Supply and Demand in mHealth Apps for Persons With Multiple Sclerosis: Systematic Search in App Stores and Scoping Literature Review

Guido Giunti, Estefanía Guisado Fernández, Enrique Dorronzoro Zubiete, Octavio Rivera Romero, Guido Giunti, Estefanía Guisado Fernández, Enrique Dorronzoro Zubiete, Octavio Rivera Romero

Abstract

Background: Multiple sclerosis (MS) is a non-curable chronic inflammatory disease of the central nervous system that affects more than 2 million people worldwide. MS-related symptoms impact negatively on the quality of life of persons with MS, who need to be active in the management of their health. mHealth apps could support these patient groups by offering useful tools, providing reliable information, and monitoring symptoms. A previous study from this group identified needs, barriers, and facilitators for the use of mHealth solutions among persons with MS. It is unknown how commercially available health apps meet these needs.

Objective: The main objective of this review was to assess how the features present in MS apps meet the reported needs of persons with MS.

Methods: We followed a combination of scoping review methodology and systematic assessment of features and content of mHealth apps. A search strategy was defined for the two most popular app stores (Google Play and Apple App Store) to identify relevant apps. Reviewers independently conducted a screening process to filter apps according to the selection criteria. Interrater reliability was assessed through the Fleiss-Cohen coefficient (k=.885). Data from the included MS apps were extracted and explored according to classification criteria.

Results: An initial total of 581 potentially relevant apps was found. After removing duplicates and applying inclusion and exclusion criteria, 30 unique apps were included in the study. A similar number of apps was found in both stores. The majority of the apps dealt with disease management and disease and treatment information. Most apps were developed by small and medium-sized enterprises, followed by pharmaceutical companies. Patient education and personal data management were among the most frequently included features in these apps. Energy management and remote monitoring were often not present in MS apps. Very few contained gamification elements.

Conclusions: Currently available MS apps fail to meet the needs and demands of persons with MS. There is a need for health professionals, researchers, and industry partners to collaborate in the design of mHealth solutions for persons with MS to increase adoption and engagement.

Keywords: apps; chronic conditions; eHealth; fatigue; fatigue management; gamification; mHealth; multiple sclerosis; usability, physical activity; user-centered design.

Conflict of interest statement

Conflicts of Interest: None declared.

©Guido Giunti, Estefanía Guisado Fernández, Enrique Dorronzoro Zubiete, Octavio Rivera Romero. Originally published in JMIR Mhealth and Uhealth (http://mhealth.jmir.org), 23.05.2018.

Figures

Figure 1
Figure 1
Study flow.
Figure 2
Figure 2
Example of energy and resource management multiple sclerosis app.

References

    1. Kingwell E, Marriott JJ, Jetté N, Pringsheim T, Makhani N, Morrow SA, Fisk JD, Evans C, Béland SG, Kulaga S, Dykeman J, Wolfson C, Koch MW, Marrie RA. Incidence and prevalence of multiple sclerosis in Europe: a systematic review. BMC Neurol. 2013 Sep 26;13:128. doi: 10.1186/1471-2377-13-128.
    1. World Health Organization. Multiple Sclerosis International Federation 2008. Atlas multiple sclerosis resources in the world 2008 .
    1. Goldenberg MM. Multiple sclerosis review. P T. 2012 Mar;37(3):175–184.
    1. Trisolini M, Honeycutt A, Wiener J, Lesesne S. Multiple Sclerosis International Federation. London, UK: Multiple Sclerosis International Federation; 2010. May, Global Economic Impact of Multiple Sclerosis; pp. 1–104.
    1. Browne P, Chandraratna D, Angood C, Tremlett H, Baker C, Taylor BV, Thompson AJ. Atlas of Multiple Sclerosis 2013: A growing global problem with widespread inequity. Neurology. 2014 Sep 09;83(11):1022–1024. doi: 10.1212/WNL.0000000000000768.
    1. Trisolini M, Honeycutt A, Wiener J, Lesesne S. Multiple Sclerosis International Federation. London, United Kingdom: Multiple Sclerosis International Federation; 2010. Global Economic Impact of Multiple Sclerosis; pp. 1–104.
    1. Lorig K, Holman H. Self-management education: history, definition, outcomes, and mechanisms. Ann Behav Med. 2003 Aug;26(1):1–7. doi: 10.1207/S15324796ABM2601_01.
    1. Schulman-Green D, Jaser S, Martin F, Alonzo A, Grey M, McCorkle R, Redeker NS, Reynolds N, Whittemore R. Processes of self-management in chronic illness. J Nurs Scholarsh. 2012 Jun;44(2):136–144. doi: 10.1111/j.1547-5069.2012.01444.x.
    1. Mirkovic J, Kristjansdottir O, Stenberg U, Krogseth T, Stange K, Ruland C. Patient Insights Into the Design of Technology to Support a Strengths-Based Approach to Health Care. JMIR Res Protoc. 2016 Aug 24;5(3):e175. doi: 10.2196/resprot.5906.
    1. Whittaker R. Issues in mHealth: findings from key informant interviews. J Med Internet Res. 2012 Oct 02;14(5):e129. doi: 10.2196/jmir.1989.
    1. Irace C, Schweitzer MA, Tripolino C, Scavelli FB, Gnasso A. Diabetes Data Management System to Improve Glycemic Control in People With Type 1 Diabetes: Prospective Cohort Study. JMIR Mhealth Uhealth. 2017 Nov 21;5(11):e170. doi: 10.2196/mhealth.8532.
    1. Lee H, Ghebre R, Le C, Jang YJ, Sharratt M, Yee D. Mobile Phone Multilevel and Multimedia Messaging Intervention for Breast Cancer Screening: Pilot Randomized Controlled Trial. JMIR Mhealth Uhealth. 2017 Nov 07;5(11):e154. doi: 10.2196/mhealth.7091.
    1. Kang H, Park H. A Mobile App for Hypertension Management Based on Clinical Practice Guidelines: Development and Deployment. JMIR Mhealth Uhealth. 2016 Feb 02;4(1):e12. doi: 10.2196/mhealth.4966.
    1. Marcolino MS, Oliveira JAQ, D'Agostino M, Ribeiro AL, Alkmim MBM, Novillo-Ortiz D. The Impact of mHealth Interventions: Systematic Review of Systematic Reviews. JMIR Mhealth Uhealth. 2018 Jan 17;6(1):e23. doi: 10.2196/mhealth.8873.
    1. Fiordelli M, Diviani N, Schulz PJ. Mapping mHealth research: a decade of evolution. J Med Internet Res. 2013;15(5):e95. doi: 10.2196/jmir.2430.
    1. Mechael P. The Case for mHealth in Developing Countries. Innovations: Technology, Governance, Globalization. 2009 Jan;4(1):103–118. doi: 10.1162/itgg.2009.4.1.103.
    1. O'Reilly GA, Spruijt-Metz D. Current mHealth technologies for physical activity assessment and promotion. Am J Prev Med. 2013 Oct;45(4):501–507. doi: 10.1016/j.amepre.2013.05.012.
    1. Riley WT, Rivera DE, Atienza AA, Nilsen W, Allison SM, Mermelstein R. Health behavior models in the age of mobile interventions: are our theories up to the task? Transl Behav Med. 2011 Mar;1(1):53–71. doi: 10.1007/s13142-011-0021-7.
    1. Maguire M. Methods to support human-centred design. Int J Hum Comput Stud. 2001 Oct;55(4):587–634. doi: 10.1006/ijhc.2001.0503.
    1. Schnall R, Rojas M, Bakken S, Brown W, Carballo-Dieguez A, Carry M, Gelaude D, Mosley JP, Travers J. A user-centered model for designing consumer mobile health (mHealth) applications (apps) J Biomed Inform. 2016 Apr;60:243–251. doi: 10.1016/j.jbi.2016.02.002.
    1. Brown W, Yen P, Rojas M, Schnall R. Assessment of the Health IT Usability Evaluation Model (Health-ITUEM) for evaluating mobile health (mHealth) technology. J Biomed Inform. 2013 Dec;46(6):1080–1087. doi: 10.1016/j.jbi.2013.08.001.
    1. Deterding S, Dixon D, Khaled R, Nacke L, Sicart M, O'Hara K. Gamification. Using game-design elements in non-gaming contexts. Proceedings of the; 2011 Annual Conference on Human Factors in Computing Systems; May 7-12, 2011; Vancouver, BC. New York, USA: ACM Press; 2011.
    1. Deterding S, Dixon D, Khaled R, Nacke L. From game design elements to gamefulness. 15th International Academic MindTrek Conference on Envisioning Future Media Environments; September 28-30, 2011; Tampere, Finland. Tampere, Finland: ACM Press; 2011. p. 11.
    1. Ferguson B. Games for Wellness-Impacting the Lives of Employees and the Profits of Employers. Games Health J. 2012 Jun;1(3):177–179. doi: 10.1089/g4h.2012.0023.
    1. Ferrara J. Games for Persuasion: Argumentation, Procedurality, and the Lie of Gamification. Games and Culture. 2013 Aug 27;8(4):289–304. doi: 10.1177/1555412013496891.
    1. Lister C, West JH, Cannon B, Sax T, Brodegard D. Just a fad? Gamification in health and fitness apps. JMIR Serious Games. 2014 Aug 04;2(2):e9. doi: 10.2196/games.3413.
    1. Giunti G, Kool J, Rivera RO, Dorronzoro ZE. Exploring the Specific Needs of Persons with Multiple Sclerosis for mHealth Solutions for Physical Activity: Mixed-Methods Study. JMIR Mhealth Uhealth. 2018 Feb 09;6(2):e37. doi: 10.2196/mhealth.8996.
    1. Giunti G, Guisado-Fernandez E, Caulfield B. Connected Health in Multiple Sclerosis: A Mobile Applications Review. IEEE 30th International Symposium on Computer-Based Medical Systems; June 22-24, 2017; Thessaloniki, Greece. IEEE; 2017.
    1. Arksey H, O'Malley L. Scoping studies: towards a methodological framework. International Journal of Social Research Methodology. 2005 Feb;8(1):19–32. doi: 10.1111/j.1365-2958.2006.05159.x. doi: 10.1080/1364557032000119616.
    1. Levac D, Colquhoun H, O'Brien KK. Scoping studies: advancing the methodology. Implement Sci. 2010 Sep 20;5:69. doi: 10.1186/1748-5908-5-69.
    1. Rivera J, McPherson A, Hamilton J, Birken C, Coons M, Iyer S, Agarwal A, Lalloo C, Stinson J. Mobile Apps for Weight Management: A Scoping Review. JMIR Mhealth Uhealth. 2016 Jul 26;4(3):e87. doi: 10.2196/mhealth.5115.
    1. Moher D, Liberati A, Tetzlaff J, Altman DG, PRISMA Group Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement. PLoS Med. 2009 Jul 21;6(7):e1000097. doi: 10.1371/journal.pmed.1000097.
    1. Tinschert P, Jakob R, Barata F, Kramer J, Kowatsch T. The Potential of Mobile Apps for Improving Asthma Self-Management: A Review of Publicly Available and Well-Adopted Asthma Apps. JMIR Mhealth Uhealth. 2017 Aug 02;5(8):e113. doi: 10.2196/mhealth.7177.
    1. Masterson CRM, Maurer MS, Reading M, Hiraldo G, Hickey KT, Iribarren S. Review and Analysis of Existing Mobile Phone Apps to Support Heart Failure Symptom Monitoring and Self-Care Management Using the Mobile Application Rating Scale (MARS) JMIR Mhealth Uhealth. 2016 Jun 14;4(2):e74. doi: 10.2196/mhealth.5882.
    1. Mendiola MF, Kalnicki M, Lindenauer S. Valuable features in mobile health apps for patients and consumers: content analysis of apps and user ratings. JMIR Mhealth Uhealth. 2015 May 13;3(2):e40. doi: 10.2196/mhealth.4283.
    1. Giunti G, Giunta D, Guisado-Fernandez E, Bender J, Fernandez-Luque L. A biopsy of Breast Cancer mobile applications: state of the practice review. Int J Med Inform. 2018 Feb;110:1–9. doi: 10.1016/j.ijmedinf.2017.10.022.
    1. Bender JL, Yue RYK, To MJ, Deacken L, Jadad AR. A lot of action, but not in the right direction: systematic review and content analysis of smartphone applications for the prevention, detection, and management of cancer. J Med Internet Res. 2013 Dec 23;15(12):e287. doi: 10.2196/jmir.2661.
    1. Johnson D, Deterding S, Kuhn K, Staneva A, Stoyanov S, Hides L. Gamification for health and wellbeing: A systematic review of the literature. Internet Interventions. 2016 Nov;6:89–106. doi: 10.1016/j.invent.2016.10.002.
    1. Lorig KR, Holman H. Self-management education: history, definition, outcomes, and mechanisms. Ann Behav Med. 2003 Aug;26(1):1–7. doi: 10.1207/S15324796ABM2601_01.
    1. Perrin RA. Management of multiple sclerosis. Am J Manag Care. 2013 Nov;19(16 Suppl):s301–306.
    1. Wicks P, Chiauzzi E. 'Trust but verify'--five approaches to ensure safe medical apps. BMC Med. 2015 Sep 25;13:205. doi: 10.1186/s12916-015-0451-z.
    1. Gullikson S, Blades R, Bragdon M, McKibbon S, Sparling M, Toms E. The impact of information architecture on academic web site usability. The Electronic Library. 1999 Oct;17(5):293–304. doi: 10.1108/02640479910330714.
    1. Shneiderman B, Plaisant C, Hesse B. Improving Healthcare with Interactive Visualization. Computer. 2013 May;46(5):58–66. doi: 10.1109/MC.2013.38.
    1. Bodenheimer T, Wagner EH, Grumbach K. Improving primary care for patients with chronic illness. JAMA. 2002 Oct 09;288(14):1775–1779.
    1. Ritvo P, Obadia M, Santa MD, Alibhai S, Sabiston C, Oh P, Campbell K, McCready D, Auger L, Jones JM. Smartphone-Enabled Health Coaching Intervention (iMOVE) to Promote Long-Term Maintenance of Physical Activity in Breast Cancer Survivors: Protocol for a Feasibility Pilot Randomized Controlled Trial. JMIR Res Protoc. 2017 Aug 24;6(8):e165. doi: 10.2196/resprot.6615.
    1. DeMasi O, Feygin S, Dembo A, Aguilera A, Recht B. Well-Being Tracking via Smartphone-Measured Activity and Sleep: Cohort Study. JMIR Mhealth Uhealth. 2017 Oct 05;5(10):e137. doi: 10.2196/mhealth.7820.
    1. Khedr M, El-Sheimy N. A Smartphone Step Counter Using IMU and Magnetometer for Navigation and Health Monitoring Applications. Sensors (Basel) 2017 Nov 08;17(11) doi: 10.3390/s17112573.
    1. Korinek EV, Phatak SS, Martin CA, Freigoun MT, Rivera DE, Adams MA, Klasnja P, Buman MP, Hekler EB. Adaptive step goals and rewards: a longitudinal growth model of daily steps for a smartphone-based walking intervention. J Behav Med. 2018 Feb;41(1):74–86. doi: 10.1007/s10865-017-9878-3.
    1. Motl RW, McAuley E, Snook EM. Physical activity and multiple sclerosis: a meta-analysis. Mult Scler. 2005 Aug;11(4):459–463. doi: 10.1191/1352458505ms1188oa.
    1. Petajan JH, Gappmaier E, White AT, Spencer MK, Mino L, Hicks RW. Impact of aerobic training on fitness and quality of life in multiple sclerosis. Ann Neurol. 1996 Apr;39(4):432–441. doi: 10.1002/ana.410390405.
    1. Motl RW, Snook EM. Physical activity, self-efficacy, and quality of life in multiple sclerosis. Ann Behav Med. 2008 Feb;35(1):111–115. doi: 10.1007/s12160-007-9006-7.
    1. Klaren RE, Motl RW, Dlugonski D, Sandroff BM, Pilutti LA. Objectively quantified physical activity in persons with multiple sclerosis. Arch Phys Med Rehabil. 2013 Dec;94(12):2342–2348. doi: 10.1016/j.apmr.2013.07.011.
    1. Latimer-Cheung AE, Martin GKA, Hicks AL, Motl RW, Pilutti LA, Duggan M, Wheeler G, Persad R, Smith KM. Development of evidence-informed physical activity guidelines for adults with multiple sclerosis. Arch Phys Med Rehabil. 2013 Sep;94(9):1829–1836.e7. doi: 10.1016/j.apmr.2013.05.015.
    1. Braley TJ, Chervin RD. Fatigue in multiple sclerosis: mechanisms, evaluation, and treatment. Sleep. 2010 Aug;33(8):1061–1067.
    1. AlMarshedi A, Wills G, Ranchhod A. Guidelines for the Gamification of Self-Management of Chronic Illnesses: Multimethod Study. JMIR Serious Games. 2017 May 12;5(2):e12. doi: 10.2196/games.7472.
    1. Stoyanov SR, Hides L, Kavanagh DJ, Zelenko O, Tjondronegoro D, Mani M. Mobile app rating scale: a new tool for assessing the quality of health mobile apps. JMIR Mhealth Uhealth. 2015 Mar 11;3(1):e27. doi: 10.2196/mhealth.3422.
    1. Davis F. MIT Thesis. Massachusetts: MIT; 1985. A technology acceptance model for empirically testing new end-user information systems: Theory and results. Management.
    1. Venkatesh V, Morris M, Davis G, Davis F. User Acceptance of Information Technology: Toward a Unified View. MIS Quarterly. 2003 Dec;27(3):425–427. doi: 10.2307/30036540.

Source: PubMed

Sponsors and Collaborators

Medical Conditions

Drug Interventions

3
Subscribe