The shape of health: A comparison of five alternative ways of visualizing personal health and wellbeing

Abstract

The combination of clinical and personal health and wellbeing data can tell us much about our behaviors, risks and overall status. The way this data is visualized may affect our understanding of our own health. To study this effect, we conducted a small experiment with 30 participants in which we presented a holistic overview of the health and wellbeing of two modeled individuals, one of them with metabolic syndrome. We used an insight-based methodology to assess the effectiveness of the visualizations. The results show that adequate visualization of holistic health data helps users without medical background to better understand the overall health situation and possible health risks related to lifestyles. Furthermore, we found that the application of insight-based methodology in the health and wellbeing domain remains unexplored and additional research and methodology development are needed.

Health figures: an open source JavaScript library for health data visualization

“…An innovative approach for health data visualization is the Health Graph (hGraph), released publicly by MITRE corporation [3]. In an earlier study [4], it was found that the hGraph-type radial plot can enhance deep understanding of health data and enable the user to create meaningful health insights based on the interrelationships between the measurements. However, the hGraph shows a static overview of a persons wellness.…”

“…Thus, in addition to a static snapshot such as in hGraph, a temporal way of presenting the data is also needed. While hGraph visualization is useful for the purpose of understanding with a quick glance the overall situation, it lacks features such as a clear division of measurements according to their category, a distribution of the labels to avoid clutter and the notion of time or evolution of the data [4].…”

“…We describe its main advantages and how they can address these challenges. In a previous study [4] we identified possible improvements and based on our own implementation we addressed these issues and extended the features of the hGraph to better address large data sources.…”

On the usefulness of map-based dashboards for decision making

“…The insight-based methodology has been used for applications of clinical data [29], health and well being [30], and bioinformatics [28], [31]. Common for these studies is their focus on open-ended protocol, quantitative insight analysis, and the domain knowledge relevance of the chosen participants [12].…”

“…This allowed further analysis and distinguishing between different types of insight. The characteristics used were based on the original work by North [12] and previous similar case studies [28], [30], [31].…”