Is Suicide Ideation a Surrogate Endpoint for Geriatric Suicide?
Bibliographic record
Abstract
The present study explored the validity of treating suicide ideation as a surrogate endpoint that can serve as a proxy for suicide in clinical intervention research with suicidal seniors. Two criteria; that suicide ideation is modulated by the proposed intervention and that modulation of suicide ideation leads to a quantitative reduction in suicide rates, were the focus of this review. A series of literature searches of the PsychINFO and Medline databases were conducted on the terms geriatric, elderly, seniors, suicide, self-destruction, clinical, randomized, trial, treatment, intervention , and ideation . Articles were analyzed if they provided sufficient information to examine whether an intervention effectively led to a reduction in suicide ideation among seniors. Two hundred and eight articles were considered for potential inclusion in this study, with 19 articles meeting final inclusion criteria. The articles reviewed were divided into three broad categories: articles supporting suicide ideation as a surrogate endpoint for geriatric suicide ( n = 6); those not supporting this hypothesis ( n = 1); and those providing insufficient information to test the hypothesis ( n = 12). The present analysis provided modest evidence for suicide ideation as a surrogate endpoint for geriatric suicide, due, in part, to a paucity of randomized controlled trials of treatment interventions for suicidal seniors, thus demonstrating a clear need for research in this area. Implications of utilizing surrogate endpoints in suicide research are discussed.
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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 | 0.104 | 0.279 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.003 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.001 | 0.004 |
| Scholarly communication | 0.004 | 0.006 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".