Dataset for 'Self-processing in relation to emotion and reward processing in depression'

This dataset is for a study examining the role of self processing in relation to emotion and reward processing in depression. Participants (n = 144) with varying levels of depression symptoms completed cognitive tasks measuring self processing independently and in combination with emotion and reward processing over two session approximately one week apart. This dataset contains the raw trial level and cleaned aggregate data used for analysis for each of these cognitive tasks (Associative Learning, Go/No-Go Self-Esteem, Social Evaluation Learning), self-report questionnaire data for mood, demographics and output from the clinical interview schedule-revised (.csv, .xlsx and .RDA files). Code used for cleaning and analysis is also provided in the form of R Notebook files.

depression, self, emotion, reward, social cognition

Cite this dataset as:
Hobbs, K., Button, K., 2021. Dataset for 'Self-processing in relation to emotion and reward processing in depression'. Bath: University of Bath Research Data Archive. Available from:


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Hobbs_Self …
application/zip (80MB)
Creative Commons: Attribution 4.0


Self_Emotion … Analysis_210813.Rmd
text/plain (121kB)
Creative Commons: Attribution 4.0

Data analysis code for aggregated data as reported in the manuscript


Katie Hobbs
University of Bath


Jie Sui
University of Aberdeen

Marcus R. Munafo
University of Bristol

David Kessler
University of Bristol

University of Bath
Rights Holder


Collection date(s):

From 1 October 2018 to 22 May 2019

Geographical coverage:

10 West, Department of Psychology, University of Bath, BA2 7AY


Data collection method:

We recruited participants aged 18 to 65, fluent in English, with normal or corrected to normal vision, through campus advertising at the University of Bath. As depression severity is positively skewed within the general population (Tomitaka et al., 2015), to ensure balanced levels of depression we screened participants using the Patient Health Questionnaire (PHQ-9; Kroenke et al., 2001). We recruited an equal number of participants with no depression (PHQ-9 less than or equal to 4), mild depression (PHQ-9 5-9) and moderate to severe depression (PHQ-9 greater than or equal to 10). Participants completed self-report depression measures (PHQ-9, BDI-II) across two sessions approximately one week apart. We measured self, emotion, and reward processing, separately and in combination, using three cognitive tasks. This included simple associative learning task, a self-esteem go/no-go task, and a social evaluation learning task.

Data processing and preparation activities:

Data was anonymised prior to cleaning, through random re-assignment of unique IDs and removal of potentially identifying variables (e.g. exact date of sessions). Aside from the anonymisation changes, the raw data is provided as well as the code used to clean data to produce the aggregate data used for analysis. For clarity the code used for anonymisation is provided in the R scripts for cleaning raw data in comments.

Technical details and requirements:

The data was cleaned and analysed using R version 3.6. Data is provided in .CSV, .XLSX and .RDA files which can be opened with a variety of software.

Additional information:

A data dictionary is provided outlining the organisation of data and describing individual variables.

Documentation Files

Self_Emotion … Depression_readme.txt
text/plain (5kB)
Creative Commons: Attribution 4.0


Medical Research Council (MRC)

GW4 BioMed Doctoral Training Partnership

Publication details

Publication date: 7 September 2021
by: University of Bath

Version: 1


URL for this record:

Related papers and books

Hobbs, C., Sui, J., Kessler, D., Munafò, M. R., and Button, K. S., 2021. Self-processing in relation to emotion and reward processing in depression. Psychological Medicine, 1-13. Available from:

Related online resources

Hobbs, C., Kessler, D., Munafo, M. R., Sui, J., and Button, K. S., 2020. Biased Self-Referential Processing in Depression. OSF. Available from:

Contact information

Please contact the Research Data Service in the first instance for all matters concerning this item.

Contact person: Katie Hobbs


Faculty of Humanities & Social Sciences