ArticlePloS one2021
Prediction of suicidal ideation and attempt in 9 and 10 year-old children using transdiagnostic risk features.
Article in PloS one, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers, 3 of them syntheses that pooled it.
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Who cites it
17 citing papers in PubMed, 3 syntheses or guidelines pooled it.
- Loneliness as an Interface Between Alzheimer's Disease and Suicidal Behaviour: A Systematic Review, Meta-Analysis and Meta-Analytic Factor Analysis.Psychogeriatrics : the official journal of the Japanese Psychogeriatric Society · 2026Pooled it
- Role of machine learning algorithms in suicide risk prediction: a systematic review-meta analysis of clinical studies.BMC medical informatics and decision making · 2024Pooled it
- The use of machine learning on administrative and survey data to predict suicidal thoughts and behaviors: a systematic review.Frontiers in psychiatry · 2024Pooled it
- Identifying patterns and predictors of social health in adolescence using data from the Adolescent Brain Cognitive Development Study.Developmental psychology · 2026Article
- Understanding the emergence of suicidal thoughts and behaviors in adolescence from a brain and behavioral developmental perspective.Neuropsychopharmacology : official publication of the American College of Neuropsychopharmacology · 2026Review
- Longitudinal panel networks of risk and protective factors for early adolescent suicidality in the ABCD sample.Development and psychopathology · 2025Article
- Prediction of suicidal attempts among Chinese adolescents with mood disorders: a clinical study using a machine learning approach.BMC psychiatry · 2025Article
- Prediction of Adolescent Suicide Attempt by Integrating Clinical, Neurocognitive and Geocoded Neighborhood Environment Data.Schizophrenia bulletin · 2025Article
- A multi-level examination of impulsivity and links to suicide ideation among Native American youth.Journal of affective disorders · 2024Article
- Automatically extracting social determinants of health for suicide: a narrative literature review.Npj mental health research · 2024Review
- The Role of Individual Discrimination and Structural Stigma in the Mental Health of Sexual Minority Youth.Journal of the American Academy of Child and Adolescent Psychiatry · 2024Article
- Neurocognitive and clinical characteristics of elementary school-aged children with a history of suicidal thoughts and behaviors.Journal of affective disorders · 2023Article
- Suicidal Behaviors in Early Adolescence: The Interaction Between School Connectedness and Mental Health.School mental health · 2023Article
- Suicidal Crisis among Children and Young People: Associations with Adverse Childhood Experiences and Socio-Demographic Factors.International journal of environmental research and public health · 2023Article
- A Deeper Dive Into the Relation Between Psychotic-like Experiences and Suicidal Ideation and Behaviors in Children Across the United States.Schizophrenia bulletin · 2022Article
- Transforming the Future of Adolescent Health: Opportunities From the Adolescent Brain Cognitive Development Study.The Journal of adolescent health : official publication of the Society for Adolescent Medicine · 2022Article
- Negative Urgency and Lack of Perseverance Predict Suicidal Ideation and Attempts Among Young Adolescents.Journal of clinical child and adolescent psychology : the official journal for the Society of Clinical Child and Adolescent Psychology, American Psychological Association, Division 53Article
Corrections and comments
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Authors and funding
9 authors.
Funding
Abstract
The objective of the current study was to build predictive models for suicidal ideation in a sample of children aged 9-10 using features previously implicated in risk among older adolescent and adult populations. This case-control analysis utilized baseline data from the Adolescent Brain and Cognitive Development (ABCD) Study, collected from 21 research sites across the United States (N = 11,369). Several regression and ensemble learning models were compared on their ability to classify individuals with suicidal ideation and/or attempt from healthy controls, as assessed by the Kiddie Schedule for Affective Disorders and Schizophrenia-Present and Lifetime Version. When comparing control participants (mean age: 9.92±0.62 years; 4944 girls [49%]) to participants with suicidal ideation (mean age: 9.89±0.63 years; 451 girls [40%]), both logistic regression with feature selection and elastic net without feature selection predicted suicidal ideation with an AUC of 0.70 (CI 95%: 0.70-0.71). The random forest with feature selection trained to predict suicidal ideation predicted a holdout set of children with a history of suicidal ideation and attempt (mean age: 9.96±0.62 years; 79 girls [41%]) from controls with an AUC of 0.77 (CI 95%: 0.76-0.77). Important features from these models included feelings of loneliness and worthlessness, impulsivity, prodromal psychosis symptoms, and behavioral problems. This investigation provided an unprecedented opportunity to identify suicide risk in youth. The use of machine learning to examine a large number of predictors spanning a variety of domains provides novel insight into transdiagnostic factors important for risk classification.
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