Background Hepatocellular carcinoma (HCC), one of the leading contributors to the global cancer burden, often places patients in a dual predicament of pronounced death anxiety and suboptimal treatment adherence. Prior research has largely treated death anxiety and adherence as independent, homogeneous constructs, thereby overlooking potential within-population heterogeneity and their co-occurring patterns. This study adopted a person-centered approach to identify joint latent profiles of death anxiety and treatment adherence among patients with HCC and to examine factors associated with profile membership. Methods A cross-sectional design was employed. From October to November 2025, 586 patients with HCC were recruited via convenience sampling from five tertiary general hospitals in Shenzhen, Beijing and Lhasa, China. Data were collected using the Death Anxiety Scale (DAS), General Medication Adherence Scale (GMAS), Health Literacy Scale Short-Form (HLS-SF), and Fear of Progression Questionnaire–Short Form (FoP-Q-SF). Results Latent profile analysis identified three qualitatively distinct subgroups: low death anxiety–high treatment adherence, moderate death anxiety–moderate treatment adherence, and high death anxiety–low treatment adherence. Across profiles, death anxiety and treatment adherence exhibited a clear inverse co-variation pattern. Multinomial logistic regression indicated that health literacy and fear of disease progression were key psychosocial factors differentiating profile membership. In addition, demographic and disease-related variables showed varying predictive effects on profile assignment. Conclusions Patients in the high death anxiety–low treatment adherence profile may represent a clinically important high-risk subgroup for targeted screening and supportive care. Clinical practice should emphasize assessment of health literacy and profile-specific psychosocial needs when planning stratified interventions. However, because of the cross-sectional design, the observed associations should not be interpreted causally, and longitudinal studies are needed to examine temporal transitions between profiles and their effects on subsequent treatment outcomes.
Sheng et al. (2026) studied this question.