Participants and Migratory Backgrounds
Of the invited patients, 452 agreed to participate. Questionnaires with missing demographic data (n=2) were excluded. Also excluded were a total of 27 participants with more than 50% missing items in the knowledge (n=9), attitude (n=23), or behavior (n=20) domains and 3 participants with missing migratory background information. Data of 420 participants were analyzed (women: 41.4% (n=174), mean age: 42.2±15.5 years) (Figure 1).
Of the participants, 245 (58.3%) preferred the Turkish questionnaire. In addition to these 245 people, 103 participants (58.8%) from the 175 preferring the German questionnaire had a migratory background, making a total of 348 (82.8%). There were 72 (17.1%) German participants without migratory background. Of the 348 patients with migratory history, 90 (25.8%) had a German nationality. From the 71 participants with a migratory background who were born in Germany, only 42 (59.1%) had a German nationality. Regarding migratory background, there were significant differences concerning age, sex, and preferred language. Among the participants with migratory backgrounds, prominent countries of origin were Turkey, Bulgaria, and Irak, while Turkish, Bulgarian, Kurdish, and Arabic were the commonly spoken native languages (Table 1).
Table 1: Sociodemographic characteristics
|
Migratory Background
|
|
|
Yes
|
No
|
|
|
n/Mean
|
%/SD
|
n/Mean
|
%/SD
|
Test
|
p
|
Sex
|
Female
|
130
|
37.4
|
44
|
61.1
|
13.542#
|
0.001
|
Male
|
216
|
62.1
|
28
|
38.9
|
|
|
Other
|
2
|
0.6
|
0
|
0
|
|
|
Age (years)
|
39.3
|
12.6
|
56
|
20.2
|
6.476$
|
<0.001
|
Total years of schooling
|
13.1
|
4.5
|
12.6
|
3.4
|
1.411$
|
0.158
|
Was infected with COVID-19
|
Yes
|
59
|
18.7
|
8
|
12.5
|
1.395*
|
0.237
|
No
|
257
|
81.3
|
56
|
87.5
|
|
|
Preferred language
|
Turkish
|
245
|
70.4
|
0
|
0
|
121.655*
|
<0.001
|
German
|
103
|
29.6
|
72
|
100
|
|
|
Nationality
|
Turkish
|
197
|
57.9
|
|
|
|
|
German
|
90
|
26.5
|
72
|
100
|
|
|
Bulgarian
|
26
|
7.6
|
|
|
|
|
Other
|
27
|
7.9
|
|
|
|
|
Country of origin
|
Turkey
|
263
|
76.5
|
|
|
|
|
Germany
|
12
|
3.5
|
72
|
100
|
|
|
Bulgaria
|
28
|
8.1
|
|
|
|
|
Other
|
41
|
11.9
|
|
|
|
|
Native language
|
Turkish
|
263
|
77.8
|
|
|
|
|
German
|
19
|
5.6
|
72
|
100
|
|
|
Bulgarian
|
12
|
3.6
|
|
|
|
|
Kurdish
|
13
|
3.8
|
|
|
|
|
Arabic
|
8
|
2.4
|
|
|
|
|
Other
|
23
|
6.8
|
|
|
|
|
Place of birth
|
Turkey
|
207
|
60.7
|
|
|
|
|
Germany
|
71
|
20.8
|
72
|
100
|
|
|
Bulgaria
|
25
|
7.3
|
|
|
|
|
Irak
|
9
|
2.6
|
|
|
|
|
Other
|
29
|
8.5
|
|
|
|
|
#Fisher’s exact test, *Chi-square, $Mann-Whitney U test, SD: Standard Deviation
Descriptive Findings and Outcomes
Responses to the scale items are summarized in Table 2. On the average, the knowledge regarding COVID-19 was high. Regarding attitudes, there was a relatively low fear of death due to COVID-19. Also, very few participants thought that faith would play a role in protection from the disease. Behavior scores on the other hand, were comparatively higher (Table 2). Cronbach’s alpha reliability coefficients for the knowledge, attitude, and behavior domains were 0.732, 0.695, and 0.716, respectively.
Table 2: Domains and descriptive statistics of the survey items
Subscale 1: COVID-19 Knowledge
|
Correct n (%)
|
False n (%)
|
1. The cause of the Corona-infection a virus
|
353 (87.4)
|
51 (12.6)
|
2. How COVID-19 spreads is not known
|
287 (69.5)
|
126 (30.5)
|
3. COVID-19 can spread through the air in enclosed spaces
|
388 (93.3)
|
28 (6.7)
|
4. COVID-19 can spread through close contact (e.g. hugging)
|
394 (93.8)
|
26 (6.2)
|
5. COVID-19 can spread through sexual contact
|
242 (59.9)
|
162 (40.1)
|
6. COVID-19 is often transmitted through food
|
333 (80.2)
|
82 (19.8)
|
Which of the following measures can reduce the risk of transmitting COVID-19?
|
408 (96.5)
|
15 (3.5)
|
7. Washing hands after touching potentially infected surfaces
|
412 (97.4)
|
11 (2.6)
|
8. Wearing a face mask when entering crowds
|
368 (90.2)
|
40 (9.8)
|
9. Taking antibiotics
|
335 (80.5)
|
81 (19.5)
|
10. Drinking vinegar
|
363 (87.5)
|
52 (12.5)
|
11. Drinking carrot juice
|
405 (96)
|
17 (4)
|
12. Keeping a distance of 1.5 meters from people
|
400 (95.7)
|
18 (4.3)
|
13. Lubricate butter in the nostrils
|
311 (75.1)
|
103 (24.9)
|
14. Eating garlic
|
222 (54.8)
|
183 (45.2)
|
15. The use of the Corona app
|
401 (94.8)
|
22 (5.2)
|
16. Frequent ventilation when in the same room with others
|
374 (88.6)
|
48 (11.4)
|
17. Avoiding closed rooms with strangers
|
397 (94.3)
|
24 (5.7)
|
18. Avoiding crowds
|
382 (91)
|
38 (9)
|
19. Drinking holy water
|
394 (94.3)
|
24 (5.7)
|
Which of the following symptoms are common in COVID-19?
|
407 (96.9)
|
13 (3.1)
|
20. Cough
|
363 (89.4)
|
43 (10.6)
|
21. Fever
|
395 (96.8)
|
13 (3.2)
|
22. Dysuria
|
387 (95.3)
|
19 (4.7)
|
23. Increased appetite
|
391 (93.8)
|
26 (6.2)
|
24. Weight gain
|
287 (69.5)
|
126 (30.5)
|
25. Loss of taste and smell
|
388 (93.3)
|
28 (6.7)
|
Subscale 2: COVID-19 Attitude
5-Agree, 4-Partially agree, 3-Not sure, 2-Partially disagree, 1-Disagree
|
Mean
|
SD
|
1. COVID-19 is dangerous
|
4.47
|
1.04
|
2. In reality, COVID-19 does not exist
|
1.63
|
1.24
|
3. The danger of COVID-19 is exaggerated
|
2.42
|
1.52
|
4. I am afraid of dying if I should get COVID-19
|
2.50
|
1.45
|
5. Believers are protected from COVID-19
|
1.47
|
1.12
|
6. COVID-19 was created purposely to control the world
|
2.47
|
1.50
|
7. Vaccination against COVID-19 is safe
|
3.19
|
1.29
|
Subscale 3: COVID-19 Behavior
1-Never, 2-Very rare, 3-Off and on, 4-Frequent, 5-Very frequent
|
Mean
|
SD
|
1. How often do you wash your hands?
|
4.38
|
0.64
|
2. How often do you wear a mask when you are outside?
|
4.19
|
0.90
|
3. How much attention do you pay to keeping distance?
|
4.16
|
0.88
|
4. How often do you accept guests?
|
2.13
|
0.88
|
5. How often do you go visiting others?
|
1.82
|
0.91
|
6. How often do you enter crowded places?
|
2.05
|
0.91
|
7. How often do you use public transport?
|
2.27
|
1.23
|
|
Yes n (%)
|
No n (%)
|
Not sure n (%)
|
Have you already been vaccinated against COVID-19?
|
23 (5.5)
|
397 (94.5)
|
|
Will you get vaccinated against COVID-19?
|
198 (47.8)
|
77 (18.6)
|
139 (33.6)
|
Why? Can you please elaborate? ……………………………………………..…………………………
|
A total of 197 participants (47.9%) intended to get vaccinated. There were significant differences in the mean knowledge, attitude, and behavior scores regarding migratory background. Those with a migratory background were mostly not intending to be vaccinated, and had lower scores in all three subscales. However, COVID-19 knowledge scores were relatively high for both groups (Table 3).
Table 3: Descriptive statistics and comparisons between the migratory backgrounds
|
Migratory Background
|
|
|
Yes
(n=348)
|
No
(n=72)
|
Total
(n=420)
|
|
|
n
|
%
|
n
|
%
|
n
|
%
|
Test
|
p
|
Have you already been vaccinated against COVID-19?
|
Yes
|
16
|
4.6
|
7
|
9.7
|
23
|
5.5
|
3.027#
|
0.091
|
No
|
332
|
95.4
|
65
|
90.3
|
397
|
94.5
|
|
|
Will you get vaccinated against COVID-19?
|
Yes
|
145
|
42.3
|
52
|
76.5
|
197
|
47.9
|
26.818*
|
<0.001
|
No
|
70
|
20.4
|
7
|
10.3
|
77
|
18.7
|
|
|
Not sure
|
128
|
37.3
|
9
|
13.2
|
137
|
33.3
|
|
|
|
Mean
|
SD
|
Mean
|
SD
|
Mean
|
SD
|
|
|
Knowledge score
|
21.2
|
3.4
|
23.3
|
1.7
|
21.6
|
3.2
|
5.660$
|
<0.001
|
Attitude score
|
3.6
|
0.8
|
4.2
|
0.7
|
3.7
|
0.8
|
5.317$
|
<0.001
|
Behavior score
|
4.0
|
0.6
|
4.3
|
0.5
|
4.1
|
0.6
|
3.715&
|
<0.001
|
*Chi-square, #Fisher’s exact test, &Independent samples t-test, $Mann-Whitney U test, SD: Standard Deviation
Of the 411 patients who indicated their intentions of accepting or refusing vaccination, 253 (61.5%) expressed 1-3 reasons for their thoughts (total 294). After categorization of the free texts, the most common three reasons were self-protection (n=49), concerns about safety or mistrust in vaccines (n=45), and the perception that vaccines were not sufficiently studied (n=25) (Figure 2).
Of the people with a migratory background, 12.6% (n=44) agreed or somewhat agreed that COVID-19 actually did not exist. This proportion was 5.6% (n=4) among the non-immigrant participants (Chi-square=11.623, p=0.020). Also, those believing that the COVID-19 was purposely created to control the world were higher among participants with a migratory background (agree+somewhat agree answers 30.6% (n=106) vs. 5.6% (n=4)) (Chi-square=33.020, p<0.001).
Multivariable Analyzes
Responses to the question “Will you get vaccinated against COVID-19?” were merged into two categories as ‘No+Not sure’ and ‘Yes.’ Positive vaccination intentions ranged from 26.9% to 68.5% between different practices.
All investigated variables were related to the vaccination intention. Furthermore, participants with a preference for a German questionnaire had higher intentions compared to those preferring a Turkish questionnaire (n=99/57.9% vs. n=99/40.6%, Chi-square=12.091, p=0.001) and men had higher intentions to get vaccinated compared to women (Table 4).
A multiple logistic regression model was fit to the data to estimate and test the relation of predictors of vaccination intention. Independent predictors of the model included sex (male/female), migratory background (yes/no), age (years), duration of schooling (years), a previous infection (yes/no), knowledge score, attitude score, and behavior score.
Multivariable analysis changed the significance levels. Age, male sex, years of schooling (borderline significant), migratory background, and high attitude scores positively affected the vaccination intention (Table 3). The most significant variable was the migratory background with an odds ratio (OR) of 3.1, followed by attitude scores (OR 2.9) and sex (OR=2.2).
Table 4: Univariate analyses and multiple logistic regression model concerning the agreement for COVID-19 vaccination
|
Univariate Comparisons
|
Multiple Logistic Regression Model
|
|
n/Mean
|
%/SD
|
n/Mean
|
%/SD
|
|
|
|
95% CI
|
B
|
Wald
|
p
|
OR
|
95% CI
|
Wald
|
p
|
OR
|
Lower
|
Upper
|
Lower
|
Upper
|
Age (years)
|
37.7
|
13.5
|
46.5
|
15.8
|
30.745
|
<0.001
|
1.042
|
1.027
|
1.057
|
0.022
|
4.459
|
0.035
|
1.022
|
1.002
|
1.042
|
Sex (male)
|
112
|
46.3
|
130
|
53.7
|
8.608
|
0.003
|
1.817
|
1.219
|
2.707
|
0.782
|
8.256
|
0.004
|
2.185
|
1.282
|
3.725
|
Total years of schooling
|
12.3
|
4.1
|
13.7
|
4.5
|
10.9
|
0.001
|
1.086
|
1.034
|
1.14
|
0.062
|
3.582
|
0.058
|
1.064
|
0.998
|
1.134
|
Migratory background (no)
|
16
|
23.5
|
52
|
76.5
|
23.705
|
<0.001
|
4.438
|
2.436
|
8.085
|
1.125
|
6.767
|
0.009
|
3.082
|
1.32
|
1.195
|
Was infected with COVID-19 (no)
|
150
|
48.2
|
161
|
51.8
|
4.446
|
0.035
|
1.813
|
1.043
|
3.152
|
0.472
|
2.003
|
0.157
|
1.603
|
0.834
|
|
Knowledge score
|
20.9
|
3.5
|
22.1
|
2.8
|
11.525
|
0.001
|
1.121
|
1.049
|
1.192
|
-0.029
|
0.364
|
0.546
|
0.971
|
0.883
|
1.068
|
Attitude score
|
3.4
|
0.8
|
4.1
|
0.6
|
62.542
|
<0.001
|
3.762
|
2.709
|
5.224
|
1.057
|
23.393
|
<0.001
|
2.877
|
1.875
|
4.414
|
Behavior score
|
3.9
|
0.6
|
4.2
|
0.4
|
26.018
|
<0.001
|
2.841
|
1.902
|
4.243
|
0.296
|
1.111
|
0.292
|
1.344
|
0.776
|
2.33
|
Constant
|
|
|
|
|
|
|
|
|
|
-6.117
|
19.508
|
<0.001
|
|
|
|
SD: Standard deviation, CI: Confidence interval, OR: Odds ratio