Dataset for “Lack of optimistic biases in depression and social anxiety is reflected in reduced positive self-beliefs, but distinct processing of social feedback”
This study aimed to examine learning of social evaluations associated with psychopathology. We used two independent datasets (n = 552 and n = 807) to assess the relationship between depression (PHQ-9), social anxiety (BFNE), and learning of positive and negative evaluations about the self and an other.
Cite this dataset as:
Hobbs, K.,
Hoffmann, J.,
Button, K.,
2023.
Dataset for “Lack of optimistic biases in depression and social anxiety is reflected in reduced positive self-beliefs, but distinct processing of social feedback”.
Bath: University of Bath Research Data Archive.
Available from: https://doi.org/10.15125/BATH-01108.
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Data
Dataset 2 Data Archive.zip
application/zip (1MB)
Creative Commons: Attribution 4.0
Dataset comprised of individual participant level data from participants recruited online with data for the social evaluation learning task and self-report measures of depression and social anxiety (dataset 2).
Mixed access regime: The files from dataset 2 are available as open access, however as studies in dataset 1 did not obtain consent from participants to publish data as open access this data has been made available only to bona fide researchers with ethical approval.
Creators
Katie Hobbs
University of Bath
Janina Hoffmann
University of Bath
Katherine Button
University of Bath
Contributors
University of Bath
Rights Holder
Documentation
Data collection method:
This study aimed to examine learning of social evaluations associated with psychopathology. We created two datasets for this study. Firstly, we collated individual participant data from ten studies previously collected within this research group (dataset 1; n = 552). To assess the reliability of our findings from dataset 1, we collected a second independent dataset using the online recruitment platform Prolific (dataset 2; n = 807). In both datasets participants completed self-report measures of mood including depression (PHQ-9) and social anxiety (BFNE), and a computerised cognitive task where participants were asked to learn whether the computer liked the self and a fictional other based on the computers’ feedback to selection of a positive or negative social evaluative word pairs. In dataset 1 participants completed the study materials in psychology labs under the supervision of researchers. In dataset 2 participants completed the study materials independenly using online survey (qualtrics) and cognitive task (inquisit) software.
Data processing and preparation activities:
Data was anonymised through assignment of unique subject IDs and removal of potentially identifying information.
Technical details and requirements:
R version 4.0.5
Additional information:
In the associated manuscript for this study we report findings from two datasets. Our first dataset was comprised of individual participant level data from ten studies previously conducted within this research group (dataset 1). To validate the findings of this first dataset, we collected a second independent dataset using the online recruitment platform Prolific (dataset 2). The files from dataset 2 are available as open access, however as studies in dataset 1 did not obtain consent from participants to publish data as open access this data has been made available under restricted access conditions. Four different data files are included for each dataset relating to (1) questionnaire measures (2) trial level social evaluation learning task data, (3) aggregate level SEL task outcome data for all trials completed per referential condition-rule block, and (4) aggregate level SEL task outcome data for 20 trials completed per referential condition-rule block. In our analyses for aggregated data we used the files with 20 trials to match with the minimum number of trials completed in one study in dataset 1.
Methodology link:
Hoffmann, J., Hobbs, C., Button, K., Hopkins, A. K., and Moutoussis, M., 2020. Individual differences in social evaluation learning. Open Science Framework. Available from: https://doi.org/10.17605/OSF.IO/HX6P9.
Documentation Files
README.txt
text/plain (4kB)
Creative Commons: Attribution 4.0
Legal and Ethical Documents
Consent.docx
application/vnd.openxmlformats-officedocument.wordprocessingml.document (14kB)
Creative Commons: Attribution 4.0
Consent form for dataset 2
Funders
University of Bath
https://doi.org/10.13039/501100000835
Medical Research Council
https://doi.org/10.13039/501100000265
GW4 BioMed MRC Doctoral Training Partnership
MR/N0137941/1
Publication details
Publication date: 2 July 2023
by: University of Bath
Version: 1
DOI: https://doi.org/10.15125/BATH-01108
URL for this record: https://researchdata.bath.ac.uk/id/eprint/1108
Related papers and books
Hoffmann, J. A., Hobbs, C., Moutoussis, M., and Button, K. S., 2023. Lack of optimistic biases in depression and social anxiety is reflected in reduced positive self-beliefs, but distinct processing of social feedback. Center for Open Science. Available from: https://doi.org/10.31234/osf.io/h6ety.
Related theses
Hobbs, C., 2022. A neurocognitive investigation of the role of reinforcement learning in updating dysfunctional self-schema in depression: A putative mechanism for antidepressant action? (Alternative Format Thesis). Thesis (PhD). University of Bath. Available from: https://researchportal.bath.ac.uk/en/studentTheses/a-neurocognitive-investigation-of-the-role-of-reinforcement-learn.
Contact information
Please contact the Research Data Service in the first instance for all matters concerning this item.
Contact person: Katherine Button
Faculty of Humanities & Social Sciences
Psychology