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

 描述（由申请人提供）：同性恋、双性恋和其他男男性行为者（以下简称MSM）的艾滋病毒感染率持续上升，部分原因是药物使用。MSM越来越多地使用社交网站（SNS）来寻找药物使用者和性伴侣。然而，目前还没有研究使用自动化的实时数据收集和分析程序来监测MSM使用的SNS平台范围内的药物使用和性伴侣寻求，以告知干预措施的制定。本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，以帮助了解MSM中物质使用和艾滋病毒风险行为的模式。在第一阶段，MSM的焦点小组（n=~8/焦点小组; N=24）将用于开发一个词汇，用于识别通过不同的SNS平台在MSM中寻求物质使用和性伴侣。这些研究结果将指导开发一个文化上一致的数据收集和挖掘模块（DCMM;互联网软件，系统地搜索SNS收集数据的可分析格式）与迭代反馈，从社区咨询委员会（CAB）和试点测试MSM（n=6）。在第二阶段，DCMM将收集50名MSM使用SNS的数据（例如，频率、强度）药物使用和艾滋病毒风险/保护行为（例如，简介、帖子的内容）。将每周通过自我报告评估风险行为，并使用快速口服HIV检测和通过指甲样本进行药物检测，在研究期结束时收集风险行为的生物标志物进行验证。这项研究将导致随后的R34应用程序开发和测试使用机器学习技术的即时适应性干预（JTAI）。本研究的具体目的是：（1）开发并评估一个文化一致的DCMM来研究MSM的社交网络使用模式、物质使用和HIV风险及保护行为;（2）使用文化一致的DCMM确定50名MSM的技术使用模式、物质使用模式和HIV风险行为之间的关联，自我报告的数据收集和生物标志物的物质使用和艾滋病毒;（3）评估的可行性和计算要求的即时适应性干预，以减少物质使用和艾滋病毒的风险行为的男男性接触者。通过设计和测试一个文化上一致的DCMM，以捕捉SNS数据的MSM物质使用和寻求性伴侣，这项研究奠定了基石，以发展技术为基础的物质使用和艾滋病毒的预防和治疗工作专门为MSM。

 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.