A Chatbot to Support Young People During the COVID-19 Pandemic in New Zealand: Evaluation of the Real-World Rollout of an Open Trial

• Published in: Journal of medical Internet research 2022-11, Vol.24 (11), p.e38743-e38743
• Main Authors: Ludin, Nicola, Holt-Quick, Chester, Hopkins, Sarah, Stasiak, Karolina, Hetrick, Sarah, Warren, Jim, Cargo, Tania
• Format: Article
• Language: English
• Subjects: Behavior therapy; Child & adolescent mental health; Cognitive behavioral therapy; Cognitive therapy; Cognitive-behavioral factors; Computer mediated communication; Content management software; Coronaviruses; COVID-19; Dissemination; Epidemics; Evidence-based medicine; Feasibility; Graph representations; Health services; Infrastructure; Medical technology; Mental health; Mental health care; Natural language; New Zealand; Original Paper; Pandemics; Positive psychology; Teenagers; Worry; Youth
• ISSN: 1438-8871; 1439-4456; 1438-8871
• DOI: 10.2196/38743

The number of young people in New Zealand (Aotearoa) who experience mental health challenges is increasing. As those in Aotearoa went into the initial COVID-19 lockdown, an ongoing digital mental health project was adapted and underwent rapid content authoring to create the Aroha chatbot. This dynamic digital support was designed with and for young people to help manage pandemic-related worry. Aroha was developed to provide practical evidence-based tools for anxiety management using cognitive behavioral therapy and positive psychology. The chatbot included practical ideas to maintain social and cultural connection, and to stay active and well. Stay-at-home orders under Aotearoa’s lockdown commenced on March 20, 2020. By leveraging previously developed chatbot technology and broader existing online trial infrastructure, the Aroha chatbot was launched promptly on April 7, 2020. Dissemination of the chatbot for an open trial was via a URL, and feedback on the experience of the lockdown and the experience of Aroha was gathered via online questionnaires and a focus group, and from community members. In the 2 weeks following the launch of the chatbot, there were 393 registrations, and 238 users logged into the chatbot, of whom 127 were in the target age range (13-24 years). Feedback guided iterative and responsive content authoring to suit the dynamic situation and motivated engineering to dynamically detect and react to a range of conversational intents. The experience of the implementation of the Aroha chatbot highlights the feasibility of providing timely event-specific digital mental health support and the technology requirements for a flexible and enabling chatbot architectural framework.