What do we know about health-related knowledge translation in the Circumpolar North? Results from a scoping review
Bibliographic record
Abstract
BACKGROUND: Health research knowledge translation (KT) is important to improve population health outcomes. Considering social, geographical and cultural contexts, KT in Inuit communities often requires different methods than those commonly used in non-Inuit populations. OBJECTIVES: To examine the extent, range and nature of literature about health-related KT in Inuit communities. DESIGN: A scoping review was conducted. A search string was used to search 2 English aggregator databases, ProQuest and EBSCOhost, on 12 March 2015. Study selection was conducted by 2 independent reviewers using inclusion and exclusion criteria. To be included, studies had to explicitly state that KT approaches were used to share human health research results in Inuit communities in the Circumpolar North. Articles that evaluated or assessed KT approaches were thematically analysed to identify and characterize elements that contributed to KT success or challenges. RESULTS: From 680 unique records identified in the initial search, 39 met the inclusion criteria and were retained for analysis. Of these 39 articles, 17 evaluated the KT approach used; thematic analysis identified 3 themes within these 17 articles: the value of community stakeholders as active members in the research process; the importance of local context in tailoring KT strategies and messaging; and the challenges with varying and contradictory health messaging in KT. A crosscutting gap in the literature, however, included a lack of critical assessment of community involvement in research. The review also identified a gap in assessments of KT in the literature. Research primarily focused on whether KT methods reflected the local culture and needs of the community. Assessments rarely focused on whether KT had successfully elicited its intended action. CONCLUSIONS: This review synthesized a small but burgeoning area of research. Community engagement was important for successful KT; however, more discussion and discourse on the tensions, challenges and opportunities for improvement are necessary.
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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 | 0.109 | 0.382 |
| Meta-epidemiology (narrow) | 0.002 | 0.003 |
| Meta-epidemiology (broad) | 0.008 | 0.008 |
| Bibliometrics | 0.045 | 0.044 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.016 | 0.018 |
| Open science | 0.004 | 0.009 |
| Research integrity | 0.006 | 0.004 |
| Insufficient payload (model declined to judge) | 0.007 | 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".