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Record W4409337369 · doi:10.5334/ijic.icic24577

The Participatory Research to Action (PR2A) Framework: applications and opportunities for authentic engagement of experts-by-experience from inception to uptake

2025· article· en· W4409337369 on OpenAlexaboutno aff
Justine Giosa, Paul Holyoke, Valentina Cardozo, Olinda Habib Perez

Bibliographic record

VenueInternational Journal of Integrated Care · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicParticipatory Visual Research Methods
Canadian institutionsnot available
Fundersnot available
KeywordsParticipatory action researchCitizen journalismAction (physics)Action researchKnowledge managementSociologyPublic relationsEngineering ethicsPolitical scienceComputer scienceEngineeringWorld Wide WebPedagogy

Abstract

fetched live from OpenAlex

Participatory approaches to health services research represent a paradigm shift that values the knowledge of experts-by-experience, including patients, caregivers, members of the general public, healthcare providers, and decision-makers. While many frameworks have been developed, they are generally tailored to a sector, health condition, research stage, or research design. After an extensive literature scan and our team's deep expertise in community-based, applied health services research, the SE Research Centre developed a novel framework to guide the involvement of experts-by-experience, incorporating concepts from service design, co-design, and integrated knowledge translation. Our Participatory Research to Action (PR2A) framework offers flexible yet structured guidance for engaging with experts-by-experience in the complete research cycle, from development of questions and methods to relationship-building, prototype testing and evaluation. The PR2A framework emphasizes creative approaches and embeds meaningful engagement of experts-by-experience through six iterative stages: 1) Readiness; 2) Discover; 3) Define; 4) Develop; 5) Deliver; and 6) Measure. In this interactive workshop, delegates interested in creative, rigorous co-design research will learn about the features of the PR2A framework and how to apply it within their research settings and projects. First, we will describe the PR2A framework and its development. We will then provide two case studies showcasing the application of the PR2A framework in federally-funded research studies across Canada: (1) the co-design and testing of Our Dementia Journey Journal, an interactive resource to facilitate sustainable relationship building between caregivers and care providers of persons living with dementia, including versions to respect culture-specific approaches to dementia in First Nations and South Asian communities in Canada; and (2) the co-design of tools and approaches for non-mental health specialists in home and community care to start non-stigmatizing mental health conversations with clients and their caregivers. Then we will introduce delegates to a real research scenario about post-cardiac surgery care and provide materials and an opportunity for delegates to be supported in small groups to work through the PR2A framework to address the scenario. The small group work will be designed to resemble the Develop stage of the framework, enabling the delegates to experience part of the framework as participants. Finally, in a share-back session, delegates will have an opportunity to share their experience with the PR2A framework, and how it may offer new paths for their future research. Workshop outline: 1. 10 minutes – PR2A framework introduction 2. 12 minutes – Case 1: Applying the PR2A in the development and cultural adaptation of Our Dementia Journey Journal 3. 12 minutes – Case 2: Applying the PR2A in developing a process and tools for starting non-stigmatizing mental health conversations 4. 10 minutes – Introduction of the post-cardiac surgery care scenario 5. 36 minutes – Small group experience using the PR2A framework 6. 10 minutes – Wrap up, questions, and reflections Takeaways: Delegates will be provided with template PR2A materials, be equipped with experience working through the framework, and be given access to additional online resources and examples to inform their future participatory research practice; authentically engaging experts-by-experience throughout the full research cycle.

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)0.004
metaresearch head score (Gemma)0.006
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.758
Threshold uncertainty score0.678

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
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 head0.724
GPT teacher head0.671
Teacher spread0.053 · 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 designOther design
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

Citations1
Published2025
Admission routes1
Has abstractyes

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