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Record W2144160012 · doi:10.1177/1744629512463840

Evaluating quality of life in adults with profound learning difficulties resettled from hospital to supported living in the community

2012· article· en· W2144160012 on OpenAlexaff
David Sines, Elaine Hogard, Roger Ellis

Bibliographic record

VenueJournal of Intellectual Disabilities · 2012
Typearticle
Languageen
FieldHealth Professions
TopicGeriatric Care and Nursing Homes
Canadian institutionsLakehead University
Fundersnot available
KeywordsStakeholderQuality of life (healthcare)AccommodationPsychologyCommunity serviceNursingQualitative researchGerontologyMedical educationMedicineSociologyPublic relationsSocial science

Abstract

fetched live from OpenAlex

This article describes a longitudinal evaluation of the quality of life of service users with profound learning difficulties who were resettled from hospital accommodation to supported housing in the community. The Trident approach was used for the design of the evaluation with data gathered regarding outcomes, process and stakeholder perspectives. Using a specially designed tool, quality of life was measured in seven domains for 39 service users in the hospital as a base line and at six months, twelve months and eighteen months in supported housing. A statistically significant improvement in quality of life overall and in each of the seven domains was found. Questionnaire surveys of parents/next of kin and support staff confirmed these findings as did a number of qualitative case studies.

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)0.003
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 score0.004
Threshold uncertainty score0.017

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.001
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 head0.138
GPT teacher head0.444
Teacher spread0.306 · 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

Citations19
Published2012
Admission routes1
Has abstractyes

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