Evidence map›Paper›PMID 40205389›Full record

ArticleJournal of neuroengineering and rehabilitation2025

Healthcare practitioners and robotic-assisted rehabilitation: understanding needs and barriers.

Giovanna Nicora, Enea Parimbelli, Maria Cristina Mauro, Francesca Falchini, Marco Germanotta, Alessio Fasano, Giuseppina Sgandurra, Elena Beani, Emanuele Gruppioni, Francesca Bugané and 3 more

Abstract read
In one paragraph

Article in Journal of neuroengineering and rehabilitation, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing 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

7 citing papers in PubMed.

  1. Review
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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

13 authors.

Giovanna NicoraDepartment of Electrical, Computer and Biomedical Engineering, University of Pavia, Pavia, Italy. giovanna.nicora@unipv.it.
Enea ParimbelliDepartment of Electrical, Computer and Biomedical Engineering, University of Pavia, Pavia, Italy.
Maria Cristina MauroIRCCS Fondazione Don Carlo Gnocchi, Florence, Italy.
Francesca FalchiniIRCCS Fondazione Don Carlo Gnocchi, Florence, Italy.
Marco GermanottaIRCCS Fondazione Don Carlo Gnocchi, Florence, Italy.
Alessio FasanoIRCCS Fondazione Don Carlo Gnocchi, Florence, Italy.
Giuseppina SgandurraDepartment of Developmental Neuroscience, IRCCS Fondazione Stella Maris, Pisa, Italy.
Elena BeaniDepartment of Developmental Neuroscience, IRCCS Fondazione Stella Maris, Pisa, Italy.
Emanuele GruppioniCentro Protesi INAIL, Istituto Nazionale Assicurazione Contro Gli Infortuni Sul Lavoro, Bologna, Italy.
Francesca BuganéCentro Protesi INAIL, Istituto Nazionale Assicurazione Contro Gli Infortuni Sul Lavoro, Bologna, Italy.
Irene Giovanna Aprile *IRCCS Fondazione Don Carlo Gnocchi, Florence, Italy.
Silvana Quaglini *Department of Electrical, Computer and Biomedical Engineering, University of Pavia, Pavia, Italy.
Mission 1 Fit4MedRob Consortium

Funding

Ministero dell'Istruzione, dell'Università e della Ricerca #PNC0000007
6 · The paper itself

Abstract

backgroundsIn recent years, numerous robotic devices, together with allied technologies, have been developed to support rehabilitation, both in research settings and industry. Although robotic-assisted rehabilitation and related technologies hold significant promise for supporting healthcare practitioners and enhancing patient care, their use in clinical practice remains limited. One of the motivations could be that final users' needs have not been given due consideration so far. As a matter of fact, understanding user needs and perceptions is crucial for designing these technological devices and for creating new organizational models within hospitals aiming to establish and maintain robotics-assisted rehabilitation gyms.

methodsWe developed and distributed an online survey to the Italian community of healthcare practitioners working in rehabilitation, to depict the current landscape of robotic-assisted rehabilitation and to understand their opinions and demands across various domains and diseases. The questionnaire is divided into two main parts. The first section pertains to the respondents' demographics and professional experience. The second part includes questions about eight different categories of rehabilitative devices. For each category, practitioners can indicate whether they use a device in their practice, their perceptions, and any perceived barriers. Additionally, they can fill out a System Usability Scale for a specific device in that category.

resultsWe collected answers from 423 Italian rehabilitation professionals, including various clinical roles, that revealed significant insights into the use of robotics in rehabilitation. Gender distribution shows a high prevalence of female professionals. 40% of respondents reported being unfamiliar with any robotics devices. Advanced treadmills are the most known and used robots. Generally, usage and experience with devices are associated with positive attitudes towards robotics-assisted rehabilitation. Lack of financial resources and scientific evidence, as well as lack of opportunities and training, are the most reported barriers.

conclusionsDespite a general positivity towards technology, there is a substantial lack of awareness about rehabilitation devices among professionals. The survey highlights the need for enhanced training and education on robotics in rehabilitation programs. Additionally, the limited focus on home rehabilitation is noted. The study emphasizes the importance of verifying both the effectiveness and economic sustainability of robotic devices in clinical practice.

Indexed as

Attitude of Health PersonnelHealth PersonnelRehabilitationRoboticsAdultFemaleHumansItalyMaleMiddle AgedSurveys and QuestionnairesQuestionnaireRobotsSurveySUSTechnology adoptionUser needs

Identifiers

PMID40205389
PMCPMC11983797

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.