Data Visualization for Chronic Neurological and Mental Health Condition Self-management: Systematic Review of User Perspectives

Ashley Polhemus; Jan Novak; Shazmin Majid; Sara Simblett; Daniel Morris; Stuart Bruce; Patrick Burke; Marissa F Dockendorf; Gergely Temesi; Til Wykes

doi:10.2196/25249

Data Visualization for Chronic Neurological and Mental Health Condition Self-management: Systematic Review of User Perspectives

JMIR Ment Health. 2022 Apr 28;9(4):e25249. doi: 10.2196/25249.

Authors

Ashley Polhemus^{1

2}, Jan Novak³, Shazmin Majid^{3

4}, Sara Simblett⁵, Daniel Morris⁵, Stuart Bruce⁶, Patrick Burke⁶, Marissa F Dockendorf⁷, Gergely Temesi⁸, Til Wykes^{5

9}

Affiliations

¹ Merck Research Labs, Information Technology, Merck, Sharpe, & Dohme, Zurich, Switzerland.
² Epidemiology, Biostatistics and Prevention Institute, University of Zürich, Zürich, Switzerland.
³ Merck Research Labs, Information Technology, Merck, Sharpe, & Dohme, Prague, Czech Republic.
⁴ School of Computer Science, University of Nottingham, Nottingham, United Kingdom.
⁵ Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, United Kingdom.
⁶ RADAR-CNS Patient Advisory Board, London, United Kingdom.
⁷ Global Digital Analytics and Technologies, Merck, Sharpe, & Dohme, Kenilworth, NJ, United States.
⁸ Merck Research Labs, Information Technology, Merck, Sharpe, & Dohme, Vienna, Austria.
⁹ National Institute for Health Research, Maudsley Biomedical Research Centre, South London and Maudsley National Health Services Foundation Trust, London, United Kingdom.

PMID: 35482368
PMCID: PMC9100378
DOI: 10.2196/25249

Abstract

Background: Remote measurement technologies (RMT) such as mobile health devices and apps are increasingly used by those living with chronic neurological and mental health conditions. RMT enables real-world data collection and regular feedback, providing users with insights about their own conditions. Data visualizations are an integral part of RMT, although little is known about visualization design preferences from the perspectives of those living with chronic conditions.

Objective: The aim of this review was to explore the experiences and preferences of individuals with chronic neurological and mental health conditions on data visualizations derived from RMT to manage health.

Methods: In this systematic review, we searched peer-reviewed literature and conference proceedings (PubMed, IEEE Xplore, EMBASE, Web of Science, Association for Computing Machinery Computer-Human Interface proceedings, and the Cochrane Library) for original papers published between January 2007 and September 2021 that reported perspectives on data visualization of people living with chronic neurological and mental health conditions. Two reviewers independently screened each abstract and full-text article, with disagreements resolved through discussion. Studies were critically appraised, and extracted data underwent thematic synthesis.

Results: We identified 35 eligible publications from 31 studies representing 12 conditions. Coded data coalesced into 3 themes: desire for data visualization, impact of visualizations on condition management, and visualization design considerations. Data visualizations were viewed as an integral part of users' experiences with RMT, impacting satisfaction and engagement. However, user preferences were diverse and often conflicting both between and within conditions.

Conclusions: When used effectively, data visualizations are valuable, engaging components of RMT. They can provide structure and insight, allowing individuals to manage their own health more effectively. However, visualizations are not "one-size-fits-all," and it is important to engage with potential users during visualization design to understand when, how, and with whom the visualizations will be used to manage health.

Keywords: data visualization; digital health; mental health; neurology; remote measurement technology; user-centered design.

©Ashley Polhemus, Jan Novak, Shazmin Majid, Sara Simblett, Daniel Morris, Stuart Bruce, Patrick Burke, Marissa F Dockendorf, Gergely Temesi, Til Wykes. Originally published in JMIR Mental Health (https://mental.jmir.org), 28.04.2022.

Publication types

Review