Open AccessCharacteristics and subtypes of depressive symptoms in Chinese female breast cancer patients of different ages: a cross-sectional study
Author(s) -
Yanyan Li,
Hong Liu,
Yaoyao Sun,
Jie Li,
Yanhong Chen,
Xuan Zhang,
Juan Wang,
Liuliu Wu,
Ди Шао,
Fenglin Cao
Publication year - 2021
Publication title -
aims public health
Language(s) - English
Resource type - Journals
ISSN - 2327-8994
DOI - 10.3934/publichealth.2021055
Subject(s) - breast cancer , suicidal ideation , depression (economics) , depressive symptoms , medicine , cross sectional study , clinical psychology , psychomotor learning , psychiatry , cancer , poison control , injury prevention , anxiety , pathology , cognition , environmental health , economics , macroeconomics
Purpose To identify the characteristics and subtypes of depressive symptoms and explore the relationship between depressive subtypes and age among Chinese female breast cancer patients. Method In this cross-sectional study, 566 breast cancer patients were recruited from three tertiary comprehensive hospital in Shandong Province, China through convenient sampling from April 2013 to June 2019. Depressive symptoms were measured using the Patient Health Questionnaire-9 (PHQ-9). Data analyses included descriptive analyses, latent class analysis. Results There were significant differences in specific depressive symptoms by age group, but no significant difference in total scores on PHQ-9. The depressive subtypes were severe (Class 4), relatively severe (Class 3; with lower psychomotor agitation/retardation and suicidal ideation), moderate (Class 2; with higher psychomotor agitation/retardation and suicidal ideation), and mild depressive symptoms (Class 1). The distribution of depression subtypes is different in various age groups. In the 45–59 age groups, severe symptoms subtype showed the highest ratios (i.e. 50.3%). Conclusion This is the first study that analyses depressive symptom characteristics and identifies depressive subtypes in Chinese women with breast cancer across ages to explore symptom heterogeneity. Our findings can contribute to identifying the mechanisms behind these relationships and developing targeted interventions for patients with specific depressive subtypes.