The Interplay between Participatory Health Research and Implementation Research: Canadian Research Funding Perspectives
Bibliographic record
Abstract
OBJECTIVES: The objective of this paper is to investigate what participatory health research (PHR) can offer implementation research (IR) and vice versa and discuss what health research funders can do to foster the intersection of both fields. METHODS: We contrast points of divergence and convergence between IR and PHR. We reflect on whether community engagement is necessary and on the unintended consequences of participation in IR. We describe how a research funder can incentivize PHR in IR. RESULTS: Participation is encouraged in IR but the nuances of who is involved merit greater attention in IR. PHR and IR differ in emphasis placed on the scale-up of the intervention. However, they share a common interest in generating real-world contextually relevant evidence. CONCLUSIONS: We need to assess whether and how funding practices influence researchers in how they undertake PHR. Researchers need to better account for participatory approaches to ensure that any potentially harmful consequences are described (and better understood so they can be mitigated in the future) and elucidate the ways in which these processes do or do not enable implementation and scale-up of interventions in IR.
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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: Incentives · Genre: Review About the Canadian research system: yes · About a Canadian topic: yes | Not applicable | low |
| gpt | Metaresearch Domain: Incentives · Genre: Review About the Canadian research system: yes · About a Canadian topic: yes | Other design | high |
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 | 0.312 | 0.030 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.012 | 0.008 |
| Science and technology studies | 0.025 | 0.008 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.004 | 0.003 |
| Research integrity | 0.001 | 0.012 |
| Insufficient payload (model declined to judge) | 0.002 | 0.004 |
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".