Journal of Medical Internet Research最新文献_第3页

Key Components and Barriers in Web-Based Suicide Prevention Gatekeeper Training: Systematic Narrative Review. 网络自杀预防看门人培训的关键组成部分和障碍：系统叙述回顾。

IF 6 2区医学 Q1 HEALTH CARE SCIENCES & SERVICES

Journal of Medical Internet Research

Pub Date : 2026-02-05 DOI: 10.2196/81572

Olivier Ferlatte, Emmanuelle Gareau, Keven Lee, Kinda Wassef, John Lindsay Oliffe, Hannah Kia, Brock Dumville

Background: Gatekeeper training programs (GTPs) are a key component of contemporary suicide prevention strategies, equipping community members and non-mental health professionals with the skills to identify, engage with, and refer individuals at risk of suicide. Increasingly, these programs are delivered via the web, offering a compelling alternative to in-person training through greater scalability, flexibility, and cost-effectiveness. However, little consensus exists regarding the design, modes of delivery, and implementation strategies of web-based GTPs. Further, there is a limited understanding of which components affect their usability and engagement.Objective: This systematic narrative review aims to identify the key components-including facilitators and barriers-of web-based GTPs.Methods: We systematically searched web-based databases (CINAHL, Embase, MEDLINE, PsycINFO, and Web of Science) to identify peer-reviewed articles published between 2000 and 2025 that involved web-based GTPs. After screening, 59 studies met the inclusion criteria and were analyzed using content analysis to identify key components and barriers affecting the delivery and receipt of web-based GTPs.Results: Results were organized under 3 categories: design, content, and pedagogy. Key design considerations emphasized accessibility for diverse learning styles and digital literacy levels, customizability for different user groups, privacy protection, and the long-term sustainability of training content and delivery platforms. Core training content covered four domains: (1) suicide-related knowledge (eg, prevalence, myths, and at-risk groups), (2) gatekeeping skills (eg, understanding risk factors, recognizing warning signs, problem-solving and safety planning), (3) resource awareness (eg, available local resources and referral procedures), and (4) general mental health education (eg, mental fitness, mindfulness, and self-care strategies for gatekeepers). In terms of pedagogy, the reviewed studies used a wide range of strategies that comprised interactive learning activities (eg, simulation, practice exercises), periodic knowledge checks (eg, quizzes), and reinforcement mechanisms (eg, booster sessions). Additionally, fostering a sense of community (eg, online support spaces or discussion forums) and promoting trainees' autonomy (eg, self-paced training) were highlighted as key components of training delivery.Conclusions: Web-based GTPs represent a promising avenue for expanding access to suicide prevention training. Their effectiveness may be strengthened through the integration of frameworks tailored to web-based learning environments, as well as interactive and user-centered design elements that support learning and retention. Future research should examine the acceptability, feasibility, and sustainability of these programs, while also refining their ada

背景：看门人培训计划（GTPs）是当代自杀预防策略的关键组成部分，使社区成员和非精神卫生专业人员具备识别、接触和转诊自杀风险个体的技能。这些课程越来越多地通过网络交付，通过更大的可扩展性、灵活性和成本效益，提供了面对面培训的引人注目的替代方案。然而，关于基于web的gtp的设计、交付模式和实施策略，几乎没有达成共识。此外，对于哪些组件会影响其可用性和用户粘性的理解也很有限。目的：这篇系统的叙述性综述旨在确定基于网络的gtp的关键组成部分，包括促进因素和障碍。方法：我们系统地检索了基于Web的数据库（CINAHL、Embase、MEDLINE、PsycINFO和Web of Science），以确定2000年至2025年间发表的涉及基于Web的gtp的同行评议文章。筛选后，59项研究符合纳入标准，并使用内容分析来确定影响基于web的gtp交付和接收的关键组成部分和障碍。结果：结果分为设计、内容和教学三大类。关键的设计考虑强调了不同学习方式和数字素养水平的可访问性、不同用户群体的可定制性、隐私保护以及培训内容和交付平台的长期可持续性。核心培训内容涵盖四个领域：(1)自杀相关知识（例如，流行、误解和高危人群）；(2)把关技能（例如，了解风险因素、识别警告信号、解决问题和安全规划）；(3)资源意识（例如，可用的当地资源和转诊程序）；(4)一般心理健康教育（例如，把关人的心理健康、正念和自我保健策略）。在教学法方面，所审查的研究使用了广泛的策略，包括互动学习活动（例如，模拟，练习），定期知识检查（例如，测验）和强化机制（例如，助推器会议）。此外，培养社区意识（例如，在线支持空间或讨论论坛）和促进学员的自主权（例如，自定进度培训）被强调为培训交付的关键组成部分。结论：基于网络的gtp代表了一个有希望的途径，以扩大获得自杀预防培训。通过整合为基于网络的学习环境量身定制的框架，以及支持学习和保留的交互式和以用户为中心的设计元素，可以加强其有效性。未来的研究应该检查这些项目的可接受性、可行性和可持续性，同时也要改进它们对不同人群的适应性。在这方面，协同设计方法可以促进根据目标人群的需求和具体情况定制此类方案。总体而言，加强基于网络的gtp的设计和交付可能最终改善其对自杀预防工作的贡献。

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引用次数: 0

Interactions of Technology and Obsessive-Compulsive Disorder Symptomatology in Adults: Qualitative Interview Study. 技术与成人强迫症症状学的相互作用：定性访谈研究。

IF 6 2区医学 Q1 HEALTH CARE SCIENCES & SERVICES

Journal of Medical Internet Research

Pub Date : 2026-02-05 DOI: 10.2196/85033

Lucas Occhino-Moede, Kaitlyn Sulivan-Pascual, Kendall Phelan, Harrison Wang, Daniel Mokhtar, Elisa Liu, Erica Schug, Megan Mirkis, Thomas Baek, Tamerlane Visher, Ujjwal Pasupulety, Adam Charles Frank

Background: Obsessive-compulsive disorder (OCD) affects 1%-3% of the population and is marked by intrusive obsessions and compulsive behaviors that impair daily functioning. As digital technologies have become ubiquitous, their features may interact with OCD symptom dimensions in ways that both exacerbate and alleviate symptoms. While case reports and clinical anecdotes suggest such interactions, systematic investigation of patients' lived experiences with technology remains limited.Objective: This study aimed to explore how individuals with OCD perceive and navigate their interactions with modern technologies, and to identify how specific features of technology may contribute to, reinforce, or relieve obsessive-compulsive symptom cycles.Methods: We conducted semistructured interviews (n=24) with adults self-reporting a diagnosis of OCD, recruited through online OCD communities and advocacy networks. Interviews were conducted via the HIPAA (Health Insurance Portability and Accountability Act)-compliant platform Zoom (Zoom Communications) between May and December 2024 (median duration 51, IQR 6.5 minutes). Transcripts were coded in Dedoose (version 9.2.22; SocioCultural Research Consultants) using a constructivist grounded theory approach. Coding proceeded iteratively through open and focused coding, with theoretical saturation reached after 15 interviews. Constant comparison and analytic memoing guided the development of a conceptual framework linking technology features to OCD symptom dimensions.Results: Participants (median age 26, IQR 12.8, range 20-64 years; 67%, 16/24 women, 29%, 7/24 men, and 4%, 1/24 nonbinary) described technology as both a trigger for and a coping tool against OCD symptoms. Analysis produced four central technology-related categories: (1) information-provision platforms (eg, social media, search engines, large language models, etc) that triggered disturbing-thought obsessions and enabled compulsive checking and reassurance-seeking; (2) gamification and quantification features (eg, streaks, progress bars, and tracking metrics) that reinforced "not-just-right" and symmetry-based compulsions; (3) notifications that provoked urges to clear, check, and maintain control, spanning both disturbing-thought and symmetry domains; and (4) user interfaces whose complexity and customizability elicited compulsive ordering, avoidance behaviors, and digital overwhelm.Conclusions: This study characterizes how interactions between OCD and digital technologies manifest across established symptom domains, most notably disturbing-thought and "not-just-right" categories. Participants overwhelmingly experienced compulsive checking, reassurance-seeking, and ordering behaviors reinforced by features such as information-provision, gamification, notifications, and user interfaces. These findings highlight the clinical relevance of tec

背景：强迫症（OCD）影响1%-3%的人口，其特征是侵入性的强迫和强迫行为，损害日常功能。随着数字技术变得无处不在，它们的特征可能以加重或减轻症状的方式与强迫症症状维度相互作用。虽然病例报告和临床轶事表明了这种相互作用，但对患者与技术的生活经历的系统调查仍然有限。目的：本研究旨在探讨强迫症患者如何感知和驾驭他们与现代技术的互动，并确定技术的特定特征如何有助于、加强或缓解强迫症症状周期。方法：我们进行了半结构化访谈（n=24），受访对象是通过在线强迫症社区和倡导网络招募的自我报告强迫症诊断的成年人。访谈于2024年5月至12月期间通过符合HIPAA（健康保险流通与责任法案）的平台Zoom （Zoom通信）进行（中位数持续时间51，IQR 6.5分钟）。在Dedoose（版本9.2.22；社会文化研究顾问）中使用建构主义扎根理论方法对成绩单进行编码。通过开放和集中的编码进行迭代，在15次访谈后达到理论饱和。不断的比较和分析备忘录指导了将技术特征与强迫症症状维度联系起来的概念框架的发展。结果：参与者（中位年龄26岁，IQR 12.8，范围20-64岁；67%，16/24女性，29%，7/24男性，4%，1/24非二元）将技术描述为强迫症症状的触发和应对工具。分析产生了四个与技术相关的核心类别：(1)信息提供平台（如社交媒体、搜索引擎、大型语言模型等），这些平台引发了令人不安的思想困扰，并使强迫性检查和寻求安慰成为可能；(2)游戏化和量化功能（如条纹、进度条和跟踪指标），强化“不正确”和基于对称的强迫；(3)引起清理、检查和维持控制冲动的通知，跨越干扰思想和对称域；(4)用户界面的复杂性和可定制性引发了强迫性订购、回避行为和数字淹没。结论：这项研究描述了强迫症和数字技术之间的相互作用是如何在已建立的症状领域中表现出来的，最明显的是令人不安的想法和“不正确”的类别。绝大多数参与者都经历了强迫性检查、寻求安慰和订购行为，这些行为被信息提供、游戏化、通知和用户界面等功能所强化。这些发现强调了与技术相关的强迫行为的临床相关性，并建议对其进行系统评估，将其纳入心理教育，并在数字设计中加以考虑。

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引用次数: 0

Communicative Behaviors in an Internet-Based Intervention for Individuals With Autism: Mixed Methods Analysis. 基于互联网的自闭症个体交流行为干预：混合方法分析。

IF 6 2区医学 Q1 HEALTH CARE SCIENCES & SERVICES

Journal of Medical Internet Research

Pub Date : 2026-02-04 DOI: 10.2196/76527

Britta Westerberg, Karin Jacobson, Maria Unenge Hallerbäck, Susanne Bejerot, Fredrik Holländare

Background: To meet the needs of individuals diagnosed with autism, internet-based interventions have been developed with a variety of objectives. A deeper understanding of the mechanisms of change may help tailor interventions to individual needs. The communicative behaviors of individuals with autism participating in text-based internet-based interventions remain largely unexplored, as do their potential relations to clinical outcomes. An improved understanding of participants' behaviors may help therapists better tailor support, promote engagement, and enhance treatment outcomes.

Objective: This study aimed to explore the communicative behaviors of individuals with autism participating in an internet-based intervention and to examine whether different behavioral patterns were associated with treatment outcomes or treatment adherence.

Methods: Messages from 34 participants enrolled in an 18-week internet-based cognitive behavioral therapy program were analyzed using abductive qualitative content analysis. Correlational analyses were used to examine the relationships between qualitative categories and change scores on outcome measures and rates of module completion.

Results: Fourteen behavioral categories were identified and grouped into three overarching domains: (1) "This is me," which encompasses the participants' narratives on identity, personality, autistic functioning, current and past circumstances, and worldview; (2) "Working with the treatment," which included statements related to engagement with the treatment process; and (3) "I struggle," which comprised of past and present negative experiences and challenges. Correlational analyses revealed associations between several behavioral categories and improvements in quality of life and treatment adherence.

Conclusions: The findings highlight the importance of self-narrative formulation among individuals with autism and suggest that certain communicative behaviors-particularly those involving identity reflection and recognition of treatment-related gains-were positively associated with therapeutic outcomes. The findings enhance our understanding of how individuals with autism engage in internet-based cognitive behavioral therapy and may serve as a valuable source of information for therapists when guiding expectations regarding client outcomes and identifying participants who may benefit from additional support.

Trial registration: ClinicalTrials.gov NCT03570372; https://clinicaltrials.gov/study/NCT03570372.

背景：为了满足被诊断为自闭症的个体的需求，基于互联网的干预措施已经被开发出来，目的多种多样。对变化机制的更深入了解可能有助于根据个人需求量身定制干预措施。参与基于文本的互联网干预的自闭症个体的交流行为在很大程度上仍未被探索，它们与临床结果的潜在关系也是如此。对参与者行为的更好理解可以帮助治疗师更好地定制支持，促进参与，并提高治疗效果。目的：本研究旨在探讨参与网络干预的自闭症个体的交流行为，并检验不同的行为模式是否与治疗结果或治疗依从性相关。方法：采用溯因定性内容分析，对34名参加为期18周的网络认知行为治疗项目的参与者的信息进行分析。相关分析用于检验定性类别与结果测量和模块完成率的变化分数之间的关系。结果：确定了14种行为类别，并将其分为三个主要领域：(1)“这就是我”，包括参与者对身份、个性、自闭症功能、当前和过去情况以及世界观的叙述；(2)“与治疗一起工作”，包括与参与治疗过程有关的陈述；(3)“我挣扎”，包括过去和现在的负面经历和挑战。相关分析揭示了几种行为类别与生活质量改善和治疗依从性之间的关联。结论：研究结果强调了自闭症患者自我叙述形成的重要性，并表明某些交流行为——特别是那些涉及身份反思和对治疗相关成果的认识的行为——与治疗结果呈正相关。这些发现增强了我们对自闭症患者如何参与基于互联网的认知行为治疗的理解，并且可以作为治疗师在指导对客户结果的期望和确定可能从额外支持中受益的参与者时的宝贵信息来源。试验注册：ClinicalTrials.gov NCT03570372；https://clinicaltrials.gov/study/NCT03570372。

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引用次数: 0

Digital Phenotyping for Adolescent Mental Health: Feasibility Study Using Machine Learning to Predict Mental Health Risk From Active and Passive Smartphone Data. 青少年心理健康的数字表型：利用机器学习从主动和被动智能手机数据预测心理健康风险的可行性研究。

IF 6 2区医学 Q1 HEALTH CARE SCIENCES & SERVICES

Journal of Medical Internet Research

Pub Date : 2026-02-04 DOI: 10.2196/72501

Balasundaram Kadirvelu, Teresa Bellido Bel, Aglaia Freccero, Martina Di Simplico, Dasha Nicholls, A Aldo Faisal

Background: Adolescents are particularly vulnerable to mental disorders, with over 75% of lifetime cases emerging before the age of 25 years. Yet most young people with significant symptoms do not seek support. Digital phenotyping, leveraging active (self-reported) and passive (sensor-based) data from smartphones, offers a scalable, low-burden approach for early risk detection. Despite this potential, its application in school-going adolescents from general (nonclinical) populations remains limited, leaving a critical gap in community-based prevention efforts.Objective: This study evaluated the feasibility of using a smartphone app to predict mental health risks in nonclinical adolescents by integrating active and passive data streams within a machine learning (ML) framework. We examined the utility of this approach for identifying risks related to internalizing and externalizing difficulties, eating disorders, insomnia, and suicidal ideation.Methods: Participants (n=103; mean age 16.1 years, SD 1.0) from 3 UK secondary schools used the Mindcraft app (Brain and Behaviour Lab) for 14 days, providing daily self-reports (eg, mood, sleep, and loneliness) and continuous passive sensor data (eg, location, step count, and app usage). We developed a deep learning model incorporating contrastive pretraining with triplet margin loss to stabilize user-specific behavioral patterns, followed by supervised fine-tuning for binary classification of 4 mental health outcomes, namely, the Strengths and Difficulties Questionnaire (SDQ)-high risk, insomnia, suicidal ideation, and eating disorder. Performance was assessed using leave-one-subject-out cross-validation (LOSO-CV), with balanced accuracy as the primary metric. Comparative analyses were conducted using CatBoost (Yandex) and multilayer perceptron (MLP) models without pretraining. Feature importance was assessed using Shapley Additive Explanations (SHAP) values, and associations between key digital features and clinical scales were analyzed.Results: Integration of active and passive data outperformed single-modality models, achieving mean balanced accuracies of 0.71 (0.03) for SDQ-high risk, 0.67 (0.04) for insomnia, 0.77 (0.03) for suicidal ideation, and 0.70 (0.03) for eating disorder. The contrastive learning approach improved representation stability and predictive robustness. SHAP analysis highlighted clinically relevant features, such as negative thinking and location entropy, underscoring the complementary value of combining subjective and objective data. Correlation analyses confirmed meaningful associations between key digital features and mental health outcomes. Performance in an independent external validation cohort (n=45) achieved balanced accuracies of 0.63-0.72 across outcomes, suggesting generalizability to new settings.Conclusions: This study demonstrates the feasibility and uti

背景：青少年特别容易受到精神障碍的影响，超过75%的终生病例出现在25岁之前。然而，大多数有明显症状的年轻人并不寻求帮助。利用智能手机主动（自我报告）和被动（基于传感器）数据的数字表型，为早期风险检测提供了一种可扩展、低负担的方法。尽管有这种潜力，但它在普通（非临床）人群中学龄青少年中的应用仍然有限，在以社区为基础的预防工作中留下了重大空白。目的：本研究通过在机器学习（ML）框架内整合主动和被动数据流，评估使用智能手机应用程序预测非临床青少年心理健康风险的可行性。我们研究了这种方法在识别与内在化和外在化困难、饮食失调、失眠和自杀意念相关的风险方面的效用。方法：来自3所英国中学的参与者（n=103，平均年龄16.1岁，SD 1.0）使用Mindcraft应用程序（大脑和行为实验室）14天，提供每日自我报告（如情绪、睡眠和孤独感）和连续的被动传感器数据（如位置、步数和应用程序使用情况）。我们开发了一个深度学习模型，将对比预训练与三联体边际损失相结合，以稳定用户特定的行为模式，然后对4种心理健康结果进行监督微调，即优势和困难问卷(SDQ)-高风险，失眠，自杀意念和饮食失调。使用留一受试者的交叉验证（LOSO-CV）评估效果，以平衡准确性为主要指标。使用CatBoost （Yandex）和未经预训练的多层感知器（MLP）模型进行比较分析。使用Shapley加性解释（SHAP）值评估特征重要性，并分析关键数字特征与临床量表之间的关联。结果：主动和被动数据的整合优于单模态模型，sdq -高风险的平均平衡精度为0.71(0.03)，失眠的平均平衡精度为0.67(0.04)，自杀意念的平均平衡精度为0.77(0.03)，饮食失调的平均平衡精度为0.70（0.03）。对比学习方法提高了表征稳定性和预测鲁棒性。SHAP分析突出了消极思维、位置熵等临床相关特征，强调主客观数据相结合的互补价值。相关分析证实了关键数字特征与心理健康结果之间有意义的关联。在独立的外部验证队列（n=45）中，各结果的准确性达到了0.63-0.72的平衡，表明了对新设置的可推广性。结论：本研究证明了基于智能手机的数字表型预测非临床学龄期青少年心理健康风险的可行性和实用性。通过将主动和被动数据与先进的机器建模技术相结合，该方法有望在社区环境中进行早期检测和可扩展的干预策略。

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引用次数: 0

Effect of Digital Health Interventions on College Students' Lifestyle Behaviors: Systematic Review. 数字健康干预对大学生生活方式行为的影响：系统评价。

IF 6 2区医学 Q1 HEALTH CARE SCIENCES & SERVICES

Journal of Medical Internet Research

Pub Date : 2026-02-04 DOI: 10.2196/82192

Qingyuan Zhou, Jiajun Jiang, Zhihua Yin, Ruishi Fan

Background: College students undergo a critical transition from adolescence to adulthood, during which lifestyle behaviors such as physical activity, sedentary behavior, diet, and sleep are key determinants of long-term health. Digital health interventions (DHIs) are increasingly recognized as a promising strategy for improving these behaviors among college students.Objective: This systematic review aims to evaluate the effectiveness and applicability of DHIs targeting lifestyle behaviors among college students by analyzing intervention objectives, modalities, functionalities, outcomes, and other key characteristics.Methods: In accordance with the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) 2020 guidelines, multiple scientific databases, including Scopus, Web of Science, PubMed, MEDLINE, PsycINFO, SPORTDiscus, ProQuest Central, APA PsycArticles, ERIC, and Academic Search Premier, were searched for studies published between January 2010 and December 2025 (initial search: August 5, 2025; updated search: December 27, 2025). The inclusion criteria were original empirical studies on DHIs targeting lifestyle behaviors (physical activity, sedentary behavior, diet, and sleep) among college students, published in English. Studies focusing on nondigital interventions, lacking sufficient methodological details, or not reporting lifestyle behavior-related outcomes were excluded. Quality assessment was conducted in 2 stages: all studies were first evaluated using the Mixed Methods Appraisal Tool (2018 version), followed by Risk of Bias 2 for randomized controlled trials and Joanna Briggs Institute critical appraisal tools for nonrandomized studies. A narrative synthesis was used to present and synthesize the findings.Results: A total of 2998 records were retrieved, of which 46 publications met the inclusion criteria. These included 30 (65%) studies related to physical activity, 26 (57%) studies to diet, 10 (22%) studies related to sedentary behavior, and 6 (13%) studies related to sleep. This review enabled an examination of the effects of DHIs on college students' lifestyle behaviors. DHIs primarily used mobile apps, web-based platforms, and mobile communication technologies, with core functionalities such as education, guidance, monitoring, and prompting. DHIs were more effective in improving physical activity and diet; however, evidence for reducing sedentary behavior and improving sleep remained limited. Of the 46 studies, 31 (67%) reported positive effects, with larger sample sizes and intervention durations of 8-16 weeks being associated with more favorable outcomes.Conclusions: This review focuses on college students, addressing a gap in the literature that often centers on general adult populations. Unlike previous reviews that focus on a single behavior, this study integrates multiple lifestyle behaviors

背景：大学生正处于从青春期到成年期的关键过渡时期，在此期间，体育活动、久坐行为、饮食和睡眠等生活方式行为是长期健康的关键决定因素。数字健康干预（DHIs）越来越被认为是改善大学生这些行为的一种有前途的策略。目的：本系统综述旨在通过分析干预目标、方式、功能、结果和其他关键特征，评估DHIs针对大学生生活方式行为的有效性和适用性。方法：根据PRISMA（系统评价和荟萃分析首选报告项目）2020指南，检索2010年1月至2025年12月间发表的研究，包括Scopus、Web of Science、PubMed、MEDLINE、PsycINFO、SPORTDiscus、ProQuest Central、APA PsycArticles、ERIC和Academic Search Premier等多个科学数据库（初始检索：2025年8月5日；更新检索：2025年12月27日）。纳入标准为针对大学生生活方式行为（体育活动、久坐行为、饮食和睡眠）的DHIs的原始实证研究，以英文发表。研究集中于非数字干预，缺乏足够的方法细节，或没有报告生活方式行为相关的结果被排除在外。质量评估分两个阶段进行：首先使用混合方法评估工具（2018版）对所有研究进行评估，然后使用随机对照试验的偏倚风险2和乔安娜布里格斯研究所对非随机研究的关键评估工具进行评估。采用叙事综合的方法来呈现和综合研究结果。结果：共检索到2998篇文献，其中符合纳入标准的文献46篇。其中包括30项（65%）与体育活动有关的研究，26项（57%）与饮食有关的研究，10项（22%）与久坐行为有关的研究，6项（13%）与睡眠有关的研究。本综述旨在探讨DHIs对大学生生活方式行为的影响。DHIs主要使用移动应用程序、基于web的平台和移动通信技术，具有教育、指导、监控和提示等核心功能。DHIs在改善身体活动和饮食方面更有效；然而，减少久坐行为和改善睡眠的证据仍然有限。在46项研究中，31项（67%）报告了积极效果，样本量较大，干预持续时间为8-16周，结果更有利。结论：这篇综述的重点是大学生，填补了文献中通常以普通成年人为中心的空白。与以往关注单一行为的综述不同，本研究整合了多种生活方式行为，并评估了不同方式和功能的DHIs。这些贡献有助于完善大学生未来的DHIs，并为高等教育中的健康促进策略提供信息。尽管DHIs显示出改善生活方式行为的潜力，但其长期有效性的证据仍然有限。未来的干预措施应优先考虑多行为整合、互动性和人群差异化设计，以提高准确性、可持续性和公平性。本研究有几个局限性，包括与样本代表性、干预改进和方法严谨性有关的问题。试验注册：PROSPERO CRD420251119078；https://www.crd.york.ac.uk/PROSPERO/view/CRD420251119078。

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引用次数: 0

Transformer-Based Topic Modeling: Characterizing Cannabis Product Adverse Experiences Self-Reported as Requiring Medical Attention on Reddit. 基于变压器的主题建模：表征大麻产品不良经历自我报告为需要医疗关注在Reddit上。

IF 6 2区医学 Q1 HEALTH CARE SCIENCES & SERVICES

Journal of Medical Internet Research

Pub Date : 2026-02-04 DOI: 10.2196/82661

Tim Ken Mackey, Matthew C Nali, Meng Zhen Larsen, Zhuoran Li, Cassandra L Taylor, Beverly Wolpert, Catharine Trice

This study uses keyword filtering, a transformer-based algorithm, and inductive content coding to identify and characterize cannabis adverse experiences as discussed on the social media platform Reddit and reports a total of 1177 self-reported adverse experiences requiring medical attention.

本研究使用关键词过滤、基于变压器的算法和归纳内容编码来识别和描述社交媒体平台Reddit上讨论的大麻不良经历，共报告了1177例需要就医的自我报告不良经历。

引用次数: 0

The Effectiveness of the Headspace App for Improving Sleep: Randomized Controlled Trial. Headspace应用程序改善睡眠的有效性：随机对照试验。

IF 6 2区医学 Q1 HEALTH CARE SCIENCES & SERVICES

Journal of Medical Internet Research

Pub Date : 2026-02-04 DOI: 10.2196/56287

Zoltan Andre Torok, Larisa Gavrilova, Amish Patel, Matthew Jason Zawadzki

Background: Improving sleep is critical for optimizing short-term and long-term health. Although in-person meditation training has been shown to impact sleep positively, there is a gap in our understanding of whether apps that teach self-guided meditation are also effective.

Objective: This study aims to test whether Headspace (Headspace, Inc) improves sleep quality, tiredness, sleep duration, and sleep efficiency.

Methods: Staff employees (N=135; mean age 38.1, SD 10.9; 75.0% female; 59.3% non-Hispanic White; 27.1% Hispanic) from a university in California's San Joaquin Valley participated in the study. Participants were randomized to complete 10 minutes of daily meditation via the Headspace app for 8 weeks or waitlist control. Sleep assessments were taken for 4 consecutive days at baseline, and then for 4-day bursts at 2, 5, and 8 weeks after randomization. Sleep quality and subjective sleep duration were assessed each morning with a sleep diary, tiredness was assessed throughout the day using ecological momentary assessment, and objective sleep duration and efficiency were measured using a Fitbit Charge 2.

Results: Both subjective and objective sleep outcomes improved. For subjective sleep outcomes, multilevel modeling revealed that those in the Headspace condition, compared to the control group, reported better sleep quality at sessions 2 (β=0.48, SE=0.12; P<.001), 5 (β=0.91, SE=0.13; P<.001), and 8 (β=0.69, SE=0.15; P<.001) compared to baseline, and a decrease in tiredness at session 5 (β=-0.58, SE=0.19; P=.001) compared to baseline, but not at sessions 2 or 8. For objective sleep outcomes, those in the Headspace condition compared to the control group had longer sleep durations at session 5 (β=23.96, SE=12.19; P=.04) compared to baseline, but not at sessions 2 or 8. There were no significant effects for sleep efficiency.

Conclusions: This study continues adding to the ever-developing field of mobile health apps by demonstrating that Headspace can positively impact sleep quality, tiredness, and duration.

背景：改善睡眠对优化短期和长期健康至关重要。尽管面对面的冥想训练已被证明对睡眠有积极影响，但我们对教授自我引导冥想的应用程序是否也有效的理解存在差距。目的：本研究旨在检验Headspace （Headspace, Inc .）是否能改善睡眠质量、疲劳程度、睡眠持续时间和睡眠效率。方法：加州圣华金河谷一所大学的员工（N=135名，平均年龄38.1岁，SD 10.9，女性75.0%，非西班牙裔白人59.3%，西班牙裔27.1%）参与研究。参与者被随机分配到每天通过Headspace应用程序进行10分钟的冥想，持续8周，或者接受候补名单控制。在基线连续4天进行睡眠评估，然后在随机化后的2、5和8周进行4天的睡眠评估。每天早上用睡眠日记评估睡眠质量和主观睡眠持续时间，用生态瞬间评估全天的疲劳程度，用Fitbit Charge 2测量客观睡眠持续时间和效率。结果：主观和客观睡眠结果均有改善。对于主观睡眠结果，多层次建模显示，与对照组相比，Headspace条件下的受试者在第2次会话中报告了更好的睡眠质量（β=0.48， SE=0.12）；结论：本研究通过证明Headspace对睡眠质量、疲劳和持续时间有积极影响，继续为不断发展的移动健康应用领域增加了新的内容。

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引用次数: 0

The Impact of a Health Coaching App on the Subjective Well-Being of Individuals With Multimorbidity: Mixed Methods Study. 健康指导应用程序对多重疾病个体主观幸福感的影响：混合方法研究

IF 6 2区医学 Q1 HEALTH CARE SCIENCES & SERVICES

Journal of Medical Internet Research

Pub Date : 2026-02-04 DOI: 10.2196/78738

Isabelle Symes, Alexandra Burton, Daniela Mercado, Feifei Bu

Background: Multimorbidity, the coexistence of 2 or more chronic conditions, is associated with poor well-being. Health coaching apps offer cost-effective and accessible support. However, there is a lack of evidence of the impact of health coaching apps on individuals with multimorbidity.

Objective: This study aimed to assess the impact and acceptability of a health coaching app (the Holly Health [HH] app) on the subjective well-being (SWB) of adults with multimorbidity.

Methods: This study used an explanatory-sequential mixed methods design, with quantitative secondary data analysis in the first phase and qualitative interviews in the second phase. In the quantitative phase (n=565), pre- and post-SWB (Office for National Statistics' 4 personal well-being questions [ONS4]) scores from existing app users with multimorbidity were analyzed using Bayesian growth curve modeling to assess the impact of HH. In the qualitative phase (n=22), data were collected via semistructured interviews and analyzed using reflexive thematic analysis. Mechanisms of action that supported SWB were categorized using the Multi-Level Leisure Mechanisms Framework.

Results: There was a significant increase in life satisfaction (Coef.=0.71, 95% highest density interval [HDI] 0.52-0.89), worthwhileness (Coef.=0.62, 95% HDI 0.43-0.81), and happiness (Coef.=0.74, 95% HDI 0.54-0.92) and a decrease in anxiety (Coef.=-0.50, 95% HDI -0.74 to -0.25) before and after using the HH app. Overall, 8 acceptable app features activated 5 mechanisms of action, including behavioral, psychological, and social mechanisms. Three additional factors influenced the acceptability of the health coaching app: type of chronic condition, availability of time, and the use of other support tools.

Conclusions: The study demonstrates that health coaching apps could be effective and acceptable support tools for individuals with multimorbidity. This study contributes to understanding why health coaching apps support SWB and could be used to inform the development of future digital health interventions in multimorbidity.

背景：多重疾病，即两种或两种以上慢性疾病的共存，与健康状况不佳有关。健康指导应用程序提供成本效益高且易于获取的支持。然而，缺乏证据表明健康指导应用程序对患有多种疾病的个人有影响。目的：本研究旨在评估健康指导应用程序（Holly health [HH]应用程序）对多重疾病成人主观幸福感（SWB）的影响和可接受性。方法：本研究采用解释-序列混合方法设计，第一阶段采用定量二手资料分析，第二阶段采用定性访谈。在定量阶段（n=565），使用贝叶斯增长曲线模型分析患有多种疾病的现有应用程序用户在swb（国家统计局的4个个人幸福感问题[ONS4]）之前和之后的得分，以评估HH的影响。在定性阶段（n=22），通过半结构化访谈收集数据，并使用反身性主题分析进行分析。使用多层次休闲机制框架对支持SWB的作用机制进行了分类。结果：使用HH应用程序前后，生活满意度（Coef =0.71, 95%最高密度区间[HDI] 0.52-0.89）、价值感（Coef =0.62, 95% HDI 0.43-0.81）和幸福感（Coef =0.74, 95% HDI 0.54-0.92）显著增加，焦虑感（Coef =-0.50, 95% HDI -0.74 - -0.25）显著降低。总体而言，8个可接受的应用程序功能激活了5种作用机制，包括行为机制、心理机制和社会机制。另外三个因素影响了健康指导应用的可接受性：慢性病的类型、时间的可用性以及其他支持工具的使用。结论：本研究表明，健康指导应用程序可以成为多种疾病患者有效和可接受的支持工具。这项研究有助于理解为什么健康指导应用程序支持SWB，并可用于为未来多疾病数字健康干预措施的发展提供信息。

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引用次数: 0

Effects of Digital Health Interventions to Promote Safer Sex Behaviors Among Youth: Systematic Review and Bayesian Network Meta-Analysis. 数字健康干预促进青少年安全性行为的效果：系统评价和贝叶斯网络元分析。

IF 6 2区医学 Q1 HEALTH CARE SCIENCES & SERVICES

Journal of Medical Internet Research

Pub Date : 2026-02-04 DOI: 10.2196/87071

Yiran Zhu, Wenwen Peng, Die Hu, Edmond Pui Hang Choi, Maritta Anneli Välimäki, Ci Zhang, Xianhong Li

Background: Youth aged 15-24 years carry a disproportionate HIV/sexually transmitted infections (STIs) burden. In recent years, different modalities of digital health interventions (DHIs) have been explored to promote safer sex behaviors among youth, but their comparative effectiveness across modalities and relative to nondigital interventions (NDIs) remains unclear.Objective: This study aimed to compare DHI modalities on safer sex behaviors and HIV/STI incidence, rank modalities using Bayesian network meta-analysis (NMA), and position their effectiveness relative to NDIs.Methods: A systematic review and Bayesian NMA of randomized controlled trials were conducted by comprehensively searching PubMed, EMBASE, Web of Science, and Cochrane Library (inception to November 2025). Eligible studies were those that enrolled youth aged 15-24 years and evaluated mobile app-based intervention, telecommunication-based intervention (TCI), static web-based intervention (SWI), or interactive online-based intervention (IOI)-with an NDI or another DHI. Primary outcomes were condom use at last sexual contact, consistent condom use, and proportion of condom use. Secondary outcomes included condom use self-efficacy, number of sexual partners, and STI incidence (including HIV). Risk of bias was assessed with the Cochrane Risk of Bias 2 tool, and certainty of evidence with GRADE/CINeMA (Confidence in NMA). Bayesian random-effects NMAs estimated odds ratios (ORs) with 95% credible intervals (CrIs), and complementary frequentist NMAs provided 95% CIs and 95% prediction intervals.Results: Twenty-four randomized controlled trials (20,134 participants) were included, forming treatment networks across 5 intervention types. TCI was the only intervention that significantly improved condom use at last sex compared with NDI (OR 1.13, 95% CrI 1.02-1.26). For consistent condom use, SWI and IOI outperformed TCI (SWI vs TCI: OR 1.77, 95% CrI 1.03-3.06; IOI vs TCI: OR 1.68, 95% CrI 1.02-2.76). For the proportion of condom use, IOI outperformed SWI (OR 1.34, 95% CrI 1.01-1.80), and mobile app-based intervention ranked highest in probability rankings, though estimates lacked precision. For STI incidence, NDI was associated with fewer STIs than SWI (OR 0.61, 95% CrI 0.46-0.82).Conclusions: This is the first NMA to compare the effectiveness of DHIs on condom use and HIV/STI outcomes among youth populations. It demonstrates that the impact of DHIs on HIV prevention varies substantially by intervention modality and outcome type. While TCI demonstrates the most consistent improvement in condom use at last sex, SWI and IOI may be more effective for promoting consistent condom use, though estimates remain imprecise. However, wide prediction intervals and low-certainty evidence suggest that self-reported behavioral changes may not translate into reductions in HIV/STI incidents wit

背景：15-24岁的青年背负着不成比例的艾滋病毒/性传播感染负担。近年来，人们探索了不同模式的数字健康干预（DHIs）来促进青少年更安全的性行为，但它们在不同模式下的相对有效性以及相对于非数字干预（ndi）的有效性仍不清楚。目的：本研究旨在比较DHI模式对安全性行为和HIV/STI发病率的影响，使用贝叶斯网络荟萃分析（NMA）对模式进行排名，并相对于ndi对其有效性进行定位。方法：综合检索PubMed、EMBASE、Web of Science、Cochrane Library（建库至2025年11月），对随机对照试验进行系统评价和贝叶斯NMA分析。符合条件的研究招募了15-24岁的青少年，并评估了基于移动应用程序的干预、基于电信的干预（TCI）、静态基于网络的干预（SWI）或交互式基于网络的干预（IOI）——采用NDI或另一种DHI。主要结局是最后一次性接触时使用避孕套、持续使用避孕套和使用避孕套的比例。次要结果包括避孕套使用的自我效能、性伴侣数量和性传播感染发生率（包括HIV）。采用Cochrane Risk of bias 2工具评估偏倚风险，并采用GRADE/CINeMA （NMA置信度）评估证据的确定性。贝叶斯随机效应nma估计的比值比（or）具有95%可信区间（CrIs），互补频率nma提供95% ci和95%预测区间。结果：纳入24项随机对照试验（20134名受试者），形成5种干预类型的治疗网络。与NDI相比，TCI是唯一能显著改善末次性行为中安全套使用的干预措施（OR 1.13, 95% CrI 1.02-1.26）。对于持续使用避孕套，SWI和IOI优于TCI （SWI vs TCI: OR 1.77, 95% CrI 1.03-3.06; IOI vs TCI: OR 1.68, 95% CrI 1.02-2.76）。对于避孕套使用的比例，IOI优于SWI (OR 1.34, 95% CrI 1.01-1.80)，基于移动应用程序的干预在概率排名中排名最高，尽管估计缺乏准确性。在性传播感染发生率方面，与SWI相比，NDI与较少的性传播感染相关（OR 0.61, 95% CrI 0.46-0.82）。结论：这是第一个比较DHIs在青年人群中避孕套使用和艾滋病毒/性传播感染结果有效性的NMA。研究表明，DHIs对艾滋病毒预防的影响因干预方式和结果类型而有很大差异。虽然TCI显示了在最后性行为中避孕套使用的最一致的改善，但SWI和IOI可能更有效地促进了避孕套的持续使用，尽管估计仍然不精确。然而，广泛的预测间隔和低确定性证据表明，如果不结合线下服务和更广泛的结构支持，自我报告的行为改变可能不会转化为艾滋病毒/性传播感染事件的减少。未来的试验可能考虑纳入标准化的结果指标和更长时间的随访，以更准确地估计DHIs的有效性，并指导以青年为中心的数字化艾滋病毒/性传播感染预防的推广。

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引用次数: 0

Correction: Culturally Adapted Guided Internet-Based Cognitive Behavioral Therapy for Hong Kong People With Depressive Symptoms: Randomized Controlled Trial. 更正：香港抑郁症患者的文化适应指导基于互联网的认知行为疗法：随机对照试验。

IF 6 2区医学 Q1 HEALTH CARE SCIENCES & SERVICES

Journal of Medical Internet Research

Pub Date : 2026-02-03 DOI: 10.2196/88495

Jia-Yan Pan, Jonas Rafi

[This corrects the article DOI: 10.2196/64303.].

[更正文章DOI: 10.2196/64303]。

引用次数: 0