Dataset for "The effect of acute citalopram on self-referential emotional processing and social cognition in healthy volunteers",Acute_Citalopram_Self_Social_Cognition,

  • Catherine Hobbs (Contributor)
  • Susannah E Murphy (Contributor)
  • Lucy Wright (Contributor)
  • James Carson (Contributor)
  • Van Assche Indra (Contributor)
  • Jessica O'Brien (Contributor)
  • Mayowa Oyesanya (Contributor)
  • Jie Sui (Contributor)
  • Marcus R Munafò (Contributor)
  • David Kessler (Contributor)
  • Catherine J Harmer (Contributor)
  • Katherine Button (Contributor)



This dataset is for a study examining whether acute administration of citalopram is associated with an increase in positive affective learning biases about the self and increases in prosocial behaviour. 41 healthy volunteers were randomised to either an acute 20 mg dose of citalopram (n = 20) or matched placebo (n = 21) in a between-subjects double-blind design. Participants completed computer-based cognitive tasks designed to measure referential affective processing, social cognition and expression of prosocial behaviours. This included a prisoners' dilemma task, the social evaluation learning task, a referential categorisation and recall task, an affective go/no-go association task and simple associative learning tasks. Participants also completed trait measures of mood and personality at baseline, and state measures of mood and side effects at baseline, post-drug and post-testing timepoints. Data for all questionnaire and cognitive task measures are included in this dataset in both raw and aggregated formats.,This study was pre-registered on Open Science Framework (, which details the study methodology and data analysis plans. Briefly, this study used a randomised between-subject double-blind design where participants were allocated to receive an acute dose of citalopram (20 mg) or placebo. Participants completed a number of cognitive tasks and self-report questionnaires of mood and personality.,Data files were anonymised by generating hashed IDs to replace participant unique identifiers using the digest package in R. Variables which could potentially identify participants were removed, including specific employment details, specific language spoken as a first language, and age in years and months (only years were retained).,R version 3.6 was used to clean and analyse the data. Full details of the process for cleaning the data can be found in the Raw anonymised data R scripts. Full details for analysing the data can be found in the Acute_Citalopram_Paper_Statistics.Rmd file.,The data for this study has been separated into two parts (1) the merged raw files produced by each of the cognitive tasks / questionnaires, (2) the cleaned data files and scripts that reflect the data analysis reported in our paper. For the raw data I have provided both .xlsx and .csv files, although I imported the data into R using .xlsx so there may be some discrepancies when using the .csv files with the R scripts. For the cleaned data for analysis I have provided the R dataframe files and .csv files. I imported the data into R using the dataframe files so again there may be discrepancies when using the R script with the .csv files. It is therefore recommended to use the .xlsx files for the raw data and the R dataframe files for the cleaned data if also using the accompanying R scripts.,
Date made available1 Jan 2020
PublisherUniversity of Bath

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