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Record W4224257900 · doi:10.3138/cjpe.70805

Planning the Evaluation of Patient Engagement in the PriCare Research Program

2022· article· en· W4224257900 on OpenAlexaffvenue
Alya Danish, Marlène Karam, Véronique Sabourin, Catherine Hudon, Judy L. Porter, Donna Rubenstein, Mike Warren

Bibliographic record

VenueCanadian Journal of Program Evaluation · 2022
Typearticle
Languageen
FieldHealth Professions
TopicMental Health and Patient Involvement
Canadian institutionsUniversité de Sherbrooke
Fundersnot available
KeywordsPerspective (graphical)Logic modelCorporate governanceKey (lock)Health carePsychologyProcess managementKnowledge managementMedical educationSociologyMedicineComputer scienceBusinessPolitical scienceArtificial intelligence

Abstract

fetched live from OpenAlex

Abstract: The involvement of patients, their families, or their representatives is becoming increasingly common in health-care research. However, theoretical justification of patient engagement (PE) and consistent guidance on how to include patients as key stakeholders on research teams are still lacking. This paper describes how the PriCare group integrates PE into its program’s governance structure and uses a program logic perspective to engage patients in the planning phases of a research study based on resources, processes, and relationships, guided by the SPOR-CIHR’s PE framework. The PriCare approach facilitates the evaluation and continuous improvement of PE.

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)0.074
metaresearch head score (Gemma)0.001
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: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.792
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0740.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0020.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.835
GPT teacher head0.638
Teacher spread0.197 · 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.

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

Citations5
Published2022
Admission routes2
Has abstractyes

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