Evaluation of a psychiatric day hospital program for elderly patients with mood disorders
Bibliographic record
Abstract
BACKGROUND: Very little is known about the utility of psychiatric day hospitals for elderly adults with mood disorders. The objectives of this study were to evaluate a long-standing day-hospital program and to explore whether demographic and non-demographic patient characteristics were associated with treatment outcomes. METHOD: We used t-tests to compare retrospective admission and discharge data for 708 patients over a 16-year period, and multiple regression to examine predictors of improvement. RESULTS: Depressed patients showed statistically and clinically significant improvements on the Geriatric Depression Scale and the Hamilton Depression Rating Scale. The number and severity of depressive symptoms at admission were strongly related to treatment outcomes. After controlling for initial levels of depression, demographic characteristics did not predict improvement, and axis I and II diagnoses modestly and inconsistently predicted improvement. CONCLUSIONS: A biopsychosocially-focused day-hospital treatment program was associated with improvements in depression in a large sample of elderly adults with mood disorders. Except for depression severity at admission, patient characteristics had very little impact on treatment outcomes, suggesting that day hospital programs are beneficial for a wide range of depressed elderly adults.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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) | 0.002 | 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".