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Virtual reality and paranoid ideations in people with an 'at-risk mental state' for psychosis.

Valmaggia, LR; Freeman, D; Green, C; Garety, P; Swapp, D; Antley, A; Prescott, C; (2007) Virtual reality and paranoid ideations in people with an 'at-risk mental state' for psychosis. Br J Psychiatry Suppl , 51 s63-s68. 10.1192/bjp.191.51.s63.

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Abstract

BACKGROUND: Virtual reality provides a means of studying paranoid thinking in controlled laboratory conditions. However, this method has not been used with a clinical group. AIMS: To establish the feasibility and safety of using virtual reality methodology in people with an at-risk mental state and to investigate the applicability of a cognitive model of paranoia to this group. METHOD: Twenty-one participants with an at-risk mental state were assessed before and after entering a virtual reality environment depicting the inside of an underground train. RESULTS: Virtual reality did not raise levels of distress at the time of testing or cause adverse experiences over the subsequent week. Individuals attributed mental states to virtual reality characters including hostile intent. Persecutory ideation in virtual reality was predicted by higher levels of trait paranoia, anxiety, stress, immersion in virtual reality, perseveration and interpersonal sensitivity. CONCLUSIONS: Virtual reality is an acceptable experimental technique for use with individuals with at-risk mental states. Paranoia in virtual reality was understandable in terms of the cognitive model of persecutory delusions.

Type: Article
Title: Virtual reality and paranoid ideations in people with an 'at-risk mental state' for psychosis.
Location: England
DOI: 10.1192/bjp.191.51.s63
Keywords: Adolescent, Adult, Computer Simulation, Delusions, Feasibility Studies, Female, Humans, Male, Paranoid Disorders, Psychiatric Status Rating Scales, Psychometrics, Psychotic Disorders, Stress, Psychological, User-Computer Interface
UCL classification: UCL > School of BEAMS > Faculty of Engineering Science
UCL > School of BEAMS > Faculty of Engineering Science > Computer Science
URI: http://discovery.ucl.ac.uk/id/eprint/128308
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