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Filter Cart

Viewable at the top right of NDA pages, the Filter Cart is a temporary holder for filters and data they select. Filters are added to the Workspace first, before being submitted to The Filter Cart. Data selected by filters in the Filter Cart can be added to a Data Package or an NDA Study from the Data Packaging Page, by clicking the 'Create Data Package / Add Data to Study' button.

The filter cart supports combining multiple filters together, and depending on filter type will use "AND" or "OR"  when combining filters.

Multiple selections from the same filter type will result in those selections being applied with an ‘OR’ condition. For example, if you add an NDA Collection Filter with selections for both collections 2112 and 2563 to an empty Workspace, the subjects from NDA Collection 2112 ‘OR’ NDA Collection 2563 will be added to your Workspace even if a subject is in both NDA Collections. You can then add other NDA Collections to your Workspace which further extends the ‘OR’ condition.

If a different filter type is added to your Workspace, or a filter has already been submitted to the Filter Cart, the operation then performs a logical ‘AND’ operation. This means that given the subjects returned from the first filter, only those subjects that matched the first filter are returned by the second filter (i.e., subjects that satisfied both filters).

When combining other filters with the GUID filter, please note the GUID filter should be added last. Otherwise, preselected data may be lost. For example, a predefined filter from Featured Datasets may select a subset of data available for a subject. When combined with a GUID filter for the same subject, the filter cart will contain all data available from that subject, data structure, and dataset; this may be more data than was selected in the predefined filter for that subject. Again, you should add the GUID Filter as the last filter to your cart. This ensures 'AND' logic between filters and will limit results to the subjects, data structures, and datasets already included in your filter cart.

Note that only the subjects specific to your filter will be added to your Filter Cart and only on data shared with the research community. Other data for those same subjects may exist (i.e., within another NDA Collection, associated with a data structure that was not requested in the query, etc.). So, users should select ‘Find all Subjects Data’ to identify all data for those specific subjects. 

Additional Tips:

  • You may query the data without an account, but to gain access you will need to create an NDA user account and apply for access.  Most data access requires that you or your lab are sponsored by an NIH recognized institution with Federal Wide Assurance (FWA).  Without access, you will not be able to obtain individual-level data. 

    Once you have selected data of interest you can:
  • Create a data package - This allows you to specify format for access/download
  • Assign to Study Cohort - Associate the data to an NDA Study allowing for a DOI to be generated and the data to be linked directly to a finding, publication, or data release. 
  • Find All Subject Data - Depending on filter types being used, not all data associated with a subject will be selected.  Data may be restricted by data structure, NDA Collection, or outcome variables (e.g., NDA Study). ‘Find All Data’ expands the fliter criteria by replacing all filters in your Filter Cart with a single Query by GUID filter for all subjects selected by those filters.

    Please Note:
  • When running a query, it may take a moment to populate the Filter Cart. Queries happen in the background so you can define other queries during this time. 
  • When you add your first filter, all data associated with your query will be added to the Filter Cart (e.g., a Concept, an NDA Collection, a Data Structure/Element, etc.). As you add additional filters, they will also display in the Filter Cart. Only the name of filter will be shown in the Filter Cart, not the underlying structures. 
  • Information about the contents of the Filter Cart can be seen by clicking "Edit”.
  • Once your results appear in the Filter Cart, you can create a data package or assign subjects to a study by selecting the 'Package/Assign to Study' option. You can also 'Edit' or 'Clear' filters.
     

Frequently Asked Questions

  • The Filter Cart currently employs basic AND/OR Boolean logic. A single filter may contain multiple selections for that filter type, e.g., a single NDA Study filter might contain NDA Study 1 and NDA Study 2. A subject that is in EITHER 1 OR 2 will be returned.  Adding multiple filters to the cart, regardless of type, will AND the result of each filter.  If NDA Study 1 and NDA Study 2 are added as individual filters, data for a subject will only be selected if the subject is included in  BOTH 1 AND 2.

    When combining other filters with the GUID filter, please note the GUID filter should be added last. Otherwise, preselected data may be lost. For example, a predefined filter from Featured Datasets may select a subset of data available for a subject. When combined with a GUID filter for the same subject, the filter cart will contain all data available from that subject, data structure, and dataset; this may be more data than was selected in the predefined filter for that subject. Again, you should add the GUID Filter as the last filter to your cart. This ensures 'AND' logic between filters and will limit results to the subjects, data structures, and datasets already included in your filter cart.

  • Viewable at the top right of NDA pages, the Filter Cart is a temporary holder of data identified by the user, through querying or browsing, as being of some potential interest. The Filter Cart is where you send the data from your Workspace after it has been filtered.

  • After filters are added to the Filter Cart, users have options to ‘Create a Package’ for download, ‘Associate to Study Cohort’, or ‘Find All Subject Data’. Selecting ‘Find All Subject Data’ identifies and pulls all data for the subjects into the Filter Cart. Choosing ‘Create a Package’ allows users to package and name their query information for download. Choosing ‘Associate to Study Cohort’ gives users the opportunity to choose the Study Cohort they wish to associate this data.

Glossary

  • Once your filter cart contains the subjects of interest, select Create Data Package/Assign to Data Study which will provide options for accessing item level data and/or assigning to a study.  

  • Once queries have been added to your workspace, the next step is to Submit the Filters in the workspace to the Filter Cart.  This process runs the queries selected, saving the results within a filter cart attached to your account.  

  • The Workspace within the General Query Tool is a holding area where you can review your pending filters prior to adding them to Filter Cart. Therefore, the first step in accessing data is to select one or more items and move it into the Workspace. 

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ABCD Youth Fitbit Daily Physical Activity Summaries

5,761 Shared Subjects

This instrument includes daily physical activity (and sedentary behavior) at the minute level based on heart rate and accelerometer data from fitbit.  
Clinical Assessments
Activity
04/08/2020
abcd_fbdpas01
10/27/2020
View Change History
01
Query Element Name Data Type Size Required Description Value Range Notes Aliases
subjectkey GUID Required The NDAR Global Unique Identifier (GUID) for research subject NDAR*
src_subject_id String 20 Required Subject ID how it's defined in lab/project
interview_date Date Required Date on which the interview/genetic test/sampling/imaging/biospecimen was completed. MM/DD/YYYY
interview_age Integer Required Age in months at the time of the interview/test/sampling/imaging. 0 :: 1260 Age is rounded to chronological month. If the research participant is 15-days-old at time of interview, the appropriate value would be 0 months. If the participant is 16-days-old, the value would be 1 month.
sex String 20 Required Sex of subject at birth M;F; O; NR M = Male; F = Female; O=Other; NR = Not reported gender
eventname String 60 Required The event name for which the data was collected
fit_ss_protocol_startdate Date Recommended First day of (expected) wear of 3 week protocol fitbit_ss_protocol_startdate
fit_ss_protocol_wear Integer Recommended Is this day during the 3 week protocol period? 0;1 0=no; 1=yes fitbit_ss_protocol_wear
fit_ss_wear_date Date Recommended Date of Participant Wear Only days included in the protocol wear period are aggregated into the weekly data fitbit_ss_wear_date
fit_ss_day_total_steps_no_el Integer Recommended Total number of steps observed in all minutes (no exclusions) from midnight (00:00) to 11:59PM (23:59) regardless of sleep categorization Potentially useful to see if there are exclusions that include a large amount of activity (EX: Repeated HR at high levels, indicative of exercise time being excluded. EX 2: Many steps taken during periods being identified as "sleep" by 60 second algorithm) fitbit_ss_day_total_steps_no_exclusions
fit_ss_day_min Integer Recommended Number of minutes with heart rate value from midnight (00:00) to 11:59P (23:59) not identified as sleep (at 60 second "classic" level) or exclusion rules fitbit_ss_day_min
fit_ss_night_min Integer Recommended Number of minutes with Heart Rate Value from midnight (00:00) to 11:59P (23:59) that ARE identified as sleep (at 60 second "classic" level) or exclusion rules fitbit_ss_night_min
fit_ss_sleep_min Integer Recommended Number of minutes with Heart Rate Value from midnight (00:00) to 11:59P (23:59) that ARE identified as sleep (at 60 second "classic" level) or exclusion rules from the first minute of sleep on the day in question to the first minute of awake on the next day (i.e crosses midnight) Not useful for much analysis beyond the number of minutes that participants spent in bed. For more complete data on sleep quantity and quality refer to sleep data at daily and weekly levels. fitbit_ss_sleep_min
fit_ss_30_second_data_existed Integer Recommended Does 30 second sleep data exist for this day 0;1 0=no; 1=yes fitbit_ss_30_second_data_existed
fit_ss_excl_day_min Integer Recommended Number of minutes from midnight (00:00) to 11:59P (23:59) not identified as sleep (at 60 second "classic" level) excluded for any reason fitbit_ss_excl_day_min
fit_ss_excl_day_min_hr50 Integer Recommended Number of minutes from midnight (00:00) to 11:59P (23:59) not identified as sleep (at 60 second "classic" level) excluded because HR was lower than 50 bpm 50 BPM was identified as being the lowest physiologically likely HR threshold fitbit_ss_excl_day_min_hr50
fit_ss_excl_day_min_nohr Integer Recommended Number of minutes from midnight (00:00) to 11:59P (23:59) not identified as sleep (at 60 second "classic" level) excluded because there was no HR value for the given minute Lack of a HR value is strongly indicative on non-wear. fitbit_ss_excl_day_min_nohr
fit_ss_excl_day_min_hr_rept Integer Recommended Number of minutes from midnight (00:00) to 11:59P (23:59) not identified as sleep (at 60 second "classic" level) excluded because there were identical HR values repeated for 10+ instances Repeating HR is indicative of either non-wear or disrupted wear that makes all other gathered variables of interest suspect fitbit_ss_excl_day_min_hr_rept
fit_ss_excl_night_min Integer Recommended Number of minutes from midnight (00:00) to 11:59P (23:59) identified as sleep (at 60 second "classic" level) excluded for any reason fitbit_ss_excl_night_min
fit_ss_excl_night_min_hr50 Integer Recommended Number of minutes from midnight (00:00) to 11:59P (23:59) identified as sleep (at 60 second "classic" level) excluded because HR was lower than 50 bpm 50 BPM was identified as being the lowest physiologically likely HR threshold fitbit_ss_excl_night_min_hr50
fit_ss_excl_night_min_nohr Integer Recommended Number of minutes from midnight (00:00) to 11:59P (23:59) identified as sleep (at 60 second "classic" level) excluded because there was no HR value for the given minute Lack of a HR value is strongly indicative on non-wear. fitbit_ss_excl_night_min_nohr
fit_ss_excl_night_min_hr_rept Integer Recommended Number of minutes from midnight (00:00) to 11:59P (23:59) identified as sleep (at 60 second "classic" level) excluded because there were identical HR values repeated for 10+ instances Repeating HR is indicative of either non-wear or disrupted wear that makes all other gathered variables of interest suspect fitbit_ss_excl_night_min_hr_rept
fit_ss_excl_sleep_min Integer Recommended Number of minutes from the first minute of sleep on the day in question to the first minute of awake on the next day excluded for any reason (these data cross midnight) fitbit_ss_excl_sleep_min
fit_ss_excl_sleep_min_hr50 Integer Recommended Number of minutes from the first minute of sleep on the day in question to the first minute of awake on the next day excluded because HR was lower than 50 bpm (these data cross midnight) 50 BPM was identified as being the lowest physiologically likely HR threshold fitbit_ss_excl_sleep_min_hr50
fit_ss_excl_sleep_min_nohr Integer Recommended Number of minutes from the first minute of sleep on the day in question to the first minute of awake on the next day excluded because there was no HR value for the given minute (these data cross midnight) Lack of a HR value is strongly indicative on non-wear. fitbit_ss_excl_sleep_min_nohr
fit_ss_excl_sleep_min_rept Integer Recommended Number of minutes from the first minute of sleep on the day in question to the first minute of awake on the next day excluded because there were identical HR values repeated for 10+ instances (these data cross midnight) Repeating HR is indicative of either non-wear or disrupted wear that makes all other gathered variables of interest suspect fitbit_ss_excl_sleep_min_rept
fit_ss_day_min_gt_600 Integer Recommended Does this day have >599 minutes of non-sleep wear after all exclusions 0;1 0=no; 1=yes Must be yes to be included in weekly aggregation. fitbit_ss_day_min_gt_600
fit_ss_sleep_min_gt_300 Integer Recommended Does this day have >299 minutes of sleep wear (based on 60 second data from fitabase) after all exclusions 0;1 0=no; 1=yes Based on first minute of sleep on the day in question to the first minute of awake on the next day fitbit_ss_sleep_min_gt_300
fit_ss_first_hr_date Date Recommended First day that HR appears in fitabase record fitbit_ss_first_hr_date
fit_ss_weekday Integer Recommended Day of the week 1::7 1=Sunday, 2=Monday, 3=Tuesday, 4=Wednesday, 5=Thursday, 6=Friday, 7=Saturday fitbit_ss_weekday
fit_ss_wkno Integer Recommended Week number since start of protocol Only first 3 weeks will be included in weekly aggregation (protocol length of wear) fitbit_ss_wkno
fit_ss_weekend_ind Integer Recommended Is this day a weekend (Saturday or Sunday) 0;1 0=no; 1=yes fitbit_ss_weekend_ind
fit_ss_total_min Integer Recommended Total number of valid minutes after all exclusions from midnight (00:00) to 11:59 PM (23:59) regardless of sleep status fitbit_ss_total_min
fit_ss_total_step Integer Recommended Total number of steps observed after all exclusions from midnight (00:00) to 11:59 PM (23:59) regardless of sleep status fitbit_ss_total_step
fit_ss_total_ave_met Float Recommended Average METS/minute of all valid minutes after all exclusions from midnight (00:00) to 11:59 PM (23:59) regardless of sleep status 1 MET=Resting Metabolism of average individual (adult)= 3.5 ml/kg/min of O2 consumption fitbit_ss_total_ave_met
fit_ss_total_sedentary_min Integer Recommended Number of minutes of sedentary (<1.5 METS) time observed in all valid minutes after all exclusions from midnight (00:00) to 11:59 PM (23:59) regardless of sleep status fitbit_ss_total_sedentary_min
fit_ss_total_light_active_min Integer Recommended Number of minutes of lightly active time (1.5-2.9 METS) observed in all valid minutes after all exclusions from midnight (00:00) to 11:59 PM (23:59) regardless of sleep status fitbit_ss_total_light_active_min
fit_ss_total_fairly_active_min Integer Recommended Number of minutes of moderately active (3-5.9 METS) time observed in all valid minutes after all exclusions from midnight (00:00) to 11:59 PM (23:59) regardless of sleep status fitbit_ss_total_fairly_active_min
fit_ss_total_very_active_min Integer Recommended Number of minutes of vigorously active (>6 METS) time observed in all valid minutes after all exclusions from midnight (00:00) to 11:59 PM (23:59) regardless of sleep status fitbit_ss_total_very_active_min
fit_ss_fitbit_totalsteps Integer Recommended Fitbit based number of steps for the day FROM DAILY LEVEL SUMMARY Small differences in this value compared to "total step" variable indicative of HR based exclusions. Very large differences likely indicative of poor data capture at minute level fitbit_ss_fitbit_total_steps, fitbit_ss_fitbitbit_totalsteps
fit_ss_fitbit_sedentarymin Integer Recommended Fitbit based number of minutes spent in sedentary (<1.5 METS) time for the day FROM DAILY LEVEL SUMMARY Small differences in this value compared to "Sedentary min" variable indicative o HR based exclusions. Very large differences likely indicative of poor data capture at minute level fitbit_ss_fitbit_sedentary_min, fitbit_ss_fitbitbit_sedentarymin
fit_ss_fitbit_lightlyactivemin Integer Recommended Fitbit based number of minutes spent in light activity (1.5-2.9 METS) for the day FROM DAILY LEVEL SUMMARY Small differences in this value compared to "light_active_min" variable indicative of HR based exclusions. Very large differences likely indicative of poor data capture at minute level fitbit_ss_fitbit_lightly_active_min, fitbit_ss_fitbitbit_lightlyactivemin
fit_ss_fitbit_fairlyactivemin Integer Recommended Fitbit based number of minutes spent in moderate activity (3-5.9 METS) for the day FROM DAILY LEVEL SUMMARY Small differences in this value compared to "fairly_active_min" variable indicative of HR based exclusions. Very large differences likely indicative of poor data capture at minute level fitbit_ss_fitbit_fairly_active_min, fitbit_ss_fitbitbit_fairlyactivemin
fit_ss_fitbit_veryactivemin Integer Recommended Fitbit based number of minutes spent in vigorous (>6 METS) for the day FROM DAILY LEVEL SUMMARY Small differences in this value compared to "very_active_min" variable indicative of HR based exclusions. Very large differences likely indicative of poor data capture at minute level fitbit_ss_fitbit_very_active_min, fitbit_ss_fitbitbit_veryactivemin
fit_ss_fitbit_restingheartrate Integer Recommended Fitbit based number resting heart rate for the day FROM DAILY LEVEL SUMMARY Low(er) resting heart rate is usually indicative of a) stronger cardiac muscle/better cardiorespiratory fitness and b) improved (para)sympathetic nervous tone fitbit_ss_fitbit_resting_heartrate, fitbit_ss_fitbitbit_restingheartrate
fit_ss_mstep_lt_80_dailystep Integer Recommended Is the QC'd step value after all exclusions 80%+ the value of the daily level as reported by fitbit 0=QC'd value 80%+ of daily reported level. 1=QC'd value <80% of daily reported value. A value of 1 indicates that there is likely data loss at the minute level of steps and active level (and possibly heart rate) fitbit_ss_mstep_lt_80_daily_step, fitbit_ss_mstep_lt_80_dailystep
fit_ss_dayt_total_steps Integer Recommended Total number of steps observed during non-sleep (night) valid minutes
fit_ss_dayt_ave_met_value Float Recommended Average METS/minute during non-sleep (night) valid minutes 1 MET=Resting Metabolism of average individual (adult)= 3.5 ml/kg/min of O2 consumption
fit_ss_dayt_sedentary_min Float Recommended Number of minutes of sedentary (<1.5 METS) time observed during non-sleep (night) valid minutes
fit_ss_dayt_light_active_min Float Recommended Number of minutes of lightly active time (1.5-2.9 METS) observed during non-sleep (night) valid minutes
fit_ss_dayt_farily_active_min Float Recommended Number of minutes of moderately active (3-5.9 METS) time observed during non-sleep (night) valid minutes
fit_ss_dayt_very_active_min Integer Recommended Number of minutes of vigorously active (>6 METS) time observed during non-sleep (night) valid minutes
Data Structure

This page displays the data structure defined for the measure identified in the title and structure short name. The table below displays a list of data elements in this structure (also called variables) and the following information:

  • Element Name: This is the standard element name
  • Data Type: Which type of data this element is, e.g. String, Float, File location.
  • Size: If applicable, the character limit of this element
  • Required: This column displays whether the element is Required for valid submissions, Recommended for valid submissions, Conditional on other elements, or Optional
  • Description: A basic description
  • Value Range: Which values can appear validly in this element (case sensitive for strings)
  • Notes: Expanded description or notes on coding of values
  • Aliases: A list of currently supported Aliases (alternate element names)
  • For valid elements with shared data, on the far left is a Filter button you can use to view a summary of shared data for that element and apply a query filter to your Cart based on selected value ranges

At the top of this page you can also:

  • Use the search bar to filter the elements displayed. This will not filter on the Size of Required columns
  • Download a copy of this definition in CSV format
  • Download a blank CSV submission template prepopulated with the correct structure header rows ready to fill with subject records and upload

Please email the The NDA Help Desk with any questions.