In this focus on collaboration we will look at the various ways researchers and academic writers work together. This is part of a series of posts based on SAGE Research Cases.
The selected cases are open access until the end of February, 2019. If the links have expired you can access them through with a 30-day free trial of the Cases platform, using your academic email address.
Sometimes we collaborate with site representatives or participants. In this case, the researchers discuss the ways they collaborated to analyze data. They show the step-by-step process they used with the Atlas.ti data analysis platform.
Riccardi, F.,Mizrahi, T., Garcia, M., Korazim-Kőrösy, Y., & Blumsack, A. (2017). Using Atlas.ti in qualitative research for analyzing inter-disciplinary community collaboration. SAGE Research Methods Cases.doi:10.4135/9781473995895
This case study describes the methodology used to analyze qualitative data accumulated from 50 professionals representing six different health and human service professions: social work, public health, nursing, community psychology, law, and medicine. They were brought together
for a day of simulated exercises and reflections to collaborate on a community health issue.
This case study describes the fundamentals of qualitative coding and analysis, including the integration of computer-aided ATLAS.ti qualitative analysis software. The program was used to code and analyze 21 transcribed group deliberations. This case study is a practical application
for Master’s level students, doctoral candidates, academics, and practitioners on the use of qualitative coding software and its relevance to social work and public health scholarship, exploring the intersections of inter-disciplinary collaboration in community health settings.
Learn more about collaboration on SAGE MethodSpace:
- Interview with Dr. Bagale Chilisa, Part 3
- Visual & Narrative Methods in Indigenous Research
- Intercultural Research: Interview with Rebecca Bayeck
- Q & A with Dr. Bagele Chilisa, Part 2
- Epistemological Questions in Indigenous Research