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SYSTEMATIC REVIEW article
Front. Psychiatry
Sec. Digital Mental Health
Volume 16 - 2025 |
doi: 10.3389/fpsyt.2025.1506776
Social Robots in Adult Psychiatry: A Summary of Utilisation and Impact
Provisionally accepted- Medical University of Graz, Graz, Austria
Social robots are increasingly becoming more prevalent in healthcare, including nursing, geriatric care, and treatment for children on the autism spectrum. Their assistance is believed to hold promise in mitigating the effects of staffing shortages and enhancing current mental health treatment. Nevertheless, the application of social robotics in psychiatry remains restricted and controversial. This scoping review aims to provide an overview of the literature on social robots in adult psychiatry concerning their use, effects, and acceptability. We conducted a literature search, including PubMed and PsycINFO, to identify literature on robot interventions for adult psychiatric patients. Methodological quality was assessed using the 'Mixed Methods Appraisal Tool'. Usage and target variables were unique to every included original study (N = 7) and suggested a wide range of possible implications for patient treatment and care. Social robots were used to reduce symptoms, improve functioning, and gain insights into characteristic features of specific mental health conditions. The included studies were concerned with the following diagnoses: schizophrenia (N = 3), autism spectrum disorder (N = 2), and intellectual disability (N = 2). The sample sizes were too small to generalise the outcome, but overall trends showed some positive effects on the selected symptoms. Observations and participant feedback suggested high acceptance and enjoyment of the users. Although the evidence regarding the benefits of robotic interventions in adult psychiatry is still low, it suffices to assume that investing in larger, randomised, and controlled trials is worthwhile and promising.
Keywords: social robot, Mental Health, Schizophrenia, Autism Spectrum Disoder, Intellectual Disability, Digital Health
Received: 06 Oct 2024; Accepted: 20 Jan 2025.
Copyright: © 2025 Kling, Haeussl, Dalkner, Fellendorf, Lenger, Finner, Ilić, Smolak, Stojec, Zwigl and Reininghaus. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence:
Alfred Haeussl, Medical University of Graz, Graz, Austria
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