Evidence map›Paper›PMID 37527545›Full record

ArticleJMIR formative research2023

Exploring Young Adults' Views About Aroha, a Chatbot for Stress Associated With the COVID-19 Pandemic: Interview Study Among Students.

Annie Kang, Sarah Hetrick, Tania Cargo, Sarah Hopkins, Nicola Ludin, Sarah Bodmer, Kiani Stevenson, Chester Holt-Quick, Karolina Stasiak

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Article in JMIR formative research, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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3 · Its place in the literature

Who cites it

4 citing papers in PubMed.

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4 · The record

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PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors.

Annie KangFaculty of Arts, University of Auckland, Auckland, New Zealand.ORCID https://orcid.org/0009-0009-1183-2885
Sarah HetrickDepartment of Psychological Medicine, Faculty of Medical and Health Sciences, University of Auckland, Auckland, New Zealand.ORCID https://orcid.org/0000-0003-2532-0142
Tania CargoDepartment of Psychological Medicine, Faculty of Medical and Health Sciences, University of Auckland, Auckland, New Zealand.ORCID https://orcid.org/0000-0002-4675-9894
Sarah HopkinsDepartment of Psychological Medicine, Faculty of Medical and Health Sciences, University of Auckland, Auckland, New Zealand.ORCID https://orcid.org/0000-0002-4705-5362
Nicola LudinDepartment of Psychological Medicine, Faculty of Medical and Health Sciences, University of Auckland, Auckland, New Zealand.ORCID https://orcid.org/0000-0003-0399-7558
Sarah BodmerDepartment of Psychological Medicine, Faculty of Medical and Health Sciences, University of Auckland, Auckland, New Zealand.ORCID https://orcid.org/0000-0003-2012-0512
Kiani StevensonDepartment of Psychological Medicine, Faculty of Medical and Health Sciences, University of Auckland, Auckland, New Zealand.ORCID https://orcid.org/0000-0003-4263-9171
Chester Holt-QuickKekeno Tech, Auckland, New Zealand.ORCID https://orcid.org/0000-0002-8350-919X
Karolina StasiakDepartment of Psychological Medicine, Faculty of Medical and Health Sciences, University of Auckland, Auckland, New Zealand.ORCID https://orcid.org/0000-0002-1153-3123

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundIn 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.

objectiveIn 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.

methodsWe 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).

resultsA 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.

conclusionsChatbots 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.

Indexed as

acceptabilitychatbotCOVID-19mental healthqualitative methodsyoung adults

Identifiers

PMID37527545
PMCPMC10574714

What OpenQuestion holds

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LicenceCC BY
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.