Ergonomic visualization of personal health data
- Ergonomische Visualisierung persönlicher Gesundheitsdaten
Theis, Sabine Wilrun; Nitsch, Verena (Thesis advisor); Jochems, Nicole (Thesis advisor)
Aachen (2019, 2020)
Dissertation / PhD Thesis
Dissertation, Rheinisch-Westfälische Technische Hochschule Aachen, 2019
The present dissertation deals with the ergonomic design of data visualizations. Four empirical studies were carried out, and a practical design and application recommendations were derived. Each study addressed one of the following steps within the user-centered development process: context analysis, task analysis, and evaluation. The first study (1a) examined health information needs of older adults through a qualitative-quantitative mixed-method design. Information needs were considered as a context and prerequisite for the visualization of health data. Different needs were identified: some deal with health data as a coping strategy, while others avoid health data for fear of causing or exacerbating illness. Many older people are already collecting paper-based health information as a basis for sharing with healthcare professionals or making decisions about their own health. Results of the first study motivated the further age-differentiated consideration of the ergonomic visualization of health data. Study 1b additionally demonstrated the expected relationship between information needs and technology usage on the basis of a representative German survey. According to the survey, an increased need for information leads to an increased use of mobile information and communication technology among older people. Study two identified e-health tasks and data types relevant for older people and e-health experts and summarized them into an empirically built general task-data-taxonomy. Practitioners can use this taxonomy to investigate functional system requirements, while researchers can use it to select experimental tasks for evaluation studies. Overall, time-based, multivariate data and health monitoring were the most relevant task and data type. Building on previous studies, in study 3 the influence of pre-attentive graphical features on the performance and demands of young, old and very old people in dealing with data visualizations was investigated. With regard to the task execution time and the number of errors, no age effects could be detected. However, in general the number of participants' findings on data decreased with age. While the difference between young and old people was only marginal, the amount of data obtained by the very elderly decreased significantly by about half. Pre-attentive features in data visualizations can reduce the performance measured in task execution time and reduce the error rate and mental workload.