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Record W3111806256 · doi:10.1002/alz.040918

Policy, practice, and public awareness: A review of national and international approaches to improve diagnosis and post‐diagnostic support for people living with dementia

2020· review· en· W3111806256 on OpenAlexaboutno aff
Marie Poole, Jane Wilcock, Greta Rait, Henry Brodaty, Louise Robinson

Bibliographic record

VenueAlzheimer s & Dementia · 2020
Typereview
Languageen
FieldMedicine
TopicDementia and Cognitive Impairment Research
Canadian institutionsnot available
Fundersnot available
KeywordsDementiaThematic analysisPublic relationsQualitative researchPsychologyPolitical scienceMedicineNursingMedical educationSociologySocial sciencePathology

Abstract

fetched live from OpenAlex

Abstract Background International policy emphasises the importance of gaining a diagnosis and access to better support to for people living with dementia and those providing support. The COGNISANCE programme aligns with key policy objectives to advance dementia diagnosis and post‐diagnostic support across three continents. COGNISANCE comprises an international team from Australia, Canada, Netherlands, Poland and the UK. Researchers, people living with dementia, informal care partners, health and social care professionals and key national and international dementia organisations are working together to co‐design, deliver and evaluate toolkits and campaigns; to improve the dementia diagnostic process and post‐diagnostic support in partner countries. Our aim was to review existing evidence to inform the development of new international dementia toolkits and campaigns. The review included: national and international dementia plans/strategies; evidence‐based guidelines; and public awareness campaigns from our partner countries and international organisations. Method Undertaking a qualitative approach, we applied scoping review framework methodology, conducted online searches for sources, and consulted with partner countries, national and international organisations. Where needed, documents were translated into English to ensure broad representation and facilitate analysis. Concepts relating to diagnosis, and post diagnostic support were extracted from each source and mapped. Thematic analysis of the evidence elicited core themes, components, and gaps in current approaches to improving diagnosis and post‐diagnostic support. Result Analysis of documents from five partner countries and four international organisations relating to diagnosis and post diagnostic support revealed 15 themes from 15 dementia strategies and 13 guidelines; and 13 themes from 13 national and international public awareness strategies. Core themes were awareness raising; information, care and support; diagnostic processes and community/social aspects of dementia. Analysis of national and international themes for diagnosis and post‐diagnostic support are indicative of central messages and target audiences; additionally, we have identified areas not yet prioritised. Conclusion Despite some cross‐country commonality in themes, considerable diversity and inconsistency remain in the key messages regarding dementia diagnosis and post diagnostic support. Awareness of current themes, emergent gaps, and alignment of key areas for different audiences will inform the co‐design of our new, international campaigns and toolkits.

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)0.046
metaresearch head score (Gemma)0.098
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.046
Threshold uncertainty score0.245

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0460.098
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0030.003
Bibliometrics0.0160.024
Science and technology studies0.0020.004
Scholarly communication0.0080.007
Open science0.0020.004
Research integrity0.0030.004
Insufficient payload (model declined to judge)0.0020.000

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 head0.105
GPT teacher head0.381
Teacher spread0.275 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations1
Published2020
Admission routes1
Has abstractyes

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