Evidence map›Paper›PMID 37847293›Full record

SynthesisJournal of neurology2024

eHealth tools to assess the neurological function for research, in absence of the neurologist - a systematic review, part I (software).

Vasco Ribeiro Ferreira, Esther Metting, Joshua Schauble, Hamed Seddighi, Lise Beumeler, Valentina Gallo

Erratum issuedOpen access · hybridAbstract readSystematic Review
In one paragraph

Synthesis in Journal of neurology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
1.1field-weighted citation impact, top 23% 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.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed, 5 citations in OpenAlex.

  1. Article
  2. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

6 authors at 2 institutions in 1 country.

Vasco Ribeiro FerreiraDepartment of Sustainable Health, University of Groningen, Campus Fryslân, Wirdumerdijk 34, 8911 CE, Leeuwarden, The Netherlands. v.ribeiro.ferreira@rug.nl.ORCID http://orcid.org/0000-0001-7060-9733
Esther MettingFaculty of Economics and Business, University of Groningen, Groningen, The Netherlands.
Joshua SchaubleDepartment of Knowledge Infrastructure, University of Groningen, Campus Fryslân, Leeuwarden, The Netherlands.
Hamed SeddighiDepartment of Sustainable Health, University of Groningen, Campus Fryslân, Wirdumerdijk 34, 8911 CE, Leeuwarden, The Netherlands.
Lise BeumelerDepartment of Sustainable Health, University of Groningen, Campus Fryslân, Wirdumerdijk 34, 8911 CE, Leeuwarden, The Netherlands.
Valentina GalloDepartment of Sustainable Health, University of Groningen, Campus Fryslân, Wirdumerdijk 34, 8911 CE, Leeuwarden, The Netherlands.
University of Groningen · NLUniversity Medical Center Groningen · NL

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundNeurological disorders remain a worldwide concern due to their increasing prevalence and mortality, combined with the lack of available treatment, in most cases. Exploring protective and risk factors associated with the development of neurological disorders will allow for improving prevention strategies. However, ascertaining neurological outcomes in population-based studies can be both complex and costly. The application of eHealth tools in research may contribute to lowering the costs and increase accessibility. The aim of this systematic review is to map existing eHealth tools assessing neurological signs and/or symptoms for epidemiological research.

methodsFour search engines (PubMed, Web of Science, Scopus & EBSCOHost) were used to retrieve articles on the development, validation, or implementation of eHealth tools to assess neurological signs and/or symptoms. The clinical and technical properties of the software tools were summarised. Due to high numbers, only software tools are presented here.

findingsA total of 42 tools were retrieved. These captured signs and/or symptoms belonging to four neurological domains: cognitive function, motor function, cranial nerves, and gait and coordination. An additional fifth category of composite tools was added. Most of the tools were available in English and were developed for smartphone device, with the remaining tools being available as web-based platforms. Less than half of the captured tools were fully validated, and only approximately half were still active at the time of data collection.

interpretationThe identified tools often presented limitations either due to language barriers or lack of proper validation. Maintenance and durability of most tools were low. The present mapping exercise offers a detailed guide for epidemiologists to identify the most appropriate eHealth tool for their research.

fundingThe current study was funded by a PhD position at the University of Groningen. No additional funding was acquired.

Indexed as

Nervous System DiseasesTelemedicineHumansNeurologistsRisk FactorsSoftwareeHealthEpidemiologyNeurological DiseasesNeurological signsNeurological symptomsSoftware

Identifiers

PMID37847293
PMCPMC10770248
OpenAlexW4387692433

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.