Professor Hee-sun Kim of the College of Nursing, Jeonbuk National University (JBNU) (Vice‑President of the Office of Research), and Dr. Se-young Jang (Jeonbuk National University Hospital) won the Excellent Poster Award at the 2026 Summer Conference of the Korean Academy of Adult Nursing for their study on depression typology and prediction of high‑risk groups among cancer patients.

With the theme 'From LLMs to Physical AI: Practical Transformation of Nursing,' the conference held at the Academy Hall of Kunsan National University featured a series of presentations sharing directions for innovation in nursing practice and research based on artificial intelligence and digital health.

At the conference, Professor Hee-sun Kim and Dr. Se-young Jang presented their research titled 'Typology of Depression and Identification of At‑Risk Groups Among Cancer Patients Using Latent Class Analysis (LCA),' which was recognized for its excellence and academic contribution.

The study used data from the Korea National Health and Nutrition Examination Survey (KNHANES) to classify depressive symptoms of cancer patients through latent class analysis (LCA) and to predict high‑risk groups for depression using decision tree analysis. It was highly regarded for moving beyond approaches based solely on simple depression scores by subdividing depression types based on patients' symptom patterns.

The results showed that depression among cancer patients was divided into latent classes with distinct symptom characteristics. Subjective health status, perceived stress, and lifestyle factors were identified as key variables predicting membership in high‑risk depression groups.

This suggests the potential to screen cancer patients' mental health problems early and to develop patient‑tailored nursing interventions based on patient characteristics. In addition, by integrating big‑data analytical techniques to precisely identify high‑risk groups for depression among cancer patients, the study demonstrated new possibilities for expanding data‑driven mental health nursing research.

Professor Hee-sun Kim said, 'Because depression in cancer patients greatly affects treatment adherence and quality of life, a precision nursing approach that reflects patients' symptom characteristics is essential. Going forward, we will continue research on patient‑centered, tailored nursing interventions using big‑data and AI‑based analytical techniques.'

Dr. Se-young Jang said, 'I am honored to share meaningful research outcomes at the conference and to receive this award. I will continue to strive to ensure that the findings contribute to the early detection of patients' mental health problems in clinical practice and to the development of effective nursing interventions.'