ArticleJournal of personalized medicine2022
Using Boosted Machine Learning to Predict Suicidal Ideation by Socioeconomic Status among Adolescents.
Article in Journal of personalized medicine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers, 1 of them a synthesis that pooled it.
What it found
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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.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
4 citing papers in PubMed, 1 synthesis or guideline pooled it, 7 citations in OpenAlex.
- Predictive Performance of Machine Learning for Suicide in Adolescents: Systematic Review and Meta-Analysis.Journal of medical Internet research · 2025Pooled it
- Diagnostic accuracy of machine learning approaches for suicide‑related outcomes: a meta‑analysis.Annals of general psychiatry · 2026Article
- National Trends and Directions for Suicide Prevention Research in South Korea: A Narrative Review.Psychiatry investigation · 2025Article
- Machine Learning-Based Prediction of Suicidal Thinking in Adolescents by Derivation and Validation in 3 Independent Worldwide Cohorts: Algorithm Development and Validation Study.Journal of medical Internet research · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors at 2 institutions in 1 country.
Funding
Abstract
(1) Background: This study aimed to use machine learning techniques to identify risk factors for suicidal ideation among adolescents and understand the association between these risk factors and socioeconomic status (SES); (2) Methods: Data from 54,948 participants were analyzed. Risk factors were identified by dividing groups by suicidal ideation and 3 SES levels. The influence of risk factors was confirmed using the synthetic minority over-sampling technique and XGBoost; (3) Results: Adolescents with suicidal thoughts experienced more sadness, higher stress levels, less happiness, and higher anxiety than those without. In the high SES group, academic achievement was a major risk factor for suicidal ideation; in the low SES group, only emotional factors such as stress and anxiety significantly contributed to suicidal ideation; (4) Conclusions: SES plays an important role in the mental health of adolescents. Improvements in SES in adolescence may resolve their negative emotions and reduce the risk of suicide.
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What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.