AI triage or manual triage? Exploring medical staffs' preference for AI triage in China

OBJECTIVES

The introduction of AI technology in healthcare presents both opportunities and challenges. The aim of this study was to investigate medical staffs' preference for AI triage and the influencing factors.

METHODS

A survey was conducted online among medical staffs in China from March 4th to April 28th, 2021. Participants were recruited through multiple channels, including medical professional platforms and social media. A total of 677 valid responses were obtained from medical staff members located in 28 provinces across China.

RESULTS

The results showed that AI triage had an overall acceptance rate of 77.1%, and 45.2% of the medical staffs surveyed preferred "AI triage exclusively." Direct experience was positively associated with medical staffs' preference for AI triage (β = 0.223, p < .001). Additionally, greater exposure to a variety of media was positively associated with the perceived value of AI technology, which, in turn, increased preference for AI triage (β = 0.040, SE = 0.013, p < .001, 95% CI = [0.017, 0.067]).

CONCLUSION

Medical staffs generally hold a favorable attitude towards AI triage, particularly in areas with a high medical burden and during pandemics. In a multimedia environment, media exposure variety impacts medical staffs' preferences through their perceived value of AI technology. This study has implications for the implementation of AI triage on a larger scale.

Heterogeneity of Attitudes toward Robots in Healthcare among the Chinese Public: A Latent Profile Analysis

Attitudes are deemed critical psychological variables that can determine end users' acceptance and adoption of robots. This study explored the heterogeneity of the Chinese public's attitudes toward robots in healthcare and examined demographic characteristics associated with the derived profile membership. The data were collected from a sample of 428 Chinese who participated in an online survey. Latent profile analysis identified three distinct subgroups regarding attitudes toward robots-optimistic (36.9%), neutral (47.2%), and ambivalent (15.9%). Interestingly, although participants in the ambivalent attitude profile held more negative attitudes toward interaction with or social influence of healthcare robots, their attitudes tended to be positive when it came to emotional interactions with healthcare robots. All the respondents reported negative attitudes toward the social influence of healthcare robots. Multivariable regression analysis results showed that there were significant differences in age, education level, monthly income, experience with computers, experience with wearable devices, and whether to follow robot-related news or not. This study confirmed the heterogeneity of the Chinese public's attitudes toward robots in healthcare and highlighted the importance of emotional interaction with and social influence of healthcare robots, which might facilitate a better understanding of the needs and expectations of potential end users for robots in healthcare to make them more acceptable in different situations.

A Multi-Industry Analysis of the Future Use of AI Chatbots

Artificial intelligence (AI) chatbots are set to be the defining technology of the next decade due to their ability to increase human capability at a low cost. However, more research is required to assess individuals’ behavioural intentions to use this technology when it becomes publicly available. This study applied an extended Technology Acceptance Model (TAM), with additional predictors of trust and privacy concerns, to assess individuals’ behavioural intentions to use AI chatbots across three industries: mental health care, online shopping, and online banking. These services were selected due to the current popularity of regular chatbots in these fields. Participants ( $N=360$ , 202 females) aged between 17 and 85 years ( $M=38.17$ , $\text{SD}=17.66$ ) completed a 71-item online, cross-sectional survey. As hypothesised, perceived usefulness and trust were significant positive predictors of behavioural intentions across all three behaviours. However, the influence of the perceived ease of use and privacy concerns on behavioural intentions differed across the three behaviours. These findings highlight that the combination of predictors within the extended TAM have different influences on behavioural intentions to use AI chatbots for mental health care, online shopping, and online banking. This research contributes to the literature by demonstrating that the influence of the variables in one field cannot be generalised across all uses of AI chatbots.

The time is ripe for robopsychology

As robotic applications become increasingly diverse, more domains of human lives are being involved, now also extending to educational, therapeutic, and social situations, with a trend to even more complex interactions. This diversity generates new research questions that need to be met with an adequate infrastructure of psychological methods and theory. In this review, we illustrate the current lack of a sub-discipline in psychology to systematically study the psychological corollaries of living in societies where the application of robotic and artificial intelligence (AI) technologies is becoming increasingly common. We thus propose that organized efforts be made toward recognition of robopsychology as a sub-discipline so that the field of psychology moves away from isolated publications of robot- and AI-related topics to a body of knowledge that is able to meet the demands for change, as the world is preparing for the Fourth Industrial Revolution. We propose a definition of robopsychology that not only covers the study of the effects of robots on human behavior, but also of robots and AI themselves, as well as acknowledging how this sub-discipline may eventually be fundamentally changed through robots and AI. In this sense, our definition mirrors an already existing definition of the field of robophilosophy.

Robot Coworkers: The Vision of Future Hoteliers

The purpose of this study is to understand how future employees in the hospitality and tourism industry envision the use of artificial intelligence in the organizations where they wish to work in the future. Through open-ended questions applied to undergraduate and master’s students in the area of tourism and hospitality, we capture their opinions when thinking about the partial or total use of robots in hospitality. Despite the increasing implementation of artificial intelligence in hospitality and tourism, existing research mainly focuses on current hoteliers and/or customers. However, anticipating how digital generations expect their future roles in a close engagement with robots allows researchers to predict and focus their attention on future problems. Their statements were subjected to a qualitative content analysis methodology, based on themes and sentiment. Participants expressed a negative view of the presence of robots in hospitality, mostly associated with a fear of job loss. Many also reported that interacting with robots is negative for both staff and customers due to robots’ lack of emotions. However, there is some division concerning the impact of robots on service quality: some believe that the service will be more efficient and with fewer failures; others believe that the limitations of robots will lead to worse service. The findings suggest that the acceptability and desirability of robotization may vary depending on the level of robotization in hotels, on the type of customer, and on the level of service provided.