A chatbot-based intervention to promote healthy coping in young adults

INTRODUCTION. Transition from highschool to university can be a critical moment, that can involve anxiety and worsen the capacity to cope with challenges. New stressors derived from Covid-19 pandemic have also impacted the quality of interpersonal relationships, general well-being and access to care. Since mHealth interventions are ideal solutions to reach people everywhere and anytime and young people are familiar with instant messaging systems, interacting with a chatbot can provide an innovative way for facilitating their psycho-education and access to healthcare interventions. The objective of the whole study is to assess the level of engagement and effectiveness of young adults’ interaction with a psychoeducational intervention delivered by the ATENA chatbot, to improve their coping and resilience skills during the Covid-19 pandemic: here we report qualitative and quantitative data on engagement and acceptability dimensions, as per the students’ experience. METHODS. A virtual coaching system, aimed at promoting well-being also by means of mindfulness practice, was piloted in a sample of 71 university students. Users interacted with a Telegram hosted chatbot twice a week, for 4 weeks. A blended training methodology including dialogues, short videos and audio tracks was deployed. UES-SF allowed to collect data on the User eXperience (UX), while acceptability was described using thematic analysis. RESULTS. User Engagement: 61 participants were in agreement with the PU factor, which measures the affective (frustration) and cognitive (effortful) aspects as a result of the interaction. Participants answered in a neutral way concerning (i) the total UES-SF score, (ii) the AE factor, regarding the sensory and visual appearance of the interface, (iii) the RW factor, measuring the hedonic aspects of experience, the felt involvement, the overall success of the interaction, and the willingness to engage with the chatbot in the future. Lastly, as regards the FA factor, which evaluates the focused concentration, absorption, and temporal dissociation, participants were in disagreement. Acceptability: A thematic analysis was carried out to analyse qualitative data. Themes that were found are three: Content, User experience and Tasks. CONCLUSION. Assessing the UX of mHealth interventions is key to learn how to best tailor psycho-educational interventions on users’ real needs. The feedback collected in this study will be the basis for the refinement of this and future mHealth interventions.