Evidence map›Paper›PMID 26323749›Full record

ArticleJMIR mHealth and uHealth2015

A New App for At-Home Cognitive Training: Description and Pilot Testing on Patients with Multiple Sclerosis.

Andrea Tacchino, Ludovico Pedullà, Laura Bonzano, Claudio Vassallo, Mario Alberto Battaglia, Gianluigi Mancardi, Marco Bove, Giampaolo Brichetto

Registry-linked trialOpen access · goldAbstract read
In one paragraph

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.

0numbers the graph read from it
0cells of the map it votes in
28citing papers in PubMed, 2 pooled it
4.2field-weighted citation impact, top 6% of its field
1 · What the graph read from 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.

2 · The registry

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.

NCT07193602 nanot yet recruitingnot on this mapstarted 2026, after this paper: background citation

Home-based Virtual Reality (VR) Headset-based Dexterity Training in Multiple Sclerosis: a Randomized-controlled Trial

TypeinterventionalSponsorChristian KammRan2026 to 2028Enrolled60ConditionsMultiple SclerosisArmsVR-based dexterity training in MS, mediation program
3 · Its place in the literature

Who cites it

28 citing papers in PubMed, 2 syntheses or guidelines pooled it, 78 citations in OpenAlex.

  1. Pooled it
  2. Pooled it
  3. 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 · 2025
    Trial
  4. Trial
  5. Trial
  6. Review
  7. Observational
  8. Review
  9. Article
  10. Article
  11. The State of the Art of Pediatric Multiple Sclerosis.International journal of molecular sciences · 2023
    Review
  12. Review
  13. Article
  14. Digital therapeutics in neurology.Journal of neurology · 2022
    Review
  15. Article
  16. Review
  17. Article
  18. Review
  19. Review
  20. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors at 3 institutions in 1 country.

Associazione Italiana Sclerosi Multipla · ITUniversity of Genoa · ITUniversity of Siena · IT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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.

Indexed as

adaptive working load algorithmscognitive impairmentcognitive rehabilitationmobile devicemobile phoneself-managementtabletusabilityworking memory

Identifiers

PMID26323749
PMCPMC4704979
OpenAlexW1898733374

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.