Sample Characteristics (N = 234).

BackgroundDepression exhibits heterogeneity. However, limited research has explored this heterogeneity in patients with non-small cell lung cancer (NSCLC) after surgery from a person-centered perspective. This study aimed to identify classes of depression using latent class analysis (LCA) in patients with NSCLC after surgery and to explore the association between these classes and demographic and clinical characteristics, physical symptoms, distress disclosure, and relationship quality.MethodsA cross-sectional study was conducted with 234 patients with NSCLC in China from March 17, 2024 to May 16, 2024. Participants provided written informed consent before participating in the study. LCA was performed to identify latent classes of depression. Binary logistic regression analysis was employed to examine the association between the identified classes and related factors.ResultThis study identified two distinct classes: the severe depression group (Class1, N = 162, 69%) and the mild depression group (Class2, N = 72, 31%). Binary logistic regression result demonstrated that, compared with the mild depression group, factors associated with the severe depression group included pain, fatigue, sleep quality, reluctance to distress disclosure and perceived low relationship quality.ConclusionsThe current study provides evidence of the heterogeneity of depression among Chinese patients with NSCLC after surgery. Healthcare providers can develop tailored interventions by identifying the unique characteristics of each depression class. For patients in the severe depression group, interventions should focus on symptom alleviation, encouraging self-disclosure, and enhancing the quality of family relationships to improve their depression. As this study is cross-sectional, future research should validate these depression classes in larger and more diverse populations, both in China and globally.Trial registrationChinese Clinical Trial Registry (ChiCTR, www.chictr.org.cn; registration no.: ChiCTR2400081943).