Usable Data Visualization for Digital Biomarkers: An Analysis of Usability, Data Sharing, and Clinician Contact

Abstract

<b><i>Background:</i></b> While digital phenotyping smartphone apps can collect vast amounts of information on participants, less is known about how these data can be shared back. Data visualization is critical to ensuring applications of digital signals and biomarkers are more informed, ethical, and impactful. But little is known about how sharing of these data, especially at different levels from raw data through proposed biomarkers, impacts patients’ perceptions. <b><i>Methods:</i></b> We compared five different graphs generated from data created by the open source mindLAMP app that reflected different ways to share data, from raw data through digital biomarkers and correlation matrices. All graphs were shown to 28 participants, and the graphs’ usability was measured via the System Usability Scale (SUS). Additionally, participants were asked about their comfort sharing different kinds of data, administered the Digital Working Alliance Inventory (D-WAI), and asked if they would want to use these visualizations with care providers. <b><i>Results:</i></b> Of the five graphs shown to participants, the graph visualizing change in survey responses over the course of a week received the highest usability score, with the graph showing multiple metrics changing over a week receiving the lowest usability score. Participants were significantly more likely to be willing to share Global Positioning System data after viewing the graphs, and 25 of 28 participants agreed that they would like to use these graphs to communicate with their clinician. <b><i>Discussion/Conclusions:</i></b> Data visualizations can help participants and patients understand digital biomarkers and increase trust in how they are created. As digital biomarkers become more complex, simple visualizations may fail to capture their multiple dimensions, and new interactive data visualizations may be necessary to help realize their full value.

Patient Experience of Digitalized Follow-up of Antidepressant Treatment in Psychiatric Outpatient Care: Qualitative Analysis

“…A primary finding of the analysis was the positive experience of the feature with visual time series plots, how it contributed to self-awareness, and how it contributed to patient-physician communications. This is consistent with previous research [ 35 , 36 ]. First, a systematic review of experiences concerning data visualization through digital apps among patients with chronic neurological and mental health conditions reported how visualization of collected data can increase self-awareness, develop communication and understanding with the health care provider, and increase the user’s adherence to a mobile app [ 36 ].…”

“…First, a systematic review of experiences concerning data visualization through digital apps among patients with chronic neurological and mental health conditions reported how visualization of collected data can increase self-awareness, develop communication and understanding with the health care provider, and increase the user’s adherence to a mobile app [ 36 ]. Furthermore, Scheuer and Torous [ 35 ] recently investigated patient perceptions on how useful digitally collected data concerning their mental illness can be if presented visually in various graphs. Simple graphs were reported as being more useful (eg, survey scores); however, by having access to graphs with more complex data, the participants perceived an increased comfort in sharing them with a health care provider.…”

Integrated Digital Mental Health Care: A Vision for Addressing Population Mental Health Needs

“… 38 Along the way, the identification of relevant digital biomarkers can support more robust population health management, identifying patients for whom outreach and proactive engagement may be warranted. 41 …”

Reverse Engineering of Digital Measures: Inviting Patients to the Conversation

“…Research into ethical and privacy matters related to digital health is expanding but still remains underexplored [94]. Engagement has also been a challenge across all digital measures in mental health to date [95], but when technology is created with patient feedback [96] and data are used to advance patient care, engagement can actually be quite high [97]. Overcoming these challenges and continuing research on digital measures in mental health, especially longitudinal studies, holds the potential to help understand mechanisms, individual-level behaviors, and finally move the field toward prevention [98, 99].…”