Digital Patient Decision Aids for Endometriosis Management: A Scoping Review
Abstract
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.
Related
- Digital Health and Technology‐Supported Interventions Supporting Advanced Practice Nurses in Cardiovascular Risk Management in Primary Care: A Scoping Review
- Experiences towards endometriosis management: A qualitative study among patients and healthcare professionals
- A scoping review protocol on digital health equity among immigrant populations: Planning and managing effective digital health services
- A scoping review of caries risk management protocols in Australia and New Zealand
- Ravulizumab monotherapy for anti-CFH antibody-associated aHUS in an elderly patient: a case report highlighting individualized clinical decision-making
BibTeX
@article{pittet2026digital,
title = {{Digital Patient Decision Aids for Endometriosis Management: A Scoping Review}},
author = {Océane Pittet and Marion Delvallée and Nicola Pluchino and Kevin Selby and Glyn Elwyn and Marie-Anne Durand and Marie‐anne Durand},
journal = {Health Expectations},
year = {2026},
month = sep,
doi = {10.1111/hex.70881},
url = {https://hal.science/hal-05799795v1},
note = {CC BY},
}
RIS
TY - JOUR
TI - Digital Patient Decision Aids for Endometriosis Management: A Scoping Review
AU - Océane Pittet
AU - Marion Delvallée
AU - Nicola Pluchino
AU - Kevin Selby
AU - Glyn Elwyn
AU - Marie-Anne Durand
AU - Marie‐anne Durand
PY - 2026
DA - 2026/09/25
JO - Health Expectations
DO - 10.1111/hex.70881
UR - https://hal.science/hal-05799795v1
AB - 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.
SN - 1369-6513
SN - 1369-7625
ER -