Citation

Wallace GT, Conner BT, Shillington AM. Clin. Psychol. Psychother. 2020; ePub(ePub): ePub.

Copyright

(Copyright © 2020, John Wiley and Sons)

DOI

10.1002/cpp.2530

PMID

33169471

Abstract

College students have an elevated risk for self-injurious thoughts and behaviors (SITBs) and there are robust differences in prevalence rates for SITBs across gender identities. While numerous constructs have been implicated as risk factors, researchers have not significantly improved at predicting SITBs, possibly due to constraints of confirmatory analyses. Classification trees are exploratory, person-centered 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 non-suicidal self-injury and suicidal ideation across self-identified females and males. 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 females, whereas alcohol use norms were important correlates among males. 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.

Language: en