Personality in Healthcare Human Robot Interaction (H-HRI)

Esterwood, Connor; Robert, Lionel

doi:10.1145/3406499.3415075

Cited by 27 publications

(21 citation statements)

References 36 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The trust and risk propensity questionnaires showed that our participants were less prone to take risks (M 4.05, SD 1.32) than the general population (Meertens and Lion, 2008) yet more prone to trust (Mayer and Davis, 1999) (M 2.93, SD 0.61). We used the cognitive trust items described in Section 3.3 as a rating of the robot's performance to compare our population to other findings compiled by Esterwood and Robert (2020): we found a very strong correlation between the cognitive and affective trust items (r 0.82, p 7.2e − 23), confirming that cognitive and affective trust go hand in hand.…”

Section: Population Statisticsmentioning

confidence: 64%

An Immersive Investment Game to Study Human-Robot Trust

et al. 2021

View full text Add to dashboard Cite

As robots become more advanced and capable, developing trust is an important factor of human-robot interaction and cooperation. However, as multiple environmental and social factors can influence trust, it is important to develop more elaborate scenarios and methods to measure human-robot trust. A widely used measurement of trust in social science is the investment game. In this study, we propose a scaled-up, immersive, science fiction Human-Robot Interaction (HRI) scenario for intrinsic motivation on human-robot collaboration, built upon the investment game and aimed at adapting the investment game for human-robot trust. For this purpose, we utilize two Neuro-Inspired COmpanion (NICO) - robots and a projected scenery. We investigate the applicability of our space mission experiment design to measure trust and the impact of non-verbal communication. We observe a correlation of 0.43 (p=0.02) between self-assessed trust and trust measured from the game, and a positive impact of non-verbal communication on trust (p=0.0008) and robot perception for anthropomorphism (p=0.007) and animacy (p=0.00002). We conclude that our scenario is an appropriate method to measure trust in human-robot interaction and also to study how non-verbal communication influences a human’s trust in robots.

show abstract

Section: Population Statisticsmentioning

confidence: 64%

An Immersive Investment Game to Study Human-Robot Trust

et al. 2021

View full text Add to dashboard Cite

show abstract

“…Currently, there is no representation for the 65+ age group in the literature. Practically, when we consider that a large segment of robotic technologies are increasingly targeting health care for those older than 65, we can begin to see an issue with existing sampling (see: [28]). This is an issue because according to table 7, the importance of personality on predicting robot acceptance seems to diminish by age.…”

Section: Limitations and Future Researchmentioning

confidence: 99%

“…There is now a tendency to assume that at least one of the Big Five personality traits can be used to understand whether a person will accept a robot [81,82]. Despite this intuitive appeal, several literature reviews on the topic have highlighted inconsistencies in the relationship between human personality and the acceptance of robots [28,82]. However, none of those studies engaged in a systematic quantitative meta-analysis to empirically examine this relationship.…”

Section: Introductionmentioning

confidence: 99%

“…This division or specification allows researchers a more precise approach to linking a particular personality trait to a particular outcome [42,66,94]. At present, the Big Five personality traits are the predominant set of traits used across many fields [57,81,82], including HRI studies [28,55,77,81,82,99]. The personality traits that make up the Big Five are extroversion, agreeableness, conscientiousness, neuroticism (sometimes called emotional instability), and openness to experience [36,50,65].…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

A Meta-Analysis of Human Personality and Robot Acceptance in Human-Robot Interaction

Esterwood

Essenmacher

Yang

et al. 2021

Proceedings of the 2021 CHI Conference on Human Factors in Computing Systems

Self Cite

View full text Add to dashboard Cite

Human personality has been identified as a predictor of robot acceptance in the human-robot interaction (HRI) literature. Despite this, the HRI literature has provided mixed support for this assertion. To better understand the relationship between human personality and robot acceptance, this paper conducts a meta-analysis of 26 studies.Results found a positive relationship between human personality and robot acceptance. However, this relationship varied greatly by the specific personality trait along with the study sample's age, gender diversity, task, and global region. This meta-analysis also identified gaps in the literature. Namely, additional studies are needed that investigate both the big five personality traits and other personality traits, examine a more diverse age range, and utilize samples from previously unexamined regions of the globe. CCS Concepts: • Computer systems organization → Robotics; • Human-centered computing → Human computer interaction (HCI).

show abstract

“…It is worth mentioning that prior to conducting the systematic literature review, authors assessed its novelty. Authors acknowledge the existence of several systematic literature reviews in the broad field of robotics [52][53][54][55][56], some of them in the field of human-robot interaction [57][58][59][60]. However, in the specific field of social robots, there are two works worth mention, one on the interaction with sexbots [61] and another on specific design guidelines for social robots for the elderly [62].…”

Section: Systematic Literature Review Using Prisma Guidelinesmentioning

confidence: 99%

User Experience in Social Robots

Shourmasti

Colomo‐Palacios

Holone

et al. 2021

Sensors

View full text Add to dashboard Cite

Social robots are increasingly penetrating our daily lives. They are used in various domains, such as healthcare, education, business, industry, and culture. However, introducing this technology for use in conventional environments is not trivial. For users to accept social robots, a positive user experience is vital, and it should be considered as a critical part of the robots’ development process. This may potentially lead to excessive use of social robots and strengthen their diffusion in society. The goal of this study is to summarize the extant literature that is focused on user experience in social robots, and to identify the challenges and benefits of UX evaluation in social robots. To achieve this goal, the authors carried out a systematic literature review that relies on PRISMA guidelines. Our findings revealed that the most common methods to evaluate UX in social robots are questionnaires and interviews. UX evaluations were found out to be beneficial in providing early feedback and consequently in handling errors at an early stage. However, despite the importance of UX in social robots, robot developers often neglect to set UX goals due to lack of knowledge or lack of time. This study emphasizes the need for robot developers to acquire the required theoretical and practical knowledge on how to perform a successful UX evaluation.

show abstract

Personality in Healthcare Human Robot Interaction (H-HRI)

Cited by 27 publications

References 36 publications

An Immersive Investment Game to Study Human-Robot Trust

An Immersive Investment Game to Study Human-Robot Trust

A Meta-Analysis of Human Personality and Robot Acceptance in Human-Robot Interaction

User Experience in Social Robots

Contact Info

Product

Resources

About