Sleep efficiency in community-dwelling persons living with dementia: exploratory analysis using machine learning.

Journal: Journal of clinical sleep medicine : JCSM : official publication of the American Academy of Sleep Medicine
PMID: 39484800

Abstract

STUDY OBJECTIVES: Sleep disturbances lead to negative health outcomes and caregiver burden, particularly in community settings. This study aimed to investigate a predictive model for sleep efficiency and its associated features in older adults living with dementia in their own homes.

Authors

  • Ji Yeon Lee
    Department of Industrial Plant Science & Technology, Chungbuk National University, South Korea.
  • Eunjin Yang
    College of Nursing, Research Institute of AI and Nursing Science, Gachon University, Yeonsu-Gu, Incheon, Republic of Korea.
  • Ae Young Cho
    Mo-Im Kim Nursing Research Institute, Yonsei University College of Nursing, Seoul, Republic of Korea.
  • YeonKyu Choi
    BRFrame Inc, Seoul, Republic of Korea.
  • SungHee Lee
    Department of Preventive Medicine, Yonsei University College of Medicine, Seoul, Korea.
  • Kyung Hee Lee
    Department of Radiology, Seoul National College of Medicine, Seoul National University Hospital, 101 Daehak-ro, Jongno-gu, Seoul, 03080, Korea (H.C., S.H.Y., S.J.P., C.M.P., J.H.L., H. Kim, E.J.H., S.J.Y., J.G.N., C.H.L., J.M.G.); CHESS Center, The First Hospital of Lanzhou University, Lanzhou, China (Q.X., J.L.); Department of Radiology, Seoul National University Bundang Hospital, Gyeonggi-do, Korea (K.H.L.); Department of Internal Medicine, Incheon Medical Center, Incheon, Korea (J.Y.K.); Department of Radiology, Seoul Medical Center, Seoul, Korea (Y.K.L.); Department of Radiology, National Medical Center, Seoul, Korea (H. Ko); Department of Radiology, Myongji Hospital, Gyeonggi-do, Korea (K.H.K.); and Department of Radiology, Chonnam National University Hospital, Gwanju, Korea (Y.H.K.).

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