ReviewBrain sciences2021
Electronic Health Interventions in the Case of Multiple Sclerosis: From Theory to Practice.
Review in Brain sciences, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 papers, 2 of them syntheses 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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
25 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Gamified Health Promotion in Schools: The Integration of Neuropsychological Aspects and CBT-A Systematic Review.Medicina (Kaunas, Lithuania) · 2024Pooled it
- Mobile App Interventions for Parkinson's Disease, Multiple Sclerosis and Stroke: A Systematic Literature Review.Sensors (Basel, Switzerland) · 2023Pooled it
- Digital Biomarkers and AI for Remote Monitoring of Fatigue Progression in Neurological Disorders: Bridging Mechanisms to Clinical Applications.Brain sciences · 2025Article
- Examining the Telehealth Readiness Among Individuals With Multiple Sclerosis.Journal of patient experience · 2025Article
- A scoping review assessing the usability of digital health technologies targeting people with multiple sclerosis.NPJ digital medicine · 2024Article
- Data on Ocrelizumab Treatment Collected by MS Patients in Germany Using Brisa App.Journal of personalized medicine · 2024Article
- Robotic systems for upper-limb rehabilitation in multiple sclerosis: a SWOT analysis and the synergies with virtual and augmented environments.Frontiers in robotics and AI · 2024Review
- Building digital patient pathways for the management and treatment of multiple sclerosis.Frontiers in immunology · 2024Review
- Feasibility and scalability of a fitness tracker study: Results from a longitudinal analysis of persons with multiple sclerosis.Frontiers in digital health · 2023Article
- Management of multiple sclerosis fatigue in the digital age: from assessment to treatment.Frontiers in neuroscience · 2023Review
- A Comprehensive Literature Search of Digital Health Technology Use in Neurological Conditions: Review of Digital Tools to Promote Self-management and Support.Journal of medical Internet research · 2022Review
- Demographic Patterns of MS Patients Using BRISA: An MS-Specific App in Germany.Journal of personalized medicine · 2022Article
- The AIMS home-video method: parental experiences and appraisal for use in neonatal follow-up clinics.BMC pediatrics · 2022Article
- Digital Innovation in Multiple Sclerosis Management.Brain sciences · 2021Article
- The sympathies of the body: functional organization and neuronal differentiation in the peripheral sympathetic nervous system.Cell and tissue research · 2021Review
- Automated Analysis of the Two-Minute Walk Test in Clinical Practice Using Accelerometer Data.Brain sciences · 2021Article
- Multiple Sclerosis Progression Discussion Tool Usability and Usefulness in Clinical Practice: Cross-sectional, Web-Based Survey.Journal of medical Internet research · 2021Article
- The Potential Impact of Digital Biomarkers in Multiple Sclerosis in The Netherlands: An Early Health Technology Assessment of MS Sherpa.Brain sciences · 2021Article
- Developing a Digital Solution for Remote Assessment in Multiple Sclerosis: From Concept to Software as a Medical Device.Brain sciences · 2021Review
- A Mobile App for Measuring Real Time Fatigue in Patients with Multiple Sclerosis: Introducing the Fimo Health App.Brain sciences · 2021Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
(1) Background: eHealth interventions play a growing role in shaping the future healthcare system. The integration of eHealth interventions can enhance the efficiency and quality of patient management and optimize the course of treatment for chronically ill patients. In this integrative review, we discuss different types of interventions, standards and advantages of quality eHealth approaches especially for people with multiple sclerosis (pwMS). (2) Methods: The electronic databases PubMed, Cochrane and Web of Science were searched to identify potential articles for eHealth interventions in pwMS; based on 62 articles, we consider different ways of implementing health information technology with various designs. (3) Results: There already exist some eHealth interventions for single users with a single-use case, interventions with a social setting, as well as eHealth interventions that integrate various single and social interventions and even those that may be used additionally for complex use cases. A key determinant of consumer acceptance is a high-quality user-centric design for healthcare practitioners and pwMS. In pwMS, the different neurological disabilities should be considered, and particular attention must be paid to the course of the treatment and the safety processes of each treatment option. (4) Conclusion: Depending on the field of application and the respective users, interventions are designed for single, social, integrated or complex use. In order to be accepted by their target group, interventions must be beneficial and easy to use.
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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.