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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(%).