Department of Medicine, Indiana University School of Medicine, USA; Indiana University Center for Aging Research, Regenstrief Institute, Inc., USA.
Department of BioHealth Informatics, IUPUI School of Informatics and Computing, USA; Parkview Mirro Center for Research and Innovation, Parkview Health, USA.
Appl Ergon. 2020 Sep;87:103107. doi: 10.1016/j.apergo.2020.103107. Epub 2020 Apr 15.
Personas can be used to understand patterns of variation in patients' performance of cognitive work, particularly self-care decision making. In this study, we used a patient-centered cognitive task analysis (P-CTA) to develop self-care decision-making personas. We collected data from 24 older adults with chronic heart failure and 14 support persons, using critical incident and fictitious scenario interviews. Qualitative analyses produced three personas but revealed that individuals exemplify different personas across situations. The Rule-Following persona seeks clear rules, exercises caution under uncertainty, and grounds actions in confidence in clinician experts. The Researching persona seeks information to gain better understanding, invents strategies, and conducts experiments independently or with clinicians. The Disengaging persona does not actively seek rules or information and does not attempt to reduce uncertainty or conduct experiments. We discuss the situational nature of personas, their use in design, and the benefits of P-CTA for studying patient decision making.
可以使用患者角色来了解患者执行认知工作（尤其是自我护理决策）时的表现变化模式。在这项研究中，我们使用以患者为中心的认知任务分析（P-CTA）来开发自我护理决策患者角色。我们通过关键事件和虚构场景访谈，从 24 名慢性心力衰竭老年患者和 14 名护理人员那里收集了数据。定性分析产生了三个患者角色，但也揭示了个体在不同情况下会体现不同的角色。循规蹈矩的患者角色寻求明确的规则，在不确定的情况下谨慎行事，并基于对临床医生专家的信任采取行动。研究型患者角色寻求信息以获得更好的理解，独立或与临床医生一起发明策略并进行实验。回避型患者角色不会主动寻找规则或信息，也不会试图减少不确定性或进行实验。我们讨论了患者角色的情境性质、它们在设计中的用途以及 P-CTA 用于研究患者决策的好处。
