[논문]The Healthy Pregnancy Research Program: transforming pregnancy research through a ResearchKit app

Radin, Jennifer M.; Steinhubl, Steven R.; Su, Andrew I.; Bhargava, Hansa; Greenberg, Benjamin; Bot, Brian M.; Doerr, Megan; Topol, Eric J.

doi:10.1038/s41746-018-0052-2

[해외논문] The Healthy Pregnancy Research Program: transforming pregnancy research through a ResearchKit app 원문보기

npj digital medicine, v.1 no.1, 2018년, pp.45 -

Radin, Jennifer M. , Steinhubl, Steven R. , Su, Andrew I. , Bhargava, Hansa , Greenberg, Benjamin , Bot, Brian M. , Doerr, Megan , Topol, Eric J.

Abstract ▼ AI-Helper

AbstractAlthough maternal morbidity and mortality in the US is among the worst of developed countries, pregnant women have been under-represented in research studies, resulting in deficiencies in evidence-based guidance for treatment. There are over two billion smartphone users worldwide, enabling researchers to easily and cheaply conduct extremely large-scale research studies through smartphone apps, especially among pregnant women in whom app use is exceptionally high, predominantly as an information conduit. We developed the first pregnancy research app that is embedded within an existing, popular pregnancy app for self-management and education of expectant mothers. Through the large-scale and simplified collection of survey and sensor generated data via the app, we aim to improve our understanding of factors that promote a healthy pregnancy for both the mother and developing fetus. From the launch of this cohort study on 16 March 2017 through 17 December 2017, we have enrolled 2058 pregnant women from all 50 states. Our study population is diverse geographically and demographically, and fairly representative of US population averages. We have collected 14,045 individual surveys and 107,102 total daily measurements of sleep, activity, blood pressure, and heart rate during this time. On average, women stayed engaged in the study for 59 days and 45 percent who reached their due date filled out the final outcome survey. During the first 9 months, we demonstrated the potential for a smartphone-based research platform to capture an ever-expanding array of longitudinal, objective, and subjective participant-generated data from a continuously growing and diverse population of pregnant women.

참고문헌 (22)

Nature F Baylis 465 689 2010 10.1038/465689a Baylis, F. Pregnant women deserve better. Nature 465, 689-690 (2010).

상세보기
Nature AM Kim 465 688 2010 10.1038/465688a Kim, A. M., Tingen, C. M. & Woodruff, T. K. Sex bias in trials and treatment must end. Nature 465, 688-689 (2010).

상세보기
10.1038/465665a Putting gender on the agenda. Nature 465,665(2010).

상세보기
Natl. Vital. Stat. Rep. JA Martin 66 1 2017 Martin, J. A., Hamilton, B. E., Osterman, M. J., Driscoll, A. K. & Mathews, T. J. Births: Final data for 2015. Natl. Vital. Stat. Rep. 66, 1 (2017).
GSMA Intelligence. The Mobile Economy, https://www.gsmaintelligence.com/research/download (2017).
United States Census Bureau. 2010 Census Urban and Rural Classification and Urban Area Criteria, https://www.census.gov/geo/reference/ua/urban-rural-2010.html (2010).
Natl. Vital. Stat. Rep. AM Branum 65 1 2016 Branum, A. M., Kirmeyer, S. E. & Gregory, E. C. Prepregnancy body mass index by maternal characteristics and state: Data from the birth certificate, 2014. Natl. Vital. Stat. Rep. 65, 1-11 (2016).
Healthc. Informa Res. Y Lee 22 73 2016 10.4258/hir.2016.22.2.73 Lee, Y., & Moon, M. Utilization and content evaluation of mobile applications for pregnancy, birth, and child care. Healthc. Informa Res. 22, 73-80 (2016).

상세보기
IMS Institute for Healthcare Informatics. Patient Adoption of mHealth: Use, Evidence and Remaining Barriers to Mainstream Acceptance http://static.correofarmaceutico.com/docs/2015/09/21/iihi_patient_adoption_of_mhealth.pdf (2015).
Sci. Data DE Webster 4 2017 10.1038/sdata.2017.5 Webster, D. E. et al. The Mole Mapper Study, mobile phone skin imaging and melanoma risk data collected using ResearchKit. Sci. Data 4, 170005 (2017).

상세보기
JAMA Cardiol. MV McConnell 2 67 2017 10.1001/jamacardio.2016.4395 McConnell, M. V. et al. Feasibility of obtaining measures of lifestyle from a smartphone app: The MyHeart Counts Cardiovascular Health Study. JAMA Cardiol. 2, 67-76 (2017).

상세보기
Nat. Biotechnol. YY Chan 35 354 2017 10.1038/nbt.3826 Chan, Y. Y. et al. The Asthma Mobile Health Study, a large-scale clinical observational study using ResearchKit. Nat. Biotechnol. 35, 354-362, https://doi.org/10.1038/nbt.3826 (2017).

상세보기
Sci. data BM Bot 3 2016 10.1038/sdata.2016.11 Bot, B. M. et al. The mPower study, Parkinson disease mobile data collected using ResearchKit. Sci. data 3, 160011 (2016).

상세보기
Int. J. Epidemiol. E Oken 44 37 2015 10.1093/ije/dyu008 Oken, E. et al. Cohort profile: project viva. Int. J. Epidemiol. 44, 37-48 (2015).

상세보기
Natl. Vital. Stat. Rep. SJ Ventura 47 1 1999 Ventura, S. J., Mosher, W. D., Curtin, S. C., Abma, J. C. & Henshaw, S. Highlights of trends in pregnancies and pregnancy rates by outcome: estimates for the United States, 1976-96. Natl. Vital. Stat. Rep. 47, 1-9 (1999).
PLoS Med. SS Oh 12 2015 10.1371/journal.pmed.1001918 Oh, S. S. et al. Diversity in clinical and biomedical research: A promise yet to be fulfilled. PLoS Med. 12, e1001918 (2015).

상세보기
BMC Pregnancy Childbirth SW McDonald 13 Suppl 1 2013 10.1186/1471-2393-13-S1-S2 McDonald, S. W. et al. The all our babies pregnancy cohort: design, methods, and participant characteristics. BMC Pregnancy Childbirth 13(Suppl 1), S2 (2013).

상세보기
J. R. Soc. Med. J Jardine 108 294 2015 10.1177/0141076815600673 Jardine, J., Fisher, J. & Carrick, B. Apple’s ResearchKit: smart data collection for the smartphone era? J. R. Soc. Med. 108, 294-296 (2015).

상세보기
iTunes. WebMD Pregnancy, https://itunes.apple.com/us/app/webmd-pregnancy/id600535431?mt=8.
Anxiety and Depression Association of America. Facts and Statistics, https://adaa.org/about-adaa/press-room/facts-statistics.
Centers for Disease Control and Prevention. High Blood Pressure Facts, https://www.cdc.gov/bloodpressure/facts.htm.
Biol. Psychiatry JI Hudson 61 348 2007 10.1016/j.biopsych.2006.03.040 Hudson, J. I., Hiripi, E., Pope, H. G. Jr & Kessler, R. C. The prevalence and correlates of eating disorders in the National Comorbidity Survey Replication. Biol. Psychiatry 61, 348-358 (2007).

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