Furhat PsychScreen Framework: Streamlining Robot-Assisted Psychological Screening Implementation

Abstract

Initial programming of social robots for psychometric assessments indicates potential reliability and validity in evaluating psychological conditions. However, on average adults express a fair level of satisfaction with robot interaction, and issues like automatic scoring errors and cultural nuances errors were encountered, particularly related to native language biases. Another challenge is simplifying the coding and implementation process for psychologists. The most advanced conversational robot, Furhat, can help addressing these issues with its robust automatic recognition system for multiple languages and open-source programming with human-readable code that enable implementations without advanced programming skills. The study propose a novel software framework to administer psychological screening using the Furhat robot platform, which can adapt to different test formats, question structures and assessment criteria. The framework combines voice administration, via the robot, with a touch screen interface offering a hybrid approach for surveys. The potential impact of the study in clinical psychology involves using social robots to enhance engagement and emotional connection with humans, while also employing automated survey assessments. This approach could uncover fears that might be overlooked by humans or other technologies. Additionally, the study presents results from three test customizations using the designed and developed open-source template for streamlining robot-assisted psychological screening.