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Identifying Basic Classes of Sexual Orientation with Latent Profile Analysis: Developing the Multivariate Sexual Orientation Classification System

机译:鉴定潜在剖面分析的性取向基本课程:开发多元性取向分类系统

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Despite considerable progress, research on sexual minorities has been hindered by a lack of clarity and consistency in defining sexual minority groups. Further, despite recent recommendations to assess the three main dimensions of sexual orientationidentity, behavior, and attractionit remains unclear how best to integrate such multivariate information to define discrete sexual orientation groups, particularly when identity and behavior fail to match. The current study used a data-driven approach to identify a parsimonious set of sexual orientation classes. Latent profile analysis (LPA) was run within a large (N=3182) and sexually diverse sample, using dimensions of sexual identity, behavior, and attraction as predictors. LPAs supported four fundamental sexual orientation classes not only in the overall sample, but also when conducted separately in men (n=980) and women (n=2175): heterosexual, homosexual, bisexual, and heteroflexible (a class representing individuals who self-identify as heterosexual or mostly heterosexual but report moderate same-sex sexual behavior and attraction). Heterosexuals reported the highest levels of psychological functioning and lowest risk behaviors. Homosexuals showed similarly high levels of psychological functioning to heterosexuals, but higher levels of risk behaviors. Bisexuals and heteroflexibles showed similarly low levels of psychological functioning and high risk taking. To facilitate applications of this classification approach, the study developed the Multivariate Sexual Orientation Classification System, reproducing the four LPA groups with 97% accuracy (kappa=.95) using just two items. Implications of this classification approach are discussed.
机译:尽管进展相当大,对性少数群体的研究已经受到缺乏清晰度和定义性少数群体的份额。此外,尽管最近的建议评估了性朝内,行为的三个主要方面,但是仍然不清楚如何最好地整合这种多元信息以定义离散性取向群体,特别是当身份和行为无法匹配时。目前的研究使用了一种数据驱动的方法来识别一组令人生畏的性取向类。潜在剖面分析(LPA)在大(n = 3182)和性别不同的样本中,使用性身份,行为和吸引力的尺寸作为预测因子。 LPA不仅在整体样本中都支持了四个基本的性取向课程,而且在男性(n = 980)和女性中单独进行(n = 2175):异性恋,同性恋,双性恋和异性的(一堂课代表自我的班级鉴定为异性恋或主要是异性恋,但报告适度同性性行为和吸引力)。异性恋报告称最高的心理运作和最低风险行为。同性恋者表现出对异性恋的同样高的心理功能,但风险行为水平较高。双性恋和异质文件表现出类似地低水平的心理功能和高风险。为了促进这种分类方法的应用,该研究开发了多变量性定位分类系统,再现了只有两个项目的精度为97%的精度(Kappa = .95)。讨论了这种分类方法的含义。

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