Preventing Injection: An mHealth intervention that leverages social networks to prevent progression to injection among young opioid users

项目摘要/摘要 阿片类药物使用障碍(OUD)是美国第二常见的药物使用障碍类型，有近2 数百万美国人使用处方阿片类药物(PO)，约57万人使用与海洛因有关的药物。OUD中的升级 在过去的二十年里，这种情况在年轻人中最为明显，他们中的许多人表现出迅速的 从非医用PO使用(16-17年/月)过渡到海洛因(19-20年/月)，其中大多数进展为注射毒品使用 (IDU)，在开始使用海洛因一年内(20-21年/月)。发展到注射吸毒者的特征是独特的高水平 与年长的同龄人相比，年轻人的风险增加，包括服药过量(OD)和艾滋病毒和丙型肝炎的发病率更高。 成瘾严重程度、心理社会功能和社交网络是向注射吸毒者过渡的有力预测因素； 然而，几乎没有关于如何防止或停止向注射吸毒者过渡的研究。鉴于……的匮乏 针对这一庞大的弱势青年群体的干预措施，我们建议调整和评估一种创新的、 采取mHealth干预措施，防止年轻的阿片类药物使用者(18-29岁)过渡到IDU。目标1：在 第1-12个月，我们将调整我们现有的移动干预，使其适用于包括日常短信在内的OUD 加上循证CBT干预措施的关键组成部分，包括药物使用功能分析、自我 管理和社交/娱乐咨询。专门针对青年的新组成部分将侧重于 关于阿片类药物使用和吸毒的同龄人，以及吸毒预防/应对培训。我们的迭代开发过程将 包括与使用阿片类药物的青年的焦点小组(n=24)、与重要的利益攸关方(例如青年)的面谈 治疗提供者(n=6)，以及阿片类药物使用青年的反馈和可用性数据(n=30)。目标2：在 13-31个月，我们将进行一项针对定制mHealth干预的小型随机对照试验 与未过渡到常规注射的年轻阿片类药物使用者(n=)比较(1) 评估加药物过量预防/应对培训(包括纳洛酮)与(2) 评估+药物过量预防/应对培训(包括纳洛酮)+我们的mHealth 干预。可行性和可接受性将通过参与者反馈、保留和使用数据进行评估。 扩散将被定义为参与者的同伴为他们自己下载干预应用程序的数量 使用。初步疗效将通过减少阿片类药物的使用(TLFB、尿液/头发毒理学)和 在4周、8周和12周以及3个月和6个月的随访中自我报告注射情况。次要结果包括 艾滋病毒/丙型肝炎危险行为、吸毒、与阿片类药物相关的问题(例如，戒断发作)以及与注射成瘾相关的社交网络 规范和行为。如果结果是有希望的，这种新的干预措施将扩大到大规模的检查- 量表效果/效果试验。这种干预可能会对改善准入产生巨大影响， 青少年阿片类药物使用干预措施的可接受性和有效性。鉴于移动电话的广泛使用 年轻人中的应用程序(98%的18至29岁的人拥有手机，每天使用移动应用程序的时间约为3小时)， 以证据为基础的移动健康干预措施可能会对这些难以接触的人群产生重大影响。

Project Summary/Abstract Opioid use disorders (OUD) are the second most common type of drug use disorder in the US, with nearly 2 million Americans with prescription opioid- (PO) and ~570,000 with heroin-related OUD. The escalation in OUD during the past two decades has been most pronounced among youth, many of whom demonstrate a rapid transition from nonmedical PO use (16-17 y/o), to heroin (19-20 y/o), with most progressing to injection drug use (IDU), within a year of starting heroin use (20-21 y/o). Progression to IDU is characterized by uniquely high levels of risk for youth, including higher rates of overdose (OD) and HIV and HCV incidence, compared to older peers. Addiction severity, psychosocial functioning, and social networks are robust predictors of transitioning to IDU; however there is virtually no research on how to prevent or halt this transition to IDU. Given the paucity of interventions targeting this large and vulnerable group of youth, we propose to adapt and evaluate an innovative, engaging mHealth intervention to prevent young opioid users (18-29) from transitioning to IDU. Aim 1: During months 1-12, we will adapt our existing mobile intervention for OUD that includes daily text messages plus key components of evidence-based CBT interventions, including Functional Analysis of Drug Use, Self- Management, and Social / Recreational Counseling. New components specific to youth will focus on the role of peers on opioid use and IDU, and OD prevention / response training. Our iterative development process will include focus groups with opioid-using youth (n=24), interviews with important stakeholders (e.g., youth treatment providers; n=6), and feedback and usability data from opioid-using youth (n=30). Aim 2: During months 13-31, we will conduct a small randomized, controlled trial of the tailored mHealth intervention with young opioid users who have not transitioned to regular injection (n=64) and compare (1) assessment plus in-person OD prevention / response training (including naloxone) versus (2) assessment plus in-person OD prevention / response training (including naloxone) plus our mHealth intervention. Feasibility and acceptability will be assessed via participant feedback, retention, and usage data. Diffusion will be defined as the number of participants' peers who download the intervention app for their own use. Preliminary effectiveness will be measured via reductions in opioid use (TLFB, urine / hair toxicology) and self-reported injection status at 4, 8, and 12 weeks, and 3 and 6 month follow-up. Secondary outcomes include HIV/HCV risk behavior, OD, opioid-related problems (e.g., withdrawal episodes), and social network IDU-related norms and behaviors. If results are promising, this novel intervention will be expanded for examination in a large- scale efficacy / effectiveness trial. This intervention may have tremendous impact on improving access, acceptability, and potency of opioid use interventions for youth. Given the extremely widespread use of mobile apps among young adults (98% of 18-29 y/o own mobile phones and spend ~3 hr/day using mobile apps), evidence-based mHealth interventions may have significant reach for this difficult-to-engage population.