Shaffer Victoria Anne, Wegier Pete, Valentine K D, Belden Jeffery L, Canfield Shannon M, Patil Sonal J, Popescu Mihail, Steege Linsey M, Jain Akshay, Koopman Richelle J
University of Missouri, Department of Psychological Sciences, Columbia, MO, United States.
Sinai Health System, Temmy Latner Center for Palliative Care, Toronto, ON, Canada.
J Med Internet Res. 2019 Mar 26;21(3):e11366. doi: 10.2196/11366.
Uncontrolled hypertension is a significant health problem in the United States, even though multiple drugs exist to effectively treat this chronic disease.
As part of a larger project developing data visualizations to support shared decision making about hypertension treatment, we conducted a series of studies to understand how perceptions of hypertension control were impacted by data variations inherent in the visualization of blood pressure (BP) data.
In 3 Web studies, participants (internet sample of patients with hypertension) reviewed a series of vignettes depicting patients with hypertension; each vignette included a graph of a patient's BP. We examined how data visualizations that varied by BP mean and SD (Study 1), the pattern of change over time (Study 2), and the presence of extreme values (Study 3) affected patients' judgments about hypertension control and the need for a medication change.
Participants' judgments about hypertension control were significantly influenced by BP mean and SD (Study 1), data trends (whether BP was increasing or decreasing over time-Study 2), and extreme values (ie, outliers-Study 3).
Patients' judgment about hypertension control is influenced both by factors that are important predictors of hypertension related-health outcomes (eg, BP mean) and factors that are not (eg, variability and outliers). This study highlights the importance of developing data visualizations that direct attention toward clinically meaningful information.
在美国,尽管有多种药物可有效治疗这种慢性疾病,但高血压控制不佳仍是一个重大的健康问题。
作为一个更大项目的一部分,该项目旨在开发数据可视化工具以支持高血压治疗的共同决策,我们进行了一系列研究,以了解血压(BP)数据可视化中固有的数据变化如何影响对高血压控制的认知。
在3项网络研究中,参与者(高血压患者的互联网样本)查看了一系列描绘高血压患者的 vignette;每个 vignette 都包含一名患者的血压图。我们研究了血压均值和标准差(研究1)、随时间变化的模式(研究2)以及极值的存在(研究3)等数据可视化如何影响患者对高血压控制的判断以及药物变更的必要性。
参与者对高血压控制的判断受到血压均值和标准差(研究1)、数据趋势(血压随时间是升高还是降低——研究2)以及极值(即异常值——研究3)的显著影响。
患者对高血压控制的判断既受到高血压相关健康结果的重要预测因素(如血压均值)的影响,也受到非重要预测因素(如变异性和异常值)的影响。本研究强调了开发能将注意力引向临床有意义信息的数据可视化工具的重要性。