Mental health research increasingly considers individual differences such as personality traits and sociodemographic factors, yet existing analytical practices rely largely on statistical software, which limits exploratory analysis and hypothesis generation. From a visualization perspective, there is a lack of domain-informed design studies that investigate how interactive visual analytics can support the joint exploration of these factors. We present a visualization design study conducted in close collaboration with personality psychology experts, aimed at supporting exploratory analysis of relationships between sociodemographic, personality, and mental health data. Through an iterative co-creation process involving interviews, design workshops, and prototyping, we designed FFM-MHI Vis, an interactive visualization system integrating coordinated views such as parallel coordinates, boxplots, scatterplots, and Sankey diagrams. The system was evaluated with domain experts through a task-based study comprising six analytical tasks. Results show high perceived usability (84.92 ± 1.94), perceived usefulness (91.42 ± 1.65%), and ease of use (87.14 ± 1.67%). We contribute with reflections and lessons learned from the design process, demonstrating how visualization can effectively support exploratory analysis and hypothesis generation in personality and mental health research.

This work was supported by national funds through Fundação para a Ciência e a Tecnologia (FCT) with references SFRH/BD/14479, UID/50009/2025, UID/50021/2025, UID/PRR/50021/2025, and UIDB/315/2025.

Design study,Psychology,Personality,Five-factor model,Mental health,Sociodemographic factors

• Computer and Information Sciences - Natural Sciences
• Electrical Engineering, Electronic Engineering, Information Engineering - Engineering and Technology
• Psychology - Social Sciences