Ethical decision-making for AI in mental health: the Integrated Ethical Approach for Computational Psychiatry (IEACP) framework.

Journal: Psychological medicine
Published Date:

Abstract

The integration of computational methods into psychiatry presents profound ethical challenges that extend beyond existing guidelines for AI and healthcare. While precision medicine and digital mental health tools offer transformative potential, they also raise concerns about privacy, algorithmic bias, transparency, and the erosion of clinical judgment. This article introduces the Integrated Ethical Approach for Computational Psychiatry (IEACP) framework, developed through a conceptual synthesis of 83 studies. The framework comprises five procedural stages - Identification, Analysis, Decision-making, Implementation, and Review - each informed by six core ethical values - beneficence, autonomy, justice, privacy, transparency, and scientific integrity. By systematically addressing ethical dilemmas inherent in computational psychiatry, the IEACP provides clinicians, researchers, and policymakers with structured decision-making processes that support patient-centered, culturally sensitive, and equitable AI implementation. Through case studies, we demonstrate framework adaptability to real-world applications, underscoring the necessity of ethical innovation alongside technological progress in psychiatric care.

Authors

  • Andrea Putica
    Department of Psychology, Counselling and Therapy, https://ror.org/01rxfrp27La Trobe University, Melbourne, VIC, Australia.
  • Rahul Khanna
    Phoenix Australia - Centre for Posttraumatic Mental Health, Department of Psychiatry, University of Melbourne, Melbourne, VIC, Australia.
  • Wiliam Bosl
    School of Nursing and Health Professions, https://ror.org/029m7xn54University of San Francisco, San Francisco, CA, USA.
  • Sudeep Saraf
    Department of Psychiatry, https://ror.org/04scfb908Alfred Health, Melbourne, VIC, Australia.
  • Juliet Edgcomb
    Mental Health Informatics and Data Science Hub, Semel Institute, University of California Los Angeles, Los Angeles, CA, USA.