ArticlePLOS mental health2025
Behavioral and social predictors of suicidal ideation and attempts among adolescents and young adults.
Article in PLOS mental health, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed.
- Hospital-Based Pediatric Suicide Risk Screening Outcomes Vary by Demographic and Clinical Characteristics.JAACAP open · 2026Article
- The sources of suicidal ambivalence: favorable and risk factors for suicidal ideation among higher vocational college freshmen-a large sample survey.BMC psychiatry · 2026Article
- Ethnoracial disparities in suicide following interpersonal violence: A nationwide cohort of over 9 million Brazilian youth.Global mental health (Cambridge, England) · 2026Article
- The associations of childhood adversities and mental disorders with suicidal thoughts and behaviors - Results from the World Mental Health International College Student Initiative.Psychiatry research · 2025Article
- The lifetime prevalence and associated factors of suicidal ideation and suicide attempts among high school adolescents in Ethiopia: a systematic review and meta-analysis.Child and adolescent psychiatry and mental health · 2025Review
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Authors and funding
2 authors.
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Abstract
Suicide is now the 2nd leading cause of death. Despite existing prevention initiatives, the incidence of suicide deaths among younger population has risen in recent years. The study aimed to determine the social and behavioral predictors of suicidal ideation (SI) and suicide attempts (SA) among adolescents and young adults. We analyzed data from the 2021 Youth Risk Behavior Surveillance System (YRBSS) involving 17,232 U.S. students in grades 9-12. Among respondents, 20.85% (3,593) reported suicidal ideation, and 10.17% (1,753) attempted suicide. Of the 3,526 participants with depression, 46.23% (1,630) experienced suicidal ideation, and 19.46% (686) attempted suicide. Among the 8,152 female participants, 27.42% (2,335) reported suicidal ideation, and 13.37% (1,090) reported suicide attempts. Also, 29.06% of 3,981 participants who were overweight experienced SI and 14.02% of them attempted suicide. We developed independent SI and SA prediction models using extreme gradient boosting (XGB), logistic regression (LR), and K-Nearest Neighbors (KNN) algorithms. The LR model demonstrated the best performance in predicting both SI and SA, with an accuracy of 0.74 (for both), specificity of 0.71 for SI; 0.69 for SA, and sensitivity (0.77 for SI; 0.81 for SA). It also achieved high positive predictive values (PPV) of 0.90 for SI; 0.95 for SA, and an area under the Receiver Operating Characteristic (AUROC) curve of 0.82 for both outcomes. The model identified cyberbullying (electronically bullied), drug use, forced sexual intercourse, sexual violence, difficulty in concentrating, and early use of alcohol or marijuana, as some of the most important and common predictors of SI and SA. In conclusion, our research advocates for the urgent development of support systems that address the early signs of suicidal behaviors. It also surfaces the fact that predicting with certainty who is likely to attempt suicide remains a challenge.
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