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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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Data Structures with shared data
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Sum Scores Mental Health Youth

11,878 Shared Subjects

Mental health summary scores - youth surveys
Clinical Assessments
Summary
01/12/2019
abcd_mhy02
05/20/2021
View Change History
02
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_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.
interview_date Date Required Date on which the interview/genetic test/sampling/imaging/biospecimen was completed. MM/DD/YYYY
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 Recommended The event name for which the data was collected
Query ple_y_ss_total_number Float Recommended Total Number of Events : Validation: No Minimum Calculation: sum([ple_died_y], [ple_injured_y], [ple_crime_y], [ple_friend_y], [ple_friend_injur_y], [ple_financial_y], [ple_sud_y], [ple_ill_y], [ple_injur_y], [ple_argue_y], [ple_job_y], [ple_away_y], [ple_arrest_y], [ple_friend_died_y], [ple_mh_y], [ple_sib_y], [ple_victim_y], [ple_separ_y], [ple_law_y], [ple_school_y], [ple_move_y], [ple_jail_y], [ple_step_fu_y], [ple_new_job_y], [ple_new_sib_y]) life_events_phenx_ss_total_number
Query ple_y_ss_total_number_nm Integer Recommended Total Number of Events : Number Missing Answers life_events_phenx_ss_total_number_nm
Query ple_y_ss_total_number_nt Integer Recommended Total Number of Events : Number Total Questions life_events_phenx_ss_total_number_nt
Query ple_y_ss_total_good Float Recommended Total Number of Good Events : Validation: No Minimum Calculation: if([ple_died_fu_y] = '1',1,0) plus if([ple_injured_fu_y] = '1',1,0) plus if([ple_crime_fu_y]= '1',1,0) plus if([ple_friend_fu_y]= '1',1,0) plus if([ple_friend_injur_fu_y]= '1',1,0) plus if([ple_financial_fu_y]= '1',1,0) plus if([ple_sud_fu_y]= '1',1,0) plus if([ple_ill_fu_y]= '1',1,0) plus if([ple_injur_fu_y]= '1',1,0) plus if([ple_argue_fu_y]= '1',1,0) plus if([ple_job_fu_y]= '1',1,0) plus if([ple_away_fu_y]= '1',1,0) plus if([ple_arrest_fu_y]= '1',1,0) plus if([ple_friend_died_fu_y]= '1',1,0) plus if([ple_mh_fu_y]= '1',1,0) plus if([ple_sib_fu_y]= '1',1,0) plus if([ple_victim_fu_y]= '1',1,0) plus if([ple_separ_fu_y]= '1',1,0) plus if([ple_law_fu_y]= '1',1,0) plus if([ple_school_fu_y]= '1',1,0) plus if([ple_move_fu_y]= '1',1,0) plus if([ple_jail_fu_y]= '1',1,0) plus if([ple_step_fu_y]= '1',1,0) plus if([ple_new_job_fu_y]= '1',1,0) plus if([ple_new_sib_fu_y] = '1',1,0) life_events_phenx_ss_total_good
Query ple_y_ss_total_good_nt Integer Recommended Total Number of Good Events : Number Total Questions life_events_phenx_ss_total_good_nt
Query ple_y_ss_total_bad Float Recommended Total Number of Bad Events : Validation: No Minimum Calculation: if([ple_died_fu_y] = '2',1,0) plus if([ple_injured_fu_y] = '2',1,0) plus if([ple_crime_fu_y]= '2',1,0) plus if([ple_friend_fu_y]= '2',1,0) plus if([ple_friend_injur_fu_y]= '2',1,0) plus if([ple_financial_fu_y]= '2',1,0) plus if([ple_sud_fu_y]= '2',1,0) plus if([ple_ill_fu_y]= '2',1,0) plus if([ple_injur_fu_y]= '2',1,0) plus if([ple_argue_fu_y]= '2',1,0) plus if([ple_job_fu_y]= '2',1,0) plus if([ple_away_fu_y] = '2',1,0) plus if([ple_arrest_fu_y]= '2',1,0) plus if([ple_friend_died_fu_y]= '2',1,0) plus if([ple_mh_fu_y]= '2',1,0) plus if([ple_sib_fu_y]= '2',1,0) plus if([ple_victim_fu_y]= '2',1,0) plus if([ple_separ_fu_y]= '2',1,0) plus if([ple_law_fu_y]= '2',1,0) plus if([ple_school_fu_y]= '2',1,0) plus if([ple_move_fu_y]= '2',1,0) plus if([ple_jail_fu_y]= '2',1,0) plus if([ple_step_fu_y]= '2',1,0) plus if([ple_new_job_fu_y]= '2',1,0) plus if([ple_new_sib_fu_y] = '2',1,0) life_events_phenx_ss_total_bad
Query ple_y_ss_total_bad_nt Integer Recommended Total Number of Bad Events : Number Total Questions life_events_phenx_ss_total_bad_nt
Query ple_y_ss_affect_sum Float Recommended How Much Affected - Sum : Validation: No Minimum Calculation: sum([ple_died_fu2_y], [ple_injured_fu2_y], [ple_crime_fu2_y], [ple_friend_fu2_y], [ple_friend_injur_fu2_y], [ple_financial_fu2_y], [ple_sud_fu2_y], [ple_ill_fu2_y], [ple_injur_fu2_y], [ple_argue_fu2_y], [ple_job_fu2_y], [ple_away_fu2_y], [ple_arrest_fu2_y], [ple_friend_died_fu2_y], [ple_mh_fu2_y], [ple_sib_fu2_y], [ple_victim_fu2_y], [ple_separ_fu2_y], [ple_law_fu2_y], [ple_school_fu2_y], [ple_move_fu2_y], [ple_jail_fu2_y], [ple_step_fu2_y], [ple_new_job_fu2_y], [ple_new_sib_fu2_y] ) life_events_phenx_ss_affect_sum
Query ple_y_ss_affect_sum_nt Integer Recommended How Much Affected - Sum : Number Total Questions life_events_phenx_ss_affect_sum_nt
Query ple_y_ss_affected_mean_nt Integer Recommended How Much Affected - Mean : Number Total Questions life_events_phenx_ss_affected_mean_nt
Query ple_y_ss_affected_good_sum Float Recommended How Much Affected Good - Sum : Validation: No Minimum Calculation: if([ple_died_fu_y] = '1',[ple_died_fu2_y],0) plus if([ple_injured_fu_y] = '1',[ple_injured_fu2_y],0) plus if([ple_crime_fu_y]= '1',[ple_crime_fu2_y],0) plus if([ple_friend_fu_y]= '1',[ple_friend_fu2_y],0) plus if([ple_friend_injur_fu_y] = '1',[ple_friend_injur_fu2_y],0) plus if([ple_financial_fu_y] = '1',[ple_financial_fu2_y],0) plus if([ple_sud_fu_y]= '1',[ple_sud_fu2_y],0) plus if([ple_ill_fu_y]= '1',[ple_ill_fu2_y],0) plus if([ple_injur_fu_y]= '1',[ple_injur_fu2_y],0) plus if([ple_argue_fu_y]= '1',[ple_argue_fu2_y],0) plus if([ple_job_fu_y]= '1',[ple_job_fu2_y],0) plus if([ple_away_fu_y]= '1',[ple_away_fu2_y],0) plus if([ple_arrest_fu_y]= '1',[ple_arrest_fu2_y],0) plus if([ple_friend_died_fu_y]= '1',[ple_friend_died_fu2_y],0) plus if([ple_mh_fu_y]= '1',[ple_mh_fu2_y],0) plus if([ple_sib_fu_y]= '1',[ple_sib_fu2_y],0) plus if([ple_victim_fu_y]= '1',[ple_victim_fu2_y],0) plus if([ple_separ_fu_y]= '1',[ple_separ_fu2_y],0) plus if([ple_law_fu_y]= '1',[ple_law_fu2_y],0) plus if([ple_school_fu_y]= '1',[ple_school_fu2_y],0) plus if([ple_move_fu_y]= '1',[ple_move_fu2_y],0) plus if([ple_jail_fu_y]= '1',[ple_jail_fu2_y],0) plus if([ple_step_fu_y]= '1',[ple_step_fu2_y],0) plus if([ple_new_job_fu_y]= '1',[ple_new_job_fu2_y],0) plus if([ple_new_sib_fu_y] = '1',[ple_new_sib_fu2_y],0) life_events_phenx_ss_affected_good_sum
Query ple_y_ss_affected_good_sum_nt Integer Recommended How Much Affected Good - Sum : Number Total life_events_phenx_ss_affected_good_sum_nt
Query ple_y_ss_affected_good_mean Float Recommended How Much Affected Good - Mean : Validation: No Minimum Calculation: [ple_y_ss_affected_good_sum] / [ple_y_ss_total_good] life_events_phenx_ss_affected_good_mean
Query ple_y_ss_affected_good_mean_nt Integer Recommended How Much Affected Good - Mean : Number Total Questions life_events_phenx_ss_affected_good_mean_nt
Query ple_y_ss_affected_bad_sum Float Recommended How Much Affected Bad - Sum : Validation: No Minimum Calculation: if([ple_died_fu_y] = '2',[ple_died_fu2_y],0) plus if([ple_injured_fu_y] = '2',[ple_injured_fu2_y],0) plus if([ple_crime_fu_y]= '2',[ple_crime_fu2_y],0) plus if([ple_friend_fu_y]= '2',[ple_friend_fu2_y],0) plus if([ple_friend_injur_fu_y] = '2',[ple_friend_injur_fu2_y],0) plus if([ple_financial_fu_y]= '2',[ple_financial_fu2_y],0) plus if([ple_sud_fu_y]= '2',[ple_sud_fu2_y],0) plus if([ple_ill_fu_y]= '2',[ple_ill_fu2_y],0) plus if([ple_injur_fu_y]= '2',[ple_injur_fu2_y],0) plus if([ple_argue_fu_y]= '2',[ple_argue_fu2_y],0) plus if([ple_job_fu_y]= '2',[ple_job_fu2_y],0) plus if([ple_away_fu_y]= '2',[ple_away_fu2_y],0) plus if([ple_arrest_fu_y]= '2',[ple_arrest_fu2_y],0) plus if([ple_friend_died_fu_y]= '2',[ple_friend_died_fu2_y],0) plus if([ple_mh_fu_y]= '2',[ple_mh_fu2_y],0) plus if([ple_sib_fu_y]= '2',[ple_sib_fu2_y],0) plus if([ple_victim_fu_y]= '2',[ple_victim_fu2_y],0) plus if([ple_separ_fu_y]= '2',[ple_separ_fu2_y],0) plus if([ple_law_fu_y]= '2',[ple_law_fu2_y],0) plus if([ple_school_fu_y]= '2',[ple_school_fu2_y],0) plus if([ple_move_fu_y]= '2',[ple_move_fu2_y],0) plus if([ple_jail_fu_y]= '2',[ple_jail_fu2_y],0) plus if([ple_step_fu_y]= '2',[ple_step_fu2_y],0) plus if([ple_new_job_fu_y]= '2',[ple_new_job_fu2_y],0) plus if([ple_new_sib_fu_y] = '2',[ple_new_sib_fu2_y],0) life_events_phenx_ss_affected_bad_sum
Query ple_y_ss_affected_bad_sum_nt Integer Recommended How Much Affected Bad - Sum : Number Total Questions life_events_phenx_ss_affected_bad_sum_nt
Query ple_y_ss_affected_bad_mean Float Recommended How Much Affected Bad - Mean : Validation: No Minimum Calculation: [ple_y_ss_affected_bad_sum] / [ple_y_ss_total_bad] life_events_phenx_ss_affected_bad_mean
Query ple_y_ss_affected_bad_mean_nt Integer Recommended How Much Affected Bad - Mean : Number Total Questions life_events_phenx_ss_affected_bad_mean_nt
Query pps_y_ss_number Integer Recommended Prodromal Psychosis Scale: Number of Yes Responses Sum: prodromal_1_y, prodromal_2_y, prodromal_3_y, prodromal_4_y, prodromal_5_y, prodromal_6_y, prodromal_7_y, prodromal_8_y, prodromal_9_y, prodromal_10_y, prodromal_11_y, prodromal_12_y, prodromal_13_y, prodromal_14_y, [prodromal_15_y, prodromal_16_y, prodromal_17_y], prodromal_18_y, prodromal_19_y], prodromal_20_y], prodromal_21_y; No minimum number of answers to be valid Loewy, R. L., Pearson, R., et al. (2011) Psychosis risk screening with the Prodromal Questionnaire--brief version (PQ-B). Schizophr Res 129(1): 42-46. prodrom_psych_ss_number
Query pps_y_ss_number_nm Integer Recommended Prodromal Psychosis Scale, Number of Yes Responses: Number Missing Answers prodrom_psych_ss_number_nm
Query pps_y_ss_number_nt Integer Recommended Prodromal Psychosis Scale, Number of Yes Responses: Number Total Questions prodrom_psych_ss_number_nt
Query pps_y_ss_bother_sum Integer Recommended Prodromal Psychosis Scale, Number of Yes Responses to Did it Bother You? Sum: pps_1_bother_yn, pps_2_bother_yn, pps_3_bother_yn, pps_4_bother_yn, pps_5_bother_yn, pps_6_bother_yn, pps_7_bother_yn, pps_8_bother_yn, pps_9_bother_yn, pps_10_bother_yn, pps_11_bother_yn, pps_12_bother_yn, pps_13_bother_yn, pps_14_bother_yn, pps_15_bother_yn, pps_16_bother_yn, pps_17_bother_yn, pps_18_bother_yn, pps_19_bother_yn, pps_20_bother_yn, pps_21_bother_yn; No minimum number of answers to be valid Loewy, R. L., Pearson, R., et al. (2011) Psychosis risk screening with the Prodromal Questionnaire--brief version (PQ-B). Schizophr Res 129(1): 42-46. prodrom_psych_ss_bother_sum
Query pps_y_ss_bother_sum_nm Integer Recommended Prodromal Psychosis Scale, Number of Yes Responses to Did it Bother You? Number Missing Answers prodrom_psych_ss_bother_sum_nm
Query pps_y_ss_bother_sum_nt Integer Recommended Prodromal Psychosis Scale, Number of Yes Responses to Did it Bother You? Number Total Questions prodrom_psych_ss_bother_sum_nt
Query pps_y_ss_bother_n_1 Integer Recommended Prodromal Psychosis Scale: Number of No Responses to Did it Bother You? Intermediate equation for Severity Score - Raw score of 0 (no) transformed to 1 (yes) and 1 (yes) transformed to 0 (no) sum(pps_1_bother_yn, pps_2_bother_yn, pps_3_bother_yn, pps_4_bother_yn, pps_5_bother_yn, pps_6_bother_yn, pps_7_bother_yn, pps_8_bother_yn, pps_9_bother_yn, pps_10_bother_yn, pps_11_bother_yn, pps_12_bother_yn, pps_13_bother_yn, pps_14_bother_yn, pps_15_bother_yn, pps_16_bother_yn, pps_17_bother_yn, pps_18_bother_yn, pps_19_bother_yn, pps_20_bother_yn, pps_21_bother_yn) No minimum number of answers to be valid prodrom_psych_ss_bother_n_1
Query pps_y_ss_bother_n_1_nm Integer Recommended Prodromal Psychosis Scale, Number of No Responses to Did it Bother You? Number Missing Answers prodrom_psych_ss_bother_n_1_nm
Query pps_y_ss_bother_n_1_nt Integer Recommended Prodromal Psychosis Scale, Number of No Responses to Did it Bother You? Number Total Questions prodrom_psych_ss_bother_n_1_nt
Query pps_y_ss_severity_score Integer Recommended Prodromal Psychosis: Severity Score Sum: (prodromal_1b_y, prodromal_2b_y, prodromal_3b_y, prodromal_4b_y, prodromal_5b_y, prodromal_6b_y, prodromal_7b_y, prodromal_8b_y, prodromal_9b_y, prodromal_10b_y, prodromal_11b_y, prodromal_12b_y, prodromal_13b_y, prodromal_14b_y, [prodromal_15b_y, prodromal_16b_y, prodromal_17b_y, prodromal_18b_y, prodromal_19b_y, prodromal_20b_y, prodromal_21b_y) + (pps_y_ss_ bother_n_1), If this score = ", then score = pps_y_ss_number; No minimum number of answers to be valid Loewy, R. L., Pearson, R., et al. (2011) Psychosis risk screening with the Prodromal Questionnaire--brief version (PQ-B). Schizophr Res 129(1): 42-46. In the Prodromal Psychosis survey, "How much did it bother you?" is typically scored 2 - 6. In the version used by ABCD,  this item was scored  1 - 5. Because the "Did it bother you" sum score is equal to the sum of the number of severity scores used in the severity score calculation, we were able to compensate for this scoring difference by adding the "Did it bother you" sum score to the severity score.  After applying this change, the severity scores reported here are comparable to those calculated using the  "How much did it bother you"  2 - 6  scoring range. prodrom_psych_ss_severity_score
Query pps_y_ss_severity_score_nm Integer Recommended Prodromal Psychosis, Severity Score: Number Missing Answers prodrom_psych_ss_severity_score_nm
Query pps_y_ss_severity_score_nt Integer Recommended Prodromal Psychosis, Severity Score: Number Total Questions prodrom_psych_ss_severity_score_nt
Query pps_ss_mean_severity Float Recommended Prodromal Psychosis: Mean Endorsed Severity Score PPS severity score/Number of yes response pps_y_ss_severity_score / pps_y_ss_number prodrom_psych_ss_mean_severity_score
Query upps_y_ss_negative_urgency Integer Recommended UPPS-P for Children Short Form (ABCD-version), Negative Urgency: upps7_y + upps11_y + upps17_y + upps20_y; Validation: Minimum of three items answered Barch, D. M., Albaugh, M.D., et al. (2017) Demographic, physical and mental health assessments in the adolescent brain and cognitive development study: Rationale and description. Dev Cogn Neurosci (In Press). upps_ss_negative_urgency
Query upps_y_ss_negative_urgency_nm Integer Recommended UPPS-P for Children Short Form (ABCD-version), Negative Urgency: Number Missing Answers upps_ss_negative_urgency_nm
Query upps_y_ss_negative_urgency_nt Integer Recommended UPPS-P for Children Short Form (ABCD-version), Negative Urgency: Number Total Questions upps_ss_negative_urgency_nt
Query upps_y_ss_lack_of_planning Integer Recommended UPPS-P for Children Short Form (ABCD-version), Lack of Planning: upps6_y + upps16_y + upps23_y + upps28_y; Validation: Minimum of three items answered Barch, D. M., Albaugh, M.D., et al. (2017) Demographic, physical and mental health assessments in the adolescent brain and cognitive development study: Rationale and description. Dev Cogn Neurosci (In Press). upps_ss_lack_of_planning
Query upps_y_ss_lack_of_planning_nm Integer Recommended UPPS-P for Children Short Form (ABCD-version), Lack of Planning: Number Missing Answers upps_ss_lack_of_planning_nm
Query upps_y_ss_lack_of_planning_nt Integer Recommended UPPS-P for Children Short Form (ABCD-version), Lack of Planning: Number Total Questions upps_ss_lack_of_planning_nt
Query upps_y_ss_sensation_seeking Integer Recommended UPPS-P for Children Short Form (ABCD-version), Sensation Seeking: upps12_y + upps18_y + upps21_y + upps27_y; Validation: Minimum of three items answered Barch, D. M., Albaugh, M.D., et al. (2017) Demographic, physical and mental health assessments in the adolescent brain and cognitive development study: Rationale and description. Dev Cogn Neurosci (In Press). upps_ss_sensation_seeking
Query upps_y_ss_sensation_seeking_nm Integer Recommended UPPS-P for Children Short Form (ABCD-version), Sensation Seeking: Number Missing Answers upps_ss_sensation_seeking_nm
Query upps_y_ss_sensation_seeking_nt Integer Recommended UPPS-P for Children Short Form (ABCD-version), Sensation Seeking: Number Total Questions upps_ss_sensation_seeking_nt
Query upps_y_ss_positive_urgency Integer Recommended UPPS-P for Children Short Form (ABCD-version), Positive Urgency: upps35_y + upps36_y + upps37_y + upps39_y; Validation: Minimum of three items answered Barch, D. M., Albaugh, M.D., et al. (2017) Demographic, physical and mental health assessments in the adolescent brain and cognitive development study: Rationale and description. Dev Cogn Neurosci (In Press). upps_ss_positive_urgency
Query upps_y_ss_positive_urgency_nm Integer Recommended UPPS-P for Children Short Form (ABCD-version), Positive Urgency: Number Missing Answers upps_ss_positive_urgency_nm
Query upps_y_ss_positive_urgency_nt Integer Recommended UPPS-P for Children Short Form (ABCD-version), Positive Urgency: Number Total Questions upps_ss_positive_urgency_nt
Query upps_y_ss_lack_of_perseverance Integer Recommended UPPS: Lack of Perseverance (GSSF) upps15_y plus upps19_y plus upps22_y plus upps24_y Validation : Minimum of three items answered upps_ss_lack_of_perseverance
Query upps_y_ss_lack_of_pers_nm Integer Recommended UPPS: Lack of Perseverance (GSSF) Number Missing Answers upps_ss_lack_of_perseverance_nm, upps_y_ss_lack_of_perseverance_nm
Query upps_y_ss_lack_of_pers_nt Integer Recommended UPPS: Lack of Perseverance (GSSF) Number Total Questions upps_ss_lack_of_perseverance_nt, upps_y_ss_lack_of_perseverance_nt
Query bis_y_ss_bis_sum Integer Recommended BIS/BAS: BIS Sum: bisbas1_y + bisbas2_y + bisbas3_y + bisbas4_y + bisbas5_y + bisbas6_y+ bisbas7_y; Validation: All items must be answered Carver, C. S. and White, T. L. (1994) Behavioral inhibition, behavioral activation and affective responses to impending reward and punishment: the BIS/BAS scales. Journal of Personality and Social Psychology 67(2): 319-333. bis_ss_bis_sum, bisbas_ss_bis_sum
Query bis_y_ss_bis_sum_nm Integer Recommended BIS/BAS, BIS Sum: Number Missing Answers bis_ss_bis_sum_nm, bisbas_ss_bis_sum_nm
Query bis_y_ss_bis_sum_nt Integer Recommended BIS/BAS, BIS Sum: Number Total Questions bis_ss_bis_sum_nt, bisbas_ss_bis_sum_nt
Query bis_y_ss_bas_rr Integer Recommended BIS/BAS: BAS Reward Responsiveness: bisbas8_y + bisbas9_y + bisbas10_y + bisbas11_y + bisbas12_y; Validation: All items must be answered Carver, C. S. and White, T. L. (1994) Behavioral inhibition, behavioral activation and affective responses to impending reward and punishment: the BIS/BAS scales. Journal of Personality and Social Psychology 67(2): 319-333. bis_ss_bas_rr, bisbas_ss_bas_rr
Query bis_y_ss_bas_rr_nm Integer Recommended BIS/BAS, BAS Reward Responsiveness: Number Missing Answers bis_ss_bas_rr_nm, bisbas_ss_bas_rr_nm
Query bis_y_ss_bas_rr_nt Integer Recommended BIS/BAS, BAS Reward Responsiveness: Number Total Questions bis_ss_bas_rr_nt, bisbas_ss_bas_rr_nt
Query bis_y_ss_bas_drive Integer Recommended BIS/BAS: BAS drive: bisbas13_y + bisbas14_y + bisbas15_y + bisbas16_y; Validation: All items must be answered Carver, C. S. and White, T. L. (1994) Behavioral inhibition, behavioral activation and affective responses to impending reward and punishment: the BIS/BAS scales. Journal of Personality and Social Psychology 67(2): 319-333. bis_ss_bas_drive, bisbas_ss_bas_drive
Query bis_y_ss_bas_drive_nm Integer Recommended BIS/BAS, BAS drive: Number Missing Answers bis_ss_bas_drive_nm, bisbas_ss_bas_drive_nm
Query bis_y_ss_bas_drive_nt Integer Recommended BIS/BAS, BAS drive: Number Total Questions bis_ss_bas_drive_nt, bisbas_ss_bas_drive_nt
Query bis_y_ss_bas_fs Integer Recommended BIS/BAS: BAS Fun Seeking: bisbas17_y + bisbas18_y + bisbas19_y + bisbas20_y; Validation: All items must be answered Carver, C. S. and White, T. L. (1994) Behavioral inhibition, behavioral activation and affective responses to impending reward and punishment: the BIS/BAS scales. Journal of Personality and Social Psychology 67(2): 319-333. bis_ss_bas_fs, bisbas_ss_bas_fs
Query bis_y_ss_bas_fs_nm Integer Recommended BIS/BAS, BAS Fun Seeking: Number Missing Answers bis_ss_bas_fs_nm, bisbas_ss_bas_fs_nm
Query bis_y_ss_bas_fs_nt Integer Recommended BIS/BAS, BAS Fun Seeking: Number Total Questions bis_ss_bas_fs_nt, bisbas_ss_bas_fs_nt
Query bis_y_ss_bism_sum Integer Recommended BIS/BAS: BIS Sum (modified): bisbas2_y + bisbas3_y + bisbas4_y + bisbas6_y; Validation: All items must be answered Pagliaccio, D., Luking, K. R., et al. (2016) Revising the BIS/BAS Scale to study development: Measurement invariance and normative effects of age and sex from childhood through adulthood. Psychol Assess 28(4): 429-442. bis_ss_bism_sum, bisbas_ss_bism_sum
Query bis_y_ss_bism_sum_nm Integer Recommended BIS/BAS, BIS Sum (modified): Number Missing Answers bis_ss_bism_sum_nm, bisbas_ss_bism_sum_nm
Query bis_y_ss_bism_sum_nt Integer Recommended BIS/BAS, BIS Sum (modified): Number Total Questions bis_ss_bism_sum_nt, bisbas_ss_bism_sum_nt
Query bis_y_ss_basm_rr Integer Recommended BIS/BAS: BAS Reward Responsiveness (modified): bisbas8_y + bisbas9_y + bisbas11_y + bisbas12_y; Validation: All items must be answered Pagliaccio, D., Luking, K. R., et al. (2016) Revising the BIS/BAS Scale to study development: Measurement invariance and normative effects of age and sex from childhood through adulthood. Psychol Assess 28(4): 429-442. bis_ss_basm_rr, bisbas_ss_basm_rr
Query bis_y_ss_basm_rr_nm Integer Recommended BIS/BAS, BAS Reward Responsiveness (modified): Number Missing Answers bis_ss_basm_rr_nm, bisbas_ss_basm_rr_nm
Query bis_y_ss_basm_rr_nt Integer Recommended BIS/BAS, BAS Reward Responsiveness (modified): Number Total Questions bis_ss_basm_rr_nt, bisbas_ss_basm_rr_nt
Query bis_y_ss_basm_drive Integer Recommended BIS/BAS: BAS drive (modified): bisbas13_y + bisbas14_y + bisbas15_y + bisbas16_y; Validation: All items must be answered Carver, C. S. and White, T. L. (1994) Behavioral inhibition, behavioral activation and affective responses to impending reward and punishment: the BIS/BAS scales. Journal of Personality and Social Psychology 67(2): 319-333. bis_ss_basm_drive, bisbas_ss_basm_drive
Query bis_y_ss_basm_drive_nm Integer Recommended BIS/BAS, BAS drive (modified): Number Missing Answers bis_ss_basm_drive_nm, bisbas_ss_basm_drive_nm
Query bis_y_ss_basm_drive_nt Integer Recommended BIS/BAS, BAS drive (modified): Number Total Questions bis_ss_basm_drive_nt, bisbas_ss_basm_drive_nt
Query delq_y_ss_sum Integer Recommended At 1 year followup: Sum of Yes answers[delq_1_y] plus [delq_2_y] plus [delq_3_y] plus [delq_4_y] plus [delq_5_y] plus [delq_6_y] plus [delq_7_y] plus [delq_8_y] plus [delq_9_y] plus [delq_10_y] At 2 year followup through 2/18/20: After 2/18/20 [delq_7_y] will be added back and the 1 year sum score algorithm will be used. Sum of Yes answers[delq_1_y] plus [delq_2_y] plus [delq_3_y] plus [delq_4_y] plus [delq_5_y] plus [delq_6_y] plus [delq_8_y] plus [delq_9_y] plus [delq_10_y] Validation: All items must be answered delq_ss_sum
Query delq_y_ss_sum_nm Integer Recommended Delinquency: Number Missing Answers delq_ss_sum_nm
Query delq_y_ss_sum_nt Integer Recommended Delinquency: Number Total Questions delq_ss_sum_nt
Query sup_y_ss_sum Integer Recommended 7UP sum ([sup_1_y]:[sup_7_y]) ; Validation: All items must be answered sup_ss_sum
Query sup_y_ss_sum_nm Integer Recommended 7UP sum: Number Missing Answers sup_ss_sum_nm
Query sup_y_ss_sum_nt Integer Recommended 7UP sum : Number Total Questions sup_ss_sum_nt
Query gish_y_ss_m_sum Integer Recommended Gish Male sum(gish_m1_y:gish_m4_y); Validation: All male items must be answered gish_ss_m_sum
Query gish_y_ss_m_sum_nm Integer Recommended GISH Number Missing Answers gish_ss_m_sum_nm
Query gish_y_ss_m_sum_nt Integer Recommended GISH Male Sum: Number Total Questions gish_ss_m_sum_nt
Query gish_y_ss_f_sum Integer Recommended GISH Female (gish_f_y:gish_f4_y); Validation: All female items must be answered gish_ss_f_sum
Query gish_y_ss_f_sum_nm Integer Recommended GISH Female Sum: Number Missing Answers gish_ss_f_sum_nm
Query gish_y_ss_f_sum_nt Float Recommended GISH female Number Total Questions gish_ss_f_sum_nt
peq_ss_relational_aggs_nm Integer Recommended Peer Experiences: Relational Aggression Number Missing peer_experiences_ss_relational_aggression_nm
peq_ss_relational_aggs_nt Integer Recommended Peer Experiences: Relational Aggression Total peer_experiences_ss_relational_aggression_nt
peq_ss_relational_victim Integer Recommended Peer Experiences: Relational Victimization Summary Score; sum(peq_left_out_vic,peq_invite_vic, peq_exclude_vic); Validation: All items must be answered peer_experiences_ss_relational_victim
peq_ss_relational_victim_nm Integer Recommended Peer Experiences: Relational Victimization Number Missing peer_experiences_ss_relational_victim_nm
peq_ss_relational_victim_nt Integer Recommended Peer Experiences: Relational Victimization Number Total peer_experiences_ss_relational_victim_nt
peq_ss_reputation_aggs Integer Recommended Peer Experiences: Reputational Aggression Summary Score; sum(peq_rumor_perp, peq_gossip_perp, peq_loser_perp); Validation: All items must be answered peer_experiences_ss_reputation_aggression
peq_ss_reputation_aggs_nm Integer Recommended Peer Experiences: Reputational Aggression Number Missing peer_experiences_ss_reputation_aggression_nm
peq_ss_reputation_aggs_nt Integer Recommended Peer Experiences: Reputational Aggression Number Total peer_experiences_ss_reputation_aggression_nt
peq_ss_reputation_victim Integer Recommended Peer Experiences: Reputational Victimization Summary Score; sum(peq_rumor_vic, peq_gossip_vic, peq_loser_vic); Validation: All items must be answered peer_experiences_ss_reputation_victim
peq_ss_reputation_victim_nm Integer Recommended Peer Experiences: Reputational Victimization Number Missing peer_experiences_ss_reputation_victim_nm
peq_ss_reputation_victim_nt Integer Recommended Peer Experiences: Reputational Victimization Number Total peer_experiences_ss_reputation_victim_nt
peq_ss_overt_aggression Integer Recommended Overt Aggression Summary Score; sum (peq_chase_perp, peq_threat_perp, peq_hit_perp); Validation: All items must be answered peer_experiences_ss_overt_aggression
peq_ss_overt_aggression_nm Integer Recommended Peer Experiences: Overt Aggression Number Missing peer_experiences_ss_overt_aggression_nm
peq_ss_overt_aggression_nt Integer Recommended Peer Experiences: Overt Aggression Number Total peer_experiences_ss_overt_aggression_nt
peq_ss_overt_victim Integer Recommended Peer Experiences: Overt Victimization Summary Score; sum(peq_chase_vic, peq_threat_vic, peq_hit_vic); Validation: All items must be answered peer_experiences_ss_overt_victim
peq_ss_overt_victim_nm Integer Recommended Peer Experiences: Overt Victimization Number Missing peer_experiences_ss_overt_victim_nm
peq_ss_overt_victim_nt Integer Recommended Peer Experiences: Overt Victimization Number Total peer_experiences_ss_overt_victim_nt
peq_ss_relational_aggs Integer Recommended Peer Experiences: Relational Aggression Summary Score; sum(peq_left_out_perp, peq_invite_perp, peq_exclude_perp); Validation: All items must be answered peer_experiences_ss_relational_aggression
pstr_ss_pr Float Recommended prorate the sum of the 10 questions
erq_ss_reappraisal_pr Integer Recommended prorate the sum of Qs 2,4,6
erq_ss_suppress_pr Integer Recommended prorate the sum of Qs 1,3,5
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
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  • 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
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