Use and Perceptions of AI Chatbots for Mental Health Support Among Adults with Lived Experience
Notsu, H.; Nguyen, P. A.; Flathers, M.; Ryan, S. J.; Noorily, J.; Wentworth, L.; Crawford, C.; Wood, M.; Gillison, D.; Torous, J.
Show abstract
Importance: AI chatbots are increasingly used for mental health support, but little is known about how adults with lived experience of mental health condition use and perceive these tools. Objective: To characterize the use and perception of AI chatbots, including for mental health purposes, among adults connected to a large US mental health organization. Design: Cross-sectional online survey conducted from March to May 2026. Setting: Adults recruited through email newsletters from the National Alliance on Mental Illness (NAMI), the largest grassroots mental health organization in the US. Participants: Adults aged 18 years older with English proficiency. Affiliation with NAMI or a diagnosis of mental health disorder was not required. Results: Of 454 participants, 316 (69.6%) reported having used an AI chatbot. Use was more common among younger participants and those with a current mental health diagnosis. Among AI users, 133 (42.1%) reported using a chatbot for mental health purposes. Mental health-related use was typically brief and focused on information gathering and in-the-moment emotion regulation. Most users rated chatbots as helpful for their mental health. Among the 95 participants with a mental health provider, only 14 (14.7%) had openly discussed their AI use with their provider. Higher frequency of AI use was associated with greater odds of disclosure (OR, 1.67; 95% CI, 1.20-2.38; P = .003). Conclusion and Relevance: In this survey of adults connected to a large mental health organization, AI chatbots were widely used but engagement for mental health purposes was typically brief and focused. Most use occurred without clinician awareness, suggesting a need for proactive conversations about AI use in routine mental health care.
Matching journals
The top 5 journals account for 50% of the predicted probability mass.
Similar papers in this journal
- The Benefits and Harms of Open Notes in Mental Health: A Delphi Survey of International Experts 96%
- Service user experiences and views regarding telemental health during the COVID-19 pandemic: a co-produced framework analysis 95%
- A mixed methods analysis of youth mental health intervention feasibility and acceptability in a North American city: perspectives from Seattle, Washington 94%
Similar papers in this journal
- Remote working in mental health services: a rapid umbrella review of pre-COVID-19 literature 95%
- Tracking private WhatsApp discourse about COVID-19: A longitudinal infodemiology study in Singapore 94%
- Artificial Intelligence (AI)-based Chatbots in Promoting Health Behavioral Changes: A Systematic Review 94%
Similar papers in this journal
- Business as Un-usual: Access to mental health and primary care services for people with severe mental illness during the COVID-19 restrictions 95%
- Applications of Large Language Models in Psychiatry: A Systematic Review 94%
- Use of the Internet and digital devices among people with severe mental ill health during the COVID-19 pandemic restrictions 94%
Similar papers in this journal
- Evaluating the Clinical Feasibility of an Artificial Intelligence-Powered Clinical Decision Support System: A Longitudinal Feasibility Study 94%
- Development and use analysis of ‘gestioemocional.cat’, a web app for promoting emotional self-care and access to professional mental health resources during the covid-19 pandemic 93%
- Exploring Patient and Staff Experiences of Video Consultations During COVID-19 in an English Outpatient Care Setting: Secondary Data Analysis of Routinely Collected Feedback Data 93%
Similar papers in this journal
- Developing contents for a digital drug adherence tool with reminder cues and personalized feedback: a formative mixed-methods study among children and adolescents living with HIV in Tanzania 93%
- Exploring perspectives on digital smoking cessation just-in-time adaptive interventions: A focus group study with adult smokers and smoking cessation professionals 93%
- Defining Destigmatizing Design Guidelines for Use in Sexual Health-Related Digital Technologies: A Delphi Study 93%
"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.