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Table 2 Characteristics of “good” and “poor” auditors from the bivariate analysis. Variables that predict being a “good” auditor from logistic regression analysis

From: Patients and relatives as auditors of safe practices in oncology and hematology day hospitals

Bivariate analysis of the P&Fs characteristics between “good” and “poor” auditors
* Good auditors (> 75% correct answers)
** Poor auditors (= < 75% correct answers)
Logistic regression analysis of the variables that predict being a “good” auditor
   Good auditors* n = 63 Poor auditors** n = 73 p value Beta p value Odds Ratio 95% CI
Age: mean (sd)   51.4 (12.5) 62.5 (12.7) 0.000 −0.061 0.001 0.940 0.908 0.974
Gender: n (%) Female 33 (46.5) 39 (53.5) 0.903      
Male 30 (47.6) 34 (52.4)       
Education: n (%) Basic level 20 (31.7) 45 (68.2) 0.000   0.006 1 (referent)   
Medium level 14 (43.8) 18 (56.3)   0.652 0.208 1.920 0.696 5.301
High level 28 (77.8) 8 (22.2)   1.738 0.001 5.684 1.947 16.591
Adverse events suffered n (%) No 22 (73.3) 8 (26.7) 0.001 0   1 (referent)   
Yes 41 (38.7) 65 (61.3)   1.658 0.002 5.250 1.861 14.806
General perception of hospital safety Totally safe 19 (31.7) 41 (68.3) 0.002      
Other categories 43 (57.3) 32 (42.7)       
  2.388 0.027 10.894 Constant
  R2 Nagelkerke = 0.411
X2 Hosmer and Lemeshow =3.530 Sig = 0.897
Type of participants: n (%) Companions 27 (60.0) 19 (40.0) 0.046      
Patients 36 (40.4) 54 (59.6)       
Type of treatment: n (%) Chemotherapy 52 (52.5) 49 (47.5) 0.05      
Transfusion 11 (31.4) 24 (68.6)       
Healthcare professional n (%) Yes 8 (57.1) 6 (42.9) 0.783      
No 54 (53.5) 49 (46.5)       
Number of Day Hospital visits: median (IQR)   6 (15–3) 7 (12–3) 0.649      
Number of hospital stays: median (IQR)   1 (2–0) 0 (1–0) 0.108