Effect of Text Messaging and Behavioral Interventions on COVID-19 Vaccination Uptake: A Randomized Clinical Trial

Shivan J Mehta, Colleen Mallozzi, Pamela A Shaw, Catherine Reitz, Caitlin McDonald, Matthew Vandertuyn, Mohan Balachandran, Michael Kopinsky, Christianne Sevinc, Aaron Johnson, Robin Ward, Sae-Hwan Park, Christopher K Snider, Roy Rosin, David A Asch, Shivan J Mehta, Colleen Mallozzi, Pamela A Shaw, Catherine Reitz, Caitlin McDonald, Matthew Vandertuyn, Mohan Balachandran, Michael Kopinsky, Christianne Sevinc, Aaron Johnson, Robin Ward, Sae-Hwan Park, Christopher K Snider, Roy Rosin, David A Asch

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.

Conflict of interest statement

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.

Figures

Figure.. Consolidated Standards of Reporting Trials Flow…
Figure.. Consolidated Standards of Reporting Trials Flow Diagram
ID indicates identification. aExcluded for receiving 1 or more vaccine doses prior to outreach.

References

    1. 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
    1. Pew Research Center . Mobile fact sheet. April 7, 2021. Accessed May 9, 2022.
    1. 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
    1. Kahneman D, Tversky A. Prospect theory: an analysis of decision under risk. Econometrica. 1979;47(2):263-291. doi:10.2307/1914185
    1. Tversky A, Kahneman D. Judgment under uncertainty: heuristics and biases. Science. 1974;185(4157):1124-1131. doi:10.1126/science.185.4157.1124
    1. 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
    1. 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
    1. 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
    1. 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
    1. 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
    1. 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
    1. 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
    1. Cialdini RB. Influence: Science and Practice. 4th ed. Allyn & Bacon; 2000.
    1. Aggarwal P, Jun SY, Huh JH. Scarcity messages. J Advertising. 2011;40(3):19-30. doi:10.2753/JOA0091-3367400302
    1. 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.
    1. 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
    1. 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
    1. 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
    1. Asch DA, Volpp KG. On the way to health. LDI Issue Brief. 2012;17(9):1-4.
    1. StataCorp . Stata Statistical Software: Release 16. StataCorp LLC; 2019.
    1. Van Rossum G, Drake FL. Python 3 Reference Manual. CreateSpace; 2009.
    1. 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.
    1. 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
    1. 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
    1. 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.

Source: PubMed

3
订阅