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JMIR Res Protoc. 2019 Oct 8;8(10):e13321. doi: 10.2196/13321.

An Analytical Mobile App for Shared Decision Making About Prenatal Screening: Protocol for a Mixed Methods Study.

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Department of Family Medicine, McGill University, Montreal, QC, Canada.
Lady Davis Institute for Medical Research, Jewish General Hospital, Montreal, QC, Canada.
Department of Family Medicine and Emergency Medicine, Faculty of Medicine, Université Laval, Québec, QC, Canada.
Centre de recherche, Centre intégré en santé et services sociaux de Chaudière-Appalaches, Lévis, QC, Canada.
Centre de recherche sur les soins et les services de première ligne de l'Université Laval, Université Laval, Québec, QC, Canada.
Programmes de bioéthique, Département de médecine sociale et préventive, École de santé publique de l'Université de Montréal, Université de Montréal, Montréal, QC, Canada.
Department of Medical Genetics, University of British Columbia, Vancouver, BC, Canada.
Centre de recherche, Centre hospitalier universitaire de Québec, Québec, QC, Canada.
Department of Molecular Biology, Medical Biochemistry and Pathology, Faculty of Medicine, Université Laval, Québec, QC, Canada.
Canadian Research Chair in Shared Decision Making and Knowledge Translation, Québec, QC, Canada.
Department of Public Health Sciences, University of Rochester Medical Center, Rochester, NY, United States.



Decisions about prenatal screening to assess the risk of genetic conditions such as Down syndrome are complex and should be well informed. Moreover, the number of available tests is increasing. Shared decision making (SDM) about testing could be facilitated by decision aids powered by mobile technology.


In this mixed methods study, we aim to (1) assess women's needs and preferences regarding using an app for considering prenatal screening, (2) develop a decision model using the analytical hierarchy process, and (3) develop an analytical app and assess its usability and usefulness.


In phase 1, we will assess the needs of 90 pregnant women and their partners (if available). We will identify eligible participants in 3 clinical sites (a midwife-led birthing center, a family practice clinic, and an obstetrician-led hospital-based clinic) in Quebec City and Montreal, Canada. Using semistructured interviews, we will assess participants' attitudes toward mobile apps for decision making about health, their current use of apps for health purposes, and their expectations of an app for prenatal testing decisions. Self-administered questionnaires will collect sociodemographic information, intentions to use an app for prenatal testing, and perceived importance of decision criteria. Qualitative data will be transcribed verbatim and analyzed thematically. Quantitative data will be analyzed using descriptive statistics and the analytic hierarchy process (AHP) method. In phase 2, we will develop a decision model using the AHP whereby users can assign relative importance to criteria when deciding between options. We will validate the model with potential users and a multidisciplinary team of patients, family physicians, primary care researchers, decision sciences experts, engineers, and experts in SDM, genetics, and bioethics. In phase 3, we will develop a prototype of the app using the results of the first 2 phases, pilot test its usefulness and usability among a sample of 15 pregnant women and their partners (if available), and improve it through 3 iterations. Data will be collected with a self-administered questionnaire. Results will be analyzed using descriptive statistics.


Recruitment for phase 1 will begin in 2019. We expect results to be available in 2021.


This study will result in a validated analytical app that will provide pregnant women and their partners with up-to-date information about prenatal screening options and their risks and benefits. It will help them clarify their values and enable them to weigh the options to make informed choices consistent with their preferences and values before meeting face-to-face with their health care professional. The app will be easy to update with the latest information and will provide women with a user-friendly experience using their smartphones or tablets. This study and the resulting app will contribute to high-quality SDM between pregnant women and their health care team.




analytic hierarchy process; decision aid; mobile app; multiple criteria decision analysis; prenatal screening; shared decision making

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