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布拉德福德出生队列新冠病毒研究:一项适应性混合方法研究的方案,旨在收集关于新冠病毒对居住在布拉德福德的家庭中健康不平等影响的可操作情报。

The Born in Bradford COVID-19 Research Study: Protocol for an adaptive mixed methods research study to gather actionable intelligence on the impact of COVID-19 on health inequalities amongst families living in Bradford.

作者信息

McEachan Rosemary R C, Dickerson Josie, Bridges Sally, Bryant Maria, Cartwright Christopher, Islam Shahid, Lockyer Bridget, Rahman Aamnah, Sheard Laura, West Jane, Lawlor Deborah A, Sheldon Trevor A, Wright John, Pickett Kate E

机构信息

Bradford Institute for Health Research, Bradford Teaching Hospitals NHS Foundation Trust, Bradford Royal Infirmary, Duckworth Lane, Bradford, BD9 6RJ, UK.

Faculties of Life Sciences and Health Studies, University of Bradford, Richmond Road, Bradford, BD7 1DP, UK.

出版信息

Wellcome Open Res. 2020 Aug 13;5:191. doi: 10.12688/wellcomeopenres.16129.1. eCollection 2020.

DOI:10.12688/wellcomeopenres.16129.1
PMID:33029561
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC7523536/
Abstract

The UK COVID-19 lockdown has included restricting social movement and interaction to slow the spread of disease and reduce demand on NHS acute services. It is likely that the impacts of restrictions will hit the least advantaged disproportionately and will worsen existing structural inequalities amongst deprived and ethnic minority groups. The aim of this study is to deliver rapid intelligence to enable an effective COVID-19 response, including co-production of interventions, that address key issues in the City of Bradford, UK, and nationally. In the longer term we aim to understand the impacts of the response on health trajectories and inequalities in these. In this paper we describe our approach and protocol. We plan an adaptive longitudinal mixed methods approach embedded with Born in Bradford (BiB) birth cohorts which have rich existing data (including questionnaire, routine health and biobank). All work packages (WP) interact and are ongoing. WP1 uses co-production and engagement methods with communities, decision-makers and researchers to continuously set (changing) research priorities and will, longer-term, co-produce interventions to aid the City's recovery. In WP2 repeated quantitative surveys will be administered during lockdown (April-June 2020), with three repeat surveys until 12 months post-lockdown with an ethnically diverse pool of BiB participants (parents, children aged 9-13 years, pregnant women: total sample pool N=7,652, N=5,154, N=1,800). A range of health, social, economic and education outcomes will be assessed. In WP3 priority topics identified in WP1 and WP2 will be explored qualitatively. Initial priority topics include children's mental wellbeing, health beliefs and the peri/post-natal period. Feedback loops will ensure findings are fed directly to decision-makers and communities (via WP1) to enable co-production of acceptable interventions and identify future priority topic areas. Findings will be used to aid development of local and national policy to support recovery from the pandemic and minimise health inequalities.

摘要

英国的新冠疫情封锁措施包括限制社交活动和互动,以减缓疾病传播并减轻国民保健服务体系(NHS)急症服务的压力。这些限制措施的影响很可能对最弱势群体造成不成比例的冲击,并加剧贫困群体和少数族裔群体中现有的结构性不平等。本研究的目的是提供快速情报,以实现有效的新冠疫情应对措施,包括共同制定干预措施,解决英国布拉德福德市及全国范围内的关键问题。从长远来看,我们旨在了解应对措施对健康轨迹及其不平等现象的影响。在本文中,我们描述了我们的方法和方案。我们计划采用一种适应性纵向混合方法,该方法嵌入了布拉德福德出生队列研究(BiB),该队列拥有丰富的现有数据(包括问卷、常规健康数据和生物样本库)。所有工作包(WP)相互作用且正在进行中。工作包1采用与社区、决策者和研究人员共同制定和参与的方法,以持续设定(不断变化的)研究重点,并将在长期内共同制定干预措施,以帮助该市恢复。在工作包2中,将在封锁期间(2020年4月至6月)进行重复的定量调查,在封锁后12个月内进行三次重复调查,调查对象为具有不同种族背景的BiB参与者(父母、9至13岁儿童、孕妇:总样本量分别为N = 7,652、N = 5,154、N = 1,800)。将评估一系列健康、社会、经济和教育成果。在工作包3中,将对工作包1和工作包2中确定的优先主题进行定性探索。初步优先主题包括儿童心理健康、健康观念以及围产期/产后时期。反馈回路将确保研究结果直接反馈给决策者和社区(通过工作包1),以便共同制定可接受的干预措施,并确定未来的优先主题领域。研究结果将用于协助制定地方和国家政策,以支持从疫情中恢复,并尽量减少健康不平等现象。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4c0c/7523536/03dddeb839f7/wellcomeopenres-5-17704-g0000.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4c0c/7523536/03dddeb839f7/wellcomeopenres-5-17704-g0000.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4c0c/7523536/03dddeb839f7/wellcomeopenres-5-17704-g0000.jpg

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