<p><strong>Background: </strong>The rapid growth of telemedicine offers convenience, flexibility, and accessibility for patients to have health care services worldwide. To succeed in telemedicine, health care practitioners and telemedicine tools must engage patients through effective communication. However, a research gap exists in understanding the communication strategies used in telemedicine and how they effectively engage patients.</p><p><strong>Objective: </strong>This study aims to identify communication strategies influencing patient engagement in telemedicine with provider-patient interactions, as well as how included studies evaluate patient engagement through a systematic review.</p><p><strong>Methods: </strong>We searched the literature comprehensively using 6 databases, Web of Science, PubMed, Scopus, MEDLINE, CINAHL, and Embase, from inception to October 2025. We included empirical, English-language studies that examined communication strategies affecting patient engagement in telemedicine with provider-patient interactions. Studies lacking actual patients or provider-patient interactions in telemedicine were excluded. We used content analysis to identify texts that were related to Theme 1: the communication strategies affecting patient engagement, and Theme 2: evaluation of patient engagement. Coded texts were analyzed to develop subthemes and themes of identified communication strategies. Methods for evaluating patient engagement were summarized. A narrative synthesis was conducted because of heterogeneity across study design and outcomes. We used the Mixed Methods Appraisal Tool to assess the quality of research included in this study.</p><p><strong>Results: </strong>This study systematically reviewed 34 peer-reviewed articles, revealing 3 overarching themes of effective communication strategies that enhance patient engagement: interpersonal communication strategies, with 6 subthemes (building relationships, supportive attitude, interactive dialogic loop, nonverbal communication, professionalism and accuracy, and tailored communication); team-level communication strategies, with 3 subthemes (training and preparation, teamwork and care coordination, and cultural and linguistic sensitivity); and system-level communication strategies, with 3 subthemes (usefulness of information, ease of use, and data privacy and security). We also found that included studies predominantly used qualitative research methods, such as semistructured interviews and focus groups, to collect patient engagement data.</p><p><strong>Conclusions: </strong>This review provides an innovative synthesis of communication strategies that promote patient engagement in telemedicine by integrating interpersonal (micro), team (meso), and system-level (macro) perspectives. Unlike previous reviews that focused on single aspects or levels of communication, this study offers a holistic framework that advances theoretical understanding of how multilevel communication strategi
背景：远程医疗的快速发展为世界各地的患者提供了方便、灵活和可及性的医疗保健服务。要在远程医疗中取得成功，医疗保健从业人员和远程医疗工具必须通过有效的沟通来吸引患者。然而，在了解远程医疗中使用的沟通策略以及它们如何有效地吸引患者方面存在研究差距。目的：本研究旨在确定影响远程医疗中医患互动的沟通策略，以及纳入研究如何通过系统回顾评估患者参与度。方法：综合检索Web of Science、PubMed、Scopus、MEDLINE、CINAHL、Embase 6个数据库自成立至2025年10月的文献。我们纳入了实证的英语研究，这些研究考察了影响远程医疗中患者参与的沟通策略和提供者与患者的互动。排除了在远程医疗中缺乏实际患者或提供者-患者互动的研究。我们使用内容分析来识别与主题1（影响患者参与的沟通策略）和主题2（患者参与的评估）相关的文本。对编码文本进行分析，以制定确定的传播策略的副主题和主题。总结了评价患者敬业度的方法。由于研究设计和结果的异质性，进行了叙述性综合。我们使用混合方法评估工具来评估纳入本研究的研究质量。结果：本研究系统回顾了34篇同行评议文章，揭示了提高患者参与度的有效沟通策略的3大主题：人际沟通策略，包括6个子主题（建立关系、支持态度、互动对话循环、非语言沟通、专业性和准确性、量身定制沟通）；团队层面的沟通策略，包括3个主题（培训和准备、团队合作和护理协调、文化和语言敏感性）；以及系统级通信策略，包含3个子主题（信息的有用性、易用性以及数据隐私和安全）。我们还发现纳入的研究主要使用定性研究方法，如半结构化访谈和焦点小组，来收集患者参与数据。结论：本综述提供了一种创新的综合沟通策略，通过整合人际（微观）、团队（中观）和系统层面（宏观）的视角，促进患者参与远程医疗。与以往的研究不同，该研究提供了一个整体框架，促进了对多层次沟通策略如何共同塑造患者参与的理论理解。实际上，研究结果为寻求提高远程医疗服务质量和可持续性的卫生保健专业人员、远程医疗开发人员和政策制定者提供了可操作的指导。在现实环境中，确定的策略可以为专业培训、平台设计和政策制定提供信息，以支持以患者为中心的数字化护理。本综述首次系统地将患者参与远程医疗的沟通策略整合到所有3个层面。未来的研究应以这一框架为基础，制定和验证患者参与的定量措施，并检查沟通策略与远程医疗结果之间的关系。
{"title":"Communication Strategies to Promote Patient Engagement in Telemedicine: Systematic Review.","authors":"Yangna Hu, Cindy Sing Bik Ngai, Rui Jiang","doi":"10.2196/85456","DOIUrl":"10.2196/85456","url":null,"abstract":"<p><strong>Background: </strong>The rapid growth of telemedicine offers convenience, flexibility, and accessibility for patients to have health care services worldwide. To succeed in telemedicine, health care practitioners and telemedicine tools must engage patients through effective communication. However, a research gap exists in understanding the communication strategies used in telemedicine and how they effectively engage patients.</p><p><strong>Objective: </strong>This study aims to identify communication strategies influencing patient engagement in telemedicine with provider-patient interactions, as well as how included studies evaluate patient engagement through a systematic review.</p><p><strong>Methods: </strong>We searched the literature comprehensively using 6 databases, Web of Science, PubMed, Scopus, MEDLINE, CINAHL, and Embase, from inception to October 2025. We included empirical, English-language studies that examined communication strategies affecting patient engagement in telemedicine with provider-patient interactions. Studies lacking actual patients or provider-patient interactions in telemedicine were excluded. We used content analysis to identify texts that were related to Theme 1: the communication strategies affecting patient engagement, and Theme 2: evaluation of patient engagement. Coded texts were analyzed to develop subthemes and themes of identified communication strategies. Methods for evaluating patient engagement were summarized. A narrative synthesis was conducted because of heterogeneity across study design and outcomes. We used the Mixed Methods Appraisal Tool to assess the quality of research included in this study.</p><p><strong>Results: </strong>This study systematically reviewed 34 peer-reviewed articles, revealing 3 overarching themes of effective communication strategies that enhance patient engagement: interpersonal communication strategies, with 6 subthemes (building relationships, supportive attitude, interactive dialogic loop, nonverbal communication, professionalism and accuracy, and tailored communication); team-level communication strategies, with 3 subthemes (training and preparation, teamwork and care coordination, and cultural and linguistic sensitivity); and system-level communication strategies, with 3 subthemes (usefulness of information, ease of use, and data privacy and security). We also found that included studies predominantly used qualitative research methods, such as semistructured interviews and focus groups, to collect patient engagement data.</p><p><strong>Conclusions: </strong>This review provides an innovative synthesis of communication strategies that promote patient engagement in telemedicine by integrating interpersonal (micro), team (meso), and system-level (macro) perspectives. Unlike previous reviews that focused on single aspects or levels of communication, this study offers a holistic framework that advances theoretical understanding of how multilevel communication strategi","PeriodicalId":16337,"journal":{"name":"Journal of Medical Internet Research","volume":"28 ","pages":"e85456"},"PeriodicalIF":6.0,"publicationDate":"2026-01-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12873561/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146010625","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Jacqueline Hodges, Wendy Cohn, Amanda Castel, Tabor Flickinger, Ava Lena Waldman, Michelle Hilgart, Olivia Kirby, Sylvia Caldwell, Karen Ingersoll
<p><strong>Background: </strong>Evaluating implementation of digital health interventions (DHIs) in practice settings is complex, involving diverse users and multistep processes. Proactive planning can ensure implementation determinants and outcomes are captured for hybrid studies, but operational guidance for designing or planning hybrid DHI studies is limited.</p><p><strong>Objective: </strong>This study aimed to proactively define, prioritize, and operationalize measurement of implementation outcomes and determinants for a DHI hybrid effectiveness-implementation trial. We describe unique advantages and limitations of planning the trial implementation evaluation among a large-scale cohort study population and share results of a pretrial organizational readiness assessment.</p><p><strong>Methods: </strong>We planned a cluster-randomized, type II hybrid effectiveness-implementation trial testing PositiveLinks, a smartphone app for HIV care, compared to usual care (n=6 sites per arm), among HIV outpatient sites in the DC Cohort Longitudinal HIV Study in Washington, DC. We (1) defined components of the DHI and associated implementation strategy; (2) selected implementation science frameworks to accomplish evaluation aims; (3) mapped framework dimensions, domains, and constructs to implementation strategy steps; (4) modified or created instruments to collect data for implementation outcome measures and determinants; and (5) developed a compatible implementation science data collection and management plan. Provider baseline surveys administered at intervention sites probed usage of digital tools and assessed provider readiness for implementation with the Organizational Readiness to Implement Change tool.</p><p><strong>Results: </strong>We specified DHI and implementation strategy toward planning measurement of DHI and broader program reach and adoption. Mapping of implementation strategy steps to the Reach Effectiveness Adoption Implementation Maintenance framework prompted considerations for how to capture understudied aspects of each dimension: denominators and demographic representativeness within reach or adoption, and provider or organization-level adaptations, dose, and fidelity within the implementation dimension. Our process also prompted the creation of tools to obtain detailed determinants across domains and constructs of the Consolidated Framework for Implementation Research within a large sample at multiple time points. Some aspects of real-world PositiveLinks implementation were not reflected within the planned hybrid trial (eg, research assistants selected as de facto site implementation leads) or were modified to preserve internal validity of effectiveness measurement (eg, "Community of Practice"). Providers and research assistants (n=17) at intervention sites self-reported high baseline use of digital tools to communicate with patients. Readiness assessment revealed high median (48, IQR 45-54) total Organizational Readiness to Impleme
{"title":"A Complex Digital Health Intervention to Support People With HIV: Organizational Readiness Survey Study and Preimplementation Planning for a Hybrid Effectiveness-Implementation Study.","authors":"Jacqueline Hodges, Wendy Cohn, Amanda Castel, Tabor Flickinger, Ava Lena Waldman, Michelle Hilgart, Olivia Kirby, Sylvia Caldwell, Karen Ingersoll","doi":"10.2196/76327","DOIUrl":"10.2196/76327","url":null,"abstract":"<p><strong>Background: </strong>Evaluating implementation of digital health interventions (DHIs) in practice settings is complex, involving diverse users and multistep processes. Proactive planning can ensure implementation determinants and outcomes are captured for hybrid studies, but operational guidance for designing or planning hybrid DHI studies is limited.</p><p><strong>Objective: </strong>This study aimed to proactively define, prioritize, and operationalize measurement of implementation outcomes and determinants for a DHI hybrid effectiveness-implementation trial. We describe unique advantages and limitations of planning the trial implementation evaluation among a large-scale cohort study population and share results of a pretrial organizational readiness assessment.</p><p><strong>Methods: </strong>We planned a cluster-randomized, type II hybrid effectiveness-implementation trial testing PositiveLinks, a smartphone app for HIV care, compared to usual care (n=6 sites per arm), among HIV outpatient sites in the DC Cohort Longitudinal HIV Study in Washington, DC. We (1) defined components of the DHI and associated implementation strategy; (2) selected implementation science frameworks to accomplish evaluation aims; (3) mapped framework dimensions, domains, and constructs to implementation strategy steps; (4) modified or created instruments to collect data for implementation outcome measures and determinants; and (5) developed a compatible implementation science data collection and management plan. Provider baseline surveys administered at intervention sites probed usage of digital tools and assessed provider readiness for implementation with the Organizational Readiness to Implement Change tool.</p><p><strong>Results: </strong>We specified DHI and implementation strategy toward planning measurement of DHI and broader program reach and adoption. Mapping of implementation strategy steps to the Reach Effectiveness Adoption Implementation Maintenance framework prompted considerations for how to capture understudied aspects of each dimension: denominators and demographic representativeness within reach or adoption, and provider or organization-level adaptations, dose, and fidelity within the implementation dimension. Our process also prompted the creation of tools to obtain detailed determinants across domains and constructs of the Consolidated Framework for Implementation Research within a large sample at multiple time points. Some aspects of real-world PositiveLinks implementation were not reflected within the planned hybrid trial (eg, research assistants selected as de facto site implementation leads) or were modified to preserve internal validity of effectiveness measurement (eg, \"Community of Practice\"). Providers and research assistants (n=17) at intervention sites self-reported high baseline use of digital tools to communicate with patients. Readiness assessment revealed high median (48, IQR 45-54) total Organizational Readiness to Impleme","PeriodicalId":16337,"journal":{"name":"Journal of Medical Internet Research","volume":"28 ","pages":"e76327"},"PeriodicalIF":6.0,"publicationDate":"2026-01-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12823349/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146018602","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
<p><strong>Background: </strong>Artificial intelligence (AI) tools are widely and freely available for clinical use. Understanding hospitalists' real-world adoption patterns in the absence of organizational endorsement is essential for healthcare institutions to develop governance frameworks and optimize AI integration.</p><p><strong>Objective: </strong>The objective of this study was to investigate hospitalist use of AI, examining the AI platforms being utilized, frequency of use, and clinical contexts of application. We hypothesized that AI use is more common among younger, less experienced hospitalists, albeit at an overall low frequency.</p><p><strong>Methods: </strong>An anonymous online survey was distributed via email to all 70 hospitalists (physicians, nurse practitioners, physician assistants) providing direct patient care at a large urban academic tertiary care hospital. Demographic data, AI platform used if any, purpose(s) for AI use, and frequency of use information was collected. CHERRIES checklist was used for creating, testing, administering, and reporting the results of the survey. Chi-square test was used where possible; when expected cell values were low, Fisher's exact test was used instead. Friedman test and pairwise Wilcoxon signed-rank test were used for analyzing the differences between frequency of AI use for various tasks. Likert-scale responses to frequency questions (Never, Rarely, Sometimes, Often, Always) were converted to ordinal values (1 - 5, respectively) to facilitate analysis.</p><p><strong>Results: </strong>Of 70 providers, 54 (77.1%) responded to the survey. No significant differences in AI usage were observed across shift type, years of practice, time allocation to hospitalist duties, sex, age, or provider designation, contrary to our hypothesis. Overall, 36 of 54 respondents (66.7%, 95% CI 53.4%-77.8%) reported using AI in clinical practice. OpenEvidence was the most used platform (28/54, 51.9%), far exceeding general-purpose tools like ChatGPT (4/54, 7.4%), suggesting preference for medical-specific platforms. Among non-users, primary concerns were AI accuracy and preference for established resources. The most common application was answering miscellaneous clinical questions (32/36, 88.9%), generating differential diagnoses (31/36, 86.1%) and determining management options (31/36, 86.1%), with much lower use for patient education materials (16/36, 44.4%). There was a statistically significant difference in the frequency of AI use across these clinical scenarios (Friedman test chi-square statistic 37.596, df 4, P<.001). Pairwise comparisons using the Wilcoxon signed-rank test revealed significant differences between use for answering miscellaneous questions and confirming suspected diagnosis (P=.003) and generating patient education materials (P=.004) respectively. Most respondents reported using AI for under 25% of clinical encounters across all use cases.</p><p><strong>Conclusions: </strong>Two-thirds of h
{"title":"Patterns of Artificial Intelligence Use in Clinical Work by Hospitalists: A Survey Study.","authors":"Prabhava Bagla, Jasmah Hanna, Bhargav Marthambadi, Stacey Watkins","doi":"10.2196/85973","DOIUrl":"https://doi.org/10.2196/85973","url":null,"abstract":"<p><strong>Background: </strong>Artificial intelligence (AI) tools are widely and freely available for clinical use. Understanding hospitalists' real-world adoption patterns in the absence of organizational endorsement is essential for healthcare institutions to develop governance frameworks and optimize AI integration.</p><p><strong>Objective: </strong>The objective of this study was to investigate hospitalist use of AI, examining the AI platforms being utilized, frequency of use, and clinical contexts of application. We hypothesized that AI use is more common among younger, less experienced hospitalists, albeit at an overall low frequency.</p><p><strong>Methods: </strong>An anonymous online survey was distributed via email to all 70 hospitalists (physicians, nurse practitioners, physician assistants) providing direct patient care at a large urban academic tertiary care hospital. Demographic data, AI platform used if any, purpose(s) for AI use, and frequency of use information was collected. CHERRIES checklist was used for creating, testing, administering, and reporting the results of the survey. Chi-square test was used where possible; when expected cell values were low, Fisher's exact test was used instead. Friedman test and pairwise Wilcoxon signed-rank test were used for analyzing the differences between frequency of AI use for various tasks. Likert-scale responses to frequency questions (Never, Rarely, Sometimes, Often, Always) were converted to ordinal values (1 - 5, respectively) to facilitate analysis.</p><p><strong>Results: </strong>Of 70 providers, 54 (77.1%) responded to the survey. No significant differences in AI usage were observed across shift type, years of practice, time allocation to hospitalist duties, sex, age, or provider designation, contrary to our hypothesis. Overall, 36 of 54 respondents (66.7%, 95% CI 53.4%-77.8%) reported using AI in clinical practice. OpenEvidence was the most used platform (28/54, 51.9%), far exceeding general-purpose tools like ChatGPT (4/54, 7.4%), suggesting preference for medical-specific platforms. Among non-users, primary concerns were AI accuracy and preference for established resources. The most common application was answering miscellaneous clinical questions (32/36, 88.9%), generating differential diagnoses (31/36, 86.1%) and determining management options (31/36, 86.1%), with much lower use for patient education materials (16/36, 44.4%). There was a statistically significant difference in the frequency of AI use across these clinical scenarios (Friedman test chi-square statistic 37.596, df 4, P<.001). Pairwise comparisons using the Wilcoxon signed-rank test revealed significant differences between use for answering miscellaneous questions and confirming suspected diagnosis (P=.003) and generating patient education materials (P=.004) respectively. Most respondents reported using AI for under 25% of clinical encounters across all use cases.</p><p><strong>Conclusions: </strong>Two-thirds of h","PeriodicalId":16337,"journal":{"name":"Journal of Medical Internet Research","volume":" ","pages":""},"PeriodicalIF":6.0,"publicationDate":"2026-01-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146046700","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
<p><strong>Background: </strong>Daytime sleepiness is prevalent among adolescents and linked to multiple health and functional impairments. Prior research has identified digital media use and insufficient sleep as key predictors, yet the reciprocal longitudinal associations among screen time, sleep, and daytime sleepiness remain understudied.</p><p><strong>Objective: </strong>This study examined the between- and within-person reciprocal longitudinal associations among adolescents' screen time, bedtime, and daytime sleepiness. It also tested whether potential adverse effects of screen time were less pronounced over time among adolescents who limited their screen exposure before sleep at baseline.</p><p><strong>Methods: </strong>We conducted a prospective 3-wave panel study at 6-month intervals in a quota-based sample of 2500 Czech adolescents (mean age 13.43, SD 1.70 years; 1250/2500, 50% girls). Data were collected through an online survey. Screen time was assessed with 3 items covering total use of computers, smartphones, tablets, and television on a typical school day; bedtime with a single item on usual bedtime before school days; and daytime sleepiness with 4 items from the Pediatric Daytime Sleepiness Scale. Screen time restriction within 1 hour before sleep at baseline was examined as a moderator. Age and sex were included as covariates.</p><p><strong>Results: </strong>Between- and within-person associations were estimated using random intercept cross-lagged panel models. Adolescents with higher screen time reported later bedtimes (r=0.23, 95% CI 0.15-0.31; P<.001) and greater daytime sleepiness (r=0.25, 95% CI 0.16-0.34; P<.001). No direct within-person effects emerged between screen time and daytime sleepiness (W1→W2: β=.02, 95% CI -0.11 to 0.16; P=.71; W2→W3: β=.02, 95% CI -0.10 to 0.14; P=.66). However, increases in screen time at Wave 1 predicted later bedtime at Wave 2 (β=.14, 95% CI 0.01-0.27; P<.05), which in turn predicted higher screen time at Wave 3 (β=.24, 95% CI 0.11-0.36; P<.001). Temporary within-person spikes in screen time coincided with delayed bedtimes (W1: r=0.16, 95% CI 0.04-0.27; P<.01; W2: r=0.23, 95% CI 0.09-0.36; P<.001; W3: r=0.09, 95% CI 0.00-0.20; P=.049). Baseline screen time restriction did not moderate within-person effects (Δχ<sup>2</sup><sub>6</sub>=5.3; P=.51).</p><p><strong>Conclusions: </strong>This study is the first to test reciprocal longitudinal associations among adolescents' screen time, bedtime, and daytime sleepiness while separating between- and within-person associations, thereby addressing potential bias common in prior cross-lagged panel studies. The findings refine theoretical understanding by indicating a complex, bidirectional, and mutually reinforcing interplay between screen time and bedtime over time-even when individual differences are accounted for-whereas daytime sleepiness does not appear to be affected by this dynamic. Additionally, negatively correlated, within-person fluctuations
背景：白天嗜睡在青少年中很普遍，并与多种健康和功能障碍有关。先前的研究已经确定数字媒体的使用和睡眠不足是关键的预测因素，但屏幕时间、睡眠和白天嗜睡之间的相互纵向关联仍未得到充分研究。目的：本研究考察了青少年屏幕时间、就寝时间和白天嗜睡时间之间的相互纵向关系。它还测试了屏幕时间的潜在不利影响是否随着时间的推移而不那么明显，这些青少年在睡前将屏幕暴露在基线上。方法：我们对2500名捷克青少年（平均年龄13.43岁，标准差1.70岁；1250/2500,50%为女孩）进行了为期6个月的前瞻性3波面板研究。数据是通过在线调查收集的。屏幕时间通过3个项目进行评估，包括在一个典型的上学日里，电脑、智能手机、平板电脑和电视的总使用情况；在上学前的正常就寝时间只做一件事；日间嗜睡和日间嗜睡，其中4项来自儿科日间嗜睡量表。睡前1小时的屏幕时间限制作为调节因素。年龄和性别被纳入协变量。结果：使用随机截距交叉滞后面板模型估计人与人之间和人与人之间的关联。屏幕时间较长的青少年报告的就寝时间较晚（r=0.23, 95% CI 0.15-0.31; P26=5.3； P= 0.51）。结论：本研究首次测试了青少年屏幕时间、就寝时间和白天嗜睡时间之间的纵向相互关联，同时分离了人与人之间的关联，从而解决了之前交叉滞后小组研究中常见的潜在偏差。研究结果表明，随着时间的推移，屏幕时间和就寝时间之间存在着复杂的、双向的、相互加强的相互作用，从而完善了理论上的理解——即使考虑到个体差异，而白天的困倦似乎并不受这种动态的影响。此外，与屏幕时间和就寝时间负相关的个人波动表明，这些行为在一定程度上是相互排斥的，可能是由共同的环境影响形成的。睡前限制看屏幕的时间并没有减轻对人的影响，这表明干预措施应该优先考虑一致的睡眠时间表，而不是仅仅关注减少看屏幕的时间。
{"title":"Longitudinal Between- and Within-Person Associations Among Screen Time, Bedtime, and Daytime Sleepiness Among Adolescents: Three-Wave Prospective Panel Study.","authors":"Michał Tkaczyk, Albert J Ksinan, David Smahel","doi":"10.2196/78972","DOIUrl":"10.2196/78972","url":null,"abstract":"<p><strong>Background: </strong>Daytime sleepiness is prevalent among adolescents and linked to multiple health and functional impairments. Prior research has identified digital media use and insufficient sleep as key predictors, yet the reciprocal longitudinal associations among screen time, sleep, and daytime sleepiness remain understudied.</p><p><strong>Objective: </strong>This study examined the between- and within-person reciprocal longitudinal associations among adolescents' screen time, bedtime, and daytime sleepiness. It also tested whether potential adverse effects of screen time were less pronounced over time among adolescents who limited their screen exposure before sleep at baseline.</p><p><strong>Methods: </strong>We conducted a prospective 3-wave panel study at 6-month intervals in a quota-based sample of 2500 Czech adolescents (mean age 13.43, SD 1.70 years; 1250/2500, 50% girls). Data were collected through an online survey. Screen time was assessed with 3 items covering total use of computers, smartphones, tablets, and television on a typical school day; bedtime with a single item on usual bedtime before school days; and daytime sleepiness with 4 items from the Pediatric Daytime Sleepiness Scale. Screen time restriction within 1 hour before sleep at baseline was examined as a moderator. Age and sex were included as covariates.</p><p><strong>Results: </strong>Between- and within-person associations were estimated using random intercept cross-lagged panel models. Adolescents with higher screen time reported later bedtimes (r=0.23, 95% CI 0.15-0.31; P<.001) and greater daytime sleepiness (r=0.25, 95% CI 0.16-0.34; P<.001). No direct within-person effects emerged between screen time and daytime sleepiness (W1→W2: β=.02, 95% CI -0.11 to 0.16; P=.71; W2→W3: β=.02, 95% CI -0.10 to 0.14; P=.66). However, increases in screen time at Wave 1 predicted later bedtime at Wave 2 (β=.14, 95% CI 0.01-0.27; P<.05), which in turn predicted higher screen time at Wave 3 (β=.24, 95% CI 0.11-0.36; P<.001). Temporary within-person spikes in screen time coincided with delayed bedtimes (W1: r=0.16, 95% CI 0.04-0.27; P<.01; W2: r=0.23, 95% CI 0.09-0.36; P<.001; W3: r=0.09, 95% CI 0.00-0.20; P=.049). Baseline screen time restriction did not moderate within-person effects (Δχ<sup>2</sup><sub>6</sub>=5.3; P=.51).</p><p><strong>Conclusions: </strong>This study is the first to test reciprocal longitudinal associations among adolescents' screen time, bedtime, and daytime sleepiness while separating between- and within-person associations, thereby addressing potential bias common in prior cross-lagged panel studies. The findings refine theoretical understanding by indicating a complex, bidirectional, and mutually reinforcing interplay between screen time and bedtime over time-even when individual differences are accounted for-whereas daytime sleepiness does not appear to be affected by this dynamic. Additionally, negatively correlated, within-person fluctuations ","PeriodicalId":16337,"journal":{"name":"Journal of Medical Internet Research","volume":"28 ","pages":"e78972"},"PeriodicalIF":6.0,"publicationDate":"2026-01-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12873560/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146018791","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Dian Zhu, Fangyuan Chang, Hongyi Yang, Yiwen Wei, Zhao Liu
<p><strong>Background: </strong>Nonadherence to antipsychotic medication remains one of the most substantial challenges in the management of schizophrenia, contributing to relapse, rehospitalization, and functional decline. Although psychoeducational interventions are a key intervention for relapse prevention, traditional formats often lack interactivity and cultural resonance, thereby limiting engagement and sustained impact. Digital health innovations offer an opportunity to improve both treatment adherence and user experience, but evidence in schizophrenia populations remains limited.</p><p><strong>Objective: </strong>This study aimed to evaluate the usage patterns, usability, and effectiveness of a narrative-based psychoeducational digital intervention designed to enhance medication adherence among individuals with schizophrenia in the maintenance phase. By employing a mixed methods design, the study integrated quantitative measures of adherence and functioning with qualitative insights into participants' experiences and perceptions.</p><p><strong>Methods: </strong>A 6-month parallel mixed methods randomized controlled trial was conducted in community mental health settings in Shanghai. Seventy individuals with schizophrenia in a stable phase were randomly assigned (1:1) to the intervention group, which received the digital narrative-based psychoeducation application (Healing Town) in addition to routine community care, or to the control group, which received routine community rehabilitation only. Quantitative evaluation focused on medication adherence, drug attitude, social functioning, and psychiatric symptoms. In parallel, qualitative data were collected through semistructured interviews with patients, caregivers, and clinicians to examine intervention usage, usability, engagement, and perceived impact.</p><p><strong>Results: </strong>Seventy participants (mean age 44.2, SD 8.057 y; 61% male) were enrolled, and 69 (98.6%) completed the 6-month trial, with one dropout during the intervention period. At 6 months, the intervention group showed significantly higher medication adherence (mean difference 1.27, 95% CI 0.30-2.24; P=.02) and more positive drug attitudes (mean difference 3.41, 95% CI 1.18-5.65; P=.002) compared with controls. Improvements in social functioning were significant within the intervention group (P=.03) but not between groups. No significant group differences were observed in psychiatric symptoms. Qualitative findings identified three overarching themes: (1) adherence and usability-patients reported enhanced treatment knowledge, confidence, and motivation, though some described challenges with feedback tone and pacing; (2) experiences and attitudes-users valued cultural relevance, immersive narratives, and gamified elements but noted occasional overstimulation; and (3) expectations and recommendations-participants expressed demand for personalized features, reminders, and dynamic content to sustain engagement.</p><p><stro
背景：抗精神病药物的不依从性仍然是精神分裂症治疗中最重大的挑战之一，导致复发、再住院和功能下降。虽然心理教育干预是预防复发的关键干预措施，但传统形式往往缺乏互动性和文化共鸣，从而限制了参与和持续影响。数字健康创新为改善治疗依从性和用户体验提供了机会，但在精神分裂症人群中的证据仍然有限。目的：本研究旨在评估基于叙事的心理教育数字干预的使用模式、可用性和有效性，旨在提高精神分裂症患者在维持期的药物依从性。通过采用混合方法设计，该研究将依从性和功能的定量测量与参与者经验和感知的定性见解结合起来。方法：在上海市社区精神卫生机构进行为期6个月的平行混合随机对照试验。70名处于稳定期的精神分裂症患者被随机（1:1）分配到干预组，干预组接受基于数字叙事的心理教育应用（Healing Town）以及常规的社区护理，对照组只接受常规的社区康复。定量评价侧重于药物依从性、药物态度、社会功能和精神症状。同时，通过对患者、护理人员和临床医生的半结构化访谈收集定性数据，以检查干预措施的使用情况、可用性、参与度和感知影响。结果：70名参与者（平均年龄44.2岁，标准差8.057岁，61%为男性）入组，69名参与者（98.6%）完成了为期6个月的试验，1名参与者在干预期间退出。6个月时，干预组患者服药依从性显著高于对照组（平均差异1.27,95% CI 0.30-2.24； P= 0.02），积极用药态度显著高于对照组（平均差异3.41,95% CI 1.18-5.65； P= 0.002）。社会功能的改善在干预组内是显著的（P=.03），但组间无显著差异。精神症状组间无显著差异。定性研究结果确定了三个总体主题：(1)依从性和可用性——尽管一些患者描述了反馈语气和节奏方面的挑战，但患者报告了治疗知识、信心和动机的增强；(2)体验和态度——用户重视文化相关性、沉浸式叙事和游戏化元素，但偶尔会注意到过度刺激；(3)期望和建议——参与者表达了对个性化功能、提醒和动态内容的需求，以保持参与度。结论：这项混合方法的研究提供了初步证据，表明基于叙事的数字心理教育干预可能会提高精神分裂症患者在维持阶段的药物依从性和药物态度，同时被认为是有吸引力的、可用的和文化相关的。此外，定性研究结果表明，支持性反馈、自适应难度和个性化特征可以增强用户动机，优化未来的可扩展性。总的来说，这种基于叙事的数字心理教育代表了一种有前途的、具有潜在成本效益的支持社区精神康复的方法，值得进一步的纵向和多地点调查。
{"title":"Assessing Usage and Usability of a Narrative-Based Psychoeducational Digital Intervention to Improve Medication Adherence Among Individuals With Schizophrenia in a Stable Phase: Mixed Methods Study.","authors":"Dian Zhu, Fangyuan Chang, Hongyi Yang, Yiwen Wei, Zhao Liu","doi":"10.2196/59175","DOIUrl":"10.2196/59175","url":null,"abstract":"<p><strong>Background: </strong>Nonadherence to antipsychotic medication remains one of the most substantial challenges in the management of schizophrenia, contributing to relapse, rehospitalization, and functional decline. Although psychoeducational interventions are a key intervention for relapse prevention, traditional formats often lack interactivity and cultural resonance, thereby limiting engagement and sustained impact. Digital health innovations offer an opportunity to improve both treatment adherence and user experience, but evidence in schizophrenia populations remains limited.</p><p><strong>Objective: </strong>This study aimed to evaluate the usage patterns, usability, and effectiveness of a narrative-based psychoeducational digital intervention designed to enhance medication adherence among individuals with schizophrenia in the maintenance phase. By employing a mixed methods design, the study integrated quantitative measures of adherence and functioning with qualitative insights into participants' experiences and perceptions.</p><p><strong>Methods: </strong>A 6-month parallel mixed methods randomized controlled trial was conducted in community mental health settings in Shanghai. Seventy individuals with schizophrenia in a stable phase were randomly assigned (1:1) to the intervention group, which received the digital narrative-based psychoeducation application (Healing Town) in addition to routine community care, or to the control group, which received routine community rehabilitation only. Quantitative evaluation focused on medication adherence, drug attitude, social functioning, and psychiatric symptoms. In parallel, qualitative data were collected through semistructured interviews with patients, caregivers, and clinicians to examine intervention usage, usability, engagement, and perceived impact.</p><p><strong>Results: </strong>Seventy participants (mean age 44.2, SD 8.057 y; 61% male) were enrolled, and 69 (98.6%) completed the 6-month trial, with one dropout during the intervention period. At 6 months, the intervention group showed significantly higher medication adherence (mean difference 1.27, 95% CI 0.30-2.24; P=.02) and more positive drug attitudes (mean difference 3.41, 95% CI 1.18-5.65; P=.002) compared with controls. Improvements in social functioning were significant within the intervention group (P=.03) but not between groups. No significant group differences were observed in psychiatric symptoms. Qualitative findings identified three overarching themes: (1) adherence and usability-patients reported enhanced treatment knowledge, confidence, and motivation, though some described challenges with feedback tone and pacing; (2) experiences and attitudes-users valued cultural relevance, immersive narratives, and gamified elements but noted occasional overstimulation; and (3) expectations and recommendations-participants expressed demand for personalized features, reminders, and dynamic content to sustain engagement.</p><p><stro","PeriodicalId":16337,"journal":{"name":"Journal of Medical Internet Research","volume":"28 ","pages":"e59175"},"PeriodicalIF":6.0,"publicationDate":"2026-01-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12818729/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146010629","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Antti Kurtti, Sanna Iivanainen, Riitta Kaarteenaho, Heidi Andersen, Antti Jekunen, Tuula Vasankari, Jussi Koivunen
<p><strong>Background: </strong>Lung cancer screening with low-dose computed tomography (LDCT) among heavy smokers can decrease lung cancer mortality. Smoking cessation intervention is recommended within the screening program; however, the methods for smoking cessation in the LDCT screening context are not well established. We have previously shown that a novel smartphone app can increase the chance for smoking cessation along with lung cancer screening. The effects of lung cancer screening, smoking cessation, and the use of smartphone apps on health-related quality of life (HRQoL) are widely unknown.</p><p><strong>Objective: </strong>This study aims to investigate the effect of lung cancer screening, smoking cessation, and the use of smoking cessation app on HRQoL, an exploratory end point of the low-dose computed tomography screening for lung cancer combined to different smoking cessation methods in Finland (LDCT-SC-FI) study.</p><p><strong>Methods: </strong>This study was conducted as a part of the LDCT-SC-FI (NCT05630950), which was a randomized controlled trial investigating different smoking cessation methods in participants undergoing lung cancer screening with LDCT. The main inclusion criteria included an age of 50-74 years, a marked smoking history (smoked ≥15 cigarettes per day for ≥25 years or smoked ≥10 cigarettes per day for ≥30 years), an active smoking status, and access to a smartphone. The recruitment was carried out by newspaper and internet advertisements and informing relevant health care units at hospital districts. The study participants (n=200), all at Oulu University Hospital, were randomized in 1:1 fashion to a yearly LDCT with standard smoking cessation (written material) or a stand-alone smartphone app-based cessation. HRQoL, an exploratory study end point, was assessed at baseline and at 1 year with Quality of Life Questionnaire Core 30 (QLQ-C30) and EQ-5D.</p><p><strong>Results: </strong>In total, 199 and 186 individuals had both questionnaires completed at baseline and at 1 year, respectively. We did not detect a change in HRQoL between the time points using QLQ-C30 global health status score or EQ-5D index score. Smoking cessation at 1-year time did not affect QLQ-C30 global health status or EQ-5D. We observed improved quality of life scores by EQ-5D at 1 year (control: mean 0.720, SD 0.197 vs app: mean 0.799, SD 0.197; improved in 17/93, 18% of controls vs 29/93, 31% in app arm), while there was no difference in means at baseline. Smartphone app arm reported reduced pain (EQ-5D effect size [ES] 0.049, 95% CI 0.006-0.12; P=.01; adjusted ES 0.026; P=.007; QLQ-C30 ES 0.076, 95% CI 0.02-0.16; P<.001; adjusted ES 0.05; P=.02) and increased mobility (EQ-5D ES 0.031, 95% CI 0.01-0.09; P=.02; adjusted ES 0.037; P=.008) at 1 year. The number of completed questionnaires in the app was associated with improved HRQoL by EQ-5D (ES 0.073, 95% CI 0.00-0.180; P=.04; adjusted ES 0.071; P=.04).</p><p><strong>Conclusions: </strong>Th
背景：在重度吸烟者中使用低剂量计算机断层扫描（LDCT）进行肺癌筛查可以降低肺癌死亡率。建议在筛查项目中进行戒烟干预；然而，在LDCT筛查的背景下戒烟的方法并没有很好地建立。我们之前的研究表明，一款新的智能手机应用程序可以增加戒烟和肺癌筛查的机会。肺癌筛查、戒烟和使用智能手机应用程序对健康相关生活质量（HRQoL）的影响尚不清楚。目的：本研究旨在探讨肺癌筛查、戒烟和使用戒烟app对HRQoL的影响，这是芬兰低剂量肺癌ct筛查结合不同戒烟方法的探索性终点（LDCT-SC-FI）研究。方法：本研究作为LDCT- sc - fi （NCT05630950）的一部分进行，该研究是一项随机对照试验，调查接受LDCT肺癌筛查的参与者的不同戒烟方法。主要纳入标准包括年龄50-74岁、有明显的吸烟史（每天吸烟≥15支≥25年或每天吸烟≥10支≥30年）、吸烟活跃状态和使用智能手机。招募通过报纸和网络广告进行，并通知医院区相关卫生保健单位。研究参与者（n=200）均来自奥卢大学医院，以1:1的方式随机分配到每年一次的LDCT，其中包括标准戒烟（书面材料）或基于智能手机应用程序的独立戒烟。HRQoL是一项探索性研究终点，在基线和1年时使用生活质量问卷Core 30 （QLQ-C30）和EQ-5D进行评估。结果：共有199人和186人分别在基线和1年时完成了问卷调查。使用QLQ-C30整体健康状态评分或EQ-5D指数评分，我们没有发现HRQoL在时间点之间的变化。戒烟1年不影响QLQ-C30整体健康状况或EQ-5D。我们观察到EQ-5D在1年后改善了生活质量评分（对照组：平均0.720,SD 0.197；应用程序组：平均0.799,SD 0.197; 17/93, 18%的对照组改善，29/93,31%的应用程序组改善），而基线平均值没有差异。智能手机应用程序组报告疼痛减轻(EQ-5D效应值[ES] 0.049, 95% CI 0.006-0.12； P= 0.01；调整后的ES 0.026； P= 0.007; QLQ-C30 ES 0.076, 95% CI 0.02-0.16；结论：这是第一个在肺癌筛查背景下测试戒烟智能手机应用程序的研究。使用开发的应用程序与改善HRQoL相关，主要是通过减少疼痛和疲劳。总之，所研究的应用程序提供了一种可行且有效的戒烟干预措施，易于在基于人群的肺癌筛查项目中实施，除了戒烟之外，还具有增强的健康益处。
{"title":"Effect of Lung Cancer Screening, Smoking Cessation, and Cessation Smartphone App to Health-Related Quality of Life Among Heavy Smokers: Randomized Controlled Trial.","authors":"Antti Kurtti, Sanna Iivanainen, Riitta Kaarteenaho, Heidi Andersen, Antti Jekunen, Tuula Vasankari, Jussi Koivunen","doi":"10.2196/81687","DOIUrl":"10.2196/81687","url":null,"abstract":"<p><strong>Background: </strong>Lung cancer screening with low-dose computed tomography (LDCT) among heavy smokers can decrease lung cancer mortality. Smoking cessation intervention is recommended within the screening program; however, the methods for smoking cessation in the LDCT screening context are not well established. We have previously shown that a novel smartphone app can increase the chance for smoking cessation along with lung cancer screening. The effects of lung cancer screening, smoking cessation, and the use of smartphone apps on health-related quality of life (HRQoL) are widely unknown.</p><p><strong>Objective: </strong>This study aims to investigate the effect of lung cancer screening, smoking cessation, and the use of smoking cessation app on HRQoL, an exploratory end point of the low-dose computed tomography screening for lung cancer combined to different smoking cessation methods in Finland (LDCT-SC-FI) study.</p><p><strong>Methods: </strong>This study was conducted as a part of the LDCT-SC-FI (NCT05630950), which was a randomized controlled trial investigating different smoking cessation methods in participants undergoing lung cancer screening with LDCT. The main inclusion criteria included an age of 50-74 years, a marked smoking history (smoked ≥15 cigarettes per day for ≥25 years or smoked ≥10 cigarettes per day for ≥30 years), an active smoking status, and access to a smartphone. The recruitment was carried out by newspaper and internet advertisements and informing relevant health care units at hospital districts. The study participants (n=200), all at Oulu University Hospital, were randomized in 1:1 fashion to a yearly LDCT with standard smoking cessation (written material) or a stand-alone smartphone app-based cessation. HRQoL, an exploratory study end point, was assessed at baseline and at 1 year with Quality of Life Questionnaire Core 30 (QLQ-C30) and EQ-5D.</p><p><strong>Results: </strong>In total, 199 and 186 individuals had both questionnaires completed at baseline and at 1 year, respectively. We did not detect a change in HRQoL between the time points using QLQ-C30 global health status score or EQ-5D index score. Smoking cessation at 1-year time did not affect QLQ-C30 global health status or EQ-5D. We observed improved quality of life scores by EQ-5D at 1 year (control: mean 0.720, SD 0.197 vs app: mean 0.799, SD 0.197; improved in 17/93, 18% of controls vs 29/93, 31% in app arm), while there was no difference in means at baseline. Smartphone app arm reported reduced pain (EQ-5D effect size [ES] 0.049, 95% CI 0.006-0.12; P=.01; adjusted ES 0.026; P=.007; QLQ-C30 ES 0.076, 95% CI 0.02-0.16; P<.001; adjusted ES 0.05; P=.02) and increased mobility (EQ-5D ES 0.031, 95% CI 0.01-0.09; P=.02; adjusted ES 0.037; P=.008) at 1 year. The number of completed questionnaires in the app was associated with improved HRQoL by EQ-5D (ES 0.073, 95% CI 0.00-0.180; P=.04; adjusted ES 0.071; P=.04).</p><p><strong>Conclusions: </strong>Th","PeriodicalId":16337,"journal":{"name":"Journal of Medical Internet Research","volume":"28 ","pages":"e81687"},"PeriodicalIF":6.0,"publicationDate":"2026-01-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12818497/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146010616","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
<p><strong>Background: </strong>During 2024-2025, global emergencies triggered intense online discourse, presenting a unique opportunity to examine how cultural factors shape emotional expression and knowledge dissemination. Understanding these dynamic mechanisms is crucial for enhancing the effectiveness of digital health communication and optimizing crisis response strategies.</p><p><strong>Objective: </strong>We analyzed how cultural and linguistic contexts influence emotional expression and thematic framing in social media comments during major emergencies in 2024-2025. We uncovered cross-cultural differences in collective emotions and narrative focuses, explaining how affective stance and discourse framing jointly shape the public construction of crisis meaning.</p><p><strong>Methods: </strong>We used a cross-sectional, convergent mixed methods design. Data were collected retrospectively from X (formerly Twitter; X Corp) and Weibo (Sina Weibo) between January 1 and December 31, 2024. Using purposive sampling, we selected 5-6 representative emergency events per month based on online visibility (capped at 600 comments/event). The dataset included 19,813 comments from X and 6536 comments from Weibo. Emotions were identified using a Cross-lingual Language Model-Robustly optimized Bidirectional Encoder Representations from Transformers approach, and thematic patterns were extracted with Bidirectional Encoder Representations from Transformers Topic. Integrated Gradients was used to interpret model outputs, while clustering and network analysis were applied to visualize cross-cultural patterns. Hofstede's cultural dimensions theory helped interpret cultural influences on discourse. This mixed computational approach enabled a detailed comparison of emotional structures and thematic discourse across linguistic communities.</p><p><strong>Results: </strong>Significant cross-platform differences were observed in emotional distribution (χ²<sub>8</sub>=8025.60; P<.001). Compared to X users, Weibo users, representing a collectivist culture, expressed concentrated negative emotions (20.37%; odds ratio [OR] 15.76, 95% CI 13.90-17.85), surprise (19.70%; OR 2.53, 95% CI 2.32-2.73), and fear (16.68%; OR 1.72, 95% CI 1.58-1.86), reflecting group-oriented anxiety and emotional contagion. In contrast, X (formerly Twitter) users in individualist contexts displayed dispersed sarcasm (43.49%; OR 55.19, 95% CI 43.95-69.21) and worry (15.30%; OR 55.27, 95% CI 34.74-87.88), indicating personalized and critical emotional styles. Topic modeling revealed dense clusters around "safety," "pray," and "resettlement" on Weibo, whereas X (formerly Twitter) comments emphasized decentralized themes of critique and responsibility. Semantic network analysis revealed a cohesive fear-prayer-rescue chain on Weibo and fragmented, debate-oriented interactions on X (formerly Twitter).</p><p><strong>Conclusions: </strong>Emergency discourse is not neutral but is systematically structured b
背景：在2024-2025年期间，全球突发事件引发了激烈的在线讨论，为研究文化因素如何影响情感表达和知识传播提供了独特的机会。了解这些动态机制对于提高数字卫生通信的有效性和优化危机应对策略至关重要。目的：分析文化和语言背景如何影响2024-2025年重大突发事件期间社交媒体评论中的情感表达和主题框架。我们揭示了集体情绪和叙事焦点的跨文化差异，解释了情感立场和话语框架如何共同塑造危机意义的公共建构。方法：采用横截面、收敛混合方法设计。数据回顾性收集于2024年1月1日至12月31日期间的X（原Twitter； X Corp）和微博（新浪微博）。使用有目的的抽样，我们根据在线可见性每月选择5-6个有代表性的紧急事件（上限为600条评论/事件）。该数据集包括来自X的19813条评论和来自微博的6536条评论。采用跨语言语言模型——稳健优化的《变形金刚》双向编码器表征方法识别情感，并利用《变形金刚》主题双向编码器表征提取主题模式。综合梯度用于解释模型输出，聚类和网络分析用于可视化跨文化模式。Hofstede的文化维度理论有助于解释文化对话语的影响。这种混合计算方法可以对不同语言群体的情感结构和主题话语进行详细的比较。结论：应急话语不是中性的，而是由塑造情绪和主题的文化价值观系统地构建起来的。整合多语言计算和定性方法，我们提供了一个使用大规模数据的可复制框架，将危机和信息流行病学研究超越了单一平台或基于调查的方法。我们的研究结果促进了对文化意义系统如何在风险和不确定性条件下转化为可观察的数字话语的理论理解。它们还为政府、公共卫生机构、国际组织和数字平台提供了实际意义，为具有文化适应性、特定于平平台的风险沟通、社区调节和危机参与战略提供信息，这些战略可以增强公众信任，改善对保护行为的遵守，并减轻与信息流行相关的危害。
{"title":"Public Emotional and Thematic Responses to Major Emergencies on Social Media, 2024-2025: Cross-Sectional Convergent Mixed Methods Study.","authors":"Xingrong Guo, Yiqian Fan, Yiming Guo","doi":"10.2196/84648","DOIUrl":"10.2196/84648","url":null,"abstract":"<p><strong>Background: </strong>During 2024-2025, global emergencies triggered intense online discourse, presenting a unique opportunity to examine how cultural factors shape emotional expression and knowledge dissemination. Understanding these dynamic mechanisms is crucial for enhancing the effectiveness of digital health communication and optimizing crisis response strategies.</p><p><strong>Objective: </strong>We analyzed how cultural and linguistic contexts influence emotional expression and thematic framing in social media comments during major emergencies in 2024-2025. We uncovered cross-cultural differences in collective emotions and narrative focuses, explaining how affective stance and discourse framing jointly shape the public construction of crisis meaning.</p><p><strong>Methods: </strong>We used a cross-sectional, convergent mixed methods design. Data were collected retrospectively from X (formerly Twitter; X Corp) and Weibo (Sina Weibo) between January 1 and December 31, 2024. Using purposive sampling, we selected 5-6 representative emergency events per month based on online visibility (capped at 600 comments/event). The dataset included 19,813 comments from X and 6536 comments from Weibo. Emotions were identified using a Cross-lingual Language Model-Robustly optimized Bidirectional Encoder Representations from Transformers approach, and thematic patterns were extracted with Bidirectional Encoder Representations from Transformers Topic. Integrated Gradients was used to interpret model outputs, while clustering and network analysis were applied to visualize cross-cultural patterns. Hofstede's cultural dimensions theory helped interpret cultural influences on discourse. This mixed computational approach enabled a detailed comparison of emotional structures and thematic discourse across linguistic communities.</p><p><strong>Results: </strong>Significant cross-platform differences were observed in emotional distribution (χ²<sub>8</sub>=8025.60; P<.001). Compared to X users, Weibo users, representing a collectivist culture, expressed concentrated negative emotions (20.37%; odds ratio [OR] 15.76, 95% CI 13.90-17.85), surprise (19.70%; OR 2.53, 95% CI 2.32-2.73), and fear (16.68%; OR 1.72, 95% CI 1.58-1.86), reflecting group-oriented anxiety and emotional contagion. In contrast, X (formerly Twitter) users in individualist contexts displayed dispersed sarcasm (43.49%; OR 55.19, 95% CI 43.95-69.21) and worry (15.30%; OR 55.27, 95% CI 34.74-87.88), indicating personalized and critical emotional styles. Topic modeling revealed dense clusters around \"safety,\" \"pray,\" and \"resettlement\" on Weibo, whereas X (formerly Twitter) comments emphasized decentralized themes of critique and responsibility. Semantic network analysis revealed a cohesive fear-prayer-rescue chain on Weibo and fragmented, debate-oriented interactions on X (formerly Twitter).</p><p><strong>Conclusions: </strong>Emergency discourse is not neutral but is systematically structured b","PeriodicalId":16337,"journal":{"name":"Journal of Medical Internet Research","volume":"28 ","pages":"e84648"},"PeriodicalIF":6.0,"publicationDate":"2026-01-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12869147/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146010772","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Ahmed Alboksmaty, Tetiana Lunova, Ara Darzi, Ana-Luisa Neves
Background: The growing reliance on virtual consultations in primary care has reshaped traditional general practitioner (GP)-patient communication dynamics, presenting new challenges that affect care quality and safety.
Objective: This study explores communication challenges and gaps, particularly relevant to virtual consultations compared with face-to-face interactions, as well as identifying mitigation strategies from both GPs' and patients' perspectives.
Methods: This qualitative study employed 4 online focus group discussions with a purposive sample of UK-based GPs and patients. Data were analyzed using a deductive-inductive thematic approach with NVivo software. The extended Shannon-Weaver communication model and the Capability, Opportunity, Motivation and Behavior model guided the analysis of communication challenges and mitigation strategies, respectively. The Consolidated Criteria for Reporting Qualitative Research were followed to ensure rigorous reporting.
Results: A total of 21 participants (12 patients and 9 GPs) took part in 4 online focus group discussions, 2 for patients and 2 for GPs. Six key themes on communication challenges emerged: 5 aligned with the extended Shannon-Weaver communication model (related to the sender-encoder, message, channel, receiver-decoder-feedback, and context), and a new one was inductively identified (patient autonomy and inclusivity). GPs, as senders, highlighted missing visual cues, affecting message clarity in remote communication channels. Patients, as receivers, reported difficulties explaining symptoms remotely, reduced emotional connection, and perceived empathy, linked to contextual challenges and the need for inclusive communication. Mitigation strategies were mapped to the Capability, Opportunity, Motivation and Behavior model: capability (training/resources), opportunity (triage/tools), and motivation (patient engagement/system adaptability), with participants emphasizing tailored training, standardized approaches, and flexible models to support effective and inclusive virtual communication.
Conclusions: This study highlights communication gaps in virtual consultations and proposes actionable mitigation strategies. Tailored use of virtual modalities, supported by structured training and policy efforts, is essential to ensure effective and safe remote communication.
{"title":"Communication Challenges and Mitigation Strategies in Primary Care Virtual Consultations: Qualitative Study.","authors":"Ahmed Alboksmaty, Tetiana Lunova, Ara Darzi, Ana-Luisa Neves","doi":"10.2196/79399","DOIUrl":"10.2196/79399","url":null,"abstract":"<p><strong>Background: </strong>The growing reliance on virtual consultations in primary care has reshaped traditional general practitioner (GP)-patient communication dynamics, presenting new challenges that affect care quality and safety.</p><p><strong>Objective: </strong>This study explores communication challenges and gaps, particularly relevant to virtual consultations compared with face-to-face interactions, as well as identifying mitigation strategies from both GPs' and patients' perspectives.</p><p><strong>Methods: </strong>This qualitative study employed 4 online focus group discussions with a purposive sample of UK-based GPs and patients. Data were analyzed using a deductive-inductive thematic approach with NVivo software. The extended Shannon-Weaver communication model and the Capability, Opportunity, Motivation and Behavior model guided the analysis of communication challenges and mitigation strategies, respectively. The Consolidated Criteria for Reporting Qualitative Research were followed to ensure rigorous reporting.</p><p><strong>Results: </strong>A total of 21 participants (12 patients and 9 GPs) took part in 4 online focus group discussions, 2 for patients and 2 for GPs. Six key themes on communication challenges emerged: 5 aligned with the extended Shannon-Weaver communication model (related to the sender-encoder, message, channel, receiver-decoder-feedback, and context), and a new one was inductively identified (patient autonomy and inclusivity). GPs, as senders, highlighted missing visual cues, affecting message clarity in remote communication channels. Patients, as receivers, reported difficulties explaining symptoms remotely, reduced emotional connection, and perceived empathy, linked to contextual challenges and the need for inclusive communication. Mitigation strategies were mapped to the Capability, Opportunity, Motivation and Behavior model: capability (training/resources), opportunity (triage/tools), and motivation (patient engagement/system adaptability), with participants emphasizing tailored training, standardized approaches, and flexible models to support effective and inclusive virtual communication.</p><p><strong>Conclusions: </strong>This study highlights communication gaps in virtual consultations and proposes actionable mitigation strategies. Tailored use of virtual modalities, supported by structured training and policy efforts, is essential to ensure effective and safe remote communication.</p>","PeriodicalId":16337,"journal":{"name":"Journal of Medical Internet Research","volume":"28 ","pages":"e79399"},"PeriodicalIF":6.0,"publicationDate":"2026-01-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12818490/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146010642","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Matthew Schmidt, Yueqi Weng, Shannon Juengst, Alexandra Holland
<p><strong>Background: </strong>Traditional rehabilitation research often excludes the voices of individuals with lived experience of traumatic brain injury (TBI), resulting in interventions that lack relevance, accessibility, and effectiveness. Community-based participatory research (CBPR) offers an alternative framework that emphasizes collaboration, power sharing, and sustained engagement with patients, caregivers, and clinicians.</p><p><strong>Objective: </strong>This study aimed to apply CBPR to guide front-end design (empathy interviews, empathy mapping, personas) and to evaluate the sociotechnical-pedagogical usability of the Electronic Problem-Solving Training (ePST) mobile health (mHealth) intervention with TBI partners.</p><p><strong>Methods: </strong>A multistep, mixed methods design case methodology was adopted, guided by CBPR principles and learning experience design. Participatory mechanisms included a 33-member Community Advisory Board and 10 Community Engagement Studios that engaged TBI survivors, caregivers, clinicians, and researchers throughout the Discover, Define, Develop, and Deliver phases of the Double Diamond model. Iterative activities included empathy interviews (n=14), persona development (n=10), rapid prototyping, and usability testing with 5 participants with TBI using think-aloud protocols and the Comprehensive Assessment of Usability for Learning Technologies instrument.</p><p><strong>Results: </strong>The co-design process successfully translated community feedback into an empathy-informed, user-centered prototype and systematically identified design considerations that single-partner approaches overlook. TBI-specific design requirements emerged, including the need for linear content progression over branching navigation, higher technical performance standards, and explicit content signaling with clarity prioritized over novel interface design. Think-aloud protocols revealed that participants struggled with mobile navigation and branching structures but excelled with sequential content progression. In addition, the input from individuals with TBI, caregivers, clinicians, and researchers led to practical refinements such as shorter microlearning lessons (5-12 min), clearer voiceover tone, and simplified navigation, directly addressing the study's objective of improving accessibility and emotional resonance. Overall usability was high, measured using the Comprehensive Assessment of Usability for Learning Technologies (CAUSLT), with an average score of 4.25 out of 5 (SD 0.72; 95% CI 3.36-5.15; n=5). Knowledge accuracy was 80% (8/10 items; 95% CI 49%-94%; n=5 participants; 2 items each), indicating that the system effectively supported learning and comprehension. Module completion was 100% (5/5; 95% CI 56.6%-100%). Average time-on-task for 10 lesson completions was 11.47 (SD 5.28; range 4.6-21.42) minutes per lesson, demonstrating strong task efficiency and engagement. Highest ratings were observed in the pedagogical
背景：传统的康复研究经常排除有创伤性脑损伤（TBI）生活经历的个体的声音，导致干预缺乏相关性、可及性和有效性。基于社区的参与性研究（CBPR）提供了另一种框架，强调协作、权力分享以及与患者、护理人员和临床医生的持续参与。目的：本研究旨在应用CBPR指导前端设计（共情访谈、共情映射、人物角色），并评估电子问题解决培训（ePST）移动健康（mHealth）干预对TBI合作伙伴的社会技术-教学可用性。方法：以CBPR原则为指导，以学习经验设计为指导，采用多步骤、混合方法设计案例法。参与机制包括一个由33名成员组成的社区咨询委员会和10个社区参与工作室，这些工作室在双钻石模型的发现、定义、开发和交付阶段与创伤性脑损伤幸存者、护理人员、临床医生和研究人员进行接触。迭代活动包括共情访谈（n=14）、角色开发（n=10）、快速原型设计和5名TBI参与者使用有声思考协议和学习技术可用性综合评估工具进行可用性测试。结果：协同设计过程成功地将社区反馈转化为基于移情的、以用户为中心的原型，并系统地确定了单个合作伙伴方法所忽略的设计考虑因素。特定于tbi的设计需求出现了，包括对线性内容进展的需求，而不是分支导航，更高的技术性能标准，以及明确的内容信号，其清晰度优先于新颖的界面设计。有声思考协议显示，参与者在移动导航和分支结构方面遇到困难，但在顺序内容进展方面表现出色。此外，来自TBI患者、护理人员、临床医生和研究人员的输入导致了实际的改进，例如更短的微学习课程（5-12分钟）、更清晰的画外音音调和简化的导航，直接解决了提高可访问性和情感共鸣的研究目标。总体可用性高，使用学习技术可用性综合评估（CAUSLT）测量，平均得分为4.25分（SD 0.72; 95% CI 3.36-5.15; n=5）。知识正确率为80%（8/10项，95% CI为49%-94%，n=5名参与者，每人2项），表明系统有效支持学习和理解。模块完成率为100% （5/5;95% CI 56.6%-100%）。完成10节课的平均完成任务时间为每节课11.47分钟（标准差5.28；范围4.6-21.42），显示出很强的任务效率和参与度。在教学可用性领域观察到最高的评级，反映了界面清晰，直观，有利于学习。总的来说，这些发现表明，在所有设计阶段应用CBPR，可以产生专门为TBI患者量身定制的技术可靠、易于使用且具有教学意义的移动健康工具。结论：在整个设计和开发周期中持续的CBPR导致ePST对TBI患者的高可用性。最终，该研究实现了一个完整的周期管道，将持续的社区伙伴关系与可测量的可用性结果联系起来，为TBI的形成性移动健康发展制定了社区知情的设计原则和可重复的混合方法。
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Adam Marcus, Georgina Lockwood-Taylor, Daniel Rueckert, Paul Bentley
<p><strong>Background: </strong>Thrombolysis and mechanical thrombectomy represent the most successful stroke innovations over the last 30 years. Quantifying innovation in stroke is essential for identifying productive research lines and prioritizing funding, but health care lacks validated methods for measuring innovation.</p><p><strong>Objective: </strong>This study aimed to systematically evaluate the relationship between stroke-related patents and publications, demonstrate the feasibility of using large language models (LLMs) in this process, and identify the most rapidly advancing innovations in stroke care by mapping them to a theoretical innovation life cycle.</p><p><strong>Methods: </strong>The Open Patent Services (European Patent Office) and PubMed databases were searched between 1993 and 2023 for "stroke OR cerebrovascular." In this bibliometric patent-publication analysis, a 13 billion-parameter Llama LLM was trained to identify patents related to stroke disease, as opposed to other references to the word "stroke," on a manually labeled subset of 5000 patents and assessed using 5-fold cross-validation. The LLM filtered irrelevant results, and the resulting patent codes were grouped into innovation clusters. For each cluster, annual patent and publication counts were normalized to adjust for global trends. Cluster-specific growth curves were plotted to analyze the rates and characteristics of growth. The innovation life cycle stage for each innovation cluster was estimated by fitting a sigmoid curve to the patent and publication data consistent with the diffusion of innovations theory by Rogers.</p><p><strong>Results: </strong>The cross-validated accuracy of the LLM was 99.2%, with a sensitivity of 96.5% and a specificity of 99.6%. An initial bibliometric search retrieved 237,035 patents and 486,664 research publications. A manual review of a random sample of patents before filtering revealed that only 11.2% (56/500) were relevant to stroke. After LLM filtering, of the 237,035 patents, 28,225 (11.9%) stroke-related patents remained. These were grouped into 7 innovation clusters: pharmacological treatment, alternative medicine, rehabilitation devices, medical imaging, diagnostic testing, surgical devices, and artificial intelligence (AI) methods. Patent and publication counts were strongly correlated across clusters (Spearman r<sub>s</sub>=0.65-0.92; P<.006) except for pharmacological treatment (r<sub>s</sub>=0.09) and alternative medicine (r<sub>s</sub>=0.55). Pharmacological treatments were the top-performing cluster over the last 30 years, accounting for 49.3% (36,005/73,094) of all patents, but patent activity in this area has plateaued since the late 2000s. AI methods, rehabilitation devices, and medical imaging exhibited exponential rates of patent growth, with annual normalized increases of 39.2%, 15.9%, and 5.8% compared to 16.9%, 5.3%, and 2.2% for publications, respectively.</p><p><strong>Conclusions: </strong>Applying an LLM
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