ObjectiveTo review research on social robots to help children in healthcare contexts in order to describe the current state of the literature and explore future directions for research and practice.DesignScoping review.Data sourcesEngineering Village, IEEE Xplore, Medline, PsycINFO and Scopus databases were searched up until 10 July 2017. Only publications written in English were considered. Identified publications were initially screened by title and abstract, and the full texts of remaining publications were then subsequently screened.Eligibility criteriaPublications were included if they were journal articles, conference proceedings or conference proceedings published as monographs that described the conceptualisation, development, testing or evaluation of social robots for use with children with any mental or physical health condition or disability. Publications on autism exclusively, robots for use with children without identified health conditions, physically assistive or mechanical robots, non-physical hardware robots and surgical robots were excluded.ResultsSeventy-three publications were included in the review, of which 50 included user studies with a range of samples. Most were feasibility studies with small sample sizes, suggesting that the robots were generally accepted. At least 26 different robots were used, with many of these still in development. The most commonly used robot was NAO. The evidence quality was low, with only one randomised controlled trial and a limited number of experimental designs.ConclusionsSocial robots hold significant promise and potential to help children in healthcare contexts, but higher quality research is required with experimental designs and larger sample sizes.

ObjectivesThis research is part of an international project to design and test a home-based healthcare robot to help older adults with mild cognitive impairment (MCI) or early dementia. The aim was to investigate the perceived usefulness of different daily-care activities for the robot, developed from previous research on needs.DesignQualitative descriptive analysis using semistructured interviews. Two studies were conducted. In the first study, participants watched videos of a prototype robot performing daily-care activities; in the second study, participants interacted with the robot itself.SettingInterviews were conducted at a university and a retirement village.ParticipantsIn study 1, participants were nine experts in aged care and nine older adults living in an aged care facility. In study 2, participants were 10 experts in aged care.ResultsThe themes that emerged included aspects of the robot’s interactions, potential benefits, the appearance, actions and humanness of the robot, ways to improve its functionality and technical issues. Overall, the activities were perceived as useful, especially the reminders and safety checks, with possible benefits of companionship, reassurance and reduced caregiver burden. Suggestions included personalising the robot to each individual, simplifying the language and adding more activities. Technical issues still need to be fixed.ConclusionThis study adds to knowledge about healthcare robots for people with MCI by developing and testing a new robot with daily-care activities including safety checks. The robot was seen to be potentially useful but needs to be tested with people with MCI.

AbstractRobots are now starting to be developed and used as receptionists in health applications. In this regard, it is important that robots’ behavioural skills are developed and researched so that people have appropriate and comfortable interactions. Smiling and use of first name are two more important social communication skills used during human interactions. While smiling and use of first name are often employed by robots in human interactions, the effect of these behaviours on perceptions of receptionist robots has not yet been experimentally investigated. This study explored the effects of robot smiling and robot use of the participant’s first name on perceptions of robot friendliness, mind, and personality, as well as attitudes and smiling behaviour. Forty participants interacted with a medical receptionist robot four times, in a two by two repeated measures design. Both smiling and use of first name had significant positive effects on participants’ perceptions of robot personality. Robot smiling also showed significant effects on participants’ overall attitudes towards robots, ratings of robot friendliness, and perceptions of the robot’s mind, and increased the frequency of participants’ own smiling. There were no significant interaction effects. Robot smiling in particular can enhance user perceptions of robots and increase reciprocal smiling.

BackgroundFor robots to be effectively used in health applications, they need to display appropriate social behaviors. A fundamental requirement in all social interactions is the ability to engage, maintain, and demonstrate attention. Attentional behaviors include leaning forward, self-disclosure, and changes in voice pitch.ObjectiveThis study aimed to examine the effect of robot attentional behaviors on user perceptions and behaviors in a simulated health care interaction.MethodsA parallel randomized controlled trial with a 1:1:1 allocation ration was conducted. We randomized participants to 1 of 4 experimental conditions before engaging in a scripted face-to-face interaction with a fully automated medical receptionist robot. Experimental conditions included a self-disclosure condition, voice pitch change condition, forward lean condition, and neutral condition. Participants completed paper-based postinteraction measures relating to engagement, perceived robot attention, and perceived robot empathy. We video recorded interactions and coded for participant attentional behaviors.ResultsA total of 181 participants were recruited from the University of Auckland. Participants who interacted with the robot in the forward lean and self-disclosure conditions found the robot to be significantly more stimulating than those who interacted with the robot in the voice pitch or neutral conditions (P=.03). Participants in the forward lean, self-disclosure, and neutral conditions found the robot to be significantly more interesting than those in the voice pitch condition (P<.001). Participants in the forward lean and self-disclosure conditions spent significantly more time looking at the robot than participants in the neutral condition (P<.001). Significantly, more participants in the self-disclosure condition laughed during the interaction (P=.01), whereas significantly more participants in the forward lean condition leant toward the robot during the interaction (P<.001).ConclusionsThe use of self-disclosure and forward lean by a health care robot can increase human engagement and attentional behaviors. Voice pitch changes did not increase attention or engagement. The small effects with regard to participant perceptions are potentially because of the limitations in self-report measures or a lack of comparison for most participants who had never interacted with a robot before. Further research could explore the use of self-disclosure and forward lean using a within-subjects design and in real health care settings.

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