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Unrealistic optimism and 'nosognosia': illness recognition in the healthy brain
Ryan McKay1, Andreas Buchmann2, Nicole Germann2
1ARC Centre of Excellence in Cognition and its Disorders, Department of Psychology, Royal Holloway, University of London, United Kingdom.
Introduction:
At the centenary of research on anosognosia, the time seems ripe to supplement work in anosognosic patients with empirical studies on nosognosia in healthy participants. To this end, we adopted a signal detection framework to investigate the lateralized recognition of illness words--an operational measure of nosognosia--in healthy participants. As positively biased reports about one's current health status (anosognosia) and future health status (unrealistic optimism) have both been associated with deficient right hemispheric functioning, and conversely with undisturbed left hemispheric functioning, we hypothesised that more optimistic participants would adopt a more conservative response criterion, and/or display less sensitivity, when identifying illnesses in our nosognosia task; especially harmful illnesses presented to the left hemisphere via the right visual field.
Material And Methods:
Thirty-two healthy right-handed men estimated their own relative risk of contracting a series of illnesses in the future, and then completed a novel computer task assessing their recognition of illness names presented to the left or right visual field. To check that effects were specific to the recognition of illness (rather than reflecting recognition of lexical items per se), we also administered a standard lateralized lexical decision task.
Results:
Highly optimistic participants tended to be more conservative in detecting illnesses, especially harmful illnesses presented to the right visual field. Contrary to expectation, they were also more sensitive to illness names in this half-field.
Conclusions:
We suggest that, in evolutionary terms, unrealistic optimism may be an adaptive trait that combines a high perceptual sensitivity to threat with a high threshold for acknowledging its presence. The signal detection approach to nosognosia developed here may open up new avenues for the understanding of anosognosia in neurological patients.
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