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Record W2617166088 · doi:10.1017/s0714980817000150

Examining Rural Older Adults’ Perceptions of Cognitive Health

2017· article· fr· W2617166088 on OpenAlexaff
Juanita-Dawne Bacsu, Sylvia Abonyi, Marc Viger, Debra Morgan, Shanthi Johnson, Bonnie Jeffery

Bibliographic record

VenueCanadian Journal on Aging / La Revue canadienne du vieillissement · 2017
Typearticle
Languagefr
FieldPsychology
TopicAging and Gerontology Research
Canadian institutionsUniversity of ReginaUniversity of SaskatchewanSaskatchewan Health
Fundersnot available
KeywordsDementiaCognitionGerontologyCognitive declinePerceptionPsychologyRural healthRural areaMedicinePsychiatryDisease

Abstract

fetched live from OpenAlex

Existing cognitive health literature focuses on the perspectives of older adults with dementia. However, little is known about the ways in which healthy older adults without dementia understand their cognitive health. In rural communities, early dementia diagnosis may be impeded by numerous factors including transportation challenges, cultural obstacles, and inadequate access to health and support services. Based on participant observation and two waves of 42 semi-structured interviews, this study examined healthy, rural older adults' perceptions of cognitive health. By providing an innovative theoretical foundation informed by local perspectives and culture, findings reveal a complex and multidimensional view of cognitive health. Rural older adults described four key areas of cognitive health ranging from independence to social interaction. As policy makers, community leaders, and researchers work to address the cognitive health needs of the rural aging demographic, it is essential that they listen to the perspectives of rural older adults.

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)0.003
metaresearch head score (Gemma)0.007
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.024
Threshold uncertainty score0.048

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0020.001
Scholarly communication0.0010.001
Open science0.0000.002
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 head0.037
GPT teacher head0.329
Teacher spread0.292 · 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

Citations6
Published2017
Admission routes1
Has abstractyes

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Same venueCanadian Journal on Aging / La Revue canadienne du vieillissementSame topicAging and Gerontology ResearchFrench-language works237,207