The effect of adding visual summaries to data visualizations on patient judgments of hypertension control

在数据可视化中添加视觉摘要对患者高血压控制评估的影响

阅读:1

Abstract

OBJECTIVES: To test the impact of visual summaries of blood pressure (BP) data (eg, stoplight and gradient displays), within the context of a patient-facing digital application connected to the EHR, on patient judgments about hypertension control. MATERIALS AND METHODS: Participants (N = 117; Internet sample of patients with hypertension) viewed graphs depicting BP data for fictitious patients. For each graph, participants rated perceived hypertension control, risk of heart attack and stroke, urgency, worry, and perceived understanding of health implications on a 0-100 slider bar and indicated the preferred action to take in response this BP data (eg, talk to doctor at next appointment, go to hospital immediately). Using a within-subjects design, all participants evaluated 12 graphs with data that varied in systolic BP mean (controlled or uncontrolled) and standard deviation (moderate or high) and included three different types of visual summaries: (1) control (average BP only), (2) stoplight, (3) gradient. Participants also completed the Graph Literacy-Short Form and the Electronic Health Literacy Scales (eHEALS). RESULTS: Measures of perceived risk of heart attack and stroke, urgency, and worry were significantly greater and perceived hypertension control was significantly lower for cases where hypertension was uncontrolled P < 0.05. However, there were no significant differences between visual summary methods on the primary outcomes. Graph literacy and electronic health literacy were globally related to judgments of hypertension control but did not interact with any of the study factors. DISCUSSION AND CONCLUSION: The verbal summary, stoplight, and gradient displays performed similarly despite the addition of more precise risk information.

特别声明

1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。

2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。

3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。

4、投稿及合作请联系:info@biocloudy.com。