SOLVE IT: Real Risk Reduction for MSM

描述(由申请人提供)：针对男男性行为者(MSM)的艾滋病毒预防工作似乎停滞不前：每年仍有18,000名MSM被诊断感染人类免疫缺陷病毒(HIV)。25岁以下的男男性同性恋者特别有可能与临时伴侣进行无保护的肛交(UAI)。传统干预减少了UAI，但这些更有意识、更深思熟虑、更认知的方法并不能解决更自动、更基于影响的决策路线。要产生这种自动的、基于影响的风险降低，需要有风险提示的经验：但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，对认知和行为技能建模的社会认知干预)，同时通过让MSM在安全的虚拟环境中体验风险线索，解决了MSM基于情感和反应性的风险决策过程。与等待名单和一对一咨询控制相比，这种方法被发现可以减少UAI。在我们正在进行的工作中，在MSM的三个种族群体(黑人/非裔美国人、拉丁裔/西班牙裔、白人/高加索人)中，初步研究结果表明，较年轻(18-24岁)的MSM风险较大(即，在过去90天内与非主要性伴有2次或更多UAI)。此外，虚拟风险承担对未来的风险承担具有独特的预测作用，甚至考虑到了传统的自我报告测量(例如，意图、自我效能)。然而，我们使用交互式视频(Solve-IAV)的工作受限于IAV技术提供的潜在学习情景的数量，以及IAV无法为用户提供更个性化的虚拟体验，这可能会增强用户在体验中的“临场感”--这也与UAI的变化有关。在经过形成性研究之后，我们在当前提案中的第一个具体目标是创建Solve-IT，这是一个覆盖各种MSM的测试情景或“风险环境”的虚拟环境，使用智能代理和游戏技术，将在全国范围内通过网络“在线”交付和评估。我们的第二个具体目标是测试Solve-IT对年轻高危MSM(黑人/非裔美国人、拉丁裔/拉美裔、白人/高加索人)的有效性，并与使用为期3个月的纵向随机对照试验(RCT)的等待名单控制组进行比较。与临时伴侣的UAI变化是主要的因变量。本课程还考察了其他探索性问题。 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MSM性行为风险的创新、综合方法的有效性，从而减少不利的健康后果(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，这是一种技术驱动的科学，可以为减少可能对公众健康造成不利影响的高风险决策提供健康应用--所有这些都可以通过网络随时获得。

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.