Improving shared decision making in cancer screening

摘要 共享决策(SDM)是许多指南在医疗时提出的常规建议 决定是对偏好敏感的，比如选择接受前列腺癌或乳腺癌筛查。 SDM通常包括提供决策辅助，即书面信息表等教育工具。 然而，许多这样的工具只是在行为科学研究理论上站不住脚，而且往往 忽视算术和识字研究中的知识。关于健康算术的文献很清楚， 许多患者很难理解单一的风险估计，更不用说多个反补贴估计了。而当 普通人的阅读水平是7-8年级，决策辅助工具通常是在9年级或更高的水平上写的 阅读水平。此外，虽然辅助决策通常要求患者澄清他们的价值观，但行为科学 一项关于情感预测的研究表明，引发人们对不熟悉的健康状况的偏好是具有挑战性的 而且容易出错。此外，尽管决策的理论方法强调逐字逐句 表示和数值细节，现代方法，包括双进程理论和模糊迹 理论上，强调理解底线的“要旨”。我们假设决策有助于 复杂的信息共享，以及对许多不熟悉的健康状态的偏好诱导，使 给人们带来沉重的负担，导致“信息过载”，阻碍了人们发挥作用的能力 决定。这项建议的目标是围绕参与者的理解进行一系列研究 在癌症筛查决策辅助工具中提供的信息，并确定它与信息的关系 超载。了解这一点将有助于优化SDM的交付和患者决策辅助工具的设计。Dr。 西格里德·卡尔松是纪念斯隆·凯特琳癌症中心的助理主治流行病学家，该中心是 世界一流的癌症中心拥有强大的癌症研究基础设施。这是K22的过渡生涯 发展奖是候选人在前列腺癌筛查方面先前研究的一个合乎逻辑的进步， 并将使她获得更多的技能和经验，以达到独立调查员的地位。通过 建议的职业发展活动，申请人寻求补充她的医学背景和 具有定性方法、行为科学和SDM方面技能的定量专业知识。卡尔松医生很长时间- 学期的职业目标是成为一名独立的、由NIH资助的调查员，并致力于 改进SDM的实际应用，优化癌症筛查的风险分层方法。 追求这一奖项将给她技能，经验和提交2个更大的所需的初步数据 竞争性R01拨款申请1)开发避免信息的癌症筛查决策辅助 在随机环境中过载并测试其对SDM结果的有效性，以及2)制定决策 将支持工具整合到电子病历中，并测试其对健康结果的有效性。

ABSTRACT Shared decision making (SDM) is a routine recommendation made by many guidelines when medical decisions are preference-sensitive, such as choosing to undergo prostate cancer or breast cancer screening. SDM typically includes provision of a decision aid, ie, an educational tool such as a written information sheet. However, many such tools are only weakly grounded in behavioral science research theory and often disregard knowledge from numeracy and literacy research. Literature on health numeracy is quite clear that many patients struggle to understand a single risk estimate, let alone multiple countervailing estimates. While the average person reads at a 7–8th grade level, decision aids are typically written at a 9th grade or higher reading level. Additionally, while decision aids often ask patients to clarify their values, behavioral science research on affective forecasting has shown that eliciting preferences for unfamiliar health states is challenging and error prone. Further, although theoretical approaches to decision making emphasize verbatim representations and numerical detail, modern approaches, including dual-process theory and fuzzy-trace theory, emphasize understanding the bottom-line “gist.” We hypothesize that decision aids that involve complex information sharing, along with preference elicitation for numerous unfamiliar health states, place a substantial burden on people that leads to “information overload,” which hinders the ability to make good decisions. The objective of this proposal is to conduct a series of studies around participants’ comprehension of the information presented in cancer screening decision aids and determine how it relates to information overload. Knowing this will inform optimization of SDM delivery and the design of patient decision aids. Dr. Sigrid Carlsson is an Assistant Attending Epidemiologist at Memorial Sloan Kettering Cancer Center, one of the world’s premier cancer centers with a strong cancer research infrastructure. This K22 Transition Career Development Award is a logical progression from the candidate’s prior research in prostate cancer screening, and will allow her to gain additional skills and experience to reach independent investigator status. Through the proposed career development activities, the applicant seeks to complement her medical background and quantitative expertise with skills in qualitative methods, behavioral sciences, and SDM. Dr. Carlsson’s long- term career goal is to become an independent, NIH-funded investigator with a research program committed to improving the practical application of SDM and optimization of risk-stratified approaches to cancer screening. Pursuing this award will give her the skills, experience, and preliminary data needed to submit 2 larger competitive R01 grant applications to 1) develop a cancer screening decision aid that avoids information overload and test its effectiveness on SDM outcomes in a randomized setting, and 2) develop a decision support tool to be integrated in the electronic medical record and test its effectiveness on health outcomes.