JMIR Publications

ABSTRACT

Background:

Cardiometabolic diseases (CMD) are a major health concern worldwide, with people living in socio-economically disadvantaged areas being disproportionately affected. Knowing one’s risk status for developing a CMD can help individuals in delaying or preventing the disease. Innovative tools and strategies such as the use of Artificial intelligence-based technology are needed to improve inclusivity, cost-effectiveness, and sustainability of screening processes.

Objective:

The aim of this study is to assess users’ perceptions of the utility and acceptance of the social robot “Furhat” for cardiometabolic risk assessment within a socio-economically disadvantaged community in Uppsala, Sweden.

Methods:

In this qualitative study, 13 semi-structured interviews were conducted with participants living in disadvantaged social areas within Uppsala, after they completed a CMD risk assessment delivered by the social robot. Participants were purposefully sampled to achieve the desired variation regarding personal characteristics such as age, gender, or area of living. A framework analysis approach was applied to the data.

Results:

Two themes were developed. The first theme Self-versus others: a matter of perception, norms and assumptions includes participants´ perceptions of who would use the robot and why, if it was installed in the community. Participants perceived older individuals, immigrants and in some instances women to be less interested in the robot screening or as having a harder time participating in it. However, there were between-group variations, especially among men and women, with participants often discounting opinions ascribed to their group by others. The second theme The robot is good, but humans are better captures participants' actual experiences of the interaction with the social robot once they have started the interaction. Although participants enjoyed the interaction with the robot, perceived it as non-judgmental, and would recommend it to others, most would prefer conducting the screening with a human. Two major contributors for this preference were language barriers experienced during the robot-participant interaction, as well as their wish for more interactive, emotionally responsive, and communicative features of the robot.

Conclusions:

This study provides insights into users’ perceptions of the utility and acceptance of a social robot for risk assessment in a community context, which can help inform the further development of this technology for health screening in a community context. In the future, the robot could be further developed to conduct risk assessments in multiple languages and offer a broader service to users such as providing appropriate information related to healthy and active living.