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Enregistrement W4414418452 · doi:10.3389/frobt.2025.1665800

Editorial: Artificial intelligence and social robotics for mental healthcare

2025· editorial· en· W4414418452 sur OpenAlexaff
José-Antonio Cervantes, Luis-Felipe Rodríguez, J. Octavio Gutiérrez-García, Francisco Cervantes, Miguel Vargas Martín, Sandra Baldassarri

Notice bibliographique

RevueFrontiers in Robotics and AI · 2025
Typeeditorial
Langueen
DomainePsychology
ThématiqueDigital Mental Health Interventions
Établissements canadiensOntario Tech University
Organismes subventionnairesnon disponible
Mots-clésMental healthSocial robotHealth careHumanoid robotRoboticsHuman–robot interactionRobotSocial intelligenceHuman multitasking

Résumé

récupéré en direct d'OpenAlex

\section*{Artificial Intelligence and Social Robotics for Mental Healthcare}In recent decades, mental health disorders such as anxiety and depression have risen dramatically across the globe \citep{baker2023mental,ten2023prevalence}. Artificial Intelligence (AI) and Social Robotics present groundbreaking prospects that could revolutionize mental healthcare \citep{hung2025ethical}. Social robots, specifically designed for human interaction by displaying emotions and engaging in conversations, along with data-driven AI, exemplify modern advancements in sectors such as education \citep{letendre2024social} and elderly care \citep{yen2024effect}. Despite these advancements, the convergence of AI and social robotics in mental health has untapped potential and presents a plethora of unresolved challenges. For instance, there is a lack of ethical norms \citep{torras2024ethics} that regulate and guide the correct use of social robots in a wide variety of contexts, ranging from assistive care for the elderly to healthcare. Therefore, in this research topic, we have collected current contributions to the design and development of social robots as well as empirical studies on human-robot interactions focused on mental health and elderly care.\section*{Articles of the research topic}The articles contributing to the design and evaluation of social robots (supported by artificial intelligence) for mental healthcare included in this research topic are as follows:\href{https://www.frontiersin.org/journals/robotics-and-ai/articles/10.3389/frobt.2025.1305685/full}{Aoki et al.} focused on how different forms of humanoid robot vitality (namely gentle and rude) impact human performance with an emphasis on mental workload. Particularly, their study explored human performance and emotional states while engaging in demanding cognitive multitasking in the presence of social robots. Experiments involving 29 participants were conducted with an iCub humanoid robot continuously displaying vitality forms through coordinated movements of its arms, torso, and head. The participants interacted with the iCub robot while performing a task battery simulating cognitive challenges encountered by aircraft pilots. Whereas some participants interacted with iCub exhibiting a rude vitality form, the others interacted with iCube exhibiting a gentle vitality form. While interacting with the robot, \href{https://www.frontiersin.org/journals/robotics-and-ai/articles/10.3389/frobt.2025.1305685/full}{Aoki et al.} recorded participants' facial expressions and electrodermal activity to assess their mental workload. Their results revealed that a robot exhibiting a gentle vitality form fostered a more positive and lower mental workload than one exhibiting a rude vitality form. \href{https://www.frontiersin.org/journals/robotics-and-ai/articles/10.3389/frobt.2025.1305685/full}{Aoki et al.}'s results offer useful insights into stress-free human-robot interaction supporting mental well-being. \href{https://www.frontiersin.org/journals/robotics-and-ai/articles/10.3389/frobt.2025.1560214/full}{Hung et al.} present an empirical study involving 46 elderly participants (from 60 to over 100 years old) on the use of social robots in the mental health area. Their study aimed to identify ethical challenges and propose mitigation strategies for implementing social robots in long-term care settings. To achieve these objectives, their research involved human-robot interaction between elderly individuals and social robots (namely Paro and Lovo robots) in separate studies. As a result of this empirical study, four key ethical challenges associated with the implementation of social robots in long-term care facilities were identified: inequitable access, participant consent, human care substitution, and concerns about infantilization. In addition, their work discussed mitigation strategies to address ethical support for older adults in long-term care settings.\href{https://www.frontiersin.org/journals/robotics-and-ai/articles/10.3389/frobt.2025.1529421/full}{Dong et al.} explored children's understanding of social robots endowed with artificial intelligence capabilities and how social robots promote learning engagement within the context of science, technology, engineering, arts, and mathematics (STEAM) education. Motivated by a lack of research on the effectiveness of social robots into primary and secondary education in informal settings, their objective was to design and evaluate a theater afterschool program (supported by social robots) to promote STEAM education and foster embodied learning. Their study took place in an elementary school involving 38 children. The children interacted with different robots, ranging from humanoid robots with human-like facial expressions to stereotypical robots. Among the participants, there were children with autism spectrum disorder, which (according to \href{https://www.frontiersin.org/journals/robotics-and-ai/articles/10.3389/frobt.2025.1529421/full}{Dong et al.}'s results) improved their social and emotional skills by interacting with social robots. \href{https://www.frontiersin.org/journals/robotics-and-ai/articles/10.3389/frobt.2024.1426717/full} {Liu et al.} present an empirical study on the influence of behaviorally anthropomorphic service robots on customer variety-seeking behavior. Their study aimed to identify the mechanisms through which robot anthropomorphism affects consumer choices, specifically examining social presence as a mediator and decision-making context as a moderator. In pursuit of these goals, their research involved a series of six experiments with ordinary consumers interacting with service robot scenarios. They found that higher behavioral anthropomorphism significantly increases variety-seeking, a relationship partially mediated by social presence. Additionally, the influence of social presence on variety-seeking was significantly stronger in public decision-making contexts. Their work provides recommendations for strategically deploying service robots to enhance customer engagement. \href{https://www.frontiersin.org/journals/robotics-and-ai/articles/10.3389/frobt.2024.1426717/full}{Liu et al.}'s results have implications related to mental healthcare because social, anthropomorphic robots should deliver services (e.g., psychological therapies and counseling), expressing emotions (as expected by users) in order to establish both a social and an emotional connection. \href{https://www.frontiersin.org/journals/robotics-and-ai/articles/10.3389/frobt.2024.1426717/full}{Kamide et al.} carried out a psychological evaluation of an avatar robot in two distinct regions (Dubai and Japan) to explore how cultural background influences psychological aspects attributed to robot avatars. Furthermore, \href{https://www.frontiersin.org/journals/robotics-and-ai/articles/10.3389/frobt.2024.1426717/full}{Kamide et al.} aimed at understanding whether (avatar) robots' fundamental psychological impressions such as warmth, competence, and discomfort are essential for developing more culturally adapted human-robot interactions. Specifically, they conducted two studies: the first involved a virtual robot used as an avatar, and the second involved a physical robot. The results suggest that participants from Dubai were more comfortable interacting with a virtual robot, whereas participants from Japan were more comfortable interacting with a physical robot. \href{https://www.frontiersin.org/journals/robotics-and-ai/articles/10.3389/frobt.2024.1426717/full}{Kamide et al.} also discussed the implications of these findings and the relationship between robot evaluations and cultural background, which is a relevant aspect for social robots designed for mental healthcare in multicultural domains.We believe this collection of articles offers valuable insights supported by empirical evidence to further advance in social robots for mental healthcare. We hope this research topic motivates the readers to embark on and contribute to this fascinating research area.

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction distillée sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.

score de la tête « metaresearch » (Codex)0,000
score de la tête « metaresearch » (Gemma)0,000
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesMéta-épidémiologie (sens strict)
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Sans objet · Signal consensuel: Sans objet
GenreSignal candidat: Éditorial · Signal consensuel: Éditorial
Score de désaccord entre enseignants0,061
Score d'incertitude au seuil1,000

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0000,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0010,000
Bibliométrie0,0000,000
Études des sciences et des technologies0,0000,000
Communication savante0,0000,000
Science ouverte0,0000,000
Intégrité de la recherche0,0010,001
Charge utile insuffisante (le modèle a refusé de juger)0,0000,000

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,032
Tête enseignante GPT0,381
Écart entre enseignants0,348 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.

Devis d'étudeSans objet
Domainenon disponible
GenreÉditorial

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations1
Publié2025
Routes d'admission1
Résumé présentoui

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