Risk factors for suicide attempt in children, adolescents, and young adults hospitalized for mental health disorders
Bibliographic record
Abstract
BACKGROUND: Suicide is a leading cause of death among children, adolescents, and young adults (AYA), and mental health disorders are a major contributing factor. Yet, suicidal behaviors among children and AYA with mental health concerns remain understudied and age-specific risk factors are poorly understood. We examined the risk factors for suicide attempt in children and AYA with mental health disorders across three age groups: pre-adolescent children (aged ≤ 12), adolescents (aged 13-17), and young adults (aged 18-25). METHODS: A cross-sectional study of children and AYA hospitalized for a mental health disorder (n = 18,018) at a private hospital system with 141 facilities across the United States (year 2014). RESULTS: Suicide attempts six months prior to hospitalization were reported in 12.1% (n = 177) pre-adolescent children, 22% (n = 1476) adolescents, and 17.9% (n = 1766) young adults. Evidence of psychological trauma was present in 55.4% of pre-adolescent children, 51.2% of adolescents, and 44.5% of young adults. Predictors for suicide attempt observed across all three age groups included the following: female sex, depressive disorder, and being a victim of bullying. Risk factors for suicide attempt specific to pre-adolescent children included being uninsured and having an unsafe home or school environment. Among AYA, suicide attempt was associated with non-Hispanic white, family history of suicide, emotional traumas, and other traumatic experiences. Alcohol use disorder was also a significant predictor of suicide attempt in young adults. CONCLUSIONS: Suicide attempts among children and AYA admitted to a hospital with mental health concerns are highly prevalent. Socioeconomic stressors appeared to be an important contributing factor of suicidal behavior in pre-adolescent children but not in older AYA. Effective suicide prevention strategies targeting children and AYA would need to consider age-specific risk factors.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".