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Klein, Savaș, and Conley (2021) argued that sexual science is overdependent on WEIRD (Western, Educated, Industrialized, Rich, and Democratic) samples. Though we agree that sexual science needs to increase its generalizability and inclusivity, we describe concerns with their measurement strategy of categorizing samples as WEIRD or Not WEIRD based on the country from which a sample was drawn. Reanalyzing their data with publicly available global metrics of Education, Industrialization, Richness, and Democratic Values (what we refer to as EIRDness), we find (1) EIRDness metrics were not particularly correlated; (2) countries coded as WEIRD by Klein et al. do not appear reliably EIRDer than those that were not; and (3) and categorical measurement models of EIRDness did not support profiles of EIRD and Not EIRD countries. With these limitations in mind, we then express further concerns about the application utility of Klein et al.'s WEIRDness critique, and unintended political implications embedded in its methodology. We conclude by harkening back to critiques of the WEIRD framework, and suggest that the pursuit of a more equitable and just sexual science – which we applaud Klein et al. for pushing our field to consider – may be better served to alternative frameworks for critiquing its sampling practices. [ABSTRACT FROM AUTHOR]

An introduction is presented in which the editor discusses various updates on "The Journal of Sex Research," which include the publication of registered reports by the journal, the increase in research manuscript submissions by the end of 2021, and the editorial board appointments in 2022.

Sexual scientists must choose from among myriad methodological and analytical approaches when investigating their research questions. How can scholars learn whether sexualities are discrete or continuous? How is sexuality constructed? And to what extent are sexuality-related groups similar to or different from one another? Though commonplace, quantitative attempts at addressing these research questions require users to possess an increasingly deep repertoire of statistical knowledge and programming skills. Recently developed open-source software offers powerful yet accessible capacity to researchers wishing to perform strong quantitative tests. Taking advantage of these new statistical opportunities will require sexual scientists to become familiar with new analyses, including taxometric analysis, tests of measurement variability and differential item functioning, and equivalence testing. In the current article, I discuss each of these analyses, providing conceptual and historical overviews. I also address common misunderstandings for each analysis that may discourage researchers from implementing them. Finally, I describe current best practices when using each analysis, providing reproducible coding examples and interpretations along the way, in an attempt to reduce barriers to the uptake of these analyses. By aspiring to explore these new statistical frontiers in sexual science, sexuality researchers will be better positioned to test their substantive theories of interest. [ABSTRACT FROM AUTHOR]

The authors talk about the update to its manuscript submission requirements by the periodical to promote more transparent reporting in conflicts of interest (COIs) and the reporting of statistical analyses. Topics discussed include the potential impact of conflicts of interest on research findings, the field of sexual research, and the standards of reporting confidence intervals.

Sexuality researchers frequently use exploratory factor analysis (EFA) to illuminate the distinguishable theoretical constructs assessed by a set of variables. EFA entails a substantive number of analytic decisions to be made with respect to sample size determination, and how factors are extracted, rotated, and retained. The available analytic options, however, are not all equally empirically rigorous. We discuss the commonly available options for conducting EFA and which options constitute best practices for EFA. We also present the results of a methodological review of the analytic options for EFA used by sexuality researchers in more than 200 EFAs, published in more than 160 articles and chapters from 1974 to 2014, in a sample of sexuality research journals. Our review reveals that best practices for EFA are actually those least frequently used by sexuality researchers. We introduce freely available analytic resources to help make it easier for sexuality researchers to adhere to best practices when conducting EFAs in their own research. [ABSTRACT FROM AUTHOR]

Sexual script research (Simon & Gagnon 1969 , 1986 ) bourgeoned following Simon and Gagnon's groundbreaking work. Empirical measurement of sexual script adherence has been limited, however, as no measures exist that have undergone rigorous development and validation. We conducted three studies to examine current dominant sexual scripts of heterosexual adults and to develop a measure of endorsement of these scripts. In Study 1, we conducted three focus groups of men ( n = 19) and four of women ( n = 20) to discuss the current scripts governing sexual behavior. Results supported scripts for sex drive, physical and emotional sex, sexual performance, initiation and gatekeeping, and evaluation of sexual others. In Study 2, we used these qualitative findings to develop a measure of script endorsement, the Sexual Script Scale. Factor analysis of data from 721 participants revealed six interrelated factors demonstrating initial construct validity. In Study 3, confirmatory factor analysis of a separate sample of 289 participants supported the model from Study 2, and evidence of factorial invariance and test-retest reliability was obtained. This article presents the results of these studies, documenting the process of scale development from formative research through to confirmatory testing, and suggests future directions for the continued development of sexual scripting theory.