Back to Search Start Over

Phenomenological examinations of delirium in advanced cancer patients: exploratory structural equation modelling and latent profile analysis

Authors :
Moon Hee Lee
Jisun Park
Kyung Lak Son
Chan Woo Yeom
Hyeju Ha
Bong Jin Hahm
Kwang Min Lee
Eun Jung Shim
Won-Hyoung Kim
Source :
BMC Palliative Care, BMC Palliative Care, Vol 19, Iss 1, Pp 1-8 (2020)
Publication Year :
2020
Publisher :
BioMed Central, 2020.

Abstract

Background This study examined phenomenological manifestations of delirium in advanced cancer patients by examining the factor structure of the Delirium Rating Scale-Revised-98 (DRS-R-98) and profiles of delirium symptoms. Methods Ninety-three patients with advanced cancer admitted to inpatient palliative care units in South Korea were examined by psychiatrists using the DRS-R-98 and the Confusion Assessment Method (CAM). The factor structure of the DRS-R-98 was examined by exploratory structural equation modelling analysis (ESEM) and profiles of delirium were examined by latent profile analysis (LPA). Results CAM-defined delirium was present in 66.6% (n = 62) of patients. Results from the ESEM analysis confirmed applicability of the core and noncore symptom factors of the DRS-R-98 to advanced cancer patients. LPA identified three distinct profiles of delirium characterizing the overall severity of delirium and its core and noncore symptoms. Class 1 (n = 55, 59.1%) showed low levels of all delirium symptoms. Class 2 (n = 17, 18.3%) showed high levels of core symptoms only, whereas Class 3 (n = 21, 22.6%) showed high levels of both core and noncore symptoms except motor retardation. Conclusions Clinical care for delirium in advanced cancer patients may benefit from consideration of the core and noncore symptom factor structure and the three distinct phenomenological profiles of delirium observed in the present study.

Details

Language :
English
ISSN :
1472684X
Volume :
19
Database :
OpenAIRE
Journal :
BMC Palliative Care
Accession number :
edsair.doi.dedup.....8ee5e34bde9263e1ce0d44ffa3d2dff0