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Record W2168871934 · doi:10.1017/s1041610206003437

Evaluation of a psychiatric day hospital program for elderly patients with mood disorders

2006· article· en· W2168871934 on OpenAlexaff
Corey S. Mackenzie, Marsha F. Rosenberg, Melissa Major

Bibliographic record

VenueInternational Psychogeriatrics · 2006
Typearticle
Languageen
FieldMedicine
TopicTreatment of Major Depression
Canadian institutionsBaycrest HospitalYork UniversityUniversity of Toronto
Fundersnot available
KeywordsPsychiatryMood disordersMoodMedicinePsychiatric hospitalPsychologyAnxiety

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.202
Threshold uncertainty score0.519

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.007
GPT teacher head0.302
Teacher spread0.295 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations13
Published2006
Admission routes1
Has abstractyes

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