Developmental trajectories of suicide risk in college students: a three-year Latent Growth Mixed Model study

TL;DR

This study tracks suicide risk changes in college students over three years and identifies different risk patterns influenced by personal and social factors.

Contribution

The study introduces a three-year longitudinal analysis of suicide risk trajectories using LGMM in a large sample of Chinese college students.

Findings

Three suicide risk trajectories were identified: slowly decreasing, slowly increasing, and rapidly increasing.

Female gender, left-behind experience, and depressive symptoms were significant risk factors for higher suicide risk trajectories.

The findings suggest the need for targeted interventions based on individual risk profiles.

Abstract

This study aimed to explore the developmental trajectories of suicide risk among college students and examine the influence of demographic, psychological, and social factors on these trajectories.

A three-year follow-up study was conducted with 3,723 first-year college students from a university in Guangdong Province, China. Data were collected in October 2020, 2021, and 2022 using the Suicide Behaviors Questionnaire-Revised (SBQ-R), University Personality Inventory (UPI), and Self-rating Depression Scale (SDS). Latent Growth Mixed Modeling (LGMM) was employed to analyze the trajectories of suicide risk.

Three distinct trajectories were identified: a “slowly decreasing suicide risk group” (81.1%), a “slowly increasing suicide risk group” (15.7%), and a “rapidly increasing suicide risk group” (3.2%). Female gender, left-behind experience, history of suicide among close relatives or acquaintances, positive psychological symptoms, and depressive symptoms were significant risk factors for higher suicide risk trajectories (all p < 0.05).

The findings highlight significant heterogeneity in suicide risk trajectories among college students, emphasizing the need for targeted interventions based on individual risk profiles.

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