Design Guidelines for Integrating AI into Mental Healthcare

Abstract

Global mental healthcare confronts daunting challenges, notably posttraumatic stress disorder (PTSD), necessitating immediate attention and innovative solutions. Many individuals requiring mental health support face various barriers, including social stigma, low perceived need, and restricted access to care providers — especially prevalent in certain regions — which impedes their quest for professional assistance. Amidst these obstacles, artificial intelligence (AI) emerges as a promising instrument, ushering in its unique challenges and opportunities. This thesis delves into these intricacies, aiming to develop comprehensive and pioneering design guidelines for AI applications within mental healthcare. The research focuses on three pivotal areas: identifying the distinct challenges and opportunities of implementing AI in mental healthcare; adapting existing AI design principles to fit the mental health landscape; and understanding the crucial role of multidisciplinary collaboration and user-centered design in this context. The primary objective is to devise guidelines that address inherent difficulties in mental healthcare, such as stigma and complexity of disorders, while leveraging potential benefits like early support intervention and expanded access to mental healthcare services. The suggested design guidelines embrace a systematic approach, encapsulating problem definition, stakeholder engagement, data acquisition, ethical and legal considerations, model design, system deployment, usage, maintenance, and iterative improvements based on feedback. Grounding these guidelines in a practical context, the thesis introduces AnchorAid, a tool that is designed theoretically and remains hypothetical. This virtual assistant provides post-trauma recovery support by gathering data, generating personalized feedback, recommending symptom management strategies, and assisting clinicians in the patient management processes. Through design guidelines establishment and their implementation via AnchorAid, this thesis lays a solid foundation for AI integration into mental healthcare.