The Maritime SPOR SUPPORT Unit (MSSU) Bridge Process: An Integrated Knowledge Translation Approach to Address Priority Health Issues and Increase Collaborative Research in Nova Scotia, Canada
Bibliographic record
Abstract
BACKGROUND: There is evidence of the benefits of integrated knowledge translation (IKT), yet there is limited research outlining the purpose of a knowledge broker (KB) within this approach. The Maritime SPOR SUPPORT Unit (MSSU) acts as a KB to support patient-oriented research across the Maritime provinces in Canada. The "Bridge Process" was developed by the Nova Scotia (NS) site as a strategy that involves work leading up to and following the Bridge Event. The process supports research addressing priority health topics discussed at the event by stakeholder groups. The objectives of this paper were to (1) describe the outputs/outcomes of this IKT approach; and (2) examine the role of the KB. METHODS: Quantitative data were collected from registration and evaluation surveys. Outputs are described with descriptive statistics. Qualitative data were collected through evaluation surveys and internal documents. Data related to KB tasks were categorized into three domains: (1) Knowledge Manager, (2) Linkage and Exchange Agent, and (3) Capacity Developer. RESULTS: The Bridge Process was implemented four times. A total of 314 participants including government, health, patient/citizen, community, and research personnel attended the events. We identified 24 priority topics, with 7 led by teams receiving support to complete related projects. Participants reported improved understanding of the research gaps and policy needs and engaged with individuals they would not have otherwise. Although patients/citizens attended each Bridge Event, only 61% of participants who completed an evaluation survey indicated that they were 'actively engaged in group discussion.' The KB's role was identified in all three domains including Knowledge Manager (eg, defining questions), Linkage and Exchange Agent (eg, engaging stakeholders), and Capacity Builder (eg, research interpretation). CONCLUSION: The MSSU facilitated an IKT approach by acting as a KB throughout the Bridge Process. This deliberative and sequential process served as an effective strategy to increase collaborative health research in the province.
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How this classification was reachedexpand
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 | 0.018 | 0.021 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.013 | 0.004 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.003 | 0.012 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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 source (direct Gemma or distilled Codex), 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".