Nctid:
NCT06229444
Payload:
{"hasResults"=>false, "derivedSection"=>{"miscInfoModule"=>{"versionHolder"=>"2024-10-04"}, "conditionBrowseModule"=>{"meshes"=>[{"id"=>"D000007251", "term"=>"Influenza, Human"}], "ancestors"=>[{"id"=>"D000012141", "term"=>"Respiratory Tract Infections"}, {"id"=>"D000007239", "term"=>"Infections"}, {"id"=>"D000009976", "term"=>"Orthomyxoviridae Infections"}, {"id"=>"D000012327", "term"=>"RNA Virus Infections"}, {"id"=>"D000014777", "term"=>"Virus Diseases"}, {"id"=>"D000012140", "term"=>"Respiratory Tract Diseases"}], "browseLeaves"=>[{"id"=>"M17522", "name"=>"Virus Diseases", "relevance"=>"LOW"}, {"id"=>"M10295", "name"=>"Influenza, Human", "asFound"=>"Influenza", "relevance"=>"HIGH"}, {"id"=>"M2561", "name"=>"COVID-19", "relevance"=>"LOW"}, {"id"=>"M10283", "name"=>"Infections", "relevance"=>"LOW"}, {"id"=>"M6368", "name"=>"Communicable Diseases", "relevance"=>"LOW"}, {"id"=>"M14978", "name"=>"Respiratory Tract Infections", "relevance"=>"LOW"}, {"id"=>"M12902", "name"=>"Orthomyxoviridae Infections", "relevance"=>"LOW"}, {"id"=>"M15149", "name"=>"RNA Virus Infections", "relevance"=>"LOW"}, {"id"=>"M14977", "name"=>"Respiratory Tract Diseases", "relevance"=>"LOW"}], "browseBranches"=>[{"name"=>"Infections", "abbrev"=>"BC01"}, {"name"=>"All Conditions", "abbrev"=>"All"}, {"name"=>"Respiratory Tract (Lung and Bronchial) Diseases", "abbrev"=>"BC08"}, {"name"=>"Symptoms and General Pathology", "abbrev"=>"BC23"}]}}, "documentSection"=>{"largeDocumentModule"=>{"largeDocs"=>[{"date"=>"2024-02-08", "size"=>144317, "label"=>"Informed Consent Form", "hasIcf"=>true, "hasSap"=>false, "filename"=>"ICF_001.pdf", "typeAbbrev"=>"ICF", "uploadDate"=>"2024-02-15T16:15", "hasProtocol"=>false}]}}, "protocolSection"=>{"designModule"=>{"phases"=>["NA"], "studyType"=>"INTERVENTIONAL", "designInfo"=>{"allocation"=>"RANDOMIZED", "maskingInfo"=>{"masking"=>"SINGLE", "whoMasked"=>["PARTICIPANT"], "maskingDescription"=>"Participants will be blinded to their study participation status, participants will not be asked to take any action to enroll in the study."}, "primaryPurpose"=>"PREVENTION", "interventionModel"=>"FACTORIAL"}, "enrollmentInfo"=>{"type"=>"ACTUAL", "count"=>17043}}, "statusModule"=>{"overallStatus"=>"COMPLETED", "startDateStruct"=>{"date"=>"2024-02-12", "type"=>"ACTUAL"}, "expandedAccessInfo"=>{"hasExpandedAccess"=>false}, "statusVerifiedDate"=>"2024-09", "completionDateStruct"=>{"date"=>"2024-09-06", "type"=>"ACTUAL"}, "lastUpdateSubmitDate"=>"2024-09-09", "studyFirstSubmitDate"=>"2024-01-19", "studyFirstSubmitQcDate"=>"2024-01-19", "lastUpdatePostDateStruct"=>{"date"=>"2024-09-19", "type"=>"ACTUAL"}, "studyFirstPostDateStruct"=>{"date"=>"2024-01-29", "type"=>"ACTUAL"}, "primaryCompletionDateStruct"=>{"date"=>"2024-08-05", "type"=>"ACTUAL"}}, "outcomesModule"=>{"otherOutcomes"=>[{"measure"=>"The exploratory objective is to assess differences in effectiveness between the four groups on ILI-related health and behavioral outcomes", "timeFrame"=>"Through study completion, approximately 10 months", "description"=>"The difference between all 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)"}], "primaryOutcomes"=>[{"measure"=>"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", "timeFrame"=>"Through study completion, approximately 10 months", "description"=>"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)"}], "secondaryOutcomes"=>[{"measure"=>"The secondary objective is to assess the accuracy of an ILI detection algorithm using self-reported symptoms and ILI diagnosis", "timeFrame"=>"Through study completion, approximately 10 months", "description"=>"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"}]}, "oversightModule"=>{"oversightHasDmc"=>false, "isFdaRegulatedDrug"=>false, "isFdaRegulatedDevice"=>false}, "conditionsModule"=>{"keywords"=>["Flu", "Influenza", "RSV", "COVID", "Wearable"], "conditions"=>["Influenza", "Influenza A", "Influenza B", "COVID-19", "Respiratory Syncytial Virus (RSV)"]}, "referencesModule"=>{"references"=>[{"pmid"=>"36890264", "type"=>"BACKGROUND", "citation"=>"Wiemken TL, Khan F, Puzniak L, Yang W, Simmering J, Polgreen P, Nguyen JL, Jodar L, McLaughlin JM. Seasonal trends in COVID-19 cases, hospitalizations, and mortality in the United States and Europe. Sci Rep. 2023 Mar 8;13(1):3886. doi: 10.1038/s41598-023-31057-1."}, {"pmid"=>"29206909", "type"=>"BACKGROUND", "citation"=>"Tokars JI, Olsen SJ, Reed C. Seasonal Incidence of Symptomatic Influenza in the United States. Clin Infect Dis. 2018 May 2;66(10):1511-1518. doi: 10.1093/cid/cix1060."}, {"pmid"=>"35759279", "type"=>"BACKGROUND", "citation"=>"Temple DS, Hegarty-Craver M, Furberg RD, Preble EA, Bergstrom E, Gardener Z, Dayananda P, Taylor L, Lemm NM, Papargyris L, McClain MT, Nicholson BP, Bowie A, Miggs M, Petzold E, Woods CW, Chiu C, Gilchrist KH. Wearable Sensor-Based Detection of Influenza in Presymptomatic and Asymptomatic Individuals. J Infect Dis. 2023 Apr 12;227(7):864-872. doi: 10.1093/infdis/jiac262."}, {"pmid"=>"35552722", "type"=>"BACKGROUND", "citation"=>"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."}, {"pmid"=>"33506230", "type"=>"BACKGROUND", "citation"=>"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."}, {"pmid"=>"36951890", "type"=>"BACKGROUND", "citation"=>"Hunter V, Shapiro A, Chawla D, Drawnel F, Ramirez E, Phillips E, Tadesse-Bell S, Foschini L, Ukachukwu V. Characterization of Influenza-Like Illness Burden Using Commercial Wearable Sensor Data and Patient-Reported Outcomes: Mixed Methods Cohort Study. J Med Internet Res. 2023 Mar 23;25:e41050. doi: 10.2196/41050."}, {"type"=>"BACKGROUND", "citation"=>"Merrill MA, Safranchik E, Kolbeinsson A, Gade P, Ramirez E, Schmidt L, Foshchini L, Althoff T. Homekit2020: A benchmark for time series classification on a large mobile sensing dataset with laboratory tested ground truth of influenza infections. Proceedings of Machine Learning Research LEAVE UNSET:1-22, 2023."}, {"pmid"=>"35480626", "type"=>"BACKGROUND", "citation"=>"Mayer C, Tyler J, Fang Y, Flora C, Frank E, Tewari M, Choi SW, Sen S, Forger DB. Consumer-grade wearables identify changes in multiple physiological systems during COVID-19 disease progression. Cell Rep Med. 2022 Apr 19;3(4):100601. doi: 10.1016/j.xcrm.2022.100601. eCollection 2022 Apr 19."}, {"pmid"=>"36963907", "type"=>"BACKGROUND", "citation"=>"Nestor B, Hunter J, Kainkaryam R, Drysdale E, Inglis JB, Shapiro A, Nagaraj S, Ghassemi M, Foschini L, Goldenberg A. Machine learning COVID-19 detection from wearables. Lancet Digit Health. 2023 Apr;5(4):e182-e184. doi: 10.1016/S2589-7500(23)00045-6. No abstract available."}, {"type"=>"BACKGROUND", "citation"=>"Rosenstock, I. M. (2000). Health Belief Model. In A. E. Kazdin (Ed.), Encyclopedia of psychology (Vol. 4, pp. 78-80). Oxford University Press."}, {"pmid"=>"35898953", "type"=>"BACKGROUND", "citation"=>"Zewdie A, Mose A, Sahle T, Bedewi J, Gashu M, Kebede N, Yimer A. The health belief model's ability to predict COVID-19 preventive behavior: A systematic review. SAGE Open Med. 2022 Jul 22;10:20503121221113668. doi: 10.1177/20503121221113668. eCollection 2022."}, {"pmid"=>"33431259", "type"=>"BACKGROUND", "citation"=>"Mercadante AR, Law AV. Will they, or Won't they? Examining patients' vaccine intention for flu and COVID-19 using the Health Belief Model. Res Social Adm Pharm. 2021 Sep;17(9):1596-1605. doi: 10.1016/j.sapharm.2020.12.012. Epub 2020 Dec 30."}, {"pmid"=>"36165548", "type"=>"BACKGROUND", "citation"=>"Gutierrez F, Wolfe J. Using the Health Belief Model to improve influenza vaccination rates. JAAPA. 2022 Oct 1;35(10):46-47. doi: 10.1097/01.JAA.0000873832.52485.65."}, {"pmid"=>"37747766", "type"=>"BACKGROUND", "citation"=>"Richardson KM, Jospe MR, Saleh AA, Clarke TN, Bedoya AR, Behrens N, Marano K, Cigan L, Liao Y, Scott ER, Guo JS, Aguinaga A, Schembre SM. Use of Biological Feedback as a Health Behavior Change Technique in Adults: Scoping Review. J Med Internet Res. 2023 Sep 25;25:e44359. doi: 10.2196/44359."}, {"pmid"=>"24275499", "type"=>"BACKGROUND", "citation"=>"McCambridge J, Witton J, Elbourne DR. Systematic review of the Hawthorne effect: new concepts are needed to study research participation effects. J Clin Epidemiol. 2014 Mar;67(3):267-77. doi: 10.1016/j.jclinepi.2013.08.015. Epub 2013 Nov 22."}, {"pmid"=>"27748683", "type"=>"BACKGROUND", "citation"=>"Mansournia MA, Higgins JP, Sterne JA, Hernan MA. Biases in Randomized Trials: A Conversation Between Trialists and Epidemiologists. Epidemiology. 2017 Jan;28(1):54-59. doi: 10.1097/EDE.0000000000000564. Erratum In: Epidemiology. 2018 Sep;29(5):e49. doi: 10.1097/EDE.0000000000000846."}, {"pmid"=>"31647125", "type"=>"BACKGROUND", "citation"=>"LaFave SE, Granbom M, Cudjoe TKM, Gottsch A, Shorb G, Szanton SL. Attention control group activities and perceived benefit in a trial of a behavioral intervention for older adults. Res Nurs Health. 2019 Dec;42(6):476-482. doi: 10.1002/nur.21992. Epub 2019 Oct 24."}, {"pmid"=>"34535755", "type"=>"BACKGROUND", "citation"=>"Lee JL, Foschini L, Kumar S, Juusola J, Liska J, Mercer M, Tai C, Buzzetti R, Clement M, Cos X, Ji L, Kanumilli N, Kerr D, Montanya E, Muller-Wieland D, Ostenson CG, Skolnik N, Woo V, Burlet N, Greenberg M, Samson SI. Digital intervention increases influenza vaccination rates for people with diabetes in a decentralized randomized trial. NPJ Digit Med. 2021 Sep 17;4(1):138. doi: 10.1038/s41746-021-00508-2."}], "seeAlsoLinks"=>[{"url"=>"https://www.cdc.gov/flu-burden/php/about/index.html?CDC_AAref_Val=https://www.cdc.gov/flu/about/burden/past-seasons.html", "label"=>"Centers for Disease Control and Prevention, National Center for Immunization and Respiratory Diseases (NCIRD). Past Seasons Estimated Influenza Disease Burden"}, {"url"=>"https://www.cdc.gov/flu-burden/php/data-vis/?CDC_AAref_Val=https://www.cdc.gov/flu/about/burden/preliminary-in-season-estimates.htm", "label"=>"Centers for Disease Control and Prevention, National Center for Immunization and Respiratory Diseases (NCIRD). Past Seasons Estimated Influenza Disease Burden"}, {"url"=>"https://www.cdc.gov/resp-net/dashboard/?CDC_AA_refVal=https%3A%2F%2Fwww.cdc.gov%2Fsurveillance%2Fresp-net%2Fdashboard.html", "label"=>"Centers for Disease Control and Prevention, Office of Public Health Data, Surveillance, and Technology. 2023. RESP-NET Interactive Dashboard."}]}, "descriptionModule"=>{"briefSummary"=>"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."}, "eligibilityModule"=>{"sex"=>"ALL", "stdAges"=>["ADULT", "OLDER_ADULT"], "minimumAge"=>"18 years", "healthyVolunteers"=>true, "eligibilityCriteria"=>"Inclusion Criteria:\n\n* Member of the Evidation platform\n* 18 years or older\n* Lives in the U.S.\n* Currently owns and uses a consumer wearable activity tracker (Apple Watch, Garmin, or Fitbit) linked to their Evidation account\n* 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)\n\nExclusion Criteria:\n\n* Does not have an Evidation account\n* Not 18 years or older\n* Does not live in the U.S.\n* Does not have an activity tracker linked to their Evidation account\n* Enrolled in an Evidation supported ILI monitoring and engagement program, or clinical study (e.g., FluSmart)"}, "identificationModule"=>{"nctId"=>"NCT06229444", "briefTitle"=>"Predict + Protect Study: Exploring the Effectiveness of a Predictive Health Education Intervention on the Adoption of Protective Behaviors Related to ILI", "organization"=>{"class"=>"INDUSTRY", "fullName"=>"Evidation Health"}, "officialTitle"=>"Predict + Protect: A Randomized Controlled Trial Exploring the Effectiveness of a Predictive Health Education Intervention on the Adoption of Protective Behaviors Related to Influenza-like Illness (ILI)", "orgStudyIdInfo"=>{"id"=>"Predict + Protect Study"}}, "armsInterventionsModule"=>{"armGroups"=>[{"type"=>"EXPERIMENTAL", "label"=>"Proactive ILI content & Predictions", "description"=>"Participants will receive predictive alerts, reactive content after reporting symptoms or receiving an asymptomatic prediction, and ILI-related health educational content", "interventionNames"=>["Behavioral: ILI Predictive Alerts, Reactive Content, and Proactive Content"]}, {"type"=>"EXPERIMENTAL", "label"=>"No Proactive ILI content & Predictions", "description"=>"Participants will receive predictive alerts and reactive content after reporting symptoms or receiving an asymptomatic prediction, but will not receive proactive ILI content", "interventionNames"=>["Behavioral: ILI Predictive Alerts, Reactive Content"]}, {"type"=>"EXPERIMENTAL", "label"=>"Proactive ILI content & No Predictions", "description"=>"Participants will not receive predictive alerts or reactive content after reporting symptoms but will receive proactive ILI content", "interventionNames"=>["Behavioral: Proactive Content"]}, {"type"=>"EXPERIMENTAL", "label"=>"No Proactive ILI content & No Predictions", "description"=>"Participants will not receive predictive alerts or reactive content after reporting symptoms or proactive ILI content", "interventionNames"=>["Behavioral: No Intervention"]}], "interventions"=>[{"name"=>"ILI Predictive Alerts, Reactive Content, and Proactive Content", "type"=>"BEHAVIORAL", "description"=>"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.", "armGroupLabels"=>["Proactive ILI content & Predictions"]}, {"name"=>"ILI Predictive Alerts, Reactive Content", "type"=>"BEHAVIORAL", "description"=>"Participants receive alerts about potential ILI illness, and reactive and personalized content about protective health behaviors.", "armGroupLabels"=>["No Proactive ILI content & Predictions"]}, {"name"=>"Proactive Content", "type"=>"BEHAVIORAL", "description"=>"Participants receive ILI-related education, feedback, and opportunities to self-monitor ILI symptoms.", "armGroupLabels"=>["Proactive ILI content & No Predictions"]}, {"name"=>"No Intervention", "type"=>"BEHAVIORAL", "description"=>"Participants will not receive predictive alerts or reactive content after reporting symptoms or proactive IILI-related health educational content", "armGroupLabels"=>["No Proactive ILI content & No Predictions"]}]}, "contactsLocationsModule"=>{"locations"=>[{"zip"=>"94402", "city"=>"San Mateo", "state"=>"California", "country"=>"United States", "facility"=>"Evidation Health", "geoPoint"=>{"lat"=>37.56299, "lon"=>-122.32553}}], "overallOfficials"=>[{"name"=>"Ernesto H.N. Ramirez, PhD", "role"=>"PRINCIPAL_INVESTIGATOR", "affiliation"=>"Evidation"}]}, "sponsorCollaboratorsModule"=>{"leadSponsor"=>{"name"=>"Evidation Health", "class"=>"INDUSTRY"}, "collaborators"=>[{"name"=>"Biomedical Advanced Research and Development Authority", "class"=>"FED"}], "responsibleParty"=>{"type"=>"SPONSOR"}}}}
