JMIR Formative Research最新文献_第9页

Using a Transdisciplinary Approach in Learning Communities for Designing Wearable Stress Management for Vulnerable Populations: Development and Usability Study. 在学习社区中使用跨学科方法为弱势群体设计可穿戴压力管理：开发和可用性研究。

IF 2 Q3 HEALTH CARE SCIENCES & SERVICES

JMIR Formative Research

Pub Date : 2026-01-09 DOI: 10.2196/75836

Manon W H Peeters, Ittay Mannheim, Paula Elisabeth van Westrienen, Leoni van Dijk, Annalisa Elia, Karolina Valterova, Evelien van de Garde-Perik, Petra Heck, Noortje Lavrijssen, Gerard Schouten, Eveline J M Wouters

Background: Software solutions for wearable-based stress monitoring offer significant potential in health care, particularly for vulnerable populations such as individuals with dementia or persistent physical symptoms. Despite technological advances, designing user-centered, ethically grounded, and contextually relevant software remains challenging. Vulnerable populations often have specific cognitive, physical, and emotional needs that require customization, yet these are rarely prioritized in mainstream development. Our so-called Sensors2Care project addressed these challenges by co-developing stress-monitoring prototypes in collaboration with stakeholders from health care, law, and technology within a transdisciplinary setting.Objective: This article has two aims: first, to describe how the Sensors2Care project operationalized the transdisciplinary approach (TDA) within a learning community (LC) to guide the development of stress-monitoring software; second, to share stakeholder needs and design requirements for wearable technologies in complex health care contexts, derived from this process.Methods: The Sensors2Care project applied a TDA embedded in an LC. This approach combined participatory design research with mixed methods across 3 iterative components: requirements gathering, prototype development, and early-stage evaluation. Research activities included scoping reviews, semistructured interviews, focus groups, legal analyses, and field testing. In the LC, students and researchers from health professions, computer science, and law collaborated with patients, (in)formal caregivers, and industry partners in a transdisciplinary consortium. User stories served as both a methodological tool and design outcome, helping to capture stakeholder needs and align input from technical, health, and legal domains. Feedback was collected continuously and used to refine requirements and prototypes throughout the development process.Results: User stories revealed 7 key themes relevant to developing and using wearable-based stress monitoring, including strategic use, notifications, user input, data insight, data access and sharing, hardware design, and support. Stakeholders emphasized the need for customization, durability, and comfort, aligned with the cognitive and physical needs of the target populations. Prototype evaluations indicated the practical relevance of these features and revealed a need for training and insight into long-term usability. Beyond their role in capturing content-driven input, user stories also supported transdisciplinary collaboration by aligning legal, health, technical, and experiential perspectives. This was facilitated by the LC structure, which enabled sustained engagement between students, researchers, and societal stakeholders and illustrated the feasibility of implementing TDA in a university context.Conclusions: </s

背景：基于可穿戴设备的压力监测软件解决方案在医疗保健领域具有巨大的潜力，特别是对于患有痴呆症或持续性身体症状的个体等弱势群体。尽管技术进步了，但设计以用户为中心的、基于伦理的、与上下文相关的软件仍然具有挑战性。弱势群体通常有特定的认知、身体和情感需求，需要定制，但这些在主流发展中很少得到优先考虑。我们所谓的Sensors2Care项目通过与医疗保健、法律和技术领域的利益相关者在跨学科环境中合作，共同开发压力监测原型，解决了这些挑战。目的：本文有两个目的：第一，描述Sensors2Care项目如何在学习社区（LC）中运用跨学科方法（TDA）来指导压力监测软件的开发；第二，分享利益相关者的需求和设计要求，可穿戴技术在复杂的医疗保健背景下，从这个过程中得出。方法：Sensors2Care项目将TDA嵌入LC。这种方法将参与式设计研究与跨3个迭代组件的混合方法结合在一起：需求收集、原型开发和早期评估。研究活动包括范围审查、半结构化访谈、焦点小组、法律分析和实地测试。在LC中，来自卫生专业、计算机科学和法律的学生和研究人员与患者、正式护理人员和跨学科联盟的行业合作伙伴合作。用户故事既是一种方法工具，也是一种设计结果，有助于捕获涉众的需求，并协调来自技术、健康和法律领域的输入。在整个开发过程中，不断收集反馈并用于细化需求和原型。结果：用户故事揭示了与开发和使用基于可穿戴设备的压力监测相关的7个关键主题，包括战略使用、通知、用户输入、数据洞察、数据访问和共享、硬件设计和支持。利益相关者强调对定制、耐用性和舒适性的需求，与目标人群的认知和身体需求保持一致。原型评估表明了这些特性的实际相关性，并揭示了对长期可用性的培训和洞察力的需求。除了在获取内容驱动输入方面的作用之外，用户故事还通过协调法律、健康、技术和经验方面的观点来支持跨学科协作。LC结构促进了这一点，使学生、研究人员和社会利益相关者之间能够持续参与，并说明了在大学环境中实施TDA的可行性。结论：本项目说明，当TDA嵌入到LC中时，如何支持针对弱势群体的道德基础、情境相关和实际适用的压力监测软件的共同开发。迭代设计过程支持法律、健康和技术方面的早期集成，而用户故事支持跨领域的结构化协作。虽然该项目产生了具体的原型和集群设计要求，但需要进一步的研究来评估医疗保健环境中的长期使用和实际实施情况。在LCs中嵌入TDA可以加强未来专业人员协作解决复杂卫生保健挑战的能力。

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引用次数: 0

Early Prediction of Cardiac Arrest Based on Time-Series Vital Signs Using Deep Learning: Retrospective Study. 基于深度学习时间序列生命体征的心脏骤停早期预测：回顾性研究。

IF 2 Q3 HEALTH CARE SCIENCES & SERVICES

JMIR Formative Research

Pub Date : 2026-01-09 DOI: 10.2196/78484

Yong Li, Lei Lv, Xia Wang

Background: Cardiac arrest (CA), characterized by an extremely high mortality rate, remains one of the most pressing global public health challenges. It not only causes a substantial strain on health care systems but also severely impacts individual health outcomes. Clinical evidence demonstrates that early identification of CA significantly reduced the mortality rate. However, the developed CA prediction models exhibit limitations such as low sensitivity and high false alarm rates. Moreover, issues with model generalization remain insufficiently addressed.

Objective: The aim of this study was to develop a real-time prediction method based on clinical vital signs, using patient vital sign data from the past 2 hours to predict whether CA would occur within the next 1 hour at 5-minute intervals, thereby enabling timely and accurate prediction of CA events. Additionally, the eICU-CRD dataset was used for external validation to assess the model's generalization capability.

Methods: We reviewed and analyzed 4063 patients from the MIMIC-III waveform database, extracting 6 features to develop a deep learning-based CA prediction model named TrGRU. To further enhance performance, statistical features based on a sliding window were also constructed. The TrGRU model was developed using a combination of transformer and gated recurrent unit architectures. The primary evaluation metrics for the model included accuracy, sensitivity, area under the receiver operating characteristic curve (AUROC), and area under the precision-recall curve (AUPRC), with generalization capability validated using the eICU-CRD dataset.

Results: The proposed model yielded an accuracy of 0.904, sensitivity of 0.859, AUROC of 0.957, and AUPRC of 0.949. The results showed that the predictive performance of TrGRU was superior to that of the models reported in previous studies. External validation using the eICU-CRD achieved a sensitivity of 0.813, an AUROC of 0.920, and an AUPRC of 0.848, indicating excellent generalization capability.

Conclusions: The proposed model demonstrates high sensitivity and a low false-alarm rate, enabling clinical health care providers to predict CA events in a more timely and accurate manner. The adopted meta-learning approach effectively enhances the model's generalization capability, showcasing its promising clinical application.

背景：心脏骤停（CA）的特点是死亡率极高，仍然是最紧迫的全球公共卫生挑战之一。它不仅对卫生保健系统造成巨大压力，而且严重影响个人健康结果。临床证据表明，早期发现CA可显著降低死亡率。然而，现有的CA预测模型存在灵敏度低、虚警率高的局限性。此外，模型泛化的问题仍然没有得到充分的解决。目的：本研究的目的是建立一种基于临床生命体征的实时预测方法，利用患者过去2小时的生命体征数据，每隔5分钟预测未来1小时内是否会发生CA，从而及时准确地预测CA事件。此外，使用eICU-CRD数据集进行外部验证，以评估模型的泛化能力。方法：回顾分析MIMIC-III波形数据库中的4063例患者，提取6个特征，建立基于深度学习的CA预测模型TrGRU。为了进一步提高性能，还构造了基于滑动窗口的统计特征。TrGRU模型是使用变压器和门控循环单元结构的组合开发的。该模型的主要评价指标包括准确率、灵敏度、受试者工作特征曲线下面积（AUROC）和精密度-召回率曲线下面积（AUPRC），并使用eICU-CRD数据集验证了模型的泛化能力。结果：该模型的准确率为0.904，灵敏度为0.859，AUROC为0.957，AUPRC为0.949。结果表明，TrGRU的预测性能优于以往研究中报道的模型。采用eICU-CRD进行外部验证，灵敏度为0.813，AUROC为0.920，AUPRC为0.848，具有良好的泛化能力。结论：该模型具有较高的敏感性和较低的误报率，使临床卫生保健提供者能够更及时、准确地预测CA事件。采用元学习方法有效增强了模型的泛化能力，显示了其临床应用前景。

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引用次数: 0

Community Experiences of Social and Nonmedical Gender-Affirming Care: Interview Study Among Transgender and/or Nonbinary Persons. 社会和非医学性别确认护理的社区经验：跨性别者和/或非二元性别者的访谈研究。

IF 2 Q3 HEALTH CARE SCIENCES & SERVICES

JMIR Formative Research

Pub Date : 2026-01-08 DOI: 10.2196/79179

Bryah Boutilier

Background: Access to care that affirms one's entire self is essential, especially for gender-diverse individuals. Gender-affirming care includes medical, social, and nonmedical supports to affirm gender identity.

Objective: This study qualitatively examined the importance of social and nonmedical gender-affirming services as described by gender-diverse community members.

Methods: Thematic analysis was conducted on qualitative data from 5 participants (3 rural and 2 urban; 2 with doctoral-level education and 3 health professionals) with experiences accessing gender-affirming care in Nova Scotia, Canada, between October 2023 and November 2023.

Results: Participants included transgender and/or nonbinary individuals who highlighted the significance of social and nonmedical gender-affirming care over traditional medical interventions. Themes included the centrality of belonging, the use of online spaces such as TikTok for gender affirmation, and the emotional impact of barriers such as cost and safety concerns. Four of 5 participants emphasized the importance of social and nonmedical gender-affirming care over medical interventions. Participants stressed the importance of fostering a sense of belonging and accessing supportive communities, which is crucial in navigating transphobic environments without support. Many felt abandoned by public systems and resorted to passing as cisgender due to barriers such as cost in accessing gender-affirming resources. Internet platforms such as TikTok provided valuable guidance, supplementing limited access to medical gender-affirming care. Participants emphasized a crucial need for health care providers to understand basic gender-affirming care, including respect for preferred pronouns and gender identities.

Conclusions: This study found that members of the gender-diverse community significantly value social and nonmedical gender-affirming care services with respect to their well-being. The findings underscore the complex interplay among social support, health care access, and resilience in transgender and/or nonbinary individuals' lives. This work can aid in exploring how best to educate health care providers in gender-inclusive care and enable increased access to all forms of care that can help affirm an individual's gender.

背景：获得能够肯定一个人整个自我的护理是至关重要的，特别是对性别多样化的个体而言。性别确认护理包括确认性别认同的医疗、社会和非医疗支持。目的：本研究定性地考察了性别多样化社区成员所描述的社会和非医疗性别肯定服务的重要性。方法：对2023年10月至2023年11月期间在加拿大新斯科舍省获得性别肯定护理经验的5名参与者（3名农村和2名城市；2名博士学历和3名卫生专业人员）的定性数据进行专题分析。结果：参与者包括跨性别和/或非二元性个体，他们强调了社会和非医学性别确认护理对传统医疗干预的重要性。主题包括归属感的中心地位，使用抖音等在线空间来确认性别，以及成本和安全问题等障碍对情感的影响。5名与会者中有4人强调社会和非医疗性别肯定护理对医疗干预的重要性。与会者强调了培养归属感和进入支持性社区的重要性，这对于在没有支持的情况下应对跨性别环境至关重要。许多人感到被公共系统抛弃，由于获得性别肯定资源的成本等障碍，他们不得不以顺性别者的身份过关。抖音等互联网平台提供了宝贵的指导，补充了获得医疗性别确认护理的有限机会。与会者强调，保健提供者必须了解基本的性别肯定护理，包括尊重首选代词和性别认同。结论：本研究发现，性别多元化社区的成员非常重视社会和非医疗性别肯定护理服务。研究结果强调了跨性别和/或非二元性个体生活中社会支持、医疗保健获取和恢复力之间复杂的相互作用。这项工作有助于探索如何最好地教育卫生保健提供者进行性别包容性护理，并使更多的人能够获得有助于确认个人性别的各种形式的护理。

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引用次数: 0

Development and Initial Validation of a Brief, Online Version of the Center for Epidemiological Studies Depression Scale (CES-D): Psychometric Study. 流行病学研究中心抑郁量表（CES-D）简短在线版本的开发和初步验证：心理测量学研究。

IF 2 Q3 HEALTH CARE SCIENCES & SERVICES

JMIR Formative Research

Pub Date : 2026-01-08 DOI: 10.2196/81595

Moshe Shmueli, Ariel Pollock Star, Nofar Tsur, Norm O'Rourke

Background: A growing volume of mental health research is conducted with participants recruited and responding online. However, to date, few psychometric scales have been specifically validated for online research.

Objective: We aimed to devise a brief, 12-item version of the Center for Epidemiological Studies Depression Scale (CES-D) in which first order factors are sufficiently measured.

Methods: We recruited 218 adults with depression and 226 comparison participants with no mental health history. Both groups completed the original 20-item CES-D and measures of social support, psychological distress, and sociodemographic information (eg, age, gender, and household income). Measurement of social support included online support, and psychological distress included symptoms of social media use disorder along with loneliness and life dissatisfaction.

Results: This brief, 12-item version of the CES-D was devised with persons with depression and replicated with comparison participants. For both, core sadness, somatic symptoms, interpersonal detachment, and absence of well-being each significantly contributed to measurement of a higher-order depression latent construct (P<.01). Structural equation modeling was performed to establish the construct validity of this 4-factor model in which depression is predicted by socioeconomic factors and depression predicts lower social support as well as greater psychological distress.

Conclusions: Responses to this 12-item, online version of the CES-D demonstrate factorial and construct validity. Clinical research is required in future to ascertain whether scores greater than 11 (of 36) are suggestive of elevated depressive symptomology.

背景：越来越多的心理健康研究是通过在线招募和回应参与者进行的。然而，到目前为止，很少有心理测量量表被专门用于在线研究。目的：我们的目的是设计一个简短的，12项版本的流行病学研究中心抑郁量表（CES-D），其中一级因素被充分测量。方法：我们招募了218名患有抑郁症的成年人和226名没有精神健康史的对照组。两组都完成了最初的20项CES-D，并测量了社会支持、心理困扰和社会人口学信息（如年龄、性别和家庭收入）。社会支持的测量包括在线支持，心理困扰包括社交媒体使用障碍的症状，以及孤独和生活不满。结果：这个简短的，包含12个项目的CES-D版本是针对抑郁症患者设计的，并在比较参与者中复制。核心悲伤、躯体症状、人际分离和缺乏幸福感都对高阶抑郁潜伏构念的测量有显著贡献(结论：对这12个项目的在线版CES-D的反应证明了因子和构念的效度。未来需要进行临床研究，以确定评分大于11分（36分）是否表明抑郁症状升高。

{"title":"Development and Initial Validation of a Brief, Online Version of the Center for Epidemiological Studies Depression Scale (CES-D): Psychometric Study.","authors":"Moshe Shmueli, Ariel Pollock Star, Nofar Tsur, Norm O'Rourke","doi":"10.2196/81595","DOIUrl":"10.2196/81595","url":null,"abstract":"Background: A growing volume of mental health research is conducted with participants recruited and responding online. However, to date, few psychometric scales have been specifically validated for online research.Objective: We aimed to devise a brief, 12-item version of the Center for Epidemiological Studies Depression Scale (CES-D) in which first order factors are sufficiently measured.Methods: We recruited 218 adults with depression and 226 comparison participants with no mental health history. Both groups completed the original 20-item CES-D and measures of social support, psychological distress, and sociodemographic information (eg, age, gender, and household income). Measurement of social support included online support, and psychological distress included symptoms of social media use disorder along with loneliness and life dissatisfaction.Results: This brief, 12-item version of the CES-D was devised with persons with depression and replicated with comparison participants. For both, core sadness, somatic symptoms, interpersonal detachment, and absence of well-being each significantly contributed to measurement of a higher-order depression latent construct (P<.01). Structural equation modeling was performed to establish the construct validity of this 4-factor model in which depression is predicted by socioeconomic factors and depression predicts lower social support as well as greater psychological distress.Conclusions: Responses to this 12-item, online version of the CES-D demonstrate factorial and construct validity. Clinical research is required in future to ascertain whether scores greater than 11 (of 36) are suggestive of elevated depressive symptomology.","PeriodicalId":14841,"journal":{"name":"JMIR Formative Research","volume":"10 ","pages":"e81595"},"PeriodicalIF":2.0,"publicationDate":"2026-01-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12828309/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145933429","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Linking Patient-Reported and Clinician-Assessed Wound Status via Chatbot-Based Digital Surveillance for Wound Infection: Retrospective Observational Study. 通过基于聊天机器人的伤口感染数字监测连接患者报告和临床评估的伤口状态：回顾性观察研究。

IF 2 Q3 HEALTH CARE SCIENCES & SERVICES

JMIR Formative Research

Pub Date : 2026-01-08 DOI: 10.2196/77685

Yung-Cheng Su, Yu-Hsien Lin, Ming-Yuan Huang

Background: Digital wound monitoring has become increasingly feasible with the widespread use of smartphones and mobile messaging platforms. Although most previous studies have focused on chronic wounds and demonstrated the clinical benefits of remote monitoring, little is known about how patients with acute wounds perceive and report wound-related changes after discharge; these factors may affect the accuracy and reliability of patient-facing digital health systems.Objective: This study aimed to evaluate the diagnostic performance of patient-reported infection symptoms in predicting clinician-initiated callbacks within a chatbot-based wound monitoring platform. A secondary objective was to identify wound features most strongly associated with patient-reported infection and examine differences between acute and chronic wound populations.Methods: This retrospective observational study was conducted at a tertiary medical center in Taipei, Taiwan, between June 30, 2022, and March 1, 2023, as part of an institutional digital health initiative. Within this program, adults with acute or chronic wounds voluntarily joined a chatbot-based monitoring system deployed through the Line messaging app using a bring-your-own-device model. Participants submitted daily symptom reports and wound photographs through the chatbot interface. For each submission, patient self-report of infection served as the primary predictor variable, while an independent review by a senior plastic surgeon determined the reference standard (callback vs no callback). Logistic regression and generalized estimating equation models were applied to account for within-subject correlation, with covariates including age, sex, and wound type. Analyses were performed separately for acute and chronic wounds.Results: This study included 159 patients; 88 (55.3%) had acute wounds and 71 (44.7%) had chronic wounds. Across the study period, 4764 wound photographs were submitted, with a median of 5 (IQR 2-18) photographs per patient. Diagnostic performance differed by wound type. For acute wounds, the area under the receiver operating characteristic curve was 0.702, with 52.6% sensitivity (95% CI 31.7-72.7) and 87.8% specificity (95% CI 84.7-90.3). For chronic wounds, the area under the receiver operating characteristic curve was 0.907, with 94.9% sensitivity (95% CI 93.3-96.2) and 86.4% specificity (95% CI 85.2-87.5). In symptom correlation analyses, redness was significantly associated with patient-reported infection in the acute wound subgroup (odds ratio [OR] 3.94, 95% CI 1.97-7.90; P<.001), whereas in the chronic wound subgroup, both redness (OR 86.35, 95% CI 57.11-130.56; P<.001) and skin darkening (OR 358.55, 95% CI 244.79-525.16; P<.001) showed significant associations (all P<.001).Conclusions: This study highlights the differences in how patients perceive and report infection-re

背景：随着智能手机和移动信息平台的广泛使用，数字伤口监测变得越来越可行。尽管大多数先前的研究都集中在慢性伤口上，并证明了远程监测的临床益处，但对于急性伤口患者在出院后如何感知和报告伤口相关的变化，我们知之甚少；这些因素可能会影响面向患者的数字卫生系统的准确性和可靠性。目的：本研究旨在评估在基于聊天机器人的伤口监测平台中，患者报告的感染症状在预测临床医生发起的回叫中的诊断性能。次要目的是确定与患者报告的感染最密切相关的伤口特征，并检查急性和慢性伤口人群之间的差异。方法：这项回顾性观察性研究于2022年6月30日至2023年3月1日在台湾台北的一家三级医疗中心进行，作为机构数字健康计划的一部分。在这个项目中，患有急性或慢性伤口的成年人自愿加入了一个基于聊天机器人的监测系统，该系统通过Line消息应用程序部署，采用自带设备的模式。参与者通过聊天机器人界面提交每日症状报告和伤口照片。对于每次提交，患者自我报告感染作为主要预测变量，而由高级整形外科医生的独立审查确定参考标准（回调vs无回调）。应用逻辑回归和广义估计方程模型来解释受试者内相关性，协变量包括年龄、性别和伤口类型。对急性和慢性伤口分别进行分析。结果：本研究纳入159例患者；急性创面88例（55.3%），慢性创面71例（44.7%）。在整个研究期间，提交了4764张伤口照片，平均每位患者5张（IQR 2-18）。不同伤口类型的诊断表现不同。对于急性伤口，受者工作特征曲线下面积为0.702，敏感性为52.6% (95% CI 31.7 ~ 72.7)，特异性为87.8% （95% CI 84.7 ~ 90.3）。对于慢性伤口，受者工作特征曲线下面积为0.907，敏感性为94.9% (95% CI 93.3 ~ 96.2)，特异性为86.4% （95% CI 85.2 ~ 87.5）。在症状相关分析中，在急性伤口亚组中，发红与患者报告的感染显著相关（优势比[OR] 3.94, 95% CI 1.97-7.90）。结论：本研究强调了急性和慢性伤口人群中患者如何感知和报告感染相关症状的差异。急性伤口较低的诊断准确性强调了有限的经验和环境限制对患者自我评估的影响。这些发现表明，面向患者的数字伤口监测系统应根据伤口的慢性性和患者的经验进行定制，并结合自适应反馈和人工智能辅助筛查，以增强患者报告的症状解释。

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引用次数: 0

Using AI Chatbot to Assist Students' Behavior Management for Obesity Prevention in Middle Schools: Feasibility Study. 利用AI聊天机器人辅助中学生行为管理预防肥胖的可行性研究

IF 2 Q3 HEALTH CARE SCIENCES & SERVICES

JMIR Formative Research

Pub Date : 2026-01-07 DOI: 10.2196/83630

Qiaoyin Tan, Yuxin Nie, Paul Son, Yizhou Qian, Amanda E Staiano, Fahui Wang, Richard R Rosenkranz, Senlin Chen

Background: Adolescent obesity remains a pressing public health challenge, particularly among socioeconomically disadvantaged populations. Artificial intelligence (AI) holds the promise for supporting students in managing daily health behaviors, but few existing studies used AI-based interventions in naturalistic settings such as schools.

Objective: This study evaluated the feasibility and preliminary impact of ProudMe Tech (Louisiana State University), an AI-assisted web app designed to help students manage 4 obesity-related behaviors: physical activity, screen time, diet, and sleep.

Methods: The 8-week, 1-arm pilot intervention study recruited 172 participants from 5 middle schools in Louisiana and used the ProudMe Tech to set behavior goals, track behaviors, record reflections, and receive AI-generated feedback. Both engagement (primary focus) and behavior impacts (secondary focus) were examined.

Results: Engagement metrics indicated varying levels of usage, averaging 8.9 (SD 7.6) behavior entries and 30.0 (SD 28.3) reflections per student, and receiving 33.5 (SD 29.7) AI feedback messages. Overall, participants recorded 6164 valid daily goals, of which 3934 (63.8%) were achieved. Natural language processing of the reflections and AI feedback messages revealed an overall neutral to positive sentiment. Pre- to postcomparisons showed (1) a significant reduction in screen time from 4.3 (SD 2.6) to 3.4 (SD 2.5) hours per day (21.6% decrease; t164=6.18, P<.001), (2) a small but significant decrease in fruit and vegetable intake from 5.7 (SD 3.8) to 5.2 (SD 3.5) servings per day (8.9% decrease; t169=2.27, P=.46), and (3) no significant changes in physical activity and sleep.

Conclusions: These findings suggest that ProudMe Tech is a feasible AI chatbot that can engage adolescents in health behavior management, but more adaptation is needed to effectively elicit improvements in health behaviors and lower the obesity risk in middle school students.

背景：青少年肥胖仍然是一个紧迫的公共卫生挑战，特别是在社会经济弱势人群中。人工智能（AI）有望支持学生管理日常健康行为，但目前很少有研究在学校等自然环境中使用基于人工智能的干预措施。目的：本研究评估了ProudMe Tech（路易斯安那州立大学）的可行性和初步影响，这是一款人工智能辅助的网络应用程序，旨在帮助学生管理4种与肥胖相关的行为：身体活动、屏幕时间、饮食和睡眠。方法：这项为期8周的单臂试点干预研究从路易斯安那州的5所中学招募了172名参与者，并使用ProudMe Tech设定行为目标，跟踪行为，记录反思并接收人工智能生成的反馈。参与（主要焦点）和行为影响（次要焦点）都被检查。结果：参与指标显示了不同的使用水平，平均每个学生8.9 （SD 7.6）个行为条目和30.0 （SD 28.3）个反思，并收到33.5 （SD 29.7）个AI反馈信息。总体而言，参与者记录了6164个有效的每日目标，其中3934个（63.8%）实现了。对反思和人工智能反馈信息的自然语言处理显示出总体上中性到积极的情绪。研究结果表明(1)使用后屏幕时间从4.3小时（SD 2.6）减少到3.4小时（SD 2.5），减少21.6% （t164=6.18）。结论：ProudMe Tech是一种可行的人工智能聊天机器人，可以让青少年参与健康行为管理，但需要更多的适应才能有效地改善中学生的健康行为，降低肥胖风险。

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引用次数: 0

Demographic and Clinical Characteristics Influencing Ecological Momentary Assessment Compliance in Individuals With Bipolar Disorder: Observational Study. 影响双相情感障碍患者生态瞬时评估依从性的人口学和临床特征：观察性研究。

IF 2 Q3 HEALTH CARE SCIENCES & SERVICES

JMIR Formative Research

Pub Date : 2026-01-07 DOI: 10.2196/74223

Linru Yin, Minghui Li, Jinhao Li, Xiaofei Hou, Jianan Song, Xinyan Li, Yue Tong, Xinyue Zhou, Lidan Yuan, Huifang Yin, Guangming Xu

Background: Bipolar disorder requires immediate and frequent daily symptom monitoring due to its extreme mood fluctuations. Ecological momentary assessment (EMA) technology uses high-frequency data collection to achieve ecologically valid capture of patient symptoms. Investigating EMA compliance among Chinese patients with bipolar disorder and its influencing factors is essential for developing more feasible daily symptom monitoring protocols.

Objective: This study aimed to investigate the 14-day compliance rate of EMA among Chinese individuals with bipolar disorder and to examine the demographic and clinical characteristics associated with that compliance.

Methods: A total of 100 adults (63 female individuals) with bipolar disorder across mood states (depressive episode, n=29, 29%; hypomanic or manic episode, n=17, 17%; euthymic state, n=54, 54%) completed self-monitoring via the WeChat Mini Program "Xunkang Assessment System" 3 times daily for 14 days. The compliance rate was calculated as the percentage of completed questionnaires out of the total required over 2 weeks. Multivariate ordinal logistic regression was used to explore the factors associated with the compliance rate.

Results: The median compliance rate was 75% (IQR 35.7%-90.4%). Compliance did not differ significantly across mood states (P=.15). In multivariable models, higher Bech-Rafaelsen Mania Scale scores and lower Functioning Assessment Short Test scores were independently associated with better compliance (Bech-Rafaelsen Mania Scale: B=0.11; P=.03 and Functioning Assessment Short Test: B=-0.06; P=.01).

Conclusions: Two-week EMA monitoring via the WeChat Mini Program is feasible among Chinese individuals with bipolar disorder across mood states. Manic symptom severity and functional impairment were associated with EMA adherence and should be considered in study design and interpretation.

背景：双相情感障碍由于其极端的情绪波动，需要立即和频繁的日常症状监测。生态瞬时评估（EMA）技术使用高频数据收集来实现对患者症状的生态有效捕获。调查中国双相情感障碍患者的EMA依从性及其影响因素对于制定更可行的日常症状监测方案至关重要。目的：本研究旨在调查中国双相情感障碍患者EMA的14天依从率，并检查与该依从性相关的人口统计学和临床特征。方法：共100例成年双相情感障碍患者（女性63例），各情绪状态（抑郁发作，n=29、29%；轻躁或躁狂发作，n=17、17%；平和状态，n=54、54%）通过微信小程序“寻康评估系统”完成自我监测，每天3次，持续14天。遵规率以两周内完成的问卷占所需问卷总数的百分比计算。采用多变量有序逻辑回归探讨影响依从率的因素。结果：中位依从率为75% （IQR为35.7% ~ 90.4%）。依从性在情绪状态之间没有显著差异（P=.15）。在多变量模型中，较高的Bech-Rafaelsen躁狂量表得分和较低的功能评估短测试得分与较好的依从性独立相关（Bech-Rafaelsen躁狂量表：B=0.11； P= 0.03；功能评估短测试：B=-0.06； P= 0.01）。结论：通过微信小程序对中国双相情感障碍患者进行两周EMA监测是可行的。躁狂症状严重程度和功能损害与EMA依从性相关，应在研究设计和解释中予以考虑。

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引用次数: 0

Adoption of an Electronic Decision Support Tool for Capacity Building of Community Health Workers: Mixed Methods Study. 采用电子决策支持工具进行社区卫生工作者能力建设：混合方法研究。

IF 2 Q3 HEALTH CARE SCIENCES & SERVICES

JMIR Formative Research

Pub Date : 2026-01-07 DOI: 10.2196/69874

Anton Elepaño, Carol Stephanie Tan-Lim, Clare Bankhead, Leonila Dans, Noleen Marie Fabian, Josephine Sanchez, Antonio Dans, Catherine Pope

Background: Complimentary subscriptions to UpToDate, a decision support tool, were provided to community health workers (CHWs) in rural and remote primary care sites as part of a government-funded health system research program. A feasibility evaluation conducted after the first year of implementation showed that UpToDate was acceptable among CHWs despite infrastructural barriers.Objective: This follow-up study evaluated the longitudinal adoption of UpToDate among CHWs and examined how sociocultural, political, and environmental factors influenced its use. Drawing on the nonadoption, abandonment, scale-up, spread, and sustainability framework, this study aimed to understand not only use patterns but also broader challenges to scale-up, spread, and sustainability in a complex health system.Methods: An explanatory mixed methods design was used combining analysis of use and program activity logs; program reports; and focus groups with CHWs, health care professionals, and program implementers. Quantitative analysis of use logs (March 2021 to September 2023) compared adoption over time by using descriptive statistics, CIs, and chi-square tests. Qualitative data came from the reanalysis of previous focus group transcripts and program reports and from a new focus group with program implementers. Reflexive thematic analysis was used to interpret how CHWs and implementers perceived and used the tool, and findings were integrated to explain quantitative trends.Results: Use of UpToDate was modest and declined over time. Monthly active use among CHWs and midwives fell substantially from 3.57% (97/2720 person-months) in 2021 to 1.07% (37/3456) in 2022 and remained low at 1.50% (39/2592) up to 2023, with markedly higher engagement in the rural site than in the remote site. Peaks in use coincided with program activities, whereas prolonged troughs followed typhoons, power outages, and other disruptions. Log data showed that users primarily consulted patient education articles rather than clinician-oriented decision tools. Qualitative analyses revealed that CHWs appropriated UpToDate as a learning aid and source of professional credibility. Structural shocks, heavy workloads, language barriers, and limited device access constrained individual use, and communal practices (shared devices and learning activities) meant that meaningful engagement often went unrecorded in vendor metrics.Conclusions: Our findings show that acceptability does not guarantee sustained use and that adoption cannot be captured fully by log-in counts. UpToDate's value for CHWs lay in how it was domesticated as a tool for building capacity and professional credibility, not in its intended function as a decision aid used at the point of care. Therefore, evaluations of digital health tools should incorporate indicators of learning and social capital alongside use metrics. Policyma

背景：作为政府资助的卫生系统研究项目的一部分，向农村和偏远初级保健站点的社区卫生工作者（chw）免费提供了决策支持工具UpToDate。实施第一年后进行的可行性评估显示，尽管基础设施存在障碍，但卫生工作者仍然可以接受“更新日期”。目的：本随访研究评估了卫生工作者对UpToDate的纵向采用情况，并考察了社会文化、政治和环境因素对其使用的影响。利用不采用、放弃、扩大、传播和可持续性框架，本研究不仅旨在了解使用模式，还旨在了解复杂卫生系统中扩大、传播和可持续性的更广泛挑战。方法：采用用户分析与项目活动日志相结合的解释混合方法设计；项目报告;以及由卫生保健工作者、卫生保健专业人员和项目执行者组成的焦点小组。使用日志的定量分析（2021年3月至2023年9月）通过使用描述性统计、ci和卡方检验比较了一段时间内的采用情况。定性数据来自对先前焦点小组记录和计划报告的重新分析，以及来自与计划实施者的新焦点小组。反身性专题分析用于解释卫生工作者和实施者如何感知和使用该工具，并将调查结果整合以解释定量趋势。结果：UpToDate的使用是适度的，并且随着时间的推移而下降。保健医生和助产士的月活跃使用率从2021年的3.57%（97/2720人月）大幅下降至2022年的1.07%（37/3456人月），直到2023年仍保持在1.50%（39/2592人月）的低位，农村地区的参与度明显高于偏远地区。用电高峰与项目活动一致，而长时间的低谷则伴随着台风、停电和其他中断。日志数据显示，用户主要查阅患者教育文章，而不是以临床医生为导向的决策工具。定性分析显示，卫生工作者将UpToDate作为学习辅助工具和专业可信度的来源。结构性冲击、繁重的工作负载、语言障碍和受限的设备访问限制了个人使用，以及公共实践（共享设备和学习活动）意味着有意义的粘性通常不会记录在供应商指标中。结论：我们的研究结果表明，可接受性并不能保证持续使用，并且不能通过登录计数完全捕获采用情况。UpToDate对卫生保健工作者的价值在于它如何被驯养为一种建设能力和专业信誉的工具，而不是它作为在护理点使用的决策辅助工具的预期功能。因此，对数字健康工具的评估应将学习和社会资本指标与使用指标结合起来。政策制定者应该认识到，基础设施的脆弱性和社区适应性影响着数字健康的吸收。将工具嵌入正在进行的培训和同侪学习结构中，提供线下和多语言支持，并投资于复原力规划，对于有意义的扩大规模和可持续性至关重要。

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引用次数: 0

Digital Health Communication and Vaccine Confidence in Mexico Using Aggregated Randomized Brand Lift Studies: Secondary Analysis. 数字健康传播和疫苗信心在墨西哥使用汇总随机品牌提升研究：二次分析。

IF 2 Q3 HEALTH CARE SCIENCES & SERVICES

JMIR Formative Research

Pub Date : 2026-01-06 DOI: 10.2196/82889

Berenice Muñoz Cordero, Rodrigo Romero Feregrino, Raul Romero Feregrino, Raúl Romero Cabello, Valeria Magali Rocha Rocha, Roberto Martinez-Medina, Liliana Aline Fernández Urrutia

Background: Digital vaccination campaigns are increasingly used to address declining vaccine confidence, yet evidence from large-scale, real-world interventions in middle-income countries is limited. Meta's Brand Lift Studies (BLS), which use randomized test-control exposure, provide Bayesian estimates of attitudinal shifts resulting from digital content. Mexico, with over 88.6 million active internet users, provides a setting to evaluate the impact of targeted campaigns on vaccine attitudes.Objective: This study evaluated the impact of 5 digital vaccination campaigns implemented by the Asociación Mexicana de Vacunología (@Vacunologia) on Facebook (Meta Platforms Inc) and Instagram (Meta Platforms Inc) in Mexico between 2021 and 2022 on key attitudinal constructs related to COVID-19 vaccine confidence.Methods: This study used a retrospective ecological design. We analyzed aggregated BLS results for 5 campaigns targeting different audiences and vaccination themes. Measured outcomes included standard ad recall, perceived importance, perceived safety, perceived efficacy, and concerns about side effects. Statistical significance within the BLS framework was defined as an incremental lift of ≥2 percentage points with ≥90% posterior probability of replication-a threshold consistent with Meta's operational Bayesian approach. Exploratory comparisons across campaigns were conducted using 1-way ANOVA, unpaired 2-tailed t tests, and Fisher exact tests.Results: Campaigns reached 84.9 million accounts and generated 179.4 million impressions with a total investment of US $215,600. All campaigns produced statistically significant improvements in at least one attitudinal outcome (Bayesian threshold ≥90%). Standard ad recall increased in 4 campaigns (ANOVA, P<.001), and concerns about side effects decreased in 2 campaigns (t test, P=.049; P=.006). Perceived safety, importance, and efficacy improved in selected audiences, with stronger effects observed among younger users and women (ANOVA, P=.005). No direct behavioral outcomes (eg, vaccination uptake) were measured; therefore, the findings reflect attitudinal rather than behavioral change. However, these constructs are recognized as proximal predictors of vaccine decision-making and constitute health-related outcomes.Conclusions: Large-scale digital vaccination campaigns can meaningfully strengthen attitudinal determinants of vaccine confidence in a middle-income context. These social media advertising campaigns effectively increased standard ad recall and improved perceptions of vaccine importance and safety, particularly among younger audiences and women in urban areas. However, changes in efficacy perceptions and concerns about side effects were limited. The innovation and implications of this study lie in evaluating large-scale, real-world digital vaccine campaigns in Latin America using experim

背景：数字疫苗接种运动越来越多地用于解决疫苗信心下降的问题，但来自中等收入国家大规模实际干预措施的证据有限。Meta的品牌提升研究（BLS）使用随机测试控制曝光，提供了由数字内容引起的态度转变的贝叶斯估计。墨西哥拥有8 860多万活跃互联网用户，为评估有针对性的运动对疫苗态度的影响提供了一个环境。目的：本研究评估了2021年至2022年期间墨西哥Asociación Mexicana de Vacunología （@Vacunologia）在Facebook （Meta平台公司）和Instagram （Meta平台公司）上实施的5次数字疫苗接种活动对与COVID-19疫苗信心相关的关键态度结构的影响。方法：本研究采用回顾性生态学设计。我们分析了针对不同受众和疫苗接种主题的5个活动的汇总BLS结果。测量结果包括标准广告召回、感知重要性、感知安全性、感知有效性和对副作用的关注。BLS框架内的统计显著性定义为≥2个百分点的增量提升，且复制的后验概率≥90%，这是与Meta的操作贝叶斯方法一致的阈值。采用单因素方差分析、非配对双尾t检验和Fisher精确检验对各活动进行探索性比较。结果：活动覆盖了8490万个账户，产生了1.794亿次印象，总投资为21.56万美元。所有活动至少在一个态度结果（贝叶斯阈值≥90%）上产生统计学上显著的改善。结论：在中等收入背景下，大规模数字疫苗接种活动可以有意地加强疫苗信心的态度决定因素。这些社交媒体广告活动有效地提高了标准广告的召回率，并改善了对疫苗重要性和安全性的认识，特别是在城市地区的年轻受众和妇女中。然而，疗效认知的变化和对副作用的关注是有限的。这项研究的创新之处在于利用实验性的劳工统计局数据评估拉丁美洲大规模、真实世界的数字疫苗运动。研究结果强调，受众细分会产生更强的感知转变，这表明量身定制的数字战略可以补充传统的公共卫生传播。虽然劳工统计局没有测量行为终点，但观察到的态度改善代表了影响疫苗相关行为的基本步骤。未来的工作应将数字态度指标与疫苗接种和流行病学数据联系起来，以评估现实世界的健康影响。

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引用次数: 0

Adapting a Sexual Health Intervention for Adolescents Exposed to Adversity: Feasibility Study. 逆境青少年性健康干预的可行性研究。

IF 2 Q3 HEALTH CARE SCIENCES & SERVICES

JMIR Formative Research

Pub Date : 2026-01-05 DOI: 10.2196/72782

Terrinieka Powell, Bianca D Smith, Naya Moser, Olivia Kachingwe, Quiana Lewis Wallace, Asari Offiong, Andrea Hwang, Emily Davie, Ashleigh LoVette

Background: Although sexual exploration is normative during adolescence, sexual activities that are unprotected and occur under the influence of substances can pose significant risks to young people. Youth exposed to adversity are among the groups most vulnerable to sexual risk-taking in adolescence. Selective interventions that consider lived experiences and the local context may help reduce sexual risk-taking among this population.

Objective: This pilot study assessed the feasibility of participant recruitment and retention as well as participant engagement with an adapted version of Focus on Youth with Informed Parents and Children Together for Black youth exposed to household challenges.

Methods: Participants were recruited using school and community presentations, digital flyers, and referrals. A total of 121 youth from 3 sites in Baltimore, Maryland, were screened. Participants completed 3 assessments: baseline, posttest, and 3-month follow-up. Participant enrollment, session attendance, and assessment completion were used to determine feasibility and engagement. Sexual health knowledge, pregnancy intentions, partner communication, and sexual behaviors were explored as secondary outcomes.

Results: Funded by the National Institutes of Health, the data for this study were collected between January 2022 and April 2023. A total of 61 youth (aged 13-16 years) were recruited and randomized to either the intervention or the control condition (n=33 and n=28, respectively). In total, 87% (53/61) of the participants completed all 3 assessments. There was high engagement: 80% (48/61) of participants attended at least 3 sessions, and 75.2% (115/153) of after-session responses revealed they would recommend a session to a friend. Among the 18 participants who reported having any sex, all 18 (100%) abstained from alcohol use and 12 (67%) abstained from drug use before sex. The intervention group showed a significant increase in sexual health knowledge. No changes in sexual health behaviors or partner communication were observed.

Conclusions: Findings suggest that recruiting, retaining, and engaging participants in the adapted Focus on Youth with Informed Parents and Children Together intervention is feasible. Additional research is needed to determine the extent to which this intervention can mitigate sexual risk-taking among youth exposed to adversity. The findings will inform the redesign of our assessments to capture additional factors that may affect sexual health behaviors.

Trial registration: ClinicalTrials.gov NCT05033821; https://clinicaltrials.gov/study/NCT05033821.

背景：虽然性探索在青春期是规范的，但在没有保护的情况下以及在药物影响下发生的性活动可能对青少年构成重大风险。面临逆境的青少年是青春期最容易发生性冒险的群体之一。考虑生活经历和当地环境的选择性干预可能有助于减少这一人群的性冒险行为。目的：本试点研究评估了参与者招募和保留的可行性，以及参与者参与针对面临家庭挑战的黑人青年的改编版“关注有知情父母和孩子的青年”的可行性。方法：通过学校和社区演示、数字传单和推荐来招募参与者。来自马里兰州巴尔的摩市3个地点的121名青少年接受了筛选。参与者完成了3项评估：基线、后测和3个月的随访。参与者登记、会议出席和评估完成情况用于确定可行性和参与度。性健康知识、怀孕意向、伴侣沟通和性行为是次要结局。结果：由美国国立卫生研究院资助，本研究的数据收集于2022年1月至2023年4月。共招募了61名青少年（13-16岁），随机分为干预组和对照组（n=33和n=28）。总共有87%（53/61）的参与者完成了所有3项评估。有很高的参与度：80%（48/61）的参与者参加了至少3个疗程，75.2%（115/153）的参与者在疗程结束后表示他们会向朋友推荐疗程。在18名报告有过性行为的参与者中，所有18人（100%）在性行为前戒酒，12人（67%）在性行为前戒酒。干预组在性健康知识方面有显著提高。没有观察到性健康行为或伴侣沟通方面的变化。结论：研究结果表明，招募、保留和吸引参与者参与“关注知情父母和孩子一起的青少年”干预是可行的。需要进一步的研究来确定这种干预在多大程度上可以减轻处于逆境中的青少年的性冒险行为。这些发现将为我们重新设计评估提供信息，以捕捉可能影响性健康行为的其他因素。试验注册：ClinicalTrials.gov NCT05033821；https://clinicaltrials.gov/study/NCT05033821。

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引用次数: 0