Psychiatry Investig.  2018 Nov;15(11):1037-1045. 10.30773/pi.2018.08.21.3.

Predicting Suicidal Ideation in College Students with Mental Health Screening Questionnaires

• Shim G
• Jeong B

• KMID: 2427571
• DOI: http://doi.org/10.30773/pi.2018.08.21.3

Abstract

OBJECTIVE
The present study aimed to identify risk factors for future SI and to predict individual-level risk for future or persistent SI among college students.
METHODS
Mental health check-up data collected over 3 years were retrospectively analyzed. Students were categorized as suicidal ideators and non-ideators at baseline. Logistic regression analyses were performed separately for each group, and the predicted probability for each student was calculated.
RESULTS
Students likely to exhibit future SI had higher levels of mental health problems, including depression and anxiety, and significant risk factors for future SI included depression, current SI, social phobia, alcohol problems, being female, low self-esteem, and number of close relationships and concerns. Logistic regression models that included current suicide ideators revealed acceptable area under the curve (AUC) values (0.7-0.8) in both the receiver operating characteristic (ROC) and precision recall (PR) curves for predicting future SI. Predictive models with current suicide non-ideators revealed an acceptable level of AUCs only for ROC curves.
CONCLUSION
Several factors such as low self-esteem and a focus on short-term rather than long-term outcomes may enhance the prediction of future SI. Because a certain range of SI clearly necessitates clinical attention, further studies differentiating significant from other types of SI are necessary.

Keyword

Suicidal ideation; Students; Logistic models; Risk factors

MeSH Terms

Anxiety
Area Under Curve
Depression
Female
Humans
Logistic Models
Mass Screening*
Mental Health*
Phobic Disorders
Retrospective Studies
Risk Factors
ROC Curve
Suicidal Ideation*
Suicide