This Self_Emotion_Reward_Processing_Depression_readme.txt file was generated on 2020-09-28 by Catherine Hobbs.

GENERAL INFORMATION

1. Title of Dataset: Self_Emotion_Reward_Processing_Depression

2. Author Information
	A. Principal Investigator Contact Information
		Name: Catherine Hobbs	
		Institution: University of Bath
		Address: Department of Psychology, University of Bath, BA2 7AY
		Email: c.hobbs@bath.ac.uk

	B. Associate or Co-investigator Contact Information
		Name: Katherine S Button	
		Institution: University of Bath
		Address: Department of Psychology, University of Bath, BA2 7AY
		Email: k.s.button@bath.ac.uk
 

3. Date of data collection: 2018-10-01 to 2019-05-22

4. Geographic location of data collection: Department of Psychology, University of Bath, BA2 7AY

5. Information about funding sources that supported the collection of the data: This study was funded by a GW4 BioMed MRC Doctoral Training Partnership awarded to Catherine Hobbs.

SHARING/ACCESS INFORMATION

1. Licenses/restrictions placed on the data: CC BY 4.0

2. Links to publications that cite or use the data: TBC

3. Links to other publicly accessible locations of the data: N/A

4. Links/relationships to ancillary data sets: N/A

5. Was data derived from another source?: No
6. Recommended citation for this dataset: Hobbs C, Sui J, Munafo M R, Kessler D, Button K S. (2020). Dataset for ÔSelf processing in relation to emotion and reward processing in depressionÕ.





DATA & FILE OVERVIEW

1. File List: 
- Raw Anonymised Data
o Data
* Associative Learning
* raw_associative_anon.csv
* raw_associative_anon.xlsx
* CIS
* raw_CIS_anon.csv
* raw_CIS_anon.xlsx
* GNAT
* raw_GNAT_anon.csv
* raw_GNAT_anon.xlsx
* Questionnaires
* raw_qs_anon.csv
* raw_qs_anon.xlsx
* SEL
* raw_SEL_anon.csv
* raw_SEL_anon.xlsx
o Data Dictionary
* RawData_Dataframes_Dictionary.xlsx
o R Scripts
* GNAT_cleaning.R
* SEL_cleaning.R
* Questionnaires_CIS_cleaning.R
* Associative_cleaning.R
- Aggregated Data for Analysis
o Data
* Associative Learning
* associative_long_matching_anon
* associative_long_matching_collapsed_anon
* associative_wide_matching_anon
* associative_wide_matching_collapsed_anon
* associative_df_trial_anon
* GNAT
* GNAT_long_Qs_anon
* GNAT_wide_Qs_anon
* GNAT_trial_clean_Qs_anon
* Questionnaires, Demographics and CIS-R
* qs_anon
* SEL
* SEL_long_anon
* SEL_long_sep_rules_anon
* SEL_wide_anon
* SEL_trial_anon
* SEL_bias_anon
o Data Dictionary
* Analysis_dataframes_Dictionary.xlsx
o R Script
* Self_Emotion_Reward_Processing_Depression_Analysis.Rmd


2. Relationship between files, if important: 
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, .csv files, and .xlsx 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.

3. Additional related data collected that was not included in the current data package: 
Data that may have identified participants has been removed. With the exception of the mean number of days between sessions (which is reported for descriptive purposes only and is not used in inferential analyses), all data necessary to replicate the results reported in the paper are provided.

4. Are there multiple versions of the dataset? No

METHODOLOGICAL INFORMATION

1. Description of methods used for collection/generation of data: 
This study was pre-registered on Open Science Framework (https://osf.io/34ma2), which details the study methodology and data analysis plans. Briefly, this study aimed to examine the role of self-reference in emotion and reward processing, separately and in combination, in relation to depression. Participants experiencing varying levels of depression (n = 144) completed self-report depression measures (PHQ-9, BDI-II) across two sessions. 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.

2. Methods for processing the data: 
All data was cleaned and analysed using R. 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 Self_Emotion_Reward_Processing_Depression_Analysis.Rmd file.

3. Instrument- or software-specific information needed to interpret the data: 
R version 3.6

4. Data specific Information 
Full details of the variables included in each dataset are available in the data dictionary files (RawData_Dataframes_Dictionary.xlsx / Analysis_dataframes_Dictionary.xlsx).