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Understanding Family Networks and Implications for Maternal Health

Understanding Family Networks and Implications for Maternal Health
了解家庭网络及其对孕产妇健康的影响
批准号:
9895327
负责人:
LISA D PEARCE
金额:
$28.61万
依托单位国家:
美国
项目类别:
财政年份:
2020
资助国家:
美国
项目状态:
已结题
起止时间:
2020-03-11 至 2022-02-28

项目摘要

项目成果

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中文摘要
翻译
项目摘要 这项新颖的探索性研究将社会网络方法应用于概念化和测量 孕妇的家庭背景。我们将研究母亲自我定义的总体结构是如何 家庭网络及其内部互动的质量通过两个途径影响孕产妇健康: 健康行为和社会心理健康。以前关于家庭和产妇保健的研究主要集中在 父母关系状况或“家庭结构”、父母间或父母与 儿童,或有关家庭支持与健康的全球性问题。我们的研究通过收集自我- 网络数据,从孕妇对他们的家庭,以捕捉结构和互动特性, 家庭我们的两个具体目标是(1)收集400个家庭网络数据和健康及出生结果数据 孕妇,和(2)测试一个概念模型,将家庭网络特征与孕产妇健康联系起来 通过行为和社会心理途径取得成果。为了实现这些目标,我们将制定一个配额, 从一个医疗保健系统的电子病历中抽取400名妇女(n=400), 主要分布在北卡罗来纳州的两个县。样本将在种族/民族、社会阶层和城市方面多样化, 郊区或农村住宅。怀孕四个月或五个月的妇女自愿同意 研究人员将参加一个45分钟的采访,其中包括一组结构化问题来衡量他们的家庭 网络和支持,冲突和控制跨越关系。我们还将包括结构较少的 问题来了解我们是否忽视了对健康至关重要的家庭动力学。网络数据我们 使用EgoWeb 2.0收集的平板电脑将进行定量分析,以检查家庭的几个方面 网络,并调查这些差异如何与孕产妇和儿童健康成果有关。我们还将 评估这些关联是否可以用女性的健康行为或心理社会状况来解释, 存在。我们将把访谈中结构性较弱的部分转录成定性数据,以便进行分析, 我们可能忽略或误解了家庭背景的哪些方面。这项研究的发现将引发 新的研究和激励政策和方案,关注更丰富的家庭动态及其 与健康有关。此外,我们使用电子病历对孕妇进行抽样,并收集健康和社会信息, 数据将为人口健康研究建立新的、开创性的替代方案。
英文摘要
PROJECT ABSTRACT This novel, exploratory research applies a social network approach to the conceptualization and measurement of pregnant women's family contexts. We will examine how the overarching structure of mothers' self-defined family networks, and the quality of interactions within them, shape maternal health through two pathways: health behaviors and psychosocial well-being. Prior research on family and maternal health focuses primarily on parents' relationship status or “family structure,” dyadic relationship quality between parents or parent and child, or global questions about family support in relation to health. Our research innovates by collecting ego- network data from pregnant women about their families to capture the structural and interactive properties of families. Our two specific aims are to (1) collect family network data and health and birth outcome data for 400 pregnant women, and (2) test a conceptual model linking family network characteristics to maternal health outcomes through behavioral and psychosocial pathways. To accomplish these aims, we will develop a quota sample of 400 women (n=400) from the electronic medical records of one health care system that is predominant in two counties of NC. The sample will be diverse in race/ethnicity, social class, and urban, suburban, or rural residence. Women in their fourth or fifth month of pregnancy who voluntarily consent to the study will participate in a 45-minute interview that includes a structured set of questions to measure their family networks and the support, conflict, and control moving across ties. We will also include less-structured questions to understand if we are overlooking family dynamics that matter for health. The network data we collect on tablets using EgoWeb 2.0 will be analyzed quantitatively, to examine several dimensions of family networks and investigate how variance in those relates to maternal and child health outcomes. We will also assess whether any of these associations are explained by women's health behaviors or psychosocial well- being. We will transcribe the less-structured parts of the interview into qualitative data for analyses to uncover which aspects of family context we might be missing or misunderstanding. Findings from this study will spark new research and motivate policies and programs that are attentive to a richer set of family dynamics and their bearing on health. Moreover, our use of EMRs for sampling pregnant women and collecting health and social data will model new, groundbreaking alternatives for population health research.
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Population Science Training Grant
Population Science Training Grant
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