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Record W4388044358 · doi:10.1108/amhid-06-2023-0019

Project ECHO-AIDD: recommendations for care of adults with intellectual and developmental disabilities

2023· article· en· W4388044358 on OpenAlexaffabout
Olivia Mendoza, Anupam Thakur, Ullanda Niel, Kendra Thomson, Yona Lunsky, Nicole Bobbette

Bibliographic record

VenueAdvances in Mental Health and Intellectual Disabilities · 2023
Typearticle
Languageen
FieldPsychology
TopicFamily and Disability Support Research
Canadian institutionsQueen's UniversityBrock UniversityUniversity of TorontoCentre for Addiction and Mental Health
Fundersnot available
KeywordsOriginalityMental healthInterprofessional educationHealth carePsychologyDescriptive statisticsValue (mathematics)Medical educationPopulationMedicineNursingPsychiatrySocial psychologyComputer science

Abstract

fetched live from OpenAlex

Purpose This study aims to describe patients presented in an interprofessional, virtual education program focused on the mental health of adults with intellectual and developmental disabilities (IDD), as well as present interprofessional recommendations for care. Design/methodology/approach In this retrospective chart review, descriptive statistics were used to describe patients. Content analysis was used to analyze interprofessional recommendations. The authors used the H.E.L.P. (health, environment, lived experience and psychiatric disorder) framework to conceptualize and analyze the interprofessional recommendations. Findings Themes related to the needs of adults with IDD are presented according to the H.E.L.P. framework. Taking a team-based approach to care, as well as ensuring care provider knowledge of health and social histories, may help better tailor care. Originality/value This project draws on knowledge presented in a national interprofessional and intersectoral educational initiative, the first in Canada to focus on this 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 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)0.000
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation 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 score0.132
Threshold uncertainty score0.918

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.002
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.064
GPT teacher head0.411
Teacher spread0.347 · 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.

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

Citations2
Published2023
Admission routes2
Has abstractyes

Explore more

Same venueAdvances in Mental Health and Intellectual DisabilitiesSame topicFamily and Disability Support ResearchFrench-language works237,207