[Skip to Content]

Claim CME

Public Health

Effect of Text Messaging and Behavioral Interventions on COVID-19 Vaccination UptakeA Randomized Clinical Trial

Educational Objective
To identify the key insights or developments described in this article

1 Credit CME

JAMA Network Open

Published Online: June 13, 2022

Original Investigation

Article Information and Disclosures

Shivan J. Mehta, MD, MBA, MSHP^1,2;

Colleen Mallozzi, MBA, RN³;

Pamela A. Shaw, PhD⁴;

Catherine Reitz, MPH^1,2;

Caitlin McDonald, MPH^1,2;

Matthew Vandertuyn, MA²;

Mohan Balachandran, MA, MS²;

Michael Kopinsky, BSE²;

Christianne Sevinc, MPH²;

Aaron Johnson, MA³;

Robin Ward, MS³;

Sae-Hwan Park, PhD³;

Christopher K. Snider, MPH²;

Roy Rosin, MBA²;

David A. Asch, MD, MBA^1,2

Author Affiliations

¹Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia
²Center for Health Care Innovation, University of Pennsylvania, Philadelphia
³Penn Medicine, University of Pennsylvania, Philadelphia
⁴Department of Biostatistics, Epidemiology, and Informatics, University of Pennsylvania, Philadelphia

Read article on JAMA Network

Read Article Claim CME

Key Points

Question Can text messaging with behavioral insights increase participation in COVID-19 vaccine outreach?

Findings In this randomized clinical trial comprising 16 045 participants, text messaging did not result in a higher response rate than outbound telephone calls. Behaviorally informed messaging did not result in a significantly higher response than usual content.

Meaning Text messaging offers a low-cost alternative to outbound telephone calls, but additional efforts are needed to increase vaccine uptake.

Abstract

Importance COVID-19 vaccine uptake among urban populations remains low.

Objective To evaluate whether text messaging with outbound or inbound scheduling and behaviorally informed content might increase COVID-19 vaccine uptake.

Design, Setting, and Participants This randomized clinical trial with a factorial design was conducted from April 29 to July 6, 2021, in an urban academic health system. The trial comprised 16 045 patients at least 18 years of age in Philadelphia, Pennsylvania, with at least 1 primary care visit in the past 5 years, or a future scheduled primary care visit within the next 3 months, who were unresponsive to prior outreach. The study was prespecified in the trial protocol, and data were obtained from the intent-to-treat population.

Interventions Eligible patients were randomly assigned in a 1:20:20 ratio to (1) outbound telephone call only by call center, (2) text message and outbound telephone call by call center to those who respond, or (3) text message, with patients instructed to make an inbound telephone call to a hotline. Patients in groups 2 and 3 were concurrently randomly assigned in a 1:1:1:1 ratio to receive different content: standard messaging, clinician endorsement (eg, “Dr. XXX recommends”), scarcity (“limited supply available”), or endowment framing (“We have reserved a COVID-19 vaccine appointment for you”).

Main Outcomes and Measures The primary outcome was the proportion of patients who completed the first dose of the COVID-19 vaccine within 1 month, according to the electronic health record. Secondary outcomes were the completion of the first dose within 2 months and completion of the vaccination series within 2 months of initial outreach. Additional outcomes included the percentage of patients with invalid cell phone numbers (wrong number or nontextable), no response to text messaging, the percentage of patients scheduled for the vaccine, text message responses, and the number of telephone calls made by the access center. Analysis was on an intention-to-treat basis.

Results Among the 16 045 patients included, the mean (SD) age was 36.9 (11.1) years; 9418 (58.7%) were women; 12 869 (80.2%) had commercial insurance, and 2283 (14.2%) were insured by Medicaid; 8345 (52.0%) were White, 4706 (29.3%) were Black, and 967 (6.0%) were Hispanic or Latino. At 1 month, 14 of 390 patients (3.6% [95% CI, 1.7%-5.4%]) in the outbound telephone call–only group completed 1 vaccine dose, as did 243 of 7890 patients (3.1% [95% CI, 2.7%-3.5%]) in the text plus outbound call group (absolute difference, −0.5% [95% CI, −2.4% to 1.4%]; P = .57) and 253 of 7765 patients (3.3% [95% CI, 2.9%-3.7%]) in the text plus inbound call group (absolute difference, −0.3% [95% CI, −2.2% to 1.6%]; P = .72). Among the 15 655 patients receiving text messaging, 118 of 3889 patients (3.0% [95% CI, 2.5%-3.6%]) in the standard messaging group completed 1 vaccine dose, as did 135 of 3920 patients (3.4% [95% CI, 2.9%-4.0%]) in the clinician endorsement group (absolute difference, 0.4% [95% CI, −0.4% to 1.2%]; P = .31), 100 of 3911 patients (2.6% [95% CI, 2.1%-3.1%]) in the scarcity group (absolute difference, −0.5% [95% CI, −1.2% to 0.3%]; P = .20), and 143 of 3935 patients (3.6% [95% CI, 3.0%-4.2%]) in the endowment group (absolute difference, 0.6% [95% CI, −0.2% to 1.4%]; P = .14).

Conclusions and Relevance There was no detectable increase in vaccination uptake among patients receiving text messaging compared with telephone calls only or behaviorally informed message content.

Trial Registration ClinicalTrials.gov Identifier: NCT04834726

Claim CME

Sign in to take quiz and track your certificates

Buy This Activity

Article Information

Accepted for Publication: April 25, 2022.

Published: June 13, 2022. doi:10.1001/jamanetworkopen.2022.16649

Open Access: This is an open access article distributed under the terms of the CC-BY License. © 2022 Mehta SJ et al. JAMA Network Open.

Corresponding Author: Shivan J. Mehta, MD, MBA, MSHP, 3600 Civic Center Blvd, 8W-206, Philadelphia, PA 19104 (shivan.mehta@pennmedicine.upenn.edu).

Author Contributions: Dr Mehta had full access to all of the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis.

Concept and design: Mehta, Mallozzi, Shaw, Vandertuyn, Balachandran, Kopinsky, Sevinc, Johnson, Ward, Rosin, Asch.

Acquisition, analysis, or interpretation of data: Mehta, Shaw, Reitz, McDonald, Ward, Park, Snider.

Drafting of the manuscript: Mehta, Reitz, McDonald, Sevinc.

Critical revision of the manuscript for important intellectual content: Mallozzi, Shaw, Vandertuyn, Balachandran, Kopinsky, Johnson, Ward, Park, Snider, Rosin, Asch.

Statistical analysis: Shaw, Reitz, McDonald, Park.

Administrative, technical, or material support: Mehta, Mallozzi, Reitz, McDonald, Vandertuyn, Balachandran, Kopinsky, Sevinc, Johnson, Ward, Park, Rosin.

Supervision: Mehta.

Conflict of Interest Disclosures: Dr Mehta reported receiving grants from the National Cancer Institute of the National Institutes of Health during the conduct of the study and personal fees from the American Gastroenterological Association and Guardant Health outside the submitted work. Dr Shaw reported receiving nonfinancial support from Inovio outside the submitted work; and having a patent owned by the University of Pennsylvania that was licensed by Novartis. Dr Asch reported being a partner and part owner of VAL Health; and receiving personal fees from the American Association for Physician Leadership, North American Center for Continuing Medical Education LLC, and Deloitte outside the submitted work. No other disclosures were reported.

Funding/Support: This trial was funded by the University of Pennsylvania Health System. Dr Mehta was supported by grant K08CA234326 from the National Cancer Institute of the National Institutes of Health.

Role of the Funder/Sponsor: The funding sources had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication.

References

Barry V , Dasgupta S , Weller DL , et al. Patterns in COVID-19 vaccination coverage, by social vulnerability and urbanicity—United States, December 14, 2020-May 1, 2021. MMWR Morb Mortal Wkly Rep. 2021;70(22):818-824. doi:10.15585/mmwr.mm7022e1 PubMed Google Scholar Crossref

Pew Research Center. Mobile fact sheet. April 7, 2021. Accessed May 9, 2022. https://www.pewinternet.org/fact-sheets/mobile-technology-fact-sheet/

Cole-Lewis H , Kershaw T . Text messaging as a tool for behavior change in disease prevention and management. Epidemiol Rev. 2010;32:56-69. doi:10.1093/epirev/mxq004 PubMed Google Scholar Crossref

Kahneman D , Tversky A . Prospect theory: an analysis of decision under risk. Econometrica. 1979;47(2):263-291. doi:10.2307/1914185 Google Scholar Crossref

Tversky A , Kahneman D . Judgment under uncertainty: heuristics and biases. Science. 1974;185(4157):1124-1131. doi:10.1126/science.185.4157.1124 PubMed Google Scholar Crossref

Loewenstein G , Brennan T , Volpp KG . Asymmetric paternalism to improve health behaviors. JAMA. 2007;298(20):2415-2417. doi:10.1001/jama.298.20.2415 PubMed Google Scholar Crossref

Chapman GB , Li M , Colby H , Yoon H . Opting in vs opting out of influenza vaccination. JAMA. 2010;304(1):43-44. doi:10.1001/jama.2010.892 PubMed Google Scholar Crossref

Mehta SJ , Day SC , Norris AH , et al. Behavioral interventions to improve population health outreach for hepatitis C screening: randomized clinical trial. BMJ. 2021;373(1022):n1022. doi:10.1136/bmj.n1022 PubMed Google Scholar Crossref

Mehta SJ , Khan T , Guerra C , et al. A randomized controlled trial of opt-in versus opt-out colorectal cancer screening outreach. Am J Gastroenterol. 2018;113(12):1848-1854. doi:10.1038/s41395-018-0151-3 PubMed Google Scholar Crossref

Milkman KL , Patel MS , Gandhi L , et al. A megastudy of text-based nudges encouraging patients to get vaccinated at an upcoming doctor’s appointment. Proc Natl Acad Sci U S A. 2021;118(20):e2101165118. doi:10.1073/pnas.2101165118 PubMed Google Scholar Crossref

Halpern SD , Ubel PA , Asch DA . Harnessing the power of default options to improve health care. N Engl J Med. 2007;357(13):1340-1344. doi:10.1056/NEJMsb071595 PubMed Google Scholar Crossref

Kahneman D , Knetsch JL , Thaler RH . Anomalies: the endowment effect, loss aversion, and status quo bias. J Econ Perspect. 1991;5(1):193-206. doi:10.1257/jep.5.1.193 Google Scholar Crossref

Cialdini RB . Influence: Science and Practice. 4th ed. Allyn & Bacon; 2000.

Aggarwal P , Jun SY , Huh JH . Scarcity messages. J Advertising. 2011;40(3):19-30. doi:10.2753/JOA0091-3367400302 Google Scholar Crossref

Cialdini RB , Trost MR . Social influence: social norms, conformity and compliance. In: Gilbert DT , Fiske ST , Lindzey G , eds. The Handbook of Social Psychology. 4th ed. McGraw-Hill; 1998:151-192.

Serper M , Reddy KR , Bewtra M , Ahmad N , Mehta SJ . COVID-19 vaccine perceptions among patients with chronic disease in a large gastroenterology and hepatology practice. Am J Gastroenterol. 2021;116(6):1345-1349. doi:10.14309/ajg.0000000000001270 PubMed Google Scholar Crossref

Gargano LM , Herbert NL , Painter JE , et al. Impact of a physician recommendation and parental immunization attitudes on receipt or intention to receive adolescent vaccines. Hum Vaccin Immunother. 2013;9(12):2627-2633. doi:10.4161/hv.25823 PubMed Google Scholar Crossref

Asch DA , Ziolek TA , Mehta SJ . Misdirections in informed consent—impediments to health care innovation. N Engl J Med. 2017;377(15):1412-1414. doi:10.1056/NEJMp1707991 PubMed Google Scholar Crossref

Asch DA , Volpp KG . On the way to health. LDI Issue Brief. 2012;17(9):1-4.PubMed Google Scholar

StataCorp. Stata Statistical Software: Release 16. StataCorp LLC; 2019.

Van Rossum G , Drake FL . Python 3 Reference Manual. CreateSpace; 2009.

Seabold S , Perktold J . Statsmodels: econometric and statistical modeling with Python. In: Proceedings of the 9th Python in Science Conference; June 28 to July 3, 2010; Austin, Texas.

Dai H , Saccardo S , Han MA , et al. Behavioral nudges increase COVID-19 vaccinations. Nature. 2021;597(7876):404-409. doi:10.1038/s41586-021-03843-2 PubMed Google Scholar Crossref

Santos HC , Goren A , Chabris CF , Meyer MN . Effect of targeted behavioral science messages on COVID-19 vaccination registration among employees of a large health system: a randomized trial. JAMA Netw Open. 2021;4(7):e2118702. doi:10.1001/jamanetworkopen.2021.18702 PubMed Google Scholar Crossref

Rabb N , Swindal M , Glick D , et al. Text messages do not increase COVID-19 vaccination four weeks after universal eligibility. Accessed April 19, 2022. https://files.osf.io/v1/resources/cg3nt/providers/osfstorage/610d86b5e3801302f5962bda?action=download&direct&version=1

AMA CME Accreditation Information

Credit Designation Statement: The American Medical Association designates this Journal-based CME activity activity for a maximum of 1.00  AMA PRA Category 1 Credit(s)™. Physicians should claim only the credit commensurate with the extent of their participation in the activity.

Successful completion of this CME activity, which includes participation in the evaluation component, enables the participant to earn up to:

1.00 Medical Knowledge MOC points in the American Board of Internal Medicine's (ABIM) Maintenance of Certification (MOC) program;;
1.00 Self-Assessment points in the American Board of Otolaryngology – Head and Neck Surgery’s (ABOHNS) Continuing Certification program;
1.00 MOC points in the American Board of Pediatrics’ (ABP) Maintenance of Certification (MOC) program;
1.00 Lifelong Learning points in the American Board of Pathology’s (ABPath) Continuing Certification program; and
1.00 credit toward the CME [and Self-Assessment requirements] of the American Board of Surgery’s Continuous Certification program

It is the CME activity provider's responsibility to submit participant completion information to ACCME for the purpose of granting MOC credit.