Alison Booth, Catriona McDaid, Ashley Scrimshire, Harvinda Singh, A. Scantlebury, C. Hewitt
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The trials have different designs, address different needs and demonstrate recruitment planning across Trauma centres, NHS Trusts and special educational settings. We describe our use of national freely available datasets, such as those provided by NHS Digital and the Office for National Statistics, to identify potential recruitment sites with consideration of health status, socio-economic status and ethnicity as well as clinical and risk factors to support inclusivity. For all three studies, we produced lists of potential recruitment sites in excess of the number anticipated as necessary to meet the recruitment targets. Discussion We reflect on the challenges to our approach and some potential future developments. The datasets used are all free to use but each has their limitations. Agreeing search parameters, acceptable proxies and identifying the appropriate datasets, then cross referencing between datasets takes considerable time and particular expertise. The case studies are trials, but the methods are generalisable for various other study types. Conclusion Through these exemplars, we aim to build on the NIHR INCLUDE project, by providing trialists with a much needed practical approach to embedding EDI into trial design at the grant application stage.","PeriodicalId":74312,"journal":{"name":"NIHR open research","volume":"82 12","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-04-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Using publicly available UK datasets to identify recruitment sites to maximise inclusion of under-served groups: three case studies\",\"authors\":\"Alison Booth, Catriona McDaid, Ashley Scrimshire, Harvinda Singh, A. Scantlebury, C. 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引用次数: 0
摘要
背景 有确凿证据表明,研究中招募的人员并不总是代表与研究最相关的人群。在研究过程中,研究设计的制定和资助决策都需要考虑是否纳入服务不足的人群。目前的实用指南侧重于设计和修改参与者招募与保留方法,但尚未涉及招募地点的选择。方法 我们介绍了三项由英国国家卫生研究院(NIHR)资助的试验的案例研究,以展示如何利用可公开获得的英国人口数据集来帮助识别服务不足的群体,并将其纳入试验。这些试验具有不同的设计,针对不同的需求,并展示了创伤中心、NHS 信托基金会和特殊教育机构的招募规划。我们介绍了如何利用国家免费提供的数据集(如由 NHS Digital 和国家统计局提供的数据集)来确定潜在的招募地点,同时考虑健康状况、社会经济状况、种族以及临床和风险因素,以支持包容性。对于所有三项研究,我们都编制了潜在招募地点清单,其数量超过了预期数量,这是实现招募目标所必需的。讨论 我们反思了我们的方法所面临的挑战以及未来可能的发展。我们使用的数据集都是免费的,但每个数据集都有其局限性。商定搜索参数、可接受的替代方法、确定适当的数据集,然后在数据集之间进行交叉引用,这些都需要大量的时间和特殊的专业知识。案例研究是试验研究,但这些方法可用于其他各种研究类型。结论 通过这些范例,我们旨在以 NIHR INCLUDE 项目为基础,为试验人员提供急需的实用方法,以便在申请基金阶段将 EDI 嵌入试验设计中。
Using publicly available UK datasets to identify recruitment sites to maximise inclusion of under-served groups: three case studies
Background There is strong evidence that those recruited into studies are not always representative of the population for whom the research is most relevant. Development of the study design and funding decisions are points in the research process where considerations about inclusion of under-served populations may usefully be made. Current practical guidance focuses on designing and modifying participant recruitment and retention approaches but an area that has not been addressed is recruitment site selection. Methods We present case studies of three NIHR funded trials to demonstrate how publicly available UK population datasets can be used to facilitate the identification of under-served communities for inclusion in trials. The trials have different designs, address different needs and demonstrate recruitment planning across Trauma centres, NHS Trusts and special educational settings. We describe our use of national freely available datasets, such as those provided by NHS Digital and the Office for National Statistics, to identify potential recruitment sites with consideration of health status, socio-economic status and ethnicity as well as clinical and risk factors to support inclusivity. For all three studies, we produced lists of potential recruitment sites in excess of the number anticipated as necessary to meet the recruitment targets. Discussion We reflect on the challenges to our approach and some potential future developments. The datasets used are all free to use but each has their limitations. Agreeing search parameters, acceptable proxies and identifying the appropriate datasets, then cross referencing between datasets takes considerable time and particular expertise. The case studies are trials, but the methods are generalisable for various other study types. Conclusion Through these exemplars, we aim to build on the NIHR INCLUDE project, by providing trialists with a much needed practical approach to embedding EDI into trial design at the grant application stage.