Latent profiles of death anxiety among young adults: associations with self-esteem, security, and perceived social support - Yu, Jingxian; Wu, Mingjie; Liang, Yongqi; Peng, Huan; Li, Na; Liu, Hanjiao (Frontiers in Psychiatry, 2025)
IntroductionDeath anxiety is a critical mental-health concern among young adults; however, its heterogeneity and underlying psychological mechanisms remain understudied. This study aimed to identify latent profiles of death anxiety in Chinese youth and examine the predictive roles of self-esteem, perceived social support, and security.MethodsWe conducted a cross-sectional survey of 623 young adults (mean age = 23.62 years, SD = 3.61) aged 18–35 years in mainland China. Latent profile analysis (LPA) was conducted to classify death anxiety subgroups based on responses to the Templer Death Anxiety Scale (C-T-DAS). Self-esteem, perceived social support, and sense of security were assessed using validated scales. Multinomial logistic regression and ANOVA were used to explore predictors and group differences.ResultsThree latent death anxiety profiles emerged, High Death Anxiety (56.2%), Moderate Cognition and Low Death Anxiety (8.8%), and Low Cognition and Moderate Death Anxiety (35%). Higher self-esteem (β = -0.46, p <.001), social support (β = -1.12, P = .004), and security (β = -2.87, P <.001) significantly predicted lower death anxiety. The high death anxiety group exhibited the lowest psychological resource scores. Older age (30–35 years) and recent acute illness recovery were associated with higher death anxiety risk (OR = 0.28, 95% CI [0.09, 0.93]). Security showed the strongest inverse association with DA (F = 50.72, P <.001), particularly in the interpersonal and controllability dimensions.ConclusionDeath anxiety among young adults is heterogeneous, influenced by distinct psychological profiles and demographic factors. Interventions should prioritize enhancing self-esteem, social support networks, and security to mitigate death anxiety, especially in high-risk subgroups. Future research should employ longitudinal designs and cross-cultural samples to validate causal pathways and refine targeted strategies.