Which knowledge synthesis method can be used to answer research questions of complex evidence?

Article type
Authors
Kastner M1, Tricco A2, Straus S3, Anthony J4, Soobiabh C4
1St. Michael's Hospital Li Ka Shing Knowledge Institute; University of Toronto
2Li Ka Shing Knowledge Institute, St. Michael's Hospital
3St. Michael's Hospital
4Li Ka Shing Knowledge Institute of St. Michael's Hospital, Canada
Abstract
Objectives: To describe the findings of a scoping review of knowledge synthesis (KS) methods, and to pilot test a conceptual algorithm aimed at helping reviewers optimize the selection of a KS method to answer a particular research question.
Description: The workshop will consist of three parts.
Part 1 (20 minutes): A presentation describing our scoping review methodology, analysis and findings (including how we selected 409 studies for inclusion, and how we compared and contrasted our 25 identified unique KS methods, their similarities/differences, strengths/limitations).
Part 2 (10 minutes): A presentation of a conceptual algorithm (informed by scoping review findings) for use by reviewers to optimize their selection of an appropriate KS method to answer a research question followed by a short discussion.
Part 3 (60 minutes): In the first 30 minutes of the session, participants will be divided into small groups and given a handout with the conceptual algorithm, as well as a list of research questions of complex evidence. They will be asked to use the conceptual algorithm to decide which KS method might be the most appropriate to address each question and why. Participants will also have the opportunity to evaluate the conceptual algorithm with a short questionnaire (part of handout). In the last 15 minutes of the session, we will invite the larger group to discuss their experience with using the conceptual algorithm and to provide suggestions for its improvement