Literature DB >> 36206046

Influence of Digital Intervention Messaging on Influenza Vaccination Rates Among Adults With Cardiovascular Disease in the United States: Decentralized Randomized Controlled Trial.

Nell J Marshall1, Jennifer L Lee1, Jessica Schroeder1, Wei-Nchih Lee1, Jermyn See1, Mohammad Madjid2, Mrudula R Munagala3, John D Piette4, Litjen Tan5, Orly Vardeny6, Michael Greenberg7, Jan Liska8, Monica Mercer7, Sandrine Samson9.   

Abstract

BACKGROUND: Seasonal influenza affects 5% to 15% of Americans annually, resulting in preventable deaths and substantial economic impact. Influenza infection is particularly dangerous for people with cardiovascular disease, who therefore represent a priority group for vaccination campaigns.
OBJECTIVE: We aimed to assess the effects of digital intervention messaging on self-reported rates of seasonal influenza vaccination.
METHODS: This was a randomized, controlled, single-blind, and decentralized trial conducted at individual locations throughout the United States over the 2020-2021 influenza season. Adults with self-reported cardiovascular disease who were members of the Achievement mobile platform were randomized to receive or not receive a series of 6 patient-centered digital intervention messages promoting influenza vaccination. The primary end point was the between-group difference in self-reported vaccination rates at 6 months after randomization. Secondary outcomes included the levels of engagement with the messages and the relationship between vaccination rates and engagement with the messages. Subgroup analyses examined variation in intervention effects by race. Controlling for randomization group, we examined the impact of other predictors of vaccination status, including cardiovascular condition type, vaccine drivers or barriers, and vaccine knowledge.
RESULTS: Of the 49,138 randomized participants, responses on the primary end point were available for 11,237 (22.87%; 5575 in the intervention group and 5662 in the control group) participants. The vaccination rate was significantly higher in the intervention group (3418/5575, 61.31%) than the control group (3355/5662, 59.25%; relative risk 1.03, 95% CI 1.004-1.066; P=.03). Participants who were older, more educated, and White or Asian were more likely to report being vaccinated. The intervention was effective among White participants (P=.004) but not among people of color (P=.42). The vaccination rate was 13 percentage points higher among participants who completed all 6 intervention messages versus none, and at least 2 completed messages appeared to be needed for effectiveness. Participants who reported a diagnosis of COVID-19 were more likely to be vaccinated for influenza regardless of treatment assignment.
CONCLUSIONS: This personalized, evidence-based digital intervention was effective in increasing vaccination rates in this population of high-risk people with cardiovascular disease. TRIAL REGISTRATION: ClinicalTrials.gov NCT04584645; https://clinicaltrials.gov/ct2/show/NCT04584645. ©Nell J Marshall, Jennifer L Lee, Jessica Schroeder, Wei-Nchih Lee, Jermyn See, Mohammad Madjid, Mrudula R Munagala, John D Piette, Litjen Tan, Orly Vardeny, Michael Greenberg, Jan Liska, Monica Mercer, Sandrine Samson. Originally published in the Journal of Medical Internet Research (https://www.jmir.org), 07.10.2022.

Entities:  

Keywords:  cardiovascular disease; digital intervention; digital messaging; immunization; influenza; mHealth; mobile health; public health; randomized trial; vaccination

Mesh:

Substances:

Year:  2022        PMID: 36206046      PMCID: PMC9587491          DOI: 10.2196/38710

Source DB:  PubMed          Journal:  J Med Internet Res        ISSN: 1438-8871            Impact factor:   7.076


  31 in total

1.  How to calculate sample size in randomized controlled trial?

Authors:  Baoliang Zhong
Journal:  J Thorac Dis       Date:  2009-12       Impact factor: 2.895

2.  Text messages for influenza vaccination among pregnant women: A randomized controlled trial.

Authors:  Mark H Yudin; Niraj Mistry; Leanne R De Souza; Kate Besel; Vishal Patel; Sonia Blanco Mejia; Robyn Bernick; Victoria Ryan; Marcelo Urquia; Richard H Beigi; Michelle H Moniz; Michael Sgro
Journal:  Vaccine       Date:  2017-01-03       Impact factor: 3.641

3.  Effect of Patient Portal Reminders Sent by a Health Care System on Influenza Vaccination Rates: A Randomized Clinical Trial.

Authors:  Peter G Szilagyi; Christina Albertin; Alejandra Casillas; Rebecca Valderrama; O Kenrik Duru; Michael K Ong; Sitaram Vangala; Chi-Hong Tseng; Cynthia M Rand; Sharon G Humiston; Sharon Evans; Michael Sloyan; Carlos Lerner
Journal:  JAMA Intern Med       Date:  2020-07-01       Impact factor: 21.873

4.  Association between influenza vaccination and cardiovascular outcomes in high-risk patients: a meta-analysis.

Authors:  Jacob A Udell; Rami Zawi; Deepak L Bhatt; Maryam Keshtkar-Jahromi; Fiona Gaughran; Arintaya Phrommintikul; Andrzej Ciszewski; Hossein Vakili; Elaine B Hoffman; Michael E Farkouh; Christopher P Cannon
Journal:  JAMA       Date:  2013-10-23       Impact factor: 56.272

5.  Large-scale influenza vaccination promotion on a mobile app platform: A randomized controlled trial.

Authors:  Wei-Nchih Lee; David Stück; Kevin Konty; Caitlin Rivers; Courtney R Brown; Susan M Zbikowski; Luca Foschini
Journal:  Vaccine       Date:  2019-11-29       Impact factor: 3.641

Review 6.  Influenza vaccines for preventing cardiovascular disease.

Authors:  Christine Clar; Zainab Oseni; Nadine Flowers; Maryam Keshtkar-Jahromi; Karen Rees
Journal:  Cochrane Database Syst Rev       Date:  2015-05-05

7.  Effects of Influenza Vaccine on Mortality and Cardiovascular Outcomes in Patients With Cardiovascular Disease: A Systematic Review and Meta-Analysis.

Authors:  Siva H Yedlapati; Safi U Khan; Swapna Talluri; Ahmed N Lone; Muhammad Zia Khan; Muhammad Shahzeb Khan; Ann M Navar; Martha Gulati; Heather Johnson; Seth Baum; Erin D Michos
Journal:  J Am Heart Assoc       Date:  2021-03-13       Impact factor: 5.501

8.  Increasing influenza vaccination rates via low cost messaging interventions.

Authors:  Ernest Baskin
Journal:  PLoS One       Date:  2018-02-14       Impact factor: 3.240

9.  A 680,000-person megastudy of nudges to encourage vaccination in pharmacies.

Authors:  Katherine L Milkman; Linnea Gandhi; Mitesh S Patel; Heather N Graci; Dena M Gromet; Hung Ho; Joseph S Kay; Timothy W Lee; Jake Rothschild; Jonathan E Bogard; Ilana Brody; Christopher F Chabris; Edward Chang; Gretchen B Chapman; Jennifer E Dannals; Noah J Goldstein; Amir Goren; Hal Hershfield; Alex Hirsch; Jillian Hmurovic; Samantha Horn; Dean S Karlan; Ariella S Kristal; Cait Lamberton; Michelle N Meyer; Allison H Oakes; Maurice E Schweitzer; Maheen Shermohammed; Joachim Talloen; Caleb Warren; Ashley Whillans; Kuldeep N Yadav; Julian J Zlatev; Ron Berman; Chalanda N Evans; Rahul Ladhania; Jens Ludwig; Nina Mazar; Sendhil Mullainathan; Christopher K Snider; Jann Spiess; Eli Tsukayama; Lyle Ungar; Christophe Van den Bulte; Kevin G Volpp; Angela L Duckworth
Journal:  Proc Natl Acad Sci U S A       Date:  2022-02-08       Impact factor: 11.205

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