Digital Patient Decision Aids for Endometriosis Management: A Scoping Review

BACKGROUND: Endometriosis treatment requires women to navigate complex, preference-sensitive decisions. Patient Decision Aids (PtDAs) help patients make value-aligned choices. However, the scope and quality of digital PtDAs for endometriosis, and the cap acity of conversational AI platforms to act as PtDAs, remain unclear. OBJECTIVES: Systematically map digital PtDAs for women of reproductive age with endometriosis, describe their content, development, and evaluation, and assess quality and replicability. SEARCH STRATEGY: Electronic databases, Google Scholar, grey literature, and web searches were conducted from inception to July 2025. SELECTION CRITERIA: We included digital PtDAs for women aged 18-49 with a clinical diagnosis of endometriosis that met the minimum criteria established to qualify as a PtDA. Additionally, we developed a prompt to generate five PtDAs using conversational AI platforms, mirroring patient or clinician decision-support queries. DATA COLLECTION AND ANALYSIS: Two independent reviewers extracted data per Joanna Briggs Institute (JBI) scoping reviews methodology. IPDAS criteria (requirements for PtDAs) and TIDieR items (intervention reporting) were applied; data were summarised descriptively and qualitatively. RESULTS: Ten PtDAs were included (five expert-developed; five AI-generated). Overall, most addressed pharmacological and surgical options, while AI-generated PtDAs included more complementary therapies. All described the health condition, decision, and options with balanced pros/cons, but most failed on important IPDAS criteria for high-quality PtDAs. Most expert-developed PtDAs also lacked transparent development reporting and had not been formally evaluated. CONCLUSIONS: Few digital PtDAs for endometriosis were identified; most showed limited adherence to IPDAS criteria, poor reporting transparency, and absent formal evaluation.