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The Adoption of AI in Mental Health Care-Perspectives From Mental Health Professionals: Qualitative Descriptive Study.

Melody ZhangJillian ScandiffioSarah YounusTharshini JeyakumarInaara KarsanRebecca CharowMohammad SalhiaDavid Wiljer
Published in: JMIR formative research (2023)
AI technologies are starting to emerge in mental health care. Although many digital tools, web-based services, and mobile apps are designed using AI algorithms, mental health professionals have generally been slower in the adoption of AI. As indicated by this study's findings, the implications are 3-fold. At the individual level, digital professionals must see the value in digitally compassionate tools that retain a humanistic approach to care. For mental health professionals, resistance toward AI adoption must be acknowledged through educational initiatives to raise awareness about the relevance, practicality, and benefits of AI. At the organizational level, digital professionals and leaders must collaborate on governance and funding structures to promote employee buy-in. At the societal level, digital and mental health professionals should collaborate in the creation of formal AI training programs specific to mental health to address knowledge gaps. This study promotes the design of relevant and sustainable education programs to support the adoption of AI within the mental health care sphere.
Keyphrases
  • mental health
  • artificial intelligence
  • healthcare
  • machine learning
  • electronic health record
  • deep learning
  • public health
  • quality improvement
  • primary care
  • mental illness
  • palliative care
  • chronic pain
  • pain management