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

NCT06229444 | Completed

• 1 other identifier: Predict + Protect Study
• Study Type: interventional
• Target: 17,043
• Locations: 1 country
• Sites: 1

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.

Conditions

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

Keywords

Flu; Influenza; RSV; COVID; Wearable

Outcome Measures

Primary Outcomes (1)

• 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)

  Through study completion, approximately 10 months

Secondary Outcomes (1)

• 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

Other Outcomes (1)

• The exploratory objective is to assess differences in effectiveness between the four groups on ILI-related health and behavioral outcomes

  Through study completion, approximately 10 months

Study Arms (4)

Proactive ILI content & Predictions

EXPERIMENTAL

Participants will receive predictive alerts, reactive content after reporting symptoms or receiving an asymptomatic prediction, and ILI-related health educational content

Behavioral: ILI Predictive Alerts, Reactive Content, and Proactive Content

No Proactive ILI content & Predictions

EXPERIMENTAL

Participants will receive predictive alerts and reactive content after reporting symptoms or receiving an asymptomatic prediction, but will not receive proactive ILI content

Behavioral: ILI Predictive Alerts, Reactive Content

Proactive ILI content & No Predictions

EXPERIMENTAL

Participants will not receive predictive alerts or reactive content after reporting symptoms but will receive proactive ILI content

Behavioral: Proactive Content

No Proactive ILI content & No Predictions

EXPERIMENTAL

Participants will not receive predictive alerts or reactive content after reporting symptoms or proactive ILI content

Behavioral: No Intervention

Interventions

ILI Predictive Alerts, Reactive Content, and Proactive Content BEHAVIORAL

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.

Proactive ILI content & Predictions

ILI Predictive Alerts, Reactive Content BEHAVIORAL

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

No Proactive ILI content & Predictions

Proactive Content BEHAVIORAL

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

Proactive ILI content & No Predictions

No Intervention BEHAVIORAL

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

No Proactive ILI content & No Predictions

Eligibility Criteria

• Age: 18 Years+
• Sex: all
• Healthy Volunteers: Yes
• Age Groups: Adult (18-64), Older Adult (65+)

You may qualify if:

• Member of the Evidation platform
• 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)

You may not qualify if:

• 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)

Sponsors & Collaborators

• Evidation Health: lead
• Biomedical Advanced Research and Development Authority: collaborator

Study Sites (1)

Evidation Health

San Mateo, California, 94402, United States

Location

Related Publications (18)

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• Mezlini A, Shapiro A, Daza EJ, Caddigan E, Ramirez E, Althoff T, Foschini L. Estimating the Burden of Influenza-like Illness on Daily Activity at the Population Scale Using Commercial Wearable Sensors. JAMA Netw Open. 2022 May 2;5(5):e2211958. doi: 10.1001/jamanetworkopen.2022.11958.

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• Shapiro A, Marinsek N, Clay I, Bradshaw B, Ramirez E, Min J, Trister A, Wang Y, Althoff T, Foschini L. Characterizing COVID-19 and Influenza Illnesses in the Real World via Person-Generated Health Data. Patterns (N Y). 2020 Dec 13;2(1):100188. doi: 10.1016/j.patter.2020.100188. eCollection 2021 Jan 8.

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  BACKGROUND

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• Rosenstock, I. M. (2000). Health Belief Model. In A. E. Kazdin (Ed.), Encyclopedia of psychology (Vol. 4, pp. 78-80). Oxford University Press.

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Related Links

• Centers for Disease Control and Prevention, National Center for Immunization and Respiratory Diseases (NCIRD). Past Seasons Estimated Influenza Disease Burden
• Centers for Disease Control and Prevention, National Center for Immunization and Respiratory Diseases (NCIRD). Past Seasons Estimated Influenza Disease Burden
• Centers for Disease Control and Prevention. COVID Data Tracker.
• Centers for Disease Control and Prevention, Office of Public Health Data, Surveillance, and Technology. 2023. RESP-NET Interactive Dashboard.

MeSH Terms

Conditions

Influenza, Human; COVID-19

Condition Hierarchy (Ancestors)

Respiratory Tract Infections; Infections; Orthomyxoviridae Infections; RNA Virus Infections; Virus Diseases; Respiratory Tract Diseases; Pneumonia, Viral; Pneumonia; Coronavirus Infections; Coronaviridae Infections; Nidovirales Infections; Lung Diseases

Study Officials

• Ernesto H.N. Ramirez, PhD

  Evidation

  PRINCIPAL INVESTIGATOR

Study Design

• Study Type: interventional
• Phase: not applicable
• Allocation: RANDOMIZED
• Masking: SINGLE
• Who Masked: PARTICIPANT
• Masking Details: Participants will be blinded to their study participation status, participants will not be asked to take any action to enroll in the study.
• Purpose: PREVENTION
• Intervention Model: FACTORIAL
• Sponsor Type: INDUSTRY
• Responsible Party: SPONSOR

Study Record Dates

• First Submitted: January 19, 2024
• First Posted: January 29, 2024
• Study Start: February 12, 2024
• Primary Completion: August 5, 2024
• Study Completion: September 6, 2024
• Last Updated: September 19, 2024

Record last verified: 2024-09

Locations

US (1)