Predict + Protect Study: Exploring the Effectiveness of a Predictive Health Education Intervention on the Adoption of Protective Behaviors Related to ILI

Not Applicable

Active, not recruiting

• Conditions: Respiratory Syncytial Virus (RSV); Influenza; Influenza A; COVID-19; Influenza B
• Interventions: Behavioral: ILI Predictive Alerts, Reactive Content, and Proactive Content; Behavioral: ILI Predictive Alerts, Reactive Content; Behavioral: Proactive Content; Behavioral: No Intervention

• Registration Number: NCT06229444
• Lead Sponsor: Evidation Health

Brief Summary

The goal of this prospective, digital randomized controlled trial is to evaluate the effectiveness of a predictive ILI detection algorithm and associated alerts during influenza season for adults living in the contigent United States. The main study objectives are to assess the effectiveness of predictive ILI detection algorithm and associated alerts on protective behaviors related to ILI and assess the accuracy of a predictive ILI detection algorithm using participant self-reported ILI symptoms and diagnosis.

Detailed Description

Not available

Study Timeline

• Study First Submitted: 2024-01-19
• Study First Submitted QC: 2024-01-19
• Study First Posted: 2024-01-29
• Study Start: 2024-02-12
• Status Verified: 2024-08
• Primary Completion: 2024-08-05
• Last Update Submitted: 2024-08-27
• Last Update Posted: 2024-08-29
• Study Completion: 2024-09-06

Recruitment & Eligibility

• Status: ACTIVE_NOT_RECRUITING
• Sex: All
• Target Recruitment: 15000

Inclusion Criteria

• Member of the Evidation platform
• 18 years or older
• Lives in the U.S.
• Currently owns and uses a consumer wearable activity tracker (Apple Watch, Garmin, or Fitbit) linked to their Evidation account
• Meets data density requirements for wearable data: Steps and heart rate data present for 15% of the last 60 days (or no fewer than 2 total days for Evidation accounts less than 60 days old)

Exclusion Criteria

• Does not have an Evidation account
• Not 18 years or older
• Does not live in the U.S.
• Does not have an activity tracker linked to their Evidation account
• Enrolled in an Evidation supported ILI monitoring and engagement program, or clinical study (e.g., FluSmart)

Study & Design

• Study Type: INTERVENTIONAL
• Study Design: FACTORIAL

Arm && Interventions

Group	Intervention	Description
Proactive ILI content & Predictions	ILI Predictive Alerts, Reactive Content, and Proactive Content	Participants will receive predictive alerts, reactive content after reporting symptoms or receiving an asymptomatic prediction, and ILI-related health educational content
No Proactive ILI content & Predictions	ILI Predictive Alerts, Reactive Content	Participants will receive predictive alerts and reactive content after reporting symptoms or receiving an asymptomatic prediction, but will not receive proactive ILI content
Proactive ILI content & No Predictions	Proactive Content	Participants will not receive predictive alerts or reactive content after reporting symptoms but will receive proactive ILI content
No Proactive ILI content & No Predictions	No Intervention	Participants will not receive predictive alerts or reactive content after reporting symptoms or proactive ILI content

Primary Outcome Measures

Name	Time	Method
The primary objective of this study is to assess the effectiveness of a predictive ILI detection algorithm and associated alerts on ILI-related health and behavioral outcomes	Through study completion, approximately 10 months	The difference between the predictive alert and the no predictive alert groups in the proportion of cohort members who performed any target health behavior 1-4 (i.e. performed at least one of: reduced spread, tested, sought medical attention, or was treatment adherent)

Secondary Outcome Measures

Name	Time	Method
The secondary objective is to assess the accuracy of an ILI detection algorithm using self-reported symptoms and ILI diagnosis	Through study completion, approximately 10 months	Evaluate algorithm performance (against labels from self-reported ILI symptoms and/or self-reported positive diagnosis) overall and per model deployed. Algorithm performance will be assessed across a variety of dimensions including ROC AUC, sensitivity, specificity, PPV, and NPV

Trial Locations

Locations (1)

Evidation Health; 🇺🇸 San Mateo, California, United States