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Identifying candidate quality indicators of tools that support the practice of knowledge translation: a scoping

Aunima R Bhuiya¹, Julie Makarski², Leigh Hayden³

¹Dalla Lana School of Public Health, Institute of Health Policy, Management, and Evaluation (IHPME), University of Toronto, Toronto, ON, Canada.

JBI Evidence Synthesis

|September 16, 2022

Abstract

Objective:

The objective of this scoping review is to identify and characterize relevant knowledge translation methods tools (those that provide guidance for optimized knowledge translation practice) to uncover candidate quality indicators to inform a future quality assessment tool for knowledge translation strategies.

Introduction:

Knowledge translation strategies (defined as including knowledge translation interventions, tools, and products) target various knowledge users, including patients, clinicians, researchers, and policy-makers. The development and use of strategies that support knowledge translation practice have been rapidly increasing, making it difficult for knowledge users to decide which to use. There is limited evidence-based guidance or measures to help assess the overall quality of knowledge translation strategies.

Inclusion Criteria:

Empirical and non-empirical documents will be considered if they explicitly describe a knowledge translation methods tool and its development, evaluation or validation, methodological strengths or limitations, and/or use over time. The review will consider a knowledge translation methods tool if it falls within at least one knowledge translation domain (ie, implementation, dissemination, sustainability, scalability, integrated knowledge translation) in the health field.

Methods:

We will conduct a systematic search of relevant electronic databases and gray literature. The search strategy will be developed iteratively by an experienced medical information specialist and peer-reviewed with the PRESS checklist. The search will be limited to English-only documents published from 2005 onward. Documents will be independently screened, selected, and extracted by 2 researchers. Data will be analyzed and summarized descriptively, including the characteristics of the included documents, knowledge translation methods tools, and candidate quality indicators.

Scoping Review Registration:

Open Science Framework ( https://osf.io/chxvq ).

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