Suicide and Self-Harm in Adolescents During the COVID-19 Pandemic: A U.S. Virtual Pediatric Systems, LLC, Database Study of PICU Admissions, 2016–2021
Bibliographic record
Abstract
OBJECTIVES: To characterize the epidemiology of suicide and self-harm among adolescents admitted to PICUs during the first 2 years of the COVID-19 pandemic in the United States. DESIGN: Descriptive analysis of a large, multicenter, quality-controlled database (Virtual Pediatric Systems [VPS]), and of a national public health dataset (U.S. Centers for Disease Control and Prevention web-based Wide-ranging ONline Data for Epidemiology Research [CDC WONDER]). SETTING: The 69 PICUs participating in the VPS database that contributed data for the entire the study period, January 1, 2016, to December 31, 2021. PATIENTS: Adolescents older than 12 years to younger than 18 years old admitted to a participating PICU during the study period with a diagnosis involving self-harm or a suicide attempt (VPS sample), or adolescent suicide deaths over the same period (CDC WONDER sample). INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: We identified 10,239 suicide deaths and 7,692 PICU admissions for self-harm, including 5,414 admissions in the pre-pandemic period (Q1-2016 to Q1-2020) and 2,278 in the pandemic period (Q2-2020 to Q4-2021). Compared with the pre-pandemic period, there was no increase in the median (interquartile range) number of suicide deaths per quarter (429 [399-453] vs. 416 [390-482]) or PICU admissions for self-harm per quarter (315 [289-353] vs. 310 [286-387]) during the pandemic period, respectively. There was an increase in the ratio of self-harm PICU admissions to all-cause PICU admissions per quarter during the pandemic (1.98 [1.43-2.12]) compared with the pre-pandemic period per quarter (1.59 [1.46-1.74]). We also observed a significant decrease in all-cause PICU admissions per quarter early in the pandemic compared with the pre-pandemic period (16,026 [13,721-16,297] vs. 19,607 [18,371-20,581]). CONCLUSIONS: The number of suicide deaths and PICU admissions per quarter for self-harm remained relatively constant during the pandemic, while the number of all-cause PICU admissions per quarter decreased compared with the pre-pandemic period. The resultant higher ratio of self-harm admissions to all-cause PICU admissions may have contributed to the perception that more adolescents required critical care for mental health-related conditions early in the pandemic.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".