Evidence map›Paper›PMID 37462759›Full record

SynthesisJournal of medical systems2023

mHealth Impact on Gait and Dynamic Balance Outcomes in Neurorehabilitation: Systematic Review and Meta-analysis.

Marta Moreno-Ligero, David Lucena-Anton, Alejandro Salazar, Inmaculada Failde, Jose A Moral-Munoz

Open access · hybridAbstract readMeta-AnalysisSystematic Review
In one paragraph

Synthesis in Journal of medical systems, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
2.2field-weighted citation impact, top 12% 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

6 citing papers in PubMed, 10 citations in OpenAlex.

  1. Walking as a Window to the Brain: Redefining Gait in Neurology.Medical sciences (Basel, Switzerland) · 2026
    Review
  2. Review
  3. A review of concurrent sonified biofeedback in balance and gait training.Journal of neuroengineering and rehabilitation · 2025
    Review
  4. Review
  5. Review
  6. 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

5 authors at 2 institutions in 1 country.

Marta Moreno-LigeroDepartment of Biomedicine, Biotechnology and Public Health, Faculty of Nursing and Physiotherapy, University of Cadiz, 11009, Cadiz, Spain.
David Lucena-AntonDepartment of Nursing and Physiotherapy, Faculty of Nursing and Physiotherapy, University of Cadiz, 11009, Cadiz, Spain. david.lucena@uca.es.
Alejandro SalazarBiomedical Research and Innovation Institute of Cadiz (INiBICA), University of Cadiz, 11009, Cadiz, Spain.
Inmaculada FaildeDepartment of Biomedicine, Biotechnology and Public Health, Faculty of Nursing and Physiotherapy, University of Cadiz, 11009, Cadiz, Spain.
Jose A Moral-MunozDepartment of Nursing and Physiotherapy, Faculty of Nursing and Physiotherapy, University of Cadiz, 11009, Cadiz, Spain.
Universidad de Cádiz · ESBiomedical Research and Innovation Institute of Cadiz · ES

Funding

Ministerio de Ciencia e Innovación FPU19/04377
6 · The paper itself

Abstract

Gait and dynamic balance are two main goals in neurorehabilitation that mHealth systems could address. To analyze the impact of using mHealth systems on gait and dynamic balance outcomes in subjects with neurological disorders. Randomized controlled trials (RCT) published in PubMed, Web of Science, Scopus, and PEDro databases were searched up to April 2023. Studies including adults with neurological disorders, analyzing the effectiveness of mHealth systems on gait and dynamic balance compared with conventional therapy and/or not intervention, were included. The PEDro scale and the Cochrane Collaboration's 2.0 tool were used for the methodological quality and risk of bias assessment. The Review Manager 5.4 software was used to obtain meta-analyses. 13 RCT were included in the systematic review and 11 in the meta-analyses, involving 528 subjects. A total of 21 mobile applications were identified for gait and balance training, and to enhance physical activity behaviors. There were significant differences in gait parameters, speed by 0.10 s/m (95% confidence interval (CI)=0.07,0.13;p<0.001), cadence by 8.01 steps/min (95%CI=3.30,12.72;p<0.001), affected step length by 8.89 cm (95%CI=4.88,12.90;p<0.001), non-affected step length by 8.08 cm (5%CI=2.64,13.51;p=0.004), and in dynamic balance, Timed Up and Go by -7.15 s (95%CI=-9.30,-4.99;p<0.001), and mobility subscale of Posture Assessment Scale for Stroke by 1.71 points (95%CI=1.38,2.04;p<0.001). Our findings suggested the use of mHealth systems for improving gait in subjects with neurological disorders, but controversial results on dynamics balance recovery were obtained. However, the quality of evidence is insufficient to strongly recommend them, so further research is needed.

Indexed as

Neurological RehabilitationStrokeStroke RehabilitationTelemedicineAdultGaitHumansMotor ActivityPostural BalanceBalanceGaitmHealthMobile applicationsNeurological disordersRehabilitation

Identifiers

PMID37462759
PMCPMC10354142
OpenAlexW4384627487

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.