Open AccessExploring Psychoneurological Symptom Clusters in Acute Stroke Patients: A Latent Class Analysis
Author(s) -
Xiaofang Dong,
Sen Yang,
Yuanli Guo,
Peihua Lv,
Yanjin Liu
Publication year - 2022
Publication title -
journal of pain research
Language(s) - Uncategorized
Resource type - Journals
SCImago Journal Rank - 0.888
H-Index - 49
ISSN - 1178-7090
DOI - 10.2147/jpr.s350727
Subject(s) - latent class model , medicine , stroke (engine) , depression (economics) , anxiety , logistic regression , multinomial logistic regression , quality of life (healthcare) , social support , descriptive statistics , clinical psychology , psychiatry , psychology , mechanical engineering , statistics , mathematics , nursing , machine learning , computer science , engineering , economics , psychotherapist , macroeconomics
To identify latent classes of acute stroke patients with distinct experiences with the symptom clusters of depression, anxiety, fatigue, sleep disturbance, and pain symptoms and assess, if the selected variables determine a symptom-cluster experience in acute stroke patients.