Knowledge translation: a case study in a public health network in Manguinhos, Brazil
Bibliographic record
Abstract
Abstract Background This paper presents a post hoc analysis of knowledge translation (KT) actions and strategies implemented by three projects in a sociotechnical network, in Rio de Janeiro, Brazil. In order to assess the actions and practices of knowledge producers (mostly researchers) and knowledge users (residents of Manguinhos) we applied the KT model developed by the Québec Public Health Institute. Methods This case study relied mainly on document analysis (texts produced by the network coordination, meeting minutes and reports, management reports and promotional material), interviews with knowledge producers (N = 10), and focus group with knowledge users (4 participants). Framework analysis was applied to provide clear steps to follow and structured outputs of summarized data. A content analysis of this material used categories such as: project development; KT products elaboration; and interaction between knowledge producers and users. Data were coded based on the KT model to understand whether and how the eight dimensions were implemented. Results The findings reveal that, albeit there were differences among the three cases, the KT dimensions related to the co-construction of knowledge, what to be translated, and how to translate were more extensively implemented. Even though KT was a new concept for most knowledge producers, all three cases had previous practical experience on how to disseminate knowledge in the Territory of Manguinhos. However, dimensions related to KT evaluation and resources were less frequently implemented. Conclusions More attention must be paid to the dimensions involving the feasibility, resources and evaluation of projects. Creating research organizations working together in the KT process with support, infrastructure, theoretical and methodological competences about KT may facilitate the integration of these dimensions. Key messages Through our study, we provide more evidence and progress about how the KT process can be improved in low- and middle-income countries, such as Brazil. We display an overview of the challenges that public health researchers in Brazil have in applying KT strategies to improve the public health care.
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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 | 0.007 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.007 | 0.004 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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".