5. Data analysis

Data was analyzed in SPSS (released 2013, IBM SPSS Statistics, version 22.0; IBM Corp., Chicago, IL, USA). Baseline characteristics of respondents, results on the current practice domain and the influencing factors on innovation and individual level were descriptively analyzed (median with interquartile range [IQR] and percentages). Influencing factors on organization and professional level were analyzed by the use of multivariate logistic regression analysis. As dependent variable, the current practice was converted to a bivariate variable (‘never,’ ‘rarely,’ ‘about half the time’ versus ‘usually,’ ‘always’) per type of surgery. The following baseline characteristics were used as independent variables among gynecologists; years of work experience, type of institution, special interest, number of (vaginal) hysterectomies performed annually and knowledge of current literature. Among trainees the imputed independent variables were; year of residency, number of (vaginal) hysterectomies performed with or without supervision and the knowledge of current literature. At first, univariate logistic regression analysis was performed and independent variables with a p-value ≤0.20 were analyzed in multivariate logistic regression analysis. The multivariate analysis was performed using backward-stepwise method and a p-value ≤0.05 was considered statistically significant.