Psychiatry research · 2026
Latent profile and network analysis of anxiety and depressive symptoms among undergraduates.
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Li Chengling, Yang Shaoqing, Liu Xiaoling, Liu Huiying, Li Chaoqi, Li Yajing, Li Ling, Dou HongXin
Аннотация
OBJECTIVE: Anxiety and depressive symptoms vary substantially among undergraduate students. This study combined latent profile and symptom network analyses to identify distinct subtypes of co-occurring anxiety and depressive symptoms in undergraduates and clarify the core symptom characteristics of each subtype. The results offer cross-sectional empirical support for developing stratified, targeted psychological interventions in university settings.
METHODS: This cross-sectional cluster survey recruited 17,136 full-time undergraduates from two universities in Tangshan City. Participants completed the Generalized Anxiety Disorder Scale and the Patient Health Questionnaire-Depression Scale. Latent profile analysis was used to classify symptom subtypes, and symptom network models were built to detect core symptom nodes for each subgroup. Repeated resampling verified the reliability of all network models. The Network Comparison Test (NCT) was further applied to examine subgroup differences in network topology and global symptom connectivity strength.
RESULTS: A three-class latent profile model was selected based on model parsimony, interpretability, subgroup size distribution, and compatibility with subsequent analyses. The sample was divided into three subgroups: low-symptom (74.2%), moderate-symptom (22.7%), and high-symptom (3.05%). Network analyses showed that depressive symptoms dominated the core nodes of both low- and moderate-symptom subgroups. In comparison, the high-symptom subgroup exhibited a dual-core pattern with concurrent anxiety and depressive symptoms, and all subgroup networks achieved adequate statistical reliability. Network comparisons indicated significant topological differences only between the low- and moderate-symptom subgroups (P < 0.05), with no topological distinctions observed among other subgroup pairs (P > 0.05). Notably, pairwise comparisons revealed statistically significant differences in global symptom connectivity strength across all three subgroups (P < 0.05).
CONCLUSION: Undergraduate anxiety and depressive symptoms fall into three unique latent subtypes. While low- and moderate-symptom subtypes are primarily defined by depressive symptoms, the high-symptom subtype features prominent coexisting anxiety and depressive core symptoms. The subtype patterns identified in this cross-sectional study provide rigorous empirical evidence for universities to design and implement stratified, individualized psychological interventions.
METHODS: This cross-sectional cluster survey recruited 17,136 full-time undergraduates from two universities in Tangshan City. Participants completed the Generalized Anxiety Disorder Scale and the Patient Health Questionnaire-Depression Scale. Latent profile analysis was used to classify symptom subtypes, and symptom network models were built to detect core symptom nodes for each subgroup. Repeated resampling verified the reliability of all network models. The Network Comparison Test (NCT) was further applied to examine subgroup differences in network topology and global symptom connectivity strength.
RESULTS: A three-class latent profile model was selected based on model parsimony, interpretability, subgroup size distribution, and compatibility with subsequent analyses. The sample was divided into three subgroups: low-symptom (74.2%), moderate-symptom (22.7%), and high-symptom (3.05%). Network analyses showed that depressive symptoms dominated the core nodes of both low- and moderate-symptom subgroups. In comparison, the high-symptom subgroup exhibited a dual-core pattern with concurrent anxiety and depressive symptoms, and all subgroup networks achieved adequate statistical reliability. Network comparisons indicated significant topological differences only between the low- and moderate-symptom subgroups (P < 0.05), with no topological distinctions observed among other subgroup pairs (P > 0.05). Notably, pairwise comparisons revealed statistically significant differences in global symptom connectivity strength across all three subgroups (P < 0.05).
CONCLUSION: Undergraduate anxiety and depressive symptoms fall into three unique latent subtypes. While low- and moderate-symptom subtypes are primarily defined by depressive symptoms, the high-symptom subtype features prominent coexisting anxiety and depressive core symptoms. The subtype patterns identified in this cross-sectional study provide rigorous empirical evidence for universities to design and implement stratified, individualized psychological interventions.