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Denzin’s Paradigm Shift: Revisiting Triangulation in Qualitative Research
Open accessAbstract
One approach to promote social change, mitigate bias, and enhance reaching data saturation is through triangulation: multiple sources of data. Triangulation adds depth to the data that are collected. In this scholarly essay, the authors discuss the continuing relevance of Denzin’s approach to triangulation of data. Included is a critique of researchers who have posited other approaches to triangulation that appear to be merely a renaming of Denzin’s original paradigm rather new outcomes. The intended audience is novice researchers and doctoral students who can benefit from clarity on some common misconceptions about triangulation.
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“The supplementary group was recruited to conduct triangulation and enhance the reliability of the research (Creswell, 2015;Fusch et al., 2018).”
From “Your Addiction, her Sexual Suffering”—A Qualitative Inquiry into the Effects of Compulsive Sexual Behaviors on Intimate Female Partners (2025) · cites this paper as Fusch et al., 2018
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“Engaging a cohort of supplementary research participants provided an avenue for triangulation and thus enhanced methodological rigour (Creswell, 2015;Fusch et al., 2018).”
From The Lived Experiences and Well-Being of Female Partners Following Discovery or Disclosure of Their Male Partner’s Compulsive Sexual Behaviours: An Australian Phenomenological Study (2025) · cites this paper as Fusch et al., 2018
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“Engaging this group of supplementary research participants provided an avenue for triangulation and thus enhanced methodological rigor (Creswell, 2015;Fusch et al., 2018).”
From “Your Addiction, her Sexual Suffering”—A Qualitative Inquiry into the Effects of Compulsive Sexual Behaviors on Intimate Female Partners (2025) · cites this paper as Fusch et al., 2018
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Cites
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Establishing trustworthiness and authenticity in qualitative pharmacy research
Amin, M. E. K., Nørgaard, L. S., Cavaco, A. M., Witry, M. J., Hillman, L., Cernasev, A., & Desselle, S. P. (2020) · Research in Social and Administrative Pharmacy · doi:10.1016/j.sapharm.2020.02.005 · Cited by 329
Algorithmic bias in machine learning-based marketing models
Akter, S., Dwivedi, Y. K., Sajib, S., Biswas, K., Bandara, R. J., & Michael, K. (2022) · Journal of Business Research · doi:10.1016/j.jbusres.2022.01.083 · Cited by 242
Akter, S., Bandara, R., Hani, U., Fosso Wamba, S., Foropon, C., & Papadopoulos, T. (2019) · International Journal of Information Management · doi:10.1016/j.ijinfomgt.2019.01.020 · Cited by 193
Factors influencing data saturation in qualitative studies
Mwita, K. (2022) · International Journal of Research in Business and Social Science (2147-4478) · doi:10.20525/ijrbs.v11i4.1776 · Cited by 348
Application of triangulation in qualitative research
Donkoh, S. (2023) · Journal of Applied Biotechnology & Bioengineering · doi:10.15406/jabb.2023.10.00319 · Cited by 170
Metadata
- Authors
- Fusch, P., Fusch, G. E., & Ness, L. R.
- Affiliations
- Walden University (US)
- Corresponding author
- Fusch, Patricia
- Venue
- Journal of Social Change
- Publisher
- Walden University
- Published
- 2018-01-01
- Volume
- 10
- Issue
- 1
- ISSN
- 1931-1540 (ISSN-L)
- OpenAlex
- W2785352827
- Cited by
- 551
- References
- 76
- Citations by year
- 2026: 67 · 2025: 82 · 2024: 103 · 2023: 92 · 2022: 73 · 2021: 69 · 2020: 57 · 2019: 6 · 2018: 1
- FWCI
- 107.83
- Type
- journal article
- Language
- en
- Open access
- diamond
- doi.org
- Locations
- Journal of Social Change (publishedVersion)
- ScholarWorks (Walden University) (submittedVersion)
- Topics
- Social Sciences › Education › Qualitative Research Methods and Applications
- Social Sciences › Education › Educational Research and Methods
- Social Sciences › Sociology and Political Science › Data Analysis and Archiving
- Keywords
- triangulation, qualitative research methodology, multi-source data, data saturation, researcher bias, paradigm shift, qualitative research design
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