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Confidence, accuracy judgments and feedback in schizophrenia and bipolar disorder: a time series network analysis

Published online by Cambridge University Press:  28 April 2022

Varsha D. Badal Open the ORCID record for Varsha D. Badal [Opens in a new window] ,
Colin A. Depp Open the ORCID record for Colin A. Depp [Opens in a new window] ,
Philip D. Harvey ,
Robert A. Ackerman ,
Raeanne C. Moore  and
Amy E. Pinkham
Varsha D. Badal
Affiliation:
Department of Psychiatry, University of California San Diego, San Diego, California, USA Sam and Rose Stein Institute for Research on Aging, University of California San Diego, San Diego, California, USA
Colin A. Depp*
Affiliation:
Department of Psychiatry, University of California San Diego, San Diego, California, USA Sam and Rose Stein Institute for Research on Aging, University of California San Diego, San Diego, California, USA VA San Diego Healthcare System, La Jolla, California, USA
Philip D. Harvey
Affiliation:
Department of Psychiatry and Behavioral Sciences, University of Miami Miller School of Medicine, Miami, FL, USA Research Service, Miami VA Healthcare System, Miami, FL, USA
Robert A. Ackerman
Affiliation:
School of Behavioral and Brain Sciences, The University of Texas at Dallas, Richardson, TX, USA
Raeanne C. Moore
Affiliation:
Department of Psychiatry, University of California San Diego, San Diego, California, USA VA San Diego Healthcare System, La Jolla, California, USA
Amy E. Pinkham
Affiliation:
School of Behavioral and Brain Sciences, The University of Texas at Dallas, Richardson, TX, USA Department of Psychiatry, University of Texas Southwestern Medical School, Dallas, TX, USA
*
Author for correspondence: Colin A. Depp, E-mail: cdepp@ucsd.edu
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Abstract

Background

Inaccurate self-assessment of performance is common among people with serious mental illness, and it is associated with poor functional outcomes independent from ability. However, the temporal interdependencies between judgments of performance, confidence in accuracy, and feedback about performance are not well understood.

Methods

We evaluated two tasks: the Wisconsin Card Sorting Test (WCST) and the Penn Emotion recognition task (ER40). These tasks were modified to include item-by-item confidence and accuracy judgments, along with feedback on accuracy. We evaluated these tasks as time series and applied network modeling to understand the temporal relationships between momentary confidence, accuracy judgments, and feedback. The sample constituted participants with schizophrenia (SZ; N = 144), bipolar disorder (BD; N = 140), and healthy controls (HC; N = 39).

Results

Network models for both WCST and ER40 revealed denser and lagged connections between confidence and accuracy judgments in SZ and, to a lesser extent in BD, that were not evidenced in HC. However, associations between feedback regarding accuracy with subsequent accuracy judgments and confidence were weaker in SZ and BD. In each of these comparisons, the BD group was intermediate between HC and SZ. In analyses of the WCST, wherein incorporating feedback is crucial for success, higher confidence predicted worse subsequent performance in SZ but not in HC or BD.

Conclusions

While network models are exploratory, the results suggest some potential mechanisms by which challenges in self-assessment may impede performance, perhaps through hyperfocus on self-generated judgments at the expense of incorporation of feedback.

Keywords

Bipolar disordercognitionmetacognitionnetwork analysisschizophreniacausal time series analysis
Type
Original Article
Information
Psychological Medicine , Volume 53 , Issue 9 , July 2023 , pp. 4200 - 4209
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Copyright
Copyright © The Author(s), 2022. Published by Cambridge University Press

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