# Greeting

After graduating from Kobe University in 2003, I worked as a nurse in an acute-care hospital and a long-term care health facility until 2012. I then entered the graduate program at Osaka University, where I studied epidemiology while continuing clinical work in special nursing homes, short-stay services, dementia group homes, and a home-visit nursing station until 2016. From 2016, I was engaged in research and education as an assistant professor and lecturer at Kobe University. In August 2024, I joined Shiga University of Medical Science with the establishment of the Clinical Nursing Data Science area in the doctoral program.

My research has focused on generating evidence that supports physical and mental health, particularly among older adults. In community-based healthy longevity studies, I examined cross-sectional and longitudinal associations between late-life hypertension and cognitive function, showing that blood pressure management is important for preventing cognitive decline at age 70, while nutritional status and frequency of going outdoors are related to maintaining cognitive function at age 80. In studies of home-care service users and family caregivers, I used wearable devices, which were still emerging ICT tools at the time, to clarify causal relationships between sleep and psychological states, as well as the effects of sleep on home blood pressure, through micro-longitudinal research designs. I am now advancing ICT-based studies in long-term care facilities and AI-based analyses of electronic health record data.

Building on these experiences, our laboratory addresses research questions across all stages of lifelong development, not only older adulthood. At Shiga University of Medical Science, we collaborate with other areas in the Division of Lifelong Development Nursing Practice Science and aim to disseminate new knowledge that supports nursing practice through data science. We welcome visitors, students, and collaborators who are interested in this kind of research.

Signed: Hirochika Ryuno, Project Professor, Shiga University of Medical Science / October 15, 2025

# Laboratory Overview

Nursing settings in Japan generate and accumulate a large amount of data every day. Our laboratory uses these data with statistical analysis, AI, and other data science methods to produce new evidence that can improve the quality of nursing care and support clinical decision-making.

## Main Research Themes

- Visualization and evaluation of nursing practice using clinical nursing data.

- Analysis of nursing documentation through natural language processing.

- Development of data science methods that can be used in clinical settings.

- Ethical and social issues related to the use of AI in nursing practice.

- Assessment of daily rhythms using ICT, including wearable devices, and their relationships with health outcomes.

## Current Projects

- Machine learning and scientific long-term care information systems: Since 2024, we have been analyzing electronic health record data from long-term care facilities using large language models and machine learning to identify factors associated with residents' quality of life and well-being. We are also developing an on-premises AI system that automatically generates care plans and nursing summaries, and evaluating its content validity together with care professionals. This work is conducted in collaboration with Professor Takemura and graduate students at the Graduate School of Applied Informatics, University of Hyogo.

- Wearable-device studies in long-term care facilities: Since 2023, we have been investigating physical activity, sleep, and their longitudinal associations with nutritional status among residents of long-term care facilities, with the aim of informing future interventions. This project is conducted with Professor Kamide and colleagues at University of Osaka Graduate School of Medicine and other collaborating researchers.

- Visualization of nursing practice at the university hospital: From 2026, we are contributing to institutional quality improvement and large-scale workload assessment by visualizing nursing practice using clinical nursing data. This work is conducted with the Nursing Department of Shiga University of Medical Science Hospital and collaborators in Division of Adult Health Nursing.

## Previous Research

- Remote meetings during the COVID-19 pandemic: From 2021 to 2023, we examined the use and effects of ICT for connecting long-term care facility residents with their families. Using a mixed-methods approach, we showed that online meetings contributed to the well-being of both residents and family members.

- International comparative research on family caregivers: From 2018 to 2020, we compared health-related issues among family caregivers in Japan, Taiwan, Indonesia, and Thailand, and reported differences associated with cultural backgrounds.

- Micro-longitudinal research on caregiver burden at home: From 2016 to 2017, we used wearable devices and home blood pressure monitors to examine relationships among sleep, psychological states, caregiver burden, and morning blood pressure in family caregivers through a micro-longitudinal design.

- Healthy longevity study(SONIC study): From 2013 to 2017, during graduate training, we participated in the SONIC study and reported cross-sectional and longitudinal associations between hypertension and cognitive function in later life.

## For Graduate Students and Research Students

In the master's and doctoral programs, we support health care professionals who want to acquire a data science perspective and conduct research grounded in clinical practice. Although the laboratory has particular expertise in research related to older adults, we welcome projects across all stages of lifelong development.

We also collaborate with laboratories across the Division of Lifelong Development Nursing Practice Science and provide analytical support for diverse topics, including cardiovascular nursing, diabetes nursing, perioperative nursing, and perinatal nursing. We look forward to working with students and collaborators who want to open new possibilities for nursing practice through research.

Contact Form: https://forms.gle/zMX8Xp13grBV7MPU7