| Literature DB >> 35428643 |
Corina Elena Niculaescu1, Isabel Sassoon2, Irma Cecilia Landa-Avila3, Ozlem Colak3, Gyuchan Thomas Jun3, Panagiotis Balatsoukas3.
Abstract
OBJECTIVES: The present study explored public's willingness to use COVID-19 immunity certificates across six different domestic scenarios.Entities:
Keywords: COVID-19; health informatics; public health
Mesh:
Year: 2022 PMID: 35428643 PMCID: PMC9013794 DOI: 10.1136/bmjopen-2021-058317
Source DB: PubMed Journal: BMJ Open ISSN: 2044-6055 Impact factor: 2.692
Figure 1Description of the six scenarios (the number represents one of the three settings while the letter the design option, convenience or privacy). GP, general practitioner; NHS, National Health Service.
Summary statistics and reliability of HBM measures, and willingness to share immunity status
| Survey items | Mean | Median | SD | Minimum | Maximum | Alpha | |
| COVID-19 perceived susceptibility (HBM) | I am at risk of getting COVID-19 (SARS-CoV-2) | 3.5243 | 4 | 1.1255 | 1 | 5 | 0.7095 |
| It is likely that I will get COVID-19 (SARS-COV-2) | 2.9401 | 3 | 1.0122 | 1 | 5 | ||
| Individuals in my household are at risk for getting COVID-19 (SARS-COV-2) | 3.4438 | 4 | 1.1310 | 1 | 5 | ||
| I feel knowledgeable about my risk of getting COVID-19 (SARS-COV-2) | 4.1255 | 4 | 0.7460 | 1 | 5 | ||
| Certificate severity (HBM) | I feel that without this service I will not be able to return to my workplace | 2.4476 | 2 | 1.1558 | 1 | 5 | 0.8485 |
| I feel that without this service my chances of getting a job will be affected | 2.5918 | 3 | 1.1631 | 1 | 5 | ||
| I feel that without this service I will not be able to book face-to-face appointments with my GP/dentist | 2.8371 | 3 | 1.2455 | 1 | 5 | ||
| I feel that without this service I will not be able to go to the theatre/movies/sports events | 3.2715 | 4 | 1.1636 | 1 | 5 | ||
| I feel that without this service I will not be able to travel internationally | 3.912 | 4 | 1.1252 | 1 | 5 | ||
| I feel that without this service I will not enjoy the same liberties I did before the pandemic | 3.6667 | 4 | 1.1692 | 1 | 5 | ||
| Willingness to share immunity status with service providers | Theatre/Cinema/Gallery | 3.2921 | 4 | 1.3998 | 1 | 5 | – |
| Pub/Restaurant | 3.2228 | 4 | 1.4159 | 1 | 5 | ||
| GP/Dentist | 4.47 | 5 | 0.9219 | 1 | 5 | ||
| Hospitality sector | 3.4663 | 4 | 1.3717 | 1 | 5 | ||
| Sports event | 3.3015 | 4 | 1.4012 | 1 | 5 | ||
| Airport/Airline | 3.8764 | 4 | 1.2538 | 1 | 5 |
GP, general practitioner; HBM, Health Belief Model.
Figure 2Distribution of number of responses (N) across settings (visiting the general practitioner (GP), dining in a restaurant, attending a performance in the theatre) and design options (convenience/privacy).
Acceptance of different service designs and settings
| Response | No | Yes |
| Scenario 1A: visiting the GP/convenience option | 44 | 490 (92%) |
| Scenario 1B: visiting the GP/privacy option | 129 | 405 (76%) |
| Scenario 2A: dining in a restaurant/convenience option | 329 | 205 (38%) |
| Scenario 2B: dining in a restaurant/privacy option | 85 | 449 (84%) |
| Scenario 3A: attending a performance in the theatre/convenience option | 324 | 210 (39%) |
| Scenario 3B: attending a performance in the theatre/privacy option | 89 | 445 (83%) |
Summary of the coefficients of the generalised linear mixed model fit
| Fixed effects | Estimate | SE | Z value | Pr (>|z|) |
| (Intercept) | 4.1636 | 0.2646 | 15.7300 | <2e-16*** |
| Dining in a restaurant setting | −5.0121 | 0.2837 | −17.6700 | <2e-16*** |
| Attending a performance in the theatre setting | −4.9398 | 0.2822 | −17.5000 | <2e-16*** |
| Privacy option | −2.0736 | 0.2504 | −8.2800 | <2e-16*** |
| Dining in a restaurant setting | 5.8747 | 0.3595 | 16.3400 | <2e-16*** |
| Attending a performance in the theatre Setting* privacy option | 5.7127 | 0.3557 | 16.0600 | <2e-16*** |
The coefficients in log-odds form of the GLMM model and their significance. The estimates of the fixed effects are conditional on the random effects. The estimated effects have a binary outcome with a logit link; hence, the raw estimates are on the log-odds scale. The intercept refers to the log-odds for willingness to use immunity certificates in scenario 1A (visiting the GP/convenience option). A positive value for log-odds estimates respondents being likely to be willing to use the certificate in that setting and option. The coefficients on the log-odds scale are additive.
Significance codes 0 ‘***’; 0.001 ‘**’; 0.01 ’*’; 0.05 ‘.’; 0.1 ‘ ’.
GLMM, Generalised Linear Mixed Effects Model; GP, general practitioner.
Figure 3(A) Index of certificate severity (perceived severity of not using immunity certificates) and (B) index of COVID-19 susceptibility across settings and design options (convenience/privacy).
Figure 4Willingness to share immunity status with service providers (theatre/cinema/gallery) by across settings and design options (convenience/privacy).