Frontiers in digital health最新文献

{"title":"Editorial: Generative AI and large language models in medicine: applications, challenges, and opportunities.","authors":"Fahim Sufi, Seedahmed S Mahmoud","doi":"10.3389/fdgth.2026.1986903","DOIUrl":"https://doi.org/10.3389/fdgth.2026.1986903","url":null,"abstract":"","PeriodicalId":73078,"journal":{"name":"Frontiers in digital health","volume":"8 ","pages":"1986903"},"PeriodicalIF":5.2,"publicationDate":"2026-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13627441/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149119421","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Undocumented migrants' and asylum seekers' healthcare rights and (medical) data protection: exploring digital health opportunities and risks through the use-case of an electronic personal health record for undocumented migrants and asylum seekers in the Netherlands.","authors":"P Tensen, J M Meulesteen, G Trogrlić, S A van der Wees, E Beune, S J M van de Vijver, C Agyemang","doi":"10.3389/fdgth.2026.1876248","DOIUrl":"https://doi.org/10.3389/fdgth.2026.1876248","url":null,"abstract":"<p><strong>Introduction: </strong>Despite the opportunities of electronic personal health records (EPHRs) to improve the continuity of care for undocumented migrants' (UDMs) and asylum seekers', implementing digital health technologies for these groups also result in legal concerns related to medical data protection. This exploratory study maps legal frameworks governing UDMs' and asylum seekers' access to healthcare, medical records and personal (medical) data protection in the Netherlands and examines barriers in practice according to (legal) experts. Using an EPHR as a concrete case, it further explores the opportunities, barriers, risks, and recommendations of the implementation of a digital health tool for these groups.</p><p><strong>Methods: </strong>A qualitative socio-legal study combining doctrinal legal analysis and expert interviews was applied. Thirteen (legal) experts were purposively selected and interviewed using a semi-structured guide. Afterwards, three legal experts reflected upon the results.</p><p><strong>Results: </strong>Despite the legal provisions guaranteeing UDMs' and asylum seekers' rights in healthcare, rights seemed inconsistently upheld in practice. Participants reported that many remain unaware of their rights, and their vulnerable circumstances could further impede the effective exercise of these rights. Participants recognised the potential of EPHRs to improve care access and efficiency, however, risks were also mentioned about (medical) data protection, particularly due to access by government agencies or other third parties, and recommended a highly secure, privacy-by-design EPHR, transparent communication, targeted education, and end-user involvement in the design.</p><p><strong>Discussion: </strong>This study highlights a central dilemma in digital health: whether and how an EPHR can enhance continuity of care for UDMs and asylum seekers without increasing risks of exclusion, forced disclosure, data misuse, or surveillance. Guaranteed software safety, transparent communication, education of users and professionals, and an inclusive design are proposed as conditions for responsible EPHR implementation, alongside stronger enforcement and awareness of existing rights.</p>","PeriodicalId":73078,"journal":{"name":"Frontiers in digital health","volume":"8 ","pages":"1876248"},"PeriodicalIF":5.2,"publicationDate":"2026-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13627290/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149119484","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Healthcare consumers' perceptions and experiences of an Australian prescription drug monitoring program: a cross-sectional survey.","authors":"Emma Tay, Meredith Makeham, Tracey-Lea Laba, Melissa Baysari","doi":"10.3389/fdgth.2026.1745292","DOIUrl":"https://doi.org/10.3389/fdgth.2026.1745292","url":null,"abstract":"<p><strong>Background: </strong>Prescription drug monitoring programs (PDMPs) are increasingly being recognised as a medication safety initiative to minimise harms from high-risk prescription medications. This study explored healthcare consumers' experiences and perceptions of a state-wide PDMP in NSW, Australia, \"SafeScript NSW\". We examined, 1) awareness and understanding of SafeScript NSW, and 2) perceptions of impacts of SafeScript NSW.</p><p><strong>Methods: </strong>Cross-sectional online survey was used; invitations were distributed via mailing lists and physical mailouts. Data collection occurred between May-August 2023, one year post roll-out of SafeScript NSW. All NSW-based consumers were eligible to participate. Rating scale and free-text response items were included. Descriptive statistics were used for analysis of quantitative data and a general inductive analysis approach used to code and identify themes from qualitative data.</p><p><strong>Results: </strong>77 consumers responses received. Two-thirds identified as female (51/77; 66.2%). Respondents were from all regions (metropolitan, regional, and rural) of NSW. Opioids and benzodiazepines were the top two PDMP-monitored medicines taken regularly. Most respondents (50/74; 67.6%) had not heard of SafeScript NSW prior to the survey and did not perceive it to be useful for identifying medicines-related harms (51/73; 69.9%). Close to half of the respondents noted no impacts of the system on their healthcare, including time spent at visits (10/22; 45.5%), or quality of care received (10/22; 45.5%). Over 50 free-text comments were received describing perceived impacts of SafeScript NSW which provided a more nuanced understanding of consumer experiences. The majority (59.6%) of these comments described negative experiences, including some reporting inability to access treatment and experiencing stigma.</p><p><strong>Conclusions: </strong>This study explored healthcare consumers' experiences and perceptions of SafeScript NSW. Consumers had poor overall awareness and knowledge of SafeScript NSW and its impacts. Although primarily a practitioner-facing tool, our findings suggest additional dissemination of information and engagement of relevant consumers would foster consumer trust and confidence in their healthcare experiences and PDMP systems. Policies governing PDMP should account for the diverse needs of patients and practitioners. Realisation of PDMP's desired benefits should invite confidence and trust in care, and aim to avoid unintended harms to patients who may inadvertently be prevented from medically appropriate care.</p>","PeriodicalId":73078,"journal":{"name":"Frontiers in digital health","volume":"8 ","pages":"1745292"},"PeriodicalIF":5.2,"publicationDate":"2026-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13627383/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149119445","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Effectiveness of chatbot interventions in individuals for hypertension management: a systematic review and narrative synthesis.","authors":"Shahwar Fatima Ansari, Noor A Abu Saifan, Reem Khalifa Alneyadi, Aleena Hassan, Yanli Liu, Soundarya Ashok, Javaid Nauman, Luai A Ahmed, Reem Al Sheryani, Azhar T Rahma","doi":"10.3389/fdgth.2026.1911937","DOIUrl":"https://doi.org/10.3389/fdgth.2026.1911937","url":null,"abstract":"<p><strong>Introduction: </strong>Hypertension is a major global risk factor for cardiovascular disease and requires long-term management. Recently, digital health tools such as chatbots have been introduced to support patient self-management. This systematic review aims to assess the effectiveness of chatbot interventions designed for individual hypertension management evaluating their impact on clinical outcomes, primarily changes in systolic and diastolic blood pressure and to explore the improvement in knowledge and self-management skills, as well as implementation outcomes such as feasibility, acceptability, and adoption in routine healthcare settings.</p><p><strong>Materials and methods: </strong>This study followed the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) guidelines. The research question was structured by the PICOT framework, focusing on patients with hypertension or elevated Blood Pressure (BP) receiving chatbot-based interventions compared with usual care or other digital approaches, with outcomes including changes in systolic and diastolic BP, medication adherence, behaviour changes, implementation outcomes, and improvement in knowledge and self-management skills. A literature search was conducted in PubMed, Embase, Scopus and Web of Science for studies published from 2015 onwards, identifying 316 studies, of which 177 underwent title and abstract screening and 9 were finally included. Two independent reviewers performed screening and full-text review and assessed quality using Covidence. Inter-Rater Reliability (IRR) was assessed using pairwise Cohen's Kappa (<i>κ</i>), with values ranging from 0.38 to 1.00 and a mean of 0.59, indicating overall moderate agreement. Data extraction focused on changes in systolic and diastolic BP, adherence, self-monitoring, and patient engagement.</p><p><strong>Results: </strong>Evidence is heterogeneous and mostly low-to-moderate certainty. Chatbot interventions were associated with improvements in both Systolic Blood Pressure (SBP) and Diastolic Blood Pressure (DBP), medication adherence, and adherence to home BP monitoring. Improvements in self-monitoring and engagement were more consistent across studies, while BP and medication adherence outcomes varied, with some studies reporting limited or non-significant effects.</p><p><strong>Discussion/conclusion: </strong>Chatbot interventions show potential as an accessible tool to support hypertension self-management. They may help improve patient engagement and monitoring behaviours, however, their effects on BP and medication adherence vary and may depend on intervention design and how they are used in practice.</p><p><strong>Systematic review registration: </strong>https://www.crd.york.ac.uk/PROSPERO/view/CRD420251172042, PROSPERO CRD420251172042.</p>","PeriodicalId":73078,"journal":{"name":"Frontiers in digital health","volume":"8 ","pages":"1911937"},"PeriodicalIF":5.2,"publicationDate":"2026-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13623939/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149119483","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Exploring public health equity in digital access: voices from marginalized groups using the \"Mawid\" application in Saudi Arabia.","authors":"Fahad M Al-Anezi","doi":"10.3389/fdgth.2026.1917318","DOIUrl":"https://doi.org/10.3389/fdgth.2026.1917318","url":null,"abstract":"<p><strong>Background: </strong>Digitalization of healthcare services can significantly enhance the services and access to quality care. However, the equity implications of access to healthcare by such digital health platforms for marginalized populations remain underexplored, especially in the countries which are rapidly transforming their healthcare system through digitalization, such as Saudi Arabia. In this context, this study aims to investigate digital inclusion and health equity among users of the Saudi Ministry of Health's \"Mawid\" application.</p><p><strong>Methods: </strong>A qualitative exploratory design was adopted in this study using five focus groups discussions (25 participants with five participants in each group) as an approach for data collection. Each focus group is categorically included participants of older adults, rural residents, low-income individuals, people with disabilities, and intersectional users who combined these characteristics respectively. Braun and Clarke's thematic analysis framework was used to identify key patterns and themes from the data collected through discussions.</p><p><strong>Results: </strong>Findings revealed that Mawid often functioned as a conditional gatekeeper to healthcare, with barriers related to digital literacy, infrastructural constraints, time poverty, and accessibility. Participants relied heavily on informal support networks, frequently at the cost of privacy and autonomy. Uniform system design was perceived to disadvantage users with complex social and health needs.</p><p><strong>Conclusion: </strong>Government-managed digital health applications enhances efficiency of healthcare operations, but may reinforce health inequities, if equity-centred digital design and alternative access pathways are not considered in the system design and formulation of digital health strategies.</p>","PeriodicalId":73078,"journal":{"name":"Frontiers in digital health","volume":"8 ","pages":"1917318"},"PeriodicalIF":5.2,"publicationDate":"2026-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13625048/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149119466","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Application of artificial intelligence in hepatology.","authors":"Zekai Hu, Yajie Lin, Hainv Gao, Leyao Shuai, Zhaowei Tong, Chenqi Nie, Zhe Yang, Junsheng Zhao","doi":"10.3389/fdgth.2026.1851723","DOIUrl":"https://doi.org/10.3389/fdgth.2026.1851723","url":null,"abstract":"<p><p>Artificial intelligence (AI) is being applied across diagnostic and therapeutic workflows in hepatology. This narrative review summarizes recent advances in AI for liver disease. In medical imaging and digital pathology, computer vision enables automated quantitative analysis of ultrasound, CT, MRI, and histologic images, with the aim of improving the consistency of lesion detection, disease staging, and prognostic assessment. In biomarker research, machine learning can analyze high-dimensional liquid-biopsy and multi-omics data to develop diagnostic and prognostic models; some have outperformed conventional markers in their study cohorts. Electronic health records (EHRs) and large language models (LLMs) are also being investigated for clinical decision support and personalized management. However, most reported evidence remains retrospective, and clinical adoption is limited by data heterogeneity, poor interpretability, uncertain generalizability, and regulatory requirements. Progress will require standardized datasets, external and prospective validation, clinically relevant endpoints, and human-centered implementation before gains in model performance can be translated into better patient outcomes.</p>","PeriodicalId":73078,"journal":{"name":"Frontiers in digital health","volume":"8 ","pages":"1851723"},"PeriodicalIF":5.2,"publicationDate":"2026-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13624904/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149119343","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"CDTD-Agent: a retrieval-augmented multi-agent digital health framework for integrated diabetes care: a single-case expert-rated pilot study.","authors":"Jieyi Zhang, Luqing Wu, Jielong Wu, Xiaoming Han, Lijin Lin, Nengjiang Zhao, Zhihai Zhang, Miaona Cai, Meiqi Chen, Shuyu Yang, Bo Li","doi":"10.3389/fdgth.2026.1923975","DOIUrl":"https://doi.org/10.3389/fdgth.2026.1923975","url":null,"abstract":"<p><strong>Background: </strong>Diabetes management increasingly requires coordination across Western medicine, traditional Chinese medicine (TCM), and lifestyle-based health management. General-purpose large language models (LLMs) can generate clinical text but may lack reliable source grounding and structured cross-disciplinary reasoning.</p><p><strong>Methods: </strong>We developed CDTD-Agent, a retrieval-augmented multi-agent framework that combines a domain-specific knowledge base with an Extract-Retrieve-Reason workflow. The knowledge base included 12 medical textbooks, 8 clinical guidelines, and 183 expert-reviewed diabetes cases. In a blinded single-case pilot evaluation, 30 senior experts rated anonymized recommendations from CDTD-Agent, GPT-4o, DeepSeek-V3.2-Exp, Doubao, and two attending physicians across eight dimensions. Linear mixed-effects models accounted for repeated ratings within evaluators, with Holm correction across eight omnibus tests and global Benjamini-Hochberg correction across 40 focused CDTD-Agent-versus-comparator contrasts. A <i>post hoc</i> backbone-only ablation compared the full framework with Qwen3-235B-A22B using the same case and external prompt without retrieval or role-structured multi-agent processing.</p><p><strong>Results: </strong>Significant source effects were detected in all eight dimensions after Holm correction (all adjusted <i>p</i> < 0.001). After global false discovery rate correction, CDTD-Agent received significantly higher ratings than all three general-purpose LLMs in five dimensions: safety, examination appropriateness, Western medicine treatment appropriateness, TCM treatment appropriateness, and evidence adherence. The largest differences occurred in Western medicine treatment appropriateness, where CDTD-Agent scored 4.07 ± 0.94 versus 1.37-1.60 for the general-purpose LLMs (all adjusted <i>p</i> < 0.001). Non-parametric sensitivity analyses agreed with the mixed-effects results for 39 of 40 focused contrasts. In the <i>post hoc</i> ablation, the full framework outperformed the backbone-only condition in seven of eight dimensions after Holm correction; health management was not significantly different (adjusted <i>p</i> = 0.080).</p><p><strong>Conclusion: </strong>In this standardized complex T2DM case, CDTD-Agent received favorable expert ratings relative to the evaluated general-purpose LLMs in several clinically important dimensions. These findings are scenario-specific and do not establish generalizable clinical performance or isolate the effects of individual framework components. Multicase, repeated-generation, factorial-ablation, external, and prospective validation is needed before clinical deployment.</p>","PeriodicalId":73078,"journal":{"name":"Frontiers in digital health","volume":"8 ","pages":"1923975"},"PeriodicalIF":5.2,"publicationDate":"2026-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13623845/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149119430","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The epistemic economy of vocal biomarker startups: a qualitative interview study of data practices and governance.","authors":"Abigail Yuhan, Sonal Swain, Robin Zhao, John Ramos, Anaïs Rameau","doi":"10.3389/fdgth.2026.1895383","DOIUrl":"10.3389/fdgth.2026.1895383","url":null,"abstract":"<p><strong>Background and aims: </strong>Vocal biomarker technology has emerged as a promising non-invasive health assessment tool, with artificial intelligence enabling the screening, diagnosis, and monitoring of conditions including Parkinson's disease, Alzheimer's disease, depression, and heart failure. Vocal biomarkers are defined as vocal features, alone or in combination, validated as indicators of clinical outcomes. Startups in this space are generating substantial investment and anticipatory discourse around future commercialization, while the scientific foundation and governance framework remain unestablished. Drawing on Sabina Leonelli's epistemic economy framework, which analyzes how data are produced, valued, and governed within social, institutional, and commercial arrangements, we examine how voice data are converted into entities with clinical and commercial value, and at what scientific and ethical cost.</p><p><strong>Methods: </strong>We performed a qualitative interview study using an interpretive framework. Virtual semi-structured interviews were conducted with representatives from eleven vocal biomarker startups identified through purposive sampling. Interviews addressed data collection methods, IRB compliance, informed consent, participant demographics, geographic sourcing, and financial incentives. Two researchers independently performed thematic analysis, reconciling differences via discussion.</p><p><strong>Results: </strong>Six themes were identified: (1) the absence of shared data standards introduced substantial hardware and protocol heterogeneity, uncontrolled confounding, and label noise, undermining scientific validity; (2) IRB engagement ranged from robust multi-site review to complete absence of oversight; (3) consent practices varied from granular opt-in to implied consent and minimal disclosures; (4) voice data were acknowledged as inherently non-anonymizable, creating unresolved privacy and re-identification risks; (5) data sourcing was asymmetric, with collection from low- and middle-income countries in 4 out of 11 startups while targeting commercial deployment in high-income countries; and (6) commercial incentives produced proprietary protocols that preclude independent validation and impede data sharing.</p><p><strong>Conclusion: </strong>The vocal biomarker startup ecosystem operates as an epistemic economy in which methodological, regulatory, and governance choices tend to favor commercial interests and high-income populations over scientific rigor and equity. Standardized data provenance requirements, reassessment of voice data's risk classification under existing privacy frameworks (e.g., HIPAA, GDPR), and participatory governance including source communities are urgently needed to ensure vocal biomarker products are scientifically valid, ethically grounded, and equitably developed.</p>","PeriodicalId":73078,"journal":{"name":"Frontiers in digital health","volume":"8 ","pages":"1895383"},"PeriodicalIF":5.2,"publicationDate":"2026-09-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13619882/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149083035","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Telepsychology and digital mental health communication: an exploratory mixed-methods study of tikTok content.","authors":"Andrea M Carrero, Jobana F Agredo, Lucía Catalina Martínez Ruiz, José A González","doi":"10.3389/fdgth.2026.1900544","DOIUrl":"10.3389/fdgth.2026.1900544","url":null,"abstract":"<p><strong>Background: </strong>Telepsychology consolidated as a mainstream mental health care modality following the COVID-19 pandemic, supported by evidence of clinical efficacy comparable to in-person therapy and a recognized potential to democratize access to care. Against this evolving clinical landscape, social media platforms have simultaneously emerged as major environments for the public circulation of psychological knowledge.</p><p><strong>Objective: </strong>To explore the relationship between scientific evidence on telepsychology and its discursive representation in highly viewed Spanish-language TikTok content, and to identify implications for digital mental health literacy and professional communication practices.</p><p><strong>Methods: </strong>An exploratory mixed-methods design with qualitative emphasis integrated a scoping review (PRISMA-ScR) across Scopus, Web of Science, and PubMed (2020-2025; <i>n</i> = 39 articles) and an inductive thematic analysis of TikTok content (<i>N</i> = 50 videos; 1,286,360 total views). Searches were conducted from a newly created TikTok account with no prior interaction history, configured in Colombia, to reduce algorithmic personalization bias. Three exploratory corpus-descriptive indicators-the Telepsychology Gap Index (TGI), Digital Telepsychology Legitimacy Index (DTLI), and Simplified Circulation Index (SCI)-were computed as heuristic comparators.</p><p><strong>Results: </strong>The scientific literature consistently supported the clinical viability and democratizing potential of telepsychology. Within the TikTok corpus, 64% of content featured simplified definitions or subjectivist experiential narratives with minimal reference to ethical or regulatory frameworks. Corpus-descriptive indicators revealed a substantial gap between scientific representation and digital circulation (TGI = 0.80), limited presence of clinical foundations in digital discourse (DTLI = 0.36), and a predominance of simplified over technically grounded content (SCI = 1.78).</p><p><strong>Conclusions: </strong>Within the analyzed corpus, telepsychology undergoes a process of digital discursive reinterpretation in which communicative accessibility and immediate subjective experience displace clinical precision as central evaluative criteria. These findings underscore the need to strengthen digital mental health literacy and professionals' evidence-based communication skills online. Given the exploratory design, findings are specific to a non-probabilistic Spanish-language TikTok corpus and are not generalizable prevalence estimates. Future research should extend this agenda through larger multilingual samples, additional platforms, computational social science approaches, and longitudinal designs examining how digital representations of telepsychology shape users' expectations and engagement with digital mental health care.</p>","PeriodicalId":73078,"journal":{"name":"Frontiers in digital health","volume":"8 ","pages":"1900544"},"PeriodicalIF":5.2,"publicationDate":"2026-09-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13621891/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149083076","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Impact of coping profiles on social identity in a youth chronic pain recommender system: qualitative descriptive study.","authors":"Antonia Barbaric, Joseph Saliba, Anya Nair, Vina Mohabir, Jennifer Stinson, Alex Mariakakis, Quynh Pham, Joseph A Cafazzo, Chitra Lalloo","doi":"10.3389/fdgth.2026.1727940","DOIUrl":"10.3389/fdgth.2026.1727940","url":null,"abstract":"<p><strong>Background: </strong>Chronic pain affects one in five children and adolescents worldwide yet remains one of the most underrecognized and undertreated illnesses, emphasizing the need for accessible, personalized digital health support. The Power over Pain portal delivers such support through a virtual stepped-care pathway, but like many digital interventions, is vulnerable to declining user engagement over time. Health recommender systems (HRSs) can personalize resource delivery and combat \"choice overload,\" thereby encouraging sustained use. This study investigates the application of a health recommender system (HRS) as a way of increasing engagement with relevant virtual care resources for pediatric chronic pain. The perceived value of the HRS was evaluated through a qualitative descriptive study involving ten participants diagnosed with chronic pain.</p><p><strong>Results: </strong>Thematic analysis revealed four main themes: (1) HRS serves as a catalyst for important dialogue in routine care; (2) coping results from the HRS are selectively applied by users according to their needs; (3) the HRS creates a personable experience, positively influencing willingness to engage in care; (4) interacting with the HRS may affirm participants' social identities, fostering a sense of belonging in the pain community and potentially enhancing long-term resource engagement.</p><p><strong>Conclusion: </strong>These findings challenge the traditional focus on recommendation accuracy alone, suggesting instead that the effectiveness of an HRS may also be influenced by design features that support validation, shared experience, and potential social identification, which can deepen engagement and promote involvement in care. Future work should investigate the impact of mechanisms that reinforce users' social identities to understand their effects on sustained use and self-management behaviors.</p>","PeriodicalId":73078,"journal":{"name":"Frontiers in digital health","volume":"8 ","pages":"1727940"},"PeriodicalIF":5.2,"publicationDate":"2026-09-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13619948/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149083131","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}