Repository logo
 

Jumping to attributions during social evaluation.

Published version
Peer-reviewed

Repository DOI


Change log

Authors

Lau, Isabel HW 
Norman, Jessica 
Stothard, Melanie 
Carlisi, Christina O 
Moutoussis, Michael 

Abstract

Social learning is crucial for human relationships and well-being. Self- and other- evaluations are universal experiences, playing key roles in many psychiatric disorders, particularly anxiety and depression. We aimed to deepen our understanding of the computational mechanisms behind social learning, which have been implicated in internalizing conditions like anxiety and depression. We built on prior work based on the Social Evaluation Learning Task (SELT) and introduced a new computational model to better explain rapid initial inferences and progressive refinement during serial social evaluations. The Social Evaluation Learning Task-Revised (SELT-R) was improved by stakeholder input, making it more engaging and suitable for adolescents. A sample of 130 adults from the UK completed the SELT-R and questionnaires assessing symptoms of depression and anxiety. 'Classify-refine' computational models were compared with previously successful Bayesian models. The 'classify-refine' models performed better, providing insight into how people infer the attributes and motives of others. Parameters of the best fitting model from the SELT-R were correlated with Anxiety factor scores, with higher symptoms associated with greater decision noise and higher (less flexible) policy certainty. Our results replicate findings regarding the classify-refine process and set the stage for future investigations into the cognitive mechanisms of self and other evaluations in internalizing disorders.

Description

Acknowledgements: We thank Katherine Button, Janina Hoffman, Giles Story and the UCL Theoretical Neurobiology group for invaluable discussions. We thank Prof. Peter Fonagy for funding which helped with the coding of the task. COC and JN were supported by a Prudence Trust Senior Research Fellowship. IHWL was supported by a British Association for Psychopharmacology Summer Internship. The Department of Imaging Neuroscience is supported by the Wellcome Trust through a Platform Grant, the Max-Planck Society and by University College London.


Funder: British Association for Psychopharmacology Summer Internship


Funder: Prudence Trust Senior Research Fellowship

Keywords

Humans, Female, Male, Adult, Anxiety, Depression, Young Adult, Adolescent, Social Learning, Surveys and Questionnaires, Middle Aged, Bayes Theorem

Journal Title

Sci Rep

Conference Name

Journal ISSN

2045-2322
2045-2322

Volume Title

14

Publisher

Springer Science and Business Media LLC