ArticleJournal of medical Internet research2019
Adherence and Satisfaction of Smartphone- and Smartwatch-Based Remote Active Testing and Passive Monitoring in People With Multiple Sclerosis: Nonrandomized Interventional Feasibility Study.
Article in Journal of medical Internet research, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. It is linked to trial NCT02952911 (Monitoring of Multiple Sclerosis), which is not on this map. Cited by 82 papers, 2 of them syntheses that pooled it.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Monitoring of Multiple Sclerosis (MS) Participants With the Use of Digital Technology (Smartphones and Smartwatches) - A Feasibility Study
Who cites it
82 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- The role of machine learning in developing non-magnetic resonance imaging based biomarkers for multiple sclerosis: a systematic review.BMC medical informatics and decision making · 2022Pooled it
- Assessing the usability of wearable devices to measure gait and physical activity in chronic conditions: a systematic review.Journal of neuroengineering and rehabilitation · 2021Pooled it
- Neural correlates of digital measures shown by structural MRI: a post-hoc analysis of a smartphone-based remote assessment feasibility study in multiple sclerosis.Journal of neurology · 2023Trial
- A smartphone sensor-based digital outcome assessment of multiple sclerosis.Multiple sclerosis (Houndmills, Basingstoke, England) · 2022Trial
- Remote Vital Sign Monitoring in Acutely Unwell Hospital at Home Patients: Nonrandomized Feasibility Study.JMIR formative research · 2026Article
- Strategies for integrating artificial intelligence and cognitive assessment to predict disability progression in relapsing-remitting multiple sclerosis: A model development study.PLOS digital health · 2026Article
- Beyond Relapses: A Multimodal Biomarker Framework for Progression Independent of Relapse Activity and Smouldering Multiple Sclerosis.Brain sciences · 2026Review
- Clinical telemonitoring and telerehabilitation of cognition in rare neurological diseases: a scoping review.Journal of neurology · 2026Article
- Digital patient experience tools in multiple sclerosis: a landscape analysis of the global Patient-Reported Outcomes in Multiple Sclerosis (PROMS) initiative.EClinicalMedicine · 2026Article
- MS360°: a conceptual digital-first, data-driven hybrid care framework for personalised multiple sclerosis management.NPJ digital medicine · 2026Review
- Assessing verbal and spatial memory via smartphone.Frontiers in digital health · 2026Article
- MSPEECH (multiple sclerosis monitoring through speech interaction in clinic and at home): a Living Lab study protocol for co-created, speech-based digital biomarkers in multiple sclerosis.Frontiers in digital health · 2026Article
- Simulation of Clinical Visits as a Novel Approach to Evaluate Digital Health in Multiple Sclerosis: Simulation Study.JMIR medical informatics · 2025Article
- Sensors in Multiple Sclerosis.Current neurology and neuroscience reports · 2025Review
- Review
- Experiences of People with Multiple Sclerosis in Sensor-Based Jump Assessment.Bioengineering (Basel, Switzerland) · 2025Article
- Longitudinal Digital Phenotyping of Multiple Sclerosis Severity Using Passively Sensed Behaviors and Ecological Momentary Assessments: Real-World Evaluation.Journal of medical Internet research · 2025Article
- Digital Biomarkers and AI for Remote Monitoring of Fatigue Progression in Neurological Disorders: Bridging Mechanisms to Clinical Applications.Brain sciences · 2025Article
- Investigating Measurement Equivalence of Smartphone Sensor-Based Assessments: Remote, Digital, Bring-Your-Own-Device Study.Journal of medical Internet research · 2025Article
- Long-term acceptability of MSReactor digital cognitive monitoring among people living with multiple sclerosis.Multiple sclerosis (Houndmills, Basingstoke, England) · 2025Article
22 more citing papers are in PubMed but not listed here.
Corrections and comments
- Erratum issued
Authors and funding
15 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundCurrent clinical assessments of people with multiple sclerosis are episodic and may miss critical features of functional fluctuations between visits.
objectiveThe goal of the research was to assess the feasibility of remote active testing and passive monitoring using smartphones and smartwatch technology in people with multiple sclerosis with respect to adherence and satisfaction with the FLOODLIGHT test battery.
methodsPeople with multiple sclerosis (aged 20 to 57 years; Expanded Disability Status Scale 0-5.5; n=76) and healthy controls (n=25) performed the FLOODLIGHT test battery, comprising active tests (daily, weekly, every two weeks, or on demand) and passive monitoring (sensor-based gait and mobility) for 24 weeks using a smartphone and smartwatch. The primary analysis assessed adherence (proportion of weeks with at least 3 days of completed testing and 4 hours per day passive monitoring) and questionnaire-based satisfaction. In-clinic assessments (clinical and magnetic resonance imaging) were performed.
resultsPeople with multiple sclerosis showed 70% (16.68/24 weeks) adherence to active tests and 79% (18.89/24 weeks) to passive monitoring; satisfaction score was on average 73.7 out of 100. Neither adherence nor satisfaction was associated with specific population characteristics. Test-battery assessments had an at least acceptable impact on daily activities in over 80% (61/72) of people with multiple sclerosis.
conclusionsPeople with multiple sclerosis were engaged and satisfied with the FLOODLIGHT test battery. FLOODLIGHT sensor-based measures may enable continuous assessment of multiple sclerosis disease in clinical trials and real-world settings.
trial registrationClinicalTrials.gov: NCT02952911; https://clinicaltrials.gov/ct2/show/NCT02952911.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.