Experiences of health tracking in mobile apps for multiple sclerosis: A qualitative content analysis of user reviews

Ashley Polhemus; Sara Simblett; Erin Dawe Lane; Benjamin Elliott; Sagar Jilka; Esther Negbenose; Patrick Burke; Janice Weyer; Jan Novak; Marissa F Dockendorf; Gergely Temesi; Til Wykes; RADAR-CNS

doi:10.1016/j.msard.2022.104435

Experiences of health tracking in mobile apps for multiple sclerosis: A qualitative content analysis of user reviews

Mult Scler Relat Disord. 2023 Jan:69:104435. doi: 10.1016/j.msard.2022.104435. Epub 2022 Nov 28.

Authors

Affiliations

¹ Merck Research Labs Information Technology, Merck Sharp, & Dohme, Kenilworth, NJ, USA; Epidemiology Biostatistics and Prevention Institute, University of Zürich, Zürich, Switzerland. Electronic address: ashley.polhemus1@msd.com.
² Institute of Psychiatry, King's College London, London, UK.
³ RADAR-CNS Patient Advisory Board, King's College London, London, UK.
⁴ Merck Research Labs Information Technology, Merck Sharp, & Dohme, Kenilworth, NJ, USA.
⁵ Institute of Psychiatry, King's College London, London, UK; South London and Maudsley NHS Foundation Trust, London, UK.
⁶ The RADAR-CNS Consortium (www.radar-cns.org).

PMID: 36493561
DOI: 10.1016/j.msard.2022.104435

Abstract

Background: Mobile health applications (apps) are promising condition self-management tools for people living with multiple sclerosis (MS). However, most existing apps do not include health tracking features. This gap has been raised as a priority research topic, but the development of new self-management apps will require designers to understand the context and needs of those living with MS. Our aim was to conduct a content analysis of publicly available user reviews of existing MS self-management apps to understand desired features and guide the design of future apps.

Methods: We systematically reviewed MS self-management apps which were publicly available in English on the Google Play and iOS app stores. We then conducted sentiment and content analysis of recent user reviews which referenced health tracking and data visualization to understand self-reported experiences and feedback.

Results: Searches identified 75 unique apps, of which six met eligibility criteria and had reviews. One hundred and thirty-seven user reviews of these apps were eligible, though most were associated with a single app (n=108). Overall, ratings and sentiment scores skewed highly positive (Median [IQR]: Ratings - 5 [4-5], Sentiment scores - 0.70 [0.44-0.86]), though scores of individual apps varied. Content analysis revealed five themes: reasons for app usage, simple user experience, customization and flexibility, feature requests, and technical issues. Reviewers suggested that app customization, interconnectivity, and consolidated access to desired features should be considered in the design of future apps. User ratings weakly correlated with review sentiment scores (ρ = 0.27 [0.11-0.42]).

Conclusions: Self-tracking options in MS apps are currently limited, though the apps that offer these functions are considered useful by individuals with MS. Additional qualitative research is required to understand how specific app features and opportunities for personalization should be incorporated into new self-management tools for this population.

Keywords: Data visualization; Digital health; Graphs; Multiple sclerosis; Self-management; mHealth.

Publication types

Systematic Review

MeSH terms

Humans
Mobile Applications*
Multiple Sclerosis* / therapy
Qualitative Research
Self-Management*
Telemedicine*