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改变研究文化以解决试验招募地点与疾病负担最重人群居住地之间的不匹配问题:一项定性研究。

Shifting research culture to address the mismatch between where trials recruit and where populations with the most disease live: a qualitative study.

机构信息

Nuffield Department of Primary Care Health Sciences, University of Oxford, Radcliffe Observatory Quarter, Woodstock Road, Oxford, OX2 6GG, UK.

出版信息

BMC Med Res Methodol. 2021 Apr 21;21(1):80. doi: 10.1186/s12874-021-01268-z.

DOI:10.1186/s12874-021-01268-z
PMID:33882874
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC8058580/
Abstract

BACKGROUND

Research participation is beneficial to patients, clinicians and healthcare services. There is currently poor alignment between UK clinical research activity and local prevalence of disease. The National Institute of Health Research is keen to encourage chief investigators (CIs) to base their research activity in areas of high patient need, to support equity, efficiency and capacity building. We explored how CIs choose sites for their trials and suggest ways to encourage them to recruit from areas with the heaviest burden of disease.

METHODS

Qualitative, semi-structured telephone interviews with a purposive sample of 30 CIs of ongoing or recently completed multi-centre trials, all of which were funded by the UK National Institute of Health Research.

RESULTS

CIs want to deliver world-class trials to time and budget. Approaching newer, less research-active sites appears risky, potentially compromising trial success. CIs fear that funders may close the trial if recruitment (or retention) is low, with potential damage to their research reputation. We consider what might support a shift in CI behaviour. The availability of 'heat maps' showing the disparity between disease prevalence and current research activity will help to inform site selection. Embedded qualitative research during trial set up and early, appropriate patient and public involvement and engagement can provide useful insights for a more nuanced and inclusive approach to recruitment. Public sector funders could request more granularity in recruitment reports and incentivise research activity in areas of greater patient need. Accounts from the few CIs who had 'broken the mould' suggest that nurturing new sites can be very successful in terms of efficient recruitment and retention.

CONCLUSION

While improvements in equity and capacity building certainly matter to CIs, most are primarily motivated by their commitment to delivering successful trials. Highlighting the benefits to trial delivery is therefore likely to be the best way to encourage CIs to focus their research activity in areas of greatest need.

摘要

背景

参与研究对患者、临床医生和医疗服务有益。目前,英国的临床研究活动与当地疾病流行情况之间存在着严重的不一致。英国国家卫生研究院(National Institute of Health Research)热衷于鼓励首席研究员(CIs)将其研究活动集中在高需求患者所在的地区,以支持公平、效率和能力建设。我们探讨了 CIs 如何选择其试验地点,并提出了一些鼓励他们从疾病负担最重的地区招募患者的方法。

方法

对正在进行或最近完成的 30 项多中心试验的 CIs 进行了有针对性的半结构式电话访谈,这些试验均由英国国家卫生研究院资助。

结果

CIs 希望按时、按预算开展世界级的试验。接近较新、研究活动较少的站点似乎存在风险,可能会影响试验的成功。CIs 担心,如果招募(或保留)率低,资助者可能会关闭试验,从而损害他们的研究声誉。我们考虑了可能支持 CIs 行为转变的因素。提供显示疾病流行率与当前研究活动之间差异的“热点图”将有助于指导站点选择。在试验设置和早期阶段嵌入定性研究,以及适当的患者和公众参与和参与,可以为更细致和包容的招募方法提供有用的见解。公共部门资助者可以要求在招募报告中提供更详细的信息,并鼓励在患者需求更大的地区开展研究活动。少数几位“打破常规”的 CIs 的经验表明,培育新的站点在高效招募和保留方面可以非常成功。

结论

虽然公平和能力建设的改善对 CIs 确实很重要,但大多数 CIs 主要是出于成功开展试验的承诺。因此,强调对试验交付的好处可能是鼓励 CIs 将其研究活动集中在最需要的领域的最佳方式。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/62ec/8059268/6f33369df5a2/12874_2021_1268_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/62ec/8059268/fe8c50934883/12874_2021_1268_Fig1_HTML.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/62ec/8059268/6f33369df5a2/12874_2021_1268_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/62ec/8059268/fe8c50934883/12874_2021_1268_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/62ec/8059268/f3369b89b735/12874_2021_1268_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/62ec/8059268/27f45a792178/12874_2021_1268_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/62ec/8059268/90d202a09b0e/12874_2021_1268_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/62ec/8059268/6f33369df5a2/12874_2021_1268_Fig5_HTML.jpg

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