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Record W2899192278 · doi:10.14283/jfa.2018.30

Social and Societal Implications of Frailty, Including Impact on Canadian Healthcare Systems

2018· article· en· W2899192278 on OpenAlexaffabout
Melissa K. Andrew, Suzanne Dupuis‐Blanchard, Colleen J. Maxwell, Anik Giguère, Janice Keefe, Kenneth Rockwood, Philip St. John

Bibliographic record

VenueThe Journal of Frailty & Aging · 2018
Typearticle
Languageen
FieldMedicine
TopicFrailty in Older Adults
Canadian institutionsUniversity of ManitobaDalhousie UniversityUniversité LavalUniversity of WaterlooMount Saint Vincent UniversityUniversité de Moncton
Fundersnot available
KeywordsGerontologyAction (physics)Intervention (counseling)MedicineSocial policyHealth careSocial determinants of healthCall to actionHealth policyPublic relationsEconomic growthPublic healthNursingPolitical scienceBusiness

Abstract

fetched live from OpenAlex

Frailty has many social and societal implications. Social circumstances are key both as contributors to frail older adults' health outcomes and as practical facilitators or barriers to intervention and supports. Frailty also has important societal implications for health systems and social care policy. In this discussion paper, we use a social ecology framework to consider the social and societal implications and impact of frailty at each level, from the individual, through relationships with family and friend caregivers, institutions, health systems, neighborhoods and communities, to society at large. We conclude by arguing that attention to these issues at a policy level is critical. We identify three target actions: 1) Social dimensions of frailty should be systematically considered when frailty is assessed. 2) Action is needed at the level of policies and programs to improve support for caregivers. 3) Policy review across all portfolios will benefit from a social frailty lens.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.571
Threshold uncertainty score0.968

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.109
GPT teacher head0.407
Teacher spread0.298 · 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.

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

Citations44
Published2018
Admission routes2
Has abstractyes

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