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Record W2170345342 · doi:10.1352/2008.46:446-455

Emergency Psychiatric Services for Individuals With Intellectual Disabilities: Perspectives of Hospital Staff

2008· article· en· W2170345342 on OpenAlexaffabout
Yona Lunsky, Carolyn Gracey, Sara Gelfand

Bibliographic record

VenueIntellectual and developmental disabilities · 2008
Typearticle
Languageen
FieldMedicine
TopicDown syndrome and intellectual disability research
Canadian institutionsUniversity of TorontoCentre for Addiction and Mental Health
Fundersnot available
KeywordsRespite careMainstreamIntellectual disabilityPsychiatric hospitalNursingMedicineMental healthPsychiatryEconomic shortageMental illnessPsychologyGovernment (linguistics)

Abstract

fetched live from OpenAlex

Strains on the mainstream mental health system can result in inaccessible services that force individuals with intellectual disabilities into the emergency room (ER) when in psychiatric crisis. The purpose of this study was to identify clinical and systemic issues surrounding emergency psychiatry services for people with intellectual disabilities, from the perspective of hospital staff. Focus groups were conducted with emergency psychiatry staff from 6 hospitals in Toronto, Canada. Hospital staff reported a lack of knowledge regarding intellectual disabilities and a shortage of available community resources. Hospital staff argued that caregivers need more community and respite support to feel better equipped to deal with the crisis before it escalates to the ER and that hospital staff feel ill prepared to provide the necessary care when the ER is the last resort. Input from hospital staff pointed to deficiencies in the system that lead caregivers to use the ER when other options have been exhausted. Both staff and caregivers need support and access to appropriate services if the system is to become more effective at serving the psychiatric needs of this complex population.

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)0.005
metaresearch head score (Gemma)0.012
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.046
Threshold uncertainty score0.091

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.012
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0070.002
Scholarly communication0.0040.002
Open science0.0010.003
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0030.000

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 head0.028
GPT teacher head0.287
Teacher spread0.259 · 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 designQualitative
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

Citations50
Published2008
Admission routes2
Has abstractyes

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