Identifying and reducing cognitive biases created by decision aids
Identifying and reducing cognitive biases created by decision aids
批准号:
7364735
负责人:
PETER A UBEL
金额:
$42.79万
依托单位国家:
美国
项目类别:
财政年份:
2000
资助国家:
美国
项目状态:
已结题
起止时间:
2000-07-01 至 2012-07-31
关键词:
AddressAdvisory CommitteesAffectAffectiveAreaCaringClinicalCognitionCognitiveCollaborationsComputer information processingDecision AidDecision MakingDevelopmentElementsEmotionalEnsureExpert OpinionFaceFollow-Up StudiesGrantHealthInternationalLearningMedicalMethodsNumbersOutcomePamphletsPatient CarePatient PreferencesPatientsPlayPopulationProbabilityProcessRandomizedRandomized Controlled Clinical TrialsReactionRecommendationResearchRoleScienceSourceStagingStandards of Weights and MeasuresSurveysTargeted ResearchTechniquesTest ResultTestingTimeUncertaintyVotingWorkbaseimprovedpreferenceresearch study
中文摘要
描述(由申请人提供):决策辅助(DAs)为患者提供关于偏好敏感决策的信息,其中患者的偏好可能在确定最佳决策方面发挥关键作用,并允许他们比在典型的临床遇到中有更多的时间来处理信息。国际患者辅助决策标准合作组织(IPDAS)是一个国际专家组,它建立了一份内容清单,鼓励辅助决策开发人员将这些内容写入辅助决策标准。然而,它没有提供关于如何呈现此类内容或如何确保此类内容不会产生决策偏差的指导。我们最初的资助旨在识别和减少由DAs产生的认知偏差。我们发现了可能由自动识别产生的多种认知偏差,并开发了几种减少或消除这些偏差的实用技术。但我们的工作还没有完成。为了扩大我们的成就并响应IPDAS的建议,我们提议针对DAs可能产生的其他几个偏见进行研究,并开发消除或减少它们的技术。此外,我们建议开展研究,不仅关注认知在人们决策中的作用,还关注情感的作用。因此,我们计划确定当患者使用决策辅助工具时可能出现的决策偏差类型,无论这些偏差是通过认知过程还是情感过程产生的,并确定减少它们的方法。具体而言,我们旨在探讨与决策辅助相关的四个偏差来源:(1)模糊概率的呈现;(2)关于概率的上下文信息的呈现;(3)人们对健康结果的情感反应;(4)人们在单一决策中整合概率和效用的方法。对于每个来源,我们将确定影响患者决策的多个因素。我们建议确定每个问题的范围,描述导致偏差的情况,以及减少或消除偏差的测试方法。我们所有的研究都将使用已有决策辅助工具的材料。我们的方法包括两个不同的研究阶段。在第一阶段,我们使用迭代随机调查实验来探索哪些决策辅助元素会产生偏见。我们将向人们展示假设的医疗决策,基于真实决策辅助工具的材料,以及人们决策任务的各个方面,以检验关于如何最大限度地减少决策偏差的假设。我们的初步研究将考虑相关因素的一个子集,后续研究将深入研究在我们的第一次实验中重要的因素,并测试由于功率和复杂性原因未包括在内的其他因素。在第二阶段,我们将展示我们的第一阶段的结果对病人护理的相关性。对于每一个偏倚来源,我们的研究将以一项随机试验的消除偏倚技术交付给患者群体。我们的研究旨在改善患者决策辅助工具,即为患者提供医疗决策信息的小册子、网站或视频,并帮助他们做出最符合自己偏好的决定。虽然辅助决策的内容已经有了国际标准,但我们的研究结果将帮助辅助决策开发者了解如何在辅助决策中最好地呈现信息,以避免认知和情感偏见。这项工作对于确保患者充分了解情况并能够参与有关其医疗保健的决策至关重要。
英文摘要
DESCRIPTION (provided by applicant): Decision aids (DAs) provide patients with information about preference sensitive decisions in which patients' preferences are likely to play a key role in determining what the best decision is and allow them more time to process the information than they would in a typical clinical encounter. An international group of experts, the International Patient Decision Aids Standards (IPDAS) Collaboration, has established a list of content that decision aid developers are encouraged to put into DAs. However, it provided no guidance about how to present such content, or how to make sure such content does not create decision biases. Our original grant aimed to identify and reduce cognitive biases created by DAs. We identified multiple cognitive biases that could be created by DAs and have developed several practical techniques for reducing or eliminating these biases. But our work is not done. To extend our accomplishments and respond to the IPDAS recommendations, we are proposing to conduct research targeting several additional biases that are potentially created by DAs and developing techniques to eliminate or reduce them. In addition, we propose to conduct studies that focus not only on the role that cognition plays in people's decisions, but also the role of affect. We thus plan to identify the kind of decision biases likely to arise when patients use decision aids, regardless of whether those biases arise through cognitive or affective processes, and identify ways to reduce them. Specifically, we aim to explore four sources of biases relevant to decision aids: (1) presentation of ambiguous probabilities (2) presentation of contextual information about probabilities (3) people's affective reaction to health outcomes, and (4) people's methods of integrating probability and utility in a single decision. For each source, we will identify multiple factors which bias patient decisions. We propose to identify the scope of each problem, delineate the circumstances under which biases result, and test methods for reducing or eliminating the biases. All our studies will use materials from pre-existing decision aids. Our approach includes two distinct research stages. In the first stage, we use iterative randomized survey experiments to explore which decision aid elements generate bias. We will present people with hypothetical medical decisions, based on material from real decision aids, and vary aspects of the decision task across people, to test hypotheses about how to minimize decision biases. Our initial studies will consider a subset of the relevant factors, and follow-up studies will drill down on factors that are significant in our first experiments and also test additional factors not included due to power and complexity reasons. In the second stage, we will demonstrate the relevance of our first-stage results for patient care. For each source of bias, our research will culminate with a randomized trial of a debiasing technique delivered to a patient population. Relevance Statement Our research aims to improve patient decision aids, which are booklets, websites, or videos that provide patients with information about medical decisions and help them to make the decision that best matches their own preferences. While international standards exist for the content of decision aids, our results will help decision aid developers know how to best present the information in decision aids so as to avoid cognitive and emotional biases. This work is essential to ensuring that patients are fully informed and able to participate in decision making regarding their medical care.
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批准号:6753121
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项目类别:
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资助金额:$2.79万
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财政年份:2003
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负责人:PETER A UBEL
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依托单位:
Identifying and reducing cognitive biases created by decision aids
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