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Record W2888126996 · doi:10.1177/1471301218793463

Young onset dementia: Public involvement in co-designing community-based support

2018· article· en· W2888126996 on OpenAlexfundno aff
Andrea Mayrhofer, Elspeth Mathie, Jane McKeown, Claire Goodman, Lisa Irvine, Natalie Hall, Michael Walker

Bibliographic record

VenueDementia · 2018
Typearticle
Languageen
FieldHealth Professions
TopicMental Health and Patient Involvement
Canadian institutionsnot available
FundersNational Institute for Health Research Collaboration for Leadership in Applied Health Research and Care Yorkshire and HumberUniversity of HertfordshireNational Institute for Health and Care ResearchAlzheimer SocietyUniversity of ExeterUniversity of East AngliaAlzheimer's Society
KeywordsDementiaService delivery frameworkService providerProject commissioningAged careCommunity serviceService (business)GerontologyPsychologyNursingMedicinePublishingPublic relationsPolitical scienceBusiness

Abstract

fetched live from OpenAlex

Whilst the support requirements of people diagnosed with young onset dementia are well-documented, less is known about what needs to be in place to provide age-appropriate care. To understand priorities for service planning and commissioning and to inform the design of a future study of community-based service delivery models, we held two rounds of discussions with four groups of people affected by young onset dementia (n = 31) and interviewed memory services (n = 3) and non-profit service providers (n = 7) in two sites in England. Discussions confirmed published evidence on support requirements, but also reframed priorities for support and suggested new approaches to dementia care at the community level. This paper argues that involving people with young onset dementia in the assessment of research findings in terms of what is important to them, and inviting suggestions for solutions, provides a way for co-designing services that address the challenges of accessing support for people affected by young onset dementia.

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)0.005
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.675
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0030.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0060.002

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 head0.295
GPT teacher head0.436
Teacher spread0.141 · 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 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

Citations40
Published2018
Admission routes1
Has abstractyes

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