How to best convey continuous outcomes in patient decision aids

IF 9 3区 医学 Q1 MEDICINE, GENERAL & INTERNAL
Glyn Elwyn, Marie Anne Durand, Thomas Agoritsas, Martin Mayer
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Abstract

The work of transforming scientific publications into tools that can support people in comparing treatments, tests and other interventions has been driven by efforts to support shared decision-making. The International Patient Decision Aids Standards (IPDAS) Collaboration has published many articles that guide this process. IPDAS, and others in this field, have considered the challenges of representing complex concepts such as effect sizes, ORs and relative risk rates in terms and formats that are easier to understand by people with varying levels of health literacy and numeracy. The underlying task is how to simplify research results without misleading people, which is essential when communicating healthcare information. Selecting outcome probabilities and comparing data collected from different populations with various study designs would be misleading. Further, only providing relative instead of absolute risk estimates would lead to misinterpretation in most situations, framing that affects both professionals and patients.1 For example, imagine a person with a 4% 10-year risk of breast cancer recurrence: telling that person their risk of breast cancer coming back could be cut in half, or reduced by 50%, using treatment Y (relative risk) is misleading. The more informative approach would be telling them their risk could be reduced from 4% to 2% (absolute risk), a risk that is perhaps even clearer if portrayed in natural frequency (n in 100). This article tackles the challenge of untangling complicated, heterogeneous evidence to deliver comparative information to non-scientists while at the same time avoiding misrepresenting the underlying data. Our focus here is to describe some of the editorial challenges of presenting complex scientific information, particularly when published as continuous outcomes in ways that are accurate yet accessible to a broad public, irrespective of their health literacy and numeracy levels. Those editorial challenges have materialised when developing tools to promote shared decision-making. The …
如何在患者决策辅助工具中最好地传达连续性结果
将科学出版物转化为可帮助人们比较治疗、检验和其他干预措施的工具的工作,是由支持共同决策的努力所推动的。国际患者决策辅助标准(IPDAS)合作组织发表了许多文章,为这一过程提供指导。IPDAS 以及该领域的其他组织已经考虑了如何用术语和格式来表示效应大小、OR 和相对风险率等复杂概念的挑战,以便让不同健康知识水平和计算能力的人更容易理解。其根本任务是如何在不误导人们的情况下简化研究结果,这对于传播医疗保健信息至关重要。选择结果概率和比较从不同人群和不同研究设计中收集的数据会产生误导。此外,在大多数情况下,只提供相对而非绝对的风险估计值会导致误解,这对专业人士和患者都有影响。1 例如,想象一个 10 年乳腺癌复发风险为 4% 的人,告诉他使用 Y 治疗方法(相对风险)可将其乳腺癌复发风险降低一半或 50%,这就是误导。更有参考价值的方法是告诉他们,他们的风险可以从 4% 降到 2%(绝对风险),如果用自然频率(n in 100)来描述这种风险,也许会更加清晰。本文探讨的难题是如何理清复杂的异质证据,向非科学家提供比较信息,同时避免对基础数据的错误表述。我们在此重点描述了编辑在呈现复杂的科学信息时所面临的一些挑战,尤其是在以连续性结果的形式发布时,既要准确无误,又要让广大公众能够理解,无论他们的健康知识水平和计算能力如何。在开发促进共同决策的工具时,这些编辑方面的挑战就显现出来了。这...
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来源期刊
BMJ Evidence-Based Medicine
BMJ Evidence-Based Medicine MEDICINE, GENERAL & INTERNAL-
CiteScore
8.90
自引率
3.40%
发文量
48
期刊介绍: BMJ Evidence-Based Medicine (BMJ EBM) publishes original evidence-based research, insights and opinions on what matters for health care. We focus on the tools, methods, and concepts that are basic and central to practising evidence-based medicine and deliver relevant, trustworthy and impactful evidence. BMJ EBM is a Plan S compliant Transformative Journal and adheres to the highest possible industry standards for editorial policies and publication ethics.
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