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Published on: February 16, 2011
The Use of Arts-Based Methods to Enhance Patient Engagement in Health Research
Emily K Phillips1, Anna M Chudyk2, Caroline Monnin3
1Applied Health Sciences, Faculty of Graduate Studies, University of Manitoba, Winnipeg, Manitoba, Canada.
Arts-based methods (ABM) enhance patient and care partner engagement in research (PER) by enabling deeper understanding and shifting power dynamics. Utilizing ABM can operationalize PER, eliciting aesthetic knowledge and strengthening inclusivity in healthcare research.
Area of Science:
- Health Services Research
- Qualitative Research Methods
- Patient and Public Involvement
Background:
- Patient and care partner engagement in research (PER) is crucial for advancing healthcare knowledge.
- Arts-based methods (ABM) offer unique ways to share complex, aesthetic knowledge beyond verbal communication.
- The synergy between PER and ABM, both participatory and collaborative, is underexplored.
Purpose of the Study:
- To identify and summarize the applications of arts-based methods (ABM) in patient and care partner engagement in research (PER).
- To explore the impacts of using ABM within PER initiatives.
- To understand how ABM can enhance the quality and inclusivity of PER.
Main Methods:
- A narrative review was conducted.
- Searches were performed across CINAHL, Scopus, and PubMed databases.
- Fifteen relevant articles were included in the synthesis.
Main Results:
- A diverse range of ABM were employed in PER studies.
- ABM were found to be decolonizing, empowering individuals with lived experience, and reducing tokenism.
- Participants shared aesthetic knowledge directly through art, fostering deeper emotional and relational understanding.
Conclusions:
- Researchers should leverage the participatory strengths of ABM to engage people with lived experience meaningfully.
- ABM can operationalize PER, facilitating the elicitation of aesthetic knowledge and promoting equitable power dynamics.
- Consideration of ABM is recommended for enhancing PER beyond traditional data collection.
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