Hee-Ju Kim1, Patrick S Malone2. 1. College of Nursing, Catholic University of Korea, Seoul, South Korea. Electronic address: heeju0906@gmail.com. 2. Malone Quantitative, Durham, NC, USA. Electronic address: malone@malonequantitative.com.
Abstract
PURPOSE: (a) To identify subgroups with unique psychoneurological symptom-cluster experience (depression, cognitive impairment, fatigue, sleep disturbance, and pain) and (b) to examine whether the selected demographic, clinical, psychological, and biological factors determine a symptom-cluster experience in cancer patients. METHOD: The sample included 203 patients with diverse cancer types recruited from a Korean university hospital. Latent profile analyses were conducted to identify subgroups. Influencing factors of subgroup membership (demographic/clinical variables, hemoglobin level, social support, and psychological stress) were included as covariates in latent profile analysis and analyzed by multinomial logistic regression. RESULTS: Latent profile analyses classified patients into two subgroups with a unique symptom cluster experience: patients experiencing high intensity in all symptoms within the cluster (the all-high-symptom subgroup, 71%) and patients experiencing low intensity in all symptoms within the cluster (all-low-symptom subgroup, 29%). The validity of the two subgroups was confirmed by the group classification accuracy (97% of the all-low-symptom subgroup and 99% of the all-high-symptom subgroup) and by significant Wald's mean equality tests, showing each symptom (depression, cognitive impairment, fatigue, sleep disturbance, and pain) significantly differentiated the two subgroups (ps < .001). Psychological stress independently determined the subgroup membership. Patients with high levels of stress were more likely to be in the all-high-symptom group (OR = 4.69, p < .0001). Hemoglobin level, cancer diagnosis, social support, and previous chemotherapy experience did not influence group membership. CONCLUSIONS: A large number of patients experience five psychoneurological symptoms simultaneously due to psychological stress. Interventions targeted to stress would be beneficial for those patients.
PURPOSE: (a) To identify subgroups with unique psychoneurological symptom-cluster experience (depression, cognitive impairment, fatigue, sleep disturbance, and pain) and (b) to examine whether the selected demographic, clinical, psychological, and biological factors determine a symptom-cluster experience in cancerpatients. METHOD: The sample included 203 patients with diverse cancer types recruited from a Korean university hospital. Latent profile analyses were conducted to identify subgroups. Influencing factors of subgroup membership (demographic/clinical variables, hemoglobin level, social support, and psychological stress) were included as covariates in latent profile analysis and analyzed by multinomial logistic regression. RESULTS: Latent profile analyses classified patients into two subgroups with a unique symptom cluster experience: patients experiencing high intensity in all symptoms within the cluster (the all-high-symptom subgroup, 71%) and patients experiencing low intensity in all symptoms within the cluster (all-low-symptom subgroup, 29%). The validity of the two subgroups was confirmed by the group classification accuracy (97% of the all-low-symptom subgroup and 99% of the all-high-symptom subgroup) and by significant Wald's mean equality tests, showing each symptom (depression, cognitive impairment, fatigue, sleep disturbance, and pain) significantly differentiated the two subgroups (ps < .001). Psychological stress independently determined the subgroup membership. Patients with high levels of stress were more likely to be in the all-high-symptom group (OR = 4.69, p < .0001). Hemoglobin level, cancer diagnosis, social support, and previous chemotherapy experience did not influence group membership. CONCLUSIONS: A large number of patients experience five psychoneurological symptoms simultaneously due to psychological stress. Interventions targeted to stress would be beneficial for those patients.
Authors: Rebecca E Salomon; Jamie Crandell; Keely A Muscatell; Hudson P Santos; Ruth A Anderson; Linda S Beeber Journal: Nurs Res Date: 2020 Mar/Apr Impact factor: 2.381
Authors: Yufen Lin; Deborah W Bruner; Sudeshna Paul; Andrew H Miller; Nabil F Saba; Kristin A Higgins; Dong M Shin; Wenhui Zhang; Christine Miaskowski; Canhua Xiao Journal: Cancer Date: 2022-08-15 Impact factor: 6.921
Authors: Joosun Shin; Kate Oppegaard; Alejandra Calvo-Schimmel; Carolyn Harris; Bruce A Cooper; Steven M Paul; Yvette P Conley; Marilyn J Hammer; Frances Cartwright; Kord M Kober; Jon D Levine; Christine Miaskowski Journal: Cancer Nurs Date: 2022-04-12 Impact factor: 2.760
Authors: Rebecca E Salomon; Keely A Muscatell; Jamie Crandell; Ruth A Anderson; Linda S Beeber Journal: Nurs Res Date: 2021 Set/Oct 01 Impact factor: 2.381