{"title":"User perceptions and experiences of an AI-driven conversational agent for mental health support.","authors":"Beenish Moalla Chaudhry, Happy Rani Debi","doi":"10.21037/mhealth-23-55","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>The increasing prevalence of artificial intelligence (AI)-driven mental health conversational agents necessitates a comprehensive understanding of user engagement and user perceptions of this technology. This study aims to fill the existing knowledge gap by focusing on Wysa, a commercially available mobile conversational agent designed to provide personalized mental health support.</p><p><strong>Methods: </strong>A total of 159 user reviews posted between January, 2020 and March, 2024, on the Wysa app's Google Play page were collected. Thematic analysis was then used to perform open and inductive coding of the collected data.</p><p><strong>Results: </strong>Seven major themes emerged from the user reviews: \"a trusting environment promotes wellbeing\", \"ubiquitous access offers real-time support\", \"AI limitations detract from the user experience\", \"perceived effectiveness of Wysa\", \"desire for cohesive and predictable interactions\", \"humanness in AI is welcomed\", and \"the need for improvements in the user interface\". These themes highlight both the benefits and limitations of the AI-driven mental health conversational agents.</p><p><strong>Conclusions: </strong>Users find that Wysa is effective in fostering a strong connection with its users, encouraging them to engage with the app and take positive steps towards emotional resilience and self-improvement. However, its AI needs several improvements to enhance user experience with the application. The findings contribute to the design and implementation of more effective, ethical, and user-aligned AI-driven mental health support systems.</p>","PeriodicalId":74181,"journal":{"name":"mHealth","volume":"10 ","pages":"22"},"PeriodicalIF":2.2000,"publicationDate":"2024-07-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11304096/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"mHealth","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.21037/mhealth-23-55","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2024/1/1 0:00:00","PubModel":"eCollection","JCR":"Q2","JCRName":"HEALTH CARE SCIENCES & SERVICES","Score":null,"Total":0}
引用次数: 0
Abstract
Background: The increasing prevalence of artificial intelligence (AI)-driven mental health conversational agents necessitates a comprehensive understanding of user engagement and user perceptions of this technology. This study aims to fill the existing knowledge gap by focusing on Wysa, a commercially available mobile conversational agent designed to provide personalized mental health support.
Methods: A total of 159 user reviews posted between January, 2020 and March, 2024, on the Wysa app's Google Play page were collected. Thematic analysis was then used to perform open and inductive coding of the collected data.
Results: Seven major themes emerged from the user reviews: "a trusting environment promotes wellbeing", "ubiquitous access offers real-time support", "AI limitations detract from the user experience", "perceived effectiveness of Wysa", "desire for cohesive and predictable interactions", "humanness in AI is welcomed", and "the need for improvements in the user interface". These themes highlight both the benefits and limitations of the AI-driven mental health conversational agents.
Conclusions: Users find that Wysa is effective in fostering a strong connection with its users, encouraging them to engage with the app and take positive steps towards emotional resilience and self-improvement. However, its AI needs several improvements to enhance user experience with the application. The findings contribute to the design and implementation of more effective, ethical, and user-aligned AI-driven mental health support systems.