152 Chapter 7 Statistical analysis The sample size was calculated based on a compliance rate to active ERAS elements of 57% in a previous study and the hypothesis that the ERAS App would increase patient compliance to 62%.17 Using a 2-sided alpha of 0.05, with 90% power and a standard deviation of 9, 140 patients were estimated to be required for the study. Data were analysed according to intention to treat protocol. Statistical analyses were conducted using IBM SPSS version 28.0. Baseline characteristics were summarized using descriptive statistics and compared between the intervention and control groups and between the included and excluded patients. Continuous normally distributed variables were reported as mean ± standard deviation, and non-normally distributed continuous variables were reported as median and interquartile range (IQR). Distributions were evaluated using visual inspection of histograms. Categorical variables were presented as frequencies and percentages. Independent t-tests, Mann-Whitney U tests, Chi-squared tests, and Fisher's exact tests were used to assess differences between groups as appropriate. A two-tailed p-value ≤ 0.05 was considered statistically significant. The extent of surgery was categorized as either being major or minor, with minor surgery defined as stoma creation/removal combined with an enterocutaneous fistula correction and major surgery including all the other operations. The selected ERAS elements were dichotomously scored as being fully complete or incomplete. The overall compliance is the average of all individual completion percentages. If a specific ERAS element was not present in the local pathway, it was not included into the calculation of overall compliance for these hospitals. Multivariate linear regression with stepwise backward selection was used to account for potential confounding and stratifying factors. PROMs were only included in the analysis if the patient completed >80% of the questionnaire per domain. Missing data were corrected using the participants’ mean outcome of the (domain of the) PROM. Baseline activity was calculated using the mean of the data recorded the week before surgery. For missing values, a cut-off value of 20% was applied. Postoperative activity was analysed using a Toeplitz linear mixed model. Graphs were generated to visualize daily step count.
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