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运用“出声思考”法捕捉专家和新手糖尿病视网膜分级医师的临床决策过程。

Capturing the clinical decision-making processes of expert and novice diabetic retinal graders using a 'think-aloud' approach.

机构信息

Queens University Belfast, Centre for Public Health, Belfast, UK.

Orbis International, New York, NY, USA.

出版信息

Eye (Lond). 2022 May;36(5):1019-1026. doi: 10.1038/s41433-021-01554-6. Epub 2021 May 10.

Abstract

BACKGROUND

Diabetic eye screening programmes have been developed worldwide based on evidence that early detection and treatment of diabetic retinopathy are crucial to preventing sight loss. However, little is known about the decision-making processes and training needs of diabetic retinal graders, particularly in low- and middle-income countries.

OBJECTIVES

To provide data for improving evidence-based diabetic retinopathy training to help novice graders process fundus images more like experts.

SUBJECTS/METHODS: This is a mixed-methods qualitative study conducted in southern Vietnam and Northern Ireland. Novice diabetic retinal graders in Vietnam (n = 18) and expert graders in Northern Ireland (n = 5) were selected through a purposive sampling technique. Data were collected from 21st February to 3rd September 2019. The interviewer used neutral prompts during think-aloud sessions to encourage participants to verbalise their thought processes while grading fundus images from anonymised patients, followed by semi-structured interviews. Thematic framework analysis was used to identify themes, supported by illustrative quotes from interviews. Mann-Whitney U tests were used to compare graders' performance.

RESULTS

Expert graders used a more systematic approach when grading images, considered all four images per patient and used available software tools such as red-free filters prior to making a decision on management. The most challenging features for novice graders were intra-retinal microvascular abnormalities and new vessels, which were more accurately identified by experts.

CONCLUSION

Taking more time to grade fundus images and adopting a protocol-driven "checklist" approach may help novice graders to function more like experts.

摘要

背景

基于早期发现和治疗糖尿病视网膜病变对预防视力丧失至关重要的证据,全球范围内已开发出糖尿病眼病筛查计划。然而,对于糖尿病视网膜病变分级师的决策过程和培训需求知之甚少,尤其是在低收入和中等收入国家。

目的

提供数据以改进基于证据的糖尿病视网膜病变培训,帮助新手分级师更像专家一样处理眼底图像。

受试者/方法:这是在越南南部和北爱尔兰进行的一项混合方法定性研究。通过目的性抽样技术,在越南选择了 18 名新手糖尿病视网膜分级师和北爱尔兰的 5 名专家分级师。数据收集于 2019 年 2 月 21 日至 9 月 3 日。在“出声思考”过程中,访谈者使用中立提示鼓励参与者在对匿名患者的眼底图像进行分级时表达他们的思维过程,然后进行半结构化访谈。使用主题框架分析来识别主题,并通过访谈中的说明性引用来支持。使用曼-惠特尼 U 检验比较分级师的表现。

结果

专家分级师在分级图像时采用了更系统的方法,考虑了每位患者的四张图像,并在做出管理决策之前使用了红滤光片等可用的软件工具。新手分级师最具挑战性的特征是视网膜内微血管异常和新生血管,而这些特征在专家中被更准确地识别。

结论

花更多的时间来分级眼底图像,并采用基于协议的“检查表”方法,可能有助于新手分级师更像专家一样工作。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5eee/9046294/a888cf072faf/41433_2021_1554_Fig1_HTML.jpg

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