Preferences and predictors driving opioid-involved polysubstance use profiles and trajectories: Implications for improving care

项目摘要/摘要 最近服药过量死亡率的变化是由涉及多种物质的死亡迅速增加推动的， 最常见的包括阿片类药物，其次是兴奋剂。先前的研究已经发现重要的个体(例如， 黑人/非裔美国人种族、共病心理/身体健康)、社会(例如家庭支持)和社区 与PSU、治疗和结果相关的因素(例如，治疗可用性)。然而，人们对此知之甚少 关于可修改的个人层面的激励因素(例如，用来缓解戒断)和偏好驱动高- 危险多物质使用(PSU)行为(例如，静脉注射、涉及阿片类药物的PSU频率较高、 故意使用合成阿片类药物和同时使用物质)，这一点很重要，必须告知和 量身定做的治疗服务。行为经济学(BE)理论提供了一个新的框架和目标 了解药物使用偏好的措施，强调药物影响药物使用 复合体中不确定的负面结果的估值(即需求)和贬值(例如过量风险) 环境，并可为临床护理提供信息。这一点尤其关键，因为患有阿片类药物相关PSU的人 是最不可能得到有效的药物过量预防或治疗的人之一。正如我们所展示的，尽管 死于阿片类药物、兴奋剂或酒精过量的85%的人是在医疗机构中看到的 (例如，初级和精神卫生保健)，只有一小部分人得到有效的护理，这表明新的战略正在 需要能够在卫生系统中实施的卫生系统，这是这些人口的一个重要的共同触点。数据 是理解这些错综复杂的个人层面的模式、激励因素和偏好驱动的关键 PSU，以及已知的社区和社会因素，以改善对阿片类药物相关PSU患者的护理。 我们将进行一项前瞻性队列研究(N=400)，招募不同样本的服用阿片类药物的成年人- 参与PSU(过度抽样兴奋剂联合使用和黑人/非裔美国人以提高代表性)，从2 密歇根州的大型医疗系统。在基线注册后，我们将收集每周详细数据，以可靠地 捕捉使用和共同使用的细微差别和动态模式和动机(例如，同时或顺序， 吸毒过量等危险行为。)四个多星期。跨基线、4个月、8个月和12个月的其他衡量标准 (例如，行为经济选择偏好、共病心理/身体健康、功能、其他社会和 社区因素和治疗使用)将提供有关概况和纵向的全面信息 多发性硬化症的行为轨迹和治疗。队列数据将由利益相关者访谈补充，以 阐明患者和提供者对PSU的看法以及如何调整策略(例如，纳洛酮和低障碍 Moud处理)以提高摄取率。该项目将通过提供关键的新技术，对公共卫生产生重大影响 对PSU的动机和模式的洞察，是PSU配置文件中的选择偏好，以及细微差别 PSU和治疗的模式和轨迹，以提供可在 卫生系统，以改善多发性硬化症患者的不同人群的健康状况和预后。

Project Summary/Abstract Recent changes in overdose mortality are driven by rapid increases in polysubstance-involved deaths, most often including opioids followed by stimulants. Prior studies have found important individual (e.g., Black/African American race, comorbid mental/physical health), social (e.g., family supports), and community factors (e.g., treatment availability) associated with PSU, treatment, and outcomes. However, little is known about the modifiable individual-level motivators (e.g. use to alleviate withdrawal) and preferences driving high- risk polysubstance use (PSU) behaviors (e.g., intravenous use, higher frequency of opioid-involved PSU, intentional use of synthetic opioids, and simultaneous use of substances), which is important to inform and tailor treatment services. Behavioral economic (BE) theory provides a novel framework and objective measures to understand substance use preferences, emphasizing substance use is impacted by drug valuation (i.e., demand) and devaluing of uncertain negative outcomes (e.g., overdose risk) in complex environments and can inform clinical care. This is especially critical given that people with opioid-involved PSU are among the least likely to receive effective overdose prevention or treatments. As we have shown, although >85% of people who died from opioid, stimulant or alcohol-involved overdose are seen in healthcare settings (e.g., primary and mental health care), only a tiny fraction receive effective care, suggesting new strategies are needed that can be implemented in health systems, an important common touchpoint for this population. Data are critically needed to understand these intricate individual-level patterns, motivators and preferences driving PSU, along with known community and social factors, to improve care for people with opioid-involved PSU. We will conduct a prospective cohort study (N=400), recruiting a diverse sample of adults with opioid- involved PSU (over-sampling stimulant co-use and Black/African Americans to enhance representation) from 2 large health systems in Michigan. Following baseline enrollment, we will collect weekly detailed data to reliably capture nuanced and dynamic patterns and motivators of use and co-use (e.g., simultaneous or sequential, overdose risk behaviors, etc.) over four weeks. Additional measures across baseline, 4-,8-, and 12-months (e.g., behavioral economic choice preferences, comorbid mental/physical health, functioning, other social and community factors, and treatment use) will provide comprehensive information on profiles and longitudinal trajectories of PSU behaviors and treatment. Cohort data will be complemented by stakeholder interviews to elucidate patient and provider perspectives on PSU and how to tailor strategies (e.g., naloxone and low-barrier MOUD treatment) to enhance uptake. This project will have high public health impact by providing critical new insights on motives and patterns of PSU, BE choice preferences across PSU profiles, as well as nuanced patterns and trajectories of PSU and treatment to inform actionable strategies that can be implemented in health systems to improve health and outcomes across the diverse population of people with PSU.