Classification trees identify shared and distinct correlates of nonsuicidal self‐injury and suicidal ideation across gender identities in emerging adults. (15th November 2020) - Wallace, Gemma T.; Conner, Bradley T.; Shillington, Audrey M.
Abstract : College students have an elevated risk for self‐injurious thoughts and behaviours (SITBs), and there are robust differences in prevalence rates for SITBs across gender identities. Although numerous constructs have been implicated as risk factors, researchers have not significantly improved at predicting SITBs, possibly owing to constraints of confirmatory analyses. Classification trees are exploratory, person‐centred analyses that enable joint examination of numerous correlates and their interactions. Thus, classification trees may discern previously unstudied risk factors and identify distinct subpopulations with elevated risk for SITBs. We tested classification trees that evaluated 298 potential correlates of nonsuicidal self‐injury and suicidal ideation across self‐identified women and men. Data came from 5, 131 college students who completed the National College Health Assessment, which assesses a wide range of health‐related constructs. Models produced parsimonious decision trees that accounted for a substantial amount of outcome variability (38.3–51.5%). Psychopathology, poorer psychological well‐being, and other SITBs emerged as important correlates for all participants. Trauma, disordered eating, and heavy alcohol use were salient among women, whereas alcohol use norms were important correlates among men. Importantly, models identified several constructs that may be amenable to intervention. Results support the use of exploratory analyses to explicate heterogeneity among individuals who engage in SITBs and suggest that gender identity is an important moderator for certain risk factors.