Understanding users in small area cancer mapping : insights from the early stages of a user-centered design process

Cancer mapping is critical for understanding the spatial patterns of cancer burden, identifying disparities and informing targeted interventions. However, the limited availability of accessible, local-level cancer data and user-friendly mapping tools hinders both professional users, who need finer-scale data to analyze community-level cancer burden, and the general public, who need clear and intuitive visualizations to better understand their cancer risk. Cancer Analytics and Maps for Small Areas (CAMSA) is a visual analytics platform designed to address the diverse needs of end users, including the general public, public health professionals, and researchers, by visualizing small-area cancer data. This paper presents the early stages of CAMSA’s development following an iterative user-centered design (UCD) process. Through needs assessment interviews, usability evaluation focus groups and implementation capacity surveys, we identified five use cases: cancer burden exploration, health disparities identification, risk factor analysis, customized spatial and statistical analysis, and communication and collaboration. The alpha version of CAMSA was developed to fulfill core functional requirements to detect spatial patterns (e.g., clusters) of cancer burden across different stratification groups including race, sex and year. Usability evaluations, conducted through post-development focus groups, informed the extended functional requirements for the beta version to enhance its functionality. Findings from this iterative process underscore the importance of meeting the needs of the general public (providing comprehensible knowledge), and public health professionals and researchers (clarification of statistical uncertainty). This study showcases the effectiveness of user-centered design in ensuring the accessibility and practicality of CAMSA.