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Table 6 Demographic features and school education

From: How do hospitalised patients with Turkish migration background estimate their language skills and their comprehension of medical information – a prospective cross-sectional study and comparison to native patients in Germany to assess the language barrier and the need for translation

 

T

G

Significance

 

(n = 121)

(n = 121)

 

Age y ± SD

44.94 ± 17.70

56.93 ± 16.72

p <0.0001

Males n (%)

45 (37.2)

66 (54.5)

p =0.0097

Patient’s nationality

   

German n (%)

37 (30.58)

121 (100)

 

Binational# n (%)

4 (3.30)

0 (0)

 

Turkish n (%)

80 (66.12)

0 (0)

 

Patient’s birthplace

   

Germany n (%)

35 (28.93)

121 (100)

 

Turkey n (%)

86 (71.07)

0 (0)

 

Highest school education a

(n = 109)

(n = 121)

 

Primary school

15 (13.76)

12 (9.92)

 

Junior high school

64 (58.72)

81 (66.94)

 

High school

9 (8.26)

9 (7.44)

 

College

21 (19.27)

19 (15.70)

p =0.491

  1. T, Patients with Turkish migration background. G: German patients without migration background. y, Year; SD, Standard deviation; n, Number; Binational, Patients with a double (Turkish/German) nationality. n(%) relates to the group with the same migration background. a = not all patients responded to this question (T: n =109, G: n = 121); results are depicted as n(%).