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Filter Cart

The Filter Cart provides a powerful way to query and access data for which you may be interested.  

A few points related to the filter cart are important to understand with the NDA Query/Filter implementation: 

First, the filter cart is populated asyncronously.  So, when you run a query, it may take a moment to populate but this will happen in the background so you can define other queries during this time.  

When you are adding your first filter, all data associated with your query will be added to the filter cart (whether it be a collection, a concept, a study, a data structure/elment or subjects). Not all data structures or collections will necessarily be displayed.  For example, if you select the NDA imaging structure image03, and further restrict that query to scan_type fMRI, only fMRI images will appear and only the image03 structure will be shown.  To see other data structures, select "Find All Subject Data" which will query all data for those subjects. When a secord or third filter is applied, an AND condition is used.  A subject must exist in all filters.  If the subject does not appear in any one filter, that subjects data will not be included in your filter cart. If that happens, clear your filter cart, and start over.  

It is best to package more data than you need and access those data using other tools, independent of the NDA (e.g. miNDAR snapshot), to limit the data selected.  If you have any questions on data access, are interested in using avaialble web services, or need help accessing data, please contact us for assistance.  

Frequently Asked Questions



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NDA provides a single access to de-identified autism research data. For permission to download data, you will need an NDA account with approved access to NDA or a connected repository (AGRE, IAN, or the ATP). For NDA access, you need to be a research investigator sponsored by an NIH recognized institution with federal wide assurance. See Request Access for more information.

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Download Definition as
Download Submission Template as
Element NameData TypeSizeRequiredDescriptionValue RangeNotesAliases
subjectkeyGUIDRequiredThe NDAR Global Unique Identifier (GUID) for research subjectNDAR*
src_subject_idString20RequiredSubject ID how it's defined in lab/project
interview_dateDateRequiredDate on which the interview/genetic test/sampling/imaging/biospecimen was completed. MM/DD/YYYYRequired field
interview_ageIntegerRequiredAge in months at the time of the interview/test/sampling/imaging.0 :: 1260Age 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.
sexString20RequiredSex of the subjectM;FM = Male; F = Femalegender
version_formString100RequiredForm used/assessment name
t4rp_1String100RecommendedHow did Texting 4 Relapse Prevention help you understand your illness better?
t4rp_2String100RecommendedHow do you think Texting 4 Relapse Prevention helped you keep track of your symptoms better?
t4rp_3String100RecommendedHow did the program affect your daily life?
t4rp_4String100RecommendedWhat parts of the program did you find most interesting or fun?
t4rp_5String100RecommendedWhat things can we change to make Texting 4 Relapse Prevention better in the future?
t4rp_6String100RecommendedWhat parts of Texting 4 Relapse Prevention were confusing or hard to use?
t4rp_7String100RecommendedWhat did you like best about Texting 4 Relapse Prevention?
t4rp_8String100RecommendedWhat did you like the least about Texting 4 Relapse Prevention?
t4rp_9String100RecommendedWhen, if ever, did you find it hard to read the messages?
t4rp_10String100RecommendedWhen, if ever, was hard to reply to the messages?
t4rp_11String100RecommendedAs a provider, how did Texting 4 Relapse Prevention affect your clinical work?
t4rp_12String100RecommendedDid your patients give you any feedback about the program that you think would be helpful for us to know?
t4rp_13String100RecommendedWhat, if any, negative consequences did the intervention have for the patient?
t4rp_14String100RecommendedHow can we improve Texting 4 Relapse Prevention?
t4rp_15String100RecommendedLastly, if Texting 4 Relapse Prevention were rolled out in clinics in the area, how useful do you think it would be in improving clinical care?
t4rp_16IntegerRecommendedP. I like the Texting 4 Relapse Prevention program. C. My patients liked the Texting 4 Relapse Prevention program.1::51=strongly disagree; 5=strongly agreepas_a1
t4rp_17IntegerRecommendedP. The suggestions the program sent me to help with my symptoms were useful for me.1::51=strongly disagree; 5=strongly agreepas_a2
t4rp_18IntegerRecommendedP. The text messages helped me notice when my symptoms were getting worse faster than I used to before I started the program; C. Texting 4 Relapse Prevention helped my patients better identify when their symptoms got worse earlier than they usually do.1::51=strongly disagree; 5=strongly agreepas_a3
t4rp_19IntegerRecommendedP. Texting 4 Relapse Prevention made it easier to contact my provider when my symptoms got worse; C. The automated system made it easier for me to quickly follow-up with my patients if needed.1::51=strongly disagree; 5=strongly agreepas_a4
t4rp_20IntegerRecommendedP. I found the text messages annoying.1::51=strongly disagree; 5=strongly agreepas_a5
t4rp_21IntegerRecommendedP. The text messages were easy to understand; C. My patients were sometimes confused by the program messages.1::51=strongly disagree; 5=strongly agreepas_a6
t4rp_22IntegerRecommendedP. The text messages that asked me to reply were easy to answer.1::51=strongly disagree; 5=strongly agreepas_a7
t4rp_23IntegerRecommendedP. The text messages were positive and helped me feel supported; C. The intervention helped my patients feel supported.1::51=strongly disagree; 5=strongly agreepas_a8
t4rp_24IntegerRecommendedP. Texting 4 Relapse Prevention got in the way of my daily activities.1::51=strongly disagree; 5=strongly agreepas_a9
t4rp_25IntegerRecommendedP. Texting 4 Relapse Prevention sent me too many text messages every day.1::51=strongly disagree; 5=strongly agreepas_a10
t4rp_26IntegerRecommendedP. If Texting for Relapse Prevention was offered again, I would sign up for it.1::51=strongly disagree; 5=strongly agreepas_a11
t4rp_27IntegerRecommendedP. I would recommend the Texting 4 Relapse Prevention program to other patients who have a similar illness as I do; C. I would recommend Texting 4 Relapse Prevention to other clinicians who have patients with schizophrenia or SAD.1::51=strongly disagree; 5=strongly agreepas_a12
t4rp_28IntegerRecommendedC. As a clinician, I liked the Texting 4 Relapse Prevention program.1::51=strongly disagree; 5=strongly agree
t4rp_29IntegerRecommendedC. I would be unlikely to use this intervention with my patients if it were made available in my clinic.1::51=strongly disagree; 5=strongly agree
t4rp_30IntegerRecommendedC. The automated system made it easier for me to monitor my patients.1::51=strongly disagree; 5=strongly agree
t4rp_31IntegerRecommendedC. The intervention helped my patients better monitor their own symptoms of schizophrenia or schizoaffective disorder.1::51=strongly disagree; 5=strongly agree
t4rp_32IntegerRecommendedC. The program didn't really help my patient's improve their coping skills related to symptom management.1::51=strongly disagree; 5=strongly agree
t4rp_33IntegerRecommendedAcceptability score12::60pat_acc_scale
t4rp_34IntegerRecommended(Patient estimate) How many messages did you receive from the Texting 4 Relapse Prevention program yesterday?pes1
t4rp_35IntegerRecommended(Patient estimate) How many messages did you send to the program yesterday?pes2
t4rp_36IntegerRecommended(Patient estimate) How many messages did you receive from the program in the last 7 days? Your best guess is fine.pes3
t4rp_37IntegerRecommended(Patient estimate) How many messages did you send to the program in the last 7 days? Your best guess is fine.pes4
t4rp_38IntegerRecommended(Patient estimate) In general, how often did you read the program messages in the past 7 days?1::51=Never (0 messages in the past week); 2=Rarely (1-5 messages); 3=Sometimes (6-14 messages); 4=Often (15 - 27messages); 5=always (28 messages)pes5
t4rp_39IntegerRecommended(Program count) Messages sent previous day:
t4rp_40IntegerRecommended(Program count) Messages received previous day:
t4rp_41IntegerRecommended(Program count) Messages sent previous week (7 days):
t4rp_42IntegerRecommended(Program count) Messages received previous week (7 days):
t4rp_ydxString10Recommendedyears since psychiatric diagnosis
psych_hosp_totalIntegerRecommendedTotal number of psychiatric hospitalizations
t4rp_txtString10Recommendedtext messaging tenure
t4rp_cellString10Recommendedlength of time with current cell phone number
t4rp_sentFloatRecommendedaverage number of text messages sent each day
t4rp_recFloatRecommendedaverage number of text messages received each day
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.

Distribution for DataStructure: t4rp01 and Element:
Chart Help

Filters enable researchers to view the data shared in NDA before applying for access or for selecting specific data for download or NDA Study assignment. For those with access to NDA shared data, you may select specific values to be included by selecting an individual bar chart item or by selecting a range of values (e.g. interview_age) using the "Add Range" button. Note that not all elements have appropriately distinct values like comments and subjectkey and are not available for filtering. Additionally, item level detail is not always provided by the research community as indicated by the number of null values given.

Filters for multiple data elements within a structure are supported. Selections across multiple data structures will be supported in a future version of NDA.