<p>Predictors of Passive and Active Suicidal Ideation and Suicide Attempt Among Older People: A Study in Tertiary Care Settings in Thailand</p>
Bibliographic record
Abstract
Purpose: This study compared predictors of passive suicidal ideation (SI), active SI, and suicide attempt (SA) among elderly Thai patients in tertiary care settings. Patients and Methods: Psychiatric diagnoses and suicidality of 803 older people were assessed using the Mini-International Neuropsychiatric Interview and the Structured Clinical Interview for DSM-IV-TR. All participants completed the Montreal Cognitive Assessment, multidimensional scale of perceived social support (MSPSS), 15-item Thai geriatric depression scale (TGDS-15), 10-item perceived social scale and the Core Symptoms Index. The chi-square test, t -test and ANOVA were used for bivariate analysis of predictors of specific suicidality types. Multiple logistic regression was used to determine the predictors for each type of suicidality. Results: The patients’ mean age was 69.24 ± 6.90 years, and the majority were female (69.74%). Passive SI, active SI and SA were found among 20.42%, 3.74% and 2.37%, respectively, of the patients. Major depressive disorder (MDD) was a predictor of both passive and active SI (OR = 2.06 and 3.74, respectively). Other predictors of passive SI included hypomania (OR = 8.27) and positive score on the TGDS-15 (OR = 1.29). Predictors of active SI included agoraphobia (OR = 6.84) and hypomania (OR = 7.10). Predictors of SA included a family history of alcohol dependence (OR = 14.16), a history of depression (OR = 4.78) and agoraphobia (OR = 19.89). Surprisingly, hypertension and self-reported anxiety symptoms were protective factors for passive SI (OR = 0.51 and 0.85, respectively). Likewise, MSPSS was a protective factor for SA (OR = 0.90). Conclusion: Predictors of each type of suicidality differed. MDD was the main predictor for SI; however, agoraphobia and poor perceived social support were more pronounced among individuals with SA. Further investigation, especially in longitudinal fashion, should be warranted. Keywords: suicide, elderly, risk, predictor
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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".