the CFI and TLI indices, estimated values above 0.90 and 0.95 indicate an acceptable and good fit level, respectively (Hu & Bentler, 1999; Marsh et al., 2004). For the RMSEA and SRMR indices, values equal to or less than 0.05 and 0.08 are considered good and acceptable, respectively (Browne & Cudeck, 1992; Hu & Bentler, 1999).

Evidence of reliability

We estimated reliability for each dimension from the optimal solution using Cronbach's alpha and McDonald's omega coefficients (Goodboy & Martin, 2020; Hayes & Coutts, 2020). A value of Cronbach's alpha or MacDonald's omega above 0.7 was considered acceptable for research or measurement purposes (McNeish, 2018). Higher values of 0.8 or above were indicative of better reliability.

Measurement invariance

To assess whether the FSFI is interpreted in the same way across different groups of individuals, we performed tests of measurement invariance (Vandenberg & Lance, 2000) for the following demographic and sexual variables of interest: age generation (Gen Z, Gen Y, Gen X), regions of the country (north, capital, south), civil status (single vs. in a relationship), BDSM practitioner (BSDM vs. non-BDSM), paraphilic interest (paraphilic vs. non-paraphilic). These were chosen based on the objectives of other studies associated with the CSSS, particularly for the latter two, to expand the FSFI application into other less explored sexual diversities.

The age generation criterion followed the Strauss–Howe generational theory (Strauss & Howe, 1991), where Gen Z were those born between 1997–2012, Gen Y/Millennia those born between 1981–1996, and Gen X were born between 1965–1980. Meanwhile, the division by regions of the country is based on the geographical, political, financial, and sociocultural division of the country from north and south to its capital, Santiago. This is mainly due to Chile's high level of centralization of resources destined for Santiago, fostering such division (Mardones, 2006; Thayer, 2011), as well as other sociocultural and financial repercussions (Herrera & Pino, 2023). Furthermore, civil status divided people between those who were single (i.e., single, separated, divorced, and widowed), and those in a relationship (i.e., in a relationship, common law, engaged/married). Moreover, BDSM practice divided people between those who performed BDSM-like behaviors (defined as "sexual practices such as bondage, discipline, domination, submission, sadism, masochism, among others") and those who do not, by asking them about their BDSM monthly practice frequency. Similarly, paraphilic interest divided people between those who self-identify as having a paraphilia (i.e., voyeurist, exhibitionist, frouterist, sadist, masochist, fetishist, zoophilic, sexually attracted to elders or gerontophilic, sexually attracted to minors), and those who do not, by answering to the statement "Sexually speaking, I consider myself:"

We examined the invariance of the estimated parameters of the optimal solution following a specification sequence that successively incorporated more restrictive models (Widaman et al., 2010) to represent the different levels of equivalence in the model's parameters: (1) configural invariance as a baseline model, where all parameters were freely estimated to examine whether the factorial structure remains constant across groups, (2) metric invariance (incorporating constraints to factor loads) to examine whether latent variables are related to items in the same way, (3) scalar invariance (adding constraints to the intercepts), and (4) residual invariance (incorporating constraints to the residuals of the indicators). Additionally, we examined the structural invariance of the model at the level of the variance of factors and the covariance between the model's factors.

Decreases in CFI and TLI (ΔCFI/ΔTLI ≤ .010) and increases in RMSEA (ΔRMSEA ≤ .015) will be used to determine which level of measurement invariance was achieved (Chen, 2007). Should a model not achieve at least the first four levels of invariance, we will assess partial measurement invariance by allowing specific parameters to vary across groups depending on the level of invariance at which it is observed, following established recommendations (Chen, 2007).

Evidence of criterion-related validity

In order to evaluate criterion-related validity, we assessed women' sexual satisfaction following Sprecher (2001) definition of the construct as a favorable balance of reward and cost of sexual and non-sexual dimensions of an individual's intimate life. Therefore, we asked them the following question "How satisfied are you with the following aspects of your sexual life?" regarding their: sexual fantasies, foreplay, oral sex, vaginal sex, anal sex, sex communication, and compatibility through a five-point Likert scale (1 = "completely unsatisfied" to 5 = completely satisfied"). This statement and its dimensions were chosen for their similarity to other scales that measure sexual satisfaction (e.g., Fülöp et al., 2022; Meston & Trapnell, 2005), yet expanding into a standard measure evaluating common sexual behaviors (e.g., Herbenick et al., 2010), and aspects related to women' sexual function such as sex communication (Mallory et al., 2019) and partner sexual compatibility (Offman & Matheson, 2005), to enhance comparability and to reduce any sexual or gender diversities biased of psychometric scales.

To assess the criterion validity, we performed Pearson correlation tests. Similarly, we used the FSD cut-off score by Wiegel et al. (2005) to compare them across all criterion variables using Student's t-tests, Cohen's d, η², and Cramer's V as effect sizes. The magnitude of the effect size was established following Cohen (1988), where d = .2–.4 is a small effect; .5–.7 an intermediate effect; and ≥ .8 a large effect; while η² = .010–.059 is a small effect; .060–.139 an intermediate effect and ≥ .14 a large effect; and finally Cramer's V values with one degree of freedom of ≤ .10 was considered small, ≥ .30 as medium, and ≥ .50 as large (Cramer, 1946).

Factor analysis and reliabilities

Table 2 presents the fit indices for both tested models. The five-factor model yielded acceptable fit indexes, whereas the six-factor model exhibited excellent fit to the data. Both the AIC and BIC criteria also corroborated this trend, demonstrating that the six-factor model offers a much better complexity and fit to the data than the five-factor model. Accordingly, all subsequent statistical analyses were performed using the six-factor model in line with these results.

[Insert Table 2 here]

Standardized factor loadings for the six-factor model ranged from .60 to .86, whereas inter-factor covariances were positive and ranged between moderate and strong (p < .001). Meanwhile, the internal consistency indices for all sub-dimensions and the whole scale were good, and Cronbach's alpha (α) and McDonald's omega (ω) were consistently equal or larger than 0.80 (see Table 3 and Figure 1).

[Insert Table 3 here]

[Insert Figure 1 here]

Measurement invariance analyses

Table 4 presents the multigroup analyses of the FSFI by relationship status, age generation, country regions, BDSM practitioner, and paraphilia self-identification.

[Insert Table 4 here]

When examining the factor structure by relationship status, we obtained evidence of a good fit of the six-factor solution for both groups. The configural model exhibited good fit indices. Furthermore, the multigroup analyses yielded evidence that the measurement model was psychometrically equivalent by relationship status when models were increasingly constrained, revealing that no noteworthy variations in overall fit were detected according to ∆CFI, ∆TLI, and ∆RMSEA. Similarly, we obtained the same trend and very similar indices in terms of configural model fit for age generation, country regions, BDSM practitioner, and paraphilic interest. Moreover, the multigroup analyses yielded evidence that the measurement model was psychometrically equivalent by age generation, country regions, BDSM practitioner, and paraphilic interest when models were increasingly constrained, revealing that no noteworthy variations in overall fit were detected according to ∆CFI, ∆TLI, and ∆RMSEA. In other words, the six-factor model achieved the factor covariance level of measurement invariance for all sociodemographic variables evaluated, allowing a meaningful comparison of FSFI scores across their sub-dimensions.

Criterion-related validity

Table 5 presents the scores, comparisons, and effect size for the criterion variables by groups of interest. Women' satisfaction with different aspects of their intimate lives showed statistically significant differences by relationship status in foreplay, sex communication, and sex compatibility (ps < .001); by region of the country in sex communication and sex compatibility (ps < .01), and by paraphilic interests in sexual fantasies, vaginal sex, anal sex, and sex communication (ps < .05). However, most of these differences were of a smaller magnitude than a small effect size of Cohen' standards (i.e., ds < .2; η² < .01), except for those found for sex communication and sex compatibility between women in a relationship and those single (d = .35; d = .39, respectively). Meanwhile, statistically significant differences were found between women who practice BDSM-like behaviors and those who do not across all criterion variables (ps < .001), where those who do practice them scored higher than those who do not, with effect sizes ranging between small to medium (i.e., ds = .21–.52). For comparison across levels of the sociodemographic variables of interest by FSFI dimensions, and the FSD criterion, see Supplementary table 2 and 3, respectively.

[Insert Table 5 here]

Table 6 presents the Pearson correlations between the criterion variables and the FSFI sub-dimensions. All criterion variables correlate positively and significantly with all FSFI sub-dimensions and total scores. Satisfaction with "vaginal sex" correlated higher across 5/6 FSFI sub-dimensions than all other criterion variables (rs = .29–.59; p < .001), whereas the FSFI sub-dimension "satisfaction" also correlated higher across criterion variables (rs = .33–.60; p < .001). Conversely, the criterion variable "anal sex" (rs .21–.37; p < .001) and the sub-dimension "pain" (rs .11–.29; p < .001) obtained the lowest correlations with the FSFI sub-dimensions and criteria variables, respectively. Furthermore, when comparing women with and without FSD across criterion variables, those with FSD scored statistically significantly lower than those without FSD across all criterion variables (ps < .001), with effect sizes ranging between a medium to large magnitude. The highest difference between these groups was for the criterion variable of satisfaction with vaginal sex (t = 17.8; p < .001; d = 1.16).

[Insert Table 6 here]

Finally, we offered a comparison table between our study sample FSFI total score across the age groups presented in previous FSF studies conducted using the FSFI in Chilean women (Blümel, Binfa, et al., 2004; Blümel et al., 2009; see Supplementary Table 4).

Female sexual function and dysfunction are perhaps at the core of current sex research. Recent systematic reviews (McCool et al., 2018; West et al., 2004) replicate the high FSD prevalence across different populations, making its accurate assessment still an active research area by either improving the existing alternatives (Grover & Shouan, 2020) and offering new ones (Giraldi et al., 2011). Therefore, the present study evaluated the psychometric properties of the FSFI in a Chilean sample, demonstrating the FSFI possesses good structural validity and reliability while being capable of meaningfully compare individuals across relationship status, age generations, regions of Chile, BSDM practices, and paraphilic interests.

Structural validity

The present study provides support for the six-factor solution in Chilean adult women. This latent structure was first proposed by the scale authors when the FSFI was developed (Rosen et al., 2000)—though primarily by following its theoretical model since the data supported a five-factor solution favoring the conflation of desire and arousal. Other validation studies have also found acceptable solutions involving a two- (Wolpe et al., 2017), three- (Chang et al., 2009), four- (Sun et al., 2011), and five-factor (Forbes et al., 2014) solutions, where the five- and six-factor are the most replicated solutions (Neijenhuijs et al., 2019). Thus, there are, at least, two forefronts to address this controversy of the FSFI structural validity: data/psychometrics and the theory.

From the data, as summarized by Neijenhuijs et al. (2019), the structural validity of the FSFI is inconsistent and of low quality according to the consensus-based standards for the selection of health measurement instruments (COSMIN) methodology (Prinsen et al., 2018). Whereas there is no consistent factorial solution obtained through confirmatory factor analysis (CFA), most studies replicating the five-factor solution do so using principal component analysis (PCA), which is considered only indirect support (Kim, 2008). Both techniques allow capturing the variance in variables in a smaller set through data extraction, interpretation, and rotation, choosing the number of factors or components. PCA creates one or more components from a larger set of measured variables through an inductive approach, whereas CFA does the opposite through a deductive, theory-driven approach, where items work as indicators of a latent factor that would best reproduce the observed correlation; variables create components, factors create variables (Tabachnick, 2001). Thus, CFA is considered direct evidence of structural validity. From the theory, sexual desire and arousal often conflate—in the five-factor solution—so much so that, at least for women, it appears that sexual desire could precede sexual arousal, as well as follow it, or be indistinguishable from one another (Brotto et al., 2009; Graham et al., 2004). Following this line of thought, the DSM-V (APA, 2013) introduced revisions that resulted in the reclassification of hypoactive sexual desire disorder and sexual arousal disorder as sexual interest/arousal disorder. However, much like the several other validation studies using CFA replicating a six-factor solution (e.g., Bartula & Sherman, 2015; Burri et al., 2010; Hevesi et al., 2017), there is also evidence against the conflation of sexual desire and arousal demonstrating it is not always a proper fit to the data (Clayton et al., 2012). Similarly, while the present study showed that the six-factor solution provides a better goodness-of-fit to conceptualize sexual desire and arousal as separate (though related) theoretical and empirical dimensions of the sexual response, it is also fair to say the five-factor solution provides acceptable fit indices, and this study evidence does not necessarily put into question other studies supporting the five-factor solution. Moreover, there are still several different layers to consider when using CFA, such as the sociocultural characteristics of the sample, its size, the researcher's subjectivity when analysing the solution, goodness-of-fit indicators, etc. (Kim, 2008), which also influence the ultimate decision of a factor solution. Therefore, it would be unsurprising that the FSFI may show different factor structures in different contexts or samples of relevant characteristics (e.g., Hevesi et al., 2017). Moving forward, our understanding of why there is variability in the structural validity of the FSFI what seems important to know for whom and why a factorial solutions provides a better fit to the data. There are two main ways to ascertain this: through measurement invariance analyses assessing theoretically relevant variables would allow us to understand 'for whom' a conflation between desire and arousal or lack thereof works best, while cross-cultural validations would allow us to understand the reason/why may be the case.

Criterion validity

Our results demonstrated that Chilean women differ in their satisfaction with some of the construct criteria variables across the sociodemographic variables of interest. Despite the several statistically significant differences found across groups, fewer reached an effect size of a small magnitude according to Cohen (1988) standards. Out of those, on the one hand, Chilean women in a relationship had a significantly higher satisfaction with their sexual communication and compatibility than those who were single. A recent systematic review showed that the role of being or not in a relationship with female sexual function is unclear (McCool et al., 2018), where its influence depends on other contextual and sexual factors. Sexual communication (Frederick et al., 2017) and partner' sexual compatibility (Offman & Matheson, 2005) are both predictors of sexual satisfaction, which was also the case for Chilean women in a relationship who scored significantly higher than single women in sexual satisfaction (see Supplementary Table 2). These observations also coincide with previous findings in Chilean women, where being in a relationship was a protective factor against FSD (Blümel, Binfa, et al., 2004; Blümel et al., 2009). On the other hand, women who practice BDSM-like behaviors had a significantly higher satisfaction across all criterion variables than those who do not. Similarly, Chilean women who practice BDSM-like behaviors were less likely to have FSD than those who do not (see Supplementary Table 3). Unpublished data from our laboratory demonstrate a similar trend amongst the whole population who not only practice BDSM-like behaviors, but also who self-identifies as such in comparison to those who do not (https://osf.io/an9te/). We discuss these two demographic and the other sociodemographic factors of interest more in-depth in the following section.

Measurement invariance

As a multifactorial construct, sexual function is highly modulated by sociocultural contexts, such as people's relationship status For instance, women in relationships have better sexual satisfaction and higher sexual self-esteem than single women (Antičević et al., 2017). Particularly, after establishing measurement invariance across relationship status, Park and MacDonald (2022) demonstrated that sexual desire involving a partner in single women, yet not for solitary sexual desire, was negatively related to sexual satisfaction; whereas for those in a relationship, a lower solitary desire and higher sexual desire involving a partner were associated with greater sexual satisfaction. However, in a five-year longitudinal analysis of women in a relationship or single demonstrated that those in a relationship had worse desire, arousal, lubrication, and satisfaction at year five, whereas this was also true for the satisfaction for single women. Conversely, the orgasm function was the only one improving at year five in women in a relationship, and with a much larger magnitude for single women (Gunst et al., 2017). Certain contextual factors, such as being pregnant or having children, have also shown to modulate women' sexual function (DeJudicibus & McCabe, 2002). Yet, when that occurs in interaction of a romantic relationship, relationship satisfaction and perceptions of partner's desire correlated negatively with solitary sexual desire, whereas relationship satisfaction correlated positively with dyadic sexual desire (Cappell et al., 2016). Meanwhile, in a multi-stage, clustered, and stratified population probability sample study of sexually active British women, no association between relationship status, relationship duration or general happiness with the relationship with sexual pain was found (Mitchell et al., 2017), though women who report higher emotional closeness with their partners have lower odds of experiencing sexual pain (Fergus et al., 2020). Altogether, it is clear the influence that being or not in a relationship has on female sexual function (FSF) is highly dependable on several factors. Thus, this study's findings demonstrate that the FSFI is a reliable capable to meaningfully address relationship status as a (co)variable to explore in future FSF studies.

When it comes to age, it is worth remembering that sexual function problems can be experienced at any point in the individuals lives (APA, 2013). However, studies consistently show that FSF tends to worsen with age (Berman et al., 1999; Clayton & Harsh, 2016; McCool et al., 2018). In a large study conducted in the US with 31,581 women, the prevalence of self-reported sexual problems involving desire, arousal, and orgasm-related increased linearly with age. Yet, the levels of distress due to sexual problems were the lowest in elderly women (12.6%) in comparison to middle-aged and younger women combined (25%; Shifren et al., 2008). Adolescents and younger adults are not except of FSD (O’Sullivan, 2015). Among women between 18–29 years old, with at least one partner in the past year, the rate of FSD ranged between 19 to 32% (Laumann et al., 1999), meanwhile another study reported that FSD rates increased with age starting at 26.2% for 18–19 years old, moving up to 44.3% for 20–29-year-olds, and 41.2% for 30–39-year-olds (Song et al., 2008). Amongst the natural endocrine events that come with time and choice, pregnancy and menopause are two important events that strongly modulate women' sexual function. For instance, pregnancy and postpartum are associated with a drastic reduction in desire, pain on intercourse, impediments, or decreased ability or fear of achieving orgasm (Clayton & Harsh, 2016). The prevalence of sexual problems in women that go through childbirth ranges between 41–83% during the two to three months after delivery (Fehniger et al., 2013; Leeman & Rogers, 2012). Though, key elements influencing the return to enjoyable sexual activity after childbirth involve more than just recovering from perineal trauma, dealing with vaginal dryness due to breastfeeding, or managing the impacts of postpartum depression treatment, as well as sufficient rest, while fostering a suitable environment for intimacy (Leeman & Rogers, 2012). Finally, an study with women ages 57 to 85 showed that the most common sexual problem for elder women are low sexual desire (43%) and reduced vaginal lubrication (Lindau et al., 2007). Clearly, as people age, there is a general decline in health, that in combination with other psychosocial changes and life events associated with adult life, conspire against women' sexual function (Ambler et al., 2012). Therefore, the present study provides the first demonstration that the FSFI is capable to meaningfully compare across different age groups, allowing future studies to explore these intersectionalities in FSF.

When it comes to geographical location, cross-cultural findings on FSF often show variations (McCool et al., 2016). For example, in the context of Latin America, and while using a sample of women between 40 to 59 years old from 11 countries, Blümel et al. (2009) showed that FSFI total scored varied between 20.6 to 29.9, while the percentage of FSD ranged between 21–98.5%. One way to understand these differences is through the erotic equity model which proposes a socio-structural analysis as to how a system enables or fail to promote positive aspects of sexuality and wellbeing (Higgins et al., 2022). Therefore, a greater financial, educational, and job limitations would lead to a poor sexual wellbeing, especially sexual satisfaction and overall functioning. Particularly, Chilean studies on FSF have been conducted almost exclusively with women from our capital city. Moreover, judging by the concentration of votes our last presidential elections, our country's provinces concentrate different political ideologies or views (García, 2021), which have also shown to be indirectly associated with sexual satisfaction (Sánchez-Fuentes et al., 2016), and to modulate sexual behaviors such as people's dating strategies (Tybur et al., 2015). Furthermore, Herrera and Pino (2023) showed that when creating two new provinces there was an increase in mean, median, and mode of individual's income in one of the provinces (i.e., Los Ríos), while not in the other (i.e., Arica y Parinacota), suggesting that other financial and sociocultural factors interact with that process. For instance, for the year 2022, Los Ríos's gross domestic product (GDP) was nearly double than Arica y Parinacota's (4.410M vs 2.610M USD; Banco Central de Chile, 2023). When comparing the FSFI scores between Santiago (2022 GDP = 139.921M USD) and the rest of the country, the financial inequities do not reflect higher FSFI scores in favor of Santiago (Supplemental Tables 3 and 4). In fact, significant difference were found in the 'orgasm' and 'satisfaction' dimensions, where the south scores in the 'orgasm' sub-scale were significantly lower than the rest of Chile, while Santiago scores in the 'satisfaction' subscale were significantly lower than the rest of Chile (ps < 0.05). However, the magnitude of the differences were very small (Cohen's d = .23; d = .42, respectively), thus demonstrating the multifactorial nature of sexual wellbeing and sexual function. Whereas the erotic equity model hypothesis did not explain the FSFI score differences found in the Chilean population, the present study still provides the first demonstration that the FSFI is capable of meaningfully compare amongst regions of Chile. This is of special interest for the CSSS future studies focused on people' sexual function, and its relationship with socio-demographic variables, in a country whose sexual research has been deemed outdated and limited (Quintana, 2023).

When it comes to sexual behaviors, the extensive range of human sexual behaviors can be categorized between those normative or frequent (Herbenick et al., 2010) and non-normative, and while these distinctions aren't always sharply defined, the latter generally encompasses sexual activities, expressions, and behaviors that are less common within the population (Pfaus et al., 2020; Wismeijer & van Assen, 2013), often associated to the BSDM community (Ambler et al., 2017). Given these behaviors and the BSDM community have suffered from a long history of stigma of being deviant, immoral, non-natural, etc. (Bering, 2013), researchers have been interested in exploring differences between BDSM and non-BDSM practitioners. While some studies show no differences (Monteiro Pascoal et al., 2015), more frequently studies report a significant better sexual function and wellbeing of BDSM practitioners and people from the BDSM community than the general population (Botta et al., 2019; Monteiro Pascoal et al., 2015; Strizzi et al., 2022; Wismeijer & van Assen, 2013). This is not to say that BDSM practitioners do not suffer from, at least, some degree of sexual dysfunction (Huang et al., 2023). Interestingly, a comparison between people who perceive themselves as either sexually dominant or submissive demonstrated that dominant men had more biological male children (Jozifkova & Kolackova, 2017). Curiously, this relates to findings in animals where sexual fetishes not only modulate reproductive yield (Cetinkaya & Domjan, 2006), but also sexual arousal, as well as partner preference (Quintana, Desbiens, et al., 2019; Quintana, González, et al., 2019). Finally, across all variables of interest for the measurement invariance analyses, only did BDSM practitioner showed significant differences when comparing across its sublevel, where BDSM practitioners had a significant higher scores in five out of seven FSFI dimensions, and lower risk of scoring below the FSD criterion than non-BDSM practitioners (see Supplementary Tables 2 and 3), corroborating previous findings. Altogether, the FSFI demonstrates to be a valuable tool to meaningfully compare across people who do and do not perform BDSM behavior, which proves of great value for the study of sexual wellbeing of the BDSM community.

Finally, when it comes to paraphilic interests, there is only study on this population' sexual function, and yet paraphilia-associated sexual arousal patterns estimates may go as high as 62.4% in the population (Ahlers et al., 2011). Castellini et al. (2018) assessed the relationship among paraphilic thoughts and behaviors, hypersexuality, and psychopathology in a sample of university students. They showed, amongst other findings, that, aside for sadistic and transvestic behaviors, women with paraphilic behaviors (i.e., voyeurism, exhibitionism, fetishism, masochism, frotteurism, and pedophilia) scored higher than those without them across all domains of the FSFI. However, there are many studies addressing different component of it individually. For instance, Mundy and Cioe (2019) demonstrated that individuals with criminal or combined paraphilic interests experienced lower sexual satisfaction without engaging in paraphilia-related behavior, while those solely interested in legal paraphilias showed unaffected satisfaction. Moreover, disclosure to partners correlated with higher satisfaction, regardless of paraphilic interest or engaging with the partner in these behaviors. Our study found no significant differences in terms of FSF, FSD, nor across the criterion variable scores between people with paraphilic interest. Whereas null results often fall short in demonstrating the relevance in findings, these results demonstrate that are perhaps not only perhaps the first assessment of women with paraphilic interests' sexual functioning, but they also demonstrate that this group does not differ significantly sexual functioning and wellbeing from those who do not manifest the same interests. Similarly, the present study is also the first demonstration the FSFI is able to compare between paraphilic interests and lack thereof, allowing future studies to meaningfully compare these groups along with other FSF-related constructs.

Limitations and future studies

The study caveats need acknowledgment. Firstly, our study did not involve a clinical group diagnosed with sexual dysfunction, a recognized gold standard for ascertaining the presence of Female Sexual Dysfunction (FSD). This omission hindered the assessment of FSFI's sensitivity and specificity in the Chilean population. Secondly, the study was conducted during the SARS-CoV-2 pandemic's second wave, limiting the sample size, and potentially biasing results towards lower sexual function scores (Quintana, 2022). Future research should assess the potential impact of pandemic-related factors on scores. Thirdly, the online nature of the study restricted participation to individuals with internet access, affecting sample diversity and representativeness. Lastly, the sample primarily comprised cisgender and heterosexual individuals despite attempts to include gender-diverse participants (Quintana, 2023), falling short of the intended diversity. Future studies must actively recruit a wider gender and sexual orientation sample and analyze FSFI measurement consistency across these identities.

All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki Declaration and its later amendments or comparable ethical standards. The study was approved by the Bioethics Committee of the Universidad de Tarapacá N°05/2021.

Acknowledgements

The CSSS would like to thank all university academics who contributed to the recruitment of participant, and all our participants for the valuable contribution.

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Table 1. Study sociodemographic characteristics

Sex	n	%	Gender	n	%
Female	1854	99.1	Women	1848	98.8
Male	2	0.1	Men	3	0.2
Intersex	2	0.1	Non-binary	15	0.8
Prefer not to say	6	0.3	Gender fluid	1	<0.1
			Multi-gender	3	0.2
Sexual orientation	n	%	Marital status	n	%
Heterosexual	1595	85.2	Single	555	29.8
Homosexual (gay or lesbian)	1	<0.1	In a relationship	626	33.6
Bisexual	189	10.2	Common law	173	9.3
Queer	5	0.3	Married and/or engaged	398	21.4
Asexual	5	0.3	De facto separated	47	2.5
Pansexual	40	2.2	Divorced	59	3.2
Other (mono or polysexual) not included	8	0.4	Widowed	5	0.3
Other (mono or polysexual) not included
Prefer not to say	14	0.7
Religion	n	%	Ethnicity	n	%
Atheist or none	552	29.7	None in particular	1548	82.9
Agnostic	257	13.8	Afrodescendant	11	0.6
Catholic	694	37.4	Aymara	52	2.8
Judaism	107	5.8	Atacameño	22	1.2
Hinduism	2	0.1	Quechua	6	0.3
Taoism	5	0.3	Kolla	6	0.3
Other	233	12.6	Diaguita	43	2.3
			Rapanui	8	0.4
			Mapuche	144	7.7
			Yaghan	1	<0.1
			Other	27	1.4
Provinces of the country	n	%		n	%
Arica and Parinacota	127	6.8	Maule	91	4.9
Tarapacá	55	3.0	Ñuble	18	1.0
Antofagasta	276	14.9	Bio-Bio	119	6.4
Atacama	156	8.4	Araucanía	51	2.7
Coquimbo	120	6.5	Los Ríos	16	0.9
Valparaíso	165	8.9	Los Lagos	31	1.7
Metropolitan	569	30.6	Aysén	3	0.2
O’Higgins	52	2.8	Magallanes	9	0.5
Level of education	n	%	Average monthly income (CLP)	n	%
Basic education	9	0.5	Less than 250,000	492	26.6
High school/Technical	235	12.6	Between 250,000 and 500,000	312	16.9
Advanced technical studies	142	7.6	Between 500,000 and 1,000,000	430	23.3
Incomplete university education	506	27.2	Between 1,000,000 and 1,500,000	292	15.8
University education complete	742	39.8	Between 1,500,000 and 2,000,000	185	10.0
Master's degree/MBA	205	11.0	Between 2,000,000 and 3,000,000	83	4.5
PhD	24	1.3	Between 3,000,000 and 5,000,000	39	2.1
			More than 5,000,000	15	0.8

Table 1. (continued)

Employment and education status	n	%			n	%
Working full time	734	39.4	Working full-time and studying part-time		98	5.3
Working part-time	207	11.1	Working full-time and studying part-time
Studying full time	326	17.5	Working part-time and studying full-time		148	7.9
Studying part-time	43	2.3	Working part-time and studying full-time
Working and studying full-time	69	3.7	Not working or studying		146	7.8
Working and studying part-time	93	5.0
Political orientation	n	%	Measurement invariance categories		n	%
None in particular	756	41.0	Relationship status	Single	666	35.7
Purely left-wing	335	17.9		In a relation	1197	64.3
Between center and left	429	23.0	Age generation	Gen Z	771	42.0
Center	95	5.1		Gen Y/Millenials	851	46.4
Between center and right	205	11.0		Gen X	213	11.6
Purely right-wing	38	2.0	Region	North	899	48.4
				Metropolitan	569	30.6
				South	390	21.0
			BDSM practice	Non-BDSM	1284	73.5
				BDSM	462	26.5
			Paraphilic interest	Non-paraphilic	1432	76.5
				Paraphilic	439	23.5

Note. Due to missing values, not all group sizes sum up to the total sample size. n = group size, % = Percentage.

Table 2. Summary of fit indices for confirmatory factor solutions of the IIEF

Models	fp	χ2	df	χ2/df	CFI	TLI	RMSEA [90% CI]	SRMR	AIC	BIC
M1. Five-factor model	67	1,298.524^***	142	9.145	.922	.906	.066 [.063 – .069]	.045	79,612.998	79,983.791
M2. Six-factor model	72	725.786^***	137	5.298	.960	.950	.048 [.045 – .051]	.032	78,895.062	79,293.526

Note. fp = Free Parameters; χ² = Chi-square; df = Degrees of Freedom; CFI = Comparative Fit Index; TLI = Tucker-Lewis Index; RMSEA = Root Mean Square Error of Approximation; 90% CI = 90% Confidence interval; SRMR = Standardized Root Mean Square Residual; AIC = Akaike Information Criterion; BIC = Bayesian Information Criterion.

^* p < .05; ^** p < .01; ^*** p < .001

Table 3. Six-factor solution statistics

Items	Descriptive Statistics			Factor loadings						Reliability
Items	Mean(SD)	Skew	Kurt	Des	Aro	Lub	Org	Sat	Pain	α if item is dropped	ω if item is dropped
Item 1	3.73(1.030)	-0.443	-0.490	.852^***						.757	--
Item 2	3.58(0.980)	-0.311	-0.321	.845^***						.685	--
Item 3	4.44(0.878)	-1.693	2.591		.764^***					.777	.781
Item 4	4.01(0.898)	-0.753	0.291		.793^***					.772	.777
Item 5	4.24(0.880)	-0.975	0.324		.677^***					.812	.815
Item 6	4.25(0.978)	-1.317	1.250		.754^***					.798	.801
Item 7	4.42(0.928)	-0.703	2.484			.733^***				.868	.874
Item 8	4.35(0.797)	-1.408	2.476			.834^***				.840	.846
Item 9	4.38(0.928)	-1.533	1.767			.813^***				.837	.847
Item 10	4.37(0.808)	-1.507	2.755			.852^***				.835	.837
Item 11	3.92(1.244)	-0.964	-0.174				.870^***			.798	.801
Item 12	3.90(1.043)	-1.063	0.840				.806^***			.839	.840
Item 13	4.02(1.162)	-1.199	0.528				.841^***			.828	.836
Item 14	4.28(1.060)	-1.561	1.690					.603^***		.820	.823
Item 15	4.13(1.027)	-1.190	0.797					.868^***		.658	.659
Item 16	3.79(1.140)	-1.152	0.877					.814^***		.701	.701
Item 17	4.34(0.955)	-1.540	1.927						.858^***	.834	.834
Item 18	4.37(0.962)	-1.622	2.165						.842^***	.836	.836
Item 19	4.35(0.921)	-1.347	1.201						.842^***	.837	.837
Factors	Mean(SD)	Skew	Kurt	Des	Aro	Lub	Org	Sat	Pain	α	ω
Desire	7.31(1.86)	-0.485	-0.255	-						.837	.837
Arousal	16.94(2.97)	-1.229	1.490	.714^***	-					.834	.836
Lubrication	17.52(2.97)	-1.564	2.667	.458^***	.626^***	-				.879	.883
Orgasm	11.84(3.09)	-1.109	0.535	.316^***	.637^***	.416^***	-			.875	.877
Satisfaction	12.21(2.73)	-1.136	0.755	.464^***	.763^***	.461^***	.629^***	-		.802	.812
Pain	13.05(2.56)	-1.480	1.818	.305^***	.430^***	.607^***	.359^***	.299^***		.884	.884
Total score	78.89(11.78)	-1.176	1.612	.619^***	.854^***	.755^***	.728^***	.735^***	.625^***	.915	.918

Note. Descriptives: SD = Standard deviation; Skew = Skewness; Kurt = Kurtosis. Factor loadings: Des = Desire; Aro = Arousal; Lub = Lubrication; Org = Orgasm; Sat = Satisfaction. Reliability: α = Cronbach's alpha; ω = McDonald's omega.

^* p < .05; ^** p < .01; ^*** p < .001.

Table 4. Measurement invariance across sociodemographic variables of interest

Groups	Model	Fit indices					Model comparison
Groups	Model	MLR χ2	df	CFI	TLI	RMSEA [90% CI]	Pair	Δχ2	Δdf	ΔCFI	ΔTLI	ΔRMSEA
Relationship status	1. Configural	809.147^***	144	.964	.956	.046 [.042 – .049]
	2. Metric	825.108^***	131	.964	.957	.045 [.041 – .048]	M2-M1	17.727	13	<.001	.001	-.001
	3. Scalar	955.746^***	118	.956	.950	.048 [.045 – .052]	M3-M2	157.477^***	13	-.008	-.007	.003
	4. Residual	1,099.919^***	99	.954	.951	.048 [.045 – .052]	M4-M3	56.971^***	19	-.002	.001	<.001
	5. Factor variance	1,028.807^***	93	.953	.951	.048 [.045 – .052]	M5-M4	18.900^**	6	-.001	<.001	<.001
	6. Factor covariance	1,061.819^***	78	.952	.952	.048 [.045 – .051]	M6-M5	35.287^**	15	-.001	.001	<.001
Age generation	1. Configural	1,001.147^***	216	.962	.953	.047 [.043 – .051]
	2. Metric	983.786^***	190	.963	.956	.045 [.041 – .049]	M2-M1	26.652	26	.001	.003	-.002
	3. Scalar	1,073.986^***	164	.958	.954	.046 [.043 – .050]	M3-M2	97.279^***	26	-.005	-.002	.001
	4. Residual	1,189.227^***	126	.953	.952	.047 [.044 – .051]	M4-M3	102.191^***	38	-.005	-.002	.001
	5. Factor variance	1,258.719^***	114	.949	.949	.049 [.045 – .052]	M5-M4	63.269^***	12	-.004	-.003	.002
	6. Factor covariance	1,300.600^***	84	.948	.951	.048 [.044 – .051]	M6-M5	46.876^*	30	-.001	.002	-.001
Region	1. Configural	1,001.147^***	216	.962	.952	.048 [.044 – .052]
	2. Metric	1,024.500^***	190	.962	.955	.047 [.043 – .050]	M2-M1	28.727	26	0.000	0.003	-0.001
	3. Scalar	1,068.203^***	164	.961	.956	.046 [.042 – .050]	M3-M2	39.858^***	26	-0.001	0.001	-0.001
	4. Residual	1,121.464^***	126	.960	.959	.045 [.041 – .048]	M4-M3	67.944^***	38	-0.001	0.003	-0.001
	5. Factor variance	1,131.979^***	114	.959	.959	.044 [.041 – .048]	M5-M4	17.580^**	12	-0.001	0.000	-0.001
	6. Factor covariance	1,198.118^***	84	.957	.960	.044 [.041 – .048]	M6-M5	60.752 ^**	30	-0.002	0.001	0.000
BDSM practice	1. Configural	783.033^***	216	.963	.954	.046 [.042 – .050]
	2. Metric	825.108^***	190	.964	.957	.045 [.042 – .049]	M2-M1	41.118^***	26	.001	.003	-.001
	3. Scalar	837.098^***	164	.961	.956	.042 [.042 – .049]	M3-M2	9.373	26	-.003	-.001	<.001
	4. Residual	843.121^***	126	.962	.960	.043 [.040 – .047]	M4-M3	27.577	38	.001	.004	-.002
	5. Factor variance	858.407^***	114	.962	.960	.043 [.040 – .047]	M5-M4	15.375^*	12	<.001	-.000	<.001
	6. Factor covariance	880.549^***	84	.961	.961	.043 [.039 – .046]	M6-M5	25.009^*	30	-.001	-.001	<.001
Paraphilic interest	1. Configural	908.728^***	144	.958	.948	.050 [.046 – .053]
	2. Metric	909.624^***	131	.959	.951	.048 [.045 – .052]	M2-M1	6.885	13	.001	.003	-.002
	3. Scalar	945.490^***	118	.958	.952	.048 [.045 – .051]	M3-M2	34.723^***	13	-.001	.001	<.001
	4. Residual	954.691^***	99	.958	.955	.046 [.043 – .050]	M4-M3	32.705^*	19	<.001	.003	-.002
	5. Factor variance	979.159^***	93	.957	.955	.046 [.043 – .050]	M5-M4	24.468^***	6	-.001	<.001	<.001
	6. Factor covariance	1,026.338^***	78	.955	.955	.046 [.043 – .065]	M6-M5	46.919^***	15	-.002	<.001	<.001

Note. MLR = Maximum Likelihood Robust procedure; χ² = Chi-square; df = degrees of freedom; CFI = Comparative Fit Index; TLI = Tucker-Lewis Index; RMSEA = Root-Mean-Square Error of Approximation; ΔCFI, ΔTLI, and ΔRMSEA = Change in CFI/TLI, RMSEA values compared to the preceding model. Bold letters indicate the final level of invariance that was achieved.

^* p < .05; ^** p < .01; ^*** p < .001.

Table 5. Sexual satisfaction dimensions across sociodemographic variables of interest

Groups		Sexual fantasies		Foreplay		Oral sex		Vaginal sex
		Mean (SD)	t/F (d/ η²)‡	Mean (SD)	t/F (d/ η²)‡	Mean (SD)	t/F (d/ η²)‡	Mean (SD)	t/F (d/ η²)‡
Relationship status	Single	3.50 (1.35)	1.95 (.10)	4.05 (1.09)	2.01^* (.10)	3.95 (1.26)	1.92† (.09)	4.34 (0.94)	.35 (.02)
	In a relation	3.36 (1.43)		3.94 (1.10)		3.83 (1.36)		4.32 (0.96)
Region	North	3.48 (1.41)	1.83† (< .001)	4.02 (1.12)	1.59 (< .01)	3.95 (1.30)	2.71 (<.01)	4.38 (0.95)	1.88 (< .01)
	Santiago	3.35 (1.31)		3.91 (1.07)		3.79 (1.33)		4.29 (0.93)
	South	3.35 (1.50)		3.98 (1.09)		3.82 (1.34)		4.29 (0.97)
Age generation	Gen Z	3.59 (1.33)	9.37†^*** (.01)	4.13 (1.01)	12.96†^*** (.01)	4.03 (1.22)	10.04†^*** (.01)	4.40 (0.95)	3.86^* (< .01)
	Gen Y/Millenials	3.30 (1.40)		*3.87* (1.12)		3.75 (1.36)		4.28 (0.94)
	Gen X	3.32 (1.54)		*3.84* (1.23)		3.83 (1.41)		4.26 (0.93)
BDSM practice	Non-BDSM	3.27 (1.43)	8.41†^*** (.42)	3.90 (1.12)	4.5^*** (.25)	3.78 (1.37)	5.27†^*** (.52)	4.29 (0.97)	3.02†^** (.16)
	BDSM	3.84 (1.18)		4.17 (0.97)		4.12 (1.12)		4.44 (0.88)
Paraphilic interest	Non-Paraphilic	3.37 (1.44)	2.49†^* (.13)	4.00 (1.08)	1.48† (.13)	3.89 (1.33)	.96 (.05)	4.37 (0.93)	3.00^** (.02)
	Paraphilic	3.55 (1.27)		3.91 (1.15)		3.82 (1.29)		4.21 (1.02)
Groups		Anal sex		Communication		Compatibility
		Mean (SD)	t/F (d/ η²)‡	Mean (SD)	t/F (d/ η²)‡	Mean (SD)	t/F (d/ η²)‡
Relationship status	Single	1.90 (1.95)	.63 (.03)	3.79 (1.36)	6.73†^*** (.35)	3.98 (1.26)	7.16†^*** (.39)
	In a relation	1.84 (1.96)		4.20 (1.05)		4.39 (0.94)
Region	North	1.92 (2.00)	.94† (<.01)	4.16 (1.12)	8.71†^*** (<.01)	4.33 (1.03)	5.15^** (<.01)
	Santiago	1.86 (1.89)		3.90 (1.25)		4.15 (1.13)
	South	1.75 (1.95)		4.02 (1.22)		4.18 (1.10)
Age generation	Gen Z	1.65 (1.95)	10.11^*** (.01)	4.25 (1.14)	17.78^*** (.02)	4.41 (1.02)	16.96^*** (.02)
	Gen Y/Millenials	2.09 (1.97)		*3.92* (1.19)		*4.11* (1.10)
	Gen X	1.86 (1.89)		*3.87* (1.18)		*4.14* (1.10)
BDSM practice	Non-BDSM	1.71 (1.93)	5.6^*** (.30)	3.98 (1.20)	3.36^*** (.19)	4.17 (1.11)	4.07†^*** (.21)
	BDSM	2.31 (1.95)		4.20 (1.15)		4.40 (1.01)
Paraphilic interest	Non-Paraphilic	1.79 (1.96)	3.22†^*** (.19)	4.09 (1.14)	2.45†^* (.14)	4.26 (1.06)	1.46† (.08)
	Paraphilic	2.13 (1.91)		3.92 (1.32)		4.17 (1.16)

Note. M = Mean; SD = Standard deviation; t = Student's t-test; F = Fisher's F test; d = Cohen's d effect size; η² =eta squared effect size. Participants responded to the question "How satisfied are you with the following aspects of your sex life?" for each category, for which response alternatives ranged between 1 ("completely unsatisfied") to 5 ("completely satisfied"). † Equal variance not assumed, Brown-Forsythe correction applied. ‡ For the age generation groups, we used the F test and η² instead (means in bold are the ones that differed significantly using Bonferroni's post-hoc correction).

^* p < .05; ^** p < .01; ^*** p < .001

Table 6. Association of sexual function and dysfunction with sexual satisfaction dimensions

How satisfied are you with the following aspects of your sex life?	Sexual satisfaction dimensions							Female sexual dysfunction comparison
	Des	Aro	Lub	Org	Sat	Pain	Total	No FSD M(SD)	FSD M(SD)	t-Test t(d)
Sexual fantasies	.270^***	.357^***	.227^***	.242^***	.393^***	.134^***	.381^***	3.61(1.33)	2.70(1.41)	11.4^*** (0.68)
Foreplay	.322^***	.477^***	.337^***	.311^***	.518^***	.210^***	.505^***	4.19(0.95)	3.18(1.23)	15.0^*** (0.82)
Oral sex	.196^***	.340^***	.193^***	.288^***	.408^***	.136^***	.371^***	4.05(1.24)	3.22(1.41)	10.5^*** (0.65)
Vaginal sex	.293^***	.524^***	.354^***	.429^***	.577^***	.290^***	.585^***	4.56(0.74)	3.49(1.15)	17.1^*** (1.27)
Anal sex	.228^***	.329^***	.219^***	.265^***	.326^***	.211^***	.368^***	2.03(2.01)	1.29(1.62)	7.4^*** (0.38)
Communication	.192^***	.383^***	.218^***	.287^***	.595^***	.107^***	.422^***	4.25(1.07)	3.31(1.30)	13.1^*** (0.84)
Compatibility	.198^***	.409^***	.213^***	.292^***	.598^***	.125^***	.433^***	4.43(0.95)	3.53(1.23)	13.2^*** (0.88)

Note. Sexual satisfaction: Des = Desire; Aro = Arousal; Lub = Lubrication; Org = Orgasm; Sat = Satisfaction. FSD = Female sexual dysfunction; M = Mean; SD = Standard deviation; t = Student's t-test; d = Cohen's d effect size.

^* p < .05; ^** p < .01; ^*** p < .001.

The authors declare no competing interests.

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Psychometric evidence of the Female Sexual Function Index (FSFI) in a Chilean representative sample

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Participants

Measures

Sexual function

Female Sexual Function

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Statistical analyses

Missing data

Evidence of construct validity

Evidence of reliability

Measurement invariance

Evidence of criterion-related validity

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Structural validity

Criterion validity

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