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Population Modelling in Affective Disorders
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 computation...
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer International Publishing
2021
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8047557/ https://www.ncbi.nlm.nih.gov/pubmed/33875934 http://dx.doi.org/10.1007/s40473-021-00229-6 |
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author | Pulcu, Erdem |
author_facet | Pulcu, Erdem |
author_sort | Pulcu, Erdem |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-8047557 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Springer International Publishing |
record_format | MEDLINE/PubMed |
spelling | pubmed-80475572021-04-15 Population Modelling in Affective Disorders Pulcu, Erdem Curr Behav Neurosci Rep Mood and Anxiety Disorders (E Pulcu and C Harmer, Section Editors) 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. Springer International Publishing 2021-04-15 2021 /pmc/articles/PMC8047557/ /pubmed/33875934 http://dx.doi.org/10.1007/s40473-021-00229-6 Text en © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Mood and Anxiety Disorders (E Pulcu and C Harmer, Section Editors) Pulcu, Erdem Population Modelling in Affective Disorders |
title | Population Modelling in Affective Disorders |
title_full | Population Modelling in Affective Disorders |
title_fullStr | Population Modelling in Affective Disorders |
title_full_unstemmed | Population Modelling in Affective Disorders |
title_short | Population Modelling in Affective Disorders |
title_sort | population modelling in affective disorders |
topic | Mood and Anxiety Disorders (E Pulcu and C Harmer, Section Editors) |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8047557/ https://www.ncbi.nlm.nih.gov/pubmed/33875934 http://dx.doi.org/10.1007/s40473-021-00229-6 |
work_keys_str_mv | AT pulcuerdem populationmodellinginaffectivedisorders |