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Record W2797324674

Comprehensive preventive care assessments for adults with intellectual and developmental disabilities: Part 1: How do we know if it is happening?

2018· article· en· W2797324674 on OpenAlexaffabout
Glenys Smith, Hélène Ouellette‐Kuntz, Michael Green

Bibliographic record

VenuePubMed · 2018
Typearticle
Languageen
FieldMedicine
TopicDown syndrome and intellectual disability research
Canadian institutionsInstitute for Clinical Evaluative SciencesQueen's University
Fundersnot available
KeywordsMedicineCancer screeningPreventive careFamily medicineHealth careOdds ratioDiagnosis codePreventive healthcareMEDLINEGerontologyEnvironmental healthCancerPublic healthNursingPopulationInternal medicine
DOInot available

Abstract

fetched live from OpenAlex

OBJECTIVE: To determine how best to measure the provision of comprehensive preventive care assessment of adults with intellectual and developmental disabilities (IDD). DESIGN: Cross-sectional study. SETTING: Ontario. PARTICIPANTS: Adults with IDD between 40 and 64 years of age in 2013 and 2014. MAIN OUTCOME MEASURES: screening), was identified using administrative health data. RESULTS: A total of 28 825 adults with IDD were identified in 2013 and 2014. Overall, 12.1% of adults with IDD received a health examination; 51.2% received a high (≥ 0.6) PCQS. Male patients were more likely to have received all of their eligible screening maneuvers if they had had a health examination compared with female patients (odds ratio of 5.73 vs 3.99, respectively). CONCLUSION: Less than 60% of adults with IDD appear to be receiving comprehensive preventive care. Future studies assessing the quality of preventive care received by adults with IDD should combine health examination billing codes and the PCQS.

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)0.002
metaresearch head score (Gemma)0.014
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 score0.425
Threshold uncertainty score0.846

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.014
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
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 head0.058
GPT teacher head0.321
Teacher spread0.263 · 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

Citations2
Published2018
Admission routes2
Has abstractyes

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