Pragmatic AI-augmentation in mental healthcare: Key technologies, potential benefits, and real-world challenges and solutions for frontline clinicians

The integration of artificial intelligence (AI) technologies into mental health holds the promise of increasing patient access, engagement, and quality of care, and of improving clinician quality of work life. However, to date, studies of AI technologies in mental health have focused primarily on ch...

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Published in:Frontiers in psychiatry Vol. 13; p. 990370
Main Authors: Kellogg, Katherine C., Sadeh-Sharvit, Shiri
Format: Journal Article
Language:English
Published: Frontiers Media S.A 06-09-2022
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Summary:The integration of artificial intelligence (AI) technologies into mental health holds the promise of increasing patient access, engagement, and quality of care, and of improving clinician quality of work life. However, to date, studies of AI technologies in mental health have focused primarily on challenges that policymakers, clinical leaders, and data and computer scientists face, rather than on challenges that frontline mental health clinicians are likely to face as they attempt to integrate AI-based technologies into their everyday clinical practice. In this Perspective, we describe a framework for “pragmatic AI-augmentation” that addresses these issues by describing three categories of emerging AI-based mental health technologies which frontline clinicians can leverage in their clinical practice—automation, engagement, and clinical decision support technologies. We elaborate the potential benefits offered by these technologies, the likely day-to-day challenges they may raise for mental health clinicians, and some solutions that clinical leaders and technology developers can use to address these challenges, based on emerging experience with the integration of AI technologies into clinician daily practice in other healthcare disciplines.
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This article was submitted to Digital Mental Health, a section of the journal Frontiers in Psychiatry
Reviewed by: Luke Balcombe, Griffith University, Australia; Sonia Israel, McGill University, Canada
Edited by: Uffe Kock Wiil, University of Southern Denmark, Denmark
ISSN:1664-0640
1664-0640
DOI:10.3389/fpsyt.2022.990370