AI4HealthyCities:关于纽约市心血管健康的社会决定因素的混合方法人种学研究方案。

BMJ public health Pub Date : 2025-08-18 eCollection Date: 2025-01-01 DOI:10.1136/bmjph-2024-002382
Anna-Maria Volkmann, Elizabeth Adamson, Emma Boxley, David Napier, Peter Speyer, Reekarl Pierre, Wenqin Zhang, Yongkang Zhang
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引用次数: 0

摘要

导言:心血管疾病是全球和纽约市发病率和死亡率的主要原因。在城市社区之间以及不同社会经济地位、种族和族裔背景的人群之间,患病率和风险因素仍然存在显著差异。这些差距是由健康的社会决定因素,包括住房、就业、获得医疗保健和结构性不平等等复杂的相互作用形成和维持的。这项研究建立在先前在AI4HealthyCities倡议下进行的定量研究的基础上,该倡议应用机器学习来识别心血管脆弱性和社会劣势的空间集群。这项研究通过产生关于代表性不足人口的分类定性数据,解决了这项工作中的关键差距。该研究还旨在探索特定社会决定因素可能导致心血管风险的机制,包括行为和人口中介的作用。通过结合生活经验和系统层面的观点,该研究将提供情境化的见解,以支持当地利益相关者设计更有效、更公平的干预措施。方法和分析:这项混合方法的人种学研究将分三个阶段收集数据:专家访谈、社区圆桌会议和纽约市三个行政区(布鲁克林、布朗克斯和皇后区)的脆弱性评估。定性数据将使用演绎和归纳相结合的方法进行分析。专题综合将用于确定各区之间和各区内部的模式。将与社区利益攸关方、一个研究指导小组和AI4HealthyCities全球专家委员会合作,审查研究设计和中期结果。伦理与传播:本研究已获得威尔康奈尔医学伦理委员会的伦理批准(代码:23-04025988)。该项目的研究结果将通过会议、演讲活动和同行评议出版物进行传播。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

AI4HealthyCities: a protocol for a mixed-method ethnographic study on the social determinants of cardiovascular health in New York City.

AI4HealthyCities: a protocol for a mixed-method ethnographic study on the social determinants of cardiovascular health in New York City.

AI4HealthyCities: a protocol for a mixed-method ethnographic study on the social determinants of cardiovascular health in New York City.

AI4HealthyCities: a protocol for a mixed-method ethnographic study on the social determinants of cardiovascular health in New York City.

Introduction: Cardiovascular disease is a leading cause of morbidity and mortality globally and in New York City. Significant disparities in prevalence and risk factors persist across city neighbourhoods and among populations of varying socio-economic status, racial and ethnic backgrounds. These disparities are shaped and sustained by the complex interplay of social determinants of health, including housing, employment, access to healthcare and structural inequities. This study builds on prior quantitative research conducted under the AI4HealthyCities initiative, which applied machine learning to identify spatial clusters of cardiovascular vulnerability and social disadvantage. This research addresses key gaps in that work by generating disaggregated, qualitative data on underrepresented populations. The study also aims to explore the mechanisms through which specific social determinants may contribute to cardiovascular risk, including the role of behavioural and demographic mediators. By combining lived experiences and system-level perspectives, the research will provide contextualised insights to support local stakeholders in designing more effective, equity-oriented interventions.

Methods and analysis: This mixed-method ethnographic study will collect data in three phases: expert interviews, community roundtables and vulnerability assessments across three New York City boroughs (Brooklyn, the Bronx and Queens). Qualitative data will be analysed using a combination of deductive and inductive approaches. Thematic synthesis will be used to identify patterns across and within boroughs. Study design and interim findings will be reviewed in collaboration with community stakeholders, a research steering group and the AI4HealthyCities Global Expert Council.

Ethics and dissemination: This study has received ethical approval from the Ethics Committee of Weill Cornell Medicine (code number: 23-04025988). The findings of the project will be disseminated via conferences, speaking engagements and peer-reviewed publications.

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