Clinical Trial Details
— Status: Completed
Administrative data
| NCT number |
NCT04801524 |
| Other study ID # |
IRB#21-000268 (2) |
| Secondary ID |
|
| Status |
Completed |
| Phase |
N/A
|
| First received |
|
| Last updated |
|
| Start date |
February 7, 2021 |
| Est. completion date |
January 1, 2022 |
Study information
| Verified date |
September 2022 |
| Source |
University of California, Los Angeles |
| Contact |
n/a |
| Is FDA regulated |
No |
| Health authority |
|
| Study type |
Interventional
|
Clinical Trial Summary
This study investigates whether and which type of text-based reminders affect the take-up of
the COVID-19 vaccine.
Description:
Our primary research question is whether vaccine takeup can be boosted by a text-message
reminder encouraging eligible patients to schedule a vaccination appointment. Patients, when
becoming eligible for receiving the COVID-19 vaccine at UCLA Health, will be first notified
about their eligibility and encouraged to schedule a vaccination appointment via one of the
channels (email, voice call, or snail mail) depending on the contact information available to
UCLA Health. Eligible patients will also receive a text-message reminder after the initial
invitation. Eight days after the first text reminder, patients eligible for our study will be
randomized at a 1:6 ratio into a holdout control arm that does not receive a second text
message vs. a text-message arm that receives a second text message.
Our secondary research question concerns which type of text reminder is more effective. To
study this question, we will nest a 2x3 factorial design within the text-message arm. The
first factor has two levels and is whether the text message focuses on patients' personal
benefits or prosocial benefits. The second factor has three levels and is whether the text
message highlights the early access patients have to the vaccine, whether it highlights that
the vaccine offers the promise of a fresh start, or neither.
- In the Holdout arm: patients will not receive a second text message about COVID-vaccine.
- In the text-message arm, all participants will receive a text message that invites them
to schedule their vaccination appointment and includes a link to the appointment website
- In the Self-benefit sub-arm, participants will be reminded that the vaccine helps
protect themselves from COVID.
- In the Prosocial-benefit sub-arm, participants will be reminded that the vaccine
helps protect their family, friends, and community from COVID.
- In the Early access + self-benefit sub-arm, participants will be reminded that they
have early access to COVID-19 vaccine and should take the opportunity to protect
themselves from COVID.
- In the Early access + prosocial-benefit sub-arm, participants will be reminded that
they have early access to COVID-19 vaccine and should take the opportunity to
protect their family, friends, community from COVID.
- In the Fresh start + self-benefit sub-arm, participants will be reminded that the
vaccine offers the promise of a fresh start and they should take the opportunity to
protect themselves from COVID and chart a new path forward.
- In the Early access + prosocial-benefit sub-arm, participants will be reminded that
the vaccine offers the promise of a fresh start and they should take the
opportunity to protect their family, friends, community from COVID and help our
nation chart a new path forward.
Patients will enter our study on a rolling basis, as they become eligible to get the vaccine
(and if they fit our inclusion criteria for receiving the second text message). Those in the
text-message arm will receive the second text message on the workday on or closest to the 8th
day following the first text message. Specifically, if t denotes the date of the first text
message, then t+8 is the 8th day following the first text message.If t+8 is Saturday, the
second text message will be sent on Friday; if t+8 is Sunday, the second text message will be
sent on Monday. We will measure a) whether patients schedule a COVID-19 vaccination
appointment for the first dose and b) whether and when patients get the first dose of
COVID-19 vaccine.
The study will stop assigning patients to the early access + self-benefit sub-arm OR the
early access + prosocial-benefit sub-arm when UCLA health opens appointments to everyone
regardless of priority status related to age, health conditions or occupations. This will be
done because at this point the concept of early access is likely no longer credible. At that
point, we will randomize future patients eligible for our study at a 1:4 ratio into the
holdout control arm and a text-message arm that receives a second text message. Within the
text-message arm, we will nest a 2x2 factorial design, where the two factors will be a)
whether the text message will focus on patients' personal benefits or prosocial benefits and
b) whether or not the text message highlights that the vaccine offers the promise of a fresh
start.
Analysis:
For the main analysis, we will run ordinary least squares regressions (OLS) with robust
standard errors to predict the aforementioned outcome variables, except that we will use a
Cox proportional hazards model with administrative censoring to predict time of obtaining the
first COVID-19 vaccine. The significance level will be 0.05. Our primary hypothesis is that
the text-message arm is significantly better than the holdout arm, so our primary analysis
will compare the six text-message sub-arms altogether with the holdout group.
Our secondary analysis will investigate whether (1) the three sub-arms highlighting
self-benefits, (2) the three sub-arms highlighting prosocial benefits, (3) the two sub-arms
highlighting early access, and (4) the two sub-arms highlighting fresh start are better than
the holdout arm.
Furthermore, we will test (1) the effect of highlighting prosocial benefits (vs.
self-benefits), (2) the effect of highlighting early access, (3) the effect of highlighting
the promise of a fresh start, (4) whether the combination of early access and prosocial
benefits will outperform early access alone or prosocial benefits alone, and (5) whether the
combination of fresh start and prosocial benefits will outperform fresh start alone or
prosocial benefits alone.
Our regressions will include the following control variables:
- Participant age
- Indicators for participant race/ethnicity (Black non-Hispanic, Hispanic, Asian
non-Hispanic, white non-Hispanic, other/mixed, unknown; white non-Hispanic omitted)
- Whether the patient's preferred language is Spanish (which affects the language of text)
- Indicators for participant gender (male, female, other/unknown)
- Social vulnerability index score
- COVID19 Risk Factors Model
- Indicators for the batches of patients (patients will become eligible and receive
initial communications in batches)
As a robustness check, we will re-run the analysis as a logit regression (instead of an OLS
regression) for binary outcome variables.
We will explore the following moderators:
- Whether the patient is female or male
- Whether the patient is Black, Caucasian, Hispanic, or other
- Whether the patient's preferred language is Spanish
- Whether the patient is 65+ (including 65) or below 65
- Patient's Social vulnerability index score
- Patient's COVID risk score
- Patient's population risk score
- Whether the patient is married (which is a proxy for whether they live together with
family members)
- Whether or not the patient received a flu shot in either the 2019-2020 season or the
2020-2021 flu season prior to receiving our text message according to the patient's
medical record
- The day of the week when the text message is sent to a patient. We will compare each day
of the week.
- How strongly the participant's neighborhood is in favor of the Republican (vs.
Democratic) Party if UCLA Health eventually agrees to provide de-identified address
(e.g., zipcode)
- The arm that patients were assigned to for the first text message (see our
pre-registration for the RCT related to the first text message at NCT04800965)
- Number of days between the date the first batch of patients received the initial
invitation to get COVID vaccine at UCLA Health and the date a patient in question
received the initial invitation
- The number of patients who have received the initial invitation to get COVID vaccine at
UCLA Health before a patient in question received the initial invitation.
Plan for Early and Subsequent Analyses
To inform policy as soon as possible, we plan to first assess the effects of our
interventions in the early phase of vaccination outreach at UCLA Health. For this purpose, we
plan to first analyze the data from the start of this RCT to the end of February. Given that
we are using a 6-day time window for our primary dependent variable, we will examine data
from patients who are randomized to either the holdout or text-message arm in this RCT before
or on Feb 23, 2021. For this population, we will test:
1. whether the text-message arm is significantly better than the holdout arm;
2. whether the three sub-arms highlighting self-benefits, the three sub-arms highlighting
prosocial benefits, the two sub-arms highlighting early access, and the two sub-arms
highlighting fresh start are better than the holdout arm.
3. we will report the raw data for each sub-arm without conducting hypothesis testing
across conditions that are not pre-registered in (1)-(4).
In our early analysis, we will include controls that are available to us (it is possible that
we do not have all of the controls described above at the time of early report).
However, if by Feb 23, we do not reach 40K (which gives us 80% power to detect a 2pp
difference between the holdout arm and the text message arm, assuming that holdout arm has a
50% baseline) for this RCT, we will only report estimated treatment effects and 95%
confidence intervals but we will not perform any hypothesis testing.
After all UCLA patients have been invited (or if vaccine distribution plan changes and UCLA
Health no longer sends out text messages to patients at some point), we will do the following
additional analyses:
- If the additional data collected afterward exceeds 40K (which gives us 80% power to
detect a 2pp difference between the holdout arm and the text message arm), then we will
analyze the main effect of sending a text message (vs. holdout) and report the raw data
for each sub-arm (to see if the patterns are qualitatively comparable with those in the
early data).
- If we do not reach the sample size for the early analysis, then we will use all the data
(including the early data and subsequent data) to analyze the aforementioned questions
for the early data.
- We will use the full sample (including the early data and subsequent data) to analyze
(1) the effect of highlighting prosocial benefits (vs. self-benefits), (2) the effect of
highlighting early access, (3) the effect of highlighting the promise of a fresh start,
(4) whether the combination of early access and prosocial benefits will outperform early
access alone or prosocial benefits alone, and (5) whether the combination of fresh start
and prosocial benefits will outperform fresh start alone or prosocial benefits alone,
and (6) the aforementioned heterogeneous treatment effects.
