Using decision tree to predict non-suicidal self-injury among young adults: the role of depression, childhood maltreatment and recent bullying victimization.

Non-suicidal self-injury (NSSI) is a significant mental health issue requiring a deeper understanding of its underlying causes, such as childhood maltreatment, adult bullying victimization, and depression. Previous studies have not adequately addressed the cumulative risks of these factors on NSSI among college students. This population-based study investigates these cumulative risk factors. The cross-sectional study included 63 university's college students with a mean age of 19.6 years ( = 95,833). Two Chi-Square Automatic Interaction Detection (CHAID) decision tree models were used to classify subgroups based on childhood maltreatment and adult bullying victimization experiences and to investigate their cumulative risks of NSSI. Recursive partitioning algorithms determined each predictor variable's relative importance. The CHAID model accurately predicted NSSI behaviours with an overall accuracy rate of 77.8% for individuals with clinically relevant depressive symptoms and 97.2% for those without. Among depressed individuals, childhood emotional abuse was the strongest NSSI predictor (Chi-Square, 650.747; adjusted  < .001), followed by sexual and physical abuse. For non-depressed individuals, emotional abuse in childhood was the strongest NSSI predictor (Chi-Square, 2084.171; adjusted  < .001), with sexual and verbal bullying in the past year representing the most significant proximal risks. Emotional abuse during childhood profoundly impacts individuals, increasing the risk of NSSI in both depressed and non-depressed individuals. Clinically relevant depressive symptoms have a moderating effect on the relationship between childhood maltreatment, adult bullying victimization, and NSSI. Identifying these factors can inform targeted interventions to prevent NSSI development among young adults.