READ ME File For 'Dataset: Sleep Quality and the Self: An Investigation of the Relationship Between Sleep Quality and the Multidimensional Self' Dataset DOI: https://doi.org/10.5258/SOTON/D3534 ReadMe Author: James W Butterworth, University of Southampton https://orcid.org/0000-0002-0867-7353 This dataset supports the thesis entitled: Sleep Quality and the Self: An Investigation of the Relationship Between Sleep Quality and the Multidimensional Self. AWARDED BY: University of Southampton DATE OF AWARD: 2025 Date of data collection: October 2018 - September 2023 Information about geographic location of data collection: All online data collected from UK residents and UK University students currently residing in the UK. All in-person data (e.g. actigraphy) collected from UK University students, currently residing in the UK. Licence: CC-BY Related projects/Funders: This project was funded by the University of Southampton Jubilee Scholarship. -------------------- DATA & FILE OVERVIEW -------------------- This dataset contains seven [7] files of four [4] studies that were created to examine the findings of this thesis. All files are SPSS files, saved as .sav file type. The first data file (titled: Sleep and Self S1 (11.10.22)_FINAL) contains quantitative data collected via online survey for Study 1. This data examines the correlational relationship between sleep quality and multiple self-constructs. The second and third data files (titled: Sleep and Self S2 (09.08.23) - coupled; Sleep and Self S2 (09.08.23) - uncoupled) contains quantitative data collected via online survey/diary for Study 2. This study used a longitudinal sleep diary method to record nightly sleep quality compared to daily self-constructs. The coupled dataset matches prior night sleep quality to succeeding day self-construct. The uncoupled dataset matches succeeding night sleep quality to prior day self-construct. The fourth and fifth data files (titled: Sleep and Self S3 (25.08.23) - coupled; Sleep and Self S3 (25.08.23) - uncoupled) contains quantitative data collected via online survey/diary, and via actigraphy for Study 3. This study used a longitudinal sleep diary method to record nightly sleep quality compared to daily self-constructs, using both self-report and actigraphy methods. The coupled dataset matches prior night sleep quality to succeeding day self-construct. The uncoupled dataset matches succeeding night sleep quality to prior day self-construct. The sixth and seventh data files (titled: Sleep and Self S4 (01.09.23) - coupled; Sleep and Self S4 (01.09.23) - uncoupled) contains quantitative data collected via online survey/diary for Study 4. This study used a longitudinal sleep diary method to record nightly sleep quality compared to daily self-constructs. Participants were assigned to 4 groups with different experimental manipulations to enhance 1 of 3 self-constructs: self-compassion, self-control, self-esteem, or control group (no manipulation). The coupled dataset matches prior night sleep quality to succeeding day self-construct. The uncoupled dataset matches succeeding night sleep quality to prior day self-construct. -------------------------- METHODOLOGICAL INFORMATION -------------------------- Studies 1 - 4 collected online self-report data. Study 3 additionally used actigraphy for physiological sleep data. Studies 2 - 4 used a longitudinal design, from seven [7] - fourteen [14] days. Initial online data was created and distributed via Qualtrics.com survey platform. Data was collected via the University of Surrey Research Platform (SONA) and Prolific (prolific.com) for non-student samples. Data were downloaded to Microsoft Excel. Data were cleaned (e.g. removal of appropriate participants), re-coded as necessary (e.g. reverse scored data), and transfered to SPSS for statistical analysis. Available SPSS files include final datasets used for statistical analysis. Actigraphy data was collected using wristwatch-like actigraphy devices, named: Micro Mini-Motionlogger (Ambulatory Monitoring Inc., Ardsley, NY). Actigraphy data was processed using the "zero-crossing" method, a measure of movement frequency whereby activity signals are compared with a fixed sensitivity threshold. I followed the guidelines set by the manufacturer of this device (Ambulatory Monitoring Inc.) and corroborated in prior research (Jean-Louis et al., 2001). Data were then downloaded to Microsoft Excel and followed the same procedure as all online data. Data was collected, processed, and analysed entirely by the Thesis Author, James W Butterworth. -------------------------- DATA-SPECIFIC INFORMATION -------------------------- Sleep and Self S1 (11.10.22)_FINAL Number of variables: 441 Number of cases/rows: 315 Data are labelled and described in file. Date that the file was created: October 2022 Sleep and Self S2 (09.08.23) - Coupled Number of variables: 583 Number of cases/rows: 201 Data are labelled and described in file. Date that the file was created: August, 2023 Sleep and Self S2 (09.08.23) - Uncoupled Number of variables: 583 Number of cases/rows: 201 Data are labelled and described in file. Date that the file was created: August, 2023 Sleep and Self S3 (25.08.23) - Coupled Number of variables: 590 Number of cases/rows: 40 Data are labelled and described in file. Date that the file was created: August, 2023 Sleep and Self S3 (25.08.23) - Uncoupled Number of variables: 590 Number of cases/rows: 40 Data are labelled and described in file. Date that the file was created: August, 2023 Sleep and Self S4 (01.09.23) - Coupled Number of variables: 483 Number of cases/rows: 258 Data are labelled and described in file. Date that the file was created: September, 2023 Sleep and Self S4 (01.09.23) - Uncoupled Number of variables: 483 Number of cases/rows: 258 Data are labelled and described in file. Date that the file was created: September, 2023