SARS-CoV-2
Conditions
Keywords
antibodies
Brief summary
Repeat testing for SARS-CoV-2 antibodies in disadvantaged communities will help identify active and recovered infections over time, and as more is understood about antibody protection, it may help identify persons who have immunity. Many questions about social barriers and behavioral facilitators remain unanswered. This project aims to evaluate the effectiveness of risk-based messaging and incentives that promote repeated testing for SARS-CoV-2 antibodies, as well as to understand social and behavioral determinants of COVID-19 testing and variations within sub-groups of this population.
Detailed description
The rapid spread of the SARS-CoV-2 virus has greatly impacted underserved populations. This project aims to understand social and behavioral determinants of COVID-19 testing and variations within sub-groups of this population. In partnership with the largest federally qualified health center in the United States, investigators will collect survey data and conduct a randomized experiment on 2,160 individuals (540 families) to evaluate the effectiveness of risk-based messaging and incentives that promote repeated testing for SARS-CoV-2 antibodies. In a 2 x 2 (Messaging x Incentive) factorial experiment, participants complete a comprehensive set of social and behavioral surveys to identify determinants of commitment to testing. Participants are then randomized to receive customized messaging promoting repeated testing. Messaging will focus upon either (1a) household risk or (1b) personal risk of COVID-19. Participants are also randomly assigned to an incentive condition that either (2a) insures against losing baseline rewards for initial testing, or (2b) entry into a lottery with a small chance to win $150 if both tests are completed. Both the loss protection and lottery conditions carry the same incentive costs. Previous work in similar populations demonstrates that adherence to planned health behaviors is higher with insurance-based incentives than cash payments of equal value. This experiment compares insurance-based incentives to lottery incentives that have been shown to be effective in multiple contexts. Finally, the investigators evaluate if social and behavioral determinants of health result in heterogeneous treatment effects that can inform customization of incentive offerings in future programs devoted to increasing uptake of testing or vaccinations among underserved populations.
Interventions
BEHAVIORALFamily Risk Messaging
Family risk framing may engender concern for loved ones. It may also make it easier to mentally simulate family burdens with COVID-19 such as knowing how several people in the family becoming sick could adversely affect the lives of everyone in the family. Households randomized to family risk messaging will receive the following message: Antibody testing will help you understand your family's risk of getting COVID-19.
BEHAVIORALPersonal Risk Messaging
Personal risk framing may engender concern for oneself. Households randomized to personal risk messaging will receive the following message: Antibody testing will help you understand your risk of getting COVID-19.
BEHAVIORALLoss Protection
Household members are offered a baseline incentive with a 90% (9 in 10) chance of $60 and receive insurance on winning the baseline incentive for repeat antibody testing.
BEHAVIORALLottery Incentive
Household members are offered a baseline incentive with a 90% (9 in 10) chance of $60 and receive a bonus lottery incentive with a 4 small (1 in 25) chance of winning $150 for repeat antibody testing.
Sponsors
AltaMed Health Services Corporation
National Institute on Aging (NIA)
University of Southern California
Study design
Allocation
RANDOMIZED
Intervention model
FACTORIAL
Primary purpose
HEALTH_SERVICES_RESEARCH
Masking
NONE
Eligibility
Sex/Gender
ALL
Age
5 Years to No maximum
Healthy volunteers
No
Inclusion criteria
* Adults and children 5 years of age and older
Exclusion criteria
* Children under 5 years of age
Design outcomes
Primary
| Measure | Time frame | Description |
|---|---|---|
| Attendance Rate at Time 2 SARS-CoV-2 Antibody Test | 6 months | Effectiveness of risk-based messaging and incentives to encourage attendance at Time 2 testing for SARS-CoV-2 antibodies |
Secondary
| Measure | Time frame | Description |
|---|---|---|
| Social and Behavioral Determinants of Antibody Testing | 6 months | Characterize barriers to access, bias, risk attitude and incentive preferences assessed through survey responses |
Countries
United States
Participant flow
Recruitment details
Between June 2021 and December 2022, potential participants were contacted by phone by a bilingual coordinator and invited to participate in a study about COVID-19.
Pre-assignment details
We drew a simple random sample of patient households without replacement from AltaMed registry. Each household sampled was contacted to identify eligibility and interest. Households met inclusion criteria if at least one member was a patient at AltaMed and the household contained at least one adult and at least one member 5 to 17 years of age.
Participants by arm
| Arm | Count |
|---|---|
| Personal Risk + Loss Protection Personal Risk + Loss Protection
Personal Risk Messaging: Personal risk framing may engender concern for oneself. Households randomized to personal risk messaging will receive the following message: Antibody testing will help you understand your risk of getting COVID-19.
Loss Protection: Household members are offered a baseline incentive with a 90% (9 in 10) chance of $60 and receive insurance on winning the baseline incentive for repeat antibody testing. | 626 |
| Personal Risk + Lottery Incentive Personal Risk + Lottery Incentive
Personal Risk Messaging: Personal risk framing may engender concern for oneself. Households randomized to personal risk messaging will receive the following message: Antibody testing will help you understand your risk of getting COVID-19.
Lottery Incentive: Household members are offered a baseline incentive with a 90% (9 in 10) chance of $60 and receive a bonus lottery incentive with a 4 small (1 in 25) chance of winning $150 for repeat antibody testing. | 550 |
| Family Risk + Loss Protection Family Risk + Loss Protection
Family Risk Messaging: Family risk framing may engender concern for loved ones. It may also make it easier to mentally simulate family burdens with COVID-19 such as knowing how several people in the family becoming sick could adversely affect the lives of everyone in the family. Households randomized to family risk messaging will receive the following message: Antibody testing will help you understand your family's risk of getting COVID-19.
Loss Protection: Household members are offered a baseline incentive with a 90% (9 in 10) chance of $60 and receive insurance on winning the baseline incentive for repeat antibody testing. | 539 |
| Family Risk + Lottery Incentive Family Risk + Lottery Incentive
Family Risk Messaging: Family risk framing may engender concern for loved ones. It may also make it easier to mentally simulate family burdens with COVID-19 such as knowing how several people in the family becoming sick could adversely affect the lives of everyone in the family. Households randomized to family risk messaging will receive the following message: Antibody testing will help you understand your family's risk of getting COVID-19.
Lottery Incentive: Household members are offered a baseline incentive with a 90% (9 in 10) chance of $60 and receive a bonus lottery incentive with a 4 small (1 in 25) chance of winning $150 for repeat antibody testing. | 449 |
| Total | 2,164 |
Baseline characteristics
| Characteristic | Personal Risk + Loss Protection | Personal Risk + Lottery Incentive | Family Risk + Loss Protection | Family Risk + Lottery Incentive | Total |
|---|---|---|---|---|---|
| Age, Continuous | 25.71 years STANDARD_DEVIATION 16.92 | 24.44 years STANDARD_DEVIATION 15.64 | 25.58 years STANDARD_DEVIATION 16.78 | 26.42 years STANDARD_DEVIATION 16.61 | 25.5 years STANDARD_DEVIATION 16.51 |
| Ethnicity (NIH/OMB) Hispanic or Latino | 578 Participants | 501 Participants | 481 Participants | 408 Participants | 1968 Participants |
| Ethnicity (NIH/OMB) Not Hispanic or Latino | 38 Participants | 46 Participants | 58 Participants | 38 Participants | 180 Participants |
| Ethnicity (NIH/OMB) Unknown or Not Reported | 10 Participants | 3 Participants | 0 Participants | 3 Participants | 16 Participants |
| Race (NIH/OMB) American Indian or Alaska Native | 4 Participants | 0 Participants | 1 Participants | 1 Participants | 6 Participants |
| Race (NIH/OMB) Asian | 16 Participants | 14 Participants | 8 Participants | 7 Participants | 45 Participants |
| Race (NIH/OMB) Black or African American | 5 Participants | 12 Participants | 25 Participants | 18 Participants | 60 Participants |
| Race (NIH/OMB) More than one race | 32 Participants | 16 Participants | 28 Participants | 29 Participants | 105 Participants |
| Race (NIH/OMB) Native Hawaiian or Other Pacific Islander | 0 Participants | 0 Participants | 0 Participants | 1 Participants | 1 Participants |
| Race (NIH/OMB) Unknown or Not Reported | 528 Participants | 470 Participants | 438 Participants | 369 Participants | 1805 Participants |
| Race (NIH/OMB) White | 41 Participants | 38 Participants | 39 Participants | 24 Participants | 142 Participants |
| Region of Enrollment United States | 626 participants | 550 participants | 539 participants | 449 participants | 2164 participants |
| Sex/Gender, Customized Female | 373 Participants | 319 Participants | 307 Participants | 266 Participants | 1265 Participants |
| Sex/Gender, Customized Male | 249 Participants | 231 Participants | 231 Participants | 179 Participants | 890 Participants |
| Sex/Gender, Customized Non binary | 0 Participants | 0 Participants | 1 Participants | 0 Participants | 1 Participants |
| Sex/Gender, Customized Unknown or Not reported | 4 Participants | 0 Participants | 0 Participants | 4 Participants | 8 Participants |
Adverse events
| Event type | EG000 affected / at risk | EG001 affected / at risk | EG002 affected / at risk | EG003 affected / at risk |
|---|---|---|---|---|
| deaths Total, all-cause mortality | 0 / 626 | 0 / 550 | 0 / 539 | 0 / 449 |
| other Total, other adverse events | 0 / 626 | 0 / 550 | 0 / 539 | 0 / 449 |
| serious Total, serious adverse events | 0 / 626 | 0 / 550 | 0 / 539 | 0 / 449 |
Outcome results
Primary
Attendance Rate at Time 2 SARS-CoV-2 Antibody Test
Effectiveness of risk-based messaging and incentives to encourage attendance at Time 2 testing for SARS-CoV-2 antibodies
Time frame: 6 months
Population: Participants who attended Time 1 antibody testing.
| Arm | Measure | Value (COUNT_OF_PARTICIPANTS) |
|---|---|---|
| Personal Risk + Loss Protection | Attendance Rate at Time 2 SARS-CoV-2 Antibody Test | 123 Participants |
| Personal Risk + Lottery Incentive | Attendance Rate at Time 2 SARS-CoV-2 Antibody Test | 84 Participants |
| Family Risk + Loss Protection | Attendance Rate at Time 2 SARS-CoV-2 Antibody Test | 129 Participants |
| Family Risk + Lottery Incentive | Attendance Rate at Time 2 SARS-CoV-2 Antibody Test | 78 Participants |
p-value: 0.00395% CI: [0.42, 1.97]Mixed Models Analysis
p-value: <0.00195% CI: [0.68, 2.24]Mixed Models Analysis
p-value: 0.0195% CI: [0.26, 1.96]Mixed Models Analysis
Secondary
Social and Behavioral Determinants of Antibody Testing
Characterize barriers to access, bias, risk attitude and incentive preferences assessed through survey responses
Time frame: 6 months
Population: This analysis was conducted on heads of households who completed the baseline survey.
| Arm | Measure | Group | Value (COUNT_OF_PARTICIPANTS) |
|---|---|---|---|
| Personal Risk + Loss Protection | Social and Behavioral Determinants of Antibody Testing | Reported the biggest barrier to getting the vaccine is money | 12 Participants |
| Personal Risk + Loss Protection | Social and Behavioral Determinants of Antibody Testing | Scored <=5 on risk aversion scale of 0-10, with 0 being more risk averse and 10 more risk prone | 88 Participants |
| Personal Risk + Loss Protection | Social and Behavioral Determinants of Antibody Testing | Reported the most trusted source of COVID-19 information is their medical provider | 49 Participants |
| Personal Risk + Lottery Incentive | Social and Behavioral Determinants of Antibody Testing | Reported the biggest barrier to getting the vaccine is money | 21 Participants |
| Personal Risk + Lottery Incentive | Social and Behavioral Determinants of Antibody Testing | Scored <=5 on risk aversion scale of 0-10, with 0 being more risk averse and 10 more risk prone | 75 Participants |
| Personal Risk + Lottery Incentive | Social and Behavioral Determinants of Antibody Testing | Reported the most trusted source of COVID-19 information is their medical provider | 47 Participants |
| Family Risk + Loss Protection | Social and Behavioral Determinants of Antibody Testing | Reported the most trusted source of COVID-19 information is their medical provider | 41 Participants |
| Family Risk + Loss Protection | Social and Behavioral Determinants of Antibody Testing | Reported the biggest barrier to getting the vaccine is money | 17 Participants |
| Family Risk + Loss Protection | Social and Behavioral Determinants of Antibody Testing | Scored <=5 on risk aversion scale of 0-10, with 0 being more risk averse and 10 more risk prone | 72 Participants |
| Family Risk + Lottery Incentive | Social and Behavioral Determinants of Antibody Testing | Reported the biggest barrier to getting the vaccine is money | 10 Participants |
| Family Risk + Lottery Incentive | Social and Behavioral Determinants of Antibody Testing | Scored <=5 on risk aversion scale of 0-10, with 0 being more risk averse and 10 more risk prone | 54 Participants |
| Family Risk + Lottery Incentive | Social and Behavioral Determinants of Antibody Testing | Reported the most trusted source of COVID-19 information is their medical provider | 40 Participants |
Comparison: Comparison of Time 2 attendance between study arms among respondents who indicated that money was the biggest barrier to getting the vaccine.p-value: 0.40995% CI: [-0.98, 0.4]Regression, Logistic
Comparison: Comparison of Time 2 attendance between study arms among respondents who indicated that money was the biggest barrier to getting the vaccine.p-value: 0.09895% CI: [-0.09, 1.1]Regression, Logistic
Comparison: Comparison of Time 2 attendance between study arms among respondents who indicated that money was the biggest barrier to getting the vaccine.p-value: 0.98295% CI: [-0.71, 0.73]Regression, Logistic
Comparison: Comparison of Time 2 attendance between study arms among respondents who indicated that their medical provider was the most trusted source of COVID-19 information.p-value: 0.17795% CI: [-0.67, 0.12]Regression, Logistic
Comparison: Comparison of Time 2 attendance between study arms among respondents who indicated that their medical provider was the most trusted source of COVID-19 information.p-value: 0.11795% CI: [-0.08, 0.74]Regression, Logistic
Comparison: Comparison of Time 2 attendance between study arms among respondents who indicated that their medical provider was the most trusted source of COVID-19 information.p-value: 0.80995% CI: [-0.39, 0.5]Regression, Logistic
Comparison: Comparison of Time 2 attendance between study arms among respondents who scored below or equal to 5 on the risk aversion scale (scale of 0-10, with 0 being more risk averse and 10 being more risk prone).p-value: 0.84795% CI: [-0.34, 0.41]Regression, Logistic
Comparison: Comparison of Time 2 attendance between study arms among respondents who scored below or equal to 5 on the risk aversion scale (scale of 0-10, with 0 being more risk averse and 10 being more risk prone).p-value: 0.99395% CI: [-0.39, 0.38]Regression, Logistic
Comparison: Comparison of Time 2 attendance between study arms among respondents who scored below or equal to 5 on the risk aversion scale (scale of 0-10, with 0 being more risk averse and 10 being more risk prone).p-value: 0.67195% CI: [-0.51, 0.33]Regression, Logistic