Knowledge translation strategies designed for public health decision-making settings: a scoping review
Autor: | Mei Chung, Amy Lischko, Naisi Zhao, Susan Koch-Weser |
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Rok vydání: | 2020 |
Předmět: |
Health Knowledge
Attitudes Practice medicine.medical_specialty 030505 public health Health (social science) Knowledge management business.industry Process (engineering) Computer science Public health Decision Making Public Health Environmental and Occupational Health MEDLINE Translational Research Biomedical 03 medical and health sciences 0302 clinical medicine Knowledge translation medicine Humans Public Health 030212 general & internal medicine 0305 other medical science business Citation Public health policy |
Zdroj: | International Journal of Public Health. 65:1571-1580 |
ISSN: | 1661-8564 1661-8556 |
Popis: | To review and describe available Knowledge Translation (KT) strategies that are designed for or applied in public health decision-making settings. KT is the exchange, synthesis, and ethically sound application of knowledge. This review proposes that KT strategies in public health settings should be understood as action plans that promote evidence use and facilitate evidence-informed decision-making. This scoping review included studies that reported on KT strategies applied in public health settings, published between 2010 and 2017. Studies were searched using Medline, online KT database, and citation tracing. Data from 305 included studies were synthesized using a coding form and conceptually mapped to identify KT strategies used in public health settings. A total of 124 unique examples of KT methods or tools were identified and summarized into 38 recommended and promising KT strategies. Built on the lists of recommended strategies, this review synthesized a framework that matched all 38 KT strategies to 10 key components of the evidence-informed decision-making process. The public health KT strategies summarized and organized by this review promote a better understanding and more effective use of KT strategies. |
Databáze: | OpenAIRE |
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