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This is a prospective randomized clinical trial evaluating how behaviorally-informed outreach text messages affect the take-up of bivalent COVID-19 booster. The investigators will test the impact of sending text reminders as well as the importance of elevating vaccination intentions, facilitating action, and their combination.
Full description
Shortly after COVID-19 bivalent boosters were authorized, UCLA Health emailed its patients encouraging them to get the covid booster either at UCLA Health or at local pharmacies. The investigators plan to conduct a randomized controlled trial, several weeks after this initial communication, to test how text-based reminders that boost intentions and/or facilitate action affect the take-up of COVID-19 bivalent boosters. Among all UCLA Health patients eligible to receive the COVID-19 bivalent booster, the investigators will randomly select 35% for this trial, 40% for another trial (Pre-registration title: "Information Provision and Consistency Framing to Increase COVID-19 Booster Uptake") and 25% for a third trial (Pre-registration title: "Effects of Prompt to Bundle Covid-19 Booster and Flu Shot"). The three trials will be run simultaneously.
Patients randomly selected for this trial will be randomized at an equal share to 6 conditions: an Holdout condition that does not receive a text reminder and 5 additional conditions that receive a text message (Facilitate Action Narrowly, Facilitate Action Broadly, Boost Intention, Boost Intentions+Facilitate Action Narrowly, Boost Intentions+Facilitate Action Broadly; see description in the Arm/Interventions section). Within each arm, patients are further randomized into one of the 33 time slots for when they will receive the text message (i.e., 3 time points per day including 9am, 12pm, 4pm for 11 days). Days 1-4 and 8-11 have slightly fewer patients than Days 5-7.
To test whether reminders that facilitate action by providing appointment scheduling links increase vaccine uptake, the investigators will compare the holdout condition to the combination of the 4 arms that contain appointment scheduling links.
With this trial, the investigators will investigate several additional research questions.
Analysis:
The investigators will run ordinary least squares regressions (OLS) with robust standard errors to predict the aforementioned outcome variables, except that the investigators will use a Cox proportional hazards model with administrative censoring to predict time of obtaining the booster. The significance level will be 0.05. The regressions will include the following control variables:
The investigators will investigate the following moderators for (1) the effect of sending text reminders to facilitate action, (2) the additive effect of adding appointment scheduling links (vs. only boosting intentions), and (3) the additive effect of boosting intentions (vs. only facilitating action with appointment scheduling links):
Additional information: Three days into this trial, the investigators learned that the supply of boosters at UCLA Health is very limited and patients could not find appointments at UCLA Health. The investigators verified that local pharmacies continue to have appointments available. Thus, the investigators updated all text messages to (1) explain that UCLA Health has limited booster appointments available, (2) no longer provide a direct link to schedule appointments at UCLA Health, and (3) instead encourage patients to make an appointment at either CVS Pharmacy or local pharmacies (depending on the arm). As a result, instead of analyzing the originally preregistered outcome measures of "booster take-up at UCLA/CVS in 2 weeks" and "booster take-up at UCLA/CVS in 4 weeks", the investigators will measure vaccine uptake at CVS in 2 weeks and 4 weeks. In terms of the outcome measure of "Link click rate in 1 week", the investigators will still look at whether patients click on any link in the text message.
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Inclusion Criteria:
Exclusion Criteria (for analysis purposes only):
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154,977 participants in 6 patient groups
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Central trial contact
Jeffrey Fujimoto, MD, MBA
Data sourced from clinicaltrials.gov
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