A descriptive qualitative examination of knowledge translation practice among health researchers in Manitoba, Canada
Bibliographic record
Abstract
BACKGROUND: The importance of effective translation of health research findings into action has been well recognized, but there is evidence to suggest that the practice of knowledge translation (KT) among health researchers is still evolving. Compared to research user stakeholders, researchers (knowledge producers) have been under-studied in this context. The goals of this study were to understand the experiences of health researchers in practicing KT in Manitoba, Canada, and identify their support needs to sustain and increase their participation in KT. METHODS: Qualitative semi-structured interviews were conducted with 26 researchers studying in biomedical; clinical; health systems and services; and social, cultural, environmental and population health research. Interview questions were open-ended and probed participants' understanding of KT, their experiences in practicing KT, barriers and facilitators to practicing KT, and their needs for KT practice support. RESULTS: KT was broadly conceptualized across participants. Participants described a range of KT practice experiences, most of which related to dissemination. Participants also expressed a number of negative emotions associated with the practice of KT. Many individual, logistical, and systemic or organizational barriers to practicing KT were identified, which included a lack of institutional support for KT in both academic and non-academic systems. Participants described the presence of good relationships with stakeholders as a critical facilitator for practicing KT. The most commonly identified needs for supporting KT practice were access to education and training, and access to resources to increase awareness and promotion of KT. While there were few major variations in response trends across most areas of health research, the responses of biomedical researchers suggested a unique KT context, reflected by distinct conceptualizations of KT (such as commercialization as a core component), experiences (including frustration and lack of support), and barriers to practicing KT (for example, intellectual property concerns). CONCLUSIONS: The major findings of this study were the continued variations in conceptualization of KT, and persisting support needs that span basic individual to comprehensive systemic change. Expanding the study to additional regions of Canada will present opportunities to compare and contrast the state of KT practice and its influencing factors.
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How this classification was reachedexpand
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 | 0.081 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.000 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".