Exploring the Correlates of Suicide Attempts Among Individuals With Major Depressive Disorder
Bibliographic record
Abstract
OBJECTIVE: There are no previous studies describing the correlates of suicide attempts in individuals with major depressive disorder in a nationally representative sample. This study explores the sociodemographic variables, mental disorders, and specific depressive symptoms associated with suicide attempts in depression. METHOD: Data were drawn from Wave 1 of the National Epidemiologic Survey on Alcohol and Related Conditions (NESARC), a large (N = 43,093) nationally representative survey of mental illness in the United States conducted between 2001 and 2002. Persons with lifetime major depressive disorder (N = 5128; diagnosed according to DSM-IV) were categorized according to the presence (N = 865) or absence (N = 4263) of a lifetime history of suicide attempts. Multivariate logistic regression was used to compare the 2 groups across a broad range of socio-demographic and mental disorder correlates, as well as to compare specific depressive symptoms associated with a history of suicide attempts. Positive predictive values (PPVs) were calculated to evaluate the effectiveness of each correlate in predicting suicide attempts. Analyses were conducted separately for men and women. RESULTS: Sociodemographic factors significantly associated with a history of suicide attempts included Hispanic or Latino ethnicity (p < .05), younger age (p < .01), and low annual income (p < .01). A history of suicide attempt was significantly associated with any anxiety, personality, or substance use disorder among both men and women (all p < .01). Personality disorder comorbidity was most predictive of suicide attempt. In men, suicide attempts had a strong association with dependent personality disorder (adjusted odds ratio [AOR] = 3.81; 95% CI = 1.14 to 12.73), whereas in women, suicide attempts had a strong association with antisocial personality disorder (AOR = 2.71; 95% CI = 1.72 to 4.25). Dependent personality disorder predicted suicide attempt in almost three quarters of depressed men (PPV = 74.3%; 95% CI = 54.2 to 87.6). The depressive symptom most strongly associated with a history of suicide attempts in both men and women was feelings of worthlessness (AOR = 5.48, 95% CI = 3.36 to 8.94 for men; AOR = 4.93, 95% CI = 3.56 to 6.84 for women). CONCLUSIONS: This study contributes to the existing literature on risk factors for suicide attempts in depressed individuals. Identifying specific depressive symptoms and comorbid mental illnesses may improve the clinical assessment of suicide risk in people with major depressive disorder.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".