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

BACKGROUND: 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 mo...

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Autores principales: Abbasgholizadeh Rahimi, Samira, Archambault, Patrick M, Ravitsky, Vardit, Lemoine, Marie-Eve, Langlois, Sylvie, Forest, Jean-Claude, Giguère, Anik M C, Rousseau, François, Dolan, James G, Légaré, France
Formato: Online Artículo Texto
Lenguaje:English
Publicado: JMIR Publications 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6913686/
https://www.ncbi.nlm.nih.gov/pubmed/31596249
http://dx.doi.org/10.2196/13321
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author Abbasgholizadeh Rahimi, Samira
Archambault, Patrick M
Ravitsky, Vardit
Lemoine, Marie-Eve
Langlois, Sylvie
Forest, Jean-Claude
Giguère, Anik M C
Rousseau, François
Dolan, James G
Légaré, France
author_facet Abbasgholizadeh Rahimi, Samira
Archambault, Patrick M
Ravitsky, Vardit
Lemoine, Marie-Eve
Langlois, Sylvie
Forest, Jean-Claude
Giguère, Anik M C
Rousseau, François
Dolan, James G
Légaré, France
author_sort Abbasgholizadeh Rahimi, Samira
collection PubMed
description BACKGROUND: 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. OBJECTIVE: 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. METHODS: 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. RESULTS: Recruitment for phase 1 will begin in 2019. We expect results to be available in 2021. CONCLUSIONS: 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. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/13321
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spelling pubmed-69136862020-01-02 An Analytical Mobile App for Shared Decision Making About Prenatal Screening: Protocol for a Mixed Methods Study Abbasgholizadeh Rahimi, Samira Archambault, Patrick M Ravitsky, Vardit Lemoine, Marie-Eve Langlois, Sylvie Forest, Jean-Claude Giguère, Anik M C Rousseau, François Dolan, James G Légaré, France JMIR Res Protoc Protocol BACKGROUND: 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. OBJECTIVE: 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. METHODS: 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. RESULTS: Recruitment for phase 1 will begin in 2019. We expect results to be available in 2021. CONCLUSIONS: 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. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/13321 JMIR Publications 2019-10-08 /pmc/articles/PMC6913686/ /pubmed/31596249 http://dx.doi.org/10.2196/13321 Text en ©Samira Abbasgholizadeh Rahimi, Patrick M Archambault, Vardit Ravitsky, Marie-Eve Lemoine, Sylvie Langlois, Jean-Claude Forest, Anik M C Giguère, François Rousseau, James G Dolan, France Légaré. Originally published in JMIR Research Protocols (http://www.researchprotocols.org), 08.10.2019. https://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in JMIR Research Protocols, is properly cited. The complete bibliographic information, a link to the original publication on http://www.researchprotocols.org, as well as this copyright and license information must be included.
spellingShingle Protocol
Abbasgholizadeh Rahimi, Samira
Archambault, Patrick M
Ravitsky, Vardit
Lemoine, Marie-Eve
Langlois, Sylvie
Forest, Jean-Claude
Giguère, Anik M C
Rousseau, François
Dolan, James G
Légaré, France
An Analytical Mobile App for Shared Decision Making About Prenatal Screening: Protocol for a Mixed Methods Study
title An Analytical Mobile App for Shared Decision Making About Prenatal Screening: Protocol for a Mixed Methods Study
title_full An Analytical Mobile App for Shared Decision Making About Prenatal Screening: Protocol for a Mixed Methods Study
title_fullStr An Analytical Mobile App for Shared Decision Making About Prenatal Screening: Protocol for a Mixed Methods Study
title_full_unstemmed An Analytical Mobile App for Shared Decision Making About Prenatal Screening: Protocol for a Mixed Methods Study
title_short An Analytical Mobile App for Shared Decision Making About Prenatal Screening: Protocol for a Mixed Methods Study
title_sort analytical mobile app for shared decision making about prenatal screening: protocol for a mixed methods study
topic Protocol
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6913686/
https://www.ncbi.nlm.nih.gov/pubmed/31596249
http://dx.doi.org/10.2196/13321
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