Decision tree classifier in predicting high risk of suicide in nursing students after COVID-19 pandemic

Suicide is the fourth leading cause of death among people aged 15-29. The aim of this study is to measure the risk of suicide among nursing students after the COVID-19 pandemic and to identify the factors associated with the risk of suicidal ideation.

A cross-sectional study was carried out with nursing students. A convenience sample was selected with all first-year undergraduate students from a single university center in Madrid, Spain (n = 196). Suicide risk (Plutchik scale) was measured as a dependent variable, and sex, age, emotional regulation (ERQ questionnaire), resilience (RS-14 scale), personality traits (BPI inventory) and quality of life (EQ-5D questionnaire) as independent variables. A predictive model was created using a classification tree algorithm to identify the most important predictors of high suicide risk.

The results showed that a total of 16.4% of the students were at high risk for suicide. The independent predictors of high suicide risk were age (OR 1.10), responsibility (OR 0.83), neuroticism (OR 1.64), and quality of life (OR 0.98). In the classification tree prediction model, neuroticism increased suicide risk (62.5%) and responsibility decreased suicide risk.

Around 16% of the nursing students are at high risk of suicide after the COVID-19 pandemic. This prevalence may change when considering neuroticism and responsibility personality traits.