ArticleJournal of religion and health2026
Artificial Intelligence at the Boundary of Spiritual Experience and Psychopathology: A Scoping Review of Evidence from Türkiye, the USA, the UK, Poland, South Korea, and Israel.
Article in Journal of religion and health, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
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Corrections and comments
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Authors and funding
5 authors.
Funding
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Abstract
The rapid integration of artificial intelligence (AI) into everyday life has created new intersections among digital technology, spirituality, mystical experience, and psychopathology. This scoping review aimed to map evidence on how AI mediates, reinforces, detects, predicts, or interprets religious and spiritual experiences at the boundary with psychosis and dissociation. PubMed, Web of Science, Embase, the Cochrane Library, and Scopus were searched through June 30, 2026, with supplementary reference-list screening and forward citation tracking. Study selection followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews. Nine studies from Türkiye, the USA, the UK, Poland, South Korea, and Israel were included. The evidence comprised clinical case reports, retrospective electronic health record analyses, qualitative studies, machine-learning investigations, and conceptual modeling. Conversational AI was reported as a catalyst, amplifier, co-author, or object of spiritually framed delusions, particularly in the presence of psychosis, mania, sleep disruption, substance exposure, or impaired reality testing. Conversely, natural language processing and machine-learning models showed preliminary potential for identifying documented psychotic episodes and predicting relapse. AI may therefore contribute to the reinforcement of psychopathological experiences while also offering preliminary support for psychiatric screening and risk prediction. Prospective, culturally diverse, and externally validated research is needed to clarify causal mechanisms and establish clinical, ethical, and technological safeguards.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.