Digital Patient Decision Aids for Endometriosis Management: A Scoping Review
Océane Pittet, Marion Delvallée, Nicola Pluchino, Kevin Selby, Glyn Elwyn, Marie‐Anne DurandABSTRACT
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.