Oral Presentation (max 20 mins) National Suicide Prevention Conference 2025

Suicide Trajectories in Australian University Students: Longitudinal Predictors of Suicide Risk Group Membership (#65)

Thomas McAlpine 1
  1. Curtin University, Victoria Park, WA, Australia

BACKGROUND: Suicide remains a leading cause of death for young people worldwide. This is also true in Australia, where suicide is the leading cause of death for those between the ages of 15-24 and 25-44. Given the majority of university students are young people, and that approximately one third of students experience suicidal ideation at any one time, university students represent an important demographic in which to understand the trajectories of suicidal behaviour over the span of their enrolment at university.

METHOD: As part of the World Health Organization’s World Mental Health- International College Survey Initiative (WMH-ICS), 596 Australian university students from five consecutive cohorts (2017-2021) were followed over the course of their degree, assessed yearly from when they first started their degree to three-year follow-up. Growth Mixture Modelling will be retrospectively applied to determine different sub-types of students based on their suicidal behaviour trajectories, operationalised as suicidal plans or attempts at each time point. A wide range of behavioural and psychosocial variables were assessed at baseline and will be used to determine predictors of group membership.

RESULTS: We expect different sub-types of students to be observed within this longitudinal data. Results will show which baseline predictor variables are significantly related to class membership such that higher levels of certain predictors will predispose students to be in the higher risk group/s.

DISCUSSION: Understanding the predictors of the suicide risk trajectories in university students is valuable for several reasons. Firstly, it provides direction for which variables ought to be included in university screening tools seeking to detect those who may be at risk of subsequent suicidal behaviour. Secondly, by identifying unique predictors of these trajectories, it allows insight for interventions to specifically target these variables where possible and intervene for groups of students that may be at higher risk before they reach crises.