How Artificial Intelligence Shapes Knowledge Access and Decision-Making Among Birthing People: A Scoping Review Protocol

The Science of Birth is offering a stipend of CAD$5000 to a graduate student or early career scholar to undertake a scoping review of the following topic:

Background and Rationale
Artificial intelligence (AI) is rapidly transforming how individuals access health information and make decisions. Birthing people—those who are pregnant, postpartum, or planning pregnancy—are increasingly turning to AI-enabled tools such as chatbots, symptom checkers, and personalized content platforms for guidance. These tools have the potential to expand access to timely, tailored information, particularly in contexts where healthcare access is limited. However, concerns remain regarding accuracy, bias, health literacy demands, and the potential for AI to influence decision-making in ways that may not align with clinical best practices or individual preferences.

While recent reviews have examined AI applications in perinatal care and the use of conversational agents for information delivery, there remains no comprehensive synthesis of how AI shapes knowledge access, interpretation, and decision-making among birthing people

Objective
To systematically map and synthesize the existing literature on how AI influences knowledge access and decision-making among birthing people across the perinatal continuum.

Research Questions

1. What types of AI tools are used by birthing people to access health information?
2. How do these tools shape knowledge acquisition, understanding, and trust in information?
3. In what ways does AI influence health-related decision-making (e.g., care-seeking, treatment choices, parenting practices)?
4. What are the reported benefits, risks, and equity implications of AI use in this population?

Methods
This scoping review will follow established methodological frameworks (e.g., Arksey and O’Malley, Joanna Briggs Institute guidance). A comprehensive search strategy will be developed in consultation with a health sciences librarian and applied across databases such as MEDLINE, Embase, CINAHL, PsycINFO, and Scopus. Grey literature sources (e.g., policy reports, organizational publications) will also be included to capture emerging evidence.

Eligibility criteria will include studies and reports that:

• Involve birthing people (pregnant, postpartum, or preconception populations)
• Examine AI-enabled tools (e.g., chatbots, machine learning–driven platforms, virtual assistants)
• Address knowledge access, information use, or decision-making outcomes

Two reviewers will independently screen titles/abstracts and full texts. Data will be extracted using a standardized charting form, capturing study characteristics, AI tool type, population, outcomes, and key findings. Results will be synthesized descriptively and thematically.

Expected Outcomes
This review will provide a comprehensive overview of how AI is currently shaping knowledge access and decision-making among birthing people. It will identify gaps in evidence, including underserved populations, underexplored outcomes, and methodological limitations. Findings will inform the development of evidence-based guidelines, digital health interventions, and policy recommendations to ensure AI supports safe, equitable, and informed decision-making in perinatal care.

Significance
As AI becomes embedded in everyday health information ecosystems, understanding its impact on vulnerable and high-stakes populations is critical. This scoping review will generate foundational knowledge to guide clinicians, researchers, and health system leaders in leveraging AI responsibly to support birthing people.

Timeline: December 1, 2027.

Knowledge Translation: Findings will be shared through peer-reviewed publication, conference presentations, and stakeholder briefs targeting clinicians and digital health developers. 

Please submit application to contact@scienceofbirth.ca:

• Name
• Supervisor: (if relevant)
• Email
• Copy of Curriculum Vitae