An innovative web-based decision-aid about birth after cesarean for shared decision making in Taiwan: study protocol for a randomized control trial

Abstract

Abstract Background Taiwan has a high national caesarean rate coupled with a low vaginal birth after caesarean (VBAC) rate. This study aims to develop and evaluate a web-based decision-aid with communication support tools, to increase shared decision making (SDM) about birth after caesarean. Methods A quantitative approach will be adopted using a randomized pre-test and post-test experimental design in a medical centre in northern Taiwan. The web-based decision aid consists of five sections. Section 1 provides a two-part video to introduce SDM and how to participate in SDM. Section 2 presents an overview of functions and features of the birth decision-aid. Section 3 presents relevant VBAC information, including definitions, benefits and risks, and an artificial intelligence (AI) calculator for rate and likelihood of VBAC success. Section 4 presents the information regarding elective repeat caesarean delivery (ERCD), involving definitions, benefits, and risks. Section 5 comprises four steps of decision making to meet women’s values and preferences. Pregnant women who have had one previous caesarean and are eligible for VBAC, will be recruited at 14–16 weeks. Participants will complete a baseline survey prior to random allocation to either the control group (usual care) or intervention group (usual care plus an AI-decision aid). A follow up survey at 35–38 weeks will measure change in decisional conflict, knowledge, birth mode preference, and decision-aid acceptability. Actual birth outcomes and satisfaction will be assessed one month after birth. Discussion The innovative web-based decision-aid with support tools will help to promote pregnant women’s decision-making engagement and communication with their providers and improve opportunities for supportive communication about VBAC SDM in Taiwan. Linking web-based AI data analysis into the medical record will also be assessed for feasibility during implementation in clinical practice. Trial registration ClinicalTrials.gov identifier (NCT05091944), Registered on October 24, 2021.