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Record W2750645742 · doi:10.2196/jopm.8756

Evolving Patient-Researcher Collaboration: An Illustrative Case Study of a Patient-Led Knowledge Translation Event

2017· article· en· W2750645742 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
venuePublished in a venue whose home country is Canada.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueJournal of Participatory Medicine · 2017
Typearticle
Languageen
FieldHealth Professions
TopicMental Health and Patient Involvement
Canadian institutionsResearch Canada
Fundersnot available
KeywordsGeneral partnershipKnowledge translationEvent (particle physics)Context (archaeology)MedicineMedical educationTranslational researchKnowledge managementPolitical scienceComputer science

Abstract

fetched live from OpenAlex

Patient engagement occurs when patients actively collaborate in health research in ways that are meaningful to them. Resources to facilitate patient engagement have been developed, but their approach is mainly toward building competencies in the early stages of forming new practices of patient engagement. This paper describes a patient-led collaboration in rheumatology, in the context of an established patient-researcher partnership. Using a case study approach, we report on a research knowledge translation event, titled eROAR2013 (Reaching Out with Arthritis Research), led by members of the Arthritis Patient Advisory Board (APAB), which is a group of volunteer advocates living with arthritis based at Arthritis Research Canada. We provide an overview of APAB's decade-long history, describe the planning and the event itself, and report on the challenges encountered, reflections and solutions pertinent for sustaining patient-researcher collaborative practices.

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.

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)0.003
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.196
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.623
GPT teacher head0.592
Teacher spread0.031 · 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