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Denzin’s Paradigm Shift: Revisiting Triangulation in Qualitative Research
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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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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
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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