Delusions

PurposePersecutory delusions are a central psychotic experience, at the severe end of a paranoia spectrum in the general population. The aim of the review is to provide an introduction to the understanding of persecutory delusions, highlight key putative causal factors that have the potential to be translated into efficacious treatment, and indicate future research directions.MethodsA narrative literature review was undertaken to highlight the main recent areas of empirical study concerning non-clinical and clinical paranoia.ResultsSix main proximal causal factors are identified: a worry thinking style, negative beliefs about the self, interpersonal sensitivity, sleep disturbance, anomalous internal experience, and reasoning biases. Each has plausible mechanistic links to the occurrence of paranoia. These causal factors may be influenced by a number of social circumstances, including adverse events, illicit drug use, and urban environments.ConclusionsThere have been numerous replicated empirical findings leading to a significant advance in the understanding of persecutory delusions, now beginning to be translated into cognitive treatments. The first trials specifically focussed on patients who have persecutory delusions in the context of psychotic diagnoses are occurring. Initial evidence of efficacy is very promising.

BackgroundPersecutory delusions may be unfounded threat beliefs maintained by safety-seeking behaviours that prevent disconfirmatory evidence being successfully processed. Use of virtual reality could facilitate new learning.AimsTo test the hypothesis that enabling patients to test the threat predictions of persecutory delusions in virtual reality social environments with the dropping of safety-seeking behaviours (virtual reality cognitive therapy) would lead to greater delusion reduction than exposure alone (virtual reality exposure).MethodConviction in delusions and distress in a real-world situation were assessed in 30 patients with persecutory delusions. Patients were then randomised to virtual reality cognitive therapy or virtual reality exposure, both with 30 min in graded virtual reality social environments. Delusion conviction and real-world distress were then reassessed.ResultsIn comparison with exposure, virtual reality cognitive therapy led to large reductions in delusional conviction (reduction 22.0%, P = 0.024, Cohen's d = 1.3) and real-world distress (reduction 19.6%, P = 0.020, Cohen's d = 0.8).ConclusionCognitive therapy using virtual reality could prove highly effective in treating delusions.

Recent research has shown that worry is associated with distressing paranoia. Therefore, the aim was to target worry in a therapeutic intervention for individuals with delusions. It was predicted that a worry intervention would reduce levels of worry and paranoia distress. Twenty-four individuals with persistent persecutory delusions and high levels of worry were randomly assigned to receive a four session cognitive-behavioural worry intervention (W-CBT) or treatment as usual (TAU). The worry intervention was specifically designed not to target the content of delusions. In this open-label evaluation, assessments of worry and paranoia were conducted at baseline, at one month (end of treatment) and at two months. The worry intervention achieved a statistically significant reduction in worry which was maintained at two month follow up. A significant reduction in delusional distress was also reported. There was an indication that the worry intervention may also reduce the frequency of paranoid thoughts but this was not statistically significant. In the first trial specifically for persecutory delusions, a brief worry intervention was shown to have benefits. The results support a causal role for worry in paranoid experience.

The integration of artificial intelligence (AI) into daily life has introduced unprecedented forms of human-machine interaction, prompting psychiatry to reconsider the boundaries between environment, cognition, and technology. This Viewpoint reviews the concept of "AI psychosis," which is a framework to understand how sustained engagement with conversational AI systems might trigger, amplify, or reshape psychotic experiences in vulnerable individuals. Drawing from phenomenological psychopathology, the stress-vulnerability model, cognitive theory, and digital mental health research, the paper situates AI psychosis at the intersection of predisposition and algorithmic environment. Rather than defining a new diagnostic entity, it examines how immersive and anthropomorphic AI technologies may modulate perception, belief, and affect, altering the prereflective sense of reality that grounds human experience. The argument unfolds through 4 complementary lenses. First, within the stress-vulnerability model, AI acts as a novel psychosocial stressor. Its 24-hour availability and emotional responsiveness may increase allostatic load, disturb sleep, and reinforce maladaptive appraisals. Second, the digital therapeutic alliance, a construct describing relational engagement with digital systems, is conceptualized as a double-edged mediator. While empathic design can enhance adherence and support, uncritical validation by AI systems may entrench delusional conviction or cognitive perseveration, reversing the corrective principles of cognitive-behavioral therapy for psychosis. Third, disturbances in theory of mind offer a cognitive pathway: individuals with impaired or hyperactive mentalization may project intentionality or empathy onto AI, perceiving chatbots as sentient interlocutors. This dyadic misattribution may form a "digital folie à deux," where the AI becomes a reinforcing partner in delusional elaboration. Fourth, emerging risk factors, including loneliness, trauma history, schizotypal traits, nocturnal or solitary AI use, and algorithmic reinforcement of belief-confirming content may play roles at the individual and environmental levels. Building on this synthesis, we advance a translational research agenda and five domains of action: (1) empirical studies using longitudinal and digital-phenotyping designs to quantify dose-response relationships between AI exposure, stress physiology, and psychotic symptomatology; (2) integration of digital phenomenology into clinical assessment and training; (3) embedding therapeutic design safeguards into AI systems, such as reflective prompts and "reality-testing" nudges; (4) creation of ethical and governance frameworks for AI-related psychiatric events, modeled on pharmacovigilance; and (5) development of environmental cognitive remediation, a preventive intervention aimed at strengthening contextual awareness and reanchoring experience in the physical and social world. By applying empirical rigor and therapeutic ethics to this emerging interface, clinicians, researchers, patients, and developers can transform a potential hazard into an opportunity to deepen understanding of human cognition, safeguard mental health, and promote responsible AI integration within society.