4.1 Article

AI-Based and Digital Mental Health Apps: Balancing Need and Risk

期刊

IEEE TECHNOLOGY AND SOCIETY MAGAZINE
卷 42, 期 1, 页码 25-36

出版社

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/MTS.2023.3241309

关键词

COVID-19; Pandemics; Virtual assistants; Mental health; Machine learning; Linguistics; Chatbots

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Mental health and well-being have become increasingly important in public health discussions, especially due to the COVID-19 pandemic revealing significant gaps in existing mental health services. This article specifically examines the implications of digital mental health applications in the form of chatbots, which utilize conversational artificial intelligence to provide support and assistance.
Mental health and well-being are increasingly important topics in discussions on public health [1]. The COVID-19 pandemic further revealed critical gaps in existing mental health services as factors such as job losses and corresponding financial issues, prolonged physical illness and death, and physical isolation led to a sharp rise in mental health conditions [2]. As such, there is increasing interest in the viability and desirability of digital mental health applications. While these dedicated applications vary widely, from platforms that connect users with healthcare professionals to diagnostic tools to self-assessments, this article specifically explores the implications of digital mental health applications in the form of chatbots [3]. Chatbots can be text based or voice enabled and may be rule based (i.e., linguistics based) or based on machine learning (ML). They can utilize the power of conversational agents well-suited to task-oriented interactions, like Apple's Siri, Amazon's Alexa, or Google Assistant. But increasingly, chatbot developers are leveraging conversational artificial intelligence (AI), which is the suite of tools and techniques that allow a computer program to seemingly carry out a conversational experience with a person or a group.

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