Depression and anxiety · 2026
Psychosocial Distress Patterns and Their Associations With Deliberate Self-Harm and Suicidality: A Latent Profile Analysis Among Chinese University Students.
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Xiong Anqi, Huang Yan, Yang Yi, Li Yuan, Xiong Siqi, Yu Yanxing, Luo Biru, Liao Shujuan
Аннотация
BACKGROUND: Deliberate self-harm (DSH) and suicidality are critical public health concerns among university students, a group facing unique psychosocial stressors. While existing literature has revealed the variable-centered characteristics of psychosocial distress and DSH within this population, a person-centered perspective provides a more nuanced understanding of individual differences, which helps inform the development of targeted interventions.
OBJECTIVES: This study aims to identify distinct psychosocial distress profiles among Chinese university students, examine their associations with DSH and suicidality, and explore the sociodemographic factors that influence these profiles.
METHODS: A nationwide cross-sectional survey was conducted among 30,992 Chinese university students. Psychosocial distress was assessed using validated scales for loneliness, depressive symptoms, sleep quality, and problematic internet use (PIU). Latent profile analysis (LPA) was employed to identify psychosocial distress profiles. The Bolck-Croon-Hagenaars (BCH) method was applied to compare DSH and suicidality across these profiles, and the R3STEP approach was used to examine sociodemographic correlates of profile membership.
RESULTS: Three distinct psychosocial distress profiles were identified: Class 1 (minimal distress profile, 60.08%), Class 2 (moderate distress profile, 34.72%), and Class 3 (severe distress profile, 5.20%). Participants in Class 3 reported significantly higher levels of DSH (M = 7.47) and suicidality (M = 1.98) than those in Class 2 (DSH: M = 2.10, suicidality: M = 0.44) and Class 1 (DSH: M = 0.32, suicidality: M = 0.05) (all p < 0.001). Sociodemographic characteristics, including screen time, exercise duration, enrolled program, romantic relationship status, number of romantic relationships, and sexual experience, differed significantly across profiles (all p < 0.001).
CONCLUSION: Based on the selected latent profile solution, approximately 40% of Chinese university students were classified as experiencing elevated psychosocial distress. These profiles were associated with increased levels of DSH and suicidality. Tailored interventions informed by psychosocial distress profiles and sociodemographic characteristics may help improve health management and risk reduction. Given the cross-sectional design, temporal relationships cannot be established, and reverse causation cannot be ruled out. Future longitudinal and interventional studies are needed to validate these findings and facilitate their translation into practice.
OBJECTIVES: This study aims to identify distinct psychosocial distress profiles among Chinese university students, examine their associations with DSH and suicidality, and explore the sociodemographic factors that influence these profiles.
METHODS: A nationwide cross-sectional survey was conducted among 30,992 Chinese university students. Psychosocial distress was assessed using validated scales for loneliness, depressive symptoms, sleep quality, and problematic internet use (PIU). Latent profile analysis (LPA) was employed to identify psychosocial distress profiles. The Bolck-Croon-Hagenaars (BCH) method was applied to compare DSH and suicidality across these profiles, and the R3STEP approach was used to examine sociodemographic correlates of profile membership.
RESULTS: Three distinct psychosocial distress profiles were identified: Class 1 (minimal distress profile, 60.08%), Class 2 (moderate distress profile, 34.72%), and Class 3 (severe distress profile, 5.20%). Participants in Class 3 reported significantly higher levels of DSH (M = 7.47) and suicidality (M = 1.98) than those in Class 2 (DSH: M = 2.10, suicidality: M = 0.44) and Class 1 (DSH: M = 0.32, suicidality: M = 0.05) (all p < 0.001). Sociodemographic characteristics, including screen time, exercise duration, enrolled program, romantic relationship status, number of romantic relationships, and sexual experience, differed significantly across profiles (all p < 0.001).
CONCLUSION: Based on the selected latent profile solution, approximately 40% of Chinese university students were classified as experiencing elevated psychosocial distress. These profiles were associated with increased levels of DSH and suicidality. Tailored interventions informed by psychosocial distress profiles and sociodemographic characteristics may help improve health management and risk reduction. Given the cross-sectional design, temporal relationships cannot be established, and reverse causation cannot be ruled out. Future longitudinal and interventional studies are needed to validate these findings and facilitate their translation into practice.