Journal of Medical Internet Research最新文献

{"title":"25 Years of Digital Health Toward Universal Health Coverage in Low- and Middle-Income Countries: Rapid Systematic Review.","authors":"Bry Sylla, Ouedraogo Ismaila, Gayo Diallo","doi":"10.2196/59042","DOIUrl":"https://doi.org/10.2196/59042","url":null,"abstract":"<p><strong>Background: </strong>Over the last 25 years, digital health interventions in low- and middle-income countries have undergone substantial transformations propelled by technological advancements, increased internet accessibility, and a deeper appreciation of the benefits of digital tools in enhancing health care availability.</p><p><strong>Objective: </strong>This study aims to examine the evolution, impact, and prospects of digital health interventions in low- and middle-income countries, highlighting their role in improving health care accessibility and equity.</p><p><strong>Methods: </strong>A retrospective analysis of digital health initiatives scanning the past two and a half decades focused on the progression from basic SMS platforms to sophisticated mobile health apps and other health digital interventions. Relevant literature and case studies were reviewed to elucidate key milestones, successes, challenges, and opportunities in advancing digital health initiatives in low- and middle-income regions.</p><p><strong>Results: </strong>Digital health initiatives in low- and middle-income countries initially targeted specific health concerns, such as malaria diagnosis and treatment, through text-based platforms, demonstrating their efficacy in reaching remote and marginalized communities. With the proliferation of mobile phone ownership and internet access, these interventions evolved into comprehensive mobile health apps, facilitating self-care support, patient education, chronic disease monitoring, and remote consultations. The COVID-19 pandemic further accelerated the adoption of digital health interventions, particularly in disseminating health information, supporting contact tracing efforts, and enabling virtual consultations to alleviate strain on health care systems.</p><p><strong>Conclusions: </strong>The future of digital health interventions in low- and middle-income countries holds immense promise, fueled by emerging technologies such as artificial intelligence, machine learning, and blockchain. However, challenges persist in ensuring equitable access to digital health technologies, addressing disparities in digital literacy, and establishing robust health care infrastructure. Collaboration among governments, health care providers, technology innovators, and communities is essential to overcome these challenges and harness the full potential of digital health to improve health care outcomes in low- and middle-income countries.</p>","PeriodicalId":16337,"journal":{"name":"Journal of Medical Internet Research","volume":"27 ","pages":"e59042"},"PeriodicalIF":5.8,"publicationDate":"2025-05-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144179920","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}

{"title":"Understanding Gender-Specific Daily Care Preferences: Topic Modeling Study.","authors":"Kyungmi Woo, Se Hee Min, Aeri Kim, Subin Choi, Gregory L Alexander, Terrence O'Malley, Maria D Moen, Maxim Topaz","doi":"10.2196/64160","DOIUrl":"https://doi.org/10.2196/64160","url":null,"abstract":"<p><strong>Background: </strong>Daily preferences are a reflection of how adults wish to have their needs and values addressed, contributing to joy and satisfaction in their daily lives. Clinical settings often regard older adults as a uniform group, neglecting the diversity within this population, which results in a shortfall of person-centered care that overlooks their distinct daily care preferences. At the heart of person-centered care lies the imperative to comprehend and integrate these preferences into the care process. Recognizing and addressing gender differences in older adults is critical to customizing care plans, thereby optimizing quality of life and well-being for individuals. This study addresses the need to understand the diverse daily care preferences of adults, particularly among older populations, who represent a growing demographic with unique needs and interests.</p><p><strong>Objective: </strong>This study aims to identify and analyze the key themes and daily care preferences from unstructured adult text narratives with a focus on uncovering gender-specific variations.</p><p><strong>Methods: </strong>This study used 4350 deidentified, unstructured textual data from MyDirectives (MyDirectives, Inc), an interactive online platform. Advanced topic modeling techniques were used to extract meaningful themes, and gender-specific term frequency and distribution were examined to identify gender differences in these elements.</p><p><strong>Results: </strong>The study sample included 2883 women (mean age 63.02, SD 13.69 years) and 1467 men (mean age 67.07, SD 11.73 years). Our analysis identified six major themes: (1) \"entertainment\" (12.14%, 528/4350), (2) \"music\" (10.39%, 452/4350), (3) \"personal interests and memories\" (38.18%, 1661/4350), (4) \"intimate relationships\" (14.92%, 649/4350), (5) \"natural comforts\" (16.18%, 704/4350), and (6) \"emotional, cultural, and spiritual foundations\" (8.18%, 356/4350). Gender differences were evident: women were more likely to express preferences for \"personal interests and memories\" (40.7% vs 33.3%), \"natural comforts\" (18.4% vs 11.9%), and \"emotional and spiritual foundations\" (9.3% vs 6.1%) than men. Men expressed stronger preferences for \"entertainment\" (18.1% vs 9.1%) and \"music\" (16.8% vs 7.2%). Common terms across all participants included \"dog,\" \"love,\" \"friends,\" and \"book.\" Notably, the study revealed significant gender differences in daily care preferences, especially regarding familial relationships and entertainment choices.</p><p><strong>Conclusions: </strong>The findings underscore the importance of recognizing individual daily care preferences in person-centered care, particularly regarding gender. Understanding these preferences is crucial for improving care quality and patient satisfaction, thereby enhancing the overall quality of life for adults receiving care across our health care system.</p>","PeriodicalId":16337,"journal":{"name":"Journal of Medical Internet Research","volume":"27 ","pages":"e64160"},"PeriodicalIF":5.8,"publicationDate":"2025-05-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144182316","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}

{"title":"Aligning With the Goals of the Planetary Health Concept Regarding Ecological Sustainability and Digital Health: Scoping Review.","authors":"Mathea Berger, Jan Peter Ehlers, Julia Nitsche","doi":"10.2196/71795","DOIUrl":"https://doi.org/10.2196/71795","url":null,"abstract":"<p><strong>Background: </strong>Climate change, driven by greenhouse gas emissions, threatens human health and biodiversity. While the digitalization of health care, including telemedicine and artificial intelligence, offers sustainability benefits, it also raises concerns about energy use and electronic waste. Balancing these factors is key to a sustainable health care future.</p><p><strong>Objective: </strong>The objective of this review was to examine the extent to which digitalization in the health care sector influences environmental sustainability. Specifically, it aimed to assess how digitalization can contribute to reducing the health care sector's impact on global climate change. From these findings, conclusions were drawn regarding the extent to which digitalization aligns with the objectives of the Planetary Health movement and how these 2 movements may mutually reinforce each other.</p><p><strong>Methods: </strong>A scoping review guided by the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) 2020 guidelines using databases such as PubMed and Scopus was conducted, and 58 quantitative studies from 2009 to 2024 were analyzed for environmental, social, and economic outcomes aligned with Planetary Health goals.</p><p><strong>Results: </strong>This review analyzed 58 studies on the environmental impact of digitalization in health care primarily focusing on telemedicine, which was examined in 91% (53/58) of the studies. Most studies (56/58, 97%) quantified transport-related emissions avoided through digitalization, with some also assessing emissions from health care facilities, medical equipment, and energy consumption. Findings indicated that telemedicine significantly reduces carbon dioxide emissions, with total avoided emissions amounting to approximately 830 million kg. A substantial proportion of the studies (36/58, 62%) focused on social aspects, highlighting factors such as patient satisfaction, time efficiency, and overall convenience. In addition, economic considerations were analyzed in 48% (28/58) of the studies, emphasizing cost reductions and resource optimization. However, only 12% (7/58) of the studies evaluated the full life cycle impact of digital technologies, highlighting the need for further research on their long-term environmental sustainability.</p><p><strong>Conclusions: </strong>This review calls for further research beyond telemedicine, advocating for life cycle analyses and actionable strategies for a sustainable digitalization in health care systems. The Planetary Health framework is highlighted as a guide for ensuring sustainable digital transformation in health care.</p>","PeriodicalId":16337,"journal":{"name":"Journal of Medical Internet Research","volume":"27 ","pages":"e71795"},"PeriodicalIF":5.8,"publicationDate":"2025-05-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144173962","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}

{"title":"Digital Therapeutics in China: Comprehensive Review.","authors":"Nan Jiang, Xiru Yu, Yuxi Yang, Guanqiao Li, Chanchan He, Man Ping Wang, Yih Chung Tham, Tien Yin Wong, Keqin Rao","doi":"10.2196/70955","DOIUrl":"https://doi.org/10.2196/70955","url":null,"abstract":"&lt;p&gt;&lt;strong&gt;Background: &lt;/strong&gt;Digital therapeutics (DTx) are software-driven interventions that provide personalized, evidence-based treatments for various medical conditions. China's rapid technological adoption, large population, and supportive government policies position it as a potential global leader in DTx. However, challenges remain in clinical trial standardization, regulatory approval, product development, and reimbursement models. A comprehensive assessment of clinical evidence, commercialization trends, and regulatory frameworks is essential for understanding China's evolving DTx ecosystem and its global implications.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Objective: &lt;/strong&gt;This study systematically reviews and analyzes the DTx landscape in China, focusing on clinical trials, commercial products, regulatory frameworks, and pricing and reimbursement models. The findings provide insights for countries aiming to develop, regulate, and integrate DTx solutions into health care systems.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Methods: &lt;/strong&gt;This comprehensive review integrates multiple methodological approaches to examine different aspects of the DTx ecosystem in China. We conducted a systematic review and meta-analysis to evaluate clinical trials, searching PubMed, Google Scholar, IEEE, Web of Science, and ScienceDirect until July 2024. Meta-analyses used random-effects models, reporting results as standardized mean differences (SMDs) and 95% CIs. For commercial products, a scoping review using the National Medical Products Administration database was performed. Regulatory policies were systematically identified through a manual review of official government sources, while pricing and reimbursement models were analyzed through a comprehensive assessment of public and private insurance policies, government initiatives, and commercial pathways.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Results: &lt;/strong&gt;: A total of 96 clinical trials on DTx in China were identified, with cognitive disorders (n=21, 22%) and diabetes (n=20, 21%) being the most frequently studied, followed by cardiovascular diseases (n=8, 8%), sleeping disorders (n=6, 6%), and smoking cessation (n=6, 6%). Meta-analysis for diabetes DTx showed a trend toward improved hemoglobin A&lt;sub&gt;1c&lt;/sub&gt; levels in digital intervention groups compared to controls (SMD -0.96, 95% CI -2.03 to 0.11) but did not reach statistical significance (I²=97%). Meta-analysis for cognitive disorder DTx showed significant improvement in global cognitive function in DTx-treated participants (SMD 0.65, 95% CI 0.37-0.94), despite notable heterogeneity (I²=71.7%). The commercial landscape analysis identified 97 active DTx solutions, primarily targeting cognitive impairment (38 companies), ophthalmic diseases (30 companies), and respiratory diseases (5 companies). The regulatory review highlighted China's reliance on general medical device policies under the National Medical Products Administration rather than DTx-specific regulations, with emerging regional innovation policies su","PeriodicalId":16337,"journal":{"name":"Journal of Medical Internet Research","volume":"27 ","pages":"e70955"},"PeriodicalIF":5.8,"publicationDate":"2025-05-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144159547","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}

{"title":"Smartphone- and Tablet-Based Tools to Assess Cognition in Individuals With Preclinical Alzheimer Disease and Mild Cognitive Impairment: Scoping Review.","authors":"Rosanne L van den Berg, Sophie M van der Landen, Matthijs J Keijzer, Aniek M van Gils, Maureen van Dam, Kirsten A Ziesemer, Roos J Jutten, John E Harrison, Casper de Boer, Wiesje M van der Flier, Sietske Am Sikkes","doi":"10.2196/65297","DOIUrl":"10.2196/65297","url":null,"abstract":"&lt;p&gt;&lt;strong&gt;Background: &lt;/strong&gt;Assessment of cognitive decline in the earliest stages of Alzheimer disease (AD) is important but challenging. AD is a neurodegenerative disease characterized by gradual cognitive decline. Disease stages range from preclinical AD, in which individuals are cognitively unimpaired, to mild cognitive impairment (MCI) and dementia. Digital technologies promise to enable detection of early, subtle cognitive changes. Although the field of digital cognitive biomarkers is rapidly evolving, a comprehensive overview of the reporting of psychometric properties (ie, validity, reliability, responsiveness, and clinical meaningfulness) is missing. Insight into the extent to which these properties are evaluated is needed to identify the validation steps toward implementation.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Objective: &lt;/strong&gt;This scoping review aimed to identify the reporting on quality characteristics of smartphone- and tablet-based cognitive tools with potential for remote administration in individuals with preclinical AD or MCI. We focused on both psychometric properties and practical tool characteristics.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Methods: &lt;/strong&gt;This scoping review was conducted following the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews) guidelines. In total, 4 databases (PubMed, Embase, Web of Science, and PsycINFO) were systematically searched from January 1, 2008, to January 5, 2023. Studies were included that assessed the psychometric properties of cognitive smartphone- or tablet-based tools with potential for remote administration in individuals with preclinical AD or MCI. In total, 2 reviewers independently screened titles and abstracts in ASReview, a screening tool that combines manual and automatic screening using an active learning algorithm. Thereafter, we manually screened full texts in the web application Rayyan. For each included study, 2 reviewers independently explored the reported information on practical and psychometric properties. For each psychometric property, examples were provided narratively.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Results: &lt;/strong&gt;In total, 11,300 deduplicated studies were identified in the search. After screening, 50 studies describing 37 different digital tools were included in this review. Average administration time was 13.8 (SD 10.1; range 1-32) minutes, but for 38% (14/37) of the tools, this was not described. Most tools (31/37, 84%) were examined in 1 language. The investigated populations were mainly individuals with MCI (34/37, 92%), and fewer tools were examined in individuals with preclinical AD (8/37, 22%). For almost all tools (36/37, 97%), construct validity was assessed through evaluation of clinical or biological associations or relevant group differences. For a small number of tools, information on structural validity (3/37, 8%), test-retest reliability (12/37, 32%), responsiveness (6/37, 16%), or clinical meaningfulness (0%) was reported.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Co","PeriodicalId":16337,"journal":{"name":"Journal of Medical Internet Research","volume":"27 ","pages":"e65297"},"PeriodicalIF":5.8,"publicationDate":"2025-05-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144159566","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}

{"title":"Exploring the Application Capability of ChatGPT as an Instructor in Skills Education for Dental Medical Students: Randomized Controlled Trial.","authors":"Siyu Huang, Chang Wen, Xueying Bai, Sihong Li, Shuining Wang, Xiaoxuan Wang, Dong Yang","doi":"10.2196/68538","DOIUrl":"10.2196/68538","url":null,"abstract":"&lt;p&gt;&lt;strong&gt;Background: &lt;/strong&gt;Clinical operative skills training is a critical component of preclinical education for dental students. Although technology-assisted instruction, such as virtual reality and simulators, is increasingly being integrated, direct guidance from instructors remains the cornerstone of skill development. ChatGPT, an advanced conversational artificial intelligence model developed by OpenAI, is gradually being used in medical education.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Objective: &lt;/strong&gt;This study aimed to compare the effects of ChatGPT-assisted skill learning on performance, cognitive load, self-efficacy, learning motivation, and spatial ability, with the aim of evaluating the potential of ChatGPT in clinical operative skills education.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Methods: &lt;/strong&gt;In this study, 187 undergraduate dental students recruited from a first-class university in China were randomly divided into a ChatGPT group and a blank control group. Among them, the control group used videos for skill acquisition, and the ChatGPT group used ChatGPT in addition to the videos. After 1 week of intervention, skills were tested using desktop virtual reality, and cognitive load was measured by recording changes in pupil diameter with an eye tracker. In addition, a spatial ability test was administered to analyze the effect of ChatGPT on those with different spatial abilities. Finally, a questionnaire was also used to assess cognitive load and self-efficacy during the learning process.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Results: &lt;/strong&gt;A total of 192 dental undergraduates from a top-tier Chinese university were initially recruited for the experiment by October 25, 2024. Following eye-tracking calibration procedures, 5 participants were excluded, resulting in 187 eligible students successfully completing the experimental protocol by November 2, 2024. Following a short-term intervention administered through randomized allocation, superior performance (ChatGPT group: mean 73.12, SD 10.06; control group: mean 65.54, SD 12.48; P&lt;.001) was observed among participants in the ChatGPT group, along with higher levels of self-efficacy (P=.04) and learning motivation (P=.02). In addition, cognitive load was lower in the ChatGPT group according to eye-tracking measures (ChatGPT group: mean 0.137, SD 0.036; control group: mean 0.312, SD 0.032; P&lt;.001). The analysis of the learning performance of participants with different spatial abilities in the 2 modalities showed that compared to the learners with high spatial abilities (ChatGPT group: mean 76.58, SD 9.23; control group: mean 73.89, SD 11.75; P=.22), those with low spatial abilities (ChatGPT group: mean 70.20, SD 10.71; control group: mean 55.41, SD 13.31; P&lt;.001) were more positively influenced by ChatGPT.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Conclusions: &lt;/strong&gt;ChatGPT has performed outstandingly in assisting dental skill learning, and the study supports the integration of ChatGPT into skills teaching and provides new ideas for modernizing skill teaching.&lt;/p&gt;&lt;","PeriodicalId":16337,"journal":{"name":"Journal of Medical Internet Research","volume":"27 ","pages":"e68538"},"PeriodicalIF":5.8,"publicationDate":"2025-05-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144150711","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}

{"title":"Evaluation of Diagnostic Recommendations Embedded in Medication Alerts: Prospective Single-Arm Interventional Study.","authors":"Yu-Chen Liu, Guan-Ling Lin, Jeremiah Scholl, Yi-Chun Hung, Yu-Jing Lin, Yu-Chuan Li, Hsuan-Chia Yang","doi":"10.2196/70731","DOIUrl":"10.2196/70731","url":null,"abstract":"<p><strong>Background: </strong>Potentially inappropriate prescribing in outpatient care contributes to adverse outcomes and health care inefficiencies. Clinical decision support systems (CDSS) offer promising solutions, but their effectiveness is often constrained by incomplete medical records.</p><p><strong>Objective: </strong>This study aims to evaluate the effectiveness of a machine learning-based CDSS for enhancing diagnostic recommendations, which are system-suggested diagnoses, ensuring that each prescribed medication has a corresponding diagnosis documented and meets medication appropriateness.</p><p><strong>Methods: </strong>This prospective single-arm interventional study was conducted over 1 year in the outpatient departments of a hospital. The system provided diagnostic recommendations based on machine learning algorithms trained on data from the National Health Insurance Research Database. Outcome measures included alert rates, acceptance rates of diagnostic recommendations, and variability in system performance across specialties. Descriptive and trend analyses were used to evaluate the system's effectiveness.</p><p><strong>Results: </strong>This study included 438,558 prescriptions from 44 physicians across 23 specialties, involving 125,000 unique patients in the outpatient departments of a regional teaching hospital. MedGuard, embedded with diagnostic recommendations, achieved an overall alert rate of 2.28% and a diagnostic recommendation acceptance rate of 56.55%. All accepted recommendations resulted in actionable changes, including prescription adjustments or the addition of missing diagnoses. Ophthalmology achieved the highest acceptance rate at 96.59%, while rheumatology, surgery, psychiatry, and infectious disease recorded acceptance rates of 0%, 0%, 24.74%, and 35%, respectively. Over the years, acceptance rates for potentially inappropriate prescriptions stabilized at 51%, despite increasing prescription volumes.</p><p><strong>Conclusions: </strong>This study demonstrates the potential of embedding diagnostic recommendations into alerts within a machine learning-based clinical decision support system to improve diagnostic completeness and support safer outpatient care. Future efforts should refine alerts to align with specialty-specific workflows and validate their effectiveness in diverse clinical settings.</p>","PeriodicalId":16337,"journal":{"name":"Journal of Medical Internet Research","volume":"27 ","pages":"e70731"},"PeriodicalIF":5.8,"publicationDate":"2025-05-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144150708","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}

{"title":"Ingroup Favoritism Surrounding COVID-19 Vaccinations in the Hispanic Communities: Experimental Study.","authors":"Juwon Hwang, Asya Cooley, Skye Cooley, Robert Hinck","doi":"10.2196/71188","DOIUrl":"10.2196/71188","url":null,"abstract":"&lt;p&gt;&lt;strong&gt;Background: &lt;/strong&gt;Hispanic communities have been disproportionately affected by the COVID-19 pandemic. In addition to elevated health risks and burdens, these populations have faced persistent barriers to accessing accurate, timely information regarding the pandemic's trajectory, including vaccine-related updates. To address these challenges, it is crucial to examine the conditions under which Hispanics are most likely to seek information about COVID-19 vaccinations.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Objective: &lt;/strong&gt;Grounded in social identity theory and self-categorization theory, the primary goal of this study is to investigate how ethnic and linguistic cues influence information-seeking preferences related to COVID-19 vaccinations among Hispanic individuals. The first aim is to compare Hispanic and non-Hispanic participants in terms of their preferences for COVID-19 vaccine-related social media pages, in which the ethnicity of individuals shown in the images (Hispanic vs non-Hispanic) and the language in the text (Spanish vs English) vary. The second aim is to identify which combination of ethnic imagery and language in the text is most preferred among Hispanic participants when seeking COVID-19 vaccination information.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Methods: &lt;/strong&gt;A total of 936 participants (Hispanic: n=448; non-Hispanic: n=488) were included in the study. We created experimental social media group pages modeled after Facebook groups, in which the ethnicity of individuals shown in the imagery and the language used in the text were manipulated. A total of 4 conditions were developed: (1) Hispanic imagery with Spanish text, (2) non-Hispanic imagery with Spanish text, (3) Hispanic imagery with English text, and (4) non-Hispanic imagery with English text. Participants were asked to indicate the extent to which they would be willing to seek help from each social media group page, under the assumption that they were looking for information or assistance related to the COVID-19 vaccine, regardless of their actual vaccination status. A between-subjects ANOVA and a one-way repeated-measures ANOVA were conducted to analyze the data.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Results: &lt;/strong&gt;The findings indicated that Hispanic participants significantly preferred social media pages featuring Hispanic imagery and Spanish text compared to non-Hispanic participants. Moreover, a page with non-Hispanic imagery and English text was less preferred by Hispanic than by non-Hispanic individuals. Among Hispanic participants, the condition featuring Hispanic imagery and Spanish text emerged as the most favored, particularly when compared to conditions featuring non-Hispanic imagery paired with either Spanish or English text. Notably, there was no significant difference between the preference for the condition with Hispanic imagery and Spanish text and the condition with Hispanic imagery and English text, suggesting that imagery may have a stronger influence than language in shaping preferences.&lt;/p&gt;&lt;p&gt;&lt;str","PeriodicalId":16337,"journal":{"name":"Journal of Medical Internet Research","volume":"27 ","pages":"e71188"},"PeriodicalIF":5.8,"publicationDate":"2025-05-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144150715","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}

{"title":"Google Trends for the Human Papillomavirus Vaccine in India From 2010 to 2024: Infodemiological Study.","authors":"Rashmi Mehra, Arindam Ray, Amrita Kumari, Amanjot Kaur, Rhythm Hora, Syed F Quadri, Seema Singh Koshal, Bodhisatwa Ray, Shyam Kumar Singh, Abida Sultana, Arup Deb Roy","doi":"10.2196/69729","DOIUrl":"https://doi.org/10.2196/69729","url":null,"abstract":"<p><strong>Background: </strong>Human papillomavirus (HPV) is a leading cause of cervical cancer. It has a substantial impact on global public health, with low- and middle-income countries, including India, facing the highest burden. In 2022, India reported 127,526 new cases and 79,906 deaths due to cervical cancer, projected to increase by 61% by 2040. Although the National Technical Advisory Group on Immunization recommended the HPV vaccine for cervical cancer prevention, it is yet to be a part of India's universal immunization program.</p><p><strong>Objective: </strong>This study aims to examine online interest in the HPV vaccine in India from January 2010 to April 2024 using Google Trends.</p><p><strong>Methods: </strong>A cross-sectional analysis of Google Trends data was performed, using the relative search volume to track interest on a scale of 0-100. Trends were analyzed annually using 1-way ANOVA and joinpoint regression to identify significant changes in search behavior related to public health events. Statistical significance was set at P<.05.</p><p><strong>Results: </strong>The average annual growth in HPV vaccine-related searches was 13.7% (95% CI 7.9%-19.1%), with the highest relative search volume in 2024 (49.5) and the lowest in 2017 (3.38). Spikes in search interest aligned with key events like the 2018 National Technical Advisory Group on Immunization recommendation and the 2022 launch of the indigenous HPV vaccine. The results highlight online search data's value in tracking public interest, which fluctuates in response to health policy changes or developments on social media. In India, targeted digital strategies will be vital for addressing vaccine hesitancy and increasing HPV vaccine uptake.</p><p><strong>Conclusions: </strong>Google Trends data can inform public health strategies by identifying periods of high interest, aiding in the promotion of HPV vaccination in India.</p>","PeriodicalId":16337,"journal":{"name":"Journal of Medical Internet Research","volume":"27 ","pages":"e69729"},"PeriodicalIF":5.8,"publicationDate":"2025-05-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144159549","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}

{"title":"Attitudes Toward AI Usage in Patient Health Care: Evidence From a Population Survey Vignette Experiment.","authors":"Simon Kühne, Jannes Jacobsen, Nicolas Legewie, Jörg Dollmann","doi":"10.2196/70179","DOIUrl":"https://doi.org/10.2196/70179","url":null,"abstract":"&lt;p&gt;&lt;strong&gt;Background: &lt;/strong&gt;The integration of artificial intelligence (AI) holds substantial potential to alter diagnostics and treatment in health care settings. However, public attitudes toward AI, including trust and risk perception, are key to its ethical and effective adoption. Despite growing interest, empirical research on the factors shaping public support for AI in health care (particularly in large-scale, representative contexts) remains limited.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Objective: &lt;/strong&gt;This study aimed to investigate public attitudes toward AI in patient health care, focusing on how AI attributes (autonomy, costs, reliability, and transparency) shape perceptions of support, risk, and personalized care. In addition, it examines the moderating role of sociodemographic characteristics (gender, age, educational level, migration background, and subjective health status) in these evaluations. Our study offers novel insights into the relative importance of AI system characteristics for public attitudes and acceptance.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Methods: &lt;/strong&gt;We conducted a factorial vignette experiment with a probability-based survey of 3030 participants from Germany's general population. Respondents were presented with hypothetical scenarios involving AI applications in diagnosis and treatment in a hospital setting. Linear regression models assessed the relative influence of AI attributes on the dependent variables (support, risk perception, and personalized care), with additional subgroup analyses to explore heterogeneity by sociodemographic characteristics.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Results: &lt;/strong&gt;Mean values between 4.2 and 4.4 on a 1-7 scale indicate a generally neutral to slightly negative stance toward AI integration in terms of general support, risk perception, and personalized care expectations, with responses spanning the full scale from strong support to strong opposition. Among the 4 dimensions, reliability emerges as the most influential factor (percentage of explained variance [EV] of up to 10.5%). Respondents expect AI to not only prevent errors but also exceed current reliability standards while strongly disapproving of nontraceable systems (transparency is another important factor, percentage of EV of up to 4%). Costs and autonomy play a comparatively minor role (percentage of EVs of up to 1.5% and 1.3%), with preferences favoring collaborative AI systems over autonomous ones, and higher costs generally leading to rejection. Heterogeneity analysis reveals limited sociodemographic differences, with education and migration background influencing attitudes toward transparency and autonomy, and gender differences primarily affecting cost-related perceptions. Overall, attitudes do not substantially differ between AI applications in diagnosis versus treatment.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Conclusions: &lt;/strong&gt;Our study fills a critical research gap by identifying the key factors that shape public trust and acceptance of AI in health care, particularly reliability, ","PeriodicalId":16337,"journal":{"name":"Journal of Medical Internet Research","volume":"27 ","pages":"e70179"},"PeriodicalIF":5.8,"publicationDate":"2025-05-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144159541","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}