Bias in favour of self-selected hypotheses is associated with delusion severity in schizophrenia

Abstract

Introduction

Delusions are typically characterised by idiosyncratic, self-generated explanations used to interpret events, as opposed to the culturally normative interpretations. Thus, a bias in favour of one's own hypotheses may be a fundamental aspect of delusions.

Methods

We tested this possibility in the current study by comparing judgements of self-selected hypotheses to judgements of externally selected ones in a probabilistic reasoning task. This allowed us to equate self- and externally selected hypotheses in terms of objectively quantifiable supporting evidence. It is normal to be biased in favour of self-selected hypotheses, but we expected this bias to be exacerbated in schizophrenia patients relative to healthy and psychiatric controls, and to be correlated with the severity of delusions in the schizophrenia sample.

Results

As expected, all groups showed the self-selection bias. Although this bias was not increased in schizophrenia patients relative to the control groups, it was significantly correlated with the severity of delusions in the schizophrenia sample.

Conclusions

These results fit with an account holding that the hypersalience of an individual's own interpretations of events, relative to culturally normative interpretations, may manifest in a self-selection bias, contributing to the delusional state in schizophrenia.

Keywords:

• Delusions
• Hypersalience
• Probabilistic reasoning
• Schizophrenia
• Self-selection bias

This work was supported by the Natural Sciences and Engineering Research Council of Canada Operating Grant (RGPIN 343016-07), the Canadian Institutes of Health Research New Investigator Award (TSW), the Michael Smith Foundation for Health Research Scholar Award (TSW), the Natural Sciences and Engineering Research Council of Canada Post Graduate Scholarship Award (JCW), and the Michael Smith Foundation for Health Research Senior Trainee Award (JCW). The authors would like to thank Sarah Flann and Sara Hughes for their assistance with data collection and data management.