• 文献检索
  • 文档翻译
  • 深度研究
  • 学术资讯
  • Suppr Zotero 插件Zotero 插件
  • 邀请有礼
  • 套餐&价格
  • 历史记录
应用&插件
Suppr Zotero 插件Zotero 插件浏览器插件Mac 客户端Windows 客户端微信小程序
定价
高级版会员购买积分包购买API积分包
服务
文献检索文档翻译深度研究API 文档MCP 服务
关于我们
关于 Suppr公司介绍联系我们用户协议隐私条款
关注我们

Suppr 超能文献

核心技术专利:CN118964589B侵权必究
粤ICP备2023148730 号-1Suppr @ 2026

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验

深入了解孕期变化(BUMP):一项针对从孕前到产后女性的数字可行性研究方案

Better Understanding of the Metamorphosis of Pregnancy (BUMP): protocol for a digital feasibility study in women from preconception to postpartum.

作者信息

Goodday S M, Karlin E, Brooks A, Chapman C, Karlin D R, Foschini L, Kipping E, Wildman M, Francis M, Greenman H, Li Li, Schadt E, Ghassemi M, Goldenberg A, Cormack F, Taptiklis N, Centen C, Smith S, Friend S

机构信息

4YouandMe, Seattle, WA, USA.

Department of Psychiatry, University of Oxford, Oxford, UK.

出版信息

NPJ Digit Med. 2022 Mar 30;5(1):40. doi: 10.1038/s41746-022-00579-9.

DOI:10.1038/s41746-022-00579-9
PMID:35354895
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC8967890/
Abstract

The Better Understanding the Metamorphosis of Pregnancy (BUMP) study is a longitudinal feasibility study aimed to gain a deeper understanding of the pre-pregnancy and pregnancy symptom experience using digital tools. The present paper describes the protocol for the BUMP study. Over 1000 participants are being recruited through a patient provider-platform and through other channels in the United States (US). Participants in a preconception cohort (BUMP-C) are followed for 6 months, or until conception, while participants in a pregnancy cohort (BUMP) are followed into their fourth trimester. Participants are provided with a smart ring, a smartwatch (BUMP only), and a smart scale (BUMP only) alongside cohort-specific study apps. Participant centric engagement strategies are used that aim to co-design the digital approach with participants while providing knowledge and support. The BUMP study is intended to lay the foundational work for a larger study to determine whether participant co-designed digital tools can be used to detect, track and return multimodal symptoms during the perinatal window to inform individual level symptom trajectories.

摘要

更好地理解孕期变化(BUMP)研究是一项纵向可行性研究,旨在通过数字工具更深入地了解孕前和孕期症状体验。本文描述了BUMP研究的方案。目前正在通过患者提供者平台和美国的其他渠道招募1000多名参与者。对孕前队列(BUMP-C)的参与者进行为期6个月的跟踪,或直至怀孕,而对孕期队列(BUMP)的参与者则跟踪至孕晚期。除了特定队列的研究应用程序外,还为参与者提供智能戒指、智能手表(仅适用于BUMP)和智能体重秤(仅适用于BUMP)。采用以参与者为中心的参与策略,旨在与参与者共同设计数字方法,同时提供知识和支持。BUMP研究旨在为一项更大规模的研究奠定基础工作,以确定参与者共同设计的数字工具是否可用于在围产期窗口检测、跟踪和反馈多模式症状,从而了解个体水平的症状轨迹。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8bc3/8967890/f2681b034025/41746_2022_579_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8bc3/8967890/dcea81d497b9/41746_2022_579_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8bc3/8967890/f2681b034025/41746_2022_579_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8bc3/8967890/dcea81d497b9/41746_2022_579_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8bc3/8967890/f2681b034025/41746_2022_579_Fig2_HTML.jpg

相似文献

1
Better Understanding of the Metamorphosis of Pregnancy (BUMP): protocol for a digital feasibility study in women from preconception to postpartum.深入了解孕期变化(BUMP):一项针对从孕前到产后女性的数字可行性研究方案
NPJ Digit Med. 2022 Mar 30;5(1):40. doi: 10.1038/s41746-022-00579-9.
2
Folic acid supplementation and malaria susceptibility and severity among people taking antifolate antimalarial drugs in endemic areas.在流行地区,服用抗叶酸抗疟药物的人群中,叶酸补充剂与疟疾易感性和严重程度的关系。
Cochrane Database Syst Rev. 2022 Feb 1;2(2022):CD014217. doi: 10.1002/14651858.CD014217.
3
Understanding multifactorial influences on the continuum of maternal weight trajectories in pregnancy and early postpartum: study protocol, and participant baseline characteristics.了解孕期和产后早期孕产妇体重轨迹连续体的多因素影响:研究方案及参与者基线特征
BMC Pregnancy Childbirth. 2015 Mar 28;15:71. doi: 10.1186/s12884-015-0490-7.
4
OptimalMe Intervention for Healthy Preconception, Pregnancy, and Postpartum Lifestyles: Protocol for a Randomized Controlled Implementation Effectiveness Feasibility Trial.针对孕前、孕期和产后健康生活方式的OptimalMe干预措施:一项随机对照实施有效性可行性试验方案
JMIR Res Protoc. 2022 Jun 9;11(6):e33625. doi: 10.2196/33625.
5
Leveraging Digital Technology in Conducting Longitudinal Research on Mental Health in Pregnancy: Longitudinal Panel Survey Study.利用数字技术开展孕期心理健康纵向研究:纵向面板调查研究
JMIR Pediatr Parent. 2021 Apr 27;4(2):e16280. doi: 10.2196/16280.
6
Fecundability in relation to use of mobile computing apps to track the menstrual cycle.与使用移动计算应用程序来跟踪月经周期相关的生育能力。
Hum Reprod. 2020 Oct 1;35(10):2245-2252. doi: 10.1093/humrep/deaa176.
7
Use of HIV pre-exposure prophylaxis during the preconception, antepartum and postpartum periods at two United States medical centers.美国两家医疗中心在孕前、产前和产后期间使用艾滋病毒暴露前预防药物的情况。
Am J Obstet Gynecol. 2016 Nov;215(5):632.e1-632.e7. doi: 10.1016/j.ajog.2016.06.020. Epub 2016 Jul 19.
8
Preconception and early pregnancy maternal haemodynamic changes in healthy women in relation to pregnancy viability.健康女性孕前及孕早期母体血流动力学变化与妊娠存活的关系。
Hum Reprod. 2017 May 1;32(5):985-992. doi: 10.1093/humrep/dex050.
9
The MothersBabies Study, an Australian Prospective Cohort Study Analyzing the Microbiome in the Preconception and Perinatal Period to Determine Risk of Adverse Pregnancy, Postpartum, and Child-Related Health Outcomes: Study Protocol.《母婴研究》,澳大利亚前瞻性队列研究,分析围孕期微生物组,以确定不良妊娠、产后和儿童相关健康结局的风险:研究方案。
Int J Environ Res Public Health. 2023 Sep 9;20(18):6736. doi: 10.3390/ijerph20186736.
10
Chorionic Bump: An Early Ultrasound Marker for Adverse Obstetric Outcome.绒毛膜隆起:不良产科结局的早期超声标志物。
Gynecol Obstet Invest. 2019;84(3):237-241. doi: 10.1159/000493477. Epub 2018 Nov 2.

引用本文的文献

1
Adherence to digital pregnancy care - lessons learned from the SMART start feasibility study.坚持数字孕期护理——从SMART start可行性研究中汲取的经验教训。
NPJ Digit Med. 2025 Aug 30;8(1):561. doi: 10.1038/s41746-025-01966-8.
2
Advancing equitable access to innovation in breast cancer.推进乳腺癌创新的公平可及性。
NPJ Breast Cancer. 2025 Jul 10;11(1):71. doi: 10.1038/s41523-025-00768-1.
3
Using Social Media to Engage and Enroll Underrepresented Populations: Longitudinal Digital Health Research.利用社交媒体吸引和招募代表性不足的人群:纵向数字健康研究。

本文引用的文献

1
Exclusively Digital Health Interventions Targeting Diet, Physical Activity, and Weight Gain in Pregnant Women: Systematic Review and Meta-Analysis.专门针对孕妇饮食、身体活动和体重增加的数字健康干预措施:系统评价和荟萃分析。
JMIR Mhealth Uhealth. 2020 Jul 10;8(7):e18255. doi: 10.2196/18255.
2
Acknowledging and Addressing Allostatic Load in Pregnancy Care.承认并解决孕期中的应激负荷问题。
J Racial Ethn Health Disparities. 2021 Feb;8(1):69-79. doi: 10.1007/s40615-020-00757-z. Epub 2020 May 7.
3
Indicators of retention in remote digital health studies: a cross-study evaluation of 100,000 participants.
JMIR Form Res. 2025 Apr 15;9:e68093. doi: 10.2196/68093.
4
Analysis of the Application Value of Low Molecular Weight Heparin Combined with Heparin in Patients with Chorionic Bump in Early Pregnancy.低分子肝素联合肝素在早孕期绒毛下血肿患者中的应用价值分析
Int J Womens Health. 2025 Apr 7;17:973-982. doi: 10.2147/IJWH.S507845. eCollection 2025.
5
Deep learning model using continuous skin temperature data predicts labor onset.利用连续皮肤温度数据的深度学习模型预测分娩开始。
BMC Pregnancy Childbirth. 2024 Nov 25;24(1):777. doi: 10.1186/s12884-024-06862-9.
6
Shaping Adoption and Sustained Use Across the Maternal Journey: Qualitative Study on Perceived Usability and Credibility in Digital Health Tools.塑造母婴全程中的采用和持续使用:数字健康工具感知可用性和可信度的定性研究。
JMIR Hum Factors. 2024 Oct 1;11:e59269. doi: 10.2196/59269.
7
Value of Engagement in Digital Health Technology Research: Evidence Across 6 Unique Cohort Studies.参与数字健康技术研究的价值:6 项独特队列研究的证据。
J Med Internet Res. 2024 Sep 3;26:e57827. doi: 10.2196/57827.
8
A Comprehensive Review of the Role of Artificial Intelligence in Obstetrics and Gynecology.人工智能在妇产科领域作用的全面综述
Cureus. 2023 Feb 12;15(2):e34891. doi: 10.7759/cureus.34891. eCollection 2023 Feb.
9
The Post-Roe Political Landscape Demands a Morality of Caution for Women's Health.后罗伊时代的政治格局要求谨慎行事,以维护女性健康的道德底线。
J Med Internet Res. 2022 Oct 20;24(10):e41417. doi: 10.2196/41417.
远程数字健康研究中的留存指标:对10万名参与者的跨研究评估
NPJ Digit Med. 2020 Feb 17;3:21. doi: 10.1038/s41746-020-0224-8. eCollection 2020.
4
Economic burden of maternal morbidity - A systematic review of cost-of-illness studies.产妇发病率的经济负担 - 疾病成本研究的系统评价。
PLoS One. 2020 Jan 16;15(1):e0227377. doi: 10.1371/journal.pone.0227377. eCollection 2020.
5
Exploring the validity of allostatic load in pregnant women.探讨孕妇应激负荷的有效性。
Midwifery. 2020 Mar;82:102621. doi: 10.1016/j.midw.2019.102621. Epub 2019 Dec 28.
6
Wearable Technology for High-Frequency Cognitive and Mood Assessment in Major Depressive Disorder: Longitudinal Observational Study.用于重度抑郁症高频认知和情绪评估的可穿戴技术:纵向观察研究
JMIR Ment Health. 2019 Nov 18;6(11):e12814. doi: 10.2196/12814.
7
Unlocking stress and forecasting its consequences with digital technology.利用数字技术揭示压力并预测其后果。
NPJ Digit Med. 2019 Jul 31;2:75. doi: 10.1038/s41746-019-0151-8. eCollection 2019.
8
The REDCap consortium: Building an international community of software platform partners.REDCap 联盟:构建软件平台合作伙伴的国际社区。
J Biomed Inform. 2019 Jul;95:103208. doi: 10.1016/j.jbi.2019.103208. Epub 2019 May 9.
9
Role of maternal age and pregnancy history in risk of miscarriage: prospective register based study.母亲年龄和妊娠史与流产风险的关系:前瞻性基于登记的研究。
BMJ. 2019 Mar 20;364:l869. doi: 10.1136/bmj.l869.
10
Dr.VAE: improving drug response prediction via modeling of drug perturbation effects.VAE 博士:通过建模药物干扰效应来改善药物反应预测。
Bioinformatics. 2019 Oct 1;35(19):3743-3751. doi: 10.1093/bioinformatics/btz158.