MétaCan
Menu
Back to cohort
Record W2557295611 · doi:10.1080/07317115.2016.1263709

Improving Mental Health in the Community: Outcome Evaluation of a Geriatric Mental Health Day Treatment Service

2016· article· en· W2557295611 on OpenAlexafffund
Christine Knight, Richard M. Alarie

Bibliographic record

VenueClinical Gerontologist · 2016
Typearticle
Languageen
FieldPsychology
TopicDigital Mental Health Interventions
Canadian institutionsAlberta Health Services
FundersAlberta Health Services
KeywordsMental healthMental health servicePsychologyPsychiatryOutcome (game theory)Service (business)GerontologyMedicine

Abstract

fetched live from OpenAlex

OBJECTIVES: This program evaluation reviewed the outcomes of a new 10-week multi-modal mental health day treatment program for elderly clients with mood and anxiety disorders. METHODS: A retrospective chart review of clients admitted during the first 3 years of the program (N = 255) was conducted. Paired sample t-tests were used to compare admission and discharge data. Focus groups were run with clients who attended the program during the previous months, to delineate the strengths of the program and to identify areas for improvement. RESULTS: Analyses showed statistically and clinically significant improvements in client symptomatology, as evidenced by reductions on the Geriatric Depression Scale and the Clinical Outcomes in Routine Evaluation Outcome Measure in clients who completed the program. Focus group participants overwhelmingly described the program as very beneficial, but the desire for on-going follow-up was clearly articulated. CONCLUSIONS: A practice model employing group-based cognitive-behavioural and interpersonal strategies that emphasizes behavioral activation and socialization is associated with a reduction in depressive symptoms and psychological distress in a large sample of elderly adults in a day treatment service with mild to moderate symptoms of depression and anxiety. CLINICAL IMPLICATIONS: In the future, a mechanism for on-going mental health support should be included. Many clients want to remain connected to the system, but there is not always a clear path along the continuum of care, particularly for clients who no longer meet criteria for a psychiatric disorder.

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)0.012
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.939
Threshold uncertainty score0.993

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0120.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.384
GPT teacher head0.561
Teacher spread0.177 · 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

Citations5
Published2016
Admission routes2
Has abstractyes

Explore more

Same venueClinical GerontologistSame topicDigital Mental Health InterventionsFrench-language works237,207