Predicting suicidal ideation in college students with mental health screening questionnaires.

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.