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Record W1199178691 · doi:10.1177/1084822315591812

Self-Rated Health, Cognition, and Dual Sensory Impairment Are Important Predictors of Depression Among Home Care Clients in Ontario

2015· article· en· W1199178691 on OpenAlexaffabout
Dawn M. Guthrie, Éric R. Thériault, Jacob G. S. Davidson

Bibliographic record

VenueHome Health Care Management & Practice · 2015
Typearticle
Languageen
FieldMedicine
TopicDementia and Cognitive Impairment Research
Canadian institutionsBrandon UniversityWilfrid Laurier University
Fundersnot available
KeywordsDepression (economics)MedicineCognitionGerontologyCognitive impairmentOddsHealth careOdds ratioClinical psychologyPsychiatryLogistic regression

Abstract

fetched live from OpenAlex

Depression can be a disabling and debilitating condition among older adults (aged 65+). This study examined risk factors for symptoms of depression in a large sample of older home care clients ( n = 218,850) in Ontario, Canada, using existing data collected with the Resident Assessment Instrument for Home Care (RAI-HC). The RAI-HC has been mandated across the province since 2002. The most important predictors of depression were lower self-rated health (odds ratio [OR] = 3.4), cognitive impairment (OR = 2.9), dual sensory impairment (OR = 1.2), and a primary language other than English or French (OR = 1.5). This suggests that not only physical health but also sensory impairments and communication difficulties increase the risk for depression among home care recipients.

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)0.002
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 score0.136
Threshold uncertainty score0.274

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.018
GPT teacher head0.324
Teacher spread0.305 · 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

Citations16
Published2015
Admission routes2
Has abstractyes

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