Technological folie à deux: feedback loops between AI chatbots and mental health
Open accessAbstract
Artificial intelligence chatbots have achieved unprecedented adoption, with millions now using these systems for emotional support and companionship in contexts of widespread social isolation and capacity-constrained mental health services. While some users report psychological benefits, concerning edge cases are emerging, including reports of suicide, violence, and delusional thinking linked to emotional relationships with chatbots. To understand these risks we need to consider the interaction between human cognitive-emotional biases and chatbot behavioural tendencies, the latter including companionship-reinforcing behaviours such as sycophancy, role-play and anthropomimesis. Individuals with preexisting mental health conditions may face increased risks of chatbot-induced changes in beliefs and behaviour, particularly where these conditions manifest in altered belief-updating, reality-testing, and social isolation. To address this emerging public health concern, we need coordinated action across clinical practice, AI development, and regulatory frameworks.
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Common concerns associated with LLM-CBs are hallucinations (incorrect information generated by LLM-CBs, including incorrect health advice) and sycophancy (LLM-CBs' tendencies to agree with the user despite potentially incorrect or harmful statements).
“Common concerns associated with LLM-CBs are hallucinations (i.e., incorrect information generated by LLM-CBs, including incorrect health advice)15 and sycophancy (i.e., LLM-CBs’ tendencies to agree with the user despite potentially incorrect or harmful statements)16.”
From A scoping review on the mental health harms of LLM-based chatbots (2026) · cites this paper as [16]
Split into 2 atoms — 1 confirmed, 1 partially supported, 0 disputed, 0 misattributed, 0 unverifiable. Expand the claim to see per-atom verdicts.
Experimental — accuracy not yet measuredDohnány et al. introduced the term folie à deux (i.e., induced psychosis) or bidirectional belief amplification in the context of "AI psychosis," noting that users' inputs feed LLM-CBs' memory and chatbots adapt to delusional thoughts.
“Dohnány et al. introduced the term folie à deux (i.e., induced psychosis) or bidirectional belief amplification in the context of “AI psychosis,” noting that users’ inputs feed LLM-CBs’ memory and chatbots adapt to delusional thoughts16.”
From A scoping review on the mental health harms of LLM-based chatbots (2026) · cites this paper as [16]
In “Feedback loops and technological folie à deux” (page unavailable), the paper applies folie à deux to human–chatbot interactions and describes bidirectional belief amplification, including chatbot adaptation to user-expressed paranoia. It says users’ reinforced beliefs feed back through conversational context, but does not establish that those inputs are stored in chatbot memory; its discussion of external memory systems describes future systems. (LLM, conf=0.84)
Experimental — accuracy not yet measuredAs LLM-CBs adapt to the user's delusional input, reality checks may be outsourced to LLM-CBs.
“As LLM-CBs adapts to the user’s delusional input16, reality checks may be outsourced to LLM-CBs140.”
From A scoping review on the mental health harms of LLM-based chatbots (2026) · cites this paper as [16]
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AI-Driven Iatrogenesis: Risks of Using Generative AI for Mental Health Support (Preprint)Preprint
Prodan, A., Occhipinti, J., Meadows, G. N., Jeste, D. V., Satake, Y., Świeboda, P., & Martin, M. (2026) · doi:10.2196/preprints.114150
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Kotas, M., Pichowicz, W., Karska, J., Żełabowski, K., Piotrowski, P., & Misiak, B. (2026) · Schizophrenia Research · doi:10.1016/j.schres.2026.10.010
- Authors
- Dohnány, S., Kurth-Nelson, Z., Spens, E., Luettgau, L., Reid, A., Gabriel, I., Summerfield, C., Shanahan, M., & Nour, M. M.
- Affiliations
- University of Oxford (GB)
- University College London (GB)
- Oxford Health NHS Foundation Trust (GB)
- University of London (GB)
- Imperial College London (GB)
- Corresponding author
- Nour, Matthew M.
- ORCID
- Venue
- Nature Mental Health
- Published
- 2026-03-10
- Volume
- 4
- Issue
- 3
- Pages
- 336-345
- ISSN
- 2731-6076 (ISSN-L)
- PMC
- PMC7618964
- OpenAlex
- W7134947688
- Cited by
- 51
- References
- 95
- Citations by year
- 2026: 51
- FWCI
- 300.37
- Type
- journal article
- Language
- en
- Open access
- green
- pmc.ncbi.nlm.nih.gov
- Licence
- Locations
- Nature Mental Health (publishedVersion)
- PubMed (publishedVersion)
- PubMed Central (publishedVersion, cc-by)
- MPG.PuRe (Max Planck Society) (submittedVersion)
- Funders
- Wellcome Trust (315364/Z/24/Z)
- Merton College, University of Oxford (NA)
- Topics
- Social Sciences › Psychology › Applied Psychology › Digital Mental Health Interventions
- Social Sciences › Safety Research › Ethics and Social Impacts of AI
- Social Sciences › Psychology › Social Psychology › Social Robot Interaction and HRI
- Keywords
- AI chatbots, mental health, emotional support, social isolation, sycophancy, role play, belief updating, suicide, AI regulation
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