理解卫生技术的设计权衡:混合方法方法。

Katie O'Leary, Jordan Eschler, Logan Kendall, Lisa M Vizer, James D Ralston, Wanda Pratt
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引用次数: 13

摘要

我们介绍了一种混合方法来确定人们如何权衡与健康和健康自我管理技术相关的价值权衡。我们的方法结合了访谈和q -方法论,这是一种来自心理学的方法,特别适合于量化意见。我们从慢性病自我管理和技术采用的理论中推导出结构化数据收集和q方法分析的框架。为了说明这种新方法的力量,我们对9名患有2型糖尿病的老年人和9名患有哮喘儿童的母亲进行了实地研究。我们的混合方法方法为HCI中的健康设计科学提供了三个关键优势:(1)它提供了结构化的健康科学理论框架来指导数据收集和分析;(2)增强了非结构化数据的编码,具有极化和共识观点的统计模式;(3)它使参与者能够积极权衡对他们个人最重要的竞争价值观。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Understanding Design Tradeoffs for Health Technologies: A Mixed-Methods Approach.

Understanding Design Tradeoffs for Health Technologies: A Mixed-Methods Approach.

Understanding Design Tradeoffs for Health Technologies: A Mixed-Methods Approach.

Understanding Design Tradeoffs for Health Technologies: A Mixed-Methods Approach.

We introduce a mixed-methods approach for determining how people weigh tradeoffs in values related to health and technologies for health self-management. Our approach combines interviews with Q-methodology, a method from psychology uniquely suited to quantifying opinions. We derive the framework for structured data collection and analysis for the Q-methodology from theories of self-management of chronic illness and technology adoption. To illustrate the power of this new approach, we used it in a field study of nine older adults with type 2 diabetes, and nine mothers of children with asthma. Our mixed-methods approach provides three key advantages for health design science in HCI: (1) it provides a structured health sciences theoretical framework to guide data collection and analysis; (2) it enhances the coding of unstructured data with statistical patterns of polarizing and consensus views; and (3) it empowers participants to actively weigh competing values that are most personally significant to them.

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