Engaging indigenous patient partners in patient-oriented research: lessons from a one-year initiative
Bibliographic record
Abstract
BACKGROUND: Patient-oriented research (POR) is a specific application of participatory research that promotes active patient engagement in health research. There is a growing concern that people involved in POR do not reflect the diversity of the population such research aims to serve, but are rather those more 'easily' engaged with institutions, organizations and society. Indigenous peoples are among such groups generally underrepresented in POR. The "Indigenous patient partners platform project" was a small-scale initiative aimed to address the issue of the underrepresentation of Indigenous people in patient-oriented research by recruiting, orienting and supporting Indigenous patient partners in Québec (Canada). This article reports on the findings of an evaluation conducted at the end of the project to garner lessons and identify strategies for engaging Indigenous patient partners in patient-oriented research. METHODS: = 6) were patients and organizational partners. Thematic analysis was performed by two members of the research team. Patient partners actively contributed to validating the interpretation of result and knowledge translation. RESULTS: Results point to four key components of Indigenous patient partner engagement in POR: initiation of partnership, interest development, capacity building and involvement in research. Specific lessons emphasize the importance of community connections in recruiting, sustaining and motivating patient partners, the need to be flexible in the engagement process, and the importance of consistently valuing patient partner contributions and involvement. CONCLUSIONS: There is a need to engage Indigenous patient partners in POR to ensure that healthcare practices, policies and research take their particular needs, stories and culture into account. While results of this evaluation are generally consistent with the existing literature on patient engagement, they offer additional insight into how to effectively engage Indigenous patient partners in research, which might also be relevant to the involvement of other marginalized populations who have been historically and systemically disempowered.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.010 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.004 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.005 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".