| Literature DB >> 35358977 |
Maria Ada Presotto1, Rudolf A Jörres2, Wolfgang Gesierich3, Jörn Bullwinkel4, Klaus F Rabe4, Konrad Schultz5, Franziska Kaestner6, Dominik Harzheim6, Michael Kreuter1, Felix J F Herth1, Franziska Christina Trudzinski1.
Abstract
BACKGROUND: Gender differences in vaccine acceptance among health care workers (HCWs) are well documented, but the extent to which these depend on occupational group membership is less well studied. We aimed to determine vaccine acceptance and reasons of hesitancy among HCWs of respiratory clinics in Germany with respect to gender and occupational group membership.Entities:
Keywords: COVID-19 pandemic; Health care workers; Perceived infection risk; Specialized lung clinics; Vaccination
Mesh:
Substances:
Year: 2022 PMID: 35358977 PMCID: PMC9059044 DOI: 10.1159/000522518
Source DB: PubMed Journal: Respiration ISSN: 0025-7931 Impact factor: 3.966
Demographic characteristics of responders to the survey
| Demographic characteristics | |
|---|---|
| Gender (information provided) | 785 |
| Male | 220 (28) |
| Female | 565 (72) |
| Age group (information provided) | 772 |
| 18–25 years | 60 (7.8) |
| 26–35 years | 169 (21.9) |
| 36–45 years | 193 (25.0) |
| 46–55 years | 196 (25.4) |
| 56–65 years | 147 (19.0) |
| >65 years | 7 (0.9) |
| Profession (information provided) | 762 |
| Nursing service | 234 (30.7) |
| Medical service | 148 (19.4) |
| Pharmacy/clinical lab | 17 (2.2) |
| Cleaning service, laundry, patient transport, kitchen, casino | 8 (1.0) |
| Technical department | 22 (2.9) |
| Administration | 119 (15.6) |
| Others | 214 (28.1) |
| Lung clinic (information provided) | 762 |
| Thoraxklinik Heidelberg | 303 (39.7) |
| Asklepios Gauting | 114 (14.9) |
| Klinik Bad Reichenhall | 41 (5.3) |
| LungenClinic Grosshansdorf | 113 (14.8) |
| Fachkliniken Wangen | 191 (25.0) |
| Working department (information provided) | 643 |
| Anaesthesia | 36 (5.5) |
| Thoracic surgery | 48 (7.4) |
| Pneumology | 215 (33.4) |
| Thoracic oncology | 57 (8.8) |
| Clinical research | 29 (4.5) |
| Others (physiotherapists, social services) | 258 (40.1) |
Fig. 1Fears about COVID-19 disease and COVID-19 vaccine. a–d Histograms for fears about COVID-19 disease. I am very afraid of contracting COVID-19 (p < 0.001) (a), I am very afraid about a severe course of the disease (p = 0.004) (b), I am afraid that I might die from COVID-19 (p < 0.001) (c), I am afraid of COVID 19 late effects (p < 0.001) (d). *p value ≤0.05. e–h Histograms for fears about COVID-19 vaccine. I consider the vaccinations against other viruses such as influenza to be sufficiently tested (p < 0.001) (e), I consider the currently available vaccines against COVID-19 to be sufficiently tested (p < 0.001) (f), I have concerns about possible allergic reactions to the vaccination (p < 0.001) (g), I have concerns about possible late effects of vaccination (p < 0.001) (h). *p value ≤0.05.
Demographic characteristics and answers to 4 questions of the survey stratified for vaccine acceptance or hesitancy
| All | Ready to be vaccinated, % | Not ready to be vaccinated, % | ||
|---|---|---|---|---|
| Gender (female/male) | 486/187 | 72.2/77.5 | 27.8/22.5 | 0.095 |
| Age groups | ||||
| 18–25 years | 56 | 53.6 | 46.4 |
|
| 26–35 years | 151 | 72.8 | 27.2 | |
| 36–45 years | 164 | 77.4 | 22.6 | |
| 46–55 years | 163 | 73.0 | 27.0 | |
| 56–65 years | 126 | 78.6 | 21.4 | |
| >65 years | 6 | 66.7 | 33.3 | |
| Unknown | 28 | 57.1 | 42.9 | |
| Professional groups | ||||
| Group 1* | 152 | 65.8 | 34.2 |
|
| Nurses | 206 | 72.8 | 27.2 | |
| Physicians | 116 | 84.5 | 15.5 | |
| Others | 185 | 76.2 | 23.8 | |
| Questions | ||||
| Do you have or have you had COVID-19 yourself? (yes/no) | 59/635 | 69.5/73.1 | 30.5/26.9 | 0.325 |
| Are you involved in direct patient care? (yes/no) | 340/159 | 76.7/66.8 | 23.3/33.2 |
|
| Have you had contact with patients with COVID-19 in the last 3 months? | ||||
| (yes/no) | 325/210 | 75.4/69.5 | 24.6/30.5 | 0.072 |
| Do you work in a “high-risk area”? (yes/no)** | 291/208 | 77.9/70.3 | 22.1/29.7 |
|
Statistical comparisons between the two groups were based on contingency tables and χ2 statistics. Statistically significant differences (p < 0.05) are marked in bold type. * Group 1: administration, cleaning service, laundry, patient transport, kitchen, casino, technical department, pharmacy, clinical lab. ** Risk area: operating theatre, endoscopy, COVID ward, intensive care unit, tests ambulance, emergency room.
Determinants of vaccination acceptance in multiple binary logistic regression analysis for men and women (n = 654)
| Predictor | B | SE | OR | 95% CI for OR | ||
|---|---|---|---|---|---|---|
| lower | upper | |||||
| Gender male/female | 0.05 | 0.25 | 1.05 | 0.65 | 1.71 | 0.842 |
| Age <35 years | –0.50 | 0.22 | 0.61 | 0.40 | 0.93 |
|
| Fear of COVID-19 late effects | 1.05 | 0.21 | 2.86 | 1.88 | 4.34 |
|
| Fear of late effects of vaccination | –2.07 | 0.21 | 0.13 | 0.08 | 0.19 |
|
| Professional groups (overall) | 0.136 | |||||
| Relative to group 1* | – | – | – | – | – | – |
| Nurses | 0.14 | 0.27 | 1.15 | 0.67 | 1.97 | 0.615 |
| Physicians | 0.79 | 0.35 | 2.20 | 1.10 | 4.38 |
|
| Others | 0.32 | 0.28 | 1.38 | 0.79 | 2.41 | 0.258 |
Predictors were gender, age <35 years, fear of COVID-19 late effects, fear of late effects of vaccination, and professional groups. B, unstandardized estimate; SE, standard error; OR, odds ratio (= exp [B]); 95% CI, 95% confidence interval of OR. * Group 1: administration, cleaning service, laundry, patient transport, kitchen, casino, technical department, pharmacy, clinical lab. Statistically significant differences (p < 0.05) are marked in bold type.
Fig. 2a, b Vaccination acceptance and hesitancy. ORs according to multiple logistic regression analyses in males (a, see online suppl. Table S1) and females (b, see online suppl. Table S2) illustrating the effect of several individual characteristics on vaccination acceptance. Fear of COVID-19 late effects was a positive predictor of vaccine acceptance, fear of late effects of vaccination a negative predictor. Moreover, younger age (<35 years) was a negative predictor, and being a physician a positive predictor but not all of these were statistically significant (p < 0.05), and there were differences between males and females. Professional groups were analysed relative to group 1 (**administration, cleaning service, laundry, patient transport, kitchen, casino, technical department, pharmacy, clinical lab).