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Record W2396018514

Dependency, chronic conditions and pain in seniors.

2006· article· en· W2396018514 on OpenAlexaffabout
Heather Gilmour, Jungwee Park

Bibliographic record

VenuePubMed · 2006
Typearticle
Languageen
FieldSocial Sciences
TopicHealth disparities and outcomes
Canadian institutionsStatistics Canada
Fundersnot available
KeywordsActivities of daily livingMedicineDependency (UML)DementiaLogistic regressionChronic painGerontologyChronic diseasePhysical therapyDiseaseInternal medicine
DOInot available

Abstract

fetched live from OpenAlex

OBJECTIVES: This article presents the prevalence of dependency and selected chronic conditions among Canadians aged 65 or older living in households. Associations between chronic conditions and dependency in activities of daily living (ADL) and instrumental activities of daily living (IADL) are examined. DATA SOURCE: Estimates are based on data from the 2003 Canadian Community Health Survey. ANALYTICAL TECHNIQUES: Cross-tabulations were used to estimate the prevalence of ADL/IADL dependency and chronic conditions. Associations between chronic conditions and dependency were studied using multiple logistic regression models. MAIN RESULTS: The prevalence of ADL/IADL dependency and chronic conditions increased with age. IADL dependency was more common than ADL dependency. When chronic pain was taken into account, associations between ADL dependency and arthritis/rheumatism, diabetes and urinary incontinence were no longer significant, and the association between IADL dependency and diabetes lost significance. Regardless of chronic pain, Alzheimer's disease or other dementia and the effects of stroke were significantly related to dependency.

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)0.000
metaresearch head score (Gemma)0.001
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 score0.457
Threshold uncertainty score0.908

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.000

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 head0.016
GPT teacher head0.279
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

Citations78
Published2006
Admission routes2
Has abstractyes

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