Jang (2024)

Study Information

• First Author: Jang
• Year: 2024
• Paper DOI: https://doi.org/10.1038/s41597-024-04147-6
• Topics: panic symptoms, digital phenotyping, behavior

Data Characteristics

• Participants: 43 (patients diagnosed with mood disorders, anxiety disorders, trauma and stressor-related disorders, and obsessive-compulsive and related disorder)
• Time Points: 402
• Days: 402
• Beeps per Day: 1
• Sampling Scheme: 1x/day in the evening
• Raw Timestamp: yes
• Implicit Missingness: yes

Data Availability

• Cross-sectional Data: yes
• Passive Sensor Data: yes
• Link to Original Data: https://zenodo.org/records/14190139
• Link to Codebook: https://static-content.springer.com/esm/art%3A10.1038%2Fs41597-024-04147-6/MediaObjects/41597_2024_4147_MOESM1_ESM.pdf
• Link to Code: https://github.com/DigitalHealthcareLab/24PanicPrediction
• License: CC-BY 4.0

Data Access

• Zenodo DOI: 10.5281/zenodo.17347469
• R: openesm::get_dataset("0017_jang")
• Python: openesm.get_dataset("0017_jang")

Additional Comments

some item coding unclear; large amount of additional data available on Zenodo; number of max. time points calculated as the maximum span between first and last date in the data set; raw time stamp only for some variables

Citation

Jang, S., hui Sun, T., Shin, S., Lee, H.-J., Shin, Y.-B., Yeom, J. W., Park, Y. R., & Cho, C.-H. (2024). A digital phenotyping dataset for impending panic symptoms: A prospective longitudinal study. Scientific Data, 11(1), 1264. https://doi.org/10.1038/s41597-024-04147-6

Changelog

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