Evidence map›Paper›PMID 34082710›Full record

ArticleBMC geriatrics2021

Promoting neuroplasticity and neuropsychological functioning in frailty through an app-based sensorimotor training: study protocol for a randomized trial.

Florian Beier, Martin Löffler, Frauke Nees, Lucrezia Hausner, Lutz Frölich, Herta Flor

Registry-linked trialAbstract readClinical Trial Protocol
In one paragraph

Article in BMC geriatrics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT03666039 (Reversing Maladaptive Reorganization in Frail Brains), which is not on this map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
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.

NCT03666039 nacompletednot on this map

Reversing Maladaptive Reorganization in Frail Brains: Sensorimotor Training, Brain Plasticity and the Role of Brain-derived Neurotrophic Factor

TypeinterventionalSponsorCentral Institute of Mental Health, MannheimRan2017 to 2021Enrolled66ConditionsNeuroplasticity, SensorimotorArmsTrainings app
3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Trial
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

6 authors.

Florian BeierInstitute of Cognitive and Clinical Neuroscience, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Square J5, 68159, Mannheim, Germany.
Martin LöfflerInstitute of Cognitive and Clinical Neuroscience, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Square J5, 68159, Mannheim, Germany.
Frauke NeesInstitute of Cognitive and Clinical Neuroscience, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Square J5, 68159, Mannheim, Germany.
Lucrezia HausnerInstitute of Cognitive and Clinical Neuroscience, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Square J5, 68159, Mannheim, Germany.
Lutz FrölichDepartment of Geriatric Psychiatry, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany.
Herta FlorInstitute of Cognitive and Clinical Neuroscience, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Square J5, 68159, Mannheim, Germany. herta.flor@zi-mannheim.de.ORCID 0000-0003-4809-5398

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundFrailty is characterized by an age-related decline in multiple physiological systems, leading to a high vulnerability to stressors, adverse health outcomes, and low quality of life. Neuroscientific models of pathological aging emphasize the loss of sensorimotor stimulation and reduced neuromodulatory capacities as core processes in age-related cognitive and bodily decline, which may be associated with maladaptive plastic changes in the brain. We plan to increase sensorimotor stimulation in frail persons through a newly developed app-based training program and link the training trials to biological and psychological correlates of age-associated vulnerability and health indices.

methodsWe will conduct a randomized trial, applying an app-based sensorimotor home training (N = 30) in people suffering from frailty. An app-based relaxation training will serve as an active control condition (N = 30). Both interventions will last for 90 days each. The sensorimotor training includes unimodal and multimodal sensory discrimination tasks in the visual, auditory, and tactile domain, as well as sensorimotor precision tasks. The tasks will be implemented using an adaptive training algorithm and enriched with motivational components embedded in a virtual training environment. We expect a pre-post reduction of frailty status and associated functional decline related to refinement of representational maps within the sensorimotor system and improved sensorimotor function such as extremity function. Secondary analyses will study the influence of BDNF genotype as moderating variable. Additional outcomes will include measures of perceptual and cognitive functioning, quality of life as well as BDNF serum levels. Measurements will take place before training (baseline), after 60 days (assessment 1), and at the end of the training after 90 days (assessment 2). DISCUSSION: In our randomized trial, we aim to characterize a multidimensional concept of frailty and to target maladaptive behaviors and neuroplasticity using an app-based sensorimotor training. This type of intervention might provide further knowledge and new possibilities for preventing decline and preserving function in older adults.

trial registrationClinicalTrials.gov NCT03666039 . Registered 11 September 2018 - Retrospectively registered. Protocol version: Version 4 revised (issue date: 19 May 2021).

Indexed as

FrailtyMobile ApplicationsAgedAgingHumansNeuronal PlasticityQuality of LifeAgingFrailtyNeuroplasticitySensorimotor functioningTraining app

Identifiers

PMID34082710
PMCPMC8173957

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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.