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Observational Study
. 2021 Apr 16;9(4):e19564.
doi: 10.2196/19564.

Usability of a Mobile App for Real-Time Assessment of Fatigue and Related Symptoms in Patients With Multiple Sclerosis: Observational Study

Miklos Palotai  1 , Max Wallack  1 , Gergo Kujbus  2 , Adam Dalnoki  2 , Charles Guttmann  1
Affiliations
Observational Study

Usability of a Mobile App for Real-Time Assessment of Fatigue and Related Symptoms in Patients With Multiple Sclerosis: Observational Study

Miklos Palotai et al. JMIR Mhealth Uhealth. .

Abstract

Background: Although fatigue is one of the most debilitating symptoms in patients with multiple sclerosis (MS), its pathogenesis is not well understood. Neurogenic, inflammatory, endocrine, and metabolic mechanisms have been proposed. Taking into account the temporal dynamics and comorbid mood symptoms of fatigue may help differentiate fatigue phenotypes. These phenotypes may reflect different pathogeneses and may respond to different mechanism-specific treatments. Although several tools have been developed to assess various symptoms (including fatigue), monitor clinical status, or improve the perceived level of fatigue in patients with MS, options for a detailed, real-time assessment of MS-related fatigue and relevant comorbidities are still limited.

Objective: This study aims to present a novel mobile app specifically designed to differentiate fatigue phenotypes using circadian symptom monitoring and state-of-the-art characterization of MS-related fatigue and its related symptoms. We also aim to report the first findings regarding patient compliance and the relationship between compliance and patient characteristics, including MS disease severity.

Methods: After developing the app, we used it in a prospective study designed to investigate the brain magnetic resonance imaging correlates of MS-related fatigue. In total, 64 patients with MS were recruited into this study and asked to use the app over a 2-week period. The app features the following modules: Visual Analogue Scales (VASs) to assess circadian changes in fatigue, depression, anxiety, and pain; daily sleep diaries (SLDs) to assess sleep habits and quality; and 10 one-time questionnaires to assess fatigue, depression, anxiety, sleepiness, physical activity, and motivation, as well as several other one-time questionnaires that were created to assess those relevant aspects of fatigue that were not captured by existing fatigue questionnaires. The app prompts subjects to assess their symptoms multiple times a day and enables real-time symptom monitoring through a web-accessible portal.

Results: Of 64 patients, 56 (88%) used the app, of which 51 (91%) completed all one-time questionnaires and 47 (84%) completed all one-time questionnaires, VASs, and SLDs. Patients reported no issues with the usage of the app, and there were no technical issues with our web-based data collection system. The relapsing-remitting MS to secondary-progressive MS ratio was significantly higher in patients who completed all one-time questionnaires, VASs, and SLDs than in those who completed all one-time questionnaires but not all VASs and SLDs (P=.01). No other significant differences in demographics, fatigue, or disease severity were observed between the degrees of compliance.

Conclusions: The app can be used with reasonable compliance across patients with relapsing-remitting and secondary-progressive MS irrespective of demographics, fatigue, or disease severity.

Keywords: depression; fatigue; mobile application; mobile phone; multiple sclerosis; real-time assessment.

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Conflict of interest statement

Conflicts of Interest: MP and MW reported no disclosures. GK is the director of the Mobilengine. AD is the CEO of the Mobilengine. CG has received support from Mobilengine (free use of platform and programming by Mobilengine Engineers), the National Multiple Sclerosis Society, the International Progressive Multiple Sclerosis Alliance, the US Office for Naval Research, and travel support from Roche Pharmaceuticals; CG owns stock in Roche, Novartis, GlaxoSmithKline, Alnylam, Protalix Biotherapeutics, Arrowhead Pharmaceuticals, Cocrystal Pharma, and Sangamo Therapeutics.

Figures

Figure 1
Figure 1
Sample screens for simple choice (A), multiple choice (B), number box (C), and text box (D) questions used in the one-time questionnaire module. Users can freely navigate forward and backward between questions within the same block using the forward (green) and backward (gray) arrows at the bottom of the screen. Under the arrows, a status bar indicates how far through the one-time questions a user is.
Figure 2
Figure 2
Sample screens for Visual Analogue Scales for fatigue (A), depression (B), anxiety (C), and pain (D). Users can freely navigate forward and backward between questions using the forward (green) and backward (gray) arrows at the bottom of the screen. Under the arrows, a status bar indicates the progress of the user in the Visual Analogue Scale.
Figure 3
Figure 3
Sample screens for the sleep diary module. Sleep diary is activated by tapping on the “I’m going to sleep now” icon (A). Then, the user is prompted to indicate whether they were taking a nap or going to sleep for the night (B), as well as their intended wake-up time (C). Upon awakening, the user selects the “I just woke up” icon (D).
Figure 4
Figure 4
Algorithm of Visual Analogue Scale and sleep diary assessments. VAS: Visual Analogue Scale.
Figure 5
Figure 5
Patient compliance in our study cohort. MS: multiple sclerosis.
Figure 6
Figure 6
Time to completion of one-time questionnaires (expressed in hours). Patients (indicated by blue rhombuses) were asked to answer all one-time questions within 3 days of enrollment (indicated by the dashed vertical red line).
See this image and copyright information in PMC

References

    1. Wallin MT, Culpepper WJ, Campbell JD, Nelson LM, Langer-Gould A, Marrie RA, Cutter GR, Kaye WE, Wagner L, Tremlett H, Buka SL, Dilokthornsakul P, Topol B, Chen LH, LaRocca NG. The prevalence of MS in the United States. Neurology. 2019 Feb 15;92(10):1029–40. doi: 10.1212/wnl.0000000000007035. - DOI - PMC - PubMed
    1. Bakshi Rohit. Fatigue associated with multiple sclerosis: diagnosis, impact and management. Mult Scler. 2003 Jun;9(3):219–27. doi: 10.1191/1352458503ms904oa. - DOI - PubMed
    1. Cavallari M, Palotai M, Glanz BI, Egorova S, Prieto JC, Healy BC, Chitnis T, Guttmann CR. Fatigue predicts disease worsening in relapsing-remitting multiple sclerosis patients. Mult Scler. 2016 Dec 11;22(14):1841–9. doi: 10.1177/1352458516635874. - DOI - PubMed
    1. Miller P, Soundy A. The pharmacological and non-pharmacological interventions for the management of fatigue related multiple sclerosis. J Neurol Sci. 2017 Oct 15;381:41–54. doi: 10.1016/j.jns.2017.08.012. - DOI - PubMed
    1. Yang TT, Wang L, Deng XX, Yu G. Pharmacological treatments for fatigue in patients with multiple sclerosis: a systematic review and meta-analysis. J Neurol Sci. 2017 Sep 15;380:256–61. doi: 10.1016/j.jns.2017.07.042. - DOI - PubMed

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