Department of Psychology, Ryerson University, 350 Victoria Street, Toronto, ON, M5B 2K3, Canada.
Department of Sociology, Anthropology and Criminology, University of Windsor, Windsor, ON, Canada.
Arch Sex Behav. 2018 Jan;47(1):309-321. doi: 10.1007/s10508-017-0948-y. Epub 2017 Apr 20.
Using latent class analysis (LCA), we examined patterns of participation in multiple scenes, how sexual risk practices vary by scene, and psychosocial factors associated with these patterns among 470 gay, bisexual, and other men who have sex with men (GBM) recruited from Toronto. We calculated posterior probability of being in a class from participation in nine separate scenes. We used Entropy, the Bayesian information criterion and the Lo-Mendel-Rubin likelihood ratio test to identify the best fit model. Fit indices suggested a four-class solution. Half (50%) of the GBM reported no or minimal participation in any scene, 28% reported participating in the dance club scene, 16% reported participating in the BDSM, bear, and leather scenes, and 6% reported participating in circuit, party and play, and sex party scenes. Compared to GBM who did not participate in scenes, GBM participating in the BDSM-Bear-Leather scene were more likely to be older, white, to report higher sexual self-esteem, and to engage in condomless anal sex; Party and Play scene members were more likely to be of Asian origin, and to use drugs before and during sex, whereas Dance Club scene members were more likely to be younger and to report lower self-esteem but higher hope. LCA allowed us to identify distinct social niches or micro-cultures and factors characterizing these micro-cultures. GBM differ in their risk for HIV and STIs according to characteristics associated with participation in distinct micro-cultures associated with scenes. Tailored interventions may be needed that focus on reducing HIV risk and promoting sexual health in specific contexts such as the BDSM-Bear-Leather and Party and Play.
使用潜在类别分析（LCA），我们检查了 470 名男同性恋、双性恋和其他与男性发生性关系的男性（GBM）在多伦多参与多个场景的模式、性风险行为在不同场景中的差异以及与这些模式相关的社会心理因素。我们根据参与九个独立场景的情况计算了属于某个类别的后验概率。我们使用信息熵、贝叶斯信息准则和洛-门德尔-鲁宾似然比检验来确定最佳拟合模型。拟合指数表明存在四个类别的解决方案。一半（50%）的 GBM 报告没有或几乎没有参与任何场景，28%的 GBM 报告参与了舞蹈俱乐部场景，16%的 GBM 报告参与了 BDSM、熊和皮革场景，6%的 GBM 报告参与了电路、派对和娱乐以及性派对场景。与不参与场景的 GBM 相比，参与 BDSM-熊-皮革场景的 GBM 更有可能是年龄较大、白人、报告性自尊心更高、并进行无保护的肛交；派对和娱乐场景的参与者更有可能是亚洲血统，并且在性行为前后使用毒品，而舞蹈俱乐部场景的参与者更有可能是年轻人，并且自尊心较低但希望较高。LCA 使我们能够识别不同的社会利基或微文化以及这些微文化的特征。根据与不同场景相关的特定微文化参与相关的特征，GBM 在 HIV 和性传播感染的风险方面存在差异。可能需要有针对性的干预措施，重点是在特定情况下减少 HIV 风险并促进性健康，例如 BDSM-熊-皮革和派对和娱乐。
