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Review
. 2025 Jul;34(7):2031-2048.
doi: 10.1007/s11136-025-03964-5. Epub 2025 Apr 25.

Understanding data visualization techniques in qualitative studies used to develop and validate patient-reported outcome measures: a targeted literature review

Caroline Seo #  1 , Sophia Hu #  2 , Bellinda L King-Kallimanis  3 , Ashley E Chang  4 , Antoine Regnault  5 , Amitai S Miller  2 , Manraj N Kaur  2   6
Affiliations
Review

Understanding data visualization techniques in qualitative studies used to develop and validate patient-reported outcome measures: a targeted literature review

Caroline Seo et al. Qual Life Res. 2025 Jul.

Abstract

Purpose: Qualitative data that reflects patients' experiences are the foundation of any patient-reported outcome measure (PROM) development and validation study; however, there is limited understanding of the type of data visualization techniques that facilitate communication of this data. The goal of this targeted literature review was to investigate data visualization methods that have been used in published PROM development and validation literature to report qualitative results.

Methods: A literature search in OVID via MEDLINE was conducted among the top 10 non-disease-specific journals publishing PROM qualitative development and validation studies. Studies that reported qualitative methods to develop/validate a PROM and included data visualization in the form of tables or figures were included. Article characteristics and data visualization types were extracted.

Results: A total of 185 articles were included in data extraction. Most articles (n = 109, 59.1%) included figures (n = 172, average 2 relevant figures per article) in the form of hierarchy/flowcharts (n = 124, 72.1%) and bar charts (n = 29, 16.9%). Information reported in figures included depiction of conceptual frameworks (n = 112, 65.1%) and concept frequency (n = 40, 24.4%). Most articles (n = 152, 81.7%) included tables (n = 307, average 2 relevant tables per article). Information reported in tables included concept frequency (n = 133, 43.3%) and cognitive debriefing and revisions (n = 91, 29.6%).

Conclusion: Data visualization techniques used to report qualitative results in the identified PROM qualitative development and validation studies were heterogeneous, and many studies did not utilize any data visualization techniques. This study will inform the development of guidance for using data visualizations to report qualitative PROM research.

Keywords: Data visualization; Development; Patient-reported outcome; Qualitative; Validation.

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Conflict of interest statement

Declarations. Conflicts of interest: Ms. Caroline Seo is a full time employee at AstraZeneca, Dr. King-Kallimanis reports receiving grant support directly paid to their institution and not related to the project from the following: AstraZeneca, Boehringer Ingelheim, Bristol Myers Squibb, Jazz Pharma, Genentech, Eli Lilly, Janssen, Takeda, Daiichi Sankyo, Blueprint Medicines, Janssen, Amgen, Seagen, and Manta Cares. Dr. King-Kallimanis report receiving consulting fees from Eli Lilly, Bristol Myers Squibb, AbbVie, Adelphi Values and Shionogi. The remaining authors have no conflict of interest to disclose.

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