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Mestre, D., Pires, R., Gonçalves, B., Henriques-Calado, J., Alves, T. & Gama, S. (2026). Exploring the relationship between personality, sociodemographic factors, and mental health: A design study. Information Visualization. N/A

D. Mestre et al.,  "Exploring the relationship between personality, sociodemographic factors, and mental health: A design study", in Information Visualization, vol. N/A, 2026

@article{mestre2026_1780724008468,
	author = "Mestre, D. and Pires, R. and Gonçalves, B. and Henriques-Calado, J. and Alves, T. and Gama, S.",
	title = "Exploring the relationship between personality, sociodemographic factors, and mental health: A design study",
	journal = "Information Visualization",
	year = "2026",
	volume = "N/A",
	number = "",
	doi = "10.1177/14738716261449157",
	url = "https://journals.sagepub.com/home/IVI"
}

TY  - JOUR
TI  - Exploring the relationship between personality, sociodemographic factors, and mental health: A design study
T2  - Information Visualization
VL  - N/A
AU  - Mestre, D.
AU  - Pires, R.
AU  - Gonçalves, B.
AU  - Henriques-Calado, J.
AU  - Alves, T.
AU  - Gama, S.
PY  - 2026
SN  - 1473-8716
DO  - 10.1177/14738716261449157
UR  - https://journals.sagepub.com/home/IVI
AB  - 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.
ER  -