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

Evidation Health17,043 enrolled

Overview

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.

Study Type

INTERVENTIONAL

Allocation

RANDOMIZED

Purpose

PREVENTION

Masking

SINGLE

Enrollment

17,043

Conditions

Influenza Influenza A Influenza B COVID-19 Respiratory Syncytial Virus (RSV)

Interventions

ILI Predictive Alerts, Reactive Content, and Proactive ContentBEHAVIORAL

Participants receive ILI-related education, feedback, and opportunities to self-monitor ILI symptoms, in addition they also receive alerts about potential ILI illness, and reactive and personalized content about protective health behaviors.

ILI Predictive Alerts, Reactive ContentBEHAVIORAL

Participants receive alerts about potential ILI illness, and reactive and personalized content about protective health behaviors.

Proactive ContentBEHAVIORAL

Participants receive ILI-related education, feedback, and opportunities to self-monitor ILI symptoms.

No InterventionBEHAVIORAL

Participants will not receive predictive alerts or reactive content after reporting symptoms or proactive IILI-related health educational content

Eligibility

Sex: ALLMin age: 18 YearsHealthy volunteers:

Medical Language ↔ Plain English

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)

Outcomes

Primary Outcomes

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

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)

Time frame: Through study completion, approximately 10 months

Secondary Outcomes

The secondary objective is to assess the accuracy of an ILI detection algorithm using self-reported symptoms and ILI diagnosis

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