Background: 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. Objective: 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. Methods: 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. Results: 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. Conclusions: 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.

Background: In March 2020, New Zealand was plunged into its first nationwide lockdown to halt the spread of COVID-19. Our team rapidly adapted our existing chatbot platform to create Aroha, a well-being chatbot intended to address the stress experienced by young people aged 13 to 24 years in the early phase of the pandemic. Aroha was made available nationally within 2 weeks of the lockdown and continued to be available throughout 2020. Objective: In this study, we aimed to evaluate the acceptability and relevance of the chatbot format and Aroha’s content in young adults and to identify areas for improvement. Methods: We conducted qualitative in-depth and semistructured interviews with young adults as well as in situ demonstrations of Aroha to elicit immediate feedback. Interviews were recorded, transcribed, and analyzed using thematic analysis assisted by NVivo (version 12; QSR International). Results: A total of 15 young adults (age in years: median 20; mean 20.07, SD 3.17; female students: n=13, 87%; male students: n=2, 13%; all tertiary students) were interviewed in person. Participants spoke of the challenges of living during the lockdown, including social isolation, loss of motivation, and the demands of remote work or study, although some were able to find silver linings. Aroha was well liked for sounding like a “real person” and peer with its friendly local “Kiwi” communication style, rather than an authoritative adult or counselor. The chatbot was praised for including content that went beyond traditional mental health advice. Participants particularly enjoyed the modules on gratitude, being active, anger management, job seeking, and how to deal with alcohol and drugs. Aroha was described as being more accessible than traditional mental health counseling and resources. It was an appealing option for those who did not want to talk to someone in person for fear of the stigma associated with mental health. However, participants disliked the software bugs. They also wanted a more sophisticated conversational interface where they could express themselves and “vent” in free text. There were several suggestions for making Aroha more relevant to a diverse range of users, including developing content on navigating relationships and diverse chatbot avatars. Conclusions: Chatbots are an acceptable format for scaling up the delivery of public mental health and well-being–enhancing strategies. We make the following recommendations for others interested in designing and rolling out mental health chatbots to better support young people: make the chatbot relatable to its target audience by working with them to develop an authentic and relevant communication style; consider including holistic health and lifestyle content beyond traditional “mental health” support; and focus on developing features that make users feel heard, understood, and empowered.

Following general anaesthesia (GA), patients frequently experience sleep disruption and fatigue, which has been hypothesized to result at least in part by GA affecting the circadian clock. Here, we provide the first comprehensive time-dependent analysis of the effects of the commonly administered inhalational anaesthetic, isoflurane, on the murine circadian clock, by analysing its effects on (a) behavioural locomotor rhythms and (b) PER2::LUC expression in the suprachiasmatic nuclei (SCN) of the mouse brain. Behavioural phase shifts elicited by exposure of mice (n = 80) to six hours of GA (2% isoflurane) were determined by recording wheel-running rhythms in constant conditions (DD). Phase shifts in PER2::LUC expression were determined by recording bioluminescence in organotypic SCN slices (n = 38) prior to and following GA exposure (2% isoflurane). Full phase response curves for the effects of GA on behaviour and PER2::LUC rhythms were constructed, which show that the effects of GA are highly time-dependent. Shifts in SCN PER2 expression were much larger than those of behaviour (c. 0.7 h behaviour vs. 7.5 h PER2::LUC). We discuss the implications of this work for understanding how GA affects the clock, and how it may inform the development of chronotherapeutic strategies to reduce GA-induced phase-shifting in patients.

BACKGROUND In March 2020, New Zealand was plunged into its first nationwide lockdown to halt the spread of COVID-19. Our team rapidly adapted our existing chatbot platform to create Aroha, a well-being chatbot intended to address the stress experienced by young people aged 13 to 24 years in the early phase of the pandemic. Aroha was made available nationally within 2 weeks of the lockdown and continued to be available throughout 2020. OBJECTIVE In this study, we aimed to evaluate the acceptability and relevance of the chatbot format and Aroha’s content in young adults and to identify areas for improvement. METHODS We conducted qualitative in-depth and semistructured interviews with young adults as well as in situ demonstrations of Aroha to elicit immediate feedback. Interviews were recorded, transcribed, and analyzed using thematic analysis assisted by NVivo (version 12; QSR International). RESULTS A total of 15 young adults (age in years: median 20; mean 20.07, SD 3.17; female students: n=13, 87%; male students: n=2, 13%; all tertiary students) were interviewed in person. Participants spoke of the challenges of living during the lockdown, including social isolation, loss of motivation, and the demands of remote work or study, although some were able to find silver linings. Aroha was well liked for sounding like a “real person” and peer with its friendly local “Kiwi” communication style, rather than an authoritative adult or counselor. The chatbot was praised for including content that went beyond traditional mental health advice. Participants particularly enjoyed the modules on gratitude, being active, anger management, job seeking, and how to deal with alcohol and drugs. Aroha was described as being more accessible than traditional mental health counseling and resources. It was an appealing option for those who did not want to talk to someone in person for fear of the stigma associated with mental health. However, participants disliked the software bugs. They also wanted a more sophisticated conversational interface where they could express themselves and “vent” in free text. There were several suggestions for making Aroha more relevant to a diverse range of users, including developing content on navigating relationships and diverse chatbot avatars. CONCLUSIONS Chatbots are an acceptable format for scaling up the delivery of public mental health and well-being–enhancing strategies. We make the following recommendations for others interested in designing and rolling out mental health chatbots to better support young people: make the chatbot relatable to its target audience by working with them to develop an authentic and relevant communication style; consider including holistic health and lifestyle content beyond traditional “mental health” support; and focus on developing features that make users feel heard, understood, and empowered.

BACKGROUND The number of young people in New Zealand who experience mental health challenges is increasing. As New Zealand was going into its 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. OBJECTIVE 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. METHODS Stay at home orders under New Zealand’s lockdown commenced on 20 March 2020. By leveraging previously developed chatbot technology and broader existing online trial infrastructure, the Aroha chatbot was launched promptly on 7 April 2020. Dissemination of the chatbot for an open trial was via a URL, feedback on experience of the lockdown and on the experience of Aroha was gathered via online questionnaires, a focus group, and from community members. RESULTS In the two 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. CONCLUSIONS 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.