Evidence map›Paper›PMID 41710267›Full record

ArticleFrontiers in digital health2026

Patient's healthcare needs in the traditional and technological neuro-rehabilitation field: a survey methodological approach.

Elena Beani, Alessio Fasano, Maria Cristina Mauro, Marco Germanotta, Monia Andrea Papa, Silvana Quaglini, Gaetano Maria Celardo, Federica Camuncoli, Giovanni Cioni, Francesca Fedeli and 9 more

Abstract read
In one paragraph

Article in Frontiers in digital health, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the 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.

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

1 citing paper in PubMed.

  1. Article
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

19 authors.

Elena BeaniDepartment of Developmental Neuroscience, IRCCS Fondazione Stella Maris, Pisa, Italy.
Alessio FasanoIRCCS Fondazione Don Carlo Gnocchi, Florence, Italy.
Maria Cristina MauroIRCCS Fondazione Don Carlo Gnocchi, Florence, Italy.
Marco GermanottaIRCCS Fondazione Don Carlo Gnocchi, Florence, Italy.
Monia Andrea PapaIRCCS Fondazione Don Carlo Gnocchi, Florence, Italy.
Silvana QuagliniDepartment of Electrical, Computer and Biomedical Engineering, University of Pavia, Pavia, Italy.
Gaetano Maria CelardoDepartment of Clinical and Experimental Medicine, University of Pisa, Pisa, Italy.
Federica CamuncoliDepartment of Developmental Neuroscience, IRCCS Fondazione Stella Maris, Pisa, Italy.
Giovanni CioniDepartment of Developmental Neuroscience, IRCCS Fondazione Stella Maris, Pisa, Italy.
Francesca FedeliFightthestroke Foundation, Milan, Italy.
Paolo FogarFNATC, Federazione Nazionale Associazioni Trauma Cranico, Pordenone, Italy.
Giuseppe TurchettiInstitute of Management, Scuola Superiore Sant'Anna, Pisa, Italy.
Leopoldo TriesteInstitute of Management, Scuola Superiore Sant'Anna, Pisa, Italy.
Christian CiprianiThe BioRobotics Institute, Scuola Superiore Sant'Anna, Pisa, Italy.
Giovanni ComandèLIDER-Lab, University Scuola Superiore Sant'Anna, Pisa, Italy.
Stefano DenicolaiITIR-Institute for Transformative Innovation Research, University of Pavia, Pavia, Italy.
Giuseppina SgandurraDepartment of Developmental Neuroscience, IRCCS Fondazione Stella Maris, Pisa, Italy.
Irene Giovanna AprileIRCCS Fondazione Don Carlo Gnocchi, Florence, Italy.
Mission 1 Fit4Med Consortium

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: In recent years, many robotic devices and technologies have been developed to support rehabilitation. These technologies have started penetrating clinical practice, and healthcare practitioners have started to be trained in their use, but only in selected healthcare environments. As a matter of fact, several barriers still exist for a wider dissemination of robotics-assisted rehabilitation, and little is known about the real needs of patients and their caregivers when they undertake a rehabilitation process. To address this issue a survey has been developed as a preparatory step for the effective use of robots and technologies in rehabilitation. The survey aims to identify and highlight patient's needs which are often unexpressed, enabling the co-creation of future rehabilitation solutions with patients and their caregivers. Methods: The methodology for developing the survey involves reaching out to as many people with neurological disorders as possible, understanding their needs in relation to specific functional areas, and using innovative methods such as online platforms to maximize outreach. Common functional domains for different neurological conditions were developed with a holistic view of people with disabilities, using the categories and domains defined by the new International Classification of Functioning, Disability and Health (ICF). Results: Surveys addressed to patients, caregivers of adults and of children were developed by sharing the same content and exploring the rehabilitation carried out, both traditional and technological, with particular focus on the willingness to adopt technology, if not yet integrated in the current care. Discussion: This approach aims to develop future rehabilitation strategies that utilize the increasing availability of neurorehabilitation technologies in a more effective and personalized way. This study highlights the importance of focusing on the fundamental role of addressing patients' needs in driving innovation and adoption of neurorehabilitation technologies, prior to clinical effectiveness. This is pivotal in identifying the specific desiderata, to co-create together with the end users new solutions to empower the patient-professional relationship and optimize the satisfaction related to the treatment and, as a consequence, the adherence to the intervention and its results.

Indexed as

healthcare needsneurorehabilitationpatients' needssurveytechnological rehabilitation

Identifiers

PMID41710267
PMCPMC12910480

What OpenQuestion holds

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LicenceCC BY
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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.