Perspectives of People with Serious Mental Illness on Artificial Intelligence-Based Companions: "If no one told you I love you today, you have someone that cares for you.".

Authors

Vedant Tapiavala, Sai S Chilakapati, Dylan Moore, Shamika Morales, Adithi Kumaran, Rebecca Heller, Jonathan Werlin, Karen L Fortuna

Published in

Community mental health journal. Sep 25, 2026. Epub Sep 25, 2026.

Abstract

Artificial intelligence (AI) is reshaping healthcare by enhancing clinical decision making, communication, and patient monitoring systems. Still, it is essential that these technologies lessen, rather than deepen, feelings of loneliness. This study centers the perspectives of individuals with serious mental illnesses, such as schizophrenia spectrum disorder, bipolar disorder, and major depressive disorder, to explore how they interpret and engage with conversational and companion-based AI in healthcare settings. By examining their perspectives, expectations, and concerns, the study highlights design factors that shape the perceived trustworthiness of AI tools. A secondary analysis of three focus groups was conducted across three supportive housing facilities in New York City, where qualitative data was subsequently collected, transcribed, and analyzed using RADar analysis. This study determined that participants expressed strong concerns about data privacy and misuse, but also recognized AI's potential to support reminders, mental health, and daily functioning. Trust in AI increased when tools were personalized, human-centered, and co-developed with people who understand lived experiences of serious mental illnesses. However, concerns remained about loss of critical thinking and overreliance. By emphasizing the lived experiences of adults with serious mental illness, this study identifies the factors that influence how they trust, use, and engage with AI in mental health care. These insights can guide the development of AI tools for individuals with serious mental illnesses.

PMID:
42789145
Bibliographic data and abstract were imported from PubMed on 26 Sep 2026.

Read full publication at:
Please sign in to see all details.

Stats

1-terrible, 9-excellent. How would you rate this publication? Sign in in to submit your rating.

Post a comment

You need to be signed in to post comments. You can sign in here.

Comments

There are no comments yet.