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Record W3154826442 · doi:10.1111/jrh.12578

Functional status in rural and urban adults: The Canadian Longitudinal Study on Aging

2021· article· en· W3154826442 on OpenAlexafffundabout
Philip St. John, Verena Menec, Robert B. Tate, Nancy E. Newall, Megan E. O’Connell, Denise Cloutier

Bibliographic record

VenueThe Journal of Rural Health · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicHealth disparities and outcomes
Canadian institutionsUniversity of VictoriaUniversity of SaskatchewanBrandon UniversityUniversity of Manitoba
FundersCanadian Institutes of Health ResearchGovernment of Canada
KeywordsRuralityDemographyCensusLogistic regressionCohortMedicineGerontologyRural areaPopulationGeographyCohort studyLongitudinal studyEnvironmental health

Abstract

fetched live from OpenAlex

PURPOSE: To document the prevalence of functional impairment in middle-aged and older adults from rural regions and to determine urban-rural differences. METHODS: We have conducted a secondary analysis using data from an ongoing population-based cohort study, the Canadian Longitudinal Study on Aging (CLSA). We used a cross-sectional sample from the baseline wave of the "tracking cohort." The definition of rurality was the same as the one used in the CLSA sampling frame and based on the 2006 census. This definition includes rural areas, defined as all territory lying outside of population centers, and population centers, which collectively cover all of Canada. We grouped these into "Urban," "Peri-urban," "Mixed" (areas with both rural and urban areas), and "Rural," and compared functional status across these groups. Functional status was measured using the Older Americans Resource Survey (OARS) and categorized as not impaired versus having any functional impairment. Logistic regression models were constructed for the outcome of functional status and adjusted for covariates. FINDINGS: No differences were found in functional status between those living in rural, mixed, peri-urban, and urban areas in unadjusted analyses and in analyses adjusting for sociodemographic and health-related factors. There were no rural-urban differences in any of the individual items on the OARS scales. CONCLUSIONS: We found no rural-urban differences in functional status.

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)0.003
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.233
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.056
GPT teacher head0.370
Teacher spread0.314 · 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.

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

Citations9
Published2021
Admission routes3
Has abstractyes

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