BACKGROUND
Healthcare is shifting towards five proactive approaches (P5 medicine), personalized, participatory, preventive, predictive, and precision-focused services. This patient-centered care leverages technologies such as AI-integrated robots, which can personalize and enhance services for users with disabilities. These advancements are crucial, given the World Health Organization's projection of a global shortage of up to 10 million healthcare workers by 2030.
OBJECTIVE
This study aimed to investigate the acceptance of a humanoid assistive robot among users with physical disabilities during 1) AI-powered (Wizard of Oz) robotic performance of predefined personalized assistance tasks, and 2) operator-controlled robotic performance (simulated distant service).
METHODS
An explorative qualitative design was used, involving user-testing in a simulated home environment and individual interviews. Directed content analysis was based on the Almere model and the Model of Domestic Robot Acceptance (DSRA).
RESULTS
Nine participants with physical disabilities, aged 27-78, engaged in robot interactions. They shared their perceptions across seven acceptance concepts: Hedonic Attitudes, Utilitarian Attitudes, Personal Norms, Social Norms, Control Beliefs, Facilitating Conditions, and Intention to Use. Participants valued the robot's usefulness for practical services, but not personal care. They preferred automation but accepted remote control of the robot for some tasks. Privacy concerns were mixed.
CONCLUSIONS
The study highlights the complex interplay of functional expectations, technological readiness, and personal and societal norms affecting the acceptance of physically assistive robots. Participants were generally positive about robotic assistance, as they increase independence and lessen the need for human caregivers, even though they acknowledged some current shortcomings. They were open to try more home testing if future robots could perform most tasks autonomously. AI in robotics offers new possibilities for creating more adaptable and personalized assistive technologies, potentially enhancing their effectiveness and viability for individuals with disabilities.