Classification of self-care patterns in Korean adults with prediabetes using unsupervised machine learning: a secondary data analysis

• 발행기관: 한국기초간호학회
• 저자명: Mi-Kyoung Cho Myoung-Lyun Heo
• 간행물 정보: 『Journal of Korean Biological Nursing Science』제27권 제4호, 586~597쪽, 전체 12쪽
• 주제분류: 의약학 > 의학일반
• 파일형태: PDF
• 발행일자: 2025.11.30

국문 초록

Purpose: This study aimed to classify self-care patterns among Korean adults with prediabetes using an unsupervised machine learning approach. The classification was grounded in Orem’s Self-Care The-ory, focusing on self-care demands, self-care agencies, and self-care behaviors. Methods: A secondary data analysis was conducted using the 2023 Korea National Health and Nutrition Examination Survey. Variables were selected and categorized according to the theoretical components of Orem’s model. Principal component analysis was applied for dimensionality reduction, followed by K-means cluster-ing to identify distinct self-care pattern groups. All variables were standardized using min–max nor-malization. Group differences were examined using analysis of variance and the chi-square test. Re-sults: Three self-care pattern groups were identified: the high self-care performance group, the latent self-care risk group, and the self-care vulnerable group. These groups exhibited distinct profiles across self-care demands, agencies, and behaviors. Significant intergroup differences were also observed in education level, income, health literacy, fasting blood glucose, and hemoglobin A1c levels. Conclusion: Self-care patterns among adults with prediabetes can be effectively classified through unsupervised learning techniques. The findings highlight the importance of developing tailored nursing interventions that consider multidimensional self-care profiles. This study underscores the applicability of Orem’s Self-Care Theory and demonstrates the potential of machine learning in identifying at-risk subgroups for early intervention.

목차

INTRODUCTION

METHODS

RESULTS

DISCUSSION

CONCLUSION

ORCID

CONFLICT OF INTEREST

AUTHORSHIP

FUNDING

DATA AVAILABILITY

ACKNOWLEDGMENTS

REFERENCES

키워드

Nursing Self care Prediabetic state Machine learning Cluster analysis