The World Health Organization reports a high prevalence of mental health problems globally, with depression and anxiety being the most common. College students are particularly vulnerable to these issues, impacting their academic performance, well-being, and even leading to suicidal tendencies. This study addresses the concerning increase in depression and anxiety among university students and its negative correlation with student satisfaction with university life. Student satisfaction is a crucial indicator of overall well-being and impacts university reputation and quality. This research, using large-sample longitudinal data from Chinese college students, aims to explore the longitudinal correlations among depression, anxiety, and student satisfaction with university life, providing valuable insights for improving mental health interventions and enhancing the overall university experience. The study's contributions include being one of the few to utilize large-sample longitudinal data from Chinese students, employing a customer satisfaction model to explain the relationships, and clarifying the complex and often conflicting findings concerning the anxiety-satisfaction relationship.

Existing research demonstrates a strong link between depression, anxiety, and student satisfaction with university life. Many studies show a negative correlation between depression and anxiety and student satisfaction. However, the relationship between anxiety and satisfaction is less consistent; while some studies highlight a negative correlation, especially during stressful periods like the COVID-19 pandemic, others suggest a positive relationship due to some students effectively managing their anxiety through positive thinking. The literature also points to the predictive nature of these variables. Depression negatively predicts student satisfaction, and vice versa, as does student satisfaction negatively predicting depression. The impact of anxiety on student satisfaction and vice versa is less clear in the literature.

This study used longitudinal data collected from Chinese college students across two time points (T1: junior year, T2: senior year). A total of 2298 participants completed the initial survey (T1), with 2070 completing the follow-up survey (T2) one year later. The DASS-42 scale measured depression and anxiety, while student satisfaction with university life was assessed using a 9-item scale. Control variables included gender, age, extroversion, and family social status. Data analysis employed correlation analysis using Stata 15.0 and cross-lagged panel models (CLPM) using Mplus 8.3. Five CLPM models were constructed: autoregressive (M1), preceding (M2), outcome (M3), interaction (M4), and control (M5). Model fit was evaluated using CFI, TLI, RMSEA, and SRMR. Given the large sample size, the chi-square/degrees of freedom ratio was not used for assessing model fit.

Correlation analysis revealed significant negative correlations between depression and student satisfaction at both time points. Anxiety was negatively correlated with student satisfaction only at T1. Depression and anxiety were positively correlated at both time points. The cross-lagged models showed that depression at T1 negatively predicted student satisfaction at T2 (βps = -0.061, p = 0.003). Conversely, student satisfaction at T1 negatively predicted depression at T2 (βsp = -0.067, p = 0.001). These relationships held true even after controlling for gender, age, extroversion, and family social status. Regarding anxiety, anxiety at T1 did not significantly predict student satisfaction at T2. However, student satisfaction at T1 negatively predicted anxiety at T2 (βSA = -0.042, p = 0.047), a relationship that persisted after controlling for covariates. Overall, the models demonstrated good fit (CFI > 0.90, TLI > 0.90, RMSEA < 0.10, SRMR < 0.10).

The findings support the hypothesized negative relationship between depression and student satisfaction, confirming the significant impact of depression on students' overall university experience. The bidirectional relationship between depression and satisfaction suggests interventions targeting either variable may positively influence the other. The non-significant relationship between anxiety and satisfaction at T2, unlike the T1 finding, and the overall lack of predictive power of anxiety on satisfaction, warrant further investigation. The significant negative predictive effect of student satisfaction on both depression and anxiety highlights the importance of creating a supportive and positive campus environment. The customer satisfaction model provides a useful framework for understanding these relationships, emphasizing the importance of aligning student expectations with actual experiences.

This study demonstrates a robust negative correlation between depression and student satisfaction with university life among Chinese college students. While anxiety's predictive relationship with satisfaction is less clear, student satisfaction negatively predicts both depression and anxiety. These findings emphasize the need for universities to prioritize creating positive campus environments and offering timely mental health support services to improve student well-being and academic success. Future research could explore cultural variations, examine the specific factors contributing to satisfaction, and investigate interventions aimed at improving both satisfaction and mental health.

This study relied on self-reported measures, which may be susceptible to bias. The effect sizes for some correlations were small. The sample consisted primarily of higher-grade students, limiting the generalizability of findings to lower-grade students. The scales used to measure student satisfaction, extroversion, and family social status lacked previous validation and testing.