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Virtual reality study of paranoid thinking in the general population

Department of Psychology, Institute of Psychiatry, King's College London

Angus Antley, MS

Department of Computer Science, University College London

Mel Slater, DSc

Department of Computer Science, University College London, UK, and Universitat Politècnica de Catalunya, Barcelona, Spain

Paul Bebbington, PhD

Department of Mental Health Sciences, University College London, Royal Free and University College Medical School, London

Matthew Gittins, MSc and Graham Dunn, PhD

Health Methodology Research Group, School of Community Based Medicine, University of Manchester, Manchester

Elizabeth Kuipers, PhD

Department of Psychology, Institute of Psychiatry, King's College London

David Fowler, MSc

School of Medicine, Health Policy and Practice, University of East Anglia, Norwich

Philippa Garety, PhD

Department of Psychology, Institute of Psychiatry, King's College London, UK

Correspondence: Dr Daniel Freeman, Department of Psychology, PO Box 77, Institute of Psychiatry, King's College London, Denmark Hill, London, SE5 8AF, UK. Email: D.Freeman{at}iop.kcl.ac.uk

Declaration of interest

None. Funding detailed in Acknowledgements.

Background

Judging whether we can trust other people is central to social interaction, despite being error-prone. A fear of others can be instilled by the contemporary political and social climate. Unfounded mistrust is called paranoia, and in severe forms is a central symptom of schizophrenia.

Aims

To demonstrate that individuals without severe mental illness in the general population experience unfounded paranoid thoughts, and to determine factors predictive of paranoia using the first laboratory method of capturing the experience.

Method

Two hundred members of the general public were comprehensively assessed, and then entered a virtual reality train ride populated by neutral characters. Ordinal logistic regressions (controlling for age, gender, ethnicity, education, intellectual functioning, socio-economic status, train use, playing of computer games) were used to determine predictors of paranoia.

Results

The majority agreed that the characters were neutral, or even thought they were friendly. However, a substantial minority reported paranoid concerns. Paranoia was strongly predicted by anxiety, worry, perceptual anomalies and cognitive inflexibility.

Conclusions

This is the most unambiguous demonstration of paranoid ideation in the general public so far. Paranoia can be understood in terms of cognitive factors. The use of virtual reality should lead to rapid advances in the understanding of paranoia.

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