Nicole M Rau1, Kamrul Hasan2, Sheikh Iqbal Ahamed2, Onur Asan3, Kathryn E Flynn3, Mir A Basir4. 1. Medical College of Wisconsin, Department of Pediatrics, 999 N 92ndSt, Suite C410, PO Box 1997, Wauwatosa, WI, 53226, United States. 2. Marquette University, Department of Computer Science, Katharine R. Cudahy Hall, Room 201 1313 W. Wisconsin Avenue, Milwaukee, WI, 53233, United States. 3. Medical College of Wisconsin, Department of Medicine, 9200 W. Wisconsin Ave, Suite C5500, Milwaukee, WI, 53226, United States. 4. Medical College of Wisconsin, Department of Pediatrics, 999 N 92ndSt, Suite C410, PO Box 1997, Wauwatosa, WI, 53226, United States. Electronic address: mbasir@mcw.edu.
Abstract
BACKGROUND: As technology has advanced over the last decade, handheld Mobile Health (mHealth) applications have increased in popularity. Pregnancy is one area of mHealth that has rapidly expanded, however very few pregnancy apps are developed in collaboration with health professionals. This creates an environment where the pregnancy information women are accessing may be inaccurate or even dangerous. Additionally, there are relatively few medical apps devoted to prematurity or targeted to women at risk for premature birth. To address the gap in premature birth education, we assembled a multidisciplinary team, including health care professionals, and developed the Preemie Prep for Parents (P3) app. METHODS: Our team previously conducted 5 focus group meetings to assess the information needs of our target audience. Based on this information we developed a low fidelity P3 prototype. Our software development team transferred the low fidelity prototype into a high fidelity prototype which was hosted on Test Flight (a beta testing platform). We performed heuristic evaluation as well as user testing to improve the P3 app. RESULTS: User testing of the high fidelity P3 prototype was performed with 13 diverse participants. 6 participants were parents of currently admitted Neonatal Intensive Care Unit (NICU) babies and 7 participants were women who had been or were currently pregnant. The native language of participants included English, Spanish, and Hmong and their educational level varied between completing high school and graduate degree. Participants provided feedback on the content of the P3 app, as well as its organization and aesthetics. The feedback led to 83 iterations of the P3 app prior to its deployment. Overall, participants noted that the information was "informative" and "reliable". They also noted that the P3 app provided control over the information they could view and when they viewed it, stating "I could see info on my time". Overall, participants felt that the P3 app was a valuable tool for mothers in preterm labor and it would help them ask questions. CONCLUSIONS: Development of a mHealth app provides unique challenges regarding content, reliability of information, organization, and aesthetics. Creation of the P3 app to address the educational needs of women at risk for premature birth required assembling a multidisciplinary team, which included target users, and implementing an iterative design process. The efficacy of this app in improving user knowledge and decreasing anxiety is currently being tested in a randomized controlled trial.
BACKGROUND: As technology has advanced over the last decade, handheld Mobile Health (mHealth) applications have increased in popularity. Pregnancy is one area of mHealth that has rapidly expanded, however very few pregnancy apps are developed in collaboration with health professionals. This creates an environment where the pregnancy information women are accessing may be inaccurate or even dangerous. Additionally, there are relatively few medical apps devoted to prematurity or targeted to women at risk for premature birth. To address the gap in premature birth education, we assembled a multidisciplinary team, including health care professionals, and developed the Preemie Prep for Parents (P3) app. METHODS: Our team previously conducted 5 focus group meetings to assess the information needs of our target audience. Based on this information we developed a low fidelity P3 prototype. Our software development team transferred the low fidelity prototype into a high fidelity prototype which was hosted on Test Flight (a beta testing platform). We performed heuristic evaluation as well as user testing to improve the P3 app. RESULTS: User testing of the high fidelity P3 prototype was performed with 13 diverse participants. 6 participants were parents of currently admitted Neonatal Intensive Care Unit (NICU) babies and 7 participants were women who had been or were currently pregnant. The native language of participants included English, Spanish, and Hmong and their educational level varied between completing high school and graduate degree. Participants provided feedback on the content of the P3 app, as well as its organization and aesthetics. The feedback led to 83 iterations of the P3 app prior to its deployment. Overall, participants noted that the information was "informative" and "reliable". They also noted that the P3 app provided control over the information they could view and when they viewed it, stating "I could see info on my time". Overall, participants felt that the P3 app was a valuable tool for mothers in preterm labor and it would help them ask questions. CONCLUSIONS: Development of a mHealth app provides unique challenges regarding content, reliability of information, organization, and aesthetics. Creation of the P3 app to address the educational needs of women at risk for premature birth required assembling a multidisciplinary team, which included target users, and implementing an iterative design process. The efficacy of this app in improving user knowledge and decreasing anxiety is currently being tested in a randomized controlled trial.
Authors: Marilyn M Schapira; Sumedha Chhatre; Jason M Prigge; Jessica Meline; Dana Kaminstein; Keri L Rodriguez; Liana Fraenkel; Jeffrey D Kravetz; Jeff Whittle; Lori A Bastian; Anil Vachani; Scott Akers; Susan Schrand; Jennifer V Ibarra; Onur Asan Journal: JMIR Form Res Date: 2022-04-08
Authors: Andrew M Novick; Melissa Kwitowski; Jack Dempsey; Danielle L Cooke; Allison G Dempsey Journal: Curr Psychiatry Rep Date: 2022-07-23 Impact factor: 8.081