Exploring the perspectives of community members as research partners in rural and remote areas
Bibliographic record
Abstract
BACKGROUND: Community engagement in research has the potential to support the development of meaningful health promotion interventions to address health inequities. People living in rural and remote areas face increased barriers to participation in health research and may be unjustly excluded from participation. It is necessary to understand the process of patient and public engagement from the perspective of community members to support partnered research in underserved areas. The aim of this project was to increase understanding on how to include community members from rural and remote areas as partners on research teams. METHODS: Using purposive sampling, we completed semi-structured interviews with a representative sample of 12 community members in rural and remote areas of northern British Columbia, Canada. Interviews were audio recorded and transcribed verbatim. Following an integrated knowledge translation approach, an inductive thematic analysis was completed to incorporate researcher and knowledge user perspectives. RESULTS: The factors important to community members for becoming involved in research include: 1) relevance; 2) communication; and 3) empowering participation. The analysis suggests projects must be relevant to both communities and individuals. Most participants stated that they would not be interested in becoming partners on research projects that did not have a direct benefit or value for their communities. Participants expressed the need for clear expectations and clarification of preferred communication mechanisms. Communication must be regular, appropriate in length and content, and written in a language that is accessible. It is essential to ensure that community members are recognized as subject matter experts, to provide appropriate training on the research process, and to use research outcomes to support decision making. CONCLUSIONS: To engage research partners in rural and remote communities, research questions and outcomes should be co-produced with community members. In-person relationships can help establish trust and bidirectional communication mechanisms are prudent throughout the research process, including the appropriate sharing of research findings. Although this project did not include community members as research team members or in the co-production of this research article, we present guidelines for research teams interested in adding a patient or public perspective to their integrated knowledge translation teams.
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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 arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | Metaresearch Domain: Methods · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Qualitative | low |
| gpt | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Qualitative | low |
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.032 | 0.038 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.025 | 0.015 |
| Scholarly communication | 0.010 | 0.006 |
| Open science | 0.003 | 0.013 |
| Research integrity | 0.004 | 0.006 |
| Insufficient payload (model declined to judge) | 0.004 | 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, unvalidatedLabeled directly by 2 models reading the full record.
The models disagree on parts of this classification; every voice is preserved in the section at the end of the page.
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".