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
基本信息
- 批准号:9895327
- 负责人:
- 金额:$ 28.61万
- 依托单位:
- 依托单位国家:美国
- 项目类别:
- 财政年份:2020
- 资助国家:美国
- 起止时间:2020-03-11 至 2022-02-28
- 项目状态:已结题
- 来源:
- 关键词:AddressAgeAttentionBehavioralBirthCesarean sectionCharacteristicsChildChild HealthComputer softwareComputerized Medical RecordConceptionsConflict (Psychology)ConsentCountyDataData AnalysesDevelopmentDimensionsDiseaseEgoEnvironmentEthnic OriginFamilyFamily RelationshipFamily dynamicsFamily health statusFamily memberFutureHealthHealth behaviorHealthcare SystemsIndividualInterviewLearningLifeLife Cycle StagesLinkMajor Depressive DisorderMaternal HealthMaternal MortalityMaternal and Child HealthMeasurementMeasuresMediatingMedical RecordsMethodsModelingMood DisordersMothersNamesNatureNorth CarolinaOutcomeParentsParticipantPathway interactionsPersonal SatisfactionPoliciesPopulation ResearchPregnancyPregnant WomenPrenatal careProcessPropertyPsychosocial FactorRaceResearchResearch PersonnelRiskRoleSamplingScienceSelf EfficacyShapesSmokingSocial ClassSocial EnvironmentSocial NetworkSocial supportSourceStressStructureTabletsTestingUnited StatesWomanWomen&aposs HealthWorkantepartum depressioncritical perioddensityexperiencefamily influencefamily structurefamily supporthealth dataimprovedin uteroinnovationmaternal depressionmaternal morbiditymeetingsmembernovelpopulation healthpregnancy hypertensionprogramspsychosocialrural residencesocialsocial engagementstandard measuresuburbtool
项目摘要
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.
项目摘要
项目成果
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