1 Registered Measurement Report Proposal:
A Large-Scale Test of the Replicability and Generalizability of
Survey Measures in Close Relationship and Sexuality Science
Stéphanie Gauvin
Queen’s University
Kathleen E. Merwin
Dalhousie University
Chelsea D. Kilimnik
University of Texas at Austin
Jessica Maxwell
University of Auckland
John Kitchener Sakaluk
University of Victoria
Author note: This research is being supported by a SSHRC Insight Development Grant awarded to Dr. Sakaluk, a SSHRC Postdoctoral Fellowship awarded to Dr. Maxwell, an Ontario Women’s Health Scholar Award funded by the Ontario Ministry for Health and Long Term Care awarded to Stéphanie Gauvin, a CIHR Doctoral Fellowship awarded to Chelsea Kilimnik, a Joseph-Armand Bombardier Canada Graduate Scholarship funded by SSHRC awarded to Kathleen Merwin, and a Student Research Development Award from the International Academy of Sex Research, Co-Awarded to Stéphanie Gauvin and Kathleen Merwin.
2 Abstract
When measurement models are not replicable and/or generalizable, clinical assessments become of questionable utility, and unreplicable findings from studies using those measures will follow.
Inspired by recent examinations of measurement in neighboring fields of psychology, we propose a Registered Report, in order to evaluate the replicability and generalizability of 20 well- known and emerging measures assessing elements of romantic relationships and sexuality. After collecting a large sample of that is both sexually and relationally diverse, we will evaluate the taxometric structure, measurement model replicability, reliability, and generalizability of each measure across a multitude of theorized sources of noninvariance. Our results are likely to be of high value to clinical researchers and practitioners alike, as we identify which measures can produce credible assessments, while simultaneously revealing measures with limited replicability and/or generalizability, as well as relational and sexual concepts for which groups may have radically different mental constructions.
Key words: invariance; generalizability; measurement; relationships; replicability; sexuality
3 Registered Measurement Report Proposal:
A Large-Scale Test of the Replicability and Generalizability of
Survey Measures in Close Relationship and Sexuality Science
Romantic and sexual relationships are critically important forms of social relationships in adolescence and adulthood, as they confer benefits onto one’s physical health (Holt-Lunstad et al., 2010), emotional well-being (Mikulincer & Shaver, 2007), and sense of happiness and meaning in life (Diener & Seligman, 2002; Muise, Schimmack, & Impett, 2015). It is therefore unsurprising that romantic and sexual relationships have become the topics of widespread psychological scholarship (see Impett & Muise, 2018; Maxwell & McNulty, 2019; Muise,
Maxwell, & Impett, 2018), as well as targets of therapeutic intervention when they go awry (see
Binik & Hall, 2014; Mitchell et al., 2013). A considerable amount of attention has been paid, in particular, to developing psychological assessments that measure experiences in romantic and sexual relationships (e.g., Milhausen, Sakaluk, Fisher, Davis, & Yarber, 2019), which has enabled close relationships and sexuality scholars to expand their topical breadth. Yet within social (e.g., Earp & Trafimow, 2015) and more recently clinical psychology (Tackett, Brandes,
King, & Markon, 2018; Tackett et al., 2017), concerns about problematic methodological trends and the replicability of research findings are being borne out (e.g., Sakaluk, Williams, Kilshaw,
& Rhyner, 2019), and the concerns from these “parent disciplines” have also trickled down into the interdisciplinary fields of close relationship research (e.g., Campbell, Loving, & LeBel, 2014;
Joel, Eastwick, & Finkel, 2018) and sexual science (Sakaluk, 2016; Sakaluk & Graham, 2018).
Rarely mentioned and vastly underappreciated is the importance of sound psychological measurement practices as a central contributor to replicable psychological findings (Flake &
Fried, 2019; Sakaluk, 2019; Sakaluk & Fisher, 2019; Sakaluk, Kilshaw, & Fisher, 2019). As
4 Meehl and colleagues argued (1990a, 1990b), measurement is a crucial auxiliary theory for substantive theory testing in psychological research; if the auxiliary theory of measurement is in question, then doubt is cast upon the meaningfulness of whatever conclusions researchers might draw about the variables under study.
A first effort to evaluate the soundness of fifteen popular measures in social and personality psychology (Hussey & Hughes, 2018), however, invites cause for concern, as only
60% of the measures demonstrated good validity, and only 33% demonstrated a replicable factor structure. With the present Registered Report, we propose conducting a similar measurement audit to Hussey and Hughes (2018), but specifically for assessments in close relationships and sexual science, using a larger selection of measures and a broader set of criteria for evaluating candidate measures.
The Replication Crisis in Clinical, Relationship, and Sexual Science Situating
Measurement in the Replication Crisis
Psychologists are increasingly calling for greater attention to issues of measurement (e.g.,
Flake & Fried, 2019, Sakaluk, 2019, Sakaluk, Kilshaw, & Fisher, 2019). Although sometimes it goes unspoken where measurement features in the process of theory-testing, and why it is so critical to the meaningfulness of theory-testing, Meehl’s derivation of the observed conditional
(1990a, 1990b) helps to articulate the place and importance of measurement more explicitly.
Namely, widespread failures to replicate might come about not because of the usual methodological suspects (e.g., lack of transparency in original research, p-hacking, HARKing;
Nelson et al., 2018), but rather, because the effect to be replicated is based upon a lacklustre theory of and/or lackadaisical approach to measurement (Flake & Fried, 2019), thereby undermining the logical chain necessary for substantive theory-testing.
5 Although psychologists might not explicitly conceptualize the process of factor analyzing a measure’s items as generating or testing a theory of measurement, established factor structures are indeed statements of measurement theory (Borsboom, 2005) that can be corroborated or falsified, and these measurement models can be replicated or fail to replicate. Traditionally, social scientists have adopted an attitude of “Measurement, Schmeasurement” (Flake & Fried,
2019); measurement is not an issue taken seriously, as measurement models are typically investigated once or twice and never again (Sakaluk, 2019). A recent measurement-focused replicability investigation, however, suggests this collective mindset may have been deleterious for the field of social and personality psychology. Using a colossal sample size (N = 151,698),
Hussey and Hughes (2018) found that only 33% of the common measures they investigated possessed factor structures that replicated well, while only 66% had measurement models that were reasonably consistent across gender and age (i.e., factorial invariance), and only 27% possessed both a replicable measurement structure and good evidence of invariance. As the field of social psychology, in particular, continues to grapple with the mechanisms undermining the replicability of its effects, the spectre of measurement issues raised by Hussey and Hughes’s
(2018) investigation presents a chilling contender.
Measurement and Replicability in Clinical, Relationship, and Sexual Science
Replicability conversations in clinical psychology and sexual science are in their relative infancy (e.g., Sakaluk, 2016; e.g, Tackett et al., 2017). The field of close relationship science, meanwhile, has contributed early and frequently to the discussion (e.g., Campbell et al., 2014).
Still, despite differences in the visibility of replicability discussion, there is every reason to presume that measurement may be an equal (if not even more substantial) contributor or detractor to the replicability of research findings in these areas.
6 Clinical and counseling psychologists, for example, move through accredited training programs with packed curricula that leave little in the way of encouragement and/or opportunity for trainees to invest in elective statistical courses, such as in psychological measurement (Ord,
Ripley, Hook, & Erspamer, 2016). Close relationship and sexual scientists meanwhile, are beset by the training burden of an interdisciplinary science, in which they must develop competencies in multiple disciplines’ concepts, theories, and methods (Sakaluk, 2019; Wiederman & Whitley
Jr., 2001). And even should it be the case that clinical, close relationship, and sexual science are no worse for wear in terms of training in psychological measurement, it is likely that the use of psychological measures takes on a greater applied importance in these areas versus generalist psychological research. That is, clinicians working with clients presenting with relationship and/or sexual problems will depend heavily on the integrity of the assessment tools to identify client needs and track client progress—practices that will have a very real impact on the lives of those seeking clinical services.
Together, the importance of the auxiliary theory of measurement (Meehl, 1990a), concerning results from Hussey and Hughes’s (2018) measurement replicability investigation in a neighboring field, and a variety of discipline-specific considerations, render a large-scale investigation of the psychological measures in close relationship and sexual science clearly necessary. What is not as clear is which among the plethora of existing psychological measures deserves priority consideration for having its measurement model corroborated or falsified, and tested for replicability across a variety of individual and group differences.
Identifying Priority Relationship- and Sexuality-Related Measures
Within the field of relationship and sexuality science there are three interlinking areas of measurement that may be of particular interest to researchers and clinicians alike: clinical
7 sexuality, generalist sexuality, and generalist relational. Clinical sexuality includes measures commonly employed to facilitate assessment of sexual dysfunction, while generalist sexuality and relational measures examine broader aspects of how individuals interact in and perceive their sexual and romantic relationships outside of sexual functioning. Clinical guidelines (e.g., Pukall,
Gauvin, & Eccles, 2019) often recommend clinicians working in sex or relationship counselling consider all three areas in their work with clients.
Clinical sexuality. Sexual dysfunctions, as defined by the Diagnostic and Statistical
Manual of Mental Disorders (DSM-5; American Psychiatric Association, 2013) are common for both men and women (see McCabe et al., 2016, for a review). Characterized by disturbances in a person’s ability to respond sexually and/or to experience sexual pleasure, and the distress associated with these disturbances, sexual dysfunctions are often framed within the psychological and physical changes associated with the first three stages of the sexual response cycle (Masters & Johnson, 1966; Pukall, Gauvin, & Eccles, 2019). As disruptions in one stage are likely to perpetuate challenges in another, sexual dysfunctions are often comorbid, making the assessment and diagnosis process difficult for clinicians. Diagnostic tools—such as self- report measures—exist to facilitate the assessment process for clinicians. The replicability and generalizability of clinical sexuality measures is particularly important because unlike many other fields of measurement, the domain of sexual dysfunctions is one in which measures directly impact the real lives of clients vis-a-vis assessment and diagnoses, which in some countries are often necessary prerequisites for subsidized psychological and medical interventions. The assumption that measures are generalizable across diverse groups is risky as it can result in clinicians pathologizing normative sexual experiences or underdiagnosing sexual dysfunctions. Given that so many experience sexual dysfunction at some point in their lives
8 (McCabe et al., 2016), the success of interventions can only be realized if the correct individuals are assessed and diagnosed properly.
Despite their applied importance for tailoring clinical management, psychometric investigations into sexual dysfunction measures have been relatively rare, and when carried out, they have relied upon particularly modest and non-diverse samples. What is considered a
‘normal’ response at each stage of the sexual response cycle, however, as well as the patterns of distress experienced when the response is not perceived as ‘normal,’ may differ based on group membership, such as in the cases of conceptualizations of sex (Handy, Stanton, & Meston, 2018;
Horowitz & Spicer, 2013; Richters & Song, 1999), subjective experiences of arousal (Handy et al.2018), and orgasm (Blair, Cappell, & Pukall, 2017). The failure to replicate measures like these—or find that their measurement models are only valid for particular groups of individuals—would therefore suggest critical gaps in clinical assessment and treatment of sexual dysfunction.
Generalist sexual well-being. Sexual well-being is a biopsychosocial experience that goes beyond the absence of sexual dysfunction and disease (see Kismödi, Corona, Maticka-
Tyndale, Rubio-Aurioles, & Coleman, 2017), and is considered to be an important aspect of overall physical and mental health and well-being (see Diamond & Huebner, 2012). A broad suite of attitudes, beliefs, motives, and behaviors fall under this umbrella of “generalist sexual- well-being” (World Health Organization, 2006), indirectly and directly promoting positive experiences that contribute to a sense of sexual wellness (e.g., Laumann, 2006; McCabe et al.,
2010), while simultaneously reducing the likelihood of negative experiences (e.g., Auslander et al., 2007; Frederick, Lever, Gillespie, & Garcia, 2017).
9 Despite the rich body of research measuring generalist aspects of sexuality, researchers have paid little attention to how these measurement models may differ across individuals and relationships. If the psychometric properties of these measures of sexual well-being fail to generalize across a variety of contextual factors, this would put the major theories which rely upon these measures into question.
Beyond theory testing, measurement in generalist sexual wellbeing intersects with clinical sexuality as many psychological treatments are based upon the findings of studies that have used generalist sexual wellbeing measures (e.g., sexual script flexibility; Barksy, Friedman,
& Rosen, 2005, communication; Corsini-Munt et al., 2014, approach avoidance goals; Muise,
Boudreau, & Rosen, 2016). Furthermore, as outcomes like sexual pleasure and satisfaction are frequently used to evaluate treatment effectiveness (rather than sexual functioning per se) (e.g.,
Brotto & Woo, 2010; Pereira, Arias-Carrión, Machado, Nardi, & Silva, 2013), ungeneralizable measurement would call into question whether the efficacy of these treatments holds across groups/contexts.
Differences in sexual repertoires or sexual scripts of groups—which are individuals definitions of sex and how individuals engage sexually—are likely to result in differences by group membership in how individuals conceptualize their sexuality. For example, what is considered ‘normal’ or ‘taboo’, and how people communicate about sex may change as a function of cultural and relational context s (e.g., Maticka‐Tyndale et al., 2005; MacNeil &
Byers, 2005). Even definitions of what makes sex satisfying can vary by gender (McNulty and
Fisher, 2008) or sexual orientation (Mark, Garcia & Fisher, 2015).
Generalist relationships. Relationship science has examined several different aspects of romantic relationship functioning, such as the standards people hold for their partners, and how
10 couples resolve issues and communicate (for review see Finkel, Simpson, & Eastwick, 2017).
There is a growing body of work recognizing the importance of social context in shaping relationship dynamics (e.g., Campos & Kim, 2017; Karney, Kreitz, & Sweeney, 2004; McNulty,
2016; Ross, Karney, Nguyen, & Bradbury, 2018). Despite recognition that factors such as ethnicity and environmental stressors can change relationship dynamics, little research has gone into ensuring our measures are applicable across these factors (with a few notable exceptions, e.g., Gere & MacDonald, 2013). This has important practical repercussions in that couple therapists may be using these measures to assess and advise their clients when in reality these measures and related findings may not apply universally (e.g., Ross et al., 2018).
For example, some research suggests that one of the most widely investigated constructs in relationship research—attachment—does not equivalently manifest across cultures (see
Rothbaum, Weisz, Pott, Miyake, & Morelli, 2000; Wang & Mallinckrodt, 2006). Other examples of differentially constructed relationship concepts include attractiveness (e.g., Wheeler & Kim,
1997), social support (Burleson, & Mortenson, 2003), and even particular communication patterns (Ross et al., 2018). Studies examining the structure of measures of relationship quality across gender have also challenged the assumption that measures of generalist relationships hold in all contexts, with researchers finding that women and men may define relationship quality differently (e.g., Beam, Marcus, Turkheimer, & Emery, 2018; Verhofstadt, Buysse, Rosseel, &
Peene, 2006).
What Might Prompt Differential Mental Constructions of Relationships and/or Sexuality?
Even if the measurement models of our target scales are replicable in our entire sample, they may not be generalizable. That is, the measurement model for a particular scale may be reasonable for some subset of participants, but for others, important features of the measurement
11 model (e.g., which items load onto which factor(s), loading values, intercept values) may be different (i.e., noninvariant, or demonstrating differential item functioning), thereby indicating that the scale is not well-suited for particular types of statistical comparisons (see Vandenberg &
Lance, 2000).
Although traditionally researchers have labeled differences in measurement as reflecting some sort of test “bias” (e.g., Hambleton & Rogers, 1989), this understanding is not necessarily true—or may be entirely nonsensical—in a context where item responses can not be considered
“correct” or “incorrect”. Instead, systematic differences in measurement models could be understood as situated in the person, as opposed to the measure, and therefore as reflecting bona fide divergent mental constructions of intrapsychic concepts (see Sakaluk, 2019). In other words, if latent variables reflect real theoretical entities (Borboom, 2005), and measurement models capture the structure of those theoretical entities, then system differences in measurement models may actually capture how seemingly similar psychological concepts are constructed and/or manifest differently for particular groups of people.
With this social construction perspective in mind (e.g., Gergen, 1985; Hacking, 1999), we describe below several types of grouping and individual difference variables that we think are likely to reveal divergent measurement models (and thereby different social constructions) of our target relationship and sexuality scales.
Gender/sex. Interest in gender and/or sex differences in relationship and sexuality variables is considerable. The literatures of both exploratory and theory-driven tests of gender and sex differences in relationships and sexuality are massive, consisting of thousands of studies
(see Impett & Peplau, 2006; Petersen & Hyde, 2010; Schmitt, 2005), shaping both theories, (e.g.,
Buss & Schmitt; 1993, Eagly & Wood, 1999; Hyde, 2005; Simon & Gagnon, 1986),
12 methodologies (Kenny, Kashy, & Cook, 2006), and lay public perceptions (e.g., Gray, 1993).
And though van Anders (2015) aptly noted that researchers regularly ignore adequately locating potential differences in biological and/or social processes (and therefore, we use her term gender/sex to acknowledge this ambiguity), there is no denying gender/sex is one of the—if not the—most popular variables in relationship and sexual science. Should measurement models in relationship and sexual science fail to generalize across gender/sex, it would therefore pose a substantial problem to the integrity and application of these literatures.
There is reason to believe that men and women construe their romantic and sexual relationships differently (e.g., Neto, 2012). Indeed, theories describing differential patterns of evolutionary (SST; Buss & Schmitt, 1999) and/or cultural pressure (Eagly & Wood, 1999;
Wiederman, 2005) across gender/sex lead one to not only expect levels of relationship and sexuality variables to potentially differ, but also potentially the meaning of relationship and sexuality variables. Further divergences in measurement models across gender/sex in relationship (e.g., Beam et al., 2018) and sexuality variables (e.g., Carpenter, Janssen, Graham,
Vorst, & Wicherts, 2008) might be driven by differences in relational and/or sexual attention
(Rubin, Peplau, & Hill, 1981), cost/benefit appraisals (see review by Haselton & Buss, 2000), experiences (Frederick, John, Garcia, & Lloyd, 2018, Horne & Johnson, 2019), goals (Mark,
Herbenick, Fortenberry, Sanders, & Reece, 2014), identity (see review by Impett & Peplau,
2006), or needs (Fisher, Moore, & Pittenger, 2012).
Sexual orientation and relationship composition. In contrast to research on gender/sex differences, there is a dearth of research examining differences across sexual orientation as research has historically excluded LGBTQ* participants (e.g., Andersen & Zou, 2015). Further, the little research that exists has sometimes neglected the fact that sexual orientation (i.e., sexual
13 minority versus not) and the composition of a sexual relationship (i.e., same- versus mixed- gender) do not always align (e.g., bisexual individuals in mixed-sex relationships). Indeed, the way researchers classify participants’ sexual orientation matters as the pattern of associations between sexual orientation and health outcome measures differed when researchers grouped participants by sexual identity, behavior, or attraction (Lindley, Walsemann, & Carter, 2012).
Within the limited sexuality research comparing individuals based on sexual orientation or relationship composition (i.e., gender of partner versus sexual orientation identity, monogamy and partner number), findings are mixed. Some research has found differences across majority and minority groups based on relationship composition (e.g., satisfaction with specific sexual activities, orgasm frequency; Blair et al., 2018) or orientation (e.g., orgasm frequency in women;
Garcia, Lloyd, Wallen, & Fisher, 2014), with others finding no differences (e.g., Holmberg &
Blair, 2009) across relationship composition or orientation (e.g., orgasm frequency in men;
Garcia et al., 2014). To our knowledge, none of these studies have examined whether the measures used are reliable or invariant across diverse relationships, which may contribute to the mixed pattern of results.
Sexual minorities are also likely to have different experiences with internal and external forms of stigma, which can influence the experiences and conceptualizations of sexuality and relationships and relate to lower sexual and relational well-being (e.g., Doyle & Molix, 2015;
Frost & Meyer, 2009). Given that sources of information for sexuality often focus on the heteronormative (e.g., Carpenter, 1998; Seabrook et al., 2016), individuals in same-gender relationships may not have set expectations for sexual interactions, which may allow them to have more flexible scripts (e.g., the type or number of sexual activities included; Horowitz &
Spicer, 2013; Richters & Song, 1999, expectations on length of sexual interactions; Blair &
14 Pukal, 2014), and construct what it means to be sexually satisfied in more nuanced ways (e.g.,
McClelland, 2010).
Relationship landscape (status, configuration, length). Not only can an individual’s gender and sexual orientation affect how they respond to relationship and sexuality measures, but so too can factors of the relationship itself. For example, knowing whether measures are comparable across relationship status (single vs. in a relationship) is critical, given researchers sometimes ask single individuals to respond to scales using retrospective or hypothetical future romantic relationships (e.g., Harris, 2002; Sprecher, Felmlee, Metts, Fehr, & Vanni, 1998).
Further, findings that sex in the context of committed relationships affords greater benefits than when single (Armstrong England, & Fogarty, 2012; Herbenick et al., 2010) and greater personal well-being (Muise et al., 2016), might suggest that there are important relationship status differences in the conceptualizatins of sex. Two recent studies also support this possibility, as both the Fear of Being Single Scale (Cantarella, Spielmann, MacDonald, Joel, & Impett, in prep) and the Sexual Motivations Scale (Jarden, Garey, & Zvolensky, 2017) yielded divergent measurement parameters for single and romantically attached participants.
Relationship length is another important factor that may affect individuals’ interpretation of measures. Commitment (a potential proxy for relationship length), for example, plays a role in individuals’ perceptions of important mate characteristics to relationship quality (e.g., Neff &
Karney, 2003). Components of relationship quality (e.g., Fletcher, Simpson, & Thomas, 2000) could therefore be weighted differently as relationships progress and become more committed.
Relationship length can also alter how one thinks about and flexibly defines sexuality-related concepts, including reducing importance of penetration in sexuality (Hinchliff & Gott, 2004) and intercourse for love (O’leary et al., 2012) in long-term relationships.
15 Other relational factors—such as level of romantic and sexual exclusivity—could also meaningfully alter the conceptualization of relationship concepts. Consider the example of romantic jealousy: those involved in consensually non-monogamous (CNM) relationships tend to manage jealousy better (e.g., de Visser & McDonald, 2010) and construe romantic jealousy differently than those in monogamous relationships (Ritchie & Barker, 2006). Taken together, these findings highlight the possibility that characteristics of one’s relationship (or lack thereof) may alter an individual’s understandings of relational and sexual constructs.
Developmental trajectories (e.g., adulthood, major milestones, and aging). Sexuality and relationships are lifelong processes which change in tandem with life transitions and milestones, such as moving into adulthood, marriage, parenthood, and aging. These changes can be additive such that experiences during earlier life stages may influence behaviours and beliefs at later stages. Understanding how sexuality and relationship constructs may shift across the lifespan is key to developmentally situating assessments of these constructs in both clinical practice and developmental theory.
Emerging adulthood, for example, is an oft-discussed period of transition, wherein multiple facets of identity are in flux (Arnett, 1998, 2000, 2004; Schwartz, Côté, & Arnett,
2005), frameworks for sexuality and relationships are learned through experimentation (e.g.,
Bandura, 1977), and many ‘firsts’ are experienced (e.g., virginity loss, long-term relationship, living with a partner, marriage). Challenges to measurement during this time are highlighted with the example of ‘virginity loss’, where definitions and frameworks (e.g., virginity as a gift, rite of passage) both vary across individual characteristics (e.g., sexual orientation and gender;
Carpenter, 2001) and shape choice of partner, safer sex practices, satisfaction, and impact on life
(Carpenter, 2001; Humphreys, 2013). During emerging adulthood, gaining experience with
16 sexuality and long-term relationships fosters comfort with testing a range of sexual activities
(Kaestle & Halpern, 2007; Laumann et al., 1994) thus allowing individuals to consider broader definitions and expectations for sexuality (Carpenter, 2010; McCabe, Tanner, & Heiman, 2010;
Simon & Gagnon, 1986). Given the instability of relationships and sexuality during this time of experimentation, it is not implausible—if not likely—that mental representations and therefore measurement models would also be unstable at this time.
Shifts in measurement stability may also occur as physical and physiological changes across the lifespan influence conceptualizations of sexual functioning as the reference point of
‘normal’ changes. Pregnancy, childbirth, and the transition to parenthood each present challenges to sexuality and relationships with many physical and psychological changes during these periods (Bartellas, Crane, Daley, Bennett, & Hutchens, 2000; Galazka, Drosdzol-Cop,
Naworska, Czajkowska, Skrzypulec‐Plint, 2015; Pauleta, Pereira, Graça, 2010; Pauls, Occhino,
Dryfhout, 2008). Navigating these changes—which are often accompanied by decreases in sexual desire, frequency, and satisfaction (e.g., Rosen, Bailey, & Muise, 2018)—may alter how parents conceptualize their sexuality as sexuality becomes renegotiated through redefining roles and experimentation and rediscovering pleasure postpartum (Gauvin, Pukall, 2018; Muise et al.,
2017; Rosen et al.,, 2018).
When considering the physiological and relationship changes that occur over the lifespan, life stage (i.e., age) may also need to be considered when thinking about how individuals conceptualize and navigate their sexuality. Recently, calls for tailoring clinical management of erectile dysfunction (ED) according to age have emerged after differences by age group for intercourse-specific and overall sexual satisfaction were found after controlling for the degree of
ED (Capogrosso et al., 2019). These differences in satisfaction across age groups, however, are
17 difficult to interpret as differences in measurement could be reflecting differences in how satisfaction is constructed as older individuals tending to conceptualize sexual satisfaction in terms of quality rather than quantity (McCarthy, 2001). Changes in experiences with aging may also intersect with other aspects of identity (e.g., responses to menopause differ across race, ethnicity, social class, and relationship characteristics; Avis et al., 2001; Avis et al., 2004).
Sexual/relational experience (consensual and non-consensual). Although related to some of the previously discussed potential sources of noninvariance, histories of nonconsensual sexual experiences (NSEs) may prove to be a uniquely powerful force in shaping constructions of sexuality and relational schemas (Kilimnik, Boyd, Stanton, & Meston, 2018). For example, individuals whose first experiences with sexuality were nonconsensual may begin schema development with sexual traumatization, stigmatization, and feelings of shame, betrayal, and powerlessness (Finkelhor & Browne, 1985). Indeed, recent research examining women with and without NSEs supports this possibility, as NSE history status and the age of NSE onset relative to sexual development played a role in how measures of sexuality contributed to an overall latent variable of sexual well-being (Kilimnik & Meston, 2018).
Failing to examine the role of NSE histories in the validity of measurement tools leaves significant room for error in how these constructs may differ for this population. This may result in inaccurate inferences about the decrements in the psychosexual well-being of individuals with
NSE histories, and thus, compromise the development of appropriate interventions and the assessment of treatment efficacy. Continuing to examine the outcomes of NSEs on an assumption that the constructs are similar across those with and without these experiences is doing a disservice to this potentially vulnerable population. As such, NSE histories are important
18 considerations in the assessment of sexual health and relational well-being and, thus, the measurement tools for these constructs.
The Present Registered Measurement Report
The subfields of close relationship and sexual science have seen an explosion in the number of measures that are available for use in research and clinical practice (e.g., Milhausen,
Sakaluk, Fisher, Davis, & Yarber, 2019). Yet the dialogue surrounding replicability concerns in these fields (Campbell, Loving, & LeBel, 2014; Sakaluk, 2016) and clinical science (e.g.,
Tackett & Miller, 2019; Tacket et al., 2017), as well as the increasing recognition of the role of measurement in replicability (e.g., Flake & Fried, 2019; Hussey & Hughes, 2018), provides motivation for a critical investigation of the state of measurement in close relationship and sexual science. Indeed, researchers and clinicians in these areas must remain informed about the replicability and generalizability of their assessment tools. Scales with measurement models that are not replicable (e.g., Hussey & Hughes, 2018) will contribute to unreplicable literatures of substantive effects (e.g., Open Science Collaboration, 2015); scales that are not generalizable, meanwhile, will only yield replicable research findings for prilleged groups (Henrich, Heine, &
Norenzayan, 2010), and will be uninformative—or potentially iatrogenic—for clinical practice with members of sexual and/or relational groups for whom the measurement model does not reflect their experiences (e.g., Schechinger, Sakaluk, & Moors, 2018).
Following from—and expanding upon—the example of Hussey and Hughes (2018), we propose to conduct a large-scale analysis of the replicability and generalizability of several popular measures in the close relationships and sexual science. Our selection of measures and sampling plan mutually informed one another, as we sought out measures that were widely used in scientific and/or clinical work for which we could provide a more appreciably precise test (i.e.,
19 with a superficially larger sample) of replicability and generalizability than what the original authors of these scales were able to accommodate. As in Hussey and Hughes (2018), we propose calculating reliability for each measure (and sub-scale), and well as performing a confirmatory test of the measure’s established factor structure.
Additionally, however, we also propose to also conduct an analysis of each measures latent structure via taxometric analyses (Ruscio, Haslam, & Ruscio, 2006). Although often unappreciated in close relationship and sexual science (Sakaluk, 2019), replicability and generalizability of a given measure would immediately be called into question if a measurement model of what had been assumed to be a (series of) continuous latent dimension(s) instead better supported a set of discrete latent categories. Secondly, we propose testing the variability of measurement models across a much wider range of individual differences than just gender and age (as in Hussey & Hughes, 2018; see our previous selection of variables that might prompt different mental constructions), and whenever possible calculating a standardized metric of the magnitude of which measurement models diverge (Nye & Drasgow, 2011).
Proposed Methods
Our proposed sample size, sample composition, exclusions, and all measures are described below and in greater detail in our Supplemental Materials. All of our current materials are—and future data and materials will be made—available on our OSF Project for this registered report (https://osf.io/w23cy/).
Proposed Sample and Procedure
Participants will be n = 1000 heterosexual monogamously-oriented individuals and n =
250 LGBTQ individuals, both recruited from a Prolific panel, and n = 250 consensually non- monogamous individuals recruited via targeted advertising through community organizations
20 and websites. We have selected these sampling targets because together, they exceed general heuristics for recommended minimum sample sizes for taxometrics, latent variable modeling, and invariance testing (see Sakaluk, 2019 for a review). But perhaps more importantly, our target sample size will be considerably larger than the vast majority of samples used to develop and test the measures we have selected in their original publication(s) (see Table 1). We therefore consider our sampling plan as both meeting current standards of methodological rigour in latent variable modeling and expectations for performing good-faith high-powered tests of replicability
(e.g., Cheung et al., 2016).
Branching Question. As some of the sexual functioning measures employed in the current study are designed based on participant genitalia, to appropriately branch participants to the relevant measures (see Figure 1) we will also ask participants to select which of two options
(“Penis, strapless, or girl penis”or “Vagina or front hole”) best represents the genitalia they currently have. We also provide an open-ended textbox for participants to elaborate if these two options are not representative for them. If a participants response in the open-ended textbox reflects that the participant was branched incorrectly, their data for sexual functioning will be removed. Further, when relevant, participants who are in a current relationship will respond to measures with respect to their current partner, whereas individuals who are currently single will respond based on their most recent partner.
Proposed Measures
Target measures. We selected a total of 20 measures, based on emerging and pre- existing measures of relevance and influence in clinical and research in the fields of clinical sexuality, generalist sexuality, and generalist relationship. The order of the 20 measures will be
21 randomized across participants. Brief overviews of the selected measures are displayed in Table
1, with detailed descriptions presented in the Supplemental Materials.
Potential sources of noninvariance. Mapping onto our literature review, we examine potential sources of noninvariance across the following domains: gender/sex (including current gender and sex assigned at birth; Bauer, Braimoh, Scheim, & Dharma, 2017, and current genitalia), sexual orientation and relationship composition (including sexual orientation, current partners gender, number of same-sex/other-sex sexual experiences), relationship landscape
(including relationship status, relationship length, and relationship structure; Schechinger,
Sakaluk, & Moors, 2018), developmental trajectories (including age, number of sexual/romantic partners, pregnancy/pariety status), and sexual/relational experiences (including age of sexual debut, nonconsensual sexual experiences). Full details for details of these measures are included in our supplemental materials.
Proposed Analytic Plan
As in Hussey and Hughes (2018), we propose appraising the replicability and generalizability of our candidate measures using multiple indexes. All of our analyses will be conducted in R (R Core Team, 2019) and our data, materials, and analytic scripts will be made openly available on the Open Science Framework to ensure reproducibility and verification of our work (sample scripts for the RR Stage 1 are available in our OSF Project).
Confirming taxometric structure. We will first appraise the latent structure of our candidate measures using taxometric analyses (Ruscio et al., 2006); this is a necessary first step as the remaining proposed analyses are only defensible for a given candidate measure if a dimensional structure is supported, as the remaining analyses presume a dimensional structure.
22 We will therefore only continue with the subsequent analytic steps for a given measure if taxometric analysis supports a dimensional structure for the measure.
One of the most crucial initial steps in taxometric analysis is the selection of indicator variables; a small number (5 or fewer, see Ruscio 2018, as cited in Sakaluk, 2019) of non- redundant items is needed to optimize the informativeness of taxometric analysis. As most of our candidate measures contain more items than this modest threshold, we will therefore repeat our taxometric analysis on three random samples (without replacement) of 5 indicator variables per measure, and note if there are discrepancies.
In lieu of relying on more subjectively determined elements of taxometric analysis (i.e., plausible taxon base-rates), we will evaluate all measures latent structure using comparative curve fit index (CCFI) profiles (see Ruscio, Carney, Dever, Pliskin, & Wang, 2018), examining average CCFIs across taxon base-rates of 2.5% to 97.5%. We will report average CCFIs from the three most popularly reported methods, including means above and below a cut (MAMBAC), maximum eigenvalues (MAXEIG), and latent mode (L-MODE), with average CCFIs < .45 providing support for dimensional structure, CCFIs > .55 providing support for categorical structure, and .45 < CCFIs < .55 providing ambiguous evidence (Ruscio et al., 2006; Sakaluk,
2018), noting when there are discrepancies. All taxometric analyses will be conducted using the
RTaxometrics() package (Ruscio & Wang, 2017).
Confirming measurement model. If a given candidate measure yields a dimensional structure, we will then proceed to fit a confirmatory factor analysis (CFA) model of the measurement model specified by the original authors of the measure (Beaujean, 2014). All CFA models will be fit using the lavaan() package (Rosseel, 2012), with robust maximum-likelihood estimation (MLR) if a candidate measure’s response scale contains more than four response
23 options, and a categorical estimator (ULS) if the response scale contains four or fewer response options (Rhemtulla, Brosseau-Liard, & Savalei, 2012); missing data will be handled using full- information maximum-likelihood (FIML), when possible. We will use the marker-variable method of scale-setting and model identification, as we are interested in measurement parameters, and scale-setting methods do not impact model fit.
We will then appraise the fit of a given measurement model using both the RMSEA and
CFI (Hu & Bentler, 1999). However, given the growing recognition of how model fit cut-offs are sensitive to model reliability, we will calibrate our interpretation based on the standardized loadings in a given model (see McNeish, An, & Hancock, 2018). Specifically, for median standardized loadings similar to Hu and Bentler (1999) (λ = .70), we will use the traditional cutoffs for our indexes (RMSEA < .06; CFI >.95); however, as recommended by McNiesh et al.,
(2018), we will use more lenient cutoffs if median standardized loadings are appreciably higher
(λ = .90: RMSEA < .20; CFI > .775) and more stringent cutoffs if median standardized loadings are appreciable lower (λ = .40: RMSEA < .02, CFI > .975).
Reliability. We will then appraise the general reliability of our candidate measures, estimating reliability at scale and/or sub-scale level(s), depending on how the original authors suggested the scale ought to be scored. Given the innumerous and often ignored criticisms of the coefficient α for estimating reliability (see McNeish, 2018 for a review), we will primarily rely upon Hussey and Hughes’s (2018) strategy of estimating and reporting ɷt and ɷh, which provide the proportion of variance not attributable to measurement error and the proportion of variance attributable to the primary factor of a set of indicators, respectively. Estimates of ɷt and ɷh will be calculated using the semTools::reliability() function (Jorgensen, Pornprasertmanit,
Schoemann, & Rosseel, 2018), based on the fitted CFA models. We propose following Hussey
24 and Hughes (2018), using a cutoff of ɷt >.70, and then using ɷh to provide greater context about researchers’ assumptions that a given factor is unidimensional. However, we will also calculate and report ɑ, in order to provide a more direct comparison of reliability estimates between original measurement studies and our new sample.
Testing (in)variability in measurement. Finally, we will test the generalizability of our measurement models. We will use multi-group CFA models for evaluating measurement invariance across categorical variables (e.g., sexual orientation) that may drive different constructions of relationship and sexuality variables, and multiple-indicator multiple-cause
(MIMIC) models of differential item function for continuous variables (e.g., number of sexual partners) that may drive different constructions of relationship and sexuality variables (see
Sakaluk, 2019, for a review of these methods).
Multi-group CFA. Multi-group CFA models will be fit using the same selection of estimation, scale-setting, missing data methods, and fit indexes as described in the Confirmatory measurement modeling section. We will evaluate configural invariance (i.e., the same general pattern of items loading onto factors), loading invariance, and intercept invariance using the permutation randomization method (Jorgensen, Kite, Chen, & Short, 2018; Kite, Jorgensen, &
Chen, 2018) via the semTools::permuteMeasEq() function. Further, we will calculate and report the median estimate and range of a standardized effect sizes of noninvariance—dMACS (see Nye
& Drasgow, 2011)—for each item of a factor, in order to provide the context for the extent of any potential noninvariance.
MIMIC models of DIF. MIMC models of DIF will be fit using the same selection of estimation, scale-setting, missing data methods, and fit indexes as described in the Confirmatory measurement modeling section, and as with the multi-group CFA analyses, we will evaluate the
25 presence of DIF using the permutation randomization method (Jorgensen et al., 2018). However, in order to adequately model non-uniform DIF (i.e., loading noninvariance), we will need to additionally specify a latent interaction term between a given DIF covariate (e.g., number of sexual partners) and a given latent variable (e.g., sexual satisfaction); indicators for this latent interaction term will be created using the double-mean-centered product indicators approach (see
Sakaluk, 2019, for an overview of this approach to MIMIC model testing of DIF).
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1
Table 1
Summary of Measures Included in the Present Study
Scale Citation Subscales (number of Items) Rating Scale Orig. Dev.
Study n’s
Clinical Sexuality
Female Sexual Distress Scale—Revised Derogatis et al., 2008 Total (13) 5-point 78-296
Female Sexual Function Index —Revised Boehmer et al., 2012 Total (19) 5-point 128-170 for sexual minority women Desire (2)
Arousal (4)
Lubrication (4)
Orgasm (3)
Satisfaction (3)
Pain (3)
2
International Index of Erectile Functioning Rosen et al., 1997 Total (15) 5-point 130-148
Erectile function (6)
Orgasmic function (2)
Sexual desire (2)
Intercourse satisfaction (2)
Overall Satisfaction (2)
International Index of Erectile Functioning Coyne et al., 2010 Total (14) 5-point 486 for Men who Have Sex With Men Erectile function (7)
Orgasmic function (2)
Sexual desire (2)
Intercourse Satisfaction (2)
Overall Satisfaction (1)
Sexual Functioning Questionnaire Renaud & Byers, 2001 Total (8) 5-point 307
3
Sexual Desire Inventory-2 Spector et al., 1996 Total (14) 8-point, 300
Dyadic sexual desire (8) 9-point Solitary sexual desire (3)
Sexual Excitation/Sexual Inhibition — Short Milhausen et al., 2010 Total (30) 4-point 481
Form for Women/Men Inhibitory cognitions (8)
Relationship importance (5)
Arousability (5)
Partner characteristics and
behaviors (5)
Setting (4)
Dyadic elements of the
sexual interaction (3)
Sexual Sensation Seeking Scale Kalichman et al., 1994 Total (10) 4-point 106-296
4
Sexual Compulsivity Scale Kalichman et al., 1994 Total (10) 4-point 102-296
Generalist Sexuality
Global Measure of Sexual Satisfaction Lawrance & Byers, 1995 Total (5) 7-point 90
New Sexual Satisfaction Scale Štulhofer et al., 2010 Total (20) 5-point 212-729
Ego-focused (10)
Partner- and sexual activity-
centred (10)
Sexual Communal Strength Scale Muise, Impett, For Having Sex (6) 5-point 44 dyads -
Desmarais, & Kogan, For Not Having Sex (4) 193 2013; Muise, Kim, individuals Impett, & Rosen, 2017
5
Verbal and Non-Verbal Sexual Santos-Iglesias & Byers, Total (28) 7-point 184-216
Communication Scale 2018 Verbal sexual
communication (13)
Nonverbal sexual initiation
and pleasure (8)
Nonverbal sexual refusal (7)
Barriers to Sexual Communication - Short Rehman et al., 2018 Total (20) 5-point 229
Form Threat to partner (7)
Threat to self (7)
Threat to relationship (6)
SexTalk Jonason et al., 2016 Total (20) 5-point 238-303
Individualistic (16)
Mutualistic (4)
6
SexFlex Scale Gauvin & Pukall, 2018 Total (6) 4-point 468-483
Implicit Theories of Sexuality Scale Maxwell et al., 2017 Total (10) 7-point 308-456
Sexual destiny (5)
Sexual growth (5)
Approach and Avoidance Goals for Sex Impett & Muise; personal Total (21) 7-point 121
communication; Impett, Self-focused approach goals
Peplau, & Gable, 2005; (5)
Partner-focused approach
goals (6)
Self-focused avoidance
goals (4)
Partner-focused avoidance
goals (6)
7
Generalist Relational
Dyadic Adjustment Scale Spanier, 1976 Total (32) 2-point, 218
Dyadic consensus (13) 5-point,
Dyadic satisfaction (10) 6-point,
Dyadic cohesion (5) 7-point
Affectional expression (4)
Perceived Relationship Quality Inventory Fletcher, Simpson, & Total (18) 7-point 100-200
Thomas, 2000 Satisfaction (3)
Commitment (3)
Intimacy (3)
Trust (3)
Passion (3)
Love (3)
1
Figure 1. Survey Flow Contingency for Sexual Functioning Measures.
2 Supplemental Materials: Proposed Measures
Clinical Sexuality
Female Sexual Distress Scale-Revised (FSDS-R). We will use the Female Sexual
Distress Scale-Revised (FSDS-R; Derogatis, Clayton, Lewis-D’Agostino, Wunderlich, & Fu,
2008) to assess sexual distress in all participants, regardless of gender/sex, as it was recently validated for men (Santos-Iglesias, Mohamed, Danko, & Walker, 2018). The FSDS-R consists of
13 items (e.g., How often do you feel stressed about sex?) that participants will rate on a 5-point
Likert scale, with higher scores indicating greater sexual distress. In the development of the original FSDS (Derogatis, Rosen, Leiblum, Burnett, & Heiman, 2002) researchers conducted three studies to develop and validate the measure using principal component analysis. Study 1 started with a 20-item ‘prototype’ measure and used a principal component analysis to yield the unidimensional factor structure (consisting of 12 items) on a sample of 78 women (60 control; 18 with a variety of sexual dysfunctions), the majority of whom were white and married. Study 2 used a principal component analysis to yield the unidimensional factor structure (consisting of 13 items) on a sample of 174 women with Female Sexual Arousal Disorder (FSAD), the majority of whom were white and married. Study 3 started with a 12-item measure (from Study 1) and used a principal components analysis and replicated the single factor structure using a sample of 145 women diagnosed with hypoactive sexual desire disorder (HSDD; consisting of surgically menopausal women and naturally menopausal women) and 102 women in an age-matched comparison group (consisting of both pre- and post-menopausal women). The unidimensional structure of the Dutch version of the original 12-item FSDS was supported using a principal component analysis with a sample of 324 heterosexual women (234 with a sexual dysfunction and 108 in control group; Ter Kuile, Brauer, & Laan, 2006).
3 The FSDS-R is a 13-item revised version of the FSDS that includes one additional item asking participants to rate their level of distress related to low sexual desire (i.e., “Are you bothered by low sexual desire?”; Derogatis et al., 2008). The FSDS-R was validated in a sample of 296 women with hypoactive sexual desire disorder (n = 136), another female sexual dysfunction (n = 48) or no female sexual dysfunction (n = 75). The one-factor structure was replicated with Polish (Nowosielski, Wróbel, Sioma-Markowska, & Poręba, 2013), Persian
(Ghassami, Asghari, Shaeeri, Soltaninejad, & Safarinejad, 2014; Nekoo et al., 2014), and
Turkish (Aydin, Onaran, Topalan, Aydin, & Dansuk, 2016) versions of the scale. Using confirmatory factor analysis, the one-factor structure of the FSDS-R was also supported with a sample of 127 men with sexual dysfunctions and 267 control men (Santos-Iglesias et al., 2018).
Using an additional sample of 188 women with sexual dysfunctions and 155 control women,
Santos-Iglesias et al. (2018) found that the factor structure was invariant across gender and sexual function status. The majority of men and women in the study by Santos-Iglesias et al.
(2018) were heterosexual/straight, white/caucasian, in a romantic relationship, and sexually active.
Female Sexual Function Index for sexual minority women (FSFI-SMW). We will use the Female Sexual Function Index for sexual minority women (FSFI-SMW; Boehmer, Timm,
Ozonoff, & Potter, 2012) to assess sexual functioning for participants who indicate on the genitalia branching question that they have a vagina/front hole regardless of who they engage in sexual behaviour with. The FSFI-SMW retains the items and response sets of the original FSFI
(Rosen et al., 2000) but uses ‘vaginal penetration’ instead of ‘intercourse’ to be inclusive to all women regardless of the gender/sex of their sexual partner(s). The FSFI-SMW is a 19-item measure assessing the sexual functioning of women in the past four weeks across the six
4 domains of: across six domains, including: desire (2 items, e.g., “How would you rate your level
(degree) of sexual desire or interest?”), arousal (4 items, e.g., “How often did you feel sexual aroused (turned on) during sexual activity or intercourse?”), lubrication (4 items, e.g., “How difficult was it to become lubricated (wet) during sexual activity or intercourse?”), orgasm (3 items, e.g., “When you had sexual stimulation or intercourse, how difficult was it for you to reach orgasm?”), satisfaction (3 items, e.g., “How satisfied have you been with your overall sexual life?”), and pain (3 items, e.g., “How would your rate your level (degree) of discomfort or pain during or following vaginal penetration?”; Rosen et al., 2000). Participants respond to the items on a 5-point Likert scale (ranging from: 1 = Almost never or never; Very low or none at all; Almost never or never; Very low or no confidence; Extremely difficult or impossible; Very dissatisfied; to 5 = Almost always or always; Very high; Very high confidence; Not difficult; Very satisfied). Fifteen of the items also include a zero category (Did not attempt vaginal penetration or No sexual activity) that is not included as the low end of the scale but is an option for individuals who were not sexually active in the past four weeks (Meyer-Bahlburg & Dolezal,
2007). While the authors of the FSFI-SMW (n = 170) did not assess the structure of the measure, they implemented the six component model suggested by the original FSFI. In the development of the original FSFI, researchers used a principal components analysis of the 19 items with a sample of 128 women with female sexual arousal disorder and 131 age-matched comparison women (Rosen et al., 2000). The results suggested a five component solution (combining the arousal and desire domains), but the authors opted for a six component solution based on clinical considerations of the diagnostic relevance of a distinction between arousal and desire. Research on the structure of the FSFI using confirmatory factor analyses with samples of both sexually active (n = 389) and sexually inactive (n = 119) women, found that while the six factor structure
5 held with only sexually active women’s data in the analysis, the distinct factors explained minimal variance when sexually inactive women were included (Hevesi, Mészáros, Kövi, Márki,
& Szabó, 2017). Instead, a single latent factor of sexual functioning better explained the variance of the model when including both samples of women.
International Index of Erectile Function (IIEF). We will use the International Index of
Erectile Function (IIEF; Rosen et al., 1997) to assess sexual functioning for participants who indicate on the genitalia branching question that they have as penis/strapless/girl dick and report engaging in sexual behaviour with a female partner. The IIEF consists of 15 items that assess five domains of male sexual functioning over the past four weeks: erectile function (6 items; e.g.,
“How often were you able to get an erection during sexual activity?”), orgasmic function (2 items; e.g., “When you had sexual stimulation or intercourse, how often did you ejaculate?”), sexual desire (2 items; e.g., “How would you rate your level of sexual desire?”), intercourse satisfaction (2 items; e.g., “When you attempted sexual intercourse, how often was it satisfactory for you?”), and overall satisfaction (2 items; e.g., “How satisfied have you been with your overall sex life?”). Items are rated on 5-point Likert scales (ranging from 1 = Almost never or never; Extremely difficult; One or two attempts; No enjoyment at all; Very low or none at all;
Very dissatisfied to 5 = Almost always or always; Not Difficult; Eleven or more attempts; Very highly enjoyable; Very high; Very satisfied). Nine of the items also include a zero category that is not included in the calculation of sexual functioning scores, but reflect an option for participants who did not attempt sexual activity in the past four weeks (Yule, Davison, & Brotto,
2011). Higher scores reflect better sexual functioning. Researchers used a principal components analysis to yield the five component structure on a sample of 148 men with erectile dysfunction and 130 men in an age-matched comparison group (Rosen et al., 1997). A principal component
6 analysis of the Portugese version of the IIEF suggested a two-component model, but confirmatory factor analyses of both the two- and five-factor structures provided better support for the five-factor structure (Gomes & Nobre, 2012). Confirmatory factor analyses assessing four different models of the German version of the IIEF, however, also found that the five-factor solution had the best fit but indicated that a four-factor model resulted in good model fit as well
(Kriston, Günzler, Harms, & Berner, 2008). Yet, other research using principal components analyses have suggested two component (Malay version; Lim et al., 2003; Wiltnick, Hauck,
Phadayanon, Weidner, & Beutel, 2003) and four component structures (German version;
Kriston, Günzler, Harms, & Berner, 2008).
International Index of Erectile Functioning for men who have sex with men (IIEF-
MSM). The International Index of Erectile functioning for men who have sex with men (IIEF-
MSM; Coyne et al., 2010) is a modified version of the original IIEF (Rosen et al., 1997), which was developed and validated for use with HIV-positive men who have sex with men (Coyne et al., 2010). We use the IIEF-MSM to assess the sexual functioning of participants who indicate on the genitalia branching question that they have as penis/strapless/girl dick and report engaging in sexual behaviour with a male partner. The 14-item measure assesses men’s sexual functioning over the past four weeks across five domains including: erectile function (7 items, e.g., “How often were able to get an erection during sexual activity?”), orgasmic function (2 items, e.g.,
“When you had sexual stimulation or intercourse, how often did you ejaculate?”), sexual desire
(2 items, e.g., “How would you rate your level of sexual desire?”), intercourse satisfaction (2 items, e.g., “How much have you enjoyed sexual intercourse or other sexual activity?”), and overall satisfaction (1 item, e.g., “How satisfied have you been with your overall sex life?”).
Participants respond to the items on 5-point Likert scales (ranging from 1 = Almost never or
7 never; Extremely difficult to 5 = Almost always or always; Not Difficult), with higher scores reflecting greater sexual dysfunction. Ten of the items also used an additional zero category in the response scale that is not included in the calculation of sexual functioning scores, but reflect an option for participants who did not attempt sexual activity in the past four weeks. Participants will be asked two additional questions based on their sexual activity in the past four weeks with respect to insertive anal sex or receptive (e.g., “Have you had, or attempted to have, receptive anal intercourse?”), however, these questions will not be used to branch participants and participants will receive all scale items. To reflect changes in inclusive language since the original publication of the MSM version (Coyne et al., 2010) we have also changed the wording of active and passive intercourse to insertive and receptive, respectively. Finally, changes to the original IIEF in the IIEF-MSM version have been reverted back to the original version (e.g.,
“intercourse or other sexual activity” to “intercourse”; and “regular partner” to “partner”).
We have adopted this assessment strategy (i.e., retain the original authors item content, as best we can) so as to enable us to perform a good faith test of the replicability and generalizability of the measure, as originally proposed. We recognize the potential for this assessment strategy to reveal that some item content is (as we anticipate in some cases) ungeneralizable and therefore in need of revision. These items are not included in the measure’s structure or scoring. We are adopting the more conservative language of the In. ADD language change . The measure was developed using a principal components analysis with a sample of 486 MSM presenting for routine HIV care at various HIV treatment clinics across Europe. The results of the analysis indicated a four component solution but authors chose to retain a five component solution to be consistent with the original IIEF (Coyne et al., 2010).
8 Sexual Functioning Questionnaire (SFQ). We will use the Sexual Functioning
Questionnaire (SFQ; Lawrance & Byers, 1992; MacNeil & Byers, 1997; Renaud & Byers, 2001) to assess the frequency and severity of sexual problems or concerns. The measure consists of eight items assessing ‘typical’ areas of sexual functioning (i.e., unable to relax during sex, not interested in sex, feeling turned off, difficulty with sexual arousal, difficulty with sexual excitement, reaching orgasm too quickly, unable to reach orgasm, taking too long to orgasm), as well as two additional items assessing discrepancy in sexual preferences (i.e., “A sexual partner did not want to do sexual things that I wanted to do”, “A sexual partner asked me to do sexual things that I do not like to do”). Participants will indicate the frequency with which they have experienced each of the sexual problems in the past year on a 5-point Likert scale (0 = Never; to
4 = Always). Although the SFQ is used in research across a variety of contexts (e.g., autism;
Byers, Nichols, Voyer, & Reilly, 2013, herpes and human papillomavirus; Foster & Byers, 2013,
Older adults; Santos-Iglesias, Byers, & Moglia, sexual difficulties; Fallis, Purdon, & Rehman,
2013), research investigating the psychometric properties of the scale have been limited to reporting Cronbach’s alphas, with no published evaluation of the scales structure (e.g., MacNeil
& Byers, 1997; Lawrance & Byers, 1992; Renaud & Byers, 2001).
Sexual Desire Inventory-2 (SDI-2). We will use the Sexual Desire Inventory-2 (SDI-2;
Spector, Carey, & Steinberg, 1996) to assess sexual desire for all participants. The scale consists of 14 items that are split between two subscales; Dyadic Sexual Desire (e.g., “When you first see an attractive person, how strong is your sexual desire?”; 8 items) and Solitary Sexual Desire
(e.g., “ How strong is your desire to engage in sexual behavior by yourself”; 3 items), with three of the 14 items not included in either subscale. Scale anchors vary across the items, higher items related to frequency will be rated on a 8-point scale (e.g., 1 = Not at all to 8 = Many times a day)
9 and strength items will be rated on a 9-point scale (e.g., 0 = No desire to 8 = Strong desire). The
SDI-2 was developed using a factor analysis on data from 380 participants (Spector, et al., 1996), and was further validated with older adults (Spector & Fremeth, 1996; N = 40) and with dyads
(Spector & Davies, 1995 cited in Spector, Carey, & Steinberg, 2019; N = 40).. The two-factor structure of the SDI-2 was confirmed using confirmatory factor analysis using the Spanish version in a sample of 608 Spanish individuals (Ortega, Zubeidat, & Sierra, 2006). There is support in the literature that 3-factors (partner focused desire, general sexual desire for an attractive person, solitary sexual desire) better capture the dimensions of the SDI-2 (e.g.,
Moyano,Vallejo-Medina, & Sierra, 2017, Mark, Toland, Rosenkrantz, Brown, & Hong, 2018).
The 3-factor solution of the SDI-I has also been investigated in a Spanish sample with exploratory (n =3417) and confirmatory (n = 677) factor analyses (Moyano,Vallejo-Medina, &
Sierra, 2017), and with confirmatory factor analysis in a LGBTQ* sample (n = 385; Mark et al.,
2018).
Sexual Excitation/Sexual Inhibition Inventory for Women and Men (SESII-W/M).
We will use the SESII-W/M (Milhausen, Graham, Sanders, Yarber, & Maitland, 2010) to assess the sexual excitation and inhibition propensities of all participants. The SESII-W/M is a 30-item self-report measure to which participants indicate their degree of agreement to a series of self- statements using a four-point Likert scale (1 = Strongly Disagree to 4 = Strongly Agree). Sexual excitation and inhibition is assessed across six domains, including Inhibitory Cognitions (eight items assessing thoughts that inhibit sexual arousal; e.g., “Unless things are “just right” it is difficult for me to become aroused.”), Relationship Importance (five items emphasizing the importance of relationship stability to sexual excitation and instability to inhibition, e.g., “I really need to trust a partner to become fully aroused.”), Arousability (five items indicating the
10 ease at which one becomes aroused to various sexual stimuli, e.g., “Just talking about sex is enough to put me in a sexual mood.”), Partner Characteristics and Behaviors (five items reflecting elements of a sexual partner that influence excitation, e.g., “I find it arousing when a partner does something nice for me.”), Setting (four items related to sexual excitation spurred by novel or unconcealed sexual contexts, e.g., “I get really turned on if I think I may get caught while having sex.”), and Dyadic Elements of the Sexual Interaction (three items assessing dyadic elements during sexual activity that increase inhibition propensities, e.g., “If I am uncertain how my partner feels about me, it is harder for me to get aroused.”). The SESII-W/M was developed using an exploratory factor analysis and then confirmed with a confirmatory factor analysis on a sample of 481 undergraduate and graduate university students (Milhausen et al., 2010). The measure also demonstrated measurement invariance across men and women for the factor loadings and factor variances and covariances, though not across the residuals.
Sexual Sensation Seeking Scale (SSSS). We will use the Sexual Sensation Seeking
Scale (SSSS; Kalichman et al., 1994; Kalichman and Rompa, 1995) to examine individuals’ propensity for and enjoyment of novel and exciting sexual behaviour. The 10-item measure has participants rate the degree to which a number of self-statements (e.g., I like wild “uninhibited” sexual encounters) are representative of themselves using a 4-point Likert scale (1 = not at all like me; to 4 = very much like me). The authors did not originally assess the structure of the scale though it was proposed as a unidimensional construct. In a validation of the SSSS in Spanish samples, however, researchers conducted a parallel analysis and a principal components analysis on 1,272 heterosexual undergraduate men and women, yielding a two component structure
(Santos-Iglesias, Moyano, Castro, Granados, & Sierra, 2018). After the removal of two items, a
CFA was used to confirm this structure in a sample of community men and women (N = 373).
11 The two-factors were labeled as: (1) physical sensations and risky behaviors (five items) and (2) exploratory or novel sex (three items). In a third sample comprised of 1,596 undergraduate men and women, the authors demonstrated the two factor model had measurement invariance in the number of factors, loadings, and intercepts across men and women (Santos-Iglesias et al., 2018).
Sexual Compulsivity Scale (SCS). We will use the Sexual Compulsivity Scale (SCS;
Kalichman et al., 1994; Kalichman and Rompa, 1995) to assess the presence and degree of insistent, intrusive, and uncontrolled sexual thoughts and behaviors. The measure consists of 10 items (e.g., my desires to have sex have disrupted my daily life) that participants will rate on a 4- point Likert ranging from 1 (Not at all like me) to 4 (Very much like me) to indicate the extent to which they agree with each statement. The SCS was proposed as a unidimensional construct, although the authors did not originally assess the structure of the scale. The Sexual Compulsivity
Scale has enjoyed a high level of utilization with college and community samples (e.g., Benotsch et al., 1999; Burri, 2017; Cooper, Scherer, Boies, and Gordon 1999; Kalichman, & Rompa, 2001;
Kalichman, Greenberg, & Abel, 1997), including some psychometric investigations which yielded two-factor models (e.g., Kalichman & Cain, 2004; McBride, Reece, Sanders, 2008).
Generalist Sexuality
Global Measure of Sexual Satisfaction (GMSEX). To assess sexual satisfaction, we will use the unidimensional (Mark et al., 2014) Global Measure of Sexual Satisfaction (GMSEX; a subcomponent of the Interpersonal Exchange Model of Sexual Satisfaction Questionnaire;
Lawrance & Byers, 1995). We will ask participants to select on a five 7-point bipolar (Semantic
Differential) scales what best describes their overall sexual relationship with their current partner(s) using five word-pairs, such as ‘Pleasant’ to ‘Unpleasant.’. Researchers originally developed and validated the GMSEX in a pilot study of sexually active North American
12 undergraduate students in relationships of more than one year (Lawrance & Byers, 1992).
Following the initial scale creation, researchers further validated the GMSEX in a sample of long-term heterosexual North Americans (Lawrance & Byers, 1995), and examined it overtime and dyadically (Byers & MacNeil, 2006). Researchers have translated the GMSEX for use in a variety of geographic locations including China (Renaud, Byers, & Pan, 1997), Spain (Sánchez-
Fuentes, Santos-Iglesias, Byers, & Sierra, 2015), and Portugal (Pascoal, Narciso, Pereira, &
Ferreira, 2013). Researchers have used the GMSEX in heterosexual samples as well as in samples of same-sex attracted women (Byers & Cohen, 2017) and men (Peixoto, 2019).
New Sexual Satisfaction Scale (NSSS). We will use the New Sexual Satisfaction Scale
(NSSS; Štulhofer, Buško & Brouillard, 2010) to get an overall picture of sexual satisfaction for participants. The strength of this scale over other sexual satisfaction scales is that it measures orgasms (both quality and frequency of) while previous scales have not examined orgasms in relation to sexual pleasure. The scale was constructed and validated in seven unique subsamples of participants in Croatia (n = 1906) and the United States (n = 568), some being college students, some adults, and one in a non-heterosexual group (n = 360), for a total of 2474 participants (subsample n’s range 54-729). This scale consists of 20 items, split equally into two subscales (the first ten items are “ego-focused”, and the following ten items are “partner- and sexual activity-centered”), and are measured on a 5-point likert scale (1 = not at all satisfied; to 5
= extremely satisfied). Examples of items from the ego-focused subscale include “The intensity of my sexual arousal”, “The quality of my orgasms” and “The way I sexually react to my partner”; and examples of items from the partner- and sexual activity-centered scale include “My partner’s emotional opening up during sex”, “The balance between what I give and receive in sex”, and “My partner’s ability to orgasm”. To develop the scale, principle components analysis
13 was conducted in two Croatian samples to examine the proposed 5-dimensional conceptual framework for the initial pool of 35 items. After removing five items, principle components analysis was conducted on four additional samples (n’s = 212-749; two Croatian samples, two
American samples) with the remaining 30 items. The obtained 4-to-6 factor solutions differed across the samples, leading to the retention of a 2 factor solution, which had a similar pattern matrices across samples. The 2 factor solution also held in a separate sample using principal axis factoring (n = 425; Mark, Herbenick, Fortenberry, Sanders, & Reece, 2014). Total satisfaction scores on the NSSS were found to be higher in the Croatian sample than the American sample.
Men in the Croatian sample reported higher scores on the ego-centred subscale, and women in both the Croatian and American sample reported higher scores on the partner-centred subscale.
Non-heterosexual women and heterosexual men consistently reported higher satisfaction scores than non-heterosexual men.
Sexual Communal Strength Scale (SCSS; SCNS). To assess sexual communal strength—one’s willingness to meet a partner’s sexual needs—we will include two separate but related measures: the Sexual Communal Strength for Having Sex measure (SCSS; Muise, Impett,
Desmarais, & Kogan, 2013) and the Sexual Communal Strength for Not Having Sex measure
(SCSN; Muise, Kim, Impett, & Rosen, 2017). These measures were inspired by, and adapted from, a broader relational measure of willingness to meet a relationship partner’s needs
(communal strength; Mills, Clark, Ford, & Johnson, 2014) although SCSS is distinct from this general relationship construct (Muise et al., 2013). Using a five-point scale (0 = not at all; 4 = extremely) participants will respond to the 6 SCSS items such as, “How far would you be willing to go to meet your partner’s sexual needs?”, as well as to the 4 SCSN items, including, “If your
14 partner is not in the mood for sex, how easily could you accept not having sex with your partner?”
Researchers originally validated the version of sexual communal strength for having sex
(SCSS) in a sample of 44 long-term couples who had been in a relationship on average 11 years
(Muise et al., 2013), and thereafter researchers have used the measure in a variety of relational contexts including individuals experiencing sexual dysfunction (Muise, Bergeron, Impett, &
Rosen, 2017) and individuals in consensually nonmonogamous relationships (Muise, Laughton,
Moors, & Impett, 2018). Subsequently, the researchers validated a version of the questionnaire specific to meeting a partner’s need to not have sex (SCSN) in a Mechanical Turk sample of individuals in relationships. Through an Exploratory Factor Analysis, the researchers demonstrated the SCSN was independent from (i.e. a separate factor from)—although correlated with (r = .32)—the SCSS. At present researchers have administered the SCSS and SCSN scales exclusively in North American samples (Muise & Impett, 2019).
Verbal and Nonverbal Sexual Communication Questionnaire (VNSCQ). We will use the Verbal and Nonverbal Sexual Communication Questionnaire (Santos-Iglesias & Byers, 2018) to assess the frequency of nonverbal and verbal sexual communication that occurs during sexual activity. This 28-item measure is comprised of three scales, Verbal Sexual Communication (13 items; e.g., When I want to, I ask my partner for sex), Nonverbal sexual initiation and pleasure (8 items; e.g., I use nonverbal cues (smiling, caressing, etc.) to indicate to my partner that he/she is pleasing me), and nonverbal sexual refusal (7 items; e.g., I stop my partner when he/she does something sexual that I do not like but do not say anything). Participants will report how often they communicate in the way indicated by the item on a 7-point frequency scale from 1 (never) to 7 (always). The initial exploratory factor analysis was done with a sample of 216 Canadian
15 undergraduates (86 men; 130 women) and with the verbal and nonverbal subscales analyzed separately. A confirmatory factor analysis was conducted in a Spanish sample (n = 184).
Barriers to Sexual Communication Questionnaire—short form. We will use the short form of the Barriers to Sexual Communication Questionnaire (Rehman et al., 2018) to assess the types of threats activated during sexual and nonsexual communication. The measure contains 20 statements that assess threat to partner (seven items; e.g., “My partner will feel inadequate as a result of this discussion”), threat to self (seven items; e.g., “The discussion will make me feel worthless”), and threat to relationship (six items; e.g., “The discussion will cause my partner and
I to argue”). We will ask participants to rate the extent to which each statement would apply to their discussion with their partner about a sexual issue on a 5-point Likert (1 = not at all true; 5 = very true), with a not applicable response option. Researchers recruited participants in committed romantic relationships from Amazon’s Mechanical Turk who were randomized to a sexual or nonsexual condition. An exploratory factor analysis using 83 items was conducted with participants in the sexual condition (n = 229). A short form of the scale was then created using the7 items with the strongest factor loadings for each subscale. A confirmatory factor analysis was conducted using these 21 items in the same sample.
Sexual Talk During Sexual Activity Measure (SexTalk). We will use the sexual talk during sexual activity measure (SexTalk; Jonason et al., 2016) to assess the general use of individualistic (i.e., self-focused) and mutualistic (i.e., other-focused) talk during sexual activity.
The measure contains 16 items assessing four types of individualistic talk (i.e., statements which are sexually dominant or submissive, messages of ‘sexual ownership,’ and talking about sexual fantasies) and four types of mutualistic talk (i.e., short exclamations of excitement or pleasure, positive feedback or compliments, instructive statements, and messages that strengthen the
16 intimate/emotional bond with one’s partner). Participants will report on the frequency with which they engage in each type of sexual talk with their current romantic partner during sexual activity on a 5-point Likert scale (1 = Never or Not at all; to 5 =All the time or Extremely), with higher scores indicating more frequent use of and excitement from saying sexual talk.
Researchers originally validated the SexTalk measure in an online MTurk sample (N = 238) of individuals aged 19 to 68 years-old whom were single (18%) or in committed romantic relationships (72%) and identified as heterosexual (88%), homosexual (4%), and bisexual (7%;
Jonason et al., 2016). Through an Exploratory Factor Analysis, Jonason et al. (2016) demonstrated that sexual talk, as assessed by the SexTalk measure consisted of two separate (i.e., individualistic and mutualistic talk) but correlated factors (r = .47). Subsequently, researchers validated the SexTalk measure in English (Merwin & Rosen, 2019; Merwin, Bergeron, & Rosen, in preparation) and in French (Merwin, Bergeron, & Rosen, in preparation). The two-factor structure of the SexTalk measure was confirmed in an online MTurk sample of individuals (N =
303), aged 18 to 73 years-old, in committed romantic relationships of at least 6 months in duration (M = 9.44 years). Additionally, in an online sample (N = 217 couples; 77 same-sex couples) of English and French couples (aged 18 to 64 years-old) in long-term relationships (M =
5.78 years), researchers confirmed the two-factor structure and found that the two factors (i.e., individualistic and mutualistic talk) were moderately correlated (r = .40).
Sexual flexibility scale (SexFlex). We will use the SexFlex Scale (Gauvin & Pukall,
2018) to assess how frequently participants’ respond in a flexible manner when confronted with a sexual issue/challenge (e.g., “I can easily change my approach to sex if necessary because of my sexual problem(s)”), using a four-point scale(1 = seldom or never; 4 = almost always).
Internal consistency for the 6-item SexFlex Scale was found to be high across samples of men
17 and women in same-gender and mixed-gender relationships (Gauvin & Pukall, 2018). An online sample of (N = 951) men and women in same- and mixed-gender relationships between the ages of 18 and 59 were randomly assigned using SPSS 23.0 to a subsample for an exploratory (n =
483) or confirmatory (n = 468) factor analysis. The single factor structure of the SexFlex scale was found to be invariant across women and men in same and mixed-gender relationships.
Implicit theories of sexuality scale. We will use a shortened version of Implicit Theories of Sexuality Scale (Maxwell et al., 2017) to assess participants’ implicit—or lay—beliefs about contributors to successful sexual relationships. On a seven-point scale (1 = strongly disagree; to
7 = strongly agree), participants will respond to 5 items assessing their sexual destiny beliefs, or beliefs that good sexual relationships arise from natural compatibility; e.g., “A couple is either destined to have a satisfying sex life or they are not.” Using the same response options, participants will also respond to 5 items assessing their sexual growth beliefs, or beliefs that successful sexual relationships come from hard work and effort; e.g., “Successful sexual relationships require regular maintenance.” Researchers have previously validated the full
Implicit Theories of Sexuality Scale in English in two online Mechanical Turk samples of individuals aged 18-73. The Exploratory Factor Analysis sample consisted of individuals in exclusive relationships lasting at least six months (Study 1), and the Confirmatory Factor
Analysis sample consisted of individuals specifically in cohabiting or married relationships
(Study 2). Study 5 illustrated the reliability of the short version of the scale with first-time parents (n = 281 couples). Participants of all sexual orientations could participate in the validation studies, although the vast majority identified as heterosexual.
Approach/avoidance goals for sex (Cooper et al., 1998; Impett, Peplau, & Gable,
2005). We will use 21 items to assess participants’ approach and avoidance goals for sex (Impett
18 & Muise; personal communication; Impett, Peplau, & Gable, 2005). This measure is adapted from the Sexual Motivation Scale (Cooper et al., 1998) as well as hypothesized reasons women engage in unwanted sex (Impett & Peplau, 2002). The scale examines approach motivation for having sex, meaning focusing on positive outcomes for engaging in sex, as well as avoidance motivation for having sex, or a focus on avoiding negative outcomes by engaging in sex. The scale is further divided into reasons focused on the self, and reasons focused on the partner.
Thus, there are four subscales: self-focused approach goals (e.g., “To feel good or better about myself”; 5 items) partner-focused approach goals (e.g., “To express love for my partner”; 6 items), self-focused avoidance goals (e.g., “To avoid feeling guilty”; 4 items), and partner- focused avoidance goals (e.g., “To prevent my partner from getting angry at me”; 6 items).
Participants will rate these items thinking about how important the reasons are for why they typically engage in sex on a scale from from 1 (not at all important) to 7 (extremely important).
Measurement of approach and avoidance goals for engaging in sex has varied in terms of number of items administered (e.g., Impett et al., 2005; Muise et al., 2012) and number of factors extracted. Throughout the literature, using various instantiations of the measure, there is support for a 2 factor structure (Impett et al., 2005; Rosen et al., 2015) a 4 factor structure (Cooper,
Shapiro, & Powers, 1998), and a 6 factor structure (Jardin, Garey, & Zvolensky, 2017). Thus our study will test the factor structure of the 21 item version of the scale recommended by experts in these constructs (Impett & Muise, personal communication). We expect to confirm the four factor structure, but will also assess the fit of a two factor and six factor model, given past research. The original Seuxal Motivation Scale (Cooper et al., 1998) shows invariance across sexual minority status, and evidences reliability in a sample of Hispanic and Asian Americans
19 (Jardin et al., 2017). Yet, whether the recommended 21 item measure shows this invariance and generalizability remains to be seen, and will be investigated in the present study.
Generalist Relational
Dyadic Adjustment Scale (DAS). We will use the 32-item Dyadic Adjustment Scale
(DAS; Spanier, 1976) to assess participants’ satisfaction with their relationship. The DAS has four subscales Dyadic Consensus (“Level of agreement on handling financial matters”; 13 items), Dyadic Satisfaction (“How often do you discuss or have you considered divorce, separation, or terminating your relationship”; 10 items), Dyadic Cohesion (“Do you and your mate engage in outside interests together”; 5 items), and Affectional Expression (“Level of agreement on demonstrations of affection”; 4 items). Participants will respond using varying
Likert scales (2-point; 5-point; 6-point; 7-point) with varying anchors. An initial exploratory factor analysis was conducted with married (n = 218) and divorced participants (n = 94; Spanier,
1976) with a confirmatory factor analysis conducted with 205 separated/divorced participants
(Spanier & Thompson, 1982). Researchers examining the DAS’s reliability across 91 published studies (Graham, Liu, Jeziorski, 2006) and found the internal consistency for the Dyadic cohesion, Consensus, and Satisfaction subscales to be acceptable, however, the Affective
Expression subscale demonstrated low internal consistency with estimates differing by sample characteristics (sexual orientation, gender, marital status, ethnicity). In addition to problems with the Affectional Expression subscale, other studies have highlighted problems with the Dyadic
Satisfaction subscale (Crane, Busby, & Larson, 1991; Sharpley & Cross, 1982; Spanier &
Thompson, 1982). In a sample of 900 individuals who participated in the Minnesota Twin
Family Study, the DAS demonstrated measurement invariance across gender (South, Kruegar, &
Iacono, 2009).
20 Perceived Relationship Quality Components Inventory (PRQC). We will use the
PRQC (Fletcher, Simpson, & Thomas, 2000) to assess participants’ relationship quality.
Participants will respond to three items for each of the six subscales or “components” of relationship quality: satisfaction (e.g.,“How content are you with your relationship?”), commitment (e.g.,“How dedicated are you to your relationship?”), intimacy (e.g.,“How connected are you to your partner?”), trust (e.g.,“How dependable is your partner?”), passion
(e.g., “How sexually intense is your relationship?”) and love (e.g., How much do you adore your partner?”) on a seven-point scale (1 = not at all; 7 = extremely). Researchers validated the
PRQC in English in two samples of heterosexual university students (Study 1 N = 200, Study 2
N = 100), using a series of confirmatory factor analyses. The students were involved in either fairly long term heterosexual relationships (average of approximately two years; Study 1) or were in newly formed dating relationships of less than four weeks.
Proposed Sources of Measurement Invariance
Gender/sex. Following recommendations for transgender-inclusive measures of gender/sex (Bauer, Braimoh, Scheim, & Dharma, 2017) we will be asking participants about their current gender, and the sex that they were assigned at birth.
Sexual orientation and relationship composition. In line with research showing how aspects of sexual identity are not always coincident (e.g., van Anders, 2015) and may relate to health outcomes differently (e.g., Lindley, Walsemann, & Carter, 2012), we will be including multiple measures of sexual identity to assess invariance across. Participants will respond to questions asking about their sexual orientation (e.g., gay, lesbian, bisexual, heterosexual), sexual attraction (e.g., male-oriented, female-oriented; Badgett, 2009), the gender of their current
21 partner, and how many of their previous sexual and romantic partners were same- versus other- sex
Relationship landscape. To assess measurement invariance across relationship landscape we will ask participants about their relationship status (e.g., single, casually dating, married). Participants who are in a relationship will be asked about the length of their current relationship. Using language from Schechinger, Sakaluk, & Moors (2018) we will ask participants about their relationship structure (monogamous, non-monogamous, questioning).
Developmental trajectories. We will be assessing measurement invariance across age, number of sexual and relational experiences, and pregnancy/birth experiences.
Sexual/relational experience. To assess invariance across sexual/relational experiences that may influence schema development, we will be asking participants about their age of sexual debut, if they have had sexual experience in the past four weeks, if their current partner experiences sexual problems/dysfunctions. The Nonconsensual Sexual Experience Inventory -
Modified will also be used in the current study to categorize participants into groups for those with and without NSE histories in order to assess measurement invariance across these experientially defined groups.
Nonconsensual Sexual Experience Inventory - Modified (NSEI-M). The
Nonconsensual Sexual Experience Inventory is a comprehensive measure of NSEs and characteristics of these experiences (e.g., age of onset, relationship to perpetrator, degree of force or injury). The measure was originally designed for assessing women’s NSE histories (Kilimnik et al., 2018) and the NSEI-M was modified for a gender-neutral assessment of NSEs (Kilimnik
& Meston, In Review). The NSEI-M consists of six activity-specific questions to determine if individuals have ever experienced sexual acts against their will, including vaginal penetration,
22 anal penetration, penetration of another’s genitals or anus, oral sex (giving or receiving), or sexual touching or fondling (e.g., Has anyone ever inserted fingers, objects, or their penis into your anus/butt against your will?). The sixth item assesses other NSEs not covered in the previous five items. If individuals respond “yes” to any of the six NSE items, a followup question will ask about if the specific experience(s) occurred during childhood, adolescence, or adulthood.
Branching Question. As some of the sexual functioning measures employed in the current study are designed based on participant genitalia, to appropriately branch participants to the relevant measures we will also ask participants to select which of two options (“Penis, strapless, or girl penis”or “Vagina or front hole”) best represents the genitalia they currently have. We also provide an open-ended textbox for participants to elaborate if these two options are not representative for them. If a participants response in the open-ended textbox reflects that the participant was branched incorrectly, their data for sexual functioning will be removed.
Additional Measures. In addition to measures included for analyses in the current paper, we will also ask participants to report on additional demographic variables (e.g., socioeconomic status, sexual orientation of their partner) that we will be using to describe the sample. We also have included the short form of the Positive and Negative Affect Schedule (PANAS short;
Mackinnon et al., 1999), and participants who receive the IIEF will also receive the additional
IIEF-MSM questions about receptive anal penetration. These additional measures are intended for use in secondary projects.
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