Two-Eyed Seeing Application in Research Analysis: An Integrative Review

Abstract

Background Research approaches used to understand Indigenous people in Canada have predominately used Western approaches and have not reflected Indigenous ways of knowing, protocols, or worldviews. The landscape of research involving Indigenous people is changing with a growing number of Indigenous scholars reclaiming and revitalizing Indigenous knowledge. Two-Eyed Seeing provides a framework whereby conscious and deliberate conversations and research approaches are determined prior to and throughout the research process by the research team to guide a balance of each knowledge. However, Two-Eyed Seeing approaches or methods used during data analysis within the literature remains sparse necessitating this integrative review. Purpose To review the literature where Two-Eyed Seeing has been applied and to identify the approaches or methods used during data analysis and discuss the implications for research with Indigenous communities worldwide. Methods The five-stage approach outlined by Whittemore and Knafl (2005) was used to guide this integrative review. Results A total of 321 articles were reviewed from four databases, yielding 32 articles. Conclusions This integrative review is novel in that it is the first review known to specifically explore the use and application of a Two-Eyed Seeing framework during data analysis. Five main themes are presented including (1) Indigenous community member involvement with analysis, (2) Co-Learning during data analysis, (3) Visual or symbolic conceptualizations to guide analysis, (4) Statement acknowledging Indigenous knowledge during data analysis, and (5) Sharing of Traditional stories to guide data analysis. Additionally, five Two-Eyed Seeing approaches less commonly used during data analysis are provided.