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A comparison of outpatients with intellectual disability receiving specialised and general services in Ontario's psychiatric hospitals

2010· article· en· W2051871139 on OpenAlexaffabout
Yona Lunsky, Carolyn Gracey, Elspeth Bradley, Chris Koegl, Janet Durbin

Bibliographic record

VenueJournal of Intellectual Disability Research · 2010
Typearticle
Languageen
FieldMedicine
TopicDown syndrome and intellectual disability research
Canadian institutionsSurrey Place CentreCentre for Addiction and Mental Health
Fundersnot available
KeywordsDemographicsIntellectual disabilityMental healthPsychiatryMedicineService (business)Family medicineTertiary careStratified samplingHealth servicesPresentation (obstetrics)PopulationEnvironmental healthDemography

Abstract

fetched live from OpenAlex

BACKGROUND: This study compares outpatients with intellectual disability (ID) receiving specialised services to outpatients with ID receiving general services in Ontario's tertiary mental healthcare system in terms of demographics, symptom profile, strengths and resources, and clinical service needs. METHODS: A secondary analysis of Colorado Client Assessment Record data collected from all tertiary psychiatric hospitals in the province was completed for a stratified random sample of 246 outpatients identified as having ID, from both specialised and general programmes. RESULTS: Individuals with ID in specialised programmes differed from patients with ID in general programmes with regard to demographics, diagnostic profile, symptom presentation and recommended level of care. CONCLUSIONS: Further research is required to determine why individuals access some services over others and to evaluate whether specialised services are more appropriate for certain subgroups with ID than others.

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)0.006
metaresearch head score (Gemma)0.015
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Science and technology studies, Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.090
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.015
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0010.002
Science and technology studies0.0000.004
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.005
Insufficient payload (model declined to judge)0.0070.000

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 head0.068
GPT teacher head0.406
Teacher spread0.339 · 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.

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

Citations12
Published2010
Admission routes2
Has abstractyes

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