Open AccessUse of Ecomaps in Qualitative Health Research
Author(s) -
Veena Manja,
Ananya Nrusimha,
Harriet L. MacMillan,
Lisa Schwartz,
Susan M. Jack
Publication year - 2021
Publication title -
the qualitative report
Language(s) - English
Resource type - Journals
ISSN - 2160-3715
DOI - 10.46743/2160-3715/2021.4565
Subject(s) - qualitative research , credibility , confidentiality , photo elicitation , qualitative property , psychology , triangulation , health care , computer science , data science , applied psychology , medical education , knowledge management , medicine , sociology , social science , computer security , cartography , machine learning , economic growth , political science , law , economics , geography
Qualitative health research plays a central role in exploring individuals’ experiences and perceptions of wellness, illness, and healthcare services. Visual tools are increasingly used for data elicitation. An ecomap is a visual tool that applies ecosystems theory to human communities and relationships to provide an illustration of the quality of relationships. We describe the use of ecomaps in qualitative health research. Searches across eight databases identified 407 citations. We screened them in duplicate to identify 129 publications that underwent full text review and included 73 in the final synthesis. We classified and summarized data based on iterative comparisons across sources. Benefits of using ecomaps include improving rapport and engagement with study participants, facilitating iterative question development, and highlighting the social contexts of relationships. When used in conjunction with interviews, they promote data credibility through triangulation. Investigators have used ecomaps as a tool to facilitate primary and secondary analysis of data. Researchers have adapted the ecomap to meet their health research needs. Challenges to their use include additional time and training needed to complete, and potential privacy and confidentiality concerns. Ecomaps can be useful in qualitative health research to enhance data elicitation, analysis, presentation, and to augment study rigor.