Demoralization profiles and their association with depression and quality of life in Chinese patients with cancer: a latent class analysis
Supportive Care in Cancer(2022)
摘要
Purpose The study aimed to identify latent classes of demoralization and examine their associations with depression and quality of life (QOL) among patients with cancer. Methods Cross-sectional data from 874 patients with cancer from three tertiary hospitals in Fujian province were collected using a convenience sampling method. Demoralization, depression, and QOL were assessed using the Chinese version of the Demoralization Scale-II, Patient Health Questionnaire-9, and McGill Quality of Life Questionnaire. Latent class analysis was performed on demoralization profiles. Binary logistic regression and multiple stepwise linear regression were used to examine the identified classes’ associations with depression and QOL. Results Three latent classes of demoralization were identified: the “low demoralization and emotional disturbance” class (Class 1; 49.6%); “moderate demoralization and meaninglessness” class (Class 2; 29.1%); and “high demoralization and existential despair” class (Class 3; 21.3%). The severity of depression increased and the levels of QOL decreased with the three classes of demoralization. Patients with cancer being depressed in Classes 1 and 2 were 0.128 and 0.018 times that of Class 3, respectively, whereas the magnitudes of decrease in QOL scores for Classes 2 and 3 were 0.378 and 0.629, respectively. Conclusion This study revealed three heterogeneous classes of demoralization in Chinese patients with cancer and indicated that increased classes were associated with more severe depression and decreased QOL. Targeted, step-by-step psychological interventions should be developed and implemented according to the characteristics of each class of demoralization to effectively promote psychological well-being among patients with cancer.
更多查看译文
关键词
Cancer,Demoralization,Depression,Latent class analysis,Quality of life
AI 理解论文
溯源树
样例
![](https://originalfileserver.aminer.cn/sys/aminer/pubs/mrt_preview.jpeg)
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要