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Record W2604285491 · doi:10.12927/hcpap.2017.25005

Let’s Put the Pieces Together: Frailty, Social Vulnerability, the Continuum of Care, Prevention and Research are Key Considerations for a Dementia Care Strategy

2016· letter· en· W2604285491 on OpenAlexaffvenueabout
Melissa K. Andrew

Bibliographic record

VenueA Nudge Too Far? A Nudge at All? On Paying People to Be Healthy · 2016
Typeletter
Languageen
FieldHealth Professions
TopicAging, Elder Care, and Social Issues
Canadian institutionsDalhousie University
Fundersnot available
KeywordsDementiaVulnerability (computing)Health carePsychologyMedicineNursingPolitical scienceComputer scienceDisease

Abstract

fetched live from OpenAlex

Improving dementia care in Canada is a challenge to which we must rise. Dementia care strategies with a strong community focus are a key means of doing so. This paper outlines and expands upon the following five core areas that will contribute to the success of dementia care strategies: 1) the relationship between frailty and dementia is critical to understanding and addressing dementia risk and management; 2) social circumstances are important to formally consider, both as risk factors for adverse outcomes and as practical factors that contribute to care and support planning; 3) a dementia care strategy must span the continuum of care, which has important ramifications for our systems of primary, acute and long-term care; 4) prevention and public education are essential components of dementia care strategies; 5) research and evaluation are critically important to any dementia care strategy, and must be seen as core components as we strive to learn what works in dementia care. Given that a coordinated effort is needed, Canada needs to join other countries that have recognized dementia as a momentous challenge to national and global health. The time for a comprehensive national dementia care strategy is now.

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)0.004
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Research integrity
Consensus categoriesResearch integrity
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.108
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0080.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0010.003
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 head0.202
GPT teacher head0.470
Teacher spread0.268 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
Domainnot available
GenreCommentary

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

Citations7
Published2016
Admission routes3
Has abstractyes

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