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Record W4320915761 · doi:10.32388/h8g53k.4

The Effect of Group-Based Family Orientation to Community Mental Health Services

2023· preprint· en· W4320915761 on OpenAlexaff
Sharon Ripley, Sarah F. Andres, David Cawthorpe, Michelle Cooper, Alexis Dreyer, Bill Gordon, Lennie Moffatt, Melissa Getschel

Bibliographic record

VenueQeios · 2023
Typepreprint
Languageen
FieldHealth Professions
TopicGeriatric Care and Nursing Homes
Canadian institutionsUniversity of CalgaryAlberta Health Services
Fundersnot available
KeywordsMental healthOrientation (vector space)Session (web analytics)Service (business)Mental health serviceMedicineHealth servicesDemographyEnvironmental healthFamily medicinePsychiatryComputer scienceBusinessMathematics

Abstract

fetched live from OpenAlex

INTRODUCTION: A simple initial family orientation session (IGS) focusing on what families might expect by way of treatment and with the provision of community resources if required was designed and implemented in a regional mental health service. The effects of the IGS were examined in terms of clinical measures that align closely with the provincially developed SMART goals for treatment and the nationally developed mental health theme of ‘recovery-oriented services’, as well as readmission rates and cumulative lengths of stay. METHODS: Employing clinical and registration data from a regional information and registration system, we examined readmission rates and cumulative lengths of both within and between groups exposed and unexposed to IGS over comparable time periods before and after November 2016. RESULTS: The IGS-exposed group had a greater reduction in admissions and cumulative length of stay compared to the unexposed group, with the greatest reduction in IGS-exposed emergency admissions. Clinical data indicated that both IGS-exposed and unexposed groups were similar. CONCLUSIONS: The findings support the hypothesis that changes in admission rates and overall days in service were potentially an effect of the IGS. The clinical measurement system and the IGS align closely with the provincially developed SMART goals for treatment and the nationally developed mental health theme of ‘recovery-oriented services’.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.023
Threshold uncertainty score0.046

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.000

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 head0.048
GPT teacher head0.432
Teacher spread0.384 · 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 source (direct Gemma or distilled Codex), 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

Citations0
Published2023
Admission routes1
Has abstractyes

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