Bayesian modelling of Jumping-to-Conclusions bias in delusional patients

Michael Moutoussis, Richard P. Bentall, Wael El-Deredy, Peter Dayan

    Research output: Contribution to journalArticlepeer-review


    Introduction. When deciding about the cause underlying serially presented events, patients with delusions utilise fewer events than controls, showing a Jumping-to-Conclusions bias. This has been widely hypothesised to be because patients expect to incur higher costs if they sample more information. This hypothesis is, however, unconfirmed. Methods. The hypothesis was tested by analysing patient and control data using two models. The models provided explicit, quantitative variables characterising decision making. One model was based on calculating the potential costs of making a decision; the other compared a measure of certainty to a fixed threshold. Results. Differences between paranoid participants and controls were found, but not in the way that was previously hypothesised. A greater noise in decision making (relative to the effective motivation to get the task right), rather than greater perceived costs, best accounted for group differences. Paranoid participants also deviated from ideal Bayesian reasoning more than healthy controls. Conclusions. The Jumping-to-Conclusions Bias is unlikely to be due to an overestimation of the cost of gathering more information. The analytic approach we used, involving a Bayesian model to estimate the parameters characterising different participant populations, is well suited to testing hypotheses regarding hidden variables underpinning observed behaviours. © 2011 Psychology Press, an imprint of the Taylor & Francis Group, an Informa business.
    Original languageEnglish
    Pages (from-to)422-447
    Number of pages25
    JournalCognitive Neuropsychiatry
    Issue number5
    Publication statusPublished - Sept 2011


    • Bayesian reasoning
    • Jumping-to-Conclusions
    • Paranoia
    • Psychosis
    • Sequential probability ratio test


    Dive into the research topics of 'Bayesian modelling of Jumping-to-Conclusions bias in delusional patients'. Together they form a unique fingerprint.

    Cite this