AI Companions Could Ease Loneliness in Serious Mental Illness, If People Help Design Them

For millions of people living with serious mental illness, the loneliest hours of the day often arrive after the clinic closes. A new study suggests that artificial intelligence-based companions could help fill that void, but only if the people they are meant to serve are given a genuine voice in how the technology is built. The research, published in the Community Mental Health Journal, centers the perspectives of adults with conditions such as schizophrenia spectrum disorder, bipolar disorder, and major depressive disorder, a population that has too often been talked about rather than talked with in the rush to deploy conversational AI in healthcare. The study’s title borrows a phrase from a participant that captures the emotional stakes with startling clarity: “If no one told you I love you today, you have someone that cares for you.”

The research team, led by Vedant Tapiavala of Dartmouth College together with collaborators at Massachusetts General Hospital, Dartmouth’s Thayer School of Engineering, Indiana University, the Geisel School of Medicine, and The Bridge in New York City, conducted a secondary analysis of three focus groups held across three supportive housing facilities in New York City. Rather than surveying attitudes with questionnaires, the investigators collected qualitative data, transcribed the discussions, and analyzed them using the RADaR technique, a rapid and rigorous qualitative data analysis method developed for applied research. The approach allows researchers to move quickly from raw transcripts to structured themes while preserving the nuance of what participants actually said, an important consideration when the subject matter touches on trust, vulnerability, and lived experience.

The findings reveal a population that is neither naively enthusiastic nor reflexively hostile toward AI. Participants expressed strong concerns about data privacy and the potential misuse of their information, worries that are amplified for people whose psychiatric histories carry heavy social stigma. At the same time, they recognized real potential in AI tools to support medication reminders, mental health maintenance, and daily functioning. This duality, hope shadowed by caution, runs through the entire study and complicates the simple narratives that often dominate public discussion of chatbots and mental health. For this community, the question is not whether AI companions should exist, but under what conditions they can be trusted.

Trust, the study found, is not a fixed trait that users either bring to or withhold from a system. Instead, it is something that emerges from design choices. Participants reported that their confidence in AI increased when tools were personalized, human-centered, and co-developed with people who understand the lived experience of serious mental illness. That last condition may be the most consequential. A chatbot designed without input from people who have navigated psychosis, mania, or severe depression may miss the signals that matter most, or worse, respond in ways that feel dismissive or unsafe. Co-design, in which end users participate as partners rather than test subjects, emerged as a key factor shaping perceived trustworthiness.

The technical implications of this are significant. Modern conversational AI systems, particularly those built on large language models, are trained on broad datasets that reflect general human communication, not the specific communication patterns, needs, and sensitivities of people with serious mental illness. Personalization in this context means more than remembering a user’s name. It involves calibrating tone, anticipating cognitive and emotional states, respecting boundaries around sensitive topics, and integrating gracefully with clinical care teams. Participants in the study effectively described a set of design requirements that developers of mental health AI would do well to treat as specifications rather than suggestions.

Yet the study also documents a darker set of worries that the participants themselves raised: the fear of losing critical thinking and becoming overreliant on AI companions. This concern is especially poignant for a population where autonomy and self-efficacy are hard-won achievements. An AI that is always available, always agreeable, and always attentive could, in principle, substitute for human connection rather than supplement it. The researchers note that it is essential these technologies lessen, rather than deepen, feelings of loneliness, a distinction that sounds subtle but carries enormous weight for the design and deployment of companion AI in mental health care.

These concerns do not arise in a vacuum. The study’s reference list situates the work within a rapidly growing literature on the mental health risks of large language model chatbots, including recent scoping reviews on chatbot-related harms, analyses of AI-associated delusions and mechanisms of delusion co-creation, and debates in leading psychiatry journals about whether generative AI chatbots might increase psychosis risk. For people with schizophrenia spectrum disorders in particular, the possibility that an AI companion could reinforce distorted thinking is a clinical question of the first order. The study’s participants, by voicing their own concerns about overreliance, demonstrated a sophisticated awareness of these risks that contradicts stereotypes about people with serious mental illness being unable to engage critically with technology.

At the same time, the broader research landscape suggests why AI companions hold such appeal. Loneliness and social isolation are widespread among adults in the United States and are especially pronounced among people with serious mental illness, who face stigma, social withdrawal, and reduced lifespans compared with the general population. Some studies have even found that third-party evaluators perceive AI responses as more compassionate than those of expert humans, and systematic reviews of chatbots versus human healthcare professionals have examined empathy in patient care with mixed but intriguing results. Against that backdrop, a companion that offers unconditional availability and a consistent, nonjudgmental presence has an obvious emotional pull, particularly during the nights and weekends when human support is scarce.

The study’s methodology also deserves attention for what it models. By recruiting participants through supportive housing facilities and partnering with community organizations, the research team reached a population that digital health studies frequently overlook. People with serious mental illness have historically been excluded from technology design processes, sometimes on the assumption that they cannot use or evaluate complex tools. Earlier qualitative work on how patients with schizophrenia use the internet, and international consensus efforts on digital mental health for severe mental illness, have pushed back against that exclusion. This study extends that tradition by treating participants as experts in their own lives, capable of articulating precisely what would make an AI companion feel safe, useful, and trustworthy.

The path forward, the authors suggest, lies in using these lived-experience insights to guide the development of AI tools for people with serious mental illnesses. That means building privacy protections that address the specific fears participants raised, designing personalization that respects clinical complexity, involving peer specialists and people with lived experience throughout the development cycle, and building in safeguards against overreliance. It also means honest acknowledgment of the tensions involved: the same system that tells a lonely person someone cares can become a substitute for the human relationships that recovery ultimately depends on. As AI reshapes healthcare through clinical decision support, communication tools, and patient monitoring, this study offers a reminder that the people most affected by these technologies have clear views about how they should work, and that listening to them is not just ethical but essential to building systems that actually help.

Subject of Research: Perspectives of people with serious mental illness on artificial intelligence-based companions in mental health care

Article Title: 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.”

Article References: Tapiavala, V., Chilakapati, S. S., Moore, D., Morales, S., Kumaran, A., Heller, R., Werlin, J., & Fortuna, K. L. (2026). 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.”. Community Mental Health Journal. https://doi.org/10.1007/s10597-026-01732-4

Image Credits: AI Generated

DOI: 10.1007/s10597-026-01732-4

Keywords: artificial intelligence, serious mental illness, AI companions, loneliness, schizophrenia, bipolar disorder, major depressive disorder, co-design, data privacy, digital mental health, qualitative research, supportive housing