Back

Risk Factors for Suicidal Behavior in Youth and the Impact of SARS-CoV-2 Infection: A Retrospective Case-Control Study

Heslin, K. P.; Montero, M.; Faraone, S. V.; Zhang-James, Y.

2024-12-03 psychiatry and clinical psychology
10.1101/2024.12.02.24318197 medRxiv
Show abstract

BackgroundSuicide and self-harm remain critical concerns in youth. This study compares patients with and without suicidality or self-harm (SOSH), suicidality (SI/SA), and COVID-19 to investigate 53 pre-existing risk factors associated with suicidality in patients with and without COVID-19. MethodsA retrospective case-control study was conducted using TriNetX data from 111,631,250 patients across 78 healthcare networks. This study included patients aged 0-21 with any healthcare visit between January 20, 2020, and May 11, 2023. OutcomesComparison groups shared many risk factors, with specific differences. Children with SOSH and COVID-19 had higher odds of support group problems, personality disorder, thyroid disorders, and insomnia; children with SOSH without COVID-19 had higher odds of upbringing problems, anxiety and nonpsychotic disorders, sleep disorders, and autism. Adolescents with SOSH and COVID-19 had higher odds of parent-child conflict; adolescents with SOSH without COVID-19 had higher odds of education and literacy problems. Children with SI/SA and COVID-19 had higher odds of support group problems, personality disorders, and asthma; children with SI/SA without COVID-19 had higher odds of autism. Adolescents with SI/SA and COVID-19 had higher odds of asthma. The effect size of COVID-19 was not significant. SOSH was associated with increased odds of prior SARS-CoV-2 infection in children (OR 2.42) and adolescents (OR 1.88). InterpretationThis study confirms known SOSH risk factors and demonstrates their association with suicidality. We observed a significant association between SOSH and preceding SARS-CoV-2 infection. This underscores the need to focus on suicide risk in youth affected by COVID-19.

Matching journals

The top 7 journals account for 50% of the predicted probability mass.

50% of probability mass above

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.