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Record W2032777431 · doi:10.1192/pb.30.11.415

Auditing the care programme approach for people with learning disability: a 4-year audit cycle

2006· article· en· W2032777431 on OpenAlexaff
Afia Ali, Ian Hall, Claire Taylor, Stephen Attard, Angela Hassiotis

Bibliographic record

VenuePsychiatric Bulletin · 2006
Typearticle
Languageen
FieldSocial Sciences
TopicHealthcare innovation and challenges
Canadian institutionsLearning Partnership
Fundersnot available
KeywordsAuditDocumentationLearning disabilityService (business)NursingGoal Attainment ScalingData collectionMedicineBusinessPsychologyMedical educationOperations managementAccountingEngineeringComputer sciencePsychiatryIntervention (counseling)

Abstract

fetched live from OpenAlex

Aims and Method Annual audits of the enhanced care programme approach (CPA) were conducted from 2002 to 2005 to evaluate and improve the implementation of CPA in two inner-London community learning disability services. The CPA standards included those stipulated by the Department of Health. The notes of all patients on enhanced CPA were analysed using a structured data collection form. Results There was a gradual improvement in the attainment of targets by both services. Areas of strength included allocating a date for the next CPA review, crisis plans and documentation of service users' comments. Areas of weakness included completion and review of risk assessments and the availability of a care plan for the previous 6 months. Clinical Implications Completing the audit cycle and reauditing improves attainment of targets and encourages service development, but further progress is required.

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)0.054
metaresearch head score (Gemma)0.104
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.054
Threshold uncertainty score0.284

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0540.104
Meta-epidemiology (narrow)0.0010.002
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0060.004
Science and technology studies0.0040.001
Scholarly communication0.0030.002
Open science0.0030.006
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0010.000

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 head0.018
GPT teacher head0.284
Teacher spread0.267 · 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

Citations3
Published2006
Admission routes1
Has abstractyes

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