Department of BioHealth Informatics, Indiana University School of Informatics and Computing, Indianapolis, IN, USA; Indiana University Center for Aging Research (IUCAR), Regenstrief Institute, Inc., Indianapolis, IN, USA.
Department of BioHealth Informatics, Indiana University School of Informatics and Computing, Indianapolis, IN, USA.
Int J Med Inform. 2017 Dec;108:158-167. doi: 10.1016/j.ijmedinf.2017.10.006. Epub 2017 Oct 9.
Personas are a canonical user-centered design method increasingly used in health informatics research. Personas-empirically-derived user archetypes-can be used by eHealth designers to gain a robust understanding of their target end users such as patients.
To develop biopsychosocial personas of older patients with heart failure using quantitative analysis of survey data.
Data were collected using standardized surveys and medical record abstraction from 32 older adults with heart failure recently hospitalized for acute heart failure exacerbation. Hierarchical cluster analysis was performed on a final dataset of n=30. Nonparametric analyses were used to identify differences between clusters on 30 clustering variables and seven outcome variables.
Six clusters were produced, ranging in size from two to eight patients per cluster. Clusters differed significantly on these biopsychosocial domains and subdomains: demographics (age, sex); medical status (comorbid diabetes); functional status (exhaustion, household work ability, hygiene care ability, physical ability); psychological status (depression, health literacy, numeracy); technology (Internet availability); healthcare system (visit by home healthcare, trust in providers); social context (informal caregiver support, cohabitation, marital status); and economic context (employment status). Tabular and narrative persona descriptions provide an easy reference guide for informatics designers.
Personas development using approaches such as clustering of structured survey data is an important tool for health informatics professionals. We describe insights from our study of patients with heart failure, then recommend a generic ten-step personas development process. Methods strengths and limitations of the study and of personas development generally are discussed.
人物角色是一种被广泛应用于健康信息学研究的用户为中心的设计方法。人物角色(基于经验得出的用户原型)可被电子健康设计者用于深入了解他们的目标终端用户,如患者。
使用调查数据的定量分析,为心力衰竭的老年患者开发生物心理社会人物角色。
从最近因急性心力衰竭加重而住院的 32 名老年心力衰竭患者中,使用标准化调查和病历摘录收集数据。对 n=30 的最终数据集进行层次聚类分析。非参数分析用于识别聚类变量和七个结果变量的 30 个聚类之间的差异。
产生了六个大小从两个到八个患者的集群。这些生物心理社会领域和子领域在集群之间存在显著差异:人口统计学(年龄、性别);医疗状况(合并糖尿病);功能状态(疲惫、家务劳动能力、卫生保健能力、身体能力);心理状态(抑郁、健康素养、计算能力);技术(互联网可用性);医疗保健系统(家庭保健访问、对提供者的信任);社会背景(非正式照顾者支持、同居、婚姻状况);经济背景(就业状况)。表格和叙述性人物角色描述为信息学设计者提供了一个易于参考的指南。
使用聚类等方法对结构化调查数据进行人物角色开发,是健康信息学专业人员的重要工具。我们描述了我们对心力衰竭患者的研究中的见解,然后推荐了一个通用的十步人物角色开发过程。讨论了研究和人物角色开发的方法优势和局限性。