@article{ref1,
title="Using recursive partitioning to predict presence and severity of suicidal ideation amongst college students",
journal="Journal of American college health",
year="2024",
author="McCool, Matison W. and Schwebel, Frank J. and Pearson, Matthew R. and Wong, Maria M.",
volume="ePub",
number="ePub",
pages="ePub-ePub",
abstract="OBJECTIVE: Predicting the presence and severity of suicidal ideation in college students is important, as deaths by suicide amongst young adults have increased in the past 20 years. PARTICIPANTS: We recruited college students (N = 5494) from ten universities across eight states. <br><br>METHOD: Participants answered three questionnaires related to lifetime and past month suicidal ideation, and an indicator of suicidal ideation in a DSM-5 symptom measure. We used recursive partitioning to predict the presence, absence, and severity, of suicidal ideation. <br><br>RESULTS: Recursive partitioning models varied in their accuracy and performance. The best-performing model consisted of predictors and outcomes measured by the DSM-5 Level 1 Cross-Cutting Symptom Measure. Sexual orientation was also an important predictor in most models. <br><br>CONCLUSIONS: A single measure of DSM-5 symptom severity may help universities understand suicide severity to promote targeted interventions. Though further work is needed, as similar scaling amongst predictors could have influenced the model.<p /> <p>Language: en</p>",
language="en",
issn="0744-8481",
doi="10.1080/07448481.2024.2351419",
url="http://dx.doi.org/10.1080/07448481.2024.2351419"
}