Mayo Clinic Proceedings. Digital health最新文献_第8页

Using Social Media to Combat Influenza Vaccine Misinformation and Improve Uptake: A Social Media Campaign and Repeated Cross-sectional Survey Analysis 利用社交媒体打击流感疫苗错误信息并提高吸收：社交媒体活动和重复横断面调查分析

Mayo Clinic Proceedings. Digital health

Pub Date : 2025-05-23 DOI: 10.1016/j.mcpdig.2025.100229

Jessica B. Steier DrPH

Objective

To combat influenza (flu)-vaccine misinformation and improve vaccine uptake using social media.

Patients and Methods

Unbiased Science used an online survey to identify flu vaccine-hesitant demographic groups and their specific objections to vaccination. Targeted educational content was then created and deployed through a variety of media formats, including podcasts, newsletters, reels, and infographics. A postcampaign survey determined the proportion of individuals who changed their minds about vaccination as a result of the educational content. The study was conducted between October 28, 2022 and February 7, 2023.

Results

In 3626 precampaign surveys, 187 individuals (5.1%) reported being unvaccinated and not planning to get the flu vaccine (the unvaccinated group). Multivariable analysis showed that geographic region (Northeast and Southeast), gender identity (male and other), race–ethnicity (non-Hispanic Black, and non-Hispanic other), and education level (high-school or less and some college) were independently associated with being unvaccinated. The main reasons were needlephobia, dismissal of flu severity, and concerns about vaccine components, multiple vaccines, and side effects. In 838 postcampaign surveys, 39 individuals (4.7%) indicated changing their mind about vaccination: of these, 27 (69.2%) said they were more likely to get vaccinated and 22 (56.4%) had gotten vaccinated. Twenty individuals (51.3%) said they changed their mind at least in part because of the targeted educational content.

Conclusion

Social media has the potential to change attitudes and behaviors around vaccination. When science messaging is deployed across several platforms and targeted to key demographic characteristics, it has the ability to combat misinformation and influence vaccine uptake.

目的利用社交媒体打击流感（流感）疫苗的错误信息，提高疫苗的吸收率。患者和方法sunbiased Science使用了一项在线调查来确定流感疫苗犹豫不决的人口群体和他们对疫苗接种的具体反对意见。然后通过各种媒体格式创建和部署有针对性的教育内容，包括播客、时事通讯、卷轴和信息图表。一项运动后的调查确定了由于教育内容而改变对疫苗接种看法的个人比例。该研究于2022年10月28日至2023年2月7日进行。结果在3626次运动前调查中，187人（5.1%）报告未接种疫苗且不打算接种流感疫苗（未接种组）。多变量分析显示，地理区域（东北和东南）、性别认同（男性和其他）、种族（非西班牙裔黑人和非西班牙裔其他）和教育水平（高中以下和一些大学）与未接种疫苗独立相关。主要原因是针恐惧症、对流感严重程度的忽视、对疫苗成分、多种疫苗和副作用的担忧。在838项运动后调查中，39人（4.7%）表示改变了他们对疫苗接种的看法：其中27人（69.2%）表示他们更有可能接种疫苗，22人（56.4%）接种了疫苗。20人（51.3%）表示，他们至少在一定程度上是因为有针对性的教育内容而改变了主意。结论社交媒体有可能改变人们对疫苗接种的态度和行为。当科学信息在多个平台上部署并针对关键人口特征时，它就有能力打击错误信息并影响疫苗的吸收。

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引用次数: 0

A Model for Rapid Innovation for Engagement, Enrollment, and Data and Sample Collection in a Diverse Cohort Study: Insights from All of Us Participant Labs 在不同队列研究中，参与、注册、数据和样本收集的快速创新模型：来自我们所有参与者实验室的见解

Mayo Clinic Proceedings. Digital health

Pub Date : 2025-05-21 DOI: 10.1016/j.mcpdig.2025.100227

Janna Ter Meer PhD , Jessica Chen BS , Romina Foster-Bonds MHS , Andrea Goosen RN , Gayle Valensky MPH , Ethan Dinh-Luong BS , Rachele Peterson MBA , Geoffrey Ginsburg MD, PhD , Chris Lunt BS , Vik Kheterpal MD , Eric Topol MD , Allison Mandich MS , Yentram Huyen PhD , Julia Moore Vogel PhD

Objective

To improve engagement and retention of a cohort that reflects the US population within the All of Us Research Program, we created and implemented an innovation infrastructure and initiatives.

Participants and Methods

All of Us participant laboratories (APLs) established innovation-specific processes to rapidly ideate, select, implement, and evaluate cost-effective innovative initiatives, while mitigating risks. This was done within 4 priority areas: accelerating enrollment, enhancing engagement and retention, improving biospecimen collection, and broadening data types. Participants within the All of Us Research Program were engaged in this research between April 6, 2022 and May 6, 2024.

Results

We present a summary of APL processes and portfolio along with 5 specific initiatives that rapidly tested innovative ways to increase task completion and broaden biospecimen submission accessibility. Each initiative’s cost–benefit profile was evaluated by a committee of program leadership. Findings include the following: (1) offering compensation increased task completion, the degree of which was dependent on the context and amount of compensation; and (2) adding evening and weekend blood donation appointment times and distributing saliva collection kits through community partners increased donations from participants who have been historically underrepresented in biomedical research. On average, program staff predicted initiative effect sizes would be more than double their actual effect.

Conclusion

We found that large research studies can rapidly innovate to meet program goals, including a focus on diversity. We identified specific strategies and tactics to improve health research engagement and retention, with a focus on historically underrepresented in biomedical research communities, which can be used by numerous health research studies.

为了提高“我们所有人”研究项目中反映美国人口的群体的参与度和保留率，我们创建并实施了一个创新基础设施和倡议。参与者和方法我们所有的参与者实验室（api）都建立了特定于创新的流程，以快速构思、选择、实施和评估具有成本效益的创新举措，同时降低风险。这是在4个优先领域内完成的：加速注册、加强参与和保留、改进生物标本收集和扩大数据类型。“我们所有人”研究项目的参与者在2022年4月6日至2024年5月6日期间参与了这项研究。我们总结了APL的流程和组合，以及5个具体的举措，这些举措快速测试了创新的方法，以增加任务完成和扩大生物标本提交的可及性。每个项目的成本-收益概况由一个项目领导委员会评估。研究发现：(1)提供薪酬提高了任务完成度，其程度取决于薪酬的背景和金额；(2)增加晚间和周末献血预约时间，并通过社区合作伙伴分发唾液采集试剂盒，增加了生物医学研究中历史上代表性不足的参与者的献血。平均而言，项目人员预测的主动性效果大小将是实际效果的两倍以上。我们发现大型研究可以快速创新以满足项目目标，包括对多样性的关注。我们确定了具体的战略和策略，以提高健康研究的参与和保留，重点放在历史上代表性不足的生物医学研究界，这可以用于许多健康研究。

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引用次数: 0

Much More Than the Malady: The Promise of a Web-Based Digital Platform Incorporating Self-Report for Research and Clinical Care in Mild Cognitive Impairment 不仅仅是疾病：一个基于网络的数字平台的承诺，将自我报告纳入轻度认知障碍的研究和临床护理

Mayo Clinic Proceedings. Digital health

Pub Date : 2025-05-06 DOI: 10.1016/j.mcpdig.2025.100224

Andrew McGarry MD , Oliver Roesler PhD , Jackson Liscombe PhD , Michael Neumann PhD , Hardik Kothare PhD , Abhishek Hosamath MBM , Lakshmi Arbatti MS , Anusha Badathala MD , Stephen Ruhmel BS, MPH , Bryan J. Hansen PhD , Madeline Quall BA , Sandrine Istas MBio , Arthur Wallace MD, PhD , David Suendermann-Oeft PhD , Vikram Ramanarayanan PhD , Ira Shoulson MD

Traditional clinical trials in neurodegenerative disorders have utilized combinations of examination-based outcomes, global assessments by investigators and participants, and scales aimed at function, some of which are patient-reported outcomes. It is debatable whether these tools optimally convey therapeutic efficacy. A complementary approach using digital biomarkers to surpass exam-based limitations for detecting physical change coupled with a direct report from participants on what their sources of suffering are could be a useful advance in reporting beneficial effects of interventions, particularly if changes track together. We sought to determine the feasibility of remotely assessing speech, facial features, and cognition in an mild cognitive impairment (MCI) population, whether those extracted features could distinguish MCI from controls, and to explore what self-reported problems could reveal about the MCI experience. Our web-based platform was easy to use and revealed facial features in particular as capable of discriminating MCI from controls. Using the features that showed a statistically significant difference between cohorts (P<.01) produced an area under the receiver operating curve of 0.75. Self-reported problems with cognition, gait, sleep, and behavior were more common in the MCI group. The MCI was associated with 6 times more difficulty with falls (n=6 vs 1). These data support the feasibility and discriminative utility of using remote monitoring technology in combination with participant self-report in an MCI population. Future work will investigate the extent to which multimodal biomarkers combined with self-report can characterize MCI longitudinally and for potential research applications as a measure of therapeutic effect.

神经退行性疾病的传统临床试验结合了基于检查的结果、研究者和参与者的整体评估以及针对功能的量表，其中一些是患者报告的结果。这些工具是否能最佳地传达治疗效果尚存争议。利用数字生物标志物超越基于检查的身体变化检测限制的补充方法，再加上参与者直接报告他们的痛苦来源，可能是报告干预措施有益效果的有用进步，特别是如果变化是一起跟踪的。我们试图确定远程评估轻度认知障碍（MCI）人群的语音、面部特征和认知的可行性，这些提取的特征是否可以将MCI与对照组区分开来，并探索自我报告的问题可以揭示MCI体验的哪些方面。我们的基于网络的平台易于使用，并揭示了面部特征，特别是能够区分MCI和控制。使用显示队列间有统计学显著差异的特征（P< 0.01）产生接受者工作曲线下的面积为0.75。自我报告的认知、步态、睡眠和行为问题在轻度认知障碍组中更为常见。MCI与6倍以上的跌倒困难相关（n=6 vs 1）。这些数据支持在MCI人群中使用远程监测技术与参与者自我报告相结合的可行性和判别效用。未来的工作将研究多模式生物标志物结合自我报告在多大程度上可以纵向表征MCI，并作为治疗效果的衡量标准进行潜在的研究应用。

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引用次数: 0

Exploring Evaluation of eHealth Lifestyle Interventions for Preschool Children: A Scoping Review 学龄前儿童电子健康生活方式干预的评估：范围综述

Mayo Clinic Proceedings. Digital health

Pub Date : 2025-04-17 DOI: 10.1016/j.mcpdig.2025.100223

Marissa C.J. Kooij MD , Ashley J.P. Smit MSc , Linda D. Breeman PhD , Lieke Schiphof-Godart PhD , Isra Al-Dhahir MSc , Andrea W.M. Evers PhD , Koen F.M. Joosten MD, PhD

EHealth lifestyle interventions can promote positive lifestyle changes in preschool children, but they need to be evaluated to assess their effectiveness and identify areas for improvement. This scoping review aimed to examine evaluation methods, outcome measures, and methodologic strengths and weaknesses, to provide recommendations for the evaluation of eHealth lifestyle interventions for preschool children. A comprehensive literature search was conducted across 6 databases for articles published up to September 29, 2023. We identified 48 articles describing 31 interventions that met our predefined eligibility criteria. These interventions predominantly targeted children’s diet. The most frequently evaluated outcomes were effectiveness, acceptability, and usage. Effectiveness outcomes included, among others, dietary intake, anthropometrics, and child and parental behaviors. Acceptability was evaluated primarily as user satisfaction. Evaluation methods for effectiveness and acceptability included questionnaires, interviews, focus groups, and portable devices. Intervention usage was evaluated via logged use and self-reported data. On the basis of our findings, we present recommendations for future evaluation of eHealth interventions for preschool children. These recommendations focus on selecting relevant outcome measures and appropriate evaluation methods and on integrating and applying evaluation results.

电子健康生活方式干预措施可以促进学龄前儿童积极的生活方式改变，但需要对其进行评估，以评估其有效性并确定需要改进的领域。本综述旨在检查评估方法、结果测量和方法学的优缺点，为评估学龄前儿童的电子健康生活方式干预措施提供建议。对截至2023年9月29日发表的6个数据库进行了全面的文献检索。我们确定了48篇文章，描述了31项干预措施，符合我们预定义的资格标准。这些干预措施主要针对儿童的饮食。最常评估的结果是有效性、可接受性和使用率。有效性结果包括饮食摄入、人体测量、儿童和父母行为等。可接受性主要以用户满意度来评估。评估有效性和可接受性的方法包括问卷调查、访谈、焦点小组和便携式设备。通过记录使用情况和自我报告数据来评估干预措施的使用情况。基于我们的研究结果，我们提出了未来评估学龄前儿童电子健康干预措施的建议。这些建议的重点是选择有关的结果措施和适当的评价方法，以及综合和应用评价结果。

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引用次数: 0

Validation Study on Iatrogenic Nerve Damage Reduction Using Augmented Reality on Elbow Phantom 增强现实技术在医源性神经损伤修复中的应用研究

Mayo Clinic Proceedings. Digital health

Pub Date : 2025-04-16 DOI: 10.1016/j.mcpdig.2025.100221

Giacomo Riberi MD , Antonio Cangelosi MSc , Paolo Titolo MD , Elisa Dutto MD , Massimo Salvi PhD , Filippo Molinari PhD , Luca Ulrich PhD , Marco Agus PhD , Corrado Calì PhD

Objective

To compare augmented reality (AR) and classical intraoperative C-arm surgical navigation and evaluate whether head-mounted display improves surgical accuracy in the placement of a rod-like object, such as K-wire, using an anatomically accurate elbow phantom.

Participants and Methods

Data were collected between January 10, 2024, and March 15, 2024. We developed an AR system, X-ray simulation system and surgical phantom to test K-wire placement in 3 locations of the distal humerus and proximal ulnar bones. An initial phase with only X-ray as guidance was performed as case control; in later phases, the candidates were allowed to also use the head-mounted display. The evaluation parameters were time, placement angle, number of X-ray images taken, number of attempts, and distance from anatomical structures.

Results

In total, 19 physicians participated in the study. We analyzed 193 K-wire placements attempts that resulted in 150 estimated correct positions. This reflects a real-world scenario where multiple placements might be attempted to correctly place a K-wire. Compared with standard procedure, the use of AR resulted in −53.8 seconds in K-wire placement time, −47% of angular error from the K-wire target, −80% X-ray images taken to reach the estimate correct position, and decrease in distance variability of −81%, of the K-wire from anatomical structures of interest.

Conclusions

Compared with C-arm, AR navigation improved time, and angle of placement, requiring less X-ray images.

目的比较增强现实（AR）与传统的术中c臂手术导航，并评估头戴式显示器是否能提高手术准确性，使用解剖学上准确的肘关节假体放置棒状物体（如k线）。参与者和方法数据收集于2024年1月10日至2024年3月15日。我们开发了AR系统、x射线模拟系统和手术假体来测试在肱骨远端和尺骨近端3个位置放置k -丝。初始阶段仅以x射线为指导，作为病例控制；在后期阶段，候选人也被允许使用头戴式显示器。评价参数为时间、放置角度、x线影像拍摄次数、尝试次数、距离解剖结构的距离。结果共19名医生参与研究。我们分析了193次k线放置尝试，产生了150个估计正确的位置。这反映了一个现实世界的场景，在这个场景中，可能会尝试多种位置来正确放置k线。与标准方法相比，AR的使用导致k线放置时间缩短- 53.8秒，k线目标的角度误差减少- 47%，达到估计正确位置的x射线图像减少- 80%，k线与感兴趣解剖结构的距离变化减少- 81%。结论与c臂相比，AR导航缩短了放置时间，改善了放置角度，减少了x线图像需求。

{"title":"Validation Study on Iatrogenic Nerve Damage Reduction Using Augmented Reality on Elbow Phantom","authors":"Giacomo Riberi MD , Antonio Cangelosi MSc , Paolo Titolo MD , Elisa Dutto MD , Massimo Salvi PhD , Filippo Molinari PhD , Luca Ulrich PhD , Marco Agus PhD , Corrado Calì PhD","doi":"10.1016/j.mcpdig.2025.100221","DOIUrl":"10.1016/j.mcpdig.2025.100221","url":null,"abstract":"<div><h3>Objective</h3><div>To compare augmented reality (AR) and classical intraoperative C-arm surgical navigation and evaluate whether head-mounted display improves surgical accuracy in the placement of a rod-like object, such as K-wire, using an anatomically accurate elbow phantom.</div></div><div><h3>Participants and Methods</h3><div>Data were collected between January 10, 2024, and March 15, 2024. We developed an AR system, X-ray simulation system and surgical phantom to test K-wire placement in 3 locations of the distal humerus and proximal ulnar bones. An initial phase with only X-ray as guidance was performed as case control; in later phases, the candidates were allowed to also use the head-mounted display. The evaluation parameters were time, placement angle, number of X-ray images taken, number of attempts, and distance from anatomical structures.</div></div><div><h3>Results</h3><div>In total, 19 physicians participated in the study. We analyzed 193 K-wire placements attempts that resulted in 150 estimated correct positions. This reflects a real-world scenario where multiple placements might be attempted to correctly place a K-wire. Compared with standard procedure, the use of AR resulted in −53.8 seconds in K-wire placement time, −47% of angular error from the K-wire target, −80% X-ray images taken to reach the estimate correct position, and decrease in distance variability of −81%, of the K-wire from anatomical structures of interest.</div></div><div><h3>Conclusions</h3><div>Compared with C-arm, AR navigation improved time, and angle of placement, requiring less X-ray images.</div></div>","PeriodicalId":74127,"journal":{"name":"Mayo Clinic Proceedings. Digital health","volume":"3 2","pages":"Article 100221"},"PeriodicalIF":0.0,"publicationDate":"2025-04-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143942075","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Optimizing Digital Management of Research and Collaboration With Academic Information Manager 利用学术信息管理优化研究与合作的数字化管理

Mayo Clinic Proceedings. Digital health

Pub Date : 2025-04-16 DOI: 10.1016/j.mcpdig.2025.100222

Peyman Nejat MD , Vitali Fedosov MD, PhD , Chady Meroueh MD , Hugo Botha MB, ChB , Svetlana Herasevich MD, MS , Ing Tiong MS, MA , David Martin MD, PhD , Brian W. Pickering MD, MS , Vitaly Herasevich MD, PhD

Objective

To evaluate the efficacy, efficiency, and usability of the current iteration of the fully automatic Academic Information Manager (AIM) within the Department of Anesthesiology and Perioperative Medicine.

Participants and Methods

AIM was designed, developed, and deployed to address the growing need for digital information management in academic research. In a randomized, unblinded crossover study from April 1, 2020 to August 1, 2020, 15 participants completed 8 tasks using both AIM and conventional information retrieval methods. We assessed task completion time (efficiency), task completion status and accuracy (efficacy), subjective mental workload using the National Aeronautics and Space Administration Task Load Index (NASA-TLX), and system usability using System Usability Scale questionnaire, with and without AIM.

Results

Using AIM resulted in a significant time saving, with significantly higher task completion (99% vs 57%) and accuracy (99% vs 59%) compared with conventional methods. The NASA-TLX scores with AIM showed a statistically significant decrease in mental demand, temporal demand, effort, and frustration, along with an increase in performance, compared with those without AIM. The System Usability Scale score for AIM was above the 90th percentile.

Conclusion

Using AIM, we observed a significant increase in efficacy and efficiency, along with a decreased mental workload, as measured by NASA-TLX, and improved usability scores. Implementing AIM will help new investigators quickly and intuitively identify ongoing research at our institution. It will also enable them to broadcast their research interests to find potential collaborators.

目的评价麻醉与围手术期医学部现有全自动学术信息管理系统（AIM）的有效性、效率和可用性。saim的设计、开发和部署是为了满足学术研究中对数字信息管理日益增长的需求。在2020年4月1日至2020年8月1日的随机、非盲交叉研究中，15名参与者分别使用AIM和传统信息检索方法完成8项任务。我们评估了任务完成时间（效率）、任务完成状态和准确性（功效）、主观心理负荷（美国国家航空航天局任务负荷指数（NASA-TLX））和系统可用性（系统可用性量表）问卷，分别使用和不使用AIM。结果与常规方法相比，使用AIM可显著节省时间，任务完成率（99% vs 57%）和准确率（99% vs 59%）均显著提高。与没有AIM的人相比，有AIM的NASA-TLX分数在精神需求、时间需求、努力和挫败感方面都有统计学上的显著下降，同时表现也有所提高。AIM的系统可用性量表得分高于90个百分位数。使用AIM，我们观察到疗效和效率显著提高，同时减少了NASA-TLX测量的精神工作量，并提高了可用性分数。实施AIM将帮助新的研究人员快速直观地识别我们机构正在进行的研究。它还将使他们能够传播自己的研究兴趣，以寻找潜在的合作者。

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引用次数: 0

InfoKids+: A Validation Study of a Pediatric Acuity Risk Stratification Algorithm InfoKids+：一项儿科急性风险分层算法的验证研究

Mayo Clinic Proceedings. Digital health

Pub Date : 2025-04-15 DOI: 10.1016/j.mcpdig.2025.100220

Carl A. Starvaggi MD , Sophie Affentranger MMed , Noelie Lengeler MMed , Johan N. Siebert MD , Annick Galetto-Lacour MD , Rainer Tan PhD , Manon Jaboyedoff MD , Claudia E. Kuehni MD , Mary-Anne Hartley PhD , Kristina Keitel PhD

Objective

To prospectively validate InfoKids+, a pediatric acuity electronic risk stratification algorithm (eRSA), against a nurse-based triage standard (nbTS).

Participants and Methods

We conducted a prospective validation study in a Swiss university hospital pediatric emergency department to assess the performance of a pediatric acuity eRSA, InfoKids+, on the basis of a well-established parental guidance application, InfoKids. Participants completed the eRSA once seated in a consultation booth. We compared the acuity levels from InfoKids+ (urgent, <4 hours; nonurgent, <24 hours; and no emergency, ≥24 hours) against an nbTS. The primary outcome was the level of agreement and rate of alignment between InfoKids+ and the reference standard.

Results

We included 1990 participants from June 3, 2020, through January 31, 2022. InfoKids+ showed a slight level of agreement with the nbTS (κ_lw=0.08; 95% CI, 0.06-0.10). InfoKids+ triaged 1762 (89%) cases as urgent (<4 hours), 106 (5%) as nonurgent (≤24 hours), and 122 (6%) as no emergency (≥24 hours), compared with 810 (41%), 843 (42%), and 337 (17%) triages by the nbTS, respectively (P<.001). InfoKids+ acuity level aligned with the reference standard in 888 (45%) cases, whereas it overreferred and underreferred in 999 (50%) and 103 (5%) cases, respectively (P<.001).

Conclusion

In summary, our study uncovered notable discrepancies between the InfoKids+ algorithmic triage and conventional nurse-based triage. Our results highlight the critical need for rigorous validation of such tools for accuracy and safety before public release to ensure these tools are beneficial and do not inadvertently cause harm or misallocation of resources.

目的针对基于护士的分诊标准（nbTS），对儿童急症电子风险分层算法（eRSA） InfoKids+进行前瞻性验证。参与者和方法我们在瑞士一所大学医院的儿科急诊科进行了一项前瞻性验证研究，在完善的家长指导应用程序InfoKids的基础上，评估儿童视力eRSA （InfoKids+）的性能。参与者坐在咨询台后完成eRSA。我们比较了InfoKids+(紧急，4小时；非紧急，24小时；无紧急情况，≥24小时)。主要结果是InfoKids+与参考标准之间的一致性水平和一致性率。从2020年6月3日到2022年1月31日，我们纳入了1990名参与者。InfoKids+与nbTS略有一致(κlw=0.08；95% ci, 0.06-0.10)。InfoKids+将1762例（89%）病例分类为紧急（4小时），106例（5%）为非紧急（≤24小时），122例（6%）为无紧急（≥24小时），而nbTS分别为810例（41%），843例（42%）和337例（17%）（P< 001）。在888例（45%）病例中，InfoKids+视力水平符合参考标准，而在999例（50%）和103例（5%）病例中，InfoKids+视力水平过高和过低（P<.001）。总之，我们的研究揭示了InfoKids+算法分诊与传统护士分诊之间的显著差异。我们的结果强调了在公开发布之前对这些工具的准确性和安全性进行严格验证的关键需求，以确保这些工具是有益的，不会无意中造成伤害或资源分配不当。

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引用次数: 0

Gender Disparities in Artificial Intelligence–Generated Images of Hospital Leadership in the United States 美国人工智能生成的医院领导图像中的性别差异

Mayo Clinic Proceedings. Digital health

Pub Date : 2025-04-08 DOI: 10.1016/j.mcpdig.2025.100218

Mia Gisselbaek MD , Joana Berger-Estilita MD, PhD , Laurens Minsart MD , Ekin Köselerli MD , Arnout Devos PhD , Francisco Maio Matos PhD , Odmara L. Barreto Chang MD, PhD , Peter Dieckmann PhD , Melanie Suppan MD , Sarah Saxena MD, PhD

Objective

To evaluate demographic representation in artificial intelligence (AI)–generated images of hospital leadership roles and compare them with real-world data from US hospitals.

Patients and Methods

This cross-sectional study, conducted from October 1, 2024 to October 31, 2024, analyzed images generated by 3 AI text-to-image models: Midjourney 6.0, OpenAI ChatGPT DALL-E 3, and Google Gemini Imagen 3. Standardized prompts were used to create 1200 images representing 4 key leadership roles: chief executive officers, chief medical officers, chief nursing officers, and chief financial officers. Real-world demographic data from 4397 US hospitals showed that chief executive officers were 73.2% men; chief financial officers, 65.2% men; chief medical officers, 85.7% men; and chief nursing officers, 9.4% men (overall: 60.1% men). The primary outcome was gender representation, with secondary outcomes including race/ethnicity and age. Two independent reviewers assessed images, with interrater reliability evaluated using Cohen κ.

Results

Interrater agreement was high for gender (κ=0.998) and moderate for race/ethnicity (κ=0.670) and age (κ=0.605). DALL-E overrepresented men (86.5%) and White individuals (94.5%). Midjourney showed improved gender balance (69.5% men) but overrepresented White individuals (75.0%). Imagen achieved near gender parity (50.3% men) but remained predominantly White (51.5%). Statistically significant differences were observed across models and between models and real-world demographics.

Conclusion

Artificial intelligence text-to-image models reflect and amplify systemic biases, overrepresenting men and White leaders, while underrepresenting diversity. Ethical AI practices, including diverse training data sets and fairness-aware algorithms, are essential to ensure equitable representation in health care leadership.

目的评估人工智能（AI）生成的医院领导角色图像中的人口统计学代表性，并将其与来自美国医院的真实数据进行比较。患者和方法本横断面研究于2024年10月1日至2024年10月31日进行，分析了3种AI文本到图像模型生成的图像：Midjourney 6.0、OpenAI ChatGPT DALL-E 3和谷歌Gemini Imagen 3。使用标准化提示创建了1200个代表4个关键领导角色的图像：首席执行官、首席医疗官、首席护理官和首席财务官。来自美国4397家医院的真实人口统计数据显示，首席执行官中有73.2%是男性；首席财务官中，男性占65.2%；首席医务官，85.7%为男性；首席护理官中，9.4%是男性（总体：60.1%是男性）。主要结果是性别代表性，次要结果包括种族/民族和年龄。两名独立审稿人对图像进行评估，使用Cohen κ评估图像间信度。结果性别间的一致性较高（κ=0.998），种族/民族间的一致性中等（κ=0.670），年龄间的一致性中等（κ=0.605）。DALL-E在男性（86.5%）和白人（94.5%）中比例过高。中期显示性别平衡有所改善（69.5%为男性），但白人个体比例过高（75.0%）。Imagen几乎实现了性别平等（50.3%的男性），但仍以白人为主（51.5%）。在模型之间以及模型与现实世界人口统计数据之间观察到统计学上的显著差异。人工智能文本到图像模型反映并放大了系统性偏见，过度代表男性和白人领导者，而低估了多样性。道德人工智能实践，包括各种训练数据集和公平意识算法，对于确保卫生保健领导层的公平代表性至关重要。

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引用次数: 0

Erratum to “Impact of Ambient Artificial Intelligence Documentation on Cognitive Load” “环境人工智能文档对认知负荷的影响”的勘误

Mayo Clinic Proceedings. Digital health

Pub Date : 2025-04-04 DOI: 10.1016/j.mcpdig.2025.100219

引用次数: 0

Quantifying the Unknowns of Plaque Morphology: The Role of Topological Uncertainty in Coronary Artery Disease 量化未知斑块形态：拓扑不确定性在冠状动脉疾病中的作用

Mayo Clinic Proceedings. Digital health

Pub Date : 2025-03-28 DOI: 10.1016/j.mcpdig.2025.100217

Yashbir Singh ME, PhD , Quincy A. Hathaway MD, PhD , Karthik Dinakar PhD , Leslee J. Shaw PhD , Bradley Erickson MD, PhD , Francisco Lopez-Jimenez MD, MBA, MSc , Deepak L. Bhatt MD, MPH, MBA

This article aimed to explore topological uncertainty in medical imaging, particularly in assessing coronary artery calcification using artificial intelligence (AI). Topological uncertainty refers to ambiguities in spatial and structural characteristics of medical features, which can impact the interpretation of coronary plaques. The article discusses the challenges of integrating AI with topological considerations and the need for specialized methodologies beyond traditional performance metrics. It highlights advancements in quantifying topological uncertainty, including the use of persistent homology and topological data analysis techniques. The importance of standardization in methodologies and ethical considerations in AI deployment are emphasized. It also outlines various types of uncertainty in topological frameworks for coronary plaques, categorizing them as quantifiable and controllable or quantifiable and not controllable. Future directions include developing AI algorithms that incorporate topological insights, establishing standardized protocols, and exploring ethical implications to revolutionize cardiovascular care through personalized treatment plans guided by sophisticated topological analysis. Recognizing and quantifying topological uncertainty in medical imaging as AI emerges is critical. Exploring topological uncertainty in coronary artery disease will revolutionize cardiovascular care, promising enhanced precision and personalization in diagnostics and treatment for millions affected by cardiovascular diseases.

本文旨在探讨医学成像中的拓扑不确定性，特别是使用人工智能（AI）评估冠状动脉钙化。拓扑不确定性是指医学特征的空间和结构特征的模糊性，这可能影响冠状动脉斑块的解释。本文讨论了将人工智能与拓扑因素集成的挑战，以及对传统性能指标之外的专门方法的需求。它强调了量化拓扑不确定性的进展，包括使用持久同调和拓扑数据分析技术。强调了人工智能部署中方法标准化和伦理考虑的重要性。它还概述了冠状动脉斑块拓扑框架中的各种类型的不确定性，将其分类为可量化和可控或可量化和不可控制。未来的方向包括开发包含拓扑洞察的人工智能算法，建立标准化协议，以及探索伦理影响，通过复杂拓扑分析指导的个性化治疗计划彻底改变心血管护理。随着人工智能的出现，识别和量化医学成像中的拓扑不确定性至关重要。探索冠状动脉疾病的拓扑不确定性将彻底改变心血管护理，有望提高数百万受心血管疾病影响的诊断和治疗的准确性和个性化。

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