Rethinking Generative Artificial Intelligence Use in Schizophrenia Spectrum Disorders: A Metacognitive Framework

The rapid expansion of generative artificial intelligence (AI) in daily life and mental health contexts has generated both enthusiasm and concern. Within schizophrenia spectrum disorders (SSDs), generative AI use is sometimes framed as inherently destabilizing or unsafe. Such blanket assertions risk reinforcing longstanding stigmatizing assumptions that individuals with SSDs cannot engage responsibly with emerging technologies. Drawing on emerging literature on generative AI in mental health and SSDs, as well as the integrated model of metacognition, we propose a conceptual framework in which baseline metacognitive capacity may influence how individuals engage with generative AI tools. Individuals with relatively intact metacognitive capacity may be better able to approach and utilize generative AI in a reflective manner. In contrast, individuals with more limited metacognitive capacity may be more vulnerable to passively accepting AI-generated content, outsourcing reflection, or experiencing adverse outcomes. We hypothesize that metacognitive capacity may represent one individual-level factor influencing the relationship between generative AI engagement and outcomes, alongside characteristics of the individual, technology, and broader clinical and social context. These proposed relationships remain theoretical and require empirical validation. We conclude with anti-stigma implications, calling for nuanced approaches to generative AI use in SSDs and greater inclusion of individuals with lived experience in conversations about technological innovation.