Assessing Fetal Health by Pregnant Women in China Using Mobile Health Application
Abstract
This study endeavours to tackle the critical problem of inadequate evidence-based content in mobile health applications (mHealth apps), which adversely impact the accuracy of pregnancy outcomes. To this end, a conceptual framework for evaluating the visualization of fetal health is proposed through a systematic literature review method. This research aims to achieve the following objectives: (1) identify crucial health information that pregnant women in China need to know, (2) determine the best mHealth apps for pregnant women in China, and (3) evaluate the key components for assessing fetal health using mHealth apps among pregnant women in China. The results include fetal health variables, pregnancy complication variables, healthy diet variables, self-care practice variables, and user interface variables. This study contributes to proposing a design of mHealth apps by generating evidence-based visualized fetal assessment methods to foster prenatal attachment and reduce adverse pregnancy outcomes. This study presents a theoretical framework for mHealth apps aimed at pregnant women.
References
Alhusen, J. L., Gross, D. (2012). The influence of maternal-fetal attachment and health practices on neonatal outcomes in low-income, urban women. Research in Nursing & Health, 35(2), 112–120.
Allahem, H., & Sampalli, S. (2022). Automated labour detection framework to monitor pregnant women with a high risk of premature labour using machine learning and deep learning. Informatics in Medicine Unlocked, 28, 100771. 2023-02-19.
Alsswey, A., Naufal, I., & Bervell, B. (2018). Investigating the Acceptance of Mobile Health Application User Interface Cultural-Based Design to Assist Arab Elderly Users. International Journal of Advanced Computer Science and Applications, 9(8).
Bland, C. & Flynn, A. C. (2020). Smartphone applications available to pregnant women in the United Kingdom: An assessment of nutritional information. Maternal & Child Nutrition, 16(2). 2023-02-19.
Choi, D. (2019, December 31). How to build products with expert users. Medium.
Christensen, L. B., & Petersen, P. E. (2003). Self-reported gingival conditions and self-care in the oral health of Danish women during pregnancy. Journal of Clinical Periodontology, 30(11), 949–953.
Clapp, J. (1991). Exercise and fetal health. J Dev Physiol, 15(1), 9–14. PubMed.
Costa, D. (1998). A prospective study of the impact of psychosocial and lifestyle variables on pregnancy complications. Journal of Psychosomatic Obstetrics & Gynecology, 19(1), 28–37.
Dederichs, M. (2022). Piloting an Innovative Concept of e–Mental Health and mHealth Workshops With Medical Students Using a Participatory Co-design Approach and App Prototyping: Case Study. JMIR Medical Education, 8(1). 2023-03-22.
Doyle, I.-M., Borrmann, B, (2017). Determinants of dietary patterns and diet quality during pregnancy: A systematic review with narrative synthesis. Public Health Nutrition, 20(6), 1009–1028. 2023-04-26.
Green, J. & Huberty, J. (2022). Pregnant women’s use of a consumer-based meditation mobile app: A descriptive study. Digital Health, 8, 20552076221089098. 2023-02-19.
Hadar, E., & Dollinger, S. (2022). Mobile Self-Operated Home Ultrasound System for Remote Fetal Assessment During Pregnancy. Telemedicine and E-Health, 28(1), 93–101. 2023.
Ibrahim, R. (2011). Demystifying the Arduous Doctoral Journey: The Eagle Vision of a Research Proposal. Electronic Journal of Business Research Methods, 9(2), Article 2.
Islam, M. N. & Islam. (2020). Investigating usability of mobile health applications in Bangladesh. BMC Medical Informatics and Decision Making, 20(1), 19. 2023-02-19.
Keshavjee, K., & Kyba, R. (2022). Designing Disease-Specific mHealth Apps for Clinical Value. Smart and Pervasive Healthcare. 2023-03-22.
Khalil, A., & Nicolaides, K. H. (2013). Maternal age and adverse pregnancy outcome: A cohort study. Ultrasound in Obstetrics & Gynecology, 42(6), 634–643.
Kodama, T., & Takaki, S. (2022). Association Between Smartphone Applications for Pregnant Women and Psychological Distress in Japan. Journal of Psychosocial Nursing and Mental Health Services, 1–7. 2023-02-19.
Larsson, M. (2009). A descriptive study of the use of the Internet by women seeking pregnancy-related information. Midwifery, 25(1), 14–20.
Levin, J. S. (1988). Maternal stress and pregnancy outcomes: A review of the psychosocial literature. Journal of Psychosomatic Obstetrics & Gynecology, 9(1), 3–16.
Liu, Y. (2022). Effect of initial COVID-19 outbreak during first trimester on pregnancy outcome in Wuxi, China. BMC Pregnancy and Childbirth, 22(1), 1–7. 2023-02-19.
Luo, N., Ibrahim, R., & Abidin, S. Z. (2022). Transformation of Children’s Paintings into Public Art to Improve Public Spaces and Enhance People’s Happiness. International Journal of Environmental Research and Public Health, 19(24), Article 24. Q2.
Lyall, K. & Santangelo, S. L. (2012). Pregnancy complications and obstetric suboptimality in association with autism spectrum disorders in children of the nurses’ health study II. Autism Research, 5(1), 21–30.
Nash, D. M., Gilliland, J. A. (2013). Determinants of Diet Quality in Pregnancy: Sociodemographic, Pregnancy-specific, and Food Environment Influences. Journal of Nutrition Education and Behavior, 45(6), 627–634. 2023-04-26.
Norbeck, J. S., & Tilden, V. P. (1983). Life Stress, Social Support, and Emotional Disequilibrium in Complications of Pregnancy: A Prospective, Multivariate Study. Journal of Health and Social Behavior, 24(1), 30.
Ramli, S. H., Rejali, Z., & Dolah, M. S. (2018). VIDEO OBSERVATION FOR DESIGNERS: A CONTEXTUAL IMMERSION OF THE O&G MANNEQUIN IN CLINICAL TRAINING. Alam Cipta, 11(2), 57–61.
Rathnayake, S., Moyle, W., Jones, C., & Calleja, P. (2021). Co-design of an mHealth application for family caregivers of people with dementia to address functional disability care needs. Informatics for Health and Social Care, 46(1), 1–17. 2023-06-24.
Samrgandi, N. (2021). User Interface Design & Evaluation of Mobile Applications. 21.
Vahter, M. (2009). Effects of Arsenic on Maternal and Fetal Health. Annual Review of Nutrition, 29(1), 381–399.
Wirawan, F., Yudhantari, D. G. A., & Gayatri, A. (2023). Pre-pregnancy Diet to Maternal and Child Health Outcome: A Scoping Review of Current Evidence. Journal of Preventive Medicine and Public Health, 56(2), 111–127. 2023-04-26.
Allahem, H., & Sampalli, S. (2022). Automated labour detection framework to monitor pregnant women with a high risk of premature labour using machine learning and deep learning. Informatics in Medicine Unlocked, 28, 100771. 2023-02-19.
Alsswey, A., Naufal, I., & Bervell, B. (2018). Investigating the Acceptance of Mobile Health Application User Interface Cultural-Based Design to Assist Arab Elderly Users. International Journal of Advanced Computer Science and Applications, 9(8).
Bland, C. & Flynn, A. C. (2020). Smartphone applications available to pregnant women in the United Kingdom: An assessment of nutritional information. Maternal & Child Nutrition, 16(2). 2023-02-19.
Choi, D. (2019, December 31). How to build products with expert users. Medium.
Christensen, L. B., & Petersen, P. E. (2003). Self-reported gingival conditions and self-care in the oral health of Danish women during pregnancy. Journal of Clinical Periodontology, 30(11), 949–953.
Clapp, J. (1991). Exercise and fetal health. J Dev Physiol, 15(1), 9–14. PubMed.
Costa, D. (1998). A prospective study of the impact of psychosocial and lifestyle variables on pregnancy complications. Journal of Psychosomatic Obstetrics & Gynecology, 19(1), 28–37.
Dederichs, M. (2022). Piloting an Innovative Concept of e–Mental Health and mHealth Workshops With Medical Students Using a Participatory Co-design Approach and App Prototyping: Case Study. JMIR Medical Education, 8(1). 2023-03-22.
Doyle, I.-M., Borrmann, B, (2017). Determinants of dietary patterns and diet quality during pregnancy: A systematic review with narrative synthesis. Public Health Nutrition, 20(6), 1009–1028. 2023-04-26.
Green, J. & Huberty, J. (2022). Pregnant women’s use of a consumer-based meditation mobile app: A descriptive study. Digital Health, 8, 20552076221089098. 2023-02-19.
Hadar, E., & Dollinger, S. (2022). Mobile Self-Operated Home Ultrasound System for Remote Fetal Assessment During Pregnancy. Telemedicine and E-Health, 28(1), 93–101. 2023.
Ibrahim, R. (2011). Demystifying the Arduous Doctoral Journey: The Eagle Vision of a Research Proposal. Electronic Journal of Business Research Methods, 9(2), Article 2.
Islam, M. N. & Islam. (2020). Investigating usability of mobile health applications in Bangladesh. BMC Medical Informatics and Decision Making, 20(1), 19. 2023-02-19.
Keshavjee, K., & Kyba, R. (2022). Designing Disease-Specific mHealth Apps for Clinical Value. Smart and Pervasive Healthcare. 2023-03-22.
Khalil, A., & Nicolaides, K. H. (2013). Maternal age and adverse pregnancy outcome: A cohort study. Ultrasound in Obstetrics & Gynecology, 42(6), 634–643.
Kodama, T., & Takaki, S. (2022). Association Between Smartphone Applications for Pregnant Women and Psychological Distress in Japan. Journal of Psychosocial Nursing and Mental Health Services, 1–7. 2023-02-19.
Larsson, M. (2009). A descriptive study of the use of the Internet by women seeking pregnancy-related information. Midwifery, 25(1), 14–20.
Levin, J. S. (1988). Maternal stress and pregnancy outcomes: A review of the psychosocial literature. Journal of Psychosomatic Obstetrics & Gynecology, 9(1), 3–16.
Liu, Y. (2022). Effect of initial COVID-19 outbreak during first trimester on pregnancy outcome in Wuxi, China. BMC Pregnancy and Childbirth, 22(1), 1–7. 2023-02-19.
Luo, N., Ibrahim, R., & Abidin, S. Z. (2022). Transformation of Children’s Paintings into Public Art to Improve Public Spaces and Enhance People’s Happiness. International Journal of Environmental Research and Public Health, 19(24), Article 24. Q2.
Lyall, K. & Santangelo, S. L. (2012). Pregnancy complications and obstetric suboptimality in association with autism spectrum disorders in children of the nurses’ health study II. Autism Research, 5(1), 21–30.
Nash, D. M., Gilliland, J. A. (2013). Determinants of Diet Quality in Pregnancy: Sociodemographic, Pregnancy-specific, and Food Environment Influences. Journal of Nutrition Education and Behavior, 45(6), 627–634. 2023-04-26.
Norbeck, J. S., & Tilden, V. P. (1983). Life Stress, Social Support, and Emotional Disequilibrium in Complications of Pregnancy: A Prospective, Multivariate Study. Journal of Health and Social Behavior, 24(1), 30.
Ramli, S. H., Rejali, Z., & Dolah, M. S. (2018). VIDEO OBSERVATION FOR DESIGNERS: A CONTEXTUAL IMMERSION OF THE O&G MANNEQUIN IN CLINICAL TRAINING. Alam Cipta, 11(2), 57–61.
Rathnayake, S., Moyle, W., Jones, C., & Calleja, P. (2021). Co-design of an mHealth application for family caregivers of people with dementia to address functional disability care needs. Informatics for Health and Social Care, 46(1), 1–17. 2023-06-24.
Samrgandi, N. (2021). User Interface Design & Evaluation of Mobile Applications. 21.
Vahter, M. (2009). Effects of Arsenic on Maternal and Fetal Health. Annual Review of Nutrition, 29(1), 381–399.
Wirawan, F., Yudhantari, D. G. A., & Gayatri, A. (2023). Pre-pregnancy Diet to Maternal and Child Health Outcome: A Scoping Review of Current Evidence. Journal of Preventive Medicine and Public Health, 56(2), 111–127. 2023-04-26.
Published
2023-09-01
How to Cite
YU, Xinxin et al.
Assessing Fetal Health by Pregnant Women in China Using Mobile Health Application.
International Journal of Business and Technology Management, [S.l.], v. 5, n. 3, p. 79-94, sep. 2023.
ISSN 2682-7646.
Available at: <https://myjms.mohe.gov.my/index.php/ijbtm/article/view/23738>. Date accessed: 06 dec. 2023.
Section
Articles
