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

Research output: Contribution to journal › Review article › peer-review

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

Original languageEnglish
Article numbere25249
JournalJMIR Mental Health
Volume9
Issue number4
DOIs
PublishedApr 2022
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Bibliographical note

Funding Information: This review was conducted as part of the Remote Assessment of Disease and Relapse-Central Nervous System (RADAR-CNS) research program. The RADAR-CNS project has received funding from the Innovative Medicines Initiative 2 Joint Undertaking under grant agreement 115902 [75]. This joint undertaking receives support from the European Union's Horizon 2020 research and innovation program and European Federation of Pharmaceutical Industries and Associations (EFPIA). This communication reflects the views of the RADAR-CNS consortium, and neither Innovative Medicines Initiative nor the European Union and EFPIA are liable for any use that may be made of the information contained herein. This paper represents independent research part funded by the National Institute for Health Research (NIHR) Biomedical Research Centre at South London and Maudsley National Health Service (NHS) Foundation Trust and King's College London. The views expressed are those of the authors and not necessarily those of the NHS, the NIHR, or the Department of Health and Social Care. TW is a National Institute of Health Research senior investigator. Funding Information: This review was conducted as part of the Remote Assessment of Disease and Relapse-Central Nervous System (RADAR-CNS) research program. The RADAR-CNS project has received funding from the Innovative Medicines Initiative 2 Joint Undertaking under grant agreement 115902 [75]. This joint undertaking receives support from the European Union’s Horizon 2020 research and innovation program and European Federation of Pharmaceutical Industries and Associations (EFPIA). This communication reflects the views of the RADAR-CNS consortium, and neither Innovative Medicines Initiative nor the European Union and EFPIA are liable for any use that may be made of the information contained herein. This paper represents independent research part funded by the National Institute for Health Research (NIHR) Biomedical Research Centre at South London and Maudsley National Health Service (NHS) Foundation Trust and King’s College London. The views expressed are those of the authors and not necessarily those of the NHS, the NIHR, or the Department of Health and Social Care. TW is a National Institute of Health Research senior investigator. Publisher Copyright: © Ashley Polhemus, Jan Novak, Shazmin Majid, Sara Simblett, Daniel Morris, Stuart Bruce, Patrick Burke, Marissa F Dockendorf, Gergely Temesi, Til Wykes.

King's Authors

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.

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