Table 2.
Associations of sociodemographic, study-related, psychological, health-related, and communication-related factors with the likelihood of a vaccination against COVID-19 among university students in the summer of 2021.
| OR (95% CI) | Wald | p | |
|---|---|---|---|
| Sociodemographic and study-related factors | |||
| Age | 1.036 (0.994–1.080) | 2.82 | .093 |
| Field of study (with medicine coded high) | 2.125 (1.230–3.672) | 7.30** | .007 |
| Health-related factors | |||
| Health literacy | 0.989 (0.918–1.066) | 0.08 | .779 |
| Global interest in common vaccinations | 1.017 (0.824–1.256) | 0.03 | .873 |
| Psychological factors | |||
| Confidence | 1.424 (1.239–1.638) | 24.65*** | < .001 |
| Complacency | 0.966 (0.784–1.190) | 0.11 | .744 |
| Constraints | 0.618 (0.521–0.733) | 30.65*** | < .001 |
| Calculation | 0.878 (0.805–0.957) | 8.77** | .003 |
| Collective Responsibility | 0.869 (0.747–1.011) | 3.29 | .070 |
| Communication-related factors | |||
| Media Trust | |||
| General media trust | 0.912 (0.719–1.157) | 0.58 | .448 |
| Topic-specific media trust | 0.845 (0.661–1.079) | 1.83 | .176 |
| Public broadcasting (including online outlets) | 0.962 (0.750–1.235) | 0.09 | .761 |
| Private broadcasting (including online outlets) | 0.999 (0.830–1.203) | 0.00 | .995 |
| National quality press (including online outlets) | 0.900 (0.717–1.129) | 0.83 | .363 |
| Social media | 1.355 (1.081–1.698) | 6.96** | .008 |
| Alternative news media and blogs | 0.819 (0.682–0.983) | 4.59* | .032 |
| Topic-specific trust in news sources | |||
| Federal government | 1.133 (0.907–1.415) | 1.20 | .273 |
| City government | 1.026 (0.820–1.285) | 0.05 | .820 |
| Political parties | 0.934 (0.724–1.206) | 0.27 | .601 |
| Individual politicians | 0.910 (0.721–1.150) | 0.62 | .432 |
| WHO | 0.959 (0.756–1.217) | 0.12 | .729 |
| RKI | 0.858 (0.648–1.137) | 1.13 | .287 |
| National commission on vaccination | 1.114 (0.887–1.398) | 0.86 | .353 |
| National board of ethics | 1.162 (0.962–1.403) | 2.42 | .120 |
| Hospitals | 0.875 (0.708–1.081) | 1.53 | .217 |
| Public health offices | 0.907 (0.736–1.117) | 0.85 | .358 |
| Business and industry associations | 1.122 (0.923–1.363) | 1.34 | .248 |
| Churches | 1.215 (1.027–1.438) | 5.14* | .023 |
| Intensity of general media use | |||
| TV (offline) | 1.028 (0.961–1.100) | 0.66 | .418 |
| Radio (offline) | 1.065 (0.986–1.150) | 2.55 | .110 |
| Print media (offline) | 1.002 (0.917–1.095) | 0.00 | .961 |
| Online media | 0.978 (0.804–1.190) | 0.05 | .827 |
| Topic-related information seeking | |||
| Intensity of information seeking | 1.023 (0.963–1.088) | 0.55 | .461 |
| TV (offline) (with use coded high) | 1.138 (0.801–1.617) | 0.52 | .472 |
| Radio (offline) (with use coded high) | 1.409 (0.963–2.061) | 3.12 | .077 |
| Print media (offline) (with use coded high) | 1.268 (0.888–1.810) | 1.71 | .191 |
| Conversations and chats with health professionals (with use coded high) | 1.656 (1.138–2.411) | 6.95** | .008 |
| Conversations and chats with (other) patients (with use coded high) | 1.103 (0.554–2.197) | 0.08 | .780 |
| Online news sites (with use coded high) | 0.866 (0.581–1.291) | 0.50 | .480 |
| Online TV and video streaming (e.g. Netflix) (with use coded high) | 1.257 (0.673–2.347) | 0.51 | .473 |
| Online audio streaming and podcasts (with use coded high) | 1.000 (0.683–1.464) | 0.00 | .998 |
| Video platforms (e.g., YouTube) (with use coded high) | 0.622 (0.449–0.862) | 8.15**) | .004 |
| Social media (with use coded high) | 1.334 (0.953–1.868) | 2.82) | .093 |
| COVID-19 warning app (with use coded high) | 1.360 (0.986–1.874) | 3.52) | .061 |
Binary logistic regression analysis. χ2(44) = 276.33, p < .001, n = 1,114; Nagelkerke R2 = .311; Cohen’s f2 = . 45.
*p < .05; **p < .01; ***p < .001.