SOLVE IT: Real Risk Reduction for MSM

描述（由申请人提供）：男男性行为者（MSM）的艾滋病毒预防工作似乎停滞不前：每年仍有18，000名MSM被诊断患有人类免疫缺陷病毒（HIV）。25岁以下的男男性接触者特别有可能与临时伴侣进行无保护的肛交（UAI）。传统的干预措施减少了UAI，但这些更有意识、更慎重和更认知的方法并没有解决一个更自动、更基于影响的决策途径。要产生这种自动的、基于影响的风险降低，需要有风险线索的经验：但是，现实生活中的经验可能是灾难性的。SOLVE（虚拟环境中的社会优化学习）是一种新的艾滋病毒预防方法，它整合了传统的认知方法（例如，社会认知干预建模的认知和行为技能），同时解决男男性接触者的影响为基础的和反应性的风险决策过程，通过给他们的经验与风险线索在一个安全的，虚拟的环境。与等待名单和“护理标准”一对一咨询对照相比，这种方法被发现可以减少UAI。在我们正在进行的工作中，在三个MSM种族人群（黑人/非裔美国人，拉丁裔/西班牙裔，白色/高加索人）中，初步发现年轻（18-24岁）的MSM风险更大（即，在过去90天内与非主要性伴侣发生2次或2次以上UAI）。此外，虚拟风险承担是未来风险承担的唯一预测，即使考虑到传统的自我报告措施（例如，意图、自我效能）。然而，我们使用交互式视频（SOLVE-IAV）的工作受到IAV技术提供的潜在学习情况数量的限制，并且IAV无法为用户提供更个性化的虚拟体验，这可能会增强用户的“存在感”体验-这也是与UAI变化相关的因素。我们的第一个具体目标，在目前的建议，形成性研究后，是创建解决IT，一个虚拟的环境，涵盖了一系列的测试情况或“风险的背景下”，为不同的男男性接触者，使用智能代理和游戏技术，将提供和评估“在线”在全国范围内的网络。我们的第二个具体目标是使用3个月的纵向随机对照试验（RCT），与等待名单对照组相比，测试SOLVE-IT对年轻高风险MSM（黑人/非洲裔美国人，拉丁裔/西班牙裔，白色/高加索人）的有效性。休闲伴侣的UAI变化是主要的因变量。其他探索性问题进行了检查。 公共卫生相关性：如果这项工作取得成功，它将提供进一步的证据，证明减少男男性行为者性冒险的创新综合方法的有效性，从而减少不良健康结果（例如，艾滋病毒传播）。更广泛地说，这项工作将推进优化个性化风险降低的科学，这是一项技术支持的科学，可以提供健康应用程序，以减少可能对公众健康产生不利影响的风险决策-所有这些都可以通过网络向公众提供。

DESCRIPTION (provided by applicant): HIV prevention efforts for men who have sex with men (MSM) seem stalled: 18,000 MSM are still diagnosed with Human Immunodeficiency Virus (HIV) annually. MSM under age 25 are especially likely to have unprotected anal intercourse (UAI) with casual partners. Traditional interventions have reduced UAI but these more conscious, deliberative, and cognitive approaches don't address a more automatic, affect-based route to decision-making. Experience with risk cues is needed to produce such automatic, affect-based risk reduction: But, real-life experience could be catastrophic. SOLVE (Socially Optimized Learning in Virtual Environments) is a new approach to HIV prevention that integrates traditional cognitive approaches (e.g., social-cognitive interventions modeling cognitive and behavioral skills), while addressing MSM's affect- based and reactive risky decision-making processes, by giving them experience with risk cues in a safe, virtual environment. This approach has been found to reduce UAI compared to wait-list and "standard of care" one-on-one counseling controls. Across the three ethnic populations of MSM (Black/African-American, Latino/Hispanic, White/Caucasian) in our ongoing work, preliminary findings are stronger for younger (18-24 year old) MSM who take greater risks (i.e., 2 or more UAI with non-primary sex partners in the last 90 days). Furthermore, virtual risk taking was uniquely predictive of future risk-taking, even accounting for traditional self-report measures (e.g., intent, self- efficacy). However, our work using interactive video (SOLVE-IAV) is limited by the number of potential learning situations that IAV technology affords and by IAV's inability to enable a more personalized virtual experience for the user that may enhance the user's sense of "presence" in the experience -- a factor also related to change in UAI. Our first specific aim in the current proposal, following formative research, is to create SOLVE-IT, a virtual environment covering a range of test-situations or "contexts of risk" for diverse MSM that, using Intelligent Agent and Gaming technologies, would be delivered and assessed "on-line" over the web nationally. Our second specific aim is to test the effectiveness of SOLVE-IT for young high risk MSM (Black/African-Americans, Latino/Hispanics, White/Caucasians) compared to a wait-list control group using a 3- month longitudinal randomized control trial (RCT). UAI change with casual partners is the primary dependent variable. Additional exploratory questions are examined. PUBLIC HEALTH RELEVANCE: If this work is successful it would provide further evidence for the effectiveness of an innovative, integrative approach for reducing MSM's sexual risk-taking, that would thereby reduce adverse health outcomes (e.g., HIV transmission). More broadly, the work would advance the science of optimizing personalized risk-reduction, a technology- enabled science that could provide health applications for reducing risky decisions that can adversely impact public health -- all readily available to the public over the web.