Journal of affective disorders · 2026
The heterogeneity configurations of depression risk factors among college students: A latent profile analysis based on the Predisposing, Precipitating, and Perpetuating (3P) model.
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Tian Wangdanhong, Yang Jiarong, Dai Bibing, Yang Zhuoyuan
Аннотация
BACKGROUND: Depression has become increasingly prevalent among college students in recent years. Nevertheless, existing research is largely grounded in variable-centered approaches, which assume population homogeneity and may fail to capture latent heterogeneity configurations of depression risk factors. Guided by Spielman's (1987) 3P (Predisposing, Precipitating, and Perpetuating) model, the present study aimed to identify latent profiles reflecting heterogeneous patterns of depression risk factors among college students.
METHODS: A survey was conducted among 1171 students from a university in China. Using the Dirty Dozen Scale, the Social Pain Questionnaire, the Intolerance of Uncertainty Scale-12, the Cognitive Flexibility Inventory, and the Patient Health Questionnaire-9. A latent profile analysis was performed based on predisposing, precipitating, and perpetuating factors, while differences in depressive symptoms were compared across profiles.
RESULTS: Three distinct latent profiles were identified: the High-Risk Profile (9.22%), the Moderate-Risk Profile (50.98%), and the Low-Risk Profile (39.80%). Results revealed that the three profiles differ significantly in terms of the scores of all scales. Regression analysis showed significant associations between profiles and depressive symptom severity, with individuals in the High-Risk Profile reporting higher levels of depressive symptoms, followed by those in the Moderate-Risk Profile.
CONCLUSIONS: The findings suggest that depressive symptoms among college students are associated with heterogeneous configurations of predisposing, precipitating, and perpetuating factors rather than being explained by any single factor alone. Distinct latent profiles were related to different severity of depressive symptoms, highlighting the importance of considering individual differences. This study may inform future early prevention and targeted interventions for college students.
METHODS: A survey was conducted among 1171 students from a university in China. Using the Dirty Dozen Scale, the Social Pain Questionnaire, the Intolerance of Uncertainty Scale-12, the Cognitive Flexibility Inventory, and the Patient Health Questionnaire-9. A latent profile analysis was performed based on predisposing, precipitating, and perpetuating factors, while differences in depressive symptoms were compared across profiles.
RESULTS: Three distinct latent profiles were identified: the High-Risk Profile (9.22%), the Moderate-Risk Profile (50.98%), and the Low-Risk Profile (39.80%). Results revealed that the three profiles differ significantly in terms of the scores of all scales. Regression analysis showed significant associations between profiles and depressive symptom severity, with individuals in the High-Risk Profile reporting higher levels of depressive symptoms, followed by those in the Moderate-Risk Profile.
CONCLUSIONS: The findings suggest that depressive symptoms among college students are associated with heterogeneous configurations of predisposing, precipitating, and perpetuating factors rather than being explained by any single factor alone. Distinct latent profiles were related to different severity of depressive symptoms, highlighting the importance of considering individual differences. This study may inform future early prevention and targeted interventions for college students.