  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.
