Community Based System Dynamics Models of Alcohol and Substance Exposed Pregnancy in Northern Plains American Indian Women

北部平原美洲印第安妇女酒精和物质暴露怀孕的社区系统动力学模型

• 批准号: 10271559
• 负责人: Arielle R. Deutsch
• 金额: $ 37.58万
• 依托单位: AVERA MCKENNAN
• 依托单位国家: 美国
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-10-01 至 2024-05-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10271559
• 关键词: Accounting; Address; Age; Alcohol consumption; Alcohol or Other Drugs use; Alcohols; American Indians; Area; Behavior; Biological Models; Birth; Case Management; Characteristics; Collaborations; Communities; Community Developments; Community Health; Complement; Complex; Data; Data Sources; Evaluation; Failure; Goals; Individual; Intervention; Lead; Legal; Literature; Marijuana; Methamphetamine; Methods; Modeling; Neurologic; Opioid; Outcome; Periodicity; Persons; Pharmacotherapy; Physiological; Policies; Policy Developments; Populations at Risk; Pregnancy; Pregnancy Rate; Pregnant Women; Prevention; Prevention program; Quality of Care; Race; Recommendation; Research; Research Personnel; Reservations; Risk; Risk Factors; Role; Strategic Planning; Surveys; System; Systems Integration; Testing; Tobacco; Translating; Translations; Woman; Work; alcohol measurement; alcohol prevention; base; behavior change; community based participatory research; community partnership; disparity reduction; dynamic system; health disparity; high risk; improved; in silico; innovation; interest; intervention program; intimate partner violence; models and simulation; northern plains; predictive modeling; predictive test; pregnancy prevention; pregnant; prescription opioid; programs; reproductive; simulation; socioeconomics; success; trend; unintended pregnancy

PROJECT SUMMARY Continued trends of alcohol and substance exposed pregnancy (ASEP) indicate a great need for higher quality ASEP-reduction programs, particularly those that address ASEP health disparities within at-risk populations and communities, such as American Indian (AI) women. These programs do not account for the broad constellation of factors pertinent to ASEP, in particular, the role of intimate partner violence (IPV), which forms a syndemic association with two other ASEP indicators (alcohol and substance use and unplanned pregnancy). System dynamics methods are effective strategies for understanding of how ASEP and this syndemic are nested within a broader system of interpersonal, intrapersonal, and institutional factors. This method is especially beneficial for addressing the current ASEP-related health disparities within AI communities. Community-based system dynamic models allow practitioners and policymakers to determine the best system areas for implementing policies and programs that will produce the biggest changes in ASEP. The current proposal uses community-based approaches to develop ASEP system models for AI women within two communities: a small metro and a neighboring reservation. These models allow for a researcher-community partnership to discover important system leverage points for ASEP intervention (reducing ASEP within pregnant women) and ASEP prevention (focusing on the cyclic relationship between IPV and alcohol and substance use). The goals of this project are to build and simulate system dynamic models that that represent the ASEP system in partnership with our highly collaborative community-researcher team. We will calibrate and validate these models utilizing a variety of community data sources, and then distinguish the most effective areas to target for reducing ASEP and ASEP predictors that a) generalize across communities and substance legality, and b) may be uniquely effective within specific communities or for specific substances. This work will be complemented by individual-level analyses which can estimate the strength of high-priority leverage points on individual ASEP and ASEP risk. The proposed research is significant as it accounts for the often-ignored underlying matrix of contributors which maintain community levels of ASEP and ASEP health disparities, and provides clear recommendations for high-impact methods to reduce ASEP within communities at need. This project is innovative due to the integration of system simulation and community-based approaches to address complexity, of this issue, and the integration of descriptive and predictive analyses to provide distinct empirically-based solutions to address these issues within a translational framework. The strong interdisciplinary team of researchers with unique, but complementary areas of expertise and the close working partnership between researchers and the communities of interest are together a powerful collaborative to facilitate project success and meaningful contributions to community health. Findings from this study provide critical information about highly effective ways of reducing ASEP and ASEP health disparities, as well as a clear mechanism for developing a strategic blueprint for systematic change within AI communities.

项目概要 酒精和物质暴露妊娠 (ASEP) 的持续趋势表明对更高质量的巨大需求 ASEP 减少计划，特别是那些解决高危人群中 ASEP 健康差异的计划 和社区，例如美洲印第安人 (AI) 妇女。这些计划并没有考虑到广泛的 与 ASEP 相关的一系列因素，特别是亲密伴侣暴力 (IPV) 的作用，它形成了 与其他两个 ASEP 指标（酒精和药物使用以及计划外 怀孕）。系统动力学方法是理解 ASEP 及其如何发挥作用的有效策略。 综合症嵌套在更广泛的人际、个人内部和制度因素系统中。这 该方法特别有利于解决人工智能中当前与 ASEP 相关的健康差异 社区。基于社区的系统动态模型使从业者和政策制定者能够确定 实施政策和计划的最佳系统领域，这些政策和计划将给 ASEP 带来最大的变化。这 目前的提案使用基于社区的方法为两岁以内的人工智能女性开发 ASEP 系统模型 社区：一个小型地铁和邻近的保留地。这些模型允许研究人员社区 合作伙伴关系发现 ASEP 干预的重要系统杠杆点（在 孕妇）和 ASEP 预防（重点关注 IPV 与酒精和酒精之间的循环关系） 物质使用）。该项目的目标是构建和模拟系统动态​​模型，该模型代表 ASEP 系统与我们高度协作的社区研究团队合作。我们将校准 并利用各种社区数据源验证这些模型，然后区分最有效的模型 减少 ASEP 的目标领域和 ASEP 预测因素 a) 跨社区和物质普遍适用 合法性，并且 b) 可能在特定群体内或对于特定物质具有独特的效力。这项工作将 辅之以个人层面的分析，可以估计高优先级杠杆点的强度 关于个人 ASEP 和 ASEP 风险。拟议的研究意义重大，因为它解释了经常被忽视的问题 维持 ASEP 社区水平和 ASEP 健康差异的贡献者的基本矩阵，以及 为减少社区内有需要的 ASEP 的高影响力方法提供了明确的建议。这 该项目具有创新性，因为它集成了系统模拟和基于社区的方法来解决 这个问题的复杂性，以及描述性和预测性分析的整合，以提供不同的 基于经验的解决方案在转化框架内解决这些问题。强者 跨学科研究人员团队具有独特但互补的专业领域和密切的工作 研究人员和感兴趣的社区之间的伙伴关系是一个强有力的合作 促进项目成功并为社区健康做出有意义的贡献。这项研究的结果提供 有关减少 ASEP 和 ASEP 健康差异的高效方法的关键信息，以及 为人工智能社区内的系统变革制定战略蓝图的明确机制。