Knowledge translation in health and wellness research focusing on immigrants in Canada
Bibliographic record
Abstract
INTRODUCTION Knowledge translation (KT) is a relatively new concept referring to transfers of knowledge into practice in collaboration with multiple sectors that work for the health and wellness of society. Knowledge translation is crucial to identifying and addressing the health needs of immigrants. AIM To scope the evidence on KT research engaging immigrants in the host country regarding the health and wellness of immigrants. METHODS This study followed a scoping review approach suggested by Arksey O'Malley. We identified relevant studies from both academic and grey literature using structured criteria, charted the data from the selected studies, collated, summarised and report the results. RESULTS Analysis of the eligible studies found two types of KT research: integrated KT and end-of-grant KT. Meeting or discussion with community-level knowledge-users were common KT activities among immigrants, but they were involved in the entire research process only if they were hired as members of research teams. Most KT research among immigrants explored cancer screening and used a community-based participatory action research approach. Barriers and enablers usually came from researchers rather than from the community. There was little practice of evaluation and defined frameworks to conduct KT research among immigrants in Canada. CONCLUSION This study can help the researchers and other stakeholders of health and wellness of the immigrant population to identify appropriate KT research activities for immigrants and where KT research is required to facilitate the transfer of research knowledge into action.
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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 | 0.018 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.005 |
| 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".