Evaluating the Utility of Smartphone-Based Sensor Assessments in Persons With Multiple Sclerosis in the Real-World Using an App (elevateMS): Observational, Prospective Pilot Digital Health Study

Abstract

Background Multiple sclerosis (MS) is a chronic neurodegenerative disease. Current monitoring practices predominantly rely on brief and infrequent assessments, which may not be representative of the real-world patient experience. Smartphone technology provides an opportunity to assess people’s daily-lived experience of MS on a frequent, regular basis outside of episodic clinical evaluations. Objective The objectives of this study were to evaluate the feasibility and utility of capturing real-world MS-related health data remotely using a smartphone app, “elevateMS,” to investigate the associations between self-reported MS severity and sensor-based active functional tests measurements, and the impact of local weather conditions on disease burden. Methods This was a 12-week, observational, digital health study involving 3 cohorts: self-referred participants who reported an MS diagnosis, clinic-referred participants with neurologist-confirmed MS, and participants without MS (controls). Participants downloaded the elevateMS app and completed baseline assessments, including self-reported physical ability (Patient-Determined Disease Steps [PDDS]), as well as longitudinal assessments of quality of life (Quality of Life in Neurological Disorders [Neuro-QoL] Cognitive, Upper Extremity, and Lower Extremity Function) and daily health (MS symptoms, triggers, health, mobility, pain). Participants also completed functional tests (finger-tapping, walk and balance, voice-based Digit Symbol Substitution Test [DSST], and finger-to-nose) as an independent assessment of MS-related cognition and motor activity. Local weather data were collected each time participants completed an active task. Associations between self-reported baseline/longitudinal assessments, functional tests, and weather were evaluated using linear (for cross-sectional data) and mixed-effects (for longitudinal data) regression models. Results A total of 660 individuals enrolled in the study; 31 withdrew, 495 had MS (n=359 self-referred, n=136 clinic-referred), and 134 were controls. Participation was highest in clinic-referred versus self-referred participants (median retention: 25.5 vs 7.0 days). The top 5 most common MS symptoms, reported at least once by participants with MS, were fatigue (310/495, 62.6%), weakness (222/495, 44.8%), memory/attention issues (209/495, 42.2%), and difficulty walking (205/495, 41.4%), and the most common triggers were high ambient temperature (259/495, 52.3%), stress (250/495, 50.5%), and late bedtime (221/495, 44.6%). Baseline PDDS was significantly associated with functional test performance in participants with MS (mixed model–based estimate of most significant feature across functional tests [β]: finger-tapping: β=–43.64, P<.001; DSST: β=–5.47, P=.005; walk and balance: β=–.39, P=.001; finger-to-nose: β=.01, P=.01). Longitudinal Neuro-QoL scores were also significantly associated with functional tests (finger-tapping with Upper Extremity Function: β=.40, P<.001; walk and balance with Lower Extremity Function: β=–99.18, P=.02; DSST with Cognitive Function: β=1.60, P=.03). Finally, local temperature was significantly associated with participants’ test performance (finger-tapping: β=–.14, P<.001; DSST: β=–.06, P=.009; finger-to-nose: β=–53.88, P<.001). Conclusions The elevateMS study app captured the real-world experience of MS, characterized some MS symptoms, and assessed the impact of environmental factors on symptom severity. Our study provides further evidence that supports smartphone app use to monitor MS with both active assessments and patient-reported measures of disease burden. App-based tracking may provide unique and timely real-world data for clinicians and patients, resulting in improved disease insights and management.

Are mHealth a Useful Tool for Self-Assessment and Rehabilitation of People With Multiple Sclerosis? A Review

“…Pratap et al in a large study including more than 500 pwMS described that ElevateMS can be used to longitudinally (12 weeks period) collect formation about the most common symptoms of MS. During this follow-up, they observed that the most frequent complaints are fatigue (63%), memory issues (42%) and difficulty with walking (41%). After the intervention, there were significant increased functional performances and QoL [59]. To summarize the findings of this study we listed the different mHealth according to the targeted ICF domain for both rehabilitation and self-assessment in Table 3.…”

“…Concerning the self-assessment tools six studies, using 6 different mHealth applications, have been included in the review, representing 1,129 participants (955 pwMS [88% with RRMS, 5% with SPMS and 7% with PPMS, average EDSS 2.50.5] and 174 healthy participants) [54][55][56][57][58][59]. The characteristics of the studies and participants are summarized in Table 2.…”

“…ElevateMS [59] allows collecting different data in the real-world environment of the patients such as self-reported measures of symptoms and health via 'check-in'-surveys Independent assessments of motor function via sensor-based active functional tests Encouraging to complete surveys daily and notifications to perform more comprehensive functional tests once a week.…”

A Smartphone-based Application for Self-Management in Multiple Sclerosis

“…It is also the most common debilitating neurological disorder in adults. Not only MS is regarded as a serious health problem but also its economic burden in terms of the costs associated with the patient care and treatments as well as patients' reduced economic activities have received more attention in the past years [1][2][3].…”

MSProDiscuss – Entwicklung eines digitalen Tools zur standardisierten Patientenanamnese, um Progredienz bei Multipler Sklerose zu identifizieren

“…Auch wenn sich Patienten an die anfängliche Symptomzunahme zunächst gewöhnen [26] oder sich diese als tagesabhängige Variation erklären [27], so nehmen sie doch sehr genau wahr, wie insbesondere die funktionalen Defizite und Einschränkungen des täglichen Lebens zunehmen [28]. Verschiedene Softwarelösungen und Smartphone Applikationen wie die Floodlight Testbatterie [29], der MS-CoPilot [30], elevateMS [31] oder der Open MS BioScreen [32] ermöglichen MS-Patienten ein kontinuierliches Selbst-Monitoring, um die Zunahme körperlicher und kognitiver Einschränkungen in der Alltagssituation zu erfassen. Um eine mögliche SPMS-Konversion frühzeitig anamnetisch detektieren zu können [33], müssen jedoch Patient und Neurologe in der Lage sein, die frühen Hinwei-se und oft unklaren Anzeichen während der regulären Visite zu kommunizieren bzw.…”