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Record W2887599030 · doi:10.1111/jgs.15453

Patient and Public Involvement in Identifying Dementia Research Priorities

2018· article· en· W2887599030 on OpenAlexafffundabout
Jennifer Bethell, Dorothy Pringle, Larry W. Chambers, Carole Cohen, Elana Commisso, Katherine Cowan, Phyllis Fehr, Andreas Laupacis, P Szeto, Katherine S. McGilton

Bibliographic record

VenueJournal of the American Geriatrics Society · 2018
Typearticle
Languageen
FieldHealth Professions
TopicMental Health and Patient Involvement
Canadian institutionsToronto Dementia Research AllianceUniversity Health NetworkHealth Sciences CentreAlzheimer Society of CanadaMcMaster UniversityImpactInstitute for Clinical Evaluative SciencesBruyèreYork UniversityUniversity of TorontoSt. Michael's HospitalSunnybrook Health Science CentreToronto Rehabilitation Institute
FundersAlzheimer Society Research ProgramAlzheimer Society
KeywordsMedicineDementiaMEDLINEPublic healthGerontologyFamily medicineNursingPathologyDisease

Abstract

fetched live from OpenAlex

OBJECTIVES: To engage persons with dementia, friends, family, caregivers, and health and social care providers to identify and prioritize their questions for research related to living with dementia and prevention, diagnosis, and treatment of dementia. DESIGN: The Canadian Dementia Priority Setting Partnership (PSP) followed James Lind Alliance PSP methods. Results were compared with the World Health Organization research prioritization exercise and the United Kingdom Dementia PSP. SETTING: Canada. PARTICIPANTS: In the first survey, 1,217 individuals and groups from across Canada submitted their questions about dementia. 249 participated in the interim prioritization. For the final prioritization workshop, the 28 participants included persons with dementia, friends, family, caregivers, health and social care providers, Alzheimer Society representatives, and members of an organization representing long-term care home residents. RESULTS: The Canadian Dementia PSP top 10 priorities relate to health, quality of life, societal issues, and dementia care. Five priorities overlap with one or both of the other two prioritization initiatives. CONCLUSION: These results provide researchers and research funding agencies with topics that individuals with personal or professional experience of dementia prioritize, but they are not intended to preclude research into other aspects of 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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.477
Threshold uncertainty score0.987

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 studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.001
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 head0.289
GPT teacher head0.471
Teacher spread0.181 · 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

Citations74
Published2018
Admission routes3
Has abstractyes

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