Analyzing Trends in Suicide Attempts Among the Pediatric Population in the United States: A Study Using CDC’s Youth Risk Behavior Surveillance System (YRBSS) Database
Bibliographic record
Abstract
Background Suicide is a significant public health concern among the pediatric population in the United States. This study aims to comprehensively analyze suicide attempts among adolescents using data from the Youth Risk Behavior Surveillance System (YRBSS) maintained by the Centers for Disease Control and Prevention (CDC). Methods The pediatric population of grades 9-12 students (13-17 years old) was included in the study population, and data were collected from multiple cycles of the YRBSS survey. Descriptive statistics and time-trend analyses were conducted to examine attempted suicide rates based on location, gender, race/ethnicity, school grade level, and sexual orientation. Results Significant variations in attempted suicide rates were observed among different demographic groups. In 2021, of the subset with suicide attempt, females reported a higher prevalence of attempted suicide (13.3%, n=211), while males exhibited a lower rate (6.6%, n=104). Of the total studied population in 2021, Palau had the highest attempted suicide rate (25.2%, n=3924), followed by the Northern Mariana Islands (17.6%, n=2740). Over 1991-2021, no significant location-based variations were observed. In 2021, American Indian/Alaska Native adolescents had the highest attempted suicide rate at 16% (n=2491), followed by Black adolescents (14.5%, n=2258). Ninth-grade students reported higher rates in 2021 (11.6%, n=1806). Adolescents reporting both opposite-sex (36.7%, n=5715) and same-sex-only sexual contacts or both (32.9%, n=5123) exhibited notably higher rates in 2021. Conclusion This study highlights alarming attempted suicide rates in the US pediatric population, emphasizing the need for tailored prevention efforts and mental health support. It offers essential guidance for policymakers, researchers, and mental health professionals in developing evidence-based strategies to promote youth well-being and combat the impact of suicide attempts.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.000 | 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".