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Record W3132134055 · doi:10.1186/s40900-021-00255-4

Developing a Canadian evaluation framework for patient and public engagement in research: study protocol

2021· article· en· W3132134055 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.
fundA Canadian funder is recorded on the work.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueResearch Involvement and Engagement · 2021
Typearticle
Languageen
FieldHealth Professions
TopicMental Health and Patient Involvement
Canadian institutionsDalhousie UniversityMcGill University Health CentreCanadian Foundation for Healthcare ImprovementUniversité de MontréalUniversité LavalUniversité de SherbrookeMcMaster UniversityUniversity of CalgaryAthabasca UniversityCentre Intégré Universitaire de Santé et de Services Sociaux du Saguenay–Lac-Saint-JeanImpact
FundersCanadian Institutes of Health ResearchCanada Research ChairsDiabetes Action Research and Education Foundation
KeywordsDelphi methodCommunity engagementMedical educationPublic relationsPublic engagementMedicineParticipatory action researchKnowledge managementPolitical scienceSociologyComputer science

Abstract

fetched live from OpenAlex

BACKGROUND: Patient and public engagement (PPE) in research is growing internationally, and with it, the interest for its evaluation. In Canada, the Strategy for Patient-Oriented Research has generated national momentum and opportunities for greater PPE in research and health-system transformation. As is the case with most countries, the Canadian research community lacks a common evaluation framework for PPE, thus limiting our capacity to ensure integrity between principles and practices, learn across projects, identify common areas for improvement, and assess the impacts of engagement. OBJECTIVE: This project aims to build a national adaptable framework for the evaluation of PPE in research, by: 1. Building consensus on common evaluation criteria and indicators for PPE in research; 2. Defining recommendations to implement and adapt the framework to specific populations. METHODS: Using a collaborative action-research approach, a national coalition of patient-oriented research leaders, (patient and community partners, engagement practitioners, researchers and health system leaders) will co-design the evaluation framework. We will develop core evaluation domains of the logic model by conducting a series of virtual consensus meetings using a nominal group technique with 50 patient partners and engagement practitioners, identified through 18 national research organizations. We will then conduct two Delphi rounds to prioritize process and impact indicators with 200 participants purposely recruited to include respondents from seldom-heard groups. Six expert working groups will define recommendations to implement and adapt the framework to research with specific populations, including Indigenous communities, immigrants, people with intellectual and physical disabilities, caregivers, and people with low literacy. Each step of framework development will be guided by an equity, diversity and inclusion approach in an effort to ensure that the participants engaged, the content produced, and the adaptation strategies proposed are relevant to diverse PPE. DISCUSSION: The potential contributions of this project are threefold: 1) support a national learning environment for engagement by offering a common blueprint for collaborative evaluation to the Canadian research community; 2) inform the international research community on potential (virtual) methodologies to build national consensus on common engagement evaluation frameworks; and 3) illustrate a shared attempt to engage patients and researchers in a strategic national initiative to strengthen evaluation capacity for PPE.

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)0.058
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.586
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0580.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0050.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.002
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 head0.887
GPT teacher head0.645
Teacher spread0.242 · 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