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Potentially Identifying Variables Reported in 100 Qualitative Health Research Articles: Implications for Data Sharing
Annie B Friedrich1, Jessica Mozersky2, James M DuBois2
1Medical College of Wisconsin, 8701 Watertown Plank Rd, Milwaukee, WI 53226, USA.
Forum, Qualitative Social Research
|May 25, 2026
Summary
Sharing qualitative health data is possible. Researchers can de-identify data by removing a few common variables, like profession and age, while keeping it useful for others.
Area of Science:
- Social Science Research
- Qualitative Health Studies
Background:
- Growing trend in social science research to share qualitative data.
- Researcher concerns about de-identifying qualitative data while maintaining contextual detail for secondary users.
Purpose of the Study:
- To inform discussions on qualitative data sharing.
- To determine potentially identifying variables (PIVs) reported in published qualitative health science studies.
Main Methods:
- Reviewed 100 qualitative health science studies.
- Identified and categorized potentially identifying variables (PIVs) reported in the literature.
Main Results:
- Most studies reported two or fewer PIVs (64% of studies).
- Commonly reported PIVs included profession, sex/gender, and age.
- Few PIVs are reported, suggesting de-identification is feasible.
Conclusions:
- Qualitative data can be shared while being de-identified and useful for secondary analysis.
- Commonly reported PIVs likely provide essential context for data interpretation.
- Masking study sites is recommended to reduce re-identification risk.
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