Data-Driven Personas Enhance Public Health Information System Design
Category: User-Centred Design · Effect: Strong effect · Year: 2026
Developing data-driven personas using mixed methods, combining quantitative clustering with qualitative insights from statewide surveys, leads to more realistic and actionable user representations for public health information system design.
Design Takeaway
Integrate quantitative segmentation techniques with qualitative data analysis to build rich, data-backed personas that accurately represent diverse user groups for more effective design outcomes.
Why It Matters
This approach moves beyond generic user profiles to create personas that accurately reflect the diverse needs, technological capabilities, and attitudes of a target population. This grounding in real data ensures that design decisions for public health systems are user-centric, leading to more effective and widely adopted tools.
Key Finding
By combining statistical grouping with in-depth qualitative analysis of survey data, researchers were able to create 13 distinct personas that represent a wide range of user characteristics relevant to public health information systems.
Key Findings
- K-prototype clustering identified 5 distinct user segments.
- These segments were further developed into 13 detailed personas, reflecting variations in demographics, technological readiness, and attitudes towards public health policies.
- Personas were enriched with qualitative quotes to provide deeper context and realism.
Research Evidence
Aim: To develop a novel, mixed methods approach for creating data-driven personas to inform the design of public health information systems.
Method: Mixed Methods (Quantitative Cluster Analysis and Qualitative Thematic Review)
Procedure: Two statewide surveys were analyzed. Cluster analysis (k-prototypes) was used on demographic, technological readiness, and opinion data to identify distinct user groups. Qualitative analysis of survey responses and extracted quotes further refined these clusters into detailed personas, each with a profile and representative quotes.
Sample Size: 1103 (initial survey), 143 (subset survey)
Context: Public health informatics, information system design
Design Principle
User representations should be grounded in empirical data to ensure relevance and effectiveness in design.
How to Apply
When designing information systems for large or diverse populations, utilize existing large-scale survey data. Employ cluster analysis to identify key user segments and then use qualitative data (e.g., open-ended responses, interview transcripts) to flesh out these segments into detailed, actionable personas.
Limitations
The personas are specific to the population and context of Washington State; generalizability to other regions may require adaptation. The qualitative data is derived from survey responses, which may not capture the full depth of user experience.
Student Guide (IB Design Technology)
Simple Explanation: This study shows how to create realistic 'user profiles' (personas) for designing health websites or apps by using survey data. They used math to group people and then looked at what people said to make these profiles very detailed and useful.
Why This Matters: Creating accurate personas helps you understand who you are designing for, making sure your final design meets their actual needs and is easy for them to use.
Critical Thinking: How might the choice of statistical analysis (e.g., k-prototypes vs. k-means) impact the resulting user segments and subsequent personas?
IA-Ready Paragraph: To ensure the developed design solution effectively addresses user needs, a data-driven approach to persona development was employed, drawing inspiration from methodologies like that of Garcia et al. (2026). This involved utilizing quantitative data analysis to identify distinct user segments, followed by qualitative insights to enrich these segments into detailed, actionable personas that reflect the target audience's characteristics and behaviors.
Project Tips
- Consider using existing datasets if available for your design project to build data-driven personas.
- Think about how to combine different types of data (e.g., survey results, interview notes) to create richer user profiles.
How to Use in IA
- Reference this study when explaining your methodology for developing user personas, particularly if you are using quantitative data to inform qualitative insights.
Examiner Tips
- Demonstrate how your persona development is directly linked to user research and data, rather than being purely speculative.
Independent Variable: ["Demographics","Technological readiness","Opinions about public health policies","Experience using online health tools"]
Dependent Variable: ["Persona characteristics","User segments"]
Controlled Variables: ["Statewide survey data","Mixed methods approach"]
Strengths
- Utilizes real-world, large-scale survey data.
- Employs a rigorous mixed-methods approach for robust persona development.
- Provides actionable personas for design applications.
Critical Questions
- To what extent do the identified personas represent the entire population, or are they skewed by the survey sample?
- How can the qualitative data be further analyzed to uncover deeper user motivations and pain points?
Extended Essay Application
- This research can inform an Extended Essay investigating the effectiveness of different persona development methodologies in specific design contexts, or exploring how data-driven personas influence the iterative design process.
Source
Persona Development in Washington State: Mixed Methods Approach Using Statewide Survey Data · Online Journal of Public Health Informatics · 2026 · 10.2196/75422