接触有关疾病的媒体信息可能导致医生误诊类似的临床病例。
Exposure to media information about a disease can cause doctors to misdiagnose similar-looking clinical cases.
机构信息
Prof. Dr. Schmidt is professor, Department of Psychology, Erasmus University Rotterdam, Rotterdam, the Netherlands. Dr. Mamede is associate professor, Institute of Medical Education Research Rotterdam, Erasmus Medical Center, and associate professor, Department of Psychology, Erasmus University Rotterdam, Rotterdam, the Netherlands. Dr. van den Berge is resident, Department of Internal Medicine, Erasmus Medical Center, Rotterdam, the Netherlands. Prof. Dr. van Gog is professor, Department of Psychology, Erasmus University Rotterdam, Rotterdam, the Netherlands. Prof. Dr. van Saase is professor, Department of Internal Medicine, Erasmus Medical Center, Rotterdam, the Netherlands. Prof. Dr. Rikers is professor, Department of Psychology, Erasmus University Rotterdam, Rotterdam, the Netherlands.
出版信息
Acad Med. 2014 Feb;89(2):285-91. doi: 10.1097/ACM.0000000000000107.
PURPOSE
Anecdotal evidence indicates that exposure to media-distributed disease information, such as news about an outbreak, can lead physicians to errors; influenced by an availability bias, they misdiagnose patients with similar-looking but different diseases. The authors investigated whether exposure to media-provided disease information causes diagnostic errors and whether reflection (systematic review of findings) counteracts bias.
METHOD
In 2010, 38 internal medicine residents first read the Wikipedia entry about one or another of two diseases (Phase 1). Six hours later, in a seemingly unrelated study, they diagnosed eight clinical cases (Phase 2). Two cases superficially resembled the disease in the Wikipedia entry they had read (bias expected), two cases resembled the other disease they had not read about (bias not expected), and four were filler cases. In Phase 3, they diagnosed the bias-expected cases again, using reflective reasoning.
RESULTS
Mean diagnostic accuracy scores (Phase 2; range: 0-1) were significantly lower on bias-expected cases than on bias-not-expected cases (0.56 versus 0.70, P = .016) because participants misdiagnosed cases that looked similar to a Wikipedia description of a disease more often when they had read the Wikipedia description (mean = 0.61) than when they had not (mean = 0.29). Deliberate reflection (Phase 3) restored performance on bias-expected cases to pre-bias levels (mean = 0.71).
CONCLUSIONS
Availability bias may arise simply from exposure to media-provided information about a disease, causing diagnostic errors. The bias's effect can be substantial. It is apparently associated with nonanalytical reasoning and can be counteracted by reflection.
目的
有传闻证据表明，接触媒体传播的疾病信息，如有关疫情的新闻，可能导致医生犯错；受可得性偏差的影响，他们会错误诊断出具有相似但不同疾病的患者。作者研究了接触媒体提供的疾病信息是否会导致诊断错误，以及反思（对发现结果的系统回顾）是否能纠正偏差。
方法
2010 年，38 名内科住院医师首先阅读了维基百科上关于两种疾病之一的条目（第 1 阶段）。6 小时后，在一项看似无关的研究中，他们诊断了 8 个临床病例（第 2 阶段）。其中两个病例与他们在维基百科上读到的疾病条目表面上相似（预期偏差），两个病例与他们未读到的另一种疾病相似（非预期偏差），还有四个是填充病例。在第 3 阶段，他们使用反思推理再次诊断预期偏差病例。
结果
在预期偏差病例上的平均诊断准确性评分（第 2 阶段；范围：0-1）显著低于非预期偏差病例（0.56 对 0.70，P =.016），因为参与者在阅读了维基百科对疾病的描述后，更频繁地错误诊断出与描述相似的病例（平均 0.61），而不是在没有阅读描述的情况下（平均 0.29）。深思熟虑的反思（第 3 阶段）将预期偏差病例的表现恢复到了偏见前的水平（平均 0.71）。
结论
可得性偏差可能仅仅由于接触媒体提供的疾病信息而产生，导致诊断错误。这种偏差的影响可能是巨大的。它显然与非分析性推理有关，可以通过反思来纠正。
Zotero 插件