Zikmund-Fisher Brian J, Ubel Peter A, Smith Dylan M, Derry Holly A, McClure Jennifer B, Stark Azadeh, Pitsch Rosemarie K, Fagerlin Angela
VA Health Services Research & Development Center of Excellence, VA Ann Arbor Healthcare System, Ann Arbor, MI, USA.
Patient Educ Couns. 2008 Nov;73(2):209-14. doi: 10.1016/j.pec.2008.05.010.
To experimentally test whether using pictographs (image matrices), incremental risk formats, and varied risk denominators would influence perceptions and comprehension of side effect risks in an online decision aid about prophylactic use of tamoxifen to prevent primary breast cancers.
We recruited 631 women with elevated breast cancer risk from two healthcare organizations. Participants saw tailored estimates of the risks of 5 side effects: endometrial cancer, blood clotting, cataracts, hormonal symptoms, and sexual problems. Presentation format was randomly varied in a three factor design: (A) risk information was displayed either in pictographs or numeric text; (B) presentations either reported total risks with and without tamoxifen or highlighted the incremental risk most relevant for decision making; and (C) risk estimates used 100 or 1000 person denominators. Primary outcome measures included risk perceptions and gist knowledge.
Incremental risk formats consistently lowered perceived risk of side effects but resulted in low knowledge when displayed by numeric text only. Adding pictographs, however, produced significantly higher comprehension levels.
Pictographs make risk statistics easier to interpret, reducing biases associated with incremental risk presentations.
Including graphs in risk communications is essential to support an informed treatment decision-making process.
通过实验测试在关于使用他莫昔芬预防原发性乳腺癌的在线决策辅助工具中,使用象形图(图像矩阵)、增量风险格式和不同的风险分母是否会影响对副作用风险的认知和理解。
我们从两个医疗保健机构招募了631名乳腺癌风险升高的女性。参与者看到了5种副作用风险的定制估计:子宫内膜癌、血液凝固、白内障、激素症状和性问题。呈现格式在三因素设计中随机变化:(A)风险信息以象形图或数字文本显示;(B)呈现方式要么报告使用和不使用他莫昔芬的总风险,要么突出与决策最相关的增量风险;(C)风险估计使用100或1000人的分母。主要结局指标包括风险认知和要点知识。
增量风险格式始终降低了对副作用风险的感知,但仅以数字文本显示时导致知识水平较低。然而,添加象形图产生了显著更高的理解水平。
象形图使风险统计更容易解释,减少了与增量风险呈现相关的偏差。
在风险沟通中纳入图表对于支持明智的治疗决策过程至关重要。