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      Technological risks and ethical implications of using robots in long-term care

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          Abstract

          Introduction

          The pandemic provides a unique opportunity to examine new directions in innovative technological approaches in long-term care (LTC) homes. While robotics could enhance staff capacity to provide care, there are potential technology risks and ethical concerns involved in technology use among older people residing in communal aged care homes. This qualitative descriptive study explores the technological risks and ethical issues associated with the adoption of robots in the specific context of LTC homes.

          Methods

          The research team including patient and family partners employed purposive and snowballing methods to recruit 30 LTC participants: frontline interdisciplinary staff, operational leaders, residents and family members, and ethics experts in dementia care. Semi-structured interviews were conducted. Thematic analysis was performed to identify themes that capture empirical experiences and perspectives of a diverse group of LTC stakeholders about robotic use.

          Results

          Technological risks include safety, increased workload, privacy, cost and social justice, and human connection. The findings offer practical insights based on the LTC perspective to contribute to the robot ethics literature. We propose a list of pragmatic recommendations, focusing on six principles (ETHICS): Engagement of stakeholders, Technology benefit and risk assessment, Harm mitigation, Individual autonomy, Cultural safety and justice, Support of privacy.

          Conclusions

          There is both a growing interest as well as fear in using robotics in LTC. Practice leaders need to reflect on ethical considerations and engage relevant stakeholders in making technology decisions for everyday care.

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          Most cited references35

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          Granny and the robots: ethical issues in robot care for the elderly

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            Optimising costs in reducing rate of falls in older people with the improvement of balance by means of vestibular rehabilitation (ReFOVeRe study): a randomized controlled trial comparing computerised dynamic posturography vs mobile vibrotactile posturography system

            Background Accidental falls, especially for the elderly, are a major health issue. Balance disorders are one of their main causes. Vestibular rehabilitation (VR) has proven to be useful in improving balance of elderly patients with instability. Its major handicap is probably its cost, which has prevented its generalisation. So, we have designed a clinical trial with posturographic VR, to assess the optimum number of sessions necessary for a substantial improvement and to compare computerised dynamic posturography (CDP) (visual feedback) and mobile posturography (vibrotactile feedback). Methods Design: randomized controlled trial. It is an experimental study, single-center, open, randomized (balanced blocks of patients) in four branches in parallel, in 220 elderly patients with high risk of falls; follow-up period: twelve months. Setting: Department of Otorhinolaryngology of a tertiary referral hospital. Participants: people over 65 years, fulfilling two or more of the following requirements: a) at least one fall in the last twelve months. b) take at least 16 s or require some support in perform the “timed up and go” test. c) a percentage of average balance in the sensory organization test (SOT) of the CDP  60%. Intervention: Four differents protocols of vestibular rehabilitation (randomization of the patients). Main outcome measure: The percentage of average balance in the SOT-CDP. Secondary measures: time and supports in the “timed up and go” test, scores of the CDP and Vertiguard, and rate of falls. Discussion Posturographic VR has been proven to be useful for improving balance and reducing the number of falls among the aged. However, its elevated cost has limited its use. It is possible to implement two strategies that improve the cost-benefit of posturography. The first involves optimising the number of rehabilitation sessions; the second is based on the use of cheaper posturography systems. Trial registration ClinicalTrials.gov identifier: NCT03034655. Registered on 25 January 2017.
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              Your Robot Therapist Will See You Now: Ethical Implications of Embodied Artificial Intelligence in Psychiatry, Psychology, and Psychotherapy

              Background Research in embodied artificial intelligence (AI) has increasing clinical relevance for therapeutic applications in mental health services. With innovations ranging from ‘virtual psychotherapists’ to social robots in dementia care and autism disorder, to robots for sexual disorders, artificially intelligent virtual and robotic agents are increasingly taking on high-level therapeutic interventions that used to be offered exclusively by highly trained, skilled health professionals. In order to enable responsible clinical implementation, ethical and social implications of the increasing use of embodied AI in mental health need to be identified and addressed. Objective This paper assesses the ethical and social implications of translating embodied AI applications into mental health care across the fields of Psychiatry, Psychology and Psychotherapy. Building on this analysis, it develops a set of preliminary recommendations on how to address ethical and social challenges in current and future applications of embodied AI. Methods Based on a thematic literature search and established principles of medical ethics, an analysis of the ethical and social aspects of currently embodied AI applications was conducted across the fields of Psychiatry, Psychology, and Psychotherapy. To enable a comprehensive evaluation, the analysis was structured around the following three steps: assessment of potential benefits; analysis of overarching ethical issues and concerns; discussion of specific ethical and social issues of the interventions. Results From an ethical perspective, important benefits of embodied AI applications in mental health include new modes of treatment, opportunities to engage hard-to-reach populations, better patient response, and freeing up time for physicians. Overarching ethical issues and concerns include: harm prevention and various questions of data ethics; a lack of guidance on development of AI applications, their clinical integration and training of health professionals; ‘gaps’ in ethical and regulatory frameworks; the potential for misuse including using the technologies to replace established services, thereby potentially exacerbating existing health inequalities. Specific challenges identified and discussed in the application of embodied AI include: matters of risk-assessment, referrals, and supervision; the need to respect and protect patient autonomy; the role of non-human therapy; transparency in the use of algorithms; and specific concerns regarding long-term effects of these applications on understandings of illness and the human condition. Conclusions We argue that embodied AI is a promising approach across the field of mental health; however, further research is needed to address the broader ethical and societal concerns of these technologies to negotiate best research and medical practices in innovative mental health care. We conclude by indicating areas of future research and developing recommendations for high-priority areas in need of concrete ethical guidance.
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                Author and article information

                Journal
                J Rehabil Assist Technol Eng
                J Rehabil Assist Technol Eng
                spjrt
                JRT
                Journal of Rehabilitation and Assistive Technologies Engineering
                SAGE Publications (Sage UK: London, England )
                2055-6683
                17 June 2022
                Jan-Dec 2022
                : 9
                : 20556683221106917
                Affiliations
                [1 ]School of Nursing, Ringgold 8166, universityUniversity of British Columbia; , Vancouver, BC, Canada
                [2 ]Community Engagement Advisory Network, Vancouver, BC, Canada
                [3 ]Ringgold 453480, universityAlzheimer Society of British Columbia; , Vancouver, BC, Canada
                [4 ]UBC IDEA Lab, School of Nursing, Ringgold 8166, universityUniversity of British Columbia; , Vancouver, BC, Canada
                Author notes
                [*]Lillian Hung, School of Nursing, University of British Columbia, T201-2211 Wesbrook Mall, Vancouver, BC V6T 2B5, Canada. Email: lillian.hung@ 123456ubc.ca
                Author information
                https://orcid.org/0000-0002-7916-2939
                Article
                10.1177_20556683221106917
                10.1177/20556683221106917
                9208036
                35733613
                11f8979b-b41b-4493-b481-04e50aeac465
                © The Author(s) 2022

                This article is distributed under the terms of the Creative Commons Attribution-NonCommercial 4.0 License ( https://creativecommons.org/licenses/by-nc/4.0/) which permits non-commercial use, reproduction and distribution of the work without further permission provided the original work is attributed as specified on the SAGE and Open Access pages ( https://us.sagepub.com/en-us/nam/open-access-at-sage).

                History
                Funding
                Funded by: University of British Columbia Hampton Fund;
                Funded by: Canada Research Chair award;
                Categories
                Original Research Article
                Custom metadata
                ts10
                January-December 2022

                robots,ethics,long term care,assistive technology,risks,dementia,qualitative study,senior care,social connection

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