Revealing symptom-level vulnerabilities between academic involution and anxiety: a network analysis

BACKGROUND: Academic involution-escalating but low-yield academic effort-has become a salient feature of Chinese higher education. Although initial studies suggest a positive association between involution and anxiety, the specific symptom-to-symptom associations remain unclear. METHODS: A cross-sectional survey was conducted among 1,403 undergraduates in Shandong Province, China (mean age = 19.3 years; 34.9% male). Academic involution was assessed with the 24-item Academic Involution Scale, and anxiety symptoms with the 20-item Zung Self-Rating Anxiety Scale. A regularized partial correlation network was estimated using Graphical Gaussian Models with EBIC-LASSO. Central and bridge nodes were identified via expected influence (EI) and bridge expected influence (BEI). RESULTS: Academic involution dimensions were positively correlated with anxiety (r = 0.35-0.63, p < 0.001). In the network, the most central anxiety symptoms were dizziness (EI = 1.20), panic (EI = 1.17), and faintness (EI = 1.12). Effort-reward (BEI = 0.38) and self-monitoring (BEI = 0.26) showed the highest bridge expected influence values in the network. Bootstrapping indicated narrow confidence intervals and stable centrality estimates (CS = 0.75). CONCLUSIONS: These findings highlight that academic involution was conditionally associated with anxiety symptoms in specific cognitive-behavioral (effort-reward imbalance, self-monitoring) and physiological (somatic hyperarousal) patterns. Identifying central and bridge symptoms provides a hypothesis‑generating framework for generating more targeted hypotheses for future intervention research on both cognitive evaluations and bodily manifestations of stress.