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Record W4308550533 · doi:10.1177/23333936221129836

Research Partnerships with Patients Living with Type 2 Diabetes: Practices and Challenges in Quebec Among People New to Canada

2022· article· en· W4308550533 on OpenAlexaffabout
Séraphin Balla, Maman Joyce Dogba, Monika Kastner

Bibliographic record

VenueGlobal Qualitative Nursing Research · 2022
Typearticle
Languageen
FieldHealth Professions
TopicHealth Policy Implementation Science
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsInclusion (mineral)BeneficiaryPublic relationsEquity (law)Diversity (politics)Participatory action researchHealth careGeneral partnershipPsychologyMedicinePolitical scienceGerontologySociologySocial psychology

Abstract

fetched live from OpenAlex

Patients are increasingly encouraged to participate in health research programs as partners, with the aim to ensure that studies address their priorities. In response, the Strategy for Patient-Oriented Research (SPOR) has been created in Canada to transform the patient's role in research from a passive beneficiary to a more proactive partner of change within the healthcare system. This research investigates what people new to Canada living with type 2 diabetes think about participating in research partnerships. Using an ethnographic approach, 31 people new to Canada with a diagnosis of type 2 diabetes were interviewed. Findings indicated that few people new to Canada were represented among the Diabetes Action Canada (DAC) Network's Circles of Patient Partners in Quebec. Barriers to engagement in research were: lack of information; competing priorities; language barrier and privacy concerns; preconceptions about being a patient partner; prejudices on research engagement as something demanding and binding; and the matter of religious and gender differences. Some participants questioned the extent to which involvement in research can really meet their expectations considering institutional control over research, funding requirements that often dictate priorities and the biomedical approach which still, in many respects, dominates health research. Implications for achieving equity, diversity, and inclusion of patient partners in research are discussed.

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)0.024
metaresearch head score (Gemma)0.015
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 score0.079
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0240.015
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.004
Science and technology studies0.0030.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.002
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 head0.838
GPT teacher head0.722
Teacher spread0.117 · 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 designQualitative
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

Citations0
Published2022
Admission routes2
Has abstractyes

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