Journal article
A megastudy of text-based nudges encouraging patients to get vaccinated at an upcoming doctor's appointment
Proceedings of the National Academy of Sciences - PNAS, v 118(20), 2101165118
18 May 2021
PMID: 33926993
Featured in Collection : UN Sustainable Development Goals @ Drexel
Abstract
Many Americans fail to get life-saving vaccines each year, and the availability of a vaccine for COVID-19 makes the challenge of encouraging vaccination more urgent than ever. We present a large field experiment (N = 47,306) testing 19 nudges delivered to patients via text message and designed to boost adoption of the influenza vaccine. Our findings suggest that text messages sent prior to a primary care visit can boost vaccination rates by an average of 5%. Overall, interventions performed better when they were 1) framed as reminders to get flu shots that were already reserved for the patient and 2) congruent with the sort of communications patients expected to receive from their healthcare provider (i.e., not surprising, casual, or interactive). The best-performing intervention in our study reminded patients twice to get their flu shot at their upcoming doctor's appointment and indicated it was reserved for them. This successful script could be used as a template for campaigns to encourage the adoption of life-saving vaccines, including against COVID-19.
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Details
- Title
- A megastudy of text-based nudges encouraging patients to get vaccinated at an upcoming doctor's appointment
- Creators
- Katherine L. Milkman - University of PennsylvaniaMitesh S. Patel - University of PennsylvaniaLinnea Gandhi - University of PennsylvaniaHeather N. Graci - University of PennsylvaniaDena M. Gromet - University of PennsylvaniaHung Ho - University of PennsylvaniaJoseph S. Kay - University of PennsylvaniaTimothy W. Lee - University of PennsylvaniaModupe Akinola - Columbia UniversityJohn Beshears - Harvard UniversityJonathan E. Bogard - University of California, Los AngelesAlison Buttenheim - University of PennsylvaniaChristopher F. Chabris - Geisinger Health SystemGretchen B. Chapman - Decision Sciences (United States)James J. Choi - Yale UniversityHengchen Dai - University of California, Los AngelesCraig R. Fox - University of California, Los AngelesAmir Goren - Geisinger Health SystemMatthew D. Hilchey - University of TorontoJillian Hmurovic - University of PennsylvaniaLeslie K. John - Harvard UniversityDean Karlan - Northwestern UniversityMelanie Kim - University of TorontoDavid Laibson - Harvard UniversityCait Lamberton - University of PennsylvaniaBrigitte C. Madrian - Brigham Young UniversityMichelle N. Meyer - Geisinger Health SystemMaria Modanu - Columbia UniversityJimin Nam - Harvard UniversityTodd Rogers - Harvard UniversityRenante Rondina - University of TorontoSilvia Saccardo - Decision Sciences (United States)Maheen Shermohammed - Geisinger Health SystemDilip Soman - University of TorontoJehan Sparks - University of California, Los AngelesCaleb Warren - University of ArizonaMegan Weber - University of California, Los AngelesRon Berman - University of PennsylvaniaChalanda N. Evans - University of Pennsylvania Health SystemChristopher K. Snider - Penn Center for AIDS ResearchEli Tsukayama - University of Hawaii–West OahuChristophe Van den Bulte - University of PennsylvaniaKevin G. Volpp - University of PennsylvaniaAngela L. Duckworth - University of Pennsylvania
- Publication Details
- Proceedings of the National Academy of Sciences - PNAS, v 118(20), 2101165118
- Publisher
- Natl Acad Sciences
- Number of pages
- 3
- Grant note
- AKO Foundation P30AG034532 / National Institute on Aging of the National Institutes of Health; United States Department of Health & Human Services; National Institutes of Health (NIH) - USA; NIH National Institute on Aging (NIA) Flu Lab Penn Center for Precision Medicine Accelerator Fund Bill and Melinda Gates Foundation; Bill & Melinda Gates Foundation
- Resource Type
- Journal article
- Language
- English
- Academic Unit
- Pediatrics; Marketing
- Web of Science ID
- WOS:000655732000014
- Scopus ID
- 2-s2.0-85105148403
- Other Identifier
- 991021862297204721
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- Collaboration types
- Domestic collaboration
- International collaboration
- Web of Science research areas
- Multidisciplinary Sciences