Peh Joo Ho, Zi Lin Lim, Jenny Liu, Nur Khaliesah Mohamed Riza, Ying Jia Chew, Yi Ying Lim, Hui Ling Tan, Su-Ann Goh, Han Boon Oh, Chi Hui Chin, Sing Cheer Kwek, Zhi Peng Zhang, Desmond Luan Seng Ong, Swee Tian Quek, Sujith Wijerathne, Philip Tsau Choong Iau, Mikael Hartman, Jingmei Li
<p><strong>Background: </strong>Mammography screening uptake in Singapore remains below 40% despite campaigns and subsidies. Natural language processing (NLP) can extract nuanced attitudes from free text that fixed response options miss, revealing latent factors influencing breast cancer (BC) screening behavior.</p><p><strong>Objective: </strong>This study characterized women's attitudes toward mammography using mixed methods data, examined associations between BC awareness and screening willingness, and identified barriers and facilitators through NLP of free-text responses.</p><p><strong>Methods: </strong>We conducted a cross-sectional study within the Breast Screening Tailored for Her multicenter cohort in Singapore (October 2021-December 2023). In total, 4169 women aged 35-59 years (median 48, IQR 43-54) were recruited via convenience sampling (3 hospitals and 2 polyclinics). Participants completed online structured questionnaires on demographics and screening history, then a BC education quiz with feedback. Participants answering >80% correctly were classified as "BC-aware." Posteducation, participants reported screening willingness (motivated or neutral) with optional free-text explanations. Logistic regression models (adjusted for study site, age, ethnicity, marital status, housing, and education) examined the associations with willingness. For 3819 English-language respondents, biterm topic modeling identified themes and sentiment analysis quantified emotional tone. Statistical significance: α=.05.</p><p><strong>Results: </strong>Overall, 79% (3287/4169) were BC-aware, and 94% (3908/4169) reported increased motivation posteducation. BC-aware women had higher screening motivation than BC-unaware women (adjusted odds ratio [aOR] 2.88, 95% CI 2.19-3.80; P<.001). Motivation was higher among those with larger public housing (OR 1.81, 95% CI 1.30-2.50; P<.001) and private housing vs 1-3 room units (OR 2.69, 95% CI 1.75-4.13; P<.001), married vs not separated, divorced, or widowed (OR 2.38 [inverse of 0.42], 95% CI 1.75-3.13; P<.001), and prior screening attendance (OR 3.49, 95% CI 2.71-4.50; P<.001). Women who disagreed that mammography was expensive had higher motivation (aOR 1.94, 95% CI 1.50-2.50; P<.001). Among 3819 English respondents, 94% (3579/3819) were motivated and 6% (240/3819) neutral. Free-text responses came from 34% (1220/3579) of motivated and 64% (153/240) of neutral participants. Biterm topic modeling revealed motivated participants emphasized early detection benefits, health awareness, BC risk, and logistics; neutral participants focused on mammography pain experiences and cost barriers. Mean sentiment was 0.207 (range: -1.00 to 1.65), with motivated participants displaying more positive sentiments than neutral participants (linear regression, P<.001). Identical words carried different emotional tones across subgroups: "health" had positive sentiment among motivated participants (mean difference, Welch t tests P<.05) but nega
背景：尽管进行了宣传和补贴，新加坡的乳房x光检查使用率仍低于40%。自然语言处理（NLP）可以从自由文本中提取出固定响应选项遗漏的细微态度，揭示影响乳腺癌（BC）筛查行为的潜在因素。目的：本研究利用混合方法数据分析了女性对乳房x光检查的态度，研究了乳腺癌意识与筛查意愿之间的关系，并通过自由文本回复的自然语言处理确定了障碍和促进因素。方法：我们在新加坡（2021年10月- 2023年12月）为她量身定制的多中心队列乳腺筛查中进行了横断面研究。通过方便抽样（3家医院和2家综合诊所）共招募了4169名年龄在35-59岁之间的妇女（中位数48，IQR 43-54）。参与者完成了关于人口统计和筛查历史的在线结构化问卷调查，然后是BC教育测试和反馈。回答bbbb80 %正确率的参与者被归类为“BC-aware”。教育后，参与者报告了筛选意愿（有动机的或中立的），并提供了可选的自由文本解释。Logistic回归模型（根据研究地点、年龄、种族、婚姻状况、住房和教育程度进行调整）检验了与意愿的关系。对3819名英语受访者，使用双词主题建模识别主题，情感分析量化情绪基调。统计学意义：α= 0.05。结果：总体而言，79%（3287/4169）的人意识到bc， 94%（3908/4169）的人表示教育后的动机增加了。有bc意识的女性比没有bc意识的女性有更高的筛查动机（调整优势比[aOR] 2.88, 95% CI 2.19-3.80）。结论：将定量调查与NLP相结合，发现同样的筛查概念在有动机的女性和中性女性之间的情感框架是不同的，这一发现被单独的知识或意图为中心的方法所忽略。在实践中，这些发现支持了针对情感定制的BC教育和预防策略的必要性。
{"title":"Breast Cancer Screening Knowledge and Sentiments in Singaporean Women: Mixed Methods Study Using Topic Modeling, Sentiment Analysis, and Structured Questionnaire Data.","authors":"Peh Joo Ho, Zi Lin Lim, Jenny Liu, Nur Khaliesah Mohamed Riza, Ying Jia Chew, Yi Ying Lim, Hui Ling Tan, Su-Ann Goh, Han Boon Oh, Chi Hui Chin, Sing Cheer Kwek, Zhi Peng Zhang, Desmond Luan Seng Ong, Swee Tian Quek, Sujith Wijerathne, Philip Tsau Choong Iau, Mikael Hartman, Jingmei Li","doi":"10.2196/78439","DOIUrl":"https://doi.org/10.2196/78439","url":null,"abstract":"<p><strong>Background: </strong>Mammography screening uptake in Singapore remains below 40% despite campaigns and subsidies. Natural language processing (NLP) can extract nuanced attitudes from free text that fixed response options miss, revealing latent factors influencing breast cancer (BC) screening behavior.</p><p><strong>Objective: </strong>This study characterized women's attitudes toward mammography using mixed methods data, examined associations between BC awareness and screening willingness, and identified barriers and facilitators through NLP of free-text responses.</p><p><strong>Methods: </strong>We conducted a cross-sectional study within the Breast Screening Tailored for Her multicenter cohort in Singapore (October 2021-December 2023). In total, 4169 women aged 35-59 years (median 48, IQR 43-54) were recruited via convenience sampling (3 hospitals and 2 polyclinics). Participants completed online structured questionnaires on demographics and screening history, then a BC education quiz with feedback. Participants answering >80% correctly were classified as \"BC-aware.\" Posteducation, participants reported screening willingness (motivated or neutral) with optional free-text explanations. Logistic regression models (adjusted for study site, age, ethnicity, marital status, housing, and education) examined the associations with willingness. For 3819 English-language respondents, biterm topic modeling identified themes and sentiment analysis quantified emotional tone. Statistical significance: α=.05.</p><p><strong>Results: </strong>Overall, 79% (3287/4169) were BC-aware, and 94% (3908/4169) reported increased motivation posteducation. BC-aware women had higher screening motivation than BC-unaware women (adjusted odds ratio [aOR] 2.88, 95% CI 2.19-3.80; P<.001). Motivation was higher among those with larger public housing (OR 1.81, 95% CI 1.30-2.50; P<.001) and private housing vs 1-3 room units (OR 2.69, 95% CI 1.75-4.13; P<.001), married vs not separated, divorced, or widowed (OR 2.38 [inverse of 0.42], 95% CI 1.75-3.13; P<.001), and prior screening attendance (OR 3.49, 95% CI 2.71-4.50; P<.001). Women who disagreed that mammography was expensive had higher motivation (aOR 1.94, 95% CI 1.50-2.50; P<.001). Among 3819 English respondents, 94% (3579/3819) were motivated and 6% (240/3819) neutral. Free-text responses came from 34% (1220/3579) of motivated and 64% (153/240) of neutral participants. Biterm topic modeling revealed motivated participants emphasized early detection benefits, health awareness, BC risk, and logistics; neutral participants focused on mammography pain experiences and cost barriers. Mean sentiment was 0.207 (range: -1.00 to 1.65), with motivated participants displaying more positive sentiments than neutral participants (linear regression, P<.001). Identical words carried different emotional tones across subgroups: \"health\" had positive sentiment among motivated participants (mean difference, Welch t tests P<.05) but nega","PeriodicalId":16337,"journal":{"name":"Journal of Medical Internet Research","volume":"28 ","pages":"e78439"},"PeriodicalIF":6.0,"publicationDate":"2026-03-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12974998/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147433640","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>Type 2 diabetes (T2D) is emerging as a growing global public health crisis. Early and effective interventions can reduce T2D incidence among at-risk populations. Compared with traditional approaches, digital health technologies offer promising opportunities for prevention, with eHealth literacy (eHL) emerging as a critical determinant of digital prevention outcomes.</p><p><strong>Objective: </strong>This systematic review aims to synthesize and explain the pathways and mechanisms through which eHL supports T2D prevention among at-risk populations.</p><p><strong>Methods: </strong>We searched Scopus, Web of Science, and PubMed databases for English-language original research published between January 1, 2000, and August 14, 2025. Studies included were prevention research involving eHL engagement among populations at risk for T2D. Nonoriginal literature, such as editorials and abstracts, as well as research protocols, was excluded. The findings were synthesized using a thematic analysis approach, integrating the Theoretical Domains Framework with the eHL model. Two reviewers independently screened literature and extracted data, and discrepancies were resolved by a third reviewer. The Mixed Methods Appraisal Tool was used to assess risk of bias.</p><p><strong>Results: </strong>This review included 28 studies (n=13,100), mostly quantitative and published within the past decade, targeting people with prediabetes, prior gestational diabetes, and overweight/metabolic risk. Study quality was moderate to high (Mixed Methods Appraisal Tool 60%-100%) with no high risk of bias. eHL supported prevention mainly through knowledge (28/28), behavioral regulation (16/28), social influences (15/28), environmental resources (12/28), and goals (11/28), while emotions, memory, attention, decision process, and beliefs about competence were rarely addressed. Health literacy (27/28), information literacy (20/28), and communicative eHL (20/28) were most common; critical eHL and media literacy were not addressed. Studies reported positive outcomes: high engagement, weight loss (≥5%), improved glycemic markers, and enhanced lifestyle behaviors.</p><p><strong>Conclusions: </strong>This is the first systematic exploration of eHL mechanism pathways in T2D prevention via theoretical mapping. We found interventions yield positive effects despite highly uneven mechanism application: extant research relies excessively on knowledge and behavioral pathways while underemphasizing emotional support, autonomy, and critical evaluation-factors linked to long-term adherence. We provide a mechanism-based framework and identify critical gaps, including the absence of focus on critical eHL and media literacy. This review is limited by substantial variation across studies that did not allow for meta-analysis and by the limited evidence base on eHL. Future interventions should explore and test emotional and autonomy support, information discernment training, and
背景：2型糖尿病（T2D）正在成为日益严重的全球公共卫生危机。早期和有效的干预措施可以降低高危人群中糖尿病的发病率。与传统方法相比，数字卫生技术为预防提供了有希望的机会，电子卫生素养（eHL）正在成为数字预防结果的关键决定因素。目的：本系统综述旨在综合和解释eHL支持高危人群T2D预防的途径和机制。方法：检索Scopus、Web of Science和PubMed数据库，检索2000年1月1日至2025年8月14日期间发表的英文原创研究。纳入的研究包括在T2D风险人群中开展eHL的预防研究。非原创文献，如社论和摘要，以及研究方案，被排除在外。将理论领域框架与eHL模型相结合，采用主题分析方法对研究结果进行了综合。两位审稿人独立筛选文献和提取数据，差异由第三位审稿人解决。采用混合方法评估工具评估偏倚风险。结果：本综述包括28项研究（n=13,100），主要是定量研究，发表于过去十年，目标人群为糖尿病前期、妊娠糖尿病前期和超重/代谢风险人群。研究质量为中高（混合方法评价工具60%-100%），无高偏倚风险。eHL主要通过知识（28/28）、行为调节（16/28）、社会影响（15/28）、环境资源（12/28）和目标（11/28）来支持预防，而很少涉及情绪、记忆、注意、决策过程和能力信念。健康素养（27/28）、信息素养（20/28）和交际型eHL（20/28）最为常见；关键的eHL和媒体素养没有得到解决。研究报告了积极的结果：高参与度，体重减轻（≥5%），血糖指标改善，生活方式行为改善。结论：这是通过理论作图首次系统探索eHL在T2D预防中的机制途径。我们发现，尽管机制应用极不平衡，但干预措施仍能产生积极的效果：现有的研究过度依赖知识和行为途径，而低估了情感支持、自主性和关键评估——与长期坚持相关的因素。我们提供了一个基于机制的框架，并确定了关键差距，包括缺乏对关键eHL和媒体素养的关注。由于研究之间存在很大差异，不允许进行荟萃分析，并且eHL的证据基础有限，因此本综述受到限制。未来的干预措施应探索和测试情绪和自主支持、信息识别训练和可及性优化在T2D预防中的作用。这些全面、以公平为重点的干预办法将有助于确保eHL成为真正有效的公共卫生工具，惠及所有人，特别是高危人群和弱势群体。
{"title":"eHealth Literacy and Type 2 Diabetes Prevention Among At-Risk Populations: Mechanistic Systematic Review Using Theory-Driven Thematic Analysis.","authors":"Jingyi Li, Arina Anis Azlan, Nurzihan Hassim, Yuan Wang, Ruina Guo","doi":"10.2196/77788","DOIUrl":"10.2196/77788","url":null,"abstract":"<p><strong>Background: </strong>Type 2 diabetes (T2D) is emerging as a growing global public health crisis. Early and effective interventions can reduce T2D incidence among at-risk populations. Compared with traditional approaches, digital health technologies offer promising opportunities for prevention, with eHealth literacy (eHL) emerging as a critical determinant of digital prevention outcomes.</p><p><strong>Objective: </strong>This systematic review aims to synthesize and explain the pathways and mechanisms through which eHL supports T2D prevention among at-risk populations.</p><p><strong>Methods: </strong>We searched Scopus, Web of Science, and PubMed databases for English-language original research published between January 1, 2000, and August 14, 2025. Studies included were prevention research involving eHL engagement among populations at risk for T2D. Nonoriginal literature, such as editorials and abstracts, as well as research protocols, was excluded. The findings were synthesized using a thematic analysis approach, integrating the Theoretical Domains Framework with the eHL model. Two reviewers independently screened literature and extracted data, and discrepancies were resolved by a third reviewer. The Mixed Methods Appraisal Tool was used to assess risk of bias.</p><p><strong>Results: </strong>This review included 28 studies (n=13,100), mostly quantitative and published within the past decade, targeting people with prediabetes, prior gestational diabetes, and overweight/metabolic risk. Study quality was moderate to high (Mixed Methods Appraisal Tool 60%-100%) with no high risk of bias. eHL supported prevention mainly through knowledge (28/28), behavioral regulation (16/28), social influences (15/28), environmental resources (12/28), and goals (11/28), while emotions, memory, attention, decision process, and beliefs about competence were rarely addressed. Health literacy (27/28), information literacy (20/28), and communicative eHL (20/28) were most common; critical eHL and media literacy were not addressed. Studies reported positive outcomes: high engagement, weight loss (≥5%), improved glycemic markers, and enhanced lifestyle behaviors.</p><p><strong>Conclusions: </strong>This is the first systematic exploration of eHL mechanism pathways in T2D prevention via theoretical mapping. We found interventions yield positive effects despite highly uneven mechanism application: extant research relies excessively on knowledge and behavioral pathways while underemphasizing emotional support, autonomy, and critical evaluation-factors linked to long-term adherence. We provide a mechanism-based framework and identify critical gaps, including the absence of focus on critical eHL and media literacy. This review is limited by substantial variation across studies that did not allow for meta-analysis and by the limited evidence base on eHL. Future interventions should explore and test emotional and autonomy support, information discernment training, and ","PeriodicalId":16337,"journal":{"name":"Journal of Medical Internet Research","volume":"28 ","pages":"e77788"},"PeriodicalIF":6.0,"publicationDate":"2026-03-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12975002/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147433776","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}
Bingyan Gong, Nisha Yao, Hangxin Xie, Chuncheng Huang, Kishimoto Tomoko, Howard Berenbaum, Wenting Mu
<p><strong>Background: </strong>Cognitive Behavioral Therapy (CBT) is the most examined psychotherapy for depression and anxiety, but delivery faces significant barriers such as limited access, cost, and time constraints. CBT-oriented psychological chatbots offer a promising means of addressing these challenges. Yet, their overall efficacy, user engagement, and acceptability have not been systematically synthesized.</p><p><strong>Objective: </strong>To evaluate the efficacy, user engagement, and acceptability of CBT-oriented chatbots for adults with depressive and/or anxiety symptoms.</p><p><strong>Methods: </strong>A systematic search of nine databases, including PubMed, Cochrane Central Register of Controlled Trials, Embase, Web of Science, PsycINFO, CINAHL, China National Knowledge Infrastructure (CNKI), WanFang, and VIP Databases was conducted from inception to February 2026. Eligibility criteria included randomized controlled trials (RCTs) comparing CBT-oriented chatbots to control groups in adults with depressive and/or anxiety symptoms. Risk of bias (ROB) was assessed using the Cochrane risk-of-bias tool. Random-effects meta-analyses (Hartung-Knapp-Sidik-Jonkman adjustment) calculated pooled effect sizes (Hedges'g), 95% confidence intervals (CIs), and 95% prediction intervals (PIs). Heterogeneity was evaluated using the I² statistic, and Galbraith plots were utilized to identify outliers for subsequent sensitivity analyses. Subgroup and meta-regression analyses examined potential moderators. The certainty of evidence was evaluated using the GRADE approach. Data on user engagement and acceptability were extracted and synthesized using narrative and quantitative methods where available.</p><p><strong>Results: </strong>Twenty-nine eligible RCTs were included. CBT-oriented psychological chatbots produced a moderate reduction in depressive symptoms at post-intervention (g = -0.55, 95% CI -0.70 to -0.40, 95% PI -1.23 to 0.13) and a small reduction in anxiety symptoms (g = -0.26, 95% CI -0.37 to -0.14, 95% PI -0.67 to 0.15). At follow-up, effects were small for depression (g = -0.32, 95% CI -0.55 to -0.09, 95% PI -0.93 to 0.29) and non-significant for anxiety (g = -0.19, 95% CI -0.43 to 0.04, 95% PI -0.84 to 0.46). Subgroup and meta-regression analyses revealed that anxiety outcomes were significantly moderated by clinical profiles - showing distinct advantages for comorbid symptoms - and the proportion of female participants. The CBT-oriented chatbots received an adequate level of engagement that complied with digital intervention standards. Although user satisfaction ratings were generally favorable, technical limitations and repetitive interaction patterns remain to be addressed to enhance overall acceptability. Regarding the limitations of evidence, the overall certainty was rated as very low to low, predominantly driven by high RoB and substantial heterogeneity.</p><p><strong>Conclusions: </strong>This study innovatively isolates CBT-oriente
背景：认知行为疗法（CBT）是治疗抑郁和焦虑的最常用的心理疗法，但其治疗面临着准入、成本和时间限制等重大障碍。面向cbt的心理聊天机器人为解决这些挑战提供了一种很有希望的方法。然而，它们的整体功效、用户参与度和可接受性尚未得到系统的综合。目的：评估面向cbt的聊天机器人对患有抑郁和/或焦虑症状的成年人的疗效、用户参与度和可接受性。方法：系统检索PubMed、Cochrane Central Register of Controlled Trials、Embase、Web of Science、PsycINFO、CINAHL、CNKI、万方、VIP等9个数据库，检索时间自成立至2026年2月。入选标准包括随机对照试验（rct），将面向cbt的聊天机器人与患有抑郁和/或焦虑症状的成年人的对照组进行比较。使用Cochrane风险-偏倚工具评估偏倚风险（ROB）。随机效应荟萃分析（hartung - knap - sidik - jonkman调整）计算了合并效应大小（Hedges’g）、95%置信区间（ci）和95%预测区间（pi）。使用I²统计量评估异质性，并使用Galbraith图识别异常值以进行后续敏感性分析。亚组和元回归分析检查了潜在的调节因素。使用GRADE方法评估证据的确定性。在可用的情况下，使用叙述和定量方法提取和综合有关用户参与度和可接受性的数据。结果：纳入29项符合条件的随机对照试验。以cbt为导向的心理聊天机器人在干预后产生了抑郁症状的中度减少（g = -0.55, 95% CI -0.70至-0.40,95% PI -1.23至0.13）和焦虑症状的轻微减少（g = -0.26, 95% CI -0.37至-0.14,95% PI -0.67至0.15）。在随访中，对抑郁的影响较小（g = -0.32, 95% CI -0.55至-0.09,95% PI -0.93至0.29），对焦虑的影响不显著（g = -0.19, 95% CI -0.43至0.04,95% PI -0.84至0.46）。亚组和荟萃回归分析显示，焦虑结果受到临床概况（共病症状表现出明显优势）和女性参与者比例的显著缓解。面向cbt的聊天机器人获得了符合数字干预标准的足够参与度。尽管用户满意度评级总体上是有利的，但技术限制和重复的交互模式仍有待解决，以提高总体可接受性。关于证据的局限性，总体确定性被评为非常低到低，主要是由高RoB和大量异质性驱动的。结论：本研究创新性地将面向cbt的聊天机器人从更广泛的数字干预中分离出来，为理论基础的治疗方法提供了精确的、方法驱动的评估。这篇综述为该领域提供了重要的证据，证明这些工具能在短期内产生显著的缓解，特别是对共病性焦虑的缓解。在现实世界中，CBT聊天机器人作为可扩展的、低障碍的一线工具提供了巨大的潜力。为了保持参与，未来的发展必须从严格的基于规则的脚本发展到自适应的、大型语言模型（LLM）驱动的架构，同时确保临床安全。临床试验：PROSPERO CRD42024615506；https://www.crd.york.ac.uk/PROSPERO/view/CRD42024615506。
{"title":"Efficacy, User Engagement, and Acceptability of CBT-oriented Psychological Chatbots for Adults With Depressive and/or Anxiety Symptoms: Systematic Review and Meta-analysis of Randomized Controlled Trials.","authors":"Bingyan Gong, Nisha Yao, Hangxin Xie, Chuncheng Huang, Kishimoto Tomoko, Howard Berenbaum, Wenting Mu","doi":"10.2196/82677","DOIUrl":"https://doi.org/10.2196/82677","url":null,"abstract":"<p><strong>Background: </strong>Cognitive Behavioral Therapy (CBT) is the most examined psychotherapy for depression and anxiety, but delivery faces significant barriers such as limited access, cost, and time constraints. CBT-oriented psychological chatbots offer a promising means of addressing these challenges. Yet, their overall efficacy, user engagement, and acceptability have not been systematically synthesized.</p><p><strong>Objective: </strong>To evaluate the efficacy, user engagement, and acceptability of CBT-oriented chatbots for adults with depressive and/or anxiety symptoms.</p><p><strong>Methods: </strong>A systematic search of nine databases, including PubMed, Cochrane Central Register of Controlled Trials, Embase, Web of Science, PsycINFO, CINAHL, China National Knowledge Infrastructure (CNKI), WanFang, and VIP Databases was conducted from inception to February 2026. Eligibility criteria included randomized controlled trials (RCTs) comparing CBT-oriented chatbots to control groups in adults with depressive and/or anxiety symptoms. Risk of bias (ROB) was assessed using the Cochrane risk-of-bias tool. Random-effects meta-analyses (Hartung-Knapp-Sidik-Jonkman adjustment) calculated pooled effect sizes (Hedges'g), 95% confidence intervals (CIs), and 95% prediction intervals (PIs). Heterogeneity was evaluated using the I² statistic, and Galbraith plots were utilized to identify outliers for subsequent sensitivity analyses. Subgroup and meta-regression analyses examined potential moderators. The certainty of evidence was evaluated using the GRADE approach. Data on user engagement and acceptability were extracted and synthesized using narrative and quantitative methods where available.</p><p><strong>Results: </strong>Twenty-nine eligible RCTs were included. CBT-oriented psychological chatbots produced a moderate reduction in depressive symptoms at post-intervention (g = -0.55, 95% CI -0.70 to -0.40, 95% PI -1.23 to 0.13) and a small reduction in anxiety symptoms (g = -0.26, 95% CI -0.37 to -0.14, 95% PI -0.67 to 0.15). At follow-up, effects were small for depression (g = -0.32, 95% CI -0.55 to -0.09, 95% PI -0.93 to 0.29) and non-significant for anxiety (g = -0.19, 95% CI -0.43 to 0.04, 95% PI -0.84 to 0.46). Subgroup and meta-regression analyses revealed that anxiety outcomes were significantly moderated by clinical profiles - showing distinct advantages for comorbid symptoms - and the proportion of female participants. The CBT-oriented chatbots received an adequate level of engagement that complied with digital intervention standards. Although user satisfaction ratings were generally favorable, technical limitations and repetitive interaction patterns remain to be addressed to enhance overall acceptability. Regarding the limitations of evidence, the overall certainty was rated as very low to low, predominantly driven by high RoB and substantial heterogeneity.</p><p><strong>Conclusions: </strong>This study innovatively isolates CBT-oriente","PeriodicalId":16337,"journal":{"name":"Journal of Medical Internet Research","volume":" ","pages":""},"PeriodicalIF":6.0,"publicationDate":"2026-03-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147433781","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}
Linda C Grøndal-Eeles, Janne Dugstad, Hilde Eide, Etty Nilsen
Background: Telecare is seen as a promising technology aimed at enhancing the accessibility and efficiency of health care services. Although focus on quality has been highly prioritized within the health care services, there is a need to explore the quality of telecare services in general and municipal telecare call centers (CCs) in particular, as health and assistive technologies are increasingly being implemented in patients' homes.
Objective: The study sought to explore which factors influence the quality of telecare services provided by municipal telecare CCs in Norway, evaluated through the anchored, realistic, cocreated, human, integrated, and evaluated (ARCHIE) framework.
Methods: The study had a multiple-case design. Interviews were the main source of data from 15 informants from 5 municipal telecare CCs across Norway. Observation and document studies were used for background and contextualization. To explore and evaluate quality, a combined deductive-inductive analysis was conducted.
Results: Evaluated against the ARCHIE framework, none of the quality criteria were fully met. Due to the telecare service not being sufficiently anchored for all patients, it was challenging to provide realistic technologies. The collaborative work was difficult, with challenges in recruiting patients. The human principle was characterized by variation of knowledge and national guidelines. Municipal telecare CCs were not integrated into the health care services, and data must be used to a greater extent for evaluation and learning than is currently the case.
Conclusions: The findings suggest that municipal telecare CC services have several shortcomings in providing high-quality health care. Relating the quality principles identified by the ARCHIE framework to normalization process theory constructs indicates that the CC service remains in a transitional phase of normalization. To improve the telecare CC services and enhance communication and integration, policymakers need to reduce fragmentation in the broader health care system. Further national standardization to professionalize the telecare CC services should be developed. The telecare CCs need to improve their service related to all indicators of the ARCHIE framework. Training for telecare operators should be prioritized.
{"title":"Quality Challenges in Municipal Telecare Call Center Services: Qualitative Evaluation Using the Anchored, Realistic, Cocreated, Human, Integrated, and Evaluated (ARCHIE) Framework.","authors":"Linda C Grøndal-Eeles, Janne Dugstad, Hilde Eide, Etty Nilsen","doi":"10.2196/76054","DOIUrl":"https://doi.org/10.2196/76054","url":null,"abstract":"<p><strong>Background: </strong>Telecare is seen as a promising technology aimed at enhancing the accessibility and efficiency of health care services. Although focus on quality has been highly prioritized within the health care services, there is a need to explore the quality of telecare services in general and municipal telecare call centers (CCs) in particular, as health and assistive technologies are increasingly being implemented in patients' homes.</p><p><strong>Objective: </strong>The study sought to explore which factors influence the quality of telecare services provided by municipal telecare CCs in Norway, evaluated through the anchored, realistic, cocreated, human, integrated, and evaluated (ARCHIE) framework.</p><p><strong>Methods: </strong>The study had a multiple-case design. Interviews were the main source of data from 15 informants from 5 municipal telecare CCs across Norway. Observation and document studies were used for background and contextualization. To explore and evaluate quality, a combined deductive-inductive analysis was conducted.</p><p><strong>Results: </strong>Evaluated against the ARCHIE framework, none of the quality criteria were fully met. Due to the telecare service not being sufficiently anchored for all patients, it was challenging to provide realistic technologies. The collaborative work was difficult, with challenges in recruiting patients. The human principle was characterized by variation of knowledge and national guidelines. Municipal telecare CCs were not integrated into the health care services, and data must be used to a greater extent for evaluation and learning than is currently the case.</p><p><strong>Conclusions: </strong>The findings suggest that municipal telecare CC services have several shortcomings in providing high-quality health care. Relating the quality principles identified by the ARCHIE framework to normalization process theory constructs indicates that the CC service remains in a transitional phase of normalization. To improve the telecare CC services and enhance communication and integration, policymakers need to reduce fragmentation in the broader health care system. Further national standardization to professionalize the telecare CC services should be developed. The telecare CCs need to improve their service related to all indicators of the ARCHIE framework. Training for telecare operators should be prioritized.</p>","PeriodicalId":16337,"journal":{"name":"Journal of Medical Internet Research","volume":"28 ","pages":"e76054"},"PeriodicalIF":6.0,"publicationDate":"2026-03-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12974923/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147433783","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}
Anthony J Levinson, Stephanie Ayers, Sandra Clark, Rebekah Woodburn, Amy Schneeberg, Dima Hadid, Nick Kates, Gillian Strudwick, Roland Grad, Alexandra Papaioannou, Maureen Dobbins, Henry Siu, Dante Duarte, Karen Saperson, Sharon Marr, Doug Oliver, Sarah Neil-Sztramko
<p><strong>Background: </strong>Dementia prevention through the reduction of modifiable risk factors is gaining attention as a public health strategy. However, public knowledge of dementia risk and protective factors remains low. Web-based education offers a potential solution to raise awareness and promote risk-reduction behaviors.</p><p><strong>Objective: </strong>This randomized controlled trial evaluated the effectiveness of DementiaRisk.ca, an internet-based multimedia educational intervention, in increasing knowledge of dementia risk factors, intentions to engage in risk reduction behaviors, and changes in health behaviors.</p><p><strong>Methods: </strong>A 2-arm randomized controlled trial was conducted with 510 participants (265 in the intervention group and 245 in the control group). Participants were randomized to receive either the e-learning about dementia risk and promoting brain health, which included a multimedia lesson and microlearning emails, or a control intervention focused on mild cognitive impairment. Outcomes included knowledge of dementia risk factors, intentions to engage in risk reduction, and health behaviors, measured at baseline (T1), 4 weeks (T2), and 2 months postintervention (T3). Outcomes were analyzed using linear mixed effects models with fixed effects for group, time, and their interaction, and a random intercept for participants.</p><p><strong>Results: </strong>Of the 510 randomized participants, 405 (79.4%) completed all intervention components. Participants were predominantly female (n=309, 60.6%) and aged 55 years or older (n=284, 55.7%). Baseline mean dementia knowledge scores were 17.0 (SD 5.5) in the intervention group and 17.4 (SD 6.0) in the control group. At T2, scores increased to 25.8 (SD 4.5) and 23.6 (SD 5.1), respectively, yielding a between-group difference of 2.2 points (95% CI 1.2-3.2; P<.001), which was sustained at T3. Both groups showed significant improvements in knowledge, intentions, and health behaviors over time, with larger knowledge gains in the intervention group and particularly among participants with lower educational attainment. Intentions to engage in dementia risk reduction improved in both groups at T2 (intervention: +1.0, 95% CI 0.2-1.8; control: +1.4, 95% CI 0.5-2.3), with no significant between-group difference. Self-reported physical activity increased from 31.7 (SD 25.0) to 38.6 (SD 27.5) in the intervention group and from 29.9 (SD 23.5) to 32.5 (SD 26.6) in the control group, with a between-group difference of 5.4 points at T2 (95% CI 0.3-10.5; P=.04). No significant between-group differences were observed for diet, alcohol use, or other health behaviors. Qualitative findings indicated that participants valued the intervention for improving awareness of dementia risk factors, motivating proactive lifestyle changes, and enhancing confidence in applying prevention information.</p><p><strong>Conclusions: </strong>This internet-based dementia risk reduction e-learning progr
{"title":"Effects of Internet-Based Dementia Risk Reduction Education on Risk and Protective Factor Knowledge, Intentions, and Health Behaviors: Randomized Controlled Trial.","authors":"Anthony J Levinson, Stephanie Ayers, Sandra Clark, Rebekah Woodburn, Amy Schneeberg, Dima Hadid, Nick Kates, Gillian Strudwick, Roland Grad, Alexandra Papaioannou, Maureen Dobbins, Henry Siu, Dante Duarte, Karen Saperson, Sharon Marr, Doug Oliver, Sarah Neil-Sztramko","doi":"10.2196/79405","DOIUrl":"10.2196/79405","url":null,"abstract":"<p><strong>Background: </strong>Dementia prevention through the reduction of modifiable risk factors is gaining attention as a public health strategy. However, public knowledge of dementia risk and protective factors remains low. Web-based education offers a potential solution to raise awareness and promote risk-reduction behaviors.</p><p><strong>Objective: </strong>This randomized controlled trial evaluated the effectiveness of DementiaRisk.ca, an internet-based multimedia educational intervention, in increasing knowledge of dementia risk factors, intentions to engage in risk reduction behaviors, and changes in health behaviors.</p><p><strong>Methods: </strong>A 2-arm randomized controlled trial was conducted with 510 participants (265 in the intervention group and 245 in the control group). Participants were randomized to receive either the e-learning about dementia risk and promoting brain health, which included a multimedia lesson and microlearning emails, or a control intervention focused on mild cognitive impairment. Outcomes included knowledge of dementia risk factors, intentions to engage in risk reduction, and health behaviors, measured at baseline (T1), 4 weeks (T2), and 2 months postintervention (T3). Outcomes were analyzed using linear mixed effects models with fixed effects for group, time, and their interaction, and a random intercept for participants.</p><p><strong>Results: </strong>Of the 510 randomized participants, 405 (79.4%) completed all intervention components. Participants were predominantly female (n=309, 60.6%) and aged 55 years or older (n=284, 55.7%). Baseline mean dementia knowledge scores were 17.0 (SD 5.5) in the intervention group and 17.4 (SD 6.0) in the control group. At T2, scores increased to 25.8 (SD 4.5) and 23.6 (SD 5.1), respectively, yielding a between-group difference of 2.2 points (95% CI 1.2-3.2; P<.001), which was sustained at T3. Both groups showed significant improvements in knowledge, intentions, and health behaviors over time, with larger knowledge gains in the intervention group and particularly among participants with lower educational attainment. Intentions to engage in dementia risk reduction improved in both groups at T2 (intervention: +1.0, 95% CI 0.2-1.8; control: +1.4, 95% CI 0.5-2.3), with no significant between-group difference. Self-reported physical activity increased from 31.7 (SD 25.0) to 38.6 (SD 27.5) in the intervention group and from 29.9 (SD 23.5) to 32.5 (SD 26.6) in the control group, with a between-group difference of 5.4 points at T2 (95% CI 0.3-10.5; P=.04). No significant between-group differences were observed for diet, alcohol use, or other health behaviors. Qualitative findings indicated that participants valued the intervention for improving awareness of dementia risk factors, motivating proactive lifestyle changes, and enhancing confidence in applying prevention information.</p><p><strong>Conclusions: </strong>This internet-based dementia risk reduction e-learning progr","PeriodicalId":16337,"journal":{"name":"Journal of Medical Internet Research","volume":"28 ","pages":"e79405"},"PeriodicalIF":6.0,"publicationDate":"2026-03-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12975120/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147433832","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>Digital biomarkers are gaining interest as proxy markers for mental health, as they enable passive and continuous data collection. However, the association between digital biomarkers of health and anxiety, both generalized anxiety disorder and anxiety symptoms, remains unknown.</p><p><strong>Objective: </strong>This systematic review and meta-analysis examined the association between digital biomarkers of health obtained from wrist-worn wearables and anxiety in adults.</p><p><strong>Methods: </strong>Systematic literature searches were conducted across 6 databases, including unpublished gray literature. The final search was done on September 21, 2025. Cross-sectional or longitudinal studies investigating the association between digital biomarkers from wrist-worn wearables and anxiety were eligible. Studies using inferential statistics or machine learning methods were both eligible. Studies were excluded if participants received diagnoses of neurodegenerative disorders or physical health conditions. Two risk-of-bias tools were used: the National Heart, Lung, and Blood Institute assessment tool for inferential statistical studies, and the modified version of the Quality Assessment of Diagnostic Accuracy Studies-2 for machine learning studies. Whenever possible, effect sizes were combined across studies, for each digital biomarker of health separately, using random-effects meta-analyses. Sensitivity analyses were performed to assess whether results differed according to anxiety type (state or trait) and age group. Otherwise, studies were synthesized narratively.</p><p><strong>Results: </strong>A total of 44 studies from 42 articles were eligible. Among these, 36 studies used inferential statistical approaches for analysis (21 reporting sleep characteristics, 8 reporting physical activity, 2 reporting heart rate variability, and 5 reporting more than 1 type), and 8 studies used machine learning approaches. Sample size ranged from 17 to 170,320. Meta-analyses on 4 sleep metrics found no associations: sleep efficiency (Fisher z=-0.07, 95% CI -0.14 to 0.002; P=.06; PI -0.19 to 0.05), wake after sleep onset (Fisher z=0.13, 95% CI -0.04 to 0.30; P=.11; PI -0.15 to 0.41), total sleep time (Fisher z=0.009, 95% CI -0.01 to 0.03; P=.28; PI -0.02 to 0.03), and sleep onset latency (Fisher z=0.04, 95% CI -0.07 to 0.15; P=.08; PI -0.19 to 0.27). Qualitative syntheses revealed that lower physical activity levels and higher heart rate were associated with greater anxiety symptoms. Machine learning studies using wrist-worn wearable data alone showed varied performance, with predictive performance improving when wearable data were combined with other data sources.</p><p><strong>Conclusions: </strong>This is the first review to synthesize evidence from inferential statistical (mostly fair quality) and machine learning studies examining association between wearable-derived digital biomarkers and anxiety. Meta-analyses found no associatio
背景：数字生物标记物作为心理健康的代理标记物越来越受到关注，因为它们可以被动和连续地收集数据。然而，健康的数字生物标志物与焦虑之间的关系，包括广泛性焦虑障碍和焦虑症状，仍然未知。目的：本系统综述和荟萃分析检验了从腕带可穿戴设备获得的健康数字生物标志物与成年人焦虑之间的关系。方法：对6个数据库进行系统文献检索，包括未发表的灰色文献。最后一次搜寻于2025年9月21日完成。调查腕部可穿戴设备的数字生物标志物与焦虑之间关系的横断面或纵向研究是合格的。使用推理统计或机器学习方法的研究都是合格的。如果参与者被诊断为神经退行性疾病或身体健康状况，则排除研究。使用了两种偏倚风险工具：国家心脏、肺和血液研究所的评估工具用于推理统计研究，以及改进版的诊断准确性研究质量评估-2用于机器学习研究。在可能的情况下，使用随机效应荟萃分析，对每个健康数字生物标志物的效应大小进行了综合研究。进行敏感性分析以评估结果是否因焦虑类型（状态或特征）和年龄组而异。否则，研究是叙述性的。结果：42篇文章共纳入44项研究。其中，36项研究使用推理统计方法进行分析（21项报告睡眠特征，8项报告身体活动，2项报告心率变异性，5项报告超过一种类型），8项研究使用机器学习方法。样本量从17到170,320不等。对4项睡眠指标的荟萃分析发现：睡眠效率（Fisher z=-0.07, 95% CI -0.14至0.002；P= 0.06; PI -0.19至0.05）、睡眠开始后醒来（Fisher z=0.13, 95% CI -0.04至0.30；P= 0.11; PI -0.15至0.41）、总睡眠时间（Fisher z=0.009, 95% CI -0.01至0.03；P= 0.28; PI -0.02至0.03）和睡眠开始潜伏期（Fisher z=0.04, 95% CI -0.07至0.15；P= 0.08; PI -0.19至0.27）没有关联。定性综合显示，较低的体力活动水平和较高的心率与更大的焦虑症状相关。单独使用腕带可穿戴数据的机器学习研究显示出不同的性能，当可穿戴数据与其他数据源结合使用时，预测性能得到改善。结论：这是第一次综合推论统计（大部分是公平质量）和机器学习研究证据的综述，研究了可穿戴设备衍生的数字生物标志物与焦虑之间的关系。荟萃分析发现，睡眠指标和焦虑之间没有关联。尽管基于有限的研究，较低的体力活动水平和较高的心率与更大的焦虑症状有关。当与其他数据源（如自我报告和临床数据）集成时，数字生物标志物可能比作为单独的筛选工具更有用。试验注册：PROSPERO CRD42023409995；https://www.crd.york.ac.uk/PROSPERO/view/CRD42023409995。
{"title":"Association Between Digital Biomarkers of Health and Anxiety: Systematic Review and Meta-Analysis.","authors":"Yolanda Lau, Natalia Chemas, Heema Ajeet Gokani, Rachel Morrell, Harisd Phannarus, Claudia Cooper, Zuzana Walker, Harriet Demnitz-King, Natalie L Marchant","doi":"10.2196/73812","DOIUrl":"https://doi.org/10.2196/73812","url":null,"abstract":"<p><strong>Background: </strong>Digital biomarkers are gaining interest as proxy markers for mental health, as they enable passive and continuous data collection. However, the association between digital biomarkers of health and anxiety, both generalized anxiety disorder and anxiety symptoms, remains unknown.</p><p><strong>Objective: </strong>This systematic review and meta-analysis examined the association between digital biomarkers of health obtained from wrist-worn wearables and anxiety in adults.</p><p><strong>Methods: </strong>Systematic literature searches were conducted across 6 databases, including unpublished gray literature. The final search was done on September 21, 2025. Cross-sectional or longitudinal studies investigating the association between digital biomarkers from wrist-worn wearables and anxiety were eligible. Studies using inferential statistics or machine learning methods were both eligible. Studies were excluded if participants received diagnoses of neurodegenerative disorders or physical health conditions. Two risk-of-bias tools were used: the National Heart, Lung, and Blood Institute assessment tool for inferential statistical studies, and the modified version of the Quality Assessment of Diagnostic Accuracy Studies-2 for machine learning studies. Whenever possible, effect sizes were combined across studies, for each digital biomarker of health separately, using random-effects meta-analyses. Sensitivity analyses were performed to assess whether results differed according to anxiety type (state or trait) and age group. Otherwise, studies were synthesized narratively.</p><p><strong>Results: </strong>A total of 44 studies from 42 articles were eligible. Among these, 36 studies used inferential statistical approaches for analysis (21 reporting sleep characteristics, 8 reporting physical activity, 2 reporting heart rate variability, and 5 reporting more than 1 type), and 8 studies used machine learning approaches. Sample size ranged from 17 to 170,320. Meta-analyses on 4 sleep metrics found no associations: sleep efficiency (Fisher z=-0.07, 95% CI -0.14 to 0.002; P=.06; PI -0.19 to 0.05), wake after sleep onset (Fisher z=0.13, 95% CI -0.04 to 0.30; P=.11; PI -0.15 to 0.41), total sleep time (Fisher z=0.009, 95% CI -0.01 to 0.03; P=.28; PI -0.02 to 0.03), and sleep onset latency (Fisher z=0.04, 95% CI -0.07 to 0.15; P=.08; PI -0.19 to 0.27). Qualitative syntheses revealed that lower physical activity levels and higher heart rate were associated with greater anxiety symptoms. Machine learning studies using wrist-worn wearable data alone showed varied performance, with predictive performance improving when wearable data were combined with other data sources.</p><p><strong>Conclusions: </strong>This is the first review to synthesize evidence from inferential statistical (mostly fair quality) and machine learning studies examining association between wearable-derived digital biomarkers and anxiety. Meta-analyses found no associatio","PeriodicalId":16337,"journal":{"name":"Journal of Medical Internet Research","volume":"28 ","pages":"e73812"},"PeriodicalIF":6.0,"publicationDate":"2026-03-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147390267","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}
Katarina Åsberg, Oskar Lundgren, Hanna Henriksson, Pontus Henriksson, Ann Catrine Eldh, Preben Bendtsen, Marie Löf, Marcus Bendtsen
<p><strong>Background: </strong>Digital interventions have shown promise in supporting healthy behaviors among university students; however, few interventions support simultaneous change across multiple health behaviors. Moreover, behavioral interventions are typically evaluated as a whole, making it challenging to disentangle the contribution of individual components to the overall effects.</p><p><strong>Objective: </strong>This study estimated the effects of the components of a digital behavior intervention on alcohol, diet, physical activity, and smoking outcomes among university students in Sweden.</p><p><strong>Methods: </strong>A double-blind randomized factorial trial with 6 two-level factors was conducted. University students in Sweden were proactively recruited through student health care centers and social media. Participants were eligible if they were aged 18 years or older and had at least one health behavior classified as unhealthy. The effects of 6 components were estimated: screening and feedback; goal-setting and planning; motivation; skills and know-how; mindfulness; and self-authored SMS text messages. Primary outcomes were weekly alcohol consumption and frequency of heavy episodic drinking, average daily fruit and vegetable consumption, weekly sugary drink consumption, weekly moderate-to-vigorous physical activity (MVPA), and 4-week point prevalence of smoking.</p><p><strong>Results: </strong>A total of 1704 students were randomized. The effectiveness of individual and pairwise components was estimated using available data from 1118 (65.61%) participants at 2 months and 874 (51.29%) at 4 months, with sensitivity analyses conducted using imputed missing data. Most consistently, the evidence indicated that screening and feedback affected fruit and vegetable consumption (2-month mean difference 0.11, compatibility interval [CoI] -0.02 to 0.24; probability of effect [POE] 94.7% and 4-month mean difference 0.12, CoI -0.03 to 0.26; POE 94.4%), as did skills and know-how (2-month mean difference 0.19, CoI 0.06-0.33; POE 99.8% and 4-month mean difference 0.14, CoI 0.01-0.28; POE 96.9%). The combination of these 2 components was even more effective (2-month mean difference 0.30, CoI 0.11-0.48; POE 99.9% and 4-month mean difference 0.26, CoI 0.05-0.46; POE 99.4%). The motivation and mindfulness components, both individually and in combination, increased MVPA at 2 months (combined mean difference 78.0, CoI 28.3-128.2; POE 99.9%); however, this effect was not observed at 4 months. Combining screening and feedback with skills and know-how increased MVPA at 4 months (mean difference 60.1, CoI 3.6-116.5; POE 98.2%). Heavy episodic drinking was reduced at 2 months by screening and feedback (incidence rate ratio 0.87, CoI 0.74-1.02; POE 95.2%), and the effect was greater when combined with goal-setting and mindfulness. There was some evidence that the motivation component was harmful with respect to heavy episodic drinking and that self-authore
{"title":"Effectiveness of the Components of a Digital Multiple Health Behavior Intervention Among University Students (Buddy): Factorial Randomized Trial.","authors":"Katarina Åsberg, Oskar Lundgren, Hanna Henriksson, Pontus Henriksson, Ann Catrine Eldh, Preben Bendtsen, Marie Löf, Marcus Bendtsen","doi":"10.2196/88884","DOIUrl":"https://doi.org/10.2196/88884","url":null,"abstract":"<p><strong>Background: </strong>Digital interventions have shown promise in supporting healthy behaviors among university students; however, few interventions support simultaneous change across multiple health behaviors. Moreover, behavioral interventions are typically evaluated as a whole, making it challenging to disentangle the contribution of individual components to the overall effects.</p><p><strong>Objective: </strong>This study estimated the effects of the components of a digital behavior intervention on alcohol, diet, physical activity, and smoking outcomes among university students in Sweden.</p><p><strong>Methods: </strong>A double-blind randomized factorial trial with 6 two-level factors was conducted. University students in Sweden were proactively recruited through student health care centers and social media. Participants were eligible if they were aged 18 years or older and had at least one health behavior classified as unhealthy. The effects of 6 components were estimated: screening and feedback; goal-setting and planning; motivation; skills and know-how; mindfulness; and self-authored SMS text messages. Primary outcomes were weekly alcohol consumption and frequency of heavy episodic drinking, average daily fruit and vegetable consumption, weekly sugary drink consumption, weekly moderate-to-vigorous physical activity (MVPA), and 4-week point prevalence of smoking.</p><p><strong>Results: </strong>A total of 1704 students were randomized. The effectiveness of individual and pairwise components was estimated using available data from 1118 (65.61%) participants at 2 months and 874 (51.29%) at 4 months, with sensitivity analyses conducted using imputed missing data. Most consistently, the evidence indicated that screening and feedback affected fruit and vegetable consumption (2-month mean difference 0.11, compatibility interval [CoI] -0.02 to 0.24; probability of effect [POE] 94.7% and 4-month mean difference 0.12, CoI -0.03 to 0.26; POE 94.4%), as did skills and know-how (2-month mean difference 0.19, CoI 0.06-0.33; POE 99.8% and 4-month mean difference 0.14, CoI 0.01-0.28; POE 96.9%). The combination of these 2 components was even more effective (2-month mean difference 0.30, CoI 0.11-0.48; POE 99.9% and 4-month mean difference 0.26, CoI 0.05-0.46; POE 99.4%). The motivation and mindfulness components, both individually and in combination, increased MVPA at 2 months (combined mean difference 78.0, CoI 28.3-128.2; POE 99.9%); however, this effect was not observed at 4 months. Combining screening and feedback with skills and know-how increased MVPA at 4 months (mean difference 60.1, CoI 3.6-116.5; POE 98.2%). Heavy episodic drinking was reduced at 2 months by screening and feedback (incidence rate ratio 0.87, CoI 0.74-1.02; POE 95.2%), and the effect was greater when combined with goal-setting and mindfulness. There was some evidence that the motivation component was harmful with respect to heavy episodic drinking and that self-authore","PeriodicalId":16337,"journal":{"name":"Journal of Medical Internet Research","volume":"28 ","pages":"e88884"},"PeriodicalIF":6.0,"publicationDate":"2026-03-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147390264","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}
Hannah Robin Friedman, Hillary J Mull, Jenice Ria Guzman-Clark, Daniel J Sturgeon, Marva V Foster
<p><strong>Background: </strong>Black veterans and veterans from lower socioeconomic backgrounds are more likely to have uncontrolled hypertension. One potential explanatory factor is reduced access to specific treatments that result in improved chronic disease management. In the Veterans Health Administration (VHA), veterans with hypertension may enroll in a remote patient monitoring (RPM) program, which consists of patient education, daily home blood pressure (BP) monitoring, health coaching, and case management. Barriers for socioeconomically disadvantaged patients may exist for similar programs in other health systems; however, the VHA is an integrated health care system, and these barriers may differ for veteran populations.</p><p><strong>Objective: </strong>The objective of this study was to assess the relationship between veteran race and neighborhood socioeconomic status and the likelihood of enrolling in the VHA RPM program.</p><p><strong>Methods: </strong>The study sample included VHA-enrolled veterans with a diagnosis of hypertension (average BP >130/80 mm Hg on ≥2 BP readings) between fiscal years 2020 and 2023. We ran random-effects logistic regression models to assess the relationship between veteran race and Area Deprivation Index and RPM enrollment each year, controlling for potential demographic and clinical confounders. For sensitivity analysis, we limited our sample to veterans with stage 2 hypertension (BP >140/90 mm Hg) and on antihypertensive medication.</p><p><strong>Results: </strong>Overall use of RPM was low, with only 4.1% (56,553/1,390,995; 95% CI 4%-4.1%) of veterans being enrolled in RPM. Black veterans, who represented 26.6% (n=35,096) of all veterans, were more likely (odds ratio [OR] 1.65, 95% CI 1.59-1.70) to enroll in RPM compared to White veterans. Asian American or Pacific Islander veterans were less likely to enroll (OR 0.83, 95% CI 0.74-0.94). We found no meaningful association between Area Deprivation Index and RPM enrollment (OR 1.00, 95% CI 0.99-1.00). When limiting our sample to those with stage or grade 2 hypertension, we found a similar association (OR 1.61, 95% CI 1.50-1.72) between Black race and RPM enrollment but no significant association with Asian or Pacific Islander race (OR 1.02, 95% CI 0.80-1.29).</p><p><strong>Conclusions: </strong>Prior research on RPM in veterans has examined duration or outcomes of RPM enrollment but not the probability of initial enrollment. We found higher enrollment rates in the VHA RPM program among Black veterans but slightly lower enrollment among Asian American or Pacific Islander veterans. Higher enrollment among Black veterans and among those with higher comorbidity burden suggests that the VHA RPM program is successfully reaching those who could most benefit, despite low overall enrollment. Given the low enrollment in RPM, future research should focus on improving uptake among veterans who could additionally benefit from the program. Non-VHA systems, particularl
背景：黑人退伍军人和社会经济背景较低的退伍军人更容易出现不受控制的高血压。一个潜在的解释因素是减少了获得特定治疗的机会，从而改善了慢性病的管理。在退伍军人健康管理局（VHA），患有高血压的退伍军人可以参加远程患者监测（RPM）计划，该计划包括患者教育、每日家庭血压监测、健康指导和病例管理。其他卫生系统的类似规划可能存在对社会经济弱势患者的障碍；然而，退伍军人管理局是一个综合医疗保健系统，这些障碍对退伍军人群体可能有所不同。目的：本研究的目的是评估退伍军人种族与社区社会经济地位和参加VHA RPM计划的可能性之间的关系。方法：研究样本包括在2020年至2023财政年度期间诊断为高血压（血压读数≥2，平均血压为130/80 mm Hg）的vha招募的退伍军人。在控制潜在的人口统计学和临床混杂因素的情况下，我们运行随机效应logistic回归模型来评估每年退伍军人种族与地区剥夺指数和RPM入学率之间的关系。为了进行敏感性分析，我们将样本限制在2期高血压（血压140/90毫米汞柱）并服用抗高血压药物的退伍军人。结果：RPM的总体使用率较低，只有4.1% （56,553/1,390,995;95% CI 4%-4.1%）的退伍军人参加了RPM。黑人退伍军人占所有退伍军人的26.6% (n=35,096)，与白人退伍军人相比，他们更有可能参加RPM（比值比[OR] 1.65, 95% CI 1.59-1.70）。亚裔美国人或太平洋岛民退伍军人报名参加的可能性较小（or 0.83, 95% CI 0.74-0.94）。我们发现区域剥夺指数与RPM入组无显著关联（OR 1.00, 95% CI 0.99-1.00）。当我们将样本限制在2期或2级高血压患者时，我们发现黑人种族与RPM入组之间存在类似的关联（or 1.61, 95% CI 1.50-1.72），但与亚洲或太平洋岛民种族没有显著关联（or 1.02, 95% CI 0.80-1.29）。结论：先前对退伍军人转转速的研究只考察了转转速入组的持续时间或结果，而没有考察初始入组的概率。我们发现黑人退伍军人的VHA RPM项目的入学率较高，而亚裔美国人或太平洋岛民退伍军人的入学率略低。较高的黑人退伍军人入学率和较高的合并症负担表明，尽管总体入学率较低，但VHA RPM计划成功地惠及了那些最可能受益的人。考虑到RPM的低入学率，未来的研究应该集中在提高退伍军人的吸收，他们可以从该计划中额外受益。非VHA系统，特别是那些服务于低收入或社会经济弱势地区的系统，应该为符合条件的患者探索补贴或免费的RPM计划，类似于VHA为退伍军人提供的免费模式。
{"title":"The Effect of Veteran Race and Socioeconomic Status on Enrollment in Remote Patient Monitoring for Hypertension: Retrospective Observational Cross-Sectional Study.","authors":"Hannah Robin Friedman, Hillary J Mull, Jenice Ria Guzman-Clark, Daniel J Sturgeon, Marva V Foster","doi":"10.2196/78423","DOIUrl":"https://doi.org/10.2196/78423","url":null,"abstract":"<p><strong>Background: </strong>Black veterans and veterans from lower socioeconomic backgrounds are more likely to have uncontrolled hypertension. One potential explanatory factor is reduced access to specific treatments that result in improved chronic disease management. In the Veterans Health Administration (VHA), veterans with hypertension may enroll in a remote patient monitoring (RPM) program, which consists of patient education, daily home blood pressure (BP) monitoring, health coaching, and case management. Barriers for socioeconomically disadvantaged patients may exist for similar programs in other health systems; however, the VHA is an integrated health care system, and these barriers may differ for veteran populations.</p><p><strong>Objective: </strong>The objective of this study was to assess the relationship between veteran race and neighborhood socioeconomic status and the likelihood of enrolling in the VHA RPM program.</p><p><strong>Methods: </strong>The study sample included VHA-enrolled veterans with a diagnosis of hypertension (average BP >130/80 mm Hg on ≥2 BP readings) between fiscal years 2020 and 2023. We ran random-effects logistic regression models to assess the relationship between veteran race and Area Deprivation Index and RPM enrollment each year, controlling for potential demographic and clinical confounders. For sensitivity analysis, we limited our sample to veterans with stage 2 hypertension (BP >140/90 mm Hg) and on antihypertensive medication.</p><p><strong>Results: </strong>Overall use of RPM was low, with only 4.1% (56,553/1,390,995; 95% CI 4%-4.1%) of veterans being enrolled in RPM. Black veterans, who represented 26.6% (n=35,096) of all veterans, were more likely (odds ratio [OR] 1.65, 95% CI 1.59-1.70) to enroll in RPM compared to White veterans. Asian American or Pacific Islander veterans were less likely to enroll (OR 0.83, 95% CI 0.74-0.94). We found no meaningful association between Area Deprivation Index and RPM enrollment (OR 1.00, 95% CI 0.99-1.00). When limiting our sample to those with stage or grade 2 hypertension, we found a similar association (OR 1.61, 95% CI 1.50-1.72) between Black race and RPM enrollment but no significant association with Asian or Pacific Islander race (OR 1.02, 95% CI 0.80-1.29).</p><p><strong>Conclusions: </strong>Prior research on RPM in veterans has examined duration or outcomes of RPM enrollment but not the probability of initial enrollment. We found higher enrollment rates in the VHA RPM program among Black veterans but slightly lower enrollment among Asian American or Pacific Islander veterans. Higher enrollment among Black veterans and among those with higher comorbidity burden suggests that the VHA RPM program is successfully reaching those who could most benefit, despite low overall enrollment. Given the low enrollment in RPM, future research should focus on improving uptake among veterans who could additionally benefit from the program. Non-VHA systems, particularl","PeriodicalId":16337,"journal":{"name":"Journal of Medical Internet Research","volume":"28 ","pages":"e78423"},"PeriodicalIF":6.0,"publicationDate":"2026-03-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147390310","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}
Liuyang Yang, Liyu Shan, Xiaolin Cao, Jinzhao Cui, Michael Tong, Yan Niu, Ting Zhang
Unlabelled: Traditional epidemic intelligence relies heavily on human epidemiologists for data interpretation and reporting, which makes it resource intensive, slow to respond, and vulnerable to variability in professional expertise. To overcome these limitations, we propose an expanded conceptual epidemic intelligence quadripartite framework that extends the classical trinity of (1) surveillance, (2) risk evaluation, and (3) early warning with a fourth pillar, (4) decision support and intervention optimization through AI agents. Acting as 24/7 digital epidemiologists, multiagent systems can integrate heterogeneous signals from multisource surveillance systems, conduct contextual risk evaluation and adaptive forecasting, generate tailored early warnings, and provide actionable recommendations for targeted control-closing the loop between detection and response. Embedding interpretability and mandatory human-in-the-loop oversight enhances trust and accountability. Nonetheless, real-world deployment requires addressing context-specific challenges of data quality, interoperability, robustness, governance, circular reporting, and equity. If designed with transparency, inclusiveness, and resilience, AI agents have the potential to transform epidemic intelligence into a continuously adaptive and globally connected system.
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Jinming Shi, Ming Ye, Dongxu Sun, Xianying He, Yaoen Lu, Linlin Wang, Haotian Chen, Wenchao Wang, Jie Zhao, Fangfang Cui
<p><strong>Background: </strong>Telepathology has emerged as a transformative digital health solution to address the global shortage of pathologists and the unequal distribution of diagnostic services, particularly in underserved and rural areas. In Henan Province, China, high diagnostic demand, rapid population growth, and limited pathology expertise exacerbate regional health care inequities, leading to delayed diagnoses and restricted access to specialist care.</p><p><strong>Objective: </strong>This study aimed to design, implement, and evaluate a province-wide telepathology system integrating web and mobile platforms to enhance diagnostic quality, efficiency, and equitable access across health care tiers.</p><p><strong>Methods: </strong>We conducted a retrospective, multicenter observational study using deidentified data from 120 health care institutions between 2016 and 2024. The system used a 3-tier architecture with virtual private network-secured transmission and a Browser-Server framework, supporting standardized whole-slide image acquisition, remote review, and reporting via web interfaces and a WeChat (Tencent) mini-program. System performance was assessed by consultation volume, turnaround time, concurrency, and diagnostic concordance in a subset of 1027 cases with paired tertiary-hospital expert diagnoses. Economic impact was estimated using previously published per-case savings, reflecting patient travel and ancillary cost reductions. Additional assessments included workflow integration, mobile platform use, and system stability under peak load.</p><p><strong>Results: </strong>Over 8 years, the network processed 72,916 consultations encompassing 355,104 whole-slide images, supporting 220-300 concurrent users with stable performance. Median turnaround time was 10.06 (IQR 1.63-29.10) hours, with 96.41% (70,298/72,916) of cases completed within 72 hours. County-level hospitals contributed 77.63% (56,603/72,916) of consultations, demonstrating substantial engagement from lower-tier institutions. In the diagnostic subset, originating-site preliminary classifications achieved 0.90 sensitivity and 0.75 specificity relative to expert reference diagnoses, with 17.2% discordance corrected through remote expert review. Estimated annual direct cost savings ranged from US $0.14 to $0.63 million. Mobile-enabled access facilitated remote review and reporting without compromising data security, supporting integration into routine clinical workflows across diverse hospital settings.</p><p><strong>Conclusions: </strong>The Henan Province telepathology system demonstrates that a centrally coordinated, scalable digital health platform can improve diagnostic efficiency, quality, and equity in resource-constrained settings. High county-level hospital use highlights its potential to reduce geographic and structural diagnostic inequities. Future work should explore formal cost-effectiveness evaluation, artificial intelligence-assisted diagnostic support, a
{"title":"Telepathology and Mobile Health System for Province-Wide Pathology Consultation in Henan, China: Retrospective Evaluation Study.","authors":"Jinming Shi, Ming Ye, Dongxu Sun, Xianying He, Yaoen Lu, Linlin Wang, Haotian Chen, Wenchao Wang, Jie Zhao, Fangfang Cui","doi":"10.2196/75172","DOIUrl":"https://doi.org/10.2196/75172","url":null,"abstract":"<p><strong>Background: </strong>Telepathology has emerged as a transformative digital health solution to address the global shortage of pathologists and the unequal distribution of diagnostic services, particularly in underserved and rural areas. In Henan Province, China, high diagnostic demand, rapid population growth, and limited pathology expertise exacerbate regional health care inequities, leading to delayed diagnoses and restricted access to specialist care.</p><p><strong>Objective: </strong>This study aimed to design, implement, and evaluate a province-wide telepathology system integrating web and mobile platforms to enhance diagnostic quality, efficiency, and equitable access across health care tiers.</p><p><strong>Methods: </strong>We conducted a retrospective, multicenter observational study using deidentified data from 120 health care institutions between 2016 and 2024. The system used a 3-tier architecture with virtual private network-secured transmission and a Browser-Server framework, supporting standardized whole-slide image acquisition, remote review, and reporting via web interfaces and a WeChat (Tencent) mini-program. System performance was assessed by consultation volume, turnaround time, concurrency, and diagnostic concordance in a subset of 1027 cases with paired tertiary-hospital expert diagnoses. Economic impact was estimated using previously published per-case savings, reflecting patient travel and ancillary cost reductions. Additional assessments included workflow integration, mobile platform use, and system stability under peak load.</p><p><strong>Results: </strong>Over 8 years, the network processed 72,916 consultations encompassing 355,104 whole-slide images, supporting 220-300 concurrent users with stable performance. Median turnaround time was 10.06 (IQR 1.63-29.10) hours, with 96.41% (70,298/72,916) of cases completed within 72 hours. County-level hospitals contributed 77.63% (56,603/72,916) of consultations, demonstrating substantial engagement from lower-tier institutions. In the diagnostic subset, originating-site preliminary classifications achieved 0.90 sensitivity and 0.75 specificity relative to expert reference diagnoses, with 17.2% discordance corrected through remote expert review. Estimated annual direct cost savings ranged from US $0.14 to $0.63 million. Mobile-enabled access facilitated remote review and reporting without compromising data security, supporting integration into routine clinical workflows across diverse hospital settings.</p><p><strong>Conclusions: </strong>The Henan Province telepathology system demonstrates that a centrally coordinated, scalable digital health platform can improve diagnostic efficiency, quality, and equity in resource-constrained settings. High county-level hospital use highlights its potential to reduce geographic and structural diagnostic inequities. Future work should explore formal cost-effectiveness evaluation, artificial intelligence-assisted diagnostic support, a","PeriodicalId":16337,"journal":{"name":"Journal of Medical Internet Research","volume":"28 ","pages":"e75172"},"PeriodicalIF":6.0,"publicationDate":"2026-03-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147390278","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}
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