DIGITAL HEALTH最新文献

{"title":"Artificial intelligence-assisted phenotyping of sepsis: Research progress, clinical challenges, and translational prospects.","authors":"Hang Ruan, Jing-Kun Lee, Jie Xiong, Li-Juan Zou, Shu-Sheng Li","doi":"10.1177/20552076261481028","DOIUrl":"10.1177/20552076261481028","url":null,"abstract":"<p><p>Sepsis remains a leading cause of mortality in intensive care units worldwide, a challenge exacerbated by pathophysiological and clinical heterogeneity that limits the effectiveness of uniform management strategies, motivating the development of phenotype-guided approaches to diagnosis and treatment. Artificial intelligence (AI)-assisted phenotyping can stratify patients with sepsis into distinct subpopulations with differential immune profiles and heterogeneous treatment responses. This narrative review synthesizes recent advances in AI-assisted sepsis phenotyping, focusing on three persistent research bottlenecks: terminological inconsistency, fragmented integration between prognostic stratification and treatment-response phenotyping, and ambiguous clinical translation pathways. A standardized nomenclature is proposed to improve cross-study comparability, accompanied by a delineation of mainstream AI methodological frameworks, critical care datasets, and multilevel validation systems tailored for intensive care unit scenarios. Eight complementary research dimensions are mapped, including transcriptomic endotyping, single-cell profiling, electronic health record-derived clinical phenotyping, dynamic trajectory modeling, organ dysfunction stratification, biomarker panels, multi-omic integration, and treatment-response phenotyping, with treatment-response phenotyping highlighted as the highest-priority translational frontier. Critical analysis of predominant translational barriers, such as limited model generalizability, insufficient interpretability, poor workflow compatibility, and regulatory uncertainty, is presented alongside stage-specific actionable roadmaps designed to promote real-world clinical deployment. By constructing a unified interdisciplinary framework, this review defines key future research priorities to accelerate the evidence-based transition from algorithmic prototypes to bedside precision sepsis management.</p>","PeriodicalId":51333,"journal":{"name":"DIGITAL HEALTH","volume":"12 ","pages":"20552076261481028"},"PeriodicalIF":3.9,"publicationDate":"2026-08-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13498814/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148801415","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Attitudes towards personalised nutrition recommendations in health apps: Results of a cross-sectional online survey.","authors":"Sabrina Antor, Anna Strüven, Kathrin Gemesi, Georges Weis, Katja Lotz, Hans Hauner, Stefan Brunner, Christina Holzapfel","doi":"10.1177/20552076261456525","DOIUrl":"10.1177/20552076261456525","url":null,"abstract":"<p><strong>Objective: </strong>Dietary advice is increasingly shifting towards personalisation enabled by digital technologies. As personalised nutrition recommendation applications rely on user data, little is known about how users differ in attitudes towards data sharing, desired app features, and expected benefits.</p><p><strong>Methods: </strong>In a cross-sectional survey conducted in Germany, adults aged ≥18 years completed a standardised online-questionnaire assessing participant characteristics and attitudes towards personalised nutrition in health applications. Behavioural intention (BI) was measured using the Technology Acceptance Model 3 questionnaire. Four items yielded count-based outcomes (number of selected options). Descriptive statistics, generalised additive models, and exploratory cluster analysis based on age, body mass index (BMI), and BI were conducted using RStudio.</p><p><strong>Results: </strong>In total, 1,070 participants completed this cross-sectional survey (42.4 ± 15.3 years; BMI 25.6 ± 6.0 kg/m²; 75% female). An exploratory cluster analysis (age, BMI, BI) identified three user groups. Clusters differed in expected benefits, willingness to share parameters, core aspects of personalised advice, and perceived importance of app features (all P ≤ 0.01), with small to moderate effect sizes (η² = 0.006 - 0.10).</p><p><strong>Conclusion: </strong>Age, BMI, and BI modify users' attitudes towards personalised dietary advice in health apps, while their overall explanatory power was limited. Responses varied within similar clusters, suggesting apps should be flexible and modular to accommodate individual preferences.</p>","PeriodicalId":51333,"journal":{"name":"DIGITAL HEALTH","volume":"12 ","pages":"20552076261456525"},"PeriodicalIF":3.9,"publicationDate":"2026-08-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13494340/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148801420","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Validation of federated analytics across secure data environments: A comparative study of synthetic healthcare datasets using machine learning and general linear models.","authors":"Suzy Gallier, Alexander Topham, James Hodson, David McNulty, Tom Charles Giles, Sam Cox, Mahalakshmi J Chaganty, Lauren Cooper, Stephen Perks, Philip R Quinlan, Elizabeth Sapey","doi":"10.1177/20552076261467828","DOIUrl":"10.1177/20552076261467828","url":null,"abstract":"<p><strong>Objectives: </strong>To enable research and innovation, most health data systems are moving away from a model of pooled data egress and instead highlight the benefits of federated analytics to support data analysis across different settings. This study aimed to assess whether the results of analyses using general linear models (GLMs) and machine learning (ML) models were altered depending on whether a federated or pooled data (\"non-federated\") approach was taken.</p><p><strong>Methods: </strong>A Conditional Transformation Generative Adversarial Network created two synthetic datasets (training set: N=10,000; test set: N=1,000), using data from 381 asthma patients. Synthetic data was either distributed across Trusted Research Environments (TREs) or pooled. GLMs (one-way analysis of variance) and ML models (gradient boosted decision trees) were produced, using federated and non-federated approaches. The consistency of predictions produced by the ML models and GLM results were compared.</p><p><strong>Results: </strong>Federated GLMs were identical to those produced using a non-federated approach. However, ML models produced by federated and non-federated approaches, and using different data distributions between TREs, were non-identical. Despite this, applying the ML models to the test set returned similar predictive accuracies (area under the receiver operating characteristic curve: 0.663-0.669) and classification accuracies (84.7-90.4%) for federated and non-federated models.</p><p><strong>Conclusions: </strong>GLMs return identical models for federated and pooled data approaches. Whilst federation of ML analysis results in non-identical models, these have comparable accuracy to traditional non-federated models. These results highlight the viability of federated approaches for reliable and accurate data analysis in sensitive domains.</p>","PeriodicalId":51333,"journal":{"name":"DIGITAL HEALTH","volume":"12 ","pages":"20552076261467828"},"PeriodicalIF":3.9,"publicationDate":"2026-08-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13494341/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148801130","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Efficiency and accessibility of physiotherapist-led real-time telerehabilitation in chronic low back pain: An interview study.","authors":"Jenny Sivertsson, Ninni Sernert, Helena Brisby, Hanna Hebelka, Kerstin Lagerstrand, Kristina Åhlund","doi":"10.1177/20552076261475794","DOIUrl":"10.1177/20552076261475794","url":null,"abstract":"<p><strong>Objective: </strong>Individually tailored exercise is the first-line treatment for chronic low back pain. Today, physiotherapists offer various forms of telerehabilitation, such as real-time exercise programmes via videoconferencing. However, these approaches have been sparsely studied. Knowledge of participants' experiences is limited, and a deeper understanding is essential for planning and implementing telerehabilitation. The aim of this study is to explore the experiences of individuals with chronic low back pain participating in exercise-based real-time group telerehabilitation.</p><p><strong>Methods: </strong>This study is part of an ongoing randomized controlled trial (<i>n</i> = 90) evaluating real-time group telerehabilitation compared to advice on physical activity. The intervention was delivered via Microsoft Teams™ twice weekly for three months. After the telerehabilitation intervention, a strategic sampling approach was applied, and 19 participants took part in semi-structured interviews. The interviews were audio-recorded, transcribed verbatim, and analysed using qualitative content analysis.</p><p><strong>Results: </strong>The analysis resulted in four categories and 11 sub-categories. The categories were: conditions influencing the telerehabilitation experience, a tailored telerehabilitation programme, the dual nature of remote interaction, and enhanced physical function and well-being. These categories led to an overarching theme: real-time telerehabilitation was efficient and accessible.</p><p><strong>Conclusion: </strong>This interview study shows that physiotherapist-led real-time group telerehabilitation is perceived as efficient and accessible, though not without challenges. These findings enhance our understanding of telerehabilitation and suggest that telerehabilitation may complement conventional rehabilitation, offering comparable efficiency while improving accessibility.</p>","PeriodicalId":51333,"journal":{"name":"DIGITAL HEALTH","volume":"12 ","pages":"20552076261475794"},"PeriodicalIF":3.9,"publicationDate":"2026-08-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13494333/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148801381","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Health halo effect in supplement marketing: A content analysis of unregulated medical claims in community pharmacies.","authors":"Marwan Alrasheed, Saad Alobid, Mohammed Almasoud, Basmah Alfageh, Rawan Almadfaa, Reema Almoqran, Abdulaziz Alkhonizan, Aliyah Almobarak, Faisal Nasser, Musab Gari, Abdulrahman Alsuhibani","doi":"10.1177/20552076261477561","DOIUrl":"10.1177/20552076261477561","url":null,"abstract":"<p><strong>Background: </strong>Dietary supplements are widely promoted online, often using persuasive health claims that may contribute to the \"health halo effect,\" where consumers may infer unproven therapeutic benefits. In Saudi Arabia, the rise of online listings by nutraceutical and dietary supplement companies has amplified the visibility of such claims, raising questions about their regulatory compliance.</p><p><strong>Objective: </strong>To examine the nature and regulatory risk of health-related claims in dietary supplements marketed by nutraceutical and dietary supplement companies through Saudi pharmacy websites and assess their alignment with SFDA guidelines.</p><p><strong>Methods: </strong>A cross-sectional content analysis was conducted on 209 supplement products which yielded 251 distinct health-related claims extracted from leading Saudi pharmacy websites. Claims were thematically categorized and assessed using a rule-based natural language processing (NLP) classifier aligned with Saudi Food and Drug Authority (SFDA) regulatory tiers. Each claim was assigned a risk level of low, medium, or high, based on language and references to medical conditions. A verb frequency analysis was conducted to explore linguistic patterns. Chi-square testing was used to examine the association between claim categories and regulatory risk.</p><p><strong>Results: </strong>Of the 251 claims analyzed, 173 (68.9%) were classified as low risk, 7 (2.8%) as medium risk, and 71 (28.3%) as high risk. The most common claim categories were bone/joint health (14%), immune support (10%), general wellness/wellbeing (10%), hair/skin/nails (7%), energy/fatigue (7%), antioxidant/detox (6%), and cardiovascular health (6%). High-risk claims were most concentrated in categories related to bone/joint health, general wellness, and cardiovascular support. The most frequent action verbs were \"support,\" \"improve,\" and \"treat.\" A significant association was observed between claim category and regulatory risk level (p < 0.001).</p><p><strong>Conclusion: </strong>A substantial proportion of supplement claims implies therapeutic benefit. Strengthening regulatory oversight and consumer education is essential to mitigate the health halo effect and ensure safe supplement use.</p>","PeriodicalId":51333,"journal":{"name":"DIGITAL HEALTH","volume":"12 ","pages":"20552076261477561"},"PeriodicalIF":3.9,"publicationDate":"2026-08-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13494279/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148801465","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Frail older adults' challenges in using telehealth services: A scoping review.","authors":"Kristina Åhlund, Ann Svensson, Lilisbeth Perestelo-Perez, Ángel Acebes, Johannes Hobbelen, Margareta Karlsson","doi":"10.1177/20552076261479799","DOIUrl":"10.1177/20552076261479799","url":null,"abstract":"<p><strong>Objective: </strong>Telehealth is increasingly used to expand access to healthcare, but rapid digitalization risks exacerbating exclusion among frail older adults, who often face intersecting limitations related to health, resources, and digital competence. As this group frequently has complex care needs, mapping their experiences is essential to ensure equitable access to digital care. The aim was to map the challenges frail older adults experience when using telehealth services.</p><p><strong>Methods: </strong>This scoping review followed Arksey and O'Malley's framework and PRISMA-ScR guidelines. PubMed, CINAHL, Scopus, and Web of Science were searched for peer-reviewed empirical studies published in English (January 2015-June 2026). Studies were included if they addressed relevant challenges from the perspectives of frail older adults or those with multimorbidity, disability, cognitive impairment, or dependency. Data were charted and analyzed narratively.</p><p><strong>Results: </strong>Of 7200 studies identified, 22 were included. All of them used qualitative methods and were conducted in Europe, North America, and Asia; only four applied formal frailty assessments. Five domains were identified: 1) digital accessibility, 2) digital skills, 3) health status, 4) digital support, and 5) financial resources.</p><p><strong>Conclusions: </strong>As frail older adults face multiple, interconnected challenges to telehealth use, including technological and environmental constraints, limited digital competence, health-related impairments, insufficient support, and financial challenges, services should be designed to align with their needs and life circumstances. Accessible design, structured support, affordable connectivity, and active involvement of frail older adults are essential to ensure equitable and inclusive digital healthcare.</p>","PeriodicalId":51333,"journal":{"name":"DIGITAL HEALTH","volume":"12 ","pages":"20552076261479799"},"PeriodicalIF":3.9,"publicationDate":"2026-08-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13494289/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148801434","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Mobilizing participation: The first German stakeholder conference on engaging patients and self-help organizations in digital health research.","authors":"Paula Nadler, Manuel Schaper, Thomas M Duda, Hartmut Gartzke, Wiebke Papenthin, Verena Winter, Silke Schicktanz, Sabine Wöhlke","doi":"10.1177/20552076261467869","DOIUrl":"https://doi.org/10.1177/20552076261467869","url":null,"abstract":"<p><strong>Background: </strong>Digital transformation in the healthcare sector within the European Union (EU) raises various ethical concerns regarding the use of health research data and regarding how to address such concerns through ethical governance.</p><p><strong>Methods: </strong>This article presents the results of the first German national stakeholder conference - a structured discourse process for developing political or ethical positions through citizen participation - which included patient organizations (POs) and self-help organizations (SHOs) (N=45). Participants were asked to describe their positions regarding participation and engagement in digital health research and health research data-sharing policies in an interactive process, facilitated by researchers from health care ethics.</p><p><strong>Results: </strong>POs/SHOs emphasize the ethical relevance of patient autonomy and transparency as preconditions for trust. Therefore, data protection and transparent consent procedures are seen as a necessary part of responsible research. While recognizing the potential of large-scale data use to increase research efficiency, they stress the importance of promoting patient-centeredness through participatory approaches. Structured participation requires clear definition of tasks, empowerment of POs/SHOs, understanding of the special features of voluntary structures, and target group-oriented, barrier-free communication of research results. Their support depends on upholding strong legal safeguards and respecting individual rights. Additional demands include improved digital literacy, health literacy, and financial resources.</p><p><strong>Conclusions: </strong>Future research should focus on dynamic consent models and fair participation structures. From the start, it should be clarified to POs/SHOs whether intended research projects are oriented toward the public good or primarily commercial. This can be an important factor in their decision to participate in research.</p>","PeriodicalId":51333,"journal":{"name":"DIGITAL HEALTH","volume":"12 ","pages":"20552076261467869"},"PeriodicalIF":3.9,"publicationDate":"2026-08-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13490783/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148801482","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Evaluation and comparison of large language model responses to common discharge questions from patients with acute coronary syndrome after percutaneous coronary intervention: An expert-rated comparative study.","authors":"Dachang Qiu, Qingjiang Wang, Wenlong Yan, Sumin Yang","doi":"10.1177/20552076261481380","DOIUrl":"https://doi.org/10.1177/20552076261481380","url":null,"abstract":"<p><strong>Background: </strong>After percutaneous coronary intervention (PCI), patients with acute coronary syndrome (ACS) require long-term medication, risk-factor control, rehabilitation, and symptom recognition. Large language models (LLMs) are increasingly used for health consultation, but their quality, safety, and stability in post-PCI discharge education remain unclear.</p><p><strong>Methods: </strong>Twenty-five standardized Chinese discharge questions were submitted to ChatGPT 5.5 Instant and DeepSeek V3. Each model generated three responses per question (150 total). Three cardiovascular experts rated the original Chinese responses across five Likert domains and two binary safety judgments. Comparisons used exact paired permutation tests, question-clustered bootstrap confidence intervals, and Holm adjustment for six quality-score comparisons.</p><p><strong>Results: </strong>Overall, 149/150 responses (99.3%; 95% CI, 96.3%-100.0%) met the primary safety criterion: 75/75 for ChatGPT (100.0%; 95% CI, 95.2%-100.0%) and 74/75 for DeepSeek (98.7%; 95% CI, 92.8%-100.0%). The paired risk difference was 1.3 percentage points (95% CI, -1.3 to 2.7; P=1.000). One DeepSeek response contained both a major error and a potentially harmful recommendation. After pairing and Holm adjustment, ChatGPT scored higher in accuracy, guideline concordance, completeness, and total quality (adjusted P=0.015, 0.015, 0.019, and 0.005). Five-domain satisfactory response rates did not differ significantly (100.0% vs 90.7%; P=0.125).</p><p><strong>Conclusions: </strong>Both models produced few expert-adjudicated safety flags in this limited question set. ChatGPT received higher ratings in selected quality domains, but sparse safety events and restricted question coverage preclude conclusions of equivalence or clinical safety. LLM-generated discharge information should supplement, not replace, individualized clinical advice.</p>","PeriodicalId":51333,"journal":{"name":"DIGITAL HEALTH","volume":"12 ","pages":"20552076261481380"},"PeriodicalIF":3.9,"publicationDate":"2026-08-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13490778/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148801419","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Use of mHealth interventions to enhance self-regulation and self-efficacy in individuals living with obesity: Scoping review.","authors":"Marcela Ely, Asghar Ahmadi, Syed M Shariq, Andrea Duchonova, Roman Filo, Barbora Kastovska, Ondrej Zach, Holly B Jimison, Steriani Elavsky","doi":"10.1177/20552076261474266","DOIUrl":"https://doi.org/10.1177/20552076261474266","url":null,"abstract":"<p><strong>Objectives: </strong>Mobile health (mHealth) technologies are increasingly employed to facilitate lifestyle modification and weight management among individuals with obesity. However, their effectiveness depends on the integration of theory-driven design. Within Social Cognitive Theory, self-regulation and self-efficacy are considered key mechanisms for initiating and sustaining health behavior change. This scoping review aimed to map and categorize mHealth intervention components related to self-regulation and self-efficacy, explore their digital operationalization and personalization strategies, and identify the theoretical frameworks guiding their design.</p><p><strong>Methods: </strong>A systematic literature search was conducted across six databases to identify studies that examined mHealth interventions targeting adults living with obesity and addressing behavioral modification in obesity management. The review applied Joanna Briggs Institute (JBI) methodology for scoping reviews and is reported following the PRISMA-ScR guidelines.</p><p><strong>Results: </strong>Forty-four studies met the inclusion criteria. Theoretical grounding was present in a total of twenty-five interventions (25/44; 56.8%), with Social Cognitive Theory being the most prevalent framework (15/25; 60%). Findings indicate widespread integration of self-regulation and self-efficacy components within mHealth interventions, operationalized through in-app logs, wearable devices, prompts and reminders, gamification, and social support etc. While mHealth technologies have increasingly integrated advanced sensors and AI-enabled features, the aspect of personalization has remained predominantly static rather than adaptive. The mHealth interventions aimed at managing obesity commonly incorporate components related to self-regulation and self-efficacy, yet theoretical integration, dynamic personalization, and consistent reporting remain limited.</p><p><strong>Conclusion: </strong>This scoping review highlights the need for clearer documentation of behavioral mechanisms and proposes reporting recommendations to improve transparency and replicability.</p>","PeriodicalId":51333,"journal":{"name":"DIGITAL HEALTH","volume":"12 ","pages":"20552076261474266"},"PeriodicalIF":3.9,"publicationDate":"2026-08-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13490795/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148800655","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Do engagement metrics reflect educational value in short-form diabetes videos?","authors":"Varshitha Hantur Dinakar, Neeraj Singh, Monika Srivastav","doi":"10.1177/20552076261481592","DOIUrl":"https://doi.org/10.1177/20552076261481592","url":null,"abstract":"","PeriodicalId":51333,"journal":{"name":"DIGITAL HEALTH","volume":"12 ","pages":"20552076261481592"},"PeriodicalIF":3.9,"publicationDate":"2026-08-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13490780/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148801421","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}