TY - JOUR
T1 - Experiences of health tracking in mobile apps for multiple sclerosis
T2 - A qualitative content analysis of user reviews
AU - RADAR-CNS
AU - Polhemus, Ashley
AU - Simblett, Sara
AU - Dawe Lane, Erin
AU - Elliott, Benjamin
AU - Jilka, Sagar
AU - Negbenose, Esther
AU - Burke, Patrick
AU - Weyer, Janice
AU - Novak, Jan
AU - Dockendorf, Marissa F.
AU - Temesi, Gergely
AU - Wykes, Til
N1 - Funding Information:
This paper was written in support of the RADAR-CNS program, a collaborative research effort focusing on the development of RMT for monitoring central nervous system disease progression. We acknowledge all partners in the RADAR-CNS consortium (www.radar-cns.org) for their input and support of this work. The RADAR-CNS project has received funding from the Innovative Medicines Initiative 2 Joint Undertaking (www.imi.europa.eu) under grant agreement no. 115902. 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; www.imi.europa.eu). This communication reflects the views of the RADAR-CNS consortium and neither the 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 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 paper was written in support of the RADAR-CNS program, a collaborative research effort focusing on the development of RMT for monitoring central nervous system disease progression. We acknowledge all partners in the RADAR-CNS consortium ( www.radar-cns.org ) for their input and support of this work. The RADAR-CNS project has received funding from the Innovative Medicines Initiative 2 Joint Undertaking ( www.imi.europa.eu ) under grant agreement no. 115902 . 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; www.imi.europa.eu ). This communication reflects the views of the RADAR-CNS consortium and neither the 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 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:
© 2022
PY - 2023/1
Y1 - 2023/1
N2 - 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.
AB - 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.
KW - Data visualization
KW - Digital health
KW - Graphs
KW - mHealth
KW - Multiple sclerosis
KW - Self-management
UR - http://www.scopus.com/inward/record.url?scp=85144034630&partnerID=8YFLogxK
U2 - 10.1016/j.msard.2022.104435
DO - 10.1016/j.msard.2022.104435
M3 - Article
C2 - 36493561
AN - SCOPUS:85144034630
SN - 2211-0348
VL - 69
JO - Multiple Sclerosis and Related Disorders
JF - Multiple Sclerosis and Related Disorders
M1 - 104435
ER -