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Background The use of telemedicine for the management of patients with Inflammatory Bowel Disease (IBD) has developed quickly over the past few years. In our tertiary referral Centre for IBD we have provided our patients an asynchronous telemedicine service, the App Care4today® IBD (Bepatient, Paris, France). Its main function is the remote monitoring of patients’ symptoms and disease activity (abdominal pain and bowel movements). In addition, it evaluates the quality of life through the EQ-5D-5L questionnaire, it provides information on topics to implement patient education (e.g., smoking), and it allows patients to insert reminders for the therapy. Decision trees (DT) and random forests (RF) are two machine learning (ML) techniques which have been increasingly utilized in the last few years due to their ability to uncover non-linear relationships between covariates and outputs. Methods The aims of our study were to evaluate the app use, satisfaction and trust of IBD patients, and to identify the possible determinants influencing its trust through a ML analysis. From April 26th to May 21st 2021, we have consecutively proposed to all IBD patients (familiar with smartphones and mobile Apps) on biological therapy to download Care4today® IBD. Ease of use, patients’ satisfaction and trust were assessed through a 5 points Likert scale questionnaire adapted on the SUTAQ (Service User Technology Acceptability Questionnaire). ML tools, DT and RF, were used to identify the determinants of patients’ trust. Results Out of 135 enrolled patients (among 151 patients), 87 (64.4%) used the app. Among the patients who compiled the questionnaire (39/87, 44.8%), 92.4% trusted to use the App, 94.9% showed confidence in the monitoring system. On contrast, disagreement (92.4% giving a score &amp;lt;3/5) was expressed for the statement “the Apps can replace my regular health care”. The DT showed that the variable which has influenced the most patients’ trust is the conviction that the App is a tool useful for a better monitoring of their disease by physicians, since it represented the root of the tree which explains the final decision. The RF confirmed that this variable influenced the most patients’ trust with a 15% increase in mean squared error (IncMSE) and 7.10 IncNodePurity. Conclusion More than half of our patients actively used the Care4today IBD App, and more than four of every five of those who responded to the survey proved to be well disposed to its usage, showing a good level of confidence and trust in it. The knowledge of patients’ trust determinants (App utility is the most relevant) is the key point in order to implement the use of these new digital monitoring options, which may help to better manage the disease, through tight control and personalized medicine

P528 Feasibility, satisfaction and machine learning analysis of factors influencing IBD patients’ trust in the mobile application Care4today IBD