The geriatric depression scale in palliative care
Bibliographic record
Abstract
OBJECTIVE: This research examined the psychometric properties of previously published short forms of the Geriatric Depression Scale (GDS) in patients receiving palliative care. It also uses the full form of the GDS to examine the prevalence of nonsomatic symptoms of depression in palliative patients. METHOD: Participants were 84 patients with advanced cancer attending palliative care outpatient clinics. Scores for short forms of the GDS were derived from administering the original 30-item scale. Patients also completed the single item numerical analogue scale for depression from the Edmonton Symptom Assessment System and parallel numerical analogue scales for will-to-live and hope. A subset of the sample completed the measures twice. Short forms were judged on the extent to which they captured information gained from the full scale and their internal consistency, test-retest reliability, convergent and concurrent validity, and their distribution of scores. RESULTS: Overall, five short forms showed good psychometric properties at both visits. Two of these forms were very brief. Some nonsomatic symptoms assessed on the full GDS were reported with high frequency. However, few individuals reported a large number of symptoms. At both visits, patients identified as likely to have severe depression gave different responses from other patients on most items on the GDS-30. SIGNIFICANCE OF RESULTS: Several short forms of the GDS may be appropriate for use in palliative care. Patients identified as likely to have severe depression showed many of the same symptoms that characterise depression in other geriatric populations.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".