ArticleJMIR mHealth and uHealth2015
A New App for At-Home Cognitive Training: Description and Pilot Testing on Patients with Multiple Sclerosis.
Article in JMIR mHealth and uHealth, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT07193602 (Home-based Virtual Reality), which is not on this map. Cited by 28 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.
Home-based Virtual Reality (VR) Headset-based Dexterity Training in Multiple Sclerosis: a Randomized-controlled Trial
Who cites it
28 citing papers in PubMed, 2 syntheses or guidelines pooled it, 78 citations in OpenAlex.
- Exploring the potential of artificial intelligence in individualized cognitive training: A systematic review.PloS one · 2025Pooled it
- Training Cognitive Functions Using Mobile Apps in Breast Cancer Patients: Systematic Review.JMIR mHealth and uHealth · 2019Pooled it
- Home-based, computer-assisted cognitive rehabilitation for attention in pediatric onset multiple sclerosis: a randomized, multicenter pilot study.Neurological sciences : official journal of the Italian Neurological Society and of the Italian Society of Clinical Neurophysiology · 2025Trial
- Face-to-Face or Telematic Cognitive Stimulation in Patients with Multiple Sclerosis and Cognitive Impairment: Why Not Both?Behavioural neurology · 2017Trial
- Adaptive vs. non-adaptive cognitive training by means of a personalized App: a randomized trial in people with multiple sclerosis.Journal of neuroengineering and rehabilitation · 2016Trial
- The Use of Patient-Reported Outcome Measures in Developmental Age: A Complementary Tool for Pediatric Multiple Sclerosis Prognosis.Neurology and therapy · 2026Review
- Finnish Registry-Based Protocol for Screening and Management of Fatigue and Cognitive Problems in Multiple Sclerosis: Observational Study.JMIR human factors · 2025Observational
- Challenging Cognitive Load Theory: The Role of Educational Neuroscience and Artificial Intelligence in Redefining Learning Efficacy.Brain sciences · 2025Review
- An Internet- and Kinect-Based Multiple Sclerosis Fitness Intervention Training With Pilates Exercises: Development and Usability Study.JMIR serious games · 2023Article
- Cognitive impairment in multiple sclerosis: "classic" knowledge and recent acquisitions.Arquivos de neuro-psiquiatria · 2023Article
- The State of the Art of Pediatric Multiple Sclerosis.International journal of molecular sciences · 2023Review
- Cognitive rehabilitation in multiple sclerosis: Three digital ingredients to address current and future priorities.Frontiers in human neuroscience · 2023Review
- Focus on neglected features of cognitive rehabilitation in MS: Setting and mode of the treatment.Multiple sclerosis (Houndmills, Basingstoke, England) · 2022Article
- Digital therapeutics in neurology.Journal of neurology · 2022Review
- Factors Associated With the Experience of Cognitive Training Apps for the Prevention of Dementia: Cross-sectional Study Using an Extended Health Belief Model.Journal of medical Internet research · 2022Article
- Digital Intervention for the Management of Alzheimer's Disease.Current Alzheimer research · 2022Review
- Additive and interaction effects of working memory and motor sequence training on brain functional connectivity.Scientific reports · 2021Article
- Is mHealth a Useful Tool for Self-Assessment and Rehabilitation of People with Multiple Sclerosis? A Systematic Review.Brain sciences · 2021Review
- Mobile health (mHealth) usage, barriers, and technological considerations in persons with multiple sclerosis: a literature review.JAMIA open · 2021Review
- Electronic Health Interventions in the Case of Multiple Sclerosis: From Theory to Practice.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
8 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundCognitive impairment is common in people with neurological diseases and severely affects their social and professional life. It has been shown that intensive and personalized cognitive rehabilitation (CR), based on working memory exercises, leads to improved cognitive status of healthy and cognitive-impaired subjects. New technologies would help to promote accessible, at-home, and self-managed CR interventions.
objectiveThe aim of this paper is to describe the design of Cognitive Training Kit (COGNI-TRAcK), an app for mobile devices, to self-administer an at-home, intensive, and personalized CR intervention based on working memory exercises, and test its disposability-to-use (usability, motivation to use, compliance to treatment) on cognitive-impaired patients with multiple sclerosis (MS).
methodsCOGNI-TRAcK includes user-friendly interfaces for personal data input and management and for CR intervention configurations. Inner routines automatically implement adaptive working load algorithms and allow data processing and analysis. A dedicated team developed COGNI-TRAcK with C# programming language, by using the platform Xamarin Studio 4.0.10 for Android (API level 15 and following). Three exercises based on working memory are now available. To assess the disposability-to-use of the system, patients with MS were selected as likely users due to the young age of disease onset. Cognitive-impaired patients with MS (N=16) with a mean age of 49.06 years (SD 9.10) and a mean score of 3.75 (SD 1.92) on the Expanded Disability Status Scale (EDSS) were submitted to an 8-week at-home intervention administered by the app. The intervention consisted of 5 daily scheduled 30-minute sessions per week. Disposability-to-use of COGNI-TRAcK was investigated by means of a questionnaire administered to patients at the end of the training.
resultsThe adherence to the treatment was 84% (33.4/40). Of the patients with MS, 94% (15/16) understood the instructions given, 100% (16/16) felt independent to use COGNI-TRAcK at home, 75% (12/16) found the exercises interesting, and 81% (13/16) found the exercises useful and were motivated to use the app again. Moreover, during the exercises, patients with MS were highly motivated to perform well (mean score 3.19/4, SE 0.16), experienced rather low levels of stress (mean score 2.19/4, SE 0.26), were not bored (mean score 1.81/4, SE 0.30), and felt amusement (mean score 2.25/4, SE 0.23).
conclusionsAs COGNI-TRAcK is highly usable, motivating, and well-accepted by patients with MS, its effectiveness can now be investigated. To improve COGNI-TRAcK, new releases should contain more working memory exercises, have enhanced perceived amusement, and promote Internet communication procedures for data transfer and fostering remote control of the intervention.
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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.