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Key Identifiers

Participants across prior releases had various identifiers (e.g., Id, ID, Subject Id, EAS ID, GCRC Id). In an effort to reduce confusion, all participants are now labeled with textttparticipant_id that is standard across deliverables. Timepoint Identifiers

Across EAS data there are multiple variables that track when participants completed various study components. The following defines each Timepoint Identifier you may encounter in the data.

  • burst: An integer representing a given participant’s number of visits to the Einstein clinic since 2017. Burst = 0 indicates that the participant never did the EMA. Burst = 99 means that the participant did the EMA in previous waves but did not do it that wave. This can change from year to year.
  • burst_cumulative: An integer representing number of visits to the einstein clinic since 2017. (Does not include Burst 0 or 99)
  • wave: An integer representing number of visits to the einstein clinic over time.
  • device_date: The calendar date in YYYY/MM/DD format for a given sensor

Cohort Definition​

Given that the EAS has existed and been recruiting for multiple years, there is a binary cohort variable that allows researchers to sort participants by cohort. Cohort is distinguishable as follows:

  • If participant_id ≥ 13000 then cohort=2; new cohort, 2023 and beyond
  • If participant_id ≥ 12000 then cohort=1; new cohort, 2017 to early 2023
  • If participant_id < 12000 then cohort=0; old cohort, prior to 2017

Vintages​

We as a team decided to make protocol changes from the 2017 grant to now - as a result, we have two vintages of data: The 2017–2022 vintage, and the 2023–2028 vintage. A non-exhaustive example of changes you can expect to see in the 2023–2028 vintage include added take-home-packet variables, added sensor variables, and the addition of Atmotube, ActivPAL and CGM sensor data streams.

Dates & Times​

In an effort to clarify time stamps accross all data, we made some standardization decisions. In the EMA data, we standardize in the following way: all date/timestamps were reduced to a set of columns, herein: dt_start_date, dt_start_time, dt_end_date, dt_end_time. In sensor data, we have standardized all devices to have a device_date We include the three visits to the clinic as the variables day_1_appointment_date, day_2_appointment_date, and day_3_appointment_date.