An emergent challenge in geriatric care is improving the quality of care, which requires insight from stakeholders. Qualitative methods offer detailed insights, but they can be biased and have limited generalizability, while quantitative methods may miss nuances. Network-based approaches, such as quantitative ethnography (QE), can bridge this methodological gap. By leveraging the strengths of both methods, QE provides profound insights into need-finding interviews. In this paper, to better understand geriatric care attitudes, we interviewed ten nursing assistants, used QE to analyze the data, and compared their daily activities in real life with training experiences. A two-sample t-test with a large effect size (Cohen's d=1.63) indicated a significant difference between real-life and training activities. The findings suggested incorporating more empathetic training scenarios into the future design of our geriatric care simulation. The results have implications for human-computer interaction and human factors. This is illustrated by presenting an example of using QE to analyze expert interviews with nursing assistants as caregivers to inform subsequent design processes.

翻译：老年护理领域的一个新兴挑战是提升护理质量，这需要从利益相关者处获取深入见解。定性方法能提供详细洞察，但可能存在偏见且普适性有限，而定量方法则可能遗漏细微差异。基于网络的方法，如定量民族志（QE），能够弥合这一方法论鸿沟。通过融合两种方法的优势，QE为需求发现访谈提供了深刻的洞察。本文为更好地理解老年护理态度，访谈了十名护理助理，运用QE分析数据，并比较了他们在现实生活中的日常活动与培训经历。大效应量的双样本t检验（Cohen's d=1.63）表明现实生活与培训活动存在显著差异。研究结果建议在未来老年护理模拟设计中纳入更多共情式培训场景。该结果对人机交互与人因工程具有启示意义。本文通过展示使用QE分析护理助理作为照护者的专家访谈以指导后续设计流程的实例，对此进行了阐释。