BACKGROUND:
Taiwan reports one of the world’s highest cesarean section (CS) rates and a low rate of vaginal birth after cesarean (VBAC). Concerns over maternal and neonatal risks often discourage VBAC attempts. Shared decision-making (SDM), supported by decision aids, facilitates informed, value-based choices.

OBJECTIVES:
This study developed and evaluated an innovative artificial intelligence (AI)-integrated, web-based decision aid designed to enhance SDM for pregnant women with a prior CS.

METHODS:
A randomized pretest-post test controlled trial was conducted in a medical center in northern Taiwan. Eligible participants (14–16 weeks’ gestation, with one prior CS) were randomly assigned to either the control group (usual care) or the intervention group (usual care plus access to the AI-based decision aid). Primary outcomes included decisional conflict, knowledge, and birth mode preference, assessed at baseline and at 35–37 weeks’ gestation. Secondary outcomes included actual birth mode and decision satisfaction, assessed one month postpartum.

RESULTS:
Sixty-four women completed the study (33 control, 31 intervention). Baseline characteristics were comparable. The intervention group experienced significantly greater reductions in decisional conflict—especially in feeling informed (p < 0.001) and clarity of values (p = 0.035). While knowledge scores improved in both groups, the increase was greater in the intervention group. VBAC preference rose to 51.6% post-intervention, compared to 21.2% in the control group. The actual VBAC rate was significantly higher in the intervention group (26.5% vs. 6.1%, p = 0.021). Both groups reported high satisfaction with their decisions, and the intervention was rated highly acceptable.

CONCLUSIONS:
The AI-integrated web-based decision aid significantly improved decision quality, increased VBAC preference and success, and supported SDM in prenatal care. It offers a scalable solution to promote preference-aligned maternal decision-making.

KEY MESSAGE:
An AI-enhanced, web-based decision aid effectively reduces decisional conflict and increases both informed VBAC preference and actual VBAC rates, supporting personalized, evidence-based obstetric care. Poster session 1 (Group A)