Evidence map›Paper›PMID 41113200›Full record

ArticleFrontiers in psychiatry2025

The use of the social robot NAO in medical settings: how to facilitate interactions between healthcare professionals and patients with autism spectrum disorder.

Federico Biagi, Cristina Iani, Luigi Biagiotti

Abstract read
In one paragraph

Article in Frontiers in psychiatry, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

3 authors.

Federico BiagiDepartment of Engineering "Enzo Ferrari", University of Modena and Reggio Emilia, Modena, Italy.
Cristina IaniDepartment of Surgery, Medicine, Dentistry and Morphological Sciences, University of Modena and Reggio Emilia, Reggio Emilia, Italy.
Luigi BiagiottiDepartment of Engineering "Enzo Ferrari", University of Modena and Reggio Emilia, Modena, Italy.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objectives: This study investigates how to facilitate the use of the social robot NAO in medical settings to support interactions with children diagnosed with Autism Spectrum Disorder (ASD). The objective was to develop intuitive control methods that enable healthcare professionals to easily integrate the robot into clinical practice. Methods: Two control modes were designed: Puppet mode, where clinicians manually operate the robot via a graphical console, and Assistant mode, where a Large Language Model translates clinicians' spoken requests into robot actions and dialogue. Twenty-three doctors evaluated both modes through video demonstrations and completed questionnaires assessing usability, usefulness, and ethical acceptability. Results: Both modes were considered effective and user-friendly. Assistant mode was perceived as more intuitive and adaptable, facilitating seamless interaction, whereas Puppet mode was judged slightly more reassuring for patients and somewhat more appropriate in terms of robot actions. Conclusion: Overall, both approaches were positively received, with Assistant mode emerging as the preferred option for integration into clinical workflows due to its perceived simplicity and flexibility. These findings highlight clinicians' positive perceptions of two novel control modes and emphasize NAO's potential to enhance patient engagement and reduce stress. Further empirical validation with children in real clinical trials is warranted to confirm these benefits and optimize robot-assisted interventions in ASD care.

Indexed as

autism spectrum disorderhealthcare professionalsNAOpatientssocial robot

Identifiers

PMID41113200
PMCPMC12528083

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.