Trial reportMultiple sclerosis (Houndmills, Basingstoke, England)2022
A smartphone sensor-based digital outcome assessment of multiple sclerosis.
Trial report in Multiple sclerosis (Houndmills, Basingstoke, England), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT02952911 (Monitoring of Multiple Sclerosis), which is not on this map. Cited by 60 papers, 1 of them a synthesis that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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
60 citing papers in PubMed, 1 synthesis or guideline pooled it, 106 citations in OpenAlex.
- Characterizing gait in people with multiple sclerosis using digital data from smartphone sensors: A proposed framework.Multiple sclerosis (Houndmills, Basingstoke, England) · 2025Pooled 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
- Reliability and acceptance of dreaMS, a software application for people with multiple sclerosis: a feasibility study.Journal of neurology · 2023Trial
- 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
- Clinical telemonitoring and telerehabilitation of cognition in rare neurological diseases: a scoping review.Journal of neurology · 2026Article
- Wearables for Telemonitoring in ATTR-Amyloidosis: Current Perspectives.Sensors (Basel, Switzerland) · 2026Review
- AI-enabled Living Labs: Accelerating innovation in multiple sclerosis care and research.Multiple sclerosis (Houndmills, Basingstoke, England) · 2026Review
- Stride-level measurement of gait as an early sensitive marker of disability progression in ambulatory patients with multiple sclerosis.EClinicalMedicine · 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
- Monitoring cognition in multiple sclerosis via adaptive smartphone games-first insights from a validation study.Frontiers in digital health · 2026Article
- Development and Usability of MSafe: A Fall Risk Application for Older Adults with Multiple Sclerosis.Sensors (Basel, Switzerland) · 2025Article
- Sensors in Multiple Sclerosis.Current neurology and neuroscience reports · 2025Review
- Review
- Longitudinal Digital Phenotyping of Multiple Sclerosis Severity Using Passively Sensed Behaviors and Ecological Momentary Assessments: Real-World Evaluation.Journal of medical Internet research · 2025Article
- Performance of machine learning models for predicting high-severity symptoms in multiple sclerosis.Scientific reports · 2025Observational
- Investigating Measurement Equivalence of Smartphone Sensor-Based Assessments: Remote, Digital, Bring-Your-Own-Device Study.Journal of medical Internet research · 2025Article
- Identifying Biomarkers for Remyelination and Recovery in Multiple Sclerosis: A Measure of Progress.Biomedicines · 2025Review
- A New Smartphone-Based Cognitive Screening Battery for Multiple Sclerosis (icognition): Validation Study.Journal of medical Internet research · 2025Article
- CoGames: Development of an adaptive smartphone-based and gamified monitoring tool for cognitive function in Multiple Sclerosis.Journal of neurology · 2025Observational
- Development and validation of an electronic Symbol-Digit Modalities Test for remote monitoring of people with multiple sclerosis.European journal of neurology · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
16 authors at 5 institutions in 3 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundSensor-based monitoring tools fill a critical gap in multiple sclerosis (MS) research and clinical care.
objectiveThe aim of this study is to assess performance characteristics of the Floodlight Proof-of-Concept (PoC) app.
methodsIn a 24-week study (clinicaltrials.gov: NCT02952911), smartphone-based active tests and passive monitoring assessed cognition (electronic Symbol Digit Modalities Test), upper extremity function (Pinching Test, Draw a Shape Test), and gait and balance (Static Balance Test, U-Turn Test, Walk Test, Passive Monitoring). Intraclass correlation coefficients (ICCs) and age- or sex-adjusted Spearman's rank correlation determined test-retest reliability and correlations with clinical and magnetic resonance imaging (MRI) outcome measures, respectively.
resultsSeventy-six people with MS (PwMS) and 25 healthy controls were enrolled. In PwMS, ICCs were moderate-to-good (ICC(2,1) = 0.61-0.85) across tests. Correlations with domain-specific standard clinical disability measures were significant for all tests in the cognitive (
conclusionThe Floodlight PoC app captures reliable and clinically relevant measures of functional impairment in MS, supporting its potential use in clinical research and practice.
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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.