SNS-based Data Mining to Understand MSM Substance use and HIV Risk Behavior

 描述(申请人提供)：同性恋、双性恋和其他男男性行为者(下称男男性接触者)的艾滋病毒发病率继续上升，部分原因是药物使用。男男性接触者越来越多地使用社交网站(SNS)来寻找吸毒和性伴侣。然而，目前还没有研究使用自动、实时的数据收集和分析程序来监控MSM使用的各种SNS平台上的药物使用和性伴侣寻找，以告知干预发展。这个项目将建立在常规活动理论的基础上，利用SNS互动进行研究，以帮助理解MSM中的药物使用模式和艾滋病毒危险行为。在第一阶段，将利用MSM的焦点小组(n=8/焦点小组；N=24)开发一个词典，用于通过不同的SNS平台识别MSM中的药物使用和性伴侣寻找。这些发现将指导开发具有文化一致性的数据收集和挖掘模块(DCMM；系统地搜索SNS以可分析的格式收集数据的互联网软件)，其中包括社区咨询委员会(CAB)的迭代反馈和MSM(n=6)的试点测试。在第二阶段，DCMM将从50名MSM那里收集关于SNS使用(例如，频率、强度)、药物使用和艾滋病毒风险/防护行为(例如，个人资料、帖子内容)的数据。每周将通过自我报告对危险行为进行评估，并通过指甲样本进行快速口腔艾滋病毒检测和药物测试，在研究结束时收集危险行为的生物标记物进行验证。这项研究将导致后续的R34应用，以开发和测试使用机器学习技术的即时自适应干预(JTAI)。拟议研究的具体目的是：(1)开发和评估文化契合的DCMM用于研究MSM的社交网络使用模式、物质使用与艾滋病毒风险和保护行为的效用；(2)使用文化契合的DCMM、自我报告数据收集和物质使用与艾滋病毒风险的生物标记物，确定50名MSM样本中技术使用模式、物质使用与艾滋病毒风险行为之间的关联；以及(3)评估及时适应干预的可行性和计算要求，以减少MSM中的物质使用和艾滋病毒风险行为。通过设计和测试一个文化上一致的DCMM来捕获关于MSM物质使用和性伴侣寻找的SNS数据，这项研究为开发专门为MSM量身定做的基于技术的物质使用和艾滋病毒预防和治疗工作奠定了基础。

 DESCRIPTION (provided by applicant): HIV incidence among gay, bisexual and other men who have sex with men (hereafter MSM) continues to rise, driven in part by substance use. MSM are increasingly using social networking sites (SNS) to find substance use and sexual partners. However, no studies currently exist that use automated, real-time data collection and analysis procedures to monitor substance use and sexual partner seeking across the range of SNS platforms used by MSM to inform intervention development. This project will build on Routine Activities Theory to conduct research using SNS interactions to aid in understanding patterns of substance use and HIV risk behavior among MSM. During Phase 1, focus groups of MSM (n=~8/focus group; N=24) will be used to develop a lexicon for identifying substance use and sexual partner seeking among MSM via diverse SNS platforms. These findings will guide the development of a culturally congruent data collection and mining module (DCMM; internet software that systematically searches SNS to gather data in an analyzable format) with iterative feedback from a community advisory board (CAB) and pilot testing by MSM (n=6). During Phase 2, the DCMM will gather data from 50 MSM on SNS use (e.g., frequency, intensity) substance use and HIV risk/protective behaviors (e.g., content of profiles, postings). Risk behaviors will be assessed weekly via self- report and validated with biomarkers of risk behaviors to be collected at the end of the study period using a rapid oral HIV test and drug test via nail sample. This research will result in a subsequent R34 application to develop and test a just-in-time adaptive intervention (JTAI) using machine learning technology. The specific aims of the proposed research are to: (1) Develop and assess the utility of a culturally congruent DCMM to study the SNS use patterns, substance use and HIV risk and protective behaviors of MSM; (2) Determine associations between patterns of technology use, substance use and HIV risk behaviors among a sample of 50 MSM using a culturally congruent DCMM, self-report data collection and biomarkers for substance use and HIV; and (3) Evaluate the feasibility and the computational requirements of a just-in-time adaptive intervention to reduce substance use and HIV risk behavior among MSM. By devising and testing a culturally congruent DCMM to capture SNS data on MSM substance use and sexual partner seeking this study lays the building blocks to developing technology-based substance use and HIV prevention and treatment efforts tailored specifically for MSM.