Levina Olga S, Heimer Robert, Odinokova Veronika, Bodanovskaya Zinaida, Safiullina Liliya, Irwin Kevin S, Niccolai Linda M
Hum Organ. 2012 Spring;71(1):32-43. doi: 10.17730/humo.71.1.9130380u68614w47.
Street-based sex work in Russia, as in many countries, carries with it a high risk for violence and the transmission of infectious diseases. The male partners of female sex workers are both cause and recipient of such risks. Because little is known about the men, we undertook a preliminary study to determine the feasibility of recruiting and interviewing them, develop typologies that describe partners, and derive hypotheses for further study and risk reduction intervention projects. We were able to conduct open-ended, qualitative interviews with street-based sex workers and, largely through these contacts, their male partners. To these data, we added interviews with social work and medical experts who engage with the sex workers. The text of interviews from 37 respondents were analyzed to identify commonly mentioned partner characteristics in five distinct domains: sociodemographics, behavioral patterns of the partners, motivations in seeking sex services, levels of partner engagement with the sex workers, and the social circumstances that moderate the engagement. Four of the five domains (all but sociodemographics) proved useful in identifying typologies that were best described as populated points in a matrix generated from the intersection of the four domains. The data were too limited to specify which of the points in the matrix are most common, but the points populated are useful in generating hypotheses for further study and in identifying potential avenues for risk reduction interventions.
与许多国家一样,俄罗斯街头性工作伴随着遭受暴力和感染传染病的高风险。女性性工作者的男性伴侣既是此类风险的起因,也是风险的承受者。由于对这些男性了解甚少,我们开展了一项初步研究,以确定招募并访谈他们的可行性,制定描述伴侣类型的分类法,并得出可用于进一步研究和降低风险干预项目的假设。我们能够对街头性工作者进行开放式的定性访谈,并主要通过这些联系找到她们的男性伴侣。对于这些数据,我们补充了对与性工作者打交道的社会工作和医学专家的访谈。我们对37名受访者的访谈文本进行了分析,以确定在五个不同领域中经常提到的伴侣特征:社会人口统计学、伴侣的行为模式、寻求性服务的动机、伴侣与性工作者的交往程度,以及调节这种交往的社会环境。事实证明,五个领域中的四个(除社会人口统计学外的所有领域)有助于识别分类法,这些分类法最好被描述为从四个领域的交叉点生成的矩阵中的填充点。数据有限,无法确定矩阵中的哪些点最常见,但这些填充点有助于为进一步研究生成假设,并确定降低风险干预措施潜在的途径。