A comparison of the prevalence and risk factors of suicidal ideation and suicide attempts in two American Indian population samples and in a general population sample
Bibliographic record
Abstract
The current study aimed to examine whether the prevalence and risk factors for suicidal ideation and attempts differ when comparing two American Indian reservation samples to the U.S. general population. Data were from the baseline nationally representative National Comorbidity Survey (N = 5,877) and the representative American Indian Service Utilization, Psychiatric Epidemiology, Risk and Protective Factors Project (AI-SUPERPFP; N = 3,084). Face-to-face interviews were conducted using the fully structured World Health Organization Composite International Diagnostic Interview. American Indians from these Northern Plains and Southwest tribes appeared significantly less likely to have suicidal thoughts in their lifetime when compared with the general population, odds ratio (OR) of 0.49 (99% CI [0.36, 0.66]) and 0.36 (99% CI [0.25, 0.51]), respectively. However, members of the Northern Plains tribe were more likely to have attempted suicide in their lifetime compared with the general population (OR = 1.96, 99% CI [1.45, 2.65]). Suicide attempts without suicidal ideation were more common in the two American Indian samples than in the general population. In contrast, correlates of suicidal behavior appear quite similar when comparing the groups. Increased attention is needed to determine why rates of ideation and attempts may differ in American Indians when compared with the general population.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".