NPJ Digital Medicine最新文献_第9页

How might Hospital at Home enable a greener and healthier future? 居家医院如何实现更环保、更健康的未来？

IF 12.4 1区医学

NPJ Digital Medicine Pub Date : 2024-09-16 DOI: 10.1038/s41746-024-01249-8

Dylan Powell, Fanny Burrows, Geraint Lewis, Stephen Gilbert

引用次数: 0

A randomized trial testing digital medicine support models for mild-to-moderate alcohol use disorder 测试轻度至中度酒精使用障碍数字医学支持模式的随机试验

IF 12.4 1区医学

NPJ Digital Medicine Pub Date : 2024-09-14 DOI: 10.1038/s41746-024-01241-2

Andrew Quanbeck, Ming-Yuan Chih, Linda Park, Xiang Li, Qiang Xie, Alice Pulvermacher, Samantha Voelker, Rachel Lundwall, Katherine Eby, Bruce Barrett, Randall Brown

{"title":"A randomized trial testing digital medicine support models for mild-to-moderate alcohol use disorder","authors":"Andrew Quanbeck, Ming-Yuan Chih, Linda Park, Xiang Li, Qiang Xie, Alice Pulvermacher, Samantha Voelker, Rachel Lundwall, Katherine Eby, Bruce Barrett, Randall Brown","doi":"10.1038/s41746-024-01241-2","DOIUrl":"10.1038/s41746-024-01241-2","url":null,"abstract":"This paper reports the results of a hybrid effectiveness-implementation randomized trial that systematically varied levels of human oversight required to support the implementation of a digital medicine intervention for persons with mild-to-moderate alcohol use disorder (AUD). Participants were randomly assigned to three groups representing possible digital health support models within a health system: self-monitored use (SM; n = 185), peer-supported use (PS; n = 186), or a clinically integrated model CI; (n = 187). Across all three groups, the percentage of self-reported heavy drinking days dropped from 38.4% at baseline (95% CI [35.8%, 41%]) to 22.5% (19.5%, 25.5%) at 12 months. The clinically integrated group showed significant improvements in mental health and quality of life compared to the self-monitoring group (p = 0.011). However, higher attrition rates in the clinically integrated group warrant consideration in interpreting this result. Results suggest that making a self-guided digital intervention available to patients may be a viable option for health systems looking to promote alcohol risk reduction. This study was prospectively registered at clinicaltrials.gov on 7/03/2019 (NCT04011644).","PeriodicalId":19349,"journal":{"name":"NPJ Digital Medicine","volume":" ","pages":"1-10"},"PeriodicalIF":12.4,"publicationDate":"2024-09-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.nature.com/articles/s41746-024-01241-2.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142231290","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Variational Bayes machine learning for risk adjustment of general outcome indicators with examples in urology 变异贝叶斯机器学习用于一般结果指标的风险调整，以泌尿外科为例

IF 12.4 1区医学

NPJ Digital Medicine Pub Date : 2024-09-14 DOI: 10.1038/s41746-024-01244-z

Harvey Jia Wei Koh, Dragan Gašević, David Rankin, Stephane Heritier, Mark Frydenberg, Stella Talic

{"title":"Variational Bayes machine learning for risk adjustment of general outcome indicators with examples in urology","authors":"Harvey Jia Wei Koh, Dragan Gašević, David Rankin, Stephane Heritier, Mark Frydenberg, Stella Talic","doi":"10.1038/s41746-024-01244-z","DOIUrl":"10.1038/s41746-024-01244-z","url":null,"abstract":"Risk adjustment is often necessary for outcome quality indicators (QIs) to provide fair and accurate feedback to healthcare professionals. However, traditional risk adjustment models are generally oversimplified and not equipped to disentangle complex factors influencing outcomes that are out of a healthcare professional’s control. We present VIRGO, a novel variational Bayes model trained on routinely collected, large administrative datasets to risk-adjust outcome QIs. VIRGO uses detailed demographics, diagnosis, and procedure codes to provide individualized risk adjustment and explanations on patient factors affecting outcomes. VIRGO achieves state-of-the-art on external datasets and features capabilities of uncertainty expression, explainable features, and counterfactual analysis capabilities. VIRGO facilitates risk adjustment by explaining how patient factors led to adverse outcomes and expresses the uncertainty of each prediction, allowing healthcare professionals to not only explore patient factors with unexplained variance that are associated with worse outcomes but also reflect on the quality of their clinical practice.","PeriodicalId":19349,"journal":{"name":"NPJ Digital Medicine","volume":" ","pages":"1-11"},"PeriodicalIF":12.4,"publicationDate":"2024-09-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.nature.com/articles/s41746-024-01244-z.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142231294","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Can social media encourage diabetes self-screenings? A randomized controlled trial with Indonesian Facebook users 社交媒体能否鼓励糖尿病自我筛查？针对印度尼西亚 Facebook 用户的随机对照试验

IF 12.4 1区医学

NPJ Digital Medicine Pub Date : 2024-09-13 DOI: 10.1038/s41746-024-01246-x

Manuela Fritz, Michael Grimm, Ingmar Weber, Elad Yom-Tov, Benedictus Praditya

{"title":"Can social media encourage diabetes self-screenings? A randomized controlled trial with Indonesian Facebook users","authors":"Manuela Fritz, Michael Grimm, Ingmar Weber, Elad Yom-Tov, Benedictus Praditya","doi":"10.1038/s41746-024-01246-x","DOIUrl":"10.1038/s41746-024-01246-x","url":null,"abstract":"Nudging individuals without obvious symptoms of non-communicable diseases (NCDs) to undergo a health screening remains a challenge, especially in middle-income countries, where NCD awareness is low but the incidence is high. We assess whether an awareness campaign implemented on Facebook can encourage individuals in Indonesia to undergo an online diabetes self-screening. We use Facebook’s advertisement function to randomly distribute graphical ads related to the risk and consequences of diabetes. Depending on their risk score, participants receive a recommendation to undergo a professional screening. We were able to reach almost 300,000 individuals in only three weeks. More than 1400 individuals completed the screening, inducing costs of about US$0.75 per person. The two ads labeled “diabetes consequences” and “shock” outperform all other ads. A follow-up survey shows that many high-risk respondents have scheduled a professional screening. A cost-effectiveness analysis suggests that our campaign can diagnose an additional person with diabetes for about US$9.","PeriodicalId":19349,"journal":{"name":"NPJ Digital Medicine","volume":" ","pages":"1-13"},"PeriodicalIF":12.4,"publicationDate":"2024-09-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.nature.com/articles/s41746-024-01246-x.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142174956","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Long-term changes in wearable sensor data in people with and without Long Covid Long Covid 患者和非 Long Covid 患者的可穿戴传感器数据的长期变化

IF 12.4 1区医学

NPJ Digital Medicine Pub Date : 2024-09-13 DOI: 10.1038/s41746-024-01238-x

Jennifer M. Radin, Julia Moore Vogel, Felipe Delgado, Erin Coughlin, Matteo Gadaleta, Jay A. Pandit, Steven R. Steinhubl

引用次数: 0

Results and implications for generative AI in a large introductory biomedical and health informatics course 大型生物医学和健康信息学入门课程中生成式人工智能的结果和影响

IF 12.4 1区医学

NPJ Digital Medicine Pub Date : 2024-09-13 DOI: 10.1038/s41746-024-01251-0

William Hersh, Kate Fultz Hollis

引用次数: 0

A randomized controlled trial investigating experiential virtual reality communication on prudent antibiotic use 一项随机对照试验，调查虚拟现实体验式传播对谨慎使用抗生素的影响

IF 12.4 1区医学

NPJ Digital Medicine Pub Date : 2024-09-12 DOI: 10.1038/s41746-024-01240-3

Adéla Plechatá, Guido Makransky, Robert Böhm

{"title":"A randomized controlled trial investigating experiential virtual reality communication on prudent antibiotic use","authors":"Adéla Plechatá, Guido Makransky, Robert Böhm","doi":"10.1038/s41746-024-01240-3","DOIUrl":"10.1038/s41746-024-01240-3","url":null,"abstract":"Antimicrobial resistance (AMR) is a global health threat. This randomized controlled trial evaluates the impact of experiential virtual reality (VR) versus information provision via VR or leaflet on prudent antibiotic use. A total of 249 (239 analyzed) participants were randomized into three conditions: VR Information + Experience, VR Information, or Leaflet Information. All participants received AMR information, while those in the VR Information + Experience condition additionally engaged in a game, making treatment decisions for their virtual avatar’s infection. Participants in the VR Information + Experience condition showed a significant increase in prudent use intentions from baseline (d = 1.48). This increase was significantly larger compared to the VR Information (d = 0.50) and Leaflet Information (d = 0.79) conditions. The increase in intentions from baseline remained significant at follow-up in the VR Information + Experience condition (d = 1.25). Experiential VR communication shows promise for promoting prudent antibiotics use.","PeriodicalId":19349,"journal":{"name":"NPJ Digital Medicine","volume":" ","pages":"1-8"},"PeriodicalIF":12.4,"publicationDate":"2024-09-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.nature.com/articles/s41746-024-01240-3.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142170392","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Ethical debates amidst flawed healthcare artificial intelligence metrics 医疗人工智能指标缺陷中的伦理争论

IF 12.4 1区医学

NPJ Digital Medicine Pub Date : 2024-09-11 DOI: 10.1038/s41746-024-01242-1

Jack Gallifant, Danielle S. Bitterman, Leo Anthony Celi, Judy W. Gichoya, Joao Matos, Liam G. McCoy, Robin L. Pierce

引用次数: 0

Understanding activity and physiology at scale: The Apple Heart & Movement Study 大规模了解活动和生理学苹果心脏与运动研究

IF 12.4 1区医学

NPJ Digital Medicine Pub Date : 2024-09-10 DOI: 10.1038/s41746-024-01187-5

James Truslow, Angela Spillane, Huiming Lin, Katherine Cyr, Adeeti Ullal, Edith Arnold, Ron Huang, Laura Rhodes, Jennifer Block, Jamie Stark, James Kretlow, Alexis L. Beatty, Andreas Werdich, Deepali Bankar, Matt Bianchi, Ian Shapiro, Jaime Villalpando, Sharon Ravindran, Irida Mance, Adam Phillips, John Earl, Rahul C. Deo, Sumbul A. Desai, Calum A. MacRae

引用次数: 0

Adherence to non-pharmaceutical interventions following COVID-19 vaccination: a federated cohort study 接种 COVID-19 疫苗后坚持非药物干预措施：联合队列研究

IF 12.4 1区医学

NPJ Digital Medicine Pub Date : 2024-09-10 DOI: 10.1038/s41746-024-01223-4

Benjamin Rader, Neil K. R. Sehgal, Julie Michelman, Stefan Mellem, Marinanicole D. Schultheiss, Tom Hoddes, Jamie MacFarlane, Geoff Clark, Shawn O’Banion, Paul Eastham, Gaurav Tuli, James A. Taylor, John S. Brownstein

{"title":"Adherence to non-pharmaceutical interventions following COVID-19 vaccination: a federated cohort study","authors":"Benjamin Rader, Neil K. R. Sehgal, Julie Michelman, Stefan Mellem, Marinanicole D. Schultheiss, Tom Hoddes, Jamie MacFarlane, Geoff Clark, Shawn O’Banion, Paul Eastham, Gaurav Tuli, James A. Taylor, John S. Brownstein","doi":"10.1038/s41746-024-01223-4","DOIUrl":"10.1038/s41746-024-01223-4","url":null,"abstract":"In pandemic mitigation, strategies such as social distancing and mask-wearing are vital to prevent disease resurgence. Yet, monitoring adherence is challenging, as individuals might be reluctant to share behavioral data with public health authorities. To address this challenge and demonstrate a framework for conducting observational research with sensitive data in a privacy-conscious manner, we employ a privacy-centric epidemiological study design: the federated cohort. This approach leverages recent computational advances to allow for distributed participants to contribute to a prospective, observational research study while maintaining full control of their data. We apply this strategy here to explore pandemic intervention adherence patterns. Participants (n = 3808) were enrolled in our federated cohort via the “Google Health Studies” mobile application. Participants completed weekly surveys and contributed empirically measured mobility data from their Android devices between November 2020 to August 2021. Using federated analytics, differential privacy, and secure aggregation, we analyzed data in five 6-week periods, encompassing the pre- and post-vaccination phases. Our results showed that participants largely utilized non-pharmaceutical intervention strategies until they were fully vaccinated against COVID-19, except for individuals without plans to become vaccinated. Furthermore, this project offers a blueprint for conducting a federated cohort study and engaging in privacy-preserving research during a public health emergency.","PeriodicalId":19349,"journal":{"name":"NPJ Digital Medicine","volume":" ","pages":"1-7"},"PeriodicalIF":12.4,"publicationDate":"2024-09-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.nature.com/articles/s41746-024-01223-4.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142160355","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0