Preventing Alcohol Exposed Pregnancy among Urban Native Young Women During the COVID-19 Pandemic

COVID-19对美国印第安人和阿拉斯加原住民（AIAN）社区的破坏性影响一直是 记录良好，主要关注保留地社区，往往是农村和偏远地区。但更多 超过72%的AIAN居住在城市环境中，占种族群体的大多数，但也有一小部分-通常不到20%。 1% -大多数城市社区。许多城市的AIAN与部落社区和文化紧密相连 做法，通常在城市地区和保留地之间旅行以参加家庭活动或 重要的文化庆典和仪式。然而，这个群体可能会经历不同的文化， 与那些生活在保留地的人相比，这一流行病的社会和经济影响。那些 差异可能对酒精暴露妊娠（AEP）风险至关重要。一般人群的早期数据 这表明青年人饮酒增加，妇女获得有效避孕药具的机会减少。的 联合使用可能会增加AEP的风险，对于城市AIAN年轻女性-通常当地 资源-这种风险可能特别高。然而，随着研究努力争先恐后地监测最危险的 在大流行病中，这一人群很脆弱，往往被忽视。我们对这一现象的影响 COVID-19，酒精使用，性活动或避孕药具使用的变化，以评估城市人群的风险 人工智能。同样，我们对这些年轻女性如何能够找到适应力， 他们的社区有能力克服这一流行病带来的困难， 疫苗的承诺我们的项目，本土WYSE选择，使用随机试验来评估文化 将适当的AEP预防计划转化为智能手机应用程序，用于城市AIAN年轻女性（16岁- 20)全国范围内。随着我们的研究基础设施的到位，我们有机会利用行为的变化， 城市AIAN年轻女性，她们的家庭和社区的态度和看法，因为他们浏览 大流行病的动态变化。我们将（1）包括额外的调查措施， 700，以捕捉四个主要领域不断变化的疫情：（a）COVID-19疾病、风险暴露和安全;（B） 社会和经济影响;（c）对COVID-19疫苗的态度、经验和现状;以及（d）文化和 历史创伤的影响。为了将这些发现结合起来，我们将（2）对以下人员进行深入访谈 根据基线调查答复有目的地选择参与者。为了最大限度地了解 我们将招募和面试年轻人， 来自我们RCT样本的女性（n=32）。我们还将定期采访选定的参与者（n=8） 每隔两年进行一次，以便随着大流行情况的变化纵向记录他们的经验。与 这种定性的设计-即横截面的见解补充了城市AIAN年轻的纵向视图 妇女在不断变化的环境中的历程-我们将能够将我们的统计结果 在一个灵活的解释框架内。

The devastating impact of COVID-19 on American Indian and Alaska Native (AIAN) communities has been well-documented, with substantial focus on reservation communities, often rural and remote. However, more than 72% of AIANs reside in urban settings, a majority of the racial group, but a small fraction – often less than 1% - of most urban communities. Many urban AIANs are tightly connected to tribal communities and cultural practices, commonly traveling between urban areas and reservations to participate in family events or important cultural celebrations and ceremonies. However, this group is likely to experience different cultural, social, and economic impacts of the pandemic compared to those living in reservation settings. Those differences are likely critical to alcohol-exposed pregnancy (AEP) risk. Early data in the general population indicate increased alcohol use by youth, and decreased access to effective contraception among women. The combination is likely to increase risk of AEP, and for urban AIAN young women – often with limited local resources – that risk may be especially elevated. Yet, as research efforts scramble to monitor risk of the most vulnerable in a pandemic, this demographic often becomes invisible. We know little about the impact of COVID-19, the changes in alcohol use, sexual activity, or contraceptive use to assess risk among urban AIANs. Similarly, we know little about the way in which these young women are able to find resilience and strength in their communities to overcome the hardships presented by the pandemic or to engage in the promise of vaccines. Our project, Native WYSE CHOICES, uses a randomized trial to evaluate a culturally appropriate AEP prevention program translated to a smartphone app for urban AIAN young women (ages 16- 20) nationally. With our research infrastructure in place, we have the opportunity to tap shifts in behaviors, attitudes, and perceptions of urban AIAN young women, their families, and communities as they navigate the changing dynamics of the pandemic. We will (1) include additional survey measures with a national sample of 700 to capture the evolving pandemic in four main areas: (a) COVID-19 disease, risk exposure, and safety; (b) social and economic impacts; (c) COVID-19 vaccine attitudes, experience, and status; and (d) cultural and historical trauma impacts. To contextualize these findings, we will (2) conduct in-depth interviews with participants purposively selected based on baseline survey responses. To maximize insights in the diversity of experience of the pandemic and gain timely, in-the-moment, insights, we will recruit and interview young women from our RCT sample (n=32) over 2 years. We will also interview selected participants (n=8) at regular intervals over 2 years to capture their experiences longitudinally as circumstances of the pandemic shift. With this qualitative design – i.e. cross-sectional insights complemented by a longitudinal view of urban AIAN young women’s journey through the changing circumstances – we will be able to integrate our statistical findings within an agile interpretive frame.