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Population Modelling in Affective Disorders

Abstract:
Abstract Purpose of Review The prevalence of affective disorders is on the rise. This upward trajectory leads to a substantial personal and societal cost. There is growing body of literature demonstrating decision-making impairments associated with affective disorders, and more studies are using computational modelling methods to infer underlying mechanisms of these impairments from participant choice behaviour. However, lack of population modelling suggests that data resources may still be underutilised. Recent Findings A number of recent studies associated major depression with abnormal risky decision-making as well as impairments in temporal discounting and social decision-making. These domains capture relevant aspects of real-life decision-making. Consequently, data from these studies can be used to define behavioural phenotypes for major depression. Summary The manuscript describes a detailed proposal for population modelling to capture changes in the prevalence rate of major depression. The population modelling approach can also identify which decision-making domains can account for a larger part of impairments in psychosocial functioning and how behavioural interventions built on computational principles can target these to improve real-life psychosocial functioning in patient groups.
Publication status:
Published
Peer review status:
Peer reviewed

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Publisher copy:
10.1007/s40473-021-00229-6

Authors

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Institution:
University of Oxford
Role:
Author
ORCID:
0000-0002-2170-0677


Publisher:
Springer
Journal:
Current Behavioral Neuroscience Reports More from this journal
Volume:
8
Issue:
2
Pages:
21-27
Publication date:
2021-04-15
DOI:
EISSN:
2196-2979
ISSN:
2196-2979


Language:
English
Keywords:
Pubs id:
1173886
Local pid:
pubs:1173886
Source identifiers:
W3153080589
Deposit date:
2026-03-24
ARK identifier:
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