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Record W4281291710 · doi:10.1186/s12961-022-00863-w

Engaging people with lived experience on advisory councils of a national not-for-profit: an integrated knowledge translation case study of Heart & Stroke Mission Critical Area Councils

2022· article· en· W4281291710 on OpenAlexafffundabout
Krystina B. Lewis, Nedra Peter, Christine Faubert, Mary Elizabeth Harriman, Patrice Lindsay, Anne Simard, Cindy Yip, Ian D. Graham, Anita Kothari

Bibliographic record

VenueHealth Research Policy and Systems · 2022
Typearticle
Languageen
FieldHealth Professions
TopicHealth Policy Implementation Science
Canadian institutionsOttawa HospitalWestern UniversityUniversity of Ottawa
FundersCanadian Institutes of Health Research
KeywordsKnowledge translationHealth services researchQualitative researchMedicinePublic relationsGroup cohesivenessPublic healthNursingSociologyPolitical scienceKnowledge management

Abstract

fetched live from OpenAlex

BACKGROUND: In 2018, the Heart and Stroke Foundation of Canada transformed its approach to organizational strategic planning and priority-setting. The goal was to generate impact from bench to bedside to community, to improve the health of Canadians. It engaged researchers, clinician scientists, health systems leaders, and community members including people with lived experience (PWLE) on six Mission Critical Area (MCA) councils, each of which was co-chaired by a researcher or clinician scientist and a person with lived experience. Together, council members were tasked with providing advice to Heart & Stroke about the most relevant and impactful priorities of our time. The aim of this research was to explore the value of the MCA councils to Heart & Stroke, and to council members themselves. The research questions focused on understanding the process of managing and participating on the councils, the challenges and outcomes. METHODS: Using an integrated knowledge translation approach, we conducted a case study with developmental evaluation over a 2-year time period (2018-2020). We collected qualitative data from various sources (Heart & Stroke team responsible for managing the councils, council co-chairs, council members, and key informants). We collected documents and analysed them for contextual background. RESULTS: Participants noted that the MCA councils continuously evolved over the 2 years in various ways: from an uncertain direction to a concrete one, better integrating the voice of PWLE, and increased cohesiveness within and across MCA councils. This evolution was achieved in parallel with successes and challenges at three levels: the MCA councils and its members, Heart & Stroke, and Canadians. The MCA councils were disbanded in 2020, yet learnings, developments, initiatives and established partnerships remain as their legacy. CONCLUSIONS: Heart & Stroke's intended objectives for the MCA councils, to promote engagement and dialogue among community members including PWLE, clinician scientists, and researchers, and to provide advice into Heart & Stroke's strategic renewal process, were achieved. This collaborative structure and process for PWLE engagement within a community of multidisciplinary clinician scientists and researchers is possible yet requires flexibility, commitment to stakeholder relationship management, and considerable resources. These findings may be helpful for other not-for-profit and funding organizations interested in engaging the public and other stakeholders into their organizational activities.

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

Direct model labels (unvalidated)

Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.

Model armCategoriesStudy designConfidence
gemmano category
Domain: not available · Genre: Empirical
About the Canadian research system: no · About a Canadian topic: no
Qualitativelow
gptMetaresearch
Domain: Methods · Genre: Empirical
About the Canadian research system: no · About a Canadian topic: no
Observationallow
models splitAgreement compares identical category sets and study designs across arms.

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)0.035
metaresearch head score (Gemma)0.007
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Science 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 score0.031
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0350.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0040.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.941
GPT teacher head0.733
Teacher spread0.208 · 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

Labeled directly by 2 models reading the full record.

Metaresearch

The models disagree on parts of this classification; every voice is preserved in the section at the end of the page.

Study designQualitative · Observational
DomainMethods
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

Citations5
Published2022
Admission routes3
Has abstractyes

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