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

Salah Hamdoun, Rebecca Monteleone, Terri Bookman, Katina Michael

Research output: Contribution to journalArticlepeer-review

8 Scopus citations

Abstract

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.

Original languageEnglish (US)
Pages (from-to)25-36
Number of pages12
JournalIEEE Technology and Society Magazine
Volume42
Issue number1
DOIs
StatePublished - Mar 1 2023

ASJC Scopus subject areas

  • General Engineering
  • General Social Sciences

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