The Effect of Robot Attentional Behaviors on User Perceptions and Behaviors in a Simulated Health Care Interaction: Randomized Controlled Trial

A Robotic Companion for Psychological Well-being: A Long-term Investigation of Companionship and Therapeutic Alliance

Social support plays a crucial role in managing and enhancing one's mental health and well-being. In order to explore the role of a robot's companion-like behavior on its therapeutic interventions, we conducted an eight-week-long deployment study with seventy participants to compare the impact of (1) a control robot with only assistant-like skills, (2) a coach-like robot with additional instructive positive psychology interventions, and (3) a companion-like robot that delivered the same interventions in a peer-like and supportive manner. The companion-like robot was shown to be the most effective in building a positive therapeutic alliance with people, enhancing participants' well-being and readiness for change. Our work offers valuable insights into how companion AI agents could further enhance the efficacy of the mental health interventions by strengthening their therapeutic alliance with people for long-term mental health support.

Artificial intelligence technologies and compassion in healthcare: A systematic scoping review

Background

Advances in artificial intelligence (AI) technologies, together with the availability of big data in society, creates uncertainties about how these developments will affect healthcare systems worldwide. Compassion is essential for high-quality healthcare and research shows how prosocial caring behaviors benefit human health and societies. However, the possible association between AI technologies and compassion is under conceptualized and underexplored.

Objectives

The aim of this scoping review is to provide a comprehensive depth and a balanced perspective of the emerging topic of AI technologies and compassion, to inform future research and practice. The review questions were: How is compassion discussed in relation to AI technologies in healthcare? How are AI technologies being used to enhance compassion in healthcare? What are the gaps in current knowledge and unexplored potential? What are the key areas where AI technologies could support compassion in healthcare?

Materials and methods

A systematic scoping review following five steps of Joanna Briggs Institute methodology. Presentation of the scoping review conforms with PRISMA-ScR (Preferred Reporting Items for Systematic reviews and Meta-Analyses extension for Scoping Reviews). Eligibility criteria were defined according to 3 concept constructs (AI technologies, compassion, healthcare) developed from the literature and informed by medical subject headings (MeSH) and key words for the electronic searches. Sources of evidence were Web of Science and PubMed databases, articles published in English language 2011-2022. Articles were screened by title/abstract using inclusion/exclusion criteria. Data extracted (author, date of publication, type of article, aim/context of healthcare, key relevant findings, country) was charted using data tables. Thematic analysis used an inductive-deductive approach to generate code categories from the review questions and the data. A multidisciplinary team assessed themes for resonance and relevance to research and practice.

Results

Searches identified 3,124 articles. A total of 197 were included after screening. The number of articles has increased over 10 years (2011, n = 1 to 2021, n = 47 and from Jan-Aug 2022 n = 35 articles). Overarching themes related to the review questions were: (1) Developments and debates (7 themes) Concerns about AI ethics, healthcare jobs, and loss of empathy; Human-centered design of AI technologies for healthcare; Optimistic speculation AI technologies will address care gaps; Interrogation of what it means to be human and to care; Recognition of future potential for patient monitoring, virtual proximity, and access to healthcare; Calls for curricula development and healthcare professional education; Implementation of AI applications to enhance health and wellbeing of the healthcare workforce. (2) How AI technologies enhance compassion (10 themes) Empathetic awareness; Empathetic response and relational behavior; Communication skills; Health coaching; Therapeutic interventions; Moral development learning; Clinical knowledge and clinical assessment; Healthcare quality assessment; Therapeutic bond and therapeutic alliance; Providing health information and advice. (3) Gaps in knowledge (4 themes) Educational effectiveness of AI-assisted learning; Patient diversity and AI technologies; Implementation of AI technologies in education and practice settings; Safety and clinical effectiveness of AI technologies. (4) Key areas for development (3 themes) Enriching education, learning and clinical practice; Extending healing spaces; Enhancing healing relationships.

Conclusion

There is an association between AI technologies and compassion in healthcare and interest in this association has grown internationally over the last decade. In a range of healthcare contexts, AI technologies are being used to enhance empathetic awareness; empathetic response and relational behavior; communication skills; health coaching; therapeutic interventions; moral development learning; clinical knowledge and clinical assessment; healthcare quality assessment; therapeutic bond and therapeutic alliance; and to provide health information and advice. The findings inform a reconceptualization of compassion as a human-AI system of intelligent caring comprising six elements: (1) Awareness of suffering (e.g., pain, distress, risk, disadvantage); (2) Understanding the suffering (significance, context, rights, responsibilities etc.); (3) Connecting with the suffering (e.g., verbal, physical, signs and symbols); (4) Making a judgment about the suffering (the need to act); (5) Responding with an intention to alleviate the suffering; (6) Attention to the effect and outcomes of the response. These elements can operate at an individual (human or machine) and collective systems level (healthcare organizations or systems) as a cyclical system to alleviate different types of suffering. New and novel approaches to human-AI intelligent caring could enrich education, learning, and clinical practice; extend healing spaces; and enhance healing relationships.

Implications

In a complex adaptive system such as healthcare, human-AI intelligent caring will need to be implemented, not as an ideology, but through strategic choices, incentives, regulation, professional education, and training, as well as through joined up thinking about human-AI intelligent caring. Research funders can encourage research and development into the topic of AI technologies and compassion as a system of human-AI intelligent caring. Educators, technologists, and health professionals can inform themselves about the system of human-AI intelligent caring.

A social robot-based platform for health behavior change toward prevention of childhood obesity

Childhood obesity is a major public health challenge which is linked with the occurrence of diseases such as diabetes and cancer. The COVID-19 pandemic has forced changes to the lifestyle behaviors of children, thereby making the risk of developing obesity even greater. Novel preventive tools and approaches are required to fight childhood obesity. We present a social robot-based platform which utilizes an interactive motivational strategy in communication with children, collects self-reports through the touch of tangible objects, and processes behavioral data, aiming to: (a) screen and assess the behaviors of children in the dimensions of physical activity, diet, and education, and (b) recommend individualized goals for health behavior change. The platform was integrated through a microservice architecture within a multi-component system targeting childhood obesity prevention. The platform was evaluated in an experimental study with 30 children aged 9-12 years in a real-life school setting, showing children's acceptance to use it, and an 80% success rate in achieving weekly personal health goals recommended by the social robot-based platform. The results provide preliminary evidence on the implementation feasibility and potential of the social robot-based platform toward the betterment of children's health behaviors in the context of childhood obesity prevention. Further rigorous longer-term studies are required.

Technical Methods for Social Robots in Museum Settings: An Overview of the Literature

Robots have become increasingly present in our daily lives, and we see several settings wherein this technology might positively impact people. One of these settings, and the focus of this paper, is the museum. This paper provides an overview of the literature on how robots can help people within the museum context and explores the state-of-the-art methods or technologies employed by researchers to allow robots to interact within this environment. Five key features were found to be essential to integrate into social museum robots: social navigation (including safe and successful motions); perception (how robots can use visual skills to understand the environment); speech (verbal communication with visitors); gestures (non-verbal cues) and behavior generation (how the robot combines the four skills to adopt different behaviors). The paper subsequently analyzes the integration of these features into robotic systems for a complete and appropriate collection of behaviors in the museum setting.

Have I Got the Power? Analysing and Reporting Statistical Power in HRI

This article presents a discussion of the importance of power analyses, providing an overview of when power analyses should be run in the context of the field of Human-Robot Interaction, as well as some examples of how to perform a power analysis. This work was motivated by the observation that the majority of papers published in the proceedings of recent HRI conferences did not report conducting a power analysis; an observation that has concerning implications for many conclusions drawn by these studies. This work is intended to raise awareness and encourage researchers to conduct power analyses when designing research studies using human participants.

Robot Pets as "Serious Toys"- Activating Social and Emotional Experiences of Elderly People

When robots are used as part of meaningful play, for example to enhance wellbeing, they can be considered "serious toys". Our study examines the potential of robotic pet toys viewed as companions, which activate social and emotional experiences of the elderly by increasing their wellbeing. In order to study the benefits of using Golden Pup, a commercial robot dog, we designed and performed a research intervention at a senior day activity center with 10 participants of ages 65-80+ years who were joined by a playful group of preschoolers. In this study, we were mainly interested in the firsthand user experiences.This study suggests how robotic pets can be used to activate the social and emotional experiences of elderly, and illustrated the role of building a relationship with a robotic pet. We present novel results on how a robot dog with a natural interface (NUI) may be used to evoke social and emotional experiences in older adults as part of playful, intergenerational group activities.

Older adults' experiences and perceptions of living with Bomy, an assistive dailycare robot: a qualitative study

An aging global population and preference for aging-in-place pose the opportunity for home-based robots to assist older adults with their daily routines. However, there is limited research into the experiences of older adults using robots in their own homes. In this descriptive qualitative feasibility study, older self-supporting and community-dwelling adults with various age-related health needs used Bomy, a dailycare robot in their homes for up to one week. The study explored the usefulness of the robot and participants' perceptions and experiences of using it. Bomy reminded them of daily activities and delivered cognitive stimulation games. Semi-structured in-person interviews were conducted, and data were analyzed thematically. Findings revealed an acceptance toward robots and the value of assistive dailycare robots. Participants perceived Bomy as a companion and made suggestions for improvement, including resolving technical issues associated with long-term use. Future functions should be personalizable, to accommodate each user's health needs and could also include smoke detection and reading aloud functions. Dailycare robots show promising potential in elderly care, especially in providing reminders for medication, health and wellbeing. This study highlights the importance of co-design and testing robotics in the environments for which they have been developed. Widespread implementation of Bomy might be feasible in the future, with some further adjustments.

Guidance for Acupuncture Robot with Potentially Utilizing Medical Robotic Technologies

Acupuncture is gaining increasing attention and recognition all over the world. However, a lot of physical labor is paid by acupuncturists. It is natural to resort to a robot which can improve the accuracy as well as the efficacy of therapy. Several teams have separately developed real acupuncture robots or related technologies and even went to the stage of clinical trial and then achieved success commercially. A completed clinical practical acupuncture robot is not far from reach with the combination of existing mature medical robotic technologies. A hand-eye-brain coordination framework is proposed in this review to integrate the potential utilizing technologies including force feedback, binocular vision, and automatic prescription. We should take acupuncture prescription with artificial intelligence and future development trends into account and make a feasible choice in development of modern acupuncture.

What Makes a Robot Social? A Review of Social Robots from Science Fiction to a Home or Hospital Near You

Purpose of Review

We provide an outlook on the definitions, laboratory research, and applications of social robots, with an aim to understand what makes a robot social—in the eyes of science and the general public.

Recent Findings

Social robots demonstrate their potential when deployed within contexts appropriate to their form and functions. Some examples include companions for the elderly and cognitively impaired individuals, robots within educational settings, and as tools to support cognitive and behavioural change interventions.

Summary

Science fiction has inspired us to conceive of a future with autonomous robots helping with every aspect of our daily lives, although the robots we are familiar with through film and literature remain a vision of the distant future. While there are still miles to go before robots become a regular feature within our social spaces, rapid progress in social robotics research, aided by the social sciences, is helping to move us closer to this reality.

Acceptability of Using a Robotic Nursing Assistant in Health Care Environments: Experimental Pilot Study

BACKGROUND

According to the US Bureau of Labor Statistics, nurses will be the largest labor pool in the United States by 2022, and more than 1.1 million nursing positions have to be filled by then in order to avoid a nursing shortage. In addition, the incidence rate of musculoskeletal disorders in nurses is above average in comparison with other occupations. Robot-assisted health care has the potential to alleviate the nursing shortage by automating mundane and routine nursing tasks. Furthermore, robots in health care environments may assist with safe patient mobility and handling and may thereby reduce the likelihood of musculoskeletal disorders.

OBJECTIVE

This pilot study investigates the perceived ease of use and perceived usefulness (acceptability) of a customized service robot as determined by nursing students (as proxies for nursing staff in health care environments). This service robot, referred to as the Adaptive Robotic Nurse Assistant (ARNA), was developed to enhance the productivity of nurses through cooperation during physical tasks (eg, patient walking, item fetching, object delivery) as well as nonphysical tasks (eg, patient observation and feedback). This pilot study evaluated the acceptability of ARNA to provide ambulatory assistance to patients.

METHODS

We conducted a trial with 24 participants to collect data and address the following research question: Is the use of ARNA as an ambulatory assistive device for patients acceptable to nurses? The experiments were conducted in a simulated hospital environment. Nursing students (as proxies for nursing staff) were grouped in dyads, with one participant serving as a nurse and the other acting as a patient. Two questionnaires were developed and administrated to the participants based on the Technology Acceptance Model with respect to the two subscales of perceived usefulness and perceived ease of use metrics. In order to evaluate the internal consistency/reliability of the questionnaires, we calculated Cronbach alpha coefficients. Furthermore, statistical analyses were conducted to evaluate the relation of each variable in the questionnaires with the overall perceived usefulness and perceived ease of use metrics.

RESULTS

Both Cronbach alpha values were acceptably high (.93 and .82 for perceived usefulness and perceived ease of use questionnaires, respectively), indicating high internal consistency of the questionnaires. The correlation between the variables and the overall perceived usefulness and perceived ease of use metrics was moderate. The average perceived usefulness and perceived ease of use metrics among the participants were 4.13 and 5.42, respectively, out of possible score of 7, indicating a higher-than-average acceptability of this service robot.

CONCLUSIONS

The results served to identify factors that could affect nurses' acceptance of ARNA and aspects needing improvement (eg, flexibility, ease of operation, and autonomy level).