Medical education · 2025
Mental health longitudinal trajectories and predictors in medical students: Latent growth mixture model analysis.
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Chen Yinhai, Ran Xu, Zhou Tong, Huang Rong, Su Lin, Ke Xiong
Аннотация
BACKGROUND: The high-pressure environment of medical education presents significant challenges to the long-term psychological well-being of medical students. Although anxiety and depression are well-documented among medical students, few studies have explored the developmental trajectories of these symptoms over time. This study aims to explore the two-year developmental trajectories of anxiety and depression symptoms in medical students and identify key predictors of these trajectories.
METHODS: This longitudinal study involved 810 medical students from a Chinese medical school, with data collected over four waves spanning two years. A total of 730 students completed the baseline survey and were included in the analysis, yielding a valid response rate of 90.1%. Participants completed the Patient Health Questionnaire-9 (PHQ-9) for depression and the Generalized Anxiety Disorder-7 (GAD-7) scale for anxiety. Latent Growth Mixture Modelling (LGMM) was used to identify the latent trajectories of depression and anxiety symptoms, with full information maximum likelihood estimation applied to handle missing follow-up data. Regression analysis was conducted to determine predictors of these trajectories.
RESULTS: The four waves of data for both depression and anxiety symptoms fit the model well. Depression followed two trajectories: a slowly decreasing group (92.0%) and a significantly increasing group (8.0%). Anxiety exhibited three trajectories: a low level-slow decreasing group (72.7%), a high level-significantly decreasing group (21.2%) and a low level-significantly increasing group (6.1%). Significant predictors of these trajectories included family structure, quality of relationships with parents and roommates, social support, past suicidal ideation and self-harming behaviour. Higher levels of social support were associated with decreasing symptom trajectories, whereas poor family relationships and past suicidal ideation predicted increasing symptoms.
CONCLUSIONS: Depression and anxiety symptoms in medical students follow distinct developmental trajectories, providing a basis for targeted psychological interventions. Strengthening social support should be a priority for educational institutions and policymakers.
METHODS: This longitudinal study involved 810 medical students from a Chinese medical school, with data collected over four waves spanning two years. A total of 730 students completed the baseline survey and were included in the analysis, yielding a valid response rate of 90.1%. Participants completed the Patient Health Questionnaire-9 (PHQ-9) for depression and the Generalized Anxiety Disorder-7 (GAD-7) scale for anxiety. Latent Growth Mixture Modelling (LGMM) was used to identify the latent trajectories of depression and anxiety symptoms, with full information maximum likelihood estimation applied to handle missing follow-up data. Regression analysis was conducted to determine predictors of these trajectories.
RESULTS: The four waves of data for both depression and anxiety symptoms fit the model well. Depression followed two trajectories: a slowly decreasing group (92.0%) and a significantly increasing group (8.0%). Anxiety exhibited three trajectories: a low level-slow decreasing group (72.7%), a high level-significantly decreasing group (21.2%) and a low level-significantly increasing group (6.1%). Significant predictors of these trajectories included family structure, quality of relationships with parents and roommates, social support, past suicidal ideation and self-harming behaviour. Higher levels of social support were associated with decreasing symptom trajectories, whereas poor family relationships and past suicidal ideation predicted increasing symptoms.
CONCLUSIONS: Depression and anxiety symptoms in medical students follow distinct developmental trajectories, providing a basis for targeted psychological interventions. Strengthening social support should be a priority for educational institutions and policymakers.