Welcome to BeautiFi:
BeautiFi
What is it about?
Welcome to BeautiFi:
App Details
App Screenshots
App Store Description
Welcome to BeautiFi:
The BeautiFi app is a proprietary platform of ObvioHealth being used to carry out a proof-of-concept (POC) project with a potential client (Sponsor).
The POC will simulate a study, following the normal process of a clinical trial (consent, screening, active trial), but the participants will not be standard participants and will instead be employees of the Sponsor. The data collected will not be used or analyzed for research purposes. Instead, the experience of the Sponsor team will be used to determine if they would like to proceed with ObvioHealth and initiate a real research project.
ObvioHealth’s IRB of record, Advarra, has reviewed the project and made the determination that the proct does not meet the DHHS definition of human subjects research under 45 CFR 46, so does not require IRB oversight.
User Journey
Users who are identified for this project by the Sponsor will complete the registration form via the web and be invited to download BeautiFi.
Upon download, the user will create an account and complete the simulated Informed Consent process. Because this is not a research project, this will be a simulation, not a true informed consent proces. Users will also have the opportunity to connect with a member of the mock study team to ask questions prior to signing the informed consent form.
Once the simulated consent process is completed, the users will be presented with a screening questionnaire task. Those that provide responses that mark them as eligible will be invited to continue to the one-day data collection period. Because this is a POC, the responses may be generated for testing purposes rather than being accurate responses from the user.
One-day Data Collection Period
Users will contribute data to the study by completing two questionnaires over a 1-day period.
NOTE: Because this is a POC, the user responses may be generated for testing purposes rather than being accurate responses from the user.
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