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Custom Variables Overview

 

Creating a Custom Variable in Ripple

Custom variables allow you to tailor the information captured for participants in your study. These variables are created and managed at the study level and require Study Admin permissions to set up. Below is a step-by-step guide to creating and managing custom variables:

Steps to Create a Custom Variable

  1. Navigate to Study Settings:

    • Go to the Study Settings tab of the specific study.

  2. Go to the Requirements Section:

    • On the left side of the Study Settings page, click on the Requirements section.

  3. Locate the "Create a New Custom Variable" Button:

    • Scroll to the bottom of the Requirements page.
    • Click the Create a New Custom Variable button to open the custom variable creation window.

Custom Variable Configuration

Once the creation window is open, you will configure your new custom variable by filling out the following fields:

1. Variable Type

    • Selector: A dropdown menu to choose the type of variable (e.g., single-select, number, multiple-choice).
    • Choose the most suitable type based on the data you want to collect.

2. Variable Name

    • Field Type: Short text field.
    • Purpose: A brief description of the variable, which will appear on participant profiles.
    • Example: "Dietary Restrictions" or "Preferred Day of Contact."

3. Variable Options (if applicable)

    • Field Type: Text fields to add options for variables requiring multiple-choice answers.
    • To add another option:
      • Click the Add Option button, and a new text field will appear.
      • Enter the new option into the blank field.
    • Example: For "Dietary Restrictions," options could include "Vegan," "Vegetarian," "Gluten-Free," etc.



    4. Save the Variable:
  • Once all fields are completed, click Save to finalize the custom variable.
  • The new variable will now appear in the participant profile cards for this specific study.

Finalizing and Viewing Custom Variables

Managing Options:

    • To delete an option:
      • Click the red garbage can icon next to the option.
  • To add additional options:
      • Click Add Option and type the new choice in the blank field.

 

Example of Final View in Participant Profile

The custom variable will appear as a labeled field in the participant’s profile card. For example:

Preferred Day of Contact

    • Monday
    • Tuesday
    • Wednesday
    • Thursday
    • Friday

By creating custom variables, you can collect study-specific information that aligns with your research needs, enhancing participant profiles and overall study customization.

Global and Blinded Custom Variables in Ripple

Ripple allows you to manage custom variables at both the global and study-specific levels, with options for making these variables visible or restricted to certain users. Here's a detailed breakdown of Global Custom Variables and Blinded Custom Variables:

1. Global Custom Variables

    • Global Custom Variables appear on a participant's profile card in the registry and in any study where the participant is added.
    • Changes to a global variable in one study will automatically be reflected across all studies where the participant is present, as well as in the registry.

Example:

    • Variable: Preferred Day of Contact
      • Added to Study A and Study B.
      • If "Sunday" is entered in Study A, it will automatically update to "Sunday" in Study B and in the registry.
      • If the value is changed to "Monday" in Study A, this change will also be reflected in Study B and the registry.

Purpose:

    • Ensures consistency for participant data that is relevant across multiple studies.
    • Useful for information like contact preferences, demographics, or other general details.

2. Blinded Custom Variables

    • Blinded Custom Variables are restricted to Study Admin users and are only visible within the study profile card for the specific study.
    • Content in a Global Blinded Variable will never be visible in the registry or to users without Study Admin permissions.

Non-Admin User View:

    • For users without Study Admin permissions, blinded variables will appear as hidden or inaccessible.
    • For example, instead of seeing the content of the variable, non-admin users might see a placeholder or blank field indicating that the data is restricted.

Purpose:

    • Protects sensitive or confidential study-specific information.
    • Ideal for data such as specific medical details, lab results, or private study notes.

Key Differences Between Global and Blinded Custom Variables

Feature Global Custom Variable Blinded Custom Variable
Visibility Visible in the registry and all studies. Visible only to Study Admins within a study.
Data Sharing Synced across all studies and the registry. Data is study-specific and not shared globally.
Non-Admin Access Fully visible to all users with access to studies. Not visible to non-admin users.
Use Case Shared participant details across studies. Sensitive or confidential data.

Practical Use Cases

  • Global Custom Variables: Contact preferences, demographic information, or shared participant history.
  • Blinded Custom Variables: Study-specific notes, medical data, or any information restricted to admins.

By understanding and utilizing these variable types, you can efficiently manage participant data while maintaining control over visibility and confidentiality.

Additional Features for Custom Variables in Ripple

Ripple provides several additional tools to manage and modify custom variables effectively. Below are key features that enhance the customization and usability of variables across studies.

1. Convert a Single-Select Variable to Multi-Select

    • Function: The Convert button allows you to change a single-select variable (where only one option can be chosen) into a multi-select variable (where multiple options can be selected).
    • Important Note: This action is irreversible—once converted, the variable cannot be changed back to single-select.
    • Use Case: If you initially set up a single-choice variable like "Preferred Contact Method" (Phone, Email, Text) and later decide participants may use multiple methods, converting it allows selection of more than one option.

2. Editing a Global Variable

    • Global Variables are locked by default, preventing accidental changes.
    • To make changes:
      • Click the Unlock button to enable editing.
      • Modify the global variable as needed.
      • The variable will automatically re-lock when the page is reloaded.
    • Use Case: If you need to update a shared participant detail like "Preferred Contact Day," unlocking allows edits that will reflect across all studies where the variable is used.

3. Adding an Existing Global Variable to Your Study

    • The Add an Existing Global Variable button lets you reuse a previously created Global Variable from another study.
    • Clicking this button opens a window displaying Add a Global Custom Variable in your Ripple site.
    • Select the desired variable to import it into your study.
    • Use Case: If multiple studies share common variables like "Emergency Contact" or "Allergies," you can reuse them instead of creating duplicates.

 

Reordering Custom Variables in Ripple

Organizing custom variables in a participant profile card helps prioritize the most important information. Ripple provides a Reorder tool that allows you to drag and drop custom variables into the desired order.

How to Reorder Custom Variables

  1. Locate the Custom Variable to Move

    • Navigate to the Study Settings tab.
    • Find the custom variable list within the study settings.

  2. Use the Reorder Tool

    • Hover over the variable you want to move.
    • Click and hold a section of the variable using the four-pronged cursor.

  3. Move the Variable

    • Drag the variable up or down in the list using your mouse scroll or keyboard arrows.

  4. Save the New Order

    • Release the mouse to drop the variable into its new position.
    • The updated order will now reflect in all participant profile cards for that study.

Why Reorder Custom Variables?

  • Place high-priority variables at the top for easy access.
  • Keep participant profiles organized and structured.
  • Improve workflow efficiency by ensuring frequently used variables appear first.