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名男男性行为者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尤其有可能与临时伴侣进行无保护的肛交。传统的干预措施已经减少了UAI，但这些更加有意识、深思熟虑和认知的方法并不能解决更自动、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，社会认知干预模拟认知和行为技能），同时通过在安全的虚拟环境中给男同性恋者提供风险线索的经验，解决他们基于情感和反应性的风险决策过程。与等候名单和“标准护理”一对一咨询控制相比，这种方法已被发现可以减少UAI。在我们正在进行的工作中，在MSM的三个种族人群中（黑人/非裔美国人，拉丁裔/西班牙裔，白人/高加索人），初步发现对于年龄较小（18-24岁）的MSM有更大的风险（即在过去90天内与非主要性伴侣发生过2次或更多的UAI）。此外，即使考虑到传统的自我报告措施（如意图、自我效能），虚拟风险承担也能独特地预测未来的风险承担。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境数量的限制，并且IAV无法为用户提供更个性化的虚拟体验，这可能会增强用户在体验中的“存在感”——这也是与UAI变化相关的一个因素。我们当前提案的第一个具体目标是，在形成性研究之后，创建SOLVE-IT，这是一个虚拟环境，涵盖了各种MSM的一系列测试情况或“风险环境”，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通过一项为期3个月的纵向随机对照试验（RCT），测试SOLVE-IT对年轻高危男同性恋者（黑人/非裔美国人，拉丁裔/西班牙裔，白人/高加索人）的有效性。随机伴侣的UAI变化是主要的因变量。考察其他探索性问题。

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.