Investigating the psychometric properties of the Geriatric Suicide Ideation Scale (GSIS) among community-residing older adults
Bibliographic record
Abstract
OBJECTIVES: To investigate the psychometric properties of the Geriatric Suicide Ideation Scale (GSIS) among community-residing older adults. METHOD: We recruited 173 voluntary participants, 65 years and older, into a 2+ year longitudinal study of the onset or exacerbation of depressive symptoms and suicide ideation. We assessed the internal consistency of the GSIS and its four component subscales, and its shorter and longer duration test-retest reliability, convergent (depression, social hopelessness, and loneliness), divergent (psychological well-being, life satisfaction, perceived social support, and self-rated health), discriminant (basic and instrumental activities of daily living and social desirability), criterion (history of suicide behavior), and predictive validity (future suicide ideation). RESULTS: The GSIS demonstrated strong test-retest reliability and internal consistency. Baseline GSIS scores were significantly positively associated with suicide risk factors, negatively associated with potential resiliency factors, and not associated with functional impairment or social desirability. GSIS scores significantly differentiated between participants with as compared to those without a history of suicide behavior. Baseline GSIS scores significantly predicted suicide ideation at a 2+ year follow-up assessment. CONCLUSION: Findings suggest strong measurement characteristics for the GSIS with community-residing older adults, including impressive consistency over time. These results are consistent with research attesting to the empirical and pragmatic strengths of this measure. These findings have implications for the monitoring of suicide risk when aiming to enhance mental health and well-being and prevent suicide in later life.
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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 | 0.007 | 0.021 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".