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Record W1971772464 · doi:10.3109/09638237.2014.954694

A 10-year service evaluation of an assertive community treatment team: trends in hospital bed use

2014· article· en· W1971772464 on OpenAlexaff
Loopinder Sood, A. J. Owen

Bibliographic record

VenueJournal of Mental Health · 2014
Typearticle
Languageen
FieldPsychology
TopicHealthcare Decision-Making and Restraints
Canadian institutionsSt. Michael's Hospital
Fundersnot available
KeywordsAssertive community treatmentService (business)AssertivenessMedicinePsychologyNursingPsychiatryMental healthPsychotherapistMental illnessBusiness

Abstract

fetched live from OpenAlex

BACKGROUND: Studies of assertive community treatment (ACT) have shown various benefits, including reduced hospital bed use. In the UK, this finding was not replicated by randomised controlled trials (RCTs), which lacked fidelity to the model. Conversely, observational studies, while limited by their inherent weakness in implying causality, have shown lower bed use. Against this background many ACT teams are being disestablished in the UK. AIMS: To observe the long-term effect of ACT on bed use, incorporating methods of analysis which mitigate against some weaknesses of observational design. METHODS: Bed use was compared for equal periods of time either side of starting support from an ACT team. RESULTS: Ninety-three people were followed for up to 10.5 years after starting ACT. Hospital bed use was compared for each person, showing a reduction from a mean of 72 d per year prior to ACT to 44 d per year during ACT (p = 0.0018). CONCLUSIONS: The results demonstrate that ACT is associated with reduced bed use in the UK and that it is possible to use an observational design with enhanced analysis techniques to increase evidence for causality. These techniques may have value in other service evaluations.

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)0.005
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 score0.918
Threshold uncertainty score0.854

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.000
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 head0.123
GPT teacher head0.478
Teacher spread0.355 · 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

Citations21
Published2014
Admission routes1
Has abstractyes

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