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Record W2030140469 · doi:10.1352/2009.114:52-60

Gender Differences in Psychiatric Diagnoses Among Inpatients With And Without Intellectual Disabilities

2009· article· en· W2030140469 on OpenAlexaff
Yona Lunsky, Elspeth Bradley, Carolyn Gracey, Janet Durbin, Chris Koegl

Bibliographic record

VenueAmerican Journal on Intellectual and Developmental Disabilities · 2009
Typearticle
Languageen
FieldMedicine
TopicDown syndrome and intellectual disability research
Canadian institutionsUniversity of TorontoSurrey Place CentreCentre for Addiction and Mental Health
Fundersnot available
KeywordsIntellectual disabilityPsychiatryMoodMedical diagnosisSubstance abusePsychiatric diagnosisClinical psychologySexual abusePsychologyMood disordersMedicinePoison controlSuicide preventionAnxietySchizophrenia (object-oriented programming)

Abstract

fetched live from OpenAlex

There are few published studies on the relationship between gender and psychiatric disorders in individuals with intellectual disabilities. Adults (N = 1,971) with and without intellectual disabilities who received inpatient services for psychiatric diagnosis and clinical issues were examined. Among individuals with intellectual disabilities, women were more likely to have a diagnosis of mood disorder and sexual abuse history; men were more likely to have a substance abuse diagnosis, legal issues, and past destructive behavior. Gender difference patterns found for individuals with intellectual disabilities were similar to those of persons without intellectual disabilities, with the exception of eating disorder and psychotic disorder diagnoses. Gender issues should receive greater attention in intellectual disabilities inpatient care.

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)0.001
metaresearch head score (Gemma)0.005
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 score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
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 head0.037
GPT teacher head0.292
Teacher spread0.255 · 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

Citations28
Published2009
Admission routes1
Has abstractyes

Explore more

Same venueAmerican Journal on Intellectual and Developmental DisabilitiesSame topicDown syndrome and intellectual disability researchFrench-language works237,207