Background: China's diabetes epidemic faces critical gaps in glycemic control, with only 50.1% of treated patients achieving hemoglobin A1C (HbA1c) targets in 2021. Conventional interventions struggle with scalability in primary care, particularly for vulnerable populations.
Objective: This study aimed to evaluate the use of a WeChat-based health education tool (the WeWalk mini program, the Bayu Health public account, and a WeChat group) for improving glycemic control in community-dwelling patients with type 2 diabetes mellitus.
Methods: This multicenter randomized controlled trial enrolled 600 adults with type 2 diabetes from 3 communities in Chongqing, randomly allocating participants 1:1 to either a 12-week WeChat-based intervention (n=300, 50%) or a control group (n=300, 50%) in September 2020. The control group received 4 face-to-face traditional health education sessions, whereas the intervention group participated in a digital program: a 4-week course followed by an 8-week practical implementation. At baseline and 12 weeks after the intervention began, both groups were examined in terms of HbA1c and fasting blood glucose (FBG) as the primary outcomes, as well as variables such as blood lipid profile, blood pressure, and physical fitness-related indexes as secondary outcomes. Longitudinal glycemic control was assessed through triplicate FBG measurements extracted from standardized electronic health records at the 2-year follow-up. Independent t tests or Mann-Whitney U tests were used to assess changes from baseline to follow-up between groups.
Results: A total of 92.7% (556/600) of the participants completed the 12-week follow-up visit. The WeChat-based intervention demonstrated superior glycemic control outcomes, with intervention participants achieving a 0.59% greater HbA1c reduction than controls (-0.03% vs 0.56%; P<.001) and significant improvements in FBG levels (-0.69 vs 0.00 mmol/L; Δ=0.69; P=.001). Subgroup analysis revealed that WeChat-based health education was significantly effective in patients with diabetes with a disease duration of <10 years, educational level of junior high school or lower, and annual family income of
Conclusions: WeChat-based health education was beneficial for glycemic control in primary health care settings. However, the sustained efficacy and feasibility of this approach require further investigation.
背景：中国糖尿病流行在血糖控制方面存在严重缺口，2021年仅有50.1%的治疗患者达到血红蛋白A1C （HbA1c）目标。常规干预措施难以在初级保健中实现可扩展性，特别是对弱势群体而言。目的：本研究旨在评估基于微信的健康教育工具（WeWalk小程序、巴渝健康公众账号和微信组）在改善社区2型糖尿病患者血糖控制方面的作用。方法：本多中心随机对照试验招募了来自重庆3个社区的600名2型糖尿病成人患者，于2020年9月将参与者1:1随机分配到12周的微信干预组（n=300, 50%）或对照组（n=300, 50%）。对照组接受了4次面对面的传统健康教育课程，而干预组则参加了一个数字项目：为期4周的课程，随后是为期8周的实践实施。在基线和干预开始后12周，两组均以HbA1c和空腹血糖（FBG）作为主要结局，以及血脂、血压和身体健康相关指标等变量作为次要结局。在2年的随访中，通过从标准化电子健康记录中提取的三次FBG测量来评估纵向血糖控制。使用独立t检验或Mann-Whitney U检验来评估组间从基线到随访的变化。结果：92.7%（556/600）的参与者完成了为期12周的随访。基于微信的干预显示出更好的血糖控制结果，干预参与者的HbA1c降低率比对照组高0.59% （-0.03% vs 0.56%）。结论：基于微信的健康教育有利于初级卫生保健机构的血糖控制。然而，这种方法的持续有效性和可行性需要进一步调查。
{"title":"WeChat-Based Intervention for Glycemic Control in Patients With Type 2 Diabetes Mellitus: Multicenter Randomized Controlled Trial.","authors":"Chuanfen Zheng, Xiong Dou, Xiaotao Xiong, En-Yu Lei, Ming Jiang, Yulin Wu, Jing Yu, Xianjun Wang, Ling Zhang, Honghui Rong, Lu Lu, Fengju Li, Ting Luo, Xiangyu Ma, Ji-An Chen","doi":"10.2196/80738","DOIUrl":"10.2196/80738","url":null,"abstract":"<p><strong>Background: </strong>China's diabetes epidemic faces critical gaps in glycemic control, with only 50.1% of treated patients achieving hemoglobin A1C (HbA1c) targets in 2021. Conventional interventions struggle with scalability in primary care, particularly for vulnerable populations.</p><p><strong>Objective: </strong>This study aimed to evaluate the use of a WeChat-based health education tool (the WeWalk mini program, the Bayu Health public account, and a WeChat group) for improving glycemic control in community-dwelling patients with type 2 diabetes mellitus.</p><p><strong>Methods: </strong>This multicenter randomized controlled trial enrolled 600 adults with type 2 diabetes from 3 communities in Chongqing, randomly allocating participants 1:1 to either a 12-week WeChat-based intervention (n=300, 50%) or a control group (n=300, 50%) in September 2020. The control group received 4 face-to-face traditional health education sessions, whereas the intervention group participated in a digital program: a 4-week course followed by an 8-week practical implementation. At baseline and 12 weeks after the intervention began, both groups were examined in terms of HbA1c and fasting blood glucose (FBG) as the primary outcomes, as well as variables such as blood lipid profile, blood pressure, and physical fitness-related indexes as secondary outcomes. Longitudinal glycemic control was assessed through triplicate FBG measurements extracted from standardized electronic health records at the 2-year follow-up. Independent t tests or Mann-Whitney U tests were used to assess changes from baseline to follow-up between groups.</p><p><strong>Results: </strong>A total of 92.7% (556/600) of the participants completed the 12-week follow-up visit. The WeChat-based intervention demonstrated superior glycemic control outcomes, with intervention participants achieving a 0.59% greater HbA1c reduction than controls (-0.03% vs 0.56%; P<.001) and significant improvements in FBG levels (-0.69 vs 0.00 mmol/L; Δ=0.69; P=.001). Subgroup analysis revealed that WeChat-based health education was significantly effective in patients with diabetes with a disease duration of <10 years, educational level of junior high school or lower, and annual family income of <CN ¥50,000 (US $7172.10) . These benefits persisted throughout the 2-year follow-up, where the intervention group maintained lower FBG levels (6.87 vs 7.35 mmol/L; P=.001).</p><p><strong>Conclusions: </strong>WeChat-based health education was beneficial for glycemic control in primary health care settings. However, the sustained efficacy and feasibility of this approach require further investigation.</p>","PeriodicalId":14756,"journal":{"name":"JMIR mHealth and uHealth","volume":"14 ","pages":"e80738"},"PeriodicalIF":6.2,"publicationDate":"2026-02-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12923094/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146258214","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}
Jonathan Nkurunziza, Sarah Nuss, Eve Hiyori Estrada, Marthe Kubwimana, Adeline Adwoa Boatin, Laban Bikorimana, Richard Ribon Fletcher, Nissi Byiringiro, Bethany Hedt-Gauthier, Vincent Kalumire Cubaka
<p><strong>Background: </strong>Mobile health (mHealth) apps are increasingly leveraged to support community health workers (CHWs) in delivering high-quality care, particularly in low- and middle-income countries. However, despite the proliferation of mHealth tools, few have been implemented at scale, partly due to limited attention to usability and acceptability among end users. In sub-Saharan Africa, mHealth tools designed for CHWs often lack systematic evaluation using validated instruments tailored to local contexts. Without such assessments, it is difficult to ensure that these tools can be integrated effectively into CHW workflows and scaled sustainably.</p><p><strong>Objective: </strong>This study aimed to adapt and validate existing mHealth usability and acceptability assessment tools to be contextually appropriate for CHWs in Rwanda. Specifically, we sought to ensure contextual appropriateness for CHWs supporting postoperative home follow-up for women after cesarean delivery. The resulting tool was designed for use in an implementation study of a novel CHW-led mHealth app.</p><p><strong>Methods: </strong>This study was conducted in the Kirehe district, Rwanda, from October 2022 to March 2023. We adapted 2 established tools-the mHealth App Usability Questionnaire and selected items from the Practitioner Opinion (Acceptability) Scale-and added new items that reflect core functions of the CHW-focused mHealth app. All items were translated into Kinyarwanda and simplified to align with CHWs' educational levels. We conducted a three-stage validation that consisted of (1) content validity testing with 8 local and international experts using a recommended content validity index threshold of >0.78; (2) face validity testing with 10 CHWs using a recommended face validity index threshold of ≥0.60; and (3) reliability testing using responses from 30 CHWs, with a Cronbach α coefficient of ≥0.70 indicating acceptable internal consistency.</p><p><strong>Results: </strong>Of the 25 items assessed, 22 (88%) achieved a content validity index score of >0.78 for both clarity and relevance. The face validity index across all 22 items was 0.991, indicating strong comprehensibility and relevance to CHWs. Internal consistency was high: the Cronbach α was 0.86 for the mHealth App Usability Questionnaire items, 0.73 for the Practitioner Opinion (Acceptability) Scale items, and 0.87 for the newly developed questions. The final tool-named the Community Health Worker mHealth Usability and Acceptability Assessment Tool-included 22 items with strong content validity, face validity, and internal reliability.</p><p><strong>Conclusions: </strong>This study presents a rigorously adapted and validated tool for assessing mHealth usability and acceptability among CHWs in Rwanda. The Community Health Worker mHealth Usability and Acceptability Assessment Tool can guide future evaluations of mHealth interventions in similar contexts and serve as a model for localizing mHealth a
{"title":"Adapting and Validating Tools to Assess the Usability and Acceptability of mHealth Tools Among Community Health Workers in Rural Settings: Development and Usability Study.","authors":"Jonathan Nkurunziza, Sarah Nuss, Eve Hiyori Estrada, Marthe Kubwimana, Adeline Adwoa Boatin, Laban Bikorimana, Richard Ribon Fletcher, Nissi Byiringiro, Bethany Hedt-Gauthier, Vincent Kalumire Cubaka","doi":"10.2196/64916","DOIUrl":"10.2196/64916","url":null,"abstract":"<p><strong>Background: </strong>Mobile health (mHealth) apps are increasingly leveraged to support community health workers (CHWs) in delivering high-quality care, particularly in low- and middle-income countries. However, despite the proliferation of mHealth tools, few have been implemented at scale, partly due to limited attention to usability and acceptability among end users. In sub-Saharan Africa, mHealth tools designed for CHWs often lack systematic evaluation using validated instruments tailored to local contexts. Without such assessments, it is difficult to ensure that these tools can be integrated effectively into CHW workflows and scaled sustainably.</p><p><strong>Objective: </strong>This study aimed to adapt and validate existing mHealth usability and acceptability assessment tools to be contextually appropriate for CHWs in Rwanda. Specifically, we sought to ensure contextual appropriateness for CHWs supporting postoperative home follow-up for women after cesarean delivery. The resulting tool was designed for use in an implementation study of a novel CHW-led mHealth app.</p><p><strong>Methods: </strong>This study was conducted in the Kirehe district, Rwanda, from October 2022 to March 2023. We adapted 2 established tools-the mHealth App Usability Questionnaire and selected items from the Practitioner Opinion (Acceptability) Scale-and added new items that reflect core functions of the CHW-focused mHealth app. All items were translated into Kinyarwanda and simplified to align with CHWs' educational levels. We conducted a three-stage validation that consisted of (1) content validity testing with 8 local and international experts using a recommended content validity index threshold of >0.78; (2) face validity testing with 10 CHWs using a recommended face validity index threshold of ≥0.60; and (3) reliability testing using responses from 30 CHWs, with a Cronbach α coefficient of ≥0.70 indicating acceptable internal consistency.</p><p><strong>Results: </strong>Of the 25 items assessed, 22 (88%) achieved a content validity index score of >0.78 for both clarity and relevance. The face validity index across all 22 items was 0.991, indicating strong comprehensibility and relevance to CHWs. Internal consistency was high: the Cronbach α was 0.86 for the mHealth App Usability Questionnaire items, 0.73 for the Practitioner Opinion (Acceptability) Scale items, and 0.87 for the newly developed questions. The final tool-named the Community Health Worker mHealth Usability and Acceptability Assessment Tool-included 22 items with strong content validity, face validity, and internal reliability.</p><p><strong>Conclusions: </strong>This study presents a rigorously adapted and validated tool for assessing mHealth usability and acceptability among CHWs in Rwanda. The Community Health Worker mHealth Usability and Acceptability Assessment Tool can guide future evaluations of mHealth interventions in similar contexts and serve as a model for localizing mHealth a","PeriodicalId":14756,"journal":{"name":"JMIR mHealth and uHealth","volume":"14 ","pages":"e64916"},"PeriodicalIF":6.2,"publicationDate":"2026-02-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12966820/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146258235","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}
Clara Sophia Zoeller, Claudia Niessner, Manuel Fleps, Thorsten Klein, Anke Hanssen-Doose, Alexander Burchartz, Alexander Woll, Thorsten Stein
Background: Good motor performance skills (MPS) are relevant in all stages of life. Higher MPS are associated with enhanced cognitive abilities and physical and mental health. The assessment of MPS is important to identify deficits in MPS at an early stage and to implement interventions to address these deficits. One method to assess MPS is through marker-based motion capture in a laboratory setting with multiple cameras. However, this approach is expensive and time-consuming, making it impractical, for example, in large-scale studies for MPS assessment. Recent advancements (eg, artificial intelligence) in technology (eg, smartphone cameras) have opened up innovative solutions for various challenges (eg, testing large sample sizes). A potential solution is using video-based smartphone apps to assess MPS through markerless motion capture with a single camera.
Objective: The objectives of this scoping review were to summarize existing smartphone apps designed to digitally assess MPS through motion capture, identify the target population of the apps, determine whether the apps have been validated, and summarize the specific MPS that were assessed.
Methods: The scoping review was conducted in accordance with the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analysis extension for Scoping Reviews) guidelines. The search was conducted in March 2024 using PubMed, Scopus, SPORTDiscus, Web of Science, Education Resources Information Centre, and SAGE Publications. All included studies investigated video-based motion capture smartphone apps to assess MPS.
Results: A total of 10 studies met the inclusion criteria. Seven different smartphone apps were used within the studies, 6 of which have already been validated. The MPS assessed through the apps were gait, breaststroke, running, countermovement jump, and shoulder mobility, and 1 study assessed a functional movement test battery. The studied populations were healthy adults, older adults, athletes, or individuals with neurological illnesses.
Conclusions: The assessment of MPS through smartphone apps represents a promising tool, which can be used in a variety of fields, such as health and performance monitoring, coaching, and scientific research. In the future, more studies should focus on developing new smartphone apps to assess different MPS and validate these apps.
背景：良好的运动表现技能（MPS）在人生的各个阶段都是相关的。高MPS与增强的认知能力和身心健康有关。对MPS的评估对于在早期阶段确定MPS的缺陷并实施干预措施以解决这些缺陷非常重要。评估MPS的一种方法是在实验室环境中使用多个摄像机进行基于标记的动作捕捉。然而，这种方法既昂贵又耗时，使得它在诸如MPS评估的大规模研究中不切实际。技术（如智能手机相机）的最新进步（如人工智能）为各种挑战（如测试大样本量）提供了创新的解决方案。一个潜在的解决方案是使用基于视频的智能手机应用程序，通过单个摄像头的无标记动作捕捉来评估MPS。目的：本次范围审查的目的是总结现有的智能手机应用程序，旨在通过动作捕捉对MPS进行数字评估，确定应用程序的目标人群，确定应用程序是否已经过验证，并总结评估的特定MPS。方法：范围评价按照PRISMA-ScR（系统评价首选报告项目和范围评价扩展元分析）指南进行。检索于2024年3月使用PubMed、Scopus、SPORTDiscus、Web of Science、教育资源信息中心和SAGE Publications进行。所有纳入的研究都调查了基于视频的动作捕捉智能手机应用程序来评估MPS。结果：共有10项研究符合纳入标准。研究中使用了7种不同的智能手机应用程序，其中6种已经得到验证。通过应用程序评估的MPS包括步态、蛙泳、跑步、反向跳跃和肩部活动能力，还有一项研究评估了功能运动测试电池。研究人群包括健康成年人、老年人、运动员或患有神经系统疾病的个体。结论：通过智能手机应用程序评估MPS是一种很有前途的工具，可用于各种领域，如健康和绩效监测，教练和科学研究。在未来，更多的研究应该集中在开发新的智能手机应用程序，以评估不同的MPS和验证这些应用程序。
{"title":"Video-Based Motion Capture Smartphone Apps for Testing Human Motor Performance Skills: Scoping Review.","authors":"Clara Sophia Zoeller, Claudia Niessner, Manuel Fleps, Thorsten Klein, Anke Hanssen-Doose, Alexander Burchartz, Alexander Woll, Thorsten Stein","doi":"10.2196/65474","DOIUrl":"10.2196/65474","url":null,"abstract":"<p><strong>Background: </strong>Good motor performance skills (MPS) are relevant in all stages of life. Higher MPS are associated with enhanced cognitive abilities and physical and mental health. The assessment of MPS is important to identify deficits in MPS at an early stage and to implement interventions to address these deficits. One method to assess MPS is through marker-based motion capture in a laboratory setting with multiple cameras. However, this approach is expensive and time-consuming, making it impractical, for example, in large-scale studies for MPS assessment. Recent advancements (eg, artificial intelligence) in technology (eg, smartphone cameras) have opened up innovative solutions for various challenges (eg, testing large sample sizes). A potential solution is using video-based smartphone apps to assess MPS through markerless motion capture with a single camera.</p><p><strong>Objective: </strong>The objectives of this scoping review were to summarize existing smartphone apps designed to digitally assess MPS through motion capture, identify the target population of the apps, determine whether the apps have been validated, and summarize the specific MPS that were assessed.</p><p><strong>Methods: </strong>The scoping review was conducted in accordance with the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analysis extension for Scoping Reviews) guidelines. The search was conducted in March 2024 using PubMed, Scopus, SPORTDiscus, Web of Science, Education Resources Information Centre, and SAGE Publications. All included studies investigated video-based motion capture smartphone apps to assess MPS.</p><p><strong>Results: </strong>A total of 10 studies met the inclusion criteria. Seven different smartphone apps were used within the studies, 6 of which have already been validated. The MPS assessed through the apps were gait, breaststroke, running, countermovement jump, and shoulder mobility, and 1 study assessed a functional movement test battery. The studied populations were healthy adults, older adults, athletes, or individuals with neurological illnesses.</p><p><strong>Conclusions: </strong>The assessment of MPS through smartphone apps represents a promising tool, which can be used in a variety of fields, such as health and performance monitoring, coaching, and scientific research. In the future, more studies should focus on developing new smartphone apps to assess different MPS and validate these apps.</p>","PeriodicalId":14756,"journal":{"name":"JMIR mHealth and uHealth","volume":"14 ","pages":"e65474"},"PeriodicalIF":6.2,"publicationDate":"2026-02-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12919747/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146226865","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}
Shujie Jiang, Xianru Gao, Haiqing Diao, Yang Zhang, Guangyu Lu, Xiaoguang Liu, Yuping Li
<p><strong>Background: </strong>Type 2 diabetes mellitus (T2DM) is a prevalent chronic metabolic disorder that poses substantial challenges to global health care systems and patient management. Telemedicine, defined as the use of information and communication technologies to enhance health care delivery, has emerged as a potential tool to improve access to care and facilitate the management of T2DM.</p><p><strong>Objective: </strong>This systematic review and meta-analysis aimed to evaluate the clinical effectiveness of various telemedicine interventions compared with usual care in glycemic control, and cardiovascular health in adults with T2DM.</p><p><strong>Methods: </strong>A comprehensive literature search was conducted across databases such as PubMed, Cochrane Library, and Web of Science for randomized controlled trials (RCTs) published up to August 23, 2024. Eligible RCTs compared telemedicine interventions with usual care in adults with T2DM. The primary outcome assessed was hemoglobin A<sub>1c</sub> (HbA<sub>1c</sub>) levels, while the secondary outcomes included mean glucose, fasting blood glucose, BMI, weight, systolic blood pressure, diastolic blood pressure, high-density lipoprotein cholesterol, and low-density lipoprotein cholesterol. The quality of the included studies was examined via the Cochrane risk-of-bias tool. Data were extracted and analyzed using a random-effects model, and meta-regression was performed to explore potential moderators. The quality of the evidence was assessed via the Grading of Recommendations, Assessment, Development, and Evaluation approach.</p><p><strong>Results: </strong>A total of 58 RCTs, encompassing 13,942 participants, were included in the analysis. Our findings showed that telemedicine interventions significantly improved HbA<sub>1c</sub> levels compared with usual care (mean difference [MD] -0.38, 95% CI -0.49 to -0.27; Z=6.94; P<.001), despite high heterogeneity (I²=96%). Significant effects were also found for fasting blood glucose (MD -11.29, 95% CI -17.65 to -4.93; Z=3.48; P<.001), weight (MD -1.33, 95% CI -2.23 to -0.44; Z=2.91; P=.004), BMI (MD -0.43, 95% CI -0.72 to -0.13; Z=2.84; P=.004), systolic blood pressure (MD -2.14, 95% CI -3.02 to -1.26; Z=4.76; P<.001), and diastolic blood pressure (MD -1.24, 95% CI -2.02 to -0.46; Z=1.10; P=.002). No significant between-group differences were found in high-density lipoprotein cholesterol and low-density lipoprotein cholesterol improvement. Subgroup analyses revealed that telemedicine delivered by physicians, dietitians, and researchers achieved the most significant reductions in HbA<sub>1c</sub> levels. Short-term and long-term interventions showed significant HbA<sub>1c</sub> improvements, while medium-term interventions did not achieve statistical significance. Meta-regression analysis did not identify any statistically significant moderators.</p><p><strong>Conclusions: </strong>This review highlights telemedicine's superior effectiveness over
背景：2型糖尿病（T2DM）是一种普遍存在的慢性代谢紊乱，对全球卫生保健系统和患者管理提出了重大挑战。远程医疗被定义为利用信息和通信技术来加强卫生保健服务，已成为改善获得保健和促进2型糖尿病管理的潜在工具。目的：本系统综述和荟萃分析旨在评价各种远程医疗干预与常规护理相比在成人T2DM患者血糖控制和心血管健康方面的临床效果。方法：综合检索PubMed、Cochrane Library、Web of Science等数据库，检索截至2024年8月23日发表的随机对照试验（rct）。符合条件的随机对照试验比较了远程医疗干预与常规护理对成年T2DM患者的影响。评估的主要结局是血红蛋白A1c （HbA1c）水平，而次要结局包括平均血糖、空腹血糖、BMI、体重、收缩压、舒张压、高密度脂蛋白胆固醇和低密度脂蛋白胆固醇。通过Cochrane风险偏倚工具检查纳入研究的质量。使用随机效应模型提取数据并进行分析，并进行meta回归以探索潜在的调节因子。通过推荐分级、评估、发展和评价方法评估证据的质量。结果：共纳入58项随机对照试验，共13942名受试者。我们的研究结果显示，与常规护理相比，远程医疗干预显著改善了HbA1c水平（平均差[MD] -0.38, 95% CI -0.49至-0.27；Z=6.94； P1c水平）。短期和长期干预均能显著改善HbA1c，而中期干预无统计学意义。meta回归分析未发现任何统计学上显著的调节因子。结论：本综述强调了远程医疗在改善T2DM患者HbA1c水平方面优于常规护理，无论干预类型如何。由医生、营养师和研究人员领导的远程医疗在控制血糖水平方面显示出最大的功效。此外，远程医疗干预有望监测2型糖尿病患者的体重和心血管健康。试验注册：PROSPERO CRD42024608130；https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=608130。
{"title":"Clinical Improvements From Telemedicine Interventions for Managing Type 2 Diabetes Compared With Usual Care: Systematic Review, Meta-Analysis, and Meta-Regression.","authors":"Shujie Jiang, Xianru Gao, Haiqing Diao, Yang Zhang, Guangyu Lu, Xiaoguang Liu, Yuping Li","doi":"10.2196/70429","DOIUrl":"10.2196/70429","url":null,"abstract":"<p><strong>Background: </strong>Type 2 diabetes mellitus (T2DM) is a prevalent chronic metabolic disorder that poses substantial challenges to global health care systems and patient management. Telemedicine, defined as the use of information and communication technologies to enhance health care delivery, has emerged as a potential tool to improve access to care and facilitate the management of T2DM.</p><p><strong>Objective: </strong>This systematic review and meta-analysis aimed to evaluate the clinical effectiveness of various telemedicine interventions compared with usual care in glycemic control, and cardiovascular health in adults with T2DM.</p><p><strong>Methods: </strong>A comprehensive literature search was conducted across databases such as PubMed, Cochrane Library, and Web of Science for randomized controlled trials (RCTs) published up to August 23, 2024. Eligible RCTs compared telemedicine interventions with usual care in adults with T2DM. The primary outcome assessed was hemoglobin A<sub>1c</sub> (HbA<sub>1c</sub>) levels, while the secondary outcomes included mean glucose, fasting blood glucose, BMI, weight, systolic blood pressure, diastolic blood pressure, high-density lipoprotein cholesterol, and low-density lipoprotein cholesterol. The quality of the included studies was examined via the Cochrane risk-of-bias tool. Data were extracted and analyzed using a random-effects model, and meta-regression was performed to explore potential moderators. The quality of the evidence was assessed via the Grading of Recommendations, Assessment, Development, and Evaluation approach.</p><p><strong>Results: </strong>A total of 58 RCTs, encompassing 13,942 participants, were included in the analysis. Our findings showed that telemedicine interventions significantly improved HbA<sub>1c</sub> levels compared with usual care (mean difference [MD] -0.38, 95% CI -0.49 to -0.27; Z=6.94; P<.001), despite high heterogeneity (I²=96%). Significant effects were also found for fasting blood glucose (MD -11.29, 95% CI -17.65 to -4.93; Z=3.48; P<.001), weight (MD -1.33, 95% CI -2.23 to -0.44; Z=2.91; P=.004), BMI (MD -0.43, 95% CI -0.72 to -0.13; Z=2.84; P=.004), systolic blood pressure (MD -2.14, 95% CI -3.02 to -1.26; Z=4.76; P<.001), and diastolic blood pressure (MD -1.24, 95% CI -2.02 to -0.46; Z=1.10; P=.002). No significant between-group differences were found in high-density lipoprotein cholesterol and low-density lipoprotein cholesterol improvement. Subgroup analyses revealed that telemedicine delivered by physicians, dietitians, and researchers achieved the most significant reductions in HbA<sub>1c</sub> levels. Short-term and long-term interventions showed significant HbA<sub>1c</sub> improvements, while medium-term interventions did not achieve statistical significance. Meta-regression analysis did not identify any statistically significant moderators.</p><p><strong>Conclusions: </strong>This review highlights telemedicine's superior effectiveness over","PeriodicalId":14756,"journal":{"name":"JMIR mHealth and uHealth","volume":"14 ","pages":"e70429"},"PeriodicalIF":6.2,"publicationDate":"2026-02-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12961393/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146219766","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}
Xia Liu, Tammo H A Bijmolt, Marijke C Leliveld, Ernst H Noppers
<p><strong>Background: </strong>Goal personalization features integrated into mobile health apps have the potential to enhance physical activity, as some evidence shows that the personalized goals generated by algorithms are more effective than default or fixed goals. However, it remains unclear whether goals set by users are more effective than fixed goals and which personalization strategy is more effective for different user segments.</p><p><strong>Objective: </strong>This field study aimed to evaluate (1) the efficacy of 2 step goal personalization strategies-personalized-by-you and personalized-by-the-algorithm-and (2) which strategy is more effective among users with different activity levels.</p><p><strong>Methods: </strong>All users of SamenGezond, a Dutch mobile health app, have a default goal of 2000 steps per day, 5 days a week. For this study, 2 random groups were selected, totaling 5800 users. Subsequently, an email was sent to 3800 users in group 1, asking whether they were satisfied with their current goal. Those who were not satisfied were offered 2 personalization options: to set a goal themselves or to have the algorithm integrated in the app set goals for them. In total, 1399 users responded: 230 chose to set their own goals (personalized-by-you group), 236 opted for setting the goal by the algorithm (personalized-by-the-algorithm group), and 933 chose to keep the default goal (not-changed group). The algorithm used a moving-window percentile rank method based on step data from the previous 4 weeks. Users who did not personalize retained the default goal. The remaining 2000 users in group 2 did not receive the email and also retained the default goal. To evaluate the effectiveness of step goal personalization strategies, we used propensity score matching and difference-in-difference analysis.</p><p><strong>Results: </strong>Users in the personalized-by-you group increased weekly step count by 3793 a week, while those in the personalized-by-the-algorithm group increased by 4315 steps a week, compared with the not-changed group (users with default goals). The 2 strategies appear to have a similar effect. Interestingly, users in the not-changed group also increased their weekly steps by 1759. Furthermore, the effectiveness of each strategy varied by baseline activity level. The personalized-by-you strategy was effective for medium- (increase of 5842 steps) and high-active users (increase of 4266 steps) but not for low-active users (increase of 384 steps; P=.82). Conversely, the personalized-by-the-algorithm strategy was effective for low- (increase of 5095 steps) and medium-active users (increase of 5278 steps) but not for high-active users (increase of 1446 steps; P=.51).</p><p><strong>Conclusions: </strong>Step goal personalization demonstrates short-term effectiveness. However, their impact varies by users' baseline activity levels, indicating the need for a tailored approach for different user segments. Future studies should e
{"title":"Effectiveness of Step Goal Personalization Strategies on Physical Activity in a Mobile Health App: A Field Study.","authors":"Xia Liu, Tammo H A Bijmolt, Marijke C Leliveld, Ernst H Noppers","doi":"10.2196/81779","DOIUrl":"10.2196/81779","url":null,"abstract":"<p><strong>Background: </strong>Goal personalization features integrated into mobile health apps have the potential to enhance physical activity, as some evidence shows that the personalized goals generated by algorithms are more effective than default or fixed goals. However, it remains unclear whether goals set by users are more effective than fixed goals and which personalization strategy is more effective for different user segments.</p><p><strong>Objective: </strong>This field study aimed to evaluate (1) the efficacy of 2 step goal personalization strategies-personalized-by-you and personalized-by-the-algorithm-and (2) which strategy is more effective among users with different activity levels.</p><p><strong>Methods: </strong>All users of SamenGezond, a Dutch mobile health app, have a default goal of 2000 steps per day, 5 days a week. For this study, 2 random groups were selected, totaling 5800 users. Subsequently, an email was sent to 3800 users in group 1, asking whether they were satisfied with their current goal. Those who were not satisfied were offered 2 personalization options: to set a goal themselves or to have the algorithm integrated in the app set goals for them. In total, 1399 users responded: 230 chose to set their own goals (personalized-by-you group), 236 opted for setting the goal by the algorithm (personalized-by-the-algorithm group), and 933 chose to keep the default goal (not-changed group). The algorithm used a moving-window percentile rank method based on step data from the previous 4 weeks. Users who did not personalize retained the default goal. The remaining 2000 users in group 2 did not receive the email and also retained the default goal. To evaluate the effectiveness of step goal personalization strategies, we used propensity score matching and difference-in-difference analysis.</p><p><strong>Results: </strong>Users in the personalized-by-you group increased weekly step count by 3793 a week, while those in the personalized-by-the-algorithm group increased by 4315 steps a week, compared with the not-changed group (users with default goals). The 2 strategies appear to have a similar effect. Interestingly, users in the not-changed group also increased their weekly steps by 1759. Furthermore, the effectiveness of each strategy varied by baseline activity level. The personalized-by-you strategy was effective for medium- (increase of 5842 steps) and high-active users (increase of 4266 steps) but not for low-active users (increase of 384 steps; P=.82). Conversely, the personalized-by-the-algorithm strategy was effective for low- (increase of 5095 steps) and medium-active users (increase of 5278 steps) but not for high-active users (increase of 1446 steps; P=.51).</p><p><strong>Conclusions: </strong>Step goal personalization demonstrates short-term effectiveness. However, their impact varies by users' baseline activity levels, indicating the need for a tailored approach for different user segments. Future studies should e","PeriodicalId":14756,"journal":{"name":"JMIR mHealth and uHealth","volume":"14 ","pages":"e81779"},"PeriodicalIF":6.2,"publicationDate":"2026-02-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12916092/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146219757","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>As the world's population ages, the prevalence of chronic low back pain (CLBP) is increasing, placing a substantial burden on individuals and health care systems. Mobile health (mHealth) apps offer a potentially scalable solution to support self-management, but little is known about how, why, for whom, and under what circumstances such tools work in real-world settings.</p><p><strong>Objectives: </strong>This study aimed to test and refine 3 program theories-developed through a previous realist review-on how mobile apps support CLBP self-management. The goal was to understand the key contextual factors and mechanisms that influence when and why a digital self-management intervention may succeed or fail.</p><p><strong>Methods: </strong>A realist evaluation was conducted using one-on-one telephone interviews with 9 participants who had used the Curable app for 3 months to self-manage their CLBP. Realist interviews followed a teacher-learner cycle to explore, test, and refine the program theories. Abductive and retroductive analysis was used to develop context-mechanism-outcome configurations (CMOCs), which were synthesized into refined theories of digital self-management in chronic pain.</p><p><strong>Results: </strong>A total of 20 CMOCs were constructed, supporting 3 overarching program theories centered on empowerment, self-management burden, and timing. First, the app was empowering when it offered credible and accessible knowledge that helped participants understand their pain, build confidence, and reduce reliance on health care providers. However, engagement depended on individual beliefs and expectations: those with strong biomedical views struggled to connect with the app's psychosocial framing. Second, while the app could ease the burden of self-management by offering support between appointments, it could also increase burden during flare-ups, when users lacked the capacity to engage. Features such as proactive content delivery and low-demand interfaces were viewed as essential for continued use. Third, timing emerged as a key factor. Early introduction was beneficial for some, but others needed to first accept the chronicity of their condition before they were ready to engage with self-management tools. Trust in the source recommending the app also influenced engagement. While clinician endorsement was often valued-especially early in the self-management journey-participants who had experienced unmet needs or disillusionment in clinical encounters reported that peer recommendations or nonclinical sources held greater weight. This highlights the importance of aligning recommendations with individuals' evolving relationships with authority and trust.</p><p><strong>Conclusions: </strong>Mobile apps like Curable (Curable Inc) can support empowerment and continuity of care in CLBP, but their success depends on personalization, timing, and relational dynamics. To prevent feelings of abandonment, such tools shou
{"title":"Mobile App-Supported Self-Management for Chronic Low Back Pain: Realist Evaluation.","authors":"Rebecca Hunter, Trish Gorely, Michelle Beattie","doi":"10.2196/66435","DOIUrl":"10.2196/66435","url":null,"abstract":"<p><strong>Background: </strong>As the world's population ages, the prevalence of chronic low back pain (CLBP) is increasing, placing a substantial burden on individuals and health care systems. Mobile health (mHealth) apps offer a potentially scalable solution to support self-management, but little is known about how, why, for whom, and under what circumstances such tools work in real-world settings.</p><p><strong>Objectives: </strong>This study aimed to test and refine 3 program theories-developed through a previous realist review-on how mobile apps support CLBP self-management. The goal was to understand the key contextual factors and mechanisms that influence when and why a digital self-management intervention may succeed or fail.</p><p><strong>Methods: </strong>A realist evaluation was conducted using one-on-one telephone interviews with 9 participants who had used the Curable app for 3 months to self-manage their CLBP. Realist interviews followed a teacher-learner cycle to explore, test, and refine the program theories. Abductive and retroductive analysis was used to develop context-mechanism-outcome configurations (CMOCs), which were synthesized into refined theories of digital self-management in chronic pain.</p><p><strong>Results: </strong>A total of 20 CMOCs were constructed, supporting 3 overarching program theories centered on empowerment, self-management burden, and timing. First, the app was empowering when it offered credible and accessible knowledge that helped participants understand their pain, build confidence, and reduce reliance on health care providers. However, engagement depended on individual beliefs and expectations: those with strong biomedical views struggled to connect with the app's psychosocial framing. Second, while the app could ease the burden of self-management by offering support between appointments, it could also increase burden during flare-ups, when users lacked the capacity to engage. Features such as proactive content delivery and low-demand interfaces were viewed as essential for continued use. Third, timing emerged as a key factor. Early introduction was beneficial for some, but others needed to first accept the chronicity of their condition before they were ready to engage with self-management tools. Trust in the source recommending the app also influenced engagement. While clinician endorsement was often valued-especially early in the self-management journey-participants who had experienced unmet needs or disillusionment in clinical encounters reported that peer recommendations or nonclinical sources held greater weight. This highlights the importance of aligning recommendations with individuals' evolving relationships with authority and trust.</p><p><strong>Conclusions: </strong>Mobile apps like Curable (Curable Inc) can support empowerment and continuity of care in CLBP, but their success depends on personalization, timing, and relational dynamics. To prevent feelings of abandonment, such tools shou","PeriodicalId":14756,"journal":{"name":"JMIR mHealth and uHealth","volume":"14 ","pages":"e66435"},"PeriodicalIF":6.2,"publicationDate":"2026-02-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12912768/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146213161","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}
Marta Pawełczak-Szastok, Anna Syska-Bielak, Aleksandra Krzywon, Michał Jarząb
<p><strong>Background: </strong>eHealth is an increasingly used method of health care in the field of psycho-oncology. While many reports highlight the positive impact of psychological eHealth tools, some patients refuse to use them.</p><p><strong>Objective: </strong>This study aimed to expand knowledge of the motivation and psychoemotional functioning of patients who consciously refuse to use eHealth technology in the form of a mobile psycho-oncology app offered as part of a clinical trial. To our knowledge, this is the first study to address this topic.</p><p><strong>Methods: </strong>A retrospective cross-sectional study was conducted between December 2022 and February 2023 to investigate the reasons why 56 patients with breast cancer refused to use the psycho-oncology mobile app offered as part of a clinical trial by the Breast Cancer Unit. The primary aim of the study was to analyze patients' self-reported reasons for not engaging with the app, while also exploring their psychoemotional functioning, including stress levels (measured using the distress thermometer), personality traits (measured using the Ten-Item Personality Inventory), coping strategies (measured using the Coping Orientation to Problems Experienced Questionnaire), and Self-efficacy (measured using the General Self-Efficacy Scale). Participants in this study declined the app intervention but agreed to participate in this separate observational study, indicating that their refusal was related to the app itself rather than to participation in clinical research in general.</p><p><strong>Results: </strong>The patients experienced a clinically meaningful elevation in stress levels (mean 5, SD 2.1 points) and Self-efficacy (mean 32.1, SD 5.1 points). Among 5 dimensions of personality traits, patients scored highest in Agreeableness (mean 6.5, SD 0.8 stens) and Conscientiousness (mean 6.4, SD 0.9) and lowest in Neuroticism (mean 3.4, SD 1.8) (other dimensions: Extraversion [mean 5.8, SD 1.6 stens] and Openness to Experiences [mean 4.4, SD 1.5 stens]). In terms of coping with stress, patients most frequently used the strategies of Active Coping (mean 2.6, SD 0.5 points), Acceptance (mean 2.6, SD 0.6 points), and Seeking Emotional Support (mean 2.6, SD 0.6 points), and least frequently used the strategies of Psychoactive Substance Use (mean 0.2, SD 0.6 points) and Restraint (mean 0.5, SD 0.7 points). Patient responses regarding refusal to participate in app testing were divided into four categories: (1) Focus on Life Outside the Disease, (2) Focus on Disease and Treatment, (3) Denial Mechanism, and (4) Technical Issues. Statistically significant differences were found between the groups. The Focus on Life Outside the Disease group of patients had higher levels of Self-efficacy, lower Neuroticism, and more frequent use of the Positive reevaluation strategy compared to the other groups.</p><p><strong>Conclusions: </strong>Our patients' decision not to use the eHealth psycho-oncology app
{"title":"Reluctance to Use a Psycho-Oncology Mobile App Among Patients With Primary Breast Cancer: Retrospective Cross-Sectional Survey.","authors":"Marta Pawełczak-Szastok, Anna Syska-Bielak, Aleksandra Krzywon, Michał Jarząb","doi":"10.2196/71412","DOIUrl":"10.2196/71412","url":null,"abstract":"<p><strong>Background: </strong>eHealth is an increasingly used method of health care in the field of psycho-oncology. While many reports highlight the positive impact of psychological eHealth tools, some patients refuse to use them.</p><p><strong>Objective: </strong>This study aimed to expand knowledge of the motivation and psychoemotional functioning of patients who consciously refuse to use eHealth technology in the form of a mobile psycho-oncology app offered as part of a clinical trial. To our knowledge, this is the first study to address this topic.</p><p><strong>Methods: </strong>A retrospective cross-sectional study was conducted between December 2022 and February 2023 to investigate the reasons why 56 patients with breast cancer refused to use the psycho-oncology mobile app offered as part of a clinical trial by the Breast Cancer Unit. The primary aim of the study was to analyze patients' self-reported reasons for not engaging with the app, while also exploring their psychoemotional functioning, including stress levels (measured using the distress thermometer), personality traits (measured using the Ten-Item Personality Inventory), coping strategies (measured using the Coping Orientation to Problems Experienced Questionnaire), and Self-efficacy (measured using the General Self-Efficacy Scale). Participants in this study declined the app intervention but agreed to participate in this separate observational study, indicating that their refusal was related to the app itself rather than to participation in clinical research in general.</p><p><strong>Results: </strong>The patients experienced a clinically meaningful elevation in stress levels (mean 5, SD 2.1 points) and Self-efficacy (mean 32.1, SD 5.1 points). Among 5 dimensions of personality traits, patients scored highest in Agreeableness (mean 6.5, SD 0.8 stens) and Conscientiousness (mean 6.4, SD 0.9) and lowest in Neuroticism (mean 3.4, SD 1.8) (other dimensions: Extraversion [mean 5.8, SD 1.6 stens] and Openness to Experiences [mean 4.4, SD 1.5 stens]). In terms of coping with stress, patients most frequently used the strategies of Active Coping (mean 2.6, SD 0.5 points), Acceptance (mean 2.6, SD 0.6 points), and Seeking Emotional Support (mean 2.6, SD 0.6 points), and least frequently used the strategies of Psychoactive Substance Use (mean 0.2, SD 0.6 points) and Restraint (mean 0.5, SD 0.7 points). Patient responses regarding refusal to participate in app testing were divided into four categories: (1) Focus on Life Outside the Disease, (2) Focus on Disease and Treatment, (3) Denial Mechanism, and (4) Technical Issues. Statistically significant differences were found between the groups. The Focus on Life Outside the Disease group of patients had higher levels of Self-efficacy, lower Neuroticism, and more frequent use of the Positive reevaluation strategy compared to the other groups.</p><p><strong>Conclusions: </strong>Our patients' decision not to use the eHealth psycho-oncology app","PeriodicalId":14756,"journal":{"name":"JMIR mHealth and uHealth","volume":"14 ","pages":"e71412"},"PeriodicalIF":6.2,"publicationDate":"2026-02-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12904500/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146194563","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}
Joel Crawford, Jenny Blomqvist, Katarina Ulfsdotter Gunnarsson, Preben Bendtsen, Marcus Bendtsen
Background: Smoking is a leading cause of mortality and morbidity worldwide. Efforts to reduce smoking prevalence have used SMS text message-based interventions, which typically send participants a series of short, informational, motivational, and practical messages over a set period. Evidence highlights the efficacy of using this approach to support smoking cessation, with such trials typically reporting the average treatment effects, in which causal inference is made regarding the average effect of a treatment on a heterogeneous sample. Nonetheless, using this approach to assessing treatment effects means we are unable to account for individual factors that impact the effectiveness of a treatment on outcomes, such as age, gender, and genetics.
Objective: This study aimed to estimate the individualized effects of an SMS text message-based smoking cessation intervention to ascertain which individuals benefited the most and least during an effectiveness trial.
Methods: Data from a randomized controlled trial including 1012 adults from the Swedish general population were used. The trial assessed the effects of an SMS text message-based intervention, NEXit (Nicotine Exit), that aimed to change behavior by increasing the importance of change, boosting knowledge on how to change, and instilling confidence for change. Outcomes assessed in the trial were prolonged abstinence and point prevalence of smoking cessation. Individualized treatment effects were modeled using baseline factors (demographics, psychosocial variables, and past behavior) to study who benefited the most and least from the intervention.
Results: For prolonged abstinence, there was evidence of heterogeneous effects, with those benefiting the most from NEXit being older adults, female participants, individuals with high confidence in their ability to quit, and those who believed that quitting was important. For point prevalence abstinence, older individuals and those reporting high confidence in the ability to quit, the importance of quitting, and knowledge for change benefited the most. For both outcomes, individuals who reported smoking for a longer duration and smoking more at baseline benefited less.
Conclusions: The results demonstrate how individuals respond differently to an SMS text message-based smoking cessation intervention. This provides an insight into who benefits the most and least from the intervention in terms of demographics, baseline characteristics, and behaviors. The study highlights which individuals need to be specifically targeted and/or have content developed to suit their individual needs to further reduce the prevalence of smoking.
{"title":"Individualized Treatment Effects of a Digital Smoking Cessation Intervention Among Individuals Looking Online for Help: Secondary Analysis of a Randomized Controlled Trial.","authors":"Joel Crawford, Jenny Blomqvist, Katarina Ulfsdotter Gunnarsson, Preben Bendtsen, Marcus Bendtsen","doi":"10.2196/63578","DOIUrl":"10.2196/63578","url":null,"abstract":"<p><strong>Background: </strong>Smoking is a leading cause of mortality and morbidity worldwide. Efforts to reduce smoking prevalence have used SMS text message-based interventions, which typically send participants a series of short, informational, motivational, and practical messages over a set period. Evidence highlights the efficacy of using this approach to support smoking cessation, with such trials typically reporting the average treatment effects, in which causal inference is made regarding the average effect of a treatment on a heterogeneous sample. Nonetheless, using this approach to assessing treatment effects means we are unable to account for individual factors that impact the effectiveness of a treatment on outcomes, such as age, gender, and genetics.</p><p><strong>Objective: </strong>This study aimed to estimate the individualized effects of an SMS text message-based smoking cessation intervention to ascertain which individuals benefited the most and least during an effectiveness trial.</p><p><strong>Methods: </strong>Data from a randomized controlled trial including 1012 adults from the Swedish general population were used. The trial assessed the effects of an SMS text message-based intervention, NEXit (Nicotine Exit), that aimed to change behavior by increasing the importance of change, boosting knowledge on how to change, and instilling confidence for change. Outcomes assessed in the trial were prolonged abstinence and point prevalence of smoking cessation. Individualized treatment effects were modeled using baseline factors (demographics, psychosocial variables, and past behavior) to study who benefited the most and least from the intervention.</p><p><strong>Results: </strong>For prolonged abstinence, there was evidence of heterogeneous effects, with those benefiting the most from NEXit being older adults, female participants, individuals with high confidence in their ability to quit, and those who believed that quitting was important. For point prevalence abstinence, older individuals and those reporting high confidence in the ability to quit, the importance of quitting, and knowledge for change benefited the most. For both outcomes, individuals who reported smoking for a longer duration and smoking more at baseline benefited less.</p><p><strong>Conclusions: </strong>The results demonstrate how individuals respond differently to an SMS text message-based smoking cessation intervention. This provides an insight into who benefits the most and least from the intervention in terms of demographics, baseline characteristics, and behaviors. The study highlights which individuals need to be specifically targeted and/or have content developed to suit their individual needs to further reduce the prevalence of smoking.</p>","PeriodicalId":14756,"journal":{"name":"JMIR mHealth and uHealth","volume":"14 ","pages":"e63578"},"PeriodicalIF":6.2,"publicationDate":"2026-02-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12893526/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146165378","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>Driven by technological advancements, the proliferation of mobile sports and health apps has revolutionized health management by improving efficiency, cost-effectiveness, and accessibility. While the widespread adoption of these platforms has transformed public health practices and social well-being in China, emerging evidence suggests that inadequacies in their privacy policies may compromise personal information (PI) protection.</p><p><strong>Objective: </strong>This study aimed to conduct a systematic evaluation of privacy policy compliance among 286 mobile sports and health apps in the Chinese Mainland, benchmarking them against the Personal Information Protection Law and associated PI regulatory guidelines.</p><p><strong>Methods: </strong>This study develops a privacy policy compliance indicator scale based on the information life cycle and the legal framework for PI protection in the Chinese Mainland. This scale consists of 5 level 1 indicators and 37 level 2 indicators that assess the privacy policy compliance.</p><p><strong>Results: </strong>The privacy policy compliance of 286 sports and health apps generally performed worse, with only a minimal number (n=11, 3.8%) of apps scoring above 90 points (rated as excellent), nearly half (n=121, 42.3%) of apps scored below 60 points (rated as unqualified). Among the 5 level 1 evaluation indicators for privacy compliance in sports and health apps, the compliance rate for PI collection (mean 74%, SD 25.8%) is the highest, while the compliance rate for PI storage (mean 53.5%, SD 28.4%) is the lowest. The compliance rates for privacy policies across the remaining 3 level 1 evaluation indicators, such as PI usage (mean 54.2%, SD 24.4%), PI entrusted processing, sharing, transferring, and disclosing (mean 62.2%, SD 19.8%), and PI security and feedback (mean 61.7%, SD 21.3%), fall around 60%. Out of 37, 17 level 2 evaluation indicators show a compliance rate below 60%. The compliance rate with privacy policies for 5 level 2 evaluation indicators is exceptionally high, including collection subject (mean 97.2%, SD 16.5%), collection type (mean 99%, SD 10.2%), collection purpose (mean 96.2%, SD 19.3%), reasons for sharing, transferring, and disclosing PI (mean 91.6%, SD 27.8%), and feedback channel (mean 93.4%, SD 24.9%). Notably, 3 indicators exhibit compliance rates below 20%, including sensitive information storage (mean 14%, SD 34.7%), constraints of automatic decision-making (mean 9.4%, SD 29.3%), and deceased user rule (mean 5.2%, SD 22.3%). Authorization for sensitive information (mean 29.4%, SD 45.6%) lagged behind general information (mean 83.6%, SD 37.1%).</p><p><strong>Conclusions: </strong>Although some apps have established commendable policies, there are gaps that compromise the efficacy of PI protection. Considering this, this paper proposes targeted actions for 3 stakeholders: users, regulators, and legislators. Only through coordinated action can the app ec
{"title":"Privacy Policy Compliance of Mobile Sports and Health Apps in China: Scale Development, Data Analysis, and Prospects for Regulatory Reform.","authors":"Rengui Guo, Fanhong Chen","doi":"10.2196/73651","DOIUrl":"10.2196/73651","url":null,"abstract":"<p><strong>Background: </strong>Driven by technological advancements, the proliferation of mobile sports and health apps has revolutionized health management by improving efficiency, cost-effectiveness, and accessibility. While the widespread adoption of these platforms has transformed public health practices and social well-being in China, emerging evidence suggests that inadequacies in their privacy policies may compromise personal information (PI) protection.</p><p><strong>Objective: </strong>This study aimed to conduct a systematic evaluation of privacy policy compliance among 286 mobile sports and health apps in the Chinese Mainland, benchmarking them against the Personal Information Protection Law and associated PI regulatory guidelines.</p><p><strong>Methods: </strong>This study develops a privacy policy compliance indicator scale based on the information life cycle and the legal framework for PI protection in the Chinese Mainland. This scale consists of 5 level 1 indicators and 37 level 2 indicators that assess the privacy policy compliance.</p><p><strong>Results: </strong>The privacy policy compliance of 286 sports and health apps generally performed worse, with only a minimal number (n=11, 3.8%) of apps scoring above 90 points (rated as excellent), nearly half (n=121, 42.3%) of apps scored below 60 points (rated as unqualified). Among the 5 level 1 evaluation indicators for privacy compliance in sports and health apps, the compliance rate for PI collection (mean 74%, SD 25.8%) is the highest, while the compliance rate for PI storage (mean 53.5%, SD 28.4%) is the lowest. The compliance rates for privacy policies across the remaining 3 level 1 evaluation indicators, such as PI usage (mean 54.2%, SD 24.4%), PI entrusted processing, sharing, transferring, and disclosing (mean 62.2%, SD 19.8%), and PI security and feedback (mean 61.7%, SD 21.3%), fall around 60%. Out of 37, 17 level 2 evaluation indicators show a compliance rate below 60%. The compliance rate with privacy policies for 5 level 2 evaluation indicators is exceptionally high, including collection subject (mean 97.2%, SD 16.5%), collection type (mean 99%, SD 10.2%), collection purpose (mean 96.2%, SD 19.3%), reasons for sharing, transferring, and disclosing PI (mean 91.6%, SD 27.8%), and feedback channel (mean 93.4%, SD 24.9%). Notably, 3 indicators exhibit compliance rates below 20%, including sensitive information storage (mean 14%, SD 34.7%), constraints of automatic decision-making (mean 9.4%, SD 29.3%), and deceased user rule (mean 5.2%, SD 22.3%). Authorization for sensitive information (mean 29.4%, SD 45.6%) lagged behind general information (mean 83.6%, SD 37.1%).</p><p><strong>Conclusions: </strong>Although some apps have established commendable policies, there are gaps that compromise the efficacy of PI protection. Considering this, this paper proposes targeted actions for 3 stakeholders: users, regulators, and legislators. Only through coordinated action can the app ec","PeriodicalId":14756,"journal":{"name":"JMIR mHealth and uHealth","volume":"14 ","pages":"e73651"},"PeriodicalIF":6.2,"publicationDate":"2026-02-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12893645/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146165464","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}
Teale Masrani, David C Hodgins, Hyoun S Kim, Katherine Rittenbach, Erika Johnson, Geoffrey Messier
Background: Mobile health (mHealth) apps have shown promise to support recovery from substance use disorders. However, evidence on engagement and efficacy is still inconclusive.
Objective: This study aims to identify design considerations for optimizing engagement in mHealth apps for those recovering from problematic substance use, by analyzing real-world experiences with co-designed app features.
Methods: We co-designed, deployed, and evaluated an mHealth app. Initial co-design interviews with 14 individuals in recovery led to 3 new features integrated into an existing mHealth app. The app was deployed for a 6-week trial with 53 participants using it during their daily routines without researcher supervision. Usage patterns were analyzed throughout the trial period, and follow-up interviews with 12 app users foregrounded subjective usage experiences and considerations for future design.
Results: We developed 3 new features following co-design interviews: a goal-setting feature, a craving tracker, and a meetings log. Usage metrics revealed mixed engagement, with 45.3% (24/53) of users actively engaging with the app throughout the trial. These active users opened the app 27.1 unique times on average, with a retention rate after 30 days among active users of 45.8% (11/24), exceeding the typical mobile app retention benchmark of 7% after 30 days. Interviews revealed that participants preferred app functionality to extend beyond substance use domains to support other dimensions of their lives not directly pertaining to substance use, such as general goals and daily routines. Participants further suggested that recovery apps should act as private digital journals while also providing a sense of community and connection to broader recovery ecosystems. Additionally, mHealth designs that allow users to configure their own personalized recovery pathways in the app can benefit some users who appreciate increased autonomy, while others may become overwhelmed by a lack of prescriptive guidance.
Conclusions: It is valuable to incorporate iterative co-design methodologies into digital health and recovery app research to help optimize engagement. Furthermore, recovery apps can benefit from flexible designs with customizable degrees of user autonomy. Future designers can better cater to individual user preferences by personalizing mHealth designs so that they strike a balance between system control and user control over digital recovery pathways.
{"title":"Designing mHealth Apps for Substance Use Recovery Through Real-World Co-Design and Deployment: Mixed Methods Study.","authors":"Teale Masrani, David C Hodgins, Hyoun S Kim, Katherine Rittenbach, Erika Johnson, Geoffrey Messier","doi":"10.2196/83984","DOIUrl":"10.2196/83984","url":null,"abstract":"<p><strong>Background: </strong>Mobile health (mHealth) apps have shown promise to support recovery from substance use disorders. However, evidence on engagement and efficacy is still inconclusive.</p><p><strong>Objective: </strong>This study aims to identify design considerations for optimizing engagement in mHealth apps for those recovering from problematic substance use, by analyzing real-world experiences with co-designed app features.</p><p><strong>Methods: </strong>We co-designed, deployed, and evaluated an mHealth app. Initial co-design interviews with 14 individuals in recovery led to 3 new features integrated into an existing mHealth app. The app was deployed for a 6-week trial with 53 participants using it during their daily routines without researcher supervision. Usage patterns were analyzed throughout the trial period, and follow-up interviews with 12 app users foregrounded subjective usage experiences and considerations for future design.</p><p><strong>Results: </strong>We developed 3 new features following co-design interviews: a goal-setting feature, a craving tracker, and a meetings log. Usage metrics revealed mixed engagement, with 45.3% (24/53) of users actively engaging with the app throughout the trial. These active users opened the app 27.1 unique times on average, with a retention rate after 30 days among active users of 45.8% (11/24), exceeding the typical mobile app retention benchmark of 7% after 30 days. Interviews revealed that participants preferred app functionality to extend beyond substance use domains to support other dimensions of their lives not directly pertaining to substance use, such as general goals and daily routines. Participants further suggested that recovery apps should act as private digital journals while also providing a sense of community and connection to broader recovery ecosystems. Additionally, mHealth designs that allow users to configure their own personalized recovery pathways in the app can benefit some users who appreciate increased autonomy, while others may become overwhelmed by a lack of prescriptive guidance.</p><p><strong>Conclusions: </strong>It is valuable to incorporate iterative co-design methodologies into digital health and recovery app research to help optimize engagement. Furthermore, recovery apps can benefit from flexible designs with customizable degrees of user autonomy. Future designers can better cater to individual user preferences by personalizing mHealth designs so that they strike a balance between system control and user control over digital recovery pathways.</p>","PeriodicalId":14756,"journal":{"name":"JMIR mHealth and uHealth","volume":"14 ","pages":"e83984"},"PeriodicalIF":6.2,"publicationDate":"2026-02-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12936659/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146165375","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}
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