A Systematic Review on Visualizations for Self-Generated Health Data for Daily Activities

Abstract

Due to the development of sensing technology people can easily track their health in various ways, and the interest in personal healthcare data is increasing. Individuals are interested in controlling their wellness, which requires self-awareness and an understanding of various health conditions. Self-generated health data are easily accessed through mobile devices, and data visualization is commonly used in applications. A systematic literature review was conducted to better understand the role of visualizations and learn how to develop effective ones. Thirteen papers were analyzed for types of data, characteristics of visualizations, and effectiveness for healthcare management. The papers were selected because they represented research on personal health data and visualization in a non-clinical setting, and included health data tracked in everyday life. This paper suggests six levels for categorizing the efficacy of visualizations that take into account cognitive and physical changes in users. Recommendations for future work on conducting evaluations are also identified. This work provides a foundation for personal healthcare data as more applications are developed for mobile and wearable devices.

Patient and Clinician Experiences with Sharing Data Visualizations Integrated into Mental Health Treatment

“…Beyond the sheer size of the data, the temporal and personal/sensitive nature of the data present novel considerations. In a prior study, our team found that effective data visualizations can increase patients' understanding of digital biomarkers (e.g., sleep, step count) and help patients feel more comfortable sharing these biomarker data with care teams (Kim 2022). This demonstrates the utility of visualizations for increasing patient comfort with data sharing.…”

“…The current literature already supports the fact that data visualizations have the potential to increase engagement and effectively communicate underlying trends in patient data (van Os et al 2017;Polhemus et al 2022). Recent studies on visualizations of personal healthcare data indicate that visuals can help patients transition from low to high health literacy, increase communication between patients and healthcare providers, facilitate more informed healthcare decisions, and enable quicker data comprehension (Brewer et al 2012;Kim 2022). Additionally, effective visuals may enhance users' trust and willingness to share their smartphone data, as they are provided a transparent view of how this information is being utilized and integrated into their care (Scheuer and Torous 2022).…”

Effectiveness of genetic feedback on alcohol metabolism to reduce alcohol consumption in young adults: an open-label randomized controlled trial

“…A recent umbrella review concluded that cognitive behavioral therapy (CBT) and motivational interviewing (MI) show effectiveness in the relative long-term (more than 6 months) reduction of alcohol consumption [ 31 ]. Both CBT and MI are usually conducted over multiple sessions [ 32 , 33 ]; reports of some cases indicate that more sessions induce a greater reduction in alcohol consumption than a single session [ 34 ]. Because the SBI was implemented only once in this study, future studies should investigate the effectiveness of multiple educational campaigns conducted on a periodic schedule (e.g., once every 3–6 months) to sustain the effectiveness of the SBI.…”

“…The participants in the control group were asked to read and study the same traditional educational materials for university students as the intervention group. Generally, visualizing personal health data motivates users to increase or maintain their activities [ 34 ]. In addition, the Hawthorne effect on alcohol-use behavior may have occurred in this study [ 35 ].…”