ArticleFrontiers in psychiatry2025
A machine learning analysis of suicidal ideation and suicide attempt among U.S. youth and young adults from multilevel, longitudinal survey data.
Article in Frontiers in psychiatry, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
3 citing papers in PubMed.
- Pilot Test of the Forming Love around Autistic people to Prevent Suicide Program.Autism in adulthood · 2026Article
- Explainable AI for public health surveillance: investigating the persistent crisis of intentional injury mortality (suicide and homicide) in the Americas.Scientific reports · 2026Article
- Developing a suicide risk prediction model for hospitalized adolescents with depression in China.Frontiers in psychiatry · 2025Article
Corrections and comments
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Authors and funding
4 authors.
Funding
Abstract
Objectives: To investigate individual, interpersonal, health system, and community factors associated with suicidal ideation (SI) and attempts (SA). Methods: Utilizing nationally representative data from the National Longitudinal Study of Adolescent to Adult Health (7 Results: Approximately 2.48% and 8.97% reported SA and SI, respectively. Over 25% had depression, and 20.98% anxiety, 6.42% PTSD, 4.55% ADD/ADHD, and 2.50% LD. LASSO regression identified 20 and 21 factors associated with SA and SI. Individual-level factors associated with SI and SA included educational attainment, substance use, ADD/ADHD, depression, anxiety, and PTSD. Interpersonal-level factors included social support, household size, and parental education, while health system-level factors comprised health care receipt, health insurance, and counseling. The strongest associations were among individual-level factors followed by interpersonal and health system factors. Conclusions: The distinct factors associated with SI and SA across diagnostic subgroups highlight the importance of targeted, subgroup-specific suicide prevention interventions. These findings emphasize the value of precise, data-driven approaches for suicide prevention among diverse populations and individuals with disabilities across the life-course.
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