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Close event block logic action
Event blocks have made event scheduling very flexible. It has created a new way for your intervention to assign events to a participants in a modular manner based off of specific data. Now, the the “close event block” logic action, you can also end event blocks based off of logicprovide a framework for creating modules within a single intervention. We’ve added a new logic action that allows you to end the event block based off a scheduled rule. For example, you might want to end a daily monitoring check-in for post-surgery drains when a patient reports output over a specified value.
Most recent data in adherence snapshot
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Variables and individual responses in adherence anapshotsnapshot
The adherence snapshot just got more useful and robust! We can now show variables in the adherence snapshot! What would that look like? . For example, you could show a calculated gestational week variable above a weekly blood pressure in order to track a participants BP blood pressure over time. You can also show multiple participant responses in the adherence snapshot. For example, if you have a daily survey with 3 three questions, you can display all three responses in the adherence snapshot under the date of completion.
Update survey and conversation responses in Manage Data
In Manage Data, we have updated standardized the way we record some responses (or lack of responsedisplay missing values:
not answered ( . )
not asked ( - )
error ( ? )
Use variables in conversations and surveys
You can use your study wide global variables in conversations and surveys to make them even more customized to your participants. This could include datepersonalized dates, names or goals. Any variable you calculate can be used in these scenarios.
Calculate values in surveys and conversations
Calculating values in surveys and conversations will allow you “score” or aggregate specific responses as needed. This would be helpful in many clinical scoring tools, like the PHQ-9, in which a total number based on participant responses is relevant to their care or outcomes.
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Variables can now look at multiple sources in order to give you more flexibility in updating participant data as needed. An example of this would be if you needed to make a second version of a survey after your intervention has launched. You could make the single variable look at both the answers from version 1 and version 2 of the survey in order to make sure all participants are assigned the proper variable in logic.
Behind the Scenes
Add appropriate logic actions to W2H sections
Add noncompliant logic action to Enrollment Block events
Add assignStudyGroup logic action to Arm Event
Add ClassifyData (Set adherence snapshot category) to Enrollment Block events
Refactor: remove unnecessary stuff from our layout.php templates
Quarterly upgrade of composer/PHP dependencies
Quarterly upgrade of yarn/JS dependencies
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