ArticlePsychiatry investigation2018
Predicting Suicidal Ideation in College Students with Mental Health Screening Questionnaires.
Article in Psychiatry investigation, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers, 1 of them a synthesis that pooled it.
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Who cites it
5 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Sleep and suicide: A systematic review and meta-analysis of longitudinal studies.Clinical psychology review · 2020Pooled it
- Development and validation of a predictive model for suicidal thoughts and behaviors among freshmen.BMC psychiatry · 2025Article
- Deep graph neural network-based prediction of acute suicidal ideation in young adults.Scientific reports · 2021Article
- Sex Difference in Peripheral Inflammatory Biomarkers in Drug-Naïve Patients with Major Depression in Young Adulthood.Biomedicines · 2021Article
- Data-driven analysis using multiple self-report questionnaires to identify college students at high risk of depressive disorder.Scientific reports · 2020Article
Corrections and comments
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Authors and funding
2 authors.
Funding
Abstract
objectiveThe present study aimed to identify risk factors for future SI and to predict individual-level risk for future or persistent SI among college students.
methodsMental 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.
resultsStudents 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.
conclusionSeveral 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.
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