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Smart Data Collection for the Assessment of Treatment Effects in IBS 219 9 other inclusion centers, except for the coordinating investigator (first author) who had access to all data. An audit layer of the application tracked and stored information of all changes. Storage, servers, and privacy All software and data storage complied with international ISO27001, ISO9001, and Good Clinical Practice guidelines, and Dutch NEN7510 guidelines. Electronic diary data, web-based-questionnaire and eCRF data, and privacy sensitive personal data (Ldot) were all stored on different (non-connected) servers. Several back-ups were made per day. Access to the servers was and will be restricted, with 24-hour on-site surveillance. Data will be stored for 15 years after study completion. Outcome measures The primary outcome of the current study was patients’ adherence to the digital symptom diary, defined as the mean percentage of entries and calculated by dividing the number of actually completed entries by the number of minimal requested entries (total number of days in study). Patients were instructed to complete a diary entry on all consecutive days during the 14-day pre-treatment and 56-day treatment period, or all days until discontinuation with the study. Secondary outcomes were change in mean adherence per week over time, sociodemographic and clinical patient characteristics associated with adherence rate, mean time of diary completion, and difference in adherence between patients who were defined as responders to treatment versus non-responders. Potential data-loss and critical evaluation points were considered to explore the overall feasibility of a smartphone application as a primary data-collection tool in a RCT. Other secondary outcomes were patients’ adherence to and completeness of the additional web-based questionnaires, and investigators’ adherence to and completeness of the electronic case report file (eCRF). Statistical analysis Statistical analyses were carried out using IBM SPSS statistics 25.0 for Macintosh (Armonk, NY, USA). Data are expressed as mean and standard deviation or as number plus percentage of total. Multivariable linear regression analysis was used to investigate the association between baseline patient characteristics and adherence to the digital diary, adjusting for minimization variables (age, gender, IBS-subtype, inclusion center and